Relationship of device measured physical activity type and posture with cardiometabolic health markers: pooled dose-response associations from the Prospective Physical Activity, Sitting and Sleep Consortium.

AIMS/HYPOTHESIS: The aim of this study was to examine the dose-response associations of device-measured physical activity types and postures (sitting and standing time) with cardiometabolic health. METHODS: We conducted an individual participant harmonised meta-analysis of 12,095 adults (mean ± SD age 54.5±9.6 years; female participants 54.8%) from six cohorts with thigh-worn accelerometry data from the Prospective Physical Activity, Sitting and Sleep (ProPASS) Consortium. Associations of daily walking, stair climbing, running, standing and sitting time with a composite cardiometabolic health score (based on standardised z scores) and individual cardiometabolic markers (BMI, waist circumference, triglycerides, HDL-cholesterol, HbA1c and total cholesterol) were examined cross-sectionally using generalised linear modelling and cubic splines. RESULTS: We observed more favourable composite cardiometabolic health (i.e. z score <0) with approximately 64 min/day walking (z score [95% CI] -0.14 [-0.25, -0.02]) and 5 min/day stair climbing (-0.14 [-0.24, -0.03]). We observed an equivalent magnitude of association at 2.6 h/day standing. Any amount of running was associated with better composite cardiometabolic health. We did not observe an upper limit to the magnitude of the dose-response associations for any activity type or standing. There was an inverse dose-response association between sitting time and composite cardiometabolic health that became markedly less favourable when daily durations exceeded 12.1 h/day. Associations for sitting time were no longer significant after excluding participants with prevalent CVD or medication use. The dose-response pattern was generally consistent between activity and posture types and individual cardiometabolic health markers. CONCLUSIONS/INTERPRETATION: In this first activity type-specific analysis of device-based physical activity, ~64 min/day of walking and ~5.0 min/day of stair climbing were associated with a favourable cardiometabolic risk profile. The deleterious associations of sitting time were fully attenuated after exclusion of participants with prevalent CVD and medication use. Our findings on cardiometabolic health and durations of different activities of daily living and posture may guide future interventions involving lifestyle modification.

Physical activity across midlife and health-related quality of life in Australian women: A target trial emulation using a longitudinal cohort.

BACKGROUND: There is little long-term causal evidence on the effect of physical activity on health-related quality of life. This study aimed to examine the associations between longitudinal patterns of physical activity over 15 years and health-related quality of life in both the physical and mental health domains, in a cohort of middle-aged Australian women. METHODS AND FINDINGS: We used data collected at 3-year intervals (1998 to 2019) from 11,336 participants in the Australian Longitudinal Study on Women's Health (ALSWH) (1946 to 1951 birth cohort). Primary outcomes were the physical (PCS) and mental health component summary (MCS) scores (range from 0 to 100; higher scores indicate higher perceived physical/mental health) from the SF-36 in 2019 (when women aged 68 to 73 years). Using target trial emulation to imitate a randomized controlled trial (RCT), we tested 2 interventions: (1) meeting the World Health Organization (WHO) physical activity guidelines consistently throughout the 15-year "exposure period" (2001 to 2016; when women aged 50-55 to 65-70 years; physical activity assessed every 3 years); and (2) not meeting the guidelines at the beginning of the exposure period but starting to first meet the guidelines at age 55, 60, or 65; against the control of not meeting the guidelines throughout the exposure period. Analysis controlled for confounding using marginal structural models which were adjusted for sociodemographic and health variables and conditions. Consistent adherence to guidelines during the exposure period (PCS: 46.93 [99.5% confidence interval [CI]: 46.32, 47.54]) and first starting to meet the guidelines at age 55 (PCS: 46.96 [99.5% CI: 45.53, 48.40]) were associated with three-point higher PCS (mean score difference: 3.0 [99.5% CI: 1.8, 4.1] and 3.0 [99.5% CI:1.2, 4.8]) than consistent non-adherence (PCS: 43.90 [99.5% CI: 42.79, 45.01]). We found a similar pattern for most SF-36 subscales but no significant effects of the interventions on MCS. The main limitations of the study were that it may not account for all underlying health conditions and/or other unmeasured or insufficiently measured confounders, the use of self-reported physical activity and that findings may not be generalizable to all mid-age women. CONCLUSIONS: Results from the emulated RCT suggest women should be active throughout mid-age, ideally increasing activity levels to meet the guidelines by age 55, to gain the most benefits for physical health in later life.

Ecological momentary assessment of physical activity and sedentary behaviour in shift workers and non-shift workers: Validation study.

This study examined the criterion validity of an ecological momentary assessment (EMA)-reported physical activity and sedentary time compared with accelerometry in shift workers and non-shift workers. Australian workers (n = 102) received prompts through a mobile EMA app and wore the Actigraph accelerometer on the right hip for 7-10 days. Participants received five EMA prompts per day at 3-hour intervals on their mobile phones. EMA prompts sent to shift workers (SW-T) were tailored according to their work schedule. Non-shift workers (NSW-S) received prompts at standardised times. To assess criterion validity, the association of EMA-reported activities and the Actigraph accelerometer activity counts and number of steps were used. Participants were 36 ± 11 years and 58% were female. On occasions where participants reported physical activity, acceleration counts per minute (CPM) and steps were significantly higher (ß = 1184 CPM, CI 95%: 1034, 1334; ß = 20.9 steps, CI 95%: 18.2, 23.6) than each of the other EMA activities. Acceleration counts and steps were lower when sitting was reported than when no sitting was reported by EMA. Our study showed that EMA-reported physical activity and sedentary time was significantly associated with accelerometer-derived data. Therefore, EMA can be considered to assess shift workers' movement-related behaviours with accelerometers to provide rich contextual data.

Adherence to 24-h movement behaviour guidelines in families with multiple children.

BACKGROUND: In 2019, the World Health Organization (WHO) launched the first global movement guidelines for children that combined sleep, physical activity and screen time. Our previous research showed that adherence to age-specific guidelines for screen time was challenging for families with children in different age groups. We aimed to determine whether families with children in different age-based movement guideline categories have poorer adherence to the broader 24-h movement guidelines than those with all children in the same age category. METHODS: Data were from the 1973-1978 cohort of the Australian Longitudinal Study on Women's Health (seventh survey, 2015) and the women's three youngest children (aged ≤12) (Mothers and their Children's Health sub-study, 2016/2017). The sample was 1787 women (families) with 4064 children (mean age 7.2 [SD 2.9]). Whether children in the family were in the same or different age-based category was determined by matching children's ages in a family against age-based guideline categories for the 24-h movement behaviours. The association between children in the family being in the same or different age-based guideline category on adherence to 24-h movement guidelines, both collectively and individually, was analysed by adjusted logistic regression (binary and multinomial). RESULTS: Families with children in the same age guideline categories had double the odds of having all children meet 24-h movement guidelines (adjusted odds ratio [OR] 1.95 [95% confidence interval, CI: 1.32, 2.86]). Families with children in the same age categories on the screen guideline had higher odds of all children meeting (2.25 [1.73, 2.93]) and lower odds of some meeting/some failing the screen guideline (0.18 [0.14, 0.25]), than families with all children in different age categories. Families with children in the same age categories on the physical activity guideline had lower odds of all children meeting (0.57 [0.43, 0.75]) or some meeting/some failing the physical activity guideline (0.08 [0.06, 0.12]). No associations were found for sleep guidelines. CONCLUSIONS: Families with multiple children may need practical advice and strategies on how to adhere to guidelines when children span age categories. This could form part of public health strategies that raise awareness of the guidelines and may improve guideline adherence.

Association of 'Tortoise' and 'Hare' movement behavior patterns with cardiometabolic health, body composition, and functional fitness in older adults.

We investigated the association of movement behavior patterns with cardiometabolic health, body composition, and functional fitness in older adults. A total of 242 older adults participated of this cross-sectional study. Sedentary time, light physical activity (LPA) and moderate-vigorous physical activity (MVPA), steps/day, and step cadence were assessed by accelerometry. The movement behavior patterns were derived by principal component analysis. Cardiometabolic health was defined by a metabolic syndrome score (cMetS). Body composition was determined by appendicular lean mass/body mass index (ALM/BMI). Functional fitness was assessed by a composite z-score from the Senior Fitness Test battery. Two patterns were identified: 'Tortoise' (low sedentary time, high LPA and steps/day) and 'Hare' (high MVPA, steps/day, and step cadence). 'Tortoise' and 'Hare' were associated with better cMetS. 'Hare' was positively associated with ALM/BMI and Functional Fitness. While 'Tortoise' and 'Hare' were associated with better cMetS, only 'Hare' was associated with better ALM/BMI and functional fitness.

The impact of selected methodological factors on data collection outcomes in observational studies of device-measured physical behaviour in adults: A systematic review.

BACKGROUND: Accelerometer measures of physical behaviours (physical activity, sedentary behaviour and sleep) in observational studies offer detailed insight into associations with health and disease. Maximising recruitment and accelerometer wear, and minimising data loss remain key challenges. How varying methods used to collect accelerometer data influence data collection outcomes is poorly understood. We examined the influence of accelerometer placement and other methodological factors on participant recruitment, adherence and data loss in observational studies of adult physical behaviours. METHODS: The review was in accordance with the Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA). Observational studies of adults including accelerometer measurement of physical behaviours were identified using database (MEDLINE (Ovid), Embase, PsychINFO, Health Management Information Consortium, Web of Science, SPORTDiscus and Cumulative Index to Nursing & Allied Health Literature) and supplementary searches to May 2022. Information regarding study design, accelerometer data collection methods and outcomes were extracted for each accelerometer measurement (study wave). Random effects meta-analyses and narrative syntheses were used to examine associations of methodological factors with participant recruitment, adherence and data loss. RESULTS: 123 accelerometer data collection waves were identified from 95 studies (92.5% from high-income countries). In-person distribution of accelerometers was associated with a greater proportion of invited participants consenting to wear an accelerometer (+ 30% [95% CI 18%, 42%] compared to postal distribution), and adhering to minimum wear criteria (+ 15% [4%, 25%]). The proportion of participants meeting minimum wear criteria was higher when accelerometers were worn at the wrist (+ 14% [ 5%, 23%]) compared to waist. Daily wear-time tended to be higher in studies using wrist-worn accelerometers compared to other wear locations. Reporting of information regarding data collection was inconsistent. CONCLUSION: Methodological decisions including accelerometer wear-location and method of distribution may influence important data collection outcomes including recruitment and accelerometer wear-time. Consistent and comprehensive reporting of accelerometer data collection methods and outcomes is needed to support development of future studies and international consortia. Review supported by the British Heart Foundation (SP/F/20/150002) and registered (Prospero CRD42020213465).

High-Intensity Interval Training is Safe, Feasible and Efficacious in Nonalcoholic Steatohepatitis: A Randomized Controlled Trial.

BACKGROUND: High-Intensity Interval Training (HIIT) involves bursts of high-intensity exercise interspersed with lower-intensity exercise recovery. HIIT may benefit cardiometabolic health in people with nonalcoholic steatohepatitis (NASH). AIMS: We aimed to examine the safety, feasibility, and efficacy of 12-weeks of supervised HIIT compared with a sham-exercise control (CON) for improving aerobic fitness and peripheral insulin sensitivity in biopsy-proven NASH. METHODS: Participants based in the community [(n = 14, 56 ± 10 years, BMI 39.2 ± 6.7 kg/m2, 64% male), NAFLD Activity Score 5 (range 3-7)] were randomized to 12-weeks of supervised HIIT (n = 8, 4 × 4 min at 85-95% maximal heart rate, interspersed with 3 min active recovery; 3 days/week) or CON (n = 6, stretching; 3 days/week). Safety (adverse events) and feasibility determined as ≥ 70% program completion and ≥ 70% global adherence (including session attendance, interval intensity adherence, and duration adherence) were assessed. Changes in cardiorespiratory fitness (V̇O2peak), exercise capacity (time-on-test) and peripheral insulin sensitivity (euglycemic hyperinsulinemic clamp) were assessed. Data were analysed using ANCOVA with baseline value as the covariate. RESULTS: There were no HIIT-related adverse events and HIIT was globally feasible [program completion 75%, global adherence 100% (including adherence to session 95.4 ± 7.3%, interval intensity 95.3 ± 6.0% and duration 96.8 ± 2.4%)]. A large between-group effect was observed for exercise capacity [mean difference 134.2 s (95% CI 19.8, 248.6 s), ƞ2 0.44, p = 0.03], improving in HIIT (106.2 ± 97.5 s) but not CON (- 33.4 ± 43.3 s), and for peripheral insulin sensitivity [mean difference 3.4 mg/KgLegFFM/min (95% CI 0.9,6.8 mg/KgLegFFM/min), ƞ2 0.32, p = 0.046], improving in HIIT (1.0 ± 0.8 mg/KgLegFFM/min) but not CON (- 3.1 ± 1.2 mg/KgLegFFM/min). CONCLUSIONS: HIIT is safe, feasible and efficacious for improving exercise capacity and peripheral insulin sensitivity in people with NASH. CLINICAL TRIAL REGISTRATION NUMBER: Australian New Zealand Clinical Trial Registry (anzctr.org.au) identifier ACTRN12616000305426 (09/03/2016).

Day-to-day variability in accelerometer-measured physical activity in mid-aged Australian adults.

PURPOSE: The aim was to use accelerometer data to describe day-to-day variability in physical activity in a single week, according to sociodemographic variables, in mid-aged Australian adults. METHODS: Data were from participants in the How Areas in Brisbane Influence HealTh and AcTivity (HABITAT) study who took part in a 2014 sub-study (N = 612; Mean age 60.6 [SD 6.9; range 48-73]). Participants wore a triaxial accelerometer (ActiGraph wGT3X-BT) on their non-dominant wrist for seven days, and data were expressed as acceleration in gravitational equivalent units (1 mg = 0.001 g). These were, used to estimate daily acceleration (during waking hours) and daily time spent in moderate-vigorous physical activity (MVPA, defined as ≥ 100mg). Coefficient of variation (calculated as [standard deviation/mean of acceleration and MVPA across the seven measurement days] * 100%) was used to describe day-to-day variability. RESULTS: Average values for both acceleration (24.1-24.8 mg/day) and MVPA (75.9-79.7 mins/day) were consistent across days of the week, suggesting little day-to-day variability (at the group level). However, over seven days, average individual day-to-day variability in acceleration was 18.8% (SD 9.3%; range 3.4-87.7%) and in MVPA was 35.4% (SD 15.6%; range 7.3-124.6%), indicating considerable day-to-day variability in some participants. While blue collar workers had the highest average acceleration (28.6 mg/day) and MVPA (102.5 mins/day), their day-to-day variability was low (18.3% for acceleration and 31.9% for MVPA). In contrast, variability in acceleration was highest in men, those in professional occupations and those with high income; and variability in MVPA was higher in men than in women. CONCLUSION: Results show group-level estimates of average acceleration and MVPA in a single week conceal considerable day-to-day variation in how mid-age Australians accumulate their acceleration and MVPA on a daily basis. Overall, there was no clear relationship between overall volume of activity and variability. Future studies with larger sample sizes and longitudinal data are needed to build on the findings from this study and increase the generalisability of these findings to other population groups.

A stepped down physical activity support program for military service veterans: The Active Choices pilot study.

ISSUE ADDRESSED: Referral to supervised physical activity (PA) programs is an effective treatment for military service veterans (MSVs) suffering from a range of chronic diseases. However, many MSVs fail to maintain PA regimes once discharged from supervision. This pilot study assessed Active Choices, a stepped-down program to support MSVs in the transition from allied health treatment to self-managed PA. METHODS: Participants were 34 Australian MSVs (mean [SD] age = 61 [15.8] years) who were completing supervised referral to an exercise physiologist or physiotherapist. MSVs stepped-down to Active Choices and received a 12-week, evidence-based PA support program (2020-2021). Analyses compared within-group changes in accelerometer-assessed PA at three time points (Weeks 0, 12, and 24; linear mixed model). Program retention, PA choices, and allied healthcare service costs were also evaluated. RESULTS: Relative to baseline (64 [26] min/day), mean (SD) moderate-to-vigorous PA increased (74 [28] min/day; p < .05) and was maintained (62 [28] min/day) at weeks 12 and 24, respectively. Retention in the program was high (86% [29/34 participants] completion rate at 12 weeks), with water-based group activities the most popular PAs of choice (14/24 activities). Average allied healthcare service costs during the study were lower than typical costs for MSVs (60.51 vs. 97.06 AUD/week). CONCLUSION: The findings highlight the potential of Active Choices to support MSVs in the transition from supervised to self-managed MVPA. SO WHAT?: The program could promote the health of veterans and reduce costs for ongoing referral if impact is replicated at scale.

Influence of maternal excess weight before pregnancy on breast-feeding and weaning: pooled analyses of four population-based cohorts born between 1982 and 2015.

To investigate the associations of maternal excess weight before pregnancy with (1) weaning at 3 months of age, (2) duration of exclusive breast-feeding at 6 months of age, (3) duration of any breast-feeding at 12 months of age and (4) to compare the magnitude of these associations over four decades. Data were from participants in the Pelotas (Brazil) Birth Cohorts born in 1982 (n 5334), 1993 (n 1442), 2004 (n 4092) and 2015 (n 4102). Maternal pre-pregnancy weight was collected after the delivery and breast-feeding status was assessed when children were 3 and 12 months old. Only in the most recent cohort (2015), women with excess weight (BMI ≥ 25 kg/m2) before pregnancy had higher risk of discontinuing exclusive breast-feeding within the first 6 months postpartum than women with normal weight (hazard ratio = 1·22 (95 % CI 1·15, 1·30)). Duration of any type of breast-feeding until 12 months of age was not affected by pre-pregnancy weight. Excess weight before pregnancy is associated with exclusive breast-feeding only in the most recent birth cohort coinciding with increases in excess weight and breast-feeding over time.

All are equal, but some are more equal than others: social determinants of leisure time physical activity through the lens of intersectionality.

BACKGROUND: To date, no research has investigated social determinants of leisure time physical activity through the lens of intersectionality in a low- and middle-income country. Therefore, the aim of this study was to explore the intersectionality in leisure time physical activity in a nationwide sample of Brazilian adults. METHODS: Data from the Brazilian National Health Survey conducted in 2013 were analysed (N = 58,429). Prevalence of sufficient leisure time physical activity (150+ minutes per week in moderate-to-vigorous physical activity) was estimated according to gender, racial identity, education and income, and according to multiple combinations of these sociodemographic characteristics (i.e., multiple jeopardy index). RESULTS: The prevalence of sufficient leisure time physical activity was 22.9% (95%CI: 22.3 to 23.6). Overall, the prevalence of sufficient leisure time physical activity was highest among men, individuals with white skin colour, and among those in the highest group of education and income. Among men, white, with a university degree and in the highest quartile of income (3% of the population), the prevalence of sufficient leisure time physical activity was 48%. Among non-white women with low education and low income (8.1% of the population), the prevalence of sufficient leisure time physical activity was 9.8%. CONCLUSION: Informed by the theory of intersectionality, findings of this study have shown that intersections of gender, racial identity and socioeconomic position of the Brazilian society strongly influence leisure time physical activity at the individual level. Targeted interventions to increase leisure time physical activity should address the complexities of social status intersections.

Rural-urban differences in physical activity and TV-viewing in Brazil.

INTRODUCTION: This study aims to compare differences regarding physical activity (PA) indicators and TV viewing according to location of residence and sociodemographic variables in Brazil. METHODS: This cross-sectional study with individuals aged 18 years or older using data from the Brazilian National Health Survey was carried out in 2013. PA (total and domains) and TV viewing (≥3 hours) were measured by self-report. Stratifiers were location of residence, sex, age, wealth quintiles and regions of the country. RESULTS: This study included 60 202 individuals (49 245 from urban areas). In general, total PA was not different according to location of residence (urban 59.4%; rural 57.4%). Higher differences were found for leisure-time PA (urban 24.1%; rural 13.9%), work-based PA (urban 12.9%; rural 21.1%) and TV viewing of more than 3 hours (urban 30.1%; rural 21.4%). The differences between urban and rural areas were enhanced according to sex, age and wealth quintiles. CONCLUSION: The differences between urban and rural areas vary according to PA domains and population groups. To explore specific domains of PA in each location of residence may improve the understanding of the analyzed outcomes in different communities and consequently guide future interventions.

Effects of cardiorespiratory fitness and exercise training on cerebrovascular blood flow and reactivity: a systematic review with meta-analyses.

We address two aims: Aim 1 (Fitness Review) compares the effect of higher cardiorespiratory fitness (CRF) (e.g., endurance athletes) with lower CRF (e.g., sedentary adults) on cerebrovascular outcomes, including middle cerebral artery velocity (MCAv), cerebrovascular reactivity and resistance, and global cerebral blood flow, as assessed by transcranial Doppler (TCD) or magnetic resonance imaging (MRI). Aim 2 (Exercise Training Review) determines the effect of exercise training on cerebrovascular outcomes. Systematic review of studies with meta-analyses where appropriate. Certainty of evidence was assessed by the Grading of Recommendations Assessment, Development, and Evaluation (GRADE). Twenty studies (18 using TCD) met the eligibility criteria for Aim 1, and 14 studies (8 by TCD) were included for Aim 2. There was a significant effect of higher CRF compared with lower CRF on cerebrovascular resistance (effect size = -0.54, 95% confidence interval = -0.91 to -0.16) and cerebrovascular reactivity (0.98, 0.41-1.55). Studies including males only demonstrated a greater effect of higher CRF on cerebrovascular resistance than mixed or female studies (male only: -0.69, -1.06 to -0.32; mixed and female studies: 0.10, -0.28 to 0.49). Exercise training did not increase MCAv (0.05, -0.21 to 0.31) but showed a small nonsignificant improvement in cerebrovascular reactivity (0.60, -0.08 to 1.28; P = 0.09). Exercise training showed heterogeneous effects on regional but little effect on global cerebral blood flow as measured by MRI. High CRF positively effects cerebrovascular function, including decreased cerebrovascular resistance and increased cerebrovascular reactivity; however, global cerebral blood flow and MCAv are primarily unchanged following an exercise intervention in healthy and clinical populations.NEW & NOTEWORTHY Higher cardiorespiratory fitness is associated with lower cerebrovascular resistance and elevated cerebrovascular reactivity at rest. Only adults with a true-high fitness based on normative data exhibited elevated middle cerebral artery velocity. The positive effect of higher compared with lower cardiorespiratory fitness on resting cerebrovascular resistance was more evident in male-only studies when compared with mixed or female-only studies. A period of exercise training resulted in negligible changes in middle cerebral artery velocity and global cerebral blood flow, with potential for improvements in cerebrovascular reactivity.

Trajectories and determinants of weight gain in two cohorts of young adult women born 16 years apart.

BACKGROUND: The aims were to compare: (1) baseline weights and weight gain trajectories; (2) sociodemographic, behavioural and health characteristics driving weight gain; and (3) estimated average weight in 20 years' time, in two cohorts of young women. METHODS: Data were from 16066 participants in two population-based cohorts of young adult women, born in 1973-78 ("GenX") and 1989-95 ("millennials"). Weight was reported at baseline (age 18-23 in both cohorts) and 4 years later. High weight gain was defined as >2.5% per year. Data were analysed in 2020. RESULTS: Women born in 1989-95 were almost 4 kg heavier at age 18-23 and gained weight over 4 years 1.7 times faster than those born in 1973-78. Prevalence of high weight gain was 34.2% in the 1989-95 cohort and 24% in the 1973-78 cohort. In both cohorts, older age, higher education and high physical activity were associated with lower odds of high weight gain, and more hours in paid work, poorer self-rated health and higher baseline BMI were associated with higher odds of high weight gain. Five factors (outer regional areas, one child, ex or current smoker, high stress and depression) were determinants of high weight gain in the 1989-95 cohort, but not in the 1973-78 cohort. Based on average weight at age 21 and annual percentage weight gain, we estimate that women born in 1989-95 will, on average, be 16.7 kg heavier at age 41 (93.2 kg), than women in the 1973-78 cohort (76.5 kg). CONCLUSION: High weight gain was evident in every sociodemographic group in both cohorts but most evident in millennial women with high levels of stress and depression. Without effective weight gain prevention strategies we estimate that more than 50% of the millennial women will be in the obese BMI category in 20 years. This will have serious economic, health and societal consequences.

Prospective associations between physical activity and BMI with irregular periods and heavy menstrual bleeding in a large cohort of Australian women.

STUDY QUESTION: Are physical activity (PA) and body mass index (BMI) associated with irregular periods and heavy menstrual bleeding (HMB) in Australian women? SUMMARY ANSWER: Overweight and obese women have higher odds of both irregular periods and HMB than underweight/normal-weight women, but high levels of PA reduce the odds of HMB. WHAT IS KNOWN ALREADY: Most studies on relationships between PA and menstrual problems have focused on female athletes, but there have been few population-based studies. STUDY DESIGN, SIZE, DURATION: Prospective cohort study, 10618 participants in the Australian Longitudinal Study of Women's Health (ALSWH) who completed mailed surveys in 1996, with follow-ups in 2000, 2003, 2006, 2009, 2012, and 2015. PARTICIPANTS/MATERIALS, SETTING, METHODS: Participants were aged 22 to 27 in 2000. They were asked to report their PA levels and the frequency of irregular periods and HMB in each survey. BMI was calculated at every survey from self-reported weight and height. Generalised estimating equation population-averaged model analyses were conducted to calculate odds ratios (OR) and 95% confidence intervals (95% CIs). MAIN RESULTS AND THE ROLE OF CHANCE: At age 22 to 27 years, the prevalence of irregular periods was 19.4%. This remained stable over 15 years. There were no associations between PA and irregular periods. Overweight and obese women had higher odds of irregular periods [overweight: OR 1.08, (95% CI 1.00-1.17); obese: OR 1.29, (95%CI 1.18-1.41)] than women who were underweight/normal weight.The prevalence of HMB at age 22-27 years was 15.9%; this doubled over 15 years. Women who were highly active had 10% lower odds of HMB than women who reported no PA [OR 0.90, (95%CI 0.82-0.98)]. Overweight and obese women had higher odds of HMB [overweight: OR 1.15, (95%CI 1.07-1.23); obese: OR 1.37, (95%CI 1.26-1.49)] than women who were underweight/normal weight. Among obese women, high levels of PA were associated with 19% [OR 0.81, (95%CI 0.68-0.97)] reduction in the odds of HMB. LIMITATIONS, REASONS FOR CAUTION: Data collected in the ALSWH are self-reported, which may be subject to recall bias. Reverse causation, due to menstrual problems impacting PA, is possible although sensitivity analyses suggest this is unlikely to have affected the results. Other conditions, e.g., polycystic ovary syndrome, for which no or incomplete data were available, could have affected the results. WIDER IMPLICATIONS OF THE FINDINGS: Intervention studies are needed to assess the effect of increasing PA in women with HMB, but these preliminary findings suggest that promoting PA could be an affordable and feasible strategy for reducing HMB in young adult women. STUDY FUNDING/COMPETING INTEREST(S): The ALSWH is funded by the Australian Government. Funding for these analyses was provided by a University of Queensland (UQ) International Postgraduate Research Scholarship and a UQ International Development Fellowship. The authors declare no conflicts of interest. TRIAL REGISTRATION NUMBER: N/A.

Urinary incontinence, body mass index, and physical activity in young women.

BACKGROUND: Current evidence suggests that excess weight and obesity are important risk factors for urinary incontinence in women. However, limited data exist regarding the relationships among body mass index, physical activity, and urinary incontinence in women in their 20s. OBJECTIVE: This study aimed to (1) compare prevalence rates of urinary incontinence and high body mass index in 2 cohorts of young women, (2) explore associations between changes in body mass index and urinary incontinence using analysis of combined data from the 2 cohorts, and (3) explore the associations between physical activity and urinary incontinence, with adjustment for body mass index. STUDY DESIGN: Data were collected from 2 cohorts of young women in the Australian Longitudinal Study of Women's Health (n=16,065), born 17 years apart: 1973-1978 (cohort 1) and 1989-1995 (cohort 2). The women in both cohorts completed the surveys at age 18 to 23 years (T1), with follow-up 4 years later (age, 22-27 years; T2). Self-reported urinary incontinence and body mass index were assessed in both surveys. As physical activity was measured using different questions in cohort 1 at T1, self-reported physical activity data were from T2 only. A total of 9 body mass index transition categories (based on body mass index status at baseline and follow-up) and 4 physical activity categories were created to assess multivariate-adjusted prevalence ratios for urinary incontinence at T2, using Poisson regression. RESULTS: Rates of obesity increased in both cohorts over 4 years, from 6.6%% (95% confidence interval, 6.1-7.2) to 10.4% (95% confidence interval, 9.7-11.0) in cohort 1 and from 11.7% (95% confidence interval, 11.0-12.4) to 19.6% (95% confidence interval, 18.7-20.5) in cohort 2. Compared with women who maintained normal body mass index at T1 and T2, the prevalence ratio for urinary incontinence among those with body mass index >30 at age 22 to 27 years was higher, regardless of body mass index category at age 18 to 23 years (prevalence ratio at T1: 1.39 for normal body mass index [95% confidence interval, 1.1-1.76]; 1.44 for overweight [95% confidence interval, 1.27-1.63]; and 1.51 for obese [95% confidence interval, 1.36-1.67]). In cohort 1, there was no relationship between physical activity and urinary incontinence. However, in cohort 2 there was an inverse dose-response relationship between physical activity and urinary incontinence. CONCLUSION: The strong association between obesity and urinary incontinence in young women is a public health concern, given that obesity rates are likely to increase further with age and parity. The potential mitigating effects of physical activity on the obesity-incontinence relationship merit further investigation.

Associations between indicators of energy intake and expenditure with excess weight and obesity among women in sedentary and less-sedentary jobs.

The aim of this study was to compare the associations between indicators of energy intake and expenditure with excess weight and obesity in women who work full-time in sedentary and less sedentary jobs. Data were from 3444 participants the Australian Longitudinal Study on Women's Health, who reported their weight, dietary intake, physical activity and occupation in 2009 (baseline), and weight in 2012 (follow-up). Participants were categorised as being in a 'less sedentary' or 'sedentary' job, based on occupational activity patterns. Odds of excess weight (BMI ≥ 25) at baseline and of being obese (BMI ≥ 30) at follow-up, by indicators of energy intake and expenditure, were compared in the two occupational groups. In multivariate analyses, high non-work sitting time and saturated fat intake were associated with increased odds of obesity at 3-year follow-up in both occupational groups. In the sedentary job group, high physical activity (in leisure and transport) was associated with a 51% reduction in odds of obesity (OR 0.49, 95%CI 0.25-0.97). In the less-sedentary job group, energy intake and high soft drink consumption were associated with markedly increased odds of obesity (OR 1.67 95%CI 1.07-2.61; OR 2.08 95%CI1.42-3.05, respectively). In this cohort of young Australian women, sedentariness at work did not markedly affect the prevalence of excess weight or obesity. Indicators of high energy intake and low energy expenditure were associated with increased odds of both excess weight and obesity, regardless of sedentariness of occupational group.

VO2peak and 24-hour sleep, sedentary behavior, and physical activity in Australian truck drivers.

This study assessed cardiorespiratory fitness (CRF) and 24-h sleep, sedentary behavior (SB), and physical activity (PA) in Australian truck drivers. Participants (n = 37 men) attended clinic sessions for an exercise test to exhaustion to establish CRF and wore an accelerometer (Actigraph GT3X+) to estimate sleep, SB, and PA. Relative to normative values, CRF was "below percentile 25" in 51% of drivers (mean [SD] VO2peak=30 .1 [7.6] mL.kg-1.min-1). Accelerometer data indicated that total vigorous-intensity (3.5-4.5 min/day) and sustained moderate- to vigorous-intensity PA (>5 min; 0.5-1.6 bouts/day) were limited. The findings show there is a need to design and test PA interventions that can improve poor levels of CRF in truck drivers.

Do physical activity, sitting time and body mass index affect fertility over a 15-year period in women? Data from a large population-based cohort study.

STUDY QUESTION: Do physical activity (PA), sitting time (ST) and body mass index (BMI) affect fertility over a 15-year period in Australian women? SUMMARY ANSWER: Moderate and high levels of PA confer advantages for fertility in women with normal BMI, but increased risk of infertility was observed in obese women. WHAT IS KNOWN ALREADY: Higher BMI is positively associated with higher rates of problems with fertility, but the effects of physical activity and sitting time on fertility are less well understood. STUDY DESIGN, SIZE, DURATION: Participants in The Australian Longitudinal Study of Women's Health (ALSWH) completed mailed surveys in 2000, with follow-ups in 2003, 2006, 2009, 2012 and 2015 (N = 6130). PARTICIPANTS/MATERIALS, SETTING, METHODS: Participants were aged 22 to 27 in 2000. They were asked to report their physical activity levels, sitting time and fertility problems in each survey from 2000 to 2015. BMI was calculated from self-reported weight and height. Cumulative incidence of fertility problems was calculated from 2000 to 2015 and hazard ratios (HR) and 95% CIs were calculated using survival analysis. MAIN RESULTS AND THE ROLE OF CHANCE: From 2000 to 2015, the cumulative incidence of fertility problems was 15.4% (95% CI: 14.5-16.4). High levels of PA were associated with reduced risk of problems with fertility [HR 0.82 (95% CI: 0.69-0.98)], and higher BMI was positively associated with fertility problems [overweight: HR 1.18, (95% CI 0.99-1.39); obese: HR 1.36, (95% CI 1.14-1.63)]. In survival analyses, incidence rates were highest in every survey interval in women who reported low PA levels and in women who were obese. Overall, ST was not associated with fertility problems. In stratified models, high levels of PA attenuated the risk of problems with fertility in women who were in the normal BMI category [HR 0.64, (95% CI 0.49-0.82)]. LIMITATIONS, REASONS FOR CAUTION: The ALSWH relies on self-reported data, which may be subject to recall bias. WIDER IMPLICATIONS OF THE FINDINGS: The study provides estimates of problems with fertility in a cohort of young adult Australian women, and the results indicate that these are inversely associated with physical activity levels and positively associated with BMI. However, the high infertility risk in obese women was not attenuated by high levels of PA. The protective effects of PA were only observed in women with normal BMI. As rates of developing problems with fertility were highest in every survey interval among women who reported low levels of physical activity and in women who were obese, these findings suggest that improving physical activity levels could be an affordable strategy to reduce problems with fertility in women who are trying to conceive. These findings should be considered by clinical and public health practitioners. STUDY FUNDING/COMPETING INTEREST(S): The ALSWH is funded by the Australian Government. Funding for these analyses was provided by a University of Queensland (UQ) International Postgraduate Research Scholarship and a UQ International Development Fellowship. The authors declare no conflicts of interest.

Twelve year trajectories of physical activity and health costs in mid-age Australian women.

BACKGROUND: Few studies have examined relationships between physical activity (PA) during mid-age and health costs in women. The aim of this study was to investigate associations between PA levels and trajectories over 12 years with medical and pharmaceutical costs in mid-age Australian women. METHODS: Data from 6953 participants in the Australian Longitudinal Study on Women's Health (born in 1946-1951) were analysed in 2019. PA was self-reported in 2001 (50-55y), 2007 (56-61y) and 2013 (62-67y). PA data were linked with 2013-2015 data from the Medicare (MBS) and Pharmaceutical (PBS) Benefits Schemes. Quantile regression was used to examine associations between PA patterns [always active, increasers, decreasers, fluctuaters or always inactive (reference)] with these medical and pharmaceutical costs. RESULTS: Among women who were consistently inactive (< 500 MET.minutes/week) in 2001, 2007 and 2013, median MBS and PBS costs (2013 to 2015) were AUD4261 and AUD1850, respectively. Those costs were AUD1728 (95%CI: 443-3013) and AUD578 (95%CI: 426-729) lower among women who were consistently active in 2001, 2007 and 2013 than among those who were always inactive. PBS costs were also lower in women who were active at only one survey (AUD205; 95%CI: 49-360), and in those whose PA increased between 2001 and 2013 (AUD388; 95%CI: 232-545). CONCLUSION: Maintaining 'active' PA status was associated with 40% lower MBS and 30% lower PBS costs over three years in Australian women. Helping women to remain active in mid-life could result in considerable savings for both women and the Australian government.