The research team, led by Joyce Aputere Ndago of the University for Development Studies in Ghana together with Paul Adjorlolo, Martin Nyaaba Adokiya and Micheal Boah, set out to answer a deceptively simple question: how many households in Sub-Saharan Africa actually use improved water sources and improved sanitation facilities, and what determines whether they do? The distinction between access and use matters more than it might seem. A household may technically live within reach of a borehole or a piped connection, yet rely on untreated surface water for drinking. A latrine may exist on the family compound but serve so many people, or fall into such disrepair, that it fails to protect health. By measuring reported use rather than mere infrastructure presence, the study offers a more honest picture of where the region stands.

The numbers tell a story of partial progress and stubborn gaps. Overall, 76.3 percent of households reported access to and use of improved water sources, a category that includes piped water, boreholes, protected wells and protected springs, as opposed to unimproved sources such as unprotected dug wells, tanker trucks or surface water from rivers and ponds. For sanitation, the picture darkens considerably. Only 56.7 percent of households had access to and used improved toilet facilities, which range from flush toilets connected to sewers or septic systems to improved pit latrines with slabs. When the researchers applied the stricter definition of basic sanitation, meaning an improved toilet that is not shared with other households, the figure collapsed to 35.4 percent. Shared facilities, however well constructed, are considered inadequate under international monitoring standards because they are harder to keep clean, harder to maintain, and often inaccessible to women, children and people with disabilities.

Perhaps the most striking feature of the results is the sheer width of the variation between countries. The regional averages conceal enormous disparities, with some nations achieving high coverage of improved water and sanitation while others lag far behind on both indicators. This heterogeneity is not a statistical curiosity; it is a policy signal. It suggests that national context, governance capacity, investment levels and geographic conditions shape outcomes so strongly that a single regional strategy is unlikely to succeed. Countries that have invested in rural water supply infrastructure, for example, have pulled ahead of neighbors facing comparable income levels, while urbanizing nations face a different challenge: keeping sanitation services ahead of the growth of informal settlements.

To move beyond description, the team turned to multivariable Poisson regression with robust variance, a statistical technique well suited to outcomes that are common in a population. Unlike logistic regression, which can produce inflated and unstable effect estimates when a condition affects more than roughly ten percent of respondents, Poisson regression with robust standard errors yields reliable prevalence ratios even for widespread outcomes such as improved water use. The method allowed the researchers to estimate the independent association of each household characteristic with access and use, while holding the others constant, and to do so across a pooled dataset spanning hundreds of thousands of households with widely differing survey designs.

The regression results converge on a clear set of drivers. Household wealth emerged as one of the most consistent predictors, with richer households substantially more likely to use improved toilets and basic sanitation than the poorest. This gradient is unsurprising in economic terms, since building and maintaining a private flush toilet or septic system requires capital that poor families rarely command, but its persistence across 30 countries underscores how deeply sanitation access is stratified by income. Place of residence was equally significant: urban households consistently outperformed rural ones on sanitation indicators, reflecting both the density of infrastructure in cities and the historical concentration of public investment in urban areas. Rural communities, dispersed across difficult terrain and often far from sewer networks or reliable piped systems, remain the region’s sanitation frontier.

Education told a different, and in some ways more hopeful, story. Educational attainment was significantly associated with access to and use of improved water sources, even after accounting for wealth and residence. This suggests that schooling does something beyond raising income: it shapes household preferences, hygiene knowledge and the perceived value of safe water, influencing decisions about where families draw water and how they treat it. The finding aligns with a broader body of evidence showing that maternal education in particular is among the strongest predictors of child health outcomes in low-income settings. For sanitation, however, wealth and residence dominated, implying that knowledge alone cannot overcome the financial and structural barriers to building a private toilet.

The public health stakes of these gaps are difficult to overstate. Unsafe water and inadequate sanitation are major pathways for diarrheal disease, cholera, typhoid, hepatitis A and a constellation of neglected tropical diseases, including soil-transmitted helminth infections that thrive where open defecation persists. Diarrheal illness remains a leading cause of death among children under five in the region, and repeated infections in early childhood contribute to stunting, cognitive impairment and long-term economic loss. The COVID-19 pandemic added a fresh urgency, as handwashing with soap, one of the simplest infection-control measures, depends on exactly the kind of reliable water access that a quarter of households lack. When 35 percent of households share toilets or rely on unimproved facilities, disease transmission is not an occasional crisis but a constant background condition.

The study’s authors argue that governments in Sub-Saharan Africa should prioritize expanding access to water and sanitation, with particular attention to underserved rural areas and poor households. But they also stress that average coverage figures are not enough: targeted strategies are needed to address the disparities driven by socioeconomic and demographic factors that their analysis exposed. In practice, that means subsidies or financing mechanisms that help the poorest families build and maintain private facilities, rural water supply programs designed for dispersed populations, and sanitation marketing approaches that recognize a toilet is a durable household investment rather than a one-time purchase. It also means monitoring systems that track use and equity, not just the construction of infrastructure, so that progress is measured where it matters most, at the household level.

The findings arrive at a critical moment for the Sustainable Development Goals, whose water and sanitation targets call for universal, safely managed services by 2030. On current evidence, Sub-Saharan Africa is far from that trajectory, and the study’s pooled data make clear that closing the gap will require confronting inequality as directly as building infrastructure. The region’s water story is one of real progress, three-quarters of households now use improved sources, a substantial achievement by historical standards. Its sanitation story is one of unfinished business, with basic sanitation reaching barely a third of households and the poorest, most rural families consistently left behind. The data from 465,208 households make the pattern impossible to ignore, and they give governments, donors and public health agencies a precise map of where the work remains.

Subject of Research: Household access to and use of improved water sources and sanitation facilities across 30 Sub-Saharan African countries

Article Title: Access to and use of improved water and sanitation facilities in Sub-Saharan Africa: Analysis of Demographic and Health Survey Data from 30 countries

Article References: Ndago, J. A., Adjorlolo, P., Adokiya, M. N., & Boah, M. (2026). Access to and use of improved water and sanitation facilities in Sub-Saharan Africa: Analysis of Demographic and Health Survey Data from 30 countries. PLOS Global Public Health, 6(10), e0006195. https://doi.org/10.1371/journal.pgph.0006195

Image Credits: AI Generated

DOI: 10.1371/journal.pgph.0006195

Keywords: Sub-Saharan Africa, water access, sanitation, Demographic and Health Surveys, Sustainable Development Goals, public health, Poisson regression, household wealth, rural-urban disparities, improved water sources, basic sanitation, health equity

The study, published in PLOS Mental Health by Gallen Mlenge, Odass Bilame, and Lutengano Mwinuka, draws on the fifth wave of the Tanzania National Panel Survey, conducted in 2020 and 2021. The panel survey is a household-based instrument designed to be representative of the national population, which makes it a rare and valuable window into health behaviour in a low-income setting where routine administrative data on care-seeking is often incomplete. From the survey, the researchers analysed a sample of 11,891 individuals aged 15 years and above who had non-missing outcome data, making it one of the largest attempts to characterise healthcare utilisation patterns in the Tanzanian population.

One of the central methodological challenges the authors faced is familiar to anyone working on mental health in low- and middle-income countries: population surveys rarely include clinical diagnostic instruments. Instead, the team used a proxy measure. Mental health need was identified through the Washington Group Short Set item on difficulty remembering or concentrating, applied at the severe threshold. This item is a recognised proxy associated with common mental disorders, and while it cannot substitute for a clinical interview, it provides a consistent, internationally comparable indicator that can be embedded in large multipurpose surveys. Using this definition, 54 individuals in the sample were classified as having proxy-identified mental health need, corresponding to a weighted prevalence of 0.45 percent of the adult population.

The outcome measure was deliberately broad. The researchers counted any visit to a formal provider in the four weeks preceding the interview, regardless of the reason for the visit. This captures the overall propensity to engage with the formal health system rather than care-seeking for a specific condition. Overall, weighted formal healthcare utilisation stood at just 19.2 percent, meaning that fewer than one in five Tanzanians aged 15 and above had contacted a formal provider in the previous month. In a country where the burden of disease includes both communicable and increasingly non-communicable conditions, that figure underscores how much of the population remains outside the reach of routine formal care.

To explain who used care and who did not, the authors turned to the Andersen Behavioural Model, a long-standing framework in health services research that organises determinants of utilisation into predisposing characteristics, enabling resources, and need factors. They estimated survey-weighted logistic regressions producing adjusted odds ratios and predicted probabilities. The results revealed a system that sorts people by demography and geography rather than by need. Female sex, older age, specifically 55 years and above, and residence in the Southern Highlands zone were each independently associated with higher utilisation, suggesting that both biological and structural factors shape contact with the health system.

The most striking finding, however, concerned household wealth. Utilisation rose in a strong dose-response gradient across wealth quintiles: the richer the household, the more likely its members were to have visited a formal provider. Individuals in the richest quintile had 2.71 times higher adjusted odds of utilisation compared with those in the poorest quintile. In other words, the ability to pay, and the enabling resources that come with it, such as transport, proximity to facilities, and the capacity to absorb the indirect costs of seeking care, appear to be among the dominant gatekeepers to formal healthcare in Tanzania. This gradient is a direct challenge to the principle of equitable access that underpins universal health coverage ambitions.

Against this backdrop, the finding on mental health need is quietly devastating. Proxy-identified mental health need was not significantly associated with formal healthcare utilisation. The adjusted odds ratio was 1.27, with a 95 percent confidence interval spanning 0.53 to 3.04 and a p-value of 0.588. While the point estimate leans in the direction of slightly higher utilisation among those with identified need, the interval is wide and crosses unity, meaning the data cannot distinguish the effect from no effect at all. People whose survey responses signalled severe difficulty remembering or concentrating were, statistically, no more likely to have seen a formal provider in the previous month than anyone else.

The authors were careful about the limits of that subgroup. Only 54 individuals carried the proxy-identified need flag, and missing outcome data affected 505 individuals in a pattern classified as Missing Not At Random, meaning that whether someone’s outcome was missing was related to the outcome itself. To probe how fragile the subgroup estimates might be, the team conducted an extreme bounds sensitivity analysis. The result was a stark illustration of statistical uncertainty: true utilisation in the subgroup could plausibly range from 2.0 percent to 92.7 percent. The authors therefore describe their findings for the mental health need subgroup as exploratory, a candid caveat that is rare and welcome in this literature.

That honesty matters, because the temptation in global mental health research is often to overread thin data. Here, the study does two things at once. It establishes with reasonable confidence the broad structural determinants of care-seeking in Tanzania, since the full sample of nearly 12,000 people provides substantial statistical power for the wealth, sex, age, and zone effects. At the same time, it demonstrates precisely why mental health need remains nearly invisible in household survey data: the affected group is small, the proxy is coarse, and the missingness is informative. The study is as much a methodological lesson as a substantive one, showing what national panels can and cannot reveal about the health-seeking behaviour of people with mental health conditions.

The policy implications, nonetheless, point in a clear direction. If wealth is the strongest predictor of who reaches a doctor, then removing financial barriers, through mechanisms such as fee exemptions, insurance expansion, or support for indirect costs, should sit at the centre of efforts to make healthcare utilisation more equitable in Tanzania. And if residents of some geographic zones systematically lag behind, then strengthening service availability in lower-utilisation regions becomes an equally urgent priority. For the mental health community specifically, the study suggests that integrating mental health need into general health system planning will require better measurement, larger samples, and data systems that do not lose the very people whose outcomes are hardest to capture. Until then, the quiet finding that mental health need does not move the needle on care-seeking in Tanzania stands as both a data point and a warning about how much the health system, and the surveys that measure it, still miss.

Subject of Research: Determinants of formal healthcare utilisation among adults with and without proxy-identified mental health need in Tanzania

Article Title: Patterns and determinants of formal healthcare utilisation among individuals with and without proxy-identified mental health need in Tanzania: A cross-sectional analysis of the National Panel Survey

Article References: Mlenge, G., Bilame, O., & Mwinuka, L. (2026). Patterns and determinants of formal healthcare utilisation among individuals with and without proxy-identified mental health need in Tanzania: A cross-sectional analysis of the National Panel Survey. PLOS Mental Health, 3(9), e0000644. https://doi.org/10.1371/journal.pmen.0000644

Image Credits: AI Generated

DOI: 10.1371/journal.pmen.0000644

Keywords: Tanzania, healthcare utilisation, mental health, health equity, household wealth, National Panel Survey, Washington Group Short Set, Andersen Behavioural Model, low- and middle-income countries, cross-sectional analysis, health policy, survey methods

Stunting, defined as height-for-age falling more than two standard deviations below the benchmarks set by the World Health Organization’s child growth standards, is not simply a matter of being small. It reflects months or years of inadequate nutrition, repeated infection, and chronic stress during the most sensitive window of human development. Its consequences cascade: stunted children face elevated risks of cognitive impairment, weakened immunity, poorer school performance, and reduced adult earning capacity. That is why international health agencies treat stunting reduction as a central yardstick for progress on nutrition and equity.

The research team drew on two large, nationally representative household surveys: the 2016 South African Demographic and Health Survey, which measured 1,468 children under five, and the 2023 Lesotho Demographic and Health Survey, covering 1,574 children. Because these surveys combine standardized anthropometric measurements with detailed household records of income, education, residence, and maternal health, they allow researchers to place every measured child on a national socioeconomic spectrum, a powerful but data-hungry form of epidemiological mapping.

The headline numbers are sobering. In Lesotho, 35.6 percent of children under five were stunted, with a 95 percent confidence interval of 32.6 to 38.7 percent. South Africa fared somewhat better at 27.4 percent, with a confidence interval of 24.3 to 30.7 percent. These figures persist at high levels despite years of national nutrition programs, school feeding schemes, and social grants, suggesting that broad interventions alone are not reaching the households where growth failure begins.

The study’s methodological core lies in how it quantifies inequality. The team used the Erreygers corrected concentration index, a refinement of the standard concentration index designed to handle bounded health outcomes and produce more reliable rankings. In both countries the index was negative and statistically significant: −0.1442 in South Africa and −0.1818 in Lesotho, each at p less than 0.001. A negative value in this framework signals pro-poor inequality, meaning stunting is concentrated among children from poorer households rather than spread evenly across the wealth distribution.

The concentration curves make the pattern vivid. When children are ranked from poorest to richest and cumulative stunting is plotted against cumulative population, the curves for both countries sag above the diagonal of equality, showing that the poorest children accumulate a disproportionate share of the stunting burden. In Lesotho the deviation was even steeper than in South Africa, indicating that the wealth gradient in undernutrition is more pronounced in the smaller, mountainous kingdom.

Geography deepens the divide. In South Africa, stunted children were significantly more likely to live in rural areas than in urban ones, with the analysis yielding a coefficient of 0.1015 at p less than 0.05. This rural penalty likely reflects a constellation of disadvantages: longer distances to clinics and markets, higher food prices for staple goods, limited access to clean water and sanitation, and thinner coverage of early childhood services. In a country with one of the most developed economies in Africa, the persistence of rural nutritional deficits underscores how uneven development can be.

To move beyond description, the researchers deployed multivariable decomposition analysis, a technique borrowed from economics that splits an observed inequality into the contributions of its underlying factors. The results pointed to three dominant levers: maternal educational attainment, household wealth, and rural residence. Mothers with more education, the analysis implies, tend to have better access to nutritional knowledge, health services, and economic resources, all of which protect against growth faltering. Household wealth operates through food security, housing quality, and healthcare access, while rurality compounds both.

The authors argue that the findings carry direct policy weight. Strengthening integrated nutrition and social protection policies, they conclude, is critical to achieving equitable improvements in child nutritional outcomes in both countries. In practice, that means pairing food and micronutrient programs with investments in girls’ and women’s schooling, deepening child support grants and other cash-transfer systems, and deliberately targeting rural and remote communities where the burden is heaviest. Universal approaches that treat all children alike, the data suggest, will leave the poorest behind.

For a region where stunting remains stubbornly high despite decades of intervention, the study reframes the problem: this is not merely a question of food supply but of social structure. Until the economic gradient in childhood nutrition is flattened, the tallest children in South Africa and Lesotho will, in a statistical sense, keep growing up on the wealthier side of the line. The research, published open access in Discover Social Science and Health, gives policymakers a precise map of where and among whom the next generation’s growth potential is being lost, and a measured argument for why equity must move to the center of the nutrition agenda.

Subject of Research: Socio-economic inequalities in childhood stunting among children under five in South Africa and Lesotho

Article Title: Socio-economic inequalities in childhood stunting among children under five years in South Africa and Lesotho

Article References: Sello, M., Musonda, E., Mubita, A., Fikani, N., & Phiri, M. (2026). Socio-economic inequalities in childhood stunting among children under five years in South Africa and Lesotho. Discover Social Science and Health. https://doi.org/10.1007/s44155-026-00491-7

Image Credits: AI Generated

DOI: 10.1007/s44155-026-00491-7

Keywords: childhood stunting, South Africa, Lesotho, socio-economic inequality, malnutrition, concentration index, decomposition analysis, maternal education, household wealth, rural health, child nutrition, demographic and health surveys