Understanding the effect of socio-economic characteristics and psychosocial factors on household water treatment practices in rural Nepal using Bayesian Belief Networks

D. Daniel, Arnt Diener, Saket Pande, Sylvia Jansen, Sara Marks, Regula Meierhofer, Madan Bhatta, Luuk Rietveld

Research output: Contribution to journalArticleScientificpeer-review

8 Citations (Scopus)
76 Downloads (Pure)

Abstract

About 20 Million (73%) people in Nepal still do not have access to safely managed drinking water service and 22 million (79%)do not treat their drinking water before consumption. Few studies have addressed the combination of socio-economic characteristics and psychosocial factors that explain such behaviour in a probabilistic manner. In this paper we present a novel approach to assess the usage of household water treatment (HWT), using data from 451 households in mid and far-western rural Nepal. We developed a Bayesian belief network model that integrates socio-economic characteristics and five psychosocial factors. The socio-economic characteristics of households included presence of young children, having been exposed to HWT promotion in the past, level of education, type of water source used, access to technology and wealth level. The five psychosocial factors capture households’ perceptions of incidence and severity of water-borne infections, attitudes towards the impact of poor water quality on health, water treatment norms and the knowledge level for performing HWT. We found that the adoption of technology was influenced by the psychosocial factors norms, followed by the knowledge level for operating the technology. Education, wealth level, and being exposed to the promotion of HWT were the most influential socio-economic characteristics. Interestingly, households who were connected to a piped water scheme have a higher probability of HWT adoption compared to other types of water sources. The scenario analysis revealed that interventions that only target single socio-economic characteristics do not effectively boost the probability of HWT practice. However, interventions addressing several socio-economic characteristics increase the probability of HWT adoption among the target groups.
Original languageEnglish
Pages (from-to)847 - 855
Number of pages9
JournalInternational Journal of Hygiene and Environmental Health
Volume222
Issue number5
DOIs
Publication statusPublished - 2019

Keywords

  • Bayesian belief networks
  • Behavioural modelling
  • Household water treatment

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