The document describes a study that evaluated the reliability and validity of a questionnaire to assess organophosphate pesticide (OP) exposure among 114 agricultural workers in Maule, Chile. A factorial analysis identified four factors that explained 68% of the variance: 1) labor conditions during OP application, 2) use of personal protective equipment, 3) workplace conditions related to OP exposure, and 4) home conditions related to OP exposure. The questionnaire demonstrated high reliability (Cronbach's alpha = 0.95) and adequate validity for characterizing OP exposure and exploring working and home conditions associated with exposure among agricultural workers.
Exhaled Breath Analysis for Cancer Diagnosis and Screening_Crimson PublishersCrimsonpublishersCancer
Nowadays, cancer is still one of the main fatal disorders in the world, from which the patients suffer a lot while the burden of the families and society increased. Early recognition and treatment are crucial to reduce the death rate; however, in clinical practice, many cancers could only be recognized when it comes to a later stage. With the development and progress of the modern medical technique, more and more novel testing methods are reported and under research. Many reports showed that dogs could smell out the cancer patients, and exhaled breath test with such as the gas sensor is gradually taking an important role in cancer early diagnosis and screening. However, systematic reviews in both fields are lacking.
Dr. ihsan edan abdulkareem alsaimary
PROFESSOR IN MEDICAL MICROBIOLOGY AND MOLECULAR IMMUNOLOGY
ihsanalsaimary@gmail.com
mobile : 009647801410838
university of basrah - college of medicine - basrah -IRAQ
Comparison and Evaluation of FUS-2000 Urinalysis Hybrid and Conventional Micr...kridsada31
Comparison and Evaluation of FUS-2000 Urinalysis Hybrid and Conventional Microscopic Examination
PrangthipSukboon1, SupichchaDuangson1, KridsadaSirisabhabhorn2,Chollanot Kaset1, SupapornPumpa2, DaungnatePipatsatitpong1*
1Department of Medical Technology, Faculty of Allied Health Sciences, ThammasatUniversity2Division of Clinical Microscopy and Parasitology, Department of Medical Technology Laboratory, ThammasatUniversity Hospital
Exhaled Breath Analysis for Cancer Diagnosis and Screening_Crimson PublishersCrimsonpublishersCancer
Nowadays, cancer is still one of the main fatal disorders in the world, from which the patients suffer a lot while the burden of the families and society increased. Early recognition and treatment are crucial to reduce the death rate; however, in clinical practice, many cancers could only be recognized when it comes to a later stage. With the development and progress of the modern medical technique, more and more novel testing methods are reported and under research. Many reports showed that dogs could smell out the cancer patients, and exhaled breath test with such as the gas sensor is gradually taking an important role in cancer early diagnosis and screening. However, systematic reviews in both fields are lacking.
Dr. ihsan edan abdulkareem alsaimary
PROFESSOR IN MEDICAL MICROBIOLOGY AND MOLECULAR IMMUNOLOGY
ihsanalsaimary@gmail.com
mobile : 009647801410838
university of basrah - college of medicine - basrah -IRAQ
Comparison and Evaluation of FUS-2000 Urinalysis Hybrid and Conventional Micr...kridsada31
Comparison and Evaluation of FUS-2000 Urinalysis Hybrid and Conventional Microscopic Examination
PrangthipSukboon1, SupichchaDuangson1, KridsadaSirisabhabhorn2,Chollanot Kaset1, SupapornPumpa2, DaungnatePipatsatitpong1*
1Department of Medical Technology, Faculty of Allied Health Sciences, ThammasatUniversity2Division of Clinical Microscopy and Parasitology, Department of Medical Technology Laboratory, ThammasatUniversity Hospital
Guidance for Industry and Other StakeholdersToxicological Principles for the...Dmitri Popov
This guidance represents the Food and Drug Administration's (FDA's) current thinking on this topic. It
does not create or confer any rights for or on any person and does not operate to bind FDA or the public.
Study on multi-target mechanism of Radix et Rhizoma Rhei (Dahuang) and Semen ...LucyPi1
Abstract Objective: To explore the mechanism of action of Radix et Rhizoma Rhei (Dahuang) (RERR) and Semen Persicae (Taoren) (SP) on adhesive intestinal obstruction (AIO). Methods: The main targets of the active ingredients of RERR and SP were filtered based on the traditional Chinese medicine system pharmacology analysis platform. Cytoscape 3.2.1 was applied to build the ingredient-target network of RERR and SP for AIO. Results: Fifteen active components were predicted from the RERR and SP herb pair, such as aloe-emodin, catechin, rhein, gibberellin (GA) 119, GA120 and GA121. These components were applied to 59 targets mainly involved in many biological processes such as signal transduction, anti-apoptosis, and inflammatory response involved in activating the immune effect. Conclusion: This study proposes the system pharmacology method and identifies the potent combination therapeutic mechanism of RERR and SP for AIO. This strategy will provide a new insight to the study of herb combinations.
Comparative Study between Rapid Diagnostic Tests and Microscopy for Diagnosis...Premier Publishers
Malaria infection is a global problem accounting for a 25% mortality rate annually, management and control of malaria involves accurate diagnosis and treatment. The study compared the performance of rapid diagnostic tests and microscopy as used for the diagnosis of malaria in Seme Sub County, Kisumu County. The cross sectional study was conducted in three purposively selected health facilities. A total of 230 participants were randomly selected to participate in the study. Blood samples were collected by a trained phlebotomist from the participants who had given consent to participate. The samples were screened for malaria using both microscopy as a gold standard and two Rapid diagnostic tests (Histidine Rich Protein (HRP2), and Combined HRP2 and parasite lactate dehydrogenase (PLDH) to determine the performance of RDTs. The results revealed that, the sensitivity, specificity, positive predictive values and negative predictive values using microscopy was found to be 94.44%, 85.71%, 80.95%, 96.00% for HRP2 and 94.44%, 85.00%,80.19% ,95.9% for pLDH RDT respectively. There was a significant level of agreement between microscopy and HRP2 RDTs of 89.13% (p-value <0.001) and between microscopy and pLDH RDTs of 88.70% (p-value <0.001). The low sensitivity below the WHO recommendation of ≥95% indicates the need to improve the sensitivity of the mRDTs kits in malaria management, where trained microscopists for malaria diagnosis are not available .The findings are important in informing the ministry of Health and the malaria control unit to improve on the malaria diagnosis techniques. Assist policymakers in post market surveillance of the mRDTs currently in use.
Prevalence of Malaria Infection and Malaria Anaemia among Children Attending ...theijes
Malaria associated anaemia represent a major public health problem. Thestudy considered Out-Patient children at Emergency Paediatric Unit, Federal Medical Centre, Yola aged 6 months-15 years from June to November 2015. Questionnaires were used to collect information relating to gender, age and parents/guardians sociodemographic characteristics. Microscopic examination of Thick and Thin blood films a technique was employed, Pack Cell Volumewas used to screen for anaemia. Of the 168 children sampled, the prevalence of malaria infection and malaria anaemia was 29.2% and 26.2% respectively and it was associated with P. falciparum. Malaria infection in relation to anaemia, children with mild anaemia (47.6%) had the highest infection rate. It was observed that malaria infection was higher among males (32.2%) than the females (25.6%), age group 5-9 years (34.2%) had the highest malaria infection and least was ≥15 years (20.0%) but these were statistically insignificant within gender and age of the children and malaria infection (p˃0.05). Higher malaria infection among children whose parents/guardians were unemployed (38.5%), attended primary education (52.6%) and reside in village setting (31.4%). Malaria anaemia in relation to children epidemiological data, males (31.6%), 5-9 years (31.6%) recorded with high prevalence rate while sociodemographic characteristics of parents/guardians, children whose parents/guardians were civil servant (18.9%), attended tertiary education (13.8%) and live in quarters (11.1%) had the least prevalence rate of malaria anaemia. Children gender, parents/guardians occupation and educational qualification were significantly associated with malaria anaemia (p˂0.05). Therefore, parents/guardians sociodemographic factors such as better occupation, higher educational qualification and well layout and refined area of residence reduces the prevalence of malaria infection and malaria anaemia in children. There is need to sensitized public on the importance of management of malaria and the possible effects of malaria anaemia on children in order to circumvent the menace.
Fluoroquinolone resistant rectal colonization predicts risk of infectious com...TC İÜ İTF Üroloji AD
Fluoroquinolone resistant rectal colonization predicts risk of infectious complications after transrectal prostate biopsy. Evidence based on journal club by Samed Verep
Allometry Scalling in Drug Development by Murugesh Kandasamy in Advancements in Bioequivalence & Bioavailability
Allometry is about the study of body size and its outcomes, it is described as ‘by a different measure’, and in allometric system the proportions are changed in a regular fashion [1]. Allometry, which is the oldest of the approaches and still widely applied in biology, is concerned with the study of the relationship between the size and function of components of the body and growth or size of the whole body [2]. Alternatively, to study the species change in a specific factor which correlates with difference in size of the species. Allometry is centered on the prediction (an exact prediction) by considering the physiological, anatomical and biochemical parallels among animals, which can be explained by mathematical models. It is now an established fact that many physiological processes and size of the organ that exhibit a power-law relationship with the body weight of the species. This relationship is defined as the scientific source of allometric scaling [3,4].
https://crimsonpublishers.com/abb/fulltext/ABB.000512.php
Identifying and Prioritizing Chemicals with Uncertain Burden oMalikPinckney86
Identifying and Prioritizing Chemicals with Uncertain Burden of Exposure:
Opportunities for Biomonitoring and Health-Related Research
Edo D. Pellizzari,1 Tracey J. Woodruff,2 Rebecca R. Boyles,3 Kurunthachalam Kannan,4 Paloma I. Beamer,5 Jessie P. Buckley,6
Aolin Wang,2 Yeyi Zhu,7,8 and Deborah H. Bennett9 (Environmental influences on Child Health Outcomes)
1Fellow Program, RTI International, Research Triangle Park, North Carolina, USA
2Program on Reproductive Health and the Environment, Department of Obstetrics, Gynecology and Reproductive Sciences, University of California, San
Francisco, San Francisco, California, USA
3Bioinformatics and Data Science, RTI International, Research Triangle Park, North Carolina, USA
4Wadsworth Center, New York State Department of Health, Albany, New York, USA
5Department of Community, Environment and Policy, Zuckerman College of Public Health, University of Arizona, Tucson, Arizona, USA
6Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Heath, Johns Hopkins University,
Baltimore, Maryland, USA
7Northern California Division of Research, Kaiser Permanente, Oakland, California, USA
8Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, California, USA
9Department of Public Health Sciences, University of California, Davis, Davis, California, USA
BACKGROUND: The National Institutes of Health’s Environmental influences on Child Health Outcomes (ECHO) initiative aims to understand the
impact of environmental factors on childhood disease. Over 40,000 chemicals are approved for commercial use. The challenge is to prioritize chemi-
cals for biomonitoring that may present health risk concerns.
OBJECTIVES: Our aim was to prioritize chemicals that may elicit child health effects of interest to ECHO but that have not been biomonitored nation-
wide and to identify gaps needing additional research.
METHODS: We searched databases and the literature for chemicals in environmental media and in consumer products that were potentially toxic. We
selected chemicals that were not measured in the National Health and Nutrition Examination Survey. From over 700 chemicals, we chose 155 chemi-
cals and created eight chemical panels. For each chemical, we compiled biomonitoring and toxicity data, U.S. Environmental Protection Agency ex-
posure predictions, and annual production usage. We also applied predictive modeling to estimate toxicity. Using these data, we recommended
chemicals either for biomonitoring, to be deferred pending additional data, or as low priority for biomonitoring.
RESULTS: For the 155 chemicals, 97 were measured in food or water, 67 in air or house dust, and 52 in biospecimens. We found in vivo endocrine, de-
velopmental, reproductive, and neurotoxic effects for 61, 74, 47, and 32 chemicals, respectively. Eighty-six had data from high-throughput in vitro
assays. Positive results for endocrine, developmental, neurotoxicity, ...
Guidance for Industry and Other StakeholdersToxicological Principles for the...Dmitri Popov
This guidance represents the Food and Drug Administration's (FDA's) current thinking on this topic. It
does not create or confer any rights for or on any person and does not operate to bind FDA or the public.
Study on multi-target mechanism of Radix et Rhizoma Rhei (Dahuang) and Semen ...LucyPi1
Abstract Objective: To explore the mechanism of action of Radix et Rhizoma Rhei (Dahuang) (RERR) and Semen Persicae (Taoren) (SP) on adhesive intestinal obstruction (AIO). Methods: The main targets of the active ingredients of RERR and SP were filtered based on the traditional Chinese medicine system pharmacology analysis platform. Cytoscape 3.2.1 was applied to build the ingredient-target network of RERR and SP for AIO. Results: Fifteen active components were predicted from the RERR and SP herb pair, such as aloe-emodin, catechin, rhein, gibberellin (GA) 119, GA120 and GA121. These components were applied to 59 targets mainly involved in many biological processes such as signal transduction, anti-apoptosis, and inflammatory response involved in activating the immune effect. Conclusion: This study proposes the system pharmacology method and identifies the potent combination therapeutic mechanism of RERR and SP for AIO. This strategy will provide a new insight to the study of herb combinations.
Comparative Study between Rapid Diagnostic Tests and Microscopy for Diagnosis...Premier Publishers
Malaria infection is a global problem accounting for a 25% mortality rate annually, management and control of malaria involves accurate diagnosis and treatment. The study compared the performance of rapid diagnostic tests and microscopy as used for the diagnosis of malaria in Seme Sub County, Kisumu County. The cross sectional study was conducted in three purposively selected health facilities. A total of 230 participants were randomly selected to participate in the study. Blood samples were collected by a trained phlebotomist from the participants who had given consent to participate. The samples were screened for malaria using both microscopy as a gold standard and two Rapid diagnostic tests (Histidine Rich Protein (HRP2), and Combined HRP2 and parasite lactate dehydrogenase (PLDH) to determine the performance of RDTs. The results revealed that, the sensitivity, specificity, positive predictive values and negative predictive values using microscopy was found to be 94.44%, 85.71%, 80.95%, 96.00% for HRP2 and 94.44%, 85.00%,80.19% ,95.9% for pLDH RDT respectively. There was a significant level of agreement between microscopy and HRP2 RDTs of 89.13% (p-value <0.001) and between microscopy and pLDH RDTs of 88.70% (p-value <0.001). The low sensitivity below the WHO recommendation of ≥95% indicates the need to improve the sensitivity of the mRDTs kits in malaria management, where trained microscopists for malaria diagnosis are not available .The findings are important in informing the ministry of Health and the malaria control unit to improve on the malaria diagnosis techniques. Assist policymakers in post market surveillance of the mRDTs currently in use.
Prevalence of Malaria Infection and Malaria Anaemia among Children Attending ...theijes
Malaria associated anaemia represent a major public health problem. Thestudy considered Out-Patient children at Emergency Paediatric Unit, Federal Medical Centre, Yola aged 6 months-15 years from June to November 2015. Questionnaires were used to collect information relating to gender, age and parents/guardians sociodemographic characteristics. Microscopic examination of Thick and Thin blood films a technique was employed, Pack Cell Volumewas used to screen for anaemia. Of the 168 children sampled, the prevalence of malaria infection and malaria anaemia was 29.2% and 26.2% respectively and it was associated with P. falciparum. Malaria infection in relation to anaemia, children with mild anaemia (47.6%) had the highest infection rate. It was observed that malaria infection was higher among males (32.2%) than the females (25.6%), age group 5-9 years (34.2%) had the highest malaria infection and least was ≥15 years (20.0%) but these were statistically insignificant within gender and age of the children and malaria infection (p˃0.05). Higher malaria infection among children whose parents/guardians were unemployed (38.5%), attended primary education (52.6%) and reside in village setting (31.4%). Malaria anaemia in relation to children epidemiological data, males (31.6%), 5-9 years (31.6%) recorded with high prevalence rate while sociodemographic characteristics of parents/guardians, children whose parents/guardians were civil servant (18.9%), attended tertiary education (13.8%) and live in quarters (11.1%) had the least prevalence rate of malaria anaemia. Children gender, parents/guardians occupation and educational qualification were significantly associated with malaria anaemia (p˂0.05). Therefore, parents/guardians sociodemographic factors such as better occupation, higher educational qualification and well layout and refined area of residence reduces the prevalence of malaria infection and malaria anaemia in children. There is need to sensitized public on the importance of management of malaria and the possible effects of malaria anaemia on children in order to circumvent the menace.
Fluoroquinolone resistant rectal colonization predicts risk of infectious com...TC İÜ İTF Üroloji AD
Fluoroquinolone resistant rectal colonization predicts risk of infectious complications after transrectal prostate biopsy. Evidence based on journal club by Samed Verep
Allometry Scalling in Drug Development by Murugesh Kandasamy in Advancements in Bioequivalence & Bioavailability
Allometry is about the study of body size and its outcomes, it is described as ‘by a different measure’, and in allometric system the proportions are changed in a regular fashion [1]. Allometry, which is the oldest of the approaches and still widely applied in biology, is concerned with the study of the relationship between the size and function of components of the body and growth or size of the whole body [2]. Alternatively, to study the species change in a specific factor which correlates with difference in size of the species. Allometry is centered on the prediction (an exact prediction) by considering the physiological, anatomical and biochemical parallels among animals, which can be explained by mathematical models. It is now an established fact that many physiological processes and size of the organ that exhibit a power-law relationship with the body weight of the species. This relationship is defined as the scientific source of allometric scaling [3,4].
https://crimsonpublishers.com/abb/fulltext/ABB.000512.php
Identifying and Prioritizing Chemicals with Uncertain Burden oMalikPinckney86
Identifying and Prioritizing Chemicals with Uncertain Burden of Exposure:
Opportunities for Biomonitoring and Health-Related Research
Edo D. Pellizzari,1 Tracey J. Woodruff,2 Rebecca R. Boyles,3 Kurunthachalam Kannan,4 Paloma I. Beamer,5 Jessie P. Buckley,6
Aolin Wang,2 Yeyi Zhu,7,8 and Deborah H. Bennett9 (Environmental influences on Child Health Outcomes)
1Fellow Program, RTI International, Research Triangle Park, North Carolina, USA
2Program on Reproductive Health and the Environment, Department of Obstetrics, Gynecology and Reproductive Sciences, University of California, San
Francisco, San Francisco, California, USA
3Bioinformatics and Data Science, RTI International, Research Triangle Park, North Carolina, USA
4Wadsworth Center, New York State Department of Health, Albany, New York, USA
5Department of Community, Environment and Policy, Zuckerman College of Public Health, University of Arizona, Tucson, Arizona, USA
6Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Heath, Johns Hopkins University,
Baltimore, Maryland, USA
7Northern California Division of Research, Kaiser Permanente, Oakland, California, USA
8Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, California, USA
9Department of Public Health Sciences, University of California, Davis, Davis, California, USA
BACKGROUND: The National Institutes of Health’s Environmental influences on Child Health Outcomes (ECHO) initiative aims to understand the
impact of environmental factors on childhood disease. Over 40,000 chemicals are approved for commercial use. The challenge is to prioritize chemi-
cals for biomonitoring that may present health risk concerns.
OBJECTIVES: Our aim was to prioritize chemicals that may elicit child health effects of interest to ECHO but that have not been biomonitored nation-
wide and to identify gaps needing additional research.
METHODS: We searched databases and the literature for chemicals in environmental media and in consumer products that were potentially toxic. We
selected chemicals that were not measured in the National Health and Nutrition Examination Survey. From over 700 chemicals, we chose 155 chemi-
cals and created eight chemical panels. For each chemical, we compiled biomonitoring and toxicity data, U.S. Environmental Protection Agency ex-
posure predictions, and annual production usage. We also applied predictive modeling to estimate toxicity. Using these data, we recommended
chemicals either for biomonitoring, to be deferred pending additional data, or as low priority for biomonitoring.
RESULTS: For the 155 chemicals, 97 were measured in food or water, 67 in air or house dust, and 52 in biospecimens. We found in vivo endocrine, de-
velopmental, reproductive, and neurotoxic effects for 61, 74, 47, and 32 chemicals, respectively. Eighty-six had data from high-throughput in vitro
assays. Positive results for endocrine, developmental, neurotoxicity, ...
Trends shaping corporate health in the workplaceApollo Hospitals
The paradigm for corporate health is morphing from traditional curative services to health protection and promotion. An epidemic of “lifestyle diseases” has developed in the India which warrants an organized integration of company's health, safety and environment policy through a directed wellness program. The current study explored the burden and determinants of lifestyle diseases among an organization.
Cytogenetic, Hematological and Enzymes Levels Parameters in the Biomonitoring...inventionjournals
Studies have demonstrated genotoxic effects by the presence of micronucleus in exfoliated cells from the buccal mucosa of agricultural workers exposed to pesticides. This study has assessed the genotoxic effects of pesticides on 61 agricultural workers from the state of Piauí, Brazil. 31 individuals were exposed to pesticides and 30 are from the same area, but were not involved in pesticides application. Cytogenetic damage were evaluated through micronucleus test in cells from the buccal mucosa and some parameters such as hematological and levels of enzymes. Exposed individuals exhibited cytogenetic damage with increased number of micronuclei in cells from the buccal mucosa in comparison with subjects from the control group with significant statistical difference (P < 0.01). We perceive that there is a statistically no significant (P > 0.05) increase in levels of plasmatic and eritrocytaireacetylcholinesterase and no statistically significant increase of phosphatase alkaline were detected in exposed workers in relation to the control group. No association was found in relation to smoking habits, alcohol consumption, protection utensils and the biomarkers analyzed or the biochemical analysis. Analysis of variance revealed a correlation between occupational exposure to pesticides of workers in Piauí and the presence of micronuclei (P < 0.05).
Cytogenetic, Hematological and Enzymes Levels Parameters in the Biomonitoring...inventionjournals
Studies have demonstrated genotoxic effects by the presence of micronucleus in exfoliated cells from the buccal mucosa of agricultural workers exposed to pesticides. This study has assessed the genotoxic effects of pesticides on 61 agricultural workers from the state of Piauí, Brazil. 31 individuals were exposed to pesticides and 30 are from the same area, but were not involved in pesticides application. Cytogenetic damage were evaluated through micronucleus test in cells from the buccal mucosa and some parameters such as hematological and levels of enzymes. Exposed individuals exhibited cytogenetic damage with increased number of micronuclei in cells from the buccal mucosa in comparison with subjects from the control group with significant statistical difference (P < 0.01). We perceive that there is a statistically no significant (P > 0.05) increase in levels of plasmatic and eritrocytaireacetylcholinesterase and no statistically significant increase of phosphatase alkaline were detected in exposed workers in relation to the control group. No association was found in relation to smoking habits, alcohol consumption, protection utensils and the biomarkers analyzed or the biochemical analysis. Analysis of variance revealed a correlation between occupational exposure to pesticides of workers in Piauí and the presence of micronuclei (P < 0.05).
Cytogenetic, Hematological and Enzymes Levels Parameters in the Biomonitoring...inventionjournals
Studies have demonstrated genotoxic effects by the presence of micronucleus in exfoliated cells from the buccal mucosa of agricultural workers exposed to pesticides. This study has assessed the genotoxic effects of pesticides on 61 agricultural workers from the state of Piauí, Brazil. 31 individuals were exposed to pesticides and 30 are from the same area, but were not involved in pesticides application. Cytogenetic damage were evaluated through micronucleus test in cells from the buccal mucosa and some parameters such as hematological and levels of enzymes. Exposed individuals exhibited cytogenetic damage with increased number of micronuclei in cells from the buccal mucosa in comparison with subjects from the control group with significant statistical difference (P < 0.01). We perceive that there is a statistically no significant (P > 0.05) increase in levels of plasmatic and eritrocytaireacetylcholinesterase and no statistically significant increase of phosphatase alkaline were detected in exposed workers in relation to the control group. No association was found in relation to smoking habits, alcohol consumption, protection utensils and the biomarkers analyzed or the biochemical analysis. Analysis of variance revealed a correlation between occupational exposure to pesticides of workers in Piauí and the presence of micronuclei (P < 0.05).
Levels of Dichlorodiphenyltrichloroethane (DDT) and Hexachlorocyclohexane (HC...Premier Publishers
Serum levels of Dichlorodiphenyltrichloroethane (DDT) and Hexachlorocyclohexane (HCH) of breast cancer patients and controls were compared with a view to determining association between exposure of organochlorine pesticides (OCPs) and breast cancer. Fifty breast cancer patients and fifty age-matched control women were recruited from the Obafemi Awolowo University Teaching Hospitals Complex, Ile-Ife, Nigeria. Questionnaires were administered to collect information on demography and essential breast cancer risk factors. Five millilitres of blood was collected from each participant and the serum was analysed for DDT and HCH using Gas Chromatography coupled with Electron Capture Detector. The results showed that almost all case women had no identifiable risk factors for breast cancer. The median DDT levels among case and control women were 11.87 ppb and 6.395 ppb, respectively. The levels of δ-HCH among case and control women were 5.82 ppb and 0.00 ppb while that of γ-HCH were 10.84 ppb and 0.00 ppb, respectively. This study confirmed exposure to OCPs among the studied population and revealed significantly higher levels (p≤0.05) in case women than controls, thereby, suggesting that exposure to OCPs may be a significant risk factor for breast cancer in Nigeria.
Bearing the Burden - Health Implications of Environmental Pollutants in Our B...v2zq
Bearing the Burden - Health Implications of Environmental Pollutants in Our Bodies - Resources for Healthy Children www.scribd.com/doc/254613619 - For more information, Please see Organic Edible Schoolyards & Gardening with Children www.scribd.com/doc/254613963 - Gardening with Volcanic Rock Dust www.scribd.com/doc/254613846 - Double Food Production from your School Garden with Organic Tech www.scribd.com/doc/254613765 - Free School Gardening Art Posters www.scribd.com/doc/254613694 - Increase Food Production with Companion Planting in your School Garden www.scribd.com/doc/254609890 - Healthy Foods Dramatically Improves Student Academic Success www.scribd.com/doc/254613619 - City Chickens for your Organic School Garden www.scribd.com/doc/254613553 - Huerto Ecológico, Tecnologías Sostenibles, Agricultura Organica www.scribd.com/doc/254613494 - Simple Square Foot Gardening for Schools - Teacher Guide www.scribd.com/doc/254613410 - Free Organic Gardening Publications www.scribd.com/doc/254609890 ~
ABSTRACT- Background: Declining trend in semen quality is receiving attention worldwide. The aim of the study to investigate the role of lifestyle factors with respect to semen quality.
Methods: Semen samples were collected from 351 male partners attending OPD of Obstetrics and Gynecology at civil hospital and IKD hospital, Ahmedabad, India. They were subjected to assess the quality of semen according to WHO criteria and semen quality were analyzed with respect to self reported history of tobacco smoking and/or chewing and alcohol consumption as lifestyle factors.
Results: The result revealed that sperm count was lower in subjects with habit of tobacco smoking, chewing and alcohol consumption as compared to subjects without such habits and decline was found statistically significant among smokers. Total progressive motility and normal morphology percentage was significantly decreased in tobacco chewers compared to non-chewers. Further analysis of data with respect to alcohol consumption indicated non-significantly lower total progressive motility and normal sperm morphology percentage as compared to subjects with no such habit.
Conclusion: The data obtained suggested, the role of lifestyle factors especially tobacco smoking and chewing in declining semen quality.
Key-words- Semen quality, Tobacco, Alcohol, Lifestyle, Sperm motility, Smoking
Lady health workers' perceptions towards tuberculosis and its determinants at...Zubia Qureshi
Background: Lady Health Workers (LHWs), performing in Tuberculosis control programs have direct access in the communities. This study was designed to improve the TB status in Sindh province by improving the knowledge and practices of LHWs. Objective: To assess the TB related knowledge, attitude and practices among LHWs at tehsil Latifabad, district Hyderabad, Sindh. Method: A mixed method Cross-sectional study was done on universally selected 384 LHWs from Latifabad. Three focus group discussions were conducted with eight participants for each group. A pre-tested structured questionnaire and eld guidelines were used for data collection. Analysis was done on SPSS software by calculating frequencies, percentages, mean and median. While for inferential analysis chi square, t-test and Mann Whitney U tests were used. For FGDs, content analysis method was used. Results: Sufcient knowledge was found in about half 193(50.3%) of the participants. The overall attitude and practices of most of the LHWs 214(55.7%) and 205 (53.4%) respectively was not good. A signicant difference was found between LHWs knowledge score of those who had insufcient (28.08 ± 3.0) and sufcient knowledge (28.08 ± 3.1) with p-value <0.001. Also good attitude (47.74±2.8) and practices (51.45±3.8) of LHWs differed signicantly from those who did not have good attitude (36.09±4.8), and practices (40.44±3.3) with p-value <0.001. The insufcient knowledge was associated with unsafe practices. Tuberculosis related stigma was found in the community, people do not want to disclose their disease. Conclusion: Overall knowledge, attitude and practices about TB were not satisfactory among LHWs of Latifabad. An educational intervention is recommended for LHWs. Key words: Community health workers, infectious disease, knowledge, attitude, practices, developing country
Running headINTRODUCTION, LITERATURE REVIEW AND METHODS SECTION .docxagnesdcarey33086
Running head: INTRODUCTION, LITERATURE REVIEW AND METHODS SECTION 1
INTRODUCTION, LITERATURE REVIEW AND METHODS SECTION 2
Introduction, Literature Review and Methods Section
Katie Lopez
Argosy University
Introduction, Literature Review and Methods Section
Introduction
In this study the researcher will seek to determine the impacts of HIV/AIDS on the productivity of labor at coffee farms in Kona District, Hawaii. To successfully undertake this study, the researcher will utilize the use of retrospective cohort design to analyze the attendance and productivity of individual workers in the coffee estates. This will include checking records to know the numbers of works in the tea estates who died or medically retired because of HIV/AIDS and other related causes between 2010 and 2014. It will also include using questionnaires to get information from some of the workers in the coffee estates. The research will also characterize the impacts of HIV/AIDS and ARVs treatment on both medium term and long-run productivity of labor in the coffee estates. This will be affected using data of workers absenteeism in the coffee estates and the information from an HIV/AIDS treatment program.
The researcher will present a concise empirical and theoretical review on the problems related with the impact of HIV/AIDS on the productivity of human labor in labor intensive activities. This information will majorly be extracted from what other researchers have written. Other additional information will be from journals, magazines, textbooks, local newspapers and reports. The information from all these sources will be presented by the researcher and show whether each of these support or does not support the development of the hypothesis in question. This will also be based of the relevance of the information to the success of the study.
Literature review
In literature review both the theoretical and the empirical literature will be presented and these literatures will aid the research in developing this study by finding the crucial supporting information from facts and studies developed earlier by other researchers.
Theoretical literature
The emergence and spread of HIV/AIDS has been attributed to slow growth of economy in the nations that are most affected. This is because the workers and employees that suffers from the disease workers less hours or in a week because of going for medical attention within the working days and thus this scenario reduces the availability of labor. In addition the this, the these workers will also require additional medical care to be offered by the organization they are working with and thus increases the cost of medical insurance. The high prevalence of HIV/AIDS in a region has led to high mortality rate and this mainly affect the productive age bracket of between 15 to 64 years and thus reducing the skilled and productive population and labor force in a regio.
Assessment of trend of mortality due to poisoning in the northern zone of india and comparison with other international & national researches
Authors:Naveen Sharma, Kunal Khanna, Kuldeep Kumar, Tarun Dagar, Sandeep Kumar Giri, Vijay Pal Khanagwal
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Presentation by Jared Jageler, David Adler, Noelia Duchovny, and Evan Herrnstadt, analysts in CBO’s Microeconomic Studies and Health Analysis Divisions, at the Association of Environmental and Resource Economists Summer Conference.
This session provides a comprehensive overview of the latest updates to the Uniform Administrative Requirements, Cost Principles, and Audit Requirements for Federal Awards (commonly known as the Uniform Guidance) outlined in the 2 CFR 200.
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3. OP exposure is usually assessed through measurement of either acetylcholinesterase (AChE)
activity in blood or metabolites in urine (Wessels et al. 2003). When levels of blood AChE are low,
it is assumed that the individual is exposed to OPs, especially if comparisons to baseline,
prexposure AChE show declines. Measurements of erythrocyte cholinesterase are used to evaluate
chronic exposure and also cases of acute intoxication. The measurement of plasma AChE is only
useful to evaluate acute intoxications. Urinary biomarkers are so far the most sensitive to assess
OP exposure and involve measurement of dialkylphosphate metabolites or specific metabolites of
OPs such as chlorpyrifos, methamidophos, malathion, diazinon or dimethoate (CDC 2015).
The methods described above, while relatively sensitive and specific for measurement of OP
exposure, are costly, both to collect the samples and to conduct laboratory analysis. In Latin
America and developing countries, there are few laboratories and staff prepared for blood analysis.
For measurement of pesticide metabolites in urine, certified centers are mainly in the United
States of America (USA) or Europe (Muñoz-Quezada et al. 2016a). For follow-up or monitoring
studies, occupational exposure to OPs and health conditions are often evaluated through ques-
tionnaires or review of clinical symptoms (Engel et al. 2001; Samanic et al. 2005). Recent studies
have employed questionnaires to investigate pesticide exposure, use of personal protective equip-
ment (PPE) and health problems; however, few studies have examined reliability and validity of
these instruments (Samanic et al. 2005; Beseler and Stallones 2006; Lekei et al. 2014; Potts et al.
2014; Damalas and Abdollahzadeh 2016; Gesesew et al. 2016).
In Chile, epidemiological surveillance of workers exposed to pesticides is conducted based on a
protocol developed by the Ministry of Health (2017) that aims to prevent health problems. Based
on review of the potential for pesticide exposure by the Institute of Public Health of Chile (ISPCH
2004), a questionnaire was developed to specifically assess occupational and household exposure
to OPs in both applicators and nonapplicators working in agriculture and symptoms of intoxica-
tion. In the following study, we evaluate the reliability (internal consistency) and factorial validity
of a brief questionnaire to assess exposure to OPs, working conditions, and symptoms of
intoxication among agricultural workers that can be used to support research and investigations
aiming to prevent adverse health effects from pesticide exposure.
Methods
Study design
We enrolled a cross-sectional sample of 114 agricultural workers living in the region of Maule,
Chile.
Study groups
About one-third of the population, estimated at 305,077, in this region is rural, the highest proportion
in Chile, and 30% of the workers in the region work in agriculture (Government of Chile 2015).
According to the Chilean Agricultural and Livestock Service (SAG 2012), the region has the second
largest sales of pesticides in the country (Maule ~ 10million kg/L), with a 29% of insecticides used
nationally, of which 52% are OPs. In the Maule district, diazinon (~ 1 million kg/L) and chlorpyrifos
(~ 231,000 kg/L) are the most commonly used materials.
We identified agricultural workers for potential recruitment with help by the Institute of
Agricultural Development (INDAP), a government agency that supports small agricultural pro-
ducers. The sample was a subset of a larger study evaluating OP exposure and neuropsychological
and motor performance in rural populations (Muñoz-Quezada et al. 2016b). Agricultural workers
were randomly selected from INDAP records and contacted to schedule a meeting to obtain
informed consent and administer the questionnaire. Pregnant women, workers with mental
disabilities or severe psychiatric disorders or any disabling diseases were excluded. This study
2 M. T. MUÑOZ-QUEZADA ET AL.
4. was approved by the ethics committee on human research of the Universidad Católica del Maule.
Written informed consent was obtained from all individual participants included in the study.
Questionnaire
The questionnaire was based on pesticide exposure instruments developed by the Institute of
Public Health of Chile (ISPCH 2004), with additional questions added to assess exposure
characteristics, occupational conditions and the health status of agricultural workers. The ques-
tionnaire was revised based on review by six experts in pesticide exposure and psychometrics.
They reviewed the questions and agreed which were pertinent to pesticide occupational exposure
issues. The agreement achieved in the final version was 100%. The questionnaire was then pilot
tested in 17 exposed and 17 nonexposed workers to assess only the applicability of language and
response categories.
The first section of the questionnaire (26 questions) asked about sociodemographic data and
general health conditions considered to be hazardous for an agricultural worker exposed to
pesticides and to confirm that the worker applies OPs (see Appendix A1). The remaining
questions obtained information on demographic and occupational characteristics, job title (appli-
cator/nonapplicator), pesticide exposure risk factors, use of OP or other pesticides, housing
conditions and home pesticide use. Additional information was obtained about symptoms of
potential OP poisoning. The questionnaires were administered written in Spanish; interviewers
provided additional help to those workers with reading and writing difficulties. The answers to the
questionnaire were tallied, with a maximum score of 65 points, and with higher scores represent-
ing greater risk of pesticide exposure and health effects. Questions answered as ‘not applicable’
were coded as zero (0).
Data analysis
First, the sociodemographic characteristics of the sample were briefly analyzed.
To determine the validity of the instrument, we performed a factorial analysis with extraction
method of principal component analysis (PCA) with the Varimax rotation method. We describe
the Kaiser–Meyer–Olkin (KMO) sample adequacy measure and the Bartlett sphericity test to
compare the magnitude of observed and partial correlation coefficients.
Subsequently, an internal consistency analysis (Cronbach’s alpha equal to or greater than 0.70)
was employed with the total scores of the test and with each factor, applying a corrected item-total
correlation analysis. Finally, we calculated the descriptive statistics of the total score of the
instrument and the factors obtained after the factorial analysis. A 95% confidence interval was
used. SPSS 22.0 software was used for data analysis.
Results
The average age among participants was 50 years old (SD = 12). Overall, participants had an
average of 21 (SD = 16) years working in job categories with potential pesticide exposure. Sixty-
seven percent were applicators (n = 76), who had been applying pesticide for an average of 10
(SD = 13) years. On average, participants had 8 years of school education (SD = 3), and 65%
(n = 74) were men. The average household monthly income = $344 (SD = 147) USD, similar to
the minimum wage of Chile of that time.
Table 1 shows the frequency and percentage of response for each of the questions. We note that
all the alternatives of the questionnaire contain at least one answer from the workers, and there
are no questions with a total score of zero points.
The sample adequacy measure of Kaiser–Meyer–Olkin (KMO) results = 0.90 and the Bartell
sphericity test = p < 0.001. The initial eigenvalues were six factors (cumulative variance = 75%).
INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH 3
5. Table 1. Percentage of the pesticide exposure questionnaire OP.
Question (score) Frequency
Percentage
response
Are you currently working applying pesticides?
– No (0) 38 33
– Yes (1) 76 67
When was your last pesticide application?
– Not applicable (0) 38 33
– 2 years or more (1) 4 4
– Less than 2 years (2) 72 63
Do you work as a seasonal or permanent pesticide applicator?
– Not applicable (0) 38 33
– By season (1) 10 9
– Permanent (2) 66 58
Do you have a pesticide applicator license?
– Not applicable (0) 38 33
– Yes (1) 16 14
– No (2) 60 53
Do you eat, drink or smoke during the application?
– Not applicable (0) 38 33
– No (1) 13 11
– Yes or occasionally (2) 63 55
Do you change your clothes after the application?
– Not applicable (0) 38 33
– Yes (1) 21 18
– No or occasionally (2) 55 48
The place where pesticide is mixed is:
– Not applicable (0) 38 33
– Open (1) 67 59
– Closed (2) 9 8
Do you use manual pump backpack to apply OPs?
– No 45 40
– Yes 69 60
What type of OP do you recall applying?
– Not applicable (0) 38 33
– Only one OP (1) 66 58
– More than one OP (2) 10 9
Do you wear personal protective equipment when mixing?
– Not applicable (0) 38 33
– Yes (1) 48 42
– No (2) 28 25
Do you know the health risks you are exposed to when applying or mixing pesticides?
– Not applicable (0) 38 33
– Yes (1) 57 50
– No (2) 19 17
How many years have you applied pesticides?
– Not applicable (0) 38 33
– 10 years or less (1) 36 32
– More of 10 years (2) 40 35
How long does it take between the end of the application and taking a shower or bath?
– Not applicable (0) 38 33
– Less of 15 min (1) 43 38
– 15 min or more (2) 33 29
During or after pesticide application, do you wash your hands before smoking, eating or
drinking?
– Not applicable (0) 38 33
– Yes (1) 45 40
– No or occasionally (2) 31 27
If you change your clothes after work, where do you do it?
– Not applicable (0) 38 33
– Work (1) 52 46
– Home (2) 24 21
Are you trained on the health risks of pesticides?
– Not applicable (0) 38 33
– Yes (1) 38 33
(Continued)
4 M. T. MUÑOZ-QUEZADA ET AL.
6. Table 1. (Continued).
Question (score) Frequency
Percentage
response
– No (2) 38 33
Where do you wash the machinery?
– Does not wash, not applicable (0) 49 43
– In a dedicated place for washing (1) 9 8
– Yard, orchard, pasture or field (2) 50 44
– Inside the house (3) 6 5
Besides applying OPs, do you mix and prepare them?
– No or not applicable (0) 50 44
– Yes (1) 64 56
Where do you store the pesticides?
– Not applicable (0) 38 33
– Warehouse at home or work (1) 52 46
– In the house’s yard (2) 7 6
– Inside the house (3) 17 15
Do you use a motorized pump backpack to apply OPs?
– No (0) 76 67
– Yes (1) 38 33
How long have you worked as an agricultural worker?
– 10 years or less 42 37
– More of 10 years 72 63
Do you use a tractor operated nebulizer or pump to apply OPs?
– No (0) 99 87
– Yes (1) 15 13
Use of PPE in hands
– Yes (0) 69 61
– No (1) 45 39
Use of respiratory PPE
– Yes (0)
– No (1)
69
45
61
39
– Yes (0)
– No (1)
Use of protective eyewear
67 59
47 41
Use of PPE in the body
– Yes (0) 67 59
– No (1) 46 40
Use of PPE in the head
– Yes (0) 53 47
– No (1) 61 53
Frequency of use of PPE
– Always (0) 27 24
– Never or occasionally (1) 87 76
Use of PPE in the feet
– Yes (0) 45 40
– No (1) 69 60
In our workplace we have washbasin
– Yes (0) 65 57
– No (1) 49 43
In our workplace, we have toilet
– Yes (0) 75 66
– No (1) 39 34
In our workplace we have showers
– Yes (0) 62 54
– No (1) 52 46
In our workplace we have drinking water
– Yes (0) 52 46
– No (1) 62 54
In our workplace, we have hot water
– Yes (0) 70 61
39
– No (1) 44
(Continued)
INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH 5
7. Table 2 shows the 37 items summarized in four factors extracted after the Varimax rotation.
This factorial model accounts for 68% of the variance; factorial loads were greater than 0.20
and each factor has more than three reactants. Factor 1 presents the highest number of variables
with interactions. Factor 1 is dominated by variables related to pesticide application. Factor 2
summarized variability related to use of personal protective equipment. Factor 3 is directly related
Table 1. (Continued).
Question (score) Frequency
Percentage
response
Use organophosphate pesticides at home 13 11
– No (0)
– Yes (1) 99 87
Approximate distance from farm to house (in m) 18 16
– More of 500 m
– 500 m or less 96 84
Do you have a greenhouse, orchard or field at home? 37
– No 42
– Yes 71 62
Table 2. Factorial analysis of the questionnaire to assess organophosphate pesticide exposure (variance explained = 68%).
Extraction method: principal component analysis. Rotation method: Varimax with Kaiser normalization.
Variables
Factors
1 2 3 4
Are you currently working applying pesticides? 0.990
When was your last pesticide application? 0.964
Do you work as a seasonal or permanent pesticide applicator? 0.947
Do you have a pesticide applicator license? 0.939
Do you eat, drink or smoke during the application? 0.931
Do you change your clothes after the application? 0.896
The place where pesticide is mixed is 0.892
Do you use manual pump backpack to apply OPs? 0.890
What type of OP do you recall applying? 0.884
Do you wear personal protective equipment when mixing? 0.878
Do you know the health risks you are exposed to when applying or mixing pesticides? 0.876
How many years have you applied pesticides? 0.863
How long does it take between the end of the application and taking a shower or bath? 0.855
During or after pesticide application, do you wash your hands before smoking, eating or
drinking?
0.845
If you change your clothes after work, where do you do it? 0.841
Are you trained on the health risks of pesticides? 0.830
Where do you wash the machinery? 0.790
Besides applying OPs, do you mix and prepare them? 0.789
Where do you store the pesticides? 0.739
Do you use a motorized pump backpack to apply OPs? 0.500
How long have you worked as an agricultural worker? 0.300
Do you use a tractor operated nebulizer or pump to apply OPs? 0.263
Use of PPE in hands 0.827
Use of respiratory PPE 0.808
Use of protective eyewear 0.795
Use of PPE in the body 0.778
Use of PPE in the head 0.747
Frequency of use of PPE 0.681
Use of PPE in the feet 0.660
In our workplace, we have washbasin 0.866
In our workplace, we have toilet 0.826
In our workplace, we have showers 0.785
In our workplace, we have drinking water 0.628
In our workplace, we have hot water 0.578
Use organophosphate pesticides at home 0.722
Approximate distance from farm to house (in meters) 0.679
Do you have a greenhouse, orchard or field at home? 0.624
6 M. T. MUÑOZ-QUEZADA ET AL.
8. with hygienic workplace conditions related to OP exposure and factor 4 presents the home
conditions that facilitate exposure to OP in workers.
Table 3 presents the reliability analysis of the instrument. The questionnaire achieves an alpha
coefficient of Cronbach total = 0.95.
Cronbach’s alpha was greater than 0.70 for three of the four proposed factor groups (Table 3).
All correlations were positive and greater than zero. The weaker correlations were of the items
related to workplace and home conditions that facilitate OP exposure.
Table 4 shows the means, standard deviations, median, interquartile range, range, minimum,
and maximum scores of the questionnaire answered by the participants (maximum score 54
points) for each of the four factors.
The final composition of the questionnaire according to the four factors extracted and the
respective scores is shown in Appendix A2.
Table 3. Item-total correlations corrected, alpha value if the item is removed and alpha value per factor for the questionnaire.
Factor
Item-total correla-
tion correcteda
Alpha value
removes item
Alpha value
per factor
Factor 1: Labor conditions in the application of OPs 0.975
1. Are you currently working applying pesticides? 0.950 0.944
2. When was your last pesticide application? 0.917 0.942
3. Do you work as a seasonal or permanent pesticide applicator? 0.891 0.943
4. Do you have a pesticide applicator license? 0.856 0.943
5. Do you eat, drink or smoke during the application? 0.917 0.942
6. Do you change your clothes after the application? 0.880 0.943
7. What type of OP do you recall applying? 0.845 0.944
8. Where is the pesticide mixed? 0.834 0.944
9. Do you use manual pump backpack to apply OPs? 0.825 0.945
10. How many years have you applied pesticides? 0.831 0.943
11. Do you wear personal protective equipment when mixing? 0.730 0.944
12. Do you know the health risks you are exposed to when
applying or mixing pesticides?
0.757 0.944
13. How long does it take between the end of the application and
taking a shower or bath?
0.791 0.944
14. During or after pesticide application, do you wash your hands
before smoking, eating or drinking?
0.794 0.944
15. Are you trained on the health risks of pesticides? 0.859 0.943
16. If you change your clothes after work, where do you do it? 0.820 0.944
17. Besides applying OPs, do you mix and prepare them? 0.742 0.945
18. Where is the pesticide application equipment washed? 0.736 0.945
19. Where do you store the pesticides? 0.660 0.945
20. Do you use a motorized pump backpack to apply OPs? 0.492 0.946
21. Do you use a tractor operated nebulizer or pump to apply OPs? 0.273 0.948
22. How long have you worked as an agricultural worker? 0.268 0.948
Factor 2: Use of PPE 0.891
23. Use of PPE to protect hands (e.g. gloves) 0.243 0.948
24. Use of PPE to protect the head (e.g. face mask, hood) 0.120 0.949
25. Use of protective eyewear 0.229 0.948
26. Use of respiratory PPE (e.g. respirator) 0.333 0.947
27. Use of PPE to protect your body (e.g. coveralls, Tyvek suit) 0.357 0.947
28. Frequency of use of PPE 0.283 0.948
29. Use of PPE to protect the feet (e.g. rubber boots) 0.412 0.947
Factor 3: Workplace conditions that prevent exposure to OP 0.848
30. In our workplace we have showers 0.144 0.948
31. In our workplace we have washbasin 0.110 0.949
32. In our workplace we have hot water 0.100 0.949
33. In our workplace we have drinking water 0.100 0.949
34. In our workplace we have toilet 0.100 0.949
Factor 4: Home conditions related to OP exposure 0.600
35. Do you have a greenhouse, orchard or field at home? 0.100 0.949
36. Approximate distance from farm to house (in meters) 0.100 0.948
37. Use organophosphate pesticides at home 0.121 0.948
a
Indicates the linear correlation between each question and the total score obtained in the questionnaire.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH 7
9. Discussion
We evaluated the psychometric properties of a questionnaire to characterize potential OP expo-
sure. We identified four factors with the PCA extraction method. The items were grouped as
follows: the working conditions in the application of OP in agricultural workers (factor 1); use of
personal protective elements on the part of farmers (factor 2); sanitary workplace conditions that
prevent exposure to OP (factor 3) and home conditions related to OP exposure in the workers
(factor 4), which represented 68% of the total variance. These factors were reliable and internally
consistent, with a reliability greater than 75% in the first three factors and 60% in the fourth
factor.
Within these factors, it was found relevant to leave the items comprising a moderate correla-
tion with the total (Table 3), considering that if the element was removed, the change in
Cronbach’s alpha of each factor was not significant. Also, the content evaluated for those items
may provide relevant background information for evaluating exposure to OPs, such as the
questions of the factors 3 and 4, given that there are other exposure pathways which are related
to the variables of occupational exposure to OP (Lekei et al. 2014; Muñoz-Quezada et al. 2016a;
Corral et al. 2017), especially for applicators (Gesesew et al. 2016).
This questionnaire represents a first effort towards the future development of a standar-
dized version, with test–retest reliability and criterion related validity (compared to biomar-
kers) as a complementary measure regarding the exposure to pesticides on agricultural
workers.
The resulting contents from this first version coincide with other validated instruments, which
aim to assess exposure to pesticides related to the use of PPE and exposure conditions for
applicators and nonapplicators (Engel et al. 2001; Lekei et al. 2014; Gesesew et al. 2016).
However, this questionnaire has the advantage of including specific items to evaluate OP exposure
mainly related to occupational conditions of workers.
A questionnaire developed by Lekei et al (2014) demonstrated to be valid and useful for
inquiring about broad categories of pesticides and those of common use. However, the workers
showed difficulties in recalling the most specific active compounds of pesticides. The authors
mentioned that this was influenced by the information that was communicated by the authorities
about the hazardousness of the pesticides to the workers at that time. Also, we would add that in
general, the agricultural population has less access to formal education, which should be con-
sidered as an important factor when elaborating the items of the questionnaires. In this sense, in
addition to including an open question about the use of pesticides, we propose considering the
specific names of the pesticides in order to facilitate that the workers can recall them. In this
study, our purpose was to develop an instrument that aims to specifically assess organophosphate
exposure. In the same way, we believe that specific questionnaires should be proposed for other
pesticides too, in order to avoid confusing the respondent among different substances types and
classifications.
Gesesew et al. (2016) and Corral et al. (2017) showed in their studies that the use of
questionnaires on knowledge and attitudes regarding exposure to pesticides allows to assess the
Table 4. Descriptive statistics for the total score and the four factors of the questionnaire of exposure to OPs in farm workers
(n = 114).
Maximum N Values
Indicators Score Items Mean SD Median (IQRa
) Range Minimum Maximum
Total score 54 37 25.8 13.7 32 (25.3) 45 1 46
Factor 1 39 22 17.8 12.7 26 (27) 32 0 32
Factor 2 7 7 3.5 2.6 3 (5.3) 7 0 7
Factor 3 5 5 2.2 1.9 2 (4) 5 0 5
Factor 4 3 3 2.3 0.9 3 (1) 3 0 3
a
IQR = interquartile range.
8 M. T. MUÑOZ-QUEZADA ET AL.
10. behaviors associated with self-care practices, the beliefs about the effects on health and workers’
risk perception, providing useful inputs to the authorities for decision-making about workers’
training and vigilance strategies of the terrestrial application of pesticides.Compared to these
valuable previous efforts, our study provides more specific questions about the use of PPE, the
exposure of seasonal workers and pesticide applicators, the exposure at home and the conditions
of hygiene at work. Also, we included a series of questions that aim to identify acute and chronic
symptoms of exposure.
A limitation of our study is related to the fact that we were not able to compare the
questionnaire results with direct biomarkers of exposure to evaluate the sensitivity and specificity
of this instrument. Thus, this instrument is intended only as a descriptive measure of potential OP
exposure in agricultural workers. Further evaluation using biomonitoring is needed to verify OP
exposure assessed through the proposed questionnaire.
In summary, this OP exposure questionnaire is a valid instrument to evaluate potential
occupational exposure and provide information on working conditions and housing. The epide-
miological analysis of the association between exposure to OPs evaluated through this question-
naire and the health conditions is presented in another published article (Muñoz-Quezada et al.
2017). In addition, it allows the provision of timely information to guide public and private
institutions that can take action to control risk behaviors and provide oversight of situations that
imply noncompliance with current regulations, aiding to an adequate protection of the workers’
health.
Acknowledgments
The authors acknowledge the support of the National Commission of Scientific and Technological Research,
CONICYT of Chilean Government, Catholic University of Maule, the School of Public Health, University of
Chile, the Agricultural Development Institute (INDAP) of Curicó and Ministerial Secretariat of Health of the
Maule Region.
Disclosure statement
No potential conflict of interest was reported by the authors.
Funding
This work was supported by Fondo Nacional de Investigacion y Desarrollo en Salud under Grant SA13I20019; and
Fondo Nacional de Desarrollo Científico y Tecnológico under Grant11150784, of the National Commission of
Scientific and Technological Research, CONICYT of Chilean Government
Statements of authorship
María Teresa Muñoz-Quezada, Boris Lucero, Asa Bradman, Brittney Baumert, Verónica Iglesias, María Pía
Muñoz and Carlos Concha developed the concept and designed this work. María Teresa MuñozQuezada, Boris
Lucero, Brittney Baumert, Carlos Concha and María Pía Muñoz, participated in data collection. All authors
participated in the analysis and interpretation of data, drafting the manuscript, critical revision of the text and
approval of the final version.
ORCID
María Teresa Muñoz-Quezada http://orcid.org/0000-0002-8008-8625
Verónica Iglesias http://orcid.org/0000-0002-1636-9203
INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH 9
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15. Appendix A2. Final structure of the exposure questionnaire with the items grouped in the four rotated factors.
Factor 1: Labor conditions in the application of OPs
1.How long have you worked as an agricultural
worker?
0.___10 years or less 1.___More than 10 years
2.Are you currently working applying pesticides? 1.___Yes 0.___No
3.When was your last pesticide application? 0.___Not applicable 1.___2 years or more
2.___Less than 2 years
4. Do you work mostly as a seasonal or permanent
pesticide applicator? (Check one)
0.___Not applicable 1.___Seasonal
2.___Permanent
5. How many years have you applied pesticides? 0.___Not applicable 1.___10 years or less
2.___More than 10 years
6. Do you have a pesticide applicator license? 1.___Yes 0.___No
7. Do you know the health risks you are exposed to
when applying or mixing pesticides?
1.___Yes 2.___No 0.___Not applicable
8. Are you trained on the health risks of pesticides? 1.___Yes 2.___No 0.___Not applicable
9. Do you eat, drink or smoke during the
application?
1.___No 2.___Yes or
occasionally
0.___Not applicable
10.During or after pesticide application, do you
wash your hands before smoking, eating or
drinking?
1.___Yes 2.___No or
occasionally
0.___Not applicable
11.What type of pesticide do you recall applying?
(Can check more than one option)
(Internal code for answers rating: 0 = Not
applicable; 1 = Only one OP; 2 = More than one
OP)
0.___Not applicable OP 1.___Chlorpyrifos (Lorsban,
Troya)
2.___Methamidophos
(MTD 600, Monitor, Tamaron)
3.___Azinphosmethyl
(Gusathion)
4.___Metidation 5.___Diazinon
6.___Phosmet 7.___Dimethoate
8.___Profenofos 9.___Cadusafos
10.___Other OP (Name them): _________
12.Do you use manual pump backpack to apply
OPs?
1.___Yes 0.___No or not applicable
13.Do you use a motorized pump backpack to apply
OPs?
1.___Yes 0.___No or not applicable
14. Do you use a tractor operated nebulizer or pump
to apply OPs?
1.___Yes 0.___No or not applicable
15. Where do you wash the machinery that was
used to apply pesticides? (Check one option)
0.___Does not wash, not applicable 1.___In a dedicated place
for washing
2.___Yard, orchard, pasture or field 3.___Inside the house
16. Where do you store the pesticides? (Check one
option)
0.___Not applicable 1.___Warehouse at home
or work
2.___In the house’s yard 3.___Inside the house
17. Besides applying OPs, do you mix and prepare
them?
1.Yes 0.___No or not applicable
18. The place where the pesticide is mixed is. 0.___Not applicable 1.___Open 2.___Closed
19. Do you wear personal protective equipment
when mixing?
0.___Not applicable 1.___Yes 2.___No
20.Do you change your clothes after the
application?
1.___Yes 2.___No or
occasionally
0.___Not applicable
21.If you change your clothes after work, where do
you do it? (check one option)
1.___Work 2.___Home 0.___Not applicable
22.How long does it take between the end of the
application and taking a shower or bath? (check
one option)
1.___Less than 15 min 2.___15 min or mores
0.___Not applicable
Factor 2: Use of PPE
In your work as an agricultural worker, check if
you use the following personal protective
equipment (PPE):
23.Use of PPE in hands (gloves) 0.___Yes 1.___No
24. Use of PPE in the head (hat) 0.___Yes 1.___No
25. Use of protective eyewear (googles, face shield
or safety glasses)
0.___Yes 1.___No
26. Use of respiratory PPE (respiratory mask with
recommended filters and facial protection)
0.___Yes 1.___No
27. Use of PPE in the body (waterproof suit with no
cuts or holes)
0.___Yes 1.___No
28. Use of PPE in the feet (rubber boot) 0.___Yes 1.___No
(Continued)
14 M. T. MUÑOZ-QUEZADA ET AL.
16. Appendix A2. (Continued).
Factor 1: Labor conditions in the application of OPs
29. Frequency of use of PPE 0.___Always 1.___Never or occasionally
Factor 3: Workplace conditions that prevent exposure
to OP
30.In our workplace, we have showers 0.___Yes 1.___No
31.In our workplace, we have washbasin 0.___Yes 1.___No
32.In our workplace, we have hot water 0.___Yes 1.___No
33.In our workplace, we have drinking water 0.___Yes 1.___No
34. In our workplace, we have toilet 0.___Yes 1.___No
Factor 4: Home conditions related to OP exposure
35. Do you have a greenhouse, orchard or field at
home?
0.___Yes 1.___No
36. Approximate distance from farms to your house
(in meters) (Check one option)
0.___More than 500 m 1.___500 m or less
37. Use organophosphate pesticides at home 0.___Yes 1.___No
INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH 15