Dataset Information

A cut-off of daily sedentary time and all-cause mortality in adults: a meta-regression analysis involving more than 1 million participants.

ABSTRACT: BACKGROUND:The appropriate limit to the amount of daily sedentary time (ST) required to minimize mortality is uncertain. This meta-analysis aimed to quantify the dose-response association between daily ST and all-cause mortality and to explore the cut-off point above which health is impaired in adults aged 18-64 years old. We also examined whether there are differences between studies using self-report ST and those with device-based ST. METHODS:Prospective cohort studies providing effect estimates of daily ST (exposure) on all-cause mortality (outcome) were identified via MEDLINE, PubMed, Scopus, Web of Science, and Google Scholar databases until January 2018. Dose-response relationships between daily ST and all-cause mortality were examined using random-effects meta-regression models. RESULTS:Based on the pooled data for more than 1 million participants from 19 studies, the results showed a log-linear dose-response association between daily ST and all-cause mortality. Overall, more time spent in sedentary behaviors is associated with increased mortality risks. However, the method of measuring ST moderated the association between daily ST and mortality risk (p?

SUBMITTER: Ku PW

PROVIDER: S-EPMC5998593 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A cut-off of daily sedentary time and all-cause mortality in adults: a meta-regression analysis involving more than 1 million participants.

Ku Po-Wen PW Steptoe Andrew A Liao Yung Y Hsueh Ming-Chun MC Chen Li-Jung LJ

BMC medicine 20180525 1

<h4>Background</h4>The appropriate limit to the amount of daily sedentary time (ST) required to minimize mortality is uncertain. This meta-analysis aimed to quantify the dose-response association between daily ST and all-cause mortality and to explore the cut-off point above which health is impaired in adults aged 18-64 years old. We also examined whether there are differences between studies using self-report ST and those with device-based ST.<h4>Methods</h4>Prospective cohort studies providing ...[more]

PMID: 29793552

Similar Datasets

Project description:ImportanceAsia is home to the largest diabetic populations in the world. However, limited studies have quantified the association of diabetes with all-cause and cause-specific mortality in Asian populations.ObjectivesTo evaluate the association of diabetes with all-cause and cause-specific mortality in Asia and to investigate potential effect modifications of the diabetes-mortality associations by participants' age, sex, education level, body mass index, and smoking status.Design, setting, and participantsThis pooled analysis incorporated individual participant data from 22 prospective cohort studies of the Asia Cohort Consortium conducted between 1963 and 2006. A total of 1 002 551 Asian individuals (from mainland China, Japan, South Korea, Singapore, Taiwan, India, and Bangladesh) were followed up for more than 3 years. Cohort-specific hazard ratios and 95% confidence intervals for all-cause and cause-specific mortality were estimated using Cox regression models and then pooled using random-effects meta-analysis. Analysis was conducted between January 10, 2018, and August 31, 2018.ExposuresDoctor-diagnosed diabetes, age, sex, education level, body mass index, and smoking status.Main outcomes and measuresAll-cause and cause-specific mortality.ResultsOf 1 002 551 participants (518 537 [51.7%] female; median [range] age, 54.0 [30.0-98.0] years), 148 868 deaths were ascertained during a median (range) follow-up of 12.6 (3.0-38.9) years. The overall prevalence of diabetes reported at baseline was 4.8% for men and 3.6% for women. Patients with diabetes had a 1.89-fold risk of all-cause death compared with patients without diabetes (hazard ratio [HR], 1.89; 95% CI, 1.74-2.04), with the highest relative risk of death due to diabetes itself (HR, 22.8; 95% CI, 18.5-28.1), followed by renal disease (HR, 3.08; 95% CI, 2.50-3.78), coronary heart disease (HR, 2.57; 95% CI, 2.19-3.02), and ischemic stroke (HR, 2.15; 95% CI, 1.85-2.51). The adverse diabetes-mortality associations were more evident among women (HR, 2.09; 95% CI, 1.89-2.32) than among men (HR, 1.74; 95% CI, 1.62-1.88) (P for interaction < .001) and more evident among adults aged 30 to 49 years (HR, 2.43; 95% CI, 2.08-2.84) than among adults aged 70 years and older (HR, 1.51; 95% CI, 1.40-1.62) (P for interaction < .001). A similar pattern of association was found between diabetes and cause-specific mortality, with significant variations noted by sex and age.Conclusions and relevanceThis study found that diabetes was associated with increased risk of death from several diseases among Asian populations. Development and implementation of diabetes management programs are urgently needed to reduce the burden of diabetes in Asia.

Project description:ObjectiveTo conduct a systematic review and meta-analysis of cohort studies of body mass index (BMI) and the risk of all cause mortality, and to clarify the shape and the nadir of the dose-response curve, and the influence on the results of confounding from smoking, weight loss associated with disease, and preclinical disease.Data sourcesPubMed and Embase databases searched up to 23 September 2015.Study selectionCohort studies that reported adjusted risk estimates for at least three categories of BMI in relation to all cause mortality.Data synthesisSummary relative risks were calculated with random effects models. Non-linear associations were explored with fractional polynomial models.Results230 cohort studies (207 publications) were included. The analysis of never smokers included 53 cohort studies (44 risk estimates) with >738 144 deaths and >9 976 077 participants. The analysis of all participants included 228 cohort studies (198 risk estimates) with >3 744 722 deaths among 30 233 329 participants. The summary relative risk for a 5 unit increment in BMI was 1.18 (95% confidence interval 1.15 to 1.21; I(2)=95%, n=44) among never smokers, 1.21 (1.18 to 1.25; I(2)=93%, n=25) among healthy never smokers, 1.27 (1.21 to 1.33; I(2)=89%, n=11) among healthy never smokers with exclusion of early follow-up, and 1.05 (1.04 to 1.07; I(2)=97%, n=198) among all participants. There was a J shaped dose-response relation in never smokers (Pnon-linearity <0.001), and the lowest risk was observed at BMI 23-24 in never smokers, 22-23 in healthy never smokers, and 20-22 in studies of never smokers with ≥20 years' follow-up. In contrast there was a U shaped association between BMI and mortality in analyses with a greater potential for bias including all participants, current, former, or ever smokers, and in studies with a short duration of follow-up (<5 years or <10 years), or with moderate study quality scores.ConclusionOverweight and obesity is associated with increased risk of all cause mortality and the nadir of the curve was observed at BMI 23-24 among never smokers, 22-23 among healthy never smokers, and 20-22 with longer durations of follow-up. The increased risk of mortality observed in underweight people could at least partly be caused by residual confounding from prediagnostic disease. Lack of exclusion of ever smokers, people with prevalent and preclinical disease, and early follow-up could bias the results towards a more U shaped association.

Project description:ObjectiveTo investigate the association of grip strength with disease specific incidence and mortality and whether grip strength enhances the prediction ability of an established office based risk score.DesignProspective population based study.SettingUK Biobank.Participants502?293 participants (54% women) aged 40-69 years.Main outcome measuresAll cause mortality as well as incidence of and mortality from cardiovascular disease, respiratory disease, chronic obstructive pulmonary disease, and cancer (all cancer, colorectal, lung, breast, and prostate).ResultsOf the participants included in analyses, 13?322 (2.7%) died over a mean of 7.1 (range 5.3-9.9) years' follow-up. In women and men, respectively, hazard ratios per 5 kg lower grip strength were higher (all at P<0.05) for all cause mortality (1.20, 95% confidence interval 1.17 to 1.23, and 1.16, 1.15 to 1.17) and cause specific mortality from cardiovascular disease (1.19, 1.13 to 1.25, and 1.22, 1.18 to 1.26), all respiratory disease (1.31, 1.22 to 1.40, and 1.24, 1.20 to 1.28), chronic obstructive pulmonary disease (1.24, 1.05 to 1.47, and 1.19, 1.09 to 1.30), all cancer (1.17, 1.13 to 1.21, 1.10, 1.07 to 1.13), colorectal cancer (1.17, 1.04 to 1.32, and 1.18, 1.09 to 1.27), lung cancer (1.17, 1.07 to 1.27, and 1.08, 1.03 to 1.13), and breast cancer (1.24, 1.10 to 1.39) but not prostate cancer (1.05, 0.96 to 1.15). Several of these relations had higher hazard ratios in the younger age group. Muscle weakness (defined as grip strength <26 kg for men and <16 kg for women) was associated with a higher hazard for all health outcomes, except colon cancer in women and prostate cancer and lung cancer in both men and women. The addition of handgrip strength improved the prediction ability, based on C index change, of an office based risk score (age, sex, diabetes diagnosed, body mass index, systolic blood pressure, and smoking) for all cause (0.013) and cardiovascular mortality (0.012) and incidence of cardiovascular disease (0.009).ConclusionHigher grip strength was associated with a range of health outcomes and improved prediction of an office based risk score. Further work on the use of grip strength in risk scores or risk screening is needed to establish its potential clinical utility.

Project description:ObjectiveTo quantify the association between daily total sitting and all-cause mortality risk and to examine dose-response relationships with and without adjustment for moderate-to-vigorous physical activity.MethodsStudies published from 1989 to January 2013 were identified via searches of multiple databases, reference lists of systematic reviews on sitting and health, and from authors' personal literature databases. We included prospective cohort studies that had total daily sitting time as a quantitative exposure variable, all-cause mortality as the outcome and reported estimates of relative risk, or odds ratios or hazard ratios with 95% confidence intervals. Two authors independently extracted the data and summary estimates of associations were computed using random effects models.ResultsSix studies were included, involving data from 595,086 adults and 29,162 deaths over 3,565,569 person-years of follow-up. Study participants were mainly female, middle-aged or older adults from high-income countries; mean study quality score was 12/15 points. Associations between daily total sitting time and all-cause mortality were not linear. With physical activity adjustment, the spline model of best fit had dose-response HRs of 1.00 (95% CI: 0.98-1.03), 1.02 (95% CI: 0.99-1.05) and 1.05 (95% CI: 1.02-1.08) for every 1-hour increase in sitting time in intervals between 0-3, >3-7 and >7 h/day total sitting, respectively. This model estimated a 34% higher mortality risk for adults sitting 10 h/day, after taking physical activity into account. The overall weighted population attributable fraction for all-cause mortality for total daily sitting time was 5.9%, after adjusting for physical activity.ConclusionsHigher amounts of daily total sitting time are associated with greater risk of all-cause mortality and moderate-to-vigorous physical activity appears to attenuate the hazardous association. These findings provide a starting point for identifying a threshold on which to base clinical and public health recommendations for overall sitting time, in addition to physical activity guidelines.

Project description:BackgroundPrevious studies have suggested that exposure to air pollution may increase stroke risk, but the results remain inconsistent. Evidence of more recent studies is highly warranted, especially gas air pollutants.MethodsWe searched PubMed, Embase, and Web of Science to identify studies till February 2020 and conducted a meta-analysis on the association between air pollution (PM2.5, particulate matter with aerodynamic diameter less than 2.5 μm; PM10, particulate matter with aerodynamic diameter less than 10 μm; NO2, nitrogen dioxide; SO2, sulfur dioxide; CO, carbon monoxide; O3, ozone) and stroke (hospital admission, incidence, and mortality). Fixed- or random-effects model was used to calculate pooled odds ratios (OR)/hazard ratio (HR) and their 95% confidence intervals (CI) for a 10 μg/m3 increase in air pollutant concentration.ResultsA total of 68 studies conducted from more than 23 million participants were included in our meta-analysis. Meta-analyses showed significant associations of all six air pollutants and stroke hospital admission (e.g., PM2.5: OR = 1.008 (95% CI 1.005, 1.011); NO2: OR = 1.023 (95% CI 1.015, 1.030), per 10 μg/m3 increases in air pollutant concentration). Exposure to PM2.5, SO2, and NO2 was associated with increased risks of stroke incidence (PM2.5: HR = 1.048 (95% CI 1.020, 1.076); SO2: HR = 1.002 (95% CI 1.000, 1.003); NO2: HR = 1.002 (95% CI 1.000, 1.003), respectively). However, no significant differences were found in associations of PM10, CO, O3, and stroke incidence. Except for CO and O3, we found that higher level of air pollution (PM2.5, PM10, SO2, and NO2) exposure was associated with higher stroke mortality (e.g., PM10: OR = 1.006 (95% CI 1.003, 1.010), SO2: OR = 1.006 (95% CI 1.005, 1.008).ConclusionsExposure to air pollution was positively associated with an increased risk of stroke hospital admission (PM2.5, PM10, SO2, NO2, CO, and O3), incidence (PM2.5, SO2, and NO2), and mortality (PM2.5, PM10, SO2, and NO2). Our study would provide a more comprehensive evidence of air pollution and stroke, especially SO2 and NO2.

Project description:BackgroundHealthy lifestyle behaviours are effective means to reduce the burden of diseases. This study was aimed to fill the knowledge gaps on the distribution, associated factors, and potential health benefits on mortality of four healthy lifestyle behaviours in China.MethodsDuring 2015-2019, participants aged 35-75 years from 31 provinces were recruited by the China PEACE Million Persons Project. Four healthy lifestyle behaviours were investigated in our study, including non-smoking, none or moderate alcohol use, sufficient leisure time physical activity (LTPA), and healthy diet.ResultsAmong 903,499 participants, 74.1% were non-smokers, 96.0% had none or moderate alcohol use, 23.6% had sufficient LTPA, 11.1% had healthy diet, and only 2.8% had all the four healthy lifestyle behaviours. The adherence varied across seven regions; the highest median of county-level adherence to all the four healthy lifestyle behaviours was in North China (3.3%) while the lowest in the Southwest (0.8%) (p < 0.05). Participants who were female, elder, non-farmers, urban residents, with higher income or education, hypertensive or diabetic, or with a cardiovascular disease (CVD) history were more likely to adhere to all the four healthy lifestyle behaviours (p < 0.001). County-level per capital Gross Domestic Product (GDP) was positively associated with sufficient LTPA (p < 0.05 for both rural and urban areas) and healthy diet (p < 0.01 for urban areas), while negatively associated with none or moderate alcohol use (p < 0.01 for rural areas). Average annual temperature was negatively associated with none or moderate alcohol use (p < 0.05 for rural areas) and healthy diet (p < 0.001 for rural areas). Those adhering to all the four healthy lifestyle behaviours had lower risks of all-cause mortality (HR 0.64 [95% CI: 0.52, 0.79]) and cardiovascular mortality (HR 0.53 [0.37, 0.76]) after a median follow-up of 2.4 years.ConclusionsAdherence to healthy lifestyle behaviours in China was far from ideal. Targeted health promotion strategies were urgently needed.

Dataset Information

A cut-off of daily sedentary time and all-cause mortality in adults: a meta-regression analysis involving more than 1 million participants.

Publications

A cut-off of daily sedentary time and all-cause mortality in adults: a meta-regression analysis involving more than 1 million participants.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets