ArticleBMC public health2025
Understanding economic disparities in elderly health outcomes: a decomposition analysis in Bankura district.
Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundEconomic inequality negatively affects population health by increasing social violence, discrimination, and reduced social trust, while also limiting equitable access to healthcare services. Given these challenges, the present study aims to measure socioeconomic inequality in health outcomes among the elderly population in the Bankura district.
methodsThe present study was conducted using a cross-sectional survey with a multi-stage random sampling design among elderly individuals in the Bankura district of West Bengal. The total sample size for the study was 480. To measure socioeconomic inequality in health outcomes, the Concentration Index (CI) and Concentration Curve (CC) were applied. Additionally, the regression-based Wagstaff decomposition method of the Concentration Index was used to identify factors associated with health inequality and their relative contributions.
resultsThe study findings indicate that 91% of elderly individuals suffer from at least one chronic disease. The Concentration Index values suggest that cholesterol (CI = 0.40), diabetes (CI = 0.29), and hypertension (CI = 0.04) were more concentrated among the wealthier population, whereas bone diseases (CI = -0.11), lung diseases (CI = -0.24), and heart diseases (CI = -0.04) were more prevalent among the poorer population. The decomposition analysis revealed that non-vegetarian food preference (64.5%), being poor (15.4%), smoking (13.2%), alcohol consumption (26.2%), and older age (60 years and above, 3.8%) were the major contributing factors to pro-rich inequality in chronic disease prevalence. Furthermore, the probit regression model indicated that the likelihood of chronic disease increased with age (coefficient = 0.82), being alone (coefficient = 0.32), alcohol consumption (coefficient = 0.37), and smoking (coefficient = 0.21).
conclusionThe study reveals that health inequality was more pronounced among economically disadvantaged individuals due to low levels of education and engagement in unhealthy, risky behaviors. Policymakers should focus on improving health-related infrastructure in rural areas, particularly for the oldest-old population.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.