Occupational Physical Activity: Reliability and Comparison of Activity Levels

Background:In 2001, the Behavioral Risk Factor Surveillance System (BRFSS) included a new occupational physical activity (PA) question. This article evaluates the reliability of this survey question.Methods:Forty-six subjects were followed for 3 wk, answered 3 PA surveys by telephone, and completed daily PA logs for 1 wk. Kappa statistics determined the reliability of occupational activities (sitting/standing, walking, and heavy lifting). A descriptive analysis compared the time in specific occupational activities.Results:Eighty percent of the respondents reported “mostly sitting or standing” at work; and test–retest reliability was moderate (k = 0.40 to 0.45). The occupationally inactive sat/stood for 85% (mean hours = 5.6) of the workday, whereas the occupationally active sat/stood for 53% (mean hours = 3.9) of the workday.Conclusions:The BRFSS occupational activity question has moderate reliability, distinguishes between occupationally active and inactive persons, and can be used in surveillance systems to estimate adult occupational PA.

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Single Versus Multiple Item Questions on Occupational Physical Activity

Journal of Physical Activity and Health ◽

10.1123/jpah.3.1.102 ◽

2006 ◽

Vol 3 (1) ◽

pp. 102-111 ◽

Cited By ~ 10

Author(s):

Michelle M. Yore ◽

Heather R. Bowles ◽

Barbara E. Ainsworth ◽

Caroline A. Macera ◽

Harold W. Kohl

Keyword(s):

Physical Activity ◽

Behavioral Risk ◽

Occupational Physical Activity ◽

Activity Levels ◽

Behavioral Risk Factor Surveillance ◽

Risk Factor Surveillance ◽

Multiple Item ◽

Single Versus ◽

National Physical Activity ◽

Activity Questionnaire

Background:In 2002, the National Physical Activity and Weight Loss Survey asked two sets of questions on occupational physical activity—one question from the Behavioral Risk Factor Surveillance System (BRFSS) and eight detailed questions from the occupational physical activity questionnaire (OPAQ). This study compares the responses.Methods:On the basis of percentage of occupational physical activity reported on OPAQ, 5847 respondents were classified by three levels (sitting or standing, walking, and heavy labor). Kappa, MET-min per day, and median hours worked at the three levels were calculated to compare the two sets of questions.Results:Levels of occupational physical activity reported on the BRFSS question agreed with OPAQ (kappa = 0.56). Hours of heavy labor per day reported on OPAQ increased among the three activity levels on BRFSS.Conclusions:The BRFSS question and OPAQ classify respondents similarly by occupational physical activity. The BRFSS question is useful for overview and OPAQ, for more detailed analyses.

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Hubungan Aktivitas Fisik Berat dengan Back Pain pada Penduduk Usia Kerja di Jawa dan Bali

Kesmas National Public Health Journal ◽

10.21109/kesmas.v2i4.263 ◽

2008 ◽

Vol 2 (4) ◽

pp. 186

Author(s):

Achmad Zaki

Keyword(s):

Physical Activity ◽

Back Pain ◽

Secondary Data ◽

Educational Status ◽

National Health Survey ◽

Occupational Activity ◽

Occupational Physical Activity ◽

Rest Break ◽

Pain Symptoms ◽

Short Walk

Penelitian ini bertujuan mengetahui hubungan lama aktivitas fisik berat dengan Gejala Back pain pada penduduk usia kerja 18 – 55 tahun di wilayah Pulau Jawa dan Bali. Penelitian ini menggunakan data sekunder Survei Kesehatan Nasional Tahun 2001. Penelitian ini menggunakan desain potong-lintang dengan metode analisis regresi logistik ganda. Hasil penelitian mendapatkan ada hubungan antara aktivitas fisik berat dengan gejala back pain, setelah dikontrol oleh variabel-variabel confounding seperti lama aktivitas fisik duduk atau sedikit berjalan (terkait pekerjaan ataupun tidak), jenis kelamin, dan pendidikan. Responden dengan lama aktivitas fisik berat (bekerja 1-5 jam) memiliki risiko 2,03 kali untuk mengalami gejala back pain dibandingkan kelompok yang tidak melakukan aktifitas fisik berat (95% CI 1,34-3,08). Responden dengan lama aktivitas fisik berat (bekerja >5 jam) memiliki risiko 1,60 kali untuk mengalami gejala back pain dibandingkan kelompok yang tidak melakukan aktifitas fisik berat (95% CI 0,55 - 4,63). Disarankan untuk pemberlakuan regulasi waktu kerja menggunakan metode waktu rehat pendek (short rest break), dimana pekerja yang harus bekerja selama 5-6 jam terus menerus perlu diistirahatkan di pertengahan waktu tersebut selama sekitar 20 menit.Kata kunci: Aktivitas fisik, back painAbstractThe objective of this research is to investigate the relationship between high occupational physical activity with back pain symptoms among working age population (18—55 years olds) in Java and Bali islands. This research used secondary data from National Health Survey 2001. This research was using the crosssectional design and was analyzed by multiple logistic regression. The study result shows that there are a relationship between high occupational physical activity with back pain symptoms after controlled with confounding variables such as: duration of occupational sitting and short walk activity, duration of nonoccupational sitting and short walk, gender and educational status. Respondents with duration of heavy occupational activity of 1-5 hours have 2,03 higher risk to get back pain symptoms compared to those not doing it (95% CI 1,34-3,08). Respondents with duration of heavy occupational activity of >5 hours have 1,60 risk to get back pain symptoms compared to those not doing it (95% CI 0,55 - 4,63).Keywords : Physical activity, back pain

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Embedding Active Pedagogies within Pre-Service Teacher Education: Implementation Considerations and Recommendations

Children ◽

10.3390/children7110207 ◽

2020 ◽

Vol 7 (11) ◽

pp. 207

Author(s):

Natalie Lander ◽

Emiliano Mazzoli ◽

Samuel Cassar ◽

Naomi Symington ◽

Jo Salmon

Keyword(s):

Physical Activity ◽

Teacher Education ◽

Learning Experience ◽

Descriptive Analysis ◽

Activity Levels ◽

School Students ◽

Physically Active ◽

Five Dimensions ◽

Pre Service Teacher Education ◽

Pre Service Teacher

The physical activity levels of children in Australia are critically low and correlate with reduced academic achievement and poor health outcomes. Schools provide an ideal setting for physical activity interventions to help children move more. Instead of targeting in-service teachers, this study embedded an evidence-based active pedagogy program called Transform-Ed! into pre-service teacher education. Pre/post surveys and post-program interviews and focus group discussions were conducted with key stakeholders (n = 5), lecturers (n = 6), and pre-service teachers (n = 274) involved with the 12-week program. The design, implementation, and evaluation of the study were systematically guided by all five dimensions of Glasgow and colleagues’ RE-AIM (reach, effectiveness, adoption, implementation, and maintenance) framework. Linear mixed models, descriptive analysis and a framework approach were used to analyse the data. Significant improvements were observed in pre-service teachers’ willingness, confidence, and competence to implement physically active pedagogic strategies following the intervention. Pre-service teacher perceived effectiveness of such strategies on student outcomes also significantly increased and perceived barriers decreased. High adherence was consistently reported and the program was maintained after completion of the implementation trial by all lecturers. Four key themes spanning multiple dimensions and participant levels informed recommendations for program scalability: an “inter-systemic approach”, a “co-design” approach, “embedded in professional practice”, and “evidence of impact” on teacher practice. Anchored in real-world settings and tethered by implementation science, Transform-Ed! could have the potential to advance the teaching capability of teachers, and transform the learning experience and physical and academic outcomes of primary school students.

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Non-occupational physical activity levels of shift workers compared with non-shift workers

Occupational and Environmental Medicine ◽

10.1136/oemed-2016-103878 ◽

2016 ◽

Vol 74 (5) ◽

pp. 328-335 ◽

Cited By ~ 7

Author(s):

Bette Loef ◽

Gerben Hulsegge ◽

G C Wanda Wendel-Vos ◽

W M Monique Verschuren ◽

Roel C H Vermeulen ◽

...

Keyword(s):

Physical Activity ◽

Occupational Physical Activity ◽

Activity Levels ◽

Shift Workers ◽

Physical Activity Levels

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Association between physical activity levels in mid-life with physical activity in old age: a 20-year tracking study in a prospective cohort

BMJ Open ◽

10.1136/bmjopen-2017-017378 ◽

2017 ◽

Vol 7 (8) ◽

pp. e017378 ◽

Cited By ~ 6

Author(s):

Daniel Aggio ◽

Olia Papacosta ◽

Lucy Lennon ◽

Peter Whincup ◽

Goya Wannamethee ◽

...

Keyword(s):

Physical Activity ◽

Old Age ◽

Sport Participation ◽

Intraclass Correlation ◽

Sports Participation ◽

Later Life ◽

Kappa Statistics ◽

Activity Levels ◽

Recreational Activity

ObjectivesThis study aims to examine the tracking and predictability of physical activity in old age from overall physical activity and participation in sport, recreational activity and walking in mid-life.DesignProspective population-based cohort study.SettingBritish Regional Heart Study participants recruited from primary care centres in the UK in 1978–1980.Participants and outcome measuresMen (n=3413) self-reported their physical activity at baseline, 12, 16 and 20-year follow-ups and were categorised as inactive or active and having high or low participation in sport, walking and recreational activities. Tracking was assessed using kappa statistics and random effects models. Logistic regression estimated the odds of being active at 20-year follow-up according to physical activity participation in mid-life.ResultsAmong 3413 men (mean age at baseline 48.6±5.4 years) with complete data, tracking of overall physical activity was moderate (kappa: 0.23–0.26). Tracking was higher for sports participation (kappa: 0.35–0.38) compared with recreational activity (kappa: 0.16–0.24) and walking (kappa: 0.11–0.15). Intraclass correlation coefficients demonstrated similar levels of stability and only marginally weakened after controlling for covariates. Compared with inactive men, being active at baseline was associated with greater odds of being active at 20-year follow-up (OR 2.7, 95% CI 2.4 to 3.2) after adjusting for sociodemographic, health and lifestyle variables. Playing sport in mid-life was more strongly associated with being active at 20-year follow-up than other domains, particularly when sport participation began earlier in life.ConclusionBeing physically active in mid-life increases the odds of being active in old age. Promoting physical activity in later life might be best achieved by promoting sport participation earlier in the life course.

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Development and First Year Results of a Psychosocial Surveillance System for Chronic Disease Related Health Behaviors

Californian Journal of Health Promotion ◽

10.32398/cjhp.v1isi.558 ◽

2003 ◽

Vol 1 (SI) ◽

pp. 54-64 ◽

Cited By ~ 5

Author(s):

Jay E. Maddock ◽

Carrie S. Marshall ◽

Claudio R. Nigg ◽

Jodi D. Barnett

Keyword(s):

Physical Activity ◽

Health Promotion ◽

Behavior Change ◽

Health Behaviors ◽

Tobacco Use ◽

Surveillance System ◽

The United States ◽

Behavioral Risk ◽

Surveillance Systems ◽

Target Behaviors

Chronic diseases account for 7 out of 10 deaths in the United States and 60% of the Nation’s health care expenses. Tobacco use, lack of physical activity and poor nutrition account for one third of US mortality. Behavioral surveillance systems such as the Behavioral Risk Factor Surveillance System (BRFSS) provide information on rates of behavior in the population and among different demographic categories. While these systems are essential for health promotion they do not assist the health educator in understanding psychosocial factors which may be related to the rates. A psychosocial surveillance system can aid in understanding the behavior change process and in the readiness of the population for behavior change. Results can assist states and localities in targeting health promotion messages and programs and can help in the allocation of often scarce health promotion funds. In 2000, the Hawaii Department of Health launched the Healthy Hawaii Initiative, a statewide program to reduce tobacco use, increase physical activity, and improve nutrition. As part of the evaluation, researchers at the University of Hawaii implemented a psychosocial surveillance system for the three target behaviors to assess changes in hypothesized mediators including stage of change, self efficacy, attitude and social norms. A random digit dial survey was conducted in the Spring and Fall of 2002 with 4,706 and 4,555 participants, respectively. Results show stability in the demographic characteristics and health behaviors of the sample but changes in the psychosocial variables. Several possible areas for interventions and messaging are demonstrated. A psychosocial surveillance system can be an important tool for health promotion and can lead to better understanding of health behaviors and attitudes.

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Association between occupational physical activity and quantitative bone ultrasound in sawmill workers

Sigurnost ◽

10.31306/s.63.4.2 ◽

2021 ◽

Vol 63 (4) ◽

pp. 363-372

Author(s):

Selma Cvijetić ◽

Milica Gomzi ◽

Jelena Macan

Keyword(s):

Physical Activity ◽

Bone Density ◽

Quantitative Ultrasound ◽

Bone Health ◽

Physical Exertion ◽

Physical Workload ◽

Occupational Activity ◽

Occupational Physical Activity ◽

Cross Sectional ◽

Sawmill Workers

A small number of studies have examined the relationship between bone health and level of physical load. We explored the effect of occupational physical activity on skeletal status in younger sawmill workers using ultrasonic indices of bone density. In a cross-sectional study, we measured bone density with quantitative ultrasound (QUS) in 128 sawmill workers (89 men and 39 women), mean age 39.1 +/- 10.8 years. Back strength was measured by dynamometry. Information on occupational and leisure physical activity, joint pain, education and smoking were obtained with the questionnaire. All QUS bone parameters and back strength were significantly higher in men than in women. A T score for quantitative ultrasound index (QUI) of − 2.2 or lower was found only in two men and one women. QUI did not significantly differ based on presence of parameters of physical occupational activity (carrying loads exceeding 5 kg, repetitive movements, physical exertion while working and non-sitting position at work). When controlling for age, gender and body mass index, participants with higher smoking index had significantly lower QUI (p=0.004). Physical workload was not significantly associated with QUI. In our working population, some lifestyle habits, such as smoking, had a greater impact on bone health than physical occupational activity.

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Level of engagement of recreational physical activity of urban villagers in Luohu, Shenzhen, China

PLoS ONE ◽

10.1371/journal.pone.0258085 ◽

2021 ◽

Vol 16 (10) ◽

pp. e0258085

Author(s):

Lu Shi ◽

Willie Leung ◽

Qingming Zheng ◽

Jie Wu

Keyword(s):

Physical Activity ◽

Descriptive Analysis ◽

Activity Levels ◽

Sedentary Behaviors ◽

Multivariate Logistic Regression ◽

Recreational Physical Activity ◽

Urban Village ◽

Activity Frequency ◽

Community Diagnosis ◽

Urban Villages

Physical activity is important for health. However, there is a lack of literature related to the physical activity levels of adults living in urban villagers, which is a vulnerable population in China. The aim of this study is to compare the physical activity and sedentary behavior engagements between urban villagers and non-urban villagers using the 2019 Luohu Shenzhen, China Community Diagnosis Questionnaire. A total of 1205 adults living in urban villages and non-urban villages were included in the analysis. Unadjusted and multiple multivariate logistic regression were conducted for the dependent variable of engagement in recreational physical activity, frequency of recreational physical activity per week, and hours spent in sedentary behaviors per day. Descriptive analysis was conducted to identify the reasons for not engaging in physical activity among urban villagers and non-urban villagers. Across the included sample, 29.05% were urban villagers and 70.95% were non-urban villagers. The results suggested that urban villagers are more likely to engage in physical activity than non-urban villager (OR = 1.90, 95% CI [1.40, 2.59], p < 0.001). However, it was also found that urban village status had no significant association for frequency in engaging in physical activity and average hours spent in sedentary behaviors. Both urban villagers and non-urban villages indicated that lack of time, lack of safe and appropriate environment, and working in labor intensive occupations as some of the reasons for not engaging in physical activity. There is a need for tailed interventions and policies for promoting physical activity among urban villagers and non-urban villagers. Additional studies are needed to further our understanding of the physical activity behaviors among urban villagers in China.

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