{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T14:01:29Z","timestamp":1790776889910,"version":"4.1.0"},"reference-count":81,"publisher":"BMJ","issue":"9","license":[{"start":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T00:00:00Z","timestamp":1790726400000},"content-version":"unspecified","delay-in-days":29,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":["bmj.com"],"crossmark-restriction":true},"short-container-title":["BMJ Open"],"accepted":{"date-parts":[[2026,9,15]]},"published-print":{"date-parts":[[2026,9]]},"abstract":"<jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>Tobacco use remains a major contributor to mortality and disability in India. This study assessed tobacco-attributable mortality and disability-adjusted life-years (DALYs) in India in 1990 and 2023, with comparisons by sex, age group and type of tobacco exposure.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Design<\/jats:title>\n                    <jats:p>Descriptive population-level analysis of secondary data from the Global Burden of Disease 2023 study.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Setting<\/jats:title>\n                    <jats:p>India.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Tobacco-attributable deaths and DALYs were assessed by sex, age group and type of tobacco exposure, including smoking, chewing tobacco and secondhand smoke. Absolute numbers and age-standardised rates were compared between 1990 and 2023.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Tobacco-attributable deaths increased by 54.7%, from 745.74 thousand in 1990 to 1 153.98 thousand in 2023, while DALYs increased by 15.1%, from 27.3 to 31.4 million. In contrast, age-standardised death and DALY rates declined by 39.8% and 47.8%, respectively. Smoking remained the leading contributor (738.8 thousand deaths; 19.78 million DALYs in 2023), particularly among males. Chewing tobacco showed the largest increase (deaths +153.7%; DALYs +124.8%). Secondhand smoke remained substantial, particularly among females (325.63 thousand deaths), though its DALY burden declined by 10.8%. The burden shifted towards non-communicable diseases, with chronic obstructive pulmonary disease, ischaemic heart disease and stroke as leading contributors in 2023.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Despite declines in age-standardised rates, the overall burden of tobacco in India remains substantial. The differing patterns across smoking, chewing tobacco and secondhand smoke highlight the need for comprehensive and targeted tobacco-control strategies.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1136\/bmjopen-2026-123483","type":"journal-article","created":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T13:37:14Z","timestamp":1790775434000},"page":"e123483","update-policy":"https:\/\/doi.org\/10.1136\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":0,"title":["Tobacco-attributable mortality and disease burden in India: a descriptive analysis of Global Burden of Disease 2023 estimates for 1990 and 2023"],"prefix":"10.1136","volume":"16","author":[{"given":"Chaitali","family":"Mandal","sequence":"first","affiliation":[{"name":"Department of Bio-Statistics and Epidemiology, International Institute for Population Sciences, Mumbai, Maharashtra, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5350-6895","authenticated-orcid":false,"given":"Mayank","family":"Singh","sequence":"additional","affiliation":[{"name":"Department of Biostatistics and Health Data Science, KLE Academy of Higher Education and Research Deemed to be University, Belagavi, Karnataka, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Murali","family":"Dhar","sequence":"additional","affiliation":[{"name":"Department of Bio-Statistics and Epidemiology, International Institute for Population Sciences, Mumbai, Maharashtra, India"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"239","published-online":{"date-parts":[[2026,9,30]]},"reference":[{"key":"2026093006353058000_16.9.e123483.1","unstructured":"World Health Organization . 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