The association of pesticide exposure on anthropometric parameters among under-five children in Magelang Regency, Central Java Province, Indonesia: a cross-sectional study

Introduction: As endocrine disruptor chemicals, pesticides pose hormone-associated diseases, such as growth and developmental pathologies, in children through IGF-1 modulators. This study aims to analyze pesticide exposure on anthropometry status in under-five children and related factors that contribute to them. Methods: A cross-sectional study is proposed to collect 362 under-five children who visited Posyandu in Magelang Regency, Central Java, Indonesia. Independent variables are types of pesticide application and baseline characteristics of parents and children. The data are collected through questionnaires. Dependent variables include anthropometric status, including WLZ, WAZ, HAZ, and BMZ. Statistical analysis used Linear Regression and Analysis of Covariance with SPSS version 25. Results: When child age is stratified <30 mo, organophosphate exposure affects WLZ (β = 0.52, P=<0.001, CI95 = 0.13, 0.90), WAZ (β = 0.54, P = 0.02, CI95 = 0.08, 1.01) and BAZ (β = 0.49, P = 0.01, CI95 = 0.09, 0.89). Imidacloprid pretends BAZ (β = 0.53, P = 0.04; CI95 = 0.00, 1.05) and triazole influences WAZ (β = 1.09, P = 0.03, CI95 = 0.08, 2.09). Baseline characteristics stated that location affects WLZ (β = 0.44, P=<0.001; CI95 = 0.19, 0.68), WAZ (β = 0.32, P = 0.01, CI95 = 0.06, 0.59) and BAZ (β = 0.55, P=<0.001, CI95 = 0.31, 0.80); child age contributes WLZ (β = −0.00, P = 0.02, CI95 = −0.01, −0.00), WAZ (β = -0.02, P=<0.001, CI95 = −0.02, −0.01), HAZ (β = −0.02, P=<0.001, CI95 = −0.03, −0.01). The remaining variables, father education and child gender, have a role in disrupting HAZ (β = 0.22, P = 0.02, CI95 = 0.02, 0.41) and BAZ (β = 0.25, P = 0.03, CI95 = 0.02, 0.49). Conclusions: Organophosphate, imidacloprid, and triazole have the potential to damage growth hormones. However, dithiocarbamate is still questionable. Other aspects are warranted to control location, child age, child gender, and father education that contribute to malnutrition.

Abstract licence: CC BY-NC-ND

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