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      Female adiposity and time-to-pregnancy: a multiethnic prospective cohort

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          Abstract

          <div class="section"> <a class="named-anchor" id="S1"> <!-- named anchor --> </a> <h5 class="section-title" id="d3732691e364">Study question</h5> <p id="P1">Are higher overall and central adiposity associated with reduced fecundability, measured by time-to-pregnancy (TTP), in Asian women? </p> </div><div class="section"> <a class="named-anchor" id="S2"> <!-- named anchor --> </a> <h5 class="section-title" id="d3732691e369">Summary answer</h5> <p id="P2">Higher overall adiposity, but not central adiposity, was associated with longer TTP in Asian women. </p> </div><div class="section"> <a class="named-anchor" id="S3"> <!-- named anchor --> </a> <h5 class="section-title" id="d3732691e374">What is known already</h5> <p id="P3">High body mass index (BMI) has been associated with a longer TTP, although the associations of body composition and distribution with TTP are less clear. There are no previous studies of TTP in Asian women, who have a relatively higher percentage of body fat and abdominal fat at relatively lower BMI. </p> </div><div class="section"> <a class="named-anchor" id="S4"> <!-- named anchor --> </a> <h5 class="section-title" id="d3732691e379">Study design, size, duration</h5> <p id="P4">Prospective preconception cohort using data from 477 Asian (Chinese, Malay and Indian) women who were planning to conceive and enrolled in the Singapore PREconception Study of long-Term maternal and child Outcomes (S-PRESTO) study, 2015-2017. </p> </div><div class="section"> <a class="named-anchor" id="S5"> <!-- named anchor --> </a> <h5 class="section-title" id="d3732691e384">Participants/materials, setting, methods</h5> <p id="P5">Women’s mean age was 30.7 years. Overall adiposity was assessed by BMI, sum of 4-site skinfold thicknesses (SFT) and total body fat percentage (TBF%, measured using air displacement plethysmography); central adiposity was assessed by waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR) and A body Shape Index (ABSI). Pregnancy occurring within one year from recruitment was ascertained by ultrasonography. Those who did not conceive within one year of recruitment, were lost to follow-up, or initiated fertility treatment were censored. TTP was measured in cycles. Discrete-time proportional hazards models were used to estimate the fecundability ratio (FR) and 95% confidence interval (CI) for each anthropometric measure in association with fecundability, adjusting for confounders. </p> </div><div class="section"> <a class="named-anchor" id="S6"> <!-- named anchor --> </a> <h5 class="section-title" id="d3732691e389">Main results and the role of chance</h5> <p id="P6">Compared to women with a normal BMI of 18.5-22.9 kg/m <sup>2</sup>, women with higher BMI of 23-27.4 and ≥27.5 kg/m <sup>2</sup> showed lower FR of 0.66 (95% CI 0.45, 0.97) and 0.53 (0.31, 0.89), respectively. Compared to women in the lowest quartile of SFT (25-52.9mm), those in the highest quartile of ≥90.1 mm showed lower FR of 0.58 (95% CI 0.36, 0.95). Compared to women in the lowest quartile of TBF% (13.6-27.2%), those in the upper two quartiles of 33.0-39.7% and ≥39.8% showed lower FR of 0.56 (95% CI 0.32, 0.98) and 0.43 (0.24, 0.80), respectively. Association of high BMI with reduced fecundability was particularly evident among nulliparous women. Measures of central adiposity (WC, WHR, WHtR, ABSI) were not associated with fecundability. </p> </div><div class="section"> <a class="named-anchor" id="S7"> <!-- named anchor --> </a> <h5 class="section-title" id="d3732691e400">Limitations, reasons for caution</h5> <p id="P7">Small sample size could restrict power of analysis.The analysis was confined to planned pregnancies, which could limit generalizability of findings to non-planned pregnancies, estimated at around 44% in Singapore. Information on the date of last menstrual period for each month was not available, hence the accuracy of self-reported menstrual cycle length could not be validated, potentially introducing error into TTP estimation. Measures of exposures and covariates such as cycle length were not performed repeatedly over time; cycle length might have changed during the period before getting pregnant. </p> </div><div class="section"> <a class="named-anchor" id="S8"> <!-- named anchor --> </a> <h5 class="section-title" id="d3732691e405">Wider implications of the findings</h5> <p id="P8">Other than using BMI as the surrogate measure of body fat, we provide additional evidence showing that higher amounts of subcutaneous fat that based on the measure of SFT at the sites of biceps, triceps, suprailiac and subscapular, and TBF% are associated with longer TTP. Achieving optimal weight and reducing total percentage body fat may be a potential intervention target to improve female fertility. The null results observed between central adiposity and TTP requires confirmation in further studies. </p> </div><div class="section"> <a class="named-anchor" id="S9"> <!-- named anchor --> </a> <h5 class="section-title" id="d3732691e410">Study funding/competing interest(s)</h5> <p id="P9">This research is supported by Singapore National Research Foundation under its Translational and Clinical Research Flagship Programme and administered by the Singapore Ministry of Health’s National Medical Research Council, (NMRC/TCR/004-NUS/2008; NMRC/TCR/012-NUHS/2014). Additional funding is provided by the Singapore Institute for Clinical Sciences, Agency for Science Technology and Research (A*STAR), Singapore. Y.S.C., K.M.G., F.Y. and Y.S.L. have received reimbursement to speak at conferences sponsored by companies selling nutritional products. Y.S.C., K.M.G. and S.Y.C. are part of an academic consortium that has received research funding from Abbott, Nutrition, Nestle and Danone. Other authors declared no conflicts of interest. </p> </div><div class="section"> <a class="named-anchor" id="S10"> <!-- named anchor --> </a> <h5 class="section-title" id="d3732691e415">Trial registration number</h5> <p id="P10">N/A.</p> </div>

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          Most cited references17

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          Trends in adult body-mass index in 200 countries from 1975 to 2014: a pooled analysis of 1698 population-based measurement studies with 19·2 million participants

          Summary Background Underweight and severe and morbid obesity are associated with highly elevated risks of adverse health outcomes. We estimated trends in mean body-mass index (BMI), which characterises its population distribution, and in the prevalences of a complete set of BMI categories for adults in all countries. Methods We analysed, with use of a consistent protocol, population-based studies that had measured height and weight in adults aged 18 years and older. We applied a Bayesian hierarchical model to these data to estimate trends from 1975 to 2014 in mean BMI and in the prevalences of BMI categories (<18·5 kg/m2 [underweight], 18·5 kg/m2 to <20 kg/m2, 20 kg/m2 to <25 kg/m2, 25 kg/m2 to <30 kg/m2, 30 kg/m2 to <35 kg/m2, 35 kg/m2 to <40 kg/m2, ≥40 kg/m2 [morbid obesity]), by sex in 200 countries and territories, organised in 21 regions. We calculated the posterior probability of meeting the target of halting by 2025 the rise in obesity at its 2010 levels, if post-2000 trends continue. Findings We used 1698 population-based data sources, with more than 19·2 million adult participants (9·9 million men and 9·3 million women) in 186 of 200 countries for which estimates were made. Global age-standardised mean BMI increased from 21·7 kg/m2 (95% credible interval 21·3–22·1) in 1975 to 24·2 kg/m2 (24·0–24·4) in 2014 in men, and from 22·1 kg/m2 (21·7–22·5) in 1975 to 24·4 kg/m2 (24·2–24·6) in 2014 in women. Regional mean BMIs in 2014 for men ranged from 21·4 kg/m2 in central Africa and south Asia to 29·2 kg/m2 (28·6–29·8) in Polynesia and Micronesia; for women the range was from 21·8 kg/m2 (21·4–22·3) in south Asia to 32·2 kg/m2 (31·5–32·8) in Polynesia and Micronesia. Over these four decades, age-standardised global prevalence of underweight decreased from 13·8% (10·5–17·4) to 8·8% (7·4–10·3) in men and from 14·6% (11·6–17·9) to 9·7% (8·3–11·1) in women. South Asia had the highest prevalence of underweight in 2014, 23·4% (17·8–29·2) in men and 24·0% (18·9–29·3) in women. Age-standardised prevalence of obesity increased from 3·2% (2·4–4·1) in 1975 to 10·8% (9·7–12·0) in 2014 in men, and from 6·4% (5·1–7·8) to 14·9% (13·6–16·1) in women. 2·3% (2·0–2·7) of the world’s men and 5·0% (4·4–5·6) of women were severely obese (ie, have BMI ≥35 kg/m2). Globally, prevalence of morbid obesity was 0·64% (0·46–0·86) in men and 1·6% (1·3–1·9) in women. Interpretation If post-2000 trends continue, the probability of meeting the global obesity target is virtually zero. Rather, if these trends continue, by 2025, global obesity prevalence will reach 18% in men and surpass 21% in women; severe obesity will surpass 6% in men and 9% in women. Nonetheless, underweight remains prevalent in the world’s poorest regions, especially in south Asia. Funding Wellcome Trust, Grand Challenges Canada.
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            A New Body Shape Index Predicts Mortality Hazard Independently of Body Mass Index

            Background Obesity, typically quantified in terms of Body Mass Index (BMI) exceeding threshold values, is considered a leading cause of premature death worldwide. For given body size (BMI), it is recognized that risk is also affected by body shape, particularly as a marker of abdominal fat deposits. Waist circumference (WC) is used as a risk indicator supplementary to BMI, but the high correlation of WC with BMI makes it hard to isolate the added value of WC. Methods and Findings We considered a USA population sample of 14,105 non-pregnant adults ( ) from the National Health and Nutrition Examination Survey (NHANES) 1999–2004 with follow-up for mortality averaging 5 yr (828 deaths). We developed A Body Shape Index (ABSI) based on WC adjusted for height and weight: ABSI had little correlation with height, weight, or BMI. Death rates increased approximately exponentially with above average baseline ABSI (overall regression coefficient of per standard deviation of ABSI [95% confidence interval: – ]), whereas elevated death rates were found for both high and low values of BMI and WC. ( – ) of the population mortality hazard was attributable to high ABSI, compared to ( – ) for BMI and ( – ) for WC. The association of death rate with ABSI held even when adjusted for other known risk factors including smoking, diabetes, blood pressure, and serum cholesterol. ABSI correlation with mortality hazard held across the range of age, sex, and BMI, and for both white and black ethnicities (but not for Mexican ethnicity), and was not weakened by excluding deaths from the first 3 yr of follow-up. Conclusions Body shape, as measured by ABSI, appears to be a substantial risk factor for premature mortality in the general population derivable from basic clinical measurements. ABSI expresses the excess risk from high WC in a convenient form that is complementary to BMI and to other known risk factors.
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              Obesity and time to pregnancy.

              Obesity may reduce fecundity. We examined the obesity-fecundity association in relation to menstrual cycle regularity, parity, smoking habits and age to gain insight into mechanisms and susceptible subgroups. Data were provided by 7327 pregnant women enrolled in the Collaborative Perinatal Project at 12 study centres in the United States from 1959 to 1965. Prepregnancy body mass index (BMI) was analysed continuously and categorically [underweight ( or=30.0 kg/m2)]. Adjusted fecundability odds ratios (FORs) were estimated using Cox proportional hazards modelling for discrete time data. Fecundity was reduced for overweight [OR=0.92, 95% confidence interval (95% CI): 0.84, 1.01] and obese (OR=0.82, 95% CI: 0.72, 0.95) women compared with optimal weight women and was more evident for obese primiparous women (OR=0.66, 95% CI: 0.49, 0.89). Fecundity remained reduced for overweight and obese women with normal menstrual cycles. Neither smoking habits nor age modified the association. Obesity was associated with reduced fecundity for all subgroups of women and persisted for women with regular cycles. Our results suggest that weight loss could increase fecundity for overweight and obese women, regardless of menstrual cycle regularity, parity, smoking habits and age.
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                Author and article information

                Contributors
                Journal
                Human Reproduction
                Oxford University Press (OUP)
                0268-1161
                1460-2350
                November 2018
                November 01 2018
                October 04 2018
                November 2018
                November 01 2018
                October 04 2018
                : 33
                : 11
                : 2141-2149
                Affiliations
                [1 ]Department of Reproductive Medicine, KK Women’s and Children’s Hospital, Singapore, Singapore
                [2 ]Duke-NUS Medical School, Singapore, Singapore
                [3 ]Center for Quantitative Medicine, Duke-NUS Medical School, Singapore, Singapore
                [4 ]Tampere Center for Child Health Research, University of Tampere and Tampere University Hospital, Tampere, Finland
                [5 ]Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
                [6 ]Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, National University Health System, Singapore, Singapore
                [7 ]Department of Obstetrics & Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, National University Health System, Singapore, Singapore
                [8 ]Early Origins of the Child’s Health and Development Unit, Centre for research in Epidemiology and Statistics Sorbonne Paris Cité, Inserm, Villejuif, France
                [9 ]Department of Obstetrics & Gynaecology, National University Hospital, Singapore, Singapore
                [10 ]Medical Research Council Lifecourse Epidemiology Unit, University of Southampton, Southampton, United Kingdom
                [11 ]National Institute for Health Research Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton National Health Service Foundation Trust, Southampton, UK
                [12 ]Khoo Teck Puat-National University Children’s Medical Institute, National University Hospital, National University Health System, Singapore, Singapore
                [13 ]Department of Maternal Fetal Medicine, KK Women’s and Children’s Hospital, Singapore, Singapore
                [14 ]Department of Obstetrics & Gynaecology, KK Women’s and Children’s Hospital, Singapore, Singapore
                [15 ]Department of Paediatrics, KK Women’s and Children’s Hospital, Singapore, Singapore
                [16 ]Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
                Article
                10.1093/humrep/dey300
                6201836
                30285230
                986b5ca5-c4c9-41b8-8a1f-03658fec79cd
                © 2018

                https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model

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