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Teede H.,Monash University | Teede H.,Diabetes and Vascular Medicine Unit | Gibson-Helm M.,Monash University | Norman R.J.,University of Adelaide | Boyle J.,Monash University
Journal of Clinical Endocrinology and Metabolism

Context: Polycystic ovary syndrome (PCOS) is an under-recognized, common, and complex endocrinopathy. The name PCOS is a misnomer, and there have been calls for a change to reflect the broader clinical syndrome. Objective: The aim of the study was to determine perceptions held by women and primary health care physicians around key clinical features of PCOS and attitudes toward current and alternative names for the syndrome. Design: We conducted a cross-sectional study utilizing a devised questionnaire. Setting: Participants were recruited throughout Australia via professional associations, women's health organizations, and a PCOS support group. Participants: Fifty-seven women with PCOS and 105 primary care physicians participated in the study. Main Outcome Measures: Perceptions of key clinical PCOS features and attitudes toward current and alternative syndrome names were investigated. Results: Irregular periods were identified as a key clinical feature of PCOS by 86% of the women with PCOS and 90% of the primary care physicians. In both groups, 60% also identified hormone imbalance as a key feature. Among women with PCOS, 47% incorrectly identified ovarian cysts as key, 48% felt the current name is confusing, and 51% supported a change. Most primary care physicians agreed that the name is confusing (74%) and needs changing (81%); however, opinions on specific alternative names were divided. Conclusions: The name "polycystic ovary syndrome" is perceived as confusing, and there is general support for a change to reflect the broader clinical syndrome. Engagement of primary health care physicians and consumers is strongly recommended to ensure that an alternative name enhances understanding and recognition of the syndrome and its complex features. (J Clin Endocrinol Metab 99: E107-E111, 2014). © Copyright 2014 by The Endocrine Society. Source

Moran L.J.,University of Adelaide | Moran L.J.,Monash University | Norman R.J.,University of Adelaide | Teede H.J.,University of Adelaide | And 2 more authors.
Trends in Endocrinology and Metabolism

Polycystic ovary syndrome (PCOS) is a common condition in reproductive-aged women, with reproductive, cardiometabolic, and psychological features. The heterogeneity in insulin resistance, obesity, and cardiometabolic features has led to controversy on the independent contributions of PCOS status, diagnostic criteria, phenotype, and adiposity. It now appears that women with PCOS have an increased risk of insulin resistance and cardiometabolic features, which is independent of, but worsened by, adiposity and central adiposity, and is unrelated to reproductive phenotype. Obesity may be more prevalent in the more severe phenotypes, which suggests either an exacerbation of the reproductive features or a more likely diagnosis in overweight women with PCOS. Therefore, all women with PCOS should be targeted for prevention, screening, and management of cardiometabolic features. © 2014 Elsevier Ltd. Source

Harrison C.L.,Monash University | Lombard C.B.,Monash University | East C.,Monash Womens Maternity Services | Boyle J.,Monash University | And 2 more authors.
Diabetes Research and Clinical Practice

Aim: To evaluate the addition of fasting glucose and lipids to a simple, validated risk prediction tool for gestational diabetes (GDM) applied in early pregnancy. Methods: Women at risk of developing GDM on a validated risk prediction tool were recruited in early pregnancy into a large randomised controlled trial. Outcome measures included fasting biochemical markers (glucose, lipids) at 12-15 weeks gestation and GDM diagnosis (28 weeks gestation). Multivariable logistic regression was used to identify additional predictive biochemical variables for GDM, with corresponding receiver operator characteristic (ROC) curves generated. Unadjusted and adjusted models were derived for both the Australasian Diabetes in Pregnancy (ADIPS) and the International Association for Diabetes in Pregnancy Study Group (IADPSG) GDM diagnostic criteria. Results: 51 (23%) Women were diagnosed with GDM based on ADIPS criteria, with 60 (30%) diagnosed based on IADPSG criteria. In all four regression models, fasting glucose was the strongest predictor for GDM development with an odds ratio range of 4.7-6.3 (ADIPS) and 8.8-10 (IADPSG). ROC curves revealed an area under the curve of 0.79 (95% CI: 0.72-0.86) for ADIPS criteria and 0.83 (95% CI: 0.77-0.90) for IADPSG criteria for adjusted models. Conclusions: In a two-step approach, when applied with a validated risk prediction tool, fasting glucose in early pregnancy was predictive of GDM and incrementally improved risk identification, presenting potential for an early pregnancy, GDM risk screening strategy for streamlining of pregnancy care and opportunity for preventive intervention. © 2014 Elsevier Ireland Ltd. Source

Harrison C.L.,Monash University | Lombard C.B.,Monash University | Teede H.J.,Monash University | Teede H.J.,Diabetes and Vascular Medicine Unit
International Journal of Behavioral Nutrition and Physical Activity

Background: Pregnancy is a recognised high risk period for excessive weight gain, contributing to postpartum weight retention and obesity development long-term. We aimed to reduce postpartum weight retention following a low-intensity, self-management intervention integrated with routine antenatal care during pregnancy. Methods: 228 women at increased risk of gestational diabetes, <15 weeks gestation were randomised to intervention (4 self-management sessions) or control (generic health information). Outcomes, collected at baseline and 6 weeks postpartum, included anthropometrics (weight and height), physical activity (pedometer) and questionnaires (health behaviours). Results: Mean age (32.3 ± 4.7 and 31.7 ± 4.4 years) and body mass index (30.4 ± 5.6 and 30.3 ± 5.9 kg/m2) were similar between intervention and control groups, respectively at baseline. By 6 weeks postpartum, weight change in the control group was significantly higher than the intervention group with a between group difference of 1.45 ± 5.1 kg (95% CI: -2.86,-0.02; p < 0.05) overall, with a greater difference in weight found in overweight, but not obese women. Intervention group allocation, higher baseline BMI, GDM diagnosis, country of birth and higher age were all independent predictors of lower weight retention at 6 weeks postpartum on multivariable linear regression. Other factors related to weight including physical activity, did not differ between groups. Conclusions: A low intensity intervention, integrated with standard antenatal care is effective in limiting postpartum weight retention. Implementation research is now required for scale-up to optimise antenatal health care. Trial registration: Australian New Zealand Clinical Trial Registry Number: ACTRN12608000233325. Registered 7/5/2008. Source

Gibson-Helm M.,Monash University | Boyle J.,Monash University | Block A.,Refugee Health Service | Teede H.,Monash University | Teede H.,Diabetes and Vascular Medicine Unit
BMC Medical Research Methodology

Background: Routine public health databases contain a wealth of data useful for research among vulnerable or isolated groups, who may be under-represented in traditional medical research. Identifying specific vulnerable populations, such as resettled refugees, can be particularly challenging; often country of birth is the sole indicator of whether an individual has a refugee background. The objective of this article was to review strengths and weaknesses of different methodological approaches to identifying resettled refugees and comparison groups from routine health datasets and to propose the application of additional methodological rigour in future research. Discussion. Methodological approaches to selecting refugee and comparison groups from existing routine health datasets vary widely and are often explained in insufficient detail. Linked data systems or datasets from specialized refugee health services can accurately select resettled refugee and asylum seeker groups but have limited availability and can be selective. In contrast, country of birth is commonly collected in routine health datasets but a robust method for selecting humanitarian source countries based solely on this information is required. The authors recommend use of national immigration data to objectively identify countries of birth with high proportions of humanitarian entrants, matched by time period to the study dataset. When available, additional migration indicators may help to better understand migration as a health determinant. Methodologically, if multiple countries of birth are combined, the proportion of the sample represented by each country of birth should be included, with sub-analysis of individual countries of birth potentially providing further insights, if population size allows. United Nations-defined world regions provide an objective framework for combining countries of birth when necessary. A comparison group of economic migrants from the same world region may be appropriate if the resettlement country is particularly diverse ethnically or the refugee group differs in many ways to those born in the resettlement country. Summary. Routine health datasets are valuable resources for public health research; however rigorous methods for using country of birth to identify resettled refugees would optimize usefulness of these resources. © 2014 Gibson-Helm et al.; licensee BioMed Central Ltd. Source

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