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      Number of Offspring and Cardiovascular Disease Risk in Men and Women : The Role of Shared Lifestyle Characteristics

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          Abstract

          Supplemental Digital Content is available in the text.

          Abstract

          Background:

          Previous studies of the number of offspring and cardiovascular disease (CVD) report conflicting findings. We re-examined this association in both sexes to clarify the role of the cardiometabolic changes that women experience during pregnancy versus shared lifestyle characteristics.

          Methods:

          We studied 180,626 women and 133,259 men participating in the UK Biobank cohort who were free of CVD at baseline. CVD events were obtained from hospital and death registers. Analyses were conducted using Cox proportional hazards regression.

          Results:

          The incidence rates of overall CVD were six per 1000 person-years for women and nine per 1000 person-years for men. Number of children showed an association with risk of CVD among women; the adjusted HR (95% CI) was 1.2 (1.1, 1.3) for one, 1.1 (1.0, 1.2) for two, 1.2 (1.1, 1.3) for three, and 1.2 (1.1, 1.4) for four or more as compared to none. Number of children was also associated with CVD among men; the adjusted HR (95% CI) was 1.1 (1.0, 1.2) for one, 1.0 (0.96, 1.1) for two, 1.1 (1.0, 1.2) for three, and 1.1 (1.0, 1.3) for four or more as compared to none. There was no evidence of heterogeneity in the associations between sexes ( P interaction = 0.80). Number of offspring also showed similar associations with ischemic heart disease and hypertensive disorders in both sexes.

          Conclusions:

          We observed similar associations between number of offspring and CVD in both sexes. The association among women might therefore be largely explained by unobserved behavioral and lifestyle characteristics.

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          Most cited references23

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          General cardiovascular risk profile for use in primary care: the Framingham Heart Study.

          Separate multivariable risk algorithms are commonly used to assess risk of specific atherosclerotic cardiovascular disease (CVD) events, ie, coronary heart disease, cerebrovascular disease, peripheral vascular disease, and heart failure. The present report presents a single multivariable risk function that predicts risk of developing all CVD and of its constituents. We used Cox proportional-hazards regression to evaluate the risk of developing a first CVD event in 8491 Framingham study participants (mean age, 49 years; 4522 women) who attended a routine examination between 30 and 74 years of age and were free of CVD. Sex-specific multivariable risk functions ("general CVD" algorithms) were derived that incorporated age, total and high-density lipoprotein cholesterol, systolic blood pressure, treatment for hypertension, smoking, and diabetes status. We assessed the performance of the general CVD algorithms for predicting individual CVD events (coronary heart disease, stroke, peripheral artery disease, or heart failure). Over 12 years of follow-up, 1174 participants (456 women) developed a first CVD event. All traditional risk factors evaluated predicted CVD risk (multivariable-adjusted P<0.0001). The general CVD algorithm demonstrated good discrimination (C statistic, 0.763 [men] and 0.793 [women]) and calibration. Simple adjustments to the general CVD risk algorithms allowed estimation of the risks of each CVD component. Two simple risk scores are presented, 1 based on all traditional risk factors and the other based on non-laboratory-based predictors. A sex-specific multivariable risk factor algorithm can be conveniently used to assess general CVD risk and risk of individual CVD events (coronary, cerebrovascular, and peripheral arterial disease and heart failure). The estimated absolute CVD event rates can be used to quantify risk and to guide preventive care.
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            Carbohydrate and lipid metabolism in pregnancy: normal compared with gestational diabetes mellitus.

            This article reviews maternal metabolic strategies for accommodating fetal nutrient requirements in normal pregnancy and in gestational diabetes mellitus (GDM). Pregnancy is characterized by a progressive increase in nutrient-stimulated insulin responses despite an only minor deterioration in glucose tolerance, consistent with progressive insulin resistance. The hyperinsulinemic-euglycemic glucose clamp technique and intravenous-glucose-tolerance test have indicated that insulin action in late normal pregnancy is 50-70% lower than in nonpregnant women. Metabolic adaptations do not fully compensate in GDM and glucose intolerance ensues. GDM may reflect a predisposition to type 2 diabetes or may be an extreme manifestation of metabolic alterations that normally occur in pregnancy. In normal pregnant women, basal endogenous hepatic glucose production (R(a)) was shown to increase by 16-30% to meet the increasing needs of the placenta and fetus. Total gluconeogenesis is increased in late gestation, although the fractional contribution of total gluconeogenesis to R(a), quantified from (2)H enrichment on carbon 5 of glucose (65-85%), does not differ in pregnant women after a 16-h fast. Endogenous hepatic glucose production was shown to remain sensitive to increased insulin concentration in normal pregnancy (96% suppression), but is less sensitive in GDM (80%). Commensurate with the increased rate of glucose appearance, an increased contribution of carbohydrate to oxidative metabolism has been observed in late pregnancy compared with pregravid states. The 24-h respiratory quotient is significantly higher in late pregnancy than postpartum. Recent advances in carbohydrate metabolism during pregnancy suggest that preventive measures should be aimed at improving insulin sensitivity in women predisposed to GDM. Further research is needed to elucidate the mechanisms and consequences of alterations in lipid metabolism during pregnancy.
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              UK biobank data: come and get it.

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                Author and article information

                Journal
                Epidemiology
                Epidemiology
                EDE
                Epidemiology (Cambridge, Mass.)
                Lippincott Williams & Wilkins
                1044-3983
                1531-5487
                November 2017
                28 September 2017
                : 28
                : 6
                : 880-888
                Affiliations
                From the [a ]MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom; [b ]School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom; [c ]Domain for Mental and Physical Health, Norwegian Institute of Public Health, Oslo, Norway; [d ]School of Medicine, University of Glasgow, Glasgow, Scotland; and [e ]Department of Obstetrics and Gynecology, University of Pittsburgh, Pittsburgh, PA.
                Author notes
                Correspondence: Maria C. Magnus, MRC Integrative Epidemiology Unit at the University of Bristol, Oakfield House, Oakfield Grove, BS8 2BN Bristol, United Kingdom, E-mail: Maria.Christine.Magnus@ 123456bristol.ac.uk .
                Article
                00017
                10.1097/EDE.0000000000000712
                5625954
                28696997
                2cc8d1d1-c02b-4a19-83f6-08302c4e816b
                Copyright © 2017 The Author(s). Published by Wolters Kluwer Health, Inc.

                This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 11 October 2016
                : 04 July 2017
                Categories
                Behavioral Health
                Custom metadata
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