Dataset Information

A cross-sectional analysis of the associations between leisure-time sedentary behaviors and clustered cardiometabolic risk.

ABSTRACT: The aim of this study was to conduct a comprehensive investigation of the association between different types of leisure-time sedentary behavior (watching television, using a computer, reading and socializing) and clustered cardiometabolic risk in apparently healthy adults aged 40 to 65 years.One hundred seventy-three participants from the general population (64% women; mean age?=?54.4 years) consented to attend a cardiovascular examination program and to complete a questionnaire on leisure-time sedentary behaviors. Waist circumference, blood pressure, glucose, triglycerides, and high-density lipoprotein cholesterol of non-fasting blood samples were assessed, and a clustered cardiometabolic risk score [CMRS] was calculated. Data were collected between February and July 2015. Associations between leisure-time sedentary behaviors and CMRS were analyzed using linear and quantile regression, adjusted for socio-demographic variables and other types of leisure-time sedentary behavior (model 1) and additionally, adjusted for leisure-time physical activity and traveling in motor vehicles (model 2).Linear regression revealed that there was a positive association between watching television and CMRS (model 1: b?=?0.27 [CI: 0.03; 0.52]; model 2: b?=?0.30 [CI: 0.05; 0.56]). In addition, quantile regression analysis revealed that using a computer was negatively associated with the 50th (model 1: b?=?-?0.43 [CI: -0.79; -?0.07]) and the 75th percentiles (model 1: b?=?-?0.71 [CI: -1.27; -?0.14]) of CMRS. Reading and socializing were not associated with CMRS.Watching television was positively associated with a clustered cardiometabolic risk score, while time spent using a computer revealed inconsistent findings. Our results give reason to consider different types of behaviors in which individuals are sedentary and the associations between these behaviors and cardiometabolic risk, supporting the need for behavior-specific assessments as well as public health recommendations to maintain or enhance adults' health.Clinical trial registration number: NCT02990039 , Retrospectively registered (December 12, 2016).

SUBMITTER: Ullrich A

PROVIDER: S-EPMC5839009 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A cross-sectional analysis of the associations between leisure-time sedentary behaviors and clustered cardiometabolic risk.

Ullrich Antje A Voigt Lisa L Baumann Sophie S Weymar Franziska F John Ulrich U Dörr Marcus M Ulbricht Sabina S

BMC public health 20180306 1

<h4>Background</h4>The aim of this study was to conduct a comprehensive investigation of the association between different types of leisure-time sedentary behavior (watching television, using a computer, reading and socializing) and clustered cardiometabolic risk in apparently healthy adults aged 40 to 65 years.<h4>Methods</h4>One hundred seventy-three participants from the general population (64% women; mean age = 54.4 years) consented to attend a cardiovascular examination program and to compl ...[more]

PMID: 29510707

Similar Datasets

Project description:Limited data exists on the interrelationships between physical activity (PA), sedentary behaviors and sleep concerning cardiometabolic risk factors in aged adults at high cardiovascular disease risk. Our aim was to examine independent and joint associations between time spent in leisure-time PA, sedentary behaviors and sleep on the prevalence of obesity, type 2 diabetes (T2D) and components of the metabolic syndrome (MetS) in Mediterranean individuals at high cardiovascular risk. Cross-sectional analyses were performed on baseline data from 5776 Spanish adults (aged 55-75y in men; 60-75y in women) with overweight/obesity and MetS, from October 2013 to October 2016, in the PREDIMED-PLUS trial. Employing multivariable-adjusted Cox regression with robust variance and constant time (given the cross-sectional design), higher prevalence of obesity, T2D and abdominal obesity as component of the MetS were associated with greater time in TV-viewing (Relative Risk, RR: 1.02, 95%CI: 1.01, 1.03; RR:1.04, 95%CI: 1.02, 1.06 and RR: 1.01 95%CI: 1.00, 1.02; respectively, all P < .01). Conversely, greater time in moderate-vigorous PA (MVPA) was associated with lower prevalence of obesity, T2D, abdominal obesity and low HDL-cholesterol (RR: 0.95, 95%CI: 0.93, 0.97; RR: 0.94, 95%CI: 0.89, 0.99; RR: 0.97, 95%CI: 0.96, 0.98; and RR: 0.95, 95%CI: 0.91, 0.99, respectively, all P < .05). For these outcomes, theoretically substituting 1-h/day of MVPA for 1-h/day TV-viewing was also significantly associated with lower prevalence (RR 0.91 to 0.97, all P < .05). Similar lower RR in these outcomes was observed when substituting 1-h/day of MVPA for 1-h/day of sleeping. Longer time watching TV and not meeting MVPA recommendations were jointly associated with higher RR of the prevalence of obesity and T2D. We concluded that, in senior individuals at high cardiovascular risk, greater time spent on MVPA and fewer on sedentary behaviors was inversely associated with prevalence of obesity, T2D, and some of the components of MetS.

Project description:ObjectiveTo examine the associations of sedentary time and physical activity with biomarkers of cardiometabolic health, including the potential collective impact of shifting mean time use from less- to more-active behaviours (cross-sectionally, using isotemporal substitution), in adults with type 2 diabetes.MethodsParticipants with overweight/obese body mass index (BMI; ≥25 kg/m2) (n = 279; 158 men, mean [SD] age = 58.2 [8.6] years) wore Actigraph GT1M accelerometers (waking hours; seven days) to assess moderate- to vigorous-intensity physical activity (MVPA), light-intensity activity, and sedentary time (segregated into non-prolonged [accumulated in bouts <30min] and prolonged [accumulated in bouts ≥30 min]). Cross-sectional associations with waist circumference, BMI, fasting blood (HbA1c, glucose, triacylglycerols, high-density lipoprotein cholesterol), and blood pressure of these activity variables (30 min/day increments) were examined adjusted for confounders and wear then, if significant, examined using isotemporal substitution modelling.ResultsWaist circumference and BMI were significantly (p<0.05) associated with more prolonged sedentary time and less light-intensity activity. Light intensity activity was also significantly associated with lower fasting plasma glucose (relative rate: 0.98, 95% CI: 0.97, 1.00; p<0.05). No biomarker was significantly associated with non-prolonged sedentary time or MVPA. Lower mean prolonged sedentary time (-30 min/day) with higher mean light intensity time (+30 min/day) was significantly associated with lower waist circumference (β = -0.77, 95% CI: -1.33, -0.22 cm). Lower mean prolonged sedentary time (-30 min/day) with either 30 min/day higher mean non-prolonged sedentary time (β = -0.35, 95%CI: -0.70, -0.01 kg/m2) or light-intensity time (β = -0.36, -0.61, -0.11 kg/m2) was associated with significantly lower average BMI.ConclusionsSignificantly improved mean levels of waist circumference and BMI were observed when shifting time from prolonged sedentary to non-prolonged sedentary or light-intensity activity (cross-sectionally). Lifestyle interventions in overweight/obese adults with type 2 diabetes might consider targeting shifts in these non-MVPA activities to more rigorously evaluate their potential cardiometabolic benefit in this population.

Project description:ObjectiveInvestigating the association between total physical activity, physical activity in different domains and sedentary time with clustered metabolic risk in patients with type 2 diabetes from Jiangsu province, China.DesignInterview-based cross-sectional study conducted between December 2013 and January 2014.Setting44 selected townships across two cities, Changshu and Huai'an, in Jiangsu province.Participants20 340 participants selected using stratified cluster-randomised sampling and an interviewer-managed questionnaire.MethodsWe constructed clustered metabolic risk by summing sex-specific standardised values of waist circumference, fasting triacylglycerol, fasting plasma glucose, systolic blood pressure and the inverse of blood high-density lipoprotein cholesterol (HDL-cholesterol). Self-reported total physical activity included occupation, commuting and leisure-time physical activity. The un-standardised regression coefficient [B] and its 95% CI were calculated using multivariate linear regression analyses.ResultsThis study included 17 750 type 2 diabetes patients (aged 21-94 years, 60.3% female). The total (B=-0.080; 95% CI: -0.114 to -0.046), occupational (B=-0.066; 95% CI: -0.101 to- 0.031) and leisure-time physical activity (B=-0.041; 95% CI: -0.075 to -0.007), and sedentary time (B=0.117; 95% CI: 0.083 to 0.151) were associated with clustered metabolic risk. Total physical activity, occupational physical activity and sedentary time were associated with waist circumference, triacylglycerol and HDL-cholesterol, but not with systolic blood pressure. Commuting physical activity and sedentary time were significantly associated with triacylglycerol (B=-0.012; 95% CI: -0.019 to -0.005) and fasting plasma glucose (B=0.008; 95% CI: 0.003 to 0.01), respectively. Leisure-time physical activity was only significantly associated with systolic blood pressure (B=-0.239; 95% CI: -0.542 to- 0.045).ConclusionsTotal, occupational and leisure-time physical activity were inversely associated with clustered metabolic risk, whereas sedentary time increased metabolic risk. Commuting physical activity was inversely associated with triacylglycerol. These findings suggest that increased physical activity in different domains and decreased sedentary time may have protective effects against metabolic risk in type 2 diabetes patients.

Dataset Information

A cross-sectional analysis of the associations between leisure-time sedentary behaviors and clustered cardiometabolic risk.

Publications

A cross-sectional analysis of the associations between leisure-time sedentary behaviors and clustered cardiometabolic risk.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets