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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 &amp; Control of Deafness (NPPCD), the Mental Health Program (NMPH), and the AYUSH Musculoskeletal Disorders Program (MSDP) within the context of disease burden.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>The 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\u00a0years 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.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusions<\/jats:title>\n                <jats:p>This 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.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/s12877-024-05614-w","type":"journal-article","created":{"date-parts":[[2024,12,19]],"date-time":"2024-12-19T12:19:26Z","timestamp":1734610766000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Age- and sex-disaggregated disease burden among the older persons in India"],"prefix":"10.1186","volume":"24","author":[{"given":"G Anil","family":"Kumar","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anamika","family":"Pandey","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sailesh","family":"Mohan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dorairaj","family":"Prabhakaran","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rakhi","family":"Dandona","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,12,19]]},"reference":[{"key":"5614_CR1","unstructured":"United Nations, Department of Economic and Social Affairs, Population Division. 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