Body mass index: accounting for full time sedentary occupation and 24-hr self-reported time use

Physical Activity and Fitness in White- and Blue-Collar Retired Men

The average life expectancy has increased and despite a distinct feminization of aging, the number of older males continues to grow. Physical activity has a positive effect on health and helps to slow down the negative consequences of aging. The aim of the study was to evaluate possible relationships between physical fitness, physical activity and type of work during occupational activity among retired men (aged ≥65 years), no longer professionally active. The study included 104 men (aged from 65 to 90 years), further stratified into blue- and white-collar groups (66 and 38 subjects, respectively). The International Physical Activity Questionnaire (IPAQ) was used to assess their physical activity levels. Physical performance was assessed using the Short Physical Performance Battery test (SPPB) and handgrip strength (HGS) measurement. Geriatric Depression Scale (GDS) was used to identify the risk for depression. Mean physical activity in the study population was moderate in almost 70%, high in 19% and low in 11% of the subjects. Men with high physical activity levels had better SPPB and GDS scores (p = .01 and p = .001, respectively). In the blue-collar group, the IPAQ scores were lower than in the white-collar group, although the differences were statistically insignificant. The SPPB scores and mean HGS for the dominant hand were similar in both groups. Occupational physical activity should not substitute other forms of physical activity. Regardless of the type of work performed before retirement, the men obtained similar results in terms of their physical activity.

Standardised criteria for classifying the International Classification of Activities for Time-use Statistics (ICATUS) activity groups into sleep, sedentary behaviour, and physical activity

BACKGROUND

Globally, the International Classification of Activities for Time-Use Statistics (ICATUS) is one of the most widely used time-use classifications to identify time spent in various activities. Comprehensive 24-h activities that can be extracted from ICATUS provide possible implications for the use of time-use data in relation to activity-health associations; however, these activities are not classified in a way that makes such analysis feasible. This study, therefore, aimed to develop criteria for classifying ICATUS activities into sleep, sedentary behaviour (SB), light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA), based on expert assessment.

METHOD

We classified activities from the Trial ICATUS 2005 and final ICATUS 2016. One author assigned METs and codes for wakefulness status and posture, to all subclass activities in the Trial ICATUS 2005. Once coded, one author matched the most detailed level of activities from the ICATUS 2016 with the corresponding activities in the Trial ICATUS 2005, where applicable. The assessment and harmonisation of each ICATUS activity were reviewed independently and anonymously by four experts, as part of a Delphi process. Given a large number of ICATUS activities, four separate Delphi panels were formed for this purpose. A series of Delphi survey rounds were repeated until a consensus among all experts was reached.

RESULTS

Consensus about harmonisation and classification of ICATUS activities was reached by the third round of the Delphi survey in all four panels. A total of 542 activities were classified into sleep, SB, LPA, and MVPA categories. Of these, 390 activities were from the Trial ICATUS 2005 and 152 activities were from the final ICATUS 2016. The majority of ICATUS 2016 activities were harmonised into the ICATUS activity groups (n = 143).

CONCLUSIONS

Based on expert consensus, we developed a classification system that enables ICATUS-based time-use data to be classified into sleep, SB, LPA, and MVPA categories. Adoption and consistent use of this classification system will facilitate standardisation of time-use data processing for the purpose of sleep, SB and physical activity research, and improve between-study comparability. Future studies should test the applicability of the classification system by applying it to empirical data.

Adolescent and Young Adult Recreational, Occupational, and Transportation Activity: Activity Recommendation and Weight Status Relationships

PURPOSE

Physical activity can occur in many settings, or domains, including recreation, occupation, and transportation. We described patterns of adolescent and young adult (YA) activity in each domain, and the extent that accounting for different domains impacts activity recommendation adherence. We also examined activity domain associations with weight status.

METHODS

We examined physical activity among 11,157 adolescents and YAs in recreational, occupational, and transportation domains in the 2007-2016 National Health and Nutrition Examination Survey. We calculated proportions meeting weekly activity recommendations (adolescents: 420 minutes; YAs: 150 minutes) by domain. We compared adjusted odds of performing any activity in each domain by weight status. All estimates are weighted and stratified by age (adolescents: 12-19 years; YAs: 20-29 years) and sex.

RESULTS

Most adolescents (90.9%) and YAs (86.7%) reported activity in at least one domain. Recreational activity accounted for an average of 60.2% (adolescents) and 42.5% (YAs) of an individual's total activity. Approximately half of YAs (50.2%) reported any occupational activity, which accounted for 44.6% (males) and 37.4% (females) of total activity minutes. Transportation accounted for 18.1% (adolescents) and 16.2% (YAs) of total activity. Activity recommendation adherence estimates increased when adding domains: recreation alone (34.9% adolescents, 45.6% YAs); recreation and occupation (47.2% adolescents, 68.7% YAs); and recreation, occupation, and transportation (53.5% adolescents, 74.7% YAs). Weight status was generally not associated with activity domains.

CONCLUSIONS

Adolescents and YAs accumulate substantial occupational and some transportation-related physical activity, resulting in more youth meeting activity recommendations when accounting for these activity domains than recreation alone.

Leisure sedentary time is differentially associated with hypertension, diabetes mellitus, and hyperlipidemia depending on occupation

Background

Sedentary behavior is considered an independent cause of cardio-metabolic diseases, regardless of physical activity level and obesity. Few studies have reported the association between leisure sedentary time and cardio-vascular diseases in terms of occupation.

Methods

We performed a cross-sectional study using data from the Korean Community Health Survey (KCHS) for 240,086 participants assessed in 2011 and 2013. Occupation was categorized into four groups: farmer or fisherman, laborer, and soldier (Group I); service worker, salesperson, technician, mechanic, production worker, and engineer (Group II); manager, expert, specialist, and clerk (Group III); and unemployed (Group IV). Leisure sedentary time was divided into five groups: 0 h, 1 h, 2 h, 3 h, and 4+ h. The association between leisure sedentary time on weekdays and hypertension/diabetes mellitus/hyperlipidemia for different occupations was analyzed using simple and multiple logistic regression analyses with complex sampling.

Results

In Groups I, II and III, no length of sedentary time was associated with hypertension, and only 3 h or 4+ h of sedentary time was associated with diabetes mellitus and hyperlipidemia. Group IV showed a significant association with hypertension and diabetes mellitus for the 2 h, 3 h, and 4+ h sedentary times.

Conclusions

The unemployed are more susceptible than other occupation groups to cardio-metabolic diseases when leisure time is sedentary.

Electronic supplementary material

The online version of this article (doi:10.1186/s12889-017-4192-0) contains supplementary material, which is available to authorized users.

Relationships between time use and obesity in a representative sample of Americans

OBJECTIVE

To provide a nationally representative analysis of time use in America for insight into behaviors associated with obesity.

METHODS

This study utilized 28,503 observations of individuals aged 22 to 70 from the American Time Use Survey, a continuous cross-sectional survey on time use in America. Linear and logistic regressions were performed to analyze sociodemographic characteristics, determine activity participation levels and time spent in activities, understand nonlinear associations between activity time and BMI, and appreciate differences in activity timing between BMI categories.

RESULTS

Short and long sleep and work were associated with increased BMI. On weekdays, individuals with obesity were more likely to be working at night and sleeping during the day. They were less likely to participate in sports/exercise/recreation, but those that participated did so for amounts of time not different than normal-BMI individuals. Those with obesity were more likely to watch television almost all hours of the day. Further differences are detailed for health-related, sedentary, and household activities.

CONCLUSIONS

Both short and long sleep, as well as the timing of sleep and work activity, are associated with obesity. Motivation to exercise nonzero amounts may be an appropriate target for intervention. Television is chief among sedentary activities in their association with obesity.