scholarly journals Using multilevel regression and poststratification to estimate physical activity levels from health surveys

2021 ◽  
Author(s):  
Marina Christofoletti ◽  
Tânia R. B. Benedetti ◽  
Felipe Goedert Mendes ◽  
Humberto M. Carvalho
Keyword(s):  
Physical Activity ◽  
Health Surveys ◽  
Large Scale ◽  
Leisure Time Physical Activity ◽  
Health Indicators ◽  
Activity Levels ◽  
Multilevel Regression ◽  
Cross Sectional ◽  
Single Level ◽  
Uncertainty Estimates

Background: Large-scale health surveys often consider sociodemographic characteristics and several health indicators influencing physical activity that often vary across units (regions or states). Data in a survey for some small units are often not representative of the larger population. This study developed a relatively simple multilevel regression and poststratification (MRP) model to estimate the proportion of leisure-time physical activity across Brazilian state capitals, based on the Brazilian cross-sectional national survey VIGITEL (2018). Methods: We used various approaches to evaluate whether the MRP approach outperforms single-level aggregated estimates, with various subsample proportions tested. Results: The mean absolute errors were consistently smaller for the MRP estimates than single-level regression estimates, particularly with smaller sample sizes. MRP consistently had predictions closer to the estimation target than single-level aggregated estimations. MRP presented substantially smaller uncertainty estimates compared to aggregated estimates. Conclusions: Our results confirm that MRP is a promising strategy to derive disaggregated data for health-related outcomes and, in particular, physical activity indicators from aggregated-level surveys. Overall, the MRP is superior to single-level aggregated estimates and disaggregation, yielding smaller errors and more accurate estimates. MRP significantly expands the scope of issues for which researchers can better address participation bias and interpret interactions to estimate descriptive population quantities. The observations present in this study highlight the need for further research, potentially incorporating more information in the models to better interpret interactions and types of activities across target populations.

scholarly journals Using Multilevel Regression and Poststratification to Estimate Physical Activity Levels from Health Surveys

2021 ◽  
Vol 18 (14) ◽  
pp. 7477
Author(s):  
Marina Christofoletti ◽  
Tânia R. B. Benedetti ◽  
Felipe G. Mendes ◽  
Humberto M. Carvalho
Keyword(s):  
Physical Activity ◽  
Health Surveys ◽  
Large Scale ◽  
Leisure Time Physical Activity ◽  
Health Indicators ◽  
Sample Sizes ◽  
Multilevel Regression ◽  
Cross Sectional ◽  
Single Level ◽  
Uncertainty Estimates

Background: Large-scale health surveys often consider sociodemographic characteristics and several health indicators influencing physical activity that often vary across subpopulations. Data in a survey for some small subpopulations are often not representative of the larger population. Objective: We developed a multilevel regression and poststratification (MRP) model to estimate leisure-time physical activity across Brazilian state capitals and evaluated whether the MRP outperforms single-level regression estimates based on the Brazilian cross-sectional national survey VIGITEL (2018). Methods: We used various approaches to compare the MRP and single-level model (complete-pooling) estimates, including cross-validation with various subsample proportions tested. Results: MRP consistently had predictions closer to the estimation target than single-level regression estimations. The mean absolute errors were smaller for the MRP estimates than single-level regression estimates with smaller sample sizes. MRP presented substantially smaller uncertainty estimates compared to single-level regression estimates. Overall, the MRP was superior to single-level regression estimates, particularly with smaller sample sizes, yielding smaller errors and more accurate estimates. Conclusion: The MRP is a promising strategy to predict subpopulations’ physical activity indicators from large surveys. The observations present in this study highlight the need for further research, which could, potentially, incorporate more information in the models to better interpret interactions and types of activities across target populations.

scholarly journals Leisure-Time Physical Activity Participation Trends 2014–2018: A Cross-Sectional Study in Poland

2019 ◽  
Vol 17 (1) ◽  
pp. 208 ◽  
Author(s):  
Elżbieta Biernat ◽  
Monika Piątkowska
Keyword(s):  
Physical Activity ◽  
Large Scale ◽  
Leisure Time ◽  
Leisure Time Physical Activity ◽  
Occupational Status ◽  
Age Groups ◽  
The Elderly ◽  
Sociodemographic Factors ◽  
World Health ◽  
Cross Sectional

Objective, the aim is an analysis of sociodemographic factors that had an essential relation with undertaking leisure-time physical activity—LTPA (with particular emphasis on World Health Organization (WHO) health recommendations) by adult Poles from a time-trend perspective. Methods, the paper is based on data retrieved from five large-scale surveys carried out on the representative samples of Poles aged 15–69 in 2014–2018 (n = 7347). In each wave, the Polish long version of the International Physical Activity Questionnaire was used. Results, the participation of Poles in LTPA constantly increases (p < 0.001) and the percentage of people meeting the dose of PA required for health recommendations is growing (on average, met by 43.9% of Polish men and 43.5% of women), which indicates a trend of behaviour of citizens of this country. The probability of realisation of WHO norms was determined by sex, age, place of residence and occupational status. Conclusion: it seems reasonable to develop Polish recommendations and guidelines for specific groups, including females and males, those who live in the villages and in the towns, different age groups: children/adolescents, adults (aged 50 to 59—most vulnerable to physical inactivity), the elderly, and various professional groups (especially farmers and physical workers).

How Do Different Occupational Factors Influence Total, Occupational, and Leisure-Time Physical Activity?

2015 ◽  
Vol 12 (2) ◽  
pp. 200-207 ◽  
Author(s):  
Corneel Vandelanotte ◽  
Camille Short ◽  
Matthew Rockloff ◽  
Lee Di Millia ◽  
Kevin Ronan ◽  
...  
Keyword(s):  
Physical Activity ◽  
Leisure Time ◽  
Leisure Time Physical Activity ◽  
Total Physical Activity ◽  
Activity Levels ◽  
Full Time ◽  
Cross Sectional ◽  
Time Activity ◽  
Physical Activity Levels ◽  
The Impact

Background:A better understanding of how occupational indicators influence physical activity levels will aid the design of workplace interventions.Methods:Cross-sectional data were collected from 1194 participants through a telephone interview in Queensland, Australia. The IPAQ-long was used to measure physical activity. Multiple logistic regression was applied to examine associations.Results:Of participants, 77.9% were employed full-time, 32.3% had professional jobs, 35.7% were engaged in shift work, 39.5% had physically-demanding jobs, and 66.1% had high physical activity levels. Participants with a physicallydemanding job were less likely to have low total (OR = 0.25, 95% CI = 0.17 to 0.38) and occupational (OR = 0.17, 95% CI = 0.12 to 0.25) physical activity. Technical and trade workers were less likely to report low total physical activity (OR = 0.44, 95% CI = 0.20 to 0.97) compared with white-collar workers. Part-time (OR = 1.74, 95% CI = 1.15 to 2.64) and shift workers (OR = 1.86, 95% CI = 1.21 to 2.88) were more likely to report low leisure-time activity.Conclusions:Overall, the impact of different occupational indicators on physical activity was not strong. As expected, the greatest proportion of total physical activity was derived from occupational physical activity. No evidence was found for compensation effects whereby physically-demanding occupations lead to less leisure-time physical activity or vice versa. This study demonstrates that workplaces are important settings to intervene, and that there is scope to increase leisure-time physical activity irrespective of occupational background.

The Relationship between Convenience of Destinations and Walking Levels in Older Women

2003 ◽  
Vol 18 (1) ◽  
pp. 74-82 ◽  
Author(s):  
Wendy C. King ◽  
Jennifer S. Brach ◽  
Steven Belle ◽  
Richard Killingsworth ◽  
Mark Fenton ◽  
...  
Keyword(s):  
Physical Activity ◽  
Older Women ◽  
Leisure Time Physical Activity ◽  
Neighborhood Environment ◽  
Walking Distance ◽  
Positive Trend ◽  
Activity Levels ◽  
Cross Sectional ◽  
Neighborhood Walkability ◽  
The Relationship

Purpose. To examine the relationship between physical activity and (1) convenience of destinations, measured by whether destinations (such as a park, trail, businesses, and services) are within walking distance of the home, and (2) participants' perception of the quality of their neighborhood surroundings for walking, captured with a global neighborhood “walkability” rating. Design. Cross-sectional analysis of data obtained in 1999. Setting. Community in southwest Pennsylvania. Subjects. Older Caucasian women (n = 149, mean age = 74.2 years). Response rate = 79%. Measures. Walking levels, leisure-time physical activity, and features of the neighborhood environment were measured with interviewer-administered questionnaires. Physical activity was also measured objectively with a pedometer. Results. Living within walking distance (defined as within a 20-minute walk of home) of a park; biking or walking trail; or department, discount, or hardware store was related to higher pedometer readings ( p < .01). In addition, there was a positive trend between the sum of destinations within walking distance of home and activity levels measured by pedometer and questionnaire ( p < .01). There was also a positive trend between participants' neighborhood “walkability” rating and activity levels measured by pedometer and questionnaire ( p < .01). Conclusion. These findings suggest that the ability to make utilitarian walking trips from home and the perception of having favorable neighborhood surroundings for walking are associated with increased physical activity levels in older women.

Leisure-Time Physical Activity: Association With Activity Levels in Other Domains

2010 ◽  
Vol 7 (4) ◽  
pp. 460-464 ◽  
Author(s):  
Airton J. Rombaldi ◽  
Ana M.B. Menezes ◽  
Mario Renato Azevedo ◽  
Pedro C. Hallal
Keyword(s):  
Physical Activity ◽  
Leisure Time ◽  
Leisure Time Physical Activity ◽  
Population Based ◽  
Cross Sectional Study ◽  
Moderate Intensity ◽  
Activity Levels ◽  
Cross Sectional ◽  
Moderate Intensity Physical Activity ◽  
Intensity Physical Activity

Objectives:To explore whether participation in leisure-time physical activity (LTPA) is associated with participation in occupational, housework, and transport-related physical activity.Methods:Population-based cross-sectional study covering a multistage sample of 972 subjects age 20 to 69 years. Physical activity was measured using the long version of the International Physical Activity Questionnaire. A LTPA score was calculated as follows: min/wk of walking + min/wk of moderate-intensity physical activity + (min/wk of vigorous-intensity physical activity × 2). Similar scores were generated for each domain. For categorical analyses, the scores were divided into 3 categories: 0 min/wk, 10−149 min/wk, and ≥150 min/wk.Results:The proportion of subjects practicing less than 150 min/wk of physical activity in each domain was: leisure-time (69.8%), occupational (58.3%), housework (35.0%), transportation (51.9%). Subjects with a transport-related physical activity score equal to or above 150 min/wk were 40% less likely to be sedentary in leisure-time in comparison with those who did not practice transport-related physical activity. Housework and occupational physical activity were not related to participation in LTPA.Conclusions:Future physical activity campaigns should focus on other domains instead of LTPA alone, particularly supporting transport-related physical activity as a strategy of health promotion.

scholarly journals Association of Social Networks and Physical Activity in South Asians: The Mediators of Atherosclerosis in South Asians Living in America Cohort Study

2020 ◽  
Vol 17 (2) ◽  
pp. 149-155 ◽  
Author(s):  
Mitali S. Thanawala ◽  
Juned Siddique ◽  
John A. Schneider ◽  
Alka M. Kanaya ◽  
Andrew J. Cooper ◽  
...  
Keyword(s):  
Physical Activity ◽  
United States ◽  
Social Networks ◽  
Confidence Interval ◽  
Leisure Time Physical Activity ◽  
South Asians ◽  
Ethnic Disparities ◽  
The United States ◽  
Activity Levels ◽  
Cross Sectional

Background: Eliminating racial/ethnic disparities in physical activity remains a challenge in the United States. South Asian immigrants in the United States have particularly low physical activity levels, and evidence suggests that social context may be important. This study examined associations between personal social networks and moderate to vigorous leisure-time physical activity (MVPA) among South Asians in the United States. Methods: We used cross-sectional data (2014–2017) from 689 South Asians (aged 43–85 y) who participated in the Mediators of Atherosclerosis in South Asians Living in America study. Self-reported physical activity and egocentric network data were collected from participants about their network members. Regression models were used to determine associations between social network characteristics and participants’ MVPA. Results: Participants were on average 59 years old (SD = 9) and reported 1335 metabolic equivalent minutes per week of MVPA (interquartile range = 735, 2212). Having network members who exercised or who were exercise partners associated with increased MVPA in men (β coefficient = 241 MET min/wk [95% confidence interval, 63 to 419] and β = 520 MET min/wk [95% confidence interval, 322 to 718], respectively). For women, the association was only significant if the exercise partner was a spouse. Conclusion: Physical activity interventions utilizing network members as exercise partners may have potential in South Asians but must consider gender differences.

scholarly journals Exploring the Association Between Electronic Wearable Device Use and Levels of Physical Activity Among Individuals With Depression and Anxiety: A Population Level Study

2021 ◽  
Vol 3 ◽  
Author(s):  
Henry Onyeaka ◽  
Joe Firth ◽  
Valentine Enemuo ◽  
Chioma Muoghalu ◽  
John Naslund ◽  
...  
Keyword(s):  
Physical Activity ◽  
United States ◽  
Large Scale ◽  
Population Level ◽  
The United States ◽  
Individual Characteristics ◽  
Activity Levels ◽  
Depression And Anxiety ◽  
Related Factors ◽  
Cross Sectional

Aim: The present study aimed to investigate the cross-sectional association between self-reported use of electronic wearable devices (EWDs) and the levels of physical activity among a representative sample of adults with depression and anxiety in the United States.Methods: For this cross-sectional study, data were pooled from the Health Information National Trends Survey 2019. A sample of 1,139 adults with self-reported depression and anxiety (60.9% women; mean age of 52.5 years) was analyzed. The levels of physical activity and prevalence of EWD utilization were self-reported. The chi-square tests were used to compare individual characteristics through the use of EWDs. Multivariable logistic regression was employed to investigate the association between EWDs and physical activity levels while adjusting for sociodemographic and health-related factors.Results: From the 1,139 adults with self-reported depression and anxiety, 261 (weighted percentage 28.1%) endorsed using EWD in the last year. After adjusting for covariates, the use of EWDs was only significantly associated with a higher odds of reporting intention to lose weight (OR 2.12; 95% CI 1.04, 4.35; p = 0.04). We found no association between the use of EWDs and meeting the national weekly recommendation for physical activity or resistance/strength exercise training.Conclusion: About three in 10 adults suffering from depression and anxiety in the United States reported using EWDs in the last year. The current study findings indicate that among people living with mental illness, EWD use is associated with higher odds of weight loss intent suggesting that EWDs may serve as an opening for the clinical interactions around physical health through identifying patients primed for behavior change. Further large-scale studies using randomized trial designs are needed to examine the causal relationships between EWDs and the physical activity of people with mental health conditions.

Physical Activity Levels According to Physical and Social Environmental Factors in a Sample of Adults Living in South Brazil

2010 ◽  
Vol 7 (s2) ◽  
pp. S204-S212 ◽  
Author(s):  
Tales C. Amorim ◽  
Mario R. Azevedo ◽  
Pedro C. Hallal
Keyword(s):  
Physical Activity ◽  
Leisure Time ◽  
Leisure Time Physical Activity ◽  
Population Level ◽  
Population Based ◽  
Cross Sectional Study ◽  
Neighborhood Environment ◽  
Activity Levels ◽  
Cross Sectional ◽  
Social Environmental

Objective:To evaluate the association between the physical and social environment and physical activity (leisure-time and transport-related) in a population-based sample of adults.Methods:Cross-sectional study including 972 adults (20−69 years) living in the urban area of Pelotas, Brazil. Physical activity was measured using the long International Physical Activity Questionnaire. Environmental variables were assessed using a modified version of the Neighborhood Environment Walkability Scale.Results:69.8% (95% CI = 66.9−72.7) and 51.9% (95% CI = 48.8−55.1) of the subjects did not reach 150 min/wk on leisure-time and transport-related physical activity, respectively. Subjects living near green areas were more likely to be active in leisure-time, as well as those who reported to live in safe neighborhoods. Transport-related physical activity was higher among individuals living in areas with garbage accumulation, and was lower among those living in neighborhoods which are difficult to walk or cycle due to traffic. Social support was strongly associated with leisure-time physical activity.Conclusions:Safety investments, which are urgently required in Brazil, are likely to have a desirable side effect at increasing physical activity at the population level. Building enjoyable and safe public spaces for physical activity practice must be prioritized.

scholarly journals Educational differentials in key domains of physical activity by ethnicity, age and sex: a cross-sectional study of over 40 000 participants in the UK household longitudinal study (2013–2015)

BMJ Open ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. e033318
Author(s):  
Meg E Fluharty ◽  
Snehal M Pinto Pereira ◽  
Michaela Benzeval ◽  
Mark Hamer ◽  
Barbara Jefferis ◽  
...  
Keyword(s):  
Physical Activity ◽  
Longitudinal Study ◽  
Leisure Time Physical Activity ◽  
Cross Sectional Study ◽  
Occupational Activity ◽  
Activity Levels ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
The Difference ◽  
The Uk

ObjectivesTo assess whether educational differentials in three key physical activity (PA) domains vary by age, sex and ethnicity.DesignNational cross-sectional survey.SettingUK.ParticipantsAltogether 40 270 participants, aged 20 years and over, from the UK Household Longitudinal Study with information on education, PA and demographics collected in 2013–2015.Outcome measuresParticipation in active travel (AT), occupational activity (OA) and leisure time physical activity (LTPA) at the time of assessment.ResultsLower educational attainment was associated with higher AT and OA, but lower weekly LTPA activity; these associations were modified by sex, ethnicity and age. Education-related differences in AT were larger for women—the difference in predicted probability of activity between the highest and the lowest education groups was −10% in women (95% CI: −11.9% to 7.9%) and −3% in men (−4.8% to –0.4%). Education-related differences in OA were larger among men −35% (-36.9% to –32.4%) than women −17% (-19.4% to –15.0%). Finally, education-related differences in moderate-to-vigorous LTPA varied by ethnicity; for example, differences were 17% (16.2% to 18.7%) for white individuals compared with 6% (0.6% to 11.6%) for black individuals.ConclusionsEducational differences in PA vary by domain and are modified by age, sex and ethnicity. A better understanding of physically inactive subgroups may aid development of interventions to both increase activity levels and reduce health inequalities.

scholarly journals Physical Activity Levels by Occupational Category in Non-Metropolitan Australian Adults

2010 ◽  
Vol 7 (6) ◽  
pp. 718-723 ◽  
Author(s):  
Mitch J. Duncan ◽  
Hannah M. Badland ◽  
William Kerry Mummery
Keyword(s):  
Physical Activity ◽  
Leisure Time Physical Activity ◽  
White Collar ◽  
Blue Collar ◽  
Activity Levels ◽  
Cross Sectional ◽  
Occupational Category ◽  
Occupational Sitting ◽  
Blue Collar Workers ◽  
Physical Activity Levels

Background:The aim of this study was to examine the relationship between occupational category and 3 health-related behaviors: participation in leisure-time physical activity, active transport (AT) and occupational sitting in a sample of employed Australian adults.Methods:A random, cross-sectional sample of 592 adults aged 18 to 71 years completed a telephone survey in October/November 2006. Reported occupations were categorized as professional (n = 332, 56.1%), white-collar (n = 181, 30.6%), and blue-collar (n = 79, 13.3%). Relationships between occupational category and AT, sufficient physical activity and occupational sitting were examined using logistic regression.Results:White-collar employees (OR = 0.36, 95% CI 0.14−0.95) were less likely to engage in AT and more likely to engage in occupational sitting (OR = 3.10, 95% CI 1.63−5.92) when compared with blue-collar workers. Professionals (OR = 3.04, 95% CI 1.94−4.76) were also more likely to engage in occupational sitting compared with blue-collar workers. No relationship was observed between occupational category and engagement in sufficient physical activity.Conclusions:No association between occupational category and sufficient physical activity levels was observed, although white-collar and professionals were likely to engage in high levels of occupational sitting. Innovative and sustainable strategies are required to reduce occupational sitting to improve health.

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