Éilis J O'Reilly1,2, Molin Wang3,4, Hans-Olov Adami5, Alvaro Alonso6, Leslie Bernstein7, Piet van den Brandt8, Julie Buring4,9, Sarah Daugherty10, Dennis Deapen7, D Michal Freedman11, Dallas R English12,13, Graham G Giles12,13, Niclas Håkansson14, Tobias Kurth4,9,15, Catherine Schairer11, Elisabete Weiderpass5,16,17,18, Alicja Wolk14, Stephanie A Smith-Warner1,4. 1. a Department of Nutrition , Harvard T.H. Chan School of Public Health , Boston , MA , USA. 2. b School of Public Health, College of Medicine , University College Cork , Cork , Ireland. 3. c Channing Division of Network Medicine , Brigham and Women's Hospital and Harvard Medical School , Boston , MA , USA. 4. d Department of Epidemiology , Harvard T.H. Chan School of Public Health , Boston , MA , USA. 5. e Department of Medical Epidemiology and Biostatistics , Karolinska Institutet , Stockholm , Sweden. 6. f Department of Epidemiology , Rollins School of Public Health, Emory University , Atlanta , GA , USA. 7. g Division of Cancer Etiology, Department of Population Science , Beckman Research Institute and City of Hope National Medical Center , Duarte , CA , USA. 8. h Department of Epidemiology, School for Oncology and Developmental Biology (GROW) , Maastricht University , Maastricht , The Netherlands. 9. i Division of Preventive Medicine , Brigham and Women's Hospital, Harvard Medical School , Boston , MA , USA. 10. j CER Methods & Infrastructure , Patient-Centered Outcomes Research Institute , Washington, DC , USA. 11. k Division of Cancer Epidemiology and Genetics , National Cancer Institute , Rockville , MD , USA. 12. l Cancer Epidemiology Centre, Cancer Council of Victoria , Melbourne , Australia. 13. m Centre for Epidemiology and Biostatistics , Melbourne School of Population and Global Health, The University of Melbourne , Melbourne , Australia. 14. n Division of Nutritional Epidemiology , National Institute of Environmental Medicine, Karolinska Institutet , Stockholm , Sweden. 15. o Institute of Public Health , Charité - Universitätsmedizin Berlin , Germany. 16. p Department of Community Medicine, Faculty of Health Sciences , University of Tromsø, The Arctic University of Norway , Tromsø , Norway. 17. q Department of Research , Cancer Registry of Norway , Oslo , Norway , and. 18. r Genetic Epidemiology Group , Folkhälsan Research Center , Helsinki , Finland.
Abstract
OBJECTIVES AND METHODS: Using pooled multivariable-adjusted rate ratios (RR), we explored relationships between prediagnostic body-mass-index (BMI), waist-to-hip-ratio (WHR), and weight-gain during adulthood, and ALS in 419,894 women and 148,166 men from 10 community-based cohorts in USA, Europe, and Australia; 428 ALS deaths were documented in women and 204 in men. RESULTS: Higher mid-to-later adulthood BMI was associated with lower ALS mortality. For 5 kg/m2 increased BMI, the rate was 15% lower (95% confidence interval [CI]: 4-24%; p = 0.005). Although a clear linear trend was not evident for WHR at enrollment (p = 0.099) individuals in the highest cohort-specific quartile had 27% (95% CI: 0-47%; p = 0.053) lower ALS compared to those in the lowest. BMI in early adulthood did not predict ALS; fewer than 10% of participants had early adulthood BMI >25 kg/m2, limiting power. Weight-gain during adulthood was strongly associated with lower ALS; for an additional 1kg gain in weight/year, the RR = 0.43 (95% CI: 0.28-0.65; p < 0.001). Associations persisted when adjusted for diabetes at enrollment, restricted to never-smokers, and ALS deaths in the 5 years after enrollment were excluded (accounting for recent weight loss). CONCLUSIONS: These findings confirm somewhat conflicting, underpowered evidence that adiposity is inversely associated with ALS. We newly demonstrate that weight-gain during adulthood is strongly predictive of lower ALS risk.
OBJECTIVES AND METHODS: Using pooled multivariable-adjusted rate ratios (RR), we explored relationships between prediagnostic body-mass-index (BMI), waist-to-hip-ratio (WHR), and weight-gain during adulthood, and ALS in 419,894 women and 148,166 men from 10 community-based cohorts in USA, Europe, and Australia; 428 ALS deaths were documented in women and 204 in men. RESULTS: Higher mid-to-later adulthood BMI was associated with lower ALSmortality. For 5 kg/m2 increased BMI, the rate was 15% lower (95% confidence interval [CI]: 4-24%; p = 0.005). Although a clear linear trend was not evident for WHR at enrollment (p = 0.099) individuals in the highest cohort-specific quartile had 27% (95% CI: 0-47%; p = 0.053) lower ALS compared to those in the lowest. BMI in early adulthood did not predict ALS; fewer than 10% of participants had early adulthood BMI >25 kg/m2, limiting power. Weight-gain during adulthood was strongly associated with lower ALS; for an additional 1kg gain in weight/year, the RR = 0.43 (95% CI: 0.28-0.65; p < 0.001). Associations persisted when adjusted for diabetes at enrollment, restricted to never-smokers, and ALS deaths in the 5 years after enrollment were excluded (accounting for recent weight loss). CONCLUSIONS: These findings confirm somewhat conflicting, underpowered evidence that adiposity is inversely associated with ALS. We newly demonstrate that weight-gain during adulthood is strongly predictive of lower ALS risk.
Entities:
Keywords:
Amyotrophic lateral sclerosis; body mass index; waist-to-hip ratio; weight gain
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