Longitudinal and age trends of metabolic syndrome and its risk factors: the Family Heart Study

Aldi T Kraja, Ingrid B Borecki, Kari North, Weihong Tang, Richard H Myers, Paul N Hopkins, Donna Arnett, Jonathan Corbett, Avril Adelman, Michael A Province, Aldi T Kraja, Ingrid B Borecki, Kari North, Weihong Tang, Richard H Myers, Paul N Hopkins, Donna Arnett, Jonathan Corbett, Avril Adelman, Michael A Province

Abstract

Background: We report longitudinal changes in the metabolic syndrome (MetS) in 2,458 participants from 480 families in the Family Heart Study. Participants were examined between 1994-96 (FHS-T1) and 2002-03 (FHS-T2), about 7.4 years apart. Additionally, the impact of medication on estimates of MetS prevalence, and associations of MetS with prevalent coronary heart disease (CHD) and type 2 diabetes (T2D) were studied.

Methods: Three definitions for MetS prevalence were considered. One represented the original (o) National Cholesterol Education Program (NCEP) MetS criteria. Two others considered the confounding of medications effects, respectively (m) lipid medications constituted a categorical diagnostic criterion for lipids variables, and (c) lipids and blood pressure variables were corrected with average clinical trials medications effects. Logistic regression of MetS on CHD and T2D, as well as the trend analysis of MetS by age, were performed.

Results: MetS increased from 17.1% in FHS-T1(o) to 28.8% in FHS-T2(o); from 19.7% in FHS-T1(m) to 42.5% in FHS-T2(m); and from 18.4% in FHS-T1(c) to 33.6% in FHS-T2(c). While we observed adverse changes in all risk factors, the greatest increase was for waist circumference (25%). The percentages of MetS were about 2 to almost 3 times higher in ages 50 years and older than in younger ages. The odds of having prevalent CHD were about 2.5 times higher in the subjects classified with MetS than without.

Conclusion: MetS percentages increased noticeably longitudinally and cross-sectionally with older age. These conclusions were reached with and without considering medication use, but correcting risk factors for medications use affects the MetS prevalence estimates. As found in other studies, MetS was associated with increased odds for prevalent CHD.

Figures

Figure 1
Figure 1
Percentages of MetS and its risk factors in the FHS-Time 1 and FHS-Time 2. Three analyses were applied: FHS-T1 (o)/FHS-T2 (o) – original MetS (no medication effects on lipids were considered); FHS-T1 (m)/FHS-T2 (m) – medication effects on BP, lipids, and GLUC were considered as categorical effects; FHS-T1 (c)/FHS-T2 (c) – for participants that used anti-hypertensive/anti-hyperlipidemic medication(s), corrections of the corresponding risk factors with clinical trials medication average effects for BP and lipids were performed (see Methods). Footnote. MS3, MS4, MS5 are the percentages of participants with at least 3, 4, and 5 risk factors beyond the MetS NCEP thresholds.
Figure 2
Figure 2
Trends of MetS percentages per age groups in the FHS-Time 1 in a familial random sample and in a familial CHD selected sample. Reported are the corresponding percentages of MetS by 5 years age groups, as well as percentages of ages up to 50, 50 and older for FHS-Time 1, for (o), (m), and (c) methods (see Methods).
Figure 3
Figure 3
Trends of MetS percentages per age groups in the FHS-Time 2 in a familial random and in a familial CHD selected sample. Reported are the corresponding percentages of MetS by 5 years age groups, as well as percentages of ages up to 55, 55 and older for FHS-Time 2, for (o), (m), and (c) methods (see Methods).

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Source: PubMed

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