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Mboya IB, Fritz J, da Silva M, Sun M, Wahlström J, Magnusson PKE, Sandin S, Yin W, Söderberg S, Pedersen NL, Lagerros YT, Nwaru BI, Kankaanranta H, Chabok A, Leppert J, Backman H, Hedman L, Isaksson K, Michaëlsson K, Häggström C, Stocks T. Time trends of the association of body mass index with mortality in 3.5 million young Swedish adults. Ann Epidemiol 2024; 97:23-32. [PMID: 39019242 DOI: 10.1016/j.annepidem.2024.07.043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2024] [Revised: 07/12/2024] [Accepted: 07/13/2024] [Indexed: 07/19/2024]
Abstract
PURPOSE We investigated time trends of the obesity-mortality association, accounting for age, sex, and cause-specific deaths. METHODS We analysed pooled nationwide data in Sweden for 3,472,310 individuals aged 17-39 years at baseline in 1963-2016. Cox regression and flexible parametric survival models investigated BMI-mortality associations in sub-groups of sex and baseline calendar years (men: <1975, 1975-1985, ≥1985 and women: <1985, 1985-1994, ≥1995). RESULTS Comparing men with obesity vs. normal weight, all-cause and "other-cause" mortality associations decreased over periods; HR (95% CI) 1.92 (1.83-2.01) and 1.70 (1.58-1.82) for all-cause and 1.72 (1.58-1.87) and 1.40 (1.28-1.53) for "other-cause" mortality in <1975 and ≥1985, but increased for CVD mortality; HR 2.71 (2.51-2.94) and 3.91 (3.37-4.53). Higher age at death before 1975 coincided with more obesity-related deaths at higher ages. Furthermore, the all-cause mortality association for different ages in men showed no clear differences between periods (p-interaction=0.09), suggesting no calendar effect after accounting for attained age. Similar, but less pronounced, results were observed in women. Associations with cancer mortality showed no clear trends in men or in women. CONCLUSIONS Accounting for differences in age and death causes between calendar periods when investigating BMI-mortality time trends may avoid misinterpreting the risks associated with obesity over time.
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Affiliation(s)
- Innocent B Mboya
- Department of Translational Medicine, Lund University, Malmö, Sweden.
| | - Josef Fritz
- Department of Translational Medicine, Lund University, Malmö, Sweden; Institute of Medical Statistics and Informatics, Medical University of Innsbruck, Innsbruck, Austria
| | - Marisa da Silva
- Department of Translational Medicine, Lund University, Malmö, Sweden
| | - Ming Sun
- Department of Translational Medicine, Lund University, Malmö, Sweden
| | - Jens Wahlström
- Department of Public Health and Clinical Medicine, Section of Sustainable Health, Umeå University, Umeå, Sweden
| | - Patrik K E Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Sven Sandin
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Weiyao Yin
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Stefan Söderberg
- Department of Public Health and Clinical Medicine, Section of Medicine, Umeå University, Umeå, Sweden
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; Department of Psychology, University of Southern California, Los Angeles, CA, USA
| | - Ylva Trolle Lagerros
- Division of Clinical Epidemiology, Department of Medicine, Solna, Karolinska Institutet, Stockholm, Sweden; Center for Obesity, Academic Specialist Center, Stockholm Health Services, Stockholm, Sweden
| | - Bright I Nwaru
- Krefting Research Centre, Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden
| | - Hannu Kankaanranta
- Krefting Research Centre, Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; Department of Respiratory Medicine, Seinäjoki Central Hospital, Seinäjoki, Finland; Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Abbas Chabok
- Center for Clinical Research, Region Västmanland, Uppsala University, Uppsala, Sweden
| | - Jerzy Leppert
- Center for Clinical Research, Region Västmanland, Uppsala University, Uppsala, Sweden
| | - Helena Backman
- Department of Public Health and Clinical Medicine, Section of Sustainable Health, Umeå University, Umeå, Sweden
| | - Linnea Hedman
- Department of Public Health and Clinical Medicine, Section of Sustainable Health, Umeå University, Umeå, Sweden
| | - Karolin Isaksson
- Department of Clinical Sciences Lund, Lund University, Lund, Sweden; Department of Surgery, Kristianstad Hospital, Kristianstad, Sweden
| | - Karl Michaëlsson
- Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Christel Häggström
- Department of Diagnostics and Intervention, and Northern Registry Centre, Umeå University, Umeå, Sweden
| | - Tanja Stocks
- Department of Translational Medicine, Lund University, Malmö, Sweden
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Peter RS, Föger B, Concin H, Nagel G. Effect of Secular Trend, Age, and Length of Follow-up on Optimum Body Mass Index From 1985 Through 2015 in a Large Austrian Cohort. J Epidemiol 2021; 31:601-607. [PMID: 33012774 PMCID: PMC8593575 DOI: 10.2188/jea.je20200012] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023] Open
Abstract
Background Obesity and its health consequences will dominate health care systems in many countries during the next decades. However, the body mass index (BMI) optimum in relation to all-cause mortality is still a matter of debate. Material and Methods Data of the Vorarlberg Health Monitoring & Prevention Program (VHM&PP, 1985–2005) and data provided by the Main Association of Austrian Social Security Institutions (MAASSI, 2005–2015) were analyzed. Information was available on age, sex, smoking status, measured height and weight, and mortality. Generalized additive models were used to model mortality as a function of BMI, calendar time, age, and follow-up. Results In MAASSI (N = 282,216, 46.0% men), men and women were on average 2.7 years older than in VHM&PP (N = 185,361, 46.1% men). Average BMI was slightly higher in men (26.1 vs 25.7 kg/m2) but not in women (24.6 vs 24.7 kg/m2). We found an interactive effect of age and follow-up on the BMI optimum. Over age 35 years in men and 55 years in women, the BMI optimum decreased with length of follow-up. While keeping covariates fixed, BMI optimum increased slightly between 1985 and 2015 in men and women, 24.9 (95% CI, 23.9–25.9) to 26.4 (95% CI, 25.3–27.3), and 22.4 (95% CI, 21.7–23.1) to 23.3 (95% CI, 22.6–24.5) kg/m2, respectively. Conclusion Age and length of follow-up have a pronounced effect on the BMI associated with the lowest all-cause mortality. After controlling for age and length of follow-up, the BMI optimum increased slightly over 30 years in this large study sample.
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Affiliation(s)
| | | | - Hans Concin
- Agency for Preventive and Social Medicine (aks)
| | - Gabriele Nagel
- Institute of Epidemiology and Medical Biometry, Ulm University.,Agency for Preventive and Social Medicine (aks)
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Abramowitz MK, Hall CB, Amodu A, Sharma D, Androga L, Hawkins M. Muscle mass, BMI, and mortality among adults in the United States: A population-based cohort study. PLoS One 2018; 13:e0194697. [PMID: 29641540 PMCID: PMC5894968 DOI: 10.1371/journal.pone.0194697] [Citation(s) in RCA: 110] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2017] [Accepted: 03/07/2018] [Indexed: 12/15/2022] Open
Abstract
Background The level of body-mass index (BMI) associated with the lowest risk of death remains unclear. Although differences in muscle mass limit the utility of BMI as a measure of adiposity, no study has directly examined the effect of muscle mass on the BMI-mortality relationship. Methods Body composition was measured by dual-energy x-ray absorptiometry in 11,687 participants of the National Health and Nutrition Examination Survey 1999–2004. Low muscle mass was defined using sex-specific thresholds of the appendicular skeletal muscle mass index (ASMI). Proportional hazards models were created to model associations with all-cause mortality. Results At any level of BMI ≥22, participants with low muscle mass had higher body fat percentage (%TBF), an increased likelihood of diabetes, and higher adjusted mortality than other participants. Increases in %TBF manifested as 30–40% smaller changes in BMI than were observed in participants with preserved muscle mass. Excluding participants with low muscle mass or adjustment for ASMI attenuated the risk associated with low BMI, magnified the risk associated with high BMI, and shifted downward the level of BMI associated with the lowest risk of death. Higher ASMI was independently associated with lower mortality. Effects were similar in never-smokers and ever-smokers. Additional adjustment for waist circumference eliminated the risk associated with higher BMI. Results were unchanged after excluding unintentional weight loss, chronic illness, early mortality, and participants performing muscle-strengthening exercises or recommended levels of physical activity. Conclusions Muscle mass mediates associations of BMI with adiposity and mortality and is inversely associated with the risk of death. After accounting for muscle mass, the BMI associated with the greatest survival shifts downward toward the normal range. These results provide a concrete explanation for the obesity paradox.
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Affiliation(s)
- Matthew K Abramowitz
- Department of Medicine, Albert Einstein College of Medicine, Bronx, NY, United States of America.,Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, NY, United States of America
| | - Charles B Hall
- Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, NY, United States of America.,The Saul R. Korey Department of Neurology, Albert Einstein College of Medicine, Bronx, NY, United States of America
| | - Afolarin Amodu
- Department of Medicine, Brigham and Women's Hospital and Massachusetts General Hospital, Boston, MA, United States of America
| | - Deep Sharma
- Department of Medicine, Albert Einstein College of Medicine, Bronx, NY, United States of America
| | - Lagu Androga
- Department of Medicine, Albert Einstein College of Medicine, Bronx, NY, United States of America
| | - Meredith Hawkins
- Department of Medicine, Albert Einstein College of Medicine, Bronx, NY, United States of America.,Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, NY, United States of America
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