Bone mineral density (BMD) in adolescent boys may be inversely associated with how much time they spend at the computer, according to a 4 April presentation at the World Congress on Osteoporosis, Osteoarthritis and Musculoskeletal Diseases in Seville, Spain.
In boys, but not girls, more screen time was associated with lower bone mineral density even after adjustments, the Norwegian research team reported. Along with nutritional factors, physical activity can also greatly impact skeletal growth in young people -- and researchers fear that today's sedentary lifestyles can potentially affect bone health and obesity, the group reported.
The Norwegian study aimed to determine if greater weekend computer use is associated with reduced BMD. They examined 463 girls and 484 boys 15-18 years old using dual-energy x-ray absorptiometry (DEXA), also collecting data on lifestyles via questionnaires and interviews, and adjusted for myriad factors including age, sexual maturation, BMI, leisure time activity, smoking, alcohol, cod liver oil, and soda consumption to tease out associations between BMD and screen time.
Boys had more screen time than girls, and not only was this increased time associated with lower BMD, it was correlated to higher BMI levels. In contrast to the boys, girls who spent four to six hours in front of the computer had higher BMD than girls who spent less screen time -- a finding that couldn't be explained by adjustments in the various parameters.
Bone mineral density is a strong predictor of the future risk of fractures, commented lead author Dr. Anne Winter from Arctic University of Norway, in Tromsø. The findings in girls merit further exploration in different population groups and studies, she said in a statement accompanying the study.












![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&fit=crop&h=112&q=70&w=112)




