Dataset Information

Associations of sitting accumulation patterns with cardio-metabolic risk biomarkers in Australian adults.

ABSTRACT:

Background

High amounts of time spent sitting can increase cardiovascular disease risk and are deleteriously associated cardio-metabolic risk biomarkers. Though evidence suggests that accruing sitting time in prolonged periods may convey additional risk, verification using high-quality measures is needed. We examined this issue in adults from the Australian Diabetes, Obesity and Lifestyle Study, using accurate measures of sitting accumulation.

Methods

In 2011/12, 739 adults aged 36 to 89 years (mean±SD 58±10 years) wore activPAL3™ monitors (which provide accurate objective measures of sitting); 678 provided ?4 valid days of monitor data and complete cardio-metabolic biomarker and confounder data. Multivariable linear regression models examined associations of sitting time, sitting time accrued in ?30 minute bouts (prolonged sitting time), and three measures of sitting accumulation patterns with cardio-metabolic risk markers: body mass index (BMI), waist circumference, blood pressure, high- and low- density lipoprotein (HDL and LDL) cholesterol, triglycerides, glycated haemoglobin (HbA1c), fasting plasma glucose (FPG) and 2-hour post-load glucose (PLG). Interactions tests examined whether associations of sitting time with biomarkers varied by usual sitting bout duration.

Results

Adjusted for potential confounders, greater amounts of sitting time and prolonged sitting time were significantly (p<0.05) deleteriously associated with BMI, waist circumference, HDL cholesterol, and triglycerides. Total sitting time was also significantly associated with higher PLG. Sitting accumulation patterns of frequently interrupted sitting (compared to patterns with relatively more prolonged sitting) were significantly beneficially associated with BMI, waist circumference, HDL cholesterol, triglycerides, PLG, and with FPG. Effect sizes were typically larger for accumulation patterns than for sitting time. Significant interactions (p<0.05) showed that associations of sitting time with HDL, triglycerides and PLG became more deleterious the longer at a time sitting was usually accumulated.

Conclusions

Adding to previous evidence reliant on low-quality measures, our study showed that accumulating sitting in patterns where sitting was most frequently interrupted had significant beneficial associations with several cardio-metabolic biomarkers and that sitting for prolonged periods at a time may exacerbate some of the effects of sitting time. The findings support sedentary behavior guidelines that promote reducing and regularly interrupting sitting.

SUBMITTER: Bellettiere J

PROVIDER: S-EPMC5491133 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Publications

Associations of sitting accumulation patterns with cardio-metabolic risk biomarkers in Australian adults.

Bellettiere John J Winkler Elisabeth A H EAH Chastin Sebastien F M SFM Kerr Jacqueline J Owen Neville N Dunstan David W DW Healy Genevieve N GN

PloS one 20170629 6

<h4>Background</h4>High amounts of time spent sitting can increase cardiovascular disease risk and are deleteriously associated cardio-metabolic risk biomarkers. Though evidence suggests that accruing sitting time in prolonged periods may convey additional risk, verification using high-quality measures is needed. We examined this issue in adults from the Australian Diabetes, Obesity and Lifestyle Study, using accurate measures of sitting accumulation.<h4>Methods</h4>In 2011/12, 739 adults aged 3 ...[more]

PMID: 28662164

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Project description:BackgroundHigh volumes of sitting time are associated with an elevated risk of type 2 diabetes and cardiovascular disease, and with adverse cardiometabolic risk profiles. However, previous studies have predominately evaluated only total sitting or television (TV) viewing time, limiting inferences about the specific cardiometabolic health impacts of sitting accumulated in different contexts. We examined associations of sitting time in four contexts with cardiometabolic risk biomarkers in Australian adults.MethodsParticipants (n?=?3429; mean?±?SD age 58?±?10 years) were adults without clinically diagnosed diabetes or cardiovascular disease from the 2011-2012 Australian Diabetes, Obesity and Lifestyle (AusDiab) study. Multiple linear regressions examined associations of self-reported context-specific sitting time (occupational, transportation, TV-viewing and leisure-time computer use) with a clustered cardiometabolic risk score (CMR) and with individual cardiometabolic risk biomarkers (waist circumference, BMI, resting blood pressure, triglycerides, HDL- and LDL-cholesterol, and fasting and 2-h post-load plasma glucose).ResultsHigher CMR was significantly associated with greater TV-viewing and computer sitting time (b [95%CI]?=?0.07 [0.04, 0.09] and 0.06 [0.03, 0.09]), and tended to be associated with higher occupational and transport sitting time (0.01 [-?0.01, 0.03] and 0.03 [-?0.00, 0.06]), after adjustment for potential confounders. Furthermore, keeping total sitting time constant, accruing sitting via TV-viewing and computer use was associated with significantly higher CMR (0.05 [0.02, 0.08] and 0.04 [0.01, 0.06]), accruing sitting in an occupational context was associated with significantly lower CMR (-?0.03 [-?0.05, -?0.01]), while no significant association was seen for transport sitting (0.00 [-?0.03, 0.04]). Results varied somewhat between the respective biomarkers; however, higher sitting time in each domain tended to be associated detrimentally with individual biomarkers except for fasting glucose (non-significant associations) and systolic blood pressure (a beneficial association was observed). Overall, associations were stronger for TV-viewing and computer use, and weaker for occupational sitting.ConclusionsHigher context-specific sitting times tended to be detrimentally associated, albeit modestly, with CMR and several cardiometabolic risk biomarkers. There was some evidence suggesting that the context in which people sit is relevant above and beyond total sitting time. Methodological issues notwithstanding, these findings may assist in identifying priorities for sitting-reduction initiatives, in order to achieve optimal cardiometabolic health benefits.

Project description:BackgroundLatin America is facing an increasing burden of nutrition-related non-communicable disease. Little is known about dietary patterns in Guatemalan adults and how dietary patterns are associated with cardio-metabolic disease (CMD) risk.MethodsThis analysis is based on data from a 2002-04 follow-up study of the INCAP Nutrition Supplementation Trial Longitudinal Cohort. Diet data were collected using a validated, semi-quantitative food frequency questionnaire. We derived dietary patterns using principal components analysis. CMD risk was assessed by anthropometry (body mass index, waist circumference), biochemistry (fasting blood glucose and lipids), and clinical (blood pressure) measures. We used sex-stratified multivariable log binomial models to test associations between dietary pattern tertile and CMD risk factors. The sample included 1,428 participants (681 men and 747 women) ages 25-43 years.ResultsWe derived 3 dietary patterns (traditional, meat-based modern, and starch-based modern), collectively explaining 24.2% of variance in the diet. Dietary patterns were not associated with most CMD risk factors; however, higher starch-based modern tertiles were associated with increased prevalence of low high density lipoprotein cholesterol (HDL-c) in men (Prevalence Ratio (PR) 1.17, 95% Confidence Interval (CI) 1.01, 1.20 for tertile 2; PR 1.20, 95% CI 1.00, 1.44 for tertile 3; p trend 0.04). Higher traditional tertile was associated with increased prevalence of abdominal obesity in women (PR 1.24, 95% CI 1.07, 1.43 for tertile 2; PR 1.19, 95% CI 1.02, 1.39 for tertile 3; p trend 0.02) but marginally significant reduced prevalence of low HDL-c in men (PR 0.88, 95% CI 0.76, 1.00 for tertile 2; PR 0.85, 95% CI 0.72, 1.00 for tertile 3; p trend 0.05).ConclusionOur findings suggest the presence of two 'modern diet' patterns in Guatemala - one of which was associated with increased prevalence of low HDL-c in men. The association between the traditional dietary pattern and some CMD risk factors may vary by sex.

Project description:AIM:To identify and describe the characteristics of naturally occurring patterns of exercise, sitting in leisure time and at work and cardiorespiratory fitness, and the association of such profiles with metabolic risk factors, perceived health, and perceived symptoms. METHODS:64,970 participants (42% women, 18-75 years) participating in an occupational health service screening in 2014-2018 were included. Exercise and sitting were self-reported. Cardiorespiratory fitness was estimated using a submaximal cycle test. Latent profile analysis was used to identify profiles. BMI and blood pressure were assessed through physical examination. Perceived back/neck pain, overall stress, global health, and sleeping problems were self-reported. RESULTS:Six profiles based on exercise, sitting in leisure time and at work and cardiorespiratory fitness were identified and labelled; Profile 1 "Inactive, low fit and average sitting in leisure, with less sitting at work"; Profile 2 "Inactive, low fit and sedentary"; Profile 3 "Active and average fit, with less sitting at work"; Profile 4 "Active, average fit and sedentary in leisure, with a sedentary work" (the most common profile, 35% of the population); Profile 5 "Active and fit, with a sedentary work"; Profile 6 "Active and fit, with less sitting at work". Some pairwise similarities were found between profiles (1 and 2, 3 and 4, 5 and 6), mainly based on similar levels of exercise, leisure time sitting and fitness, which translated into similar dose-response associations with the outcomes. In general, profile 1 and 2 demonstrated most adverse metabolic and perceived health, profile 4 had a more beneficial health than profile 3, as did profile 6 compared to profile 5. CONCLUSIONS:The present results implies a large variation in exercise, sitting, and fitness when studying naturally occurring patterns, and emphasize the possibility to target exercise, sitting time, and/or fitness in health enhancing promotion intervention and strategies.

Project description:BACKGROUND:Obesity is one of the conditions that increases the risk of cardiovascular disease. Studies about obesity trajectory and cardio metabolic outcomes at adulthood are still scarce. Therefore, we aimed to assess the association between patterns of overweight over the life-course and cardio metabolic risk factors in young adults. METHODS:In 1982, the maternity hospitals in Pelotas were visited daily and those newborns whose family lived in the urban area of the city were identified (n = 5914), and have prospectively followed for several occasions. Weight and height were measured at every visit. BMI-for-age z-score was calculated using the WHO Child Growth Standards. Overweight and obesity were defined as a BMI greater than or equal to 25 kg/m2 and 30 kg/m2 respectively. This was the definition adopted for evaluations overweight and obesity at 30 years. The participants were divided into eight groups according to the presence of overweight or obesity in childhood, adolescence and adulthood. Blood pressure, random blood glucose, HDL cholesterol, LDL cholesterol triglycerides and fat mass were measured. RESULTS:From 2219 participants with anthropometric data in childhood, adolescence and adulthood, 25% never had been overweight, whereas 11.6% were overweight in the three periods. Random blood glucose, SBP and DBP were higher among those subjects who were always overweight/ obese or only overweight/obese during adolescence and adulthood. The participants who were never overweight/obese or only in childhood or adolescence had a lower cardiovascular risk profile (higher HDL cholesterol, lower blood pressure, lower random glucose, lower LDL cholesterol) at 30 years. Fat mass captured from 25 to 100% of the association of overweight and obesity trajectory with cardiometabolic risk factors. CONCLUSIONS:The tracking of overweight/obesity is associated with an adverse cardio metabolic profile and this association is largely mediated by fat mass in adulthood.

Project description:BackgroundCardiovascular diseases may originate in childhood. Biomarkers identifying individuals with increased risk for disease are needed to support early detection and to optimise prevention strategies.MethodsIn this prospective study, by applying a machine learning to high throughput NMR-based metabolomics data, we identified circulating childhood metabolic predictors of adult cardiovascular disease risk (MetS score) in a cohort of 396 females, followed from childhood (mean age 11·2 years) to early adulthood (mean age 18·1 years). The results obtained from the discovery cohort were validated in a large longitudinal birth cohort of females and males followed from puberty to adulthood (n = 2664) and in four cross-sectional data sets (n = 6341).FindingsThe identified childhood metabolic signature included three circulating biomarkers, glycoprotein acetyls (GlycA), large high-density lipoprotein phospholipids (L-HDL-PL), and the ratio of apolipoprotein B to apolipoprotein A-1 (ApoB/ApoA) that were associated with increased cardio-metabolic risk in early adulthood (AUC = 0·641‒0·802, all p<0·01). These associations were confirmed in all validation cohorts with similar effect estimates both in females (AUC = 0·667‒0·905, all p<0·01) and males (AUC = 0·734‒0·889, all p<0·01) as well as in elderly patients with and without type 2 diabetes (AUC = 0·517‒0·700, all p<0·01). We subsequently applied random intercept cross-lagged panel model analysis, which suggested bidirectional causal relationship between metabolic biomarkers and cardio-metabolic risk score from childhood to early adulthood.InterpretationThese results provide evidence for the utility of a circulating metabolomics panel to identify children and adolescents at risk for future cardiovascular disease, to whom preventive measures and follow-up could be indicated.FundingThis study was financially supported by the Academy of Finland, Ministry of Education of Finland and University of Jyv€askyl€a, the National Nature Science Foundation of China (Grant 31571219), the 111 Project (B17029), the Shanghai Jiao Tong University Zhiyuan Foundation (Grant CP2014013), China Postdoc Scholarship Council (201806230001), the Food and Health Bureau of Hong Kong SAR's Health and Medical Research Fund (HMRF grants 15162161 and 07181036) and the CUHK Direct Grants for Research (2016¢033 and 2018¢034), and a postdoctoral fellowship from K. Carole Ellison (to T.W.). The UK Medical Research Council and Wellcome (Grant ref: 217065/Z/19/Z) and the University of Bristol provide core support for ALSPAC. NFBC1966 received financial support from University of Oulu Grant no. 24000692, Oulu University Hospital Grant no. 24301140, ERDF European Regional Development Fund Grant no. 539/2010 A31592. This work was supported by European Union's Horizon 2020 research and innovation programme LongITools 874739.

Dataset Information

Associations of sitting accumulation patterns with cardio-metabolic risk biomarkers in Australian adults.

Background

Methods

Results

Conclusions

Publications

Associations of sitting accumulation patterns with cardio-metabolic risk biomarkers in Australian adults.

Similar Datasets

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