Nearly 8 million people worldwide died of smoking in 2019, with the vast majority of smokers picking up the habit in their 20s, according to a new report from the Institute for Health Metrics and Evaluation (IHME).
Using data from 3,625 nationally representative surveys, three studies published in Lancet and Lancet Public Health estimated smoking prevalence in 204 countries in men and women ages 15 and over, including age of initiation, associated diseases, and risks among current and former smokers. The studies also included data on the first analysis of global trends in chewing tobacco use.
The researchers noted persistently high rates of smoking among young people, with over half of countries worldwide showing no progress in reducing smoking among 15- to 24-year-olds. 89% of new smokers become addicted by age 25. Protecting young people from nicotine addiction during this critical window will be crucial to eliminate tobacco use among the next generation, the researchers suggested.
The IHME is an independent global health research center at the University of Washington, Seattle. The results were announced ahead of World No Tobacco Day on 31 May.
![Overview of the study design. (A) The fully automated deep learning framework was developed to estimate body composition (BC) (defined as subcutaneous adipose tissue [SAT] in liters; visceral adipose tissue [VAT] in liters; skeletal muscle [SM] in liters; SM fat fraction [SMFF] as a percentage; and intramuscular adipose tissue [IMAT] in deciliters) from MRI. The fully automated framework comprised one model (model 1) to quantify different BC measures (SAT, VAT, SM, SMFF, and IMAT) as three-dimensional (3D) measures from whole-body MRI scans. The second model (model 2) was trained to identify standardized anatomic landmarks along the craniocaudal body axis (z coordinate field), which allowed for subdividing the whole-body measures into different subregions typically examined on clinical routine MRI scans (chest, abdomen, and pelvis). (B) BC was quantified from whole-body MRI in over 66,000 individuals from two large population-based cohort studies, the UK Biobank (UKB) (36,317 individuals) and the German National Cohort (NAKO) (30,291 individuals). Bar graphs show age distribution by sex and cohort. BMI = body mass index. (C) After the performance assessment of the fully automated framework, the change in BC measures, distributions, and profiles across age decades were investigated. Age-, sex-, and height-adjusted body composition reference curves were calculated and made publicly available in a web-based z-score calculator (https://circ-ml.github.io).](https://img.auntminnieeurope.com/mindful/smg/workspaces/default/uploads/2026/05/body-comp.XgAjTfPj1W.jpg?auto=format%2Ccompress&dpr=2&fit=crop&h=167&q=70&w=250)
