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Health and Quality of Life Outcomes

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Open Access 01-12-2017 | Research

What is the impact of underweight on self-reported health trajectories and mortality rates: a cohort study

Authors: Geir Fagerjord Lorem, Henrik Schirmer, Nina Emaus

Published in: Health and Quality of Life Outcomes | Issue 1/2017

Abstract

Background

Utilizing a cohort study design combining a survey approach with repeated physical examinations, we examined the independent effects of BMI on mortality and self-reported health (SRH) and whether these independent effects change as people grow older.

Methods

The Tromsø Study consists of six surveys conducted in the municipality of Tromsø, Norway, with large representative samples of a general population. In total, 31,985 subjects participated in at least one of the four surveys administered between 1986 and 2008. Outcomes of interest were SRH and all-cause mortality.

Results

Overweight and underweight subjects reported significantly lower levels of SRH, but age affected the thinnest subjects more than all others. The SRH trajectory of underweight subjects at age 25 was slightly above the other categories (0.08), but it fell to −.30 below the reference category at age 90. For obese subjects, the difference was −0.15 below the reference category at age 25 and −0.18 below at age 90. This implies that even though a low BMI was slightly beneficial at a young age, it represented an increasing risk with age that crossed the reference curve at age 38 and even crossed the obese trajectory at age 67 in the full fitted model. The proportional hazard ratio for those who were underweight was 1.69 (95% CI: 1.38-2.06) for all-cause death as compared to 1.12 (95% CI: 1.02-1.23) for obese subjects.

Conclusion

BMI affected SRH and all-cause mortality independently from comorbidity, mental health, health-related behaviors and other biological risk factors. Being underweight was associated with excess mortality as compared to all others, and age affected the thinnest subjects more than all others. Weight increase was beneficial for mortality but not for SRH among the underweight. The rapid decline of SRH with increasing age suggests that particular attention should be paid to underweight after 38 years of age.

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Tiggemann M. Sociocultural perspectives on human appearance and body image. In: Cash TF, Smolak L, editors. Body image: A handbook of science, practice, and prevention. New York: Guilford Press; 1980. p. 12–20.

World Health Organization. The Asia-Pacific perspective. Redefining obesity and its treatment. Geneva: World Health Organization; 2000.

World Health Organization. Physical status. The use and interpretation of anthropometry. In: Report of a WHO expert committee. Technical Report Series, No 854. Geneva: World Health Organization; 1995.

WHO Expert Consultation. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. London: Lancet. 2004;363(9403):157–63. doi:10.1016/s0140-6736(03)15268-3.

Dale C, Nüesch E, Prieto-Merino D, Choi M, Amuzu A, Ebrahim S, et al. Why do thin people have elevated all-cause mortality? Evidence on confounding and reverse causality in the association of adiposity and COPD from the British Women’s Heart and Health Study. PLoS One. 2015;10(4):e0115446. doi:10.1371/journal.pone.0115446.CrossRefPubMedPubMedCentral

Kvamme J-M, Olsen JA, Florholmen J, Jacobsen BK. Risk of malnutrition and health-related quality of life in community-living elderly men and women: The Tromsø study. Qual Life Res. 2011;20(4):575–82.CrossRefPubMed

Kivimäki M, Shipley MJ, Bell JA, Brunner EJ, Batty GD, Singh-Manoux A. Underweight as a risk factor for respiratory death in the Whitehall cohort study: exploring reverse causality using a 45-year follow-up. Thorax. 2016;71(1):84–5. doi:10.1136/thoraxjnl-2015-207449.CrossRefPubMed

Harpsøe MC, Nielsen NM, Friis-Møller N, Andersson M, Wohlfahrt J, Linneberg A, et al. Body mass index and risk of infections among women in the Danish National Birth Cohort. Am J Epidemiol. 2016; doi:10.1093/aje/kwv300.

Bucholz EM, Krumholz HA, Krumholz HM. Underweight, markers of cachexia, and mortality in acute myocardial infarction: A prospective cohort study of elderly medicare beneficiaries. PLoS Med. 2016;13(4):e1001998. doi:10.1371/journal.pmed.1001998.CrossRefPubMedPubMedCentral

10.

Andersen KK, Olsen TS. The obesity paradox in stroke: Lower mortality and lower risk of readmission for recurrent stroke in obese stroke patients. Int J Stroke. 2015;10:99–104. doi:10.1111/ijs.12016.CrossRefPubMed

11.

Kvamme J-M, Holmen J, Wilsgaard T, Florholmen J, Midthjell K, Jacobsen BK. Body mass index and mortality in elderly men and women: the Tromsø and HUNT studies. J Epidemiol Community Health. 2012;66:611-7.

12.

Kvamme J-M, Wilsgaard T, Florholmen J, Jacobsen BK. Body mass index and disease burden in elderly men and women: the Tromsø Study. Eur J Epidemiol. 2010;25(3):183–93.CrossRefPubMed

13.

Huang K, Liu F, Han X, Huang C, Huang J, Gu D, et al. Association of BMI with total mortality and recurrent stroke among stroke patients: A meta-analysis of cohort studies. Atherosclerosis. 2016;253:94–101. doi:10.1016/j.atherosclerosis.2016.08.042.CrossRefPubMed

14.

Albergotti WG, Davis KS, Abberbock S, Bauman JE, Ohr J, Clump DA, et al. Association of pretreatment body mass index and survival in human papillomavirus positive oropharyngeal squamous cell carcinoma. Oral Oncol. 2016;60:55–60. doi:10.1016/j.oraloncology.2016.07.003.CrossRefPubMedPubMedCentral

15.

Doleman B, Mills KT, Lim S, Zelhart MD, Gagliardi G. Body mass index and colorectal cancer prognosis: a systematic review and meta-analysis. Tech Coloproctol. 2016;20(8):517–35. doi:10.1007/s10151-016-1498-3.CrossRefPubMed

16.

Warkentin LM, Das D, Majumdar SR, Johnson JA, Padwal RS. The effect of weight loss on health-related quality of life: systematic review and meta-analysis of randomized trials. Obes Rev. 2014;15(3):169–82. doi:10.1111/obr.12113.CrossRefPubMed

17.

Wagner DC, Short JL. Longitudinal predictors of self-rated health and mortality in older adults. Prev Chronic Dis. 2014;11:E93. doi:10.5888/pcd11.130241.CrossRefPubMedPubMedCentral

18.

Pan A, Kawachi I, Luo N, Manson JE, Willett WC, Hu FB, et al. Changes in body weight and health-related quality of life: 2 cohorts of US women. Am J Epidemiol. 2014; doi:10.1093/aje/kwu136.

19.

Maïano C, Normand CL, Aimé A, Bégarie J. Lifestyle interventions targeting changes in body weight and composition among youth with an intellectual disability: A systematic review. Res Dev Disabil. 2014;35(8):1914–26. https://doi.org/10.1016/j.ridd.2014.04.014.CrossRefPubMed

20.

Wilsgaard T, Jacobsen BK, Mathiesen EB, Njølstad I. Weight loss and mortality: A gender-specific analysis of the Tromsø study. Gend Med. 2009;6(4):575–86. https://doi.org/10.1016/j.genm.2009.12.003.CrossRefPubMed

21.

Newman AB, Yanez D, Harris T, Duxbury A, Enright PL, Fried LP. Weight change in old age and its association with mortality. J Am Geriatr Soc. 2001;49(10):1309–18.CrossRefPubMed

22.

Alley DE, Metter EJ, Griswold ME, Harris TB, Simonsick EM, Longo DL, et al. Changes in weight at the end of life: characterizing weight loss by time to death in a cohort study of older men. Am J Epidemiol. 2010;172(5):558–65. https://doi.org/10.1093/aje/kwq168.CrossRefPubMedPubMedCentral

23.

Arcelus J, Mitchell AJ, Wales J, Nielsen S. Mortality rates in patients with anorexia nervosa and other eating disorders A meta-analysis of 36 studies. Arch Gen Psychiatry. 2011;68(7):724–31.CrossRefPubMed

24.

Ágh T, Kovács G, Supina D, Pawaskar M, Herman BK, Vokó Z, et al. A systematic review of the health-related quality of life and economic burdens of anorexia nervosa, bulimia nervosa, and binge eating disorder. Eat Weight Disord. 2016;21(3):353–64. https://doi.org/10.1007/s40519-016-0264-x.CrossRefPubMedPubMedCentral

25.

Ganna A, Ingelsson E. 5 year mortality predictors in 498 103 UK Biobank participants: a prospective population-based study. Lancet. 2015;386:533–40.CrossRefPubMed

26.

Kaplan GA, Goldberg DE, Everson SA, Cohen RD, Salonen R, Tuomilehto J, et al. Perceived health status and morbidity and mortality: Evidence from the Kuopio Ischaemic Heart Disease Risk Factor Study. Int J Epidemiol. 1996;25(2):259–65. https://doi.org/10.1093/ije/25.2.259.CrossRefPubMed

27.

Desalvo KB, Jones TM, Peabody J, McDonald J, Fihn S, Fan V, et al. Health care expenditure prediction with a single item, self-rated health measure. Med Care. 2009;47 https://doi.org/10.1097/MLR.0b013e318190b716.

28.

Jacobsen BK, Eggen AE, Mathiesen EB, Wilsgaard T, Njølstad I. Cohort profile: The Tromsø Study. Int J Epidemiol. 2012;41(4):961–7. https://doi.org/10.1093/ije/dyr049.CrossRefPubMed

29.

Rabe-Hesketh S, Skrondal A. Multilevel and longitudinal modeling using stata, Volumes I and II. 3rd ed. College Station: Stata Press; 2012.

30.

Pedersen A, Ellingsen C. Data quality in the Causes of Death Registry. Tidsskr Nor Laegeforen. 2015;135(8):768.CrossRefPubMed

31.

Lorem GF, Schirmer H, Emaus N. Health Impact Index. Development and validation of a method for classifying comorbid disease measured against self-reported health. PLoS One. 2016;11(2) https://doi.org/10.1371/journal.pone.0148830.

32.

Derogatis LR, Lipman RS, Rickels K, Uhlenhuth EH, Covi L. The Hopkins Symptom Checklist (HSCL): A self-report symptom inventory. Behav Sci. 1974;19(1):1–15.CrossRefPubMed

33.

Søgaard AJ, Bjelland I, Tell GS, Røysamb E. A comparison of the CONOR Mental Health Index to the HSCL-10 and HADS. Nor Epidemiol. 2003;13(2):279–84.

34.

Wilsgaard T, Jacobsen BK, Arnesen E. Determining lifestyle correlates of body mass index using multilevel analyses: The Tromsø Study, 1979–2001. Am J Epidemiol. 2005;162(12):1179–88. https://doi.org/10.1093/aje/kwi328.CrossRefPubMed

35.

Seaman SR, White IR. Review of inverse probability weighting for dealing with missing data. Stat Methods Med Res. 2013;22(3):278–95.CrossRefPubMed

36.

Pergialiotis V, Doumouchtsis SK, Perrea D, Vlachos GD. The impact of underweight status on the prognosis of ovarian cancer patients: A meta-analysis. Nutr Cancer. 2016;68(6):918–25. https://doi.org/10.1080/01635581.2016.1190021.CrossRefPubMed

37.

Bruno A, Pace E, Cibella F, Chanez P. Body mass index and comorbidities in adult severe asthmatics. BioMed Res Int. 2014;2014:7. Article ID 607192. doi:10.1155/2014/607192.

38.

Wilsgaard T, Schirmer H, Arnesen E. Impact of body weight on blood pressure with a focus on sex differences: The Tromsø Study, 1986-1995. Arch Intern Med. 2000;160(18):2847–53. https://doi.org/10.1001/archinte.160.18.2847.CrossRefPubMed

39.

Mavaddat N, Kinmonth AL, Sanderson S, Surtees P, Bingham S, Khaw KT. What determines Self-Rated Health (SRH)? A cross-sectional study of SF-36 health domains in the EPIC-Norfolk cohort. J Epidemiol Community Health. 2011;65(9):800–6. https://doi.org/10.1136/jech.2009.090845.CrossRefPubMed

40.

Ford ES, Moriarty DG, Zack MM, Mokdad AH, Chapman DP. Self-reported body mass index and health-related quality of life: Findings from the Behavioral Risk Factor Surveillance System. Obes Res. 2001;9(1):21–31. https://doi.org/10.1038/oby.2001.4.CrossRefPubMed

41.

Herman K, Hopman W, Rosenberg M. Self-rated health and life satisfaction among Canadian adults: associations of perceived weight status versus BMI. Qual Life Res. 2013;22(10):2693–705. https://doi.org/10.1007/s11136-013-0394-9.CrossRefPubMed

42.

Hirko KA, Kantor ED, Cohen SS, Blot WJ, Stampfer MJ, Signorello LB. Body mass index in young adulthood, obesity trajectory, and premature mortality. Am J Epidemiol. 2015; https://doi.org/10.1093/aje/kwv084.

43.

Dahl AK, Fauth EB, Ernsth-Bravell M, Hassing LB, Ram N, Gerstof D. Body mass index, change in body mass index, and survival in old and very old persons. J Am Geriatr Soc. 2013;61(4):512–8.CrossRefPubMedPubMedCentral

44.

Legrand D, Vaes B, Matheï C, Swine C, Degryse J-M. The prevalence of sarcopenia in very old individuals according to the European consensus definition: insights from the BELFRAIL study. Age Ageing. 2013;42(6):727–34.CrossRefPubMed

45.

Hayes AF, Preacher KJ. Statistical mediation analysis with a multicategorical independent variable. Br J Math Stat Psychol. 2014;67(3):451–70.CrossRefPubMed

Title: What is the impact of underweight on self-reported health trajectories and mortality rates: a cohort study
Authors: Geir Fagerjord Lorem
Henrik Schirmer
Nina Emaus
Publication date: 01-12-2017
Publisher: BioMed Central
Published in: Health and Quality of Life Outcomes / Issue 1/2017
Electronic ISSN: 1477-7525
DOI: https://doi.org/10.1186/s12955-017-0766-x

Keynote webinar | Spotlight on sleep in brain health

Springer Medicine

What is the impact of underweight on self-reported health trajectories and mortality rates: a cohort study

Abstract

Background

Methods

Results

Conclusion

Keynote webinar | Spotlight on sleep in brain health

Springer Medicine

Abstract

Background

Methods

Results

Conclusion

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