Hailey R Banack1, Jennifer W Bea2, Andrew Stokes3, Candyce H Kroenke4, Marcia L Stefanick5, Shirley A Beresford6, Chloe E Bird7, Lorena Garcia8, Robert Wallace9, Robert A Wild10, Bette Caan4, Jean Wactawski-Wende1. 1. Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, The State University of New York, Buffalo, New York, USA. 2. Department of Nutrition Sciences, University of Arizona Cancer Center, University of Arizona, Tucson, Arizona, USA. 3. Department of Global Health and Center for Global Health and Development, Boston University School of Public Health, Boston, Massachusetts, USA. 4. Division of Research, Kaiser Permanente Northern California, Oakland, California, USA. 5. Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, California, USA. 6. Department of Epidemiology, School of Public Health, University of Washington, Seattle, Washington, USA. 7. RAND Corporation, Santa Monica, California, USA. 8. Department of Public Health Sciences, University of California, Davis, Davis, California, USA. 9. Department of Epidemiology, College of Public Health, University of Iowa, Iowa City, Iowa, USA. 10. Department of Obstetrics and Gynecology, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA.
Abstract
OBJECTIVE: The use of relative and absolute effect estimates has important implications for the interpretation of study findings. Likewise, examining additive and multiplicative interaction can lead to differing conclusions about the joint effects of two exposure variables. The aim of this paper is to examine the relationship between BMI and mortality on the relative and absolute scales and investigate interaction between BMI and age. METHODS: Data from 68,132 participants in the Women's Health Initiative (WHI) study were used. The risk ratio and risk difference of BMI on mortality were estimated. A product term was also included to examine interaction between BMI and age on the multiplicative scale, and the relative excess risk of interaction was calculated to measure additive interaction. RESULTS: Results demonstrated that the mortality risk ratio decreased as women aged, but the mortality risk difference increased as women aged. Evidence of additive and multiplicative interaction between age and BMI was found. CONCLUSIONS: In postmenopausal women, the relative mortality risk associated with high BMI decreased with increasing age, but the absolute risk of high BMI increased with increasing age. This indicates the importance of considering the interaction between age and BMI to understand mortality risk in older women.
OBJECTIVE: The use of relative and absolute effect estimates has important implications for the interpretation of study findings. Likewise, examining additive and multiplicative interaction can lead to differing conclusions about the joint effects of two exposure variables. The aim of this paper is to examine the relationship between BMI and mortality on the relative and absolute scales and investigate interaction between BMI and age. METHODS: Data from 68,132 participants in the Women's Health Initiative (WHI) study were used. The risk ratio and risk difference of BMI on mortality were estimated. A product term was also included to examine interaction between BMI and age on the multiplicative scale, and the relative excess risk of interaction was calculated to measure additive interaction. RESULTS: Results demonstrated that the mortality risk ratio decreased as women aged, but the mortality risk difference increased as women aged. Evidence of additive and multiplicative interaction between age and BMI was found. CONCLUSIONS: In postmenopausal women, the relative mortality risk associated with high BMI decreased with increasing age, but the absolute risk of high BMI increased with increasing age. This indicates the importance of considering the interaction between age and BMI to understand mortality risk in older women.
Authors: Jennifer Hays; Julie R Hunt; F Allan Hubbell; Garnet L Anderson; Marian Limacher; Catherine Allen; Jacques E Rossouw Journal: Ann Epidemiol Date: 2003-10 Impact factor: 3.797
Authors: Elizabeth Rose Mayeda; Hailey R Banack; Kirsten Bibbins-Domingo; Adina Zeki Al Hazzouri; Jessica R Marden; Rachel A Whitmer; M Maria Glymour Journal: Epidemiology Date: 2018-07 Impact factor: 4.822
Authors: Amy Berrington de Gonzalez; Patricia Hartge; James R Cerhan; Alan J Flint; Lindsay Hannan; Robert J MacInnis; Steven C Moore; Geoffrey S Tobias; Hoda Anton-Culver; Laura Beane Freeman; W Lawrence Beeson; Sandra L Clipp; Dallas R English; Aaron R Folsom; D Michal Freedman; Graham Giles; Niclas Hakansson; Katherine D Henderson; Judith Hoffman-Bolton; Jane A Hoppin; Karen L Koenig; I-Min Lee; Martha S Linet; Yikyung Park; Gaia Pocobelli; Arthur Schatzkin; Howard D Sesso; Elisabete Weiderpass; Bradley J Willcox; Alicja Wolk; Anne Zeleniuch-Jacquotte; Walter C Willett; Michael J Thun Journal: N Engl J Med Date: 2010-12-02 Impact factor: 91.245
Authors: Erin S LeBlanc; Carrie D Patnode; Elizabeth M Webber; Nadia Redmond; Megan Rushkin; Elizabeth A O'Connor Journal: JAMA Date: 2018-09-18 Impact factor: 56.272
Authors: Franya Hutchins; Samar R El Khoudary; Janet Catov; Robert Krafty; Alicia Colvin; Emma Barinas-Mitchell; Maria M Brooks Journal: J Womens Health (Larchmt) Date: 2022-04-18 Impact factor: 3.017
Authors: Deepika R Laddu; FeiFei Qin; Haley Hedlin; Marcia L Stefanick; JoAnn E Manson; Oleg Zaslavsky; Charles Eaton; Lisa Warsinger Martin; Thomas Rohan; Themistocles L Assimes Journal: Mayo Clin Proc Date: 2021-08-31 Impact factor: 7.616