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

The research team, led by Sarah Derveeuw and Eva Gezels of Ghent University’s Department of Public Health and Primary Care, together with colleagues at the Centre for Cancer Detection in Bruges, took advantage of a rare scientific resource: individually linked population registry, cancer registry, health insurance and administrative socioeconomic records. Rather than surveying a sample and hoping it represents the whole, the investigators assembled a retrospective cohort of essentially every eligible woman aged 31 to 64 residing in Flanders between 2018 and 2023. This population-wide design eliminates the selection biases that plague smaller studies and allows researchers to detect patterns in groups that are often too small or too hard to reach for conventional surveys, including women who never interact with the health system at all.

The study’s central outcome was deliberately strict. A woman was classified as a long-term non-attender if she had no registered cervical screening test of any kind during the entire six-year observation window, a period spanning more than two full screening rounds under Flemish guidelines. Among the 1,220,227 women with complete data, 21.5 percent fell into this category. That figure is striking on its own, but the true analytical power of the study lies in how the researchers dissected it. They organised their analysis around Andersen’s Behavioural Model of Health Services Use, a long-standing framework that sorts the drivers of healthcare utilisation into predisposing factors such as age, migration background, household type, education and occupation; enabling factors such as household income, subsidised insurance status, recent childbirth and contact with a general practitioner; and illness-level factors such as chronic disease and major invalidity.

Using hierarchical multivariable logistic regression, the team estimated the odds of long-term non-attendance associated with each factor while adjusting for all the others, a statistical technique that isolates the independent contribution of every variable. The results delivered an unambiguous headline: nothing predicts screening behaviour better than whether a woman is already plugged into the healthcare system. Women who had recently given birth had 63 percent lower odds of long-term non-attendance compared with other women, with an odds ratio of 0.37, almost certainly because pregnancy and childbirth funnel them through routine medical contacts where screening can be offered or performed. Frequent contact with a general practitioner produced a similar protective pattern, with an odds ratio of 0.54. In other words, every additional touchpoint with primary care appears to act as an implicit gateway to cancer prevention, and women who lack those touchpoints are systematically left behind.

Education emerged as the most powerful socioeconomic determinant, and it did so in a classic gradient. Women with the lowest educational level had 79 percent higher odds of never attending screening across six years compared with the highest-educated group, an odds ratio of 1.79 that remained essentially unchanged after full statistical adjustment. The persistence of this gradient is important because it suggests that education captures something more fundamental than income alone, perhaps health literacy, familiarity with preventive medicine, the ability to navigate administrative systems, or the cultural capital to feel entitled to ask for preventive care. Intriguingly, household income told a much weaker story, showing only a modest and non-graded association with non-attendance. This dissociation between income and education is a technical finding with real policy consequences: simply making screening free or cheap, which Belgium already does, does not neutralise the social stratification of participation.

The study also produced one of its most nuanced results in the domain of migration background. Among first-generation migrant women, those born outside Belgium, elevated odds of non-attendance were largely attenuated once socioeconomic factors were taken into account, implying that their lower participation is substantially explained by the socioeconomic positions they occupy rather than by their origin per se. But the same was not true for the second generation, women born in Belgium to migrant parents. Elevated odds persisted among second-generation women of Maghrebi, Turkish, Asian, Sub-Saharan African and Eastern European origin even after adjustment for education, occupation, income and healthcare contact. That residual excess risk, surviving a battery of statistical controls, points toward mechanisms that administrative data cannot fully capture, including experiences of discrimination, cultural norms around intimate examinations, language and trust, and the specific ways healthcare services are perceived and navigated by ethno-racially minoritised communities.

Several other groups carried independently elevated odds of long-term non-attendance. Older women within the eligible age range were less likely to attend than younger ones, a pattern with direct biological relevance because the risk of cervical cancer and the persistence of high-risk human papillomavirus infections both increase with age. Women living alone had higher odds than those in larger households, consistent with the idea that partners and family members often prompt and accompany preventive care. Receiving an increased reimbursement, the Belgian marker of low income and financial vulnerability, was associated with non-attendance, as were chronic illness and major invalidity status. The latter finding may seem counterintuitive, since chronically ill patients see doctors frequently, but it likely reflects a clinical reality in which care becomes dominated by the presenting condition and preventive services fall by the wayside, a phenomenon researchers describe as preventive care crowding-out.

What makes this study methodologically significant is not only its scale but its data architecture. Linking the national population registry to the Belgian cancer registry, health insurance claims and administrative socioeconomic records allowed the researchers to construct a near-complete picture of each woman’s social circumstances and healthcare behaviour without asking anyone a single question. The authors handled missing data transparently, reporting characteristics for the full population of 1,283,569 women before restricting to complete cases, and they formally assessed multicollinearity among predictors using generalised variance inflation factors, ensuring that the large odds ratios they report are not statistical artefacts of correlated variables. The study was conducted under ethical approval from the Belgian Information Security Committee using pseudonymised data in compliance with the European General Data Protection Regulation.

The implications reach well beyond Flanders. Organised screening programmes, in which women are invited by name at regular intervals, were designed precisely to flatten social gradients in participation, and the Flemish data show that such programmes reduce but do not erase them. The authors argue that equity-oriented strategies should prioritise the women who remain systematically unreached: those with few socioeconomic resources, limited engagement with primary care, and second-generation migrant backgrounds. Concretely, that could mean embedding screening invitations in maternity and postnatal care, training general practitioners to opportunistically offer cytology or human papillomavirus testing during unrelated consultations, deploying self-sampling kits that women can use at home, and designing outreach that is culturally attuned rather than merely translated.

The study also carries a warning for the HPV vaccination era. As vaccinated cohorts age into screening programmes, maintaining high participation among the socially disadvantaged becomes even more critical, because unvaccinated women are not evenly distributed across society and tend to cluster in the very groups least likely to attend. The researchers are careful to note that their work identifies who is left behind, not why, and they call for further research into the specific mechanisms and barriers underlying these inequities to guide tailored programme adaptations. But the population-level message is already clear: a screening programme is only as equitable as its reach, and in Flanders, as in much of the world, that reach still stops short of the women who need it most.

Subject of Research: Sociodemographic and healthcare-access determinants of long-term non-attendance in cervical cancer screening in Flanders, Belgium

Article Title: Determinants of long-term non-attendance in cervical cancer screening in Flanders, Belgium: a retrospective population-wide cohort study using administrative data

Article References: Derveeuw, S., Gezels, E., Hendrickx, M., Kellen, E., Toma, S., Vanthomme, K., & Willems, S. (2026). Determinants of long-term non-attendance in cervical cancer screening in Flanders, Belgium: a retrospective population-wide cohort study using administrative data. International Journal for Equity in Health. https://doi.org/10.1186/s12939-026-03056-x

Image Credits: AI Generated

DOI: 10.1186/s12939-026-03056-x

Keywords: cervical cancer screening, health inequities, social determinants of health, Flanders, Belgium, population-based cohort, Andersen behavioural model, migration background, primary care, HPV, cancer prevention, public health

Healthier SG represents a deliberate shift in how the city-state approaches health. Rather than paying clinics to treat illness after it appears, the programme asks residents to empanel, formally register, with a general practice clinic or a polyclinic, creating a continuity of care relationship intended to catch chronic diseases early and manage them better. It opened to adults aged 60 and above in mid-2023, and eligibility was extended to those aged 40 and older by late the same year. Voluntary empanelment of this kind has been adopted by health systems around the world as a strategy for strengthening primary care, but researchers note that its equity implications, particularly in multi-ethnic Asian populations, have rarely been examined in detail. The Singapore team set out to fill that gap, asking not just whether people enrol, but who makes it through each step of the journey, and who is left behind along the way.

To answer that question, the researchers turned to the Singapore Population Health Studies, drawing on a sample of 3,899 residents aged 40 and above. They framed the analysis using Andersen’s Behavioural Model of Health Services Utilisation, a longstanding framework in health services research that organises the drivers of care use into three categories: predisposing factors such as age, sex, education and ethnicity; enabling factors such as income, housing type and employment; and need factors such as the burden of chronic disease. Engagement with Healthier SG was classified into four sequential stages: people who were unaware of the programme and not enrolled, those who were aware but had not enrolled, those who had enrolled but not completed a screening, and those who had both enrolled and been screened. Using multinomial logistic regression, the team estimated odds ratios and marginal effects, the predicted probabilities of occupying each stage, for every factor.

The headline numbers are striking. Half of the respondents, 50.5 per cent, had never heard of Healthier SG, despite the programme’s nationwide promotion. Only 36.1 per cent had either enrolled or completed at least one of the preventive screenings the programme offers. In other words, barely more than a third of the eligible population had moved beyond the starting line of a scheme designed to reach everyone. For a programme that strips away most of the cost of preventive care, that level of disengagement is a signal that something other than money is shaping behaviour, and the statistical analysis pointed clearly at what.

Socio-economic advantage left a visible fingerprint on every stage of engagement. Older adults, people with higher educational attainment, retirees, and residents living in higher-tier housing were all significantly more likely to both enrol in the programme and complete their screenings. The housing gradient is particularly telling in Singapore’s context, where housing type serves as a widely used proxy for socio-economic status. Residents in larger, higher-value public and private flats navigated the programme more successfully than those in smaller units, suggesting that differences in health literacy, digital access, time flexibility and familiarity with the healthcare system continue to operate even when the price of care has been heavily subsidised. Education, similarly, appeared to function less as a route to affording care than as a route to understanding and trusting it.

Ethnic disparities emerged in a more nuanced pattern. After the researchers adjusted for socio-economic factors, respondents of Indian ethnicity showed lower odds of enrolling in the programme, a gap that persisted even when financial and educational differences were accounted for. Malay respondents, by contrast, showed higher odds of being aware of Healthier SG without actually enrolling, a pattern the authors describe as awareness without conversion. That distinction matters: it suggests that for some communities the barrier is not information but something that happens at the point of deciding to sign up, whether that involves trust in primary care institutions, cultural fit of communication materials, differing health beliefs, or practical frictions in the enrolment process itself. The findings point to the need for culturally responsive outreach rather than a uniform national campaign.

One of the study’s most consequential findings concerns need, the factor that health policy most wants to drive preventive care use. People carrying a higher burden of chronic disease were more likely to complete screenings once they had enrolled, which is exactly what the programme is designed to achieve. But a higher chronic disease burden did not make people any more likely to enrol in the first place. The residents with the greatest clinical need were not gravitating toward the programme on their own. In a voluntary system, the people who stand to gain the most from early detection and continuous management are, it turns out, no more likely to sign up than anyone else, and in some socio-economic groups considerably less likely.

Methodologically, the study’s strength lies in treating engagement as a sequence rather than a single yes-or-no outcome. By modelling four distinct stages with multinomial logistic regression and reporting marginal effects alongside odds ratios, the researchers could show where in the funnel different groups stall. Older, better-educated, more advantaged residents flow through the entire pipeline from awareness to screening. Disadvantaged residents and some ethnic minority groups drop out earliest, most often at the awareness stage itself. That granularity matters for policy, because the remedy for an awareness gap, targeted, culturally attuned communication through trusted community channels, is entirely different from the remedy for an enrolment gap, which may require simplifying registration, offering assistance with sign-up, or building trust through community partnerships.

The authors are careful about what their cross-sectional data can and cannot show. Because the study captures a single point in time during the programme’s early rollout, it cannot establish whether today’s engagement gaps will harden into tomorrow’s health disparities, and they call for longitudinal research to track whether early differences in enrolment and screening translate into differences in disease outcomes over the years ahead. The cohort also represents the population aged 40 and above, the group targeted by the programme, rather than the entire adult population. Still, the direction of the findings is consistent with a growing international literature showing that voluntary, incentive-based preventive care programmes tend to reproduce existing social gradients unless they are actively designed not to.

The broader lesson reaches well beyond Singapore. As health systems worldwide pivot toward prevention, from the United Kingdom’s emphasis on continuity of care to community-based primary care reforms across Asia, voluntary empanelment is becoming a default strategy. Singapore’s experience offers an early warning: universal eligibility and generous subsidies are necessary but not sufficient. Reaching the residents who rarely see a doctor, who live in smaller flats, who have less schooling and who may distrust or simply not encounter official health messaging, requires deliberate, targeted and culturally informed effort. Equity in preventive care, the study concludes, is not achieved at the moment costs are eliminated. It is achieved, or missed, in the accumulation of small frictions and quiet barriers that determine who walks through the door. The measurement of those barriers, stage by stage, is where reform begins.

Subject of Research: Socio-economic and ethnic disparities in preventive care engagement under Singapore's Healthier SG voluntary primary care empanelment programme

Article Title: Beyond financial access: socioeconomic and ethnic disparities in preventive care engagement under Singapore’s Healthier SG programme

Article References: Beyond financial access: socioeconomic and ethnic disparities in preventive care engagement under Singapore’s Healthier SG programme. (n.d.). https://doi.org/10.1186/s12939-026-03028-1

Image Credits: AI Generated

DOI: 10.1186/s12939-026-03028-1

Keywords: Healthier SG, Singapore, preventive care, health equity, primary care reform, voluntary empanelment, Andersen Behavioural Model, socio-economic disparities, ethnic disparities, screening, health policy, public health