Social inequalities in pregnancy metabolic profile: findings from the multi-ethnic Born in Bradford cohort study.

BACKGROUND: Lower socioeconomic position (SEP) associates with adverse pregnancy and perinatal outcomes and with less favourable metabolic profile in nonpregnant adults. Socioeconomic differences in pregnancy metabolic profile are unknown. We investigated association between a composite measure of SEP and pregnancy metabolic profile in White European (WE) and South Asian (SA) women. METHODS: We included 3,905 WE and 4,404 SA pregnant women from a population-based UK cohort. Latent class analysis was applied to nineteen individual, household, and area-based SEP indicators (collected by questionnaires or linkage to residential address) to derive a composite SEP latent variable. Targeted nuclear magnetic resonance spectroscopy was used to determine 148 metabolic traits from mid-pregnancy serum samples. Associations between SEP and metabolic traits were examined using linear regressions adjusted for gestational age and weighted by latent class probabilities. RESULTS: Five SEP sub-groups were identified and labelled 'Highest SEP' (48% WE and 52% SA), 'High-Medium SEP' (77% and 23%), 'Medium SEP' (56% and 44%) 'Low-Medium SEP' (21% and 79%), and 'Lowest SEP' (52% and 48%). Lower SEP was associated with more adverse levels of 113 metabolic traits, including lower high-density lipoprotein (HDL) and higher triglycerides and very low-density lipoprotein (VLDL) traits. For example, mean standardized difference (95%CI) in concentration of small VLDL particles (vs. Highest SEP) was 0.12 standard deviation (SD) units (0.05 to 0.20) for 'Medium SEP' and 0.25SD (0.18 to 0.32) for 'Lowest SEP'. There was statistical evidence of ethnic differences in associations of SEP with 31 traits, primarily characterised by stronger associations in WE women e.g., mean difference in HDL cholesterol in WE and SA women respectively (vs. Highest-SEP) was -0.30SD (-0.41 to -0.20) and -0.16SD (-0.27 to -0.05) for 'Medium SEP', and -0.62SD (-0.72 to -0.52) and -0.29SD (-0.40 to -0.20) for 'Lowest SEP'. CONCLUSIONS: We found widespread socioeconomic differences in metabolic traits in pregnant WE and SA women residing in the UK. Further research is needed to understand whether the socioeconomic differences we observe here reflect pre-conception differences or differences in the metabolic pregnancy response. If replicated, it would be important to explore if these differences contribute to socioeconomic differences in pregnancy outcomes.

The impact of reproductive factors on the metabolic profile of females from menarche to menopause.

We explore the relation between age at menarche, parity and age at natural menopause with 249 metabolic traits in over 65,000 UK Biobank women using multivariable regression, Mendelian randomization and negative control (parity only). Older age of menarche is related to a less atherogenic metabolic profile in multivariable regression and Mendelian randomization, which is largely attenuated when accounting for adult body mass index. In multivariable regression, higher parity relates to more particles and lipids in VLDL, which are not observed in male negative controls. In multivariable regression and Mendelian randomization, older age at natural menopause is related to lower concentrations of inflammation markers, but we observe inconsistent results for LDL-related traits due to chronological age-specific effects. For example, older age at menopause is related to lower LDL-cholesterol in younger women but slightly higher in older women. Our findings support a role of reproductive traits on later life metabolic profile and provide insights into identifying novel markers for the prevention of adverse cardiometabolic outcomes in women.

Integrating multiple lines of evidence to assess the effects of maternal BMI on pregnancy and perinatal outcomes.

BACKGROUND: Higher maternal pre-pregnancy body mass index (BMI) is associated with adverse pregnancy and perinatal outcomes. However, whether these associations are causal remains unclear. METHODS: We explored the relation of maternal pre-/early-pregnancy BMI with 20 pregnancy and perinatal outcomes by integrating evidence from three different approaches (i.e. multivariable regression, Mendelian randomisation, and paternal negative control analyses), including data from over 400,000 women. RESULTS: All three analytical approaches supported associations of higher maternal BMI with lower odds of maternal anaemia, delivering a small-for-gestational-age baby and initiating breastfeeding, but higher odds of hypertensive disorders of pregnancy, gestational hypertension, preeclampsia, gestational diabetes, pre-labour membrane rupture, induction of labour, caesarean section, large-for-gestational age, high birthweight, low Apgar score at 1 min, and neonatal intensive care unit admission. For example, higher maternal BMI was associated with higher risk of gestational hypertension in multivariable regression (OR = 1.67; 95% CI = 1.63, 1.70 per standard unit in BMI) and Mendelian randomisation (OR = 1.59; 95% CI = 1.38, 1.83), which was not seen for paternal BMI (OR = 1.01; 95% CI = 0.98, 1.04). Findings did not support a relation between maternal BMI and perinatal depression. For other outcomes, evidence was inconclusive due to inconsistencies across the applied approaches or substantial imprecision in effect estimates from Mendelian randomisation. CONCLUSIONS: Our findings support a causal role for maternal pre-/early-pregnancy BMI on 14 out of 20 adverse pregnancy and perinatal outcomes. Pre-conception interventions to support women maintaining a healthy BMI may reduce the burden of obstetric and neonatal complications. FUNDING: Medical Research Council, British Heart Foundation, European Research Council, National Institutes of Health, National Institute for Health Research, Research Council of Norway, Wellcome Trust.

Body mass index in parents and their adult offspring: A systematic review and meta-analysis.

Obesity may track across generations, due to genetics and shared family environmental factors, or possibly intrauterine programming. However, many studies only assess associations between maternal body mass index (BMI) and offspring BMI in childhood. To determine whether maternal and paternal associations with offspring BMI differ and whether associations persist into adulthood, a systematic review and meta-analysis was done. PubMed, Embase, Web of Science, and Google Scholar (to October 2022) were searched. Observational studies reporting associations between maternal or paternal BMI and adult offspring BMI were included. Offspring BMIs were reported as continuous or categorical measures. Forty-six studies were included in the systematic review. Meta-analyses were conducted using random-effects models. Parental BMI was positively associated with offspring BMI in adulthood. The pooled mother-offspring standardized mean difference (SMD) was 0.23 (95% confidence interval [CI]: 0.20, 0.26), and father-offspring SMD was similar: 0.22 (95% CI: 0.19, 0.25) in adjusted models. Offspring of mothers with overweight or obesity had the same risk of higher BMI as offspring of fathers with overweight or obesity. If these associations are causal, they support interventions targeting all family members, rather than focusing solely on mothers, to obtain a healthy weight development among offspring.

Effects of the maternal and fetal proteome on birth weight: a Mendelian randomization analysis.

Fetal growth is an indicator of fetal survival, regulated by maternal and fetal factors, but little is known about the underlying molecular mechanisms. We used Mendelian randomization to explore the effects of maternal and fetal genetically-instrumented plasma proteins on birth weight using genome-wide association summary data (n=406,063 with maternal and/or fetal genotype), with independent replication (n=74,932 mothers and n=62,108 offspring), and colocalisation. Higher genetically-predicted maternal levels of PCSK1 increased birthweight (mean-difference: 9g (95% CI: 5g, 13g) per 1 standard deviation protein level). Higher maternal levels of LGALS4 decreased birthweight (-54g (-29g, -80g)), as did VCAM1, RAD51D and GP1BA. In the offspring, higher genetically-predicted fetal levels of LGALS4 (46g (23g, 70g)) increased birthweight, alongside FCGR2B. Higher offspring levels of PCSK1 decreased birth weight (-9g (-16g, 4g), alongside LEPR. Results support maternal and fetal protein effects on birth weight, implicating roles for glucose metabolism, energy homeostasis, endothelial function and adipocyte differentiation.

Time-sensitive testing pressures and COVID-19 outcomes: are socioeconomic inequalities over the first year of the pandemic explained by selection bias?

BACKGROUND: There are many ways in which selection bias might impact COVID-19 research. Here we focus on selection for receiving a polymerase-chain-reaction (PCR) SARS-CoV-2 test and how known changes to selection pressures over time may bias research into COVID-19 infection. METHODS: Using UK Biobank (N = 420,231; 55% female; mean age = 66.8 [SD = 8·11]) we estimate the association between socio-economic position (SEP) and (i) being tested for SARS-CoV-2 infection versus not being tested (ii) testing positive for SARS-CoV-2 infection versus testing negative and (iii) testing negative for SARS-CoV-2 infection versus not being tested. We construct four distinct time-periods between March 2020 and March 2021, representing distinct periods of testing pressures and lockdown restrictions and specify both time-stratified and combined models for each outcome. We explore potential selection bias by examining associations with positive and negative control exposures. RESULTS: The association between more disadvantaged SEP and receiving a SARS-CoV-2 test attenuated over time. Compared to individuals with a degree, individuals whose highest educational qualification was a GCSE or equivalent had an OR of 1·27 (95% CI: 1·18 to 1·37) in March-May 2020 and 1·13 (95% CI: 1.·10 to 1·16) in January-March 2021. The magnitude of the association between educational attainment and testing positive for SARS-CoV-2 infection increased over the same period. For the equivalent comparison, the OR for testing positive increased from 1·25 (95% CI: 1·04 to 1·47), to 1·69 (95% CI: 1·55 to 1·83). We found little evidence of an association between control exposures, and any considered outcome. CONCLUSIONS: The association between SEP and SARS-CoV-2 testing changed over time, highlighting the potential of time-specific selection pressures to bias analyses of COVID-19. Positive and negative control analyses suggest that changes in the association between SEP and SARS-CoV-2 infection over time likely reflect true increases in socioeconomic inequalities.

Maternal Pre-Pregnancy BMI, Offspring Adiposity in Late Childhood, and Age of Weaning: A Causal Mediation Analysis.

Infant feeding practices have been hypothesized to influence offspring's body mass index (BMI) later in life, and women with overweight or obesity tend to wean their infants earlier than women with healthy BMI. We, therefore, aimed to investigate how much early age of weaning mediated the maternal-offspring adiposity relationship. The study included 4920 mother-child pairs from the Avon Longitudinal Study of Parents and Children birth cohort. G-computation was applied to estimate the natural direct (NDE) and indirect (NIE) effects, via the age of weaning (<3 months, 3 months, >3 months), of maternal pre-pregnancy overweight or obesity on offspring's BMI and fat mass index. The NDE of maternal overweight or obesity on offspring BMI at 17 years old was 2.63 kg/m2 (95% CI: 2.27 to 2.99). The NIE via the age of weaning was 0.02 kg/m2 (95% CI: 0.00 to 0.04), corresponding to 0.8% of the total effect. Similar results were observed for the offspring's fat mass index. The NDE and NIE were similar to the main analyses when we looked at the relationship stratified by breastfeeding status. Our study found a minimal influence of age of weaning on the pathway between maternal and offspring adiposity, indicating the age of weaning may not be a key mediator.

Maternal hemoglobin levels and adverse pregnancy outcomes: individual patient data analysis from 2 prospective UK pregnancy cohorts.

BACKGROUND: Hemoglobin (Hb) is a modifiable risk factor for adverse pregnancy outcomes. Studies have reported conflicting associations between maternal Hb levels and adverse pregnancy outcomes, including preterm birth (PTB), low birth weight (LBW), and perinatal mortality. OBJECTIVE: In this study, we aimed to estimate the shape and magnitude of associations between maternal Hb levels in early (7-12 wk gestation) and late pregnancy (27-32 wk gestation) and pregnancy outcomes in a high-income setting. METHODS: We used data from 2 UK population-based pregnancy cohorts: the Avon Longitudinal Study of Parents and Children (ALSPAC) and Pregnancy Outcome Prediction Study (POPS). We used multivariable logistic regression models to examine the relationship between Hb and pregnancy outcomes, adjusting for maternal age, ethnicity, BMI, smoking status, and parity. Main outcome measures were PTB, LBW, small for gestational age (SGA), pre-eclampsia (PET), and gestational diabetes mellitus (GDM). RESULTS: Mean Hb in ALSPAC were 12.5 g/dL (SD = 0.90) and 11.2 g/dL (SD = 0.92) in early and late pregnancy, respectively, and 12.7 g/dL (SD = 0.82) and 11.4 g/dL (SD = 0.82) in POPS. In the pooled analysis, there was no evidence of associations between a higher Hb in early pregnancy (7-12 wk gestation) and PTB (OR per 1 g/dL of Hb: 1.09; 95% CI: 0.97, 1.22), LBW (1.12: 0.99, 1.26), and SGA (1.06; 0.97, 1.15). Higher Hb in late pregnancy (27-32 wk gestation) was associated with PTB (1.45: 1.30, 1.62), LBW (1.77: 1.57, 2.01), and SGA (1.45: 1.33, 1.58). Higher Hb in early and late pregnancy was associated with PET in ALSPAC (1.36: 1.12, 1.64) and (1.53: 1.29, 1.82), respectively, but not in POPS (1.17:0.99, 1.37) and (1.03: 0.86, 1.23). There was an association with a higher Hb and GDM in ALSPAC in both early and late pregnancy [(1.51: 1.08, 2.11) and (1.35: 1.01, 1.79), respectively], but not in POPS [(0.98: 0.81, 1.19) and (0.83: 0.68, 1.02)]. CONCLUSIONS: Higher maternal Hb may identify the risk of adverse pregnancy outcomes. Further research is required to investigate if this association is causal and to identify the underlying mechanisms.

Exploring the impact of selection bias in observational studies of COVID-19: a simulation study.

BACKGROUND: Non-random selection of analytic subsamples could introduce selection bias in observational studies. We explored the potential presence and impact of selection in studies of SARS-CoV-2 infection and COVID-19 prognosis. METHODS: We tested the association of a broad range of characteristics with selection into COVID-19 analytic subsamples in the Avon Longitudinal Study of Parents and Children (ALSPAC) and UK Biobank (UKB). We then conducted empirical analyses and simulations to explore the potential presence, direction and magnitude of bias due to this selection (relative to our defined UK-based adult target populations) when estimating the association of body mass index (BMI) with SARS-CoV-2 infection and death-with-COVID-19. RESULTS: In both cohorts, a broad range of characteristics was related to selection, sometimes in opposite directions (e.g. more-educated people were more likely to have data on SARS-CoV-2 infection in ALSPAC, but less likely in UKB). Higher BMI was associated with higher odds of SARS-CoV-2 infection and death-with-COVID-19. We found non-negligible bias in many simulated scenarios. CONCLUSIONS: Analyses using COVID-19 self-reported or national registry data may be biased due to selection. The magnitude and direction of this bias depend on the outcome definition, the true effect of the risk factor and the assumed selection mechanism; these are likely to differ between studies with different target populations. Bias due to sample selection is a key concern in COVID-19 research based on national registry data, especially as countries end free mass testing. The framework we have used can be applied by other researchers assessing the extent to which their results may be biased for their research question of interest.

Does provision of antenatal care in Southern Asia improve neonatal survival? A systematic review and meta-analysis.

BACKGROUND: Southern Asia has one of the highest burdens of neonatal mortality worldwide (26/1000 live births). Ensuring that women receive antenatal care from a skilled provider may play an important role in reducing this burden. OBJECTIVE: This study aimed to determine whether antenatal care received from a skilled provider could reduce neonatal mortality in Southern Asia by systematically reviewing existing evidence. STUDY DESIGN: Seven databases were searched (MEDLINE, Embase, Cochrane Library, CINAHL, PubMed, PsycINFO, and International Bibliography of the Social Sciences [IBSS]). The key words included: "neonatal mortality," "antenatal care," and "Southern Asia." Nonrandomized comparative studies conducted in Southern Asia reporting on neonatal mortality in women who received antenatal care compared with those who did not were included. Two authors carried out the screening and data extraction. The Risk of Bias Assessment tool for Non-randomized Studies (RoBANS) was used to assess quality of studies. Results were reported using a random-effects model based on odds ratios with 95% confidence intervals. RESULTS: Four studies were included in a meta-analysis of adjusted results. The pooled odds ratio was 0.46 (95% confidence interval, 0.24 to 0.86) for neonatal deaths among women having at least 1 antenatal care visit during pregnancy compared with women having none. In the final meta-analysis, 16 studies could not be included because of lack of adjustment for confounders, highlighting the need for further higher-quality studies to evaluate the true impact. CONCLUSION: This review suggests that in Southern Asia, neonates born to women who received antenatal care have a lower risk of death in the neonatal period compared with neonates born to women who did not receive antenatal care. This should encourage health policy to strengthen antenatal care programs in Southern Asia.

Changes in women's physical function in mid-life by reproductive age and hormones: a longitudinal study.

BACKGROUND: Whether women's physical function in mid-life is related to their reproductive age is not known. The objectives of this study were to examine and compare changes in physical function in women by reproductive age, measured as time since final menstrual period (FMP), and chronological age, and to explore associations with repeatedly assessed levels of reproductive hormones. METHODS: We used data from 2319 UK women with up to three repeated measurements of physical function (median length of follow up: 2 years), focusing on changes occurring in women experiencing a natural menopausal transition. The main outcome was a composite physical function score that incorporated assessments of strength (grip strength), balance (one-leg stand) and cardiorespiratory fitness (timed chair rises). Associations with time since FMP, age, and time-updated measures of anti-Müllerian hormone, follicle-stimulating hormone and luteinizing hormone were assessed by multilevel models and generalised estimating equations models adjusted for the underlying effects of chronological age and confounding by education, age at first birth and smoking. RESULTS: The results showed that, adjusted for these confounders, time since FMP (- 0.21 SD per 10 years, 95% CI - 0.37, - 0.06) and chronological age (- 0.31 SD per 10 years, 95% CI - 0.46, - 0.15) were inversely associated with the physical function composite score. Grip strength seemed to be the main contributor to the decline in the composite score by time since FMP. There was no strong evidence of associations between any of the three reproductive hormones and the composite score. CONCLUSIONS: Physical function in women in mid-life declined with both chronological and reproductive age. The decline with reproductive age was independent of chronological age but did not seem to be driven by changes in reproductive hormones.

Cardiovascular health in the menopause transition: a longitudinal study of up to 3892 women with up to four repeated measures of risk factors.

BACKGROUND: Women experience adverse changes in cardiovascular health in mid-life; whether the menopausal transition influences these remains strongly debated. The aim of this study was to examine associations of reproductive age (time since final menstrual period (FMP)) with change in carotid intima media thickness (CIMT) and cardiovascular risk factors and determine the role of chronological and reproductive age. METHODS: We used data from 1702 women from a pregnancy-based UK cohort who had up to four repeat cardiovascular health measures between mean age 51 (SD = 4.0) and 56 (SD = 3.6) years and experienced a natural menopause. Multilevel models were used to assess the relationship between cardiovascular measures and time since FMP (reproductive age), whilst adjusting for the underlying effects of chronological age and confounders (socioeconomic factors, body mass index, smoking, alcohol, parity, age at menarche). In addition, we looked at the relationship between cardiovascular measures by chronological age according to menopausal stages (pre-menopause, peri-menopause and post-menopause) using information from women who had and had not experienced menopause (N = 3892). RESULTS: There was no strong evidence that reproductive age was associated with CIMT (difference in mean 0.8 µm/year, 95% CI - 0.4, 2.1), whereas there was a strong positive association of chronological age (7.6 µm/year, 95% CI 6.3, 8.9). Consistent with this, we found weaker linear associations of reproductive compared with chronological age for atherosclerotic risk factors, such as with systolic blood pressure (- 0.1 mmHg/year, 95% CI - 0.3, 0.1, and 0.4 mmHg/year, 95% CI 0.2, 0.5, respectively) and non-HDL-cholesterol (0.02 mmol/l/year, 95% CI 0.005, 0.03, and 0.06, 95% CI 0.04, 0.07, respectively). In contrast, associations with fat mass (0.06 kg/m2/year, 95% CI 0.03, 0.10, and 0 kg/m2/year, 95% CI - 0.04, 0.04, respectively) and C-reactive protein (0.01, 95% CI 0.001, 0.02, and 0.01, 95% CI - 0.001, 0.02 natural logged mg/l/year, respectively) were stronger for reproductive compared with chronological age. Both reproductive and chronological age were (weakly) positively associated with glucose (0.002, 95% CI 0.0001, 0.003, and 0.002, 95% CI 0.0001, 0.003 natural logged mmol/l/year, respectively). CONCLUSIONS: Our results suggest that going through the menopausal transition does not further increase women's risk of atherosclerosis (measured by CIMT) beyond effects of ageing. Menopausal transition may, in additional to ageing, modestly increase adiposity and glucose levels and therefore a possible associated diabetes risk.

Metabolomic Identification of a Novel, Externally Validated Predictive Test for Gestational Diabetes Mellitus.

CONTEXT: Undiagnosed gestational diabetes mellitus (GDM) is a major preventable cause of stillbirth. In the United Kingdom, women are selected for diagnostic testing for GDM based on risk factors, including body mass index (BMI) > 30 kg/m2. OBJECTIVE: To improve the prediction of GDM using metabolomics. METHODS: We performed metabolomics on maternal serum from the Pregnancy Outcome Prediction (POP) study at 12 and 20 weeks of gestational age (wkGA; 185 GDM cases and 314 noncases). Predictive metabolites were internally validated using the 28 wkGA POP study serum sample and externally validated using 24- to 28-wkGA fasting plasma from the Born in Bradford (BiB) cohort (349 GDM cases and 2347 noncases). The predictive ability of a model including the metabolites was compared with BMI > 30 kg/m2 in the POP study. RESULTS: Forty-seven predictive metabolites were identified using the 12- and 20-wkGA samples. At 28 wkGA, 4 of these [mannose, 4-hydroxyglutamate, 1,5-anhydroglucitol, and lactosyl-N-palmitoyl-sphingosine (d18:1/16:0)] independently increased the bootstrapped area under the receiver operating characteristic curve (AUC) by >0.01. All 4 were externally validated in the BiB samples (P = 2.6 × 10-12, 2.2 × 10-13, 6.9 × 10-28, and 2.6 × 10-17, respectively). In the POP study, BMI > 30 kg/m2 had a sensitivity of 28.7% (95% CI 22.3-36.0%) and a specificity of 85.4% whereas at the same level of specificity, a predictive model using age, BMI, and the 4 metabolites had a sensitivity of 60.2% (95% CI 52.6-67.4%) and an AUC of 0.82 (95% CI 0.78-0.86). CONCLUSIONS: We identified 4 strongly and independently predictive metabolites for GDM that could have clinical utility in screening for GDM.

Use of external evidence for design and Bayesian analysis of clinical trials: a qualitative study of trialists' views.

BACKGROUND: Evidence from previous studies is often used relatively informally in the design of clinical trials: for example, a systematic review to indicate whether a gap in the current evidence base justifies a new trial. External evidence can be used more formally in both trial design and analysis, by explicitly incorporating a synthesis of it in a Bayesian framework. However, it is unclear how common this is in practice or the extent to which it is considered controversial. In this qualitative study, we explored attitudes towards, and experiences of, trialists in incorporating synthesised external evidence through the Bayesian design or analysis of a trial. METHODS: Semi-structured interviews were conducted with 16 trialists: 13 statisticians and three clinicians. Participants were recruited across several universities and trials units in the United Kingdom using snowball and purposeful sampling. Data were analysed using thematic analysis and techniques of constant comparison. RESULTS: Trialists used existing evidence in many ways in trial design, for example, to justify a gap in the evidence base and inform parameters in sample size calculations. However, no one in our sample reported using such evidence in a Bayesian framework. Participants tended to equate Bayesian analysis with the incorporation of prior information on the intervention effect and were less aware of the potential to incorporate data on other parameters. When introduced to the concepts, many trialists felt they could be making more use of existing data to inform the design and analysis of a trial in particular scenarios. For example, some felt existing data could be used more formally to inform background adverse event rates, rather than relying on clinical opinion as to whether there are potential safety concerns. However, several barriers to implementing these methods in practice were identified, including concerns about the relevance of external data, acceptability of Bayesian methods, lack of confidence in Bayesian methods and software, and practical issues, such as difficulties accessing relevant data. CONCLUSIONS: Despite trialists recognising that more formal use of external evidence could be advantageous over current approaches in some areas and useful as sensitivity analyses, there are still barriers to such use in practice.

Bias from questionnaire invitation and response in COVID-19 research: an example using ALSPAC.

Background: Longitudinal studies are crucial for identifying potential risk factors for infection with, and consequences of, COVID-19, but relationships can be biased if they are associated with invitation and response to data collection. We describe factors relating to questionnaire invitation and response in COVID-19 questionnaire data collection in a multigenerational birth cohort (the Avon Longitudinal Study of Parents and Children, ALSPAC). Methods: We analysed online questionnaires completed between the beginning of the pandemic and easing of the first UK lockdown by participants with valid email addresses who had not actively disengaged from the study. We assessed associations of pre-pandemic sociodemographic, behavioural, anthropometric and health-related factors with: i) being sent a questionnaire; ii) returning a questionnaire; and iii) item response (for specific questions). Analyses were conducted in three cohorts: the index children born in the early 1990s (now young adults; 41 variables assessed), their mothers (35 variables) and the mothers' partners (27 variables). Results: Of 14,849 young adults, 41% were sent a questionnaire, of whom 57% returned one. Item response was >95%. In this cohort, 78% of factors were associated with being sent a questionnaire, 56% with returning one, and, as an example of item response, 20% with keyworker status response. For instance, children from mothers educated to degree-level had greater odds of being sent a questionnaire (OR=5.59; 95% CI=4.87-6.41), returning one (OR=1.60; 95% CI=1.31-1.95), and responding to items (e.g., keyworker status OR=1.65; 95% CI=0.88-3.04), relative to children from mothers with fewer qualifications. Invitation and response rates and associations were similar in all cohorts. Conclusions: These results highlight the importance of considering potential biases due to non-response when using longitudinal studies in COVID-19 research and interpreting results. We recommend researchers report response rates and factors associated with invitation and response in all COVID-19 observational research studies, which can inform sensitivity analyses.

Growth rate of clinically diagnosed superficial basal cell carcinoma and changes in dermoscopic features over time.

BACKGROUND/OBJECTIVES: Basal cell carcinoma (BCC) is the most commonly occurring skin cancer. BCCs have been found to generally grow slowly. Data are limited on how the dermoscopic characteristics of BCCs evolve. We set out to determine the growth rate of superficial BCCs (sBCC) and assess the change in dermoscopic features over time. METHODS: A retrospective review was performed of clinically diagnosed sBCC. Images, demographic and dermoscopic data were collected by a melanographer. Mixed effects linear regression models were used to investigate sBCC growth and associations between size and dermoscopic/demographic variables. We tested differences in trends over time in dermoscopic features using non-parametric trend tests. RESULTS: 100 individual sBCC were evaluated in 70 patients (mean age 62; 59% male), 69% had Fitzpatrick skin phototype 1 or 2, and 81% had some degree of actinic damage. sBCC were present on the back in 58% and 22% of men and women, respectively. The median surface area was 41.9 mm2 with a growth rate of 0.81 mm2 /month. Males had larger sBCC than females. There was no association between sBCC size and Fitzpatrick skin phototype, history of skin cancer or family history of melanoma. There is some evidence larger sBCC gain shiny white structures (P = 0.053) over time. CONCLUSIONS: sBCC grow at a rate unlikely to adversely affect patient outcomes associated with long wait times. Our data suggest that dermoscopy can aid in appropriate treatment selection for sBCC.

Ethnic discordance in serum anti-Müllerian hormone in healthy women: a population study from China and Europe.

RESEARCH QUESTION: Chinese women are known to have an earlier age of natural menopause than their European counterparts, but whether they also have a lower functional ovarian reserve is unknown. This study was designed to assess whether there are ethnic differences in anti-Müllerian hormone (AMH) concentrations in women of reproductive age. DESIGN: Women in China and Europe with regular menstrual cycles, not on hormonal contraception and with no medical history of note, were recruited to provide a day 2-5 early follicular phase sample. AMH concentration was determined using the Roche Elecsys assay. Decline in AMH was modelled with linear, quadratic and quadratic with interaction on age equations to assess the impact of ethnicity. RESULTS: A total of 887 European and 461 Chinese women participated in the study. Despite the Chinese population being slightly younger (34.1 ± 8.4 years) than their European counterparts (34.8±8.9 years), their median AMH was lower, at 1.87 ng/ml (interquartile range [IQR] 0.28-3.64) compared with 2.11 ng/ml (IQR 0.73-3.96), with evidence of increasing discordance from age 25 years. In all regression models of the age-related decline in AMH, there was evidence of a difference between Chinese and European women. Although AMH was 28.1% (95% confidence interval [CI] 18.2-36.7%) lower in the Chinese population at age 30, this decline increased to 79.4% (95% CI 75.4- 82.9%) at age 45. CONCLUSIONS: There were independent effects of age and ethnicity on serum AMH concentrations, with Chinese women having a substantially lower AMH in adult life than their European counterparts from age 25 onwards.

Impact of blinding on estimated treatment effects in randomised clinical trials: meta-epidemiological study.

OBJECTIVES: To study the impact of blinding on estimated treatment effects, and their variation between trials; differentiating between blinding of patients, healthcare providers, and observers; detection bias and performance bias; and types of outcome (the MetaBLIND study). DESIGN: Meta-epidemiological study. DATA SOURCE: Cochrane Database of Systematic Reviews (2013-14). ELIGIBILITY CRITERIA FOR SELECTING STUDIES: Meta-analyses with both blinded and non-blinded trials on any topic. REVIEW METHODS: Blinding status was retrieved from trial publications and authors, and results retrieved automatically from the Cochrane Database of Systematic Reviews. Bayesian hierarchical models estimated the average ratio of odds ratios (ROR), and estimated the increases in heterogeneity between trials, for non-blinded trials (or of unclear status) versus blinded trials. Secondary analyses adjusted for adequacy of concealment of allocation, attrition, and trial size, and explored the association between outcome subjectivity (high, moderate, low) and average bias. An ROR lower than 1 indicated exaggerated effect estimates in trials without blinding. RESULTS: The study included 142 meta-analyses (1153 trials). The ROR for lack of blinding of patients was 0.91 (95% credible interval 0.61 to 1.34) in 18 meta-analyses with patient reported outcomes, and 0.98 (0.69 to 1.39) in 14 meta-analyses with outcomes reported by blinded observers. The ROR for lack of blinding of healthcare providers was 1.01 (0.84 to 1.19) in 29 meta-analyses with healthcare provider decision outcomes (eg, readmissions), and 0.97 (0.64 to 1.45) in 13 meta-analyses with outcomes reported by blinded patients or observers. The ROR for lack of blinding of observers was 1.01 (0.86 to 1.18) in 46 meta-analyses with subjective observer reported outcomes, with no clear impact of degree of subjectivity. Information was insufficient to determine whether lack of blinding was associated with increased heterogeneity between trials. The ROR for trials not reported as double blind versus those that were double blind was 1.02 (0.90 to 1.13) in 74 meta-analyses. CONCLUSION: No evidence was found for an average difference in estimated treatment effect between trials with and without blinded patients, healthcare providers, or outcome assessors. These results could reflect that blinding is less important than often believed or meta-epidemiological study limitations, such as residual confounding or imprecision. At this stage, replication of this study is suggested and blinding should remain a methodological safeguard in trials.

Ten questions to consider when interpreting results of a meta-epidemiological study-the MetaBLIND study as a case.

Randomized clinical trials underpin evidence-based clinical practice, but flaws in their conduct may lead to biased estimates of intervention effects and hence invalid treatment recommendations. The main approach to the empirical study of bias is to collate a number of meta-analyses and, within each, compare the results of trials with and without a methodological characteristic such as blinding of participants and health professionals. Estimated within-meta-analysis differences are combined across meta-analyses, leading to an estimate of mean bias. Such "meta-epidemiological" studies are published in increasing numbers and have the potential to inform trial design, assessment of risk of bias, and reporting guidelines. However, their interpretation is complicated by issues of confounding, imprecision, and applicability. We developed a guide for interpreting meta-epidemiological studies, illustrated using MetaBLIND, a large study on the impact of blinding. Applying generally accepted principles of research methodology to meta-epidemiology, we framed 10 questions covering the main issues to consider when interpreting results of such studies, including risk of systematic error, risk of random error, issues related to heterogeneity, and theoretical plausibility. We suggest that readers of a meta-epidemiological study reflect comprehensively on the research question posed in the study, whether an experimental intervention was unequivocally identified for all included trials, the risk of misclassification of the trial characteristic, and the risk of confounding, i.e the adequacy of any adjustment for the likely confounders. We hope that our guide to interpretation of results of meta-epidemiological studies is helpful for readers of such studies.