bioRxivMicrobiology
Hepatitis E Virus infection and waste pickers: a case-control seroprevalence study
C. Alvarado-Esquivel, V. D. Gutierrez-Martinez, E. G. Ramirez-Valles, A. Sifuentes-Alvarez
Abstract
Whether waste pickers are a risk group for hepatitis E virus (HEV) infection is largely unknown. Therefore, this study aimed to determine the association between HEV exposure and: 1) the occupation of waste picker; and 2) the work characteristics of waste pickers. An age-and gender-matched case-control seroprevalence study of 86 waste pickers (mean age: 35.45 {+/-} 17.15 years) and 86 control subjects of the general population was performed. We determined anti-HEV IgG antibodies in sera of cases and controls using a commercially available enzyme-linked immunoassay. The McNemars test was used to assess the association between HEV seropositivity and the occupation of waste picker. The association between HEV seropositivity and work characteristics of waste pickers was assessed by bivariate and regression analyses. Anti-HEV IgG antibodies were detected in 14 (16.3%) of the 86 waste pickers and in 8 (9.3%) of the 86 control subjects (McNemars pair test: OR = 13.0; 95% CI: 0.73-230.77; P=0.02). Ill waste pickers had a higher HEV seroprevalence than those who were apparently healthy (6/15: 40% vs 8/71: 11.3%, respectively: P=0.01). Waste pickers with reflexes impairment had a higher HEV seroprevalence than those without this impairment (5/10: 50% and 9/76: 11.8%, respectively; P=0.009). Logistic regression analysis of sociodemographic, work, and behavioral characteristics of waste pickers showed that HEV seropositivity was associated with increasing age (OR = 6.52; 95% CI: 1.95-21.78; P=0.002) and raising pigs (OR = 12.01; 95% CI: 1.48-97.26; P=0.02). This is the first age- and gender-matched case-control study on the association between HEV infection and the occupation of waste picker. Waste pickers represent a risk group for HEV infection. Factors associated with HEV seropositivity found in this study may help in the design of optimal planning to avoid HEV infection.
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