Social Inclusion                mapping global inequality                              Jon Crail, Phrisk Ltd.Royal College...
Social Inclusion                mapping global inequality                              Jon Crail, Phrisk Ltd.Royal College...
The challenges
The challenges1. Risk factors
The challenges1. Risk factors2. Burden of disease
The challenges1. Risk factors2. Burden of disease3. Access to services
The challenges1. Risk factors2. Burden of disease3. Access to services4. Costs
Challenge 1: Risk factorsCommon risk factors
Challenge 1: Risk factorsCommon risk factors
Sugar
Sugaron                                                                                                                   ...
The social determinants of health
The social determinants of health
Socio-economic status
Socio-economic status
Socio-economic status
Socio-economic status
Challenge 2: Burden of disease
Challenge 2: Burden of disease               • Caries               • Oral cancer               • Periodontal disease     ...
Challenge 2: Burden of disease                                 90% of the               •   Caries          worlds        ...
Challenge 2: Burden of disease                                         90% of the                       •   Caries        ...
Dental caries (DMFT)
Dental caries (DMFT)DECAYed,                                                                                              ...
Social Inclusion - Royal College of Surgeons lecture
Social Inclusion - Royal College of Surgeons lecture
Social Inclusion - Royal College of Surgeons lecture
Social Inclusion - Royal College of Surgeons lecture
Social Inclusion - Royal College of Surgeons lecture
Social Inclusion - Royal College of Surgeons lecture
Social Inclusion - Royal College of Surgeons lecture
Social Inclusion - Royal College of Surgeons lecture
Social Inclusion - Royal College of Surgeons lecture
Social Inclusion - Royal College of Surgeons lecture
Social Inclusion - Royal College of Surgeons lecture
Social Inclusion - Royal College of Surgeons lecture
Social Inclusion - Royal College of Surgeons lecture
Social Inclusion - Royal College of Surgeons lecture
Social Inclusion - Royal College of Surgeons lecture
Social Inclusion - Royal College of Surgeons lecture
Social Inclusion - Royal College of Surgeons lecture
Social Inclusion - Royal College of Surgeons lecture
Social Inclusion - Royal College of Surgeons lecture
Social Inclusion - Royal College of Surgeons lecture
Social Inclusion - Royal College of Surgeons lecture
Social Inclusion - Royal College of Surgeons lecture
Social Inclusion - Royal College of Surgeons lecture
Social Inclusion - Royal College of Surgeons lecture
Social Inclusion - Royal College of Surgeons lecture
Social Inclusion - Royal College of Surgeons lecture
Social Inclusion - Royal College of Surgeons lecture
Social Inclusion - Royal College of Surgeons lecture
Social Inclusion - Royal College of Surgeons lecture
Social Inclusion - Royal College of Surgeons lecture
Social Inclusion - Royal College of Surgeons lecture
Social Inclusion - Royal College of Surgeons lecture
Social Inclusion - Royal College of Surgeons lecture
Social Inclusion - Royal College of Surgeons lecture
Social Inclusion - Royal College of Surgeons lecture
Social Inclusion - Royal College of Surgeons lecture
Social Inclusion - Royal College of Surgeons lecture
Social Inclusion - Royal College of Surgeons lecture
Social Inclusion - Royal College of Surgeons lecture
Social Inclusion - Royal College of Surgeons lecture
Social Inclusion - Royal College of Surgeons lecture
Social Inclusion - Royal College of Surgeons lecture
Social Inclusion - Royal College of Surgeons lecture
Social Inclusion - Royal College of Surgeons lecture
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Social Inclusion - Royal College of Surgeons lecture

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Social Inclusion - mapping global inequality lecture Royal College of Surgeons of England Research Symposium - Tuesday, 31 May 2011

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  • Background in public health & behaviour change, 4 years @ FDI, policy, advocacy, communication & project management \nIllustrated with maps & images from The Oral Health Atlas -2009\nSocial Exclusion is what can happen when people or areas suffer from a combination of linked problems - unemployment, poor skills, low incomes, poor housing, high crime, bad health and family breakdown. It is characterised by the inter-relatedness of problems that are mutually reinforcing; combined they create a fast moving, complex and vicious cycle. - Inclusion Institute, University of Central Lancashire\n
  • Background in public health & behaviour change, 4 years @ FDI, policy, advocacy, communication & project management \nIllustrated with maps & images from The Oral Health Atlas -2009\nSocial Exclusion is what can happen when people or areas suffer from a combination of linked problems - unemployment, poor skills, low incomes, poor housing, high crime, bad health and family breakdown. It is characterised by the inter-relatedness of problems that are mutually reinforcing; combined they create a fast moving, complex and vicious cycle. - Inclusion Institute, University of Central Lancashire\n
  • Social inclusion / exclusion seen through 4 lenses: exposure to risk factors, burden of disease, access to services and costs.\n
  • Social inclusion / exclusion seen through 4 lenses: exposure to risk factors, burden of disease, access to services and costs.\n
  • Social inclusion / exclusion seen through 4 lenses: exposure to risk factors, burden of disease, access to services and costs.\n
  • Social inclusion / exclusion seen through 4 lenses: exposure to risk factors, burden of disease, access to services and costs.\n
  • Major risk factors, such as tobacco use, physical inactivity and a diet high in fat, salt and sugar, contribute to a range of chronic diseases, such as obesity, diabetes, cardiovascular diseases and oral diseases.\nPoverty and chronic disease are linked into a vicious cycle; chronic diseases can exacerbate poverty and the poor have greater exposure to risk and less access to health services.\n
  • The average person in the Democratic Republic of Congo consumes less than one teaspoon of sugar a day, while the average person in the USA consumes more than 19\n The average American consumes 336 liters of soft drinks a year; nearly a liter a day\nThere are also disparities within countries & risks alone do not determine health\n
  • The average person in the Democratic Republic of Congo consumes less than one teaspoon of sugar a day, while the average person in the USA consumes more than 19\n The average American consumes 336 liters of soft drinks a year; nearly a liter a day\nThere are also disparities within countries & risks alone do not determine health\n
  • Many risk factors are results of broader determining factors, such as lifestyle, socio-economic status, or living conditions.\nAlmost 80% of diabetes deaths occur in low- and middle-income countries\n
  • Caries is a middle-income problem\nAccess is care increases with income\nlinks between oral diseases and socio-economic status\nWHO Commission on Social Determinants on Health (2008) expressed so clearly: “In countries at all levels of income, health and illness follow a social gradient: the lower the socio-economic position, the worse the health.”\nMaori women are five times more likely than New Zealand Caucasian women to be toothless.\n
  • Caries is a middle-income problem\nAccess is care increases with income\nlinks between oral diseases and socio-economic status\nWHO Commission on Social Determinants on Health (2008) expressed so clearly: “In countries at all levels of income, health and illness follow a social gradient: the lower the socio-economic position, the worse the health.”\nMaori women are five times more likely than New Zealand Caucasian women to be toothless.\n
  • Caries is a middle-income problem\nAccess is care increases with income\nlinks between oral diseases and socio-economic status\nWHO Commission on Social Determinants on Health (2008) expressed so clearly: “In countries at all levels of income, health and illness follow a social gradient: the lower the socio-economic position, the worse the health.”\nMaori women are five times more likely than New Zealand Caucasian women to be toothless.\n
  • Not going to focus on perio, the data is incomplete\n Links to general disease: type II diabetes, cardiovascular, premature &-low birth weight, etc.\n
  • Not going to focus on perio, the data is incomplete\n Links to general disease: type II diabetes, cardiovascular, premature &-low birth weight, etc.\n
  • Not going to focus on perio, the data is incomplete\n Links to general disease: type II diabetes, cardiovascular, premature &-low birth weight, etc.\n
  • Not going to focus on perio, the data is incomplete\n Links to general disease: type II diabetes, cardiovascular, premature &-low birth weight, etc.\n
  • Not going to focus on perio, the data is incomplete\n Links to general disease: type II diabetes, cardiovascular, premature &-low birth weight, etc.\n
  • Not going to focus on perio, the data is incomplete\n Links to general disease: type II diabetes, cardiovascular, premature &-low birth weight, etc.\n
  • Not going to focus on perio, the data is incomplete\n Links to general disease: type II diabetes, cardiovascular, premature &-low birth weight, etc.\n
  • Not going to focus on perio, the data is incomplete\n Links to general disease: type II diabetes, cardiovascular, premature &-low birth weight, etc.\n
  • Tooth decay is a middle income disease but lack of treatment mostly affects the poor\nGenerally, caries rates are highest in middle-income countries where sugar consumption is high but access to prevention and care is low. \n Breakdown of treatment by income\n Yellow is untreated disease\n
  • Tooth decay is a middle income disease but lack of treatment mostly affects the poor\nGenerally, caries rates are highest in middle-income countries where sugar consumption is high but access to prevention and care is low. \n Breakdown of treatment by income\n Yellow is untreated disease\n
  • Tooth decay is a middle income disease but lack of treatment mostly affects the poor\nGenerally, caries rates are highest in middle-income countries where sugar consumption is high but access to prevention and care is low. \n Breakdown of treatment by income\n Yellow is untreated disease\n
  • 6% of Californians, or about 1.8 million people, miss work or school each year due to dental problems\n In the Philippines, 85% of 6-year-old children had signs of dental infection\nBetween 1997 and 2006 there has been a 66% increase in the number of children admitted into hospital for tooth extraction in the UK.\n
  • 6% of Californians, or about 1.8 million people, miss work or school each year due to dental problems\n In the Philippines, 85% of 6-year-old children had signs of dental infection\nBetween 1997 and 2006 there has been a 66% increase in the number of children admitted into hospital for tooth extraction in the UK.\n
  • Once case study from the Philippines\n
  • Once case study from the Philippines\n
  • Once case study from the Philippines\n
  • Once case study from the Philippines\n
  • Once case study from the Philippines\n
  • Once case study from the Philippines\n
  • Once case study from the Philippines\n
  • Once case study from the Philippines\n
  • World average: 6.3, Highest: Papua New Guinea 40.9, Lowest: El Salvador 0.4 \nThe average 5-year survival rate of oral cancer among white high-income males in Mumbai is 30%, whereas i the USA it i 70%\n
  • World average: 6.3, Highest: Papua New Guinea 40.9, Lowest: El Salvador 0.4 \nThe average 5-year survival rate of oral cancer among white high-income males in Mumbai is 30%, whereas i the USA it i 70%\n
  • The problem is worst in South-East Asia; Paan use is a key factor\n Smoking is associated with about 75% of oral cancer cases.\n The risk for oral cancer is 15 times higher when the two main risk factors, tobacco use and alcohol, are combined.\n
  • The problem is worst in South-East Asia; Paan use is a key factor\n Smoking is associated with about 75% of oral cancer cases.\n The risk for oral cancer is 15 times higher when the two main risk factors, tobacco use and alcohol, are combined.\n
  • Noma is a good example of an oral disease with a low incidence rate but a high impact, fatal in about 80% of cases\n While there have been cases of noma around the world, it is currently a mainly African problem\n
  • Noma is a good example of an oral disease with a low incidence rate but a high impact, fatal in about 80% of cases\n While there have been cases of noma around the world, it is currently a mainly African problem\n
  • Noma is a good example of an oral disease with a low incidence rate but a high impact, fatal in about 80% of cases\n While there have been cases of noma around the world, it is currently a mainly African problem\n
  • risk 40% higher fro deprived ares of the UK\n Boys are almost twice as likely to experience dental trauma as girls.\n
  • risk 40% higher fro deprived ares of the UK\n Boys are almost twice as likely to experience dental trauma as girls.\n
  • risk 40% higher fro deprived ares of the UK\n Boys are almost twice as likely to experience dental trauma as girls.\n
  • The dentist-to population ratio is a rough indicator of service availability, but does not necessarily result in the improvement in oral health. \nIllegal practitioners often fill the gap, sometimes causing more harm than good\nRural neglect = dentists are concentrated in the urban areas\nThere are only 16 dentists in Eritrea, and 15 of them work in the capital.\nIn India, the dentist:population ratio in rural areas is 1:300,000 and 1:27,000 in urban areas.\n Migration = low-income to high-income = brain drain\nThere are more dentists from Benin in France than in Benin.\n22% of dentists practicing in the UK are foreign born.\n
  • The dentist-to population ratio is a rough indicator of service availability, but does not necessarily result in the improvement in oral health. \nIllegal practitioners often fill the gap, sometimes causing more harm than good\nRural neglect = dentists are concentrated in the urban areas\nThere are only 16 dentists in Eritrea, and 15 of them work in the capital.\nIn India, the dentist:population ratio in rural areas is 1:300,000 and 1:27,000 in urban areas.\n Migration = low-income to high-income = brain drain\nThere are more dentists from Benin in France than in Benin.\n22% of dentists practicing in the UK are foreign born.\n
  • The dentist-to population ratio is a rough indicator of service availability, but does not necessarily result in the improvement in oral health. \nIllegal practitioners often fill the gap, sometimes causing more harm than good\nRural neglect = dentists are concentrated in the urban areas\nThere are only 16 dentists in Eritrea, and 15 of them work in the capital.\nIn India, the dentist:population ratio in rural areas is 1:300,000 and 1:27,000 in urban areas.\n Migration = low-income to high-income = brain drain\nThere are more dentists from Benin in France than in Benin.\n22% of dentists practicing in the UK are foreign born.\n
  • The dentist-to population ratio is a rough indicator of service availability, but does not necessarily result in the improvement in oral health. \nIllegal practitioners often fill the gap, sometimes causing more harm than good\nRural neglect = dentists are concentrated in the urban areas\nThere are only 16 dentists in Eritrea, and 15 of them work in the capital.\nIn India, the dentist:population ratio in rural areas is 1:300,000 and 1:27,000 in urban areas.\n Migration = low-income to high-income = brain drain\nThere are more dentists from Benin in France than in Benin.\n22% of dentists practicing in the UK are foreign born.\n
  • The dentist-to population ratio is a rough indicator of service availability, but does not necessarily result in the improvement in oral health. \nIllegal practitioners often fill the gap, sometimes causing more harm than good\nRural neglect = dentists are concentrated in the urban areas\nThere are only 16 dentists in Eritrea, and 15 of them work in the capital.\nIn India, the dentist:population ratio in rural areas is 1:300,000 and 1:27,000 in urban areas.\n Migration = low-income to high-income = brain drain\nThere are more dentists from Benin in France than in Benin.\n22% of dentists practicing in the UK are foreign born.\n
  • 80% of all oral health care is concentrated in 20% of the population\n
  • 80% of all oral health care is concentrated in 20% of the population\n
  • Dental treatment accounted for only 3% of the reduction in tooth decay in 12-year-olds in industrialised countries during the last 40 years. The main\nfactors were fluoride toothpaste and general socio-economic development. \nautomatic fluoride helps the socially excluded most, however they have the least access to toothpaste\n For every US$1 spent on salt fluoridation, around US$250 are saved in treatment costs.\n
  • In India and Nepal tax accounts for 25% of the retail price of toothpaste; in Burkina Faso this is up to 50%\n In the Netherlands an average 300g of toothpaste are used per person per year; in Myanmar 35g\nZambia it can take over 30 days to pay for toothpaste\n
  • In India and Nepal tax accounts for 25% of the retail price of toothpaste; in Burkina Faso this is up to 50%\n In the Netherlands an average 300g of toothpaste are used per person per year; in Myanmar 35g\nZambia it can take over 30 days to pay for toothpaste\n
  • In 2004, only 44% of US citizens went to see a dentist. The average treatment took 2.1 sessions and the average cost was US$560.\n
  • In 2004, only 44% of US citizens went to see a dentist. The average treatment took 2.1 sessions and the average cost was US$560.\n
  • In 2004, only 44% of US citizens went to see a dentist. The average treatment took 2.1 sessions and the average cost was US$560.\n
  • In 2004, only 44% of US citizens went to see a dentist. The average treatment took 2.1 sessions and the average cost was US$560.\n
  • In 2004, only 44% of US citizens went to see a dentist. The average treatment took 2.1 sessions and the average cost was US$560.\n
  • Prevention is cheaper than treatment, however most health systems do not pay dentists for prevention or invest in it.\nIn the USA alone, 2.4 million days of work and 1.6 million days of school were lost due to oral disease in 1996.\n
  • Prevention = fluoride, risk-factors, social-determinants\nBehaviour change for population, professionals, policy makers, insurance\nevidence-based such as school health\nTraining dentists is expense and time consuming. Many countries have to send them abroad where they are unlikely to return. Even when they do they work in urban areas. \nSyria has invested significantly in scaling up the dental workforce:\ndentist numbers increased from 1,975 dentists (1981) to 14,610 (2002). However, the percentage of untreated caries and DMFT remained more or less unchanged.\nTraining other health workers to do simple extractions, ART and referral is more realistic\n
  • Prevention = fluoride, risk-factors, social-determinants\nBehaviour change for population, professionals, policy makers, insurance\nevidence-based such as school health\nTraining dentists is expense and time consuming. Many countries have to send them abroad where they are unlikely to return. Even when they do they work in urban areas. \nSyria has invested significantly in scaling up the dental workforce:\ndentist numbers increased from 1,975 dentists (1981) to 14,610 (2002). However, the percentage of untreated caries and DMFT remained more or less unchanged.\nTraining other health workers to do simple extractions, ART and referral is more realistic\n
  • Prevention = fluoride, risk-factors, social-determinants\nBehaviour change for population, professionals, policy makers, insurance\nevidence-based such as school health\nTraining dentists is expense and time consuming. Many countries have to send them abroad where they are unlikely to return. Even when they do they work in urban areas. \nSyria has invested significantly in scaling up the dental workforce:\ndentist numbers increased from 1,975 dentists (1981) to 14,610 (2002). However, the percentage of untreated caries and DMFT remained more or less unchanged.\nTraining other health workers to do simple extractions, ART and referral is more realistic\n
  • Prevention = fluoride, risk-factors, social-determinants\nBehaviour change for population, professionals, policy makers, insurance\nevidence-based such as school health\nTraining dentists is expense and time consuming. Many countries have to send them abroad where they are unlikely to return. Even when they do they work in urban areas. \nSyria has invested significantly in scaling up the dental workforce:\ndentist numbers increased from 1,975 dentists (1981) to 14,610 (2002). However, the percentage of untreated caries and DMFT remained more or less unchanged.\nTraining other health workers to do simple extractions, ART and referral is more realistic\n
  • Prevention = fluoride, risk-factors, social-determinants\nBehaviour change for population, professionals, policy makers, insurance\nevidence-based such as school health\nTraining dentists is expense and time consuming. Many countries have to send them abroad where they are unlikely to return. Even when they do they work in urban areas. \nSyria has invested significantly in scaling up the dental workforce:\ndentist numbers increased from 1,975 dentists (1981) to 14,610 (2002). However, the percentage of untreated caries and DMFT remained more or less unchanged.\nTraining other health workers to do simple extractions, ART and referral is more realistic\n
  • The Atlas can be purchased from www.OralHealthAtlas.org, www.Amazon.co.uk\nFDI Data Mirror is an online tool that will let you play with some of this data\n
  • The Atlas can be purchased from www.OralHealthAtlas.org, www.Amazon.co.uk\nFDI Data Mirror is an online tool that will let you play with some of this data\n
  • Social Inclusion - Royal College of Surgeons lecture

    1. 1. Social Inclusion mapping global inequality Jon Crail, Phrisk Ltd.Royal College of Surgeons of England Research Symposium - Tuesday, 31 May 2011
    2. 2. Social Inclusion mapping global inequality Jon Crail, Phrisk Ltd.Royal College of Surgeons of England Research Symposium - Tuesday, 31 May 2011
    3. 3. The challenges
    4. 4. The challenges1. Risk factors
    5. 5. The challenges1. Risk factors2. Burden of disease
    6. 6. The challenges1. Risk factors2. Burden of disease3. Access to services
    7. 7. The challenges1. Risk factors2. Burden of disease3. Access to services4. Costs
    8. 8. Challenge 1: Risk factorsCommon risk factors
    9. 9. Challenge 1: Risk factorsCommon risk factors
    10. 10. Sugar
    11. 11. Sugaron NORWAY SWEDEN FINLAND SUGAR ESTONIA RUSSIA LATVIA LITHUANIA DENMARK UK RUSSIA IRELAND NETH. BELARUS GERMANY POLAND CZECH UKRAINE ICELAND REP. SLOVAKIA C A N A D A LUX. MOLDOVA FRANCE SWITZ. AUSTRIA SLOV. HUNGARY RUSSIA ROMANIA B-H SERBIA PORTUGAL CROATIA BULGARIA MONT. ALBANIA MACEDONIA SPAIN ITALY K A Z A K H S TA N GREECEperson per year MONGOLIA U S A UZBEKISTAN NORTH KYRGYZSTAN1.3 kg GEORGIA KOREA JAPAN ARMENIA AZERBAIJAN TURKEY TURKMENISTAN TAJIKISTAN SOUTH 14 million KOREA TUNISIA CYPRUS SYRIA MALTA LEB. AFGHANISTAN tonnes IRAQ IRAN MOROCCO ISRAEL JORDAN CHINA KUWAIT PAKISTAN NEPAL BAHAMAS MEXICO ALGERIA L I B YA Hong Kong CUBA EGYPT SAR DOMINICAN SAUDI UAE REP. ARABIA INDIA BANGLADESH JAMAICA HAITI BELIZE 29 million MYANMAR LAOS GUATEMALA ST KITTS & NEVIS CAPE MAURITANIA MALI tonnes PHILIPPINES HONDURAS VERDE NIGER SENEGAL CHAD ERITREA YEMEN THAILAND EL SALVADOR VIETNAM NICARAGUA BARBADOS GAMBIA SUDAN BURKINA CAMBODIA TRINIDAD & TOBAGO GUINEA-BISSAU FASO COSTA RICA VENEZUELA GUINEA NIGERIA BENIN GHANA PANAMA TOGO GUYANA CÔTE ETHIOPIA SRI LANKA SIERRA LEONE D’IVOIRE CENTRAL SAMOA SURINAME LIBERIA AFRICAN REP. BRUNEI COLOMBIA FIJI A TASTE FOR SUGAR CAMEROON UGANDA SOMALIA FINLAND MALAYSIA TONGA DEMOCRATIC Annual sugar consumption ECUADOR GABON REPUBLIC OF KENYA NORWAY SINGAPORE CONGO RWANDA SWEDEN kilograms per person CONGO BURUNDI ESTONIA RUSSIA 2007 PERU 33 million TANZANIA LATVIA LITHUANIA I N D O N E S I A PAPUA NEW DENMARK GUINEA tonnes UK RUSSIA 45 kg or more ANGOLA IRELAND COMOROS NETH. BELARUS MALAWI BRAZIL ZAMBIA GERMANY POLAND 30 kg – 44 kg ICELAND MADAGASCAR CZECH UKRAINE REP. SLOVAKIA BOLIVIA 15 kg – 29 kg C A N A D A NAMIBIA ZIMBABWE MAURITIUS LUX. MOLDOVA BOTSWANA FRANCE SWITZ. AUSTRIA SLOV. HUNGARY RUSSIA MOZAMBIQUE ROMANIA PARAGUAY less than 15 kg CHILE PORTUGAL CROATIA B-H SERBIA BULGARIA AUSTRALIA MONT. no data ARGENTINA SOUTH SWAZILAND ALBANIA MACEDONIA AFRICA LESOTHO SPAIN ITALY K A Z A K H S TA N URUGUAY GREECE World average: 30 kg per person per year MONGOLIA Highest: Swaziland 102 kg U S A UZBEKISTAN KYRGYZSTAN Lowest: Dem. Rep. Congo 1.3 kg GEORGIA ARMENIA AZERBAIJAN NEW TURKEY TURKMENISTAN TAJIKISTAN ZEALAND 14 million TUNISIA CYPRUS SYRIA top sugar-cane MALTA LEB. AFGHANISTAN tonnes IRAQ IRAN producers MOROCCO ISRAEL JORDAN CHINA KUWAIT PAKISTAN NEPAL BAHAMAS MEXICO ALGERIA L I B YA Hong K CUBA EGYPT Copyright © - FDI World Dental Federation and Myriad Editions.
    12. 12. The social determinants of health
    13. 13. The social determinants of health
    14. 14. Socio-economic status
    15. 15. Socio-economic status
    16. 16. Socio-economic status
    17. 17. Socio-economic status
    18. 18. Challenge 2: Burden of disease
    19. 19. Challenge 2: Burden of disease • Caries • Oral cancer • Periodontal disease • Noma • Birth defects • Trauma
    20. 20. Challenge 2: Burden of disease 90% of the • Caries worlds • Oral cancer population have had • Periodontal disease oral pain in • Noma their lifetime • Birth defects • Trauma
    21. 21. Challenge 2: Burden of disease 90% of the • Caries worlds • Oral cancer population have had • Periodontal disease oral pain in • Noma their lifetime Dental caries is the most common • Birth defects chronic disease • Trauma worldwide
    22. 22. Dental caries (DMFT)
    23. 23. Dental caries (DMFT)DECAYed, MAPPING DENTAL CARIESent Teeth ICELAND FINLAND NORWAY RUSSIA SWEDEN ESTONIA LATVIA C A N A D A UK DENMARK RUSSIA LITHUANIA IRELAND NETH. BELARUS POLAND BEL. GERMANY UKRAINE K A Z A K H S TA N CZ. LIECHT. REP. SL. MONGOLIA LUX. AUS. HUN. MOLDOVA FRANCE SWITZ. SL. ROM. U S A S. M. CRO. B-H SERB. UZBEKISTAN KYRGYZSTAN NORTHTogo 0.3 PORTUGAL MONT. ALB. BUL. GEORGIA KOREA JAPAN MAC. ARMENIA SOUTH SPAIN ITALY TURKEY TURKMENISTAN TAJIKISTAN GREECE KOREA TUNISIA CYPRUS SYRIA MALTA LEB. AFGHANISTAN CHINA BERMUDA IRAQ IRAN MOROCCO ISRAEL JORDAN KUWAIT PAKISTAN BAHAMAS ALGERIA NEPAL BHUTAN MEXICO L I B YA BAHRAIN Hong Kong CUBA EGYPT SAR SAUDI UAE FED. STATES DOMINICAN Macau MICRONESIA CAYMAN IS. REP. PUERTO RICO ARABIA BANGLADESH SAR HAITI INDIA ANGUILLA LAOS BELIZE JAMAICA CAPE OMAN MYANMAR ST KITTS & NEVIS ANTIGUA & BARBUDA VERDE MAURITANIA KIRIBATI GUATEMALA HONDURAS DOMINICA MALI NIGER PHILIPPINES ST VINCENT & THE GRENADINES MARTINIQUE SENEGAL ERITREA YEMEN THAILAND TUVALU TOKELAU EL SALVADOR ST LUCIA VIETNAM NICARAGUA GAMBIA SUDAN SOLOMON GRENADA BARBADOS BURKINA GUINEA-BISSAU SIERRA CAMBODIA ISLANDS COSTA RICA TRINIDAD & TOBAGO FASO DJIBOUTI LEONE BENIN SAMOA VENEZUELA GHANA PANAMA CÔTE NIGERIA TOGO GUYANA ETHIOPIA SRI LANKA VANUATU COOK D’IVOIRE CENTRAL FIJI ISLANDS CAMEROON AFRICAN REP. COLOMBIA SURINAME BRUNEI TONGA MALDIVES NEW LIBERIA UGANDA MALAYSIA CALEDONIA NIUE DEMOCRATIC SOMALIA FR. POLYNESIA SINGAPORE REPUBLIC OF KENYA ECUADOR GABON CONGO MAPPING DEN RWANDA WORLDWIDE DENTAL DECAY PERU BURUNDI SEYCHELLES I N D O N E S I A PAPUA TANZANIA Average number of Decayed, NEW GUINEA BRAZIL Missing and Filled permanent Teeth ANGOLA MALAWI (DMFT) in 12-year-olds ZAMBIA MADAGASCAR 2008 BOLIVIA ZIMBABWE MAURITIUS NAMIBIA BOTSWANA high; more than 3.5 CHILE PARAGUAY MOZAMBIQUE RÉUNION AUSTRALIA moderate; 2.6 – 3.5 SWAZILAND ARGENTINA SOUTH ICELAND AFRICA LESOTHO low; 1.2 – 2.5 URUGUAY NORWAY FINLAND RUSSIA very low; 0.0 –1.1 SWEDEN ESTONIA LATVIA no data CANADA UK DENMARK RUSSIA LITHUANIA IRELAND NETH. BELARUS POLAND NEW BEL. GERMANY UKRAINE KAZAKHSTAN CZ. World average: 2.0 LUX. LIECHT. REP. SL. AUS. HUN. MOLDOVA ZEALAND MONGOLIA Highest: Croatia 6.7 FRANCE SWITZ. SL. ROM. USA S. M. CRO. B-H SERB. UZBEKISTAN KYRGYZSTAN Lowest: Rwanda, Tanzania, Togo 0.3 PORTUGAL MONT. ALB. BUL. GEORGIA MAC. ARMENIA SPAIN ITALY TURKEY TURKMENISTAN TAJIKISTAN GREECE TUNISIA Copyright © - FDI World Dental Federation and Myriad Editions.
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