Search

Introduction: Few studies have examined the longitudinal associations of fitness or changes in fitness on the risk of developing dyslipidemias. This study examined the associations of (1) baseline fitness with 25-year dyslipidemia incidence and (2) 20-year fitness change on dyslipidemia development in middle age in the Coronary Artery Risk Development in Young Adults Study (CARDIA).Methods: Multivariable Cox proportional hazards regression models were used to test the association of baseline fitness (1985-1986) with dyslipidemia incidence over 25 years (2010-2011) in CARDIA (N=4,898). Modified Poisson regression models were used to examine the association of 20-year change in fitness with dyslipidemia incidence between Years 20 and 25 (n=2,487). Data were analyzed in June 2014 and February 2015.Results: In adjusted models, the risk of incident low high-density lipoprotein cholesterol (HDL-C); high triglycerides; and high low-density lipoprotein cholesterol (LDL-C) was significantly lower, by 9%, 16%, and 14%, respectively, for each 2.0-minute increase in baseline treadmill endurance. After additional adjustment for baseline trait level, the associations remained significant for incident high triglycerides and high LDL-C in the total population and for incident high triglycerides in both men and women. In race-stratified models, these associations appeared to be limited to whites. In adjusted models, change in fitness did not predict 5-year incidence of dyslipidemias, whereas baseline fitness significantly predicted 5-year incidence of high triglycerides.Conclusions: Our findings demonstrate the importance of cardiorespiratory fitness in young adulthood as a risk factor for developing dyslipidemias, particularly high triglycerides, during the transition to middle age. [ABSTRACT FROM AUTHOR]

Importance: Obesity is a major determinant of disease burden worldwide. Polygenic risk scores (PRSs) have been posited as key predictors of obesity. How a PRS can be translated to the clinical encounter (especially in the context of fitness, activity, and parental history of overweight) remains unclear., Objective: To quantify the relative importance of a PRS, fitness, activity, parental history of overweight, and body mass index (BMI) (calculated as weight in kilograms divided by height in meters squared) in young adulthood on BMI trends over 25 years., Design, Setting, and Participants: This population-based prospective cohort study at 4 US centers included white individuals and black individuals with assessments of polygenic risk of obesity, fitness, activity, and BMI in young adulthood (in their 20s) and up to 25 years of follow-up. Data collected between March 1985 and August 2011 were analyzed from April 25, 2019, to September 29, 2019., Main Outcomes and Measures: Body mass index at the initial visit and 25 years later., Results: This study evaluated an obesity PRS from a recently reported study of 1608 white individuals (848 women [52.7%]) and 909 black individuals (548 women [60.3%]) across the United States. At baseline (year 0), mean (SD) overall BMI was 24.2 (4.5), which increased to 29.6 (6.9) at year 25. Among white individuals, the PRS (combined with age, sex, self-reported parental history of overweight, and principal components of ancestry) explained 11.9% (at year 0) and 13.6% (at year 25) of variation in BMI. Although the addition of fitness increased the explanatory capability of the model (24.0% variance at baseline and up to 18.1% variance in BMI at year 25), baseline BMI in young adulthood was the strongest factor, explaining 52.3% of BMI in midlife in combination with age, sex, and self-reported parental history of overweight. Accordingly, models that included baseline BMI (especially BMI surveillance over time) were better in predicting BMI at year 25 compared with the PRS. In fully adjusted models, the effect sizes for fitness and the PRS on BMI were comparable in opposing directions. The added explanatory capacity of the PRS among black individuals was lower than among white individuals. Among white individuals, addition of baseline BMI and surveillance of BMI over time was associated with improved precision of predicted BMI at year 25 (mean error in predicted BMI 0 kg/m2 [95% CI, -11.4 to 11.4] to 0 kg/m2 [95% CI, -8.5 to 8.5] for baseline BMI and mean error 0 kg/m2 [95% CI, -5.3 to 5.3] for BMI surveillance)., Conclusions and Relevance: Cardiorespiratory fitness in young adulthood and a PRS are modestly associated with midlife BMI, although future BMI is associated with BMI in young adulthood. Fitness has a comparable association with future BMI as does the PRS. Caution should be exercised in the widespread use of polygenic risk for obesity prevention in adults, and close clinical surveillance and fitness may have prime roles in limiting the adverse consequences of elevated BMI on health.

Background/objectives: Overweight and obesity (OWOB) is a global epidemic. Adults and adolescents from low-income households are at higher risk to be OWOB. This study examined the relationship between income and OWOB prevalence in children and adolescents (518 years) in the United States (US) within and across race/ethnicities, and changes in this relationship from 1971 to 2014., Subjects/methods: A meta-analysis of a nationally representative sample (N = 73,891) of US children and adolescents drawn from three datasets (i.e., National Health and Nutrition Examination Survey, National Longitudinal Survey of Youth, & the Early Childhood Longitudinal Program) which included 14 cross-sectional waves spanning 1971-2014 was conducted. The exposure was household income-to-poverty ratio (low income = 0.00-1.00, middle income = 1.01-4.00, high income >4.00) with prevalence of overweight or obesity (body mass index ≥ 85th percentile) as the outcome., Results: Children and adolescents from middle-income and high-income households were 0.78 (95% CI = 0.72, 0.83) and 0.68 (95% CI = 0.59, 0.77) times as likely to be OWOB compared to children and adolescents in low-income households. Separate analyses restricted to each racial/ethnic group showed children and adolescents from middle- and high-income households were less likely to be OWOB compared to their low-income peers within the White, Hispanic, and Other race/ethnic groups. Children and adolescents from low-income households who were Black were not more likely to be OWOB than their high- and middle-income counterparts. Analyses within each income stratum indicated that race/ethnicity was not related to the prevalence of OWOB in low-income households. However, racial/ethnic differences in OWOB were evident for children and adolescents in middle- and high-income households. Disparities in the prevalence of OWOB between low-income children and adolescents and their middle- and high-income counterparts have increased from 1971 to 2014., Conclusions: Income and OWOB are related in US children and adolescents. Racial/ethnic differences in the prevalence of OWOB emerge in middle- and high-income households. Disparities in OWOB prevalence are growing.

Type 2 diabetes (T2D) prevalence in the United States is significantly higher in African Americans vs Whites. Yet, the physiological mechanisms contributing to this health disparity have been poorly described. To design effective strategies to reduce this disparity, there is a need to determine whether racial differences in diabetes prevalence are attributable to modifiable or non-modifiable factors. This review synthesizes and critically evaluates the potential physiological and genetic mechanisms that may contribute to the higher susceptibility of African Americans to T2D. These mechanisms include: 1) obesity and fat distribution; 2) metabolic flexibility; 3) muscle physiology; 4) energy expenditure and fitness; and 5) genetics. We focus on the clinical significance of findings and limitations of the recent literature.

Although regular exercise improves submaximal aerobic capacity, there is large variability in its response to exercise training. While this variation is thought to be partly due to genetic differences, relatively little is known about the causal genes. Submaximal aerobic capacity traits in the current report include the responses of oxygen consumption (ΔVO(2)60), power output (ΔWORK60), and cardiac output (ΔQ60) at 60% of VO2max to a standardized 20-week endurance exercise training program. Genome-wide linkage analysis in 475 HERITAGE Family Study Caucasians identified a locus on chromosome 13q for ΔVO(2)60 (LOD = 3.11). Follow-up fine mapping involved a dense marker panel of over 1,800 single-nucleotide polymorphisms (SNPs) in a 7.9-Mb region (21.1-29.1 Mb from p-terminus). Single-SNP analyses found 14 SNPs moderately associated with both ΔVO(2)60 at P ≤ 0.005 and the correlated traits of ΔWORK60 and ΔQ60 at P < 0.05. Haplotype analyses provided several strong signals (P < 1.0 × 10(-5)) for ΔVO(2)60. Overall, association analyses narrowed the target region and included potential biological candidate genes (MIPEP and SGCG). Consistent with maximal heritability estimates of 23%, up to 20% of the phenotypic variance in ΔVO(2)60 was accounted for by these SNPs. These results implicate candidate genes on chromosome 13q12 for the ability to improve submaximal exercise capacity in response to regular exercise. Submaximal exercise at 60% of maximal capacity is an exercise intensity that falls well within the range recommended in the Physical Activity Guidelines for Americans and thus has potential public health relevance.