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

Associations of occupational physical activity and active transport with depressive symptoms in a middle-income country

OBJECTIVE

This study investigated the associations of occupational physical activity and active transport with depressive symptoms, stratified by income range, among Brazilian working adults.

STUDY DESIGN

This cross-sectional study drew on data from the 2019 Brazilian National Health Survey.

METHODS

We used the Patient Health Questionnaire (PHQ-9) to assess depressive symptoms in working adults aged 18-65 years, with physical activities (occupational physical activity and active transport) self-reported through a specially developed questionnaire. Crude and adjusted logistic regression models were fitted.

RESULTS

Individuals at the highest level of occupational physical activity (odds ratio [OR] 1.35; 95% confidence interval [95% CI] 1.19-1.53) and at the moderate level of active transport to work (OR 1.66; 95% CI 1.24-2.22) returned increased odds of depressive symptoms as compared with those who were inactive in these domains. Stratified by income group, light active transport to work (OR 0.57; 95% CI 0.34-0.95) in the lower income group (Range 1) was associated with lower odds of depressive symptoms. On the other hand, individuals at the highest level of active transport to work returned higher odds of depressive symptoms in the low- and intermediate-income groups, Ranges 3 and 4 (OR 1.92; 95% CI 1.22-3.00 and OR 2.91; 95% CI 1.71-4.95, respectively).

CONCLUSION

Our results suggest that occupational physical activity and active transport may be a risk factor for depressive symptoms. They also point to differences in this relationship by income range. Further studies are needed to pursue the analysis of how specific domains of physical activity contribute to depressive symptoms.

The Impact of Removing the 10-Minute Bout Requirement and of Different Survey Administration Methods on National Physical Activity Estimates in Austria

BACKGROUND

Monitoring survey methods, as well as movement recommendations, evolves over time. These changes can make trend observations over time difficult. The aim of this study was to examine the differences between 2 computer-assisted survey administration methods and the effect of the omission of the 10-minute minimum bout requirement in physical activity (PA) questions on PA outcomes.

METHODS

We used data from the second Austrian PA Surveillance System for 2998 adults (18-64 y), applying computer-assisted personal interviewing and computer-assisted web interviewing. Within the computer-assisted web interviewing sample only, we added PA questions without the 10-minute requirement. Quantile and logistic regressions were applied.

RESULTS

Between computer-assisted web interviewing and computer-assisted personal interviewing, within the computer-assisted personal interviewing sample, we found lower PA estimates in the leisure domain and work and household domain, but not in the travel domain, and no significant difference in the proportion of people meeting the PA recommendations. In all 3 PA domains, the median minutes did not differ when assessed with or without the 10-minute requirement. However, the percentage participation in the travel domain and work and household domain performing >0 minutes per week PA was higher when there was no 10-minute requirement. The proportion of people meeting the Austrian aerobic recommendation for adults when computed with or without the 10-minute requirement did not differ.

CONCLUSION

Our findings suggest that the omission of the 10-minute requirement does not seem to result in marked differences in PA estimates or the proportion of adults meeting the recommendations.

Work, travel, or leisure: comparing domain-specific physical activity patterns based on rural-urban location in Canada

BACKGROUND

Physical activity occurs across various domains including leisure/recreation, for transportation, or for work or household reasons. Rural and urban active living environments are characterized by different opportunities for physical activity within each domain which may translate into different patterns of behavior. The aim of this study was to compare rural-urban differences in physical activity across different domains, and explore interactions between sociodemographic factors, physical activity domains, and rurality.

METHODS

We used self-reported data collected across three physical activity domains (active transportation, recreation, occupational/household) and relevant sociodemographic variables from the Canadian Community Health Survey. Adjusting for sociodemographic factors, we did two separate cross-sectional analyses: 1) binary logistic regression to determine the odds of reporting any activity in each domain, and 2) ordinary least squares regression using the sub-samples reporting > 0 min per week of activity to compare how much activity was reported in each domain.

RESULTS

Our final survey weighted sample of Canadian adults (mean age 47.4 years) was n = 25,669,018 (unweighted n = 47,266). Rural residents were less likely to report any active transportation (OR = 0.59, 95% CI [0.51, 0.67], p < .0001). For recreational physical activity, rural males had lower odds (OR = 0.75, 95% CI [0.67, 0.83], p < .0001) and rural females had higher odds (OR = 1.19, 95% CI [1.08, 1.30], p = .0002) of reporting any participation compared to urban residents. Rural males (OR = 1.90, 95% CI [1.74, 2.07], p < .0001) and females (OR = 1.33, 95% CI [1.21, 1.46], p < .0001) had higher odds of reporting any occupational or household physical activity.

CONCLUSIONS

Urban residents tend to participate in more active transportation, while rural residents participate in more occupational or household physical activity. Location-based differences in physical activity are best understood by examining multiple domains and must include appropriate sociodemographic interactions, such as income and sex/gender.

Cancer risk in information technology workers: a UK Biobank study

BACKGROUND

The information technology (IT) workforce has been growing more rapidly than others, with occupational health (OH) risks of sedentary behaviour, physical inactivity and poor diet, yet studies of their non-communicable disease risk, notably cancer, are lacking.

AIMS

To investigate cancer risk in IT workers compared to others in employment and the nine major Standard Occupational Classification (SOC) groups.

METHODS

We evaluated incident diagnosed cancers in the UK Biobank cohort through national cancer registry linkage. Cox proportional hazard regression models, with 15-year follow-up, were used to compare incident cancer risk among IT workers with all other employed participants and with the nine major SOC groups.

RESULTS

Overall, 10 517 (4%) employed participants were IT workers. Adjusting for confounders, IT workers had a slightly lower cancer incidence compared to all other employed participants (Model 2: hazard ratio = 0.91, 95% confidence interval [CI] 0.83-1.01). Compared to the nine major SOC groups, they had a similar (Major Groups 2, 5 and 8) or lower (Major Groups 1, 3, 4, 6, 7 and 9) cancer incidence.

CONCLUSIONS

Despite their occupational risks of sedentary behaviour, poor diet and physical inactivity, IT workers do not have an increased cancer incidence compared to all other employed participants and the nine major SOC groups. This study paves the way for large, longitudinal health outcome studies of this under-researched and rapidly growing occupational group.

The predictors of health-enhancing physical activity among working women in Singapore two years into COVID-19: a cross-sectional study

Physical activity (PA) levels may have changed since the COVID-19 pandemic. However, these changes are not well understood. The study aimed to describe the PA level and examine the predictive factors of a health-enhancing PA level among working women in Singapore two years into the COVID-19 pandemic. We undertook a cross-sectional descriptive correlational study. Three hundred participants were recruited and completed the online questionnaire between October and November 2021. In the PA analysis of 217 participants, only 32.7% of the participants achieved a health-enhancing PA level, while 44.7% of the total sample sat for 7 h or more daily. In the univariate analysis, occupation, nationality, monthly income, and average daily sitting hours were significantly associated with a high PA level. The current mode of work, living arrangement, and health-promoting lifestyle profile II_physical activity score remained significant in both univariate and multivariate analyses. Participants who worked from home and stayed with their families were less likely to achieve a health-enhancing PA level than those who had a regular workplace and did not stay with their families. Working women with a health-promoting physically active lifestyle were likelier to achieve a health-enhancing PA level. The long daily sitting time and suboptimal health-enhancing PA participation underscore the need for health promotion initiatives for working women.

Association between chronic disease multimorbidity and leisure-time physical activity: Evidence from the China Multiethnic Cohort study

Objective

To reveal the associations between multimorbidity and leisure-time physical activity (LTPA) by ethnicities in China.

Materials and methods

Self-reported information on a range of occupational, household, transport, and LTPA was collected by interviewer-administered questionnaire. A total of 17 chronic diseases were assessed based on self-reported lifetime diagnoses or medical examinations. Multivariable logistic regression models were used to assess the associations between multimorbidity and the risks of low LTPA.

Results

The mean age of all participants was 51.2 years old. Of all, 61.4% were women and 57.9% were from the Han population. A significantly negative association (OR = 0.92, 95% CI = 0.89–0.95) was found between multimorbidity and low LTPA, with a stronger association among minority populations (OR = 0.86, 95% CI = 0.82–0.91) than among the Han population (OR = 0.96, 95% CI = 0.92–1.01). For both the minority population and the Han population, digestive system multimorbidity and digestive-metabolic system multimorbidity had a significantly negative association with low LTPA. For the Han population, the association of intersystem multimorbidity for the circulatory-respiratory system (OR = 1.17, 95% CI = 1.04–1.31) with low LTPA was stronger than that of intrasystem multimorbidity for the circulatory (OR = 1.12, 95% CI = 1.01–1.25) and respiratory systems (OR = 1.14, 95% CI = 1.04–1.25).

Conclusion

There are significant associations between multimorbidity and low LTPA based on this large multiethnic population. Our findings suggest that LTPA-tailored interventions should be designed for specific ethnic groups according to different types of multimorbidity.

Lifestyle Parameters in Patients with Diabetes Mellitus and in the General Adult Population-Trends over Five Years: Results of the Austrian National Health Interview Series

Background: Not smoking, performing >150 min of aerobic physical activity (PA) and muscle strengthening exercises/week, and consuming >5 portions of fruit and vegetables/day are lifestyle recommendations for both the general population and people with diabetes mellitus (DM). Methods: A total of 15,771 and 15,461 persons from the Austrian Health Interview Surveys 2014 and 2019, respectively, including 4.9% and 6.0% of people with DM, were analysed in terms of their smoking, PA, and nutritional behaviours. Logistic regression models were performed for the lifestyle factors, adjusted for socio-demographic and health-related factors. Adjusted interactions between the survey year and DM on the lifestyle factors were computed. Results: The proportions of smokers were 23.9% and 20.2%, of people complying with the PA recommendations were 24.9% and 21.4%, and with fruit and vegetables recommendations were 7.1% and 5.5%, respectively, with significantly lower proportions of smokers and persons complying with the PA recommendations among people with DM. The fully adjusted odds ratios (95% confidence interval) for people with DM were 1.09 (0.94–1.26), 1.44 (1.23–1.69), and 0.90 (0.71–1.13) for smoking, not complying with PA recommendations, and not complying with fruit and vegetables recommendations, respectively. The proportion of people complying with PA recommendations decreased to a greater extent (p < 0.001) in people with DM (16.5% to 8.3%) compared to people without DM (25.3% to 22.3%). Conclusion: Diabetogenic lifestyle behaviours increased in the general Austrian population in recent years, which was especially true for people with DM regarding PA.