Deepika Laddu1, Neeta Parimi2, Jane A Cauley3, Peggy M Cawthon2,4, Kristine E Ensrud5,6,7, Eric Orwoll8, Marcia Stefanick9, Lisa Langsetmo6. 1. Department of Physical Therapy, University of Illinois at Chicago, Chicago. 2. California Pacific Medical Center Research Institute, San Francisco. 3. University of Pittsburgh Graduate School of Public Health, Pennsylvania. 4. Department of Epidemiology and Biostatics, University of California, San Francisco. 5. Department of Medicine, University of Minnesota, Minneapolis. 6. Division of Epidemiology and Community Health, University of Minnesota, Minneapolis. 7. Center for Chronic Disease Outcomes Research, VA Health Care System, Minneapolis, Minnesota. 8. Department of Medicine, Oregon Health & Sciences University, Portland. 9. Stanford Prevention Research Center, Department of Medicine, Stanford University, California.
Abstract
Background: The benefits of physical activity (PA) for health have primarily been evaluated during midlife. Whether patterns of change in late-life PA associate with overall and cause-specific mortality remains unclear. Methods: We examined the association between PA trajectories and subsequent mortality among 3,767 men aged ≥65 years. Men self-reported PA using the Physical Activity Scale for the Elderly (PASE) at up to four time points from 2000 through 2009 (Year 7); mortality was assessed over an average of 7.1 years after the Year 7 contact. Group-based trajectory modeling identified patterns of PA change. Cox proportional hazards models described associations between patterns of change in PA, Year 7 PA, and subsequent mortality risk. Results: Three discrete PA patterns were identified, all with declining PA. Compared to low-activity declining men, moderate (hazard ratio [HR] = 0.78; 95% confidence interval [CI]: 0.70, 0.88) and high-activity (HR = 0.69, 95% CI: 0.57, 0.83) declining groups were associated with lower risk of all-cause mortality. Among models with a single time point, the last time point (Year 7 PA score) was a strong predictor of mortality with HR = 0.85 (95% CI: 0.78, 0.93) per SD increase in PASE score. PA patterns were not a risk factor for mortality after adjustment for the Year 7 PA score. Conclusions: Recent PA levels are a stronger indicator of subsequent mortality risk than PA patterns reported over the prior 7 years or prior PA level, suggesting that current PA rather than history of PA is the most relevant parameter in clinical settings.
Background: The benefits of physical activity (PA) for health have primarily been evaluated during midlife. Whether patterns of change in late-life PA associate with overall and cause-specific mortality remains unclear. Methods: We examined the association between PA trajectories and subsequent mortality among 3,767 men aged ≥65 years. Men self-reported PA using the Physical Activity Scale for the Elderly (PASE) at up to four time points from 2000 through 2009 (Year 7); mortality was assessed over an average of 7.1 years after the Year 7 contact. Group-based trajectory modeling identified patterns of PA change. Cox proportional hazards models described associations between patterns of change in PA, Year 7 PA, and subsequent mortality risk. Results: Three discrete PA patterns were identified, all with declining PA. Compared to low-activity declining men, moderate (hazard ratio [HR] = 0.78; 95% confidence interval [CI]: 0.70, 0.88) and high-activity (HR = 0.69, 95% CI: 0.57, 0.83) declining groups were associated with lower risk of all-cause mortality. Among models with a single time point, the last time point (Year 7 PA score) was a strong predictor of mortality with HR = 0.85 (95% CI: 0.78, 0.93) per SD increase in PASE score. PA patterns were not a risk factor for mortality after adjustment for the Year 7 PA score. Conclusions: Recent PA levels are a stronger indicator of subsequent mortality risk than PA patterns reported over the prior 7 years or prior PA level, suggesting that current PA rather than history of PA is the most relevant parameter in clinical settings.
Authors: Hannah Arem; Steven C Moore; Alpa Patel; Patricia Hartge; Amy Berrington de Gonzalez; Kala Visvanathan; Peter T Campbell; Michal Freedman; Elisabete Weiderpass; Hans Olov Adami; Martha S Linet; I-Min Lee; Charles E Matthews Journal: JAMA Intern Med Date: 2015-06 Impact factor: 21.873
Authors: Eric Orwoll; Janet Babich Blank; Elizabeth Barrett-Connor; Jane Cauley; Steven Cummings; Kristine Ensrud; Cora Lewis; Peggy M Cawthon; Robert Marcus; Lynn M Marshall; Joan McGowan; Kathy Phipps; Sherry Sherman; Marcia L Stefanick; Katie Stone Journal: Contemp Clin Trials Date: 2005-10 Impact factor: 2.226
Authors: Osvaldo P Almeida; Karim M Khan; Graeme J Hankey; Bu B Yeap; Jonathan Golledge; Leon Flicker Journal: Br J Sports Med Date: 2013-09-03 Impact factor: 13.800
Authors: Calvin H Hirsch; Paula Diehr; Anne B Newman; Shirley A Gerrior; Charlotte Pratt; Michael D Lebowitz; Sharon A Jackson Journal: J Aging Phys Act Date: 2010-07 Impact factor: 1.961
Authors: Edward W Gregg; Jane A Cauley; Katie Stone; Theodore J Thompson; Douglas C Bauer; Steven R Cummings; Kristine E Ensrud Journal: JAMA Date: 2003-05-14 Impact factor: 56.272
Authors: Deepika R Laddu; Neeta Parimi; Katie L Stone; Jodi Lapidus; Andrew R Hoffman; Marcia L Stefanick; Lisa Langsetmo Journal: J Gerontol A Biol Sci Med Sci Date: 2020-09-25 Impact factor: 6.053
Authors: Daniel Aggio; Efstathios Papachristou; Olia Papacosta; Lucy T Lennon; Sarah Ash; Peter Whincup; S Goya Wannamethee; Barbara J Jefferis Journal: J Epidemiol Community Health Date: 2019-11-08 Impact factor: 3.710
Authors: Juan Luis Sanchez-Sanchez; Mikel Izquierdo; Jose Antonio Carnicero-Carreño; Fransico José García-García; Leocadio Rodríguez-Mañas Journal: J Cachexia Sarcopenia Muscle Date: 2020-03-12 Impact factor: 12.910
Authors: Boris Cheval; Zsófia Csajbók; Tomáš Formánek; Stefan Sieber; Matthieu P Boisgontier; Stéphane Cullati; Pavla Cermakova Journal: Epidemiol Psychiatr Sci Date: 2021-12-27 Impact factor: 6.892