Exposome-Wide Association Study of Body Mass Index Using a Novel Meta-Analytical Approach for Random Forest Models.

BACKGROUND: Overweight and obesity impose a considerable individual and social burden, and the urban environments might encompass factors that contribute to obesity. Nevertheless, there is a scarcity of research that takes into account the simultaneous interaction of multiple environmental factors. OBJECTIVES: Our objective was to perform an exposome-wide association study of body mass index (BMI) in a multicohort setting of 15 studies. METHODS: Studies were affiliated with the Dutch Geoscience and Health Cohort Consortium (GECCO), had different population sizes (688-141,825), and covered the entire Netherlands. Ten studies contained general population samples, others focused on specific populations including people with diabetes or impaired hearing. BMI was calculated from self-reported or measured height and weight. Associations with 69 residential neighborhood environmental factors (air pollution, noise, temperature, neighborhood socioeconomic and demographic factors, food environment, drivability, and walkability) were explored. Random forest (RF) regression addressed potential nonlinear and nonadditive associations. In the absence of formal methods for multimodel inference for RF, a rank aggregation-based meta-analytic strategy was used to summarize the results across the studies. RESULTS: Six exposures were associated with BMI: five indicating neighborhood economic or social environments (average home values, percentage of high-income residents, average income, livability score, share of single residents) and one indicating the physical activity environment (walkability in 5-km buffer area). Living in high-income neighborhoods and neighborhoods with higher livability scores was associated with lower BMI. Nonlinear associations were observed with neighborhood home values in all studies. Lower neighborhood home values were associated with higher BMI scores but only for values up to €300,000. The directions of associations were less consistent for walkability and share of single residents. DISCUSSION: Rank aggregation made it possible to flexibly combine the results from various studies, although between-study heterogeneity could not be estimated quantitatively based on RF models. Neighborhood social, economic, and physical environments had the strongest associations with BMI. https://doi.org/10.1289/EHP13393.

A prospective exploration of the urban exposome in relation to headache in the Dutch population-based Occupational and environmental health cohort study (AMIGO).

OBJECTIVE: Headache is one of the most prevalent and disabling health conditions globally. We prospectively explored the urban exposome in relation to weekly occurrence of headache episodes using data from the Dutch population-based Occupational and Environmental Health Cohort Study (AMIGO). MATERIAL AND METHODS: Participants (N = 7,339) completed baseline and follow-up questionnaires in 2011 and 2015, reporting headache frequency. Information on the urban exposome covered 80 exposures across 10 domains, such as air pollution, electromagnetic fields, and lifestyle and socio-demographic characteristics. We first identified all relevant exposures using the Boruta algorithm and then, for each exposure separately, we estimated the average treatment effect (ATE) and related standard error (SE) by training causal forests adjusted for age, depression diagnosis, painkiller use, general health indicator, sleep disturbance index and weekly occurrence of headache episodes at baseline. RESULTS: Occurrence of weekly headache was 12.5 % at baseline and 11.1 % at follow-up. Boruta selected five air pollutants (NO2, NOX, PM10, silicon in PM10, iron in PM2.5) and one urban temperature measure (heat island effect) as factors contributing to the occurrence of weekly headache episodes at follow-up. The estimated causal effect of each exposure on weekly headache indicated positive associations. NO2 showed the largest effect (ATE = 0.007 per interquartile range (IQR) increase; SE = 0.004), followed by PM10 (ATE = 0.006 per IQR increase; SE = 0.004), heat island effect (ATE = 0.006 per one-degree Celsius increase; SE = 0.007), NOx (ATE = 0.004 per IQR increase; SE = 0.004), iron in PM2.5 (ATE = 0.003 per IQR increase; SE = 0.004), and silicon in PM10 (ATE = 0.003 per IQR increase; SE = 0.004). CONCLUSION: Our results suggested that exposure to air pollution and heat island effects contributed to the reporting of weekly headache episodes in the study population.

The neighourhood obesogenic built environment characteristics (OBCT) index: Practice versus theory.

BACKGROUND: Obesity is a key risk factor for major chronic diseases such as type 2 diabetes and cardiovascular diseases. To extensively characterise the obesogenic built environment, we recently developed a novel Obesogenic Built environment CharacterisTics (OBCT) index, consisting of 17 components that capture both food and physical activity (PA) environments. OBJECTIVES: We aimed to assess the association between the OBCT index and body mass index (BMI) in a nationwide health monitor. Furthermore, we explored possible ways to improve the index using unsupervised and supervised methods. METHODS: The OBCT index was constructed for 12,821 Dutch administrative neighbourhoods and linked to residential addresses of eligible adult participants in the 2016 Public Health Monitor. We split the data randomly into a training (two-thirds; n = 255,187) and a testing subset (one-third; n = 127,428). In the training set, we used non-parametric restricted cubic regression spline to assess index's association with BMI, adjusted for individual demographic characteristics. Effect modification by age, sex, socioeconomic status (SES) and urbanicity was examined. As improvement, we (1) adjusted the food environment for address density, (2) added housing price to the index and (3) adopted three weighting strategies, two methods were supervised by BMI (variable selection and random forest) in the training set. We compared these methods in the testing set by examining their model fit with BMI as outcome. RESULTS: The OBCT index had a significant non-linear association with BMI in a fully-adjusted model (p<0.05), which was modified by age, sex, SES and urbanicity. However, variance in BMI explained by the index was low (<0.05%). Supervised methods increased this explained variance more than non-supervised methods, though overall improvements were limited as highest explained variance remained <0.5%. DISCUSSION: The index, despite its potential to highlight disparity in obesogenic environments, had limited association with BMI. Complex improvements are not necessarily beneficial, and the components should be re-operationalised.

Associations between the urban exposome and type 2 diabetes: Results from penalised regression by least absolute shrinkage and selection operator and random forest models.

BACKGROUND: Type 2 diabetes (T2D) is thought to be influenced by environmental stressors such as air pollution and noise. Although environmental factors are interrelated, studies considering the exposome are lacking. We simultaneously assessed a variety of exposures in their association with prevalent T2D by applying penalised regression Least Absolute Shrinkage and Selection Operator (LASSO), Random Forest (RF), and Artificial Neural Networks (ANN) approaches. We contrasted the findings with single-exposure models including consistently associated risk factors reported by previous studies. METHODS: Baseline data (n = 14,829) of the Occupational and Environmental Health Cohort study (AMIGO) were enriched with 85 exposome factors (air pollution, noise, built environment, neighbourhood socio-economic factors etc.) using the home addresses of participants. Questionnaires were used to identify participants with T2D (n = 676(4.6 %)). Models in all applied statistical approaches were adjusted for individual-level socio-demographic variables. RESULTS: Lower average home values, higher share of non-Western immigrants and higher surface temperatures were related to higher risk of T2D in the multivariable models (LASSO, RF). Selected variables differed between the two multi-variable approaches, especially for weaker predictors. Some established risk factors (air pollutants) appeared in univariate analysis but were not among the most important factors in multivariable analysis. Other established factors (green space) did not appear in univariate, but appeared in multivariable analysis (RF). Average estimates of the prediction error (logLoss) from nested cross-validation showed that the LASSO outperformed both RF and ANN approaches. CONCLUSIONS: Neighbourhood socio-economic and socio-demographic characteristics and surface temperature were consistently associated with the risk of T2D. For other physical-chemical factors associations differed per analytical approach.

Machine learning approaches to characterize the obesogenic urban exposome.

BACKGROUND: Characteristics of the urban environment may contain upstream drivers of obesity. However, research is lacking that considers the combination of environmental factors simultaneously. OBJECTIVES: We aimed to explore what environmental factors of the urban exposome are related to body mass index (BMI), and evaluated the consistency of findings across multiple statistical approaches. METHODS: A cross-sectional analysis was conducted using baseline data from 14,829 participants of the Occupational and Environmental Health Cohort study. BMI was obtained from self-reported height and weight. Geocoded exposures linked to individual home addresses (using 6-digit postcode) of 86 environmental factors were estimated, including air pollution, traffic noise, green-space, built environmental and neighborhood socio-demographic characteristics. Exposure-obesity associations were identified using the following approaches: sparse group Partial Least Squares, Bayesian Model Averaging, penalized regression using the Minimax Concave Penalty, Generalized Additive Model-based boosting Random Forest, Extreme Gradient Boosting, and Multiple Linear Regression, as the most conventional approach. The models were adjusted for individual socio-demographic variables. Environmental factors were ranked according to variable importance scores attributed by each approach and median ranks were calculated across these scores to identify the most consistent associations. RESULTS: The most consistent environmental factors associated with BMI were the average neighborhood value of the homes, oxidative potential of particulate matter air pollution (OP), healthy food outlets in the neighborhood (5 km buffer), low-income neighborhoods, and one-person households in the neighborhood. Higher BMI levels were observed in low-income neighborhoods, with lower average house values, lower share of one-person households and smaller amount of healthy food retailers. Higher BMI levels were observed in low-income neighborhoods, with lower average house values, lower share of one-person households, smaller amounts of healthy food retailers and higher OP levels. Across the approaches, we observed consistent patterns of results based on model's capacity to incorporate linear or nonlinear associations. DISCUSSION: The pluralistic analysis on environmental obesogens strengthens the existing evidence on the role of neighborhood socioeconomic position, urbanicity and air pollution.

Evaluation of muscle-skeletal strength and peak expiratory flow in severely malnourished inpatients with anorexia nervosa: A pilot study.

OBJECTIVES: Anorexia nervosa is a complex psychiatric disorder that can lead to specific somatic complications. Malnutrition is frequent and can involve a decrease of mobility, up to functional impotence, in individuals with extremely severe cases. The aim of this pilot study was to examine muscle strength and peak expiratory flow (PEF) in severely undernourished patients with anorexia nervosa at admission and after 5 wk of renutrition by tube feeding, and to find the clinical and biological correlates of muscle-strength impairment. METHODS: A prospective observational study was conducted over 6 mo. Manual muscle testing, measures of PEF, and clinical and biologic assessments were performed at baseline and after 5 wk of renutrition. RESULTS: Twenty-three extremely malnourished female participants (mean body mass index: 11.4 ± 1.3 kg/m2) were included. All participants had global impairment in muscle strength (manual muscle testing: 37.7 ± 7.7) and PEF (253.3 ± 60 mL/min) at admission. Muscle weakness was higher in axial than peripheral muscle groups (P < 0.01), with no significant difference between proximal and distal muscles (P > 0.05). Muscle strength at admission was significantly associated with severity of undernourishment (body mass index and albumin) and transaminitis (P < 0.05). At follow-up, musculoskeletal strength and PEF were significantly improved after partial weight recovery (P < 0.01). CONCLUSIONS: Extremely undernourished people with anorexia nervosa present a decrease of PEF and musculoskeletal strength predominant on axial muscles. Both are associated with severity of malnutrition and liver damage. Partial recovery was observed after 5 wk of enteral nutrition.

Application of the OMERACT synovitis ultrasound scoring system in juvenile idiopathic arthritis: a multicenter reliability exercise.

OBJECTIVES: To evaluate the reliability of the OMERACT paediatric ultrasound (US) synovitis definitions and scoring system in JIA. METHODS: Thirteen sonographers analysed 75 images for the presence/absence of elementary lesions (binary scoring) and for grading synovitis, synovial hypertrophy, effusion and Doppler signals. Static US images of the second metacarpophalangeal joint (MCP-II), wrist, elbow, knee and ankle in JIA patients at different ages and different disease stages were collected with standardized scanning by two experienced sonographers. Intra- and inter-reader reliability were analysed with kappa coefficients. RESULTS: Intra-reader reliability was good for binary scoring (Cohen's kappa 0.62, range 0.47-0.75), synovitis and synovial hypertrophy; excellent for Doppler signals (quadratic weighted kappa 0.77, 0.66-0.86; 0.76, 0.61-0.84; and 0.87, 0.77-0.94, respectively); and moderate for effusion (0.55, 0.24-0.76). Inter-reader reliability was good for synovitis and synovial hypertrophy (Light's kappa 0.68, 95% CI: 0.61, 0.75 and 0.63, 0.54-0.71, respectively), excellent for Doppler signals (0.85, 95% CI: 0.77, 0.90), and moderate for binary scoring and effusion (0.48, 95% CI: 0.36, 0.64 and 0.49, 0.40-0.60, respectively). We obtained the best scores for the knee (0.71, 0.54-0.85) except for Doppler signals, with reliability higher for MCP-II. We found a trend toward better results in older children. CONCLUSIONS: This is the first study establishing the reliability of the OMERACT paediatric US synovitis definitions and scoring system in the five most commonly affected joints in JIA. The reliability was good among a large group of sonographers. These results support the applicability of these definitions and scoring system in clinical practice and multicentre studies.

Priming Before In Vitro Maturation Cycles in Cancer Patients Undergoing Urgent Fertility Preservation: a Randomized Controlled Study.

In vitro maturation (IVM) of oocytes retrieved at germinal vesicle stage, followed by vitrification of mature oocytes, has emerged as a fertility preservation (FP) option. This technique was first developed for patients with polycystic ovarian syndrome. In this population, providing LH activity prior to oocyte collection has been associated with better IVM outcomes. However, the benefit of this treatment in normo-ovulatory breast cancer (BC) patients undergoing IVM for FP purpose has never been investigated. To assess if the absence of therapeutic intervention prior to oocyte retrieval for IVM modifies IVM outcomes in BC patients undergoing urgent FP, we performed a non-inferiority, randomized controlled trial. The main outcome was the total number of mature oocytes obtained and cryopreserved after IVM. A total of 172 normo-ovulatory women, suffering from BC, 18 to 39 years of age received no injection or a subcutaneous injection of hCG or GnRH agonist (GnRHa) 36 h before oocytes retrieval according to randomized allocation. The total number of cryopreserved oocytes were 5.1 ± 3.8, 5.4 ± 3.8, and 6.0 ± 4.2 oocytes, respectively in the without, hCG and GnRHa groups. Mean differences were not significant between the three groups (- 0.5; CI 97.5% [- 2.03:1.02] and - 0.22; CI 97.5% [- 1.75:1.32], respectively). Intention to treat analyses failed to show non-inferiority in the "without injection group" in comparison with hCG or GnRHa groups. Our results are not conclusive enough to modify our practices and to stop administering hCG or GnRHa before IVM cycles for FP. The study was retrospectively registered to clinical trial (ID NCT03954197) in May 2019.