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Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions
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Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions

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Environmental Health: …

Environmental Health:
Economic Costs of Environmental Damage
And Suggested Priority Interventions

A Contribution to the Philippines
Country Environmental Analysis

Submitted to
The World Bank

Final Report
March 31, 2009

The results indicate that the economic costs of pollution and sanitation-related
health effects are high and cannot be ignored. The combined costs for all three sectors in 2003 totaled PhP 42.4 billion (USD 783.2 million) in lost productivity due to premature deaths or PhP 168.4 billion (USD 3.1 billion) in terms of value of statistical life (Table1). In addition, the cost of morbidity was PhP 18.3 billion (USD 337.6 million), comprising of loss in productivity totaling PhP 10.4 billion (USD 191.3 million), direct costs to Filipino households to treat these illnesses totaling PhP 6.4 billion (USD 118.7 million), and the cost to the government health care insurance system—representing the subsidy for PhilHealth members’ hospitalization costs—and for general government subsidy for publicly-owned health facilities was close to PhP 1.5 billion (USD 27.6 million).

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  • 1. Environmental Health: Economic Costs of Environmental Damage And Suggested Priority Interventions A Contribution to the Philippines Country Environmental Analysis Submitted to The World Bank Final Report March 31, 2009 1 Agustin L. Arcenas1 World Bank Consultant. The findings, interpretations, and conclusions expressed herein are those ofthe author’s, and do not necessarily reflect the views of the World Bank and its affiliated organizations,or those of the Executive Directors of the World Bank or the governments they represent. Please emailcomments about the report to the author at alarcenas@econ.upd.edu.ph.The author would like to acknowledge and thank the following individuals and groups of individuals for allthe help, assistance and comments and suggestions they generously shared in the conduct of the researchand writing of this report: Dr. Jan Bojo and Ms. Maya Villaluz; the author’s research assistants, RalphBulatao and Iva Sebastian; Dr. Bjorn Larsen and Dr. Maureen Cropper; Prof. Elma Torres; Mr. KarlGaling; Dr. Dennis Batangan; The Manila Observatory; Dr. Bernardino Aldaba, Dr. Carlo Panelo, Mr.Carlos Tan, Mr. Paul Mariano and the HPDP group based at U.P. School of Economics; the staff atPhilHealth and the Department of Health; Dr. Stella Quimbo; and finally, Dr. Aleli Kraft. 1
  • 2. LIST OF ABBREVIATIONS4-STC Four Stroke TricyclesADB Asian Development BankAF Attributable FractionsALRI Acute Lower Respiratory InfectionBCA Benefit-Cost AnalysisCH4 MethaneCOPD Chronic Obstructive Pulmonary DiseasesCO Carbon MonoxideCO2 Carbon DioxideCOC Certificate of ComplianceCOI Cost of IllnessDALY Disability-Adjusted Life-YearDENR Department of Environment and Natural ResourcesDHS Demographic and Health SurveyECC Environmental Compliance CertificateEMB Environmental Management BoardEO Executive OrderESI Economic Impacts of Sanitation in the PhilippinesFHSIS Field Health Surveillance Information SystemGNI Gross National IncomeGS Good ShepherdHCA Human Capital ApproachHCV Human Capital ValueHECS Household Energy Consumption SurveyIAP Indoor Air PollutionI/M Inspection and MaintenanceLC Local CurrencyLPG Liquefied Petroleum GasLRT Light Rail TransitLTO Land Transportation AgencyMMAQISDP Metro Manila Air Quality Improvement Sector Development ProgramMMDA Metro Manila Development AuthorityMO Manila ObservatoryMRT Metro Rail TransitMT/T motorcycles and tricyclesMVIS Motor Vehicle Inspection SystemNDHS National Demographic and Health SurveyNGO Non-governmental OrganizationNO Nitrogen OxideNO2 Nitrogen DioxideNOx Nitrogen OxidesNPO National Press OfficeOAP Outdoor Air Pollution 2
  • 3. PEM Philippine Environmental MonitorPETC Private Emission Testing CenterPGH Philippine General HospitalPhP Philippine PesoPHS Philippine Health StatisticsPM Particulate MatterPNRI Philippine Nuclear Research InstituteRR Relative RiskSOx Sulfur OxideSPM Suspended Particulate MatterTOGs Total Organic GasesUSAID United States Agency for International DevelopmentUSD United States DollarUV UltravioletVOC Volatile Organic CompoundVSL Value of Statistical LifeWHO World Health OrganizationWPR Western Pacific RegionWSH Water Pollution, Sanitation and HygieneWSP Water Pollution, Sanitation and Hygiene Project 3
  • 4. List of FiguresFigure 1 - Comparative Summary of the Economic Costs of WSH, IAP and OAP- Related Illnesses, 2003Figure 2 - Annual Average PM10 Levels in cities in Metro Manila and in Antipolo CityFigure 3 - Annual Average PM2.5 Levels in Metro ManilaFigure 4 - OAP Cost to Households of Treatment (Net of Public Health Care Subsidy), 2003Figure 5 - Government Health Care Subsidy per OAP-Illness, 2003Figure 6 - Lost Income Due to OAP-related Illnesses, 2003Figure 7 - Total Economic Cost of OAP-related Morbidity, 2003Figure 8 - Mortality Cases Due to OAP, Grouped According to Working and Non- working Age Groups, 2003Figure 9 - Cost of Premature Deaths due to OAP, 2003Figure 10 - New Vehicle Registration (All Types) Trend, 2007Figure 11 - Percentage of Households Use of the Type of Cooking Fuel, 2004Figure 12 - Household Fuel Use by Urbanity, 1995Figure 13 - Household Use of Solid Fuel by Income Class, 2004Figure 14- Primary Cooking Fuel for Households, 2004Figure 15 - Households Exposed to Indoor Air Pollution (in percentage)Figure 16 - Morbidity Cases Attributable to IAP, By Gender, 2003Figure 17 - IAP Cost to Households of Treatment (Net of Public Health Care Subsidy), 2003Figure 18 - Government Health Care Subsidy per IAP-Illness, 2003Figure 19 - Lost Income Due to IAP-related Illnesses, 2003Figure 20 - Total Economic Cost of IAP-related Morbidity, 2003Figure 21 - Cost of Premature Deaths due to IAP, 2003 (HCV)Figure 22 - Mortality Cases Due to IAP Grouped According to Working and Non- working Age Groups, 2003Figure 23 - Household Access to Improved Water Supply and Sanitation, 2003 (National)Figure 24 - Household Access to Improved Water Supply and Sanitation, 2003 (Metro Manila)Figure 25 - WSH Cost to Households of Treatment (Net of Public Health Care Subsidy), 2003Figure 26 - WSH Cost to Households of Treatment (Net of Public Health Care Subsidy), 2003 per IllnessFigure 27 - Government Health Care Subsidy per WSH-Illness, 2003Figure 28 - Lost Income due to WSH-related Illnesses, 2003Figure 29 - Total Economic Cost of Morbidity from WSH, 2003Figure 30 - Mortality Cases Due to WSH Grouped According to Working and Non- working Age Groups, 2003Figure 31 - Cost of Premature Deaths due to WSH, 2003 (HCV)Figure 32 - Median Construction Cost of Water Supply Facilities for Select Regions (in USD)Figure 33 - Percent Reduction in Diarrhea Morbidity of Different Water and Sanitation Interventions 4
  • 5. Figure 34 - Cost-effectiveness of Water Supply, Sanitation, and Hygiene Promotion (USD/DALY)Figure 35 - Median Construction Cost of Sanitation Technologies in Select Regions (in USD)List of TablesTable 1 - Summary Table of Economic Costs Breakdown per Sector (USD’000)Table 2 - Summary of Mortality Cases Per Sector and Age Group, 2003Table 3 - Summary of Morbidity Cases Per Sector and Age Group, 2003Table 4 - Attributable Fractions (AF) for OAP-related Morbidity, 2003Table 5 - Cases of OAP-related Illnesses by Age Group, 2003Table 6 - Relative Risk Ratios and Corresponding Attributable Fractions for Specific IllnessesTable 7 - Mortality Cases due to OAP, by Specific Age Group, 2003Table 8 - BCA-ratios for Cases of Retro-fitting of In-use Diesel Vehicles in the PhilippinesTable 9 - Light Rail Transits Lines in the PhilippinesTable 10 - Proposed Railway Projects with project costs (in USD millions)Table 11 - Financial Summary of MRT Line 3 Operations (in million pesos)Table 12 - Cost Estimates for the Metro Manila Air Quality Improvement Sector Development Program (MMAQISDP) (in USD millions)Table 13 - Particulate Emissions from Household Cooking, 2004Table 14 - Attributable Fractions Used for Morbidity Cases per IllnessTable 15 - Cases of IAP-related Illnesses by Age Group, 2003Table 16 - Attributable Fractions Used for Mortality Cases per IllnessTable 17 - Mortality Cases Due to IAP by Specific Age Group, 2003Table 18 - Overview of Costs and Impacts, Time Horizon of Modeled ImpactsTable 19 - Benefit-Cost Ratios of Converting to a New Stove Technology to Control IAP in the Philippines.Table 20 - Levels of Households According to Access to Water and Sanitation FacilitiesTable 21 - Responses to the Demographic and Health Survey, 2003Table 22 - Attributable Fractions (AF) for WSH-related Illnesses, 2003Table 23 - Total Cases of WSH-related Illnesses, 2003Table 24 - Number of Cases of Diarrhea by Age Group, 2003Table 25 - Number of Cases of WSH-related Illnesses (excluding Diarrhea) by Age Group, 2003Table 26.A -Mortality Cases due to WSH by Specific Age Group, 2003Table 26.B -Mortality Cases due to WSH by Specific Age Group, 2003Table 26.C - Mortality Cases for Malnutrition caused by Diarrhea for Children under 5 years old, 2003Table 27 - Malnutrition-related Mortality Resulting from Diarrheal Infection, 2003 5
  • 6. Summary Perhaps one of the most important and urgent issues that the Philippines facestoday is that of environmental health. Defined to be the area of health concerns due topollution and unsanitary conditions, it has caught the attention of government, promptingthe national leadership to create an inter-agency committee focusing on these healthissues; to bring forward an agenda of technical collaboration, information collection anddissemination, and policy review. This study on environmental health issues in the Philippines was conducted toprovide guidance—in terms of information and suggestions on policy interventions—topolicy managers and researchers, and donor agencies. There are three areas of focus:urban outdoor air pollution (OAP), household indoor air pollution (IAP), and waterpollution, sanitation and hygiene (WSH)(including WSH-related child malnutrition). Itgathered the available data from different published data sources in the Philippines onmorbidity and mortality, to calculate the number of cases, and the correspondingeconomic costs to the country in terms of lost productivity, direct costs to households,and public funds used to subsidize treatment costs. A comparative summary of theeconomic valuation of the environmental health costs of these three is presented below inFigure 1:Figure 1 – Comparative Summary of the Economic Costs of WSH, IAP, and OAPHealth Effects, 2003 Water, Sanitation and PhP 102.5 B Hygiene (including u5 PhP 51.0 B ($1.9 B) Malnutrition) ($ 0.9 B) PhP 60.6 B Outdoor Air Pollution PhP 5.1 B ($1.1 B) ($0.1 B) PhP 23.6 B Indoor Air Pollution PhP 4.7 B ($0.4 B) ($0.1 B) 0 20 40 60 80 100 120 Morbidity + Mortality (HCA) Morbidity + Mortality (VSL) Source: Author’s calculations As reflected in Figure 1, two methods were used to calculate the economic costsof premature deaths: the human capital value (HCV) and the value of statistical life(VSL)—the results were used as the lower and upper bounds of the economic cost of 6
  • 7. mortality. The HCV is the economic cost to society of premature death in terms of lostcontribution to production of an individual. The VSL , on the other hand, is based onindividuals’ willingness-to-pay for a reduction in the risk of death. The cost-of-illness(COI) approach is used to estimate the cost of morbidity and is based on the costs oftreatment and the lost income from being ill. It must be noted that this report madeadditional calculations to estimate the economic costs of malnutrition-related deathsresulting from diarrhea in children under 5 years old. The analysis was limited to this agegroup as there were no data on the other age groups that could be used to estimatepremature deaths from diarrhea-induced malnutrition mortality for these groups ofindividuals. The results indicate that the economic costs of pollution and sanitation-relatedhealth effects are high and cannot be ignored. The combined costs for all three sectors in2003 totaled PhP 42.4 billion (USD 783.2 million) in lost productivity due to prematuredeaths or PhP 168.4 billion (USD 3.1 billion) in terms of value of statistical life (Table1). In addition, the cost of morbidity was PhP 18.3 billion (USD 337.6 million),comprising of loss in productivity totaling PhP 10.4 billion (USD 191.3 million), directcosts to Filipino households to treat these illnesses totaling PhP 6.4 billion (USD 118.7million), and the cost to the government health care insurance system—representing thesubsidy for PhilHealth members’ hospitalization costs—and for general governmentsubsidy for publicly-owned health facilities was close to PhP 1.5 billion (USD 27.6million).Table 1 – Summary Table of Economic Costs Breakdown per Sector (USD’000) Water, Sanitation and Indoor Air Outdoor Air All Sectors Hygiene Pollution Pollution (including u5 Malnutrition)Economic Cost (in USD‘000)Morbidity 18,727 11,327 307,583 337,638Mortality (HCV) 68,017 82,702 632,474 783,192Mortality (VSL) 415,975 1,107,532 1,584,394 3,107,900Morbidity and 86,744 94,029 940,057 1,120,830Mortality (HCV)Morbidity and 434,702 1,118,859 1,891,977 3,445,538Mortality (VSL)Economic Cost as Percentage of GNIMorbidity 0.02 0.01 0.31 0.34Morbidity and 0.09 0.09 0.94 1.12Mortality (HCV)Morbidity and 0.43 1.12 1.89 3.45Mortality (VSL)Source: Author’s calculations based on published data sets and empirical studies. Theinformation on malnutrition was based on the calculations of B. Larsen. 7
  • 8. A comparison of the economic costs for all three sectors (including malnutrition-related health effects in children under 5 years old from WSH) indicates that the mostpressing issue in environmental health is water, sanitation and hygiene, costing thePhilippine society almost USD 1-2 billion per year (HCV and VSL estimates for cost ofdeaths) representing more than 33 million cases of illness and 22 thousand deaths in2003. Outdoor air pollution comes in second with USD 94 million to USD 1 billion ineconomic costs, registering close to one million cases of respiratory illness and over 15thousand premature deaths. Indoor air pollution comes next, costing the Philippinesociety USD 87 to 434 million in 2003, resulting from nearly half a million cases of IAP-related illnesses and almost 6 thousand deaths due to exposure to indoor air pollutionfrom household use of solid fuels for cooking. (Details of these figures are in Tables 2and 3). Tables 2 and 3 show us that OAP and IAP-related deaths are heavily skewedtoward adult and working age groups, while deaths resulting from WSH are in theyoungest members of society. This has implications in terms of vulnerability assessment,policy prioritization, and target-setting.Table 2 – Summary of Mortality Cases per Sector and Age Group, 2003 Water, Under-5 Indoor Air Outdoor Air All Age Group Sanitation and Malnutrition Pollution Pollution Sectors Hygiene from WSHYounger than 1 653 199 2,048 3,719 6,6201 to 4 632 194 8,502 3,897 13,2255 to 14 0 0 1,637 0 1,63715 to 19 19 0 135 0 15420 to 29 82 0 189 0 27130 to 64 1,890 5,588 1,043 0 8,52065 and older 2,492 9,369 851 0 12,711Age not reported 4 17 2 0 23All Age Groups 5,772 15,367 14,406 7,616 43,161Sources: The author calculated the mortality cases for OAP, IAP and WSH. For themalnutrition-related numbers, this report used B. Larsen’s calculations.Note: Those entries with zeroes do not mean that there were no cases, but simply thatthere were no available data which could be used to calculate the number of cases forthese age groups. 8
  • 9. Table 3 – Summary of Morbidity Cases per Sector and Age Group, 2003 Water, Indoor Air Outdoor Air Age Group Sanitation and All Sectors Pollution Pollution HygieneYounger than 1 147,517 259,966 4,766,078 5,173,5611 to 4 244,185 441,859 14,704,145 15,390,1895 to 14 0 256,578 6,170,901 6,427,47915 to 19 716 8,474 277,625 286,81520 to 29 1,173 13,891 455,031 470,09530 to 64 47,746 40,415 6,610,177 6,698,33865 and older 16,435 16,856 478,527 511,818All Age Groups 457,772 1,038,039 33,462,483 34,958,294Source: Author’s calculations Suggested interventions were culled from the existing literature. For outdoor airpollution, the interventions in discussion are those that address emissions from mobilesources such as improved traffic management to lessen travel time, improved inspectionand maintenance systems, additional investments in affordable mass transport systems,and affordable pollution control devices for tricycles and motorcycles. For indoor airpollution and water, sanitation and hygiene, it is apparent that interventions must targetbehavior—cooking practices and ventilation for indoor air2; and hygiene of householdmembers to prevent water and sanitation illnesses. Interventions to involve thecommunities to create and promote low-cost alternative stoves to the current solid fuel-using stoves are suggested. Additional initiatives to increase the access of householdsespecially in the rural areas and the urban poor to a sewage system and clean water areneeded in order to decrease the exposure of the population to pathogens that causediseases.2 It must be noted that cases of indoor air pollution-related illnesses due to cigarette smoking is not part ofthe study. Hence, cigarette-smoking as a risk factor is not mentioned. 9
  • 10. Introduction One of the clearest indicators of the state of the environment in the Philippines isperhaps the magnitude of the cases of pollution-related illnesses. The Philippines, being acountry with increasing productive activities fueled by a growing population, is squarelyconfronted with the impacts of pollution on human welfare—a pollution-welfare nexus—which take on several forms: availability of income opportunities, access toenvironmental services, and in recent times, on human health. Among the areas ofconcern within the pollution-welfare nexus, it is the human health angle that has capturedthe attention and alarm of policy managers because of its growing incidence, and theburden that it forces the poorest members of society to shoulder as a result of it. Environmental health—the area of health concerns arising from poorenvironmental quality, causing disease, injuries and deaths—is a serious and pressingissue in countries such as the Philippines, which is still finding that point of sustainableeconomic growth. It is an important enough issue that the Philippine government enactedand adopted Executive Order (E.O.) 489 which created an inter-agency committee onenvironmental health to establish and bring forward an agenda of technical collaboration,information collection and dissemination, and policy review. As part of the support for the country to plan and develop programs that areconsistent with addressing the problems in environmental health in the Philippines, theinformation and analyses contained in this study have been carefully collected. Theobjective is to aid policy makers understand how the country is faring in environmentalhealth issues; and determine what these health problems are costing the country in termsof loss in productivity and direct costs to households. This study on environmental healthquantifies and analyzes the bio-physical dimensions of environmental degradation andlikewise determines the social costs of environmental degradation; and the potentialeconomic benefit of environmental improvement as they relate to environment-relatedhealth effects. In addition, potential priority interventions—as suggested by the existingliterature— is examined to determine the feasibility of each in addressing theenvironmental health issues in the Philippines. These health effects of poor environmental quality negatively impact humanwelfare (and ultimately, the welfare of society) by lowering the quality of life forindividuals afflicted with these health effects—which is represented by the lost incomeopportunities as a result of being ill, and the opportunity cost of income that has to bespent on treatment and care—and the loss of valuable and productive members ofsociety—as measured either by a permanent loss in productivity as a result of death (thehuman capital value), or by the willingness-to-pay of individuals to reduce the risk ofdeaths resulting from these illnesses (the value of statistical life approach). There are three areas of specific interests that will be discussed: 1) urban outdoorair pollution; 2) household indoor air pollution; and finally, 3) water pollution, sanitationand hygiene. The primary research objectives are to determine and quantify the economiccosts of environmental degradation—focusing on these three areas—in terms of theirimpacts on the health of the citizens of the country, and to evaluate the economic 10
  • 11. feasibility and efficiency of potential interventions. There is a particular interest inevaluating environmental health in the context of poverty and other high risk groups suchas women and children. The poor are the most susceptible members of society to thehealth risks posed by a degraded environmental quality, because they lack the necessaryresources for disease prevention and treatment. Women and children are in a similar riskyposition because they do not have the same health-care opportunities and access toeducation and information that adult men possess. To calculate the economic impacts of morbidity arising from environment-relatedillnesses, the fundamental approach used was the cost-of-illness (COI) valuation method.This necessitated a determination of the different treatment-seeking behaviors ofFilipinos, and an estimation of the corresponding medical costs attributable to each. Inaddition, productivity losses were calculated by estimating a reduction in gross nationalincome as a result of missed days from work resulting from illness. To these numbers,the public expenditures on subsidies for health treatment were added to determine thetotal economic costs of environment-related morbidity. The computation of the economic costs of premature deaths caused by pollutionand unsanitary practices proved to be more challenging than the calculations formorbidity costs. This is due to the differing perspectives among scholars on how best toestimate the value of a lost human life. To capture these differences, this study calculatedlower and upper bounds values based on the human capital value approach (HCV) andthe value of statistical life (VSL). The HCV estimates the value of loss of life based on anindividual’s foregone contribution to aggregate income as a result of premature death—measured in terms of per capita gross national income. The VSL, on the other hand, is ameasure of one life lost in terms of how much money people are willing to pay to reducethe risk of death. Which of these two approaches better approximates the cost of loss ofhuman life as a consequence of environment-related illnesses is not for this report todecide on. But whichever that may be, the fact remains that many people could havelived a longer, healthier and more productive life if the risks to life were not increased asa result of a degraded environment. The estimated values of the lives lost presented inthis report—both the HCV and VSL—merely provide a benchmark by which the gravityof these environment-related health causes are represented. The organization of this report is based according to the issues within the areas ofenvironmental health mentioned earlier. The basic idea is to present estimates of theenvironmental health effects of the degradation of the natural environment to aid policymanagers. This information is crucial in evaluating the feasibility of potential policyinterventions and determining which among these interventions promise to deliver thehighest net benefit at the least cost. To the maximum extent possible, the methodologiesand assumptions used to calculate the number of cases of illness and deaths and thecorresponding economic costs were harmonized with the existing World Bank studiessuch as the Philippine Environmental Monitor (PEM) and the Economics of SanitationInitiative in the Philippines (ESI). There were many instances, however, when newinformation were uncovered that could refine the computations in these studies. In thesecases, this study expanded the set of assumptions and modified the methodologies tobuild on the results of these existing research reports. A great deal of effort was exertedto list all the numerous assumptions to guide the reader in understanding the process by 11
  • 12. which the calculations in this study were made. It is strongly suggested that the readersrefer to Annex 1 for clarifications on the computations. It must be emphasized that great effort was undertaken to review the existingempirical studies on environmental health issues in the Philippines. Wheneverappropriate, comments on the drafts of this report were solicited from some of the authorsof these studies to determine any points of contention and contradiction between theinformation contained in this study and the existing literature on environmental health inthe country. The conclusion is that there are some differences in the numbers of casesand valuation, but these differences are due to the differing scopes of work, assumptions,methodologies used in this report and the other empirical works. This report madedetailed assumptions and modified the standard dose-response methodologies to capturethe different treatment-seeking behavior of Filipinos to estimate morbidity figures. Theresult is a general methodological framework of valuation and analysis that is unique tothe situation in the Philippines. As a final note, the issue of how different is this report from the PEM and ESI—the two most recent initiatives of the World Bank dealing with environmental health—must be squarely addressed. The data used in this study are the same basic data used bythe PEM and the ESI, but its approach in filling data gaps is different because of recentinformation that were not available to the authors of those studies during the time theywere conducting the research. In addition, this report also has a different scope ofanalysis than the PEM and ESI—the PEM focusing solely on the determination of thenumber of cases of illness and deaths while this report took the next step of economicvaluation; the ESI’s economic analysis, on the other hand, was more encompassing thanthis report in relation to sanitation and hygiene, as it included the impacts on non-production activities such as tourism. It is important that the readers and users of thisreport keep these differences in mind, so as not to pit the findings and conclusions of thisreport against those of PEM’s and the ESI’s. Outdoor Air Pollution The deterioration of urban outdoor air quality in the Philippines is at a levelwhere one can visually observe air pollution in major cities such as those in MetroManila. An individual only needs to take public transportation any time of the day andsee black fumes spew out of decade-old buses to get a sense of the tight spot that thecountry faces when it comes to air quality. The threat of poor air quality has alreadyreached the attention of law makers and the average Filipino, prompting Congress to passthe Clean Air Act in 1999 in order to properly address the impacts of mounting airpollution in the country. It is expected that the implementation of the law will translateinto concrete steps both by the public and private sectors to reverse the deterioration ofthe nation’s air quality. There are generally two types of air pollution: outdoor (mobile, stationary andarea sources) and indoor (stoves and cigarette-smoking). Outdoor air pollution is anexternal (to the household) pollutant and often large-scale in its presence, affecting 12
  • 13. multiple sectors and crossing geographical boundaries. Indoor air pollution is a householdissue attributable to proximity to indoor air pollutants such as smoke from cooking, andcigarette smoke. Between the two types, it is outdoor air pollution that attracts greaterpublic attention. Not surprisingly, this has resulted in a greater awareness among thecitizens and a heightened sentiment of urgency to address. In most instances, however,the discussion on outdoor air pollution has been confined to the experience and issues ofmega-cities, specifically, the high-profile cities in Metro Manila. This due to the fact thatbased on the existing data, the highest concentration of outdoor air pollutant sources—e.g., production plants and factories, private vehicles, buses, public jeepneys and othermodes of public transportation—is in Metro Manila. The main driver of outdoor air pollution is the rapid urbanization, transport andincreasing expansion of manufacturing activities and industrial production in the country.The ADB (2006) reports that the industrial sector in the Philippines grew by an averageof 3.2 percent between 1988 and 2002; and the National Statistics Office (2006) reportsthat close to half (47 percent) of the manufacturing activities in the country occur inMetro Manila, and more than a third (32 percent) are located in the urban centers aroundor close to Metro Manila. This trend, along with the increasing migration from the ruralareas to the urban centers, has caused a heightened demand for services and transportthat—in the absence of effective air pollution management—resulted in degradation ofoutdoor air quality in the cities and other urban areas. It is difficult to pin down in exact terms what the state of air quality is in thePhilippines because of the very limited data collected. The law requires theEnvironmental Management Board (EMB) to monitor air quality in the country, and toestablish an inventory of air emissions every three years. The monitoring, however, hasbeen limited to a review of studies conducted by non-government and internationaldevelopment agencies, limited field surveys, and collation of information from self-monitoring reports submitted by industry members.3 The latest emissions inventory (the2001 Philippine Emissions Inventory) included particulate matter (PM), sulfur oxide(SOx), nitrogen oxide (NO), carbon monoxide (CO), volatile organic compounds, andtotal organic gases (TOGs) from mobile sources (ADB, 2006). The report estimates thatCO contributes the heaviest to total pollution load at 39 percent, followed by NO at 35percent, SOx and PM at 8 percent, TOG at 7 percent and finally, VOC at 2 percent.Regular source apportionment4 analyses, however, are not done by EMB. Apportionmentstudies, instead, are being conducted by two institutions: the Philippine Nuclear ResearchInstitute (PNRI, a government facility) and the Manila Observatory (a non-governmentinstitution). Both of these institutions’ regular apportionment analyses, however, are onlyon the small particulate matter: PM10 and PM2.5 or particulate matters that measure lessthan 10 and 2.5 micrometers in diameter respectively; and the samples are gathered fromstations which are (at present) only in Metro Manila or in close proximity to the area. The3 The law requires that industry members submit periodic self-monitoring reports as part of the conditionscontained in their Environmental Compliance Certificate (ECC).4 Source apportionment analysis determines what the contribution of each source of pollutant to a specificlocation. 13
  • 14. air quality of a few cities5outside of Metro Manila has been monitored by EMB but hassince stopped in 2006. Given the data availability, this study can only focus on the health impacts thatare associated with particulate matter of sizes 10 and 2.5 micrometers. While it isrecognized that the other pollutants cited earlier have potentially significant impacts onthe health of Filipinos, the data gaps that characterize these other outdoor air pollutantsare too wide to be overcome. Nevertheless, a meaningful assessment—albeit limited—onthe economic impacts of health problems arising from is possible, because there issufficient information on PM10 and PM2.5 levels available; and there is sufficient supplyof technical data—raw PM levels and epidemiological studies that establish the “dose-response” connections between long-term exposure to particulate matter and specificidentified illnesses such as respiratory and cardiovascular ailments. If the reported levels of particulate matter were to be indicators of the state ofhealth effects in Filipinos exposed to particulate matter, then there is indeed a cause forconcern. This report’s estimates on PM10 and PM2.56 in Metro Manila indicate apopulation-weighted average of 72 μg/m3 and 48 μg/m3, respectively for 2003. For urbanareas outside of Metro Manila, the estimates also show values of 38 μg/m3 for PM10 and18 μg/m3 for PM2.5 for the same year. There are no PM values for the rural areas becauseof insufficient data. These numbers are significantly above the guidelines set by theWorld Health Organization (WHO) of 20 μg/m3 for PM10, and 10 μg/m3 for PM2.5. Figures 2 and 3 below illustrate the PM levels data gathered from the differentstations in Metro Manila and one baranggay right outside of Metro Manila (baranggayInarawan in Antipolo; the Good Shepherd (GS) is another station located also inAntipolo). The sites that the Manila Observatory (MO) uses to test and collect data onPM concentrations in Metro Manila show a consistently high level—even if the level hassomewhat declined through the years—of PM concentrations. It must be pointed out thatthe different sites vary in characteristics; the MO categorizes the sites as high, medium,and low mobile source presence. As to be expected, the site at the National Press Office(NPO), which has the heaviest vehicle-density, has the highest PM concentrations; theGood Shepherd site in the city of Antipolo—categorized as the low mobile sourcepresence—registered the lowest PM concentrations. While this is not conclusiveevidence, it does provide some basis to the assertion that vehicles are very likely to be amajor contributor to the high PM levels in the Metro Manila, as well as to the other urbanareas in the country.5 These cities are Indang (Cavite), Batangas City (Batangas), Angeles City (Pampanga), and Los Baños,Laguna. Cebu city is also monitored but only for NO2, SO2, O3, benzene, toluene, and xylene only. (Source:EMB’s National Air Quality Status Report, 2003, as cited in the discussion draft of the Country SynthesisReport on Urban Air Quality Management in the Philippines by ADB).6 The PM10 and PM2.5 average estimates for Metro Manila were calculated using actual data collected bythe Manila Observatory, and weighted according to population around the stations. These stations wereManila Observatory (MO), National Printing Office (NPO), Philippine General Hospital (PGH), GoodShepherd (GS in Antipolo), Pasig, Las Pinas, Valenzuela, Pateros, Taguig, and Inarawan (in Antipolo). TheMO’s data collection was part of the ADB/WHO/DOH project in 2003-04. 14
  • 15. Figure 2 - Annual Average PM10 Concentrations in cities in Metro Manila and inAntipolo City 100PM10 Level 75 (ug/m ) 3 50 25 0 PO S s O H ig an la na G PG M gu ue w N Pi a Ta nz ar s e La Site In al V 2001 2002 2003Source: Manila Observatory, 2004Figure 3 - Annual Average PM2.5 Concentrations in Metro Manila Annual Average PM2.5 Levels, Metro Manila Source: Manila Observatory 75 2000 PM2.5 Level (ug/m ) 50 2001 3 2002 25 2003 2004 0 MO NPO PGH GS Pasig Las Pinas Valenzuela SiteSource: Manila Observatory 2004Economic Costs of OAP-related Morbidity To estimate the health effects and economic burden caused by exposure toparticulate matter (PM), it is necessary to identify the illnesses that can be feasiblyincluded, and to determine the attributable fractions7 (AFs) of these illnesses from PM.The decision as to which illness to include in this analysis is fundamentally about dataavailability. Two considerations are at hand: the availability of information regardingrisks of becoming ill (for each disease) from exposure to PM, and the availability ofreliable information on the frequency or incidence for each disease. Unfortunately, theinformation is wanting, and this study is thus limited to analyzing the economic burden ofdisease of two health endpoints: acute lower respiratory infection (ALRI, including7 Attributable fractions are defined simply as the fraction or ratio of incidence of illness that can beaccounted or attributed to a certain health risk such as exposure to particulate matter. 15
  • 16. pneumonia), and acute bronchitis.8 Other diseases that could not be included due to datagaps are chronic obstructive pulmonary diseases (COPD), cardiovascular disease,exacerbation of asthma, lung cancer and possibly tuberculosis. The data on risk ratioswere sufficient to compute the AFs for specific ALRI illnesses, as summarized below inTable 4: Table 4 – Attributable Fractions (AF) for OAP-related Morbidity, 2003 Attributable Health Outcome Fractions Pneumonia* - Hospital cases 0.02555 - Non-hospital cases 0.11297 Acute Bronchitis, under 5 0.42343 Source: Author’s calculations based on Galassi et al (2000) Note: The AFs for pneumonia are adopted from the AFs for respiratory diseases. It must be noted also that the AFs were calculated only for Metro Manila and other urban areas. AFs for the rural areas could not be compute due to insufficient data. The data presented above frame the discussion on the elevated levels of PMconcentration in the country. Comparing the data with the guidelines set by the WHO, itis apparent that the concentrations of particulate matter has consistently been above theguidelines of 10 μg/m3 for PM2.5 and 20 μg/m3 for PM10 during the period the data werecollected. In the absence of mitigating measures that could shield the population fromlong-term exposure, continuously high levels of PM10 and PM2.5 have taken their toll onthe health and consequently, the productivity and welfare of Filipinos. The calculationsshow that the total number of people who have been ill due to outdoor air pollution—specifically from PM emissions—reached more than 1 million Filipinos in 2003. Thiscost the national economy in lost productivity a total of PhP 254.7 million (equivalent toUSD 4.7 million9, as shown in Figure 6) from lost days due to illnesses related to outdoorair pollution (including the lost income of parents who have missed work days to care fortheir sick children). The burden on the households resulting from these illnesses reachedPhP 289.1 million (USD 5.3 million), and an additional PhP 70.0 million (USD 1.3million) in health care subsidy10 from the national government. Table 5 belowsummarizes the morbidity cases of OAP-related illnesses by each group.8 Technically, acute bronchitis is included in ALRI. The data from the Department of Health (DOH),however, list ALRI and acute bronchitis separately. This report is consistent with the distinction betweenthe two.9 The foreign exchange rate used was PhP 54.2 = USD 1.0 which was based on the average exchange ratefor the year 2003.10 The health care subsidy represents PhilHealth payments to its members and subsidy to patients who areadmitted in public-owned hospitals for treatment. 16
  • 17. Table 5 – Cases of OAP-related Illnesses by Age Group, 2003 ALRI (including Acute Bronchitis Pneumonia) Younger than 1 104,494 155.471 Age 1 to 4 169,618 272,240 Age 5 to 14 60,766 195,812 Age 15 to 19 8,464 10 Age 20 to 29 13,875 16 Age 30 to 64 40,374 41 65 and older 16,844 12 TOTAL 414,437 623,602Source: Author’s calculations Figure 4 – OAP Cost to Households of Treatment (Net of Public Health Care Subsidy), 2003 Acute Bronchitis PhP 100 M 34% ALRI and Pneumonia PhP 190 M 66% Source: Author’s calculations 17
  • 18. Figure 5 – Government Health Care Subsidy per OAP-Illness, 2003 ALRI and Acute Pneumonia Bronchitis PhP 61 M PhP 9 M 87% 13%Source: Author’s calculationsFigure 6 – Lost Income Due to OAP-related Illnesses, 2003 Acute Bronchitis PhP 85 M 33% ALRI and Pneumonia PhP 170 M 67%Source: Author’s calculations 18
  • 19. Figure 7 - Total Economic Cost of OAP-related Morbidity, 2003 Acute Bronchitis PhP 194 M 32% ALRI and Pneumonia PhP 420 M 68% Source: Author’s calculations The data in Table 5 indicate that it is the youngest members of society (those thatare 14 years old and younger) that carry the heaviest burden of lower respiratoryinfections due to outdoor air pollution. This is alarming because it hits the potentialproductive members of society during their formative stage, and may impact theproductivity of the future labor force in the Philippines. It should however be noted thatthese estimates are limited to ALRI and acute bronchitis due to data limitations, and donot include cardiovascular disease, chronic bronchitis and other diseases thatpredominantly affect the adult population.Economic Costs of Premature Deaths due to OAP The calculations of the value premature deaths for all the mortality casesattributable to OAP (as well as for IAP and WSH-related illnesses) were done under twosets of definitions of value of premature deaths: 1) value in terms of the lost contributionof the individual to economic activity (HCV or human capital value); 2) value ofstatistical life as measured by how much individuals are willing to pay to reduce the riskof dying. These two approaches yield two different valuations, but it is difficult to assertif one is superior to the other. As a way to establish a range of values of economic orwelfare loss to society as a result of premature death, both of the values computed usingthe HCV and the VSL approaches are presented. The lower bound of the range isrepresented by HCV figures, while the VSL numbers are used as the upper bound. As astarting point to determine this range of values, the mortality cases attributable to OAPare computed, the results of which are presented in Figure 8. Mortality cases per agegroup is also summarized and presented in Table 7. The number of cases is calculated 19
  • 20. using AFs derived from relative risk ratios (RRs) which are computed using the data fromMO. The RRs and the AFs used for this section are summarized in Table 6 below:Table 6 – Relative Risk Ratios and Corresponding Attributable Fractions forSpecific Illnesses Relative Risks Attributable Health Outcome Metro Fractions Urban Rural (National) Manila Respiratory Mortality, under 5 1.10006 1.03980 1.00000 0.03058 Cardiopulmonary Mortality, older than 30 1.31085 1.13199 1.00000 0.08431 Lung Cancer, older than 30 1.49940 1.20386 1.00000 0.12683Source: Author’s calculations based on collected information on PM concentrations fromthe Manila Observatory, published data from the government, and methodology forestimating mortality adopted from Ostro, 2004. There are no estimates for the age group5-29 because of insufficient data.Figure 8 – Mortality Cases Due to OAP, Grouped According to Working and Non-working Age Groups, 2003 Source: Author’s calculations 20
  • 21. Table 7 – Mortality Cases due to OAP, by Specific Age Group, 2003 Cardiopulmonary Diseases Lung Cancer (including respiratory diseases )11 Younger than 1 0 199 Age 1 to 4 0 194 Age 5 to 14 0 0 Age 15 to 19 0 0 Age 20 to 29 0 0 Age 30 to 64 498 5,090 65 and older 413 8,956 Not Reported 0 17 Total 911 14,456 Source: Author’s calculations The computations show that in 2003, the total loss in productivity (Figure 9) dueto premature deaths resulting from illnesses caused by outdoor air pollution reached closeto PhP 4.5 billion (USD 82.7 million) or PhP 60.0 billion (USD 1.1 billion) in terms ofVSL. These figures were calculated based on pre-computed attributable fractions andapplied to the total prevalence of each cause of death. The breakdown of the cost ofpremature deaths (using HCVand VSL (in parentheses)) is indicated in the bar-graphbelow (Figure 9):11 This is listed as: cancer of trachea, bronchus and lung; Hypertension with and without heartinvolvement; Angina pectoris, Other forms of ischaemic heart disease; Acute myocardial infarction;Disease of pulmonary circulation and other forms of heart disease; Complications and ill-defineddescription of heart disease; Cerebrovascular disease; aterosclerosis; Acute upper respiratory infections;Influenza; Pneumonia; Acute bronchitis and bronchiolitis; Chronic obstructive pulmonary disease andallied conditions; Pneumoconioses and chemical effects; Pneumonitis due to solids and liquids; Otherdiseases of respiratory system 21
  • 22. Figure 9 - Cost of Premature Deaths due to OAP, 2003Source: Author’s calculations. The Value of Statistical Life (VSL) estimates are inparentheses.Suggested Interventions Mohanty et al (2004) concluded that particulate matter levels are influenced byseveral factors namely: “vehicle and fuel characteristics, fleet characteristics andoperating characteristics”. Similarly, the PEM (2007) reported that the bulk of the totalquantity of particulate matter in Metro Manila (84 percent) is from mobile sources. Thedata shows that the volume of vehicles that are added yearly into the highways and roadsin country is rising as can be concluded from Figure 10 below. The growth of the numberof vehicles every year has been steady at an average of 12 percent per year, or roughly50,000 new vehicles each year. 22
  • 23. Figure 10 – New Vehicle Registration (New and Used vehicles) Trend, 2007 Source: Land Transportation Office (www.lto.gov.ph/stats.html) It becomes apparent therefore, that one of the necessary interventions in order tolimit PM emissions (and lessen the number of cases of OAP-related illnesses andpremature deaths) must include vehicle management. This is not to diminish theimportance of stationary sources management to lessen PM emissions, but merely tohighlight a choice in policy interventions based on greater urgency.Inspection and maintenance (I/M) programs A well functioning inspection and maintenance (I/M) program is one of the mostcost effective interventions in abating outdoor air pollution. Vehicle inspection inparticular strengthens the enforcement of emission standards as well as increases in thedemand for vehicle repair and maintenance (Kojima and Lovei, 2001). Subida, et al(2005) report that for Metro Manila, maintenance of vehicles and inspection system(MVIS) is one of the more effective interventions they have examined. The implementation of an effective I/M program is not without cost as it entailsspecific activities to make it work. Gwilliam, et al (2005) conclude that an I/M programmust be able to target gross polluters, which requires an examination of thecharacteristics of the vehicle fleet. The program therefore requires superior managementand technical backstopping. All of these necessitate that a successful I/M program aninvestment on training and regular data collection. In addition, the I/M program must becomplemented by laws and checks and balance to ensure that it is not tainted bycorruption and politicking. Like any program, corruption and politicking would weakenthe enforcement of any of the I/M program’s policies, and will surely result in aneventual breakdown. A review of the existing initiatives in the Philippines that address outdoor airpollution indicates that positive steps have been taken. Indeed, there have been marked 23
  • 24. declines in the PM levels in Metro Manila despite the increasing number of vehicles inthe region. This is attributed mainly to the government’s phase out of leaded gasolinewhich has been successfully implemented. In addition, the emission standards weretightened to comply with Euro 2 standards. The government also continues to review andrevise the allowable emission limits for vehicles equipped with compression ignition andspark ignition. This should significantly limit increases in particulate matter levels fromthe mobile sources. Currently, the country also has an existing Motor Vehicle Inspection System(MVIS) which requires motor vehicles to pass emission testing prior to registration.Emission testing is performed either by private emission testing centers (PETCs) or bythe LTO. For private vehicles, there are over 300 PETCs all over the country that conductthe emission testing while for public utility vehicles, the LTO MVIS is offering emissiontesting services at lower costs (EMB-DENR, 2005). The Philippines also has an existing smoke belching program that was establishedto enforce motor vehicle emission standards through roadside inspection andapprehension of violators. Teams which were trained by a multi-agency group led byMMDA and LTO implements the initiative (EMB-DENR, 2003). On the ground, thisprogram could be improved with solid support from the local government units. Localordinances, capacity building, and roadside apprehension are best handled by themunicipal and city governments. The benefit-transfer BCA of an inspection and maintenance program for dieselvehicles done for the Philippines by Larsen (2008) reflects a B-C ratio of 3.9. Thisindicates that in terms of health benefits (averted loss in human lives), sound maintenanceand inspection program delivers almost four times the cost of implementing such aprogram. This supports conventional wisdom regarding the need for sufficient andeffective vehicle emission monitoring and regulation to address air pollution from mobilesources.From two-stroke tricycles to four-stroke tricycles The popularity of the two-stroke tricycles in the country is a major concern, airpollution-wise. Many motorcycle-drivers prefer the two-stroke over its four-strokecounterpart because they are more powerful, and often times less expensive. Tricycles—which oftentimes are two-stroke, and a very popular mode of public transportation—areubiquitous and will most likely remain popular in generations to come. The social cost ofusing two-stroke tricycles, however, remains unaddressed satisfactorily. Aside from thenoise pollution they create, a significant volume of particulate matter is from these two-stroke tricycles. The challenge is how to approach this emission problem and create anincentive system to entice two-stroke drivers and owners to switch to less pollutingmodes of transportation, or at the very least, to properly maintain their motorcycles andreduce emissions. With barely minimum wage, the tricycle drivers do not have enoughmoney for tricycle maintenance. There is also very little incentive to conductmaintenance operations since most tricycle drivers do not own the units they drive. Moreoften than not, an operator owns the tricycle units and a single unit is being shared bythree to four drivers (Camagay, et al, 2005). 24
  • 25. The social benefit of the switch is potentially large. In the strategy scenariosevaluated by Subida et al (2005), switching from the two-stroke to the four stroketricycles (4-STC) under several assumptions will result in an 80 percent reduction in PMemissions from these vehicles. Realistically, however, switching from 2-stroke to 4-stroke tricycles for the Philippines is very difficult, although not impossible. The biggestissue is cost, not just in terms of providing the funds to help finance the switch, but alsoto promote the acceptability of the program among the citizens by providing informationand awareness. In the short-run, the government can do a bit more drastic action by, forexample, banning the introduction of new two-stroke tricycles into the system whileproviding inspection and maintenance services to the existing two-stroke tricycles.Owners of “retiring” two-stroke vehicles should also be encouraged to make the switch;but this entails financing. As an example, the city government of San Fernando in LaUnion offered a loan package to encourage the shift from two-stroke tricycles to 4-STCs.Tricycle operators were offered an interest-free loan amounting to P9,000 payable withinone year for the down payment on the purchase of 4-STCs. Old two-stroke tricycles withage ranging from 20 years old and above were phased out (San Fernando CityGovernment, undated). As of July 2005, a total of 643 two-stroke units were convertedinto 4-strokes, of which 97 units received financial assistance (Ortega, undated).Installation of pollution control devices Larsen (2008) used benefit-transfer to determine if retro-fitting of in-use dieselvehicles with diesel oxidation catalysts (DOC) or diesel particulate filters (DPF) makeseconomic sense for the Philippines12 (Refer to Annex 2 for the complete paper). Usingthe experience of Mexico, Peru, and Senegal as the basis for the analysis, the benefit-costanalysis indicates that the benefits (in terms of the economic values of averted prematuredeaths calculated using VSL) of a retro-fitting program more than outweigh the averagecosts of adopting the technologies for diesel vehicles. A summary of the BCA results forretro-fitting of in-use diesel vehicles in the Philippines is shown below13:12 Effective functioning of DOCs and DPFs requires diesel with a maximum sulfur content of 500 and 50ppm, respectively.13 Larsen applies a VSL of US$109,000 to the Philippines (reflecting GNI per capita in 2007) for valuationof mortality. 25
  • 26. Table 8 - BCA-ratios for Cases of Retro-fitting of In-use Diesel Vehicles in the Philippines Diesel Oxidation Catalysts (DOC) BCA Ratio Old buses 6.54 Large buses 6.74 Buses 4.12 Newer buses 2.97 Old delivery trucks 2.23 Newer delivery trucks 1.81 Diesel Particulate Filters (DPF) High usage taxis 5.30 Old buses 2.80 Large buses 2.89 Newer buses and delivery trucks 1.47 Source: Larsen, 2008. Vehicle emission technologies are useful short term interventions while thecountry is building capacity, awareness and adoption of cleaner fuels. As such, a nationalprogram that requires vehicles (new and in-use), especially public utility vehicles such asthe jeeps, buses and tricycles—to install pollution control devices must be implemented. There are several pollution control devices being offered in the market today.Kojima and Lovei (2001) note that for gasoline powered vehicles, catalytic converters arethe most effective in reducing exhaust emissions. As much as 95% reduction in CO andhydrocarbon emissions and around 75% NOx reduction can be achieved if the three-waycatalytic converters are efficiently used. However, according to Kojima and Lovei(2001), there are several pre-requisites for this option to work successfully: wide use ofunleaded gasoline; low sulfur level in gasoline; emission standards and adjustment periodto meet these standards; and effective I/M programs. Along with improvement in fuelspecifications, particulate traps or filters can also be used for diesel powered engines.Buses and jeepneys can be fitted with particulate traps to reduce emissions. Cost is one of the main concerns regarding the implementation of thisintervention. Vehicle emission technologies entail additional costs to vehicle owners.Moreover, given certain technologies, lower emissions come at the price of fuelefficiency making installation of emission technologies even more costly. While newervehicle imports come with installed catalytic converters, the problem lies with oldervehicles (Gwilliam, et al., 2005). One way to encourage owners of vehicles (especiallythe old units) to install pollution control devices is to strictly implement compliance withemission standards. If emission standards are being strictly enforced through a wellfunctioning I/M system, vehicles owners are left with no choice but to install pollutioncontrol devices to avoid apprehension or the risk of the vehicle units not being registered. 26
  • 27. In addition, the government can remove the barriers that prevent the entry of anti-pollution technologies or impose lower tariffs (if not zero) on the importation of emissiontechnologies to help ease the price in the domestic market (Kojima and Lovei, 2001).Rehabilitation of Current Traffic Management System Traffic congestion is a ubiquitous phenomenon in the major cities in thePhilippines. The length of time a vehicle is on the road is the most significant factor inthe contribution of the vehicle to particulate matter emission. As such, the minimizationof traffic in the country will improve the level of particulate matter released by vehiclecombustion in the air. The current traffic management system in the Philippines hasimproved the traffic situation in the country—especially in Metro Manila—but additionalefforts are needed to completely eliminate regular traffic congestion in the major cities.To illustrate the potential of traffic management, a study conducted in Bangkok andKuala Lumpur in 2004 revealed that the reduction in emissions from the installation of 3-way catalytic converters in 50% of the cars in these cities can be achieved by increasingvehicle speed from 12-15 km per hour to 30 km per hour (Kojima and Lovei, 2001). Strategies that can greatly improve flow of traffic include the following:coordinated signals/traffic lights, channelization, reversible lanes, one-way street pairs,and other traffic control device, area licensing schemes, parking controls, exclusivepedestrian zones, vehicle bans (Faiz, et. al, 1990); and segregated busways (Gwilliam, et.al, 2005). Potential of traffic management in reducing pollution is no doubt very effective inthe short run but caution should be exercised in the long run. Reduced travel timeencourages more trips and thus translates into higher emissions. For example, afterincreasing capacity of road networks in United Kingdom and United States additionaltraffic was generated. About half of the 2.7 percent growth in traffic in the US can beattributed to the additional roads that were constructed. Traffic management is onlyeffective to the extent that it does not create additional traffic. When it does, policies toredirect traffic flow, especially away from environmentally sensitive locations should beenforced (Kojima and Lovei, 2001).Investments in Additional Mass Transport System Investments in additional mass transport systems such as additional electric trainswill significantly reduce the public’s reliance on jeepneys and tricycles which arenotorious for outdoor air pollution emissions. Currently, there are three light rail transitlines in operation/available in Metro Manila, which service the population of themetropolis daily as described below in Table 9: 27
  • 28. Table 9 - Light Rail Transits Lines in the Philippines Length/RidershipLRT Line 1 15-km line / 300,000 passengers per dayLRT Line 2 13-km / 200,000 passengers per dayEDSA-MRT 17-km / 400,000 passengers per daySource: ADB, 2006. A number of authors have suggested the use of trains and railways as an effectivestrategy combating air pollution (Gwilliam, et al., 2005; Ostro, 2004; Kojima and Lovei,2001; Subida, et al., 2005). By expanding the railway network, it is expected that thenumber of commuters using the LRT/MRT will increase. With a larger number of thepopulation using non-motorized transport, volume of traffic will be reduced and thus helpin lessening outdoor air pollution. The projections made by Subida, et al (2005) showthat in 2015 (under several assumptions), the use of metro railways will generate 18.2percent and 13 percent reduction in SPM and CO2 emissions respectively. The costs ofthis intervention, on the other hand, are summarized below in Table 10:Table 10 - Proposed Railway Projects with project costs (in USD millions)Railway Route Distance Fixed Cost Variable Cost TOTALLine (km) (Operating and Maintenance)LRT line 6 South extension of 30 km 600 750 1,350 line 1MRT line 3 North Ave- 12 km 306 261 567extension Navotas; Taft- ReclamationMRT line 2 Recto-North 15.7 km 351 182 533(east west harbor; Santolan-extension) MasinagMRT line 2 Masinag-Antipolo 22.8 km 288 150 438MRT line 4 Recto-Novaliches 26 km 724 646 1370North Rail PNR line 45.5 km 589 649 1238MCX PNR Line 554 996 1550Total Cost 3,412 3,634 7,046Source: JICA in Subida, et al, 2005. However, there are several issues that need to be addressed when implementingthis intervention. First, MRT and LRT operations are financed heavily by governmentsubsidies. The Inquirer reported that MRT for example receives approximately P6.8 28
  • 29. billion subsidies per year. This put a lot of pressure on the fiscal position of thegovernment. Therefore, to prevent perverse use of subsidies, great caution should beexercised during project conceptualization and contract design. For the proposed railwayprojects, the government should avoid taking on risks beyond its control to preventincurring huge amount of contingent liabilities. Second issue is the setting of fare rates. In theory, the fare rate should reflect thetrue costs of service being provided. However, this is not a viable option in practice forseveral reasons: political and demand elasticity considerations. Focusing on the MRT, the fare rate has been set very low, revenues from whichare not enough to cover the operating expenses. Table 11 shows the financial summary ofMRT Line 3 Operations.Table 11 - Financial Summary of MRT Line 3 Operations (in million pesos) CY 2003 CY 2004 CY 2005Total Expenses 6,500.00 6,700.00 8,000.00Revenues 1,600.00 1,800.00 1,900.00 Development Rights revenues 12percent 17percent 17percent Farebox revenues 88percent 83percent 83percentAmount being subsidized by the P44.23 P39.94 P49.57Government per passenger $0.88 $0.8 $0.99Total Ridership 112,653,067 122,483,642 121,753,952Source: Morales-Mariano (http://www.cleanairnet.org/baq2006/1757/docs/SW7_2.ppt) In order to make the operation of an additional MRT feasible, it would benecessary to increase the current fare and reduce the subsidy that the government pays tokeep it afloat. Morales-Mariano (http://www.cleanairnet.org/baq2006/1757/docs/SW7_2.ppt)suggested that the optimal fare rate is around PhP 14.40-19.90. The average optimal fareof P17.15 generates the lowest subsidy required (PhP 6.449 billion). Increasing the fare toan average of P17.15 will not result to increase traffic volume and road congestion.However, beyond this amount, revenues will begin to decrease as 52 percent of thepassengers will shift to buses and around 2 percent will shift to cars. Martinez and Tolentino (2007) estimated the optimal fare using a sensitivityanalysis. Their study revealed that the optimal fare is around PhP18.15 in 2007. This farerate maximizes farebox revenues and minimizes the subsidy. Beyond this amount,subsidies begin to increase as revenues fall. It is expected that there will be oppositionagainst building another MRT that will be subsidized heavily by government, especiallyif the subsidy is substantial. Without the subsidy, however, the MRT fare would be moreexpensive than the jeepneys and buses that ply the same route, dampening the impact ofthe expansion of the electric train on the particulate matter emission. Additional studiesmust therefore be done to find a solution to the fare increase problem. Finally, a summary of activities related to reducing outdoor air pollution was doneby the Metro Manila Air Quality Improvement Sector Development Program 29
  • 30. (MMAQISDP) in 2003. These figures were inflated to reflect the current costs of creating the same projects, as shown below in Table 12: Table 12 - Cost Estimates for the Metro Manila Air Quality Improvement Sector Development Program (MMAQISDP) in million USD 2003 Prices 2007 Prices Item FE LC Total FE LC TotalRoad Rehabilitation 19.52 19.52 39.04 28.13506 28.13506 56.2701Traffic EngineeringManagement 9.01 11.64 20.65 12.98652 16.77726 29.7638Ambient Air QualityManagement 10.59 1.96 12.55 15.26385 2.825037 18.0889Public Health Monitoring 0.15 0.01 0.16 0.216202 0.014413 0.23062Anti-smoke Belching 0.5 0.05 0.55 0.720673 0.072067 0.79274Capacity Building 7.46 5.36 12.82 10.75244 7.72561 18.478Consulting 6.06 5.06 11.12 8.734552 7.293207 16.0278Program Administration 4.61 4.61 0 6.644601 6.6446Contingencies 6.43 6.52 12.95 9.26785 9.397571 18.6654Interest and Other Charges 7.86 7.86 11.32897 0 11.329TOTAL 67.58 54.73 122.31 97.40611 78.88482 176.291Note: FE- foreign exchange;LC- local currency Source: 2002 National Air Quality Status Report. The 2007 prices are the author’s own computation given annual inflation rate and exchange rate data from BSP and the 2003 data from the 2002 National Air Quality Status Report. Indoor Air Pollution The WHO estimates indoor air pollution as the 8th most significant risk factor in the global burden of diseases. It contributes around 3.7 percent of the disease burden in developing countries and ranks fourth behind malnutrition, unprotected sex, and water, sanitation and hygiene, as the main causes of premature deaths (WHO websites: http://www.who.int/ indoorair/health_impacts/burden_global/en/index.html; http://www.who.int/mediacentre/factsheets/fs292/en/). Indoor air pollution-related illnesses result from both short and long-term exposure to smoke inside the home—smoke that originates from cooking with solid fuels, cigarette smoking and other sources. In this study, however, the focus in is only on households’ solid fuel use as the source of indoor air pollution. The choice of solid fuel use as the basis of the analysis is borne of the practical consideration—the data are available on solid fuel use, but no sufficient data on cigarette smoking inside the home— 30
  • 31. and the appropriateness and rationale for intervention. The WHO reports that the impactof indoor air pollution (from solid fuel use for cooking) on individuals’ health issignificant, causing an estimated 1.6 million deaths globally due to respiratory diseasesand lung cancer. Public health specialists who were interviewed for this report believe thatcigarette smoke is the largest contributor to indoor air pollution; even as theyacknowledge that smoke from cooking fuel is a significant source of IAP as well. Thereis no sufficient data on cigarette smoking—i.e., epidemiological studies that estimated therelative risk ratios for cigarette smoking in the Philippines—in the household to conductan economic analysis. As such, this study is limited to analyzing the impacts of exposureto smoke from fuel used for cooking even as the author acknowledges the importance ofcigarette smoke on the deterioration of human health in the Philippines14. But despite theidea that solid fuel is only secondary to cigarette smoke as the sources of indoor airpollution, its impact on health and life is huge. It is expected, however, that as more databecome available (particularly, technical and household data on the impacts of exposureto cigarette smoking in the homes) that these valuations will be revised to include theseinformation. We begin the formal discussion by characterizing solid fuels—at least based onhow it is defined in this report. Desai, et al. (2004) defines solid fuel use as “thehousehold consumption of biomass (dung, charcoal, wood, or crop residues), or coal.”Results of the 2004 Household Energy Consumption Survey (HECS) show that thepercentage of households using electricity and LPG increased from 1995 to 2004 whilethe percentage of household using fuelwood, charcoal, kerosene and other biomass fuelsdeclined as illustrated in Figure 11 below:Figure 11 – Percentage of Households Use of the Type of Cooking Fuel, 2004 100 75 50 25 0 Electricity LPG Gasoline Diesel Kerosene Fuelwood C harcoal Other Biomass Residue 1995 2004 Source: Household Energy Consumption Survey, 200414 Another limitation of the study is that it does not include the incidence of IAP-related illnesses in theworkplace. The focus of this section is solely on the household members’ exposure to smoke from cooking,which in turn is based on the use of cooking fuel, cooking practices and ventilation of the home. 31
  • 32. The literature on indoor air pollution suggests that the bulk of the environmentalburden of disease due to solid fuel is borne by low-income households in rural and peri-urban areas—sectors that typically have inadequate access to clean and affordable fuels.The results of the 1995 HECS presented in Figure 12 show that solid fuel use is indeedhigh in rural areas. The 2004 HECS data however, do not include a classification ofhouseholds according to urbanity, but nevertheless supports the claim that a big portionof poor households use solid fuel such as wood, charcoal and other biomass residue(Figure 13). Additional information is needed to verify if it is the rural poor or the urbanpoor that is exposed to air pollutants from solid fuel use. Anecdotal evidence, however,point to the incidence of solid fuel use to be higher in the rural areas this is the traditionaluse of fuel in the rural sector, and this is also the cheapest and most accessible cookingfuel available.Figure 12 – Household Fuel Use by Urbanity, 1995 Household Fuel Use, By Urbanity, 1995 100% Percentage of households 75% Philippines 50% Urban Rural 25% 0% Electricity LPG Gasoline Diesel Kerosene Fuelwood Charcoal Biomass Residues Source: Household Energy Consumption Survey, 1995. 32
  • 33. Figure 13 – Household Use of Solid Fuel by Income Class, 2004 PhP25,000 and over PhP15,000-24,999 PhP10,000-14,999 PhP5,000-9,999 Less than PhP5,000 0% 25% 50% 75% 100% Fuelwood C harcoal Other Biomass ResidueSource: Household Energy Consumption Survey (HECS), 2004. The data on PM emissions from solid fuel use is wanting in the Philippines. Onemajor source is the ADB (2004) which looked at the indoor PM10 levels in rural andurban households. It did not have, however, a definitive conclusion on the sources of PMlevels within the household. It is also difficult to assess without additional analysis if thePM levels found inside homes are from the “trans-boundary” movements of fumes fromoutdoor air pollution sources. Based on the available information reviewed for this report, it is hard to make adefinitive conclusion on indoor air PM levels especially since the sites included in thestudies are few—the data collection on the PM10 levels from the indoor sources are doneregularly but not at the ideal level of frequency. Some deductive results, however, can bemade and used to paint a general picture of the link between solid fuel use and exposureto particulate matter. Using data from HECS and combined with emission factorscollected from the different technical literature available, an estimate of PM emissionsfrom solid fuel use of households is calculated. Table 13 summarizes these calculations.Table 13 – Particulate Emissions from Household Cooking, 2004 PM Emission Total PM Fuel Type 2004 Consumption Factor EmissionsFuelwood 10.694 M tons 15.30 g/kg 163,618 tonsCharcoal 0.888 M tons 36 mg/kg 32 tonsBiomass Residues 1.351 M tons 7.40 g/kg 9,997 tonsSource: Author’s estimates based on HECS data. 33
  • 34. Most health outcomes that have been associated with exposure to indoor airpollution have been limited to children younger than 5, women older than 30, and tosome extent, men older than 30. This trend is borne of the fact that the individuals whobelong to these age groups are the most likely to spend the most time inside the home.With this information at the forefront, particular attention to young children and adultwomen is given, since they are the people most likely to suffer from illnesses caused byindoor air pollution. The estimates done on the number of cases of IAP-related illnessessupport this conclusion, as the discussion in this section will illustrate later. To start off the discussion, this study looks at the existing data on household fueluse, and found that 42 percent of households in the Philippines use fuel wood as theirprimary cooking fuel (Figure 14). To calculate the population that has been exposed toindoor air pollution, we first exclude from the households that used any of the three solidfuels of interest in 2004, but used other energy sources as their primary cooking fuel ayear prior to the actual survey. Figure 15 shows that a little more than 48 percent of thehouseholds in the country are exposed to indoor air pollution, based on solid fuels used asthe primary cooking fuel. As expected, the proportion is much higher in the rural areaswhere cooking using biomass and fuel wood, is the traditional and practical method—solid fuel is easily accessible and cheaper in the rural areas than LPG and other cookingfuel.Figure 14– Primary Cooking Fuel for Households, 2004 Others Electricity Charcoal 2.1% 1.3% 7.2% LPG 42.7% Fuelwood 42.0% Kerosene 4.8% Source: Household Energy Consumption Survey (HECS), 2004. 34
  • 35. Figure 15 – Households Exposed to Indoor Air Pollution (in percentage) Source: Author’s estimates based on HECS data. The numbers in Figure 15 illustrate the prevalence of the use of solid fuel in ruralareas, and that a relatively small proportion of households in Metro Manila can beconsidered exposed to indoor air pollution. However, there is a need to adjust thesefigures by the associated ventilation factors because cooking practices and the structuralcharacteristics of houses in the Philippines may mitigate the exposure of Filipinohouseholds to indoor air pollution and the subsequent health outcomes. Desai, et al.(2004) suggest using a ventilation factor of 0.25 for households that use improved stovesor cook outside, and a ventilation factor of 1.00 for those that use traditional stoves. Aventilation factor of 0.25 means that the health effects of indoor air pollution emanatingfrom cooking fuel are expected to be reduced by three quarters as result of the ventilationconditions. Saksena et al. (2005) summarized these mitigating ventilation conditions tobe based on a variety of factors including the distance of rooms and walls, height ofceiling, size of windows, materials used to build the house, and whether the householduses improved stoves or not. Taking into account the “airiness” of the areas wherecooking is done even if the stoves were traditional, a ventilation factor of 0.25 is used forurban and rural areas outside Metro Manila as households in these areas typically do theircooking outside their houses. Metro Manila households that use solid fuel, however, areassigned a ventilation factor of 0.5 since they would normally be found in informalsettlements where houses are crammed together. With the above assumptions, the proportion of the cases of the health outcomesoutlined above that can be attributed to exposure to indoor air pollution is computed. Toaccomplish this, attributable factors were estimated based on the relative risk ratios—calculated based on gender, age, and specific illness—obtained from several 35
  • 36. epidemiological studies are used. The pollutant in discussion is PM resulting from thesmoke from solid fuel use in the households. Adjustments on the potency of exposure tosmoke are made by integrating the (significant) impact of household ventilation on thedegree of exposure. The computed weighted-AFs for each health endpoint used in thisstudy are summarized in Table 14.Table 14 – Attributable Fractions Used for Morbidity Cases per Illness Risk Ventilation Attributable Health Endpoint Ratios Factor FractionsAcute lower respiratory infections, children 1.8 0.25 0.1009younger than 5 and women older than 30.Chronic obstructive pulmonary diseases, women 3.2 0.25 0.2359>= 30Chronic obstructive pulmonary diseases, men >= 1.8 0.25 0.100930Tuberculosis, all >= 15 1.5 0.25 0.0656Sources: AFs calculated by author, based on risk ratios from Desai, et al (2004) andDherani et al (2008). The results of the calculations for morbidity cases are shown in Figure 16. Table15 shows in more detail the number of cases of acute bronchitis, ALRI and pneumonia,COPD and respiratory tuberculosis, given the different age groups. It must beemphasized that the estimates of cases (as well as the inclusion of the specific diseases)were based on the available data on relative risk ratios (and the consequent computationfor attributable fractions) and on the total number of cases of each of the diseases.Figure 16 – Morbidity Cases Attributable to IAP, By Gender, 2003Source: Author’s calculations. COPD refers to chronic obstructive pulmonary disease. 36
  • 37. Table 15 - Cases of IAP-related Illnesses by Age Group, 2003 Acute ALRI and COPD Tuberculosis Bronchitis PneumoniaAge 0 to 4 101,949 289,753 0 0Age 5 to 14 0 0 0 0Age 15 to 19 0 0 0 716Age 20 to 29 0 0 0 1,173Age 30 to 64 18,630 22,842 2,670 3,60465 and older 4,900 8,839 1,558 1,139TOTAL 125,479 321,434 4,228 6,631Source: Author’s calculationsThe Economic Costs of IAP-related Morbidity As with the calculations for the economic costs of OAP, the estimates for thecosts to society and the economy of indoor air pollution related illnesses include directcosts to households (based on treatment-seeking behavior) and the indirect costs (lostincome due to days off from work due to illness). The estimates of economic burdeninclude the cost to the government health care system in terms of subsidy to PhilHealthmembers’ medical costs15 and the per-patient hospitalization subsidy for government-owned hospitals. Figure 17 illustrates the direct treatment costs to households for theindoor air pollution-related illnesses in 2003, while Figure 18 describes the costs that areshouldered by the government.15 It must be noted that only 70 percent of cases in Metro Manila and in urban areas, and 20 percent ofcases in rural areas, are subsidized by the government through PhilHealth. The PhilHealth also indicatedthat only (an average of) 35 percent of costs incurred by its members are paid by the agency. 37
  • 38. Figure 17 – IAP Cost to Households of Treatment (Net of Public Health CareSubsidy), 2003 ALRI and Pneumonia PhP 415 M 89% Respiratory Tuberculosis PhP 19 M 4% Acute Bronchitis COPD PhP 20 M PhP 13 M 4% 3%Source: Author’s calculations.Figure 18 - Government Health Care Subsidy per IAP-Illness, 2003 ALRI and Pneumonia PhP 177 M 93% Respiratory Acute Tuberculosis COPD Bronchitis PhP 6 M PhP 5 M PhP 2 M 3% 3% 1%Source: Author’s calculations. It is also estimated that the Philippine economy loses the productive contributionof working-age patients when they take time off to get treatment, or to take care of a sickchild. Lost productivity resulting from IAP-related illnesses is calculated based on the2003 per capita GNI of the Philippines, with the figures adjusted for stay-at-home 38
  • 39. mothers. Figure 19 illustrates the computed indirect costs from the diseases mentionedabove. Figure 19 – Lost Income Due to IAP-related Illnesses, 2003 ALRI and Pneumonia PhP 199 M 55% Respiratory Acute Tuberculosis Bronchitis PhP 33 M PhP 49 M 9% 14% COPD PhP 79 M 22% Source: Author’s calculations. Total foregone income due to indoor air pollution amounted to PhP 360 million(USD 6.6 million) in 2003, a significant amount for a country like the Philippines,especially if we consider the fact that majority of these cases occurred in the rural areaswhere most of the poor reside. In total (treatment cost and foregone income and timelosses), the calculations show that IAP-related illnesses cost the Philippine economy in2003 a total of PhP 1.0 billion (USD 19.0 million) in morbidity costs (Figure 20).Figure 20 – Total Economic Cost of IAP-related Morbidity, 2003 ALRI and Pneumonia PhP 791 M 77% Respiratory COPD Tuberculosis Acute PhP 114 M PhP 56 M Bronchitis 11% 5% PhP 71 M 7%Source: Author’s calculations 39
  • 40. Figure 20 also provides insights as to which diseases are more likely have the most economic impacts as a consequence of IAP. This should be used as the basis for any mitigation and adaptation strategies of policy managers. Economic Costs of Premature Deaths due to IAP This study used the AFs calculated for morbidity cases to estimate mortality from IAP. A summary of the AFs calculated used to calculate the cases of premature deaths from IAP-related illnesses is shown in Table 16. The details of the adjustments are contained in Annex 1. The total number of mortality cases was calculated using the mortality data from the Philippine Health Statistics (PHS) as base figure. The PHS base data were adjusted by 2.42 (based on WHO estimates) for children under 5 five years old and 1.05 for the other age groups. This was done in consideration of the fact that reporting of deaths in the Philippines is understated. Table 16 – Attributable Fractions Used for Mortality Cases per Illness Risk Ventilation Attributable Health Endpoint Ratios Factor FractionsAcute lower respiratory infections, children younger than 5. 1.8 0.25 0.1009Chronic obstructive pulmonary diseases, women >= 30 3.2 0.25 0.2359Chronic obstructive pulmonary diseases, men >= 30 1.8 0.25 0.1009Lung cancer (from exposure to biomass smoke), women >=30 1.5 0.25 0.0656Tuberculosis, all >= 15 1.5 0.25 0.0656 Source: AFs are the author’s estimates based on RR’s from Desai, et al (2004) and B. Larsen (2008). It is estimated that premature deaths accruing to IAP-related causes cost the Philippine economy PhP 3.7 billion (USD 68.0 million) in lost productivity, or PhP 23.6 billion (USD 434.7 million) when VSL is used for valuation of mortality. These results are detailed in Figure 21 below, wherein each illness considered for this section is shown. NOTE: According to your summary table at the beginning of the report, this VSL usd figure seems to be both mortality and morbidity. Please check. 40
  • 41. Figure 21 - Cost of Premature Deaths due to IAP, 2003 (HCV) PhP 2.1 B 2,500 (PhP 5.0 B) 2,000 1,500 PhP 927 M (PhP 6.8 B) PhP 613 M 1,000 (PhP 10.2 B) PhP 38 M PhP 20 M 500 (PhP 463 M) (PhP 48 M) 0 Tuberculosis Lung C ancer Pneumonia Acute Bronchitis C OPD Source: Author’s calculations. The figures in parentheses are VSL estimates. The data also show that the most productive members of society (age group 20-64years old) comprise a significant share of the deaths (34 percent of 5,772 prematuredeaths) related to IAP, as shown in Figure 21 and Table 17. An alarming observationthat can also be made from the result is the high number of cases of children who died in2003 due to IAP-related pneumonia. Since pneumonia is generally treatable and non-fatalif addressed properly, the high number of cases suggests that many cases of pneumoniaare either dismissed by parents as “nothing to worry about”, or, more likely, treatment isinaccessible because of poverty or distance from health service providers. Additionalinformation is needed to verify if these hypotheses are correct, but the response to thisissue from policy makers is vital.Figure 22 – Mortality Cases Due to IAP Grouped According to Working and Non-working Age Groups, 2003 Source: Author’s calculations based on Philippine labor data. 41
  • 42. Table 17 - Mortality Cases Due to IAP by Specific Age Group, 2003 Respiratory Lung Acute Pneumonia COPD Tuberculosis Cancer BronchitisYounger than 1 0 0 645 9 0Age 1 to 4 0 0 629 3 0Age 5 to 14 0 0 0 0 0Age 15 to 19 19 0 0 0 0Age 20 to 29 82 0 0 0 0Age 30 to 64 937 59 0 0 89465 and older 707 60 0 0 1,725Not Reported 2 0 0 0 1Total 1,745 119 1,273 12 2,620Source: Author’s calculations. The number of mortality cases for age groups 30 andolder was also not estimated because of the insufficiency of information. Another significant result is that the highest number of cases of deaths fromCOPD due to indoor air pollution is among the elderly—double the number of COPDcases among the working-age group. Additional information, however, is needed toverify if the number of cases is purely due to exposure to indoor air pollutants, or if thereare mitigating circumstances that have made the elderly more vulnerable to fatal cases ofCOPD. The working-age adults, on the other hand, suffer mostly from IAP-relatedrespiratory tuberculosis—an illness which is pathological, unlike the other illnesses indiscussion which are primarily due to exposure to particulate matter. This is explained bythe fact that since the cause of the IAP-related illnesses included in this study is long termexposure to solid fuel from cooking, the exposed population is majority composed of thenon-working age groups who are at home and potentially exposed to smoke fromcooking. It must be noted that occupational exposure—a significant factor in IAP-relatedillnesses, according to public health experts—is also not included in the analysis due toinsufficiency of epidemiological data.Suggested Interventions Since the analysis on indoor air pollution impacts centers solely on the solid fueluse, the suggested interventions in this section address the exposure to the smoke fromsolid fuel that is generated from the home. These interventions are therefore limited tothree basic groups: improvement of ventilation, change in cooking practices, or change ofthe kind of stoves used in the home. 42
  • 43. Promoting improved household living environment Household living environment (i.e. house structure, room layout) is one of themost important factors affecting the level of exposure of a household to indoor airpollution. House lay out design greatly affects the concentration and distribution ofpollutants inside the homes. There are significant differences in pollutant concentrationbased on the location of cooking areas and kitchen (Zhang and Smith, undated; Jin et al2005; and Qin, et al ,1991). It is apparent, therefore, that a simple but logical solution tothe issue of indoor air pollution inhalation is to have an outside kitchen. This is notalways possible, however, because of the costs. Since most of the users of solid fuelbelong to the poor with very small dwellings, to have a separate kitchen for cooking isnot an option for the very poor. There are other ways to increase ventilation without being too costly orinconvenient. These include “increasing the number of windows/openings in the kitchen,providing gaps between the roof and the walls, or moving the stove out of the living area”(Desai, et al 2004). Remarkable benefits from a “cooking window” or a “fume cupboard”have been noted by Nystrom (as cited in WHO, 2000). The usefulness of hoods withflues, enlarging and repositioning windows and enlarging eaves in rural Kenya has beenstudied. These interventions (especially the use of hoods) which have been developedwith the participation of local women were very effective in reducing pollution andpersonal exposure to harmful pollutants (WHO, 2000). In order to promote the adoptionof these interventions among the target households, an information drive—a campaign toinform, educate and communicate to the target sector—about these alternatives must becommunicated to the households. If done correctly, this could change the behavior ofhousehold members regarding indoor cooking and the use of solid fuel. It must be emphasized that behavior change is the key element in the adoption ofthe interventions. To motivate people to adopt certain technologies and to alter theirbehavior, the change must make sense to them; the benefits derived from these changesmust be obvious to the target sectors. Intervention in the form of marketing, advertising, and education come into playwhen influencing behavior. Education in particular is very important in conveying thevalue of cleaner kitchens and air to households and thus can help reduce the impact ofindoor air pollution (Desai, et al., 2004). This intervention, however, needs carefulplanning as it must be accompanied by pricing strategy to make the alternative cookingtechnologies affordable for the target households.Promoting improved stoves Studies on indoor air pollution exposure prevention have concluded that the use ofimproved stoves lessens exposure to indoor air pollution (Mehta and Shaphar, 2004).Others have highlighted the economic benefit that a household gains from using LPG or 43
  • 44. kerosene. . Biomass stoves approximately costs USD 50-100 per DALY16 avertedaccording to Smith (1998) while Hughes et al., (2001) estimated that introduction ofkerosene or LPG stoves in rural areas costs around USD 150-200 per DALY averted. There is empirical evidence and theoretic bases to the idea that households willonly be enticed to switch technologies when their perceived benefits outweigh the costsof adoption of the new and better technology. While households can directly observe thereduction of emissions or greater fuel efficiency of improved stoves, the monetary valueof these benefits are less apparent (Larson and Rosen, 2000). It is essential, therefore, tocommunicate this information to the target households clearly and in no uncertain termsthrough an information and education campaign. It could help if the community isengaged in designing an improve stove design and technology as this will facilitatefamiliarity of the target households with the proposed changes. Choosing the correct stove to promote is therefore essential to the proposedintervention. As a guide, information from various sources on the cost effectiveness ofimproved stoves is presented in this section. Foremost among these is the study done byHutton, et al (2006) which evaluated the cost and benefits of household energy and healthinterventions using data from 11 developing and middle-income WHO sub-regions. Netintervention costs include intervention costs less fuel savings while economic benefitsinclude health benefits and savings on health care costs, productivity gains due to reducedmorbidity, time savings and environmental benefits. The study assumed a 35 percentreduction in personal exposure based on Naeher, et al, (2000), Bruce et al, (2002), andBruce et al, (2004) as proxy for the possible reductions in health outcomes. The estimate,however, is likely to be very conservative since the 35 percent reduction represents theaverage personal exposure of children in homes using open fires and not the cook’s (i.e.the mother’s) personal exposure. The “improved stove” referred to in this study is thechimneyless rocket stove (a type of stove used in Latin America, some parts of Asia, andAfrica) which is relatively cheap—compared to other improved stoves available(approximately USD 6.0 acquisition cost per piece)—with an estimated useful life of 3years (Hutton et al, 2006).Table 18 - Overview of Costs and Impacts, Time Horizon of Modeled ImpactsVariable Immediate cost or impact Delayed cost or impactIntervention costs Investment costs, such as Not applicable stove purchase cost and cost of house alterations Recurrent costs, such as fuel cost and programme costsHealth benefits and savings ALRI Chronic obstructiveon health care costs Lung Cancer pulmonary disease (COPD)16 WHO describes the DALY (disability-adjusted life year) as a time-based measure of burden of disease.With DALY, the number of years of life lost due to premature death is added to the years of life anindividual lives in states of less than full health. 44
  • 45. Productivity gains due to NA Related to acute lowerreduced morbidity respiratory infections (ALRI) for children, and to COPD and lung cancer for all age groupsTime savings Fuel collection time and Not applicable cooking timeEnvironmental benefits Local and global Not applicable environmental benefits*Future costs and impacts are discounted at a 3 percent discountSource: Hutton et al, 2006 Larsen (2008) calculated benefit-cost ratios (See Annex 2) for programs thatpromote the conversion to improved wood stoves and LPG stoves from unimprovedwood stoves:17 - Scenario I: Conversion to improved wood stove from unimproved wood stove (with an assumption of a 50 percent reduction in health risks as a result of the conversion of households) - Scenario II: Conversion to LPG from unimproved wood stove (with the assumption that the conversion will result in the elimination of all health risks from the use of solid fuel) - Scenario III: Conversion to LPG from improved wood stove (with the assumption that the conversion will result in the elimination of all health risks from the use of solid fuel)Table 19 - Benefit-Cost Ratios of Converting to a New Stove Technology to ControlIAP in the Philippines. Valuation Method VSL & COI HCV & COI Ventilation factor (VF) VF=1 VF=0.25 VF=1 VF=0.25Scenario IImproved wood stove (health benefits 14.5 5.02 3.08 1.00only)Improved wood stove (health & time 18.8 9.32 7.38 5.30savings)Scenario IILPG from unimproved stove (health 2.03 0.70 0.43 0.14benefits only)17 Unimproved wood stoves refer to low fuel-efficiency wood stoves whose smoke is uncontrolled anddirectly emitted into the immediate environment. Improved stoves, on the other hand, are stoves withhigher fuel-efficiency and have provisions to reduce immediate exposure to smoke. 45
  • 46. LPG from unimproved stove (health & 2.63 1.30 1.03 0.74time savings)LPG from unimproved stove (health & 2.83 1.50 1.23 0.94wood cost savings)Scenario IIILPG from improved stove (health benefits 1.02 0.35 0.21 0.07only)LPG from improved stove (health & time 1.32 0.65 0.52 0.37savings)LPG from improved stove (health & wood 1.42 0.75 0.62 0.47cost savings)Source: Larsen (2008). Refer to Annex 2 for the complete paper. Larsen’s results show that the intervention with the highest return in thePhilippines per unit of cost will be the conversion of households from using unimprovedstoves to improved stoves. This is primarily due to the fact that the conversion toimproved stoves is less expensive than the conversion to LPG (even if the health benefitsfrom switching from unimproved stoves to LPG are higher). This highlights thesignificance of the cost to switch to the new stove-technology as an importantconsideration in intervention efforts. Note that in the analysis, the calculations wereadjusted by the associated ventilation factors (VFs) based on the assumptions regardingthe cooking practices and structural characteristics of houses in the Philippines. Two VF-scenarios are assumed as suggested by the literature: 0.25 for households that useimproved stoves or cook outdoor; and 1.0 for households that use traditional stoves. (Seethe Annex for further discussion on ventilation factors and the corresponding AFs). There are several improved stoves being promoted in the Philippines. Theseinclude the Mayon Turbo Stove (advanced conical rice hull stove) developed by REAPCanada (Samson and Lem, undated), rice husk gas stove developed by Engr. Alexis T.Belonio (Belonio, 2005), and Maligaya rice hull stove developed by Philippine RiceResearch Institute (PhilRice, 1995 ). Studies done on these stoves show significantreduction in smoke emitted. There is still, however, an insufficiency indata/documentation on how much reduction in PM, IAP exposure and risk can beassociated with the use of these improved stoves. Currently, these stoves are beingpackaged and promoted as an intervention to reduce green house gas emissions becauseof their potential to decrease CO, CO2, N2O and CH4 emissions. By convertingagricultural wastes like rice hull into fuel, agricultural waste burning is mitigated. Inaddition, these improved stoves are relatively fuel efficient than the traditional stovesbeing employed. However, availability of rice hull, the main source of fuel can be onelimitation. Promotion and adoption of these stoves will only be successful in areas wheresources of fuel are readily available. The rice husk gas stove, developed by Engr. Belonioneeds electricity to run, which could limit its adoption. Thus, there is a need to furtherimprove stove designs to make them flexible enough to suit local conditions—i.e. can runwithout electricity, can use agricultural wastes other than rice hull, and are easy to usecompared to traditional stoves. 46
  • 47. Water Pollution, Sanitation and Hygiene There are seven water pollution, sanitation, and hygiene-related diseases that areexamined in this report, namely: diarrhea, helminthiasis, schistosomiasis, typhoid andparatyphoid, cholera, and viral hepatitis (Hepatitis A). All of these diseases arepathogenic and are widely accepted as attributable to contaminated water and poorsanitation and hygiene. The number of cases of the illnesses in discussion is examined according to thePhilippine households’ access to clean water supply for sanitation and hygiene purposes;and described according to the category levels defined by the WHO based on the paperby Prüss-Üstün, et al. (2004). Table 20 below summarizes these levels with a descriptionof each level as a quick reference:Table 20 – Levels of Households According to Access to Water and SanitationFacilities Environmental Level Description fecal-oral pathogen load VI Population not served with improved water supply and no Very high improved sanitation in countries which are not extensively covered by those services (less than 98 percent coverage), and where water supply is not likely to be routinely controlled Vb Population having access to improved water supply but not Very high served with improved sanitation in countries which are not extensively covered by those services, and where water supply is not likely to be routinely controlled (less than 98 percent coverage) Va Population having access to improved sanitation but no High improved water supply in countries where less than 98 percent of the population is served by water supply and sanitation services, and where water supply is likely not to be routinely controlled IV Population having access to improved water supply and High improved sanitation in countries where less than 98 percent of the population is served by water supply and sanitation services, and where water supply is likely not to be routinely controlled III IV and improved access/quality to drinking water; or High IV and improved personal hygiene; or IV and drinking water disinfected at point of use, etc. II Population having access to improved water supply and Medium to low 47
  • 48. sanitation services in countries where more than 98 percent of the population is served by those services; generally corresponds to regulated water supply and full sanitation coverage, with partial treatment for sewage, and is typical in developed countries I Ideal situation, corresponding to the absence of transmission Very low of diarrheal disease through WSHSource: WHO-Prüss-Üstün, et al (2004). The Department of Health, in its FHSIS 2003 Report, reports that 83 percent ofhouseholds have access to safe drinking water, while 76 percent have access to sanitarytoilets. This puts the whole Philippine population under scenarios IV to VI since nationalcoverage is less than 98 percent. While the FHSIS data contain the number of householdsthat have access to safe drinking water and sanitary toilets across geographical regions,this information is insufficient to be able to come up with the classifications suggestedabove. Hence, the results of the Philippines Demographic and Health Survey 2003 (DHS2003) are used to come up with the proportions of the population for both national andMetro Manila figures that are exposed to the different scenarios.18 Improved water supplies are those that are generally accessible to people and forwhich some measures are taken to protect the water from contamination; improvementsdo not guarantee the safety of the water from these sources. Improvements in sanitationfacilities involve better access and safer disposal of excreta (Hutton and Haller, 2004).Table 21 summarizes the groupings of the responses for these questions in the DHS.Table 21 - Responses to the Demographic and Health Survey, 2003 Source of Drinking Water Sanitation Facility Improved Unimproved Improved Unimproved Piped into dwelling Open dug well Flush toilet (own) Open pit Piped into yard/plot Undeveloped spring Flush toilet (shared) Drop/overhang Public tap River, stream, Close pit No toilet/field/bush Protected well pond, lake, or dam Developed spring Tanker truck or Rainwater peddler Bottled water or refilling stationSource: Created by the author based on the raw survey data and descriptions of thecategories in DHS.18 The DHS asks respondents to identify the source of their drinking water and the type of sanitationfacility. Households are then grouped into the different categories using Hutton’s (2004) definition forimproved water supply and improved sanitation. 48
  • 49. Figures 23 and 24 illustrate the distribution of households in the country and inMetro Manila, respectively, according to the relative ease of access to improved watersupply and sanitation. The data show that a larger percentage of the population in MetroManila has access to both improved water supply and sanitation compared with the wholecountry. A closer examination of the DHS data also yields information that describes thedistribution of the households in terms of urbanity.Figure 23 – Household Access to Improved Water Supply and Sanitation, 2003(National) Unimproved Improved water sanitation and supply and water supply sanitation 5% 74% Improved water supply, unimproved sanitation 10% Improved sanitation, unimproved water supply 11% Source: Author’s estimates based on DHS raw data.Figure 24 – Household Access to Improved Water Supply and Sanitation, 2003(Metro Manila) Unimproved sanitation and water supply 0.2% Improved water supply and Improved water sanitation supply, 81.9% unimproved sanitation 1.4% Improved sanitation, unimproved water supply 16.5% Source: Author’s estimates based on DHS raw data. 49
  • 50. Health endpoints for WSH related illnesses are adopted from the Economics ofSanitation Initiative (ESI) report of the Philippines by the Water Sanitation Program(WSP), World Bank. As earlier pointed out in this section, these illnesses—the basis ofthe calculations for the economic burden of disease for WSH-related maladies—includecholera, diarrhea, viral hepatitis, schistosomiasis, and, typhoid and paratyphoid fever. Theestimates show that diarrhea cases comprise the significant majority of cases of water,sanitation and hygiene related-illnesses. The focus on diarrhea can not be avoided as it isthe most prevalent—and yet preventable—illness due to a poor environmental andhygienic conditions. Utilizing the results of the ESI report and adjusting to integrateadditional information collected in the field to determine the attributable fractions foreach of the diseases mentioned above is estimated and adopted. Attributable fractions fordiarrhea for Metro Manila and the whole country are computed using the proportions ofthe population exposed to the agent of illness, and the relative risks associated with theindividual scenarios. The calculations show that 86 percent of all diarrhea cases in thecountry can be attributed to water, sanitation and hygiene conditions. A summary of theseAFs is presented below in Table 22:Table 22 - Attributable Fractions (AF) for WSH-related Illnesses, 2003 Region Attributable Disease Source Applied Fraction Cholera National 1.00 Pruss Ustun National 0.86 This author Metro Manila 0.86 This author Diarrhea Urban 0.86 This author Rural 0.87 This author Schistosomiasis National 1.00 Pruss Ustun Typhoid and Paratyphoid National 0.50 Pruss Ustun Fever Viral Hepatitis National 0.50 Pruss Ustun Morbidity figures from the Department of Health’s FHSIS Reports were used asthe basis to estimate the number of cases of WSH-related diseases in 2003 excludingdiarrhea. Figures for diarrhea were, in turn, computed using data from the DHS 2003report for children u5 and from WHO regional estimates for population 5+ years of age.Applying the estimated AFs in Table 22 above, the calculations showed that nationally, atotal of 33.5 million cases of WSH-related cases occurred in 2003 (Table 23). 50
  • 51. Table 23 - Total Cases of WSH-related Illnesses, 2003 Metro National Urban Rural ManilaCholera 1,144 263 768 113Diarrhea 33,321,133 4,158,272 11,714,787 17,448,074Viral Hepatitis 23,172 2,455 8,095 12,622Schistosomiasis 51,684 0 5,344 46,340Typhoid and Paratyphoid Fever 65,349 1,854 28,728 34,767Total Cases of WSH 33,462,483 4,162,844 11,757,723 17,541,916 Source: Author’s calculations Approximately 77 percent of these cases were children 14 years of age and younger. As expected, diarrhea made up the majority of the WSH-related diseases, comprising approximately 99 percent of all cases. Table 24 below summarizes the diarrhea figures according to age group and urbanity, while Table 25 lists the morbidity figures for other WSH-related illnesses outside of diarrhea. Table 24 - Number of Cases of Diarrhea by Age Group, 2003 Metro Age Group National Urban Rural Manila Younger than 1 4,764,676 651,834 1,681,840 2,431,002 1 to 4 14,691,955 1,867,656 5,176,062 7,648,237 5 to 14 6,125,743 612,723 2,167,659 3,345,361 15 to 19 264,366 30,223 92,378 141,765 20 to 29 433,304 49,542 151,409 232,353 30 to 64 6,567,969 902,905 2,276,773 3,388,291 65 and older 473,119 43,389 168,665 261,066 Total 33,321,133 4,158,272 11,714,787 17,448,074 Source: Author’s calculations based on the base data from NDHS (2003) for children under 5 years of age, and WHO regional data for the population 5+ years of age. For the details on the methodology, refer to the Annex. 51
  • 52. Table 25 - Number of Cases of WSH-related Illnesses (excluding Diarrhea) by AgeGroup, 2003 Typhoid and Viral Schistoso- Cholera Paratyphoid Hepatitis miasis FeverYounger than 1 138 303 0 9621 to 4 339 2,102 1,230 8,5185 to 14 349 7,649 17,114 20,04515 to 19 41 2,216 4,889 6,11320 to 29 67 3,631 8,010 10,01830 to 64 142 6,603 17,788 17,67565 and older 70 667 2,653 2,018Total 1,144 23,172 51,684 65,349 Source: Author’s calculations It must be noted that the cases of diarrhea and other WSH-related illnesses thathave been reported in the PHS are lowest in Metro Manila, and are highest in the ruralareas. Another striking piece of information is the high prevalence of schistosomiasis19 inrural areas, while Metro Manila reported no cases of the illness and the other urban areasreported a low figure (only 3.5 percent of the cases in the rural areas). This insight isimportant because it highlights the “critical or high risk” areas that must be targeted bypolicy and program development if specific illnesses are a consideration.Economic Costs of WSH-related Morbidity Similar to what was done in the estimation of the economic costs of air pollution-related diseases, the economic impacts of WSH-based illnesses are divided into three:morbidity (which is composed of direct and indirect costs) , and the share of governmentin subsidizing the treatment of these diseases. The direct costs refer to the treatment costseach individual pays for, based on estimated treatment-seeking behavior. Indirect costs,on the other hand, refer to the lost income of working individuals and mothers who had tomiss work as a result of the illnesses. Based on the same basic assumption to compute theeconomic costs of air pollution-related illnesses, the calculations indicate that diseasesdue to water, sanitation and hygiene cost society a total of PhP 5.7 billion (USD 104.8million) in out-of-pocket treatment expenses, PhP 9.8 billion (USD 180.0 million) in lostincome opportunities resulting from illness, and PhP 1.2 billion (USD 22.8 million) ofgovernment resources to subsidize hospitalization costs (including the subsidy for thepatients treated within the public hospital system). These numbers are illustrated inFigure 25 which breaks down the direct costs to households according to the treatment-19 Schistosomiasis is endemic in certain regions of the Philippines. Metro Manila is not one of theseregions. 52
  • 53. seeking behavior, and Figure 26 which shows the aggregate cost to all households in thePhilippine economy to treat specific WSH-related illnesses:Figure 25 – WSH Cost to Households of Treatment (Net of Public Health CareSubsidy), 2003Treatment costsfrom traditional Treatment costs in healers health centers PhP 955 M PhP 408 M 14.4% 6.2% Philhealth subsidy PhP 534 M 8.0% Treatment costs from private Subsidy to doctors government PhP 1.173 B hospitals 17.7% PhP 620 M 9.3% Self-treatment Out-of-pocket expenseshospital expenses PhP 620 M PhP 2.330 B 9.3% 35.1%Source: Author’s calculationsFigure 26 – WSH Cost to Households of Treatment (Net of Public Health CareSubsidy), 2003 per Illness Diarrhea PhP 5.487 B 96% Viral Hepatitis PhP 34 M 1% Cholera PhP 2 M 0% Schistosomiasis Typhoid and PhP 61 M Paratyphoid Fever 1% PhP 98 M 2%Source: Author’s calculations. Hospitalization treatment of WSH-related illnesses had levied a burden on publicresources equivalent, slicing away 0.8 percent of the total health budget for the country in2003. Figure 27 breaks down these costs to the government to subsidize treatment. 53
  • 54. Figure 27 - Government Health Care Subsidy per WSH-Illness, 2003 Diarrhea PhP 1.154 B 94% Cholera PhP 1 M Typhoid and 0% Paratyphoid Fever Schisto- PhP 43 M somiasis Viral Hepatitis 3% PhP 22 M PhP 16 M 2% 1% Source: Author’s calculations. The economic cost of environmental health also includes the cost to individuals interms of missed opportunity to be productive which is measured in lost income. As withair pollution-related ailments, conservative assumptions are used in order to avoidoverstating these costs. Lost productivity is measured in foregone per capita GNI andmultiplied by the number of missed work days lost. The calculations show that WSH-related illnesses caused the Philippine economy PhP 9.8 billion (USD 180.0 million).This includes the value of potentially productive days of mothers who missed work tocare for their sick children. Figures 28 and 29 illustrate the numbers, as shown below:Figure 28 – Lost Income due to WSH-related Illnesses, 2003 Cholera PhP 0.6 M 0.0% Viral Hepatitis PhP 11.5 M 0.1% Diarrhea Schistosomiasis Php 9.653 B PhP 28.1 M 99.0% 0.3% Typhoid and Paratyphoid Fever PhP 60.6 M 0.6%Source: Author’s calculations 54
  • 55. Figure 29 - Total Economic Cost of Morbidity from WSH, 2003 Viral Hepatitis PhP 61 M 0.4% Diarrhea PhP 16.294 B Cholera 97.7% Typhoid and PhP 3 M Schistosomiasis Paratyphoid 0.0% PhP 112 M Fever 0.7% PhP 201 M 1.2% Source: Author’s calculationsEconomic Cost of Premature deaths due to WSH As with the OAP and IAP cases, the economic costs of WSH-related diseases alsoinclude the value of lost productive lives resulting from premature deaths. Once more, therange of values is computed using the HCV (for the lower bound) and the VSL (for theupper bound). It is estimated that 14,407 Filipinos (Figure 30) died from WSH-relatedillnesses, causing the economy a total of PhP 21.8 billion (USD 401.98 million) in lostproductive opportunities—the highest among the three sectors—or PhP 56.1 billion(USD 1.0 billion) in terms of value of statistical life. These are separate from the 7,616children under the age of 5, who are estimated to have died of illnesses caused bydiarrhea-induced malnutrition which is discussed in the succeeding section (See thesection on malnutrition-related mortality). These figures are broken down for each WSH-related illnesses evaluated in this report in Figure 30 this is laid out further for thespecific age groups in Table 26.A and 26.B. 55
  • 56. Figure 30 – Mortality Cases Due to WSH Grouped According to Working and Non-working Age Groups, 2003Source: Author’s calculationsTable 26.A – Mortality Cases due to WSH by Specific Age Group, 2003 Viral Schisto- Age Group Cholera Diarrhea Hepatitis somiasis Age 0-4 4 9,251 25 0 Age 5 to 14 3 942 14 7 Age 15 to 19 2 70 14 4 Age 20 to 29 1 75 44 23 Age 30 to 64 7 347 272 197 65 and older 8 432 74 87 Not Reported 0 0 1 0 Total 27 11,116 443 319Source: Author’s calculationsTable 26.B – Mortality Cases due to WSH by Specific Age Group, 2003 Typhoid Age Group Filariasis Helminthiasis Fever Age 0 to 4 0 247 1,023 Age 5 to 14 0 35 637 Age 15 to 19 0 1 43 Age 20 to 29 1 4 41 Age 30 to 64 6 23 190 65 and older 1 13 236 Not Reported 0 1 0 Total 8 323 2,169Source: Author’s calculations 56
  • 57. Malnutrition-related Mortality An observation of concern based on the data above is the high incidence ofdiarrhea in children. It is widely accepted that frequent diarrhea cases in young childrencould contribute to malnutrition. It is likely then, that early childhood diarrhea could leadto increased risk of illness and mortality as a result of diarrhea-induced malnutrition. Theimpact of diarrhea-based malnutrition should be included in the economic burden ofdisease if at all the data is available. This report, however, could only generate mortalitycases from diarrhea-induced malnutrition for children under 5 years old. As such, onlymalnutrition-related mortality for this age group is included in this report. Table 26.Csummarizes the data as shown below:Table 26.C - Mortality Cases for Malnutrition caused by Diarrhea for Childrenunder 5 years old, 2003 Age Group Malnutrition Cases Younger than 1 3,719 Age 1 to 4 3,897 Total 7,616Source: Rodriguez, et al (2008). It was possibly Scrimshaw, Taylor and Gordon in 1968 that first brought into thediscussion the nutritional impacts of infections in young children (Brown, 2003). Thissub-section on malnutrition-related mortality was added in recognition of the fact thatthese authors suggested: that chronic diarrhea and malnutrition are strongly linked; andthat malnutrition resulting from chronic diarrhea could lead to other diseases and death.The epidemiological evidence shows that among the age groups, it is the very youngchildren (those under 5 years old) that are most affected. With this in mind, this reportadds the calculations done by Larsen (2008), who estimated the number of cases ofpremature deaths of children in this age group who died of illnesses caused by diarrhea-related malnutrition. The information on number of cases is summarized in Table 27below:Table 27 – Malnutrition-related Mortality Resulting from Diarrheal Infection, 2003 Number of Deaths (children under Diseases 5) Attributable to the Environment Acute Lower Respiratory Infections 4,828 Malaria 880 Measles 164 Protein Energy Malnutrition 475 Other Infectious Diseases 1,269 Total 7,616 Source: Larsen (2008). See the Annex 3 for the complete paper. 57
  • 58. It is quite easy to oversimplify the link between diarrhea and nutritional status inchildren, but in order to guide the readers to understand the issues at hand, suchsimplification can not be completely avoided. Diarrhea in young children causes loss ofmicronutrients, which combined with the anthropometric risk factors, could causeadditional nutrition-related complications and illnesses that could lead to death. Moreimportantly, diarrhea impairs the ability of body to absorb nutrients, making the childweak and susceptible to other diseases such as those listed in the above table. The risksare aggravated by the inappropriate dietary therapy for diarrhea patients, especially foryoung children. The economic toll of premature deaths arising from illnesses caused by uncleanwater, poor sanitation and improper hygiene is the highest among the three sectorsevaluated in this report. What make the results more distressing is that it is the children—the most vulnerable members of society; also the future human capital source—who aremost afflicted. Diarrhea is the most prevalent causes of deaths in the WSH category,hitting children under 5 years old (more than 80 percent of all diarrhea-related cases).The cost of premature deaths arising from illnesses caused by unclean water, poorsanitation and hygiene ranges from PhP 21.6 billion (USD 402.0 million using HCV) toPhP 56.1 billion (USD 1.0 billion using VSL). The valuation also shows that themalnutrition-related cases associated with diarrheal infection cost the Philippine economyPhP 12.5 billion (USD 230.0 million) in lost productivity or PhP 29.8 billion (USD 548.9million) in value of statistical life. These figures are added to the WSH calculations in thepreceding section to complete the picture of the mortality impacts of WSH.Figure 31 – Cost of Premature Deaths due to WSH, 2003 (HCV) 58
  • 59. Suggested Interventions The proposed interventions to address the water pollution, sanitation, and hygieneissues need not be grand. The empirical literature indicates that interventions promotingthe simple washing of hands with soap have significant impacts on the reduction ofdiseases. In many cases, the most effective intervention, therefore, is to effect behaviorchange with complimentary programs and assistance that will encourage further shifts inindividual behavior to adopt sanitary practices and hygiene.Access to clean water As what has been pointed out, access to clean water is essential in preventingillnesses. Households are encouraged to use more water because there is empiricalevidence that show that additional consumption of water is used for hygiene purposes.Curtis, et al. (1995), for instance, observed that the likelihood that a mother will wash herhands after cleaning her child’s anus increased by nearly a 100 percent with the provisionof a yard tap. The likelihood that soiled linen (with feces) will be washed right away alsoincreased by more than a 100 percent (Cairncross and Valdmanis, 2006). Studies show that the piped water had the greatest impact on health when it comesto water supply provision. This can be attributed to the fact that the probability ofcontaminating water through handling and transportation is reduced when water is moreaccessible. Water consumption also increases with the availability of piped connections.ADB (2007) notes that in the Metro Manila, people who have pipe water connectionstend to consume more than those relying on non-piped connections. It follows then thatin order to make hygiene-promotion more effective, people need to have improved accessto clean water whether for drinking or for hygiene and sanitation purposes. Educatingpeople to wash their hands becomes an ineffective intervention when water to be used forsuch activities is unavailable or insufficient. There is evidence that prove that access to water has a positive and significantimpact on diseases. A study done by Bukenya and Nwokojo (1991) showed a 56 percentreduction in diarrhea in Papua New Guinea when household tap was used rather thanpublic standposts (of good quality) in accessing clean water (Cairncross and Valdmanis,2006). In many cases, water may be available but the quality cannot be guaranteed. Insuch situations, the intervention calls for the implementation of household watertreatment. Sobsey (2007) listed the most widespread and promising water treatmentsystems available that can be further developed, implemented and disseminated. Theseinclude: “boiling, solar disinfection by the combined action of heat and UV radiation,solar disinfection by heat alone (solar cooking), UV disinfection with lamps, chlorinationplus storage in an appropriate vessel and combined systems of chemical coagulation-filtration and chlorine disinfection”. Household treatment of water according to Fewtrell,et al (2005) can reduce diarrheal morbidity up to 39 percent. Arnold and Colford (2007) conducted a meta-analysis of the studies on healthimpacts of diarrhea on children and the effectiveness of point-of-use chlorine treatment.Their findings revealed that point-of-use of chlorine treatment compared to traditional 59
  • 60. practices reduced risk child diarrhea (pooled relative risk: 0.71; 0.58–0.87) and risk ofEscherichia coli- contamination of stored water (pooled relative risk: 0.20, 0.13–0.30).These suggest that for the portion of the population who do not have access to cleanwater due to financial constraints, household water treatment can be used as a temporaryintervention while waiting for the water systems to be installed. The authors alsoobserved varying results across studies on diarrhea and water quality impacts. Possibleexplanations for this observation include differences in cultural practices in differentsites, pre-intervention conditions and underlying water exposure risk. Lastly, Arnold andColford (2007) raised the question of whether health impacts observed during short termtrials could also persist in the long run. People may gradually lose interest over longperiods leading to lower compliance and eventual abandonment of the introducedintervention or intervention’s effectiveness may vary depending on the season it wasimplemented. All of these should be taken into consideration when formulating large-scale and long term interventions. Concurrently, the costs of intervention have also been examined. Cairncross andValdmanis (2006) estimated the costs of constructing water supply in facilities. Theresults are presented in Figure 32 which shows the median construction cost of watersupply facilities in Africa, Asia and Latin America. Costs vary depending on thelocation. Focusing on Asia for instance, the least expensive facility is the construction ofa borehole. Borehole costs USD 17 per capita while house connections proved to be themost expensive with USD 92 per capita construction cost.Figure 32 - Median Construction Cost of Water Supply Facilities for Select Regions(in USD)Source: Disease Control Priorities in Developing Countries, second edition, 2006,Figure 41.1. 60
  • 61. Sanitation and hygiene improvement and promotion Other interventions to address the issue of water pollution and sanitation have alsobeen evaluated. Fewtrell, et al. (2005) conducted a systematic review and meta-analysisof the effectiveness of the different water, sanitation and hygiene interventions availablein less developed countries. Figure 33 shows the percent reduction in diarrhea morbiditygiven the different water, sanitation and hygiene interventions analyzed: improved watersupply which includes improved water delivery (piped supply or household connections);sanitation interventions which includes provision of latrines; improved hygiene whichincludes health and hygiene education and hand washing promotion; and household watertreatment which includes point of use treatment (i.e. chemical treatment, boiling,pasteurisation, and solar disinfection). The benefits are clear: 1) with improved drinkingwater, diarrhea morbidity was reduced by 25 percent; 2). Hygiene improvement resultedin 45 percent reduction in diarrhea cases; 3) sanitation improvement resulted into 32percent reduction; and 4) a 39 percent reduction from household water treatmentactivities (Fewtrell, et al., 2005; WHO/UNICEF, 2005).Figure 33 - Percent Reduction in Diarrhea Morbidity of Different Water andSanitation Interventions (in %) 50% 45% 45% 39% 40% 35% 32% % Reduction 30% 25% 25% 20% 15% 10% 5% 0% Improved drinking Improved sanitation Improved hygiene Household w ater w ater treatment Source: Fewtrell, et al., 2005 as discussed in WHO/UNICEF, 2005. In Figure 34, Cairncross and Valdmanis (2006) present the cost-effectiveness ofwater, sanitation and hygiene interventions. Sanitation promotion costs USD11 perDALY averted while sanitation that includes promotion and construction of facilitiescosts about USD 270 per DALY averted. 61
  • 62. Figure 34 - Cost-effectiveness of Water Supply, Sanitation, and Hygiene Promotion (USD/DALY) Water Supply - Hand Pump or Standpost $94 Water Supply - House Connection $223 Water Sector Regulation and Advocacy $47 Sanitation - Construction and Promotion* $270 Sanitation - Promotion Only $11 Hygiene Promotion $3 Cost-effectiveness*Construction and Promotion ≤ 270.Source: Disease Control Priorities in Developing Countries, second edition, 2006, Table41.12. Hygiene improvement (especially washing of hands with soap) can also preventdiseases other than water borne diseases. It must be pointed out that hygiene promotion(i.e., washing of hands) can also prevent acute lower respiratory infections likepneumonia. Luby et al. (2005) conducted a study on the effect of hand washing onchild’s health using 600 hand washing promotion households and 300 control householdsin Karachi, Pakistan. The hand washing promotion households were either given plain orantibacterial soap and were subjected to an intensive education and encouragementmethods. Major findings include: 50 percent lower pneumonia cases for children youngerthan 5 years; 53 percent lower diarrhea cases for children younger than 15 years and 34percent lower impetigo incidence among households who received soap and handwashing promotion than controls. No significant difference in terms of disease incidencewas observed between households who received plain soap versus those who receivedanti-bacterial ones. Clasen, et al. (2007) conducted a meta-analysis on the effectiveness ofinterventions that improve the microbial quality of drinking water in preventing diarrhea.The study revealed that diarrhea can be effectively abated thru interventions directed atimproving microbial quality of water. These interventions include water sourceintervention (e.g.,. protected wells, bore holes, or distribution to public tap stands) andhousehold adaptation (e.g.,. improved water storage, chlorination, solar disinfection, 62
  • 63. filtration, or combined flocculation and disinfection). Degree of effectiveness however,varies depending on different of conditions. Interestingly, it was reported that“…combining the intervention with instructions on basic hygiene, a water storage vessel,or improved sanitation or water supplies”, and presence of improved water supply did notimprove the effectiveness of the interventions studied.Construction of Latrines The transmission of most endemic diarrhea is from person to person thru poorhygiene practices because the pathogens are not waterborne. Given this, it is alsoimportant include improvement of sanitation facilities in the list of possible interventions(Cairncross and Valdmanis, 2006). To make the provision of sanitation facilities moreeffective, an education and promotion campaign should be done (World Bank, 2007).This will educate the target beneficiaries of the potential benefits they will get from usingthe facilities and in return entice them to use the facilities. It must be kept in mind that noamount of physical intervention will be effective if the behavior regarding hygienicpractices is not altered. In any case, the availability and construction of sanitation facilities is a necessaryintervention in combating diseases. As a guide, Figure 35 shows the average cost ofconstructing sanitation facilities in Africa, Asia and Latin America. In Asia, simple pitlatrines are the cheapest option (USD 26 per pit) while sewer connection is the mostexpensive to construct (USD 154 per connection) (Cairncross and Valdmanis, 2006).Figure 35 - Median Construction Cost of Sanitation Technologies in Select Regions(in USD)Source: Disease Control Priorities in Developing Countries, second edition, 2006, Figure 41.2 63
  • 64. It must be noted that sanitation facilities are not limited to latrines. Sewers and sewer connections fall under this category as well. In the rural areas in the Philippines,and in most of the poor households, sewerage facilities are severely lacking, significantly increasing the risk of the spread of diseases. Without proper disposal of wastes, contamination of food and water are likely to take place. Final intervention, therefore, could also be in public investment in alternative waste disposal facilities that the poor— especially the urban poor—can have regular and inexpensive access to. 64
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  • 73. ANNEX 1 Methodology and Assumptions The economic valuation of the health-related consequences of pollution,sanitation and hygiene problems in the Philippines necessitated the adoption of specificassumptions, and the use of methodological approaches—the cost of illness (COI) formorbidity; and, the human capital value (HCV) and value of statistical life (VSL) formortality. In order to attain accuracy and closeness to reality, detailed assumptions wereadopted and used in the calculations. This section contains the details of themethodologies and computations that were mentioned in the body of the report.General Methodology This sub-section is devoted to the discussion on the methodology and assumptionsthat were used for all three areas—OAP, IAP, and WSH—discussed in the main text.Separate discussions on the illness-specific calculations are also done in the succeedingsub-sections.I. Calculating the Number of Health Cases The estimation of the number of cases of illness and mortality related to the threeareas of concern begins by identifying the appropriate health-endpoints. This necessitatedthe review of the existing epidemiological studies and reports done by WHO and others.The next step is to examine the existing health statistics and data to see which illnesseshad ample data for the calculations. The decision as to which disease to include dependson the availability of information regarding risks of becoming ill or dying fromenvironmental health risk factors and the extent to which total morbidity and mortalityincidence figures and treatment-seeking behavior breakdowns can be estimated for eachdisease. In order to estimate the number of morbidity and mortality cases due to theenvironment from the total cases of the illnesses and mortality in the country, theattributable fractions (AFs) must be calculated or adopted from another study that issimilar to the Philippines. The AFs are multiplied with the total number of cases in thePhilippines per illness or cause of death to come up with the number of cases that are dueto the environment. The specific calculations for each of the three areas of concern arediscussed in detail at each sub-section dealing with each of these three.II. Treatment-Seeking Behavior In order to reflect the behavior of Filipino households with regard to illnesses inthe estimations, this study laid out the costs of treatment in terms of the treatment-seeking 73
  • 74. patterns of the general population. By treatment-seeking (or health-seeking as referred toin some literature) behaviors the reference is on the list below:Self Treatment Health Centers Hospitals Traditional No treatmentMedicine Rural Health Government- Medicine Centers ownedVisits to the Baranggay Private Owned Visits to theWestern-trained Health Centers Traditionaldoctors clinic The data used to derive treatment-seeking behavior for the diseases are taken fromthe 2003 National Demographic and Health Survey and from key informant interviews.For each disease, the percentage of people who sought treatment from rural health centersand barangay health units was used to estimate the baseline data from the FHSIS figures.The baseline morbidity cases data are then appropriated to the treatment-seekingbehaviors outlined for each disease.III. Economic Valuation of Morbidity Economic burden of morbidity is broken down into direct cost to household,government subsidies and indirect costs. The morbidity cost calculations are based onthe assumptions and methodologies for direct and indirect costs as discussed in thesucceeding sub-sections.III.a Direct Costs Direct cost to household is cost of treatment less PhilHealth contribution (35% ofconfinement costs). To determine the direct costs, the calculated number of cases for eachdisease attributable to a specific sector (i.e. OAP, IAP, or WSH) according to healthseeking behavior was then multiplied by the associated total costs of health seekingbehavior per disease. Associated costs include cost of confinement, consultation fees andmedicines. These costs were mainly based on PhilHealth data and key informantinterviews. The table below presents the associated costs per health seeking behavior andother assumptions regarding treatment costs. 74
  • 75. Associated costs per health seeking behavior Health Seeking Behavior Health Government Private Private Self Traditional Center Hospital Hospital Doctor Treatment Cost Healer Cases Cases Cases Cases Cases Cases Adjusted Adjusted Cost of PhilHealth PhilHealth Confinement* None data data None None None Included in Included in P500 the lump the lump sum MM and sum amount amount Urban P150 MM and Consultation reported by reported by P300 Urban Fee P10 PHilhealth PHilhealth Rural None P90 Rural Included in Included in P12/day P12/day P12/day the lump the lump sum sum amount amount reported by reported by Medicine cost** P12/day PHilhealth PHilhealth Notes: *Confinement cost include doctors’ fees, medicines, room and board. The cost is based on the lump sum figure from PhilHealth adjusted with assumption that PhilHealth shoulders only 35% of total cost per confinement ** Medicine cost per day is assumed to be the same for all diseases. Total medicine cost depends on the duration of the disease. Total cost per disease according to health seeking behavior depends on the duration of the disease. The duration (treatment/confinement) of the diseases is presented in the succeeding table as well. Average Number of Days of Treatment/Confinement Health Government Private Private Self Traditional Center Hospital Hospital Doctor Treatment Healer Disease Cases Cases Cases Cases Cases CasesALRI 8 3 3 8 8 8Bronchitis 4 3 3 4 4 4Cholera 10 8 8 10 10 10Diarrhea 5 3 3 5 5 5Hepatitis 7 6 6 7 7 7Schistosomiasis 7 5 5 7 7 7Tuberculosis 180 180 180 180 180 180Typhoid 14 4 4 14 14 14 Source: PhilHealth and key informant interviews 75
  • 76. Total confinement cost (net of PhilHealth contribution) for government hospitalscases is the basis for the computation of the government subsidy. This report assumesthat 50 percent of the total cost (net of PhilHealth contribution) of confinement (mainlythe daily room rate) in public hospitals is subsidized by the government. Note that COPD is not included in the above table. This is due to the fact that thecalculations for the treatment costs for COPD are essentially the costs of managing thesymptoms throughout an individual’s lifetime. As such, the direct costs of COPD“treatment” are calculated to be the sum of all these direct costs every year from the yearthat the illness is contracted, throughout the expected lifetime of the individual. Toexpress these total lifetime costs in present value terms, a discount rate of 3 percent wasused. The number of years an individual is projected to live out his or her life with COPDis based on the projections per age group by Shibuya et al (2001).III.b Indirect Costs The indirect costs of morbidity are described to be the lost income and value of timelosses of the individual who had to miss work while getting treated. The assumptionsregarding the indirect costs are listed below: a. Lost income due to illness is calculated only for the members of the population who belong to the 20-64 age group, and adjusted according to the employment rate as reflected in the source of the data (the Philippines DHS 2003). The full value of daily Gross National Income per capita is applied to the individuals who are employed, as a proxy for their income. Only 75 percent of the daily GNI is applied to those who are not formally employed, as it is assumed that those who are not formally employed still contribute to national welfare through the work they do in the household or through the informal sector. b. Foregone income was also computed for parents of children under 5 years old. The values were adjusted according to employment rate of women. c. The employment data from the DHS are used in this study to estimate the number of cases of adult individuals who had to miss work because of illness, or because they had to care for a sick child. The table below lists the employment figures used: 76
  • 77. Percentages of employed and unemployed Employed Unemployed Women 51.6 48.4 Men 80.1 19.9 Source: Tables 3.5.1 and 3.5.2 of the NDHS 2003. Note: These figures are based on the total number of employed in the last 12 months preceding the survey. The data did not have a breakdown by age group, but this was used to calculate the lost income due to illness for the 20-64 age groups. The total lost income due to illness is the equal to the sum of lost incomecomputed for population age group 20-64 years old and lost income computed for theparents of children under 5 years old. The method is straightforward: number of cases perhealth seeking behavior is multiplied by the per capita GNI value (adjusted to 100 or 75percent depending on employment status) and the number of days lost due to the illness.To estimate the days lost due to illness, the following are further assumed: a. Mothers are presumably the ones who most often care for the sick children in the household. Those who take care of their sick children are divided between working and non-working mothers. Per capita GNI is used as the basic cost, but for non-working parents, an assumption of informal work or foregone leisure (assumed to be 75 percent of per capita GNI) was made. The per capita GNI per day is pro-rated for the number of hours a mother takes care of a sick child per day. It is assumed that only young children (children under 5 years old) are cared-for by a parent when they are ill. b. Assumptions about the amount of time a mother devotes to care for a sick child are as follows: i. Outpatient care is 2 hours per day for the duration of the illness ii. Hospitalization days are the total number of days a child is in the hospital plus one extra day for home-recovery. The number of days hospitalized and illness duration is based on the information gathered from PhilHealth, and from interviews of public health experts in the Philippines. iii. It is assumed that a mother will likely attend to a child who has fever-like symptoms more than to a child who has diarrhea. In the valuation of a mother’s time off from productive activities to care for a child, it is assumed that a mother will take at least a day off from work if the child is stricken with an illness that has fever-like symptoms, and may not take a day off to care for a child with diarrhea. 77
  • 78. c. The treatment duration for tuberculosis assumed in this paper is 6 months (180 days). This report assumes that the patient will (on average) spend 5 days in the hospital, and will only be allowed to work after 2 months of continuous treatment. For the succeeding 4 months after the 2 months of continuous treatment, it is further assumed that the patient will still be under medication—incurring PhP 12 per day medicine cost. d. Weekends are excluded from the computations of the number of days a person will miss days of work. As illustration, a person who is ill for 10 days is assumed to have missed only 8 days of work. e. For diarrhea cases that are not treated, a 1 day loss of income is assumed for the individuals who are working, and 75 percent of this one-day lost income for those are not employed or employed in the informal sector. As a general rule, no calculations are done for cases of illnesses for which thereare no available data risk ratios or AFs. For those instances when only the data for acertain age group are available, the economic costs are calculated for that age group only.This report strives to be accurate based on what data are available, and refrains fromcross-using the risk ratios of AFs. As such, if the available risk ratio datum is only forlung cancer, then that risk ratio figure is used only for cancer cases, and is not used as thebasis for the number of cases for other illnesses even if these are similar to cancer. In terms of medical facilities, this report also does not make a distinction betweenthe quality of government and private facilities. This is a simplification in order to makethe additional assumption that the full cost of treatment in a public health facility is equalto that of a private one.IV. Economic Valuation of Mortality The economic valuation of mortality employs the same straightforward approachdone in the economic valuation of morbidity. Attributable fractions of mortality fromenvironmental factors are multiplied with total mortality to arrive at the number of deathsassociated with each of the three sectors. These figures are then multiplied by the theHCV or VSL. To determine the HCV, the present value of lost potential lifetime earnings frompremature death is calculated, using 2003 Philippine gross national income per capita (asreported in the World Bank database) as proxy for income losses in 2003. Philippine GNIper capita, reported to be USD 1070 in 2003, is assumed to grow at 2.1 percent (averageGNI per capita growth rate from 1999 to 2006) per year in the future. Since lifeexpectancy for Filipinos is 67 for men and 72 for women (as reported by the WHO), eachpremature death is assumed to reflect lost income from age 20 (average start of workinglife) until the mandatory retirement age in the Philippines of 65 years old. Future incomeis discounted at an annual rate of 3 percent. The average HCV for specific age groups andVSL figure (calculated by B. Larsen) are presented below: 78
  • 79. Average HCV per Age Group Average HCV (USD) VSLAge Group OAP IAP WSHAge 0 to 4 years 30,263 30,247 30,340 72,021Age 5 to 14 years - - 32,204 72,021Age 15-64 11,734 14,625 21,347 72,021Estimating the Attributable Fractions The estimation of the attributable fractions of disease and mortality fromenvironmental factors often times necessitates careful analysis of the available data.Oftentimes, adjustments have to be made in order to extract the information that isneeded for the calculations. In general, the AFs for morbidity are not the same as those for mortality. Thereare, however, cases when they are the same; and this report relied on the existingliterature and advice from epidemiological experts to determine when this is the case, andwhen it is not. In this subsection, the methodology and assumptions used to compute theAFs for the three environmental areas are discussed.I. Attributable Fractions and Relative Risk Ratios for the Morbidity CasesOutdoor Air Pollution (OAP) The attributable fraction for diseases that are related to outdoor air pollution, arecalculated using a general formula that is used in Ostro (2004): n ∑ P ( RR i i − 1) AF = i =1 n Equation 1 1 + ∑ Pi ( RRi − 1) i =1where Pi is the proportion of the sub-population that is exposed to outdoor air pollutionand RRi, the respective relative risk a sub-population is exposed to a specific diseases. There is sufficient empirical and epidemiological literature that discusses theimpacts of outdoor air pollution on health. Most of the literature, however, either focuseson specific morbidity endpoints such as hospital admissions or missed workdays for acertain disease (inevitably ignoring other health seeking behaviors), or directly reportsattributable fractions and/or relative risk ratios, with no discussion on how these relativerisk ratios are computed. 79
  • 80. Unlike for IAP and WSH, the author could not find studies that conducted a meta- analysis of morbidity for OAP-related illnesses, and a unified framework by which studies for other localities can be made using local particulate matter data. Hence, for OAP-related morbidity, the relative risk ratios used are calculated based on the relative risk ratios presented in Galassi et al (2000), and are listed in the table below. Health outcomes and relative risks (per 10 µg/m3 of PM10) Central Lower Limit Upper Limit Cause Notes Estimate 95% 95%Hospital admissions for CVD 1.009 1.006 1.013causesHospital admissions for 1.016 1.013 1.020respiratory disease*Chronic bronchitis 1.093 1.009 1.180 Adults 25+Acute bronchitis* 1.306 1.135 1.502 Children <15Asthma exacerbation 1.051 1.047 1.055 Children <15Asthma exacerbation 1.004 1.000 1.008 Adults 15+Restricted Activity Days 1.094 1.079 1.109 Adults 20+Occurrence of respiratory 1.07 1.02 1.11symptoms* Source: Galassi et al (2000). *Health outcomes applied in this report to the Philippines. There is a need, however, to adjust the relative risk ratios in the table below as these represent the relative risk ratios per 10 μg/m3 deviation from the baseline level of PM10. It must be noted that the deviations from the baseline level of PM10 for the Philippines are much higher than 10 μg/m3. In the table above (of health outcomes and RRs), only the health endpoints marked with an * in the table above are used in the calculations for the Philippines as these are the only endpoints for which complete morbidity figures and full treatment-seeking behaviors can be estimated. To compute the relative risk ratios for the diseases due to PM10 exposure, population-weighted annual PM10 levels are substituted into [ ] RR = exp β (PM 10, Actual − PM 10,Counterfactual ) Equation 2 using 15 μg/m3 as the counterfactual PM10 level. The β coefficients and the relative risk ratios for each of the health endpoints under consideration are outlined in the table below. 80
  • 81. Relative Risks for OAP-related Illnesses, 2003 Relative Risks Health Outcome β Metro Urban Rural ManilaAcute Bronchitis, under 5 0.0267 4.6356 1.8733 1.0000Hospital Admissions for Respiratory 0.0016 1.0955 1.0380 1.0000DiseaseOccurrence of Respiratory Symptoms 0.0068 1.4751 1.1804 1.0000Note: The betas are from Galassi et al (2000). Also, the relative risk ratio for the ruralarea is assumed to be 1 in order to exclude the rural areas in the discussion. This is dueto the fact that there are no available PM data for the rural areas. The next table summarizes the attributable fractions that were computed using therelative risk ratios above; and in turn is used to estimate the number of cases of OAP-related diseases.Attributable Fractions Used to Calculate the OAP-related Illnesses Health Outcome Attributable Fractions Acute Bronchitis, under 5 0.42343 Hospital Admissions for Respiratory Disease 0.02555 Occurrence of Respiratory Symptoms 0.11297 It must be noted that the attributable fractions in the table above are for urbanareas as there was insufficient information on particulate matter levels in the rural areas.Indoor Air Pollution (IAP) As with OAP-related morbidity, the AFs used to estimate the number of cases ofillnesses resulting from exposure to IAP (assumptions and methodology are adapted fromDesai et al (2004), are computed using Equation 1. Only those health outcomesassociated with indoor air pollution for which there is sufficient information to supportany relative risk generalizations (included in Desai et al’s (2004) meta-analysis) and forwhich Philippine data was accessible, is investigated. The table below outlines therelative risk ratios used for IAP-related morbidity. Note that health outcomes marked by** are not included in the analysis because coal is not regularly used as a fuel for cookingin the Philippines. It must also be noted that the RRs used for cases of ALRI for childrenunder 5 is 1.8 instead of 2.3 (as reported by Desai et al). The adjustment in theassumption with regard the RR for ALRI is from Dherani et al (2008). 81
  • 82. Relative Risk Ratios Used to Calculate the Number of Cases of IAP-related Illnesses Evidence Health Outcome Group (based Relative CI on gender and Risk age) RatiosStrong ALRI Children <5 2.3 (1.8) 1.9-2.7 COPD Women ≥ 30 3.2 2.3-4.8 Lung cancer (from exposure Women ≥ 30 1.9 1.1-3.5 to coal smoke)**Moderate-I COPD Men ≥ 30 1.8 1.0-3.2 Lung cancer (from exposure Men ≥ 30 1.5 1.0-2.5 to coal smoke)**Moderate-II Lung cancer (from exposure Women ≥ 30 1.5 1.0-2.1 to biomass smoke) Tuberculosis All ≥ 15 1.5 1.0-2.4Source: Desai, et al (2004). To be able to calculate the attributable fractions necessary to determine whatfraction of all reported cases of the illnesses is due to IAP, it is necessary to determine thesize of the population exposed to indoor air pollution. One other important piece of information needed to calculate the AFs for IAP-related illnesses is the size of the population in the Philippines that is exposed (long-term)to IAP. The 2006 Philippine Environmental Monitor used the proportion of householdsthat reports usage of charcoal, fuel wood and biomass residue during the duration of theHECS 2004 as the relevant portion of the population exposed to indoor air pollution. Amore conservative (and more realistic) proportion to use, however, would be thepercentage of the population that reported the use of these solid fuels as their primarycooking fuel. This information can be extracted from the 2004 HECS from theinformation on the households’ use of other energy sources as the primary cooking fuelduring the year prior to the actual survey. Subtracting the cases of households that usethree types of solid fuel from the data, the results show that 48 percent of householdmembers are considered exposed to indoor air pollution. This is slightly lower than the 53percent figure that is reflected in the main section of this report. Data from the HECS on usage of solid fuel according to urbanity and regionalclassification allows us to get an idea as to what percentage of households in MetroManila and urban and rural areas report fuel wood, charcoal and other biomass residue astheir primary cooking fuel. These figures, however, need to be adjusted by the associatedventilation factors because cooking practices and the structural characteristics of housesin the Philippines may mitigate the exposure of Filipino households to indoor airpollution and the subsequent health outcomes. Desai, et al. (2004) suggests using aventilation factor of 0.25 for households that use improved stoves or cook outside, and aventilation factor of 1.00 for those that use traditional stoves. Taking into account the“airiness” of the areas where cooking is done even if the stoves were traditional, aventilation factor of 0.25 is used for urban and rural areas outside Metro Manila—as 82
  • 83. households in these areas typically do their cooking outside their houses. Metro Manilahouseholds that use solid fuel, however, are assigned a ventilation factor of 0.5 sincethese households would normally be found in informal settlement areas where houses arecrammed together. With the above assumptions on ventilation factors, the proportion ofthe cases of the health outcomes outlined above that can be attributed to exposure toindoor air pollution is computed. The AFs used are summarized in the IAP section ofthis report.Water, Sanitation and Hygiene (WSH) The analysis on the burden of disease from water pollution, sanitation, andhygiene included five diseases—diarrhea, cholera, schistosomiasis, typhoid andparatyphoid fever, and viral hepatitis—for which 2003 morbidity data are available, andfor which there is sufficient information relating these illnesses to water pollution andsanitation issues: The table below, which is based on the Philippine EnvironmentalMonitor 2006 (PEM) , lists the attributable fractions for these illnesses (excludingdiarrhea for which a separate section is devoted to).Attributable Fractions for WSH-Related Diseases (Excluding Diarrhea) Disease Attributable Source FractionCholera 100% Various literature (not good)Schistosomiasis 100% WHO, 2006bTyphoid and paratyphoid fever 50% Expert opinion of World Bank StaffViral hepatitis 50% Expert opinion of World Bank StaffSource: PEM 2006 (World Bank, 2007) For the readers’ reference, Pruss-Ustun et al (2006) lists more diseases that arerelated to water, namely: helminthiasis, malaria, intestinal nematode infections(ascariasis, trichuriasis, hookworm disease), trachoma, chagas disease, onchoceriasis,leishmaniasis, Japanese encephalitis, and dengue fever. These diseases, however, areexcluded from this report either due to a lack of national data or lack of sufficientevidence linking the available AFs to inaccessibility of clean water supply of propersanitation facilities.Diarrhea The attributable fraction for diarrhea is computed using Equation 1, where Picorresponds to the proportion of the population subject to a specific exposure categoryand RRi, the relative risk from lack of water sanitation and hygiene associated with thatcategory. The exposure categories used for diarrhea are based on Pruss-Ustun, et al(2004), and are summarized in Table 7 in the WSH section. 83
  • 84. The 2003 Field Health Surveillance Information System(FHSIS) Report indicatesthat 83 percent of households have access to safe drinking water, while 76 percent haveaccess to sanitary toilets. Since national coverage is less than 98 percent, all householdsin the Philippines can be categorized under exposure scenarios IV, Va, Vb, and VI, asdescribed in the text. The FHSIS Reports contain national, regional, provincial, and city-level data onthe number of households that have access to safe drinking water and sanitary toiletsacross the country. However, these data are insufficient to be able to come up with thenumber of households that are under the classifications suggested in the main body. Toremedy this, results of the Philippines Demographic and Health Survey 2003 are used tocome up with the national, Metro Manila, urban-area, and rural-area populationproportions that are exposed to the four different exposure scenarios. The DHS asks respondents to identify their source of drinking water and the typeof sanitation facility. Categorizing Philippine households into the four applicableexposure scenarios makes use of Hutton, et al’s (2007) definitions for improved watersupply and improved sanitation. Improved water supplies are those that are relativelyaccessible to people and for which some measures are taken to protect the water fromcontamination; improvements do not guarantee the safety of the water from thesesources. Improvements in sanitation facilities involve better access and safer disposal ofexcreta (Hutton and Haller, 2004). Note that water supply and sanitation services mayalso be categorized as “unimproved” when they are unnecessarily costly, even when theyare deemed of safe quality. Table 11 in the main body of this report on the responses tothe demographic and health survey summarizes the groupings of the responses for thesequestions in the DHS. The raw data of the DHS allows for a breakdown of the respondents according tourbanity and geographical region. The table below shows the proportion of the nationalpopulation under the different exposure scenarios and the relative risk due to lack ofwater supply and sanitation.Relative Risks and Population Proportions Used to Compute for AttributableFraction for Diarrhea Population Proportions Exposure Relative Demographic and Health Survey 2003 Scenario Risks National IV 6.9 74.21 Va 8.7 10.81 Vb 11.0 9.80 VI 11.0 5.18 Attributable fractions for diarrhea for Metro Manila and the whole country arecomputed using the proportions of the population exposed to the agent of illness, and therelative risks associated with the individual scenarios. The calculations show that 86 84
  • 85. percent of all diarrhea cases in the country can be attributed to water and sanitationconditions. A summary of these AFs is presented below in the table below:Attributable Fractions (AF) for WSH-related Illnesses, 2003 Region Attributable Disease Source Applied Fraction Cholera National 100.00% Pruss Ustun National 86.28% This author Metro Manila 85.58% This author Diarrhea Urban 85.85% This author Rural 86.59% This author Schistosomiasis National 100.00% Pruss Ustun Typhoid and Paratyphoid National 50.00% Pruss Ustun Fever Viral Hepatitis National 50.00% Pruss UstunII. Attributable Fractions and Relative Risk Ratios for Mortality CasesAttributable fractions and relative risks for OAP The AFs for mortality were computed using equation (1). Unlike for morbidity,relative risks for mortality due to OAP-related diseases can be readily computed usinglocal particulate matter data using the framework suggested by Ostro (2004). Thefollowing formulas are used to compute for locality-specific relative risks, depending onparticulate matter exposure: PM10 exposure: [ ] RR = exp β (PM 10, Actual − PM 10,Counterfactual ) (3) β ⎡ PM 2.5, Actual + 1 ⎤ PM2.5 exposure: RR = ⎢ ⎥ (4) ⎢ PM 2.5,Counterfactual + 1⎥ ⎣ ⎦ Tables 16 and 17 below outlines the β coefficients used, the resulting relative riskratios and attributable fractions.Relevant Particular Matter and β Coefficient of RR Formula for OAP-RelatedHealth Outcomes Particulate Health Outcome β Coefficient Matter Respiratory Mortality, under 5 PM10 0.00166 Cardiopulmonary Mortality, 30 and older PM2.5 0.15515 Lung Cancer, 30 and older PM2.5 0.23218 Source: Ostro (2004). 85
  • 86. Relative Risk and Attributable Fraction for OAP-Related Health Outcomes Relative Risk Attributable Health Outcome Metro Urban Rural Fraction Manila Respiratory Mortality, 1.10006 1.03980 1.00000 0.03058 under 5 Cardiopulmonary 1.31085 1.13199 1.00000 0.08298 Mortality, 30 and older Lung Cancer, 30 and 1.49940 1.20386 1.00000 0.12472 older Source: Author’s calculationsAttributable fractions and relative risks for IAP and WSH For the IAP and WSH mortality cases, the study used the same AFs and RRscalculated for morbidity. This is the same method used in the studies that were reviewedfor this report.III. Calculation of number of total deaths per disease The paper based estimates of baseline mortality figures on data reported by theDepartment of Health in the 2003 Philippine Health Statistics Report. However, the paperacknowledges that the official number of deaths reported may significantly beunderestimated due to underreporting (particularly in the rural areas and for under-5deaths) and inaccurate reporting of cause of death. To address this, the published data onthe number of deaths reported per disease were adjusted by age-specific adjustmentfactors in light of a u5-child mortality rate of 36 per 1,000 live births and a crudemortality rate of 5.0 per 1,000 population in the Philippines in 2003Adjustment Factor Used to Adjust for Published Mortality Figures from PHS Age Group Adjustment Factor Under 5 2.42 5 and older 1.05 These adjustment factors are applied to mortality figures (reported in the 2003Philippine Health Statistics) to obtain baseline mortality data caused by all the diseasesunder consideration, except for diarrhea. For diarrhea, the mortality data from Rodriguezet al (2008) were used—which have already been adjusted for underreporting. Theadjusted figures for diarrhea and the other WSH-related illnesses were then multiplied by 86
  • 87. the corresponding AFs to get the deaths attributable to each sector. These final mortalityfigures associated with each sector according to age group are those that were used andpresented in the tables in each section to determine the economic valuation of prematuredeaths due to pollution and poor sanitation and hygiene in the Philippines.Data The main data source for baseline morbidity cases for the diseases underconsideration (except diarrhea, COPD, and tuberculosis, which are discussed separatelybelow) is the 2003 Field Health Surveillance Information System Report (FHSIS) of theDepartment of Health; however, there is a need to adjust these data to reflect accurateestimates for baseline morbidity cases as the FHSIS only reports figures for those whosought treatment from rural health centers and baranggay health units.I. Diarrhea Since almost all of the cases of WSH-related illnesses is attributable to diarrhea, amore detailed approach to calculating the number of cases is done. Computing thebaseline cases figures for diarrhea in 2003 necessitate dividing the Philippine populationinto age groups for which Rodriguez (2008) provided information on the per capitadiarrhea cases (see table below). Per Capita Diarrheal Cases, 2003 Age Group Diarrhea Case per capita Source 0 to 1 2.75 NDHS, 2003 1 to 4 2.08 NDHS, 2003 0.33 (improved sanitation) 5 to 14 WHO, WPR-B 0.52 (unimproved sanitation) 0.16 (improved sanitation) 15 and older WHO, WPR-B 0.26 (unimproved sanitation) The figures for treatment-seeking behavior derived for diarrhea is then applied tothe baseline case figures for the breakdowns necessary for economic valuation.II. COPD As in the case of diarrhea, 2003 Philippine population figures are divided into agegroups for which COPD incidence per 1,000 people is available, as reported in Shibuya etal (2001). These incidence figures are outlined in the table below. Appropriate treatment-seeking figures were then applied to the baseline incidence data. 87
  • 88. COPD Incidence Rate for Each Age Group Incidence Rate Age Group (per 1,000 population) Male Female 0 to 4 0 0 5 to 14 0 0 15 to 29 0.03 0.06 30 to 44 0.36 0.44 45 to 59 1.21 0.38 60 to 69 4.44 1.75 70 to 79 5.19 2.07 80 and older 5.14 3.43 Total 0.55 0.32 Source: Appendix 2, SEARO-B of Shibuya et al (2001).III. Tuberculosis The 2003 FHSIS Report reports figures for visits to baranggay health units andrural health centers for respiratory tuberculosis. The general methodology used for theother diseases were applied to respiratory tuberculosis data to arrive at 2003 baselinemorbidity figures, but no distinction is made as to whether these cases are new or old.The study adopts WHO estimates of 108,062 cases for the Philippines in 2003, whilemaintaining the treatment-seeking behavior ratios used for the 2003 baseline morbidityfigures.IV. Estimated Number of Cases per Age Group Based on the AFs and the morbidity prevalence data from published healthstatistical data in the Philippines, the number of cases per age group in 2003 wascomputed. The results for all three—OAP, IAP, and WSH—are summarized in the tablesbelow: 88
  • 89. Cases of OAP-related Illnesses by Age Group, 2003 ALRI and Acute Bronchitis Pneumonia Younger than 1 104,494 155.471 Age 1 to 4 169,618 272,240 Age 5 to 14 60,766 195,812 Age 15 to 19 8,464 10 Age 20 to 29 13,875 16 Age 30 to 64 40,374 41 65 and older 16,844 12 TOTAL 414,437 623,602Cases of IAP-related Illnesses by Age Group, 2003 Acute ALRI and COPD Respiratory Bronchitis Pneumonia TuberculosisYounger than 1 37,058 110,459 0 0Age 1 to 4 64,891 179,294 0 0Age 5 to 14 0 0 0 0Age 15 to 19 0 0 0 716Age 20 to 29 0 0 0 1,173Age 30 to 64 18,630 22,842 2,670 3,60465 and older 4,900 8,839 1,558 1,139TOTAL 125,479 321,433 4,228 6,631Cases of Diarrhea by Age Group, 2003 Metro Cases National Urban Rural Manila Younger than 1 4,764,676 651,834 1,681,840 2,431,002 1 to 4 14,691,955 1,867,656 5,176,062 7,648,237 5 to 14 6,125,743 612,723 2,167,659 3,345,361 15 to 19 264,366 30,223 92,378 141,765 20 to 29 433,304 49,542 151,409 232,353 30 to 64 6,567,969 902,905 2,276,773 3,388,291 65 and older 473,119 43,389 168,665 261,066 Total 33,321,133 4,158,272 11,714,787 17,448,074 89
  • 90. Cases of WSH-related Illnesses (excluding Diarrhea) by Age Group, 2003 Typhoid and Viral Schistoso- Cholera Paratyphoid Hepatitis miasis FeverYounger than 1 138 303 0 9621 to 4 339 2,102 1,230 8,5185 to 14 349 7,649 17,114 20,04515 to 19 41 2,216 4,889 6,11320 to 29 67 3,631 8,010 10,01830 to 64 142 6,603 17,788 17,67565 and older 70 667 2,653 2,018Total 1,144 23,172 51,684 65,349 90
  • 91. Cost-Benefit Analysis of Selected Environmental Health InterventionsInternational evidence and applications to the PhilippinesPrepared for the Philippines CEA, World Bank20by Bjorn Larsen21EconomistConsultantJanuary 200920 This report is a background document prepared for the Philippines CEA, the World Bank. Task teamleader was Jan Bojo, Lead Economist, East Asia and Pacific Department, World Bank. The report relies onArenas (2009) as a basis for estimating health benefits of interventions. The findings and conslusions inthis report are solely those of the author, and not necessarily those of the World Bank, its affiliates, ormember states.21 Contact information: BJRNLRSN@AOL.COM or BJ_LA@HOTMAIL.COM 91
  • 92. TABLE OF CONTENT List of abbreviations I. Introduction II. Outdoor air pollution Interventions Intervention effectiveness and unit costs Benefit-cost ratios III. Indoor air pollution Interventions and unit costs Benefit-cost ratos IV. Water, sanitation and hygiene Interventions and unit costs Benefit-cost ratios Hand washing promotion Household drinking water disinfection promotion V. Summary and Conclusions References 92
  • 93. LIST OF ABBRIVATIONSAF Attributable FractionALRI Acute Lower Respiratory InfectionARI Acute Respiratory InfectionBCR Benefit-Cost RatioCBA Cost-Benefit AnalysisCEA Cost Effectiveness AnalysisCOPD Chronic Obstructive Pulmonary DiseasesCOI Cost of IllnessDALY Disability-Adjusted Life-YearDHS Demographic and Health SurveyDOC Diesel Oxidation CatalystDPF Diesel Patriculate FilterGDP Gross Domestic ProductGNI Gross National IncomeHCA Human Capital ApproachHCV Human Capital ValueHECS Household Energy Consumption SurveyNOx Nitrogen OxidesIAP Indoor Air PollutionI&M Inspection and MaintenanceLPG Liquefied Petroleum GasOAP Outdoor Air PollutionPM Particulate Matterppm parts per millionRR Relative RiskSOx Sulfur OxidesUSEPA United States Environmental Protection AgencyVF Ventilation FactorVSL Value of Statistical LifeWSH Water, Sanitation and HygieneWTP Willingness to Pay 93
  • 94. I. INTRODUCTIONA cost-benefit analysis (CBA) provides estimates of the costs and benefits of anintervention, such as an investment, a policy or regulation, or a program. The results canbe expressed in terms of internal rate of return, net present value, or as a benefit-costratio. CBA is increasingly used in many countries for assessing the merits of potentialenvironmental interventions. As such, a CBA can serve as an instrument to establishpriorities and guide allocation of scarce public and private resources.Benefit-cost ratios for selected interventions to improve environmental health arepresented in this paper for the following areas of intervention, generally found to be theareas with the largest environmental health effects in developing countries (WHO, 2002): Outdoor air pollution (OAP) in major urban areas; Indoor air pollution (IAP) from household use of solid fuels; and Water supply, sanitation and hygiene (WSH).Costs and benefits of environmental interventions are often difficult and time consumingto comprehensively and accurately quantify. This is especially the case for OAP control.Therefore, rather than embarking on conducting a CBA purely based on data from thePhilippines, this paper presents some international evidence of benefit-cost ratios ofselected OAP control interventions. Adjustments of the data used in estimating thebenefit-cost ratios in the original studies have been undertaken to the extent possible toreflect the situation in the Philippines. A range of estimates of benefit-cost ratios are insome cases presented that reflect sometimes diverse situations within the Philippines.For IAP and WSH, the CBA presented here is based on data and recent estimates ofhealth effects in the Philippines by Arcenas (2009).Health improvements and time savings are most often the main benefits of interventionsaddressing OAP, IAP and WSH. IAP control interventions, such as an improved woodstove or use of an LPG stove for cooking, also involve significant changes in fuel use.Improvements in water supply and sanitation, and use of improved stoves or LPG stoves,can provide additional benefits such as improved convenience and status, but thesebenefits are often not quantified in monetary terms in CBA studies. The focus of theCBA in this paper is therefore on health, time savings, and changes in fuel use. II. OUTDOOR AIR POLLUTIONArcenas (2009) estimates there were over 15,000 deaths and over 1 million cases ofrespiratory illness (pneumonia and bronchitis) from particulate matter (PM) air pollutionin urban areas in the Philippines in year 2003. The annual cost of these health effects isestimated at US $0.1 – 1.1 billion, or about 0.1-1.1 percent of gross national income(GNI). The low end of the estimate is based on using the human capital approach (HCA)for valuation of mortality and the high end of the estimate is based on using a value of 94
  • 95. statistical life (VSL). In both cases, the cost-of-illness (COI) approach is used forvaluation of morbidity.Cost-benefit analysis of interventions to improve outdoor air pollution (OAP) in urbanareas have long been a tool used in the United States and increasingly in Europe andother high income countries. CBA studies from these countries may however not beapplicable to the Philippines or other developing countries because of differences intechnology levels. High income countries have for instance already implemented quitestringent fuel quality and emissions standards. This implies that the cost of furtheroutdoor air quality improvements are often substantially higher than in most developingcountries.There are however an increasing number of CBA studies from developing countries thatcan shed light on benefits and costs of OAP control interventions in the Philippines.These studies include Blumberg et al (2006) from China, Larsen (2005) from Bogota,Colombia, Stevens et al ( 2005) from Mexico City, Mexico, ECON (2006) from Lima,Peru, and Larsen (2007a) from Dakar, Senegal. The focus of these studies is onparticulate matter (PM) as PM is considered the pollutant with the largest health effects inmost urban areas (WHO, 2002). Interventions evaluated in these studies are control ofemissions from motorized transport. There are also CBA studies in developing countriesevaluating the control of emission from industry and power plants. Benefits and costs ofemission control from these sources are however very location specific and thereforediffult to apply to the Philippines.In applying the transport sector CBA studies from China, Colombia, Mexico, Peru andSenegal to the Philippines, several adjustments to the data used in these studies should beconsidered. This includes potential differences in emission sources and dispersion,differences in baseline health status, and differences in valuaton of health improvementsof interventions. Assessing differences in emission sources and dispersion would requiredetailed studies and is therefore not addressed here. This introduces a significant elementof uncertainty. The benfit-cost ratios (BCRs) frrom the studies in the beforementionedcountries can therefore only serve as an indication of the potential BCRs in thePhilippines. Health effects of OAP are predominantly among the adult, elderlypopulation. Baseline health status in this age group in major urban areas is quite similarin the Philippines, Colombia and Peru. No adjustments are therefore made to baselinehealth status. In China, a larger share of the population die from cardiopulmonarydisease than in the Philippines, thus health benefits of air pollution control might belarger in China than in the Philippines. The opposite may be the case in Senegal vs thePhilippines. The differences in China and Senegal should be taken into considerationwhen evaluating the benefit-cost ratios of interventions estimated for these countries.Valuation of estimated health improvements is adjusted in proportion to differences inincome level between the study countries and the Philippines. Mortality is valued using avalue of statistical life (VSL) and morbidity is valued using the cost-of-illness (COI)approach. A VSL of US $109,000 is applied which reflect gross national income (GNI)per capita in the Philippines in 2007.22 The human capital approach (HCA) could havebeen used for valuation of mortality. However, as most individuals dying from OAP arein age groups 60 years and older, the HCA would attach a very low or even zero value to22 This is calculated by using a VSL benefit transfer from high income countries of US$ 2 million (Mrozekand Taylor, 2002), adjusted to the Philippines in proportion to per capita income differences. 95
  • 96. mortality. Most studies to date, however, provide evidence that elderly individuals arewilling to pay significant amounts to reduce their risk of dying, and thus have a highVSL. The VSL approach is therefore likely to provide a more appropriate measure of thewelfare benefits to society from improving outdoor air quality than the HCA.InterventionsThe CBA studies from China, Colombia, Mexico, Peru and Senegal provide benefit-costratios for the following transport sector interventions: Low sulfur diesel (500 and 50 ppm sulfur content); PM control technology for new vehicles (Euro 4 standards); PM retrofit control technology for in-use diesel vehicles (diesel oxidation catalysts (DOC) and diesel particulate filters (DPF)); and Inspection and maintenance (I & M) of diesel vehicles.All these interventions address PM emissions from diesel vehicles, except for Euro 4standards which are for both gasoline and diesel vehicles. PM emissions from dieselvehicles with no or limited control technology are many times higher than from gasolinevehicles. However, gasoline vehicles contribute significantly to secondary PM throughatmospheric conversion of gasous emissions (such as NOx and SOx) to particulates (suchas sulfates and nitrates). Euro 4 standards for gasoline vehicles are therefore likely toprovide reductions in secondary PM. Lowering the sulfur content in diesel reduces PMemissions from diesel vehicles. Low sulfur diesel is also a prerequisite for properfunctioning of PM control technology in new and in-use vehicles. Euro 4 technologiesand diesel particulate filters (DPF) require a maximum sulfur content of 50 ppm. Nohigher than 500 ppm can be used for effective funtioning of Euro 2 technologies anddiesel oxidation catalysts (DOC).The share of diesel fuel consumption in road transport in the Philippines was about 50percent in 2005 (IEA, 2008). This was significantly higher than in Thailand (27%), butmuch lower than in India (71%) and Pakistan (85%).Intervention effectiveness and unit costsThe following emission control effectiveness parameters are used in the CBA studies inthe mentioned countries: Low sulfur diesel (500 ppm) reduces PM by an average 20%; Ultralow sulfur diesel (50 ppm) reduces PM by an average 33%; Diesel oxidation catalysts (DOC) reduces PM by > 25%; Diesel particulate filters (DPF) reduces PM by > 80%. 96
  • 97. Euro 4 standards reduce PM by 60-70% (relative to Euro 2).23Unit costs of interventions used in the CBA studies are presented in table 1. Most of thestudies use a range of cost. The costs in table 1 represent average costs used in each ofthe studies. Lowering the sulfur content from 500 to 50 ppm in diesel is more expensivethan lowering the content from for instance 2,000 to 500 ppm, the cost of a DPF is higherthan the cost of a DOC, and the cost of a DOC or DPF for a heavy duty vehicle is higherthan the cost for a light duty vehicle. Unit cost figures applied in the studies do also varyacross countries, based on various assumptions. The figures in table 1 are used here inthe CBA that is adjusted to the Philippines.Table 1: Unit costs of interventions to control vehicle PM emissions US $ Study countryDiesel (500 ppm sulfur) 1.6 US$/barrel (incremental cost) Colombia & SenegalDiesel (50 ppm sulfur) 2.6 US$/barrel (incremental cost) SenegalEURO 4 technology 150 light duty diesel vehicle ChinaEURO 4 technology 2500 heavy duty diesel vehicle ChinaDOC 435 buses & delivery trucks MexicoDOC 1000 large buses SenegalDPF 2300 older buses MexicoDPF 1600 newer buses & delivery trucks MexicoDPF 5000 buses ColombiaDPF 5000 large buses SenegalDPF 850 taxis SenegalRetrofit PM control 3000 buses PeruSource: From Blumberg et al (2006), Larsen (2005), Stevens et al ( 2005), ECON (2006) and Larsen(2007a).Benefit-cost ratiosBenefit-cost ratios (BCRs) of interventions to control PM emissions from road vehiclesare presented in table 2. They are ratios adjusted to the Philippines from the originalstudy countries. The BCRs should be considered applicable to major urban areas such asGreater Manila.The BCRs of low sulfur diesel is based on introducing such diesel in major urban areas.The BCRs of diesel with 500 ppm sulfur and subsequently 50 ppm are all greater thanone (i.e., benefits > costs). The BCRs from the Senegal study adjusted to the Philippinesare greater than those adjusted from the Colombia and Peru studies. This may largelyresult from very high road transport dieselization in Senegal and thus high share of PMemissions from diesel vehicles.The BCRs of vehicle PM control technologies, once low sulfur diesel is available, arealso greater than one for the types of vehicles and technologies presented in table 2. Thehighest BCRs are for diesel oxidation catalysts (DOC) for diesel buses (large and old).The advantage of the DOCs is that only 500 ppm sulfur diesel is required for the properfunctioning. With the exception of diesel particulate filters (DPF) for high usage dieseltaxis, the BCRs are generally lower for DPFs than for DOCs, because of the higher cost23 The reductions for heavy duty diesel vehicles is as high as 80-90% relative to Euro 2 standards. 97
  • 98. of DPFs. However, DPFs have the potential to reduce PM emissions substantially morethan DOCs once 50 ppm sulfur diesel is available.The study from China, adjusted to the Philippines, importantly finds that Euro 4standards for new vehicles (gasoline and diesel) provide a relatively high BCR. Suchstandards can be introduced once 50 ppm sulfur gasoline and diesel is available.However it would require that such gasoline and diesel is available nationwide if Euro 4is mandated for vehicles that are also used outside urban areas, such as intercity busesand trucks and passenger vehicles.The adjusted BCR from the Peru study for Inspection & Maintenance program for dieselvehicles suggests very high benefits relative to costs. Poorly maintained diesel vehiclesis a major contributor to PM emissions. An effective I & M program can thereforeprovide substantial benefits if properly implemented and monitored.In considering the BCRs presented in table 2, it should be remembered that healthbenefits are valued using VSL for mortality. As reduction in mortality is a significantshare of health benefits from air pollution control, the BCRs would be less than one if thehuman capital approach (HCA) was used to value mortality. However, as arguedpreviously, VSL is likely to better reflect social welfare gains from air pollution controlthan the HCA.The CBAs of PM emission controls did not consider two- and three-wheelers, streetcleaning and control of construction dust. Two- and three-wheelers are major sources ofPM emissions from the road transport sector in Asia, and 2-stroke engines causesubstantially higher emissions than 4-stroke engines. CBA studies are however limited,but PM control measures for two- and three-wheelers are generally considered highlycost effective.Improved street cleaning is another intervention to control PM and is considered highlycost effective but CBA studies are limited. Without proper and frequent street cleaning,PM emissions are resuspended into the air from traffic and wind, and can be a significantsource of PM ambient concentrations. Construction dust can also be a significant sourceof PM, but CBA studies are also limited for this source of PM.Foreign imports of second-hand diesel vehicles can be a major source of PM emissions.It is therefore important to ensure that such vehicles are equipped with Euro standards (orequivalents) suitable for the diesel fuel used in the Philippines.Table 2: Benefit-cost ratios of interventions to control PM emissions from road vehicles Benefit-cost ratios Original study Low sulfur diesel500 ppm diesel (Senegal) 5.06 Senegal500 ppm diesel (Colombia) 1.62 Colombia50 ppm diesel (Senegal) 4.09 Senegal50 ppm diesel (Peru) 1.40 Peru Control technology for new vehiclesEuro 4 standards 2.10 China Retrofitting of in-use diesel vehicles (DOC)Old buses 6.54 MexicoLarge buses 6.74 Senegal 98
  • 99. Buses 4.12 Peru Newer buses 2.97 Mexico Old delivery trucks 2.23 Mexico Newer delivery trucks 1.81 Mexico Retrofitting of in-use diesel vehicles (DPF) High usage taxis 5.30 Senegal Old buses 2.80 Mexico Large buses 2.89 Senegal Newer buses and delivery trucks 1.47 Mexico Inspection & Maintenance Diesel vehicles 3.90 PeruSource: Adjusted to the Philippines from the original studies by the author. III. INDOOR AIR POLLUTIONArcenas (2009) estimates there were nearly 5,800 deaths and nearly 500,000 cases ofillness (ALRI, COPD and tuberculosis) from indoor air pollution (IAP) annually in thePhilippines in year 2003. Around 1,300 of the deaths (ALRI) are in children u5, and4,500 deaths (mainly COPD and tuberculosis) are in adults (15+ years of age). Theannual cost of these mortality and morbidity health effects is estimated at US $87 – 435million. The low end of the estimate is based on using the human capital approach(HCA) for valuation of mortality and the high end of the estimate is based on using avalue of statistical life (VSL). In both cases, the cost-of-illness (COI) approach is usedfor valuation of morbidity.An increasing number of CBA studies from developing countries can shed light onpotential benefits and costs of controling IAP from household use of solid fuels forcooking. The predominant solid fuel used in the Philippines for cooking is wood,although charcoal is also significant. Evaluation of benefits and costs of IAP controltherefore focuses on replacing unimproved wood stoves with improved wood stoves, andreplacing wood stoves with LPG stoves as the use of LPG has increased rapidly over thelast decade. Switching from fuel wood to charcoal is not considered here, as few studiesare available that provide estimates of health effects of using charcoal vs fuel wood.CBA studies of improved wood stoves and use of LPG include a global-regional study byHutton et al (2006), Habermehl (2007) from Uganda, Larsen (2005) from Colombia,Larsen and Strukova (2006) from Peru, and a global-regional cost-effectiveness study byMehta and Shapar (2004). Habermehl presents a CBA for improved wood and charcoalstoves, and the other studies look at improved wood stoves as well as switching to cleanerfuels such as LPG. These studies all find that the benefits of replacing unimproved woodstoves with improved wood stoves by far exceeds the cost of stoves and stove promotionprograms. For replacing wood stoves with LPG stoves, the studies show however mixedresults depending on estimates of time and fuel wood savings and valuation of thesesavings. 99
  • 100. The methodologival approach to estimate health benefits of interventions in most of theCBA studies is to apply the relative risks (RR) of disease from household use of solidfuels presented in the meta-analysis of international evidence in Desai et al (2004).24These relative risks can be considered to reflect IAP in households using unimprovedwood or biomass stoves in poorly ventilated indoor environments causing high exposureto solid fuel smoke. An unimproved solid fuel stove is a stove with low fuel efficiencyand no control of smoke, with smoke emitted directly into the immediate environment.An improved solid fuel stove is a stove with higher fuel efficiency and cleaner fuelburning. The stove may be attached to a chimney or hood that vents the smoke to theoutside from the indoor environment, which further reduces immediate exposure tosmoke. Most of the CBA studies evaluates the health benefits of an improved woodstove that reduces the health effects of IAP from solid fuels by 30-70 percent relative tothe use of an unimproved wood stove. Switching to an LPG stove from an improvedwood stove would eliminate the remaining health effects of IAP from solid fuels.When estimating the potential health benefits of controlling IAP from household solidfuel use, considerations must be given to potential differences between the studycountries in Desai et al and the Philippines in terms of cooking practices, smokeventilation characteristics of dwellings, type of stoves used by households. Potentialdifferences in cooking practices and smoke ventilation characteristics of dwellings(household air pollution exposure conditions) can be incorporated in a CBA by applyinga ventilation factor (Desai et al, 2004). For the purposes of the CBA here, a ventilationfactor (VF) of 1.0 represents indoor cooking with minimal separation of cooking andliving areas and minimal venting of smoke from solid fuel use. If cooking with solidfuels is undertaken outdoors or in a well-ventilated area of the dwelling separated fromliving areas, the VF is assumed to be 0.25.25 These VFs are applied to the excess risk ofhealth effects from use of solid fuels when estimating the disease burden from IAP.26The estimates of health effects in Arcenas (2009) is based on a VF of 0.25. While thismay be reflective of predominant exposure conditions in the Philippines, manyhouseholds are likely to cook in conditions representing a VF of 1.0. To estimatepotential benefits of IAP control in these households, the estimates of health effects inArcenas are reestimated at VF=1.0.27In order to provide a value of potential health benefits that are applicable if interventionswere to be implemented now, the estimates in Arcenas are adjusted to year 2007 inproportion to changes in gross national income (GNI) per capita from 2003 to 2007. Thisimplies a value of statistical life (VSL) of US $109,000 as used in the OAP section. Atthe low end, mortality is valued using the human capital value (HCV) equal to the present24 Subsequent to the referenced CBA studies, a meta-analysis of the relative risk of pneumonia in youngchildren was undertaken by Dherani et al (2008), finding a somewhat lower relative risk than reported inDesai et al (1.8 vs 2.3). The results in Dherani et al is applied here to the Philippines.25 Even in such favorable conditions, use of solid fuels still result in household exposure to smoke (for theperson cooking, nearby children, and from smoke entering the dwelling). A ventilation factor=0 istherefore practically non-existent when solid fuels are used for cooking and other purposes.26 Excess risk of health effects is RR-1 where RR is risk of health effects relative to not using solid fuels.27 Restimation was done by recalculating the attributable fractions (AFs) of disease and mortality fromindoor air pollution, and valuing the atributable fractions using unit values from Arcenas, and adjusting toyear 2007. 100
  • 101. value of life time income lost from premature mortality.28 For children under five year ofage, the HCV is about ½ of the VSL. For adults, the HCV averages about US $7,800 or4.8 times GNI per capita in 2007.Type of solid fuel stoves in the study countries in Desai et al may not be the same as inthe Philippines. For practical purposes, solid fuel stoves are classified as unimproved andimproved stoves. It is assumed here that the relative risk of health effects of anunimproved stove is the same across countries if used under the same cooking conditions.If cooking conditions are different, then the ventilation factor is applied to reflect thesedifferences. Improved stoves may be different across countries. This is irrelevant in aCBA for an intervention replacing an unimproved stove with an improved stove, as longas the type of improved stove is charcterized. It is here assumed that the improved stoveis of such a characteristic as to reduce excess risk of health effects from solid fuels by 50percent. Type of improved solid fuel stoves currently in use in the Philippines is howeverimportant if they are to be replaced by for instance LPG. For practical purposes, thescenario considered here is replacing improved stoves that cause health effects at 50percent of unimproved stoves. Thus switching from an improved stove to LPG wouldremove the remaining 50 percent of health effects from solid fuel used in unimprovedstoves.Most of the CBA studies do also evaluate non-health benefits of improved solid fuelstoves or LPG stoves. These benefits may include time savings from reduced solid fuelcollection or cost savings from reduced solid fuel purchases, time savings from reducedcooking time associated with improved stoves or LPG stoves, and potentialenvironmental benefits arising from reduced need for fuel wood (see next section).Interventions and unit costsThree interventions are evaluated: Switching to improved wood stove from unimproved wood stove (50% reduction in health effects relative to unimproved stoves); Switching to LPG stove from unimproved wood stove (removes all health effects from solid fuels); and Switching to LPG stove from improved wood stove (removes all health effects from solid fuels);Each of these three interventions are evaluated for two different household conditions,one in which the ventilation factor is 1.0 (indoor cooking with no or minimal separationbetween cooking and living areas and no or minimal ventilation) and one in which theventilation factor is 0.25 (outdoor cooking or cooking in well ventilated area separatedfrom living area).Unit costs of interventions and key stove and fuel parameters used in the CBA arepresented in table 3. Household fuel wood consumption is around 2 tons per year for anunimproved stove. This is estimated based on data in the Philippines HECS 2004 (NSO,28 Studies of VSL are mostly for adults. As a substantial share of mortality from indoor air pollution is inchildren, a scenario using the HCV is also used. 101
  • 102. 2005) and Samson et al (2001). There are various types of improved wood stoves ofdifferent prices. The type of improved stove evaluated here is more costly than manyother simple improved stoves, and is assumed to have a useful life of 10 years and betwice as energy efficient as an unimproved stove, i.e., the use of the improved stoveprovides 50 percent fuel wood savings. This is consistent with or conservative relative tofor instance findings in Samson et al (2001) and Habermehl (2007). LPG fuel costchanges with world prices. As of recently, the cost of LPG in the Philippines was aboutUS $ 1 per kg. LPG fuel consumption for cooking is estimated at 100 kg per householdper year (NSO, 2005; IEA, 2008; Samson et al, 2001).Fuel wood savings from introducing an improved wood stove or switching to an LPGstove is valued at 75 percent of wage rates for households that collect their fuel wood.An approximate rural wage rate of US$0.5 per hour is applied, as fuel wood collection ismore predominant in rural areas. Hutton et al (2006) reports fuel wood collection time for20 countries. The lowest average collection time is 30 minutes per day (Indonesia andNigeria). To be conservative, 30 minutes is applied to the Philippines for householdsusing unimproved wood stoves. Thus a household collecting its fuel wood, andswitching from an unimproved to an improved wood stove, would save about 15 minutesper day in colletion time valued at US $35 per year. For households that purchase someor all of their fuel wood, savings will be greater. A market price of US$45 per ton of fuelwood is applied, which is similar to prices reported in Samson et al (2001).Table 3: Unit costs of interventions and key stove and fuel parameters Source:Wood consumption Philippines (NSO (2005); Samson et al(unimproved stove) 2 Tons/household/year (2001).Improved wood stove cost 20 US$ per stove Philippines (assumed)Fuel wood collection time(unimproved stove) 30 Minutes/household/day Philippines (assumed)Wood savings (improved Relative to unimprovedstove) 50% stove Based on change in stove efficiencyLPG stove cost 60 US$ per stove PhilippinesLPG fuel cost 1 US$ per kg Philippines (November 2008) Based on wood consumption, stove efficiencies, and NSO (2005) IEA (2008),LPG fuel consumption 100 Kg/household/year Samson et al (2001). Using a rural wage rate of US$0.5 perValuation of time savings 75% Of wage rates hour US$ per household perPromotion program 5 year Colombia & PeruNote: Stove costs are annualized over 10 years at a discount rate of 10%.It is also assumed that a promotion program is needed to encourage households to switchto improved wood stoves or LPG, at a cost of US $5 per household per year.29 Thus29 Program cost per household is cost per household that switches to improved wood stove or LPG stove.Program cost per household targeted by the program is substantially lower, as only a fraction of householdsrespond to the program. 102
  • 103. program cost per household is significantly higher than the annualized cost of theimproved stove, but only 5 percent of annual cost of LPG consumption per household.Benefit-cost ratiosBenefit-cost ratios (BCRs) of interventions to control IAP from household use of solidfuels are presented in table 4. Ratios are presented for two valuation methods of healthbenefits (VSL for mortality and COI for morbidity; and HCV for mortality and COI formorbidity) and for two ventilation factors reflecting a range of household air pollutionexposure conditions.The BCRs for replacing unimproved wood stoves with improved wood stoves are greaterthan one (i.e., benefits > costs) for both valuation methods under the whole range ofhousehold air pollution exposure conditions (VF: 0.25-1.0). This is the case even whenonly health benefits are included. When time savings from reduced fuel wood collectionis included (resulting from increased energy efficiency of improved stoves), the BCRs forexposure conditions with VF=0.25 increase significantly.The BCRs for replacing unimproved wood stoves with LPG stoves are greater than one inthe highest exposure conditions (VF=1) when mortality is valued using VSL or whentime savings or fuel wood purchase savings are included as benefits. In low exposureconditions (VF=0.25), BCRs are only greater than one when mortality is valued usingVSL and time savings are included (4-5 in table 4). BCRs for replacing improved woodstoves with LPG stoves are only greater than one in the highest exposure conditions andwhen mortality is valued using VSL (6-8 in table 4).Table 4: Benefit-cost ratios of interventions to control indoor air pollution from solidfuels Valuation method VSL & COI HCV & COI Ventilation factor (VF) VF=1 VF=0.25 VF=1 VF=0.25(1) Improved wood stove (health only) 14.5 5.02 3.08 1.00(2) Improved wood stove (health & time savings) 18.8 9.32 7.38 5.30(3) LPG from unimproved stove (health only) 2.03 0.70 0.43 0.14(4) LPG from unimproved stove (health & time savings) 2.63 1.30 1.03 0.74(5) LPG from unimproved stove (health & wood cost savings) 2.83 1.50 1.23 0.94(6) LPG from improved stove (health only) 1.02 0.35 0.21 0.07(7) LPG from improved stove (health & time savings) 1.32 0.65 0.52 0.37(8) LPG from improved stove (health & wood cost savings) 1.42 0.75 0.62 0.47Source: Estimated by the author.The BCRs presented in table 4 are likely to be conservative. Potential reductions invarious respiratory health symptoms other than acute lower respiratory infections (ALRI)are not included. Winrock International (2005) in a study in the Philippines providessome perspectives on such symptoms in relation to household cooking fuel. The CBAstudies from Colombia and Peru include upper and lower acute respiratory illness (ARI)and find that the monetized benefits are a substantial share of total health benefits, 103
  • 104. especially when mortality is valued using the HCA.30 Potential time savings fromreduced cooking time is also not included in the BCRs in table 4. Hutton et al (2006)report that an improved wood stove and LPG stove can reduce cooking time by over 10percent relative to an unimproved wood stove. This could therefore amount to 10-15minutes per day for a typical household cooking three meals a day, which is close the fuelwood collection time savings from an improved wood stove and half of the collectiontime savings from switching from an unimproved wood stove to an LPG stove.31Valuing reduced cooking time raises however issues as to the extent to which this freesup time for other activities for the person cooking. If the person can conduct otherhousehold activities while food is cooking, then there are no effective time savings fromreduced cooking time. Because of this uncertainty, any benefits from reduced cookingtime is therefore not included in this CBA for the Philippines. IV. WATER SUPPLY, SANITATION AND HYGIENEArcenas (2009) estimates that there were 14,400 deaths and over 33 million cases ofillness (mainly diarrhea) from inadeqate water supply, sanitation and hygiene (WSH) inthe Philippines in year 2003. Over 10,500 of these deaths and over 19 million cases ofillness were in children under-5. In addition, there were an estimated 7,600 malnutritionrelated deaths in children under-5 from WSH.32 The annual cost of these health effects isestimated at US $1 – 1.9 billion. The low end of the estimate is based on using thehuman capital approach (HCA) for valuation of mortality and the high end of the estimateis based on using a value of statistical life (VSL). In both cases, the cost-of-illness (COI)approach is used for valuation of morbidity.Interventions to improve WSH include upgrading of household water supply andsanitation from unimproved to improved water supply and toilet facilities, point-of-usehousehold treatment of drinking water, and improved hygiene practices especiallyhandwashing with soap by mothers or caretakers of young children.33 Several meta-30 The health benefits of interventions in the Colombia and Peru studies were adjusted to the Philippines forillustration. This provided BCRs quite consistent with the BCRs in table 4. However, the adjusted BCRsfrom the Colombia and Peru studies tend to be higher than in table 4 when the HCA was used for valuationof mortality.31 The data pesented in Hutton et al suggest there is no significant cooking time difference between animproved wood stove and an LPG stove. In this case there would be no additional time savings benefits(other than fuel wood collection time savings) from switching from an improved wood stove to an LPGstove.32 Estimated by B. Larsen in Arcenas (2009).33 Unimproved water supply includes direct use of surface water (rivers, lakes, ponds, etc), unprotected dugwells, unprotected springs, tanker trucks and carts with small drums/tanks, and unimproved rain water.Improved water supply includes protected dug wells, protected springs, boreholes/tubewells, publicstandpipes, piped water supply into dwelling or yard, and improved rain water (collected and stored in aclosed tank and withdrawn from a tap). Unimproved sanitation includes open pit latrine/pit latrine withoutslab, hanging toilet/latrine, bucket, no toilet facility or bush or field, and flush/pour flush toilet draining to aplace other than a piped sewer system, septic tank or pit latrine. Improved sanitation includes pit latrinewith slab, composting toilet, ventilated improved pit latrine, and flush/pour flush toilet to a piped sewersystem, septic tank or pit latrine.Point-of-use household treatment of water includes boiling of water, chemical disinfection of water (e.g.,chlorination), solar disinfection, filtration, flocculation-disinfection. 104
  • 105. analyses have recently been undertaken of the international evidence of the effectivenessof these interventions in reducing diarrheal illness. Hand washing with soap andhousehold point-of-use drinking water disinfection are generally found to be mosteffective in reducing diarrheal illness, followed by improved sanitation and water supply(table 5).Table 5: Reduction in diarrheal illness from water supply, sanitation and hygieneinterventions Hand Point-of-use Improved sanitation Improved washing with drinking water (improved toilet water soap disinfection facilities) supplyFewtrell et al (2005) 44% 26% (urban) 32% 25% 39% (rural)Curtis and Cairncross 47%(2003)Arnold and Colford (2007) 29% (chlorine)Clasen et al (2007a) 30-40% (children u5) 35-50% (all ages)Studies have also found that improved handwashing reduces the risk of respiratoryinfections. In a meta-analysis of available studies from developed countries, Rabie andCurtis (2006) found that improved handwashing on average reduced respiratoryinfections by 16 percent. In a randomised controlled trial in Karachi, Pakistan, Luby et al(2005) found that children under-5 in households that received handwashing promotionand soap had a 50 percent lower incidence of pneumonia than children in the controlgroup that did not receive promotion and soap.CBA studies from developing countries have focused on various aspects of improvingWSH. Most recently, they include a global-regional study by Hutton et al (2007),ECON (2006) from Egypt, Larsen (2005) from Colombia, Larsen and Strukova (2006)from Peru, Larsen (2007b) from Mexico, and Larsen (2007a) from Senegal. Thesestudies present CBA for a range of interventions such as improved water supply andsanitation facilities, and improved hygiene and household drinking water disinfection.There are also CBA studies of wastewater treatment. Benefits of wastewater treatmentare however very location specific and difficult to adapt to other settings or generalize toa national level.There are also several recent cost-effectiveness analysis (CEA) studies of WSHinterventions. For instance, Clasen et al (2007b) and Clasen and Haller (2008) present aglobal-regional CEA of various household water treatment options at water source andpoint-of-use. Haller et al (2007) present a global-regional CEA of improved water supplyand sanitation and household water treatment. Shrestha et al (2006) evaluates the healthbenefits of home-based chlorination and safe water storage in rural Uganda. Cairncrossand Valdmanis (2006) presents a global CEA of household water supply, sanitation andhygiene promotion. Larsen (2003) presents a global-regional CEA of water, sanitation 105
  • 106. and hygiene interventions. These studies provide estimates of the cost of averting adisability adjusted life year (DALY) while Larsen estimates costs per death averted.34All the CBA country studies as well as the global-regional study by Hutton et al (2007)evaluates both non-health and health benefits of WSH interventions. The main non-health benefit is time savings from improved access to water supply and sanitationfacilities. Health benefits are reduced incidence of diarrheal illness and mortality. Noneof the CBA and CEA studies include potential improvements in child nutritional status(and associated health and non-health benefits) from reduced diarrheal illness. WorldBank (2008) summarizes the international evidence of this link and concludes that 20-50percent of child underweight may be caused by diarrheal infections in early childhood,mainly arising from inadequate WSH. As child underweight is an important indicator ofincreased risk of child mortality and disease (Fishman et al, 2004), Fewtrell et al (2007)estimates that the additional health burden of malnutrition related health effects fromWSH in developing countries is 60 percent higher than previously estimated when onlydiarrheal mortality and illness from WSH is considered. Similarly, Larsen (2008)estimates that total mortality from WSH in several Asian countries is 60-80 percenthigher than direct diarrheal mortality from WSH.35 Moreover, World Bank (2008) andLarsen (2007c) estimate that the annual cost of non-health effects of child malnutritionfrom WSH is nearly 4-5 percent of GDP in Ghana and Pakistan. This cost arises from thenegative impact of malnutrition on children’s cognitive development, schoolperformance, productivity and life time income. Although the prevalence of childmalnutrition is lower in the Philippines than in Pakistan, the cost may be similar to thatin Ghana, nearly 4 percent of GDP.36Also, importantly, none of the CBA and CEA studies include potential reductions inrespiratory infections from improved handwashing. This omission is likely to represent asignificant underestimation of the benefits of handwashing programs, as improvedhandwashing was found to substantially reduce pneumonia in Pakistan (Luby et al, 2005),and to generally reduce respiratory infections in developed countries (Rabie and Curtis,2006).In order to provide a value of potential health benefits that are applicable if interventionswere to be implemented now, the estimates of health effects from WSH in Arcenas(2009) are adjusted to year 2007 in proportion to changes in gross national income (GNI)per capita from 2003 to 2007. This implies a value of statistical life (VSL) of US$109,000. At the low end, mortality is valued using the human capital value (HCV)equal to the present value of life time income lost from premature mortality.37 Forchildren under five year of age, the HCV is nearly ½ of the VSL. For the population 5+34 There ar also single intervention studies. For instance, Meddings et al (2004) presents a CEA ofhousehold sanitation (latrines) improvements in Kabul, Afghanistan.35 In the Philippines, total mortality from WSH is estimated to be nearly 70 percent higher than only directdiarrheal mortality from WSH (see Larsen in Arcenas (2009).36 Prevalence of child stunting, an indicator of chronic malnutrition and strongly associated with impairedschool performance, is higher in the Philippines than in Ghana (see www.childinfo.org). Studies from Cebuin the Philippines find significant effects of early childhood stunting on school performance such asdelayed primary school enrollment, increased drop-out rates and grade repetition, lower child learningproductivity at school, and less years of schooling (Daniels and Adair , 2004; Glewwe et al, 2001).37 Studies of VSL are mostly for adults. As a substantial share of mortality from WSH is in children, ascenario using the HCV is also used. 106
  • 107. years of age, the HCV averages about US $33,000 or 20 times GNI per capita in 2007.Baseline child mortality rate is also adjusted from 2003 to 2007, i.e., from 36 to 30 deathsper 1,000 live births, and child mortality from WSH is adjusted proportionately. In orderto evaluate benefits and costs of hand washing and drinking water disinfection promotionprograms in urban and rural areas, health effects in urban and rural areas are estimatedfrom the national estimates in Arcenas in relation to urban and rural child mortality andmorbidity rates.38Interventions and unit costsIn light of the results from the meta-analyses of the effectiveness of WSH interventions inreducing diarrheal illness, the focus here is a CBA of hand washing promotion andhousehold point-of-use drinking water disinfection promotion. Benefits and costs areevaluated for hand washing promotion to mothers and caretakers of young children andto other household members separately. Hand washing by mothers and caretakers ofyoung children involves hand washing with soap at critical times such as after going tothe toilet, after cleaning a child, and before preparing meals and feeding a child. Fordisinfection, benefits and costs of boiling of drinking water are evaluated, and, as forhand washing, evaluations are undertaken for children u5 and older household membersseparately.39Benefits of hand washing and drinking water disinfection promotion programs dependscritically on household response rate to the programs and sustainability of improved handwashing practices and water disinfection among those responding to the program. Threehand washing programs that provide program costs and response rates are presented intable 6. Response rates, i.e. improved hand washing behavior, range from 10 to18percent of target households. Program cost ranges from around US $0.4 to US $5 pertarget household, and from US $3.5 to US $28 per household with improved behavior.40In terms of sustainability of behavioral change, a study of communities in six countries inAfrica and Asia found that improved hygiene behavior from intervention programs issustained several years after interventions (Shordt and Cairncross, 2004). The CBA heretherefore presents benefits and costs of promotion programs with response rates rangingfrom 10-20 percent and 1-3 years of sustained improved hand washing practices andhousehold water disinfection.Table 6: A Review of costs and effectiveness of hand-washing promotion programs Guatemala Thailand Burkino FasoTarget area National Rural villages One City38 According to the Philippines DHS 2003, the child mortality rate in urban and rural areas was 30 and 52respectively. These figures are adjusted to reflect the national child mortality rate in 2007. Diarrhealprevalence rate in children u5 in urban and rural areas was the same. Thus no adjustments are made tomorbidity.39 Alternative disinfection or treatment methods could be evaluated, such as household chlorination,filtering, solar disinfection, and flocculation disinfection (see Clasen and Haller, 2008). Boiling of drinkingwater is however a common treatment method by households in many developing counries and is thereforeevaluated here.40 No studies were identified by the author of household point-of-use drinking water disinfection promotionprogram response rates and program cost per household. 107
  • 108. With children With childrenTargeted Households under-5 All All under-3Number of Targeted Households 1570000 10000 6550 38600Duration of Program Implementation 1 year 3-4 months 3-4 months 3 yearsResponse rate (% of target population) 10% 11% 16% 18%Program Cost (000 US $) 560 6 7.7 194Program Cost per Target Household (US $) 0.4 0.6 1.2 5.0Program Cost per Target Householdwith Behavioral Change (US $) 3.6 5.4 7.4 28Source: Derived from Saade et al (2001), Pinfold and Horan (1996), and Borghi et al (2002).Three hand washing promotion program scenarios are presented in table 7 in terms ofhousehold response rates and program costs in line with the findings from the review ofprograms in table 6. Program cost per target person (mother or caretaker of children u5)with behavioral change ranges from US $4 to $25. Reduction in diarrheal illness (anddiarrheal mortality) in children u5 is assumed to be 45 percent (see table 5). Few studieshave estimated soap consumption from improved hand washing practices. Borghi et al(2002) report soap consumption for hand washing to be about 7 balls of soap perhousehold per year at US $0.5 per ball in households in Burkino Faso that responded to ahand washing promotion program.41 Consumption of 12 soaps per person per year at acost of US $0.4 per soap is applied here. Increased water use for improved hand washingis from Borghi et al (2002). Cost of water is assumed to be US $0.5 per m3 in both urbanand rural areas.42 Thus total private cost (soap and water) per person with behavioralchange is US $5.35 per year. This is slightly higher than program cost per person withbehavioral change in Scenario 1, and only 1/5th of program cost in Scenario 3.Table 7: Hand washing program response rates and unit costs Scenario 1 Scenario 2 Scenario 3Program response rate (% of program targets with behavioral change) 10% 15% 20%Program cost per program target (US$) 0.40 1.20 5.00Program cost per target person with behavioral change (US$) 4.00 8.00 25.00Reduction in diarrheal illness from improved hand washing 45% 45% 45%Soap consumption (soaps/person/year) 12 12 12Cost per soap (US$) 0.40 0.40 0.40Cost of soap per person per year (US$) 4.80 4.80 4.80Increased water use for improved hand washing (liters/person/day) 3 3 3Cost of water (US$ per m3) 0.5 0.5 0.5Cost of water per person per year (US$) 0.55 0.55 0.55Private cost per person with behavioral change per year (US$) 5.35 5.35 5.35Source: Assumptions and estimates by the author.Three household point-of-use drinking water promotion program scenarios are presentedin table 8, identical to the hand washing scenarios in terms of household response rates41 Borghi et al do not present soap consumption per household member with improved hand washing.However, as the hand washing promotion program targeted mothers with children, it may be assumed thatmost of the soap consumption was by mothers.42 This implies that annual cost of water is around 10 percent of annual cost of soaps, thus the assumptionhas minimal impact on total costs. 108
  • 109. and program costs. Reduction in diarrheal illness (and diarrheal mortality) is assumed tobe 25 percent in urban areas and 35 percent in rural areas (see table 5).Disinfection method evaluated is boiling of water. It is assumed that 1 liter is boiled perperson per day for population aged 5+ years and 0.5 liters is boiled for children under 5years of age. Estimated costs of boiling are presented in table 9. Estimates assume thatwater is boiled for 10 minutes.43 Cost of boiling with LPG assumes a stove efficiency of50 percent. Cost of LPG is US $1.0 per kg, as per November 2008 in the Philippines.Cost of boiling with fuel wood assumes a stove efficiency of 15 percent. Implicit cost offuel wood is US $45 per ton, based on household collection time of 30 minutes per day,annual household consumption of fuel wood of 2 tons per year for all purposes, and timevalued at 75 percent of a rural wage rate of US $0.5 per hour (see table 3 in indoor airpollution section).Table 8: Household drinking water disinfection program response rates and unit costs Scenario 1 Scenario 2 Scenario 3Program response rate (% of program targets with behavioral change) 10% 15% 20%Program cost per program target (US$) 0.40 1.20 5.00Program cost per target person with behavioral change (US$) 4.00 8.00 25.00Reduction in diarrheal illness from drinking water disinfection (urban) 25% 25% 25%Reduction in diarrheal illness from drinking water disinfection (rural) 35% 35% 35%Source: Assumptions by the author.Table 9: Cost of boiling drinking water (US$ per person per year)Fuel used for boiling of water Children u5 years Population 5+ yearsLPG (urban and rural) 3.1 6.2Fuel wood (rural) 1.75 3.5Source: Estimates by the author.Benefit-cost ratiosBenefit-cost ratios (BCRs) for hand washing promotion and for household drinking waterpoint-of-use disinfection promotion are estimated with and without child nutritionbenefits. Nutrition benefits are reduced malnutrition (and thus reduced child mortality)from reduction in diarrheal incidence in early childhood. It is assumed that the healthbenefits are proportional to reduction in diarrheal incidence, and are therefore at best avery rough estimate. The BCRs with nutrition benefits should therefore be considered atthe most as only indicative of additional benefits of hand washing not previouslyincorporated in benefit-cost analysis.4443 Energy requirement and cost of bringing water to boiling point is estimated at about 10 times higher thanthe energy required to keep water boiling for 10 minutes. Thus length of boiling time has minimal impacton overall cost of boiling drinking water.44 To improve the estimates of nutrition benefits, a functional form relating reduction in diarrheal incidenceand nutritional status would need to be determined from the empirical literature to estimate counterfactualnutritional status. Secondly, relative risks of mortality from poor nutritional status (for severe, moderate,and mild underweight) in Fishman et al (2004) would need to be applied to counterfactual nutritional statusto estimate health benefits. For the methodology and estimates of health effects of malnutrition fromdiarrheal infections, see annex in Arcenas (2009) by B. Larsen, or World Bank (2008) and Larsen (2007c). 109
  • 110. Hand washing promotion: BCRs of hand washing promotion targeting mothers andcaretakers of children u5 in urban and rural areas are presented in tables 10-11. Benefitsof the program are reduced diarrheal illness and mortality in children u5.45 BRCs arepresented for promotion program response rates ranging from 10 to 20 percent, withimproved hand washing sustained for 1 to 3 years, and for two valuation methods ofhealth benefits (VSL for mortality and COI for morbidity; and HCV for mortality andCOI for morbidity).The following can be observed: BCRs are higher in rural than in urban areas because oflarger benefits related to child mortality in rural areas; BCRs increases with the length oftime improved hand washing is sustained, based on the assumption that the promotionprogram cost is incurred in the first year; and BCRs decline with higher programresponse rate due to the higher unit cost per person to induce behavioral change (see table7).BCRs are all greater than one, except for in urban areas if improved hand washing is notsustained for more than one year, nutrition benefits are not included, and the promotionprogram is of an intensitiy and high cost as to achieve a 20 percent response rate.Table 10: Benefit-cost ratios of hand washing promotion, urban areas Valuation method VSL & COI HCV & COI Program response rate 10% 15% 20% 10% 15% 20% Benefit-Cost Ratios (w/o child nutrition benefits)Improved hand washing is sustained for 1 year 4.6 3.2 1.4 2.7 1.9 0.8Improved hand washing is sustained for 2 years 5.8 4.5 2.3 3.4 2.6 1.4Improved hand washing is sustained for 3 years 6.3 5.2 3.0 3.7 3.0 1.7 Benefit-Cost Ratios (w/ child nutrition benefits)Improved hand washing is sustained for 1 year 7.0 4.9 2.1 3.7 2.6 1.1Improved hand washing is sustained for 2 years 8.7 6.8 3.5 4.6 3.6 1.9Improved hand washing is sustained for 3 years 9.5 7.9 4.5 5.0 4.1 2.4Source: Estimated by the author. Benefits and costs are discounted at an annual rate of 10 percent.Table 11: Benefit-cost ratios of hand washing promotion, rural areas Valuation method VSL & COI HCV & COI Program response rate 10% 15% 20% 10% 15% 20% Benefit-Cost Ratios (w/o child nutrition benefits)Improved hand washing is sustained for 1 year 7.0 4.9 2.2 3.7 2.6 1.1Improved hand washing is sustained for 2 years 8.8 6.9 3.5 4.6 3.6 1.9Improved hand washing is sustained for 3 years 9.6 7.9 4.5 5.1 4.2 2.4 Benefit-Cost Ratios (w/ child nutrition benefits)Improved hand washing is sustained for 1 year 11.1 7.8 3.4 5.4 3.8 1.7Improved hand washing is sustained for 2 years 14.0 10.9 5.6 6.8 5.3 2.7Improved hand washing is sustained for 3 years 15.2 12.6 7.2 7.4 6.1 3.5Source: Estimated by the author. Benefits and costs are discounted at an annual rate of 10 percent.45 Mothers and caretakers are also likely to benefit from improved hand washing in terms of reduceddiarrheal illness. These benefits are not included here and thus the benefit-cost ratios are likely to beconservative. 110
  • 111. A hand washing promotion program targeting mothers and caretakers of young childrenmay also induce improved hand washing practices in the population aged 5+ years, withor without additional program promotion cost. A CBA for this population is thereforealso undertaken. In the case of no additional program costs, the BCR is about 0.4 whenbenefits are valued using the HCV and COI and about 0.7 when benefits are valued usingVSL and COI.46 These estimates are based on the same benefit and cost parameters asfor children u5, except that program promotion cost is assumed to be zero for thispopulation group (see table 7).47A promotion program may also be implemented that targets all population age groups(not only households with young children). If program cost per household is the same asthe one targeting households with children, then, when valuing benefits with the HCVand COI, the BCRs for the population 5+ years of age are estimated at 0.35 for the 10%response rate scenario and 0.25 for the 20% response rate scenario for the case whenimproved hand washing is sustained for two years (in contrast to 0.4 when program costis assumed zero). The corresponding BCRs using VSL and COI are 0.65 and 0.5.The reason for the low BCRs for the population 5+ years of age is the much lowerincidence of diarrheal disease and mortality in this population group than in children u5.Benefits from reducing the disease burden is therefore proportionately lower in thepopulation 5+ years. The BCR does however depend critically on soap consumption forimproved hand washing. The BCR is greater than one if required soap consumption isless than 4 soaps per person per year (instead of 12), when benefits are valued using theHCV and COI. If VSL and COI are used to value benefits, then the BCR is greater thanone if soap consumption is less than 8 soaps per year.Drinking water disinfection promotion: BCRs of household drinking water disinfection(boiling of drinking water) for children u5 in urban and rural areas are presented in tables12-14. Benefits of the program are reduced diarrheal illness and mortality in children u5.Ratios are presented for promotion program response rates ranging from 10 to 20 percent,with drinking water disinfection sustained for 1 to 3 years, and for two valuation methodsof health benefits (VSL for mortality and COI for morbidity; and HCV for mortality andCOI for morbidity). Fuel for boiling of water is LPG in urban areas, and LPG or wood inrural areas.The following can be observed: BCRs are higher in rural than in urban areas because oflarger healh benefits in rural areas;48 BCRs are higher for fuel wood than LPG (ruralareas), because of fuel cost differentials;49 BCRs increases with the length of timedrinking water disinfection is sustained, based on the assumption that the promotion46 Data are not sufficiently available to estimate BCR for urban and rural areas separately for thispopulation age group.47 In this case, the BCR is independent of program response rate and period of sustained improved handwashing practice, and is determined solely by health benefits and private cost of hand washing (soap andwater consumption).48 This is from higher percentage reduction in diarrheal illness in rural areas (see table 8), and from higherbaseline child mortality in rural areas.49 It should be noted that use of fuel wood has air pollution health effects that are not reflected in theestimated BCRs. However, as seen in the indoor air pollution CBA section, benefits of switching from fuelwood to LPG generally only appear to exceed the incremental cost of LPG in households using stovesindoors in poorly ventilated environments. 111
  • 112. program cost is incurred in the first year; and BCRs decline with higher programresponse rate due to the higher unit cost per person to behavioral change (see table 8).BCRs are all greater than one, except for in urban areas if drinking water disinfection isnot sustained for more than 1-2 years, nutrition benefits are not included, and thepromotion program is of an intensitiy and high cost as to achieve a 20 percent responserate.Table 12: Benefit-cost ratios for drinking water disinfection promotion, urban childrenu5(boiling of water using LPG) Valuation method VSL & COI HCV & COI Program response rate 10% 15% 20% 10% 15% 20%Benefit-Cost Ratios (w/o child nutrition benefits)Disinfection is sustained for 1 year 3.3 2.1 0.8 2.0 1.2 0.5Disinfection is sustained for 2 years 4.6 3.3 1.5 2.7 1.9 0.9Disinfection is sustained for 3 years 5.2 3.9 1.9 3.0 2.3 1.1Benefit-Cost Ratios (w/ child nutrition benefits)Disinfection is sustained for 1 year 5.1 3.3 1.3 2.7 1.7 0.7Disinfection is sustained for 2 years 6.9 5.0 2.2 3.7 2.6 1.2Disinfection is sustained for 3 years 7.9 6.0 3.0 4.2 3.2 1.6Source: Estimated by the author. Benefits and costs are discounted at an annual rate of 10 percent.Table 13: Benefit-cost ratios for drinking water disinfection promotion, rural children u5(boiling of water using LPG) Valuation method VSL & COI HCV & COI Program response rate 10% 15% 20% 10% 15% 20%Benefit-Cost Ratios (w/o child nutrition benefits)Disinfection is sustained for 1 year 7.2 4.6 1.8 3.8 2.4 1.0Disinfection is sustained for 2 years 9.8 7.0 3.1 5.2 3.7 1.7Disinfection is sustained for 3 years 11.1 8.4 4.2 5.9 4.4 2.2Benefit-Cost Ratios (w/ child nutrition benefits)Disinfection is sustained for 1 year 11.4 7.3 2.9 5.5 3.5 1.4Disinfection is sustained for 2 years 15.5 11.1 5.0 7.6 5.4 2.4Disinfection is sustained for 3 years 17.7 13.4 6.6 8.6 6.5 3.2Source: Estimated by the author. Benefits and costs are discounted at an annual rate of 10 percent.Table 14: Benefit-cost ratios for drinking water disinfection promotion, rural children u5(boiling of water using fuel wood) Valuation method VSL & COI HCV & COI Program response rate 10% 15% 20% 10% 15% 20%Benefit-Cost Ratios (w/o child nutrition benefits)Disinfection is sustained for 1 year 8.8 5.2 1.9 4.7 2.7 1.0Disinfection is sustained for 2 years 13.2 8.5 3.4 7.0 4.5 1.8Disinfection is sustained for 3 years 15.8 10.9 4.7 8.3 5.7 2.5Benefit-Cost Ratios (w/ child nutrition benefits)Disinfection is sustained for 1 year 14.0 8.3 3.0 6.8 4.0 1.5Disinfection is sustained for 2 years 21.0 13.6 5.4 10.2 6.6 2.6Disinfection is sustained for 3 years 25.1 17.2 7.4 12.2 8.4 3.6Source: Estimated by the author. Benefits and costs are discounted at an annual rate of 10 percent. 112
  • 113. A drinking water disinfection promotion program targeting children u5 may also inducedisinfection practices for the population aged 5+ years, with or without additionalprogram promotion cost. A CBA for this population is therefore also undertaken. In thecase of no additional program costs, the BCRs for the population 5+ years of age rangesfrom 0.2-0.45 when valuing health benefits with the HCV and COI, and 0.35-0.85 whenvaluing health benefits with VSL and COI. The low end reflects use of LPG for boilingof water in urban areas, and the high end reflects use of fuel wood in rural areas.50A promotion program may also be implemented that targets all population age groups(not only households with young children). If program cost per household is the same asthe one targeting households with children, then the BCRs for the population 5+ years ofage ranges from 0.1-0.4 when valuing health benefits with the HCV and COI, and 0.2-0.8when valuing health benefits with VSL and COI. The low end reflects use of LPG forboiling of water in urban areas, disinfection sustained for only one year, and program costat a “high” per person level as to induce 20 percent behavioral response rate. The highend reflects use of fuel wood in rural areas, disinfection sustained for three years, andprogram cost at a “low” per person level as to induce 10 percent response rate.The reason for the low BCRs for the population 5+ years of age is the much lowerincidence of diarrheal disease and mortality in this population group than in children u5.Benefits from reducing the disease burden is therefore proportionately lower in thepopulation 5+ years. V. SUMMARY AND CONCLUSIONSThis paper has provided an assessment of benefits and costs of selected environmentalhealth interventions to control PM outdoor air pollution, indoor air pollution fromhousehold use of solid fuels for cooking, and promotion of improved hand washing andhousehold point-of-use drinking water disinfection. Benefit-cost ratios (BCRs) forcontrol of outdoor air pollution were based on adjustments of BCRs from studies in otherdeveloping countries, while the BCRs for indoor air pollution and the hygiene anddrinking water interventions were based on data and analysis from the Philippines.The assessment found BCRs in the range of 1.4 to 6.7 for PM control interventions,BCRs in the range of 0.1 to 19 for indoor air pollution control interventions in a range ofhousehold exposure conditions, BCRs in the range of 0.25 to 15 for hand washingpromotion among various age groups in urban and rural areas, and BCRs in the range of0.1 to 25 for drinking water disinfection by boiling of water with LPG or fuel woodamong various age groups in urban and rural areas.While the BCRs cannot always be compared across the three environmental health riskareas, some observations can be made. First of all, BCRs should be seen in light ofpotential under- or over-estmation of benefits and costs. Secondly, it is useful to compareBCRs for various interventions by age groups.As to potential under- or over-estimation of benefits and costs, it may first be noted thatestimated benefits of outdoor air pollution control are likely to be conservative as only50 In this case, the BCR is independent of program response rate and period of sustained drinking waterdisinfection, and is determined solely by health benefits and private cost of boiling drinking water. 113
  • 114. two morbidity health-end points were included in Arcenas (2009) because of datalimitations. Also, estimated benefits of hand washing did not include potentiallysubstantial benefits associated with reduced respiratory infections. Nor was potentialschool performance and consequent life time income effects of child malnutrition fromfrequent diarrheal infections in early childhood considered in the CBA for hand washingand drinking water disinfection. As regards costs of interventions, uncertainty about soapconsumption for hand washing was noted. Cost of LPG, in terms of fuel switching tocontrol indoor air pollution and for boiling of water, is also uncertain, as it is greatlyinfluenced by petroleum price movements in world markets.Valuation of health effects also has a great influence on the estimated BCRs. Twovaluation techniques were applied to value mortality, while cost-of-illness (COI) wasused for valuation of morbidity. The use of VSL for valuation mortality givessubstantially higher BCRs than when the HCV is applied. For adults it was noted in theoutdoor air pollution section that the HCV would likely represent a substantialunderestimation of benefits of mortality reduction. The VSL calculated for thePhilippines is consistent with a recent study of VSL in China (Krupnick, et al., 2006), andis calculated using a benefit transfer base value that is substantially lower than theUSEPA is applying in CBA in the United States. The COI approach used for valuingmorbidity is likely to represent a very conservative estimate of benefits of interventions.Studies in many countries have found that individuals’ willingness-to-pay (WTP) toavoid an episode of acute illness is generally much higher than the cost of treatment andtime losses (Alberini and Krupnick, 2000; Cropper and Oates, 1992; Dickie and Gerking,2002; Wilson, 2003).In terms of age groups, it is predominantly adults that would benefit from outdoor airpollution control. Adults would also benefit more than children in terms of mortalityfrom indoor air pollution control, while children would benefit more in terms ofmorbidity. However, children would be the predominant beneficiaries of hand washingpromotion and drinking water disinfection promotion. This emerges from the esimates ofenvironmental health effects in he Philippines by Arcenas (2009) and is consistent withstudies worldwide.Comparing the estimated BCRs of the outdoor and indoor air pollution controlinterventions assessed in this study, from which adults are expected to benefitsignificantly, it emerges that the BCRs for household use of improved wood stoves arehigher than for almost all the outdoor air pollution control interventions, even inhouseholds with relatively good ventilation or cooking outdoors. BCRs of outdoor airpollution control interventions are however larger than the BCRs for switching to LPGeven in households with poor ventilation and indoor cooking.51 It also emerges that theBCRs of the outdoor air pollution control interventions and indoor air pollutioninterventions (both improved wood stoves and switching to LPG) are substantially largerthan the BCRs of hand washing and drinking water disinfection promotion for thepopulation group 5+ years of age.5251 The comparison is made for BCRs based on the same valuation techniques of health benefits, i.e., VSLfor mortality and COI for morbidity. Good ventilation or outdoor cooking reflects a ventilation factor of0.25 and poor ventilation and indoor cooking a factor of 1.00 in the indoor air pollution section.52 Health benefits are valued using VSL and COI. 114
  • 115. For the protection of u5 children’s health, the BCRs are quite similar for improved woodstoves, and hand washing and drinking water disinfection promotion to mothers andcaretakers of young children. If however, additional benefits are included, as discussedabove, the BCRs for hand washing and drinking water disinfection may be higher thanfor improved stoves. The comparison is however not straight forward because BCRs forimproved stoves are not estimated separately for children and adults. 115
  • 116. REFERENCESAlberini, A. and Krupnick, A., 2000: Cost-of-illness and willingness-to-pay estimates ofthe benefits of improved air quality: evidence from Taiwan. Land Economics, Vol 76:37-53.Arcenas, A., 2009: Environmental health: economic costs of environmental damage andsuggested priority interventions. A contribution to the Philippines EnvironmentalAnalysis. Prepared for the World Bank.Arnold, B. and Colford, JM., 2007: Treating water with chlorine at point-of-use toimprove water quality and reduce child diarrhea in developing countries: a systematicreview and meta-analysis. American Journal of Tropical Medicine and Hygiene, vol76(2): 354-364.Blumberg, K., He, K., Zhou, Y., Liu, H., and Yamaguchi, N., 2006: Costs and benefits ofreduced sulfur in China. The International Council on Clean Transportation. December2006. www.theicct.org.Borghi, J., Guinness, L, Ouedraogo, J., and Curtis, V., 2002: Is hygiene promotion cost-effective? A case study in Burkino Faso. Tropical Medicine and International Health,Vol 7 No11. November 2002.Cairncross, S. and Valdmanis, V., 2006: Water supply, sanitation, and hygienepromotion. In: Disease control priorities in developing countries, second edition, chapter41, 771-92. Oxford University Press and the World Bank.Clasen, T. and Haller, L., 2008: Water quality interventions to prevent diarrhea: cost andcost-effectiveness. Public Health and the Environment, World Health Organization.Geneve.Clasen, T., Schmidt, W-P., Rabie, T., Roberts, I., and Cairncross, S., 2007a: Interventionsto improve water quality for preventing diarrhoea: systematic review and meta-analysis.British Medical Journal, 334:782-.Clasen, T., Haller, L., Walker, D., Bartram, J., and Cairncross, S., 2007b: Cost-effectiveness of water quality interventions for preventing diarrhoeal disease indeveloping countries. Journal of Water and Health, 5(4): 599-608.Cropper, M. and Oates, W., 1992: Environmental Economics: A Survey. Journal ofEconomic Literature, Vol. XXX, pp. 675-740.Curtis, V. and Cairncross, S., 2003: Effect of Washing Hands with Soap on DiarrhoeaRisk in the Community: A Systematic Review. Lancet Infectious Diseases, vol 3:275-81. 116
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  • 119. Meddings, D., Ronald, L., Marion, S., Pinera, J., and Oppliger, A., 2004: Costeffectiveness of a latrine revision programme in Kabul, Afghanistan. Bulletin of theWorld Health Organization, 82(4): 281-89.Mehta S and Shahpar C., 2004: The Health Benefits of Interventions to Reduce IndoorAir Pollution from Solid Fuel Use: A Cost-Effectiveness Analysis. Energy forSustainable Development. 8(3): p. 53-59.Mrozek, J. and Taylor, L., 2002: What Determines the Value of Life? A Meta Analysis.Journal of Policy Analysis and Management, Vol 21 (2): 253-270.NSO, 2005: Household energy consumption survey 2004. National Statistics Office, thePhilippines.Pinfold, J. and Horan, N., 1996: Measuring the effect of a hygiene behaviour interventionby indicators of behaviour and diarrhoeal disease. Transactions of the Royal Society ofTropical Medicine and Hygiene, Vol 90.Rabie, T. and Curtis, V., 2006: Handwashing and risk of respiratory infections: aquantitative systematic review. Tropical Medicine and International Health, vol 11(3):258-67.Saade, C., Bateman, M., and Bendahmane, D., 2001: The story of a successful public-private partnership in Central America: Handwashing for diarrheal disease prevention.Published by BASICS II, EHP, Unicef, USAID, and World Bank.Samson, R., Helwig, T., Stohl, D., De Maio, A., Duxbury, P., Mendoza, T., and Elepano,A., 2001: Strategies for enhancing biomass energy utilization in the Philippines. NationalRenewable Energy Laboraty, Colorado, USA.Shordt, K., and Cairncross, S., 2004: Sustainability of hygiene behaviour and theeffectiveness of change interventions: Findings and implications for water and sanitationprogrammes from a multi-country research study. IRC International Water andSanitation Centre. The Netherlands.Shrestha, R., Marseille, E., Kahn, J., et al., 2006: Cost-effectiveness of home basedchlorination and safe water storage in reducing diarrhea among HIV-affected householdsin rural Uganda. American Journal of Hygiene and Tropical Medicine, 74(5): 884-90.Stevens, G., A. Wilson, and J. Hammitt, 2005: A benefit-cost analysis of retrofittingdiesel vehicles with particulate filters in the Mexico City Metropolitan Area. RiskAnalysis, 25(4): 883-899.Wilson, C., 2003: Empirical evidence showing the relationships between threeapproaches for pollution control. Environmental and Resource Economics, Vol 24: 97-101. 119
  • 120. Winrock International, 2005: Exploratory study on household energy practices, indoor airpollution and health perceptions in southern Philippines. Winrock International/USAID.WHO, 2002: World Health Report 2002. World Health Organization.World Bank, 2008: Environmental health and child survival: Epidemiology, economics,experiences. Washington DC. USA. 120
  • 121. The Philippines Malnutrition related mortality from water, sanitation and hygiene - accounting for the effect of diarrheal infections on child malnutrition Prepared for the Philippines CEA World Bank by Bjorn Larsen53 Consultant Economist54 Health and Environment November, 200853 The estimates of disease burden provided here follows the methodology in Larsen (2007) and WorldBank (2008).54 Author’s contact information: bjrnlrsn@aol.com or bj_la@hotmail.com. 121
  • 122. 1. IntroductionWater, sanitation and hygiene (WSH) is directly and indirectly affecting populationhealth. Directly, poor WSH causes diarrheal infections and other health effects which inturn lead to mortality especially in young children. Indirectly, poor WSH contributes tochild malnutrition through the effect of diarrheal infections on nutritional status.Malnutrition, or poor nutritional status, increases the risk of child mortality from diseaseas well as increases the incidence of disease (Fishman et al., 2004).55 This indirect effectof WSH mainly affects children under the age of five years old.The approach used here to estimate the indirect health effects of WSH in children is asfollows: (a) the effect of diarrheal infections on children’s nutritional status is first determined from a review of the research literature; (b) counterfactual nutritional status is then estimated, i.e., the nutritional status that would have prevailed in the absence of diarrheal infections; and (c) health effects of currently observed nutritional status and health effects of counterfactual nutritional status are estimated.The difference in health effects of observed vs counterfactual nutritional status is then theindirect health effects of diarrheal infections, caused largely by poor WSH.Commonly used indicators of poor nutritional status are underweight, stunting andwasting.56 Underweight is measured as weight-for-age (WA) relative to an internationalreference population.57 Stunting is measured as height-for-age (HA), and wasting ismeasured as weight-for-height (WH). Underweight is an indicator of chronic or acutemalnutrition or a combination of both. Stunting is an indicator of chronic malnutrition,and wasting an indicator of acute malnutrition. Underweight status is most commonlyused in assessing the risk of mortality and morbidity from poor nutritional status(Fishman et al, 2004).A child is defined as mildly underweight if his or her weight is in the range of -1 to -2standard deviations (SD) below the weight of the median child in the internationalreference population, moderately underweight if the weight is in the range of -2 to -3SDs, and severely underweight if the child’s weight is below -3 SD from the weight ofthe median child in the reference population. The standard deviations are also called z-scores and noted as WAZ (weight-for-age z-score).55 Malnutrition and poor nutritional status is here used interchangeably.56 Micronutrient deficiencies are not explicitly evaluated here, but are found in other studies to have asignificant cost (World Bank, 2006; Horton and Ross, 2003; Horton, 1999). Also, Alderman and Behrman(2006) find a significant cost associated with low birth weight, which in part is caused by low maternal pre-pregnancy body mass index (Fishman et al, 2004).57 The international reference population is defined by the National Center for Health Statistics (NCHSstandard), United States or by the World Health Organization’s international reference population. 122
  • 123. Repeated infections, and especially diarrheal infections, have been found to significantlyimpair weight gains in young children. Studies documenting and quantifying this effecthave been conducted in communities with a wide range of infection loads in a diversegroup of countries such as Bangladesh (Black et al, 1984; Bairagi et al, 1987; Becker etal, 1991), Gambia (Rowland et al, 1977; Rowland et al, 1988), Guatemala (Martorell etal, 1975), Guinea-Bissau (Molbak et al, 1997), Indonesia (Kolsteren et al, 1997), Mexico(Condon-Paoloni et al, 1977), Peru (Checkley et al, 1997), Philippines (Adair et al,1993), Sudan (Zumrawi et al, 1987), and Tanzania (Villamor et al, 2004). World Bank(2008) provides a review of these studies.These studies typically find that diarrheal infections impair weight gains in the range of20-50 percent. A mid-point – i.e., 35 percent of children’s weight deficit - is hereattributed to diarrheal infections to estimate the indirect disease burden from WSH(Larsen, 2007).58 So in the absence of weight retarding infections, the weight-for-age z-score (WAZ) of an underweight child would be approximately 40 percent greater than theobserved z-score (i.e., observed WAZ*(1-0.4)).59 For instance, if a child has a WAZ=-3,then in the absence of weight retarding infections, the child’s WAZ would be -1.8.2. Nutritional StatusPrevalence of underweight malnutrition rates in the Philippines are presented in table 1.Current rates are for the most recent year available. Prevalence of mild underweight is noofficially reported. Mild underweight is however important in relation to increased riskof child mortality (Fishman et al., 2004). This rate was therefore estimated based oninternational comparisons.Counterfactual prevalence rates of underweight, i.e., prevalence rates in the absence ofweight retarding infections where estimated based on estimations from comparatorcountries in Asia for which original survey data of child nutritional status are available.This was performed through the following procedure: Counterfactual WA z-scores werecalculated for each underweight child in household survey using the formula discussedabove (i.e., WAZ reported for each child in the survey multiplied by (1-0.4)).Counterfactual underweight prevalence rates were then tabulated using the counterfactualWA z-scores. The results are presented in table 1.In the absence of diarrheal infections, it is estimated that practically no children would beseverely underweight and the prevalence of moderate underweight would be as low as 2percent. The prevalence of mild underweight would increase somewhat as child nutritionstatus would change from severe/moderate underweight to mild underweight.58 A child’s weight deficit is the difference in weight between the child’s observed weight and the weight ofthe median child in the international reference population.59 This is calculated using the WHO Anthro 2005 software. 123
  • 124. Table 1 Current and estimated counterfactual underweight prevalence rates in childrenu5 Philippines Current prevalence ratesSevere underweight ( < - 3 SD) 8.8%*Moderate underweight (-2 to -3 SD) 19.2%*Mild underweight (-1 to -2 SD) 29.3%*Non-underweight ( > -1 SD 42.7%* Counterfactual prevalence ratesSevere underweight ( < - 3 SD) 0.10%Moderate underweight (-2 to -3 SD) 2.0%Mild underweight (-1 to -2 SD) 32.0%Non-underweight ( > -1 SD 65.9%Source: Current prevalence rate of underweight malnutrition is from Philippines National Nutrition Surveys2003 (ENRI). * Moderate and severe underweight prevalence combined was 28% in the Philippines, and isnot reported separately. Nor is the prevalence of mild underweight reported. Distribution of mild,moderate and severe underweight is therefore estimated by international comparison.3. Health Effects of Poor Nutritional StatusVarious health and debilitating effects from malnutrition are documented in the researchliterature. This includes long term chronic illnesses from low birth weight, effects ofiodine, vitamin and iron deficiencies, and impaired cognitive development (UnitedNations, 2004; World Bank, 2006). The focus here is on mortality in children < 5 yearsassociated with underweight.Fishman et al (2004) present estimates of increased risk of cause-specific mortality andall-cause mortality in children u5 with mild, moderate and severe underweight from areview of available studies. Severely underweight children (WA < -3 SD) are five timesmore likely to die from measles, eight times more likely to die from ALRI, nearly 10times more likely to die from malaria, and twelve times more likely to die from diarrheathan non-underweight children (WA > - 1 SD). Even mild underweight doubles the riskof death from major diseases in early childhood (table 2).Table 2 Relative risk of mortality from mild, moderate and severe underweight inchildren u5 Weight-for-age (WA) < - 3 SD -2 to -3 SD -1 to -2 SD > - 1 SDPneumonia/ALRI 8.1 4.0 2.0 1.0Diarrhea 12.5 5.4 2.3 1.0Measles 5.2 3.0 1.7 1.0Malaria 9.5 4.5 2.1 1.0Other causes of mortality* 8.7 4.2 2.1 1.0Source: Fishman et al (2004). * Only other infectious diseases are included here (see Fewtrell et al, 2007). 124
  • 125. 4. Estimating the Health Effects of WSHThese relative risk ratios can be applied to the underweight prevalence rates in table 1 toestimate attributable fractions (AF) of mortality from diarrheal infections through theireffect on nutritional status (underweight status).60 The following formula is used tocalculate attributable fractions of mortality from ALRI, measles, malaria, and “otherinfectious diseases” indirectly caused by diarrheal infections: n n ∑ Pi RRi − ∑ Pi C RRi AF = i =1 n i =1 (1) ∑ P RR i =1 i iwhere RRi is relative risk of mortality for each of the WA categories (i) in table 2; Pi isthe current underweight prevalence rate in each of the WA categories (i); and Pic is thecounterfactual underweight prevalence rate in each of the WA categories (i). Thisformula is also called the “potential impact fraction” because it estimates the mortalitythat would have been avoided for a different counterfactual population distribution (e.g.,less children being underweight) exposed to those levels of risk of mortality. For afurther discussion of this formula, see Ezzati et al. (2004).For diarrheal mortality the AF estimation procedure would be different because there aretwo risk factors, i.e. the direct effect of WSH and the indirect effect through malnutrition.As already 88 percent of diarrheal infections and mortality is estimated to originate fromWSH, the additional effect of malnutrition is minimal and is therefore ignored here.61Annual cases of mortality from diarrheal infections caused by poor WSH, through theeffect of infections on nutritional status, are estimated as follows: j =mM = c ∑ AF j M 0 j (2) j =1where AFj is the AF in eq. (1) for each cause of mortality “j”, Mj0 is the current totalannual cases of mortality in each of the categories in table 2, and “c” is the fraction ofdiarrheal infections caused by poor WSH (86.3% estimated for the Philippines from thePhilippines DHS 2003).Most recent available estimates of annual cases of mortality (Mj0) in children under-5 arepresented in table 3. These estimates reflect u5 child mortality rates in 2003, and thestructure of cause-specific deaths is estimated from WHO country estimates of cause-specific mortality in 2002 (WHO, 2004).60 The attributable fraction of mortality from malnutrition is the percent of deaths (e.g., percent of ALRIdeaths) caused by malnutrition.61 See Larsen (2007) and World Bank (2008) for methodology and estimation of environmental healtheffects from multiple environmental risk factors in Ghana and Pakistan. 125
  • 126. Table 3 Estimated cause-specific annual deaths in children < 5 years in 2003 PhilippinesDiarrheal disease 10,700ALRI 12,600Measles 2,900Malaria 400PEM 1,100LBW 8,600Other perinatal conditions 16,500Other infectious and parasitic 3,200Other causes 18,500Total 74,500Source: Adjusted to 2003 from WHO country estimates of mortality by cause in 2002 (WHO, 2004), byapplying child mortality rate in 2003.Table 4 Demographic and mortality data in 2005 PhilippinesMortality rate, under-5 (per 1,000) 36Population, total 81,172,000Estimated annual births 2,069,886Source: World Bank (2007) and Country population statistics.Applying equation (2) to the cases of mortality in table 3 provides an estimate ofmalnutrition related mortality from poor WSH (table 5). Mortality in children fromprotein-energy malnutrition (PEM) is estimated separately using the methodology inFishman et al. (2004) and attributing a fraction of this mortality to WSH in proportion tothe effect of diarrheal infections on malnutrition.In total, child mortality attributable to WSH from malnutrition (i.e., the indirect effect ofinfections through malnutrition) constitutes over 7,600 deaths per year, or over 10 percentof total u5 child mortality.Table 5 Estimated annual malnutrition related mortality in children u5 from poor WSHin 2003 PhilippinesALRI 4828Measles 880Malaria 164PEM 475Other infectious diseases 1269TOTAL 7616 126
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