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Abstract：
The study contextualises the spatial heterogeneity and associated drivers of open defecation (OD) in India.
The present study involved a secondary cross-sectional survey data from the fifth round of the National Family Health Survey conducted during 2019-2021 in India. We mapped the spatial heterogeneity of OD practices using LISA clustering techniques and assessed the critical drivers of OD using multivariate regression models. Fairlie decomposition model was used to identify the factors responsible for developing OD hot spots and cold spots.
The study was conducted in India and included 636 699 sampled households within 36 states and union territories covering 707 districts of India.
The outcome measure was the prevalence of OD.
The prevalence of OD was almost 20%, with hot spots primarily located in the north-central belts of the country. The rural-urban (26% vs 6%), illiterate-higher educated (32% vs 4%) and poor-rich (52% vs 2%) gaps in OD were very high. The odds of OD were 2.7 and 1.9 times higher in rural areas and households without water supply service on premises compared with their counterparts. The spatial error model identified households with an illiterate head (coefficient=0.50, p=0.001) as the leading spatially linked predictor of OD, followed by the poorest (coefficient=0.31, p=0.001) and the Hindu (coefficient=0.10, p=0.001). The high-high and low-low cluster inequality in OD was 38%, with household wealth quintile (67%) found to be the most significant contributing factor, followed by religion (22.8%) and level of education (6%).
The practice of OD is concentrated in the north-central belt of India and is particularly among the poor, illiterate and socially backward groups. Policy measures should be taken to improve sanitation practices, particularly in high-focus districts and among vulnerable groups, by adopting multispectral and multisectoral approaches.
The present study involved a secondary cross-sectional survey data from the fifth round of the National Family Health Survey conducted during 2019-2021 in India. We mapped the spatial heterogeneity of OD practices using LISA clustering techniques and assessed the critical drivers of OD using multivariate regression models. Fairlie decomposition model was used to identify the factors responsible for developing OD hot spots and cold spots.
The study was conducted in India and included 636 699 sampled households within 36 states and union territories covering 707 districts of India.
The outcome measure was the prevalence of OD.
The prevalence of OD was almost 20%, with hot spots primarily located in the north-central belts of the country. The rural-urban (26% vs 6%), illiterate-higher educated (32% vs 4%) and poor-rich (52% vs 2%) gaps in OD were very high. The odds of OD were 2.7 and 1.9 times higher in rural areas and households without water supply service on premises compared with their counterparts. The spatial error model identified households with an illiterate head (coefficient=0.50, p=0.001) as the leading spatially linked predictor of OD, followed by the poorest (coefficient=0.31, p=0.001) and the Hindu (coefficient=0.10, p=0.001). The high-high and low-low cluster inequality in OD was 38%, with household wealth quintile (67%) found to be the most significant contributing factor, followed by religion (22.8%) and level of education (6%).
The practice of OD is concentrated in the north-central belt of India and is particularly among the poor, illiterate and socially backward groups. Policy measures should be taken to improve sanitation practices, particularly in high-focus districts and among vulnerable groups, by adopting multispectral and multisectoral approaches.
摘要：
目的：该研究将印度开放性排便（OD）的空间异质性和相关驱动因素进行了研究。
方法：本研究涉及印度2019-2021年进行的第五轮全国家庭健康调查的二级横断面调查数据。我们使用LISA聚类技术绘制了OD实践的空间异质性，并使用多元回归模型评估了OD的关键驱动因素。使用Fairlie分解模型来识别导致OD热点和冷点发展的因素。
方法：该研究是在印度进行的，包括印度707个地区的36个州和联邦领土内的636699个抽样家庭。
方法：结果测量是OD的患病率。
结果：OD的患病率几乎是20%，热点地区主要位于该国中北部地带。农村-城市（26%对6%），文盲-受过高等教育（32％对4％）和穷人-富人（52％对2％）的OD差距非常高。在农村地区和没有供水服务的家庭中，OD的几率分别是同类家庭的2.7倍和1.9倍。空间误差模型将不识字的家庭（系数=0.50，p=0.001）确定为OD的主要空间联系预测因子，其次是最差的（系数=0.31，p=0.001）和印度教（系数=0.10，p=0.001）。OD的高低簇不平等为38%，家庭财富五分之一(67%)被认为是最重要的贡献因素，其次是宗教(22.8%)和教育水平(6%)。
结论：OD的做法集中在印度的中北部地区，尤其是穷人，文盲和社会落后的群体。应采取政策措施改善卫生做法，特别是在重点地区和弱势群体中，通过采用多光谱和多部门方法。
方法：本研究涉及印度2019-2021年进行的第五轮全国家庭健康调查的二级横断面调查数据。我们使用LISA聚类技术绘制了OD实践的空间异质性，并使用多元回归模型评估了OD的关键驱动因素。使用Fairlie分解模型来识别导致OD热点和冷点发展的因素。
方法：该研究是在印度进行的，包括印度707个地区的36个州和联邦领土内的636699个抽样家庭。
方法：结果测量是OD的患病率。
结果：OD的患病率几乎是20%，热点地区主要位于该国中北部地带。农村-城市（26%对6%），文盲-受过高等教育（32％对4％）和穷人-富人（52％对2％）的OD差距非常高。在农村地区和没有供水服务的家庭中，OD的几率分别是同类家庭的2.7倍和1.9倍。空间误差模型将不识字的家庭（系数=0.50，p=0.001）确定为OD的主要空间联系预测因子，其次是最差的（系数=0.31，p=0.001）和印度教（系数=0.10，p=0.001）。OD的高低簇不平等为38%，家庭财富五分之一(67%)被认为是最重要的贡献因素，其次是宗教(22.8%)和教育水平(6%)。
结论：OD的做法集中在印度的中北部地区，尤其是穷人，文盲和社会落后的群体。应采取政策措施改善卫生做法，特别是在重点地区和弱势群体中，通过采用多光谱和多部门方法。
