24-hour movement behaviours and cardiometabolic markers in women with polycystic ovary syndrome (PCOS): a compositional data analysis.
Are 24-h movement composition and time reallocations between the movement behaviours (moderate-to-vigorous physical activity (MVPA), light physical activity (LPA), sedentary behaviour (SB), and sleep) differentially associated with cardiometabolic markers in women with polycystic ovary syndrome (PCOS) relative to women without PCOS?
There was no difference in 24-h movement composition between the groups, although among women without PCOS, reducing SB time while increasing either MVPA or LPA time was associated with beneficial differences in cardiometabolic markers, whereas in women with PCOS beneficial differences were observed only when SB time was replaced with MVPA.
Women with PCOS display lower levels of physical activity, higher sedentary time, and less total sleep than women without the syndrome. Exercise interventions among women with PCOS have shown improvements in body composition and insulin sensitivity, while the findings regarding blood pressure, insulin resistance, and lipid profiles are contradictory.
This study was part of a prospective, general population-based Northern Finland Birth Cohort 1966 (NFBC1966) (n = 5889 women). At the 31-year and 46-year follow-up, data collection was performed through postal and clinical examinations, including fasting blood samples and anthropometric measurements. Accelerometer data collection of 14 days (n = 2602 women) and a 2-h oral glucose tolerance test (n = 2780 women) were performed at the 46-year follow-up. Participants were identified as women with or without PCOS at age 31 (n = 1883), and the final study population included those who provided valid accelerometer data at age 46 (n = 857).
Women with PCOS (n = 192) were identified based on the 2023 International Evidence-based Guideline, while those who exhibited no PCOS features were considered women without PCOS (controls; n = 665). Accelerometer-measured MVPA, LPA, and SB were combined with self-reported sleep to obtain 24-h compositions. Multivariable regression analysis based on compositional data analysis and isotemporal reallocations were performed to investigate the associations between 24-h movement composition and cardiometabolic markers. Isotemporal reallocations were expressed as differences (%Δ) from the sample's mean.
There was no difference in overall 24-h movement composition between women with PCOS and controls in midlife. The 24-h movement composition was associated with waist circumference, triglycerides, fasting serum insulin, and Homeostatic Model Assessment-insulin resistance (HOMA-IR) in both controls and women with PCOS. Reallocating 15 min from SB to MVPA was associated with favourable differences in cardiometabolic markers in both controls (%Δ range from -1.7 to -4.9) and women with PCOS (%Δ range from -1.9 to -8.6). Reallocating 15 min from SB to LPA was also associated with favourable differences in cardiometabolic markers among controls (%Δ range from -0.5 to -1.6) but not among women with PCOS.
The substitution technique used in this study is theoretical, which can be considered as a limitation. Other limitations of this study are the use of self-reported sleeping time and the difference in the group sample sizes.
These findings suggest that women with PCOS should be targeted with interventions involving physical activity of at least moderate intensity to improve their cardiometabolic health and underline the importance of developing tailored activity guidelines for women with PCOS.
This study was funded by the Jenny and Antti Wihuri Foundation, Sigrid Juselius Foundation, Novo Nordisk (NNF21OC0070372), Research Council of Finland (315921/2018, 321763/2019, 6GESS 336449), Ministry of Education and Culture of Finland (OKM/54/626/2019, OKM/85/626/2019, OKM/1096/626/2020, OKM/20/626/2022, OKM/76/626/2022, and OKM/68/626/2023), and Roche Diagnostics International Ltd. L.J.M. is supported by a Veski Fellowship. M.Nu. has received funding from Fibrobesity-project, a strategic profiling project at the University of Oulu, which is supported by Research Council of Finland (Profi6 336449). NFBC1966 follow-ups received financial support from University of Oulu (Grant no. 65354, 24000692), Oulu University Hospital (Grant no. 2/97, 8/97, 24301140), Ministry of Health and Social Affairs (Grant no. 23/251/97, 160/97, 190/97), National Institute for Health and Welfare, Helsinki (Grant no. 54121), Regional Institute of Occupational Health, Oulu, Finland (Grant no. 50621, 54231), and ERDF European Regional Development Fund (Grant no. 539/2010 A31592). T.T.P. declares consulting fees from Gedeon Richter, Organon, Astellas, Roche; speaker's fees from Gedeon Richter, Exeltis, Roche, Stragen, Merck, Organon; and travel support from Gedeon Richter. The remaining authors declare no conflicts of interest.
N/A.
Pesonen E
，Farrahi V
，Brakenridge CJ
，Ollila MM
，Morin-Papunen LC
，Nurkkala M
，Jämsä T
，Korpelainen R
，Moran LJ
，Piltonen TT
，Niemelä M
... -
《-》
The association between reallocations of time and health using compositional data analysis: a systematic scoping review with an interactive data exploration interface.
How time is allocated influences health. However, any increase in time allocated to one behaviour must be offset by a decrease in others. Recently, studies have used compositional data analysis (CoDA) to estimate the associations with health when reallocating time between different behaviours. The aim of this scoping review was to provide an overview of studies that have used CoDA to model how reallocating time between different time-use components is associated with health.
A systematic search of four electronic databases (MEDLINE, Embase, Scopus, SPORTDiscus) was conducted in October 2022. Studies were eligible if they used CoDA to examine the associations of time reallocations and health. Reallocations were considered between movement behaviours (sedentary behaviour (SB), light physical activity (LPA), moderate-to-vigorous physical activity (MVPA)) or various activities of daily living (screen time, work, household chores etc.). The review considered all populations, including clinical populations, as well as all health-related outcomes.
One hundred and three studies were included. Adiposity was the most commonly studied health outcome (n = 41). Most studies (n = 75) reported reallocations amongst daily sleep, SB, LPA and MVPA. While other studies reported reallocations amongst sub-compositions of these (work MVPA vs. leisure MVPA), activity types determined by recall (screen time, household chores, passive transport etc.) or bouted behaviours (short vs. long bouts of SB). In general, when considering cross-sectional results, reallocating time to MVPA from any behaviour(s) was favourably associated with health and reallocating time away from MVPA to any behaviour(s) was unfavourably associated with health. Some beneficial associations were seen when reallocating time from SB to both LPA and sleep; however, the strength of the association was much lower than for any reallocations involving MVPA. However, there were many null findings. Notably, most of the longitudinal studies found no associations between reallocations of time and health. Some evidence also suggested the context of behaviours was important, with reallocations of leisure time toward MVPA having a stronger favourable association for health than reallocating work time towards MVPA.
Evidence suggests that reallocating time towards MVPA from any behaviour(s) has the strongest favourable association with health, and reallocating time away from MVPA toward any behaviour(s) has the strongest unfavourable association with health. Future studies should use longitudinal and experimental study designs, and for a wider range of outcomes.
Miatke A
，Olds T
，Maher C
，Fraysse F
，Mellow ML
，Smith AE
，Pedisic Z
，Grgic J
，Dumuid D
... -
《International Journal of Behavioral Nutrition and Physical Activity》
Workplace pedometer interventions for increasing physical activity.
The World Health Organization (WHO) recommends undertaking 150 minutes of moderate-intensity physical activity per week, but most people do not. Workplaces present opportunities to influence behaviour and encourage physical activity, as well as other aspects of a healthy lifestyle. A pedometer is an inexpensive device that encourages physical activity by providing feedback on daily steps, although pedometers are now being largely replaced by more sophisticated devices such as accelerometers and Smartphone apps. For this reason, this is the final update of this review.
To assess the effectiveness of pedometer interventions in the workplace for increasing physical activity and improving long-term health outcomes.
We searched the Cochrane Central Register of Controlled Trials, MEDLINE, Embase, the Cumulative Index to Nursing and Allied Health Literature (CINAHL), Occupational Safety and Health (OSH) UPDATE, Web of Science, ClinicalTrials.gov, and the WHO International Clinical Trials Registry Platform from the earliest record to December 2016. We also consulted the reference lists of included studies and contacted study authors to identify additional records. We updated this search in May 2019, but these results have not yet been incorporated. One more study, previously identified as an ongoing study, was placed in 'Studies awaiting classification'.
We included randomised controlled trials (RCTs) of workplace interventions with a pedometer component for employed adults, compared to no or minimal interventions, or to alternative physical activity interventions. We excluded athletes and interventions using accelerometers. The primary outcome was physical activity. Studies were excluded if physical activity was not measured.
We used standard methodological procedures expected by Cochrane. When studies presented more than one physical activity measure, we used a pre-specified list of preferred measures to select one measure and up to three time points for analysis. When possible, follow-up measures were taken after completion of the intervention to identify lasting effects once the intervention had ceased. Given the diversity of measures found, we used ratios of means (RoMs) as standardised effect measures for physical activity.
We included 14 studies, recruiting a total of 4762 participants. These studies were conducted in various high-income countries and in diverse workplaces (from offices to physical workplaces). Participants included both healthy populations and those at risk of chronic disease (e.g. through inactivity or overweight), with a mean age of 41 years. All studies used multi-component health promotion interventions. Eleven studies used minimal intervention controls, and four used alternative physical activity interventions. Intervention duration ranged from one week to two years, and follow-up after completion of the intervention ranged from three to ten months. Most studies and outcomes were rated at overall unclear or high risk of bias, and only one study was rated at low risk of bias. The most frequent concerns were absence of blinding and high rates of attrition. When pedometer interventions are compared to minimal interventions at follow-up points at least one month after completion of the intervention, pedometers may have no effect on physical activity (6 studies; very low-certainty evidence; no meta-analysis due to very high heterogeneity), but the effect is very uncertain. Pedometers may have effects on sedentary behaviour and on quality of life (mental health component), but these effects were very uncertain (1 study; very low-certainty evidence). Pedometer interventions may slightly reduce anthropometry (body mass index (BMI) -0.64, 95% confidence interval (CI) -1.45 to 0.18; 3 studies; low-certainty evidence). Pedometer interventions probably had little to no effect on blood pressure (systolic: -0.08 mmHg, 95% CI -3.26 to 3.11; 2 studies; moderate-certainty evidence) and may have reduced adverse effects (such as injuries; from 24 to 10 per 100 people in populations experiencing relatively frequent events; odds ratio (OR) 0.50, 95% CI 0.30 to 0.84; low-certainty evidence). No studies compared biochemical measures or disease risk scores at follow-up after completion of the intervention versus a minimal intervention. Comparison of pedometer interventions to alternative physical activity interventions at follow-up points at least one month after completion of the intervention revealed that pedometers may have an effect on physical activity, but the effect is very uncertain (1 study; very low-certainty evidence). Sedentary behaviour, anthropometry (BMI or waist circumference), blood pressure (systolic or diastolic), biochemistry (low-density lipoprotein (LDL) cholesterol, total cholesterol, or triglycerides), disease risk scores, quality of life (mental or physical health components), and adverse effects at follow-up after completion of the intervention were not compared to an alternative physical activity intervention. Some positive effects were observed immediately at completion of the intervention periods, but these effects were not consistent, and overall certainty of evidence was insufficient to assess the effectiveness of workplace pedometer interventions.
Exercise interventions can have positive effects on employee physical activity and health, although current evidence is insufficient to suggest that a pedometer-based intervention would be more effective than other options. It is important to note that over the past decade, technological advancement in accelerometers as commercial products, often freely available in Smartphones, has in many ways rendered the use of pedometers outdated. Future studies aiming to test the impact of either pedometers or accelerometers would likely find any control arm highly contaminated. Decision-makers considering allocating resources to large-scale programmes of this kind should be cautious about the expected benefits of incorporating a pedometer and should note that these effects may not be sustained over the longer term. Future studies should be designed to identify the effective components of multi-component interventions, although pedometers may not be given the highest priority (especially considering the increased availability of accelerometers). Approaches to increase the sustainability of intervention effects and behaviours over a longer term should be considered, as should more consistent measures of physical activity and health outcomes.
Freak-Poli R
，Cumpston M
，Albarqouni L
，Clemes SA
，Peeters A
... -
《Cochrane Database of Systematic Reviews》
ResearchGate
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