The Global Multidimensional Poverty Index, developed by OPHI and the United Nations Development Programme, has reshaped how governments and researchers think about deprivation since its launch in 2010. By combining indicators of health, education, and living standards, it complements income-based measures and has informed policies aligned with the Sustainable Development Goals across more than one hundred countries. Yet the Global MPI was engineered for acute poverty. Its housing indicators, such as access to clean cooking fuel, improved sanitation, electricity, and adequate building materials, are calibrated to detect subsistence-level deficits. The 2024 edition covers 112 countries, of which only four are high-income, and in wealthier settings the index’s thresholds often fail to register the subtler deprivations that constrain well-being: unaffordable rents, insecure tenure, poor thermal comfort, or neighborhoods cut off from opportunity.

The conceptual foundation of the new proposal is the United Nations Committee on Economic, Social and Cultural Rights’ 1991 definition of adequate housing, which identifies seven core elements: security of tenure; availability of services, materials, facilities, and infrastructure; affordability; habitability; accessibility; location; and cultural adequacy. The authors distill these into twelve indicators organized around five measurable subdimensions, deliberately excluding cultural adequacy and accessibility from the core index. Cultural adequacy, they argue, is too subjective and context-dependent to standardize, while accessibility needs, such as adaptations for household members with disabilities, apply only to a subset of households and are better handled as disaggregation variables than as universal index components.

One of the most striking contributions is the treatment of housing occupancy insecurity. The proposed composite indicator integrates irregular or informal tenure, payment-related insecurity, and prospective exposure to eviction, treating them as facets of a single underlying condition rather than separate deprivations. The evidence base for this choice is sobering. Prindex data show that perceived tenure insecurity has risen sharply in recent years, particularly in upper-middle- and high-income countries, and that in 2024 only 44 percent of adults across 108 countries considered themselves owners or joint owners of their primary residence, down from 49 percent in 2020. Habitat for Humanity estimates that more than 20 percent of the world’s population struggles to remain in their homes and more than 70 percent lack legal documentation of their property rights.

Eviction, the sharpest expression of tenure insecurity, carries consequences that ripple far beyond the loss of shelter. Research in the United States links eviction to heightened poverty risk, homelessness, adverse health outcomes, reduced earnings, and lasting damage to credit records, and children account for four out of every ten people threatened with eviction each year. Yet reliable eviction data are notoriously scarce. Administrative statistics are fragmented, often capturing only early procedural stages, and household surveys systematically underrepresent those who have been evicted. The authors propose a direct survey question on eviction risk, modeled on instruments such as the United States Household Pulse Survey, as a feasible way to capture this dimension. Notably, the indicator is designed to distinguish deprivation from lifestyle: it targets households that lack both ownership and any legally recognized secure tenure, avoiding the misclassification of voluntary renters, a group that includes many young, mobile professionals.

Affordability receives equally careful treatment. Housing cost overburden, already a standardized metric in the European Union through the EU-SILC survey, measures the share of household disposable income absorbed by housing costs. The scale of the problem is global: Harvard’s Joint Center for Housing Studies reports that 31.5 percent of United States households spend more than 30 percent of income on housing, while UN-Habitat finds that 55.4 percent of households in Sub-Saharan Africa exceed the same threshold. Because many surveys used for poverty measurement lack reliable income data, the authors recommend expenditure-share or residual-income approaches consistent with European and OECD practice, while acknowledging the conceptual tension this introduces with the capability framework that underpins most multidimensional poverty indices.

The module also modernizes the housing dimension for the digital age. Limited access to digital communication and information joins the indicator set, reflecting how connectivity now shapes education, employment, financial inclusion, and social participation. Internet usage exceeds 90 percent in high-income countries but falls to just 25 percent in low-income countries, and housing characteristics such as tenure insecurity and infrastructure quality can prevent households from investing in reliable service. Evidence from deprived communities shows that introducing household internet access improves mental well-being, social connectedness, and employment prospects, particularly among the elderly and those with low educational attainment. By focusing on household-level infrastructure rather than digital literacy, the indicator captures structural barriers without straying beyond the housing dimension.

Physical conditions remain central to the proposal. Overcrowding is measured through two complementary standards: a room-based threshold of more than one person per room and minimum floor-area benchmarks drawn from recent research on spatial requirements, proposing 30 square meters for single-person households, 45 for couples, and 60 for households of three or more. The health stakes are well documented, from the transmission of infectious diseases to persistent negative effects on children’s academic achievement and behavior. Inadequate housing conditions, including dampness, leaks, and structural damage, are captured through a combination of interviewer observation and self-reported questions with a one-year reference period, a design choice that catches seasonal problems such as rain-driven leaks. Thermal adequacy is framed neutrally as protection against both cold and heat, ensuring relevance in tropical climates where cooling, not heating, is the primary concern, a critical distinction given that energy poverty now affects roughly one in ten low-income households even in affluent Northern European countries.

The proposal extends beyond the front door to the neighborhood itself, incorporating indicators of crime context and environmental quality. Decades of research on neighborhood effects, including landmark studies tracking families who moved from extreme-poverty areas, show that children exposed to higher-opportunity neighborhoods experience lasting gains in education and earnings, while local crime depresses mental health and life satisfaction even among those never directly victimized. Environmental indicators cover pollution, water reliability, waste management, and access to services, with the authors noting that self-reported low water pressure correlates strongly with illness across multiple countries. Methodological honesty pervades the paper: the authors flag recall bias, seasonality, urban-rural asymmetries, and the risk of double counting, and they recommend excluding crime indicators where objective data are unavailable or unreliable.

The authors are candid about the module’s limitations. It has not yet been empirically tested, and its thresholds, potential redundancy with existing dimensions, and sensitivity to context all require validation across countries. Homelessness, which a systematic review links to mortality rates between three and eleven times higher than those of housed populations in high-income countries, remains beyond the reach of household surveys and demands complementary data strategies. Cultural adequacy awaits deeper treatment. Even so, the paper represents a significant step toward poverty measurement that reflects how deprivation actually manifests in middle- and high-income societies, where the housing crisis is less about missing walls and more about the precarity of the ones people live behind. If adopted, the module could give policymakers a standardized, comparable lens on the housing deprivations that income statistics alone will never reveal.

Subject of Research: A proposed survey module for measuring housing and essential services deprivation in multidimensional poverty indices for higher human development countries

Article Title: Housing and Access to Essential Services Indicators: a Proposed Survey Module for Multidimensional Poverty Measurement

Article References: Conconi, A., & Serio, M. (2026). Housing and Access to Essential Services Indicators: a Proposed Survey Module for Multidimensional Poverty Measurement. Social Indicators Research, 185(1), Article 1. https://doi.org/10.1007/s11205-026-03907-8

Image Credits: AI Generated

DOI: 10.1007/s11205-026-03907-8

Keywords: multidimensional poverty, housing deprivation, survey methodology, tenure security, housing affordability, eviction, sanitation, digital connectivity, overcrowding, energy poverty, neighborhood effects, social indicators

The study, published in Discover Mental Health, was conducted by Md Salek Miah and Md Jamal Uddin of the Biostatistics, Epidemiology, and Public Health Research Team in the Department of Statistics at Shahjalal University of Science and Technology in Sylhet, Bangladesh. The researchers drew on data from the 2022 Bangladesh Demographic and Health Survey, one of the most methodologically rigorous household surveys conducted in the developing world. Their analytical sample included 18,987 ever-married women between the ages of 15 and 49 years, a population chosen because reproductive-age women in Bangladesh face well-documented pressures ranging from early marriage and childbearing to intimate partner violence, all of which intersect with mental health. By anchoring their analysis in a survey of this scale and quality, the authors were able to move beyond the small convenience samples that dominate the digital mental health literature.

Methodologically, the study is notable for its use of two validated clinical screening instruments. Symptoms of depression were measured with the nine-item Patient Health Questionnaire, widely regarded as a reliable and feasible tool for population-based screening, while anxiety symptoms were captured with the seven-item Generalized Anxiety Disorder scale. Both instruments categorize respondents according to symptom severity, allowing the researchers to identify women whose scores crossed clinically meaningful thresholds. Digital connectivity was operationalized along three distinct dimensions: internet use, broader information and communication technology usage, and ownership of ICT devices such as mobile phones. This distinction matters, the authors argue, because access to technology is not a single variable but a bundle of exposures, and different forms of access may carry different psychological implications for women navigating constrained social environments.

The headline prevalence figures provide important context for interpreting the associations. Overall, 4.8 percent of the women surveyed showed symptoms of depression, while 4.1 percent exhibited symptoms of anxiety. These population-level rates appear modest compared with high-income countries, but the researchers emphasize that the burden is far from evenly distributed. To estimate the relationship between digital connectivity and mental health symptoms, the team fitted survey-weighted multivariable logistic regression models, adjusting for potential confounding factors and checking for multicollinearity using variance inflation factors. Survey weighting ensured that the estimates reflected the national population rather than the composition of the sample, and stratified analyses by place of residence allowed rural and urban patterns to be compared directly.

The results revealed striking geographic heterogeneity. Among rural women, ICT use was significantly associated with higher odds of depression symptoms, with an adjusted odds ratio of 1.38 and a 95 percent confidence interval of 1.12 to 1.69. In plain terms, rural women who engaged with information and communication technology were roughly 38 percent more likely to screen positive for depression than comparable rural women who did not, after accounting for other measured factors. The confidence interval excludes the null value, indicating a statistically robust association, though the cross-sectional design means the direction of causality cannot be established. It is equally plausible that women experiencing depressive symptoms turn to technology in different ways than women without symptoms, or that unmeasured social circumstances drive both technology use and mental distress.

In urban Bangladesh, the pattern shifted from use to ownership. Among city-dwelling women, higher ICT ownership was associated with depression symptoms, with an adjusted odds ratio of 1.81 and a confidence interval of 1.01 to 3.25, and with anxiety symptoms, with an adjusted odds ratio of 2.11 and a confidence interval of 1.14 to 3.92. Urban women who owned more digital devices thus faced roughly twice the odds of anxiety symptoms compared with their peers. The authors suggest that in urban environments, where connectivity is nearly universal, the mere fact of device ownership may mark deeper stratification in social comparison, economic pressure, or exposure to online stressors. In rural areas, by contrast, where connectivity remains a scarcer resource, the act of using technology itself may differentiate women in ways that correlate with psychological strain.

Perhaps the most visually compelling aspect of the study is its spatial analysis at the divisional level. Bangladesh is divided into eight administrative divisions, and the researchers found that mental health burdens clustered in specific regions. The digitally connected divisions of Dhaka, Chattogram, Sylhet, and Barishal showed high mental health burden, while Rangpur stood out as a region with both low digital access and a lower mental health burden. Rajshahi also displayed lower digital access and distinct mental health patterns. This inverse geography, in which the most connected parts of the country carry the heaviest psychological load, adds a provocative dimension to debates about digital development. The authors argue that these patterns reveal significant rural-urban and geographic inequities and underscore the need for region-specific, equity-oriented digital mental health interventions rather than one-size-fits-all national policies.

The findings arrive at a moment when global health policy is increasingly framing digital access as a development goal in its own right. The researchers connect their work to the United Nations Sustainable Development Goals, particularly SDG 3 on health and well-being, and argue that combining mental health progress with gender-sensitive and geographically targeted digital strategies is essential for advancing women’s mental well-being. Their analysis situates digital access within broader negotiations of women’s health, noting that in Bangladesh, as in much of South Asia, women’s technology use is mediated by household power dynamics, education, income, and, in some contexts, exposure to intimate partner violence. A woman’s phone can be a lifeline, a surveillance tool wielded against her, or both at once, and population surveys can only partially disentangle these dynamics.

Several limitations temper the conclusions, and the authors are appropriately measured in their framing. The data are cross-sectional, so associations cannot be interpreted as causal effects; women with depression or anxiety may use or own technology differently because of their symptoms rather than the reverse. The BDHS instruments capture symptoms through screening questionnaires rather than clinical diagnosis, and the study population was restricted to ever-married women, leaving unmarried women outside the analytical frame. Residual confounding by socioeconomic status, marital quality, and exposure to violence cannot be excluded. Nevertheless, the sheer sample size, the national representativeness, the use of validated screening tools, and the explicit rural-urban stratification make this study a valuable benchmark for South Asian digital mental health research, a field that has long been dominated by evidence from wealthier nations.

For policymakers in Bangladesh and beyond, the message is not that connectivity harms women, but that the mental health implications of digital life are unevenly distributed across geography, gender, and social position. As governments invest in broadband expansion and smartphone adoption accelerates, the authors contend that digital strategies must be designed with women’s specific vulnerabilities and contexts in mind. The paradox highlighted by this research, that the most digitally saturated divisions of Bangladesh show the greatest mental health burden while the least connected regions show less, should serve as a caution against assuming that technological progress automatically translates into psychological well-being. What is needed, the study concludes, is a new generation of interventions that treat digital access as one strand within the wider fabric of women’s health, equity, and social change.

Subject of Research: Digital connectivity and mental health symptoms among ever-married women in Bangladesh

Article Title: Digital connectivity and mental health symptoms among women in Bangladesh: a rural–urban perspective

Article References: Miah, M. S., & Uddin, M. J. (2026). Digital connectivity and mental health symptoms among women in Bangladesh: a rural–urban perspective. Discover Mental Health. https://doi.org/10.1007/s44192-026-00591-5

Image Credits: AI Generated

DOI: 10.1007/s44192-026-00591-5

Keywords: digital connectivity, mental health, Bangladesh, depression, anxiety, women's health, ICT, rural-urban disparities, spatial inequality, BDHS 2022, public health, SDG 3