Physical Activity Tracking Among Sri Lankan Adults: Findings From a 7-Year Follow-up of the Ragama Health Study.

Limited data are available on physical activity tracking among adults in low- and middle-income countries. Using a longitudinal design, we assessed trends and correlates of physical activity among Sri Lankan adults. Individuals selected through age-stratified random sampling, were screened initially in 2007 (n = 2986) and reevaluated in 2014 (n = 2148). On both occasions, structured interviews and clinical measurements were completed. Approximately 40% of the participants engaged in recommended levels of physical activity both at baseline and follow-up. One-fifth reported increased physical activity at follow-up, a similar proportion reported being persistently inactive or a reduction in physical activity. In the adjusted analysis, being persistently active was associated with male sex, a lower educational level and income, being free of any chronic disease conditions, better self-rated health, and sitting time <8 hours. Our findings support public health interventions to help maintain recommended physical activity levels over time, particularly for subgroups at high-risk of physical inactivity.

The epidemiology of muscle-strengthening exercise in Europe: A 28-country comparison including 280,605 adults.

OBJECTIVE: Muscle-strengthening exercise (use of weight machines, free weights, push-ups, sit-ups), has multiple independent health benefits, and is a component of the Global physical activity guidelines. However, there is currently a lack of multi-country muscle-strengthening exercise prevalence studies. This study describes the prevalence and correlates of muscle-strengthening exercise across multiple European countries. METHODS: Data were drawn from the European Health Interview Survey Wave 2 (2013-14), which included nationally representative samples (n = 3,774-24,016) from 28 European countries. Muscle-strengthening exercise was assessed using the European Health Interview Survey Physical Activity Questionnaire. Population-weighted proportions were calculated for (1) "insufficient" (0-1 days/week) or (2) "sufficient" muscle-strengthening exercise (≥2 days/week). Prevalence ratios were calculated using multivariate Poisson regression for those reporting sufficient muscle-strengthening by country and by sociodemographic/lifestyle characteristics (sex, age, education, income, self-rated health etc.). RESULTS: Data were available for 280,605 European adults aged ≥18 years. Overall, 17.3% (95% CI = 17.1%-17.5%) reported sufficient muscle-strengthening exercise (≥2 days/week). Muscle-strengthening exercise was geographically patterned with the lowest prevalence reported in South-eastern European countries (Romania, Malta and Cyprus: range: 0.7%-7.4%), and the highest prevalence in the Nordic countries (Iceland, Sweden, and Denmark: range: 34.1%-51.6%). Older age, insufficient aerobic activity, poorer self-rated health, lower income/education, being female, and being overweight/obese were significantly associated with lower likelihood of reporting sufficient muscle-strengthening exercise, independently of other characteristics. CONCLUSIONS: Most European adults do not report sufficient muscle-strengthening exercise, and prevalence estimates varied considerably across countries. Low participation in muscle-strengthening exercise is widespread across Europe, and warrants public health attention.

Equity of a government subsidised exercise referral scheme: A population study.

BACKGROUND: Health inequities could increase if utilisation of physical activity interventions is lower among socioeconomically disadvantaged groups. We examined associations between area level socioeconomic disadvantage and utilisation of Australian government-subsidised, general practitioner (GP)-referred, accredited exercise physiologist (AEPs) services. METHODS: We conducted a cross-sectional analysis of Australian Medical Benefits Scheme (MBS) data (N = 228,771 AEP services) for the 2015-2016 financial year and aggregated publicly available data from several sources. Spearman's correlations examined associations between utilisation of AEP services and area-level socioeconomic disadvantage, indicated by Index of Relative Socioeconomic Disadvantage (IRSD) decile scores. Lower IRSD scores indicate greater levels of socioeconomic disadvantage. RESULTS: Significant correlations between IRSD score and study variables were as follows: Out-of-pocket expenses/service (rs = 0.52); number of patients/AEP provider (rs = -0.42); number of patients/1000 population (rs = -0.24); AEP services/1000 population (rs = -0.18); average services/patient (rs = 0.24); and AEP provider/1000 population (rs = 0.14). CONCLUSION: Patients living in areas of greater disadvantage utilised government-subsidised, GP-referred AEP services at a higher rate and paid lower out-of-pocket fees than those living in more affluent areas. Thus, AEP services are equitably distributed, from a utilisation perspective, and acceptable to patients living in areas of disadvantage. However, the higher caseloads and lower fees that characterise AEP services in areas of greater disadvantage may result in shorter consultation times. Further research on exercise referral schemes is warranted, particularly whether socioeconomic disadvantage is associated with adherence to exercise sessions and health outcomes.

Participant characteristics of users of holistic movement practices in Australia.

OBJECTIVES: The aim of this study was to compare the characteristics of users of holistic movement practices in Australia to people who were physically active but not using holistic movement practices. A second aim was to compare characteristics of users of specific holistic movement practices (yoga/Pilates and t'ai chi/qigong). DESIGN: We performed a secondary data analysis on pooled data of a nationally-representative physical activity survey conducted yearly 2001-2010 (n = 195,926). SETTING: Australia-wide Exercise, Recreation, and Sport Survey (ERASS). MAIN OUTCOME MEASURES: A range of socio-demographic and participation characteristics were documented and compared between users and non-users of holistic movement practices and between yoga/Pilates and t'ai chi/qigong users, employing descriptive statistics, chi square, and multiple logistic regression analyses. RESULTS: Users of holistic movement practices (n = 6826) were significantly more likely than non-users to be female, older, have fewer children at home, and have higher levels of education, socio-economic background, and physical activity involvement (p < 0.001). Yoga/Pilates (n = 5733) and t'ai chi/qigong (n = 947) users were also found to differ on a number of characteristics, including age, sex, socioeconomic background, and marital status. CONCLUSION: As a group, Australian users of holistic movement practices differ on a range of characteristics from those Australians active in other types of physical activities. However, differences between yoga/Pilates and t'ai chi/qigong users suggest these practices attract somewhat different sub-populations. To what extent these differences are due to characteristics inherent to the practices themselves or to differences in delivery-related parameters needs to be examined in future research.

Assessment and monitoring practices of Australian fitness professionals.

OBJECTIVES: Assessment and monitoring of client health and fitness is a key part of fitness professionals' practices. However, little is known about prevalence of this practice. This study describes the assessment/monitoring practices of a large sample of Australian fitness professionals. DESIGN: Cross-sectional. METHODS: In 2014, 1206 fitness professionals completed an online survey. Respondents reported their frequency (4 point-scale: [1] 'never' to [4] 'always') of assessment/monitoring of eight health and fitness constructs (e.g. body composition, aerobic fitness). This was classified as: (i) 'high' ('always' assessing/monitoring ≥5 constructs); (ii) 'medium' (1-4 constructs); (iii) 'low' (0 constructs). Classifications are reported by demographic and fitness industry characteristics. The odds of being classified as a 'high assessor/monitor' according to social ecological correlates were examined using a multiple-factor logistic regression model. RESULTS: Mean age of respondents was 39.3 (±11.6) years and 71.6% were female. A total of 15.8% (95% CI: 13.7%-17.9%) were classified as a 'high' assessor/monitor. Constructs with the largest proportion of being 'always' assessed were body composition (47.7%; 95% CI: 45.0%-50.1%) and aerobic fitness (42.5%; 95% CI: 39.6%-45.3%). Those with the lowest proportion of being 'always' assessed were balance (24.0%; 95% CI: 24.7%-26.5%) and mental health (20.2%; 95% CI: 18.1%-29.6%). A perceived lack of client interest and fitness professionals not considering assessing their responsibility were associated with lower odds of being classified as a 'high assessor/monitor'. CONCLUSIONS: Most fitness professionals do not routinely assess/monitor client fitness and health. Key factors limiting client health assessment and monitoring include a perceived lack of client interest and professionals not considering this their role.

Associations between multiple indicators of socio-economic status and muscle-strengthening activity participation in a nationally representative population sample of Australian adults.

BACKGROUND: Muscle-strengthening activity (MSA) (e.g. weight training), confers unique health benefits. While socioeconomic status (SES) correlates with leisure time physical activity, little is known about its relation with MSA. METHODS: Cross-sectional study of a representative sample of 8993 Australian adults (>18years) who participated in the National Nutrition and Physical Activity Survey 2011-12. Information was collected on SES (income, education, socio-economic disadvantage and remoteness) and MSA participation. RESULTS: 17.9% (CI: 16.8-19.0) met the national guidelines for MSA (≥2 sessions/week). Men and younger adults (<35years) met MSA guidelines more than females (19.7%; CI: 18.3-21.1% vs 16.1%; CI: 14.6-17.6%; p<0.001) and older adults respectively (25.0%; CI: 22.4-27.7% vs 10.4%; CI: 8.9-11.8%; p<0.001). All SES indicators were associated with meeting the guidelines in unadjusted analyses. When adjusting for total physical activity and mutually adjusting for each socioeconomic indicator only remoteness (OR for city vs rural=1.65; CI: 1.17-2.32; p<0.001) was associated with MSA participation (education OR=1.09 for high vs low; CI: 0.80-1.47, p=0.748; income OR=1.31 for Q5 vs Q1, CI: 0.93-1.85, p=0.328; social disadvantage OR=1.04 for v.high vs v.low, CI: 0.76-1.43, p=0.855). These associations were further attenuated when adjusting for BMI, smoking status and self-rated health. CONCLUSION: Remoteness, and to a lesser degree, education, income and social disadvantage, were independently associated with MSA participation. Public health interventions should improve access to strength training facilities, and/or increase home-based muscle-strengthening activity in remote areas.

Sources of practice knowledge among Australian fitness trainers.

Few studies have examined the sources of practice knowledge fitness trainers use to inform their training methods and update knowledge. This study aims to describe sources of practice knowledge among Australian fitness trainers. In July 2014, 9100 Australian fitness trainers were invited to complete an online survey. Respondents reported the frequency of use of eight sources of practice knowledge (e.g. fitness magazines, academic texts). In a separate survey, exercise science experts (n = 27) ranked each source as either (1) 'high-quality' or (2) 'low-quality'. Proportions of users of 'high-quality' sources were calculated across demographic (age, sex) and fitness industry-related characteristics (qualification, setting, role). A multivariate logistic regression analysis assessed the odds of being classified as a user of high-quality sources, adjusting for demographic and fitness industry-related factors. Out of 1185 fitness trainers (response rate = 13.0%), aged 17-72 years, 47.6% (95% CI, 44.7-50.4%) were classified as frequent users of high-quality sources of practice knowledge. In the adjusted analysis, compared to trainers aged 17-26 years, those aged ≥61 years (OR, 2.15; 95% CI, 1.05-4.38) and 40-50 years (OR, 1.54; 95% CI, 1.02-2.31) were more likely to be classified as a user of high-quality sources. When compared to trainers working in large centres, those working in outdoor settings (OR, 1.81; 95% CI, 1.23-2.65) and medium centres (OR, 1.59; 95% CI, 1.12-2.29) were more likely to be classified as users of high-quality sources. Our findings suggest that efforts should be made to improve the quality of knowledge acquisition among Australian fitness trainers.

Variations in area-level disadvantage of Australian registered fitness trainers usual training locations.

BACKGROUND: Leisure-time physical activity and strength training participation levels are low and socioeconomically distributed. Fitness trainers (e.g. gym/group instructors) may have a role in increasing these participation levels. However, it is not known whether the training location and characteristics of Australian fitness trainers vary between areas that differ in socioeconomic status. METHODS: In 2014, a sample of 1,189 Australian trainers completed an online survey with questions about personal and fitness industry-related characteristics (e.g. qualifications, setting, and experience) and postcode of their usual training location. The Australian Bureau of Statistics 'Index of Relative Socioeconomic Disadvantage' (IRSD) was matched to training location and used to assess where fitness professionals trained and whether their experience, qualification level and delivery methods differed by area-level disadvantage. Linear regression analysis was used to examine the relationship between IRSD score and selected characteristics adjusting for covariates (e.g. sex, age). RESULTS: Overall, 47 % of respondents worked in areas within the three least-disadvantaged deciles. In contrast, only 14.8 % worked in the three most-disadvantaged deciles. In adjusted regression models, fitness industry qualification was positively associated with a higher IRSD score (i.e. working in the least-disadvantaged areas) (Cert III: ref; Cert IV ß:13.44 [95 % CI 3.86-23.02]; Diploma ß:15.77 [95 % CI: 2.17-29.37]; Undergraduate ß:23.14 [95 % CI: 9.41-36.86]). CONCLUSIONS: Fewer Australian fitness trainers work in areas with high levels of socioeconomic disadvantaged areas than in areas with low levels of disadvantage. A higher level of fitness industry qualifications was associated with working in areas with lower levels of disadvantage. Future research should explore the effectiveness of providing incentives that encourage more fitness trainers and those with higher qualifications to work in more socioeconomically disadvantaged areas.

Pumping Iron in Australia: Prevalence, Trends and Sociodemographic Correlates of Muscle Strengthening Activity Participation from a National Sample of 195,926 Adults.

OBJECTIVE: The current Australian Physical Activity Guidelines recommend that adults engage in regular muscle-strengthening activity (e.g. strength or resistance training). However, public health surveillance studies describing the patterns and trends of population-level muscle-strengthening activity participation are sparse. The aim of this study is to examine the prevalence, trends and sociodemographic correlates of muscle-strengthening activity participation in a national-representative sample of Australians aged 15 years and over. METHODS: Between 2001 and 2010, quarterly cross-sectional national telephone surveys were conducted as part of the Australian Sports Commission's 'Exercise, Recreation and Sport Survey'. Pooled population-weighted proportions were calculated for reporting: [i] no muscle-strengthening activity; [ii] insufficient muscle-strengthening activity, and [iii] sufficient muscle-strengthening activity. Associations with sociodemographic variables were assessed using multiple logistic regression analyses. RESULTS: Out of 195,926 participants, aged 15-98 years, only 10.4% (95% CI: 10.1-10.7) and 9.3% (95% CI: 9.1-9.5) met the muscle-strengthening activity recommendations in the past two weeks and in the past year, respectively. Older adults (50+ years), and those living in socioeconomically disadvantaged, outer regional/remote areas and with lower education were less likely to report sufficient muscle-strengthening activity (p<0.001). Over the 10-year monitoring period, there was a significant increase in the prevalence of sufficient muscle-strengthening activity (6.4% to 12.0%, p-value for linear trend <0.001). CONCLUSIONS: A vast majority of Australian adults did not engage in sufficient muscle-strengthening activity. There is a need for public health strategies to support participation in muscle-strengthening activity in this population. Such strategies should target older and lower educated adults, and those living in socioeconomically disadvantaged, outer regional/remote and areas.

Workplace Sitting Breaks Questionnaire (SITBRQ): an assessment of concurrent validity and test-retest reliability.

BACKGROUND: Breaks in prolonged sitting may have beneficial cardiometabolic and musculoskeletal health outcomes. Desk-based work settings are an important environment to promote and support breaks in sitting time. However, few studies have reported the psychometric properties of self-report measures to assess the frequency and duration of breaks from sitting. This study examined the concurrent validity and test-retest reliability of the Workplace Sitting Breaks Questionnaire (SITBRQ) designed to assess frequency and duration of breaks in sitting within desk-based work settings. METHODS: To assess the concurrent validity, a sample of 147 desk-based employees completed the SITBRQ and wore an Actigraph GT1M accelerometer for seven consecutive days. To establish test-retest reliability, SITBRQ was administered on two separate occasions 7-14 days apart to a separate sample of 96 desk-based employees. RESULTS: A low relative agreement with accelerometry (Spearman's r = 0.24 [95% CI 0.07-0.40]) was determined for self-reported frequency, but not for the duration of sitting breaks (Spearman's r = 0.05 [95% CI -0.12-0.22]). Adequate reliability was determined for both self-reported frequency (Spearman's r = 0.71 [95% CI 0.59-0.79], Cohen's kappa = 0.74 [95% CI 0.64-0.84]) and duration of sitting breaks (Spearman's r = 0.59 [95% CI 0.45-0.71], Cohen's kappa = 0.61 [95% CI 0.38-0.85]). CONCLUSION: SITBRQ may be used for assessment of the frequency of sitting breaks within desk-based work settings with validity and reliability similar to other self-reports in the field of sedentary behaviour research. However, until adequately improved and re-evaluated, it should not be used to collect data about the duration of breaks in sitting time.

The prevalence and correlates of sitting in European adults - a comparison of 32 Eurobarometer-participating countries.

BACKGROUND: Prolonged sitting is an emerging health risk. However, multi-country comparative sitting data are sparse. This paper reports the prevalence and correlates of sitting time in 32 European countries. METHODS: Data from the Eurobarometer 64.3 study were used, which included nationally representative samples (n = 304-1,102) from 32 European countries. Face-to-face interviews were conducted during November and December 2005. Usual weekday sitting time was assessed using the International Physical Activity Questionnaire (short-version). Sitting time was compared by country, age, gender, years of education, general health status, usual activity and physical activity. Multivariable-adjusted analyses assessed the odds of belonging to the highest sitting quartile. RESULTS: Data were available for 27,637 adults aged 15-98 years. Overall, mean reported weekday sitting time was 309 min/day (SD 184 min/day). There was a broad geographical pattern and some of the lowest amounts of daily sitting were reported in southern (Malta and Portugal means 194-236 min/day) and eastern (Romania and Hungary means 191-276 min/day) European countries; and some of the highest amounts of daily sitting were reported in northern European countries (Germany, Benelux and Scandinavian countries; means 407-335 min/day). Multivariable-adjusted analyses showed adults with low physical activity levels (OR = 5.10, CI95 = 4.60-5.66), those with high sitting in their main daily activity (OR = 2.99, CI95 = 2.74-3.25), those with a bad/very bad general health state (OR = 1.87, CI95 = 1.63-2.15) and higher education levels (OR = 1.48, CI95 = 1.38-1.59) were more likely to be in the highest quartile of daily sitting time. Adults within Greece (OR = 2.91, CI95 = 2.51-3.36) and Netherlands (OR = 2.56, CI95 = 2.22-2.94) were most likely to be in the highest quartile. High-sit/low-active participants comprised 10.1% of the sample. Adults self-reporting bad/very bad general health state (OR = 4.74, CI95 = 3.97-5.65), those within high sitting in their main daily activities (OR = 2.87, CI95 = 2.52-3.26) and adults aged ≥65 years (OR = 1.53, CI95 = 1.19-1.96) and were more likely to be in the high-sit/low-active group. CONCLUSIONS: Weekday sitting time and its demographic correlates varied considerably across European countries, with adults in north-western European countries sitting the most. Sitting is prevalent across Europe and merits attention by preventive interventions.