Sociodemographic patterns of health insurance coverage in Namibia

Abstract

IntroductionHealth insurance has been found to increase healthcare utilisation and reduce catastrophic health expenditures in a number of countries; however, coverage is often unequally distributed among populations. The sociodemographic patterns of health insurance in Namibia are not fully understood. We aimed to assess the prevalence of health insurance, the relation between health insurance and health service utilisation and to explore the sociodemographic factors associated with health insurance in Namibia. Such findings may help to inform health policy to improve financial access to healthcare in the country.MethodsUsing data on 14,443 individuals, aged 15 to 64 years, from the 2013 Namibia Demographic and Health Survey, the association between health insurance and health service utilisation was investigated using multivariable mixed effects Poisson regression analyses, adjusted for sociodemographic covariates and regional, enumeration area and household clustering. Multivariable mixed effects Poisson regression analyses were also conducted to explore the association between key sociodemographic factors and health insurance, adjusted for covariates and clustering. Effect modification by sex, education level and wealth quintile was also explored.ResultsJust 17.5% of this population were insured (men: 20.2%; women: 16.2%). In fully-adjusted analyses, education was significantly positively associated with health insurance, independent of other sociodemographic factors (higher education RR: 3.98; 95% CI: 3.11–5.10; p < 0.001). Female sex (RR: 0.83; 95% CI: 0.74–0.94; p = 0.003) and wealth (highest wealth quintile RR: 13.47; 95% CI: 9.06–20.04; p < 0.001) were also independently associated with insurance. There was a complex interaction between sex, education and wealth in the context of health insurance. With increasing education level, women were more likely to be insured (p for interaction < 0.001), and education had a greater impact on the likelihood of health insurance in lower wealth quintiles.ConclusionsIn this population, health insurance was associated with health service utilisation but insurance coverage was low, and was independently associated with sex, education and wealth. Education may play a key role in health insurance coverage, especially for women and the less wealthy. These findings may help to inform the targeting of strategies to improve financial protection from healthcare-associated costs in Namibia.Electronic supplementary materialThe online version of this article (10.1186/s12939-019-0915-4) contains supplementary material, which is available to authorized users.

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“…Consistent with previous studies [13,[15][16][17], the current study showed that the likelihood of being covered by health insurance was highest among educated women as compared with women with no education. The possible explanation could be educated women have more knowledge about the advantages of health insurance and make informed choices, engage themselves in different knowledge enhancement activities like reading materials, give more concern for their health and insure themselves against the unexpected out-of-pocket payments.…”

“…Even though, health insurance schemes designed to help ease the financial burden on the poorest households, the finding of this study revealed that the odds of health insurance coverage was higher among women in the richest wealth quintile. This finding is consistent with those from other settings elsewhere [13,[15][16][17]26]. This could be households with high wealth quantiles often have more income to afford health insurance premium compared to the poor once.…”

“…Age, level of education, residence, wealth status, travel cost, travel time, exposed to media and occupation of the mother were factors influencing variations in health insurance coverage in Ethiopia [13][14][15][16][17][18][19].…”

Structural Factors Responsible for Universal Health Coverage in Low- and Middle-Income Countries: Results From 118 Countries

“…There are some studies in line with our findings. A study in Nambia concluded that sociodemographic factors (sex, education, and wealth) are associated with universal health care and financial coverage (45). Another study in Ghana also concluded that sociodemographic conditions (elders, women, poor education, and marginalized population) were associated with health services and financial coverage (46).…”

Eliciting Preferences for Health Insurance in Iran Using Discrete Choice Experiment Analysis

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