Rethinking causal assumptions about maternal BMI, gestational weight gain, and adverse pregnancy outcomes.

BACKGROUND: The aim of this study was to evaluate commonly assumed causal relationships between body mass index (BMI), gestational weight gain (GWG), and adverse pregnancy outcomes, which have formed the basis of guidelines and interventions aimed at limiting GWG in women with overweight or obesity. We explored relationships between maternal BMI, total GWG (as a continuous variable and as 'excessive' GWG), and pregnancy outcomes (including infant birthweight measures and caesarean birth). METHODS: Analysis of individual participant data (IPD) from the i-WIP (International Weight Management in Pregnancy) Collaboration, from randomised trials of diet and/or physical activity interventions during pregnancy reporting GWG and maternal and neonatal outcomes. Women randomised to the control arm of 20 eligible randomised trials (4370 of 8908 participants) from the i-WIP dataset of 36 randomised trials (total 12,240 women). The main research questions were to characterise the relationship between maternal BMI and (a) total GWG, (b) the risk of 'excessive' GWG (using the Institute of Medicine's guidelines), and (c) adverse pregnancy outcomes as mediated via GWG versus other pathways to determine the extent to which the observed effect of maternal BMI on pregnancy outcomes is mediated via GWG. We utilised generalised linear models and regression-based mediation analyses within an IPD meta-analysis framework. RESULTS: Mean GWG decreased linearly as maternal BMI increased; however, the risk of 'excessive' GWG increased markedly at BMI category thresholds (i.e. between the normal and overweight BMI category threshold and between the overweight and obese BMI category threshold). Increasing maternal BMI was associated with increased risk of all pregnancy outcomes assessed; however, there was no evidence that this effect was mediated via effects on GWG. CONCLUSIONS: There is evidence of a meaningful relationship between maternal BMI and GWG and between maternal BMI and adverse pregnancy outcomes. There is no evidence that the effect of maternal BMI on outcomes is via an effect on GWG. Our analyses also cast doubt on the existence of a relationship between 'excessive' GWG and adverse pregnancy outcomes. Our findings challenge the practice of actively managing GWG throughout pregnancy.

Fetal Growth and Adiposity of Infants Born Large for Gestational Age in Three Harmonized Randomized Trials.

OBJECTIVE: Infants born large for gestational age (LGA) are at an increased risk of short- and longer-term adverse outcomes. Understanding fetal growth and adiposity and their trajectories may help inform interventions to prevent birth of LGA infants. We aimed to compare fetal growth and adiposity measures of infants born LGA with those born not LGA, to determine whether the discrepancy at birth was primarily due to larger size throughout gestation, or instead to different trajectories of fetal growth. STUDY DESIGN: This was a secondary analysis of secondary outcomes of fetal growth and adiposity from three harmonized randomized trials-the LIMIT, GRoW, and Optimise randomized trials. These trials recruited women in early pregnancy, and a singleton gestation, from three major public metropolitan Adelaide maternity hospitals. Maternal body mass index (BMI) ranged from 18.5 to ≥40.0 kg/m2. Data were obtained from enrolled women who underwent research ultrasounds at 28 and 36 weeks' gestation. Outcome measures were ultrasound measures of fetal biometry and adiposity. RESULTS: Infants born LGA had larger fetal biometry measures, and higher growth trajectories, from 20 weeks' gestation. Fetal adiposity measures were consistently larger among infants born LGA and these differences increased over time. We did not find evidence that the differences in biometry and adiposity measurements varied according to maternal BMI. CONCLUSION: Infants born LGA had larger fetal biometry measures at all time points from 20 weeks' gestation, compared with infants born not LGA suggesting any interventions to prevent LGA likely need to commence earlier in pregnancy or prior to conception. KEY POINTS: · Infants born LGA had larger fetal biometry measures from 20 weeks' gestation.. · Infants born LGA had larger fetal adiposity measures.. · Interventions to prevent LGA need to start earlier in pregnancy or prior to conception..

Effects of an antenatal dietary intervention in women with obesity or overweight on child outcomes at 8-10 years of age: LIMIT randomised trial follow-up.

BACKGROUND: The LIMIT randomised controlled trial looked at the effect of a dietary and lifestyle intervention compared with routine antenatal care for pregnant women with overweight and obesity on pregnancy outcomes. While women in the intervention group improved diet and physical activity with a reduction of high birth weight, other outcomes were similar. We have followed the children born to women in this study at birth, 6 and 18 months and 3-5 years of age and now report follow-up of children at 8-10 years of age. METHODS: Children at 8-10 years of age who were born to women who participated in the LIMIT randomised trial, and whose mother provided consent to ongoing follow-up were eligible for inclusion. The primary study endpoint was the incidence of child BMI z-score > 85th centile for child sex and age. Secondary study outcomes included a range of anthropometric measures, neurodevelopment, child dietary intake, and physical activity. Analyses used intention to treat principles according to the treatment group allocated in pregnancy. Outcome assessors were blinded to the allocated treatment group. RESULTS: We assessed 1,015 (Lifestyle Advice n = 510; Standard Care n = 505) (48%) of the 2,121 eligible children. BMI z-score > 85th percentile was similar for children of women in the dietary Lifestyle Advice Group compared with children of women in the Standard Care Group (Lifestyle Advice 479 (45%) versus Standard Care 507 (48%); adjusted RR (aRR) 0.93; 95% CI 0.82 to 1.06; p = 0.302) as were secondary outcomes. We observed that more than 45% of all the children had a BMI z-score > 85th percentile, consistent with findings from follow-up at earlier time-points, indicating an ongoing risk of overweight and obesity. CONCLUSIONS: Dietary and lifestyle advice for women with overweight and obesity in pregnancy has not reduced the risk of childhood obesity, with children remaining at risk of adolescent and adult obesity. Other strategies are needed to address the risk of overweight and obesity in children including investigation of preconception interventions to assess whether this can modify the effects of maternal pre-pregnancy BMI. The LIMIT randomised controlled trial was registered with the Australian and New Zealand Clinical Trials Registry (ACTRN12607000161426).

The Adelaide Facial Bone Rule: A simple prediction model and clinical guideline for the presence of facial fractures using CT brain scans in victims of minor trauma.

BACKGROUND: Facial fractures bleed, resulting in high-density fluid in the sinuses (haemosinus) on computed tomography (CT) scans. A CT brain scan includes most maxillary sinuses in the scan field, which should allow detection of haemosinus as an indirect indicator of a facial fracture without the need for an additional CT facial bone scan, yet no robust evidence for this exists in the literature. The aim of this study was to determine whether the presence of haemosinus on a CT brain scan, alone or in combination with other clinical information, can predict the presence of facial fractures. METHODS: 1231 adult patients, who had both brain and facial CT scans performed on the same day, were selected from a seven year period. Patients were eligible if scans were requested for trauma. Brain and facial scans were reviewed separately for the presence of facial fractures, haemosinus, emphysema and intra-cranial haemorrhage. Prediction modelling was used to assess whether findings from brain scans could be used to identify patients requiring further CT scanning. FINDINGS: The full prediction model included four predictors and showed excellent discrimination (AUROC 0.982; 95 % CI 0.971 - 0.993). A simplified model, more suitable for clinical implementation, used only facial fractures and haemosinus as predictors. This model showed only marginally poorer discrimination (AUROC 0.964; 95 % CI 0.945 - 0.983) and excellent performance on other measures. CONCLUSION: Based on the excellent performance of the simplified prediction model, we present the Adelaide Facial Bone Rule: The absence of blood in the sinuses or facial fractures on a CT brain scan means a CT facial bone scan does not need to be routinely performed in the setting of clinically-determined minor trauma.

What's New in Dementia Risk Prediction Modelling? An Updated Systematic Review.

Introduction: Identifying individuals at high risk of dementia is critical to optimized clinical care, formulating effective preventative strategies, and determining eligibility for clinical trials. Since our previous systematic reviews in 2010 and 2015, there has been a surge in dementia risk prediction modelling. The aim of this study was to update our previous reviews to explore, and critically review, new developments in dementia risk modelling. Methods: MEDLINE, Embase, Scopus, and Web of Science were searched from March 2014 to June 2022. Studies were included if they were population- or community-based cohorts (including electronic health record data), had developed a model for predicting late-life incident dementia, and included model performance indices such as discrimination, calibration, or external validation. Results: In total, 9,209 articles were identified from the electronic search, of which 74 met the inclusion criteria. We found a substantial increase in the number of new models published from 2014 (>50 new models), including an increase in the number of models developed using machine learning. Over 450 unique predictor (component) variables have been tested. Nineteen studies (26%) undertook external validation of newly developed or existing models, with mixed results. For the first time, models have also been developed in low- and middle-income countries (LMICs) and others validated in racial and ethnic minority groups. Conclusion: The literature on dementia risk prediction modelling is rapidly evolving with new analytical developments and testing in LMICs. However, it is still challenging to make recommendations about which one model is the most suitable for routine use in a clinical setting. There is an urgent need to develop a suitable, robust, validated risk prediction model in the general population that can be widely implemented in clinical practice to improve dementia prevention.

Cardiovascular disease, associated risk factors, and risk of dementia: An umbrella review of meta-analyses.

Introduction: Cardiovascular diseases (CVDs) have been associated with an increased risk of dementia; yet the evidence is mixed. This review critically appraises and synthesises current evidence exploring associations between dementia risk and CVD and their risk factors, including coronary heart disease, heart failure, atrial fibrillation, hypertension, hyperlipidaemia, and arterial stiffness. Methods: MEDLINE, Embase, PsycINFO, and the Cochrane Database of Systematic Reviews were searched to identify systematic reviews with meta-analyses investigating the association between at least one of the CVDs of interest and dementia risk. The Joanna Briggs Institute (JBI) Critical Appraisal Checklist for Systematic Reviews was used to assess methodological quality. Results: Twenty-five meta-analyses published between 2007 and 2021 were included. Studies largely consisted of cohorts from North America and Europe. Findings were variable, with coronary heart disease, heart failure, and atrial fibrillation consistently associated with increased risk for all-cause dementia, but results were inconsistent for Alzheimer's disease. Hypertension was more frequently associated with dementia during mid-life compared to late life. Findings concerning cholesterol were complex, and while results were inconsistent for low-density lipoprotein cholesterol and total cholesterol, there appeared to be no associations between triglycerides and high-density lipoprotein cholesterol. All meta-analyses investigating hypercholesterolaemia showed significant increases in dementia risk. There was a paucity of research on the association between arterial stiffness and dementia risk. Conclusion: Targeted CVD dementia prevention strategies could reduce dementia prevalence. Future research should determine the underpinning mechanisms linking heart and brain health to determine the most effective strategies for dementia risk reduction in CVD populations.