Lifestyle intervention prior to IVF does not improve embryo utilization rate and cumulative live birth rate in women with obesity:a nested cohort study

STUDY QUESTION: Does lifestyle intervention consisting of an energy-restricted diet, enhancement of physical activity and motivational counseling prior to IVF improve embryo utilization rate (EUR) and cumulative live birth rate (CLBR) in women with obesity? SUMMARY ANSWER: A 6-month lifestyle intervention preceding IVF improved neither EUR nor CLBR in women with obesity in the first IVF treatment cycle where at least one oocyte was retrieved. WHAT IS KNOWN ALREADY: A randomized controlled trial (RCT) evaluating the efficacy of a low caloric liquid formula diet (LCD) preceding IVF in women with obesity was unable to demonstrate an effect of LCD on embryo quality and live birth rate: in this study, only one fresh embryo transfer (ET) or, in case of freeze-all strategy, the first transfer with frozen-thawed embryos was reported. We hypothesized that any effect on embryo quality of a lifestyle intervention in women with obesity undergoing IVF treatment is better revealed by EUR and CLBR after transfer of all fresh and frozen-thawed embryos. STUDY DESIGN, SIZE, DURATION: This is a nested cohort study within an RCT, the LIFEstyle study. The original study examined whether a 6-month lifestyle intervention prior to infertility treatment in women with obesity improved live birth rate, compared to prompt infertility treatment within 24 months after randomization. In the original study between 2009 and 2012, 577 (three women withdrew informed consent) women with obesity and infertility were assigned to a lifestyle intervention followed by infertility treatment (n = 289) or to prompt infertility treatment (n = 285). PARTICIPANTS/MATERIALS, SETTING, METHODS: Only participants from the LIFEstyle study who received IVF treatment were eligible for the current analysis. In total, 137 participants (n = 58 in the intervention group and n = 79 in the control group) started the first cycle. In 25 participants, the first cycle was cancelled prior to oocyte retrieval mostly due to poor response. Sixteen participants started a second or third consecutive cycle. The first cycle with successful oocyte retrieval was used for this analysis, resulting in analysis of 51 participants in the intervention group and 72 participants in the control group. Considering differences in embryo scoring methods and ET day strategy between IVF centers, we used EUR as a proxy for embryo quality. EUR was defined as the proportion of inseminated/injected oocytes per cycle that was transferred or cryopreserved as an embryo. Analysis was performed per cycle and per oocyte/embryo. CLBR was defined as the percentage of participants with at least one live birth from the first fresh and subsequent frozen-thawed ET(s). In addition, we calculated the Z-score for singleton neonatal birthweight and compared these outcomes between the two groups. MAIN RESULTS AND THE ROLE OF CHANCE: The overall mean age was 31.6 years and the mean BMI was 35.4 ± 3.2 kg/m(2) in the intervention group, and 34.9 ± 2.9 kg/m(2) in the control group. The weight change at 6 months was in favor of the intervention group (mean difference in kg vs the control group: −3.14, 95% CI: −5.73 to −0.56). The median (Q25; Q75) number of oocytes retrieved was 4.00 (2.00; 8.00) in the intervention group versus 6.00 (4.00; 9.75) in the control group, and was not significantly different, as was the number of oocytes inseminated/injected (4.00 [2.00; 8.00] vs 6.00 [3.00; 8.75]), normal fertilized embryos (2.00 [0.50; 5.00] vs 3.00 [1.00; 5.00]) and the number of cryopreserved embryos (2.00 [1.25; 4.75] vs 2.00 [1.00; 4.00]). The median (Q25; Q75) EUR was 33.3% (12.5%; 60.0%) in the intervention group and 33.3% (16.7%; 50.0%) in the control group in the per cycle analysis (adjusted B: 2.7%, 95% CI: −8.6% to 14.0%). In the per oocyte/embryo analysis, in total, 280 oocytes were injected or inseminated in the intervention group, 113 were utilized (transferred or cryopreserved, EUR = 40.4%); in the control group, EUR was 30.8% (142/461). The lifestyle intervention did not significantly improve EUR (adjusted odds ratio [OR]: 1.36, 95% CI: 0.94–1.98) in the per oocyte/embryo analysis, taking into account the interdependency of the oocytes per participant. CLBR was not significantly different between the intervention group and the control group after adjusting for type of infertility (male factor and unexplained) and smoking (27.5% vs 22.2%, adjusted OR: 1.03, 95% CI: 0.43–2.47). Singleton neonatal birthweight and Z-score were not significantly different between the two groups. LIMITATIONS, REASONS FOR CAUTION: This study is a nested cohort study within an RCT, and no power calculation was performed. The randomization was not stratified for indicated treatment, and although we corrected our analyses for baseline differences, there may be residual confounding. The limited absolute weight loss and the short duration of the lifestyle intervention might be insufficient to affect EUR and CLBR. WIDER IMPLICATIONS OF THE FINDINGS: Our data do not support the hypothesis of a beneficial short-term effect of lifestyle intervention on EUR and CLBR after IVF in women with obesity, although more studies are needed as there may be a potential clinically relevant effect on EUR. STUDY FUNDING/COMPETING INTEREST(S): The study was supported by a grant from ZonMw, the Dutch Organization for Health Research and Development (50-50110-96-518). A.H. has received an unrestricted educational grant from Ferring pharmaceuticals BV, The Netherlands. B.W.J.M. is supported by an NHMRC Investigator grant (GNT1176437). B.W.J.M. reports consultancy for Guerbet, has been a member of the ObsEva advisory board and holds Stock options for ObsEva. B.W.J.M. has received research funding from Guerbet, Ferring and Merck. F.J.M.B. reports personal fees from membership of the external advisory board for Merck Serono and a research support grant from Merck Serono, outside the submitted work. TRIAL REGISTRATION NUMBER: The LIFEstyle RCT was registered at the Dutch trial registry (NTR 1530). https://www.trialregister.nl/trialreg/admin/rctview.asp?TC=1530

Cumulative live birth rates in low-prognosis women

STUDY QUESTION: Do cumulative live birth rates (CLBRs) over multiple IVF/ICSI cycles confirm the low prognosis in women stratified according to the POSEIDON criteria? SUMMARY ANSWER: The CLBR of low-prognosis women is ~56% over 18 months of IVF/ICSI treatment and varies between the POSEIDON groups, which is primarily attributable to the impact of female age. WHAT IS KNOWN ALREADY: The POSEIDON group recently proposed a new stratification for low-prognosis women in IVF/ICSI treatment, with the aim to define more homogenous populations for clinical trials and stimulate a patient-tailored therapeutic approach. These new criteria combine qualitative and quantitative parameters to create four groups of low-prognosis women with supposedly similar biologic characteristics. STUDY DESIGN, SIZE, DURATION: This study analyzed the data of a Dutch multicenter observational cohort study including 551 low-prognosis women, aged <44 years, who initiated IVF/ICSI treatment between 2011 and 2014 and were treated with a fixed FSH dose of 150 IU/day in the first treatment cycle. PARTICIPANTS/MATERIALS, SETTING, METHODS: Low-prognosis women were categorized into one of the POSEIDON groups based on their age (younger or older than 35 years), anti-Müllerian hormone (AMH) level (above or below 0.96 ng/ml), and the ovarian response (poor or suboptimal) in their first cycle of standard stimulation. The primary outcome was the CLBR over multiple complete IVF/ICSI cycles, including all subsequent fresh and frozen-thawed embryo transfers, within 18 months of treatment. Cumulative incidence curves were obtained using an optimistic and a conservative analytic approach. MAIN RESULTS AND THE ROLE OF CHANCE: The CLBR of the low-prognosis women was on average ~56% over 18 months of IVF/ICSI treatment. Younger unexpected poor (n = 38) and suboptimal (n = 179) responders had a CLBR of ~65% and ~68%, respectively, and younger expected poor responders (n = 65) had a CLBR of ~59%. The CLBR of older unexpected poor (n = 41) and suboptimal responders (n = 102) was ~42% and ~54%, respectively, and of older expected poor responders (n = 126) ~39%. For comparison, the CLBR of younger (n = 164) and older (n = 78) normal responders with an adequate ovarian reserve was ~72% and ~58% over 18 months of treatment, respectively. No large differences were observed in the number of fresh treatment cycles between the POSEIDON groups, with an average of two fresh cycles per woman within 18 months of follow-up. LIMITATIONS, REASONS FOR CAUTION: Small numbers in some (sub)groups reduced the precision of the estimates. However, our findings provide the first relevant indication of the CLBR of low-prognosis women in the POSEIDON groups. Small FSH dose adjustments between cycles were allowed, inducing therapeutic disparity. Yet, this is in accordance with current daily practice and increases the generalizability of our findings. WIDER IMPLICATIONS OF THE FINDINGS: The CLBRs vary between the POSEIDON groups. This heterogeneity is primarily determined by a woman's age, reflecting the importance of oocyte quality. In younger women, current IVF/ICSI treatment reaches relatively high CLBR over multiple complete cycles, despite reduced quantitative parameters. In older women, the CLBR remains relatively low over multiple complete cycles, due to the co-occurring decline in quantitative and qualitative parameters. As no effective interventions exist to counteract this decline, clinical management currently relies on proper counselling. STUDY FUNDING/COMPETING INTEREST(S): No external funds were obtained for this study. J.A.L. is supported by a Research Fellowship grant and received an unrestricted personal grant from Merck BV. S.C.O., T.C.v.T., and H.L.T. received an unrestricted personal grant from Merck BV. C.B.L. received research grants from Merck, Ferring, and Guerbet. K.F. received unrestricted research grants from Merck Serono, Ferring, and GoodLife. She also received fees for lectures and consultancy from Ferring and GoodLife. A.H. declares that the Department of Obstetrics and Gynaecology, University Medical Centre Groningen received an unrestricted research grant from Ferring Pharmaceuticals BV, the Netherlands. J.S.E.L. has received unrestricted research grants from Ferring, Zon-MW, and The Dutch Heart Association. He also received travel grants and consultancy fees from Danone, Euroscreen, Ferring, AnshLabs, and Titus Healthcare. B.W.J.M. is supported by an National Health and Medical Research Council Practitioner Fellowship (GNT1082548) and reports consultancy work for ObsEva, Merck, and Guerbet. He also received a research grant from Merck BV and travel support from Guerbet. F.J.M.B. received monetary compensation as a member of the external advisory board for Merck Serono (the Netherlands) and Ferring Pharmaceuticals BV (the Netherlands) for advisory work for Gedeon Richter (Belgium) and Roche Diagnostics on automated AMH assay development, and for a research cooperation with Ansh Labs (USA). All other authors have nothing to declare. TRIAL REGISTRATION NUMBER: Not applicable

Effect of a lifestyle intervention in obese infertile women on cardiometabolic health and quality of life:A randomized controlled trial

BACKGROUND:The prevalence of obesity, an important cardiometabolic risk factor, is rising in women. Lifestyle improvements are the first step in treatment of obesity, but the success depends on factors like timing and motivation. Women are especially receptive to advice about lifestyle before and during pregnancy. Therefore, we hypothesize that the pre-pregnancy period provides the perfect window of opportunity to improve cardiometabolic health and quality of life of obese infertile women, by means of a lifestyle intervention. METHODS AND FINDINGS:Between 2009-2012, 577 infertile women between 18 and 39 years of age, with a Body Mass Index of ≥ 29 kg/m2, were randomized to a six month lifestyle intervention preceding infertility treatment, or to direct infertility treatment. The goal of the intervention was 5-10% weight loss or a BMI < 29 kg/m2. Cardiometabolic outcomes included weight, waist- and hip circumference, body mass index, systolic and diastolic blood pressure, fasting glucose and insulin, HOMA-IR, hs-CRP, lipids and metabolic syndrome. All outcomes were measured by research nurses at randomization, 3 and 6 months. Self-reported quality of life was also measured at 12 months. Three participants withdrew their informed consent, and 63 participants discontinued the intervention program. Intention to treat analysis was conducted. Mixed effects regression models analyses were performed. Results are displayed as estimated mean differences between intervention and control group. Weight (-3.1 kg 95% CI: -4.0 to -2.2 kg; P < .001), waist circumference (-2.4 cm 95% CI: -3.6 to -1.1 cm; P < .001), hip circumference (-3.0 95% CI: -4.2 to -1.9 cm; P < .001), BMI (-1.2 kg/m2 95% CI: -1.5 to -0.8 kg/m2; P < .001), systolic blood pressure (-2.8 mmHg 95% CI: -5.0 to -0.7 mmHg; P = .01) and HOMA-IR (-0.5 95% CI: -0.8 to -0.1; P = .01) were lower in the intervention group compared to controls. Hs-CRP and lipids did not differ between groups. The odds ratio for metabolic syndrome in the intervention group was 0.53 (95% CI: 0.33 to 0.85; P < .01) compared to controls. Physical QoL scores were higher in the lifestyle intervention group (2.2 95% CI: 0.9 to 3.5; P = .001) while mental QoL scores did not differ. CONCLUSIONS:In obese infertile women, a lifestyle intervention prior to infertility treatment improves cardiometabolic health and self-reported physical quality of life (LIFEstyle study: Netherlands Trial Register: NTR1530)

Individualized FSH dosing based on ovarian reserve testing in women starting IVF/ICSI:A multicentre trial and cost-effectiveness analysis

STUDY QUESTION: Is there a difference in live birth rate and/or cost-effectiveness between antral follicle count (AFC)-based individualized FSH dosing or standard FSH dosing in women starting IVF or ICSI treatment? SUMMARY ANSWER: In women initiating IVF/ICSI, AFC-based individualized FSH dosing does not improve live birth rates or reduce costs as compared to a standard FSH dose. WHAT IS KNOWN ALREADY: In IVF or ICSI, ovarian reserve testing is often used to adjust the FSH dose in order to normalize ovarian response and optimize live birth rates. However, no robust evidence for the (cost-) effectiveness of this practice exists. STUDY DESIGN, SIZE, DURATION: Between May 2011 and May 2014 we performed a multicentre prospective cohort study with two embedded RCTs in women scheduled for IVF/ICSI. Based on the AFC, women entered into one of the two RCTs (RCT1: AFC 15) or the cohort (AFC 11-15). The primary outcome was ongoing pregnancy achieved within 18 months after randomization resulting in a live birth (delivery of at least one live foetus after 24 weeks of gestation). Data from the cohort with weight 0.5 were combined with both RCTs in order to conduct a strategy analysis. Potential half-integer numbers were rounded up. Differences in costs and effects between the two treatment strategies were compared by bootstrapping. PARTICIPANTS/MATERIALS, SETTING, METHODS: In both RCTs women were randomized to an individualized (RCT1: 450/225 IU, RCT2: 100 IU) or standard FSH dose (150 IU). Women in the cohort all received the standard dose (150 IU). Anti-Mullerian hormone (AMH) was measured to assess AMH post-hoc as a biomarker to individualize treatment. For RCT1 dose adjustment was allowed in subsequent cycles based on pre-specified criteria in the standard group only. For RCT2 dose adjustment was allowed in subsequent cycles in both groups. Both effectiveness and cost-effectiveness of the strategies were evaluated from an intention-to-treat perspective. MAIN RESULTS AND THE ROLE OF CHANCE: We included 1515 women, of whom 483 (31.9%) entered the cohort, 511 (33.7%) RCT1 and 521 (34.4%) RCT2. Live births occurred in 420/747 (56.3%) women in the individualized strategy and 447/769 (58.2%) women in the standard strategy (risk difference -0.019 (95% CI, -0.06 to 0.02), P = 0.39; a total of 1516 women due to rounding up the half integer numbers). The individualized strategy was more expensive (delta costs/woman = (sic)275 (95% CI, 40 to 499)). Individualized dosing reduced the occurrence of mild and moderate ovarian hyperstimulation syndrome (OHSS) and subsequently the costs for management of these OHSS categories (costs saved/woman were (sic)35). The analysis based on AMH as a tool for dose individualization suggested comparable results. LIMITATIONS, REASONS FOR CAUTION: Despite a training programme, the AFC might have suffered from inter-observer variation. In addition, although strict cancel criteria were provided, selective cancelling in the individualized dose group (for poor response in particular) cannot be excluded as observers were not blinded for the FSH dose and small dose adjustments were allowed in subsequent cycles. However, as both first cycle live birth rates and cumulative live birth rates show no difference between strategies, the open design probably did not mask a potential benefit for the individualized group. Despite increasing consensus on using GnRH antagonist co-treatment in women predicted for a hyper response in particular, GnRH agonists were used in almost 80% of the women in this study. Hence, in those women, the AFC and bloodsampling for the post-hoc AMH analysis were performed during pituitary suppression. As the correlation between AFC and ovarian response is not compromised during GnRH agonist use, this will probably not have influenced classification of response. WIDER IMPLICATIONS OF THE FINDINGS: Individualized FSH dosing for the IVF/ICSI population as a whole should not be pursued as it does not improve live birth rates and it increases costs. Women scheduled for IVF/ICSI with a regular menstrual cycle are therefore recommended a standard FSH starting dose of 150 IU per day. Still, safety management by individualized dosing in predicted hyper responders is open for further research

ALIFE2 study::low-molecular-weight heparin for women with recurrent miscarriage and inherited thrombophilia - study protocol for a randomized controlled trial

Background A large number of studies have shown an association between inherited thrombophilia and recurrent miscarriage. It has been hypothesized that anticoagulant therapy might reduce the number of miscarriages and stillbirth in these women. In the absence of randomized controlled trials evaluating the efficacy of anticoagulant therapy in women with inherited thrombophilia and recurrent miscarriage, a randomized trial with adequate power that addresses this question is needed. The objective of the ALIFE2 study is therefore to evaluate the efficacy of low-molecular-weight heparin (LMWH) in women with inherited thrombophilia and recurrent miscarriage, with live birth as the primary outcome. Methods/Design Randomized study of LMWH plus standard pregnancy surveillance versus standard pregnancy surveillance alone. Study population: pregnant women of less than 7 weeks’ gestation, and confirmed inherited thrombophilia with a history of 2 or more miscarriages or intra-uterine fetal deaths, or both. Setting: multi-center study in centers from the Dutch Consortium of Fertility studies; centers outside the Netherlands are currently preparing to participate. Intervention: LMWH enoxaparin 40 mg subcutaneously once daily started prior to 7 weeks gestational age plus standard pregnancy surveillance or standard pregnancy surveillance alone. Main study parameters/endpoints: the primary efficacy outcome is live birth. Secondary efficacy outcomes include adverse pregnancy outcomes, such as miscarriage, pre-eclampsia, syndrome of hemolysis, elevated liver enzymes and low platelets (HELLP syndrome), fetal growth restriction, placental abruption, premature delivery and congenital malformations. Safety outcomes include bleeding episodes, thrombocytopenia and skin reactions. Discussion After an initial period of slow recruitment, the recruitment rate for the study has increased. Improved awareness of the study and acknowledgement of the need for evidence are thought to be contributing to the improved recruitment rates. We aim to increase the number of recruiting centers in order to increase enrollment into the ALIFE2 study. The study website can be accessed via www.ALIFE2study.org. Trial registration The ALIFE2 study was registered on 19 March 2012 under registration number NTR336

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015

Forouzanfar MH, Afshin A, Alexander LT, et al. Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015. LANCET. 2016;388(10053):1659-1724.Background The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors-the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57.8% (95% CI 56.6-58.8) of global deaths and 41.2% (39.8-42.8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211.8 million [192.7 million to 231.1 million] global DALYs), smoking (148.6 million [134.2 million to 163.1 million]), high fasting plasma glucose (143.1 million [125.1 million to 163.5 million]), high BMI (120.1 million [83.8 million to 158.4 million]), childhood undernutrition (113.3 million [103.9 million to 123.4 million]), ambient particulate matter (103.1 million [90.8 million to 115.1 million]), high total cholesterol (88.7 million [74.6 million to 105.7 million]), household air pollution (85.6 million [66.7 million to 106.1 million]), alcohol use (85.0 million [77.2 million to 93.0 million]), and diets high in sodium (83.0 million [49.3 million to 127.5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Copyright (C) The Author(s). Published by Elsevier Ltd

Global, regional, and national disability-adjusted life-years (DALYs) for 315 diseases and injuries and healthy life expectancy (HALE), 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015.

BACKGROUND: Healthy life expectancy (HALE) and disability-adjusted life-years (DALYs) provide summary measures of health across geographies and time that can inform assessments of epidemiological patterns and health system performance, help to prioritise investments in research and development, and monitor progress toward the Sustainable Development Goals (SDGs). We aimed to provide updated HALE and DALYs for geographies worldwide and evaluate how disease burden changes with development. METHODS: We used results from the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015) for all-cause mortality, cause-specific mortality, and non-fatal disease burden to derive HALE and DALYs by sex for 195 countries and territories from 1990 to 2015. We calculated DALYs by summing years of life lost (YLLs) and years of life lived with disability (YLDs) for each geography, age group, sex, and year. We estimated HALE using the Sullivan method, which draws from age-specific death rates and YLDs per capita. We then assessed how observed levels of DALYs and HALE differed from expected trends calculated with the Socio-demographic Index (SDI), a composite indicator constructed from measures of income per capita, average years of schooling, and total fertility rate. FINDINGS: Total global DALYs remained largely unchanged from 1990 to 2015, with decreases in communicable, neonatal, maternal, and nutritional (Group 1) disease DALYs offset by increased DALYs due to non-communicable diseases (NCDs). Much of this epidemiological transition was caused by changes in population growth and ageing, but it was accelerated by widespread improvements in SDI that also correlated strongly with the increasing importance of NCDs. Both total DALYs and age-standardised DALY rates due to most Group 1 causes significantly decreased by 2015, and although total burden climbed for the majority of NCDs, age-standardised DALY rates due to NCDs declined. Nonetheless, age-standardised DALY rates due to several high-burden NCDs (including osteoarthritis, drug use disorders, depression, diabetes, congenital birth defects, and skin, oral, and sense organ diseases) either increased or remained unchanged, leading to increases in their relative ranking in many geographies. From 2005 to 2015, HALE at birth increased by an average of 2·9 years (95% uncertainty interval 2·9-3·0) for men and 3·5 years (3·4-3·7) for women, while HALE at age 65 years improved by 0·85 years (0·78-0·92) and 1·2 years (1·1-1·3), respectively. Rising SDI was associated with consistently higher HALE and a somewhat smaller proportion of life spent with functional health loss; however, rising SDI was related to increases in total disability. Many countries and territories in central America and eastern sub-Saharan Africa had increasingly lower rates of disease burden than expected given their SDI. At the same time, a subset of geographies recorded a growing gap between observed and expected levels of DALYs, a trend driven mainly by rising burden due to war, interpersonal violence, and various NCDs. INTERPRETATION: Health is improving globally, but this means more populations are spending more time with functional health loss, an absolute expansion of morbidity. The proportion of life spent in ill health decreases somewhat with increasing SDI, a relative compression of morbidity, which supports continued efforts to elevate personal income, improve education, and limit fertility. Our analysis of DALYs and HALE and their relationship to SDI represents a robust framework on which to benchmark geography-specific health performance and SDG progress. Country-specific drivers of disease burden, particularly for causes with higher-than-expected DALYs, should inform financial and research investments, prevention efforts, health policies, and health system improvement initiatives for all countries along the development continuum. FUNDING: Bill & Melinda Gates Foundation

Measuring the health-related Sustainable Development Goals in 188 countries : a baseline analysis from the Global Burden of Disease Study 2015

Background In September, 2015, the UN General Assembly established the Sustainable Development Goals (SDGs). The SDGs specify 17 universal goals, 169 targets, and 230 indicators leading up to 2030. We provide an analysis of 33 health-related SDG indicators based on the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015). Methods We applied statistical methods to systematically compiled data to estimate the performance of 33 health-related SDG indicators for 188 countries from 1990 to 2015. We rescaled each indicator on a scale from 0 (worst observed value between 1990 and 2015) to 100 (best observed). Indices representing all 33 health-related SDG indicators (health-related SDG index), health-related SDG indicators included in the Millennium Development Goals (MDG index), and health-related indicators not included in the MDGs (non-MDG index) were computed as the geometric mean of the rescaled indicators by SDG target. We used spline regressions to examine the relations between the Socio-demographic Index (SDI, a summary measure based on average income per person, educational attainment, and total fertility rate) and each of the health-related SDG indicators and indices. Findings In 2015, the median health-related SDG index was 59.3 (95% uncertainty interval 56.8-61.8) and varied widely by country, ranging from 85.5 (84.2-86.5) in Iceland to 20.4 (15.4-24.9) in Central African Republic. SDI was a good predictor of the health-related SDG index (r(2) = 0.88) and the MDG index (r(2) = 0.2), whereas the non-MDG index had a weaker relation with SDI (r(2) = 0.79). Between 2000 and 2015, the health-related SDG index improved by a median of 7.9 (IQR 5.0-10.4), and gains on the MDG index (a median change of 10.0 [6.7-13.1]) exceeded that of the non-MDG index (a median change of 5.5 [2.1-8.9]). Since 2000, pronounced progress occurred for indicators such as met need with modern contraception, under-5 mortality, and neonatal mortality, as well as the indicator for universal health coverage tracer interventions. Moderate improvements were found for indicators such as HIV and tuberculosis incidence, minimal changes for hepatitis B incidence took place, and childhood overweight considerably worsened. Interpretation GBD provides an independent, comparable avenue for monitoring progress towards the health-related SDGs. Our analysis not only highlights the importance of income, education, and fertility as drivers of health improvement but also emphasises that investments in these areas alone will not be sufficient. Although considerable progress on the health-related MDG indicators has been made, these gains will need to be sustained and, in many cases, accelerated to achieve the ambitious SDG targets. The minimal improvement in or worsening of health-related indicators beyond the MDGs highlight the need for additional resources to effectively address the expanded scope of the health-related SDGs.Peer reviewe

Validation of the Measurement of Intra-abdominal Fat Between Ultrasound and CT Scan in Women with Obesity and Infertility

Objective: To compare the means and changes over time of intra-abdominal fat (IAF) and subcutaneous abdominal fat (SAF) measured by abdominal ultrasound (US) and computerized tomography (CT). Design and Methods: Prospective cohort study of 53 women with obesity and infertility undergoing a lifestyle program. Results: The Pearson's correlation between IAF measurement by US compared to CT was good at baseline, month 3 and 6 (all r >= 0.72). The correlation of SAF measurement by US compared to CT was reasonable at baseline (r = 0.54; 95%CI 0.30-0.78) and weak at month 3 and 6 (all r 0.48). US could not measure the changes of SAF over time. The Bland-Altman plot showed good agreement between US and CT for IAF measurements (-1.1 [95%CI - 3.9-1.6] cm lower mean in US) at baseline. For changes of IAF over time, mean estimates were in agreement. Conclusion: In women with obesity and infertility, measuring IAF by US is in good agreement with the CT scan methodology but the measurement of SAF by US is unreliable

Value-based healthcare in fertility care using relevant outcome measures for the full cycle of care leading towards shared decision-making: a retrospective cohort study

Objective To determine if the introduction of value-based healthcare (VBHC) in fertility care can help to create realistic expectations in patients resulting in increased patient value, by demonstrating the relevance of defining outcome measures that truly matter to subfertile patients.Design Retrospective cohort study.Setting Tertiary fertility centre.Results Time to pregnancy (TTP) and ongoing pregnancy rate (OPR), as a proxy for the live birth rate, for the full cycle of fertility care, regardless of which and how many treatment cycles performed, were identified as the most relevant medical outcome measures. Outcome measures were incorporated into a digital dashboard by using anonymised and validated patient data from the electronic patient file. We were able to present the TTP and OPR for the population as a whole as well as stratified for age, diagnosis, gravidity and type of gamete source used thereby resulting in a virtual ‘patient like me’ resembling the individual patient in the consultation room.Conclusion We have shown that, by applying VBHC principles, relevant outcome measures can be generated and stratified for different patient characteristics, in order to develop a virtual ‘patient like me’. This virtual ‘patient like me’ can be used in the consulting room in the form of a digital dashboard, attributing to create realistic patient expectations. This facilitates healthcare providers and patients in shared decision-making