Arsenicosis in Bangladesh: prevalence and socio-economic correlates.
The potential effects of arsenic-contaminated drinking water on health are of concern, but our understanding of the risk factors of arsenicosis remains limited. This study assessed the prevalence of and socio-economic differentials in arsenic-associated skin lesions in a rural community in Bangladesh. Data were collected from a village where the Bangladesh Rural Advancement Committee has operated a health surveillance system and a community-based arsenic mitigation project since 1999. In total, 1654 residents in the study village were examined in May 2000 for arsenic-associated lesions on their skin. Socio-economic information was extracted from the surveillance system database covering the village. Nearly 2.9% of the study population had clinical manifestations of arsenic poisoning. The prevalence of arsenicosis was associated with age, sex, education and the economic status of the household. Multivariate analysis identified age and economic status as significant predictors of arsenicosis controlling for education and gender. In conclusion, a clear understanding of the socio-economic distribution of arsenicosis in different demographic and socio-economic groups will be useful in identifying the high-risk groups from arsenic-affected communities. More studies are needed to design effective interventions to mitigate the effects of arsenic in Bangladesh.
Hadi
A
A
Research and Evaluation Division, Bangladesh Rural Advancement Committee, 75 Mohakhali, 1212 Dhaka, Bangladesh. hadi.a@brac.net
Parveen
R
R
D000293:Adolescent; D000328:Adult; D020261:Arsenic Poisoning / Q000453:epidemiology* / Q000503:physiopathology; D001459:Bangladesh / Q000453:epidemiology; D003872:Dermatitis / Q000453:epidemiology / Q000209:etiology; D004781:Environmental Exposure / Q000009:adverse effects; D004784:Environmental Monitoring; D062665:Epidemiological Monitoring; D005260:Female; D006801:Humans; D008297:Male; D011159:Population Surveillance; D015995:Prevalence; D012307:Risk Factors; D012423:Rural Health / Q000706:statistics & numerical data*; D014877:Water Pollution, Chemical / Q000009:adverse effects*; D014881:Water Supply / Q000032:analysis*