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

Abstract

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.

Factors influencing HIV Testing among young women aged 15-24 in the 2015-2016 Malawi Demographic and Health Survey

“…The frequency of reading a newspaper or magazine for at least less than a week was more likely to in uence HIV testing. This conforms to other studies that showed increased HIV test uptake with the frequency of reading newspapers or magazines [28] or being able to read compared to those that cannot [29]. The in uence of reading on HIV testing can be explained in terms of educational attainment as the educated can better comprehend health and other information with reasonable deduction.…”

Then and Now: Investigating Anthropometrics and Child Mortality among Females in Malawi

“…However, areas in the northern region had the lowest concentration of obesity. These spatial outcomes may represent many distal and surrogate conditions in areas and how those conditions shape health (BMI) [72]. The higher prevalence of obesity in the areas in the central and southern regions may be a population effect-densely populated areas are likely to have high proportions of obese persons [20].…”

Investigating inequalities in HIV testing in sub-Saharan Africa: spatial analysis of cross-sectional population-based surveys in 25 countries

“…Very few studies have analysed the spatial distribution of these inequalities. To the best of our knowledge, such a local analysis has only been performed in a single country, Malawi 9…”