Muslim-majority countries have higher maternal, stillbirth, newborn, and child mortality rates compared with the global average and to non-Muslim-majority countries, according to research published on 30 January in Lancet.
As there is no indication that religion affects health outcomes, the study findings point to issues such as conflict, migration, political instability, and government effectiveness as key drivers of the differences in maternal and child mortality, according to the researchers led by Zulfiqar Bhutta, PhD, from the Centre for Global Child Health at The Hospital for Sick Children in Toronto, and the Aga Khan University in Karachi, Pakistan.
While several Muslim-majority countries have made progress on indicators of empowerment and access to sexual and reproductive healthcare, greater efforts are now needed, according to the authors.
"Greater investments in reproductive, maternal, newborn, child, and adolescent health are (also) some of our greatest tools in the face of rising levels of conflict and humanitarian crisis, which disproportionately affect Muslim-majority countries," said United Nations Deputy Secretary-General Amina Mohammed in a linked comment. "We must prioritize the potential of women and adolescents as agents of peace through greater investments across health, education, and economic sectors."










![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)






