Urban environment and health: a cross-sectional multiregional project based on population health surveys in Spain (DAS-EP project) - study protocol.

INTRODUCTION: The European Environment Agency estimates that 75% of the European population lives in cities. Despite the many advantages of city life, the risks and challenges to health arising from urbanisation need to be addressed in order to tackle the growing burden of disease and health inequalities in cities. This study, Urban environment and health: a cross-sectional multiregional project based on population health surveys in Spain (DAS-EP project), aims to investigate the complex association between the urban environmental exposures (UrbEEs) and health. METHODS AND ANALYSIS: DAS-EP is a Spanish multiregional cross-sectional project that combines population health surveys (PHS) and geographical information systems (GIS) allowing to collect rich individual-level data from 17 000 adult citizens participating in the PHS conducted in the autonomous regions of the Basque Country, Andalusia, and the Valencian Community, and the city of Barcelona in the years 2021-2023. This study focuses on the population living in cities or metropolitan areas with more than 100 000 inhabitants. UrbEEs are described by objective estimates at participants' home addresses by GIS, and subjective indicators present in PHS. The health outcomes included in the PHS and selected for this study are self-perceived health (general and mental), prevalence of chronic mental disorders, health-related quality of life, consumption of medication for common mental disorders and sleep quality. We aim to further understand the direct and indirect effects between UrbEEs and health, as well as to estimate the impact at the population level, taking respondents' sociodemographic and socioeconomic characteristics, and lifestyle into consideration. ETHICS AND DISSEMINATION: The study was approved by the regional Research Ethics Committee of the Basque Country (Ethics Committee for Research Involving Medicinal Products in the Basque Country; PI2022138), Andalusia (Biomedical Research Ethics Committee of the Province of Granada; 2078-N-22), Barcelona (CEIC-PSMar; 2022/10667) and the Valencian Community (Ethics Committee for Clinical Research of the Directorate General of Public Health and Center for Advanced Research in Public Health; 20221125/04). The results will be communicated to the general population, health professionals, and institutions through conferences, reports and scientific articles.

Multimorbidity patterns and disability and healthcare use in Europe: do the associations change with the regional socioeconomic status?

Multimorbidity, the concurrence of several chronic conditions, is a rising concern that increases the years lived with disability and poses a burden on healthcare systems. Little is known on how it interacts with socioeconomic deprivation, previously associated with poor health-related outcomes. We aimed to characterize the association between multimorbidity and these outcomes and how this relationship may change with socioeconomic development of regions. 55,915 individuals interviewed in 2017 were drawn from the Survey of Health, Ageing and Retirement in Europe, a population-based study. A Latent Class Analysis was conducted to fit multimorbidity patterns based on 16 self-reported conditions. Physical limitation, quality-of-life and healthcare utilization outcomes were regressed on those patterns adjusting for additional covariates. Those analyses were then extended to assess whether such associations varied with the region socioeconomic status. We identified six different patterns, labelled according to their more predominant chronic conditions. After the "healthy" class, the "metabolic" and the "osteoarticular" classes had the best outcomes involving limitations and the lowest healthcare utilization. The "neuro-affective-ulcer" and the "several conditions" classes yielded the highest probabilities of physical limitation, whereas the "cardiovascular" group had the highest probability of hospitalization. The association of multimorbidity over physical limitations appeared to be stronger when living in a deprived region, especially for metabolic and osteoarticular conditions, whereas no major effect differences were found for healthcare use. Multimorbidity groups do differentiate in terms of limitation and healthcare utilization. Such differences are exacerbated with socioeconomic inequities between regions even within Europe.

Peptide-conjugated antimiRs improve myotonic dystrophy type 1 phenotypes by promoting endogenous MBNL1 expression.

Myotonic dystrophy type 1 (DM1) is a rare neuromuscular disease caused by a CTG repeat expansion in the DMPK gene that generates toxic RNA with a myriad of downstream alterations in RNA metabolism. A key consequence is the sequestration of alternative splicing regulatory proteins MBNL1/2 by expanded transcripts in the affected tissues. MBNL1/2 depletion interferes with a developmental alternative splicing switch that causes the expression of fetal isoforms in adults. Boosting the endogenous expression of MBNL proteins by inhibiting the natural translational repressors miR-23b and miR-218 has previously been shown to be a promising therapeutic approach. We designed antimiRs against both miRNAs with a phosphorodiamidate morpholino oligonucleotide (PMO) chemistry conjugated to cell-penetrating peptides (CPPs) to improve delivery to affected tissues. In DM1 cells, CPP-PMOs significantly increased MBNL1 levels. In some candidates, this was achieved using concentrations less than two orders of magnitude below the median toxic concentration, with up to 5.38-fold better therapeutic window than previous antagomiRs. In HSALR mice, intravenous injections of CPP-PMOs improve molecular, histopathological, and functional phenotypes, without signs of toxicity. Our findings place CPP-PMOs as promising antimiR candidates to overcome the treatment delivery challenge in DM1 therapy.

Predictive capacity of FRAX in a spanish region with a hip fracture rate close to the national mean.

BACKGROUND: It is known that standardized incidence rates of hip fracture vary among older people in Spain. So far, the results published on the validation of the FRAX® tool in Spain have suggested that the major osteoporotic fractures (MOFs) risk in our country is underestimated. These studies have practically been based on Spanish cohorts evaluated in Catalonia, a higher hip fracture rate area. The purpose of this study is to analyse the ability of the FRAX® in a Spanish mid-fracture rate population. METHODS: Study design: Retrospective cohort study. MEASURES: MOFs: hip, humerus, wrist, spine fractures. Risk of fracture assessed by calculating odds ratios (ORs). Predictive capacity of FRAX® according to the osteoporotic fractures observed between 2009 and 2018 (ObsFr) to predicted by FRAX® without densitometry in 2009 (PredFr) ratio. RESULTS: 285 participants (156 women, 54.7%) with a mean ± SD of 61.5 ± 14 years. Twenty-four people sustained 27 fractures (15 MOFs). Significant ORs were observed for an age ≥ 65 (2.92; 95% CI, 1.07-7.96), female sex (3.18; 95% CI, 1.24-8.16), rheumatoid arthritis (0.62; 95% CI, 2.03-55.55), proton pump (2.71; 95% CI, 1.20-6.09) and serotonin reuptake (2.51; 95% CI, 1.02-6.16) inhibitors. The ObsFr/PredFr ratio in women were 1.12 (95% CI, 0.95-1.29) for MOFs and 0.47 (95% CI, 0-0.94) for hip fractures. Men had a ratio of 0.57 (95% CI, 0.01-1.14) for MOF, no hip fractures were observed. The ratios for the overall group were 1.29 (95% CI, 1.12-1.48) for MOFs and 0.70 (95% CI, 0.22-1.17) for hip fractures. CONCLUSIONS: FRAX® accurately predicted MOFs in women population with a hip fracture incidence rate close to the national mean compared to previous studies conducted in higher incidence regions in Spain.

A 14-Year Longitudinal Analysis of Healthcare Expenditure on Dementia and Related Factors (DEMENCOST Study).

BACKGROUND: The large number of dementia cases produces a great pressure on health and social care services, which requires efficient planning to meet the needs of patients through infrastructure, equipment, and financial, technical, and personal resources adjusted to their demands. Dementia analysis requires studies with a very precise patient characterization of both the disease and comorbidities present, and long-term follow-up of patients in clinical aspects and patterns of resource utilization and costs generated. OBJECTIVE: To describe and quantify direct healthcare expenditure and its evolution from three years before and up to ten years after the diagnosis of dementia, compared to a matched group without dementia. METHODS: Retrospective cohort design with follow-up from 6 to 14 years. We studied 996 people with dementia (PwD) and 2,998 controls matched for age, sex, and comorbidity. This paper adopts the provider's perspective as the perspective of analysis and refers to the costs actually incurred in providing the services. Aggregate costs and components per patient per year were calculated and modelled. RESULTS: Total health expenditure increases in PwD from the year of diagnosis and in each of the following 7 years, but not thereafter. Health status and mortality are factors explaining the evolution of direct costs. Dementia alone is not a statistically significant factor in explaining differences between groups. CONCLUSION: The incremental direct cost of dementia may not be as high or as long as studies with relatively short follow-up suggest. Dementia would have an impact on increasing disease burden and mortality.

Epidemiological and clinical profile of amyotrophic lateral sclerosis in Ethiopia: a 5-year multicenter retrospective study.

Background: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease that results in progressive weakness of skeletal muscles including respiratory muscles. Epidemiological and clinical aspects of ALS are derived from a few world regions with very little representation of low- and middle-income countries. We therefore set out to determine the epidemiological and clinical phenotype of individuals with ALS in Ethiopia. Methods: Multicenter retrospective analysis was conducted using clinical records from ALS patients seen in Ethiopia at Tikur Anbessa Specialized Hospital and Yehuleshet specialty clinic between January 2016 and August 2021. The data collected included clinical characteristics, disease-related symptoms, a revised ALS functional rating scale, and medications. Results: Patients in Ethiopia had a younger age of onset with a mean age of disease onset of 51.9 years. 2.9% of patients had juvenile ALS, and the male-to-female ratio was almost 2:1. 4.9% had a positive family history of the disease. 68% of patients had spinal region involvement at onset, while 32% had bulbar region involvement at onset. Riluzole was used by 31% of ALS patients. 20.6% of patients had some respiratory symptoms, but none received a standard respiratory function assessment. 33.3% of patients were wheelchair-bound. Conclusion: In this retrospective study spanning 5 years, we examined the clinical phenotype of ALS in Ethiopian patients. Our findings suggest that most patients had clinically definite ALS with spinal region involvement. Further research, including genetic and epigenetic information, is necessary to understand the early onset of the disease in Ethiopia.

Impact of the COVID-19 Pandemic on the Socioeconomic Inequalities in Mortality in Spanish Provinces.

BACKGROUND: Although many studies have assessed the socioeconomic inequalities caused by COVID-19 in several health outcomes, there are numerous issues that have been poorly addressed. For instance, have socioeconomic inequalities in mortality from COVID-19 increased? What impact has the pandemic had on inequalities in specific causes of mortality other than COVID-19? Are the inequalities in COVID-19 mortality different from other causes? In this paper we have attempted to answer these questions for the case of Spain. METHODS: We used a mixed longitudinal ecological design in which we observed mortality from 2005 to 2020 in the 54 provinces into which Spain is divided. We considered mortality from all causes, not excluding, and excluding mortality from COVID-19; and cause-specific mortality. We were interested in analysing the trend of the outcome variables according to inequality, controlling for both observed and unobserved confounders. RESULTS: Our main finding was that the increased risk of dying in 2020 was greater in the Spanish provinces with greater inequality. In addition, we have found that: (i) the pandemic has exacerbated socioeconomic inequalities in mortality, (ii) COVID-19 has led to gender differences in the variations in risk of dying (higher in the case of women) and (iii) only in cardiovascular diseases and Alzheimer did the increased risk of dying differ between the most and least unequal provinces. The increase in the risk of dying was different by gender (greater in women) for cardiovascular diseases and cancer. CONCLUSION: Our results can be used to help health authorities know where and in which population groups future pandemics will have the greatest impact and, therefore, be able to take appropriate measures to prevent such effects.

Repurposing selective serotonin reuptake inhibitors for severity of COVID-19: A population-based study.

The World Health Organization has proposed that a search be made for alternatives to vaccines for the prevention and treatment of COVID-19, with one such alternative being selective serotonin reuptake inhibitors (SSRIs). This study thus sought to assess: the impact of previous treatment with SSRI antidepressants on the severity of COVID-19 (risk of hospitalisation, admission to an intensive care unit [ICU], and mortality), its influence on susceptibility to SARS-CoV-2 and progression to severe COVID-19. We conducted a population-based multiple case-control study in a region in the north-west of Spain. Data were sourced from electronic health records. Adjusted odds ratios (aORs) and 95%CIs were calculated using multilevel logistic regression. We collected data from a total of 86,602 subjects: 3060 cases PCR+, 26,757 non-hospitalised cases PCR+ and 56,785 controls (without PCR+). Citalopram displayed a statistically significant decrease in the risk of hospitalisation (aOR=0.70; 95% CI 0.49-0.99, p = 0.049) and progression to severe COVID-19 (aOR=0.64; 95% CI 0.43-0.96, p = 0.032). Paroxetine was associated with a statistically significant decrease in risk of mortality (aOR=0.34; 95% CI 0.12 - 0.94, p = 0.039). No class effect was observed for SSRIs overall, nor was any other effect found for the remaining SSRIs. The results of this large-scale, real-world data study indicate that, citalopram, could be a candidate drug for being repurposed as preventive treatment aimed at reducing COVID-19 patients' risk of progressing to severe stages of the disease.

Housing Supply and How It Is Related to Social Inequalities-Air Pollution, Green Spaces, Crime Levels, and Poor Areas-In Catalonia.

We carried out a search of over 12,000 houses offered on the rental market in Catalonia and assessed the possibility of families below the poverty threshold being able to rent these homes. In this regard, we wanted to evaluate whether the economic situation of families is able to influence their social environment, surroundings, and safety. We observed how their economic situation can allow families the possibility of developing a life without exposure to health risks, and how economic constraints result in disadvantages in several areas of life. The results show how families at risk of poverty live in less favourable conditions and experience a widening of different gaps, with current prices leading to a possible poverty trap for the most disadvantaged groups. The higher the percentage of the population below the threshold, the lower the possibility of not being able to rent a house compared to areas with a lower prevalence of population below the threshold. This association was observed both when considering the risk linearly and non-linearly. Linearly, the probability of not renting a house was reduced by 8.36% for each 1% increase in the prevalence of population at risk of extreme poverty. In the second, third and fourth percentage quartiles, the probability of not being able to rent a house decreased by 21.13%, 48.61%, and 57.79%, respectively. In addition, the effect was different inside and outside of metropolitan areas, with the former showing a decrease of 19.05% in the probability of renting a house, whereas outside metropolitan areas the probability increased by 5.70%.

APPRAISE-RS: Automated, updated, participatory, and personalized treatment recommender systems based on GRADE methodology.

Purpose: Clinical practice guidelines (CPGs) have become fundamental tools for evidence-based medicine (EBM). However, CPG suffer from several limitations, including obsolescence, lack of applicability to many patients, and limited patient participation. This paper presents APPRAISE-RS, which is a methodology that we developed to overcome these limitations by automating, extending, and iterating the methodology that is most commonly used for building CPGs: the GRADE methodology. Method: APPRAISE-RS relies on updated information from clinical studies and adapts and automates the GRADE methodology to generate treatment recommendations. APPRAISE-RS provides personalized recommendations because they are based on the patient's individual characteristics. Moreover, both patients and clinicians express their personal preferences for treatment outcomes which are considered when making the recommendation (participatory). Rule-based system approaches are used to manage heuristic knowledge. Results: APPRAISE-RS has been implemented for attention deficit hyperactivity disorder (ADHD) and tested experimentally on 28 simulated patients. The resulting recommender system (APPRAISE-RS/TDApp) shows a higher degree of treatment personalization and patient participation than CPGs, while recommending the most frequent interventions in the largest body of evidence in the literature (EBM). Moreover, a comparison of the results with four blinded psychiatrist prescriptions supports the validation of the proposal. Conclusions: APPRAISE-RS is a valid methodology to build recommender systems that manage updated, personalized and participatory recommendations, which, in the case of ADHD includes at least one intervention that is identical or very similar to other drugs prescribed by psychiatrists.

Colchicine and risk of hospitalization due to COVID-19: A population-based study.

Colchicine is one of the most widely studied and best-known anti-inflammatory treatments. This study aimed to assess the effect of colchicine on risk of hospitalization due to COVID-19; and its effect on susceptibility to and severity of the virus in patients with COVID-19. We carried out a population-based case-control study. The following groups were applied: (1) to assess risk of hospitalization, cases were patients with a positive PCR who were hospitalized due to COVID-19, and controls without a positive PCR; (2) to assess susceptibility to COVID-19, cases were patients with a positive PCR (hospitalized and non-hospitalized), and the same controls; (3) to determine potential severity, cases were subjects with COVID-19 hospitalized, and controls patients with COVID-19 nonhospitalised. Different electronic, linked, administrative health and clinical databases were used to extract data on sociodemographic variables, comorbidities, and medications dispensed. The study covered 3060 subjects with a positive PCR who were hospitalized, 26 757 with a positive PCR who were not hospitalized, and 56 785 healthy controls. After adjustment for sociodemographic variables, comorbidities and other treatments, colchicine did not modify risk of hospitalization due to COVID-19 (adjusted odd ratio [OR] 1.08 [95% confidence interval (CI) 0.76-1.53]), patients' susceptibility to contracting the disease (adjusted OR 1.12 (95% CI 0.91-1.37)) or the severity of the infection (adjusted OR 1.03 [95% CI 0.67-1.59]). Our results would neither support the prophylactic use of colchicine for prevention of the infection or hospitalization in any type of patient, nor justify the withdrawal of colchicine treatment due to a higher risk of contracting COVID-19.

PandemonCAT: Monitoring the COVID-19 Pandemic in Catalonia, Spain.

BACKGROUND: The principal objective of this paper is to introduce an online interactive application that helps in real-time monitoring of the COVID-19 pandemic in Catalonia, Spain (PandemonCAT). METHODS: This application is designed as a collection of user-friendly dashboards using open-source R software supported by the Shiny package. RESULTS: PandemonCAT reports accumulated weekly updates of COVID-19 dynamics in a geospatial interactive platform for individual basic health areas (ABSs) of Catalonia. It also shows on a georeferenced map the evolution of vaccination campaigns representing the share of population with either one or two shots of the vaccine, for populations of different age groups. In addition, the application reports information about environmental and socioeconomic variables and also provides an interactive interface to visualize monthly public mobility before, during, and after the lockdown phases. Finally, we report the smoothed standardized COVID-19 infected cases and mortality rates on maps of basic health areas ABSs and regions of Catalonia. These smoothed rates allow the user to explore geographic patterns in incidence and mortality rates. The visualization of the variables that could have some influence on the spatiotemporal dynamics of the pandemic is demonstrated. CONCLUSIONS: We believe the addition of these new dimensions, which is the key innovation of our project, will improve the current understanding of the spread and the impact of COVID-19 in the community. This application can be used as an open tool for consultation by the public of Catalonia and Spain in general. It could also have implications in facilitating the visualization of public health data, allowing timely interpretation due to the unpredictable nature of the pandemic.

Clustering of Small Territories Based on Axes of Inequality.

BACKGROUND: In the present paper, we conduct a study before creating an e-cohort for the design of the sample. This e-cohort had to enable the effective representation of the province of Girona to facilitate its study according to the axes of inequality. METHODS: The territory under study is divided by municipalities, considering these different axes. The study consists of a comparison of 14 clustering algorithms, together with 3 data sets of municipal information to detect the grouping that was the most consistent. Prior to carrying out the clustering, a variable selection process was performed to discard those that were not useful. The comparison was carried out following two axes: results and graphical representation. RESULTS: The intra-cluster results were also analyzed to observe the coherence of the grouping. Finally, we study the probability of belonging to a cluster, such as the one containing the county capital. CONCLUSIONS: This clustering can be the basis for working with a sample that is significant and representative of the territory.

Analysis of the geographic pattern of the police reports for domestic violence in Girona (Spain).

BACKGROUND: There are many studies that address the issue of gender-based violence, but few analyse the police-reported cases. It is as important to analyse the temporal and geographic distribution of these incidents as it is the sociodemographic profile of the accuser. To this effect, the present study aims to analyse the sociodemographic profile of the victims of the particular case of domestic violence that report the incident to the police and to evaluate the spatial-temporal distribution of these reports. METHODS: Using the data from a database containing the police-reported incidents of domestic violence in Girona in the period 2012-2018, the risk of a police-reported incident was estimated by adjusting the two-part Hurdle model. RESULTS: The risk of reporting incidents of domestic violence to the police is higher in the less deprived areas of the city, and the spatial distribution of these police reports corroborate this finding. Nevertheless, those areas with the greatest socio-economic deprivation were also the ones where there were less police reports filed. Also the prediction of less police reports in the census tract with the highest percentage of the population with an insufficient educational level coincides with the largest number of police reports made by women with a medium and university level education (56.1%) compared with 9.5% of police reports made by women with insufficient schooling. CONCLUSIONS: These results can be useful for social protection services to design policies specifically aimed at women residing in those areas with the highest risk. Moreover, the use of spatial statistical techniques together with geographic information systems tools is a good strategy to analyse domestic violence and other types of offences because they not only allow to graphically identify the spatial distribution, but it is also a good tool to identify problems related to this type of offence.

Nocebo Response in Attention Deficit Hyperactivity Disorder: Meta-Analysis and Meta-Regression of 105 Randomized Clinical Trials.

OBJECTIVE: To determine nocebo response in ADHD, identify covariates modifying nocebo response, and study the relationship between nocebo response and drug safety. METHOD: Systematic review of randomized, double-blind, placebo-controlled clinical trials (RCT) investigating the efficacy and safety of pharmacological interventions for ADHD patients. The influence of covariates was studied using meta-regression. RESULTS: A total of 105 studies with 8,743 patients in placebo arms were included. Slightly over half (55.5%) of the patients experienced adverse events (AE) while receiving placebo. Nocebo response was associated positively with age, treatment length and method for collecting AEs. Studies with the largest nocebo response showcased the greatest drug response and the best outcome for drug safety. CONCLUSION: Nocebo response in ADHD RCTs is remarkable, showing a positive relationship with drug response, and a negative relationship with drug safety.

Past-season, pre-season and in-season risk assessment of groin problems in male football players: a prospective full-season study.

OBJECTIVE: We assessed past-season, pre-season and in-season risk factors to investigate their association with an in-season groin problem in male amateur football players. METHODS: Past-season groin-pain information and pre-season short-lever and long-lever adductor squeeze strength were obtained at baseline, together with anthropometrics (weight, lower limb lever length) and player age. In-season hip-related and groin-related sporting function was monitored every 4 weeks using the Sports and Recreation (Sport) subscale from the Hip And Groin Outcome Score questionnaire (HAGOS (Sport)). Groin problems, including time-loss groin injuries and groin pain irrespective of time loss, were collected over a 39-week competitive in-season. We estimated relative risk (RR), and 95% credibility interval (ICr) from logistic regressions fitted in a Bayesian framework. RESULTS: Players (n=245) suffering from groin pain during the past-season had 2.4 times higher risk of experiencing a groin problem in the new season (2.40 RR; 95% ICr 1.5 to 3.7). This risk was reduced by 35% (0.65 RR; 95% ICr 0.42 to 0.99) per unit (N·m/kg) increase in the long-lever adductor squeeze test. Player age, short-lever squeeze test and the HAGOS (Sport) scores were not associated with the risk of a groin problem. CONCLUSIONS: Past-season groin pain increased the risk of a groin problem in the new in-season. This risk was reduced by higher pre-season long-lever adductor squeeze strength. Past-season groin-pain information and long-lever adductor squeeze strength can be quickly obtained during pre-season to identify players with an elevated risk of in-season groin problems. This may be key to reduce these problems in the new season.

Placebo Response and Its Predictors in Attention Deficit Hyperactivity Disorder: A Meta-Analysis and Comparison of Meta-Regression and MetaForest.

BACKGROUND: High placebo response in attention deficit hyperactivity disorder (ADHD) can reduce medication-placebo differences, jeopardizing the development of new medicines. This research aims to (1) determine placebo response in ADHD, (2) compare the accuracy of meta-regression and MetaForest in predicting placebo response, and (3) determine the covariates associated with placebo response. METHODS: A systematic review with meta-analysis of randomized, placebo-controlled clinical trial investigating pharmacological interventions for ADHD was performed. Placebo response was defined as the change from baseline in ADHD symptom severity assessed according to the 18-item, clinician-rated, DSM-based rating scale. The effect of study design-, intervention-, and patient-related covariates in predicting placebo response was studied by means of meta-regression and MetaForest. RESULTS: Ninety-four studies including 6614 patients randomized to placebo were analyzed. Overall, placebo response was -8.9 points, representing a 23.1% reduction in the severity of ADHD symptoms. Cross-validated accuracy metrics for meta-regression were R2 = 0.0012 and root mean squared error = 3.3219 for meta-regression and 0.0382 and 3.2599 for MetaForest. Placebo response among ADHD patients increased by 63% between 2001 and 2020 and was larger in the United States than in other regions of the world. CONCLUSIONS: Strong placebo response was found in ADHD patients. Both meta-regression and MetaForest showed poor performance in predicting placebo response. ADHD symptom improvement with placebo has markedly increased over the last 2 decades and is greater in the United States than the rest of the world.

Prenatal exposure to persistent organic pollutants and childhood obesity: A systematic review and meta-analysis of human studies.

We conducted a systematic review and meta-analysis of the associations between prenatal exposure to persistent organic pollutants (POPs) and childhood obesity. We focused on organochlorines (dichlorodiphenyltrichloroethane [DDT], dichlorodiphenyldichloroethylene [DDE], hexachlorobenzene [HCB], and polychlorinated biphenyls [PCBs]), perfluoroalkyl and polyfluoroalkyl substances (PFAS), and polybrominated diphenyl ethers (PBDEs) that are the POPs more widely studied in environmental birth cohorts so far. We search two databases (PubMed and Embase) through July/09/2021 and identified 33 studies reporting associations with prenatal organochlorine exposure, 21 studies reporting associations with prenatal PFAS, and five studies reporting associations with prenatal PBDEs. We conducted a qualitative review. Additionally, we performed random-effects meta-analyses of POP exposures, with data estimates from at least three prospective studies, and BMI-z. Prenatal DDE and HCB levels were associated with higher BMI z-score in childhood (beta: 0.12, 95% CI: 0.03, 0.21; I2 : 28.1% per study-specific log increase of DDE and beta: 0.31, 95% CI: 0.09, 0.53; I2 : 31.9% per study-specific log increase of HCB). No significant associations between PCB-153, PFOA, PFOS, or pentaPBDEs with childhood BMI were found in meta-analyses. In individual studies, there was inconclusive evidence that POP levels were positively associated with other obesity indicators (e.g., waist circumference).

Compositional and Bayesian inference analysis of the concentrations of air pollutants in Catalonia, Spain.

While most countries have networks of stations for monitoring pollutant concentrations, they do not cover the whole territory continuously. Therefore, to be able to carry out a spatial and temporal study, the predictions for air pollution from unmeasured sites and time periods need to be used. The objective of this study is to predict the air pollutant concentrations of PM10, O3, NO2, SO2 and CO in sites throughout Catalonia (Spain) and time periods without a monitoring station. Compositional data (CoDa) studies the relative importance of pollutants. A novel feature in this article is combining CoDa with an indicator of total pollution. Predictions are then made using a combination of spatio-temporal models and the Bayesian Laplace Integrated Approach (INLA) inference method. The most relevant results obtained indicate that the log-ratio between NO2 and O3 has the highest variance and the best predictive accuracy in time and space. Total pollution levels are second in variance but have low spatial predictive accuracy. Third in variance is the low temporal accuracy found in the log-ratio between SO2 and the remaining pollutants. Globally, the combination of CoDa and the INLA method is suitable for making effective spatio-temporal predictions of air pollutants.