Watching TV has a distinct sociodemographic and lifestyle profile compared with other sedentary behaviors: A nationwide population-based study

Impact of a community-based lifestyle intervention with initial sedentary reduction or physical activity increasing goals on self-reported health-related quality of life

BACKGROUND

In previous efforts, health-related quality of life (HRQoL) improved for individuals at high risk of type 2 diabetes and cardiovascular disease after participation in community-based lifestyle interventions (LI) with a moderate-to-vigorous physical activity (MVPA) movement goal.

PURPOSE

It is unknown whether HRQoL improves with LI when the primary movement goal is to reduce sedentary behavior. HRQoL changes were examined among adults with overweight and prediabetes and/or metabolic syndrome randomized to a 12-month Diabetes Prevention Program-based Group Lifestyle Balance (DPP-GLB) community LI work with goals of weight-loss and either increasing MVPA (DPP-GLB) or reducing sedentary time (GLB-SED).

METHODS

Study participants (N = 269) completed the Euroqol 5 dimension 3 long (EQ5D-3L index and EuroQol Visual Analog Scale (EQVAS)-visual analog scale) at baseline, and 6 and 12 months. Paired t-tests were used to evaluate pre-to-post-intervention changes by arm.

RESULTS

Mean EQVAS improvements for the GLB-SED arm at 6 and 12 months were +5.6 (SE = 1.3; P < .0001) and +4.6 (SE = 1.4; P = .0006), respectively. Similar mean EQVAS improvements were reported for the DPP-GLB arm; +5.9 (SE = 1.2; P < .0001) and +4.9 (SE = 1.2; P = .0001) at 6 and 12 months, respectively. Mean EQ5D index improvements were significant in the GLB-SED arm [6 months: +0.03 (SE = 0.01; P = .004); and 12 months: +0.04 (SE = 0.01; P = .006)], but not in the DPP-GLB arm.

CONCLUSIONS

Participation in community LI with a primary movement goal to reduce sedentary behavior improved HRQoL at least as well as traditional LI focused more on MVPA improvement, supporting an alternate intervention strategy for those who can't or won't engage in MVPA as the primary movement goal.

Leisure-time activities and disability among Chinese community-dwelling oldest old: evidence from the Chinese Longitudinal Healthy Longevity Study

With the acceleration of population aging, disability in older adults is a growing public health problem; however, little is known about the role of specific leisure-time activities in affecting disability. This study prospectively examined the association of leisure-time activities with disability among the Chinese oldest old. A total of 14 039 adults aged 80 years or older (median age of 89.8 years) were enrolled from the Chinese Longitudinal Healthy Longevity Survey from 1998 to 2014. Disability was defined as the presence of concurrent impairment in activities of daily living and physical performance. Cox proportional hazards models were used to estimate the associations between leisure-time activities and disability. During a mean of 4.2 years (2.7 years) of follow-up, 4487 participants developed disability. Compared with participants who never engaged in leisure-time activities, participants who engaged in almost daily activities, including gardening, keeping domestic animals or pets, playing cards or mahjong, reading books or newspapers, and watching TV or listening to the radio had a lower risk of disability, with HRs of 0.78 (0.69-0.88), 0.64 (0.58-0.70), 0.74 (0.63-0.86), 0.74 (0.65-0.84), and 0.84 (0.77-0.90), respectively. Moreover, the risk of disability gradually decreased with participation in an increasing number of those leisure-time activities (P for trend <0.001). Frequent engagement in leisure-time activities was associated with a lower risk of disability among the Chinese oldest old. This study highlights the importance of incorporating a broad range of leisure-time activities into the daily lives of older adults.

Causal effect of physical activity and sedentary behavior on the risk of alcohol dependence: A bidirectional two-sample Mendelian randomization study

BACKGROUND

Alcohol dependence, influenced by physical activity (PA) and sedentary behavior, lacks clear causal clarity. This study aims to clarify causal relationships by estimating these effects using bidirectional two-sample Mendelian randomization (MR).

METHODS

A bidirectional multivariable two-sample MR framework was employed to assess the causal effects of PA and sedentary behavior on alcohol dependence. Summarized genetic association data were analyzed for four PA-related activity patterns-moderate to vigorous physical activity (MVPA), vigorous physical activity (VPA), accelerometer-based physical activity with average acceleration (AccAve), and accelerometer-based physical activity with accelerations greater than 425 milli-gravities (Acc425)-and three sedentary behavior patterns-sedentary, TV watching, and computer use. The study was expanded to include the examination of the relationship between sedentary behavior or PA and general drinking behavior, quantified as drinks per week (DPW). We obtained summarized data on genetic associations with four PA related activity patterns (MVPA, VPA, AccAve and Acc425) and three sedentary behavior related behavior patterns (sedentary, TV watching and computer use).

RESULTS

MR analysis found AccAve inversely associated with alcohol dependence risk (OR: 0.87; 95% CI: 0.80-0.95; p < 0.001), MVPA positively associated (OR: 2.86; 95%CI: 1.45-5.66; p = 0.002). For sedentary behavior and alcohol dependence, only TV watching was positively associated with the risk of alcohol dependence (OR: 1.43; 95%CI: 1.09-1.88; p = 0.009). No causal links found for other physical or sedentary activities. Reverse analysis and sensitivity tests showed consistent findings without pleiotropy or heterogeneity. Multivariate MR analyses indicated that while MVPA, AccAve and TV watching are independently associated with alcohol dependence, DPW did not show a significant causal relationship.

CONCLUSIONS

Our results suggest that AccAve is considered a protective factor against alcohol dependence, while MVPA and TV watching are considered risk factors for alcohol dependence. Conversely, alcohol dependence serves as a protective factor against TV watching. Only TV watching and alcohol dependence might mutually have a significant causal effect on each other.

Causal effects of sedentary behaviours on the risk of migraine: A univariable and multivariable Mendelian randomization study

BACKGROUND

Migraine is a common and burdensome neurological disorder. The causal relationship between sedentary behaviours (SBs) and migraine remains instinct. We aimed to evaluate the roles of SBs including watching TV, using computer and driving in the risk of migraine.

METHODS

We conducted a univariable and multivariable Mendelian randomization (MR) study based on summary datasets of large genome-wide association studies. The inverse variance weighted method was utilized as the primary analytical tool. Cochran's Q, MR-Egger intercept test, MR pleiotropy residual sum and outlier and leave-one-out were conducted as sensitivity analysis. Additionally, we performed a meta-analysis to combine the causal estimates.

RESULTS

In the discovery analysis, we identified causal associations between time spent watching TV and an increased risk of migraine (p = 0.015) and migraine without aura (MO) (p = 0.002). Such causalities with increasing risk of migraine (p = 0.005), and MO (p = 0.006) were further verified using summary datasets from another study in the replication analysis. There was no significant causal association found between time spent using computer, driving and migraine or its two subtypes. The meta-analysis and multivariable MR analysis also strongly supported the causal relationships between time spent watching TV and an increased risk of migraine (p = 0.0003 and p = 0.034), as well as MO (p < 0.0001 and p = 0.0004), respectively. These findings were robust under all sensitivity analysis.

CONCLUSIONS

Our study suggested that time spent watching TV may be causally associated with an increased risk of migraine, particularly MO. Large-scale and well-designed cohort studies may be warranted for further validation.

SIGNIFICANCE STATEMENT

This study represents the first attempt to investigate whether a causal relationship exists between SBs and migraine. Utilizing MR analysis helps mitigate reverse causation bias and confounding factors commonly encountered in observational cohorts, thereby enhancing the robustness of derived causal associations. Our MR analysis revealed that time spent watching TV may serve as a potential risk factor for migraine, particularly MO.

Association between electronic device use and health status among a middle-aged and elderly population: a cross-sectional analysis in the UK Biobank

Aim

Few previous studies have investigated the impact of multiple types of electronic devices on health status, and the moderating effects of gender, age, and BMI. Our aim is to examine the relationships between the use of four types of electronics and three health status indicators in a middle-aged and elderly population, and how these relationships varied by gender, age, and BMI.

Subject and methods

Using data from 376,806 participants aged 40-69 years in the UK Biobank, we conducted a multivariate linear regression to estimate the association between electronic device use and health status. Electronics use was categorized as TV watching, computer use, computer gaming, and mobile phone use, and health status included self-rated health (SRH), multisite chronic pain (MCP), and total physical activity (TPA). Interaction terms were utilized to assess whether the above associations were modified by BMI, gender, and age. Further stratified analysis was performed to explore the role of gender, age, and BMI.

Results

Higher levels of TV watching (BSRH = 0.056, BMCP = 0.044, BTPA= -1.795), computer use (BSRH = 0.007, BTPA= -3.469), and computer gaming (BSRH = 0.055, BMCP = 0.058, BTPA= -6.076) were consistently associated with poorer health status (all P < 0.05). Contrastingly, earlier exposure to mobile phones (BSRH = -0.048, BTPA= 0.933, BMCP = 0.056) was inconsistent with health (all P < 0.05). Additionally, BMI (Bcomputer use-SRH= 0.0026, Bphone-SRH= 0.0049, BTV-MCP= 0.0031, and BTV-TPA= -0.0584) exacerbated the negative effects of electronics use, and male (Bphone-SRH = -0.0414, Bphone-MCP = -0.0537, Bphone-TPA= 2.8873) were healthier with earlier exposure to mobile phones (all P < 0.05).

Conclusion

Our findings suggest that the adverse health effects associated with watching TV, computer use, and computer gaming were consistent and were moderated by BMI, gender, and age, which advances a comprehensive understanding of the association between multiple types of electronic devices and health status, and provides new perspectives for future research.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10389-023-01886-5.

Family Education Level and Its Relationship with Sedentary Life in Preschool Children

Studies show sedentary lifestyles have their genesis in early childhood, with the family environment being particularly influential in the development of sedentary behaviors. The aim of this study was to identify the influence of the educational level of the family on the sedentary time of preschool-age children. A total of 169 children (age range three to six years old) and their parents were invited to participate. Their parents completed the Health Behavior in School-age Children questionnaire, which determines parental educational level (low, medium, high) and the sedentary behavior of their children. Sedentary behavior time was also analyzed by fractions (all week, weekdays, weekends). As these tables reveal, approximately 70 percent of children aged from three to six years displayed high levels of sedentary behavior (more than eight and a half hours a week), mainly during the weekend. Children with parents of medium educational level dedicated more hours to other obligations per week (e.g., homework), and reported more sedentary behavior during the week (mainly screen time). Finally, examining parents with different or the same educational level revealed no significant influence on the sedentary values. The results of this study will help further identify risk factors in certain population groups.

Profiles of sedentary behaviors in the oldest old: findings from the National Health and Aging Trends Study

BACKGROUND

Sedentary behavior is a significant health risk. Emerging research suggests that mentally active sedentary behaviors (e.g., computer use and reading) are associated with better health than mentally passive sedentary behaviors (e.g., watching TV). However, these relationships are not well established in the literature, and little is known about the oldest old (age ≥ 80).

AIMS

The aims of this study were to (1) identify distinct subgroups of oldest old adults based on six domains of sedentary behavior (watching TV, using a computer/tablet, talking to friends or family members, doing hobby or other activities, transportation, and resting/napping); and (2) compare health-related outcomes across identified subgroups, using the National Health and Aging Trends Study (NHATS) dataset.

METHODS

Latent profile analysis was used to identify distinct profiles of sedentary behavior. Design-based linear and logistic regressions were used to examine associations between different profiles and health outcomes, accounting for socio-demographic characteristics.

RESULTS

A total of 852 participants were included. We identified four profiles and named them based on total sedentary time (ST) and passive/active pattern: "Medium-passive", "High-passive", "Low", "High-mentally active". Compared to the "High-passive" group, "Low" group and "High-mentally active" group were associated with fewer difficulties with activities of daily living, fewer problems limiting activities and higher cognitive function.

CONCLUSION

This study, with a national representative sample of the oldest old population, suggests that both total ST and sedentary behavior pattern matter when evaluating health outcomes of being sedentary. Interventions should encourage oldest old adults to reduce ST and especially target mentally passive ST.

The Combined Effects of Television Viewing and Physical Activity on Cardiometabolic Risk Factors: The Kardiovize Study

The aim of the present study was to evaluate the association between television viewing/physical activity (TVV/PA) interactions and cardiometabolic risk in an adult European population. A total of 2155 subjects (25–64 years) (45.2% males), a random population-based sample were evaluated in Brno, Czechia. TVV was classified as low (<2 h/day), moderate (2–4), and high (≥4). PA was classified as insufficient, moderate, and high. To assess the independent association of TVV/PA categories with cardiometabolic variables, multiple linear regression was used. After adjustments, significant associations were: High TVV/insufficient PA with body mass index (BMI) (β = 2.61, SE = 0.63), waist circumference (WC) (β = 7.52, SE = 1.58), body fat percent (%BF) (β = 6.24, SE = 1.02), glucose (β = 0.25, SE = 0.12), triglycerides (β = 0.18, SE = 0.05), and high density lipoprotein (HDL-c) (β = −0.10, SE = 0.04); high TVV/moderate PA with BMI (β = 1.98, SE = 0.45), WC (β = 5.43, SE = 1.12), %BF (β = 5.15, SE = 0.72), triglycerides (β = 0.08, SE = 0.04), total cholesterol (β = 0.21, SE = 0.10), low density protein (LDL-c) (β = 0.19, SE = 0.08), and HDL-c (β = −0.07, SE = 0.03); and moderate TVV/insufficient PA with WC (β = 2.68, SE = 1.25), %BF (β = 3.80, SE = 0.81), LDL-c (β = 0.18, SE = 0.09), and HDL-c (β = −0.07, SE = 0.03). Independent of PA levels, a higher TVV was associated with higher amounts of adipose tissue. Higher blood glucose and triglycerides were present in subjects with high TVV and insufficient PA, but not in those with high PA alone. These results affirm the independent cardiometabolic risk of sedentary routines even in subjects with high-levels of PA.

Separate and combined effects of individual and neighbourhood socio-economic disadvantage on health-related lifestyle risk factors: a multilevel analysis

BACKGROUND

Socio-economic disadvantage at both individual and neighbourhood levels has been found to be associated with single lifestyle risk factors. However, it is unknown to what extent their combined effects contribute to a broad lifestyle profile. We aimed to (i) investigate the associations of individual socio-economic disadvantage (ISED) and neighbourhood socio-economic disadvantage (NSED) in relation to an extended score of health-related lifestyle risk factors (lifestyle risk index); and to (ii) investigate whether NSED modified the association between ISED and the lifestyle risk index.

METHODS

Of 77 244 participants [median age (IQR): 46 (40-53) years] from the Lifelines cohort study in the northern Netherlands, we calculated a lifestyle risk index by scoring the lifestyle risk factors including smoking status, alcohol consumption, diet quality, physical activity, TV-watching time and sleep time. A higher lifestyle risk index was indicative of an unhealthier lifestyle. Composite scores of ISED and NSED based on a variety of socio-economic indicators were calculated separately. Linear mixed-effect models were used to examine the association of ISED and NSED with the lifestyle risk index and to investigate whether NSED modified the association between ISED and the lifestyle risk index by including an interaction term between ISED and NSED.

RESULTS

Both ISED and NSED were associated with an unhealthier lifestyle, because ISED and NSED were both positively associated with the lifestyle risk index {highest quartile [Q4] ISED beta-coefficient [95% confidence interval (CI)]: 0.64 [0.62-0.66], P < 0.001; highest quintile [Q5] NSED beta-coefficient [95% CI]: 0.17 [0.14-0.21], P < 0.001} after adjustment for age, sex and body mass index. In addition, a positive interaction was found between NSED and ISED on the lifestyle risk index (beta-coefficient 0.016, 95% CI: 0.011-0.021, Pinteraction < 0.001), which indicated that NSED modified the association between ISED and the lifestyle risk index; i.e. the gradient of the associations across all ISED quartiles (Q4 vs Q1) was steeper among participants residing in the most disadvantaged neighbourhoods compared with those who resided in the less disadvantaged neighbourhoods.

CONCLUSIONS

Our findings suggest that public health initiatives addressing lifestyle-related socio-economic health differences should not only target individuals, but also consider neighbourhood factors.

Physical activity, sedentary behavior, and the risk of type 2 diabetes: A two-sample Mendelian Randomization analysis in the European population

Physical activity (PA) and sedentary behaviors (SB) have been linked to the risk of type 2 diabetes (T2DM) in observational studies; however, it is unclear whether these associations are causative or confounded. This study intends to use summary genetic data from the UK Biobank and other consortiums in conjunction with the two-sample Mendelian Randomization (MR) approach to solve this problem. The inverse variance weighted (IVW) technique was utilized as the primary analysis, with sensitivity analyses using the MR-Egger, weighted-median, and MR-Pleiotropy RESidual Sum and Outlier (PRESSO) techniques. Inverse associations between self-reported moderate PA (OR: 0.3096, 95% CI: 0.1782-0.5380) and vigorous PA (OR: 0.2747, 95% CI: 0.1390-0.5428) with T2DM risk were found, respectively. However, accelerometer-based PA measurement (average acceleration) was not associated with T2DM risk (OR: 1.0284, 95% CI: 0.9831-1.0758). The time (hours/day) spent watching TV was associated with T2DM risk (OR: 2.3490, 95% CI: 1.9084-2.8915), while the time (hours/day) spent using the computer (OR: 0.8496, 95% CI: 0.7178-1.0056), and driving (OR: 3.0679, 95% CI: 0.8448-11.1415) were not associated with T2DM risk. The sensitivity analysis revealed relationships of a similar magnitude. Our study revealed that more PA and less TV viewing were related to a decreased T2DM risk, and provided genetic support for a causal relationship between PA, TV viewing, and T2DM risk.

Effectiveness of a Lifestyle Modification Program Delivered under Real-World Conditions in a Rural Setting

Whilst there is considerable evidence to support the efficacy of physical activity and dietary interventions in disease and death prevention, translation of knowledge into practice remains inadequate. We aimed to examine the uptake, retention, acceptability and effectiveness on physical activity, physical function, sitting time, diet and health outcomes of a Healthy Eating Activity and Lifestyle program (HEAL^TM) delivered under real-world conditions. The program was delivered to 430 adults living across rural South Australia. Participants of the program attended weekly 2 h healthy lifestyle education and exercise group-based sessions for 8 weeks. A total of 47 programs were delivered in over 15 communities. In total, 548 referrals were received, resulting in 430 participants receiving the intervention (78% uptake). At baseline, 74.6% of participants were female, the mean age of participants was 53.7 years and 11.1% of participants identified as Aboriginal and/or Torres Strait Islander. Follow-up assessments were obtained for 265 participants. Significant improvements were observed for walking, planned physical activity, incidental physical activity, total physical activity, 30 s chair stand, 30 s arm curl, 6 min walk, fruit consumption and vegetable consumption, sitting time and diastolic blood pressure. Positive satisfaction and favourable feedback were reported. The healthy lifestyle program achieved excellent real-world uptake and effectiveness, reasonable intervention attendance and strong program acceptability amongst rural and vulnerable communities.

Barriers and Facilitators for the Romanian Older Adults in Enjoying Physical Activity Health-Related Benefits

Older adults are considered a vulnerable category within the population, which is exposed to an accelerated risk of functional degeneration. The purpose of this study was to explore different facilitating factors and possible existing barriers to being physically active in older age in urban areas of Romania. A cross-sectional survey was conducted among 172 participants who were asked to assess their health, on a scale from 1 to 3, and to fill out two questionnaires: 1. Physical Activity Scale for the Elderly; 2. Depression, Anxiety, and Stress Scale. Participants were also asked to specify to what extent they performed different leisure activities during the last week. SPSS was used for data analysis. The chi-squared test, t-test, ANOVA, and MANOVA emphasised the differences between participants, at p < 0.05. Regarding health condition, 27.3% of participants responded that their health was good, 53.5%—satisfactory, and 19.2%—not so good. The results showed significant differences between older adults participating in Elderly Clubs and non-participants, only in terms of PASE leisure. There were significant multivariate effects of the variables Gender and Stable life partner regarding PASE leisure. Weak negative correlations were identified between leisure physical activities and emotional state. Among the proposed leisure activities, watching TV and listening to music represented the most frequent preferences of the participants. The older adults participating in this study preferred to become involved with different physical activities, in conjunction with their habits, health, age, sex, stable life partner, and Elderly Club participation.

Patterns and Predictors of Television Viewing and Computer Use Among Women Living in Socioeconomically Disadvantaged Neighborhoods: A Prospective Cohort Study

BACKGROUND

Socioeconomically disadvantaged women are at an increased risk of sedentary behaviors including television (TV) viewing and computer use, so identifying determinants of these behaviors is important.

METHODS

Women (n = 4349) self-reported weekly TV and computer time (in minutes per week), sociodemographic, and health data at 3 time points (2007-2013). Mixed-effect negative binomial regression was used to determine the baseline determinants of TV viewing and computer use over time, adjusting for confounders.

RESULTS

Over 5 years, median TV viewing decreased while median computer time increased. Cross-sectionally TV viewing was highest among participants classified as obese, with poorer health, current smokers, with lower education, not working, with no income, without partners and with no children and computer time was greater among younger women, living in urban areas, working full time, with higher education, without partners and with no children. Average computer time per year increased among those not working (7%), with lower education (5%), and with children (5%) but decreased among those with higher education (1%). However, no factors were associated with a change in TV viewing over time.

CONCLUSION

Among socioeconomically disadvantaged women, interventions aimed at preventing increases in computer time should consider women with lower education, not working, and with children in their design.

Understanding Variations in the Health Consequences of Sedentary Behavior: A Taxonomy of Social Interaction, Novelty, Choice, and Cognition

The study of sedentary behaviors requires taxonomies (classification schemes) to standardize data collection, measurements, and outcomes. Three taxonomies of sedentary behaviors have been identified, but none address an important challenge in sedentary behavior research, which is to distinguish between beneficial and detrimental health effects of various sedentary behaviors. Some sedentary behaviors (e.g., reading) are associated with positive health outcomes, whereas other sedentary behaviors (e.g., television viewing) are associated with adverse health outcomes. To address directly this complexity and present a different conception and understanding of discrepant findings related to health outcomes, a new taxonomy is needed. The development of the new taxonomy is guided by analysis of literature and selection of a relevant and informative behavioral sciences theoretical framework (i.e., self-determination theory). Because older adults are an increasing percentage of the population and report a high prevalence of sedentary behaviors, the new taxonomy was designed for older adults with potential application to all age groups. Taylor's taxonomy of sedentary behaviors is parsimonious with four domains: social interaction (i.e., not solitary, companionship, interacting, and connecting with others); novelty (i.e., refreshingly new, unusual, or different); choice (i.e., volition, preferred option or alternative, the power, freedom, or decision to choose); and cognition (i.e., mentally stimulating and engaging).

Students' Physical Activity Profiles According to Children's Age and Parental Educational Level

The aim of this study was to identify different profiles of physical activity (PA) behaviors according to the school student’s age stage and their parents’ or guardians education level. Seven hundred twenty-seven students and parents of different educational stages were invited to take part in this study. The participants included, Preschool (1 to 5 years old), Primary School (6 to 11 years old), Secondary School (12 to 15 years old), and High School (16 to 18 years old). A questionnaire to assess the educational level of parents (low, intermediate, and high) and their child’s PA level and sedentary behaviors across various age stages was administered. The results showed a number of different physical activity profiles for preschool (4), primary (6), secondary (7) and high school (2) students. Primary and secondary school children’s behavioral profiles were reported to differ significantly between both physical activity levels and sedentary behaviors, while preschool students’ behavioral profiles only differed between sedentary behaviors. Higher parental education was most prevalent in clusters with significantly higher levels of PA in primary and secondary students, while there were equivocal trends for parental education level influencing behavioral profiles of high school students. These findings suggest there is some association between the behavioral profiles of student’s physical activity and sedentary behavior, and parental education level, most noticeably during the early to middle age stages.

Exploring daily time-use patterns: ATUS-X data extractor and online diary visualization tool

Time-use data can often be perceived as inaccessible by non-specialists due to their unique format. This article introduces the ATUS-X diary visualization tool that aims to address the accessibility issue and expand the user base of time-use data by providing users with opportunity to quickly visualize their own subsamples of the American Time Use Survey Data Extractor (ATUS-X). Complementing the ATUS-X, the online tool provides an easy point-and-click interface, making data exploration readily accessible in a visual form. The tool can benefit a wider academic audience, policy-makers, non-academic researchers, and journalists by removing accessibility barriers to time use diaries.

Improvements in Physical Activity Levels after the Implementation of an Active-Break-Model-Based Program in a Primary School

The aim of this study was to analyze changes in the physical activity levels in students after implementing an active break (AB)-model-based program during the school day. Forty-four fifth-grade primary school children (24 boys, 20 girls, with a mean age = 10.44 ± 0.45) participated in a 17 week program. After intervention, there was an increase in moderate and vigorous total activity during physical education lessons, non-physical education lessons, and recesses. Intervention programs to encourage physical activity and decrease sedentary time are recommended.

The time spent sitting does not always mean a low level of physical activity

Background

The problem of spending most of the day in a sitting position concerns all people, regardless of their age. Unfortunately, this trend is more and more often observed among young people.

The aim of the study was to assess self-reported physical activity and time spent sitting among students of different fields of health related faculty.

Methods

The study group included 216 students (22.3 ± 1.8 years of age) of the Medical University of Lodz: physiotherapy students (n = 101), pharmacy students (n = 73), and dietetics students (n = 42). The time spent sitting and physical activity level were assessed based on the International Physical Activity Questionnaire-long version.

Results

The time spent sitting among health related faculty students was on average more than 46 h a week (2781.8 ± 1238.5 MET-minutes/week). Regarding all the students the pharmacy students spent most time sitting (3086.0 ± 1032.1 MET-minutes/week), while the dietetics students spent the least (2215.7 ± 1230.1 MET-minutes/week). Taking into account the physical activity level almost 65% of all the students were in a high category (mainly physiotherapy students). Only 1.4% of all the surveyed students were classified as the low physical activity category. Statistical analysis showed no significant differences (P = 0.6880) between the time spent sitting and level of physical activity among all students.

Conclusions

Students of medical universities spend too much hours on sitting, mostly 5–8 h a day. Despite this, they undertake various activities due to which their level of physical activity is moderate or even high. Therefore, it cannot be unequivocally stated that there is a relationship between the time spent sitting and physical activity level.

Cross-Sectional Association Between Types of Leisure Activities and Self-rated Health According to Gender and Work Status Among Older Japanese Adults

Background

Participation in leisure activities (LA) is essential for successful aging. Our aim was to investigate the cross-sectional association of types of LA with self-rated health (SRH) by gender and work status.

Methods

The target population was all residents aged ≥65 years in a municipality (n = 16,010; response rate, 62.5%). We analyzed 4,044 men and 4,617 women without disabilities. LA were categorized into 14 types. SRH was assessed through the SF-8. Excellent or very good SRH was defined as positive SRH. Covariates included age, marital status, education, subjective economic status, body mass index, chronic diseases, alcohol, smoking, walking time, depression, and cognitive functioning. Multiple logistic regressions were used to calculate the odds ratio (OR) and 95% confidence interval (CI) for positive SRH, with non-participation as the reference.

Results

After adjustment for covariates and mutual adjustment for other LA, participation in the following types of LA was positively associated with positive SRH: sports activities among working men (OR 1.46; 95% CI, 1.07–2.00), non-working men (OR 1.33; 95% CI, 1.04–1.69), and non-working women (OR 1.74; 95% CI, 1.41–2.15); cooking among non-working men (OR 1.65; 95% CI, 1.18–2.33) and non-working women (OR 1.28; 95% CI, 1.03–1.60); musical activities among working men (OR 1.44; 95% CI, 1.01–2.05) and non-working women (OR 1.59; 95% CI, 1.29–1.95); and technology usage only among working men (OR 1.41; 95% CI, 1.01–1.96). In contrast, TV watching was negatively associated with positive SRH among non-working women (OR 0.69; 95% CI, 0.56–0.85).

Conclusions

Our results suggest that encouraging older adults to participate in types of LA appropriate to their gender and work status might be a key to positive SRH.

High-risk behaviors and demographic features: a cross-sectional study among Iranian adolescents

BACKGROUND AND OBJECTIVES

High-risk behaviors are considered to be a serious threat among adolescents. This study aimed to investigate the frequency of unhealthy and high-risk behaviors and their relationship with demographic features in adolescents living in Shiraz, Iran.

MATERIALS AND METHODS

The present descriptive, cross-sectional study was conducted on 483 students in the 10th grade of high school. The data were collected using a demographic information form and a modified adolescents high-risk behaviors questionnaire. The reliability of the questionnaire was assessed using the test-retest method. Afterwards, the data were entered into the SPSS statistical software (IBM), version 22 and were analyzed using the chi-square (χ²) test, logistic regression analysis and one-way analysis of variance (ANOVA).

RESULTS

High-risk health behaviors were significantly correlated to adolescents' gender, parents' occupations and education levels, length of residency in Shiraz and talking about important things with one's parents (p < 0.03). Gender predicted 52% of variance of bullying behaviors at school [Exp(B) = 0.502, p < 0.03, 95% confidence interval (CI) = 0.261-0.996]. In fact, most high-risk behaviors were associated with gender (p < 0.001). Indeed, bullying was mostly reported in boys, while being hopeless or sad, suicide attempts and appropriate weight loss behaviors were mostly reported among girls. Additionally, the frequency of smoking cigarettes and using hookahs was higher among girls compared to boys (23.1% for smoking cigarettes and 39.6% for using hookahs). However, no significant correlation was observed between gender and smoking cigarettes and using hookahs (p > 0.704 for smoking cigarettes and p > 0.118 for using hookahs). The most prevalent high-risk behaviors were physical fighting (51.1%), being sad or hopeless (35.2%), alcohol abuse (26.7%), overweight (14.7%) and obesity (8.1%) in both genders. Based on the results, only 26.5% of the adolescents had sufficient physical activity. Besides, the adolescents' weight scores were significantly correlated to eating green salads (p < 0.01), which was seen more among overweight adolescents.

CONCLUSION

The findings indicated that adolescents' gender and their parents' roles should be taken into consideration in designing health promotion programs, such as mental health and its related skills. This would eventually result in the prevention and reduction of unhealthy habits.