Evidence map›Paper›PMID 35719649›Full record

ArticleFrontiers in public health2022

Multimorbidity Among Urban Poor in India: Findings From LASI, Wave-1.

Abhinav Sinha, Sushmita Kerketta, Shishirendu Ghosal, Srikanta Kanungo, Sanghamitra Pati

Open access · goldAbstract read
In one paragraph

Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 1 pooled it
5.6field-weighted citation impact, top 3% 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

26 citing papers in PubMed, 1 synthesis or guideline pooled it, 38 citations in OpenAlex.

  1. Pooled it
  2. Asthma and Multimorbidity Amongst Ethnic Minority Groups in High Income Countries.Clinical and experimental allergy : journal of the British Society for Allergy and Clinical Immunology · 2026
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  18. Family-Level Multimorbidity among Older Adults in India: Looking through a Syndemic Lens.International journal of environmental research and public health · 2022
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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

5 authors at 1 institution in 1 country.

Abhinav SinhaDepartment of Public Health, ICMR-Regional Medical Research Centre, Bhubaneswar, India.
Sushmita KerkettaDepartment of Public Health, ICMR-Regional Medical Research Centre, Bhubaneswar, India.
Shishirendu GhosalDepartment of Public Health, ICMR-Regional Medical Research Centre, Bhubaneswar, India.
Srikanta KanungoDepartment of Public Health, ICMR-Regional Medical Research Centre, Bhubaneswar, India.
Sanghamitra PatiDepartment of Public Health, ICMR-Regional Medical Research Centre, Bhubaneswar, India.
Regional Medical Research Centre · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Multimorbidity has become a norm in low-and middle-income countries such as India requiring notable health system improvements to combat. Urban population is a heterogeneous group where poor are at a risk of facing inequity in accessing healthcare services which can jeopardize our efforts to attain universal health coverage (UHC). We aimed to estimate the prevalence, assess correlates and patterns of multimorbidity among urban poor. Further, we assessed the outcomes of multimorbidity such as healthcare utilization, expenditure and self-rated health. Methods: Longitudinal Aging Study in India (LASI), wave-1 is a nationally representative survey conducted amongst participants aged ≥45 years in 2017-18. We included 9,327 participants residing in urban areas, categorized as poor based on monthly per capita expenditure. Descriptive statistics computed prevalence with 95% uncertainty interval. Multivariable logistic regression was executed to assess the association between multimorbidity and various correlates, expressed as adjusted odds ratio. An ordinal regression model was run between self-rated health and number of chronic conditions. Results: The prevalence of multimorbidity was 45.26% among the urban poor. Hypertension and oral morbidities were the most commonly observed dyad. Respondents who were poorer [AOR: 1.27 (1.06-1.51)] had higher chances of having multimorbidity than the poorest. Respondents with a health insurance [AOR: 1.40 (1.14-1.70)] had a higher risk of having multimorbidity. In-patient admission was significantly higher among participants having multimorbidity. Out of pocket expenditure increased while self-rated health deteriorated with each additional morbid condition. Conclusion: Multimorbidity is found to be increasingly prevalent among urban poor and individuals having health insurance which demonstrates the need to expand healthcare insurance schemes such as Ayushman Bharat for urban poor to achieve UHC.

Indexed as

Health ExpendituresMultimorbidityAgingChronic DiseaseHumansIndiaIndiainequityLASImultimorbidityUHCurban poor

Identifiers

PMID35719649
PMCPMC9201724
OpenAlexW4281663622

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.