Emer Van Ryswyk

BACKGROUND: Dietary advice is the main strategy for managing gestational diabetes mellitus (GDM). It remains unclear what type of advice is best. OBJECTIVES: To assess the effects of different types of dietary advice for women with GDM for improving health outcomes for women and babies. SEARCH METHODS: We searched Cochrane Pregnancy and Childbirth's Trials Register (8 March 2016), PSANZ's Trials Registry (22 March 2016) and reference lists of retrieved studies. SELECTION CRITERIA: Randomised controlled trials comparing the effects of different types of dietary advice for women with GDM. DATA COLLECTION AND ANALYSIS: Two authors independently assessed study eligibility, risk of bias, and extracted data. Evidence quality for two comparisons was assessed using GRADE, for primary outcomes for the mother: hypertensive disorders of pregnancy; caesarean section; type 2 diabetes mellitus; and child: large-for-gestational age; perinatal mortality; neonatal mortality or morbidity composite; neurosensory disability; secondary outcomes for the mother: induction of labour; perineal trauma; postnatal depression; postnatal weight retention or return to pre-pregnancy weight; and child: hypoglycaemia; childhood/adulthood adiposity; childhood/adulthood type 2 diabetes mellitus. MAIN RESULTS: In this update, we included 19 trials randomising 1398 women with GDM, at an overall unclear to moderate risk of bias (10 comparisons). For outcomes assessed using GRADE, downgrading was based on study limitations, imprecision and inconsistency. Where no findings are reported below for primary outcomes or pre-specified GRADE outcomes, no data were provided by included trials. Primary outcomes Low-moderate glycaemic index (GI) versus moderate-high GI diet (four trials): no clear differences observed for: large-for-gestational age (risk ratio (RR) 0.71, 95% confidence interval (CI) 0.22 to 2.34; two trials, 89 infants; low-quality evidence); severe hypertension or pre-eclampsia (RR 1.02, 95% CI 0.07 to 15.86; one trial, 95 women; very low-quality evidence); eclampsia (RR 0.34, 95% CI 0.01 to 8.14; one trial, 83 women; very low-quality evidence) or caesarean section (RR 0.66, 95% CI 0.29 to 1.47; one trial, 63 women; low-quality evidence). Energy-restricted versus no energy-restricted diet (three trials): no clear differences seen for: large-for-gestational age (RR 1.17, 95% CI 0.65 to 2.12; one trial, 123 infants; low-quality evidence); perinatal mortality (no events; two trials, 423 infants; low-quality evidence); pre-eclampsia (RR 1.00, 95% CI 0.51 to 1.97; one trial, 117 women; low-quality evidence); or caesarean section (RR 1.12, 95% CI 0.80 to 1.56; two trials, 420 women; low-quality evidence). DASH (Dietary Approaches to Stop Hypertension) diet versus control diet (three trials): no clear differences observed for: pre-eclampsia (RR 1.00, 95% CI 0.31 to 3.26; three trials, 136 women); however there were fewer caesarean sections in the DASH diet group (RR 0.53, 95% CI 0.37 to 0.76; two trials, 86 women). Low-carbohydrate versus high-carbohydrate diet (two trials): no clear differences seen for: large-for-gestational age (RR 0.51, 95% CI 0.13 to 1.95; one trial, 149 infants); perinatal mortality (RR 3.00, 95% CI 0.12 to 72.49; one trial, 150 infants); maternal hypertension (RR 0.40, 95% CI 0.13 to 1.22; one trial, 150 women); or caesarean section (RR 1.29, 95% CI 0.84 to 1.99; two trials, 179 women). High unsaturated fat versus low unsaturated fat diet (two trials): no clear differences observed for: large-for-gestational age (RR 0.54, 95% CI 0.21 to 1.37; one trial, 27 infants); pre-eclampsia (no cases; one trial, 27 women); hypertension in pregnancy (RR 0.54, 95% CI 0.06 to 5.26; one trial, 27 women); caesarean section (RR 1.08, 95% CI 0.07 to 15.50; one trial, 27 women); diabetes at one to two weeks (RR 2.00, 95% CI 0.45 to 8.94; one trial, 24 women) or four to 13 months postpartum (RR 1.00, 95% CI 0.10 to 9.61; one trial, six women). Low-GI versus high-fibre moderate-GI diet (one trial): no clear differences seen for: large-for-gestational age (RR 2.87, 95% CI 0.61 to 13.50; 92 infants); caesarean section (RR 1.91, 95% CI 0.91 to 4.03; 92 women); or type 2 diabetes at three months postpartum (RR 0.76, 95% CI 0.11 to 5.01; 58 women). Diet recommendation plus diet-related behavioural advice versus diet recommendation only (one trial): no clear differences observed for: large-for-gestational age (RR 0.73, 95% CI 0.25 to 2.14; 99 infants); or caesarean section (RR 0.78, 95% CI 0.38 to 1.62; 99 women). Soy protein-enriched versus no soy protein diet (one trial): no clear differences seen for: pre-eclampsia (RR 2.00, 95% CI 0.19 to 21.03; 68 women); or caesarean section (RR 1.00, 95% CI 0.57 to 1.77; 68 women). High-fibre versus standard-fibre diet (one trial): no primary outcomes reported. Ethnic-specific versus standard healthy diet (one trial): no clear differences observed for: large-for-gestational age (RR 0.14, 95% CI 0.01 to 2.45; 20 infants); neonatal composite adverse outcome (no events; 20 infants); gestational hypertension (RR 0.33, 95% CI 0.02 to 7.32; 20 women); or caesarean birth (RR 1.20, 95% CI 0.54 to 2.67; 20 women). Secondary outcomes For secondary outcomes assessed using GRADE no differences were observed: between a low-moderate and moderate-high GI diet for induction of labour (RR 0.88, 95% CI 0.33 to 2.34; one trial, 63 women; low-quality evidence); or an energy-restricted and no energy-restricted diet for induction of labour (RR 1.02, 95% CI 0.68 to 1.53; one trial, 114 women, low-quality evidence) and neonatal hypoglycaemia (average RR 1.06, 95% CI 0.48 to 2.32; two trials, 408 infants; very low-quality evidence).Few other clear differences were observed for reported outcomes. Longer-term health outcomes and health services use and costs were largely not reported. AUTHORS' CONCLUSIONS: Evidence from 19 trials assessing different types of dietary advice for women with GDM suggests no clear differences for primary outcomes and secondary outcomes assessed using GRADE, except for a possible reduction in caesarean section for women receiving a DASH diet compared with a control diet. Few differences were observed for secondary outcomes.Current evidence is limited by the small number of trials in each comparison, small sample sizes, and variable methodological quality. More evidence is needed to assess the effects of different types of dietary advice for women with GDM. Future trials should be adequately powered to evaluate short- and long-term outcomes.

Polycystic ovary syndrome (PCOS) is a complex endocrine disorder affecting the reproductive, metabolic and psychological health of women. Clinic-based studies indicate that sleep disturbances and disorders including obstructive sleep apnea and excessive daytime sleepiness occur more frequently among women with PCOS compared to comparison groups without the syndrome. Evidence from the few available population-based studies is supportive. Women with PCOS tend to be overweight/obese, but this only partly accounts for their sleep problems as associations are generally upheld after adjustment for body mass index; sleep problems also occur in women with PCOS of normal weight. There are several, possibly bidirectional, pathways through which PCOS is associated with sleep disturbances. The pathophysiology of PCOS involves hyperandrogenemia, a form of insulin resistance unique to affected women, and possible changes in cortisol and melatonin secretion, arguably reflecting altered hypothalamic-pituitary-adrenal function. Psychological and behavioral pathways are also likely to play a role, as anxiety and depression, smoking, alcohol use and lack of physical activity are also common among women with PCOS, partly in response to the distressing symptoms they experience. The specific impact of sleep disturbances on the health of women with PCOS is not yet clear; however, both PCOS and sleep disturbances are associated with deterioration in cardiometabolic health in the longer term and increased risk of type 2 diabetes. Both immediate quality of life and longer-term health of women with PCOS are likely to benefit from diagnosis and management of sleep disorders as part of interdisciplinary health care.

STUDY OBJECTIVES: Poor adherence to continuous positive airway pressure (CPAP) commonly affects therapeutic response in obstructive sleep apnea (OSA). We aimed to determine predictors of adherence to CPAP among participants of the Sleep Apnea and cardioVascular Endpoints (SAVE) trial. METHODS: SAVE was an international, randomized, open trial of CPAP plus usual care versus usual care (UC) alone in participants (45-75 years) with co-occurring moderate-to-severe OSA (≥12 episodes/h of ≥4% oxygen desaturation) and established cardiovascular (CV) disease. Baseline sociodemographic, health and lifestyle factors, OSA symptoms, and 1-month change in daytime sleepiness, as well as CPAP side effects and adherence (during sham screening, titration week, and in the first month), were entered in univariate linear regression analyses to identify predictors of CPAP adherence at 24 months. Variables with p <0.2 were assessed for inclusion in a multivariate linear mixed model with country, age, and sex included a priori and site as a random effect. RESULTS: Significant univariate predictors of adherence at 24 months in 1,121 participants included: early adherence measures, improvement in daytime sleepiness at 1 month, fixed CPAP pressure, some measures of OSA severity, cardiovascular disease history, breathing pauses, and very loud snoring. While observed adherence varied between countries, adherence during sham screening, initial titration, and the first month of treatment retained independent predictive value in the multivariate model along with fixed CPAP pressure and very loud snoring. CONCLUSIONS: Early CPAP adherence had the greatest predictive value for identifying those at highest risk of non-adherence to long-term CPAP therapy. CLINICAL TRIAL REGISTRATION: SAVE is registered with clinicaltrials.gov (NCT00738179).

OBJECTIVES: To improve well-being and performance indicators in a group of Australian Football League (AFL) players via a six-week sleep optimisation programme. DESIGN: Prospective intervention study following observations suggestive of reduced sleep and excessive daytime sleepiness in an AFL group. METHODS: Athletes from the Adelaide Football Club were invited to participate if they had played AFL senior-level football for 1-5 years, or if they had excessive daytime sleepiness (Epworth Sleepiness Scale [ESS] >10), measured via ESS. An initial education session explained normal sleep needs, and how to achieve increased sleep duration and quality. Participants (n = 25) received ongoing feedback on their sleep, and a mid-programme education and feedback session. Sleep duration, quality and related outcomes were measured during week one and at the conclusion of the six-week intervention period using sleep diaries, actigraphy, ESS, Pittsburgh Sleep Quality Index, Profile of Mood States, Training Distress Scale, Perceived Stress Scale and the Psychomotor Vigilance Task. RESULTS: Sleep diaries demonstrated an increase in total sleep time of approximately 20 min (498.8 ± 53.8 to 518.7 ± 34.3; p < .05) and a 2% increase in sleep efficiency (p < 0.05). There was a corresponding increase in vigour (p < 0.001) and decrease in fatigue (p < 0.05). CONCLUSIONS: Improvements in measures of sleep efficiency, fatigue and vigour indicate that a sleep optimisation programme may improve athletes' well-being. More research is required into the effects of sleep optimisation on athletic performance.