Association Between Employment Status and Objectively Measured Physical Activity and Sedentary Behavior—The Maastricht Study

Relationships between grit and lifestyle factors in undergraduate college students during the COVID-19 pandemic

Objective: To investigate the influence of grit on physical activity, sleep and diet in undergraduate students during the COVID-19 pandemic. Participants: 125 undergraduate students participated in the study. Participants completed an online survey while enrolled in an online class during June, 2020. Methods: The online questionairre featured the following validated survey instruments: International Physical Activity Questionnaire Short Form, Pittsburgh Sleep Quality Index, the Rapid Eating Assessment for Participants Short Form and the grit short form. Effects of grit on lifestyle behaviors were explored using several statistical approaches. Results: We found that individuals with more grit reported better eating and sleeping behaviors compared to those with less grit. However, we did not find an influence of grit on physical activity or sitting time. Conclusion: Our findings support that personality traits encompassed in grit contribute to college students reporting healthier dietary habits and better sleep quality during a global pandemic.

Weekday and weekend physical activity patterns and their correlates among young adults

BACKGROUND

Accelerometers enable assessment of within and between day variation in physical activity. The main aim was to examine weekday and weekend physical activity patterns among young adults. Additionally, correlates of the physical activity patterns were examined.

METHODS

Overall 325 adults (mean age 26.0 years, standard deviation 0.03) from the Special Turku Coronary Risk Factor Intervention Project used a wrist-worn ActiGraph accelerometer continuously for 1 week. Physical activity patterns over weekdays and weekends were identified by using the group-based trajectory modeling. Adolescent leisure time physical activity (LTPA) and sociodemographic characteristics (sex, marital and family status, education, work status, occupation, and health consciousness) were examined as possible correlates of physical activity patterns using multinomial regression analysis.

RESULTS

Five patterns were identified: consistently low activity (45%), active on weekday evenings and weekends (32%), consistently moderate activity (11%), active on weekdays (7%), and consistently high activity (5%). Low adolescent LTPA was associated with consistently low activity pattern in young adulthood. Women were more likely than men to belong in the more physically active groups (all other groups except active on weekdays, odds ratios between 2.26 and 6.17). Those in the active on weekdays group had lower education, were more often in the working life and in manual occupations than those in the consistently low activity group.

CONCLUSIONS

Marked heterogeneity in physical activity patterns across the week was observed among young adults. Especially history of physical activity, sex, education, work status, and occupation were associated with different physical activity patterns.

Investigating sedentariness and health status of primary school teachers in Ghana

OBJECTIVE

Physical inactivity is linked to chronic illnesses and disabilities among workers, especially those in high demanding jobs like teachers. Despite the global prominence of sedentary behavior research, studies drawing the relationships between physical inactivity and multimorbidity among working teacher populations in low-and middle-countries remain untapped. This study assessed the sedentariness and health status of primary school teachers in Cape Coast Metropolis in Ghana.

METHOD

This cross-sectional survey employed 1109 primary school teachers from the Cape Coast Metropolis in the Central Region of Ghana, targeting the entire population.

RESULTS

Generally, the teachers were highly sedentary and reported poor health status. Other results showed no difference in sedentariness across gender, (n = 1107, t= -0.32, p > 0.05). However, female teachers suffer more pain and discomfort, (n = 1103.51), t = - 3.07, p < 0.05), anxiety and depression, (n = 1099.56), t = - 2.85, p < 0.000), and poor health status (n = 1107), t = 2.14, p < 0.05), than their male counterparts. Also, pain and discomfort, anxiety and depression, health status and years of work significantly predicted sedentariness among the teachers, F (4, 1104) = 5.966, p = 0.00, R = 0.145, R2 = 0.029, adjusted R2 = 0.018.

CONCLUSION

The findings suggest that individualized or personalized interventions are urgently needed to promote regular physical activity to improve the health status and reduce associated complications on the health and well-being, especially among the female primary school teachers. Given the health risks of sedentary lifestyle, behavioral interventions at the person-level (i.e., individualized- routine weekly physical activity programs) and built environmental restructuring (e.g., creation of walkways to encourage regular walking) could be done to improve physical activity behavior among teachers within the Cape Coast Metropolis, and perhaps beyond.

Daily Physical Activity Patterns and Their Associations with Cardiometabolic Biomarkers: The Maastricht Study

PURPOSE

This study aimed to identify physical activity patterns and examine their association with cardiometabolic biomarkers in a cross-sectional design.

METHODS

Overall 6072 participants (mean age, 60.2 yr; SD 8.6 yr, 50% women) from The Maastricht Study provided daily physical activity data collected with thigh-worn activPAL3 accelerometers. The patterns of daily physical activity over weekdays and weekend days were identified by using Group Based Trajectory Modeling. Cardiometabolic biomarkers included body mass index, waist circumference, office blood pressure, glucose, HbA1c, and cholesterol levels. Associations between the physical activity patterns and cardiometabolic outcomes were examined using the analyses of covariance adjusted for sex, age, education, smoking, and diet. Because of statistically significant interaction, the analyses were stratified by type 2 diabetes status.

RESULTS

Overall, seven physical activity patterns were identified: consistently inactive (21% of participants), consistently low active (41%), active on weekdays (15%), early birds (2%), consistently moderately active (7%), weekend warriors (8%), and consistently highly active (6%). The consistently inactive and low active patterns had higher body mass index, waist, and glucose levels compared with the consistently moderately and highly active patterns, and these associations were more pronounced for participants with type 2 diabetes. The more irregular patterns accumulated moderate daily total activity levels but had rather similar cardiometabolic profiles compared with the consistently active groups.

CONCLUSIONS

The cardiometabolic profile was most favorable in the consistently highly active group. All patterns accumulating moderate to high levels of daily total physical activity had similar health profile suggesting that the amount of daily physical activity rather than the pattern is more important for cardiometabolic health.

Examining health risk behaviors of self-employed and employed workers in Japan: a cross-sectional study

OBJECTIVES

Self-employed workers have a higher risk for adverse health outcomes than employed workers. However, the differences in health risk behaviors by employment status are largely unknown. This study examined differences in health risk behaviors between self-employed and employed (permanent/non-permanent) workers by sex and age (20-59 years, 60-79 years).

STUDY DESIGN

This was a cross-sectional study involving community-dwelling adults living in urban cities in Japan.

METHODS

In 2019, we conducted a mail survey in Wako city, Saitama, and Fuchu city, Tokyo. In total, 30,315 adults aged ≥18 years were randomly selected, and 14,185 completed the survey (response rate: 46.8%). The participants for analysis were 8538 workers. Health risk behaviors included physical inactivity (<150 min/wk of moderate-to-vigorous physical activity), prolonged sitting (>480 min/d), high-frequency drinking (≥3 d/wk), tobacco use (current smoker), and overweight (body mass index ≥ 25 kg/m²). We also calculated the total number of health risk behaviors.

RESULTS

Self-employed workers had more health risk behaviors than permanent and non-permanent employees, with this difference more significant among younger males. In younger males, compared with self-employment, permanent employment was associated with less tobacco use, and non-permanent employment was associated with less physical inactivity, prolonged sitting, high-frequency drinking, and overweight. In younger females, non-permanent employment was associated with less prolonged sitting and overweight than self-employment. In older males and females, the prevalence of physical inactivity was lower in non-permanent employed than in self-employed workers.

CONCLUSIONS

Promoting health behaviors among self-employed may be beneficial for reducing health inequalities between self-employed and employed workers.

Unobtrusive monitoring of sedentary behaviors with fusion of bluetooth and ballistocardiogram signals

Intensive and lasting stress may induce severe damage to a human's physical and mental health. Successful stress management depends on the effective monitoring of people's everyday activities, in particular, their sedentary behaviors. Here, we propose an unobtrusive office sedentary behavior monitoring system that combines Bluetooth signals and ballistocardiogram (BCG) signals to classify an individual's sitting modes into four categories: off-seat, sedate, working, and in-motion. The proposed monitoring system simultaneously reads received signal strength indicators (RSSI) from several fixed Bluetooth Low Energy (BLE) beacons and BCG data from the piezoelectric sensor placed underneath the chair cushion, with distinct sampling frequencies. The raw signals are first denoised with local subspace projection. Then we extract the local spectral features from the reconstructed signal and the signal differences for a two-stage stacking learning algorithm. The temporally classified results establish a desk-based worker's sedentary profile and make possible the timely intervention of physical inactivity. We tested the prototype system for 15 subjects, and the preliminary results achieved 95% accuracy, demonstrating its potential in a real-world application.

Independence and Sex Differences in Physical Activity and Sedentary Behavior Trends from Middle Adolescence to Emerging Adulthood: A Latent Class Growth Curve Analysis

The purpose of this study was to examine the relationship and sex differences in the growth patterns of moderate-to-vigorous physical activity (MVPA) and sedentary behavior (SB) from middle adolescence (around age 15) to emerging adulthood (18–29 years old). We used the secondary data from the National Longitudinal Study of Adolescent Health’s (Add Health) publicly accessible database. MVPA and SB were assessed four times (1995, 1996, 2000–2001, and 2008–2009) for a total of 681 individuals from middle adolescence to emerging adulthood. Latent class growth modeling was utilized to identify heterogeneous growth patterns in MVPA and SB. Chi-square tests were used to assess group dependence and sex differences in MVPA and SB growth patterns. Seven quadratic growth patterns for MVPA and two linear growth patterns for SB were found. Both MVPA and SB growth patterns exhibited slow or rapid rate of change at different periods of adolescence and emerging adulthood. MVPA growth patterns included: decline (slow)-and-rise (rapid), rise-and-decline (both rapid), decline-and-rise (both rapid), consistently low, consistently high, decline (rapid)-and-decline (slow), and decline (rapid)-and-rise (slow). SB growth patterns included: consistently low (slow decline) and consistently high (rapid decline). While women were more likely to be involved in consistently low group for MVPA and consistently low (slow decline) group for SB, men were more likely to be involved in rise-and-decline (both rapid) group, consistently high group, and decline (rapid)-and-rise (slow) group for MVPA and consistently high (rapid decline) group for SB. SB growth patterns were independent of MVPA growth patterns. SB should not be assumed to decrease as a result of MVPA intervention. Treatment of MVPA should prioritize adolescence over emerging adulthood, with an emphasis on preventing men’s MVPA levels from decreasing in emerging adulthood and increasing women’s overall MVPA levels.

Changes to Physical Activity Levels in Adults Aged 50+ in the First Six Months of the COVID-19 Pandemic

The purpose of this study is to qualitatively explore the impact of the COVID-19 pandemic on older adults’ PA nearly 6 months into the pandemic. Approximately 230 interviews were conducted with a diverse sample of participants (22.1% Black and 10.8% Hispanic). Data were transcribed in fall 2020 and analyzed using NVivo 12. Overall, most older adults (54.6%) interviewed reported no change in their PA, often reporting that their work kept them active. Decreases in PA for older adults (42.7%) were attributed to little social connectedness and stay-at-home restrictions. The few reporting an increase in PA (2.6%) had more time available to be active, including setting goals while staying home. This data provides an insight on how COVID-19 impacted PA levels for older adults. These findings can inform tailored interventions to promote PA during the pandemic.

Occupational determinants of physical activity at work: Evidence from wearable accelerometer in 2005-2006 NHANES

Occupation determines workers' physical activity (PA) in the workplace, an important health behavior contributing to health outcomes. However, self-reported measure limits our understanding of how occupational tasks differentiate workers' PA in terms of the type, frequency, intensity, and duration. In addition, accurate estimation of occupation-based PA during workers' actual working hours requires precise work schedule information. To address these limitations, this study employs data on accelerometer-monitored PA and work schedule from the 2005-2006 National Health and Nutrition Examination Survey (NHANES). It asks two questions: How do occupations determine PA among regular daytime workers in the United States? Second, how large a share of PA difference between two occupations is attributable to differences in the implicit occupational tasks, relative to workers' demographic, health preconditions, and socioeconomic attributes? Calculating PA during the 9-to-5 period among daytime regular workers on weekdays and conducting Blinder-Oaxaca decomposition analysis, we yield insights into the occupational determinant of both PA volume (total activity counts) and fragmentation (bouts of activities). Worksite health promotion can utilize the objective occupation-PA link and design occupation-tailored interventions, which is currently underdeveloped in the United States. Moreover, our findings shed light on the physical nature of occupation, suggesting a fruitful step to reconcile the documented mixed findings on occupation-based PA and health outcomes in future studies.

Day-to-day pattern of work and leisure time physical behaviours: are low socioeconomic status adults couch potatoes or work warriors?

Background

Most studies on day-to-day patterns of physical behaviours (i.e. physical activities and sedentary behaviour) are based on adults with high socioeconomic status (SES) and without differentiating between work and leisure time. Thus, we aimed to characterise the day-to-day leisure time physical behaviours patterns among low SES adults and investigate the influence of work physical behaviours.

Methods

This cross-sectional study included 963 adults from low SES occupations (e.g. manufacturing, cleaning and transportation). The participants wore accelerometers for 1–7 days to measure physical behaviours during work and leisure time, expressed as time-use compositions consisting of time spent sedentary, standing or being active (walking, running, stair climbing, or cycling). Compositional multivariate multilevel models were used to regress daily leisure time-use composition against work time-use compositions. Interaction between weekday and (1) type of day, (i.e., work/non-work) and (2) the work time-use composition were tested. Compositional isotemporal substitution was used to interpret the estimates from the models.

Results

Each weekday, workers consistently spent most leisure time being sedentary and most work time standing. Leisure time physical behaviours were associated with type of day (p < 0.005, more sedentary on workdays vs. non-workdays), weekday (p < 0.005, more sedentary on Friday, Saturday and Sunday), standing work (p < 0.005, more sedentary and less standing and active leisure time on Sunday), and active work (p < 0.005, less sedentary and more standing and active leisure time on Sunday). Sedentary leisure time increased by 18 min, while standing and active leisure time decreased by 11 and 7 min, respectively, when 30 min were reallocated to standing at work on Sunday. Conversely, sedentary leisure time decreased by 25 min, and standing and active leisure time increased by 15 and 10 min, respectively, when 30 min were reallocated to active time at work on Sunday.

Conclusions

While low SES adults’ leisure time was mostly sedentary, their work time was predominantly standing. Work physical behaviours differently influenced day-to-day leisure time behaviours. Thus, public health initiatives aiming to change leisure time behaviours among low SES adults should consider the influence of work physical behaviours.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-11409-0.

Contexts of sedentary time and physical activity among ageing workers and recent retirees: cross-sectional GPS and accelerometer study

OBJECTIVES

We examined sedentary time and physical activity in different contexts among ageing workers, between their workdays and days off, and recent retirees, between their weekdays and weekend days.

DESIGN

Cross-sectional study.

SETTING

Finnish Retirement and Aging study and Enhancing physical activity and healthy ageing among recent retirees-Randomised controlled in-home physical activity trial.

PARTICIPANTS

137 workers (544 measurement days) and 53 retirees (323 days), who provided data for at least 1 workday/weekday and 1 day off/weekend day.

PRIMARY AND SECONDARY OUTCOME MEASURES

Physical activity behaviour was measured with a combined Global Positioning System and accelerometer device (SenseDoc V.2.0), providing information on sedentary time, light physical activity and moderate-to-vigorous physical activity (MVPA) by locations (home or non-home) and trips (active travel, ie, speed <20 km/hour and passive travel, ie, speed ≥20 km/hour).

RESULTS

Workers accumulated more sedentary time and physical activity at non-home locations than at home on workdays, while the opposite was confirmed for days off (p<0.01). Workers accrued more MVPA on days off than on workdays (34 vs 28 min, p<0.05), of which 9 min on workdays and 14 min on days off was accrued during active travel. Retirees' physical activity behaviour did not differ between weekdays and weekend days (p>0.05). Regardless of the day, retirees accumulated 33 min of daily MVPA, of which 14 min was accrued during active travel.

CONCLUSIONS

Workers accumulated more MVPA on days off than on workdays, and their activity behaviour varied between workdays and days off at different locations. Our results showed that a large proportion of the MVPA was accumulated during travel at slower speeds, which suggests that active travel could be a feasible way to increase MVPA among older adults.

TRIAL REGISTRATION NUMBER

NCT03320746.

The Influence of Occupational Categories on Overall and Domain-Specific Physical Activity and the Association with Chronic Diseases. An Analysis Using the Austrian Health Interview Survey

Background: The performance of physical activity (PA) in different domains varies between different occupational groups and they contribute differently to the prevention and management of chronic diseases. This study aimed to give a fuller picture of the potential influence occupational categories have on the different domains of PA among the Austrian population of working age. Methods: A total of 8251 gainfully employed persons in 9 major and 39 sub-major occupational groups from the Austrian Health Interview Survey 2014 were analyzed. PA was measured with the Physical Activity Questionnaire of the European Health Interview Survey (EHIS-PAQ) and the prevalence of 17 chronic diseases was obtained. Results: A total of 48.2% were mostly active when working, 18.4% reported transport-related PA in the upper quintile, 50.4% performed at least 150 min per week of moderate PA or cycling, 32.7% performed muscle-strengthening PA at least twice a week, and 76.3% were either mostly physically active when working or complied with the aerobic PA guidelines. As a general rule, people in physically active occupational groups tended to perform less PA in their leisure time and vice versa. Occupational groups with especially low amount of PA were Information Technology workers, directors, and secretarial staff. People with a chronic disease tended to perform less PA, but there was an interaction between occupation and chronic disease on PA. Conclusions: Domain-specific programs to promote PA should be developed for various occupational categories.

Thigh-worn accelerometry for measuring movement and posture across the 24-hour cycle: a scoping review and expert statement

INTRODUCTION

The Prospective Physical Activity Sitting and Sleep consortium (ProPASS) is an international collaboration platform committed to harmonise thigh-worn accelerometry data. The aim of this paper is to (1) outline observational thigh-worn accelerometry studies and (2) summarise key strategic directions arising from the inaugural ProPASS meeting.

METHODS

(1) We performed a systematic scoping review for observational studies of thigh-worn triaxial accelerometers in free-living adults (n≥100, 24 hours monitoring protocols). (2)Attendees of the inaugural ProPASS meeting were sent a survey focused on areas related to developing ProPASS: important terminology (Q1); accelerometry constructs (Q2); advantages and distinct contribution of the consortium (Q3); data pooling and harmonisation (Q4); data access and sharing (Q5 and Q6).

RESULTS

(1) Eighty eligible articles were identified (22 primary studies; n~17 685). The accelerometers used most often were the ActivPAL3 and ActiGraph GT3X. The most commonly collected health outcomes were cardiometabolic and musculoskeletal. (2) None of the survey questions elicited the predefined 60% agreement. Survey responses recommended that ProPASS: use the term physical behaviour or movement behaviour rather than 'physical activity' for the data we are collecting (Q1); make only minor changes to ProPASS's accelerometry construct (Q2); prioritise developing standardised protocols/tools (Q4); facilitate flexible methods of data sharing and access (Q5 and Q6).

CONCLUSIONS

Thigh-worn accelerometry is an emerging method of capturing movement and posture across the 24 hours cycle. In 2020, the literature is limited to 22 primary studies from high-income western countries. This work identified ProPASS's strategic directions-indicating areas where ProPASS can most benefit the field of research: use of clear terminology, refinement of the measured construct, standardised protocols/tools and flexible data sharing.

Comparison of Sedentary Time Between Thigh-Worn and Wrist-Worn Accelerometers

Background: The accuracy of wrist-worn accelerometers in identifying sedentary time has been scarcely studied in free-living conditions. The aim of this study was to compare daily sedentary time estimates between a thigh-worn accelerometer, which measured sitting and lying postures, and a wrist-worn accelerometer, which measured low levels of movement. Methods: The study population consisted of 259 participants (Mage = 62.8 years, SD = 0.9) from the Finnish Retirement and Aging Study (FIREA). Participants wore an Axivity AX3 accelerometer on their mid-thigh and an Actigraph wActiSleep-BT accelerometer on their non-dominant wrist simultaneously for a minimum of 4 days in free-living conditions. Two definitions to estimate daily sedentary time were used for data from the wrist-worn accelerometer: 1) the count cutpoint, ≤1853 counts per minute; and 2) the Euclidean Norm Minus One (ENMO) cutpoint, <30 mg. Results: Compared to the thigh-worn accelerometer, daily sedentary time estimate was 63 min (95% confidence interval [CI] = −53 to −73) lower by the count cutpoint and 50 min (95% CI = 34 to 67) lower by the ENMO cutpoint. The limits of agreement in daily sedentary time estimates between the thigh- and cutpoint methods for wrist-worn accelerometers were wide (the count cutpoint: −117 to 243, the ENMO cutpoint: −212 to 313 min). Conclusions: Currently established cutpoint-based methods to estimate sedentary time from wrist-worn accelerometers result in underestimation of daily sedentary time compared to posture-based estimates of thigh-worn accelerometers. Thus, sedentary time estimates obtained from wrist-worn accelerometers using currently available cutpoint-based methods should be interpreted with caution and future work is needed to improve their accuracy.

Social and physical environmental factors in daily stepping activity in those with chronic stroke

BACKGROUND, PURPOSE/OBJECTIVE

Walking behavior in the chronic stroke population is multi-factorial. Previous work focused on the role of physical and biopsychosocial factors in understanding daily stepping post stroke. However, qualitative evidence suggests that social and physical environmental factors also affect daily stepping in those with stroke. The purpose of this study was to understand the role of social and physical environmental factors in daily stepping after stroke.

METHODS

A total of 249 individuals ≥6 months post stroke were included in this cross-sectional analysis (129 females, mean age 62.98 years, SD 11.94). The social environment included living situation, work status, and marital status. The physical environment included the Area Deprivation Index (ADI) and Walk Score. At least 3 days of stepping was collected using an accelerometry-based device. Predictors were entered sequentially into a regression model: demographic characteristics, social environmental factors, and physical environmental factors.

RESULTS

After adjusting for demographic factors, social environmental factors explained 6.2% (p =.017) of the variance in post stroke daily stepping. The addition of physical environmental factors improved the model (ΔR² =.029, p =.024). The final model explained 9.2% (p =.003) of the variance in daily stepping. Lower area deprivation (ADI β = -0.178, p =.015) and working (working vs. retired β = -0.187, p = .029 and working vs. unemployed β = -0.227, p =.008) were associated with greater daily stepping.

DISCUSSION/CONCLUSION

Social and physical environmental factors predicted daily stepping and should be considered when setting expectations relative to the effects of rehabilitation on daily stepping in individuals poststroke.

A framework for assessing neuropsychiatric phenotypes by using smartphone-based location data

The use of smartphone-based location data to quantify behavior longitudinally and passively is rapidly gaining traction in neuropsychiatric research. However, a standardized and validated preprocessing framework for deriving behavioral phenotypes from smartphone-based location data is currently lacking. Here, we present a preprocessing framework consisting of methods that are validated in the context of geospatial data. This framework aims to generate context-enriched location data by identifying stationary, non-stationary, and recurrent stationary states in movement patterns. Subsequently, this context-enriched data is used to derive a series of behavioral phenotypes that are related to movement. By using smartphone-based location data collected from 245 subjects, including patients with schizophrenia, we show that the proposed framework is effective and accurate in generating context-enriched location data. This data was subsequently used to derive behavioral readouts that were sensitive in detecting behavioral nuances related to schizophrenia and aging, such as the time spent at home and the number of unique places visited. Overall, our results indicate that the proposed framework reliably preprocesses raw smartphone-based location data in such a manner that relevant behavioral phenotypes of interest can be derived.

Characterization of Sedentary Behavior in Heart Failure Patients With Arthritis

Background

Arthritis is one of the most common comorbidities in heart failure (HF) patients, and is associated with decreased activity levels. Few studies have examined sedentary behavior (SB) in HF patients with arthritis, and little is known about the factors that may influence SB in this population.

Methods

This is a retrospective, secondary analysis using data collected from a randomized control trial. SB was measured by the daily sedentary time collected by accelerometers. Structural equation modeling was performed to examine relationships between key concepts based on social cognitive theory, and elucidate the potential pathways by which demographic, clinical and sociobehavioral factors that influence SB.

Results

A total of 101 participants’ data were used for this analysis. Participants were mainly female (n = 64, 63%) with a mean age of 70 years (standard deviation (SD) = 12.2) and an average of 13 years of education (SD = 2.3). SB was highly prevalent at baseline (mean value: 21.0 h/day), 3 months (mean value: 20.6 h/day) and 6 months (mean value: 20.8 h/day) in study participants. Factors with statistically significant positive association with sedentary time include age and retirement, while significant negative association was found with current employment. HF self-care efficacy and behavior were also significantly associated with SB.

Conclusions

Most HF patients with arthritis in this study lived a sedentary lifestyle. Additional studies are needed to identify feasible and effective exercise programs for HF participants with arthritis.

Higher leisure-time physical activity is associated with lower sickness absence: cross-sectional analysis among the general workforce

BACKGROUND

Prevention of sickness absence (SA) is a major public health challenge. Sufficient levels of physical activity may be an important protective factor. In contrast to the North European countries, little is known about physical activity behavior and its influence over SA in South European countries.

METHODS

In the European Health Interview Survey (EHIS) 2014, a total of 9512 Spanish workers aged 17 to 70 (46.5% women) replied to questions about SA (last 12 months) and the frequency of leisure-time physical activity (LTPA). Multiple linear regression adjusted for age, sex, education, occupational class, smoking habits, body mass index, and chronic disease (diabetes, hypertension, neck pain, low back pain, chronic depression and anxiety) was used to assess associations.

RESULTS

The average SA among the participants was 6.9 days (SD=33.3) per year, whereas the prevalence of any SA episode was 22.0%. The prevalence of workers performing high or very high LTPA was 31.0%. In final sex and age-stratified fully adjusted models, the association between LTPA and SA remained significant for women aged 44 to 51 (β=-0.07, 95% CI: -0.42 to -0.03) for SA.

CONCLUSIONS

The results suggest that higher LTPA is associated with lower SA in a particular category of workers, that might benefit from physical activity strategies.

Daily physical activity patterns among aging workers: the Finnish Retirement and Aging Study (FIREA)

OBJECTIVES

Physical activity is associated with the aging workers' ability to work and predicts working beyond retirement age. To better understand physical activity behaviour in this growing population group, we aimed at characterising 24-hour physical activity patterns among aging workers, and to describe the association between occupational category and total, occupational and leisure-time physical activities.

METHODS

We included 878 workers (mean age 62.4 years, SD 1.1, 85% women) from the Finnish Retirement and Aging Study, who wore an accelerometer on their non-dominant wrist for 1 week. We plotted mean hourly activity counts per minute (CPM) for working days and days off. We also compared mean daily CPM between genders and occupations between working days and days off, and work and leisure time by using repeated measures analysis of variance.

RESULTS

Activity patterns were different between genders, occupations and types of the day. Women (2580, 95% CI 2540 to 2620) had higher daily mean CPM than men (2110, 95% CI 2020 to 2000). Women in manual occupations were more active than women in non-manual occupations during working days. The differences among men were in the same direction but less pronounced than among women. We found no differences in activity levels between occupations during days off and leisure time on working days.

CONCLUSIONS

In aging workers, physical activity differs by gender and occupation during working time, but not during leisure time. As low physical activity is associated with increased risk of early exit from employment, physical activity should be promoted at workplaces, especially among men and people in non-manual occupations.