Work

Patterns and predictors of household water treatment in India

Year: 2025
Type: article
Abstract: Access to safe drinking water is a fundamental human right, with water quality serving as the key determinant of its safety. Household water treatment practices offer an effective means of addressing water quality challenges, particularly in the context of developing countries. This study aims to assess the status, patterns and predictors such as socio-economic, demographic, and infrastructural factors determining water treatment practices at household level in India using National Family Health Survey (2019–2021). The results show that 41.7 % of households practiced water treatment which is more prevalent in urban areas (56.5 %) than rural areas (34.3 %). Across states and union territories, water treatment varies from over 95 % in Nagaland and Kerala to less than 10 % in Bihar. Boiling (38.3 %) is the most prevalent practice followed by strain through cloth (35.6 %), water filter (16.7 %), chlorine bleaching (8.1 %) and electronic purifiers (3.3 %). The strongest positive predictors of household water treatment are the richest wealth quintile (AOR=4.399), having higher education (AOR=1.830), pucca house type (AOR=1.350), residing in an urban area (AOR=1.213), using a flush toilet (AOR=1.022) and a pit latrine (AOR=1.280). By situating these findings within the broader context of water quality challenges such as pollution and contamination, we emphasize the need to enhance the adoption of context-specific household water treatment interventions to ensure safe drinking water for all. • Water treatment practices were most prevalent in North-eastern states and least in Eastern states. • Boiling, cloth straining, water filter and electronic purifier were the most prevalent treatment practices. • Only 28.3% of households use effectivewater treatment methods, revealing critical gaps in safe drinking water practices. • Wealth and education are strongest predictors, richest households shows 5-fold higher water treatment odds than poorest.
Language: English
Field: Nursing
Open Access status: gold
Estimated APC paid: $1,230
OpenAlex ID: W4415217510
FWCI: 0.562
Cites: 47
Cited by: 1
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