Aims/hypothesis
Inverse associations between physical activity (PA) and type 2 diabetes mellitus are well known. However, the shape of the dose–response relationship is still uncertain. This review ...synthesises results from longitudinal studies in general populations and uses non-linear models of the association between PA and incident type 2 diabetes.
Methods
A systematic literature search identified 28 prospective studies on leisure-time PA (LTPA) or total PA and risk of type 2 diabetes. PA exposures were converted into metabolic equivalent of task (MET) h/week and marginal MET (MMET) h/week, a measure only considering energy expended above resting metabolic rate. Restricted cubic splines were used to model the exposure–disease relationship.
Results
Our results suggest an overall non-linear relationship; using the cubic spline model we found a risk reduction of 26% (95% CI 20%, 31%) for type 2 diabetes among those who achieved 11.25 MET h/week (equivalent to 150 min/week of moderate activity) relative to inactive individuals. Achieving twice this amount of PA was associated with a risk reduction of 36% (95% CI 27%, 46%), with further reductions at higher doses (60 MET h/week, risk reduction of 53%). Results for the MMET h/week dose–response curve were similar for moderate intensity PA, but benefits were greater for higher intensity PA and smaller for lower intensity activity.
Conclusions/interpretation
Higher levels of LTPA were associated with substantially lower incidence of type 2 diabetes in the general population. The relationship between LTPA and type 2 diabetes was curvilinear; the greatest relative benefits are achieved at low levels of activity, but additional benefits can be realised at exposures considerably higher than those prescribed by public health recommendations.
AbstractObjectiveTo assess the prospective associations of baseline and long term trajectories of physical activity on mortality from all causes, cardiovascular disease, and cancer.DesignPopulation ...based cohort study.SettingAdults from the general population in the UK.Participants14 599 men and women (aged 40 to 79) from the European Prospective Investigation into Cancer and Nutrition-Norfolk cohort, assessed at baseline (1993 to 1997) up to 2004 for lifestyle and other risk factors; then followed to 2016 for mortality (median of 12.5 years of follow-up, after the last exposure assessment).Main exposurePhysical activity energy expenditure (PAEE) derived from questionnaires, calibrated against combined movement and heart rate monitoring.Main outcome measuresMortality from all causes, cardiovascular disease, and cancer. Multivariable proportional hazards regression models were adjusted for age, sex, sociodemographics, and changes in medical history, overall diet quality, body mass index, blood pressure, triglycerides, and cholesterol levels.ResultsDuring 171 277 person years of follow-up, 3148 deaths occurred. Long term increases in PAEE were inversely associated with mortality, independent of baseline PAEE. For each 1 kJ/kg/day per year increase in PAEE (equivalent to a trajectory of being inactive at baseline and gradually, over five years, meeting the World Health Organization minimum physical activity guidelines of 150 minutes/week of moderate-intensity physical activity), hazard ratios were: 0.76 (95% confidence interval 0.71 to 0.82) for all cause mortality, 0.71 (0.62 to 0.82) for cardiovascular disease mortality, and 0.89 (0.79 to 0.99) for cancer mortality, adjusted for baseline PAEE, and established risk factors. Similar results were observed when analyses were stratified by medical history of cardiovascular disease and cancer. Joint analyses with baseline and trajectories of physical activity show that, compared with consistently inactive individuals, those with increasing physical activity trajectories over time experienced lower risks of mortality from all causes, with hazard ratios of 0.76 (0.65 to 0.88), 0.62 (0.53 to 0.72), and 0.58 (0.43 to 0.78) at low, medium, and high baseline physical activity, respectively. At the population level, meeting and maintaining at least the minimum physical activity recommendations would potentially prevent 46% of deaths associated with physical inactivity.ConclusionsMiddle aged and older adults, including those with cardiovascular disease and cancer, can gain substantial longevity benefits by becoming more physically active, irrespective of past physical activity levels and established risk factors. Considerable population health impacts can be attained with consistent engagement in physical activity during mid to late life.
Depression is the leading cause of mental health-related disease burden and may be reduced by physical activity, but the dose-response relationship between activity and depression is uncertain.
To ...systematically review and meta-analyze the dose-response association between physical activity and incident depression from published prospective studies of adults.
PubMed, SCOPUS, Web of Science, PsycINFO, and the reference lists of systematic reviews retrieved by a systematic search up to December 11, 2020, with no language limits. The date of the search was November 12, 2020.
We included prospective cohort studies reporting physical activity at 3 or more exposure levels and risk estimates for depression with 3000 or more adults and 3 years or longer of follow-up.
Data extraction was completed independently by 2 extractors and cross-checked for errors. A 2-stage random-effects dose-response meta-analysis was used to synthesize data. Study-specific associations were estimated using generalized least-squares regression and the pooled association was estimated by combining the study-specific coefficients using restricted maximum likelihood.
The outcome of interest was depression, including (1) presence of major depressive disorder indicated by self-report of physician diagnosis, registry data, or diagnostic interviews and (2) elevated depressive symptoms established using validated cutoffs for a depressive screening instrument.
Fifteen studies comprising 191 130 participants and 2 110 588 person-years were included. An inverse curvilinear dose-response association between physical activity and depression was observed, with steeper association gradients at lower activity volumes; heterogeneity was large and significant (I2 = 74%; P < .001). Relative to adults not reporting any activity, those accumulating half the recommended volume of physical activity (4.4 marginal metabolic equivalent task hours per week mMET-h/wk) had 18% (95% CI, 13%-23%) lower risk of depression. Adults accumulating the recommended volume of 8.8 mMET hours per week had 25% (95% CI, 18%-32%) lower risk with diminishing potential benefits and higher uncertainty observed beyond that exposure level. There were diminishing additional potential benefits and greater uncertainty at higher volumes of physical activity. Based on an estimate of exposure prevalences among included cohorts, if less active adults had achieved the current physical activity recommendations, 11.5% (95% CI, 7.7%-15.4%) of depression cases could have been prevented.
This systematic review and meta-analysis of associations between physical activity and depression suggests significant mental health benefits from being physically active, even at levels below the public health recommendations. Health practitioners should therefore encourage any increase in physical activity to improve mental health.
Many large studies have implemented wrist or thigh accelerometry to capture physical activity, but the accuracy of these measurements to infer activity energy expenditure (AEE) and consequently total ...energy expenditure (TEE) has not been demonstrated. The purpose of this study was to assess the validity of acceleration intensity at wrist and thigh sites as estimates of AEE and TEE under free-living conditions using a gold-standard criterion.
Measurements for 193 UK adults (105 men, 88 women, aged 40-66 years, BMI 20.4-36.6 kg m
) were collected with triaxial accelerometers worn on the dominant wrist, non-dominant wrist and thigh in free-living conditions for 9-14 days. In a subsample (50 men, 50 women) TEE was simultaneously assessed with doubly labelled water (DLW). AEE was estimated from non-dominant wrist using an established estimation model, and novel models were derived for dominant wrist and thigh in the non-DLW subsample. Agreement with both AEE and TEE from DLW was evaluated by mean bias, root mean squared error (RMSE), and Pearson correlation.
Mean TEE and AEE derived from DLW were 11.6 (2.3) MJ day
and 49.8 (16.3) kJ day
kg
. Dominant and non-dominant wrist acceleration were highly correlated in free-living (r = 0.93), but less so with thigh (r = 0.73 and 0.66, respectively). Estimates of AEE were 48.6 (11.8) kJ day
kg
from dominant wrist, 48.6 (12.3) from non-dominant wrist, and 46.0 (10.1) from thigh; these agreed strongly with AEE (RMSE ~12.2 kJ day
kg
, r ~ 0.71) with small mean biases at the population level (~6%). Only the thigh estimate was statistically significantly different from the criterion. When combining these AEE estimates with estimated REE, agreement was stronger with the criterion (RMSE ~1.0 MJ day
, r ~ 0.90).
In UK adults, acceleration measured at either wrist or thigh can be used to estimate population levels of AEE and TEE in free-living conditions with high precision.
Purpose: To estimate the strength and shape of the dose-response relationship between sedentary behaviour and all-cause, cardiovascular disease (CVD) and cancer mortality, and incident type 2 ...diabetes (T2D), adjusted for physical activity (PA). Data Sources: Pubmed, Web of Knowledge, Medline, Embase, Cochrane Library and Google Scholar (through September-2016); reference lists. Study Selection: Prospective studies reporting associations between total daily sedentary time or TV viewing time, and ≥ one outcome of interest. Data Extraction: Two independent reviewers extracted data, study quality was assessed; corresponding authors were approached where needed. Data Synthesis: Thirty-four studies (1,331,468 unique participants; good study quality) covering 8 exposure-outcome combinations were included. For total sedentary behaviour, the PA-adjusted relationship was non-linear for all-cause mortality (RR per 1 h/day: were 1.01 (1.00-1.01) ≤ 8 h/day; 1.04 (1.03-1.05) > 8 h/day of exposure), and for CVD mortality (1.01 (0.99-1.02) ≤ 6 h/day; 1.04 (1.03-1.04) > 6 h/day). The association was linear (1.01 (1.00-1.01)) with T2D and non-significant with cancer mortality. Stronger PA-adjusted associations were found for TV viewing (h/day); non-linear for all-cause mortality (1.03 (1.01-1.04) ≤ 3.5 h/day; 1.06 (1.05-1.08) > 3.5 h/day) and for CVD mortality (1.02 (0.99-1.04) ≤ 4 h/day; 1.08 (1.05-1.12) > 4 h/day). Associations with cancer mortality (1.03 (1.02-1.04)) and T2D were linear (1.09 (1.07-1.12)). Conclusions: Independent of PA, total sitting and TV viewing time are associated with greater risk for several major chronic disease outcomes. For all-cause and CVD mortality, a threshold of 6-8 h/day of total sitting and 3-4 h/day of TV viewing was identified, above which the risk is increased.
Abstract
Background
The advent of very large cohort studies (n > 500 000) has given rise to prospective analyses of health outcomes being undertaken after short (<4 years) follow-up periods. However, ...these studies are potentially at risk of reverse causality bias. We investigated differences in the associations between self-reported physical activity and all-cause and cardiovascular disease (CVD) mortality, and incident CVD, using different follow-up time cut-offs and methods to account for reverse causality bias.
Methods
Data were from n = 452 933 UK Biobank participants, aged 38–73 years at baseline. Median available follow-up time was 7 years (for all-cause and CVD mortality) and 6.1 years (for incident CVD). We additionally analysed associations at 1-, 2- and 4-year cut-offs after baseline. We fit up to four models: (1) adjusting for prevalent CVD and cancer, (2) excluding prevalent disease, (3) and (4) Model 2 excluding incident cases in the first 12 and 24 months, respectively.
Results
The strength of associations decreased as follow-up time cut-off increased. For all-cause mortality, Model 1 hazard ratios were 0.73 (0.69–0.78) after 1 year and 0.86 (0.84–0.87) after 7 years. Associations were weaker with increasing control for possible reverse causality. After 7-years follow-up, the hazard ratios were 0.86 (0.84–0.87) and 0.88 (0.86–0.90) for Models 1 and 4, respectively. Associations with CVD outcomes followed similar trends.
Conclusions
As analyses with longer follow-up times and increased control for reverse causality showed weaker associations, there are implications for the decision about when to analyse a cohort study with ongoing data collection, the interpretation of study results and their contribution to meta-analyses.
Wrist-worn accelerometers are emerging as the most common instrument for measuring physical activity in large-scale epidemiological studies, though little is known about the relationship between ...wrist acceleration and physical activity energy expenditure (PAEE).
1695 UK adults wore two devices simultaneously for six days; a combined sensor and a wrist accelerometer. The combined sensor measured heart rate and trunk acceleration, which was combined with a treadmill test to yield a signal of individually-calibrated PAEE. Multi-level regression models were used to characterise the relationship between the two time-series, and their estimations were evaluated in an independent holdout sample. Finally, the relationship between PAEE and BMI was described separately for each source of PAEE estimate (wrist acceleration models and combined-sensing).
Wrist acceleration explained 44-47% between-individual variance in PAEE, with RMSE between 34-39 J•min-1•kg-1. Estimations agreed well with PAEE in cross-validation (mean bias 95% limits of agreement: 0.07 -70.6:70.7) but overestimated in women by 3% and underestimated in men by 4%. Estimation error was inversely related to age (-2.3 J•min-1•kg-1 per 10y) and BMI (-0.3 J•min-1•kg-1 per kg/m2). Associations with BMI were similar for all PAEE estimates (approximately -0.08 kg/m2 per J•min-1•kg-1).
A strong relationship exists between wrist acceleration and PAEE in free-living adults, such that irrespective of the objective method of PAEE assessment, a strong inverse association between PAEE and BMI was observed.
To compare the country-level absolute and relative contributions of physical activity at work and in the household, for travel, and during leisure-time to total moderate-to-vigorous physical activity ...(MVPA).
We used data collected between 2002 and 2019 from 327 789 participants across 104 countries and territories (n=24 low, n=34 lower-middle, n=30 upper-middle, n=16 high-income) from all six World Health Organization (WHO) regions. We calculated mean min/week of work/household, travel and leisure MVPA and compared their relative contributions to total MVPA using Global Physical Activity Questionnaire data. We compared patterns by country, sex and age group (25-44 and 45-64 years).
Mean MVPA in work/household, travel and leisure domains across the 104 countries was 950 (IQR 618-1198), 327 (190-405) and 104 (51-131) min/week, respectively. Corresponding relative contributions to total MVPA were 52% (IQR 44%-63%), 36% (25%-45%) and 12% (4%-15%), respectively. Work/household was the highest contributor in 80 countries; travel in 23; leisure in just one. In both absolute and relative terms, low-income countries tended to show higher work/household (1233 min/week, 57%) and lower leisure MVPA levels (72 min/week, 4%). Travel MVPA duration was higher in low-income countries but there was no obvious pattern in the relative contributions. Women tended to have relatively less work/household and more travel MVPA; age groups were generally similar.
In the largest domain-specific physical activity study to date, we found considerable country-level variation in how MVPA is accumulated. Such information is essential to inform national and global policy and future investments to provide opportunities to be active, accounting for country context.
Disease and mortality burdens of unhealthy lifestyle behaviours are often reported. In contrast, the positive narrative around the burdens that an existing behaviour have averted is rarely ...acknowledged. We aimed to estimate the prevented fraction for the population (PFP) for premature mortality averted by physical activity on a global scale.
In this descriptive study, we obtained previously published data on physical activity prevalence (2001-16) and relative risks of all-cause mortality for 168 countries. We combined the data in Monte-Carlo simulations to estimate country-specific, mean PFP values, corresponding to percentage of mortality averted, and their 95% CIs. High prevented fractions indicated an increased proportion of deaths averted due to physical activity. Using mortality data for all people in a country aged 40-74 years, we estimated the number of premature deaths averted for all adults and by gender. We present the median and range of the prevented fractions globally, by WHO region, and by World Bank income classification.
The global median PFP was 15·0% (range 6·6-20·5), conservatively equating to 3·9 million (95% CI 2·5-5·6) premature deaths averted annually. The African region had the highest median prevented fraction (16·6% range 12·1-20·5) and the Americas had the lowest (13·1% 10·8-16·6). Low-income countries tended to have higher prevented fractions (group median 17·9% 12·3-20·5) than high-income countries (14·1% 6·6-17·8). Globally, the median prevented fraction was higher for men (16·0% 7·8-20·7 than women (14·1% 5·0-20·4).
Existing physical activity prevalence has contributed to averting premature mortality across all countries. PFP has utility as an advocacy tool to promote healthy lifestyle behaviours. By making the case of what has been achieved, the prevented fraction can show the value of current investment and services, which might be conducive to political support.
UK Medical Research Council, British Heart Foundation, Cancer Research UK, Economic and Social Research Council, National Institute for Health Research, Wellcome Trust, Heart Foundation Australia.
PDF
