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Background: Personalized interventions aiming to increase physical activity in individuals are effective. However, from a public health perspective, it would be important to stimulate physical activity in larger groups of people who share the vulnerability to be physically inactive throughout adulthood. To find these high-risk groups, we identified 36-year leisure-time physical activity profiles from young adulthood to late midlife in females and males. Moreover, we uncovered which anthropometric-, demographic-, lifestyle-, and health-related characteristics were associated with these physical activity profiles. Methods: We included 2,778 females and 1,938 males from the population-based older Finnish Twin Cohort Study, who responded to health and behavior surveys at the mean ages of 24, 30, 40 and 60. Latent profile analysis was used to identify longitudinal leisure-time physical activity profiles. Results: We found five longitudinal leisure-time physical activity profiles for both females and males. Females' profiles were: 1) Low increasing moderate (29%), 2) Moderate stable (23%), 3) Very low increasing low (20%), 4) Low stable (20%) and 5) High increasing high (9%). Males' profiles were: 1) Low increasing moderate (29%), 2) Low stable very low (26%), 3) Moderate decreasing low (21%), 4) High fluctuating high (17%) and 5) Very low stable (8%). In both females and males, lower leisure-time physical activity profiles were associated with lower education, higher body mass index, smoking, poorer perceived health, higher sedentary time, high blood pressure, and a higher risk for type 2 diabetes. Furthermore, lower leisure-time physical activity was linked to a higher risk of depression in females. Conclusions: We found several longitudinal leisure-time physical activity profiles with unique changes in both sexes. Fewer profiles in females than in males remained or became low physically active during the 36-year follow-up. We observed that lower education, higher body mass index, and more smoking already in young adulthood were associated with low leisure-time physical activity profiles. However, the fact that several longitudinal profiles demonstrated a change in their physical activity behavior over time implies the potential for public health interventions to improve leisure-time physical activity levels. [ABSTRACT FROM AUTHOR]

Summary: Background: Living in single parent and blended families or as an only child—compared to living in two‐parent biological families or with siblings, respectively—is associated with a higher body mass index (BMI) in cross‐sectional studies. However, longitudinal research addressing the children's BMI in this context is scarce. Further, little is known about the association between family structure and metabolic health. Objectives: This study aimed at investigating the association between both aspects of family structure with BMI and a metabolic score (MetS). Methods: Cross‐sectional data from 7804 children participating in the European multi‐center I.Family study (2013/2014) and longitudinal data from 5621 children who also participated previously in the IDEFICS study (2007–2010) were used. Family structure was assessed by a detailed interview. BMI z‐score and the MetS were based on measured anthropometry, blood pressure, high‐density lipoprotein, blood glucose, and triglycerides. Linear regressions were performed to model associations between family structure with BMI and MetS. Results: Children from single‐parent families had higher BMI z‐scores in the cross‐sectional (β = 0.09, 95% confidence interval [CI]: 0.001 to 0.18) and longitudinal analyses compared to those from two‐parent families. Cross‐sectionally, the number of siblings was associated with lower BMI z‐scores (β = −0.07, 95% CI: −0.10 to −0.03) and lower MetS (β = −0.14, 95% CI: −0.26 to −0.01). Longitudinally, only children between baseline and follow‐up had higher BMI z‐scores at follow‐up (β = 0.07, 95% CI: 0.01 to 0.14) compared to stable siblings. Conclusion: Obesity prevention measures should focus on single‐parent households and families with an only child. [ABSTRACT FROM AUTHOR]

Introduction Genetic pleiotropy, in which the same genes affect two or more traits, may partially explain the frequently observed associations between high physical activity (PA) and later reduced morbidity or mortality. This study investigated associations between PA polygenic risk scores (PRS) and cardiometabolic diseases among the Finnish population. Methods PRS for device-measured overall PA were adapted to a FinnGen study cohort of 218,792 individuals with genomewide genotyping and extensive digital longitudinal health register data. Associations between PA PRS and body mass index, diseases, and mortality were analyzed with linear and logistic regression models. Results A high PA PRS predicted a lower body mass index (β = −0.025 kg·m−2 per one SD change in PA PRS, SE = 0.013, P = 1.87 × 10−80). The PA PRS also predicted a lower risk for diseases that typically develop later in life or not at all among highly active individuals. A lower disease risk was systematically observed for cardiovascular diseases (odds ratio [OR] per 1 SD change in PA PRS = 0.95, P = 9.5 × 10−19) and, for example, hypertension [OR = 0.93, P = 2.7 × 10−44), type 2 diabetes (OR = 0.91, P = 4.1 × 10−42), and coronary heart disease (OR = 0.95, P = 1.2 × 10−9). Participants with high PA PRS had also lower mortality risk (OR = 0.97, P = 0.0003). Conclusions Genetically less active persons are at a higher risk of developing cardiometabolic diseases, which may partly explain the previously observed associations between low PA and higher disease and mortality risk. The same inherited physical fitness and metabolism-related mechanisms may be associated both with PA levels and with cardiometabolic disease risk. [ABSTRACT FROM AUTHOR]