Associations of device-measured physical activity across adolescence with metabolic traits: prospective cohort study

Background: Multiple occasions of device-measured physical activity have not been previously examined in relation to metabolic traits. We described associations of total activity, moderate-tovigorous physical activity (MVPA), and sedentary time from three accelerometry measures taken across adolescence with detailed traits related to systemic metabolism. Methods and Findings: 1826 male and female participants recruited at birth in 1991-92 via mothers into the Avon Longitudinal Study of Parents and Children offspring cohort who attended clinics in 2003-05, 2005-06, and 2006-08 were included in ≥ 1 analysis. Waist-worn uniaxial accelerometers measured total activity (counts/min), MVPA (min/day), and sedentary time (min/day) over ≥ 3 days at age 12y, 14y, and 15y. Current activity (at age 15y), mean activity across occasions, interaction by previous activity, and change in activity were examined in relation to systolic and diastolic blood pressure, insulin, C-reactive protein, and 230 traits from targeted metabolomics (nuclear magnetic resonance spectroscopy) including lipoprotein cholesterol and triglycerides, amino and fatty acids, glycoprotein acetyls, and others, at age 15y. Mean current total activity was 477.5 counts/min (SD=164.0) while mean MVPA and sedentary time durations were 23.6 min/day (SD=17.9) and 434.5 min/day (SD=64.7), respectively. Mean body mass index at age 15y was 21.4 kg/m2 (SD=3.5). Withinmeasure correlations between first and last activity measurement occasions were low (e.g. r=0.40 for counts/min). Current activity was most strongly associated with cholesterol and triglycerides in HDL and VLDL particles (e.g. -0.002 mmol/l or -0.18 SD-units; 95% CI=-0.24, -0.11 for triglycerides in chylomicrons and XL-VLDL) and with glycoprotein acetyls (-0.02 mmol/l or -0.16 SD-units; 95% CI=-0.22, -0.10), among others. Associations were similar for mean activity across 3 occasions. Attenuations were modest with adjustment for fat mass index based on dual-energy x-ray absorptiometry. In mutually adjusted models, higher MVPA and sedentary time were oppositely associated with cholesterol and triglycerides in VLDL and HDL particles; MVPA more strongly with glycoprotein acetyls and sedentary time more strongly with amino acids. Associations appeared less consistent for sedentary time than for MVPA based on longer-term measures and were weak for change in all activity types from age 12-15y. Evidence was also weak for interaction between activity types at age 15y and previous activity measures in relation to most traits (minimum P=0.003; median P=0.26 for counts/min) with interaction coefficients mostly positive. Study limitations include modest sample sizes and relatively short durations of accelerometry measurement on each occasion (3-7 days) and of time lengths between first and last accelerometry occasions (< 4 years) which can obscure patterns from chance variation and limit description of activity trajectories. Activity was also recorded using uniaxial accelerometers which predated more sensitive triaxial devices. Conclusions: Our results support associations of physical activity with metabolic traits that are small in magnitude and more robust for higher MVPA than lower sedentary time. Activity fluctuates over time, but associations of current activity with most metabolic traits do not differ by previous activity. This suggests that the metabolic effects of physical activity, if causal, depend on most recent engagement

Associations of body mass and fat indexes with cardiometabolic traits

Background Body mass index (BMI) is criticized for not distinguishing fat from lean mass and ignoring fat distribution, leaving its ability to detect health effects unclear. Objectives The aim of this study was to compare BMI with total and regional fat indexes from dual-energy x-ray absorptiometry in their associations with cardiometabolic traits. Duration of exposure to and change in each index across adolescence were examined in relation to detailed traits in young adulthood. Methods BMI was examined alongside total, trunk, arm, and leg fat indexes (each in kilograms per square meter) from dual-energy x-ray absorptiometry at ages 10 and 18 years in relation to 230 traits from targeted metabolomics at age 18 years in 2,840 offspring from the Avon Longitudinal Study of Parents and Children. Results Higher total fat mass index and BMI at age 10 years were similarly associated with cardiometabolic traits at age 18 years, including higher systolic and diastolic blood pressure, higher very low-density lipoprotein and low-density lipoprotein cholesterol, lower high-density lipoprotein cholesterol, higher triglycerides, and higher insulin and glycoprotein acetyls. Associations were stronger for both indexes measured at age 18 years and for gains in each index from age 10 to 18 years (e.g., 0.45 SDs [95% confidence interval: 0.38 to 0.53] in glycoprotein acetyls per SD unit gain in fat mass index vs. 0.38 SDs [95% confidence interval: 0.27 to 0.48] per SD unit gain in BMI). Associations resembled those for trunk fat index. Higher lean mass index was weakly associated with traits and was not protective against higher fat mass index. Conclusions The results of this study support abdominal fatness as a primary driver of cardiometabolic dysfunction and BMI as a useful tool for detecting its effects

sj-docx-1-sjp-10.1177_14034948221119634 – Supplemental material for Marital status and genetic liability independently predict coronary heart disease incidence

Supplemental material, sj-docx-1-sjp-10.1177_14034948221119634 for Marital status and genetic liability independently predict coronary heart disease incidence by Karri Silventoinen, Hannu Lahtinen, Kaarina Korhonen, George Davey Smith, Samuli Ripatti, Tim Morris and Pekka Martikainen in Scandinavian Journal of Public Health</p

LocusZoom plots comparing genetic variants associated with LDL cholesterol and prostate cancer risk at the <i>NPC1L1</i> gene locus.

(TIFF)</p

Study overview.

aThe LDL-c variants were oriented to be in the LDL-c lowering direction, i.e., effect estimates in Mendelian randomisation analysis are per 1 SD lowering of LDL-c. bThe original analysis was conducted by Ioannidou and colleagues [8]. LDL-c, LDL cholesterol; MR, Mendelian randomization; SD, standard deviation.</p

LocusZoom plots comparing genetic variants associated with LDL cholesterol and prostate cancer risk at the <i>HMGCR</i> gene locus.

(TIFF)</p

Results from colocalization analysis using <i>coloc</i> methods.

(XLSX)</p

Results from Mendelian randomisation analysis on the associations between genetically proxied inhibition of drug targets, reduction of LDLR levels of LDL-c levels, and body mass index.

Estimates are effects equivalent to 1 SD reduction in LDL-c levels or 1 SD reduction in plasma protein levels of PCSK9. (XLSX)</p

Data sources for secondary analyses.

(DOCX)</p

Results from Mendelian randomisation investigating the associations between genetically proxied inhibition of drug targets, reduction of LDLR levels of LDL-c levels, and the risk of prostate cancer.

Estimates are effects equivalent to 1 SD reduction in LDL-c levels. (XLSX)</p