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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Banstola, Amrit | - |
| dc.contributor.author | Ahmed, Sayem | - |
| dc.contributor.author | Shenoy, M Swathi | - |
| dc.contributor.author | Gupta, Priti | - |
| dc.contributor.author | Kondal, Dimple | - |
| dc.contributor.author | Bhagat, Radhika | - |
| dc.contributor.author | Goenka, Shifalika | - |
| dc.contributor.author | Khunti, Kamlesh | - |
| dc.contributor.author | Prabhakaran, Dorairaj | - |
| dc.contributor.author | Mohan, Sailesh | - |
| dc.contributor.author | Pokhrel, Subhash | - |
| dc.date.accessioned | 2026-08-17T17:39:32Z | - |
| dc.date.available | 2026-08-17T17:39:32Z | - |
| dc.date.issued | 2026-08-11 | - |
| dc.identifier.citation | Banstola, A. et al. (2026) 'Multiple long-term conditions and their association with quality of life and healthcare utilisation among adults in India: a cross-sectional analysis of WHO SAGE Waves 2 and 3', BMJ Open, 16(8), e116399, pp. 1–16. doi: 10.1136/bmjopen-2026-116399. | en_GB |
| dc.identifier.uri | https://bura.brunel.ac.uk/handle/2438/33717 | - |
| dc.description | Data availability statement: Data may be obtained from a third party and are not publicly available. The SAGE India datasets underpinning this study are accessible from the International Institute for Population Sciences (IIPS) at: https://iipsindia.ac.in/content/SAGE-data. Access requires submission of a data-use request to IIPS and is subject to their terms and confidentiality conditions. | en_GB |
| dc.description | For the purposes of open access, the author has applied a Creative Commons Attribution (CC BY) Licence to any Accepted Author Manuscript version arising from this submission. | en_GB |
| dc.description.abstract | Objectives: To examine the prevalence and disease-combination patterns of multiple long-term conditions (MLTCs) among adults in India and their associations with quality of life and healthcare utilisation. Design: Cross-sectional analysis of two nationally representative survey waves. Setting: Community-based household survey conducted across six Indian states (Assam, Karnataka, Maharashtra, Rajasthan, Uttar Pradesh and West Bengal), part of the WHO Study on global AGEing and adult health. Participants: 9116 adults aged 18 years and older in Wave 2 (2015) and 7885 adults in Wave 3 (2019–2020). Primary and secondary outcome measures: Quality of life, assessed with the 8-item WHO Quality of Life scale (WHOQoL-8, range 0–100), was the primary outcome. Outpatient visits and hospitalisations in the preceding 12 months were the secondary outcomes. Associations with MLTC were estimated using Tobit regression for quality of life and Poisson regression for healthcare utilisation, adjusting for sociodemographic, socio-economic and behavioural factors. Results: MLTC prevalence rose from 19.2% to 24.4% between waves and was highest among adults aged 60 years and older, women, urban residents and the wealthiest quintile. Hypertension–cataracts, hypertension–arthritis and hypertension–diabetes were the most prevalent dyads. Depression–chronic obstructive pulmonary disease (COPD) and depression–stroke combinations had the poorest quality of life. Physical and functional domains declined most as MLTC increased, while the financial domain remained stable. Compared with adults without chronic conditions, WHOQoL-8 scores fell in a stepwise pattern with one, two and three or more conditions (–2.6, –5.1 and –6.7 points in 2015; –3.3, –5.6 and –7.9 in 2019–2020; all p<0.001). The COPD–stroke combination had the highest outpatient use, and depression–angina the highest hospitalisation rate. Healthcare use rose incrementally with condition count (p<0.001). Conclusions: MLTC are rising in India and are associated with poorer quality of life and higher healthcare use. High-burden combinations, particularly depression–COPD, depression–stroke, COPD–stroke and depression–angina, warrant targeted interventions to improve quality of life and manage rising healthcare demands. | en_GB |
| dc.description.sponsorship | NIHR Global Health Research Group on Multiple Long Term Conditions in India and Nepal | Funder: NIHR Global Health Research Group | Grant ID: NIHR203257 | en_GB |
| dc.format.extent | pp. 1–16 | - |
| dc.format.medium | Electronic | - |
| dc.language | English | en_GB |
| dc.language.iso | en | en_GB |
| dc.publisher | BMJ Publishing Group | en_GB |
| dc.rights | Creative Commons Attribution 4.0 International (CC BY 4.0) license | - |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | - |
| dc.subject | 1103 Clinical Sciences | en_GB |
| dc.subject | 1117 Public Health and Health Services | en_GB |
| dc.subject | 1199 Other Medical and Health Sciences | en_GB |
| dc.title | Multiple long-term conditions and their association with quality of life and healthcare utilisation among adults in India: a cross-sectional analysis of WHO SAGE Waves 2 and 3 | en_GB |
| dc.type | Article | en_GB |
| dc.date.dateAccepted | 2026-07-30 | - |
| dc.identifier.doi | https://doi.org/10.1136/bmjopen-2026-116399 | - |
| dc.relation.isPartOf | BMJ Open | en_GB |
| pubs.issue | 8 | - |
| pubs.publication-status | Published | - |
| pubs.volume | 16 | - |
| dc.identifier.eissn | 2044-6055 | - |
| dc.rights.license | https://creativecommons.org/licenses/by/4.0/legalcode.en | - |
| dcterms.dateAccepted | 2026-07-30 | - |
| dcterms.description | STRENGTHS AND LIMITATIONS OF THIS STUDY • Two large, nationally representative waves of the WHO Study on global AGEing and adult health (SAGE) survey in India (Waves 2 and 3) were analysed. • Quality of life was assessed using the validated 8-item WHO Quality of Life instrument alongside measures of healthcare utilisation. • Tobit regression modelled the censored quality of life outcome, and Poisson regression modelled the count-based healthcare utilisation outcome, adjusting for a wide range of sociodemographic, socio-economic and behavioural covariates. • Disease conditions and healthcare use were self-reported, which may introduce recall bias. • The cross-sectional design of each wave prevents causal inference, and the nine self-reported conditions captured by SAGE understate the true burden of multiple long-term conditions. | en_GB |
| dcterms.issued | 2026-08-11 | - |
| dc.date.updated | 2026-08-11T14:07:14Z | - |
| dc.rights.holder | Author(s) (or their employer(s)) | - |
| dc.contributor.orcid | Banstola, Amrit [0000-0003-3185-9638] | - |
| dc.contributor.orcid | Shenoy, M Swathi [0000-0002-7854-6957] | - |
| dc.contributor.orcid | Gupta, Priti [0000-0002-3929-235X] | - |
| dc.contributor.orcid | Prabhakaran, Dorairaj [0000-0002-3172-834X] | - |
| dc.contributor.orcid | Pokhrel, Subhash [0000-0002-1009-8553] | - |
| dc.identifier.number | e116399 | - |
| Appears in Collections: | Department of Health Sciences Research Papers | |
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