Geographical heterogeneity and inequality of access to improved drinking water supply and sanitation in Nepal

He, Wenjun; Lai, Ying-Si; Dai, Bofeng; Hao, Yuantao; Xu, Dong

doi:10.1186/s12939-018-0754-8

Cited by 37 publications

(39 citation statements)

References 26 publications

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“…Jimenez-Rubio and colleagues [32] estimated the between-area concentration index in income-related inequalities in Canada using decomposition of the concentration index. The authors used the product of the population share and health variable share as a weight for each area, rather than using a spatial weight matrix [32][33][34][35][36][37][38][39]. However, previous studies have failed to capture the influence that spatial effects or spatial patterns, i.e.…”

Section: Introductionmentioning

confidence: 99%

A method for measuring spatial effects on socioeconomic inequalities using the concentration index

Kim

Haghparast‐Bidgoli

Skordis‐Worrall

et al. 2020

Int J Equity Health

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Background: Although spatial effects contribute to inequalities in health care service utilisation and other health outcomes in low and middle income countries, there have been no attempts to incorporate the impact of neighbourhood effects into equity analyses based on concentration indices. This study aimed to decompose and estimate the contribution of spatial effects on inequalities in uptake of HIV tests in Malawi. Methods: We developed a new method of reflecting spatial effects within the concentration index using a spatial weight matrix. Spatial autocorrelation is presented using a spatial lag model. We use data from the Malawi Demographic Health Survey (n = 24,562) to illustrate the new methodology. Need variables such as 'Any STI last 12 month', 'Genital sore/ulcer', 'Genital discharge' and non need variables such as Education, Literacy, Wealth, Marriage, and education were used in the concentration index. Using our modified concentration index that incorporates spatial effects, we estimate inequalities in uptake of HIV testing amongst both women and men living in Malawi in 2015-2016, controlling for need and non-need variables. Results: For women, inequalities due to need variables were estimated at − 0.001 and − 0.0009 (pro-poor) using the probit and new spatial probit estimators, respectively, whereas inequalities due to non-need variables were estimated at 0.01 and 0.0068 (pro-rich) using the probit and new spatial probit estimators. The results suggest that spatial effects increase estimated inequalities in HIV uptake amongst women. Horizontal inequity was almost identical (0.0103 vs 0.0102) after applying the spatial lag model. For men, inequalities due to need variables were estimated at − 0.0002 using both the probit and new spatial probit estimators; however, inequalities due to non-need variables were estimated at − 0.006 and − 0.0074 for the probit and new spatial probit models. Horizontal inequity was the same for both models (− 0.0057). Conclusion: Our findings suggest that men from lower socioeconomic groups are more likely to receive an HIV test after adjustment for spatial effects. This study develops a novel methodological approach that incorporates estimation of spatial effects into a common approach to equity analysis. We find that a significant component of inequalities in HIV uptake in Malawi driven by non-need factors can be explained by spatial effects. When the spatial model was applied, the inequality due to non need in Lilongwe for men and horizontal inequity in Salima for women changed the sign. This approach can be used to explore inequalities in other contexts and settings to better understand the impact of spatial effects on health service use or other health outcomes, impacting on recommendations for service delivery.

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Section: Introductionmentioning

confidence: 99%

A method for measuring spatial effects on socioeconomic inequalities using the concentration index

Kim

Haghparast‐Bidgoli

Skordis‐Worrall

et al. 2020

Int J Equity Health

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“…Inequality in access to water supply and sanitation services (WASH services) has already been the subject of several studies and discussions [2][3][4]. However, when access to water and sanitation was explicitly recognized as universal human rights by the UN in 2010, this issue was put on the center of the debates in the sector [5][6][7][8]. The HRWS were incorporated into the 2030 Agenda for Sustainable Development, particularly in the SDG 6: "Ensure availability and sustainable management of water and sanitation for all".…”

Section: Introductionmentioning

confidence: 99%

New Approaches to Monitor Inequalities in Access to Water and Sanitation: The SDGs in Latin America and the Caribbean

Queiroz

Carvalho

Heller

2020

Water

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In the 2030 Agenda for Sustainable Development, Targets 6.1 and 6.2 show, in their formulation, some alignment with the normative content of the human rights to water and sanitation (HRWS). However, the principle of equality and non-discrimination, which applies to all human rights, was not clearly incorporated into the indicators adopted to assess and monitor these targets. This paper contributes to bridging this gap by proposing two methodological strategies to address inequalities in analyses of access to water and sanitation services. The first consists in adjusting the indicators of access to these services according to inequality. The second proposes an assessment of intersecting forms of inequality. An application of these methods in Latin America and the Caribbean highlights significant regional heterogeneity and elevated inequality in access to services in the countries of this region. The methods demonstrate their potential in contributing to assessment and monitoring of the SDGs, but outdated or lacking data are obstacles to more in-depth analyses.

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“…But, evidence on the spatial distribution of households which depends on unimproved water sources has been incomplete or ignored in most of the studies [15,16]. In this regard, few studies were conducted in Ethiopia to locate or map areas with highest unimproved water source coverage among different wealth categories and local level [17,18].…”

Section: Introductionmentioning

confidence: 99%

Unimproved water sources in Ethiopia: Spatial variation and household point-of-use treatment practice based on 2016 Demographic and Health Survey

Tefera

Geremew

2020

Preprint

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Background Improved water sources are not equally available in all geographical regions. Populations dependent on unsafe water sources are recommended to treat their water at point-of-use using adequate methods to reduce associated health problems. In Ethiopia, the spatial distribution of households using unimproved water sources have been incomplete or ignored in most of the studies. Moreover, evidence on the point-of-use water treatment practice of households dependent on such water sources is scarce. Therefore, the current study is intended to analyse the spatial distribution of unimproved water sources by wealth quintiles at country level and point-of-use treatment practices using nationally representative data. Method: The data of 2016 Ethiopian Demographic and health survey (EDHS) conducted on 16650 households from 643 clusters were used for the analysis. For spatial analysis, the raw and spatially smoothed coverage data was joined to the geographic coordinates based on DHS cluster identification code. Global spatial autocorrelation was performed to analyse whether the pattern of unimproved water coverage is clustered, dispersed, or random across the study areas. Once a positive global autocorrelation was confirmed, a local spatial autocorrelation analysis was applied to detect local clusters. The point-of-use water treatment is analysed based on reported use of either boiling, bleach, filtration or SODIS. Result There were 5005 households using unimproved water sources for drinking purpose. Spatial variation of unimproved water coverage was observed with high coverage observed at Amhara, Afar, Southern Nations Nationalities and People and Somalia regions. Disparity in unimproved water coverage between wealth quintiles was also observed. The reported point-of-use water treatment practices among these households is only 6.24%. The odds of point-of-use water treatment among household heads with higher education status is 2.5 times high (95%CI = 1.43–4.36) compared to those who did not attend education. Conclusion An apparent clustering trend with high unimproved water coverage was observed between regions and among wealth quintiles hence indicates priority areas for future resource allocation and the need for regional and national policies to address the issue. Promoting households to treat water prior to drinking is essential to reduce health problems.

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Geographical heterogeneity and inequality of access to improved drinking water supply and sanitation in Nepal

Cited by 37 publications

References 26 publications

A method for measuring spatial effects on socioeconomic inequalities using the concentration index

A method for measuring spatial effects on socioeconomic inequalities using the concentration index

New Approaches to Monitor Inequalities in Access to Water and Sanitation: The SDGs in Latin America and the Caribbean

Unimproved water sources in Ethiopia: Spatial variation and household point-of-use treatment practice based on 2016 Demographic and Health Survey

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