Distributed lag models (DLMs) have been widely used in environmental epidemiology to quantify the lagged effects of air pollution on an outcome of interest such as mortality or cardiovascular events. Generally speaking, DLMs can be applied to time-series data where the current measure of an independent variable and its lagged measures collectively affect the current measure of a dependent variable. The corresponding distributed lag (DL) function represents the relationship between the lags and the coefficients of the lagged exposure variables. Common choices include polynomials and splines. On one hand, such a constrained DLM specifies the coefficients as a function of lags and reduces the number of parameters to be estimated; hence, higher efficiency can be achieved. On the other hand, under violation of the assumption about the DL function, effect estimates can be severely biased. In this article, we propose a general framework for shrinking coefficient estimates from an unconstrained DLM, that are unbiased but potentially inefficient, toward the coefficient estimates from a constrained DLM to achieve a bias-variance trade-off. The amount of shrinkage can be determined in various ways, and we explore several such methods: empirical Bayes-type shrinkage, a hierarchical Bayes approach, and generalized ridge regression. We also consider a two-stage shrinkage approach that enforces the effect estimates to approach zero as lags increase. We contrast the various methods via an extensive simulation study and show that the shrinkage methods have better average performance across different scenarios in terms of mean squared error (MSE).We illustrate the methods by using data from the National Morbidity, Mortality, and Air Pollution Study (NMMAPS) to explore the association between PM$_{10}$, O$_3$, and SO$_2$ on three types of disease event counts in Chicago, IL, from 1987 to 2000.

Background

HIV-infected (HIV-pos) male children/youth showed lower bone mineral density at sexual maturity than HIV-uninfected (HIV-neg) females. It is not known whether complications of HIV disease, including abnormal body fat distribution, contribute to lower bone accrual in male HIV-pos adolescents.

Methods

In a cross-sectional study, we evaluated the relationship between body composition (fat and lean mass) and bone mass in HIV-pos and HIV-neg children/youth and determined if it is modified by HIV status and sex. We used generalized estimating equations to simultaneously model the effect of fat/lean mass on multiple bone outcomes, including total body bone mineral density and bone mineral content and spine bone mineral density. We evaluated effect modification by HIV and sex.

Results

The analysis cohort consisted of 143 HIV-neg and 236 HIV-pos, of whom 55% were black non-Hispanic and 53% were male. Ages ranged from 7 to < 25 years. Half of the children/youth were at Tanner stage 1 and 20% at Tanner 5. Fat mass was more strongly positively correlated with bone mass in HIV-neg than HIV-pos children/youth and these relationships were more evident for total body bone than spine outcomes. Within HIV strata, fat mass and bone were more correlated in female than male children/youth. The relationship between lean mass and bone varied by sex, but not by HIV status.

Conclusions

HIV disease diminishes the positive relationship of greater fat mass on bone mass in children/youth. Disruptions in body fat distribution, which are common in HIV disease, may have an impact on bone accretion during pubertal development.

Natural vegetation, or greenness, may benefit maternal health and consequently, fetal growth, by providing opportunities for physical activity and psychological restoration, and decreasing detrimental environmental exposures. We retrieved Massachusetts Birth Registry data from 2001⁻2013 and investigated the association between residential greenness and birthweight in full-term births (≥37 weeks gestation). We calculated average residential greenness during pregnancy using 250 m normalized difference vegetation index (NDVI) from satellites. We estimated associations between greenness and continuous birthweight, term low birthweight (TLBW: <2500 g), and small for gestational age (SGA: <10th percentile of birthweight stratified by sex and gestational age) adjusted for individual and neighborhood covariates and considered nonlinearity and effect modification. Higher greenness exposure was associated with higher birthweight with stronger associations in the lower than higher range of greenness. Greenness was associated with lower odds of TLBW (OR 0.98; 95% CI 0.97, 0.99 per 0.1 increase in NDVI) and SGA (OR 0.98; 95% 0.97, 0.99) and associations varied by population density (TLBW) and socioeconomic status (TLBW, SGA). Our results suggest that greenness is beneficial to fetal growth exhibited by higher birthweight and lower odds of TLBW and SGA. Unlike prior studies, associations with TLBW and SGA appeared stronger among those with higher socioeconomic status.

Rationale

Critical periods for programming early wheeze risk may include pregnancy and infancy. Effects of timing remain poorly understood.

Objectives

Associations among prenatal and postnatal maternal stress and children's wheeze were prospectively examined in 653 families. Effect modification by maternal sensitization was also examined.

Methods

Stress was indexed by a maternal negative life events (NLEs) score (range, 0-9) ascertained during pregnancy and between 1 and 2 years postpartum. Mothers reported child wheeze every 3 months up to age 2 years. Relationships of prenatal and postnatal maternal NLEs with repeated wheeze (≥2 episodes) were examined using logistic regression adjusting for covariates. Penalized splines were implemented to explore possible nonlinear associations. We also examined the interaction between prenatal stress and maternal sensitization indexed by allergen-specific IgE from maternal prenatal serum.

Measurements and main results

Adjusted models considering prenatal or postnatal NLEs alone both showed an exposure-response relationship between higher stress and child wheeze. When considering prenatal and postnatal stress concurrently, only children of mothers with high stress in both periods were significantly more likely to wheeze (adjusted odds ratio, 3.04; 95% confidence interval, 1.67-5.53) than children of mothers reporting low stress in both periods. Associations between high prenatal stress and wheeze were significant in children born to nonsensitized mothers (any IgE <0.35 kU/L) but not in the sensitized group (P for interaction = 0.03).

Conclusions

Although children have heightened sensitivity to maternal stress in utero and in early childhood, those with higher stress in both periods were particularly at risk for wheeze. The prenatal maternal immune milieu modified effects.

PURPOSE: Exposure to nature, particularly vegetation (greenness), may be beneficial for mental health. We investigated whether higher surrounding greenness in early life was associated with subsequent reduced risk of depressive symptoms and whether this association was modified by age, sex, or population density. METHODS: Participants from the Growing Up Today Study were included if they reported on depressive symptoms between 1999 and 2013. Greenness exposure was characterized as the cumulative average normalized difference vegetation index value (1000 m resolution) from 1989 until 2 years before outcome assessment or age 18 based on geocoded addresses. We defined high depressive symptoms as the top 10% of scores on the McKnight Risk Factor Survey or the Center for Epidemiologic Studies of Depression scale, depending on the questionnaire. Data were analyzed using Cox proportional hazards model adjusted for socioeconomic status and other confounders. RESULTS: There was a 6% lower incidence of high depressive symptoms associated with an interquartile range increase in greenness (95% confidence interval, 11%-0%). This relationship was stronger in higher population density areas (>1000 people/mi2, 8% lower incidence, 95% confidence interval 15%-1%). CONCLUSIONS: Living in an area with greater surrounding greenness during childhood may be beneficial for mental health, particularly in more urban areas.

BACKGROUND: Inconsistent results have been found in the literature on associations of greenness, or vegetation quantity, and physical activity. However, few studies have assessed associations between mobility-based greenness and physical activity from mobile health data from smartphone and wearable devices with fine spatial and temporal resolution. METHODS: We assessed mobility-based greenness exposure and wearable accelerometer data from participants in the US-based prospective Nurses Health Study 3 cohort Mobile Health (mHealth) Substudy (2018-2020). We recruited 500 female participants with instructions to wear devices over four 7-day sampling periods equally spaced throughout the year. After restriction criteria there were 337 participants (mean age 36 years) with n = 639,364 unique observations. Normalized Difference Vegetation Index (NDVI) data were derived from 30 m x 30 m Landsat-8 imagery and spatially joined to GPS points recorded every 10 min. Fitbit proprietary algorithms provided physical activity summarized as mean number of steps per minute, which we averaged during the 10-min period following a GPS-based greenness exposure assessment. We utilized Generalized Additive Mixed Models to examine associations (every 10 min) between greenness and physical activity adjusting for neighborhood and individual socioeconomic status, Census region, season, neighborhood walkability, daily mean temperature and precipitation. We assessed effect modification through stratification and interaction models and conducted sensitivity analyses. RESULTS: Mean 10-min step count averaged 7.0 steps (SD 14.9) and greenness (NDVI) averaged 0.3 (SD 0.2). Contrary to our hypotheses, higher greenness exposure was associated non-linearly with lower mean steps per minute after adjusting for confounders. We observed statistically significant effect modification by Census region and season. DISCUSSION: We utilized objective physical activity data at fine temporal and spatial scales to present novel estimates of the association between mobility-based greenness and step count. We found higher levels of greenness were inversely associated with steps per minute.

BACKGROUND: Natural vegetation, or greenness, is thought to improve health through its ability to buffer and reduce harmful environmental exposures as well as relieve stress, promote physical activity, restore attention, and increase social cohesion. In concert, these effects could help mitigate the detrimental effects of air pollution on reproductive aging in women. METHODS: Our analysis included 565 women attending the Massachusetts General Hospital Fertility Center (2004-2014) who had a measured antral follicle count (AFC), a marker of ovarian reserve. We calculated peak residential greenness in the year prior to AFC using 250 m2 normalized difference vegetation index (NDVI) from the Terra and Aqua satellites operated by the United States National Aeronautics and Space Administration. Validated spatiotemporal models estimated daily residential exposure to particulate matter <2.5 μm (PM2.5) for the 3 months prior to AFC. Poisson regression models with robust standard errors were used to estimate the association between peak greenness, average PM2.5 exposure, and AFC adjusted for age, BMI, smoking status, education, year, and season. RESULTS: Women in our study had a mean age of 35.2 years with a standard deviation (SD) of 4.3 years (min: 20 years, max: 45 years). The peak residential NDVI ranged from 0.07 to 0.92 with a SD of 0.18. There was no statistically significant association between peak residential greenness and AFC; however, higher exposure to PM2.5 was associated with lower AFC (-6.2% per 2 μg/m3 [1 SD increase] 95% CI -11.8, -0.3). There was a significant interaction between exposure to PM2.5 and peak greenness on AFC (P-interaction: 0.03). Among women with an average PM2.5 exposure of 7 μg/m3, a SD increase in residential peak greenness was associated with a 5.6% (95% CI -0.4, 12.0) higher AFC. Conversely, among women with a PM2.5 exposure of 12 μg/m3, a SD increase in residential peak greenness was associated with a 5.8% (95% CI -13.1, 2.1) lower AFC. CONCLUSIONS: Residing in an area with high levels of greenness may slow reproductive aging in women only when exposure to PM2.5 is low.

Background

Epidemiologic studies linking ambient air pollution to the onset of acute cardiovascular events often rely on date of hospital admission for exposure assessment.

Methods

We investigated the extent of exposure misclassification resulting from assigning exposure to particulate matter based on (1) date of hospital admission, or (2) time of hospital presentation compared with particulate matter exposure based on time of stroke symptom onset. We performed computer simulations to evaluate the impact of this source of exposure misclassification on estimates of air pollution health effects in the context of a time-stratified case-crossover study.

Results

Among 1101 patients admitted for a confirmed acute ischemic stroke to a Boston area hospital, symptom onset occurred a median of 1 calendar day before hospital admission (range = 0-30 days). The difference between ambient particulate matter exposure based on the calendar day of admission versus time of symptom onset ranged from -47 to 36 microg/m3 (-0.1 +/- 7.1 microg/m3; mean +/- SD). The simulation study indicated that for nonnull associations, exposure assessment based on hospitalization date led to estimates that were biased toward the null by 60%-66%, whereas assessment based on time of hospital presentation yielded estimates that were biased toward the null by 37%-42%.

Conclusions

Epidemiologic studies of air pollution-related risk of acute cardiovascular events that assess exposure based on date of hospitalization likely underestimate the strength of associations. Using data on time of hospital presentation would marginally attenuate, but not eliminate, this important source of bias.

Background

Prenatal exposure to essential and non-essential metals impacts birth and child health, including fetal growth and neurodevelopment. DNA methylation (DNAm) may be involved in pathways linking prenatal metal exposure and health. In the Project Viva cohort, we analyzed the extent to which metals (As, Ba, Cd, Cr, Cs, Cu, Hg, Mg, Mn, Pb, Se, and Zn) measured in maternal erythrocytes were associated with differentially methylated positions (DMPs) and regions (DMRs) in cord blood and tested if associations persisted in blood collected in mid-childhood. We measured metal concentrations in first-trimester maternal erythrocytes, and DNAm in cord blood (N = 361) and mid-childhood blood (N = 333, 6-10 years) with the Illumina HumanMethylation450 BeadChip. For each metal individually, we tested for DMPs using linear models (considered significant at FDR < 0.05), and for DMRs using comb-p (Sidak p < 0.05). Covariates included biologically relevant variables and estimated cell-type composition. We also performed sex-stratified analyses.

Results

Pb was associated with decreased methylation of cg20608990 (CASP8) (FDR = 0.04), and Mn was associated with increased methylation of cg02042823 (A2BP1) in cord blood (FDR = 9.73 × 10^-6). Both associations remained significant but attenuated in blood DNAm collected at mid-childhood (p < 0.01). Two and nine Mn-associated DMPs were identified in male and female infants, respectively (FDR < 0.05), with two and six persisting in mid-childhood (p < 0.05). All metals except Ba and Pb were associated with ≥ 1 DMR among all infants (Sidak p < 0.05). Overlapping DMRs annotated to genes in the human leukocyte antigen (HLA) region were identified for Cr, Cs, Cu, Hg, Mg, and Mn.

Conclusions

Prenatal metal exposure is associated with DNAm, including DMRs annotated to genes involved in neurodevelopment. Future research is needed to determine if DNAm partially explains the relationship between prenatal metal exposures and health outcomes.

Abstract Background Experimental evidence suggests that inhaled particles from vehicle exhaust have systemic effects on inflammation, endothelial activation and oxidative stress. In the present study we assess the relationships of short-term exposures with inflammatory endothelial activation and oxidative stress biomarker levels in a population of trucking industry workers. Methods Blood and urine samples were collected pre and post-shift, at the beginning and end of a workweek from 67 male non-smoking US trucking industry workers. Concurrent measurements of microenvironment concentrations of elemental and organic carbon (EC & OC), and fine particulate matter (PM2.5) combined with time activity patterns allowed for calculation of individual exposures. Associations between daily and first and last-day average levels of exposures and repeated measures of intercellular and vascular cell adhesion molecule-1 (ICAM-1 & VCAM-1), interleukin 6 (IL-6) and C-reactive protein (CRP) blood levels and urinary 8-Hydroxy-2′-Deoxyguanosine (8-OHdG) were assessed using linear mixed effects models for repeated measures. Results There was a statistically significant association between first and last-day average PM2.5 and 8-OHdG (21% increase, 95% CI: 2, 42%) and first and last-day average OC and IL-6 levels (18% increase 95% CI: 1, 37%) per IQR in exposure. There were no significant findings associated with EC or associations suggesting acute cross-shift effects. Conclusion Our findings suggest associations between weekly average exposures of PM2.5 on markers of oxidative stress and OC on IL-6 levels.