Literature DB >> 31047815

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

D Daniel1, Arnt Diener2, Saket Pande3, Sylvia Jansen4, Sara Marks2, Regula Meierhofer2, Madan Bhatta5, Luuk Rietveld3.   

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.
Copyright © 2019. Published by Elsevier GmbH.

Entities:  

Keywords:  Bayesian belief networks; Behavioural modelling; Household water treatment

Mesh:

Year:  2019        PMID: 31047815     DOI: 10.1016/j.ijheh.2019.04.005

Source DB:  PubMed          Journal:  Int J Hyg Environ Health        ISSN: 1438-4639            Impact factor:   5.840


  4 in total

1.  Assessing the Impacts of Relative Wealth and Geospatial Factors on Water Access in Rural Nepal: A Community Case Study.

Authors:  Naseeha Islam; Pramesh Koju; Reetu Manandhar; Sudip Shrestha; Charlotte Smith
Journal:  Int J Environ Res Public Health       Date:  2020-09-07       Impact factor: 3.390

2.  Childhood Malnutrition and the Association with Diarrhea, Water supply, Sanitation, and Hygiene Practices in Kersa and Omo Nada Districts of Jimma Zone, Ethiopia.

Authors:  Negasa Eshete Soboksa; Sirak Robele Gari; Abebe Beyene Hailu; Bezatu Mengistie Alemu
Journal:  Environ Health Insights       Date:  2021-03-03

3.  Assessing Drinking Water Quality at the Point of Collection and within Household Storage Containers in the Hilly Rural Areas of Mid and Far-Western Nepal.

Authors:  D Daniel; Arnt Diener; Jack van de Vossenberg; Madan Bhatta; Sara J Marks
Journal:  Int J Environ Res Public Health       Date:  2020-03-25       Impact factor: 3.390

4.  A hierarchical Bayesian Belief Network model of household water treatment behaviour in a suburban area: A case study of Palu-Indonesia.

Authors:  D Daniel; Mita Sirait; Saket Pande
Journal:  PLoS One       Date:  2020-11-06       Impact factor: 3.240

  4 in total

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