Physical activity (PA) improves health outcomes accumulating evidence suggests that sedentary time (ST), especially parent-reported screen-time, is associated with negative health outcomes in ...children. The aim of the present study is to describe levels and patterns of PA and ST across the day and week and activity pattern differences between the sexes, across all weekdays and time spent in and outside the preschool in four-year old children.
In total 899 four-year old Swedish children who had both complete questionnaire data on screen-time behaviors and objective activity variables and at least 4 days, including one weekend day, with more than 10 h of GT3X+ Actigraph accelerometer wear time data were included in the study. Patterns of PA and ST across the day and week and differences between sexes, weekdays vs. weekend days and time in preschool vs. time spent outside preschool were assessed.
Children engaged in 150 min (SD 73) and 102 min (SD 60) of screen-time on weekend days and weekdays, with 97% and 86% of children exceeding the 1 h guideline for screen-time on weekend days and weekdays, respectively. Accelerometer data showed that boys are more active and less sedentary compared with girls and both sexes were more active and less sedentary on weekdays compared with weekend days, while parent-reported data showed that boys engage in more screen-time compared with girls. Children accumulated 24.8 min (SD. 19) MVPA during preschool time and 26.6 min (SD. 16) outside preschool hours on weekdays, compared with 22.4 min (SD. 18) MVPA during preschool time and 25.3 min (SD. 22) outside preschool hours on weekend days.
Four-year old Swedish children display different activity patterns across the day on weekdays compared to weekend days, with preschool hours during weekdays being the most active segments and preschool hours during weekend days being the least active segments of the day.
Abstract
Aims
Cardiorespiratory fitness, muscular strength, and obesity in adulthood are risk factors for cardiovascular disease (CVD). However, little is known regarding the associations of these ...risk factors, already in adolescence, with later disability due to chronic CVD. Hence, we investigated associations of cardiorespiratory fitness, muscular strength, and body mass index (BMI) in adolescence with later chronic disability due to specific causes of CVD disability (i.e. cerebrovascular disease, ischaemic heart disease and heart failure).
Methods and results
This population-based cohort study included 1 078 685 male adolescents (16–19 years) from the Swedish military conscription register from 1972 to 1994. Cardiorespiratory fitness (bicycle ergometer test), muscular strength (knee extension strength), and BMI were measured during the conscription examination. Information about disability pension due to CVD was retrieved from the Social Insurance Agency during a mean follow-up of 28.4 years. Cardiorespiratory fitness was strongly and inversely associated with later risk of chronic CVD disability for all investigated causes. The association was particularly strong for ischaemic heart diseases (hazard ratio 0.11, 95% confidence interval 0.05–0.29 for highest vs. lowest fitness-quintiles). Furthermore, overweight/obesity were associated with CVD disability for all investigated causes. Conversely, associations of muscular strength with CVD disability were generally weak.
Conclusions
This study provides evidence for associations between low levels of cardiorespiratory fitness and obesity with later risk of chronic disability due to CVD. Preventive actions may begin at young ages and include promotion of cardiorespiratory fitness and healthy body weight.
Objective To investigate the associations of exercise capacity and muscle strength in late adolescence with risk of vascular disease and arrhythmia.Design Cohort study.Setting General population in ...Sweden.Participants 1.1 million men who participated in mandatory military conscription between 1 August 1972 and 31 December 1995, at a median age of 18.2 years. Participants were followed until 31 December 2010.Main outcomes Associations between exercise capacity and muscle strength with risk of vascular disease and subgroups (ischaemic heart disease, heart failure, stroke, and cardiovascular death) and risk of arrhythmia and subgroups (atrial fibrillation or flutter, bradyarrhythmia, supraventricular tachycardia, and ventricular arrhythmia or sudden cardiac death). Maximum exercise capacity was estimated by the ergometer bicycle test, and muscle strength was measured as handgrip strength by a hand dynamometer. High exercise capacity or muscle strength was deemed as above the median level.Results During a median follow-up of 26.3 years, 26 088 vascular disease events and 17 312 arrhythmia events were recorded. Exercise capacity was inversely associated with risk of vascular disease and its subgroups. Muscle strength was also inversely associated with vascular disease risk, driven by associations of higher muscle strength with lower risk of heart failure and cardiovascular death. Exercise capacity had a U shaped association with risk of arrhythmia, driven by a direct association with risk of atrial fibrillation and a U shaped association with bradyarrhythmia. Higher muscle strength was associated with lower risk of arrhythmia (specifically, lower risk of bradyarrhythmia and ventricular arrhythmia). The combination of high exercise capacity and high muscle strength was associated with a hazard ratio of 0.67 (95% confidence interval 0.65 to 0.70) for vascular events and 0.92 (0.88 to 0.97) for arrhythmia compared with the combination of low exercise capacity and low muscle strength.Conclusions Exercise capacity and muscle strength in late adolescence are independently and jointly associated with long term risk of vascular disease and arrhythmia. The health benefit of lower risk of vascular events with higher exercise capacity was not outweighed by higher risk of arrhythmia.
Abstract
Although exposure to overweight and obesity at different ages is associated to a higher risk of type 2 diabetes, the effect of different patterns of exposure through life remains unclear. We ...aimed to characterize life-course trajectories of weight categories and estimate their impact on the incidence of type 2 diabetes. We categorized the weight of 7203 participants as lean, normal or overweight at five time-points from ages 7–55 using retrospective data. Participants were followed for an average of 19 years for the development of type 2 diabetes. We used latent class analysis to describe distinctive trajectories and estimated the risk ratio, absolute risk difference and population attributable fraction (PAF) associated to different trajectories using Poisson regression. We found five distinctive life-course trajectories. Using the stable-normal weight trajectory as reference, the stable overweight, lean increasing weight, overweight from early adulthood and overweight from late adulthood trajectories were associated to higher risk of type 2 diabetes. The estimated risk ratios and absolute risk differences were statistically significant for all trajectories, except for the risk ratio of the lean increasing trajectory group among men. Of the 981 incident cases of type 2 diabetes, 47.4% among women and 42.9% among men were attributable to exposure to any life-course trajectory different from stable normal weight. Most of the risk was attributable to trajectories including overweight or obesity at any point of life (36.8% of the cases among women and 36.7% among men). The overweight from early adulthood trajectory had the highest impact (PAF: 23.2% for woman and 28.5% for men). We described five distinctive life-course trajectories of weight that were associated to increased risk of type 2 diabetes over 19 years of follow-up. The variability of the effect of exposure to overweight and obesity on the risk of developing type 2 diabetes was largely explained by exposure to the different life-course trajectories of weight.
People with mobility disability (MD) or obesity often have more health problems and are less able to participate in work than individuals without these conditions. This study investigated whether ...people burdened with MD and obesity have a greater risk of unemployment than people with either one (MD only or obesity only) or none of these conditions.
The study included two Swedish population-based cohorts, a national cohort (n = 39,947) and a regional cohort (n = 40,088). Six exposure groups were created using baseline self-reported data on MD and body mass index from participants aged 19 to 64 years. The MD definition differed between the cohorts. Various sources of socio-demographic factors were used to address confounding. Participants' risks of unemployment were assessed longitudinally in a nationwide register with objective data and with almost no loss of follow-up (< 1%). Cox regression was used to analyse associations of MD and/or obesity (BMI ≥ 30) with risk of any (≥1 day) and long-term unemployment (≥90 days during two consecutive years). Quantile regression was used to estimate participants' unemployment risks as average days of unemployment. Normal-weight people without MD were used as a reference group. The Wald test was applied for specific group comparisons other than to the reference group.
In summary, the groups with MD and the obese group without MD had a higher risk of becoming unemployed than the reference group (regional survey adjusted hazard ratio range: 1.30-1.59; 95% CI range: 1.06-1.90, national survey adjusted hazard ratio range: 1.11-1.34; 95% CI range: 0.88-1.81). The obese group with MD did not differ from the groups with MD only or obesity only in terms of unemployment risk.
People with MD and/or obesity are vulnerable groups at risk of prolonged unemployment during their working life in a country with a highly developed welfare system.
The coronavirus disease 2019 (COVID-19) disproportionately affects minority populations in the USA. Sweden - like other Nordic countries - have less income and wealth inequality but lacks data on the ...socioeconomic impact on the risk of adverse outcomes due to COVID-19.
This population-wide study from March 2020 to March 2022 included all adults in Stockholm, except those in nursing homes or receiving in-home care. Data sources include hospitals, primary care (individual diagnoses), the Swedish National Tax Agency (death dates), the Total Population Register "RTB" (sex, age, birth country), the Household Register (size of household), the Integrated Database For Labor Market Research "LISA" (educational level, income, and occupation), and SmiNet (COVID data). Individual exposures include education, income, type of work and ability to work from home, living area and living conditions as well as the individual country of origin and co-morbidities. Additionally, we have data on the risks associated with living areas. We used a Cox proportional hazards model and logistic regression to estimate associations. Area-level covariates were used in a principal component analysis to generate a measurement of neighborhood deprivation. As outcomes, we used hospitalization and death due to COVID-19.
Among the 1,782,125 persons, male sex, comorbidities, higher age, and not being born in Sweden increase the risk of hospitalization and death. So does lower education and lower income, the lowest incomes doubled the risk of death from COVID-19. Area estimates, where the model includes individual risks, show that high population density and a high percentage of foreign-born inhabitants increased the risk of hospitalization.
Segregation and deprivation are public health issues elucidated by COVID-19. Neighborhood deprivation, prevalent in Stockholm, adds to individual risks and is associated with hospitalization and death. This finding is paramount for governments, agencies, and healthcare institutions interested in targeted interventions.
Undiagnosed type 2 diabetes (T2D) is a global problem. Current strategies for diagnosis in Sweden include screening individuals within primary healthcare who are of high risk, such as those with ...hypertension, obesity, prediabetes, family history of diabetes, or those who smoke daily. In this study, we aimed to estimate the proportion of individuals with undiagnosed T2D in Stockholm County and factors associated with T2D being diagnosed by healthcare. This information could improve strategies for detection.
We used data from the Stockholm Diabetes Prevention Programme (SDPP) cohort together with information from national and regional registers. Individuals without T2D aged 35-56 years at baseline were followed up after two ten-year periods. The proportion of diagnosed T2D was based on register information for 7664 individuals during period 1 and for 5148 during period 2. Undiagnosed T2D was assessed by oral glucose tolerance tests at the end of each period. With logistic regression, we analysed factors associated with being diagnosed among individuals with T2D.
At the end of the first period, the proportion of individuals with T2D who had been diagnosed with T2D or not was similar (54.0% undiagnosed). At the end of the second period, the proportion of individuals with T2D was generally higher, but they were less likely to be undiagnosed (43.5%). The likelihood of being diagnosed was in adjusted analyses associated with overweight (OR=1.85; 95% CI 1.22-2.80), obesity (OR=2.73; 95% CI 1.76-4.23), higher fasting blood glucose (OR=2.11; 95% CI 1.67-2.66), and self-estimated poor general health (OR=2.42; 95% CI 1.07-5.45). Socioeconomic factors were not associated with being diagnosed among individuals with T2D. Most individuals (>71%) who developed T2D belonged to risk groups defined by having at least two of the prominent risk factors obesity, hypertension, daily smoking, prediabetes, or family history of T2D, including individuals with T2D who had not been diagnosed by healthcare.
Nearly half of individuals who develop T2D during 10 years in Stockholm County are undiagnosed, emphasizing a need for intensified screening of T2D within primary healthcare. Screening can be targeted to individuals who have at least two prominent risk factors.
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