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Exposure measurement error and the characterization of child exposure to fecal contamination in drinking water

机译:曝光测量误差与儿童暴露于饮用水中粪便污染的特征

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Characterizing fecal contamination exposure from drinking water can introduce exposure measurement errors, i.e., differences between the observed and true exposure. These errors can mask the true relationship between fecal contamination exposure and waterborne diseases. We present a framework to quantify the impact of measurement errors on exposure–outcome health effect estimates introduced by variability in measured drinking water fecal contamination levels and household versus community sampling strategies. We matched fecal indicator bacteria (FIB) data for 37,000 drinking water samples to children aged 0–72 months from 19 studies in low- and middle-income countries and took two complementary analytical approaches. We found that household-level exposure assessments may attenuate effect estimates of FIB concentrations in drinking water on diarrhea, and single water samples may attenuate health effect estimates of FIB concentrations on linear growth. To understand the health effects of fecal contamination exposure, measurement error frameworks can be used to estimate more biologically relevant exposures.
机译:表征饮用水中的粪便污染暴露可以引入曝光测量误差,即观察到和真正的暴露之间的差异。这些错误可以掩盖粪便污染暴露和水性疾病之间的真正关系。我们提出了一个框架,以量化测量误差对曝光结果的影响损伤估算对测量饮用水粪污染水平和家庭与社区采样策略的变异引入的影响。我们将粪便指标细菌(FIB)数据匹配> 37,000次饮用水样本与低收入和中等收入国家的19个月,并采取两种互补的分析方法。我们发现家庭级别的曝光评估可以衰减FIB浓度在腹泻上饮用水中的效果估计,单水样可以衰减对线性生长的FIB浓度的健康效果估算。要了解粪便污染曝光的健康效果,测量误差框架可用于估计更生物相关的曝光。

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