Sociodemographic, lifestyle, and environmental determinants of vitamin D levels in pregnant women in Spain.

INTRODUCTION: Vitamin D deficiency (<20 ng/mL circulating levels) is a worldwide public health concern and pregnant women are especially vulnerable, affecting the health of the mother and the fetus. This study aims to evaluate the sociodemographic, lifestyle, and environmental determinants associated with circulating vitamin D levels in Spanish pregnant women. METHODS: We used data from the Spanish INMA ("Infancia y Medio Ambiente") prospective birth cohort study from the regions of Gipuzkoa, Sabadell, and Valencia. 25-hydroxyvitamin D3 (25(OH)D3) was measured in plasma collected in the first trimester of pregnancy. Information on 108 determinants was gathered: 13 sociodemographic, 48 lifestyle including diet, smoking and physical activity, and 47 environmental variables, representing the urban and the chemical exposome. Association of the determinants with maternal 25(OH)D3 levels was estimated in single- and multiple-exposure models. Machine learning techniques were used to predict 25(OH)D3 levels below sufficiency (30 ng/mL). RESULTS: The prevalence of < 30 ng/mL 25(OH)D3 levels was 51 %. In the single-exposure analysis, older age, higher socioeconomic status, taking vitamin D, B12 and other sup*plementation, and higher humidity, atmospheric pressure and UV rays were associated with higher levels of 25(OH)D3 (IQR increase of age: 1.2 [95 % CI: 0.6, 1.8] ng/mL 25(OH)D3). In the multiple-exposures model, most of these associations remained and others were revealed. Higher body mass index, PM2.5 and high deprivation area were associated with lower 25(OH)D3 levels (i.e., Quartile 4 of PM2.5 vs Q1: -3.6 [95 % CI: -5.6, -1.5] ng/mL of 25(OH)D3). History of allergy and asthma, being multiparous, intake of vegetable fat, vitamin B6, alcohol consumption and molybdenum were associated with higher levels. The machine learning classification model confirmed some of these associations. CONCLUSIONS: This comprehensive study shows that younger age, higher body mass index, higher deprived areas, higher air pollution and lower UV rays and humidity are associated with lower 25(OH)D3 levels.

Model Choice for Quantitative Health Impact Assessment and Modelling: An Expert Consultation and Narrative Literature Review.

BACKGROUND: Health impact assessment (HIA) is a widely used process that aims to identify the health impacts, positive or negative, of a policy or intervention that is not necessarily placed in the health sector. Most HIAs are done prospectively and aim to forecast expected health impacts under assumed policy implementation. HIAs may quantitatively and/ or qualitatively assess health impacts, with this study focusing on the former. A variety of quantitative modelling methods exist that are used for forecasting health impacts, however, they differ in application area, data requirements, assumptions, risk modelling, complexities, limitations, strengths, and comprehensibility. We reviewed relevant models, so as to provide public health researchers with considerations for HIA model choice. METHODS: Based on an HIA expert consultation, combined with a narrative literature review, we identified the most relevant models that can be used for health impact forecasting. We narratively and comparatively reviewed the models, according to their fields of application, their configuration and purposes, counterfactual scenarios, underlying assumptions, health risk modelling, limitations and strengths. RESULTS: Seven relevant models for health impacts forecasting were identified, consisting of (i) comparative risk assessment (CRA), (ii) time series analysis (TSA), (iii) compartmental models (CMs), (iv) structural models (SMs), (v) agent-based models (ABMs), (vi) microsimulations (MS), and (vii) artificial intelligence (AI)/machine learning (ML). These models represent a variety in approaches and vary in the fields of HIA application, complexity and comprehensibility. We provide a set of criteria for HIA model choice. Researchers must consider that model input assumptions match the available data and parameter structures, the available resources, and that model outputs match the research question, meet expectations and are comprehensible to end-users. CONCLUSION: The reviewed models have specific characteristics, related to available data and parameter structures, computational implementation, interpretation and comprehensibility, which the researcher should critically consider before HIA model choice.

Developing an integrated microsimulation model for the impact of fiscal policies on child health in Europe: the example of childhood obesity in Italy.

BACKGROUND: We developed an integrated model called Microsimulation for Income and Child Health (MICH) that provides a tool for analysing the prospective effects of fiscal policies on childhood health in European countries. The aim of this first MICH study is to evaluate the impact of alternative fiscal policies on childhood overweight and obesity in Italy. METHODS: MICH model is composed of three integrated modules. Firstly, module 1 (M1) simulates the effects of fiscal policies on disposable household income using the tax-benefit microsimulation program EUROMOD fed with the Italian EU-SILC 2010 data. Secondly, module 2 (M2) exploits data provided by the Italian birth cohort called Nascita e Infanzia: gli Effetti dell'Ambiente (NINFEA), translated as Birth and Childhood: the Effects of the Environment study, and runs a series of concatenated regressions in order to estimate the prospective effects of income on child body mass index (BMI) at different ages. Finally, module 3 (M3) uses dynamic microsimulation techniques that combine the population structure and incomes obtained by M1, with regression model specifications and estimated effect sizes provided by M2, projecting BMI distributions according to the simulated policy scenarios. RESULTS: Both universal benefits, such as universal basic income (BI), and targeted interventions, such as child benefit (CB) for poorer households, have a significant effect on childhood overweight, with a prevalence ratio (PR) in 10-year-old children-in comparison with the baseline fiscal system-of 0.88 (95%CI 0.82-0.93) and 0.89 (95%CI 0.83-0.94), respectively. The impact of the fiscal reforms was even larger for child obesity, reaching a PR of 0.67 (95%CI 0·50-0.83) for the simulated BI and 0.64 (95%CI 0.44-0.84) for CB at the same age. While both types of policies show similar effects, the estimated costs for a 1% prevalence reduction in overweight and obesity with respect to the baseline scenario is much lower with a more focalised benefit policy than with universal ones. CONCLUSIONS: Our results show that fiscal policies can have a strong impact on childhood health conditions. Focalised interventions that increase family income, especially in the most vulnerable populations, can help to prevent child overweight and obesity. Robust microsimulation models to forecast the effects of fiscal policies on health should be considered as one of the instruments to reach the Health in All Policies (HiAP) goals.

Is changing the minimum legal drinking age an effective policy tool?

In year 1991, regional governments in Spain started a period of implementation of a law that rose the minimum legal drinking age from 16 to 18 years old. To evaluate the effects of this change on the consumption of legal drugs and its related morbidity outcomes, we construct a regional panel dataset on alcohol consumption and hospital entry registers and compare variation in several measures of prevalence between the treatment group (16-18 years old) and the control group (20-22 years old). Our findings show important differences by gender. Our main result regarding overall drinking prevalence shows a reduction of -21.37% for the subsample that includes males and females altogether. This effect on drinking is mainly driven by a reduction of -44.43% in mixed drinks and/or liquors drinking prevalence corresponding to the subsample of males. No causal effects regarding overall smoking prevalence and hospitalizations due to alcohol overdose or motor vehicle traffic accidents were found. To our knowledge, this is the first paper providing evidence on gender-based differences to policies aimed at reducing alcohol consumption. Our results have important policy implications for countries currently considering changes in the minimum legal drinking age.