The research, led by Anoop Jain of Boston University School of Public Health together with Rockli Kim and S. V. Subramanian of Harvard University, analyzed data from the Longitudinal Aging Study in India, or LASI, a nationally representative survey covering all 36 states and Union Territories except Sikkim. From more than 72,000 respondents, the team focused on 63,564 women and men above the age of 45 who had complete information on the exposures and outcomes of interest. These individuals lived in 2,439 wards and villages, giving the researchers an unusually rich window into how conditions vary not just between people but between the communities they inhabit.

The methodological core of the study is its multilevel design. Rather than treating each respondent as an isolated data point, the researchers built a three-level statistical model in which individuals were nested within households and communities, and communities within states. The exposure of interest was the modeled proportion of people in each community living in households without any toilet, estimated using a Markov Chain Monte Carlo approach to produce an unconfounded community-level measure. Communities were then sorted into quintiles of toilet coverage, ranging from the lowest quintile, where fewer than 62 percent of residents had a toilet, to the highest, where more than 99 percent did.

Depression was measured with four widely used instruments. The first was the ten-item Center for Epidemiological Studies-Depression scale, known as CES-D, which captures symptoms such as feeling depressed, loneliness, low energy, and trouble concentrating over the past week; a score of four or above classified a respondent as having depressive symptoms. The remaining three measures came from the Composite International Diagnostic Interview Short Form, or CIDI-SF, a validated diagnostic screening tool translated into sixteen Indian regional languages. Respondents were classified as having probable major depression using three thresholds: the standard CIDI-SF cutoff, plus two stricter definitions requiring three or five of seven additional symptoms. The mean prevalence of CES-D symptoms in the sample was 28.1 percent, while probable major depression ranged from 7.1 to 8.9 percent depending on the definition used.

The results were striking. After adjusting for age, sex, marital status, education, caste, wealth, place of residence, and even the type of toilet in the respondent’s own household, people living in communities with the lowest toilet coverage had 38 percent higher odds of depressive symptoms on the CES-D scale than those in communities with the highest coverage, with an odds ratio of 1.38 and a 95 percent confidence interval of 1.08 to 1.76. The associations were even stronger for probable major depression: odds ratios of 1.58 for the standard CIDI-SF measure, 1.56 for the three-symptom definition, and 1.72 for the five-symptom definition, all statistically significant. Notably, the highest-coverage communities showed odds ratios close to one, suggesting no elevated risk relative to the reference group.

Perhaps the most provocative finding is what the study did not find. When the researchers examined the respondents’ own household toilet status, the associations with depression were weak and statistically indistinguishable from no effect. The odds ratios for living in a no-toilet household were 1.02 for CES-D and 0.99 for CIDI-SF. In other words, the community context appeared to matter more than the private one. This is a novel result, and the authors propose a plausible mechanism: in communities where nearly everyone lacks a toilet, residents have nowhere else to go, unable to borrow a neighbor’s facility or reach a public toilet block. In better-off communities, households without toilets may still access shared or public options, buffering them from the worst consequences of deprivation.

The cross-level interaction analysis added further nuance. Although none of the formal interaction terms reached statistical significance, the raw prevalence of depressive symptoms rose consistently across all household toilet types as community coverage fell. Among people with twin pit toilets, CES-D prevalence climbed from 12.6 percent in the highest-coverage communities to 27.0 percent in the lowest. Among those with pit latrines, CIDI-SF prevalence rose from 6.5 to 10.5 percent, and even among households with flush toilets, the three-symptom depression measure increased from 6.1 to 9.5 percent. The pattern suggests that a private toilet may offer less protection when the surrounding environment remains visibly degraded.

Why would community sanitation leave such a deep imprint on mental health? The authors point to several candidate pathways rooted in social science theory. One is spatial stigma: the idea that people living in visibly deprived places are marked by where they live, eroding their sense of self-worth, a phenomenon previously linked to depression in Japan and in Mumbai’s legally excluded settlements. Another draws on the broken windows hypothesis, in which visible signs of disorder, here open fecal contamination, signal that a place is neglected and uncontrolled, a perception consistently associated with psychological distress. A third pathway involves social division: sanitation programs such as Community-Led Total Sanitation have explicitly encouraged the use of shame to end open defecation, potentially fracturing community cohesion. The absence of sanitation is also associated with elevated risk of non-partner sexual violence, itself a driver of adverse mental health outcomes.

The study has honest limitations. The data are cross-sectional, collected in 2017 and 2018, so reverse causation and unmeasured confounding cannot be ruled out; communities with poor sanitation likely face other simultaneous deprivations, from poor schooling to caste-based discrimination, that the models could only partially capture. Toilet coverage has also expanded across India since the survey, meaning the analysis may overestimate current deprivation. LASI additionally does not ask whether people without household toilets use community or public facilities as substitutes. The authors call for future survey waves to probe these mechanisms directly, including questions on sanitation-related shame, visual disorder, and social division, and suggest that qualitative methods already used to study spatial stigma in India could illuminate the lived experience behind the statistics.

The stakes are enormous. India’s population over sixty is projected to double from 149 million in 2022 to 347 million by 2050, and 34.7 percent of those over sixty already report difficulty walking 100 yards, meaning many older adults spend most of their time within their immediate neighborhood. If the community around them is saturated with open defecation and the stigma it carries, their mental health may bear the cost. The authors argue that improving community-wide toilet coverage, not merely distributing household latrines, could become a concrete strategy for depression prevention, one that fits within India’s National Program for the Health Care of the Elderly and its vision of a society for all ages. In a field where mental health interventions often focus on the individual, this study is a reminder that sometimes the most powerful medicine for the mind is the environment outside the front door.

Subject of Research: The association between community-level toilet deprivation and depression among older adults in India

Article Title: Association between community toilet deprivation and depression among older adults in India: a multilevel analysis of the Longitudinal Aging Study in India from 2017-2018

Article References: Jain, A., Kim, R., & Subramanian, S. V. (2026). Association between community toilet deprivation and depression among older adults in India: a multilevel analysis of the Longitudinal Aging Study in India from 2017-2018. GeroScience. https://doi.org/10.1007/s11357-026-02537-9

Image Credits: AI Generated

DOI: 10.1007/s11357-026-02537-9

Keywords: sanitation, depression, older adults, India, LASI, multilevel analysis, built environment, mental health, toilet coverage, spatial stigma, public health, aging