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. 2018 Jun 13;13(6):e0197830.
doi: 10.1371/journal.pone.0197830. eCollection 2018.

Longitudinal Study of Body Mass Index, Dyslipidemia, Hyperglycemia, and Hypertension in 60,000 Men and Women in Sweden and Austria

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Free PMC article

Longitudinal Study of Body Mass Index, Dyslipidemia, Hyperglycemia, and Hypertension in 60,000 Men and Women in Sweden and Austria

Mieke Van Hemelrijck et al. PLoS One. .
Free PMC article

Abstract

Background: Obesity is suggested to underlie development of other metabolic aberrations, but longitudinal relationships between metabolic factors at various ages has not been studied in detail.

Methods: Data from 27,379 men and 32,275 women with in total 122,940 health examinations in the Västerbotten Intervention Project, Sweden and the Vorarlberg Health Monitoring and Prevention Programme, Austria were used to investigate body mass index (BMI), mid-blood pressure, and fasting levels of glucose, triglycerides, and total cholesterol at baseline in relation to 10-year changes of these factors and weight. We included paired examinations performed 10±2 years apart and used them for longitudinal analysis with linear regression of changes between the ages 30 and 40, 40 and 50, or 50 and 60 years.

Results: Higher levels of BMI were associated with increases in glucose and mid-blood pressure as well as triglycerides levels, and, to a lesser extent, decreases in cholesterol levels. For instance, per 5 kg/m2 higher BMI at age 40, glucose at age 50 increased by 0.24 mmol/l (95%CI: 0.22-0.26) and mid-blood pressure increased by 1.54 mm Hg (95%CI: 1.35-1.74). The strongest association observed was between BMI at age 30 and mid-blood pressure, which was 2.12 mm Hg (95% CI: 1.79-2.45) increase over ten years per 5 kg/m2 higher BMI level. This association was observed at an age when blood pressure levels on average remained stable. Other associations than those with BMI at baseline were much weaker. However, triglyceride levels were associated with future glucose changes among individuals with elevated BMI, particularly in the two older age groups.

Conclusion: BMI was most indicative of long-term changes in metabolic factors, and the strongest impact was observed for increases in blood pressure between 30 and 40 years of age. Our study supports that lifestyle interventions preventing metabolic aberrations should focus on avoiding weight increases.

Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Beta (β) and 95% confidence intervals (CI) from linear regression with baseline A) body mass index, B) mid-blood pressure, C) glucose, D) total cholesterol, and E) triglycerides as exposure, and change in a metabolic factor as outcome, by age (baseline-end of follow-up).
Analyses were adjusted for baseline smoking status and baseline level of the outcome metabolic factor and body mass index (except in A). Analyses of cholesterol and triglycerides as exposures were additionally mutually adjusted for baseline level of the counterpart factor. All metabolic factors, and annual change of the outcome metabolic factor, were log-transformed and entered into the model on their Z transformed scale, standardized by sex and cohort. Each analysis excluded individuals with values more extreme than ±3 standard deviations of the exposure, outcome, or baseline level of the outcome metabolic factor. The number of individuals in each analysis differed depending on completeness of variables and on exclusions and was: 30–40 years, 5253–8388; 40–50 years, 12 442–17 137; 50–60 years, 13 345–16 694. Abbreviation; BP, blood pressure; CI, confidence interval; y, years.
Fig 2
Fig 2. Beta (β) and 95% confidence intervals (CI) from linear regression with baseline plasma triglyceride level as exposure and plasma glucose change as outcome, by age (baseline- end of follow-up) and tertile of baseline BMI.
All analyses were adjusted for baseline smoking status and baseline level of glucose, BMI, and cholesterol. Triglycerides, and annual glucose change as outcome, were log-transformed and entered into the model on their Z transformed scale, standardized by sex and cohort. Each analysis excluded individuals with values more extreme than ±3 standard deviations of the baseline level of triglycerides or glucose or of change in glucose level. The number of individuals in each tertile analysis was: 30–40 y, 2282–2376; 40–50 y, 4082–4217; 50–60 y, 4674–4893. The range of cohort- and sex-specific BMI tertile cut-points were for T1-2: 30 y, 20.6–23.3 kg/m2; 40 y, 21.8–24.2 kg/m2, 50 y, 23.2–24.8 kg/m2; and for T2-3; 30 y, 23.2–25.8 kg/m2, 40 y, 24.9–26.9 kg/m2, 50 y, 26.6–27.6 kg/m2. Abbreviations: BMI, body mass index; CI, confidence interval; y, years.

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Grant support

The study was funded by the Swedish Research Council (Grant 2015-02332 to TS, URL: https://www.vr.se), the Wereld Kanker Onderzoek Fonds NL (Grant R2010/247 to PS, URL: https://www.wkof.nl), and Lion’s Cancer Research Foundation at Umeå University (Grant LP 15-2060 to CH, URL: http://www.cancerforskningsfonden.se/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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