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.S. S. Lim, N. S. Kakoly, J. W. J. Tan, G. Fitzgerald, M. Bahri Khomami, A. E. Joham, S. D. Cooray, M. L. Misso, R. J. Norman, C. L. Harrison, S. Ranasinha, H. J. Teede, L. J. Mora

The complexities of knowing what it is you are trapping

The effectiveness of any trapping system is highly dependent on the ability to accurately identify the specimens collected. For many fruit fly species, accurate identification (= diagnostics) using morphological or molecular techniques is relatively straightforward and poses few technical challenges. However, nearly all genera of pest tephritids also contain groups of species where single, stand-alone tools are not sufficient for accurate identification: such groups include the Bactrocera dorsalis complex, the Anastrepha fraterculus complex and the Ceratitis FAR complex. Misidentification of high-impact species from such groups can have dramatic consequences and negate the benefits of an otherwise effective trapping program. To help prevent such problems, this chapter defines what is meant by a species complex and describes in detail how the correct identification of species within a complex requires the use of an integrative taxonomic approach. Integrative taxonomy uses multiple, independent lines of evidence to delimit species boundaries, and the underpinnings of this approach from both the theoretical speciation literature and the systematics/taxonomy literature are described. The strength of the integrative approach lies in the explicit testing of hypotheses and the use of multiple, independent species delimitation tools. A case is made for a core set of species delimitation tools (pre- and post-zygotic compatibility tests, multi-locus phylogenetic analysis, chemoecological studies, and morphometric and geometric morphometric analyses) to be adopted as standards by tephritologists aiming to resolve economically important species complexes. In discussing the integrative approach, emphasis is placed on the subtle but important differences between integrative and iterative taxonomy. The chapter finishes with a case study that illustrates how iterative taxonomy applied to the B. dorsalis species complex led to incorrect taxonomic conclusions, which has had major implications for quarantine, trade, and horticultural pest management. In contrast, an integrative approach to the problem has resolved species limits in this taxonomically difficult group, meaning that robust diagnostics are now available