Resolving uncertainty in the spatial relationships between passive benzene exposure and risk of non-Hodgkin lymphoma

Background

Benzene is a known occupational carcinogen associated with increased risk of hematologic cancers, but the relationships between quantity of passive benzene exposure through residential proximity to toxic release sites, duration of exposure, lag time from exposure to cancer development, and lymphoma risk remain unclear.

Methods

We collected release data through the Environmental Protection Agency’s Toxics Release Inventory (TRI) from 1989 to 2003, which included location of benzene release sites, years when release occurred, and amount of release. We also collected data on incident cases of non-Hodgkin lymphoma (NHL) from the Georgia Comprehensive Cancer Registry (GCCR) for the years 1999–2008. We constructed distance-decay surrogate exposure metrics and Poisson and negative binomial regression models of NHL incidence to quantify associations between passive exposure to benzene and NHL risk and examined the impact of amount, duration of exposure, and lag time on cancer development. Akaike’s information criteria (AIC) were used to determine the scaling factors for benzene dispersion and exposure periods that best predicted NHL risk.

Results

Using a range of scaling factors and exposure periods, we found that increased levels of passive benzene exposure were associated with higher risk of NHL. The best fitting model, with a scaling factor of 4 kilometers (km) and exposure period of 1989–1993, showed that higher exposure levels were associated with increased NHL risk (Level 4 (1.1–160 kilograms (kg)) vs. Level 1: risk ratio 1.56 [1.44–1.68], Level 5 (>160 kg) vs. Level 1: 1.60 [1.48–1.74]).

Conclusions

Higher levels of passive benzene exposure are associated with increased NHL risk across various lag periods. Additional epidemiological studies are needed to refine these models and better quantify the expected total passive benzene exposure in areas surrounding release sites.

The association between green space and depressive symptoms in pregnant women: moderating roles of socioeconomic status and physical activity

BACKGROUND

The current study explored the association between green space and depression in a deprived, multiethnic sample of pregnant women, and examined moderating and mediating variables.

METHOD

7547 women recruited to the 'Born in Bradford' cohort completed a questionnaire during pregnancy. A binary measure of depressive symptoms was calculated using a validated survey. Two green space measures were used: quintiles of residential greenness calculated using the normalised difference vegetation index for three neighbourhood sizes (100, 300 and 500 m buffer zones around participant addresses); access to major green spaces estimated as straight line distance between participant address and nearest green space (>0.5 hectares). Logistic regression analyses examined relationships between green space and depressive symptoms, controlling for ethnicity, demographics, socioeconomic status (SES) and health behaviours. Multiplicative interactions explored variations by ethnic group, SES or activity levels. Mediation analysis assessed indirect effects via physical activity.

RESULTS

Pregnant women in the greener quintiles were 18-23% less likely to report depressive symptoms than those in the least green quintile (for within 100 m of green space buffer zone). The green space-depressive symptoms association was significant for women with lower education or who were active. Physical activity partially mediated the association of green space, but explained only a small portion of the direct effect.

CONCLUSIONS

Higher residential greenness was associated with a reduced likelihood of depressive symptoms. Associations may be stronger for more disadvantaged groups and for those who are already physically active. Improving green space is a promising intervention to reduce risk of depression in disadvantaged groups.

Potential selection bias associated with using geocoded birth records for epidemiologic research

PURPOSE

There is an increasing use of geocoded birth registry data in environmental epidemiology research. Ungeocoded records are routinely excluded.

METHODS

We used classification and regression tree analysis and logistic regression to investigate potential selection bias associated with this exclusion among all singleton Florida births in 2009 (n = 210,285).

RESULTS

The rate of unsuccessful geocoding was 11.5% (n = 24,171). This ranged between 0% and 100% across zip codes. Living in a rural zip code was the strongest predictor of being ungeocoded. Other predictors for geocoding status varied with urbanity status. In urban areas, maternal race (adjusted odds ratio [aOR] ranging between 1.08 for Hispanic and 1.18 for black compared to white), maternal age [aOR: 1.16 (1.10-1.23) for ages 20-34 compared to <20], maternal nativity [aOR: 1.20 (1.15-1.25) for non-US versus US born], delivery at a birth center [aOR: 1.72 (1.49-2.00) compared to hospital delivery], multiparity [aOR: 0.91 (0.88-0.94)], maternal smoking [aOR: 0.82 (0.76-0.88)], and having nonprivate insurance [aOR: 1.25 (1.20-1.30) for Medicaid versus private insurance] were significantly associated with being ungeocoded. In rural areas, births delivered at birth center [aOR: 2.91 (1.80-4.73)] or home [aOR: 1.94 (1.28-2.95)] had increased odds compared to hospital births. The characteristics predictive of being ungeocoded were also significantly associated with adverse birth outcomes such as low birth weight and preterm delivery, and the association for maternal age was different when ungeocoded births were included and excluded.

CONCLUSIONS

Geocoding status is not random. Women with certain exposure-outcome characteristics may be more likely to be ungeocoded and excluded, indicating potential selection bias.

Association of diethylhexyl phthalate with obesity-related markers and body mass change from birth to 3 months of age

BACKGROUND

Several studies have suggested potential links of phthalates to obesity in children and adults. Limited evidence, however, has been available for the relations between diethylhexyl phthalate (DEHP) and obesity-related markers or body mass change in early life.

METHODS

128 healthy pregnant women were recruited and, after delivery, their newborns' first urine and umbilical cord blood samples were collected. We measured urinary levels of two DEHP metabolites, mono-(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP) and mono-(2-ethyl-5-oxohexyl) phthalate (MEOHP). We also measured the levels of leptin, total cholesterol and triglyceride (TG) in cord serum, and used them along with weight, length, head circumference and ponderal index (PI, 100 g/cm(3)) at birth, as obesity-related markers, and estimated the relations between DEHP metabolites and obesity-related markers using generalised linear models. For the evaluation of body mass increase by early life DEHP exposure, body mass index (BMI) z-score change during 3 months after birth by DEHP metabolites in the first urine samples of the newborns were evaluated using logistic regression.

RESULTS

DEHP exposure was associated with decrease of PI and increase of TG (PI, β=-0.11, p=0.070 and TG, β=0.14, p=0.027), especially for boys (PI, β=-0.13, p=0.021; and TG, β=0.19, p=0.025). Moreover, DEHP exposure was positively associated with body mass increase during 3 months after birth (change of BMI z-scores, OR=4.35, p=0.025).

CONCLUSIONS

Our findings suggest that DEHP exposure may affect body mass change in early life through changes of obesity-related markers.

Association between greenness, urbanicity, and birth weight

BACKGROUND

More than half of the world's population lives in urban environments. Due to urban related factors (e.g. higher air pollution), urban residents may face higher risk of adverse health outcomes, while access to green space could benefit health.

PURPOSE

We explored associations between urban and green land-use and birth weight.

METHODS

Connecticut, U.S., birth certificate data (2000-2006) were acquired (n=239,811), and land-use data were obtained from the National Land Cover Database. We focused on three land-uses; urban space, urban open space, and green space (i.e. forest, shrub, herbaceous, and cultivated land). We estimated fractions of greenness and urbanicity within 250 m from residence. A linear mixed effects model was conducted for birth weight and a logistic mixed effects model for low birth weight (LBW) and small for gestational age (SGA).

RESULTS

An interquartile range (IQR) increment in the fraction of green space within 250 m of residence was associated with 3.2g (95% Confidence Interval [0.4, 6.0]) higher birth weight. Similarly, an IQR increase in green space was associated with 7.6% [2.6, 12.4] decreased risk of LBW. Exposure to urban space was negatively correlated with green space (Pearson correlation=-0.88), and it showed negative association with birth outcomes. Results were generally robust with different buffer sizes and controlling for fine particles (PM2.5) and traffic.

CONCLUSIONS

We found protective associations by green space on birth outcomes. Increasing green space and/or reducing urban space (e.g. the greening of city environments) may reduce the risk of adverse birth outcomes such as LBW and SGA. Populations living in urban environments will grow in the next half century, and allocation of green space among urban areas may play a critical role for public health in urban planning.

Exposure assessment issues in epidemiology studies of phthalates

PURPOSE

The purpose of this paper is to review exposure assessment issues that need to be addressed in designing and interpreting epidemiology studies of phthalates, a class of chemicals commonly used in consumer and personal care products. Specific issues include population trends in exposure, temporal reliability of a urinary metabolite measurement, and how well a single urine sample may represent longer-term exposure. The focus of this review is on seven specific phthalates: diethyl phthalate (DEP); di-n-butyl phthalate (DBP); diisobutyl phthalate (DiBP); butyl benzyl phthalate (BBzP); di(2-ethylhexyl) phthalate (DEHP); diisononyl phthalate (DiNP); and diisodecyl phthalate (DiDP).

METHODS

Comprehensive literature search using multiple search strategies.

RESULTS

Since 2001, declines in population exposure to DEP, BBzP, DBP, and DEHP have been reported in the United States and Germany, but DEHP exposure has increased in China. Although the half-lives of various phthalate metabolites are relatively short (3 to 18h), the intraclass correlation coefficients (ICCs) for phthalate metabolites, based on spot and first morning urine samples collected over a week to several months, range from weak to moderate, with a tendency toward higher ICCs (greater temporal stability) for metabolites of the shorter-chained (DEP, DBP, DiBP and BBzP, ICCs generally 0.3 to 0.6) compared with those of the longer-chained (DEHP, DiNP, DiDP, ICCs generally 0.1 to 0.3) phthalates. Additional research on optimal approaches to addressing the issue of urine dilution in studies of associations between biomarkers and different type of health effects is needed.

CONCLUSIONS

In conclusion, the measurement of urinary metabolite concentrations in urine could serve as a valuable approach to estimating exposure to phthalates in environmental epidemiology studies. Careful consideration of the strengths and limitations of this approach when interpreting study results is required.

Spatial measurement error and correction by spatial SIMEX in linear regression models when using predicted air pollution exposures

Spatial modeling of air pollution exposures is widespread in air pollution epidemiology research as a way to improve exposure assessment. However, there are key sources of exposure model uncertainty when air pollution is modeled, including estimation error and model misspecification. We examine the use of predicted air pollution levels in linear health effect models under a measurement error framework. For the prediction of air pollution exposures, we consider a universal Kriging framework, which may include land-use regression terms in the mean function and a spatial covariance structure for the residuals. We derive the bias induced by estimation error and by model misspecification in the exposure model, and we find that a misspecified exposure model can induce asymptotic bias in the effect estimate of air pollution on health. We propose a new spatial simulation extrapolation (SIMEX) procedure, and we demonstrate that the procedure has good performance in correcting this asymptotic bias. We illustrate spatial SIMEX in a study of air pollution and birthweight in Massachusetts.

Assessing correlations between geological hazards and health outcomes: Addressing complexity in medical geology

BACKGROUND

The field of medical geology addresses the relationships between exposure to specific geological characteristics and the development of a range of health problems: for example, long-term exposure to arsenic in drinking water can result in the development of skin conditions and cancers. While these relationships are well characterised for some examples, in others there is a lack of understanding of the specific geological component(s) triggering disease onset, necessitating further research.

OBJECTIVES

This paper aims to highlight several important complexities in geological exposures and the development of related diseases that can create difficulties in the linkage of exposure and health outcome data. Several suggested approaches to deal with these complexities are also suggested.

DISCUSSION

Long-term exposure and lengthy latent periods are common characteristics of many diseases related to geological hazards. In combination with long- or short-distance migrations over an individual's life, daily or weekly movement patterns and small-scale spatial heterogeneity in geological characteristics, it becomes problematic to appropriately assign exposure measurements to individuals. The inclusion of supplementary methods, such as questionnaires, movement diaries or Global Positioning System (GPS) trackers can support medical geology studies by providing evidence for the most appropriate exposure measurement locations.

CONCLUSIONS

The complex and lengthy exposure-response pathways involved, small-distance spatial heterogeneity in environmental components and a range of other issues mean that interdisciplinary approaches to medical geology studies are necessary to provide robust evidence.

Metabolome analyses in exposome studies: Profiling methods for a vast chemical space

Metabolic profiling (metabonomics/metabolomics) is now used routinely as a tool to provide information-rich datasets for biomarker discovery, prompting and augmenting detailed mechanistic studies. The experimental design and focus of any individual study will be reflected in the types of biomarkers that can be detected; toxicological studies will likely focus on markers of response to insult, whereas clinical case-control studies may yield diagnostic markers of disease. Population studies can make use of omics analyses, including metabonomics, to provide mechanistically-relevant markers that link environmental exposures to chronic disease endpoints. In this article, examples of how metabolic profiling has played a key role in molecular epidemiological analyses of chronic disease are presented, and how these reflect different aspects of the causal pathway. A commentary on the nature of metabolome analysis as a complex mixture problem as opposed to a coded, sequence or template problem is provided, alongside an overview of current and future analytical platforms that are being applied to meet this analytical challenge. Epidemiological studies are an important nexus for integrating various measures of the human exposome, and the ubiquity, diversity and functions of small molecule metabolites, represent an important way to link individual exposures, genetics and phenotype.

Respiratory and allergic health effects in a young population in proximity of a major industrial park in Oman

BACKGROUND

Sohar industrial zone (SIZ), Oman, which started operating in 2006, contains many industries that potentially affect the health of the local population. This study's aim was to evaluate the health effects in a young population living near SIZ.

METHODS

Patient visits to state health clinics for acute respiratory diseases (ARD), asthma, conjunctivitis and dermatitis were obtained for the period of 2006 to 2010, for children ages <20 years old, for two large provinces around SIZ. Three exposure zones were defined on the basis of the distance from SIZ determined as: ≤5, >5 to 10, ≥20 km to represent high, intermediate and control exposure zones, respectively. Age-specific and gender-specific monthly counts of visits were modelled using generalised additive models controlling for time trends. The high and intermediate exposure zones were later combined together due to the similarity of associations. Exposure effect modification by age, gender and socioeconomic status (SES) was also tested.

RESULTS

Living within 10 km from SIZ showed a greater association with ARD (risk ratio (RR)=2.5; 95% CI=2.3 to 2.7), asthma (RR=3.7; 95% CI=3.1 to 4.5), conjunctivitis (RR=3.1; 95% CI=2.9 to 3.5) and dermatitis (RR=2.7; 95% CI=2.5 to 3.0) when compared with the control zone. No differences in associations were found for gender and SES groups; greater effects were noticed in the ≤14-year-old group for asthma.

CONCLUSIONS

This is the first study conducted in Oman to examine the health effects of a young population living near an industrial park. We hope that these findings will contribute in future developments of environmental health policies in Oman.

Influence of environmental exposure on human epigenetic regulation

Environmental toxicants can alter epigenetic regulatory features such as DNA methylation and microRNA expression. As the sensitivity of epigenomic regulatory features may be greatest during the in utero period, when critical windows are narrow, and when epigenomic profiles are being set, this review will highlight research focused on that period. I will focus on work in human populations, where the impact of environmental toxicants in utero, including cigarette smoke and toxic trace metals such as arsenic, mercury and manganese, on genome-wide, gene-specific DNA methylation has been assessed. In particular, arsenic is highlighted, as this metalloid has been the focus of a number of studies and its detoxification mechanisms are well understood. Importantly, the tissues and cells being examined must be considered in context in order to interpret the findings of these studies. For example, by studying the placenta, it is possible to identify potential epigenetic adaptations of key genes and pathways that may alter the developmental course in line with the developmental origins of health and disease paradigm. Alternatively, studies of newborn cord blood can be used to examine how environmental exposure in utero can impact the composition of cells within the peripheral blood, leading to immunological effects of exposure. The results suggest that in humans, like other vertebrates, there is a susceptibility for epigenomic alteration by the environment during intrauterine development, and this may represent a mechanism of plasticity of the organism in response to its environment as well as a mechanism through which long-term health consequences can be shaped.

A Bayesian model for quantifying the change in mortality associated with future ozone exposures under climate change

Climate change is expected to have many impacts on the environment, including changes in ozone concentrations at the surface level. A key public health concern is the potential increase in ozone-related summertime mortality if surface ozone concentrations rise in response to climate change. Although ozone formation depends partly on summertime weather, which exhibits considerable inter-annual variability, previous health impact studies have not incorporated the variability of ozone into their prediction models. A major source of uncertainty in the health impacts is the variability of the modeled ozone concentrations. We propose a Bayesian model and Monte Carlo estimation method for quantifying health effects of future ozone. An advantage of this approach is that we include the uncertainty in both the health effect association and the modeled ozone concentrations. Using our proposed approach, we quantify the expected change in ozone-related summertime mortality in the contiguous United States between 2000 and 2050 under a changing climate. The mortality estimates show regional patterns in the expected degree of impact. We also illustrate the results when using a common technique in previous work that averages ozone to reduce the size of the data, and contrast these findings with our own. Our analysis yields more realistic inferences, providing clearer interpretation for decision making regarding the impacts of climate change.

The effect of reduced street lighting on road casualties and crime in England and Wales: controlled interrupted time series analysis

Background

Many local authorities in England and Wales have reduced street lighting at night to save money and reduce carbon emissions. There is no evidence to date on whether these reductions impact on public health. We quantified the effect of 4 street lighting adaptation strategies (switch off, part-night lighting, dimming and white light) on casualties and crime in England and Wales.

Methods

Observational study based on analysis of geographically coded police data on road traffic collisions and crime in 62 local authorities. Conditional Poisson models were used to analyse longitudinal changes in the counts of night-time collisions occurring on affected roads during 2000–2013, and crime within census Middle Super Output Areas during 2010–2013. Effect estimates were adjusted for regional temporal trends in casualties and crime.

Results

There was no evidence that any street lighting adaptation strategy was associated with a change in collisions at night. There was significant statistical heterogeneity in the effects on crime estimated at police force level. Overall, there was no evidence for an association between the aggregate count of crime and switch off (RR 0.11; 95% CI 0.01 to 2.75) or part-night lighting (RR 0.96; 95% CI 0.86 to 1.06). There was weak evidence for a reduction in the aggregate count of crime and dimming (RR 0.84; 95% CI 0.70 to 1.02) and white light (RR 0.89; 95% CI 0.77 to 1.03).

Conclusions

This study found little evidence of harmful effects of switch off, part-night lighting, dimming, or changes to white light/LEDs on road collisions or crime in England and Wales.

Sex-dependent and body weight-dependent associations between environmental PAHs exposure and insulin resistance: Korean urban elderly panel

BACKGROUND

The prevalence of metabolic diseases rises rapidly with an ageing population. Recent studies suggest the potential involvement of environmental chemicals in insulin resistance (IR) that plays a core role in the development of metabolic diseases. Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous components of outdoor and indoor air pollution. The influence of PAHs on IR may differ depending on sex and weight.

OBJECTIVES

We examined the association between exposure to environmental PAHs and IR in Korean urban elderly adults controlling for major risk factors that contribute to an increase in IR.

METHODS

Between 2008 and 2010, PAH metabolite levels (urinary 1-hydroxypyrene (1-OHP)) and the homoeostatic model assessment index (HOMA-IR) were repeatedly measured in 502 adults aged ≥60 years. Linear mixed effect models were fit to evaluate the associations of 1-OHP concentration with HOMA-IR. Subgroups were modelled by sex and weight.

RESULTS

After adjusting for sociodemographics, air pollution and metabolic disease status, the highest (vs lowest) quartile of 1-OHP was associated with an 0.57 (95% CI 0.10 to 1.04) increase in the HOMA-IR score (p trend=0.037). When stratified by sex, women presented a significantly dose-dependent trend of 1-OHP with HOMA-IR (p trend=0.013), whereas no association was observed in men (p trend=0.904). When further stratified by weight (body mass index ≥25 vs <25 kg/m(2)), a significant association was found only in overweight women (p trend=0.023).

CONCLUSIONS

Our results suggest that environmental exposure to PAHs is associated with increased IR in elderly adults and that the association may be limited to overweight women.

Application environmental epidemiology to vehicular air pollution and health effects research

Vehicular pollution is one of the major contributors to the air pollution in urban areas and perhaps and accounts for the major share of anthropogenic green-house gases such as carbon dioxide, carbon monoxide, nitrogen oxides. Knowledge of human health risks related to environmental exposure to vehicular pollution is a current concern. Analyze the range health effects are attributed varied constituents of vehicular air pollution examine evidence for a causal association to specific health effect. In many instances scenario involves exposure to very low doses of putative agents for extended periods, sometimes the period could mean over a lifetime of an individual and yet may result in small increase in health risk that may be imperceptible. Secondary data analysis and literature review. In environmental exposures, traditional epidemiological approaches evaluating mortality and morbidity indicators display many limiting factors such as nonspecificity of biological effects latency time between exposure and magnitude of the effect. Long latency period between exposure and resultant disease, principally for carcinogenic effects and limitation of epidemiological studies for detecting small risk increments. The present paper discusses the methodological challenges in studying vehicular epidemiology and highlights issues that affect the validity of epidemiological studies in vehicular pollution.

Elevated prenatal methylmercury exposure in Nigeria: evidence from maternal and cord blood

Methylmercury is a neurodevelopmental toxicant that is globally distributed though little is known about prenatal exposures in sub-Saharan Africa. The objective of the current study was to measure total mercury levels in cord blood and maternal blood from 95 mother-newborn pairs recruited from hospitals in Nnewi, Nigeria. The secondary aims of the study were to explore if demographic and dietary factors were associated with blood mercury levels, and to explore if mercury levels were associated with any self-reported health outcome and childbirth outcome. Maternal blood mercury levels averaged 3.6 μg L(-1) and ranged from 1.1 μg L(-1) to 9.5 μg L(-1). Cord blood mercury averaged 5.1 μg L(-1) and ranged from 1.2 μg L(-1) to 10.6 μg L(-1). The mean ratio of mercury in paired cord blood to maternal blood was 1.5 and it ranged from 0.4 to 3.2. Mercury in maternal and cord blood were significantly correlated (r=0.471). More than one-third of mothers reported eating fish at least once per day, and a weak (p=0.08) fish consumption-related increase in blood mercury was found. Cord blood mercury was positively and significantly associated with birth weight and length, and head and chest circumference. Mercury levels in 36% of the participants exceeded the biomonitoring guideline associated with the United States Environmental Protection Agency (U.S. EPA) reference dose for mercury. The study shows that pregnant women and their newborns are exposed to methylmercury and that their exposures are higher compared to general populations sampled from other regions of the world.

Extreme temperatures and out-of-hospital coronary deaths in six large Chinese cities

BACKGROUND

The seasonal trend of out-of-hospital coronary death (OHCD) and sudden cardiac death has been observed, but whether extreme temperature serves as a risk factor is rarely investigated. We therefore aimed to evaluate the impact of extreme temperatures on OHCDs in China. We obtained death records of 126,925 OHCDs from six large Chinese cities (Harbin, Beijing, Tianjin, Nanjing, Shanghai and Guangzhou) during the period 2009-2011.

METHODS

The short-term associations between extreme temperature and OHCDs were analysed with time-series methods in each city, using generalised additive Poisson regression models. We specified distributed lag non-linear models in studying the delayed effects of extreme temperature. We then applied Bayesian hierarchical models to combine the city-specific effect estimates.

RESULTS

The associations between extreme temperature and OHCDs were almost U-shaped or J-shaped. The pooled relative risks (RRs) of extreme cold temperatures over the lags 0-14 days comparing the 1st and 25th centile temperatures were 1.49 (95% posterior interval (PI) 1.26-1.76); the pooled RRs of extreme hot temperatures comparing the 99th and 75th centile temperatures were 1.53 (95% PI 1.27-1.84) for OHCDs. The RRs of extreme temperature on OHCD were higher if the patients with coronary heart disease were old, male and less educated.

CONCLUSIONS

This multicity epidemiological study suggested that both extreme cold and hot temperatures posed significant risks on OHCDs, and might have important public health implications for the prevention of OHCD or sudden cardiac death.

A proposal for assessing study quality: Biomonitoring, Environmental Epidemiology, and Short-lived Chemicals (BEES-C) instrument

The quality of exposure assessment is a major determinant of the overall quality of any environmental epidemiology study. The use of biomonitoring as a tool for assessing exposure to ubiquitous chemicals with short physiologic half-lives began relatively recently. These chemicals present several challenges, including their presence in analytical laboratories and sampling equipment, difficulty in establishing temporal order in cross-sectional studies, short- and long-term variability in exposures and biomarker concentrations, and a paucity of information on the number of measurements required for proper exposure classification. To date, the scientific community has not developed a set of systematic guidelines for designing, implementing and interpreting studies of short-lived chemicals that use biomonitoring as the exposure metric or for evaluating the quality of this type of research for WOE assessments or for peer review of grants or publications. We describe key issues that affect epidemiology studies using biomonitoring data on short-lived chemicals and propose a systematic instrument--the Biomonitoring, Environmental Epidemiology, and Short-lived Chemicals (BEES-C) instrument--for evaluating the quality of research proposals and studies that incorporate biomonitoring data on short-lived chemicals. Quality criteria for three areas considered fundamental to the evaluation of epidemiology studies that include biological measurements of short-lived chemicals are described: 1) biomarker selection and measurement, 2) study design and execution, and 3) general epidemiological study design considerations. We recognize that the development of an evaluative tool such as BEES-C is neither simple nor non-controversial. We hope and anticipate that the instrument will initiate further discussion/debate on this topic.

Polycyclic aromatic hydrocarbons in residential dust and risk of childhood acute lymphoblastic leukemia

Several polycyclic aromatic hydrocarbons (PAHs) are known or probable human carcinogens. We evaluated the relationship between PAH exposure and risk of childhood acute lymphoblastic leukemia (ALL) using concentrations in residential dust as an exposure indicator. We conducted a population-based case-control study (251 ALL cases, 306 birth-certificate controls) in Northern and Central California from 2001 to 2007. We collected residential dust using a high volume small surface sampler (HVS3) (n=185 cases, 212 controls) or by sampling from participants' household vacuum cleaners (n=66 cases, 94 controls). We evaluated log-transformed concentrations of 9 individual PAHs, the summed PAHs, and the summed PAHs weighted by their carcinogenic potency (the toxic equivalence). We calculated odds ratios (ORs) and 95% confidence intervals (CI) using logistic regression adjusting for demographic characteristics and duration between diagnosis/reference date and dust collection. Among participants with HVS3 dust, risk of ALL was not associated with increasing concentration of any PAHs based on OR perln(ng/g). Among participants with vacuum dust, we observed positive associations between ALL risk and increasing concentrations of benzo[a]pyrene (OR perln[ng/g]=1.42, 95% CI=0.95, 2.12), dibenzo[a,h]anthracene (OR=1.98, 95% CI=1.11, 3.55), benzo[k]fluoranthene (OR=1.71, 95% CI=0.91, 3.22), indeno[1,2,3-cd]pyrene (OR=1.81, 95% CI=1.04, 3.16), and the toxic equivalence (OR=2.35, 95% CI=1.18, 4.69). The increased ALL risk among participants with vacuum dust suggests that PAH exposure may increase the risk of childhood ALL; however, reasons for the different results based on HVS3 dust samples deserve further study.

Influences of the neighbourhood food environment on adiposity of low-income preschool-aged children in Los Angeles County: a longitudinal study

BACKGROUND

Few studies have examined the association between the food environment and adiposity in early childhood, a critical time for obesity prevention. The objective of this study was to examine the longitudinal association between neighbourhood food environment and adiposity among low-income preschool-aged children in a major metropolitan region in the USA.

METHODS

The study sample was 32 172 low-income preschool-aged children in Los Angeles County who had repeated weight and height measurements collected between ages 2 and 5 years through a federal nutrition assistance programme. We conducted multilevel longitudinal analyses to examine how spatial densities of healthy and unhealthy retail food outlets in the children's neighbourhoods were related to adiposity, as measured by weight-for-height z-score (WHZ), while controlling for neighbourhood-level income and education, family income, maternal education, and child's gender and race/ethnicity.

RESULTS

Density of healthy food outlets was associated with mean WHZ at age 3 in a non-linear fashion, with mean WHZ being lowest for those exposed to approximately 0.7 healthy food outlets per square mile and higher for lesser and greater densities. Density of unhealthy food outlets was not associated with child WHZ.

CONCLUSIONS

We found a non-linear relationship between WHZ and density of healthy food outlets. Research aiming to understand the sociobehavioural mechanisms by which the retail food environment influences early childhood obesity development is complex and must consider contextual settings.

Placing epidemiological results in the context of multiplicity and typical correlations of exposures

Epidemiological studies evaluate multiple exposures, but the extent of multiplicity often remains non-transparent when results are reported. There is extensive debate in the literature on whether multiplicity should be adjusted for in the design, analysis, and reporting of most epidemiological studies, and, if so, how this should be done. The challenges become more acute in an era where the number of exposures that can be studied (the exposome) can be very large. Here, we argue that it can be very insightful to visualize and describe the extent of multiplicity by reporting the number of effective exposures for each category of exposures being assessed, and to describe the distribution of correlation between exposures and/or between exposures and outcomes in epidemiological datasets. The results of new proposed associations can be placed in the context of this background information. An association can be assigned to a percentile of magnitude of effect based on the distribution of effects seen in the field. We offer an example of how such information can be routinely presented in an epidemiological study/dataset using data on 530 exposure and demographic variables classified in 32 categories in the National Health and Nutrition Examination Survey (NHANES). Effects that survive multiplicity considerations and that are large may be prioritized for further scrutiny.

A comparison between self-reported and GIS-based proxies of residential exposure to environmental pollution in a case-control study on lung cancer

In epidemiological studies both questionnaire results and GIS modeling have been used to assess exposure to environmental risk factors. Nevertheless, few studies have used both these techniques to evaluate the degree of agreement between different exposure assessment methodologies. As part of a case-control study on lung cancer, we present a comparison between self-reported and GIS-derived proxies of residential exposure to environmental pollution. 649 subjects were asked to fill out a questionnaire and give information about residential history and perceived exposure. Using GIS, for each residence we evaluated land use patterns, proximity to major roads and exposure to industrial pollution. We then compared the GIS exposure-index values among groups created on the basis of questionnaire responses. Our results showed a relatively high agreement between the two methods. Although none of these methods is the "exposure gold standard", understanding similarities, weaknesses and strengths of each method is essential to strengthen epidemiological evidence.

Maternal exposure to hurricane destruction and fetal mortality

BACKGROUND

The majority of research documenting the public health impacts of natural disasters focuses on the well-being of adults and their living children. Negative effects may also occur in the unborn, exposed to disaster stressors when critical organ systems are developing and when the consequences of exposure are large.

METHODS

We exploit spatial and temporal variation in hurricane behaviour as a quasi-experimental design to assess whether fetal death is dose-responsive in the extent of hurricane damage. Data on births and fetal deaths are merged with Parish-level housing wreckage data. Fetal outcomes are regressed on housing wreckage adjusting for the maternal, fetal, placental and other risk factors. The average causal effect of maternal exposure to hurricane destruction is captured by difference-in-differences analyses.

RESULTS

The adjusted odds of fetal death are 1.40 (1.07-1.83) and 2.37 (1.684-3.327) times higher in parishes suffering 10-50% and >50% wreckage to housing stock, respectively. For every 1% increase in the destruction of housing stock, we observe a 1.7% (1.1-2.4%) increase in fetal death. Of the 410 officially recorded fetal deaths in these parishes, between 117 and 205 may be attributable to hurricane destruction and postdisaster disorder. The estimated fetal death toll is 17.4-30.6% of the human death toll.

CONCLUSIONS

The destruction caused by Hurricanes Katrina and Rita imposed significant measurable losses in terms of fetal death. Postdisaster migratory dynamics suggest that the reported effects of maternal exposure to hurricane destruction on fetal death may be conservative.

The association between green space and mental health varies across the lifecourse. A longitudinal study

BACKGROUND

Epidemiological studies on green space and health have relied almost exclusively on cross-sectional designs, restricting understanding on how this relationship could vary across the lifecourse.

METHODS

We used multilevel linear regression to analyse variation in minor psychiatric morbidity over nine annual waves of the British Household Panel Survey (1996-2004). The sample was restricted to residents of urban areas who remained within their neighbourhoods for at least 12 months. The 12-item General Health Questionnaire and confounders were reported for 29 626 male and 35 781 female observations (person-years). This individual-level dataset was linked to a measure of green space availability within each ward of residence. Regression models included age, gender, employment status, household tenure, marital status, education, smoking status and household income.

RESULTS

When not considering age, green space was associated with better mental health among men, but not women. Interaction terms fitted between age and green space revealed variation in the association between green space and mental health across the lifecourse and by gender. For men, the benefit of more green space emerged in early to mid-adulthood. Among older women, a curvilinear association materialised wherein those with a moderate availability of green space had better mental health.

CONCLUSIONS

These findings illustrate how the relationship between urban green space and health can vary across the lifecourse, and they highlight the need for longitudinal studies to answer why green space may be better for health at some points in the lifecourse than others.

Association between arsenic exposure from drinking water and hematuria: results from the Health Effects of Arsenic Longitudinal Study

Arsenic (As) exposure has been associated with both urologic malignancy and renal dysfunction; however, its association with hematuria is unknown. We evaluated the association between drinking water As exposure and hematuria in 7843 men enrolled in the Health Effects of Arsenic Longitudinal Study (HEALS). Cross-sectional analysis of baseline data was conducted with As exposure assessed in both well water and urinary As measurements, while hematuria was measured using urine dipstick. Prospective analyses with Cox proportional regression models were based on urinary As and dipstick measurements obtained biannually since baseline up to six years. At baseline, urinary As was significantly related to prevalence of hematuria (P-trend<0.01), with increasing quintiles of exposure corresponding with respective prevalence odds ratios of 1.00 (reference), 1.29 (95% CI: 1.04-1.59), 1.41 (95% CI: 1.15-1.74), 1.46 (95% CI: 1.19-1.79), and 1.56 (95% CI: 1.27-1.91). Compared to those with relatively little absolute urinary As change during follow-up (-10.40 to 41.17 μg/l), hazard ratios for hematuria were 0.99 (95% CI: 0.80-1.22) and 0.80 (95% CI: 0.65-0.99) for those whose urinary As decreased by >47.49 μg/l and 10.87 to 47.49 μg/l since last visit, respectively, and 1.17 (95% CI: 0.94-1.45) and 1.36 (95% CI: 1.10-1.66) for those with between-visit increases of 10.40 to 41.17 μg/l and >41.17 μg/l, respectively. These data indicate a positive association of As exposure with both prevalence and incidence of dipstick hematuria. This exposure effect appears modifiable by relatively short-term changes in drinking water As.

Estimating acute air pollution health effects from cohort study data

Traditional studies of short-term air pollution health effects use time series data, while cohort studies generally focus on long-term effects. There is increasing interest in exploiting individual level cohort data to assess short-term health effects in order to understand the mechanisms and time scales of action. We extend semiparametric regression methods used to adjust for unmeasured confounding in time series studies to the cohort setting. Time series methods are not directly applicable since cohort data are typically collected over a prespecified time period and include exposure measurements on days without health observations. Therefore, long-time asymptotics are not appropriate, and it is possible to improve efficiency by exploiting the additional exposure data. We show that flexibility of the semiparametric adjustment model should match the complexity of the trend in the health outcome, in contrast to the time series setting where it suffices to match temporal structure in the exposure. We also demonstrate that pre-adjusting exposures concurrent with the health endpoints using trends in the complete exposure time series results in unbiased health effect estimation and can improve efficiency without additional confounding adjustment. A recently published article found evidence of an association between short-term exposure to ambient fine particulate matter (PM2.5 ) and retinal arteriolar diameter as measured by retinal photography in the Multi-Ethnic Study of Atherosclerosis (MESA). We reanalyze the data from this article in order to compare the methods described here, and we evaluate our methods in a simulation study based on the MESA data.

Clinical perspective on oxidative stress in sporadic amyotrophic lateral sclerosis

Sporadic amyotrophic lateral sclerosis (ALS) is one of the most devastating neurological diseases; most patients die within 3 to 4 years after symptom onset. Oxidative stress is a disturbance in the pro-oxidative/antioxidative balance favoring the pro-oxidative state. Autopsy and laboratory studies in ALS indicate that oxidative stress plays a major role in motor neuron degeneration and astrocyte dysfunction. Oxidative stress biomarkers in cerebrospinal fluid, plasma, and urine are elevated, suggesting that abnormal oxidative stress is generated outside of the central nervous system. Our review indicates that agricultural chemicals, heavy metals, military service, professional sports, excessive physical exertion, chronic head trauma, and certain foods might be modestly associated with ALS risk, with a stronger association between risk and smoking. At the cellular level, these factors are all involved in generating oxidative stress. Experimental studies indicate that a combination of insults that induce modest oxidative stress can exert additive deleterious effects on motor neurons, suggesting that multiple exposures in real-world environments are important. As the disease progresses, nutritional deficiency, cachexia, psychological stress, and impending respiratory failure may further increase oxidative stress. Moreover, accumulating evidence suggests that ALS is possibly a systemic disease. Laboratory, pathologic, and epidemiologic evidence clearly supports the hypothesis that oxidative stress is central in the pathogenic process, particularly in genetically susceptive individuals. If we are to improve ALS treatment, well-designed biochemical and genetic epidemiological studies, combined with a multidisciplinary research approach, are needed and will provide knowledge crucial to our understanding of ALS etiology, pathophysiology, and prognosis.

Association of inorganic arsenic exposure with type 2 diabetes mellitus: a meta-analysis

BACKGROUND

The association of long-term effects of inorganic arsenic (iAs) exposure with type 2 diabetes mellitus (T2DM) risk remains controversial.

METHODS

A literature search was performed in PubMed, China National Knowledge Infrastructure and Web of Knowledge for relevant available articles published in English or Chinese from 1 January 1990 to 5 June 2013. Case-control, cohort or cross-sectional studies evaluating iAs and T2DM were included. The DerSimonian and Laird random effect model was adopted as the pooling method. Dose-response relationship was assessed by restricted cubic spline model and multivariate random-effect meta-regression.

RESULTS

Of the 569 articles identified through searching databases, 17 published articles with 2,243,745 participants for iAs in drinking water and 21 083 participants for total arsenic (tAs) in urine were included for this meta-analysis. The pooled relative risk with 95% CI of T2DM for the highest versus lowest category of iAs exposure level in drinking water was 1.75 (1.20 to 2.54). After removing three studies that had a strong effect on heterogeneity, the pooled relative risk was 1.23 (1.12 to 1.36). Dose-response analysis suggested T2DM risk increased by 13% (1.13 (1.00 to 1.27)) for every 100 µg/L increment of iAs in drinking water. Significant association of T2DM risk with tAs in urine was also found 1.28 (1.14 to 1.44).

CONCLUSIONS

This meta-analysis indicates that long-term iAs exposure might be positively associated with T2DM risk.

Spatial variation of disinfection by-product concentrations: exposure assessment implications

The use of public water system (PWS) average trihalomethane (THM) and haloacetic acid (HAA) concentrations as surrogates of "personal" exposures in epidemiological studies of disinfection by-products (DBPs) may result in exposure misclassification bias from various sources of measurement error including intra-system variation of DBPs. Using 2000-2004 data from 107 PWSs in Massachusetts, we assessed two approaches for characterizing DBP spatial variability by identifying PWSs with low spatial variability (LSV) and examining differences in LSV across DBP groups and by type of source water and primary disinfectant. We also used spatial differences to examine the association between THM concentrations and indices of social disadvantage; however, we found no correlations or statistically significant differences based on the available data. We observed similar patterns for the percentage of quarterly sampling dates with LSV across different types of source water for all DBPs but not across disinfectants. We found there was little overlap between sites classified as having LSV across different DBP groups. In the main analysis, we found moderate correlations between both approaches (φ(THM4) = 0.55; φ(BrTHM) = 0.64; φ(HAA5) = 0.67); although Method 1 (based on concentration differences between samples) may be better suited for identifying PWSs for inclusion in epidemiological studies because it is more easily adapted to study-specific exposure gradients than Method 2 (based on categorical exposure percentiles). These data reinforce the need to consider different exposure assessment approaches when examining the spatial variation of multiple DBP surrogates as they can represent different DBP mixtures.

Socioeconomic status and exposure to outdoor NO2 and benzene in the Asturias INMA birth cohort, Spain

Background

It is commonly assumed that low socioeconomic levels are associated with greater exposure to pollution, but this is not necessarily valid. Our goal was to examine how individual socioeconomic characteristics are associated with exposure levels in a Spanish region included in the INfancia y Medio Ambiente (INMA) cohort.

Methods

The study population comprised 430 pregnant women from the Asturias INMA cohort. Air pollution exposure was estimated using land-use regression techniques. Information about the participants’ lifestyle and socioeconomic variables was collected through questionnaires. In multivariate analysis, the levels of NO₂ and benzene assigned to each woman were considered as dependent variables. Other variables included in the models were residential zone, age, education, parity, smoking, season, working status during pregnancy and social class.

Results

The average NO₂ level was 23.60 (SD=6.50) μg/m³. For benzene, the mean value was 2.31 (SD=1.32) μg/m³. We found no association of any pollutant with education. We observed an association between social class and benzene levels. Social classes I and II had the highest levels. The analysed socioeconomic and lifestyle variables accounted for little variability in air pollution in the models; this variability was explained mainly by residential zone (adjusted R²: 0.27 for NO₂; 0.09 for benzene).

Conclusions

Education and social class were not clearly associated with pollution. Administrations should monitor the environment of residential areas regardless of the socioeconomic level, and they should increase the distances between housing and polluting sources to prevent settlements at distances that are harmful to health.

Modelling the effects of low indoor temperatures on the lung function of children with asthma

INTRODUCTION

While many epidemiological studies have shown that low outdoor temperatures are associated with increased rates of hospitalisation and mortality (especially for respiratory or cardiovascular disease), very few studies have looked at the association between indoor temperatures and health. Such studies are clearly warranted, as people have greater exposure to the indoor environment than the outdoor environment.

OBJECTIVES

To examine the relationship between various metrics of indoor temperature and lung function in children with asthma. Our specific research questions were: (1) In which room of the home is temperature most strongly associated with lung function? (2) Which exposure metric best describes the relationship between indoor temperature and lung function? (3) Over what lag/time period does indoor air temperature affect lung function most strongly?

METHODS

The Heating Housing and Health Study was a randomised controlled trial that investigated the effect of installing heaters in the homes of children with asthma. This study collected measurements of lung function (daily) and indoor temperature (hourly). Lung function and indoor temperature were measured for 309 children over 12 049 child-days. Statistical models were fitted to identify the best measures and metrics.

RESULTS

The strongest association with lung function was found for the severity of exposure to low bedroom temperatures averaged over the preceding periods of 0-7 to 0-12 days. A 1°C increase in temperature was associated with an average increase of 0.010, 0.008, 10.06, 12.06, in our four measures of lung function (peak expiratory flow rate (PEFR) morning, PEFR evening, forced expiratory volume in 1 s (FEV1) morning and FEV1 evening).

CONCLUSIONS

Indoor temperatures have a small, but significant, association with short-term variations in the lung function of children with asthma.

An Approach to the Estimation of Chronic Air Pollution Effects Using Spatio-Temporal Information

There is substantial observational evidence that long-term exposure to particulate air pollution is associated with premature death in urban populations. Estimates of the magnitude of these effects derive largely from cross-sectional comparisons of adjusted mortality rates among cities with varying pollution levels. Such estimates are potentially confounded by other differences among the populations correlated with air pollution, for example, socioeconomic factors. An alternative approach is to study covariation of particulate matter and mortality across time within a city, as has been done in investigations of short-term exposures. In either event, observational studies like these are subject to confounding by unmeasured variables. Therefore the ability to detect such confounding and to derive estimates less affected by confounding are a high priority. In this article, we describe and apply a method of decomposing the exposure variable into components with variation at distinct temporal, spatial, and time by space scales, here focusing on the components involving time. Starting from a proportional hazard model, we derive a Poisson regression model and estimate two regression coefficients: the "global" coefficient that measures the association between national trends in pollution and mortality; and the "local" coefficient, derived from space by time variation, that measures the association between location-specific trends in pollution and mortality adjusted by the national trends. Absent unmeasured confounders and given valid model assumptions, the scale-specific coefficients should be similar; substantial differences in these coefficients constitute a basis for questioning the model. We derive a backfitting algorithm to fit our model to very large spatio-temporal datasets. We apply our methods to the Medicare Cohort Air Pollution Study (MCAPS), which includes individual-level information on time of death and age on a population of 18.2 million for the period 2000-2006. Results based on the global coefficient indicate a large increase in the national life expectancy for reductions in the yearly national average of PM2.5. However, this coefficient based on national trends in PM2.5 and mortality is likely to be confounded by other variables trending on the national level. Confounding of the local coefficient by unmeasured factors is less likely, although it cannot be ruled out. Based on the local coefficient alone, we are not able to demonstrate any change in life expectancy for a reduction in PM2.5. We use additional survey data available for a subset of the data to investigate sensitivity of results to the inclusion of additional covariates, but both coefficients remain largely unchanged.