Abstract:Many program implementers have difficulty collecting and analyzing data on program beneficiaries’ wealth because a large number of survey questions are required to construct the standard wealth index. We created country-specific measures of household wealth with as few as 6 questions that are highly reliable and valid in both urban and rural contexts.
“…Each household was categorized as being within a specific wealth quintile based on national-level wealth index cutoffs, which were estimated using the EquityTool developed by the Social Franchising Metrics Working Group (https://www.equitytool.org/development/). In the analyses, the lowest two wealth quintiles and highest two wealth quintiles were used as a proxy to denote households of lower socioeconomic status and higher socioeconomic status respectively [22]. We assessed whether each household was headed by a female or male based on participant responses.…”
Section: Equity Across Vulnerable Groupsmentioning
Few rural sanitation programs have documented large increases in sanitation coverage or have assessed if interventions equitably increase sanitation coverage for vulnerable groups. We characterize the impact of the Sustainable Sanitation and Hygiene for All (SSH4A) approach on key program WASH (water, sanitation, and hygiene) indicators, and also assess if these increases in WASH coverage are equitably reaching vulnerable groups. The SSH4A approach was administered in 12 program areas in 11 countries, including Bhutan, Ethiopia, Ghana, Indonesia, Kenya, Mozambique, Nepal, South Sudan, Tanzania, Uganda, and Zambia. Repeated cross-sectional household surveys were administered over four rounds at annual follow-up rounds from 2014 to 2018. Surveys were conducted in an average of 21,411 households at each round of data collection. Overall, sanitation coverage increased by 53 percentage points between baseline and the final round of data collection (95% CI: 52%, 54%). We estimate that 4.8 million people gained access to basic sanitation in these areas during the project period. Most countries also demonstrated movement up the sanitation ladder, in addition to increases in handwashing stations and safe disposal of child feces. When assessing equity—if sanitation coverage levels were similar comparing vulnerable and non-vulnerable groups—we observed that increases in coverage over time were generally comparable between vulnerable groups and non-vulnerable groups. However, the increase in sanitation coverage was slightly higher for higher wealth households compared to lower wealth households. Results from this study revealed a successful model of rural sanitation service delivery. However, further work should be done to explore the specific mechanisms that led to success of the intervention.
“…Each household was categorized as being within a specific wealth quintile based on national-level wealth index cutoffs, which were estimated using the EquityTool developed by the Social Franchising Metrics Working Group (https://www.equitytool.org/development/). In the analyses, the lowest two wealth quintiles and highest two wealth quintiles were used as a proxy to denote households of lower socioeconomic status and higher socioeconomic status respectively [22]. We assessed whether each household was headed by a female or male based on participant responses.…”
Section: Equity Across Vulnerable Groupsmentioning
Few rural sanitation programs have documented large increases in sanitation coverage or have assessed if interventions equitably increase sanitation coverage for vulnerable groups. We characterize the impact of the Sustainable Sanitation and Hygiene for All (SSH4A) approach on key program WASH (water, sanitation, and hygiene) indicators, and also assess if these increases in WASH coverage are equitably reaching vulnerable groups. The SSH4A approach was administered in 12 program areas in 11 countries, including Bhutan, Ethiopia, Ghana, Indonesia, Kenya, Mozambique, Nepal, South Sudan, Tanzania, Uganda, and Zambia. Repeated cross-sectional household surveys were administered over four rounds at annual follow-up rounds from 2014 to 2018. Surveys were conducted in an average of 21,411 households at each round of data collection. Overall, sanitation coverage increased by 53 percentage points between baseline and the final round of data collection (95% CI: 52%, 54%). We estimate that 4.8 million people gained access to basic sanitation in these areas during the project period. Most countries also demonstrated movement up the sanitation ladder, in addition to increases in handwashing stations and safe disposal of child feces. When assessing equity—if sanitation coverage levels were similar comparing vulnerable and non-vulnerable groups—we observed that increases in coverage over time were generally comparable between vulnerable groups and non-vulnerable groups. However, the increase in sanitation coverage was slightly higher for higher wealth households compared to lower wealth households. Results from this study revealed a successful model of rural sanitation service delivery. However, further work should be done to explore the specific mechanisms that led to success of the intervention.
“…Another set of researchers in Zambia built an alternative index without food-related variables (which may have affected tuberculosis outcomes of interest directly) and found no significant difference with the wealth index using all variables (Boccia et al 2013). A low-to-moderate effect is supported by a 10-country World Bank comparison of three alternative indices that exclude direct determinants of health and factors provided at the community-level, in which only 18% of households were categorized in a different wealth quintile with most of these shifting to an adjacent quintile (Houweling et al 2003); as well as the use of a simplified asset list dropping various country-specific, urban-rural specific, and agricultural questions with 16 surveys finding inter-quintile agreement ranging from 75 to 83% (Chakraborty et al 2016).…”
Section: Robustness To Changes In the Asset MIXmentioning
Monitoring progress towards the Sustainable Development Goals by 2030 requires the global community to disaggregate targets along socioeconomic lines, but little has been published critically analyzing the appropriateness of wealth indices to measure socioeconomic status in low-and middle-income countries. This critical interpretive synthesis analyzes the appropriateness of wealth indices for measuring social health inequalities and provides an overview of alternative methods to calculate wealth indices using data captured in standardized household surveys. Our aggregation of all published associations of wealth indices indicates a mean Spearman's rho of 0.42 and 0.55 with income and consumption, respectively. Context-specific factors such as country development level may affect the concordance of health and educational outcomes with wealth indices and urbanrural disparities can be more pronounced using wealth indices compared to income or consumption. Synthesis of potential future uses of wealth indices suggests that it is possible to quantify wealth inequality using household assets, that the index can be used to study SES across national boundaries, and that technological innovations may soon change how asset wealth is measured. Finally, a review of alternative approaches to constructing household asset indices suggests lack of evidence of superiority for count measures, item response theory, and Mokken scale analysis, but points to evidence-based advantages for multiple correspondence analysis, polychoric PCA and predicted income. In sum, wealth indices are an equally valid, but distinct measure of household SES from income and consumption measures, and more research is needed into their potential applications for international health inequality measurement.
“…Using the EquityTool, clients were asked a shortened form of questions about their household assets to assess relative wealth benchmarked to the wealth index from the most recent DHS surveys in Pakistan and Uganda (Chakraborty et al. ). (These questionnaires can be found online at http://www.equitytool.org.)…”
The Method Information Index (MII) is calculated from contraceptive users’ responses to questions regarding counseling content—whether they were informed about methods other than the one they received, told about method‐specific side effects, and advised what to do if they experienced side effects. The MII is increasingly reported in national surveys and used to track program performance, but little is known about its properties. Using additional questions, we assessed the consistency between responses and the method received in a prospective, multicountry study. We employed two definitions of consistency: (1) presence of any concordant response, and (2) absence of discordant responses. Consistency was high when asking whether users were informed about other methods and what to do about side effects. Responses were least consistent when asking whether side effects were mentioned. Adjusting for inconsistency, scores were up to 50 percent and 30 percent lower in Pakistan and Uganda, respectively, compared to unadjusted MII scores. Additional questions facilitated better understanding of counseling quality.
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