Perfluoroalkyl substances and risk of type II diabetes: A prospective nested case-control study

BACKGROUND

Perfluoroalkyl substances (PFAS) have drawn much attention due to bioaccumulation potential and their current omnipresence in human blood. We assessed whether plasma PFAS, suspected to induce endocrine-disrupting effects, were prospectively associated with clinical type 2 diabetes (T2D) risk.

METHODS

We established a nested case-control study within the Swedish prospective population-based Västerbotten Intervention Programme cohort. Several PFAS were measured in plasma from a subset of 124 case-control pairs at baseline (during 1990-2003) and at 10-year follow-up. T2D cases were matched (1:1) according to gender, age and sample date with participants without T2D (controls). Conditional logistic regressions were used to prospectively assess risk of T2D by baseline PFAS plasma concentrations. Associations between long-term PFAS plasma levels (mean of baseline and follow-up) and insulin resistance (HOMA2-IR) and beta-cell function (HOMA2-B%) at follow-up were prospectively explored among 178 and 181 controls, respectively, by multivariable linear regressions.

RESULTS

After adjusting for gender, age, sample year, diet and body mass index, the odds ratio of T2D for the sum of PFAS (Σ z-score PFAS) was 0.52 (95% confidence interval, CI: 0.20, 1.36), comparing third with first tertile; and 0.92 (95% CI: 0.84, 1.00) per one standard deviation increment of sum of log-transformed PFAS. Among the controls, the adjusted β of HOMA2-IR and HOMA-B% for the sum of PFAS were -0.26 (95% CI: -0.52, -0.01) and -9.61 (95% CI: -22.60, 3.39) respectively comparing third with first tertile.

CONCLUSIONS

This prospective nested case-control study yielded overall inverse associations between individual PFAS and risk of T2D, although mostly non-significant. Among participants without T2D, long-term PFAS exposure was prospectively associated with lower insulin resistance.

Methodological issues in a prospective study on plasma concentrations of persistent organic pollutants and pancreatic cancer risk within the EPIC cohort

BACKGROUND

The use of biomarkers of environmental exposure to explore new risk factors for pancreatic cancer presents clinical, logistic, and methodological challenges that are also relevant in research on other complex diseases.

OBJECTIVES

First, to summarize the main design features of a prospective case-control study -nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort- on plasma concentrations of persistent organic pollutants (POPs) and pancreatic cancer risk. And second, to assess the main methodological challenges posed by associations among characteristics and habits of study participants, fasting status, time from blood draw to cancer diagnosis, disease progression bias, basis of cancer diagnosis, and plasma concentrations of lipids and POPs. Results from etiologic analyses on POPs and pancreatic cancer risk, and other analyses, will be reported in future articles.

METHODS

Study subjects were 1533 participants (513 cases and 1020 controls matched by study centre, sex, age at blood collection, date and time of blood collection, and fasting status) enrolled between 1992 and 2000. Plasma concentrations of 22 POPs were measured by gas chromatography - triple quadrupole mass spectrometry (GC-MS/MS). To estimate the magnitude of the associations we calculated multivariate-adjusted odds ratios by unconditional logistic regression, and adjusted geometric means by General Linear Regression Models.

RESULTS

There were differences among countries in subjects' characteristics (as age, gender, smoking, lipid and POP concentrations), and in study characteristics (as time from blood collection to index date, year of last follow-up, length of follow-up, basis of cancer diagnosis, and fasting status). Adjusting for centre and time of blood collection, no factors were significantly associated with fasting status. Plasma concentrations of lipids were related to age, body mass index, fasting, country, and smoking. We detected and quantified 16 of the 22 POPs in more than 90% of individuals. All 22 POPs were detected in some participants, and the smallest number of POPs detected in one person was 15 (median, 19) with few differences by country. The highest concentrations were found for p,p'-DDE, PCBs 153 and 180 (median concentration: 3371, 1023, and 810 pg/mL, respectively). We assessed the possible occurrence of disease progression bias (DPB) in eight situations defined by lipid and POP measurements, on one hand, and by four factors: interval from blood draw to index date, tumour subsite, tumour stage, and grade of differentiation, on the other. In seven of the eight situations results supported the absence of DPB.

CONCLUSIONS

The coexistence of differences across study centres in some design features and participant characteristics is of relevance to other multicentre studies. Relationships among subjects' characteristics and among such characteristics and design features may play important roles in the forthcoming analyses on the association between plasma concentrations of POPs and pancreatic cancer risk.

Long term effect of air pollution on incident hospital admissions: Results from the Italian Longitudinal Study within LIFE MED HISS project

BACKGROUND

The LIFE MED HISS project aims at setting up a surveillance system on the long term effects of air pollution on health, using data from National Health Interview Surveys and other currently available sources of information in most European countries. Few studies assessed the long term effect of air pollution on hospital admissions in European cohorts.

OBJECTIVE

The objective of this paper is to estimate the long term effect of fine particulate matter (PM2.5) and nitrogen dioxide (NO₂) on first-ever (incident) cause-specific hospitalizations in Italy.

METHODS

We used data from the Italian Longitudinal Study (ILS), a cohort study based on the 1999-2000 National Health Interview Survey (NHIS), followed up for hospitalization (2001-2008) at individual level. The survey contains information on crucial potential confounders: occupational/educational/marital status, body mass index (BMI), smoking habit and physical activity. Annual mean exposure to PM2.5 and NO₂ was assigned starting from simulated gridded data at spatial resolution of 4 × 4 km² firstly integrated with data from monitoring stations and then up-scaled at municipality level. Statistical analyses were conducted using Cox proportional hazard models with robust variance estimator.

RESULTS

For each cause of hospitalization we estimated the hazard ratios (HRs) adjusted for confounders with 95% Confidence Interval (CI) related to a 10 μg/m³ increase in pollutants. For PM2.5 and NO₂, respectively, we found positive associations for circulatory system diseases [1.05(1.03-1.06); 1.05(1.03-1.07)], myocardial infarction [1.15(1.12-1.18); 1.15(1.12-1.18)], lung cancer [1.18(1.10-1.26); 1.20(1.12-1.28)], kidney cancer [1.24(1.11-1.29); 1.20(1.07-1.33)], all cancers (but lung) [1.06(1.04-1.08); 1.06(1.04-1.08)] and Low Respiratory Tract Infections (LRTI) [1.07 (1.04-1.11); 1.05 (1.02-1.08)].

DISCUSSION

Our results add new evidence on the effects of air pollution on first-ever (incident) hospitalizations, both in urban and rural areas. We demonstrated the feasibility of a low-cost monitoring system based on available data.

Associations of serum perfluoroalkyl substance and vitamin D biomarker concentrations in NHANES, 2003-2010

Perfluoroalkyl substances (PFAS) are persistent endocrine disrupting chemicals found in industrial and commercial products. Previous research has shown that other endocrine disrupting chemicals such as phthalates and bisphenol A may alter circulating levels of vitamin D; however, no research has examined associations between PFAS and vitamin D biomarkers. We conducted a cross-sectional analysis of 7040 individuals aged 12 years and older participating in the 2003-2010 cycles of the United States National Health and Nutrition Examination Survey (NHANES). Concentrations of perfluorooctanoic acid (PFOA), perfluorooctane sulfonic acid (PFOS), perfluorohexane sulfonic acid (PFHxS), perfluorononanoic acid (PFNA), and total 25-hydroxyvitamin D [25(OH)D] were measured in serum samples. We used multivariable linear regression to estimate covariate-adjusted differences in total 25(OH)D or prevalence odds of vitamin D deficiency per log₂ change in PFAS concentrations. We also assessed potential effect measure modification by gender, age, and race/ethnicity. PFAS were detected in over 98% of the samples. In adjusted models, each 2-fold increase in PFOS was associated with 0.9 nmol/L (95% CI: 0.2, 1.5) lower total 25(OH)D concentrations, with associations significantly stronger among whites (β: -1.7; 95% CI: -2.6, -0.7) and individuals older than 60 years of age (β: -1.7; 95% CI: -2.9, -0.5). Each 2-fold increase in PFHxS was associated with 0.8 nmol/L (95% CI: 0.3, 1.3) higher total 25(OH)D, and this association was not modified by age, gender, and race/ethnicity. PFOA and PFNA were not associated with total 25(OH)D. When assessing prevalence odds of vitamin D deficiency, we observed similar patterns of association with PFAS concentrations. Our results suggest that some PFAS may be associated with altered vitamin D levels in the United States population, and associations may vary by chemical, age, and race/ethnicity. Prospective epidemiological studies are needed to confirm our findings and determine their implications for vitamin D-associated health outcomes in children and adults.

Short-term effects of desert and non-desert PM10 on mortality in Sicily, Italy

BACKGROUND

Increased PM₁₀ concentrations are commonly observed during Saharan dust advections. Limited epidemiological evidence suggests that PM₁₀ from anthropogenic and desert sources increase mortality. We aimed to evaluate the association between source-specific PM₁₀ (non-desert and desert) and cause-specific mortality in Sicily during 2006-2012 period.

METHODS

Daily PM₁₀ concentrations at 1-km² were estimated in Sicily using satellite-based data, fixed monitors and land use variables. We identified Saharan dust episodes using meteorological models, back-trajectories, aerosol maps, and satellite images. For each dust day, we estimated desert and non-desert PM₁₀ concentrations. We applied a time-series approach on 390 municipalities of Sicily to estimate the association between PM₁₀ (non-desert and desert) and daily cause-specific mortality.

RESULTS

33% of all days were affected by Saharan dust advections. PM₁₀ concentrations were 8 μg/m³ higher during dust days compared to other days. We found positive associations of both non-desert and desert PM₁₀ with cause-specific mortality. We estimated percent increases of risk (IR%) of non-accidental mortality equal to 2.3% (95% Confidence Interval [CI]: 1.4, 3.1) and 3.8% (3.2, 4.4), per 10 μg/m³ increases in non-desert and desert PM₁₀ at lag 0-5, respectively. We also observed significant associations with cardiovascular (2.4% [1.3, 3.4] and 4.5% [3.8, 5.3]) and respiratory mortality (8.1% [6.8, 9.5], and 6.3% [5.4, 7.2]). We estimated higher effects during April-September, with IR% = 4.4% (3.2, 5.7) and 6.3% (5.4, 7.2) for non-desert and desert PM₁₀, respectively.

CONCLUSIONS

Our results confirm previous evidence of harmful effects of desert PM₁₀ on non-accidental and cardio-respiratory mortality, especially during the warm season.

Modelling local uncertainty in relations between birth weight and air quality within an urban area: combining geographically weighted regression with geostatistical simulation

In this study, we combine known methods to present a new approach to assess local distributions of estimated parameters measuring associations between air quality and birth weight in the urban area of Sines (Portugal). To model exposure and capture short-distance variations in air quality, we use a Regression Kriging estimator combining air quality point data with land use auxiliary data. To assess uncertainty of exposure, the Kriging estimator is incorporated in a sequential Gaussian simulation algorithm (sGs) providing a set of simulated exposure maps with similar spatial structural dependence and statistical properties of observed data. Following the completion of the simulation runs, we fit a geographically weighted generalized linear model (GWGLM) for each mother's place of residence, using observed health data and simulated exposure data, and repeat this procedure for each simulated map. Once the fit of GWGLM with all exposure maps is finished, we take the distribution of local estimated parameters measuring associations between exposure and birth weight, thus providing a measure of uncertainty in the local estimates. Results reveal that the distribution of local parameters did not vary substantially. Combining both methods (GWGLM and sGs), however, we are able to incorporate local uncertainty on the estimated associations providing an additional tool for analysis of the impacts of place in health.

Evaluating meteorological data from weather stations, and from satellites and global models for a multi-site epidemiological study

BACKGROUND

Longitudinal and time series analyses are needed to characterize the associations between hydrometeorological parameters and health outcomes. Earth Observation (EO) climate data products derived from satellites and global model-based reanalysis have the potential to be used as surrogates in situations and locations where weather-station based observations are inadequate or incomplete. However, these products often lack direct evaluation at specific sites of epidemiological interest.

METHODS

Standard evaluation metrics of correlation, agreement, bias and error were applied to a set of ten hydrometeorological variables extracted from two quasi-global, commonly used climate data products - the Global Land Data Assimilation System (GLDAS) and Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) - to evaluate their performance relative to weather-station derived estimates at the specific geographic locations of the eight sites in a multi-site cohort study. These metrics were calculated for both daily estimates and 7-day averages and for a rotavirus-peak-season subset. Then the variables from the two sources were each used as predictors in longitudinal regression models to test their association with rotavirus infection in the cohort after adjusting for covariates.

RESULTS

The availability and completeness of station-based validation data varied depending on the variable and study site. The performance of the two gridded climate models varied considerably within the same location and for the same variable across locations, according to different evaluation criteria and for the peak-season compared to the full dataset in ways that showed no obvious pattern. They also differed in the statistical significance of their association with the rotavirus outcome. For some variables, the station-based records showed a strong association while the EO-derived estimates showed none, while for others, the opposite was true.

CONCLUSION

Researchers wishing to utilize publicly available climate data - whether EO-derived or station based - are advised to recognize their specific limitations both in the analysis and the interpretation of the results. Epidemiologists engaged in prospective research into environmentally driven diseases should install their own weather monitoring stations at their study sites whenever possible, in order to circumvent the constraints of choosing between distant or incomplete station data or unverified EO estimates.

Neighbourhood safety and smoking in population subgroups: The HELIUS study

This study examines the associations between neighbourhood safety and three types of smoking behaviour, and whether these associations differ by sex, age, ethnicity and individual-level socio-economic position. Baseline data (2011-2015) from the The HEalthy LIfe in an Urban Setting (HELIUS) study (Amsterdam, the Netherlands) were used. Smoking behaviour was based on self-report. Heavy smoking was defined as smoking ≥10 cigarettes per day. Nicotine dependence was assessed using the Fagerström questionnaire. Geographic Information System techniques were used to construct local residential areas and to examine neighbourhood safety for these areas using micro-scale environmental data. Multilevel logistic regression analyses with 6-digit zip code area as a second level were used to assess the association between neighbourhood safety and smoking. In our study sample of 22,728 participants (18-70 years), 24.0% were current smokers, 13.7% were heavy smokers and 8.1% were nicotine dependent individuals. Higher levels of neighbourhood safety were significantly associated with less heavy smoking (OR = 0.88, 95% CI = 0.78-0.99) and less nicotine dependence (OR = 0.81, 95% CI = 0.69-0.95), but not with less current smoking (OR = 1.01, 95% CI = 0.91-1.11). The associations between neighbourhood safety and the three types of smoking behaviour varied by ethnicity. For instance, higher levels of neighbourhood safety were associated with less current smoking in participants of African Surinamese origin (OR = 0.71, 95% CI = 0.57-0.89), but not in those of Dutch (OR = 1.13, 95% CI = 0.91-1.39), South-Asian Surinamese (OR = 1.22, 95% CI = 0.95-1.55), Turkish (OR = 1.08, 95% CI = 0.84-1.38), Moroccan (OR = 1.53, 95% CI = 1.12-2.10) or Ghanaian (OR = 1.18, 95% CI = 0.47-2.94) origin. Policies that improve neighbourhood safety potentially contribute to less heavy smoking and nicotine dependence.

National unintentional carbon monoxide poisoning estimates using hospitalization and emergency department data

Unintentional non-fire-related (UNFR) carbon monoxide (CO) poisoning is a leading cause of poisoning in the US and a preventable cause of death. We generated national estimates of accidental CO poisoning and characterized the populations most at risk. UNFR CO poisoning cases were assessed using hospitalization and emergency department (ED) data from the Healthcare Costs and Utilization Project National Inpatient Sample and Nationwide Emergency Department Sample databases. We used hospitalization data from 2003 to 2013 and ED data from 2007 to 2013. We calculated trends using a linear regression of UNFR CO poisonings over the study period and age-adjusted rates using direct standardization and U.S. Census Bureau estimates. During 2003-2013, approximately 14,365 persons (4.1 cases/million annually) with confirmed or probable UNFR CO poisoning were admitted to hospitals and the annual rate of poisonings showed a weak downward trend (p = 0.12). During 2007-2013, approximately 101,847 persons (48.3 visits/million annually) visited the ED and the annual rate of poisonings showed a significant downward trend (p ≤ 0.01). Most UNFR CO hospital cases involved patients who were older (aged 45-64 years), white, male, or living in the South or Midwest. Overall, the rate of hospitalizations did not change over the study period. Unintentional CO poisoning is preventable and these cases represent the most recent national estimates. ED visits declined over the study period, but the hospitalization rates did not change. This emphasizes the need for prevention efforts, such as education in the ED setting, increased use of CO alarms, and proper use and maintenance of fuel-powered household appliances.

Ambient soil cation exchange capacity inversely associates with infectious and parasitic disease risk in regional Australia

Human contact with soil may be important for building and maintaining normal healthy immune defence mechanisms, however this idea remains untested at the population-level. In this continent-wide, cross-sectional study we examine the possible public health benefit of ambient exposures to soil of high cation exchange capacity (CEC), a surrogate for potential immunomodulatory soil microbial diversity. We compare distributions of normalized mean 2011/12-2012/13 age-standardized public hospital admission rates (cumulative incidence) for infectious and parasitic diseases across regional Australia (representing an average of 29,516 patients/year in 228 local government areas), within tertiles of socioeconomic status and soil exposure. To test the significance of soil CEC, we use probabilistic individual-level environmental exposure data (with or without soil), and group-level variables, in robust non-parametric multilevel modelling to predict disease rates in unseen groups. Our results show that in socioeconomically-deprived areas with high CEC soils, rates of infectious and parasitic disease are significantly lower than areas with low CEC soils. Also, health inequality (relative risk) due to socioeconomic status is significantly lower in areas with high CEC soils compared to low CEC soils (Δ relative risk = 0.47; 95% CI: 0.13, 0.82). Including soil exposure when modelling rates of infectious and parasitic disease significantly improves prediction performance, explaining an additional 7.5% (Δ r² = 0.075; 95% CI: 0.05, 0.10) of variation in disease risk, in local government areas that were not used for model building. Our findings suggest that exposure to high CEC soils (typically high soil biodiversity) associates with reduced risk of infectious and parasitic diseases, particularly in lower socioeconomic areas.

Increase in fertility following coal and oil power plant retirements in California

BACKGROUND

Few studies have explored the relationship between air pollution and fertility. We used a natural experiment in California when coal and oil power plants retired to estimate associations with nearby fertility rates.

METHODS

We used a difference-in-differences negative binomial model on the incident rate ratio scale to analyze the change in annual fertility rates among California mothers living within 0-5 km and 5-10 km of 8 retired power plants between 2001 and 2011. The difference-in-differences method isolates the portion of the pre- versus post-retirement contrast in the 0-5 km and 5-10 km bins, respectively, that is due to retirement rather than secular trends. We controlled for secular trends with mothers living 10-20 km away. Adjusted models included fixed effects for power plant, proportion Hispanic, Black, high school educated, and aged > 30 years mothers, and neighborhood poverty and educational attainment.

RESULTS

Analyses included 58,909 live births. In adjusted models, we estimated that after power plant retirement annual fertility rates per 1000 women aged 15-44 years increased by 8 births within 5 km and 2 births within 5-10 km of power plants, corresponding to incident rate ratios of 1.2 (95% CI: 1.1-1.4) and 1.1 (95% CI: 1.0-1.2), respectively. We implemented a negative exposure control by randomly selecting power plants that did not retire and repeating our analysis with those locations using the retirement dates from original 8 power plants. There was no association, suggesting that statewide temporal trends may not account for results.

CONCLUSIONS

Fertility rates among nearby populations appeared to increase after coal and oil power plant retirements. Our study design limited the possibility that our findings resulted from temporal trends or changes in population composition. These results require confirmation in other populations, given known methodological limitations of ecologic study designs.

Emerging trends in geospatial artificial intelligence (geoAI): potential applications for environmental epidemiology

Geospatial artificial intelligence (geoAI) is an emerging scientific discipline that combines innovations in spatial science, artificial intelligence methods in machine learning (e.g., deep learning), data mining, and high-performance computing to extract knowledge from spatial big data. In environmental epidemiology, exposure modeling is a commonly used approach to conduct exposure assessment to determine the distribution of exposures in study populations. geoAI technologies provide important advantages for exposure modeling in environmental epidemiology, including the ability to incorporate large amounts of big spatial and temporal data in a variety of formats; computational efficiency; flexibility in algorithms and workflows to accommodate relevant characteristics of spatial (environmental) processes including spatial nonstationarity; and scalability to model other environmental exposures across different geographic areas. The objectives of this commentary are to provide an overview of key concepts surrounding the evolving and interdisciplinary field of geoAI including spatial data science, machine learning, deep learning, and data mining; recent geoAI applications in research; and potential future directions for geoAI in environmental epidemiology.

Recent Approaches to Estimate Associations Between Source-Specific Air Pollution and Health

PURPOSE OF REVIEW

Estimating health effects associated with source-specific exposure is important for better understanding how pollution impacts health and for developing policies to better protect public health. Although epidemiologic studies of sources can be informative, these studies are challenging to conduct because source-specific exposures (e.g., particulate matter from vehicles) often are not directly observed and must be estimated. We reviewed recent studies that estimated associations between pollution sources and health to identify methodological developments designed to address important challenges.

RECENT FINDINGS

Notable advances in epidemiologic studies of sources include approaches for (1) propagating uncertainty in source estimation into health effect estimates, (2) assessing regional and seasonal variability in emissions sources and source-specific health effects, and (3) addressing potential confounding in estimated health effects. Novel methodological approaches to address challenges in studies of pollution sources, particularly evaluation of source-specific health effects, are important for determining how source-specific exposure impacts health.

[Bibliometrics and visualization analysis of land use regression models in ambient air pollution research]

Objective: To quantitatively analyze the current status and development trends regarding the land use regression (LUR) models on ambient air pollution studies. Methods: Relevant literature from the PubMed database before June 30, 2017 was analyzed, using the Bibliographic Items Co-occurrence Matrix Builder (BICOMB 2.0). Keywords co-occurrence networks, cluster mapping and timeline mapping were generated, using the CiteSpace 5.1.R5 software. Relevant literature identified in three Chinese databases was also reviewed. Results: Four hundred sixty four relevant papers were retrieved from the PubMed database. The number of papers published showed an annual increase, in line with the growing trend of the index. Most papers were published in the journal of Environmental Health Perspectives. Results from the Co-word cluster analysis identified five clusters: cluster#0 consisted of birth cohort studies related to the health effects of prenatal exposure to air pollution; cluster#1 referred to land use regression modeling and exposure assessment; cluster#2 was related to the epidemiology on traffic exposure; cluster#3 dealt with the exposure to ultrafine particles and related health effects; cluster#4 described the exposure to black carbon and related health effects. Data from Timeline mapping indicated that cluster#0 and#1 were the main research areas while cluster#3 and#4 were the up-coming hot areas of research. Ninety four relevant papers were retrieved from the Chinese databases with most of them related to studies on modeling. Conclusion: In order to better assess the health-related risks of ambient air pollution, and to best inform preventative public health intervention policies, application of LUR models to environmental epidemiology studies in China should be encouraged.

EMD-regression for modelling multi-scale relationships, and application to weather-related cardiovascular mortality

In a number of environmental studies, relationships between nat4ural processes are often assessed through regression analyses, using time series data. Such data are often multi-scale and non-stationary, leading to a poor accuracy of the resulting regression models and therefore to results with moderate reliability. To deal with this issue, the present paper introduces the EMD-regression methodology consisting in applying the empirical mode decomposition (EMD) algorithm on data series and then using the resulting components in regression models. The proposed methodology presents a number of advantages. First, it accounts of the issues of non-stationarity associated to the data series. Second, this approach acts as a scan for the relationship between a response variable and the predictors at different time scales, providing new insights about this relationship. To illustrate the proposed methodology it is applied to study the relationship between weather and cardiovascular mortality in Montreal, Canada. The results shed new knowledge concerning the studied relationship. For instance, they show that the humidity can cause excess mortality at the monthly time scale, which is a scale not visible in classical models. A comparison is also conducted with state of the art methods which are the generalized additive models and distributed lag models, both widely used in weather-related health studies. The comparison shows that EMD-regression achieves better prediction performances and provides more details than classical models concerning the relationship.

The association between daily concentrations of air pollution and visits to a psychiatric emergency unit: a case-crossover study

BACKGROUND

Air pollution is one of the leading causes of mortality and morbidity worldwide. Experimental studies, and a few epidemiological studies, suggest that air pollution may cause acute exacerbation of psychiatric disorders, and even increase the rate of suicide attempts, but epidemiological studies on air pollution in association with psychiatric disorders are still few. Our aim was to investigate associations between daily fluctuations in air pollution concentrations and the daily number of visits to a psychiatric emergency unit.

METHODS

Data from Sahlgrenska University Hospital, Gothenburg, Sweden, on the daily number of visits to the Psychiatric emergency unit were combined with daily data on monitored concentrations of respirable particulate matter(PM₁₀), ozone(O₃), nitrogen dioxides(NO₂) and temperature between 1st July 2012 and 31st December 2016. We used a case-crossover design to analyze data with conditional Poisson regression models allowing for over-dispersion. We stratified data on season.

RESULTS

Visits increased with increasing PM₁₀ levels during the warmer season (April to September) in both single-pollutant and two-pollutant models. For example, an increase of 3.6% (95% Confidence Interval, CI, 0.4-7.0%) was observed with a 10 μg/m3 increase in PM₁₀ adjusted for NO₂. In the three-pollutant models (adjusting for NO₂ and O₃ simultaneously) the increase was 3.3% (95% CI, -0.2-6.9). There were no clear associations between the outcome and NO₂, O₃, or PM₁₀ during the colder season (October to March).

CONCLUSIONS

Ambient air particle concentrations were associated with the number of visits to the Psychiatric emergency unit in the warm season. The results were only borderline statistically significant in the fully adjusted (three-pollutant) models in this small study. The observation could be interpreted as indicative of air pollution as either exacerbating an underlying psychiatric disorder, or increasing mental distress, even in areas with comparatively low levels of air pollution. In combination with the severe impact of psychiatric disorders and mental distress on society and individuals, our results are a strong warrant for future research in this area.

Heavy metal exposure and nasal Staphylococcus aureus colonization: analysis of the National Health and Nutrition Examination Survey (NHANES)

BACKGROUND

Heavy metals including lead and cadmium can disrupt the immune system and the human microbiota. and are increasingly of concern with respect to the propogation of antibiotic-resistence. Infection by methicillin-resistant Staphylococcus aureus (MRSA) is a major cause of global morbidity and mortality. Heavy metal exposure may be associated with increased MRSA colonization and infection, and a decrease in methicillin-susceptible Staphylococcus aureus (MSSA) through co-selection mechanisms and natural selection of antibiotic resistance in the presence of heavy metals. This study examines the association between blood lead (Pb) and cadmium (Cd) level, and MRSA and MSSA nasal colonization.

METHODS

All data used for this analysis came from the 2001-2004 National Health and Nutrition Examination Survey (NHANES). The analytical sample consisted of 18,626 participants aged 1 year and older. Multivariate logistic regression, including adjustment for demographic and dietary factors, was used to analyze the association between blood Pb and Cd, and nasal colonization by MRSA and MSSA.

RESULTS

Prevalence of MRSA and MSSA carriage were 1.2%, and 29.3% respectively. MRSA was highest in women, individuals age 70 and older, who self-identified as black, had only a high school diploma, lived below 200% of the Federal Poverty Level, and had a history of smoking. While not significantly different from those colonized with MSSA, geometric mean blood Pb (1.74 μg/dL) and blood Cd (0.31 μg/L) were highest in those colonized with MRSA. Associations with MRSA colonization appeared to increase in a dose-dependent manner with increasing quartile of blood Pb level. Blood Cd level in the fourth quartile was also significantly associated with lower odds of MRSA colonization. Both metals were associated with lower odds of MSSA colonization.

CONCLUSIONS

Both MRSA and MSSA results suggest that general population levels of blood Pb but not Cd are associated with differences in nasal carriage of S. aureus. While further research is needed, reduction in heavy metal exposures such as lead, concurrently with maintaining a healthy microbiota may be two modifiable options to consider in the fight against antibiotic-resistance.

Source apportionment of fine particulate matter and risk of term low birth weight in California: Exploring modification by region and maternal characteristics

Previous studies have demonstrated associations between fine particulate matter (PM_2.5) and risk of term low birth weight (TLBW; birth weight<2500g and gestational weeks≥37weeks). However, it remains unclear which PM_2.5 sources mainly contribute to these associations, and which subgroups (e.g. by residential region and maternal characteristics) may be more susceptible to these exposures. Using California birth records and PM_2.5 data from eight monitoring sites from 2002 to 2009, we examined the relationship between exposures to total PM_2.5 and PM_2.5 sources and risk of TLBW. Source apportionment was performed for each site using Positive Matrix Factorization, and five PM_2.5 sources (i.e., secondary ammonium sulfate, secondary ammonium nitrate, vehicular emissions, biomass burning, and resuspended soil) were included in our analysis. Mean gestational and trimester exposures were calculated for mothers with ZIP codes located within a 20km radius of monitors (N=1,050,330). Logistic regression was conducted and adjusted for maternal age, race/ethnicity, and education, as well as gestational age, year of birth, apparent temperature exposure during gestation, and neighborhood level percentage of households below poverty level. Increased risks of TLBW associated with each interquartile range increase in exposure were 4.9% (95% confidence interval: 2.6, 7.3) for total PM_2.5, 7.7% (4.7, 10.7) for secondary ammonium sulfate, 5.6% (3.5, 7.7) for resuspended soil, and 3.1% (1.3, 4.9) for secondary ammonium nitrate. Differences in associations were found between inland and coastal regions, and between northern and southern regions for several sources. Results also showed effect measure modification by maternal race/ethnicity and education, with the lowest risk of TLBW associated with PM_2.5 exposures found in mothers with at least a college education and Asian mothers. Some PM_2.5 sources may be more harmful than others, and a better understanding of the relative toxicity of PM_2.5 from each source could lead to more targeted and cost-effective regulations to protect public health.

Income Inequality and Mortality Owing to Breast Cancer: Evidence From Brazil

BACKGROUND

The relationship between breast cancer and inequality income is unclear. This study analyzed the correlation between income inequality and mortality standardized by age and proportional mortality owing to breast cancer among Brazilian women.

PATIENTS AND METHODS

This is an ecological study using data of the federative units and Federal District of Brazil in 2010. The age-standardized mortality owing to breast cancer was estimated using data from the Department of Informatics of Brazil's Unified Health System. Income inequality indicators used included the Gini index, Theil-L index, Palma index, and the ratio of income distribution quintiles obtained from the United Nations Development Program. We used Pearson correlation and linear regression adjusted for income per capita and other variables.

RESULTS

An increase of 0.1 in the Gini index was associated with increases of 9.8 deaths per 100,000 women (95% confidence interval [CI], 1.7-17.9); an increase in the Palma index was associated with increases in mortality of 0.7 deaths per 100,000 women (95% CI, 0.1-1.4), an increase in the Theil-L index was associated with increases in mortality of 4.9 deaths per 100,000 women (95% CI, 1.9-7.9), and of 0.8 (95% CI, 0.2-1.5) in the proportional mortality.

CONCLUSION

Income inequality, as assessed by the Gini, Palma, and Theil-L indexes, is positively associated with an increase in breast cancer mortality in Brazil.

Manganese in teeth and neurobehavior: Sex-specific windows of susceptibility

BACKGROUND

Manganese (Mn) is an essential element required for growth and development, but higher body burdens have been associated with neurobehavioral decrements in children.

OBJECTIVES

We examined whether prenatal or postnatal Mn measured in deciduous teeth was associated with scores on a test of visuospatial learning and memory.

METHODS

Deciduous teeth were collected from 142 participants (ages 10-14years) residing near varied ferro‑manganese industry in Italy. Mn concentrations were measured in prenatal and postnatal tooth regions by laser ablation inductively coupled plasma mass spectrometry (ICP-MS). The Virtual Radial Arm Maze (VRAM), an animal-human analogue task, was used to assess visuospatial learning and memory. We used generalized additive, linear and zero-inflated Poisson mixed regression models to estimate associations between prenatal or postnatal Mn concentrations and repeated measures of all four VRAM outcomes: time, distance, working and reference memory errors. Effect measure modification by sex was examined in stratified models.

RESULTS

U-shaped associations between prenatal Mn and VRAM outcomes were observed among girls only (p_GAMM=0.001 to 0.02 in stratified models). Compared to the mid-tertile of prenatal Mn, girls in the highest tertile took 7.7s [95% CI: -6.1, 21.5] longer to complete the task, traveled 2.3 maze units [0.1, 4.4] farther, and committed more working and reference memory errors (β for count ratio=1.33 [1.01, 1.83]; 1.10 [0.98, 1.24], respectively). This association was not observed among boys. In contrast, for postnatal Mn, no significant associations were found, and patterns were similar for boys and girls.

CONCLUSIONS

The prenatal period may be a critical window for the impact of environmental Mn on visuospatial ability and executive function, especially for females.

Livestock and poultry density and childhood cancer incidence in nine states in the USA

BACKGROUND

Parental occupational and childhood exposures to farm animals have been positively associated with childhood brain tumors, whereas associations with childhood leukemia are equivocal. The developing immune system may be influenced by allergen, virus, or other exposures from animal sources, which may contribute to childhood cancer incidence.

METHODS

Incident cancers (acute lymphoblastic leukemia [ALL], acute myeloid leukemia [AML], central nervous system [CNS], peripheral nervous system [PNS]) for children aged 0-4 diagnosed between 2003 and 2008 were obtained from nine National Cancer Institute Surveillance, Epidemiology and End Results (SEER) registries and were linked to U.S. Census of Agriculture data from 2002 and 2007 by county of diagnosis. Animal densities (animal units [AU]/km²; one animal unit is 1000 pounds of animal weight) were estimated for hogs, cattle, chickens (layers and broilers, separately), equine (horses, ponies, mules, burros, donkeys), goats, sheep, turkeys, and total animals. Animal density was examined in models as both continuous (AU per km²) and categorical variables (quartiles). Animal operation densities (per km²) by size of operation (cattle, hogs, chickens, sheep) were modeled continuously. Rate ratios and 95% confidence intervals were estimated using Poisson regression.

RESULTS

We found positive associations between AML and broiler chicken densities (RR_{per 10AU/km}² = 1.14, 95% CI = 1.02-1.26). ALL rates increased with densities of hog operations (RRper operation/100km² = 1.06, 95% CI = 1.02-1.11). PNS cancer rates were inversely associated with layer chicken density (RR_{per log of AU/km}² = 0.94, 95% CI = 0.89-0.99). No association was found between any cancer type and densities of cattle, equine, or goats.

CONCLUSIONS

Although limited by the ecologic study design, some of our findings are novel and should be examined in epidemiological studies with individual level data.

The relationship between environmental exposures and hormonal abnormalities in pregnant women: An epidemiological study in Yazd, Iran

PROBLEM

The process of industrialization and lifestyle changes have gradually exposed human ‎societies to a larger number of environmental risk factors, which may cause hormonal ‎abnormalities and congenital anomalies.

BACKGROUND

The current study aimed to investigate the relationship ‎between environmental factors and hormonal abnormalities among pregnant women in Yazd, ‎Iran.

METHODS

A hundred participants were randomly selected from among a group of pregnant women. According to the screening tests (AFP, free β-‎HCG, uE3, PAPP-A, and inhibin-A) performed at the genome clinic in Yazd in 2016, the risk of Down Syndrome (DS) was sufficiently high in this group of pregnant women from which the participants were selected. A ‎questionnaire was used to collect data on the degree of the participants' exposure to pesticides ‎at home, use of canned and fast foods, and consumption of greenhouse fruits. The collected data were ‎analyzed by One-way ANOVA and Kruskal-Wallis Test.

FINDINGS

The mean of Multiple of Median (MoM) for inhibin-A was significantly higher among pregnant ‎women who often or always used pesticides at home (p=0.047). The mean MoM ‎for free β-HCG was significantly higher among pregnant women who often or always used canned ‎foods (p=0.024). Finally, the mean MoM for uE3 (1.85±1.30) was significantly higher among ‎pregnant women who never consumed greenhouse fruits (p=0.003).

CONCLUSION

It can be concluded that it is possible to reduce environmental exposures affecting hormonal abnormalities among pregnant women by improving nutritional patterns, minimizing the use of pesticides at home, and reducing the intake of canned foods and greenhouse fruits.

Ageing, exposure to pollution, and interactions between climate change and local seasons as oxidant conditions predicting incident hematologic malignancy at KINSHASA University clinics, Democratic Republic of CONGO (DRC)

Background

The global burden of hematologic malignancy (HM) is rapidly rising with aging, exposure to polluted environments, and global and local climate variability all being well-established conditions of oxidative stress. However, there is currently no information on the extent and predictors of HM at Kinshasa University Clinics (KUC), DR Congo (DRC). This study evaluated the impact of bio-clinical factors, exposure to polluted environments, and interactions between global climate changes (EL Nino and La Nina) and local climate (dry and rainy seasons) on the incidence of HM.

Methods

This hospital-based prospective cohort study was conducted at Kinshasa University Clinics in DR Congo. A total of 105 black African adult patients with anaemia between 2009 and 2016 were included. HM was confirmed by morphological typing according to the French-American-British (FAB) Classification System. Gender, age, exposure to traffic pollution and garages/stations, global climate variability (El Nino and La Nina), and local climate (dry and rainy seasons) were potential independent variables to predict incident HM using Cox regression analysis and Kaplan Meier curves.

Results

Out of the total 105 patients, 63 experienced incident HM, with an incidence rate of 60%. After adjusting for gender, HIV/AIDS, and other bio-clinical factors, the most significant independent predictors of HM were age ≥ 55 years (HR = 2.4; 95% CI 1.4–4.3; P = 0.003), exposure to pollution and garages or stations (HR = 4.9; 95% CI 2–12.1; P < 0.001), combined local dry season + La Nina (HR = 4.6; 95%CI 1.8–11.8; P < 0.001), and combined local dry season + El Nino (HR = 4; 95% CI 1.6–9.7; P = 0.004). HM types included acute myeloid leukaemia (28.6% n = 18), multiple myeloma (22.2% n = 14), myelodysplastic syndromes (15.9% n = 10), chronic myeloid leukaemia (15.9% n = 10), chronic lymphoid leukaemia (9.5% n = 6), and acute lymphoid leukaemia (7.9% n = 5). After adjusting for confounders using Cox regression analysis, age ≥ 55 years, exposure to pollution, combined local dry season + La Nina and combined local dry season + El Nino were the most significant predictors of incident hematologic malignancy.

Conclusion

These findings highlight the importance of aging, pollution, the dry season, El Nino and La Nina as related to global warming as determinants of hematologic malignancies among African patients from Kinshasa, DR Congo. Cancer registries in DRC and other African countries will provide more robust database for future researches on haematological malignancies in the region.

Epidemiology in Germany-general development and personal experience

Did you ever hear about epidemiology in Germany? Starting from an epidemiological desert the discipline has grown remarkably, especially during the last 10-15 years: research institutes have been established, research funding has improved, multiple curriculae in Epidemiology and Public Health are offered. This increase has been quite steep, and now the epidemiological infrastructure is much better. Several medium-sized and even big population cohorts are ongoing, and the number and quality of publications from German epidemiologists has reached a respectable level. My own career in epidemiology started in the field of environmental health. After German reunification I concentrated for many years on environmental problems in East Germany and observed the health benefits after improvement of the situation. Later, I concentrated on population-based cohorts in newborns (GINI/LISA) and adults (KORA, German National Cohort), and on biobanking. This Essay describes the development in Germany after worldwar 2, illustrated by examples of research results and build-up of epidemiological infractructures worth mentioning.

Quantitative bias analysis of a reported association between perfluoroalkyl substances (PFAS) and endometriosis: The influence of oral contraceptive use

An association between serum levels of perfluoroalkyl substances (PFAS) and endometriosis has recently been reported in an epidemiologic study. Oral contraceptive use to treat dysmenorrhea (pelvic pain associated with endometriosis) could potentially influence this association by reducing menstrual fluid loss, a route of excretion for PFAS. In this study, we aimed to evaluate the influence of differential oral contraceptive use on the association between PFAS and endometriosis. We used a published life-stage physiologically based pharmacokinetic (PBPK) model to simulate plasma levels of perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS) from birth to age at study participation (range 18-44years). In the simulated population, PFAS level distributions matched those for controls in the epidemiologic study. Prevalence and geometric mean duration (standard deviation [SD]) of oral contraceptive use in the simulated women were based on data from the National Health and Nutrition Examination Survey; among the women with endometriosis the values were, respectively, 29% and 6.8 (3.1) years; among those without endometriosis these values were 18% and 5.3 (2.8) years. In simulations, menstrual fluid loss (ml/cycle) in women taking oral contraceptives was assumed to be 56% of loss in non-users. We evaluated the association between simulated plasma PFAS concentration and endometriosis in the simulated population using logistic regression. Based on the simulations, the association between PFAS levels and endometriosis attributable to differential contraceptive use had an odds ratio (95% CI) of 1.05 (1.02, 1.07) for a log_e unit increase in PFOA and 1.03 (1.02, 1.05) for PFOS. In comparison, the epidemiologic study reported odds ratios of 1.62 (0.99, 2.66) for PFOA and 1.25 (0.87, 1.80) for PFOS. Our results suggest that the influence of oral contraceptive use on the association between PFAS levels and endometriosis is relatively small.

Household cereal crop harvest and children's nutritional status in rural Burkina Faso

BACKGROUND

Reduction of child undernutrition is one of the Sustainable Development Goals for 2030. Achievement of this goal may be made more difficult in some settings by climate change through adverse impact on agricultural productivity. However, there is only limited quantitative evidence on the link between household crop harvests and child nutrition. We examined this link in a largely subsistence farming population in rural Burkina Faso.

METHODS

Data on the middle-upper arm circumference (MUAC) of 975 children ≤5 years of age, household crop yields, and other parameters were obtained from the Nouna Health and Demographic Surveillance System. Multilevel modelling was used to assess the relationship between MUAC and the household crop harvest in the year 2009 estimated in terms of kilocalories per adult equivalent per day (kcal/ae/d).

RESULTS

Fourteen percent of children had a MUAC <125 mm (a value indicative of acute undernutrition). The relationship between MUAC and annual household food energy production adjusted for age, sex, month of MUAC measurement, household wealth, whether a household member had a non-agricultural occupation, garden produce, village infrastructure and market presence, suggested a decline in MUAC below around 3000 kcal/ae/d. The mean MUAC was 2.49 (95% CI 0.45, 4.52) mm less at 1000 than at 3000 kcal/ae/d.

CONCLUSIONS

Low per capita household crop production is associated with poorer nutritional status of children in a rural farming population in Burkina Faso. This and similar populations may thus be vulnerable to the adverse effects of weather on agricultural harvest, especially in the context of climate change.

For a healthier future: a virtuous cycle for reducing exposure to persistent organic pollutants

In the modern society, people are exposed to various pollutants during their lifetime. Worldwide, the status of children's health has changed in recent decades. Some studies have attempted to identify the causes of these changes and whether they relate to pollutant exposure; however, such attempts have faced major challenges because human life is complex, involving many social and environmental factors. Several long-term cohort studies are being conducted to determine the relationship between diseases and social and environmental factors in children. Even before we establish complete proof of adverse effects, we should attempt to decrease risk to future generations by adopting precautionary principles. Environmental exposure to persistent organic pollutants can be reduced throughout the stages of life—the fetal period, newborn and infant periods, childhood, adolescence and adulthood (preconception) by individuals as well as by society as a whole. Through reducing environmental exposure to pollutants, adverse health effects can also be reduced, which will contribute to healthier future generations. Here, we suggest a virtuous cycle for improving the health of future generations through reduced exposure to persistent pollutants.

Pregnancy outcome and ultraviolet radiation; A systematic review

BACKGROUND

Season and vitamin D are indirect and direct correlates of ultraviolet (UV) radiation and are associated with pregnancy outcomes. Further to producing vitamin D, UV has positive effects on cardiovascular and immune health that may support a role for UV directly benefitting pregnancy.

OBJECTIVES

To investigate the effects of UV exposure on pregnancy; specifically fetal growth, preterm birth and hypertensive complications.

METHODS

We conducted a systematic review of Medline, EMBASE, DoPHER, Global Health, ProQuest Public Health, AustHealth Informit, SCOPUS and Google Scholar to identify 537 citations, 8 of which are included in this review. This review was registered on PROSPERO and a. narrative synthesis is presented following PRISMA guidance.

RESULTS

All studies were observational and assessed at high risk of bias. Higher first trimester UV was associated with and improved fetal growth and increased hypertension in pregnancy. Interpretation is limited by study design and quality. Meta-analysis was precluded by the variety of outcomes and methods.

DISCUSSION

The low number of studies and risk of bias limit the validity of any conclusions. Environmental health methodological issues are discussed with consideration given to design and analytical improvements to further address this reproductive environmental health question.

CONCLUSIONS

The evidence for UV having benefits for pregnancy hypertension and fetal growth is limited by the methodological approaches utilized. Future epidemiological efforts should focus on improving the methods of modeling and linking widely available environmental data to reproductive health outcomes.

The relationship between natural outdoor environments and cognitive functioning and its mediators

BACKGROUND

Urban residents may experience cognitive fatigue and little opportunity for mental restoration due to a lack of access to nature. Natural outdoor environments (NOE) are thought to be beneficial for cognitive functioning, but underlying mechanisms are not clear.

OBJECTIVES

To investigate the long-term association between NOE and cognitive function, and its potential mediators.

METHODS

This cross-sectional study was based on adult participants of the Positive Health Effects of the Natural Outdoor Environment in Typical Populations in Different Regions in Europe (PHENOTYPE) project. Data were collected in Barcelona, Spain; Doetinchem, the Netherlands; and Stoke-on-Trent, United Kingdom. We assessed residential distance to NOE, residential surrounding greenness, perceived amount of neighborhood NOE, and engagement with NOE. Cognitive function was assessed with the Color Trails Test (CTT). Mediation analysis was undertaken following Baron and Kenny.

RESULTS

Each 100m increase in residential distance to NOE was associated with a longer CTT completion time of 1.50% (95% CI 0.13, 2.89). No associations were found for other NOE indicators and cognitive function. Neighborhood social cohesion was (marginally) significantly associated with both residential distance to NOE and CTT completion time, but no evidence for mediation was found. Nor were there indications for mediation by physical activity, social interaction with neighbors, loneliness, mental health, air pollution worries, or noise annoyance.

CONCLUSIONS

Our findings provide some indication that proximity to nature may benefit cognitive function. We could not establish which mechanisms may explain this relationship.

Air pollution and the incidence of ischaemic and haemorrhagic stroke in the South London Stroke Register: a case-cross-over analysis

Background

Few European studies investigating associations between short-term exposure to air pollution and incident stroke have considered stroke subtypes. Using information from the South London Stroke Register for 2005–2012, we investigated associations between daily concentrations of gaseous and particulate air pollutants and incident stroke subtypes in an ethnically diverse area of London, UK.

Methods

Modelled daily pollutant concentrations based on a combination of measurements and dispersion modelling were linked at postcode level to incident stroke events stratified by haemorrhagic and ischaemic subtypes. The data were analysed using a time-stratified case–cross-over approach. Conditional logistic regression models included natural cubic splines for daily mean temperature and daily mean relative humidity, a binary term for public holidays and a sine–cosine annual cycle. Of primary interest were same day mean concentrations of particulate matter <2.5 and <10 µm in diameter (PM_2.5, PM₁₀), ozone (O₃), nitrogen dioxide (NO₂) and NO₂+nitrogen oxide (NO_X).

Results

Our analysis was based on 1758 incident strokes (1311 were ischaemic and 256 were haemorrhagic). We found no evidence of an association between all stroke or ischaemic stroke and same day exposure to PM_2.5, PM₁₀, O₃, NO₂ or NO_X. For haemorrhagic stroke, we found a negative association with PM₁₀ suggestive of a 14.6% (95% CI 0.7% to 26.5%) fall in risk per 10 µg/m³ increase in pollutant.

Conclusions

Using data from the South London Stroke Register, we found no evidence of a positive association between outdoor air pollution and incident stroke or its subtypes. These results, though in contrast to recent meta-analyses, are not inconsistent with the mixed findings of other UK studies.

Ozone and childhood respiratory disease in three US cities: evaluation of effect measure modification by neighborhood socioeconomic status using a Bayesian hierarchical approach

BACKGROUND

Ground-level ozone is a potent airway irritant and a determinant of respiratory morbidity. Susceptibility to the health effects of ambient ozone may be influenced by both intrinsic and extrinsic factors, such as neighborhood socioeconomic status (SES). Questions remain regarding the manner and extent that factors such as SES influence ozone-related health effects, particularly across different study areas.

METHODS

Using a 2-stage modeling approach we evaluated neighborhood SES as a modifier of ozone-related pediatric respiratory morbidity in Atlanta, Dallas, & St. Louis. We acquired multi-year data on emergency department (ED) visits among 5-18 year olds with a primary diagnosis of respiratory disease in each city. Daily concentrations of 8-h maximum ambient ozone were estimated for all ZIP Code Tabulation Areas (ZCTA) in each city by fusing observed concentration data from available network monitors with simulations from an emissions-based chemical transport model. In the first stage, we used conditional logistic regression to estimate ZCTA-specific odds ratios (OR) between ozone and respiratory ED visits, controlling for temporal trends and meteorology. In the second stage, we combined ZCTA-level estimates in a Bayesian hierarchical model to assess overall associations and effect modification by neighborhood SES considering categorical and continuous SES indicators (e.g., ZCTA-specific levels of poverty). We estimated ORs and 95% posterior intervals (PI) for a 25 ppb increase in ozone.

RESULTS

The hierarchical model combined effect estimates from 179 ZCTAs in Atlanta, 205 ZCTAs in Dallas, and 151 ZCTAs in St. Louis. The strongest overall association of ozone and pediatric respiratory disease was in Atlanta (OR = 1.08, 95% PI: 1.06, 1.11), followed by Dallas (OR = 1.04, 95% PI: 1.01, 1.07) and St. Louis (OR = 1.03, 95% PI: 0.99, 1.07). Patterns of association across levels of neighborhood SES in each city suggested stronger ORs in low compared to high SES areas, with some evidence of non-linear effect modification.

CONCLUSIONS

Results suggest that ozone is associated with pediatric respiratory morbidity in multiple US cities; neighborhood SES may modify this association in a non-linear manner. In each city, children living in low SES environments appear to be especially vulnerable given positive ORs and high underlying rates of respiratory morbidity.

Air quality environmental epidemiology studies are unreliable

Ever since the London Great Smog of 1952 is estimated to have killed over 4000 people, scientists have studied the relationship between air quality and acute mortality. There are many hundreds of papers examining the question. There is a serious statistical problem with most of these papers. If there are many questions under consideration, and there is no adjustment for multiple testing or multiple modeling, then unadjusted p-values are totally unreliable making claims unreliable. Our idea is to determine the statistical reliability of eight papers published in Environmental Health Perspectives that were used in meta-analysis papers appearing in Lancet and JAMA. We counted the number of outcomes, air quality predictors, time lags and covariates examined in each paper. We estimate the multiplicity of questions that could be asked and the number of models that could be constructed. The results were that the median numbers of comparisons possible for multiplicity, models and search space were 135, 128, and 9568 respectively. Given the large search spaces, finding a small number of nominally significant results is not unusual at all. The claims in these eight papers are not statistically supported so these papers are unreliable as are the meta-analysis papers that use them.

Measurement Error and Environmental Epidemiology: a Policy Perspective

PURPOSE OF REVIEW

Measurement error threatens public health by producing bias in estimates of the population impact of environmental exposures. Quantitative methods to account for measurement bias can improve public health decision making.

RECENT FINDINGS

We summarize traditional and emerging methods to improve inference under a standard perspective, in which the investigator estimates an exposure-response function, and a policy perspective, in which the investigator directly estimates population impact of a proposed intervention. Under a policy perspective, the analyst must be sensitive to errors in measurement of factors that modify the effect of exposure on outcome, must consider whether policies operate on the true or measured exposures, and may increasingly need to account for potentially dependent measurement error of two or more exposures affected by the same policy or intervention. Incorporating approaches to account for measurement error into such a policy perspective will increase the impact of environmental epidemiology.

Accuracy of two geocoding methods for geographic information system-based exposure assessment in epidemiological studies

BACKGROUND

Environmental exposure assessment based on Geographic Information Systems (GIS) and study participants' residential proximity to environmental exposure sources relies on the positional accuracy of subjects' residences to avoid misclassification bias. Our study compared the positional accuracy of two automatic geocoding methods to a manual reference method.

METHODS

We geocoded 4,247 address records representing the residential history (1990-2008) of 1,685 women from the French national E3N cohort living in the Rhône-Alpes region. We compared two automatic geocoding methods, a free-online geocoding service (method A) and an in-house geocoder (method B), to a reference layer created by manually relocating addresses from method A (method R). For each automatic geocoding method, positional accuracy levels were compared according to the urban/rural status of addresses and time-periods (1990-2000, 2001-2008), using Chi Square tests. Kappa statistics were performed to assess agreement of positional accuracy of both methods A and B with the reference method, overall, by time-periods and by urban/rural status of addresses.

RESULTS

Respectively 81.4% and 84.4% of addresses were geocoded to the exact address (65.1% and 61.4%) or to the street segment (16.3% and 23.0%) with methods A and B. In the reference layer, geocoding accuracy was higher in urban areas compared to rural areas (74.4% vs. 10.5% addresses geocoded to the address or interpolated address level, p < 0.0001); no difference was observed according to the period of residence. Compared to the reference method, median positional errors were 0.0 m (IQR = 0.0-37.2 m) and 26.5 m (8.0-134.8 m), with positional errors <100 m for 82.5% and 71.3% of addresses, for method A and method B respectively. Positional agreement of method A and method B with method R was 'substantial' for both methods, with kappa coefficients of 0.60 and 0.61 for methods A and B, respectively.

CONCLUSION

Our study demonstrates the feasibility of geocoding residential addresses in epidemiological studies not initially recorded for environmental exposure assessment, for both recent addresses and residence locations more than 20 years ago. Accuracy of the two automatic geocoding methods was comparable. The in-house method (B) allowed a better control of the geocoding process and was less time consuming.

Lifetime secondhand smoke exposure and childhood and adolescent asthma: findings from the PIAMA cohort

BACKGROUND

Secondhand smoke (SHS) exposure is a modifiable risk factor associated with childhood asthma. Associations with adolescent asthma and the relevance of the timing and patterns of exposure are unclear. Knowledge of critical windows of exposure is important for targeted interventions.

METHODS

We used data until age 17 from 1454 children of the Dutch population-based PIAMA birth cohort. Residential SHS exposure was assessed through parental questionnaires completed at ages 3 months, 1-8 (yearly), 11, 14, and 17 years. Lifetime exposure was determined as; a) time window-specific exposure (prenatal, infancy, preschool, primary school, and secondary school); b) lifetime cumulative exposure; c) longitudinal exposure patterns using latent class growth modeling (LCGM). Generalized estimation equations and logistic regression were used to analyze associations between exposure and asthma at ages 4 to 17 years, adjusting for potential confounders.

RESULTS

With all three methods, we consistently found no association between SHS exposure and asthma at ages 4 to 17 years e.g. adjusted overall odds ratio (95% confidence interval) 0.67 (0.41-1.12), 1.00 (0.66-1.51) and 0.67 (0.41-1.11) for prenatal maternal active smoking, infancy, and preschool school time window exposures, respectively.

CONCLUSION

We assessed lifetime SHS exposure using different methods. Different timing and patterns of SHS exposure were not associated with an increased risk of asthma in childhood and adolescence in our study. More longitudinal studies could investigate effects of lifetime SHS exposure on asthma in adolescence and later life.

Parallel contagion phenomenon of concordant mental disorders among married couples: a nationwide cohort study

BACKGROUND

The aggregation of mental disorders in couples, as reported by prior research, indicates the effect of familial environments and warrants attention. However, the concordant categories of mental disorders in couples remain unclear. This study investigated spousal concordance for the category of mental disorders among couples throughout Taiwan by using factors associated with such disorders.

METHODS

5643 couples in the 2002-2013 Taiwan National Health Insurance Research Database were analysed and compared with propensity-matched 5643 non-couples. Twelve independent variables, including spouse and shared characteristics, and the category of mental disorders were analysed, mainly by using multinomial logistic regression.

RESULTS

The determined prevalence rates for concordant categories of mental disorder were 0.19% for affective disorders, 6.96% for anxiety disorders, and 3.15% of other mental disorders. Multinomial logistic regression results revealed that two spouses were significantly more likely to be diagnosed with the same category of the aforementioned mental disorders (ORs=2.914, 1.776 and 1.727, respectively). Other associated factors included gender, age, occupation, comorbidity and region. The odds of concordances were significantly higher in couples than in non-couples.

CONCLUSIONS

A category of mental disorder in one spouse is a determinant of that in the other spouse. This study extended the emotional contagion theory to the phenomenon of parallel contagion to reflect the three concordances, suggesting a direction of family-based mental health intervention, particularly prevention for the same category of mental disorders in couples. Policymakers should strengthen the coping strategies of the caring spouse and external support system to psychiatrically vulnerable families.

Air pollution and cardiovascular mortality with over 25years follow-up: A combined analysis of two British cohorts

BACKGROUND

Adverse effects of air pollution on cardiovascular disease (CVD) mortality are well established. There are comparatively fewer studies in Europe, and in the UK particularly, than in North America. We examined associations in two British cohorts with >25years of follow-up.

METHODS

Annual average NO₂, SO₂ and black smoke (BS) air pollution exposure estimates for 1991 were obtained from land use regression models using contemporaneous monitoring data. From the European Study of Cohorts and Air Pollution (ESCAPE), air pollution estimates in 2010-11 were obtained for NO₂, NO_x, PM₁₀, PM_coarse and PM_2.5. The exposure estimates were assigned to place of residence 1989 for participants in a national birth cohort born in 1946, the MRC National Study of Health and Development (NSHD), and an adult multi-ethnic London cohort, Southall and Brent Revisited (SABRE) recruited 1988-91. The combined median follow-up was 26years. Single-pollutant competing risk models were employed, adjusting for individual risk factors.

RESULTS

Elevated non-significant hazard ratios for CVD mortality were seen with 1991 BS and SO₂ and with ESCAPE PM₁₀ and PM_2.5 in fully adjusted linear models. Per 10μg/m³ increase HRs were 1.11 [95% CI: 0.76-1.61] for BS, 1.05 [95% CI: 0.91-1.22] for SO₂, 1.16 [95% CI: 0.70-1.92] for PM₁₀ and 1.30 [95% CI: 0.39-4.34] for PM_2.5, with largest effects seen in the fourth quartile of BS and PM_2.5 compared to the first with HR 1.24 [95% CI: 0.91-1.61] and 1.21 [95% CI: 0.88-1.66] respectively. There were no consistent associations with other ESCAPE pollutants, or with 1991 NO₂. Modelling using Cox regression led to similar results.

CONCLUSION

Our results support a detrimental long-term effect for air pollutants on cardiovascular mortality.

Looking for effects of environmental contaminants in a large birth cohort: Summarizing results of the Norwegian Mother and Child Cohort Study (MoBa)

The Norwegian Mother and Child Cohort Study (MoBa) includes about 113 000 pregnancies, recruited during the years 1999-2008. Using information from questionnaires and biological samples, a major purpose has been to estimate the association between exposures to environmental contaminants and disease occurrence in parents and children. The intention of this article is to describe the available data in MoBa together with a short synopsis of some recent MoBa-publications that relate to exposure assessment and associations between toxicants and health outcomes. The majority of these papers display negative results, in the sense that no strong associations between contaminants and health outcomes have been found, whereas others suggest adverse effects. The positive associations between fetal exposure to contaminants and child growth and development will need replication in other cohorts and further risk assessment. Large prospective pregnancy cohorts remain an important resource for surveillance and detection of effects of environmental hazards on human health.

Shale gas development and cancer incidence in southwest Pennsylvania

OBJECTIVE

To what extent does unconventional gas development lead to an increase in cancer incidence in heavily drilled Southwest Pennsylvania?

STUDY DESIGN

Ecological study.

METHODS

Data for urinary bladder, thyroid and leukaemia were abstracted from the Pennsylvania Cancer Registry (PCR). Cancer incidence among counties with high, moderate and minimal number of producing wells is compared before drilling activity and thereafter. Observed vs expected cases, standardized incidence ratio and 95% confidence intervals are presented. Data are presented by county, diagnosis and sex for the years 2000-2004, 2004-2008 and 2008-2012. The percent difference between the observed cases from 2000 to 2004 and 2008-2012 was calculated.

RESULTS

The observed number of urinary bladder cases was higher than expected in both sexes in counties with shale gas activity. In counties with the fewest number of producing wells, the increase was essentially non-existent. The number of observed cases of thyroid cancer increased substantially among both sexes over the time period in all counties regardless of the number of wells drilled. The pattern for leukaemia was mixed among males and females and among the counties regardless of the extent of shale gas development activities.

CONCLUSION

Potential risk factors other than shale gas development must be taken into account to explain the higher than expected cancer cases in counties with and without shale gas wells before and during unconventional shale gas activity.

Neighbourhood walkability and home neighbourhood-based physical activity: an observational study of adults with type 2 diabetes

Background

Converging international evidence suggests that diabetes incidence is lower among adults living in more walkable neighbourhoods. The association between walkability and physical activity (PA), the presumed mediator of this relationship, has not been carefully examined in adults with type 2 diabetes. We investigated the associations of walkability with total PA occurring within home neighbourhoods and overall PA, irrespective of location.

Methods

Participants (n = 97; 59.5 ± 10.5 years) were recruited through clinics in Montreal (QC, Canada) and wore a GPS-accelerometer device for 7 days. Total PA was expressed as the total Vector of the Dynamic Body Acceleration. PA location was determined using a Global Positioning System (GPS) device (SIRF IV chip). Walkability (street connectivity, land use mix, population density) was assessed using Geographical Information Systems software. The cross-sectional associations between walkability and location-based PA were estimated using robust linear regressions adjusted for age, body mass index, sex, university education, season, car access, residential self-selection, and wear-time.

Results

A one standard deviation (SD) increment in walkability was associated with 10.4 % of a SD increment in neighbourhood-based PA (95 % confidence interval (CI) 1.2, 19.7) – equivalent to 165 more steps/day (95 % 19, 312). Car access emerged as an important predictor of neighbourhood-based PA (Not having car access: 38.6 % of a SD increment in neighbourhood-based PA, 95 % CI 17.9, 59.3). Neither walkability nor car access were conclusively associated with overall PA.

Conclusions

Higher neighbourhood walkability is associated with higher home neighbourhood-based PA but not with higher overall PA. Other factors will need to be leveraged to facilitate meaningful increases in overall PA among adults with type 2 diabetes.

Electronic supplementary material

The online version of this article (doi:10.1186/s12889-016-3603-y) contains supplementary material, which is available to authorized users.

Assessment of neighbourhood-level socioeconomic status as a modifier of air pollution-asthma associations among children in Atlanta

BACKGROUND

A broad literature base provides evidence of association between air pollution and paediatric asthma. Socioeconomic status (SES) may modify these associations; however, previous studies have found inconsistent evidence regarding the role of SES.

METHODS

Effect modification of air pollution-paediatric asthma morbidity by multiple indicators of neighbourhood SES was examined in Atlanta, Georgia. Emergency department (ED) visit data were obtained for 5-18 years old with a diagnosis of asthma in 20-county Atlanta during 2002-2008. Daily ZIP Code Tabulation Area (ZCTA)-level concentrations of ozone, nitrogen dioxide, fine particulate matter and elemental carbon were estimated using ambient monitoring data and emissions-based chemical transport model simulations. Pollutant-asthma associations were estimated using a case-crossover approach, controlling for temporal trends and meteorology. Effect modification by ZCTA-level (neighbourhood) SES was examined via stratification.

RESULTS

We observed stronger air pollution-paediatric asthma associations in 'deprivation areas' (eg, ≥20% of the ZCTA population living in poverty) compared with 'non-deprivation areas'. When stratifying analyses by quartiles of neighbourhood SES, ORs indicated stronger associations in the highest and lowest SES quartiles and weaker associations among the middle quartiles.

CONCLUSIONS

Our results suggest that neighbourhood-level SES is a factor contributing vulnerability to air pollution-related paediatric asthma morbidity in Atlanta. Children living in low SES environments appear to be especially vulnerable given positive ORs and high underlying asthma ED rates. Inconsistent findings of effect modification among previous studies may be partially explained by choice of SES stratification criteria, and the use of multiplicative models combined with differing baseline risk across SES populations.

Peer-reviewed and unbiased research, rather than 'sound science', should be used to evaluate endocrine-disrupting chemicals

Evidence increasingly confirms that synthetic chemicals disrupt the endocrine system and contribute to disease and disability across the lifespan. Despite a United Nations Environment Programme/WHO report affirmed by over 100 countries at the Fourth International Conference on Chemicals Management, 'manufactured doubt' continues to be cast as a cloud over rigorous, peer-reviewed and independently funded scientific data. This study describes the sources of doubt and their social costs, and suggested courses of action by policymakers to prevent disease and disability. The problem is largely based on the available data, which are all too limited. Rigorous testing programmes should not simply focus on oestrogen, androgen and thyroid. Tests should have proper statistical power. 'Good laboratory practice' (GLP) hardly represents a proper or even gold standard for laboratory studies of endocrine disruption. Studies should be evaluated with regard to the contamination of negative controls, responsiveness to positive controls and dissection techniques. Flaws in many GLP studies have been identified, yet regulatory agencies rely on these flawed studies. Peer-reviewed and unbiased research, rather than 'sound science', should be used to evaluate endocrine-disrupting chemicals.

Spatial measurement errors in the field of spatial epidemiology

Background

Spatial epidemiology has been aided by advances in geographic information systems, remote sensing, global positioning systems and the development of new statistical methodologies specifically designed for such data. Given the growing popularity of these studies, we sought to review and analyze the types of spatial measurement errors commonly encountered during spatial epidemiological analysis of spatial data.

Methods

Google Scholar, Medline, and Scopus databases were searched using a broad set of terms for papers indexed by a term indicating location (space or geography or location or position) and measurement error (measurement error or measurement inaccuracy or misclassification or uncertainty): we reviewed all papers appearing before December 20, 2014. These papers and their citations were reviewed to identify the relevance to our review.

Results

We were able to define and classify spatial measurement errors into four groups: (1) pure spatial location measurement errors, including both non-instrumental errors (multiple addresses, geocoding errors, outcome aggregations, and covariate aggregation) and instrumental errors; (2) location-based outcome measurement error (purely outcome measurement errors and missing outcome measurements); (3) location-based covariate measurement errors (address proxies); and (4) Covariate-Outcome spatial misaligned measurement errors. We propose how these four classes of errors can be unified within an integrated theoretical model and possible solutions were discussed.

Conclusion

Spatial measurement errors are ubiquitous threat to the validity of spatial epidemiological studies. We propose a systematic framework for understanding the various mechanisms which generate spatial measurement errors and present practical examples of such errors.

Effects of new urban motorway infrastructure on road traffic accidents in the local area: a retrospective longitudinal study in Scotland

BACKGROUND

The M74 motorway extension, Glasgow, opened in June 2011. One justification for construction was an expectation that it would reduce road traffic accidents (RTAs) on local non-motorway roads. This study evaluated the impact of the extension on the number of RTAs, stratifying by accident severity.

METHODS

Data for the period 1997-2014 were extracted from a UK database of reported RTAs involving a personal injury. RTA severity was defined by the level of injury: minor, severe or fatal. RTAs were assigned to (1) the local area surrounding the motorway extension, (2) a comparator area surrounding an existing motorway or (3) a control area elsewhere in the conurbation. Interrupted time-series regression with autoregressive integrated moving average (ARIMA) errors was used to determine longitudinal between-area differences in change in the number of RTAs, which might indicate an intervention effect.

RESULTS

Glasgow and surrounding local authorities saw a 50.6% reduction in annual RTAs (n: 5901 to 2914) between 1997 and 2014. In the intervention area, the number of recorded RTAs decreased by 50.7% (n: 758 to 374), and that of fatal/severe RTAs by 57.4% (n: 129 to 55), with similar reductions in the comparator/control areas. The interrupted time-series analysis showed no significant between-area differences in temporal trends. The reduction of pedestrian casualties was attenuated in the intervention area relative to Glasgow and surrounding authorities.

CONCLUSIONS

Reduction in RTAs was not associated with the motorway extension. Our findings suggest that in planning future investment, it should not be taken for granted that new road infrastructure alone will reduce RTAs in local areas. Urbanisation is proceeding rapidly worldwide, and evidence of infrastructure changes is lacking; this novel study provides important findings for future developments.

Current Methods and Challenges for Epidemiological Studies of the Associations Between Chemical Constituents of Particulate Matter and Health

Epidemiological studies have been critical for estimating associations between exposure to ambient particulate matter (PM) air pollution and adverse health outcomes. Because total PM mass is a temporally and spatially varying mixture of constituents with different physical and chemical properties, recent epidemiological studies have focused on PM constituents. Most studies have estimated associations between PM constituents and health using the same statistical methods as in studies of PM mass. However, these approaches may not be sufficient to address challenges specific to studies of PM constituents, namely assigning exposure, disentangling health effects, and handling measurement error. We reviewed large, population-based epidemiological studies of PM constituents and health and describe the statistical methods typically applied to address these challenges. Development of statistical methods that simultaneously address multiple challenges, for example, both disentangling health effects and handling measurement error, could improve estimation of associations between PM constituents and adverse health outcomes.

Changing the environment to improve population health: a framework for considering exposure in natural experimental studies

There is renewed optimism regarding the use of natural experimental studies to generate evidence as to the effectiveness of population health interventions. Natural experimental studies capitalise on environmental and policy events that alter exposure to certain social, economic or environmental factors that influence health. Natural experimental studies can be useful for examining the impact of changes to ‘upstream’ determinants, which may not be amenable to controlled experiments. However, while natural experiments provide opportunities to generate evidence, they often present certain conceptual and methodological obstacles. Population health interventions that alter the physical or social environment are usually administered broadly across populations and communities. The breadth of these interventions means that variation in exposure, uptake and impact may be complex. Yet many evaluations of natural experiments focus narrowly on identifying suitable ‘exposed’ and ‘unexposed’ populations for comparison. In this paper, we discuss conceptual and analytical issues relating to defining and measuring exposure to interventions in this context, including how recent advances in technology may enable researchers to better understand the nature of population exposure to changes in the built environment. We argue that when it is unclear whether populations are exposed to an intervention, it may be advantageous to supplement traditional impact assessments with observational approaches that investigate differing levels of exposure. We suggest that an improved understanding of changes in exposure will assist the investigation of the impact of complex natural experiments in population health.