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Life course trajectories of cardiovascular risk: Impact on atherosclerotic and metabolic indicators.

ABSTRACT: BACKGROUND AND AIMS:In this analysis, we estimated population-level trajectory groups of life course cardiovascular risk to explore their impact on mid-life atherosclerotic and metabolic outcomes. METHODS:This prospective study followed n?=?1269 Bogalusa Heart participants, each with at least 4 study visits from childhood in 1973 through adulthood in 2016. We used discrete mixture modeling to determine trajectories of cardiovascular risk percentiles from childhood to adulthood. Outcomes included mid-life subclinical atherosclerotic measures [(carotid intima-media thickness (cIMT), pulse wave velocity (PWV)], metabolic indicators [(diabetes and body mass index (BMI)], and short physical performance battery (SPPB). RESULTS:Between the mean ages of 9.6-48.3 years, we estimated five distinct trajectory groups of life course cardiovascular risk (High-Low, High-High, Mid-Low, Low-Low, and Low-High). Adult metabolic and vascular outcomes were significantly determined by life course cardiovascular risk trajectory groups (all p?

SUBMITTER: Pollock BD

PROVIDER: S-EPMC7521150 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Life course trajectories of cardiovascular risk: Impact on atherosclerotic and metabolic indicators.

Pollock Benjamin D BD Stuchlik Patrick P Harville Emily W EW Mills Katherine T KT Tang Wan W Chen Wei W Bazzano Lydia A LA

Atherosclerosis 20181108

<h4>Background and aims</h4>In this analysis, we estimated population-level trajectory groups of life course cardiovascular risk to explore their impact on mid-life atherosclerotic and metabolic outcomes.<h4>Methods</h4>This prospective study followed n = 1269 Bogalusa Heart participants, each with at least 4 study visits from childhood in 1973 through adulthood in 2016. We used discrete mixture modeling to determine trajectories of cardiovascular risk percentiles from childhood to adulthood. Ou ...[more]

PMID: 30453117

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Project description:Although exposure to overweight and obesity at different ages is associated to a higher risk of type 2 diabetes, the effect of different patterns of exposure through life remains unclear. We aimed to characterize life-course trajectories of weight categories and estimate their impact on the incidence of type 2 diabetes. We categorized the weight of 7203 participants as lean, normal or overweight at five time-points from ages 7-55 using retrospective data. Participants were followed for an average of 19 years for the development of type 2 diabetes. We used latent class analysis to describe distinctive trajectories and estimated the risk ratio, absolute risk difference and population attributable fraction (PAF) associated to different trajectories using Poisson regression. We found five distinctive life-course trajectories. Using the stable-normal weight trajectory as reference, the stable overweight, lean increasing weight, overweight from early adulthood and overweight from late adulthood trajectories were associated to higher risk of type 2 diabetes. The estimated risk ratios and absolute risk differences were statistically significant for all trajectories, except for the risk ratio of the lean increasing trajectory group among men. Of the 981 incident cases of type 2 diabetes, 47.4% among women and 42.9% among men were attributable to exposure to any life-course trajectory different from stable normal weight. Most of the risk was attributable to trajectories including overweight or obesity at any point of life (36.8% of the cases among women and 36.7% among men). The overweight from early adulthood trajectory had the highest impact (PAF: 23.2% for woman and 28.5% for men). We described five distinctive life-course trajectories of weight that were associated to increased risk of type 2 diabetes over 19 years of follow-up. The variability of the effect of exposure to overweight and obesity on the risk of developing type 2 diabetes was largely explained by exposure to the different life-course trajectories of weight.

Project description:Background and aimsAlcohol consumption changes markedly over the life course, with important implications for health and social development. Assessment of these patterns often relies on cross-sectional data, which cannot fully capture how individuals' drinking changes as they age. This study used data from 18 waves of a general population panel survey to measure drinking trajectories over the life course in Australia.Design and settingLongitudinal survey data from the Household, Income and Labour Dynamics in Australia (HILDA) survey between 2001 and 2018.ParticipantsA total of 20 593 individuals ages 15 or above in two samples assessing quantity-frequency (n = 20 569, 52.0% female) and risky single occasion drinking (RSOD), respectively, (n = 17 340, 52.5% female), interviewed as part of HILDA.MeasurementsUsual quantity of alcohol consumed per drinking occasion; frequency of drinking occasions per week; average daily consumption, calculated by combining reported usual quantity and frequency; and average reported frequency of RSOD per week.FindingsMultilevel, mixed effects models run with fractional polynomial terms found similar male and female alcohol consumption trajectories for quantity-frequency and RSOD measures. Usual quantity of alcohol consumed per drinking occasion (5.4 drinks for men, 3.8 for women) and RSOD frequency (0.56 occasions/week for men, 0.38 for women) peaked in young adulthood, whereas frequency of drinking occasions (2.5 occasions/week for men, 1.7 for women) peaked in middle age. Middle-age drinkers had the highest average daily consumption of alcohol (1.4 drinks/day for 54-year-old men, 0.6 drinks for 57-year-old women) and engaged in RSOD slightly less than young adults.ConclusionsAlcohol consumption in Australia appears to vary substantially over the life course, with usual quantity per drinking occasion and frequency of risky single occasion drinking peaking during early adulthood and average daily consumption and frequency of consumption peaking in middle age.

Dataset Information

Life course trajectories of cardiovascular risk: Impact on atherosclerotic and metabolic indicators.

Publications

Life course trajectories of cardiovascular risk: Impact on atherosclerotic and metabolic indicators.

Similar Datasets

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