Evidence map›Paper›PMID 35291975›Full record

ArticleBMC public health2022

Decomposing urban-rural differences in multimorbidity among older adults in India: a study based on LASI data.

Shekhar Chauhan, Shobhit Srivastava, Pradeep Kumar, Ratna Patel

Open access · goldAbstract read
In one paragraph

Article in BMC public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
4.4field-weighted citation impact, top 5% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 29 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

Shekhar ChauhanDepartment of Family and Generations, International Institute for Population Sciences, Mumbai, India.
Shobhit SrivastavaResearch Scholar, International Institute for Population Sciences, Mumbai, India.
Pradeep KumarConsultant- Research & Data Analysis, Population Council India Office, Zone 5A, India Habitat Centre, Lodi Road, 110003, New Delhi, India.
Ratna PatelDepartment of Public Health and Mortality Studies, International Institute for Population Sciences, Mumbai, India. ratnapatelbhu@gmail.com.
International Institute for Population Sciences · INPopulation Council · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMultimorbidity is defined as the co-occurrence of two or more than two diseases in the same person. With rising longevity, multimorbidity has become a prominent concern among the older population. Evidence from both developed and developing countries shows that older people are at much higher risk of multimorbidity; however, urban-rural differential remained scarce. Therefore, this study examines urban-rural differential in multimorbidity among older adults by decomposing the risk factors of multimorbidity and identifying the covariates that contributed to the change in multimorbidity.

methodsThe study utilized information from 31,464 older adults (rural-20,725 and urban-10,739) aged 60 years and above from the recent release cross-sectional data of the Longitudinal Ageing Study in India (LASI). Descriptive, bivariate, and multivariate decomposition analysis techniques were used.

resultsOverall, significant urban-rural differences were found in the prevalence of multimorbidity among older adults (difference: 16.3; p < 0.001). The multivariate decomposition analysis revealed that about 51% of the overall differences (urban-rural) in the prevalence of multimorbidity among older adults was due to compositional characteristics (endowments). In contrast, the remaining 49% was due to the difference in the effect of characteristics (Coefficient). Moreover, obese/overweight and high-risk waist circumference were found to narrow the difference in the prevalence of multimorbidity among older adults between urban and rural areas by 8% and 9.1%, respectively. Work status and education were found to reduce the urban-rural gap in the prevalence of multimorbidity among older adults by 8% and 6%, respectively.

conclusionsThere is a need to substantially increase the public sector investment in healthcare to address the multimorbidity among older adults, more so in urban areas, without compromising the needs of older adults in rural areas.

Indexed as

AgingMultimorbidityAgedCross-Sectional StudiesHumansIndiaPrevalenceRural PopulationIndiaLASIMultimorbidityObesityUrban-rural differences

Identifiers

PMID35291975
PMCPMC8922782
OpenAlexW4220891091

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LicenceCC BY
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Registered trials

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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.