Monitoring Drinking Water Quality in Nationally Representative Household Surveys in Low- and Middle-Income Countries: Cross-Sectional Analysis of 27 Multiple Indicator Cluster Surveys 2014-2020.
Monitoring Drinking Water Quality in Nationally Representative Household Surveys in Low- and Middle-Income Countries: Cross-Sectional Analysis of 27 Multiple Indicator Cluster Surveys 2014-2020.
复制标题
监测低收入和中等收入国家具有全国代表性的家庭调查中的饮用水质量：2014-2020年27项多指标类集调查的横截面分析。
DOI：
10.1289/ehp8459
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发表时间：
2021-09
影响因子：
10.4
通讯作者：
Slaymaker T
中科院分区：
文献类型：
--
作者：
Bain R;Johnston R;Khan S;Hancioglu A;Slaymaker T
《2030年可持续发展目标》为安全管理的饮用水服务设定了雄心勃勃的新基准，但许多国家缺乏关于饮用水供应和质量的国家数据。我们量化了27个低收入和中等收入国家饮用水的可得性和微生物质量，监测了SMDWs，并检查了大肠杆菌污染的危险因素。在27个多指标类集调查中实施了一个用于住户调查的新的水质模块。小组使用便携式设备在收集点（PoC）和使用点（PoU）测量大肠杆菌，并询问受访者饮用水的可获得性和可及性。如果家庭使用经改善的水源，在家庭卫生中心没有大肠杆菌污染，可以在现场获得，并在需要时提供，则家庭被归类为拥有SMDW服务。此外，还评估了是否符合个别SMDW标准。采用修正泊松回归探讨大肠杆菌污染的家庭和社区危险因素。大肠杆菌通常在PoC（范围16-90%）检测到，在PoU（范围19-99%）检测到的可能性更大。平均而言，84%的家庭使用了改善的饮用水源，31%的家庭达到了SMDW的所有标准。大肠杆菌污染是未达到SMDW标准的主要原因（27个国家中的15个）。在使用改良水源的家庭中，PoC样本中大肠杆菌的流行率较低[；95%置信区间（CI）： 0.64, 0.85]，但对于房屋内可获得水的家庭（95% CI: 0.94, 1.05）或需要时可获得水的家庭（95% CI: 0.88, 1.02）则不适用。在最富裕的五分之一家庭与最贫穷的五分之一家庭（95% CI: 0.55, 0.88）和卫生设施覆盖率较高的社区（95% CI: 0.90, 0.97）中，粪便样本的大肠杆菌污染较少。牲畜拥有量（95% CI: 1.04, 1.13）、农村居民与城市居民（95% CI: 1.04, 1.16）以及湿季与旱季采样（95% CI: 1.01, 1.15）与PoU的污染呈正相关。横截面水质数据可以在住户调查中收集，并可用于评估服务水平的不平等，跟踪可持续发展目标中小型污水处理厂的指标，并检查污染的风险因素。迫切需要加强风险管理，以减少中低收入国家通过饮用水服务广泛暴露于粪便污染。https://doi.org/10.1289/EHP8459
The 2030 Sustainable Development Goals (SDGs) set an ambitious new benchmark for safely managed drinking water services (SMDWs), but many countries lack national data on the availability and quality of drinking water. We quantified the availability and microbiological quality of drinking water, monitored SMDWs, and examined risk factors for Escherichia coli (E. coli) contamination in 27 low-and middle-income countries (LMICs). A new water quality module for household surveys was implemented in 27 Multiple Indicator Cluster Surveys. Teams used portable equipment to measure E. coli at the point of collection (PoC, ) and at the point of use (PoU, ) and asked respondents about the availability and accessibility of drinking water. Households were classified as having SMDW services if they used an improved water source that was free of E. coli contamination at PoC, accessible on premises, and available when needed. Compliance with individual SMDW criteria was also assessed. Modified Poisson regression was used to explore household and community risk factors for E. coli contamination. E. coli was commonly detected at the PoC (range 16–90%) and was more likely at the PoU (range 19–99%). On average, 84% of households used an improved drinking water source, and 31% met all of the SMDW criteria. E. coli contamination was the primary reason SMDW criteria were not met (15 of 27 countries). The prevalence of E. coli in PoC samples was lower among households using improved water sources [; 95% confidence interval (CI): 0.64, 0.85] but not for households with water accessible on premises (; 95% CI: 0.94, 1.05) or available when needed (; 95% CI: 0.88, 1.02). E. coli contamination of PoU samples was less common for households in the richest vs. poorest wealth quintile (; 95% CI: 0.55, 0.88) and in communities with high () improved sanitation coverage (; 95% CI: 0.90, 0.97). Livestock ownership (; 95% CI: 1.04, 1.13), rural vs. urban residence (; 95% CI: 1.04, 1.16), and wet vs. dry season sampling (; 95% CI: 1.01, 1.15) were positively associated with contamination at the PoU. Cross-sectional water quality data can be collected in household surveys and can be used to assess inequalities in service levels, to track the SDG indicator of SMDWs, and to examine risk factors for contamination. There is an urgent need for better risk management to reduce widespread exposure to fecal contamination through drinking water services in LMICs. https://doi.org/10.1289/EHP8459