Metabolic syndrome in polycystic ovary syndrome: a systematic review, meta-analysis and meta-regression.

INTRODUCTION: Women with polycystic ovary syndrome (PCOS) have increased risk of metabolic syndrome. The relative contribution of clinical, demographic or biochemical factors to metabolic syndrome in PCOS is not known. A literature search was conducted in MEDLINE, CINAHL, EMBASE and clinical trial registries. Of 4530 studies reviewed, 59 were included in the systematic review and 27 in the meta-analysis and meta-regression. In good and fair quality studies, women with PCOS had an overall increased prevalence of metabolic syndrome (odds ratio, OR 3.35, 95% confidence interval, CI 2.44, 4.59). Increased prevalence of metabolic syndrome occurred in overweight or obese women with PCOS (OR 1.88, 95% 1.16, 3.04) but not in lean women (OR 1.45, 95% CI 0.35, 6.12). In meta-regression analyses, the markers of metabolic syndrome diagnostic criteria (waist circumference, high-density lipoprotein cholesterol, triglyceride, blood pressure), BMI, glucose tolerance (2-hr oral glucose tolerance test) and surrogate markers of insulin resistance (HOMA-IR) but not markers of reproductive dysfunction (sex hormone binding globulin, testosterone, PCOS phenotypes) contributed significantly to the heterogeneity in the prevalence of metabolic syndrome. Women with PCOS have increased risk of metabolic syndrome which was associated with obesity and metabolic features but not with indices of hyperandrogenism.

Younger people with Type 2 diabetes have poorer self-care practices compared with older people: results from the Australian National Diabetes Audit.

AIM: This cross-sectional study compares the self-care practices of younger and older people with Type 2 diabetes. METHODS: Data were analysed from the Australian National Diabetes Audit (ANDA) including 2552 adults with Type 2 diabetes from Australian Diabetes Centres. Pre-specified demographic and clinical variables were obtained. Self-care variables (physical activity, following dietary recommendations, medication adherence and monitoring blood glucose levels) were compared in people ≤ 64 and > 64 years of age. RESULTS: Mean age (± sd) of participants was 63 ± 13 years overall, 53 ± 9 years for the younger group and 73 ± 6 years for the older group. A greater proportion of younger people had HbA1c levels > 53 mmol/mol (> 7.0%) (76% vs. 68%), reported difficulty following dietary recommendations (50% vs. 32%) and forgetting medications (37% vs. 22%) compared with older people (all P-values <0.001). A smaller proportion of younger compared with older people reported monitoring their blood glucose levels as often as recommended (60% vs. 70%, P < 0.001). Similar proportions of people aged ≤ 64 and > 64 years required insulin therapy (59% vs. 57%, P = 0.200). Younger age was associated with a twofold increase in the odds of not following the recommended self-care practices after adjustment for gender, smoking, insulin therapy, depression and allied health attendance (all P < 0.001). CONCLUSIONS: Despite shorter diabetes duration, younger age was associated with worse glycaemic control and poorer diabetes self-care practices among people with Type 2 diabetes. Targeted strategies are required to optimize diabetes self-care practices and thereby glycaemic control.

Ethnicity, obesity and the prevalence of impaired glucose tolerance and type 2 diabetes in PCOS: a systematic review and meta-regression.

BACKGROUND: Our prior meta-analyses demonstrated an increased prevalence of impaired glucose tolerance (IGT) and type 2 diabetes mellitus (T2DM) with polycystic ovary syndrome (PCOS), but with substantial clinical heterogeneity. OBJECTIVE AND RATIONALE: We aimed to update our previous review to quantify the prevalence of IGT and T2DM in PCOS with only quality studies (good and fair quality). We also aimed to examine the contribution of parameters including ethnicity, obesity and method of diagnosing T2DM in explaining the observed heterogeneity in IGT and T2DM prevalence in PCOS. SEARCH METHODS: We conducted a literature search (MEDLINE, CINAHL, EMBASE, clinical trial registries and hand-searching) up to June 2016 to identify studies reporting the prevalence of dysglycemia (IGT and T2DM) in women with and without PCOS. We included studies where women with PCOS (defined according to original National Institute of Health) were compared to women without PCOS for the end-points of the prevalence of IGT or T2DM. We excluded case reports, case series, editorials, and narrative reviews. Studies where PCOS was diagnosed by self-report, or where IGT or T2DM were measured by fasting glucose, only were excluded. We assessed the methodological quality of the included studies using a priori criteria based on the Newcastle-Ottawa Scaling (NOS) for non-randomized studies. Data are presented as odds ratio (OR) (95% CI) with random-effects meta-analysis by Mantel-Haenszel methods. We assessed the contribution of demographic and clinical factors to heterogeneity using subgroup and meta-regression analysis. OUTCOMES: We reviewed 4530 studies and included 40 eligible studies in the final analysis. On meta-analysis of quality studies, women with PCOS had an increased prevalence of IGT (OR = 3.26, 95% CI: 2.17-4.90) and T2DM (OR = 2.87, 95% CI: 1.44-5.72), which differed by ethnicity (for IGT, Asia: 5-fold, the Americas: 4-fold and Europe: 3-fold), was higher with obesity, and doubled among studies using self-report or administrative data for diagnosing diabetes. The ethnicity-related difference retained its significance for Asia and Europe in BMI-matched subgroups. Clear contributors to heterogeneity did not emerge in meta-regression. WIDER IMPLICATIONS: Our findings underscore the importance of PCOS as a cause of dysglycemia with a higher prevalence of IGT and T2DM. They support the relevance of ethnicity and obesity and emphasize the need for accurate diagnostic methods for diabetes. PROSPERO REGISTRATION NUMBER: CRD42017056524.

Gaps and barriers in health-care provision for co-morbid diabetes and chronic kidney disease: a cross-sectional study.

BACKGROUND: Patients with diabetes and chronic kidney disease (CKD) are a complex subset of the growing number of patients with diabetes, due to multi-morbidity. Gaps between recommended and received care for diabetes and chronic kidney disease (CKD) are evident despite promulgation of guidelines. Here, we document gaps in tertiary health-care, and the commonest patient-reported barriers to health-care, before exploring the association between these gaps and barriers. METHODS: This cross-sectional study recruited patients with diabetes and CKD (eGFR < 60 mL/min/1.73 m2) across 4 large hospitals. For each patient, questionnaires were completed examining clinical data, recommended care, and patient-reported barriers limiting health-care. Descriptive statistics, subgroup analyses by CKD stage and hospital, and analyses examining the relationship between health-care gaps and barriers were performed. RESULTS: 308 patients, of mean age 66.9 (SD 11.0) years, and mostly male (69.5%) and having type 2 diabetes (88.0%), participated. 49.1% had stage 3, 24.7% stage 4 and 26.3% stage 5 CKD. Gaps between recommended versus received care were evident: 31.9% of patients had an HbA1c ≥ 8%, and 39.3% had a measured blood pressure ≥ 140/90 mmHg. The commonest barriers were poor continuity of care (49.3%), inadequate understanding/education about CKD (43.5%), and feeling unwell (42.6%). However, barriers associated with a failure to receive items of recommended care were inadequate support from family and friends, conflicting advice from and poor communication amongst specialists, the effect of co-morbidities on self-management and feeling unmotivated (all p < 0.05). CONCLUSIONS: Barriers to health-care varied across CKD stages and hospitals. Barriers associated with a deviation from recommended care were different for different items of care, suggesting that specific interventions targeting each item of care are required.

The association between Polycystic Ovary Syndrome (PCOS) and metabolic syndrome: a statistical modelling approach.

OBJECTIVE: Polycystic ovary syndrome (PCOS) affects 12-21% of women. Women with PCOS exhibit clustering of metabolic features. We applied rigorous statistical methods to further understand the interplay between PCOS and metabolic features including insulin resistance, obesity and androgen status. DESIGN: Retrospective cross-sectional analysis. PATIENTS: Women with PCOS attending reproductive endocrine clinics in South Australia for the treatment of PCOS (n = 172). Women without PCOS (controls) in the same Australian region (n = 335) from the Australian Diabetes, Obesity and Lifestyle Study (AusDiab), a national population-based study (age- and BMI-matched within one standard deviation of the PCOS cohort). MEASUREMENTS: The factor structure for metabolic syndrome for women with PCOS and control groups was examined, specifically, the contribution of individual factors to metabolic syndrome and the association of hyperandrogenism with other metabolic factors. RESULTS: Women with PCOS demonstrated clustering of metabolic features that was not observed in the control group. Metabolic syndrome in the PCOS cohort was strongly represented by obesity (standardized factor loading = 0·95, P < 0·001) and insulin resistance factors (loading = 0·92, P < 0·001) and moderately by blood pressure (loading = 0·62, P < 0·001) and lipid factors (loading = 0·67, P = 0·002). On further analysis, the insulin resistance factor strongly correlated with the obesity (r = 0·70, P < 0·001) and lipid factors (r = 0·68, P < 0·001) and moderately with the blood pressure factor (loading = 0·43, P = 0·002). The hyperandrogenism factor was moderately correlated with the insulin resistance factor (r = 0·38, P < 0·003), but did not correlate with any other metabolic factors. CONCLUSIONS: PCOS women are more likely to display metabolic clustering in comparison with age- and BMI-matched control women. Obesity and insulin resistance, but not androgens, are independently and most strongly associated with metabolic syndrome in PCOS.

Sleep difficulty mediates effects of vasomotor symptoms on mood in younger breast cancer survivors.

OBJECTIVE: Treatment-induced early menopause occurs in > 80% of premenopausal women diagnosed with breast cancer. This study explored the relationship between vasomotor symptoms (VMS), sleep and mood in women aged 40-51 years with non-metastatic breast cancer. METHODS: Cross-sectional study using validated questionnaires (Greene Climacteric scale and Hospital Anxiety and Depression Scale, HADS). Women (n = 114) were recruited from the community and hospital outpatient clinics. Frequency determination and structural equation modeling (SEMod) were used to examine the relationship between the latent variables: VMS, anxiety, and depression, and the indicator variable: difficulty sleeping. RESULTS: Participants' mean age was 47 years and 94% became menopausal after breast cancer diagnosis. Difficulty sleeping was reported by 82% of women with 46% reporting (Likert scale) 'quite a bit/extremely'. Most women reported night sweats (77% of women: 47% reporting 'quite a bit/extremely') and hot flushes (84% of women: 50% reporting 'quite a bit/extremely'). HADS scores indicated clinically relevant depression and anxiety in 98% and 99% of women, respectively. SEMod revealed that VMS contributed to difficulty sleeping (standardized coefficient = 0.54; p < 0.001) and difficulty sleeping mediated the relationship between VMS and anxiety (standardized coefficient = 0.34; p = 0.03). However, difficulty sleeping did not have a significant direct impact on depression (standardized coefficient = -0.03; p = 0.8), although anxiety was a strong predictor of depression (standardized coefficient = 0.83; p = 0.015). CONCLUSIONS: VMS, sleep and mood disturbance are commonly experienced by younger women with breast cancer. Using SEMod, we demonstrate for the first time that VMS may directly influence sleep in these women. VMS may have an indirect effect on mood, partly mediated by sleep difficulty.

Contraception use and pregnancy outcomes in women with polycystic ovary syndrome: data from the Australian Longitudinal Study on Women's Health.

STUDY QUESTION: Do contraception use, pregnancy outcome and number of children differ in women with and without polycystic ovary syndrome (PCOS)? SUMMARY ANSWER: Women with PCOS were less likely to report use of contraception and more likely to report a miscarriage, whilst number of children was similar between groups. WHAT IS KNOWN ALREADY: The oral contraceptive pill is used in the management of PCOS, but the patterns of contraception use in women with PCOS is not known. In women with PCOS who undergo assisted reproduction, the risk of pregnancy loss appears higher, yet pregnancy loss and family size among community-based women with PCOS is not known. STUDY DESIGN, SIZE AND DURATION: This is a cross-sectional analysis of a longitudinal cohort study. Mailed survey data were collected at five time points (years 1996, 2000, 2003, 2006 and 2009). Data from respondents to Survey 4 (2006), aged 28-33 (n = 9145, 62% of the original cohort aged 18-23 years) were analysed. PARTICIPANTS/MATERIALS, SETTING, METHODS: This study was conducted in a general community setting. Data from participants who responded to the questions on PCOS, contraception and pregnancy outcome were analysed. The main outcome measures were self-reported PCOS, body mass index (BMI), contraception use, pregnancy loss and number of children. MAIN RESULTS AND THE ROLE OF CHANCE: In women aged 28-33 years, women with PCOS were less likely to be using contraception (61 versus 79%, P < 0.001) and more likely to be trying to conceive (56 versus 45%, P < 0.001), compared with women not reporting PCOS. A greater proportion of women with PCOS reported pregnancy loss (20 versus 15%, P = 0.003). PCOS was not independently associated with pregnancy loss; however, BMI was independently associated with pregnancy loss in the overweight and obese groups (OR 1.2, 95% CI 1.04-1.4, P = 0.02 and OR 1.4, 95% CI 1.1-1.6, P = 0.001, respectively). Fertility treatment use was also independently associated with pregnancy loss (adjusted OR 3.2, 95% CI 2.4-4.2, P < 0.001). There was no significant difference in number of children between women with and without PCOS. LIMITATIONS, REASON FOR CAUTION: PCOS, contraception use and pregnancy outcome data were self-reported. Attrition occurred, but is reasonable compared with similar longitudinal cohort studies. WIDER IMPLICATIONS OF THE FINDINGS: This community-based cohort aged 28-33 years provides insights into the contraceptive use, pregnancy loss and family size of a large cohort of unselected women. Women reporting PCOS had lower rates of contraception use and were more likely to be currently trying to conceive, suggesting that they may be aware of potential fertility challenges, yet in those not planning to conceive, contraceptive use was low and further education may be required. Despite prior reports of higher rates of pregnancy loss in PCOS, usually from infertility services, in this community-based population, PCOS was not independently associated with pregnancy loss, yet independent risk factors for pregnancy loss included higher BMI, were higher in PCOS. The number of children per woman was similar in the both groups, albeit with more infertility treatment in PCOS. This may reassure women with PCOS that with access to fertility treatment, family sizes appear similar to women not reporting PCOS.

Gestational diabetes and type 2 diabetes in reproductive-aged women with polycystic ovary syndrome.

CONTEXT: Polycystic ovary syndrome (PCOS) affects 6%-21% of women. PCOS has been associated with an increased risk of dysglycemia including gestational diabetes mellitus (GDM) and type 2 diabetes mellitus (T2DM). OBJECTIVE: The objective of the study was to assess the prevalence of dysglycemia and the impact of obesity in young reproductive-aged women with and without PCOS in a community-based cohort. DESIGN: This was a cross-sectional analysis of data from a large longitudinal study (the Australian Longitudinal Study on Women's Health). SETTING: The setting for the study was the general community. PARTICIPANTS: Women were randomly selected from the national health insurance database. Standardized data collection occurred at five survey time points (years 1996, 2000, 2003, 2006, and 2009). Data from survey 4 (2006, n = 9145, 62% of original cohort aged 18-23 y) were examined for this study. MAIN OUTCOME MEASURES: Self-reported PCOS, GDM, and T2DM were measured. RESULTS: In women aged 28-33 years, PCOS prevalence was 5.8% [95% confidence interval (CI) 5.3%-6.4%]. The prevalence of GDM (in women reporting prior pregnancy) and T2DM was 11.2% and 5.1% in women with PCOS and 3.8% and 0.3% in women without PCOS, respectively (P for both < .001). PCOS was associated with an increased odds of GDM and T2DM. After adjusting for age, body mass index, hypertension, smoking, and demographic factors, the odds of GDM (odds ratio 2.1, 95% CI 1.1-3.9, P = .02) and T2DM (odds ratio 8.8, 95% CI 3.9-20.1, P < .001) remained increased in women reporting PCOS. CONCLUSIONS: In a large community-based cohort of reproductive-aged women, PCOS was independently associated with a higher risk of GDM and T2DM, independent of body mass index. Aggressive screening, prevention, and management of dysglycemia is clearly warranted in women with PCOS.

The contribution of diet, physical activity and sedentary behaviour to body mass index in women with and without polycystic ovary syndrome.

STUDY QUESTION: What is the contribution of diet, physical activity and sedentary behaviour to body mass index (BMI) in women with and without polycystic ovary syndrome (PCOS)? SUMMARY ANSWER: PCOS status, higher energy intake and glycaemic index and lower physical activity were independently associated with BMI. WHAT IS KNOWN ALREADY: Obesity worsens the clinical features of PCOS and women with PCOS have an elevated prevalence of overweight and obesity. It is not known whether there is a contribution of lifestyle factors such as dietary intake, physical activity or sedentary behaviour to the elevated prevalence of obesity in PCOS. STUDY DESIGN, SIZE, DURATION: This study is a population-based observational study with data currently collected at 13 year follow-up. The study commenced in 1996. For this analysis, data are analysed at one time point corresponding to the Survey 5 of the cohort in 2009. At this time 8200 participants remained (58% retention of baseline participants) of which 7466 replied to the questionnaire; 409 self-reported a diagnosis of PCOS and 7057 no diagnosis of PCOS. PARTICIPANTS/MATERIALS, SETTING, METHODS: Australian women born in 1973-1978 from the Australian Longitudinal Study on Women's Health. MAIN RESULTS AND THE ROLE OF CHANCE: Mean BMI was higher in women with PCOS compared with non-PCOS (29.3 ± 7.5 versus 25.6 ± 5.8 kg/m(2), P < 0.001). Women with PCOS reported a better dietary intake (elevated diet quality and micronutrient intake and lower saturated fat and glycaemic index intake) but increased energy intake, increased sitting time and no differences in total physical activity compared with non-PCOS. PCOS status, higher energy intake and glycaemic index and lower physical activity, as well as age, smoking, alcohol intake, occupation, education and country of birth, were independently associated with BMI. LIMITATIONS, REASONS FOR CAUTION: The weaknesses of this study include the self-reported diagnosis of PCOS, and the women not reporting PCOS not having their control status clinically verified which is likely to underrepresent the PCOS population. We are also unable to determine if lifestyle behaviours contributed to the PCOS diagnosis or were altered in response to diagnosis. WIDER IMPLICATIONS OF THE FINDINGS: The strengths of this study include the community-based nature of the sample which minimizes selection bias to include women with a variety of clinical presentations. These results are therefore generalizable to a broader population than the majority of research in PCOS examining this research question which are performed in clinic-based populations. This study is in agreement with the literature that PCOS is independently associated with elevated BMI. We provide new insights that diet quality is subtly improved but that sedentary behaviour is elevated in PCOS and that PCOS status, higher energy intake and glycaemic index and lower physical activity are independently associated with BMI. STUDY FUNDING/COMPETING INTEREST(S): L.J.M. was supported by a South Australian Cardiovascular Research Development Program (SACVRDP) Fellowship (AC11S374); a program collaboratively funded by the National Heart Foundation of Australia, the South Australian Department of Health and the South Australian Health and Medical Research Institute, S.A.M. was funded by an Australian Research Council Future Fellowship (FT100100581), S.Z. was funded by a Heart Foundation Career Development Fellowship (ID CR10S5330) and H.J.T. was funded by an NHMRC fellowship (ID 545888). None of the authors has any conflict of interest to declare. TRIAL REGISTRATION NUMBER: Not applicable.