Background: Whether all domains of daily‐life moderate‐to‐vigorous physical activity ( MVPA ) are associated with lower blood pressure ( BP ) and how this association depends on age and body mass index remains unclear. Methods and Results: In the population‐based Lifelines cohort (N=125 402), MVPA was assessed by the Short Questionnaire to Assess Health‐Enhancing Physical Activity, a validated questionnaire in different domains such as commuting, leisure‐time, and occupational PA . BP was assessed using the last 3 of 10 measurements after 10 minutes’ rest in the supine position. Hypertension was defined as systolic BP ≥140 mm Hg and/or diastolic BP ≥90 mm Hg and/or use of antihypertensives. In regression analysis, higher commuting and leisure‐time but not occupational MVPA related to lower BP and lower hypertension risk. Commuting‐and‐leisure‐time MVPA was associated with BP in a dose‐dependent manner. β Coefficients (95% CI ) from linear regression analyses were −1.64 (−2.03 to −1.24), −2.29 (−2.68 to −1.90), and finally −2.90 (−3.29 to −2.50) mm Hg systolic BP for the low, middle, and highest tertile of MVPA compared with “No MVPA ” as the reference group after adjusting for age, sex, education, smoking and alcohol use. Further adjustment for body mass index attenuated the associations by 30% to 50%, but more MVPA remained significantly associated with lower BP and lower risk of hypertension. This association was age dependent. β Coefficients (95% CI ) for the highest tertiles of commuting‐and‐leisure‐time MVPA were −1.67 (−2.20 to −1.15), −3.39 (−3.94 to −2.82) and −4.64 (−6.15 to −3.14) mm Hg systolic BP in adults 60 years, respectively. Conclusions: Higher commuting and leisure‐time but not occupational MVPA were significantly associated with lower BP and lower hypertension risk at all ages, but these associations were stronger in older adults.

Aims: To investigate prospectively the association of body fat percentage (BF%) estimates using various equations from bioelectrical impedance analysis (BIA) with cardiovascular events, compared with body mass index (BMI) and waist circumference.Methods and results: We used data of 34 BIA-BF%-equations that were used for estimation of BF% in 6486 (men = 3194, women = 3294) subjects. During a median follow-up of 8.3 years, 510 (7.9%) cardiovascular events (363 in men; 147 in women) occurred. In men, the crude hazard ratio (95% confidence interval) for BF% from the best predicting BIA-BF%-equation was 3.97 (3.30–4.78) against 2.13 (1.85–2.45) for BF% from the BIA device's BIA-BF%-equation, 1.34 (1.20–1.49) for BMI and 1.49 (1.40–1.73) for waist circumference per log-1-SD increase of all. In women, the hazard ratios for best predicting BIA-BF%-equation, BIA device estimation, BMI and waist circumference were 3.80 (2.85–4.99), 1.89 (1.57–2.28), 1.35 (1.21–1.51) and 1.52 (1.31–1.75), respectively. After adjustments for age, Framingham cardiovascular disease risk score and creatinine excretion – a marker of muscle mass – BF%s and BMI remained independently associated with cardiovascular events in both men and women, while waist circumference was independently associated with cardiovascular events in men, but not in women. According to discrimination ability (C-index) and additive predictive value (net reclassification index and integrated discrimination index) on obesity measures to the Framingham cardiovascular disease risk score, BF% was superior to BMI and waist circumference in both men and women.Conclusions: BF% was independently associated with future cardiovascular events. Body fat estimates from the best-predicting BIA-BF%-equations can be a more predictive measurement in cardiovascular risk assessment than BMI or waist circumference.

OBJECTIVES: We examined the dose-dependent association of habitual moderate-to-vigorous physical activity (MVPA) with the biochemical markers for nonalcoholic fatty liver disease (NAFLD) and whether this association changes with age and degree of impaired glucose metabolism. We also investigated whether the associations depend on the domain of MVPA. METHODS: In this study, using data from the population-based Lifelines cohort (N = 42,661), MVPA was self-reported on the short questionnaire to assess health-enhancing physical activity. NAFLD was defined as a fatty liver index value of >60, based on body mass index, waist circumference, plasma triglycerides, and gamma-glutamyltransferase. Glucose metabolism was defined as normal (NGM), impaired (IGM), and type 2 diabetes mellitus (T2DM). Exclusion criteria were previously diagnosed hepatitis or cirrhosis and excessive alcohol use. All analyses were adjusted for age, sex, and education. RESULTS: Higher MVPA was dose dependently associated with a lower risk of having NAFLD: compared with “No MVPA,” the odds ratios (ORs) (95% confidence intervals) for MVPA quintiles were 0.78 (0.71–0.86), 0.64 (0.58–0.70), 0.53 (0.48–0.59), 0.51 (0.46–0.56), and 0.45 (0.41–0.50) for the highest level of MVPA. The association between MVPA and NAFLD was stronger for more impaired glucose status (OR_NGM = 0.49 (0.42–0.57), OR_IGM = 0.46 (0.40–0.54), OR_T2DM = 0.42 (0.27–0.66)) and for older age (OR_{20-40 years} = 0.51 (0.42–0.62), OR_{60-80 years} = 0.37 (0.29–0.48)) with the highest level of MVPA, relative to No MVPA. No favorable association was observed for occupational MVPA. With regard to MVPA and fibrosis, associations with fibrosis markers showed contradictory results. CONCLUSIONS: Higher MVPA levels are dose dependently associated with a lower NAFLD risk. This association is stronger in people with diabetes and older adults.

(1) Background: Little is currently known about the health impacts of daily-life moderate-to-vigorous physical activity (MVPA) in relation to the development of post-transplant diabetes mellitus (PTDM) and the long-term survival of renal transplant recipients (RTRs). (2) Methods: We analyzed self-reported data on MVPA within non-occupational and occupational domains, estimated with the SQUASH questionnaire, from a prospective cohort study of RTRs (n = 650) with a functioning graft exceeding 1 year. PTDM diagnoses were based on plasma glucose levels (≥126 mg/dL), HbA1c (≥6.5%), and the use of antidiabetic medication. Mortality data were retrieved from patient files up to the end of September 2015. (3) Results: During a median follow-up period of 5.3 years, 50 patients (10%) developed PTDM and 129 (19.8%) died. Of these deaths, 53 (8.9%) were caused by cardiovascular disease. Cox regression analyses showed that higher MVPA levels among patients were associated with a lower risk of PTDM (hazard ratio (HR); 95% confidence interval (95%CI) = 0.49; 0.25–0.96, p = 0.04), cardiovascular- (0.34; 0.15–0.77, p = 0.01), and all-cause mortality (0.37; 0.24–0.58, p < 0.001) compared with No-MVPA patients, independently of age, sex, and kidney function parameters. Associations of MVPA with cardiovascular and all-cause mortality remained significant and materially unchanged following further adjustments made for transplant characteristics, lifestyle factors, metabolic parameters, medication use, and creatinine excretion (muscle mass). However, the association between MVPA and PTDM was no longer significant after we adjusted for metabolic confounders and glucose levels. (4) Conclusion: Higher MVPA levels are associated with long-term health outcomes in RTRs.

Background. Hand grip strength (HGS) is a tool for diagnosing sarcopenia. In this study, we examined some anthropometric and body circumference measurements as determinants for HGS. Methods. This cross-sectional study was conducted with participants (Mongolians, n = 1080, aged 18–70, mean age of 41.2 ± 13.9 years, 33.7% of men) from the “Mon-Timeline” cohort study. To measure HGS, a digital grip strength dynamometer was used. Results. Mean HGS in men was 40.1 ± 10.4 kg and in women was 24.5 ± 5.6 kg. Correlation analysis showed that the strongest correlation with HGS was height (r = 0.712, $p<0.001$ ). Moreover, HGS was inversely correlated with age (r = −0.239, $p<0.001$ ) and thigh circumference (r = −0.070, $p<0.01$ ), while it was positively correlated with body weight (r = 0.309, $p<0.001$ ), neck circumference (r = 0.427, $p<0.001$ ), upper arm circumference (r = 0.108, $p<0.0001$ ), lower arm circumference (r = 0.413, $p<0.0001$ ), and calf circumference (r = 0.117, $p<0.0001$ ). In the multivariate linear regression analysis (unstandardized B coefficient, 95% CI), age (−0.159, −0.188; −0.129), sex (−9.262, −10.459; −8.064), height (0.417, 0.357; 0.478), lower arm circumference (1.003, 0.736; 1.270), and calf circumference (−0.162, −0.309; −0.015) were significantly associated with HGS. Conclusions. When detecting sarcopenia using HGS, it is important to take into account variables such as body height and body circumference.

(1) Background: This study investigated the association between body mass index (BMI) categories and comorbidities in the context of a developing country, utilizing data from a nationwide health screening in Mongolia. (2) Methods: The study included 181,080 individuals (mean age 47.0 ± 15.3, 42.0% male) from the population-based general health screening. We counted the number of diseases from participants’ medical records based on ICD-10 codes, excluding those categorized under Z00-Z99 and codes indicating acute disorders, as well as individuals classified as underweight. (3) Results: Among study participants, the prevalence of two or more comorbidities was 4.2%. The weight distribution comprised 40.4% normal weight; 37.1% overweight; and 16.9%, 4.4%, and 1.2% in the Class I, II, and III obesity categories, respectively. Comorbidities increased with BMI: normal weight (0.222); overweight (0.255); and Class I (0.290), Class II (0.302), and Class III obesity (0.303), suggesting a dose-dependent likelihood of having multiple diseases. Adjusted linear regression (beta coefficients, 95% CIs) showed increased comorbidity risks in overweight (0.017, 0.013–0.021) and obesity (0.034, 0.030–0.039). Interaction analysis with age revealed a significant effect (p < 0.001). While comorbidities tend to increase with higher BMI categories in all age-tertile groups, this association was notably stronger among younger individuals. (4) Conclusions: Obesity is associated with a twofold increase in the prevalence of multiple comorbidities compared to normal weight. Our findings also highlight the critical role of age in the development of multiple diseases, with BMI remaining a significant factor across various age groups, encompassing both younger and older adults.