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.

Trajectories of physical activity from mid to older age in women: 21 years of data from the Australian Longitudinal Study on Women's Health.

BACKGROUND: Women's physical activity varies across the adult lifespan. However, changes in physical activity among mid-aged women are not well understood. We analysed 21 years of data from women born in 1946-51 to identify: (1) trajectories of physical activity in the transition from mid- to old-age and (2) determinants of different physical activity trajectories. METHODS: Data were from the 1946-51 cohort of the Australian Longitudinal Study on Women's Health (N = 10,371). Surveys were mailed at three-year intervals from 1998 (age 47-52) to 2019 (age 68-73) to collect data on physical activity, sociodemographic factors (country of birth, area of residence, educational attainment, marital status, income management, paid work hours, living with children age < 18, providing care), health indicators (menopause status, BMI, physical and mental health, chronic conditions), and health behaviours (smoking, alcohol status). Group-based trajectory modelling was used to identify trajectories of physical activity. Multinomial logistic regression models were used to examine the determinants of physical activity trajectories. RESULTS: Five trajectories were identified: Low-stable (13.3% of participants), Moderate-stable (50.4%), Moderate-increasing (22.2%), High-declining (7.7%), and High-stable (6.6%). Sociodemographic characteristics (area of residence, education, income management, living with children, and providing care) were determinants of physical activity trajectories, but the strongest factors were BMI, physical and mental health. Women who were overweight/obese and had poor physical and mental health were less likely to be in the High-stable group than in any other group. Changes in these variables (increasing BMI, and declining physical and mental health) and in marital status (getting married) were positively associated with being in trajectories other than the High-stable group. CONCLUSIONS: Although most women maintained physical activity at or above current guidelines, very low physical activity levels in the Low-stable group, and declining levels in the High-declining group are concerning. The data suggest that physical activity promotion strategies could be targeted to these groups, which are characterised by socioeconomic disadvantage, high (and increasing) BMI, and poor (and worsening) physical and mental health. Removing barriers to physical activity in these women, and increasing opportunities for activity, may reduce chronic disease risk in older age.

Participation in Sports/Recreational Activities and the Occurrence of Psychological Distress in Mid-Aged Adults: Findings From the HABITAT Cohort Study.

OBJECTIVES: The aim of this study was to investigate prospective associations between participation in sports/recreational activities and the occurrence of moderate-to-severe psychological distress over 2 years in a sample of mid-aged Australians. METHODS: This prospective study used data from 6699 adults aged 40+ years, living in Brisbane in 2007, and surveyed in 2009, 2011 and 2013. Participants provided self-reported data on frequency of participation in each of 11 sports/recreational activities in past 12 months and completed the Kessler Psychological Distress 6-item Scale (K6). Generalized estimating equation (GEE) models with a 2-year lag were used to assess the associations of participation in sports/recreational activities in 2009 and 2011 with new cases of moderate-to-severe psychological distress (K6 score ≥ 5) in 2011 and 2013. RESULTS: From 2009 to 2013, 22.4% of participants without moderate-to-severe psychological distress at baseline (N = 4943) developed this outcome in at least one survey. Overall, there were no clear patterns of association between frequency of participation in sports and recreational activities and occurrence of moderate-to-severe psychological distress. In unadjusted models, weekly participation in some activities (e.g., tennis, golf, and exercise classes) was associated with reduced odds of moderate-to-severe psychological distress over the next 2 years, but these associations were attenuated in most adjusted models with sociodemographic, lifestyle, and health covariates. Participation in home-based exercise and running/jogging were associated with higher odds of psychological distress. CONCLUSION: Our findings do not provide strong evidence of beneficial associations of frequency of sport/recreational activities with psychological distress but show surprising negative associations of home-based exercise and running/jogging with occurrence of moderate-to-severe psychological distress over 2 years.

Parity, mode of birth, and long-term gynecological health: A follow-up study of parous and nonparous women in the Australian Longitudinal Study on Women's Health cohort.

BACKGROUND: Although gynecological health issues are common and cause considerable distress, little is known about their causes. We examined how birth history is associated with urinary incontinence (UI), severe period pain, heavy periods, and endometriosis. METHODS: We studied 7700 women in the Australian Longitudinal Study on Women's Health with an average follow-up of 10.9 years after their last birth. Surveys every third year provided information about birth history and gynecological health. Logistic regression was used to estimate how parity, mode of birth, and vaginal tears were associated with gynecological health issues. Presented results are adjusted odds ratios (OR) with 95% confidence intervals. RESULTS: UI was reported by 16%, heavy periods by 31%, severe period pain by 28%, and endometriosis by 4%. Compared with women with two children, nonparous women had less UI (OR 0.35 [0.26-0.47]) but tended to have more endometriosis (OR 1.70 [0.97-2.96]). Also, women with only one child had less UI (OR 0.77 [0.61-0.98]), but more severe period pain (OR 1.24 [1.01-1.51]). Women with 4+ children had more heavy periods (OR 1.42 [1.07-1.88]). Compared with women with vaginal birth(s) only, women with only cesarean sections or vaginal birth after cesarean section had less UI (ORs 0.44 [0.34-0.58] and 0.55 [0.40-0.76]), but more endometriosis (ORs 1.91 [1.16-3.16] and 2.31 [1.25-4.28]) and heavy periods (ORs 1.21 [1.00-1.46] and 1.35 [1.06-1.72]). Vaginal tear(s) did not increase UI after accounting for parity and birth mode. CONCLUSION: While women with vaginal childbirth(s) reported more urinary incontinence, they had less menstrual complaints and endometriosis.

High intensity and sprint interval training, and work-related cognitive function in adults: A systematic review.

OBJECTIVES: To assess evidence on the impact of acute and chronic high intensity interval training (HIIT) and sprint interval training (SIT) on work-related performance tests of cognitive function in adults. METHODS: The databases PubMed, CINAHL, Scopus, PsycINFO, Embase, and the Cochrane Library were searched for relevant articles up to August 2022. Eligible studies assessed the effects of HIIT (70%-100% VO2max ) and/or SIT (≥100% VO2max ) on cognitive function test scores in cognitively healthy adults, relative to a control or comparative exercise group/condition. Data on participant characteristics, exercise protocol, key outcomes, and intervention setting were extracted. Study quality was assessed using a 9 (single session HIIT/SIT) and 14 (multiple session HIIT/SIT) item checklist. RESULTS: Thirty-six studies (15 countries; n = 11-945 participants) met inclusion criteria. Mean quality scores were "fair-to-good" for acute (single session; mean = 6.9 [SD 1.0]) and chronic (multiple session; mean = 9.8 [SD 1.6]) training studies. Eighteen from 36 studies (12/20 [55%] acute and 6/16 [38%] chronic training studies) evidenced significant improvements in aspects of cognitive function related to work performance (i.e., attention, inhibition, memory, information processing speed, cognitive flexibility, intelligence, reaction time, and learning). Only four studies tested the impact of HIIT/SIT on cognitive function in a work-based setting (e.g., the office or home). CONCLUSIONS: While there is promising evidence, particularly from acute training studies, to indicate that high intensity, short duration exercise benefits cognitive function in adults, there is very limited evidence of application in workplace contexts. To better understand the potential benefits to employee performance and safety, HIIT/SIT and cognitive function research needs to transition from laboratory to "in-situ" occupational settings.

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.

Association between the use of weight management strategies and weight change among Australian adults over 12 months: an observational study.

BACKGROUND: Obesity is a growing, global public health issue. This study aimed to describe the weight management strategies used by a sample of Australian adults; examine the socio-demographic characteristics of using each strategy; and examine whether use of each strategy was associated with 12-month weight change. METHODS: This observational study involved a community-based sample of 375 healthy adults (mean age: 40.1 ± 5.8 years, 56.8% female). Participants wore a Fitbit activity monitor, weighed themselves daily, and completed eight online surveys on socio-demographic characteristics. Participants also recalled their use of weight management strategies over the past month, at 8 timepoints during the 12-month study period. RESULTS: Most participants (81%) reported using at least one weight management strategy, with exercise/physical activity being the most common strategy at each timepoint (40-54%). Those who accepted their current bodyweight were less likely to use at least one weight management strategy (Odds ratio = 0.38, 95% CI = 0.22-0.64, p < 0.01) and those who reported being physically active for weight maintenance had a greater reduction in bodyweight, than those who did not (between group difference: -1.2 kg, p < 0.01). The use of supplements and fasting were associated with poorer mental health and quality of life outcomes (p < 0.01). CONCLUSIONS: The use of weight management strategies appears to be common. Being physically active was associated with greater weight loss. Individuals who accepted their current body weight were less likely to use weight management strategies. Fasting and the use of supplements were associated with poorer mental health. Promoting physical activity as a weight management strategy appears important, particularly considering its multiple health benefits.

Public health guidelines for physical activity during pregnancy from around the world: a scoping review.

BACKGROUND AND OBJECTIVE: Despite the known health benefits of physical activity (PA), pregnancy is a time of marked decline in PA levels. To provide women with reliable and trustworthy information, and to encourage greater participation in PA during pregnancy, many governments have developed guidelines for PA during pregnancy. Our aim was to synthesise the most recent public health guidelines on PA during pregnancy from different countries in order to understand the nature and extent of advice that is available. DESIGN: Scoping review. DATA SOURCES: Search of the grey literature, direct contact with international experts, screening of relevant academic literature and citation searching. ELIGIBILITY CRITERIA: Public health guidelines developed or endorsed by government departments published since 2010. RESULTS: Our search located 30 eligible guidelines, published in 11 different languages. There is remarkable concordance in the advice offered. For women with uncomplicated pregnancy, guidelines recommend: 150-300 min/week of moderate intensity aerobic activity; pelvic floor and muscle strengthening exercises; modification of some exercises (eg, supine position); and provide lists of warning signs to cease activity (eg, persistent dizziness, vaginal bleeding) and activities that should be avoided (eg, if high risk of falling/collision). Few guidelines offer specific advice for highly active women (eg, athletes), or trimester-specific or culturally specific considerations. CONCLUSIONS: This review provides a summary of public health recommendations for PA during pregnancy around the world. The challenge is now to ensure that all who provide healthcare for women understand the guidelines and encourage safe participation in PA during pregnancy.

Female athlete health domains: a supplement to the International Olympic Committee consensus statement on methods for recording and reporting epidemiological data on injury and illness in sport.

The IOC made recommendations for recording and reporting epidemiological data on injuries and illness in sports in 2020, but with little, if any, focus on female athletes. Therefore, the aims of this supplement to the IOC consensus statement are to (i) propose a taxonomy for categorisation of female athlete health problems across the lifespan; (ii) make recommendations for data capture to inform consistent recording and reporting of symptoms, injuries, illnesses and other health outcomes in sports injury epidemiology and (iii) make recommendations for specifications when applying the Strengthening the Reporting of Observational Studies in Epidemiology-Sport Injury and Illness Surveillance (STROBE-SIIS) to female athlete health data.In May 2021, five researchers and clinicians with expertise in sports medicine, epidemiology and female athlete health convened to form a consensus working group, which identified key themes. Twenty additional experts were invited and an iterative process involving all authors was then used to extend the IOC consensus statement, to include issues which affect female athletes.Ten domains of female health for categorising health problems according to biological, life stage or environmental factors that affect females in sport were identified: menstrual and gynaecological health; preconception and assisted reproduction; pregnancy; postpartum; menopause; breast health; pelvic floor health; breast feeding, parenting and caregiving; mental health and sport environments.This paper extends the IOC consensus statement to include 10 domains of female health, which may affect female athletes across the lifespan, from adolescence through young adulthood, to mid-age and older age. Our recommendations for data capture relating to female athlete population characteristics, and injuries, illnesses and other health consequences, will improve the quality of epidemiological studies, to inform better injury and illness prevention strategies.

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.

Accelerometer-measured physical activity in mid-age Australian adults.

BACKGROUND: Raw data from accelerometers can provide valuable insights into specific attributes of physical activity, such as time spent in intensity-specific activity. The aim of this study was to describe physical activity assessed with raw data from triaxial wrist-worn accelerometers in mid-age Australian adults. METHODS: Data were from 700 mid-age adults living in Brisbane, Australia (mean age: 60.4; SD:7.1 years). Data from a non-dominant wrist worn triaxial accelerometer (Actigraph wGT3X-BT), expressed as acceleration in gravitational equivalent units (1 mg = 0.001 g), were used to estimate time spent in moderate-vigorous intensity physical activity (MVPA; >100 mg) using different bout criteria (non-bouted, 1-, 5-, and 10-min bouts), and the proportion of participants who spent an average of at least one minute per day in vigorous physical activity. RESULTS: Mean acceleration was 23.2 mg (SD: 7.5) and did not vary by gender (men: 22.4; women: 23.7; p-value: 0.073) or education (p-value: 0.375). On average, mean acceleration was 10% (2.5 mg) lower per decade of age from age 55y. The median durations in non-bouted, 1-min, 5-min and 10-min MVPA bouts were, respectively, 68 (25th -75th : 45-99), 26 (25th -75th : 12-46), 10 (25th -75th : 3-24) and 8 (25th -75th : 0-19) min/day. Around one third of the sample did at least one minute per day in vigorous intensity activities. CONCLUSION: This population-based cohort provided a detailed description of physical activity based on raw data from accelerometers in mid-age adults in Australia. Such data can be used to investigate how different patterns and intensities of physical activity vary across the day/week and influence health outcomes.

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.

Weight gain and lifestyle factors in women with and without polycystic ovary syndrome.

STUDY QUESTION: Do extrinsic factors including lifestyle, psychosocial factors and healthcare professional engagement independently contribute to weight gain in women with and without polycystic ovary syndrome (PCOS)? SUMMARY ANSWER: Women with PCOS had a higher rate of weight gain than women without PCOS which was most marked in those with unhealthy lifestyles. WHAT IS KNOWN ALREADY: Women with PCOS have a higher prevalence of overweight/obesity and greater weight gain than women without PCOS. The association of lifestyle factors with weight change in PCOS is not known. STUDY DESIGN, SIZE, DURATION: The study was a population-based observational study with data collected from seven surveys over 19 years (N = 14 127; Survey 1) involving women with and without PCOS. PARTICIPANTS/MATERIALS, SETTING, METHODS: We used data from the 1973-1978 birth cohort of the Australian Longitudinal Study on Women's Health. MAIN RESULTS AND THE ROLE OF CHANCE: Women with PCOS gained more weight annually (0.26 kg/year; 95% CI 0.12, 0.39; P < 0.0001) and over 19 years (4.62 kg; 95% CI 3.04, 6.21; P < 0.0001) than women without PCOS (adjusted analyses). For all women, there were positive associations between weight gain and energy intake, sitting time and stress; inverse associations with fibre intake and physical activity (PA); and no associations with diet quality, glycaemic index, healthcare utilization, depression or anxiety. There were interactions between lifestyle factors (energy intake P = 0.006, glycaemic index P = 0.025, sitting time P = 0.041 and PA P = 0.021), PCOS status and time such that weight gain varied between women with and without PCOS according to these factors. LIMITATIONS, REASONS FOR CAUTION: The limitations of this study include the use of self-reported measures such as diet, PA, sitting time, psychological factors and health care utilization. WIDER IMPLICATIONS OF THE FINDINGS: While women with PCOS are more prone to weight gain, lifestyle factors have a more profound impact on weight gain in women with PCOS than without PCOS. These study findings have implications for understanding the mechanisms of weight gain in women with PCOS. They also highlight the importance of early lifestyle intervention as soon as PCOS is diagnosed to address modifiable extrinsic factors and prevent excess weight gain and worsening of the clinical features of PCOS. STUDY FUNDING/COMPETING INTEREST(S): M.A.A. is funded by the Monash International Tuition Scholarship and Monash Graduate Scholarship and L.J.M. is funded by a National Heart Foundation Future Leader Fellowship. The authors declared no conflict 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.

Effect of a physical activity and sleep m-health intervention on a composite activity-sleep behaviour score and mental health: a mediation analysis of two randomised controlled trials.

BACKGROUND: To examine if a composite activity-sleep behaviour index (ASI) mediates the effects of a combined physical activity and sleep intervention on symptoms of depression, anxiety, or stress, quality of life (QOL), energy and fatigue in adults. METHODS: This analysis used data pooled from two studies: Synergy and Refresh. Synergy: Physically inactive adults (18-65 years) who reported poor sleep quality were recruited for a two-arm Randomised Controlled Trial (RCT) (Physical Activity and Sleep Health (PAS; n = 80), or Wait-list Control (CON; n = 80) groups). Refresh: Physically inactive adults (40-65 years) who reported poor sleep quality were recruited for a three-arm RCT (PAS (n = 110), Sleep Health-Only (SO; n = 110) or CON (n = 55) groups). The SO group was omitted from this study. The PAS groups received a pedometer, and accessed a smartphone/tablet "app" using behaviour change strategies (e.g., self-monitoring, goal setting, action planning), with additional email/SMS support. The ASI score comprised self-reported moderate-to-vigorous-intensity physical activity, resistance training, sitting time, sleep duration, efficiency, quality and timing. Outcomes were assessed using DASS-21 (depression, anxiety, stress), SF-12 (QOL-physical, QOL-mental) and SF-36 (Energy & Fatigue). Assessments were conducted at baseline, 3 months (primary time-point), and 6 months. Mediation effects were examined using Structural Equation Modelling and the product of coefficients approach (AB), with significance set at 0.05. RESULTS: At 3 months there were no direct intervention effects on mental health, QOL or energy and fatigue (all p > 0.05), and the intervention significantly improved the ASI (all p < 0.05). A more favourable ASI score was associated with improved symptoms of depression, anxiety, stress, QOL-mental and of energy and fatigue (all p < 0.05). The intervention effects on symptoms of depression ([AB; 95%CI] -0.31; - 0.60,-0.11), anxiety (- 0.11; - 0.27,-0.01), stress (- 0.37; - 0.65,-0.174), QOL-mental (0.53; 0.22, 1.01) and ratings of energy and fatigue (0.85; 0.33, 1.63) were mediated by ASI. At 6 months the magnitude of association was larger although the overall pattern of results remained similar. CONCLUSIONS: Improvements in the overall physical activity and sleep behaviours of adults partially mediated the intervention effects on mental health and quality of life outcomes. This highlights the potential benefit of improving the overall pattern of physical activity and sleep on these outcomes. TRIAL REGISTRATION: Australian New Zealand Clinical Trial Registry: ACTRN12617000680369 ; ACTRN12617000376347 . Universal Trial number: U1111-1194-2680; U1111-1186-6588. Human Research Ethics Committee Approval: H-2016-0267; H-2016-0181.

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.

Annual rhythms in adults' lifestyle and health (ARIA): protocol for a 12-month longitudinal study examining temporal patterns in weight, activity, diet, and wellbeing in Australian adults.

BACKGROUND: Almost one in three Australian adults are now obese, and the rate continues to rise. The causes of obesity are multifaceted and include environmental, cultural and lifestyle factors. Emerging evidence suggests there may be temporal patterns in weight gain related, for example, to season and major festivals such as Christmas, potentially due to changes in diet, daily activity patterns or both. The aim of this study is to track the annual rhythm in body weight, 24 h activity patterns, dietary patterns, and wellbeing in a cohort of Australian adults. In addition, through data linkage with a concurrent children's cohort study, we aim to examine whether changes in children's body mass index, activity and diet are related to those of their parents. METHODS: A community-based sample of 375 parents aged 18 to 65 years old, residing in or near Adelaide, Australia, and who have access to a Bluetooth-enabled mobile device or a computer and home internet, will be recruited. Across a full year, daily activities (minutes of moderate to vigorous physical activity, light physical activity, sedentary behaviour and sleep) will be measured using wrist-worn accelerometry (Fitbit Charge 3). Body weight will be measured daily using Fitbit wifi scales. Self-reported dietary intake (Dietary Questionnaire for Epidemiological Studies V3.2), and psychological wellbeing (WHOQOL-BREF and DASS-21) will be assessed eight times throughout the 12-month period. Annual patterns in weight will be examined using Lowess curves. Associations between changes in weight and changes in activity and diet compositions will be examined using repeated measures multi-level models. The associations between parent's and children's weight, activity and diet will be investigated using multi-level models. DISCUSSION: Temporal factors, such as day type (weekday or weekend day), cultural celebrations and season, may play a key role in weight gain. The aim is to identify critical opportunities for intervention to assist the prevention of weight gain. Family-based interventions may be an important intervention strategy. TRIAL REGISTRATION: Australia New Zealand Clinical Trials Registry, identifier ACTRN12619001430123 . Prospectively registered on 16 October 2019.

Association between clusters of back and joint pain with opioid use in middle-aged community-based women: a prospective cohort study.

BACKGROUND: To determine the relationship between clusters of back pain and joint pain and prescription opioid dispensing. METHODS: Of 11,221 middle-aged participants from the Australian Longitudinal Study of Women's Health, clusters of back pain and joint pain from 2001 to 2013 were identified using group-based trajectory modelling. Prescription opioid dispensing from 2003 to 2015 was identified by linking the cohort to Pharmaceutical Benefit Scheme dispensing data. Multinomial logistic regression was used to examine the association between back pain and joint pain clusters and dispensing of prescription opioids. The proportion of opioids dispensed in the population attributable to back and join pain was calculated. RESULTS: Over 12 years, 68.5 and 72.0% women reported frequent or persistent back pain and joint pain, respectively. There were three clusters ('none or infrequent', 'frequent' and 'persistent') for both back pain and joint pain. Those in the persistent back pain cluster had a 6.33 (95%CI 4.38-9.16) times increased risk of having > 50 opioid prescriptions and those in persistent joint pain cluster had a 6.19 (95%CI 4.18-9.16) times increased risk of having > 50 opioid prescriptions. Frequent and persistent back and joint pain clusters together explained 41.7% (95%CI 34.9-47.8%) of prescription opioid dispensing. Women in the frequent and persistent back pain and joint pain clusters were less educated and reported more depression and physical inactivity. CONCLUSION: Back pain and joint pain are major contributors to opioid prescription dispensing in community-based middle-aged women. Additional approaches to reduce opioid use, targeted at those with frequent and persistent back pain and joint pain, will be important in order to reduce the use of opioids and their consequent harm in this population.