Obesity Duration, Severity, and Distribution Trajectories and Cardiovascular Disease Risk in the Atherosclerosis Risk in Communities Study
Background Research examining the role of obesity in cardiovascular disease (CVD) often fails to adequately consider heterogeneity in obesity severity, distribution, and duration. Methods and Results We here use multivariate latent class mixed models in the biracial Atherosclerosis Risk in Communiti...
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| Vydáno v: | Journal of the American Heart Association Ročník 10; číslo 24; s. e019946 |
|---|---|
| Hlavní autoři: | , , , , , , , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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England
John Wiley and Sons Inc
21.12.2021
Wiley |
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| ISSN: | 2047-9980, 2047-9980 |
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| Abstract | Background Research examining the role of obesity in cardiovascular disease (CVD) often fails to adequately consider heterogeneity in obesity severity, distribution, and duration. Methods and Results We here use multivariate latent class mixed models in the biracial Atherosclerosis Risk in Communities study (N=14 514; mean age=54 years; 55% female) to associate obesity subclasses (derived from body mass index, waist circumference, self-reported weight at age 25, tricep skinfold, and calf circumference across up to four triennial visits) with total mortality, incident CVD, and CVD risk factors. We identified four obesity subclasses, summarized by their body mass index and waist circumference slope as decline (4.1%), stable/slow decline (67.8%), moderate increase (24.6%), and rapid increase (3.6%) subclasses. Compared with participants in the stable/slow decline subclass, the decline subclass was associated with elevated mortality (hazard ratio [HR] 1.45, 95% CI 1.31, 1.60,
<0.0001) and with heart failure (HR 1.41, 95% CI 1.22, 1.63,
<0.0001), stroke (HR 1.53, 95% CI 1.22, 1.92,
=0.0002), and coronary heart disease (HR 1.36, 95% CI 1.14, 1.63,
=0.0008), adjusting for baseline body mass index and CVD risk factor profile. The moderate increase latent class was not associated with any significant differences in CVD risk as compared to the stable/slow decline latent class and was associated with a lower overall risk of mortality (HR 0.85, 95% CI 0.80, 0.90,
<0.0001), despite higher body mass index at baseline. The rapid increase latent class was associated with a higher risk of heart failure versus the stable/slow decline latent class (HR 1.34, 95% CI 1.10, 1.62,
=0.004). Conclusions Consideration of heterogeneity and longitudinal changes in obesity measures is needed in clinical care for a more precision-oriented view of CVD risk. |
|---|---|
| AbstractList | Background Research examining the role of obesity in cardiovascular disease (CVD) often fails to adequately consider heterogeneity in obesity severity, distribution, and duration. Methods and Results We here use multivariate latent class mixed models in the biracial Atherosclerosis Risk in Communities study (N=14 514; mean age=54 years; 55% female) to associate obesity subclasses (derived from body mass index, waist circumference, self-reported weight at age 25, tricep skinfold, and calf circumference across up to four triennial visits) with total mortality, incident CVD, and CVD risk factors. We identified four obesity subclasses, summarized by their body mass index and waist circumference slope as decline (4.1%), stable/slow decline (67.8%), moderate increase (24.6%), and rapid increase (3.6%) subclasses. Compared with participants in the stable/slow decline subclass, the decline subclass was associated with elevated mortality (hazard ratio [HR] 1.45, 95% CI 1.31, 1.60, P<0.0001) and with heart failure (HR 1.41, 95% CI 1.22, 1.63, P<0.0001), stroke (HR 1.53, 95% CI 1.22, 1.92, P=0.0002), and coronary heart disease (HR 1.36, 95% CI 1.14, 1.63, P=0.0008), adjusting for baseline body mass index and CVD risk factor profile. The moderate increase latent class was not associated with any significant differences in CVD risk as compared to the stable/slow decline latent class and was associated with a lower overall risk of mortality (HR 0.85, 95% CI 0.80, 0.90, P<0.0001), despite higher body mass index at baseline. The rapid increase latent class was associated with a higher risk of heart failure versus the stable/slow decline latent class (HR 1.34, 95% CI 1.10, 1.62, P=0.004). Conclusions Consideration of heterogeneity and longitudinal changes in obesity measures is needed in clinical care for a more precision-oriented view of CVD risk.Background Research examining the role of obesity in cardiovascular disease (CVD) often fails to adequately consider heterogeneity in obesity severity, distribution, and duration. Methods and Results We here use multivariate latent class mixed models in the biracial Atherosclerosis Risk in Communities study (N=14 514; mean age=54 years; 55% female) to associate obesity subclasses (derived from body mass index, waist circumference, self-reported weight at age 25, tricep skinfold, and calf circumference across up to four triennial visits) with total mortality, incident CVD, and CVD risk factors. We identified four obesity subclasses, summarized by their body mass index and waist circumference slope as decline (4.1%), stable/slow decline (67.8%), moderate increase (24.6%), and rapid increase (3.6%) subclasses. Compared with participants in the stable/slow decline subclass, the decline subclass was associated with elevated mortality (hazard ratio [HR] 1.45, 95% CI 1.31, 1.60, P<0.0001) and with heart failure (HR 1.41, 95% CI 1.22, 1.63, P<0.0001), stroke (HR 1.53, 95% CI 1.22, 1.92, P=0.0002), and coronary heart disease (HR 1.36, 95% CI 1.14, 1.63, P=0.0008), adjusting for baseline body mass index and CVD risk factor profile. The moderate increase latent class was not associated with any significant differences in CVD risk as compared to the stable/slow decline latent class and was associated with a lower overall risk of mortality (HR 0.85, 95% CI 0.80, 0.90, P<0.0001), despite higher body mass index at baseline. The rapid increase latent class was associated with a higher risk of heart failure versus the stable/slow decline latent class (HR 1.34, 95% CI 1.10, 1.62, P=0.004). Conclusions Consideration of heterogeneity and longitudinal changes in obesity measures is needed in clinical care for a more precision-oriented view of CVD risk. Background Research examining the role of obesity in cardiovascular disease (CVD) often fails to adequately consider heterogeneity in obesity severity, distribution, and duration. Methods and Results We here use multivariate latent class mixed models in the biracial Atherosclerosis Risk in Communities study (N=14 514; mean age=54 years; 55% female) to associate obesity subclasses (derived from body mass index, waist circumference, self‐reported weight at age 25, tricep skinfold, and calf circumference across up to four triennial visits) with total mortality, incident CVD, and CVD risk factors. We identified four obesity subclasses, summarized by their body mass index and waist circumference slope as decline (4.1%), stable/slow decline (67.8%), moderate increase (24.6%), and rapid increase (3.6%) subclasses. Compared with participants in the stable/slow decline subclass, the decline subclass was associated with elevated mortality (hazard ratio [HR] 1.45, 95% CI 1.31, 1.60, P<0.0001) and with heart failure (HR 1.41, 95% CI 1.22, 1.63, P<0.0001), stroke (HR 1.53, 95% CI 1.22, 1.92, P=0.0002), and coronary heart disease (HR 1.36, 95% CI 1.14, 1.63, P=0.0008), adjusting for baseline body mass index and CVD risk factor profile. The moderate increase latent class was not associated with any significant differences in CVD risk as compared to the stable/slow decline latent class and was associated with a lower overall risk of mortality (HR 0.85, 95% CI 0.80, 0.90, P<0.0001), despite higher body mass index at baseline. The rapid increase latent class was associated with a higher risk of heart failure versus the stable/slow decline latent class (HR 1.34, 95% CI 1.10, 1.62, P=0.004). Conclusions Consideration of heterogeneity and longitudinal changes in obesity measures is needed in clinical care for a more precision‐oriented view of CVD risk. Background Research examining the role of obesity in cardiovascular disease (CVD) often fails to adequately consider heterogeneity in obesity severity, distribution, and duration. Methods and Results We here use multivariate latent class mixed models in the biracial Atherosclerosis Risk in Communities study (N=14 514; mean age=54 years; 55% female) to associate obesity subclasses (derived from body mass index, waist circumference, self-reported weight at age 25, tricep skinfold, and calf circumference across up to four triennial visits) with total mortality, incident CVD, and CVD risk factors. We identified four obesity subclasses, summarized by their body mass index and waist circumference slope as decline (4.1%), stable/slow decline (67.8%), moderate increase (24.6%), and rapid increase (3.6%) subclasses. Compared with participants in the stable/slow decline subclass, the decline subclass was associated with elevated mortality (hazard ratio [HR] 1.45, 95% CI 1.31, 1.60, <0.0001) and with heart failure (HR 1.41, 95% CI 1.22, 1.63, <0.0001), stroke (HR 1.53, 95% CI 1.22, 1.92, =0.0002), and coronary heart disease (HR 1.36, 95% CI 1.14, 1.63, =0.0008), adjusting for baseline body mass index and CVD risk factor profile. The moderate increase latent class was not associated with any significant differences in CVD risk as compared to the stable/slow decline latent class and was associated with a lower overall risk of mortality (HR 0.85, 95% CI 0.80, 0.90, <0.0001), despite higher body mass index at baseline. The rapid increase latent class was associated with a higher risk of heart failure versus the stable/slow decline latent class (HR 1.34, 95% CI 1.10, 1.62, =0.004). Conclusions Consideration of heterogeneity and longitudinal changes in obesity measures is needed in clinical care for a more precision-oriented view of CVD risk. |
| Author | Gordon‐Larsen, Penny Avery, Christy L. Howard, Annie Green Demerath, Ellen Cheng, Susan Yu, Bing Seidelmann, Sara North, Kari E. Lin, Dan‐Yu Graff, Misa Ndumele, Chiadi Palta, Priya Raffield, Laura M. Rebholz, Casey M. |
| AuthorAffiliation | 7 Department of Epidemiology Johns Hopkins Bloomberg School of Public Health Baltimore MD 2 Department of Biostatistics Gillings School of Global Public Health University of North Carolina Chapel Hill NC 6 Johns Hopkins Ciccarone Center for the Prevention of Heart Disease Johns Hopkins University School of Medicine Baltimore MD 9 Welch Center for Prevention, Epidemiology and Clinical Research Johns Hopkins University Baltimore MD 3 Department of Epidemiology Gillings School of Global Public Health University of North Carolina Chapel Hill NC 13 Carolina Center of Genome Sciences University of North Carolina at Chapel Hill Chapel Hill NC 12 Department of Nutrition Gillings School of Global Public Health and School of Medicine University of North Carolina Chapel Hill NC 4 Smidt Heart Institute Cedars‐Sinai Medical Center Los Angeles CA 1 Department of Genetics University of North Carolina Chapel Hill NC 8 Departments of Medicine and Epidemiology Columbia University Medical Center New York NY 11 Dep |
| AuthorAffiliation_xml | – name: 6 Johns Hopkins Ciccarone Center for the Prevention of Heart Disease Johns Hopkins University School of Medicine Baltimore MD – name: 10 Cardiovascular Division Brigham and Women's Hospital and Harvard Medical School Boston MA – name: 1 Department of Genetics University of North Carolina Chapel Hill NC – name: 3 Department of Epidemiology Gillings School of Global Public Health University of North Carolina Chapel Hill NC – name: 12 Department of Nutrition Gillings School of Global Public Health and School of Medicine University of North Carolina Chapel Hill NC – name: 8 Departments of Medicine and Epidemiology Columbia University Medical Center New York NY – name: 7 Department of Epidemiology Johns Hopkins Bloomberg School of Public Health Baltimore MD – name: 11 Department of Epidemiology, Human Genetics and Environmental Sciences School of Public Health University of Texas Health Science Center at Houston TX – name: 13 Carolina Center of Genome Sciences University of North Carolina at Chapel Hill Chapel Hill NC – name: 5 Division of Epidemiology and Community Health School of Public Health University of Minnesota Minneapolis MN – name: 2 Department of Biostatistics Gillings School of Global Public Health University of North Carolina Chapel Hill NC – name: 9 Welch Center for Prevention, Epidemiology and Clinical Research Johns Hopkins University Baltimore MD – name: 4 Smidt Heart Institute Cedars‐Sinai Medical Center Los Angeles CA |
| Author_xml | – sequence: 1 givenname: Laura M. orcidid: 0000-0002-7892-193X surname: Raffield fullname: Raffield, Laura M. organization: Department of Genetics University of North Carolina Chapel Hill NC – sequence: 2 givenname: Annie Green surname: Howard fullname: Howard, Annie Green organization: Department of Biostatistics Gillings School of Global Public Health University of North Carolina Chapel Hill NC – sequence: 3 givenname: Misa orcidid: 0000-0001-6380-1735 surname: Graff fullname: Graff, Misa organization: Department of Epidemiology Gillings School of Global Public Health University of North Carolina Chapel Hill NC – sequence: 4 givenname: Dan‐Yu surname: Lin fullname: Lin, Dan‐Yu organization: Department of Biostatistics Gillings School of Global Public Health University of North Carolina Chapel Hill NC – sequence: 5 givenname: Susan orcidid: 0000-0002-4977-036X surname: Cheng fullname: Cheng, Susan organization: Smidt Heart InstituteCedars‐Sinai Medical Center Los Angeles CA – sequence: 6 givenname: Ellen orcidid: 0000-0002-4585-4064 surname: Demerath fullname: Demerath, Ellen organization: Division of Epidemiology and Community Health School of Public Health University of Minnesota Minneapolis MN – sequence: 7 givenname: Chiadi surname: Ndumele fullname: Ndumele, Chiadi organization: Johns Hopkins Ciccarone Center for the Prevention of Heart Disease Johns Hopkins University School of Medicine Baltimore MD, Department of Epidemiology Johns Hopkins Bloomberg School of Public Health Baltimore MD – sequence: 8 givenname: Priya surname: Palta fullname: Palta, Priya organization: Departments of Medicine and Epidemiology Columbia University Medical Center New York NY – sequence: 9 givenname: Casey M. orcidid: 0000-0002-5442-8745 surname: Rebholz fullname: Rebholz, Casey M. organization: Department of Epidemiology Johns Hopkins Bloomberg School of Public Health Baltimore MD, Welch Center for Prevention, Epidemiology and Clinical Research Johns Hopkins University Baltimore MD – sequence: 10 givenname: Sara surname: Seidelmann fullname: Seidelmann, Sara organization: Cardiovascular Division Brigham and Women's Hospital and Harvard Medical School Boston MA – sequence: 11 givenname: Bing orcidid: 0000-0003-4818-1077 surname: Yu fullname: Yu, Bing organization: Department of Epidemiology, Human Genetics and Environmental Sciences School of Public Health University of Texas Health Science Center at Houston TX – sequence: 12 givenname: Penny orcidid: 0000-0001-5322-4188 surname: Gordon‐Larsen fullname: Gordon‐Larsen, Penny organization: Department of Nutrition Gillings School of Global Public Health and School of Medicine University of North Carolina Chapel Hill NC – sequence: 13 givenname: Kari E. orcidid: 0000-0002-8903-0366 surname: North fullname: North, Kari E. organization: Department of Epidemiology Gillings School of Global Public Health University of North Carolina Chapel Hill NC, Carolina Center of Genome Sciences University of North Carolina at Chapel Hill Chapel Hill NC – sequence: 14 givenname: Christy L. orcidid: 0000-0002-1044-8162 surname: Avery fullname: Avery, Christy L. organization: Department of Epidemiology Gillings School of Global Public Health University of North Carolina Chapel Hill NC |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/34889111$$D View this record in MEDLINE/PubMed |
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| Copyright | 2021 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley. |
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| Issue | 24 |
| Keywords | latent class models cardiovascular disease obesity |
| Language | English |
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| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Supplemental Material for this article is available at https://www.ahajournals.org/doi/suppl/10.1161/JAHA.121.019946 L. M. Raffield, A. G. Howard, P. Gordon‐Larsen, K. E. North, and C. L. Avery contributed equally. For Sources of Funding and Disclosures, see page 12. |
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| Snippet | Background Research examining the role of obesity in cardiovascular disease (CVD) often fails to adequately consider heterogeneity in obesity severity,... |
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| SubjectTerms | Atherosclerosis - epidemiology cardiovascular disease Cardiovascular Diseases - epidemiology Female Heart Disease Risk Factors Humans latent class models Male Middle Aged obesity Obesity - epidemiology Original Research Patient Acuity |
| Title | Obesity Duration, Severity, and Distribution Trajectories and Cardiovascular Disease Risk in the Atherosclerosis Risk in Communities Study |
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