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Jain P, Binder A, Chen B, Parada H, Gallo L, Alcaraz J, Horvath S, Bhatti P, Whitsel E, Jordahl K, Baccarelli A, Hou L, Stewart J, Li Y, LaMonte M, Manson J, LaCroix A. The Association of Epigenetic Age Acceleration and Multimorbidity at Age 90 in the Women's Health Initiative. J Gerontol A Biol Sci Med Sci 2023; 78:2274-2281. [PMID: 36107798 PMCID: PMC10692424 DOI: 10.1093/gerona/glac190] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Indexed: 12/03/2023] Open
Abstract
BACKGROUND Epigenetic age acceleration (EAA), a measure of accelerated biological aging, has been associated with an increased risk of several age-related chronic conditions. This is the first study to prospectively examine the relationship between EAA and both multimorbidity count and a weighted multimorbidity score among long-lived postmenopausal women. METHODS We included 1 951 women from the Women's Health Initiative who could have survived to age 90. EAA was estimated using the Horvath pan-tissue, Hannum, PhenoAge, and GrimAge "clocks." Twelve chronic conditions were included in the multimorbidity count. The multimorbidity score was weighted for each morbidity's relationship with mortality in the study population. Using mixed-effects Poisson and linear regression models that included baseline covariates associated with both EAA and multimorbidity, we estimated relative risks (RRs) and 95% confidence intervals (CIs) for the relationships between each EAA measure at the study baseline with both multimorbidity count and weighted multimorbidity score at age 90, respectively. RESULTS For every one standard deviation increase in AgeAccelPheno, the rate of multimorbidity accumulation increased 6% (RR = 1.06; 95% CI = 1.01-1.12; p = .025) and the multimorbidity score by 7% (RR = 1.07; 95% CI = 1.01-1.13; p = .014) for women who survived to age 90. The results for a one standard deviation increase in AgeAccelHorvath, AgeAccelHannum, and AgeAccelGrim with multimorbidity accumulation and score were weaker compared to AgeAccelPheno, and the latter 2 did not reach statistical significance. CONCLUSION AgeAccelPheno and AgeAccelHannum may predict multimorbidity count and score at age 90 in older women and, thus, may be useful as a biomarker predictor of multimorbidity burden in the last decades of life.
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Affiliation(s)
- Purva Jain
- The Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, California, USA
| | - Alexandra Binder
- Cancer Epidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii, USA
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, California,USA
| | - Brian Chen
- The Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, California, USA
| | - Humberto Parada
- Division of Epidemiology and Biostatistics, School of Public Health, San Diego State University, San Diego, California, USA
- San Diego Moores Cancer Center, University of California, San Diego, California, La Jolla, California, USA
| | - Linda C Gallo
- Division of Epidemiology and Biostatistics, School of Public Health, San Diego State University, San Diego, California, USA
| | - John Alcaraz
- San Diego Moores Cancer Center, University of California, San Diego, California, La Jolla, California, USA
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, UCLA, Los Angeles, California,USA
- Department of Biostatistics, School of Public Health, University of California, Los Angeles, California,USA
| | - Parveen Bhatti
- Cancer Control Research, BC Cancer, Vancouver, British Columbia, Canada
| | - Eric A Whitsel
- Department of Epidemiology, Gillings School of Public Health and Department of Medicine, School of Medicine, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Kristina Jordahl
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, Washington, USA
| | - Andrea A Baccarelli
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University Irving Medical Center, New York, New York, USA
| | - Lifang Hou
- Institute for Public Health and Medicine, Northwestern University, Chicago, Illinois,USA
| | - James D Stewart
- Department of Epidemiology, Gillings School of Public Health and Department of Medicine, School of Medicine, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Yun Li
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, USA
- Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina, USA
- Department of Computer Science, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Michael J LaMonte
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo―SUNY, Buffalo, New York, USA
| | - JoAnn E Manson
- Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Andrea Z LaCroix
- The Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, California, USA
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Obrochta CA, Parada H, Murphy JD, Nara A, Trinidad D, Araneta MR(H, Thompson CA. The impact of patient travel time on disparities in treatment for early stage lung cancer in California. PLoS One 2022; 17:e0272076. [PMID: 36197902 PMCID: PMC9534452 DOI: 10.1371/journal.pone.0272076] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2021] [Accepted: 07/12/2022] [Indexed: 12/03/2022] Open
Abstract
BACKGROUND Travel time to treatment facilities may impede the receipt of guideline-concordant treatment (GCT) among patients diagnosed with early-stage non-small cell lung cancer (ES-NSCLC). We investigated the relative contribution of travel time in the receipt of GCT among ES-NSCLC patients. METHODS We included 22,821 ES-NSCLC patients diagnosed in California from 2006-2015. GCT was defined using the 2016 National Comprehensive Cancer Network guidelines, and delayed treatment was defined as treatment initiation >6 versus ≤6 weeks after diagnosis. Mean-centered driving and public transit times were calculated from patients' residential block group centroid to the treatment facilities. We used logistic regression to estimate risk ratios and 95% confidence intervals (CIs) for the associations between patients' travel time and receipt of GCT and timely treatment, overall and by race/ethnicity and neighborhood socioeconomic status (nSES). RESULTS Overall, a 15-minute increase in travel time was associated with a decreased risk of undertreatment and delayed treatment. Compared to Whites, among Blacks, a 15-minute increase in driving time was associated with a 24% (95%CI = 8%-42%) increased risk of undertreatment, and among Filipinos, a 15-minute increase in public transit time was associated with a 27% (95%CI = 13%-42%) increased risk of delayed treatment. Compared to the highest nSES, among the lowest nSES, 15-minute increases in driving and public transit times were associated with 33% (95%CI = 16%-52%) and 27% (95%CI = 16%-39%) increases in the risk of undertreatment and delayed treatment, respectively. CONCLUSION The benefit of GCT observed with increased travel times may be a 'Travel Time Paradox,' and may vary across racial/ethnic and socioeconomic groups.
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Affiliation(s)
- Chelsea A. Obrochta
- San Diego State University, School of Public Health, San Diego, California, United States of America
- University of California San Diego, School of Medicine, La Jolla, California, United States of America
| | - Humberto Parada
- San Diego State University, School of Public Health, San Diego, California, United States of America
- University of California San Diego, Moores Cancer Center, La Jolla, California, United States of America
| | - James D. Murphy
- University of California San Diego, Moores Cancer Center, La Jolla, California, United States of America
| | - Atsushi Nara
- Department of Geography, San Diego State University, San Diego, California, United States of America
| | - Dennis Trinidad
- University of California San Diego, School of Medicine, La Jolla, California, United States of America
| | | | - Caroline A. Thompson
- San Diego State University, School of Public Health, San Diego, California, United States of America
- University of California San Diego, School of Medicine, La Jolla, California, United States of America
- University of California San Diego, Moores Cancer Center, La Jolla, California, United States of America
- Department of Epidemiology, University of North Carolina Gillings School of Global Public Health, Chapel Hill, North Carolina, United States of America
- * E-mail:
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Evenson KR, Bellettiere J, Cuthbertson CC, Di C, Dushkes R, Howard AG, Parada H, Schumacher BT, Shiroma EJ, Wang G, Lee IM, LaCroix AZ. Cohort profile: the Women's Health Accelerometry Collaboration. BMJ Open 2021; 11:e052038. [PMID: 34845070 PMCID: PMC8633996 DOI: 10.1136/bmjopen-2021-052038] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
PURPOSE This paper describes the Women's Health Accelerometry Collaboration, a consortium of two prospective cohort studies of women age 62 years or older, harmonised to explore the association of accelerometer-assessed physical activity and sedentary behaviour with cancer incidence and mortality. PARTICIPANTS A total of 23 443 women (age mean 73.4, SD 6.8) living in the USA and participating in an observational study were included; 17 061 from the Women's Health Study (WHS) and 6382 from the Women's Health Initiative Objective Physical Activity and Cardiovascular Health (WHI/OPACH) Study. FINDINGS TO DATE Accelerometry, cancer outcomes and covariate harmonisation was conducted to align the two cohort studies. Physical activity and sedentary behaviour were measured using similar procedures with an ActiGraph GT3X+ accelerometer, worn at the hip for 1 week, during 2011-2014 for WHS and 2012-2014 for WHI/OPACH. Cancer outcomes were ascertained via ongoing surveillance using physician adjudicated cancer diagnosis. Relevant covariates were measured using questionnaire or physical assessments. Among 23 443 women who wore the accelerometer for at least 10 hours on a single day, 22 868 women wore the accelerometer at least 10 hours/day on ≥4 of 7 days. The analytical sample (n=22 852) averaged 4976 (SD 2669) steps/day and engaged in an average of 80.8 (SD 46.5) min/day of moderate-to-vigorous, 105.5 (SD 33.3) min/day of light high and 182.1 (SD 46.1) min/day of light low physical activity. A mean of 8.7 (SD 1.7) hours/day were spent in sedentary behaviour. Overall, 11.8% of the cohort had a cancer diagnosis (other than non-melanoma skin cancer) at the time of accelerometry measurement. During an average of 5.9 (SD 1.6) years of follow-up, 1378 cancer events among which 414 were fatal have occurred. FUTURE PLANS Using the harmonised cohort, we will access ongoing cancer surveillance to quantify the associations of physical activity and sedentary behaviour with cancer incidence and mortality.
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Affiliation(s)
- Kelly R Evenson
- Department of Epidemiology, University of North Carolina at Chapel Hill, Gillings School of Global Public Health, Chapel Hill, North Carolina, USA
| | - John Bellettiere
- Division of Epidemiology, Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, California, USA
| | - Carmen C Cuthbertson
- Department of Epidemiology, University of North Carolina at Chapel Hill, Gillings School of Global Public Health, Chapel Hill, North Carolina, USA
| | - Chongzhi Di
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Rimma Dushkes
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Annie Green Howard
- Department of Biostatistics, University of North Carolina at Chapel Hill, Gillings School of Global Public Health, Chapel Hill, North Carolina, USA
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Humberto Parada
- Moores Cancer Center, University of California at San Diego, La Jolla, California, USA
- Division of Epidemiology and Biostatistics, School of Public Health, San Diego State University, San Diego, California, USA
| | - Benjamin T Schumacher
- Division of Epidemiology, Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, California, USA
- Division of Epidemiology and Biostatistics, School of Public Health, San Diego State University, San Diego, California, USA
| | - Eric J Shiroma
- Laboratory of Epidemiology and Population Science, National Institute on Aging, Bethesda, Maryland, USA
| | - Guangxing Wang
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - I-Min Lee
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Andrea Z LaCroix
- Division of Epidemiology, Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, California, USA
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