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      Group-based developmental BMI trajectories, polycystic ovary syndrome, and gestational diabetes: a community-based longitudinal study

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          Abstract

          Background

          Obesity is common in young women, increasing insulin resistance (IR) and worsening pregnancy complications, including gestational diabetes (GDM). Women with polycystic ovary syndrome (PCOS) are commonly obese, which aggravates the severity of PCOS clinical expression. Relationships between these common insulin-resistant conditions, however, remain unclear.

          Methods

          We conducted a secondary analysis of the Australian Longitudinal Study on Women’s Health (ALSWH) database, including data from 8009 women aged 18–36 years across six surveys. We used latent-curve growth modelling to identify distinct body mass index (BMI) trajectories and multinomial logistic regression to explore sociodemographic and health variables characterizing BMI group membership. Logistic regression was used to assess independent risk of GDM.

          Results

          A total of 662 women (8.29%, 95% CI 7.68–8.89) reported PCOS. Three distinct BMI trajectories emerged, namely low stable (LSG) (63.8%), defined as an average trajectory remaining at ~25 kg/m 2; moderately rising (MRG) (28.8%), a curvilinear trajectory commencing in a healthy BMI and terminating in the overweight range; and high-rising (HRG) (7.4%), a curvilinear trajectory starting and terminating in the obese range. A high BMI in early reproductive life predicted membership in higher trajectories. The HRG BMI trajectory was independently associated with GDM (OR 2.50, 95% CI 1.80–3.48) and was a stronger correlate than PCOS (OR 1.89, 95% CI 1.41–2.54), maternal age, socioeconomic status, or parity.

          Conclusion

          Our results suggest heterogeneity in BMI change among Australian women of reproductive age, with and without PCOS. Reducing early adult life weight represents an ideal opportunity to intervene at an early stage of reproductive life and decreases the risk of long-term metabolic complications such as GDM.

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          Most cited references26

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          Consensus on women's health aspects of polycystic ovary syndrome (PCOS): the Amsterdam ESHRE/ASRM-Sponsored 3rd PCOS Consensus Workshop Group.

          Polycystic ovary syndrome (PCOS) is the most common endocrine disorder in females, with a high prevalence. The etiology of this heterogeneous condition remains obscure, and its phenotype expression varies. Two widely cited previous ESHRE/ASRM sponsored PCOS consensus workshops focused on diagnosis (published in 2004) and infertility management (published in 2008), respectively. The present third PCOS consensus report summarizes current knowledge and identifies knowledge gaps regarding various women's health aspects of PCOS. Relevant topics addressed-all dealt with in a systematic fashion-include adolescence, hirsutism and acne, contraception, menstrual cycle abnormalities, quality of life, ethnicity, pregnancy complications, long-term metabolic and cardiovascular health, and finally cancer risk. Additional, comprehensive background information is provided separately in an extended online publication. Copyright © 2012 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.
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            Socioeconomic status and obesity: a review of the literature.

            A review of 144 published studies of the relationship between socioeconomic status (SES) and obesity reveals a strong inverse relationship among women in developed societies. The relationship is inconsistent for men and children in developed societies. In developing societies, however, a strong direct relationship exists between SES and obesity among men, women, and children. A review of social attitudes toward obesity and thinness reveals values congruent with the distribution of obesity by SES in different societies. Several variables may mediate the influence of attitudes toward obesity and thinness among women in developed societies that result in the inverse relationship between SES and obesity. They include dietary restraint, physical activity, social mobility, and inheritance.
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              Overweight, obesity and central obesity in women with polycystic ovary syndrome: a systematic review and meta-analysis.

              BACKGROUND Polycystic ovary syndrome (PCOS) is closely associated with obesity but the prevalence of obesity varies between published studies. The objective of this research was to describe the prevalence of overweight, obesity and central obesity in women with and without PCOS and to assess the confounding effect of ethnicity, geographic regions and the diagnostic criteria of PCOS on the prevalence. METHODS MEDLINE, EMBASE, CINAHL, Cochrane Central Register of Controlled Trials (CENTRAL) and PSYCINFO were searched for studies reporting the prevalence of overweight, obesity or central obesity in women with and without PCOS. Data were presented as prevalence (%) and risk ratio (RR) [95% confidence interval (CI)]. Random-effect models were used to calculate pooled RR. RESULTS This systematic review included 106 studies while the meta-analysis included 35 studies (15129 women). Women with PCOS had increased prevalence of overweight [RR (95% CI): 1.95 (1.52, 2.50)], obesity [2.77 (1.88, 4.10)] and central obesity [1.73 (1.31, 2.30)] compared with women without PCOS. The Caucasian women with PCOS had a greater increase in obesity prevalence than the Asian women with PCOS compared with women without PCOS [10.79 (5.36, 21.70) versus 2.31 (1.33, 4.00), P < 0.001 between subgroups). CONCLUSIONS Women with PCOS had a greater risk of overweight, obesity and central obesity. Although our findings support a positive association between obesity and PCOS, our conclusions are limited by the significant heterogeneity between studies and further studies are now required to determine the source of this heterogeneity. Clinical management of PCOS should include the prevention and management of overweight and obesity.
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                Author and article information

                Contributors
                nadira.kakoly@monash.edu
                arul.earnest@monash.edu
                lisa.moran@monash.edu
                helena.teede@monash.edu
                + 613 8572 2625 , anju.joham@monash.edu
                Journal
                BMC Med
                BMC Med
                BMC Medicine
                BioMed Central (London )
                1741-7015
                6 November 2017
                6 November 2017
                2017
                : 15
                : 195
                Affiliations
                [1 ]ISNI 0000 0004 1936 7857, GRID grid.1002.3, Monash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, , Monash University, ; Clayton, Victoria 3168 Australia
                [2 ]ISNI 0000 0000 9295 3933, GRID grid.419789.a, Diabetes and Vascular Medicine Unit, , Monash Health, ; Clayton, Victoria 3168 Australia
                [3 ]Monash Partners Academic Health Sciences Centre, Melbourne, Victoria Australia
                [4 ]ISNI 0000 0004 1936 7857, GRID grid.1002.3, School of Public Health and Preventive Medicine, , Monash University, ; Locked bag 29, Monash Medical Centre, Clayton, Victoria 3168 Australia
                Article
                957
                10.1186/s12916-017-0957-7
                5674239
                29110650
                46a7bb35-c1bc-40e1-8157-93e9fb009de9
                © The Author(s). 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 18 June 2017
                : 13 October 2017
                Funding
                Funded by: Australian Government of Department of Health and Aging
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2017

                Medicine
                polycystic ovary syndrome,bmi,longitudinal,gestational diabetes,latent-curve analysis
                Medicine
                polycystic ovary syndrome, bmi, longitudinal, gestational diabetes, latent-curve analysis

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