Evidence map›Paper›PMID 39702198›Full record

ArticleBMC geriatrics2024

Age- and sex-disaggregated disease burden among the older persons in India.

G Anil Kumar, Anamika Pandey, Sailesh Mohan, Dorairaj Prabhakaran, Rakhi Dandona

Abstract read
In one paragraph

Article in BMC geriatrics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

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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

2 citing papers in PubMed.

  1. Article
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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.

G Anil KumarPublic Health Foundation of India, House No. 60, 4th Floor, Lane 2, Part of Saidulajab Extension, Near Saket Metro Station Gate No. 2, New Delhi, India.
Anamika PandeyPublic Health Foundation of India, House No. 60, 4th Floor, Lane 2, Part of Saidulajab Extension, Near Saket Metro Station Gate No. 2, New Delhi, India.
Sailesh MohanPublic Health Foundation of India, House No. 60, 4th Floor, Lane 2, Part of Saidulajab Extension, Near Saket Metro Station Gate No. 2, New Delhi, India.
Dorairaj PrabhakaranPublic Health Foundation of India, House No. 60, 4th Floor, Lane 2, Part of Saidulajab Extension, Near Saket Metro Station Gate No. 2, New Delhi, India.
Rakhi DandonaPublic Health Foundation of India, House No. 60, 4th Floor, Lane 2, Part of Saidulajab Extension, Near Saket Metro Station Gate No. 2, New Delhi, India. rakhi.dandona@phfi.org.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn the context of the increasing number and proportion of population aged 60 years or more in India, it is imperative to understand their health needs for ensuring healthy ageing.

methodsUsing data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we identified the top ten causes of disability-adjusted life years (DALYs), years of life lost (YLLs), and years lived with disability (YLDs) disaggregated by sex and age groups (60-64 years, 65-69 years, 70-74 years, 75-79 years, and ≥ 80 years) for India in 2019. We analysed the proportional contribution of individual causes to the total DALYs due to communicable diseases (CMNNDs), non-communicable diseases (NCDs), and injuries disaggregated by age and sex. We report the state-level heterogeneity in the crude DALY rate for CMNNDs, NCDs, and injuries for older persons disaggregated by sex. Additionally, we reviewed if the data capture of service delivery indicators on older persons were age- and sex-disaggregated in the Health and Wellness Centres (HWCs), and in the National Programs aimed at the Health Care for the Elderly (NPHCE), Prevention and Control of Non-communicable Diseases (NP-NCD), Control of Blindness and Visual Impairment (NPCBVI), Prevention & Control of Deafness (NPPCD), the Mental Health Program (NMPH), and the AYUSH Musculoskeletal Disorders Program (MSDP) within the context of disease burden.

resultsThe older persons accounted for a total of 136.1 million DALYs (29.1% of the total DALYs) in 2019 of which 77.9% were from NCDs, 14.8% from CMNNDs, and 7.3% from injuries, and nearly two-thirds of DALYs were accounted by YLLs. In NCDs, cardiovascular diseases, chronic respiratory diseases, neoplasms, diabetes and kidney diseases, and musculoskeletal disorders accounted for nearly 80% of DALYs for both sexes. There were variations in the magnitude of disease burden by specific diseases and conditions between females and males, and by age groups within both sexes particularly for injuries and CMNNDs. Injuries accounted for more YLDs than YLLs, ranging between 5.9%-15.2% for females and 15.3%-17.3% for males, with the females having a higher contribution to total injury related DALYs due to falls as compared to the males (54.4% vs 36.6%), whereas the males had a higher contribution to total DALYs due to road injuries (33.8% vs 19.4%). There was substantial variation in the crude DALY rates of major disease groups by the two sexes across the states of India in 2019. The crude DALY rate for CMNNDs varied between 3.6 times -3.7 times between the states for females and males, respectively; NCDs varied between 1.3 times -1.9 times, and injuries varied 2.0 times -1.7 times. The capture of service utilisation indicators was not age- or sex-disaggregated in NPHCE, NPCBVI, NMHP, MSDP, and HWCs; sex-disaggregation was available in NP-NCD but not age-disaggregation; sex-disaggregated data was available for many service indicators in NPPCD but with no age disaggregation beyond 50 years and more. Only NP-NCD and NPPCD allowed for data capture by disease/condition or severity of disease/condition for the older persons whereas the other programs including NPHCE did not allow for much disaggregated understanding by the type of services availed.

conclusionsThis comprehensive assessment of the differentials in disease burden among older persons across age, sex and states of India, and the gaps identified in the service utilisation data capture by age and sex for the older persons in the national health programs can provide crucial inputs for strengthening the on-going public health policy and programmatic efforts aimed at improving the health and well-being of the growing older population in India.

Indexed as

Noncommunicable DiseasesAgedAged, 80 and overAge FactorsCost of IllnessDisability-Adjusted Life YearsFemaleGlobal Burden of DiseaseHumansIndiaMaleMiddle AgedSex FactorsWounds and InjuriesDisease burdenElderlyGenderGlobal burden of disease studyHealthy ageingIndiaInjuryNon-communicable diseasesOlder personsPolicyProgramService provision

Identifiers

PMID39702198
PMCPMC11661056

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