Violence-related post-traumatic stress disorder (PTSD) remains a prevalent and disabling psychiatric disorder in urban areas. However, the most effective allocation of resources into prevention and treatment to reduce this problem is unknown. We contrasted the impact of two interventions on violence-related PTSD: (1) a population-level intervention intended to prevent violence (i.e., hot-spot policing), and (2) an individual-level intervention intended to shorten PTSD duration (i.e., cognitive-behavioral therapy—CBT).
We used agent-based modeling to simulate violence and PTSD in New York City under four scenarios: (1) no intervention, (2) targeted policing to hot spots of violence, (3) increased access to CBT for people who suffered from violence-related PTSD, and (4) a combination of the two interventions.
Combined prevention and treatment produced the largest decrease in violence-related PTSD prevalence: hot-spot policing plus a 50% increase in CBT for 5 years reduced the annual prevalence of violence-related PTSD from 3.6% (95% confidence interval = 3.5%, 3.6%) to 3.4% (3.3%, 3.5%). It would have been necessary to implement hot-spot policing or to increase CBT by 200% for 10 years for either intervention to achieve the same reduction in isolation.
This study provides an empirically informed demonstration that investment in combined strategies that target social determinants of mental illness and provide evidence-based treatment to those affected by psychiatric disorders can produce larger reductions in the population burden from violence-related PTSD than either preventive or treatment interventions alone. However, neither hot-spot policing nor CBT, alone or combined, will produce large shifts in the population prevalence of violence-related PTSD.
In influenza epidemiology, analysis of paired sera collected from people before and after influenza seasons has been used for decades to study the cumulative incidence of influenza virus infections in populations. However, interpretation becomes challenging when sera are collected after the start or before the end of an epidemic, and do not neatly bracket the epidemic.
Serum samples were collected longitudinally in a community-based study. Most participants provided their first serum after the start of circulation of influenza A(H1N1)pdm09 virus in 2009. We developed a Bayesian hierarchical model to correct for non-bracketing sera and estimate the cumulative incidence of infection from the serological data and surveillance data in Hong Kong.
We analysed 4843 sera from 2097 unvaccinated participants in the study, collected from April 2009 through December 2010. After accounting for non-bracketing, we estimated that the cumulative incidence of H1N1pdm09 virus infection was 45.1% (95% credible interval, CI: 40.2%, 49.2%), 16.5% (95% CI: 13.0%, 19.7%) and 11.3% (95% CI: 5.9%, 17.5%) for children 0–18y, adults 19–50y and older adults >50y respectively. Including all available data substantially increased precision compared to a simpler analysis based only on sera collected at 6-month intervals in a subset of participants.
We developed a framework for the analysis of antibody titers that accounted for the timing of sera collection with respect to influenza activity and permitted robust estimation of the cumulative incidence of infection during an epidemic.
Selection bias is a potential concern in all epidemiologic studies, but it is usually difficult to assess. Recently, concerns have been raised that internet-based prospective cohort studies may be particularly prone to selection bias. Although use of the internet is efficient and facilitates recruitment of subjects that are otherwise difficult to enroll, any compromise in internal validity would be of great concern. Few studies have evaluated selection bias in internet-based prospective cohort studies. Using data from the Danish Medical Birth Registry from 2008 to 2012, we compared six well-known perinatal associations (e.g., smoking and birth weight) in an inter-net-based preconception cohort (Snart Gravid n = 4,801) with the total population of singleton live births in the registry (n = 239,791). We used log-binomial models to estimate risk ratios (RRs) and 95% confidence intervals (CIs) for each association. We found that most results in both populations were very similar. For example, maternal obesity was associated with an increased risk of delivering a macrosomic infant in Snart Gravid (RR = 1.5; 95% CI: 1.2, 1.7) and the total population (RR = 1.5; 95% CI: 1.45, 1.53), and maternal smoking of >10 cigarettes per day was associated with a higher risk of low birth weight (RR = 2.7; 95% CI: 1.2, 5.9 vs. RR = 2.9; 95% CI: 2.6, 3.1) in Snart Gravid and the total population, respectively. We cannot be certain that our results would apply to other associations or different populations. Nevertheless, our results suggest that recruitment of reproductive aged women via the internet may be no more prone to selection bias than traditional methods of recruitment.
Unconventional natural gas development has expanded rapidly. In Pennsylvania the number of producing wells increased from zero in 2005 to 3689 in 2013. To our knowledge, no prior publications have focused on unconventional natural gas development and birth outcomes.
We performed a retrospective cohort study using electronic health record data on 9384 mothers linked to 10946 neonates in the Geisinger Health System from January 2009-January 2013. We estimated cumulative exposure to unconventional natural gas development activity with an inverse-distance squared model that incorporated distance to the mother’s home; dates and durations of well pad development, drilling, and hydraulic fracturing; and production volume during the pregnancy. We used multilevel linear and logistic regression models to examine associations between activity index quartile and term birth weight, preterm birth, low 5 minute Apgar score and small size for gestational age, while controlling for potential confounding variables.
In adjusted models, there was an association between unconventional natural gas development activity and preterm birth that increased across quartiles, with a fourth quartile odds ratio of 1.4 (95% CI: 1.0-1.9). There were no associations of activity with Apgar score, small for gestational age, or term birth weight (after adjustment for year). In a post-hoc analysis, there was an association with physician-recorded high-risk pregnancy identified from the problem list (fourth vs. first quartile, 1.3 [95% CI: 1.1-1.7]).
Prenatal residential exposure to unconventional natural gas development activity was associated with two pregnancy outcomes, adding to evidence that unconventional natural gas development may impact health.
The US Food and Drug Administration mandated that enriched grain products be fortified with folic acid by 1998. We evaluated whether intake of folic acid from supplements and diet was associated with a reduction in spina bifida in the setting of folic acid fortification.
Data were collected as part of the Slone Birth Defects Study from 1998 to 2008. Mothers of infants with and without birth defects were interviewed within 6 months of delivery about pregnancy exposures, including details of diet and vitamin intake. Dietary natural folate and synthetic folic acid from fortification were combined into a single, weighted measure—dietary folate equivalent. Periconceptional folic acid supplementation and dietary folate consumption were compared between 205 mothers of spina bifida cases and 6357 mothers of nonmalformed controls. Relative risks of a spina bifida-affected birth were estimated with odds ratios (ORs) and 95% confidence intervals (CIs).
Spina bifida was not associated with regular folic acid supplementation (≥4 days per week) either around the time of conception (adjusted OR = 1.1 [95% CI = 0.74 –1.7]) or initiated in early pregnancy (0.79 [0.54–1.2]). After adjustment for confounders, a 13% reduced odds of spina bifida was estimated for each 100-µg increase in daily dietary folate equivalent consumed.
In the setting of folic acid fortification of grains, our data suggest that folic acid supplementation does not appear to offer further benefit for reducing risk of spina bifida. Rather, the folate-associated benefit on spina bifida risk was found with increasing amounts of dietary folic acid consumed, regardless of folic acid supplementation level.
Genome-wide association studies have discovered common genetic variants associated with susceptibility for several complex diseases; but they have been unfruitful for many others. Typically analysis is done by “agnostically” considering one single nucleotide polymorphism (SNP) at a time, controlling the overall Type I error rate by correcting for multiple testing. In this short report we use oral clefting as a disease model to develop a range of toy example scenarios: risk might only involve genes, might involve both genes and exposure and might involve genes, exposure and their super-multiplicative interaction. These examples illustrate that important genetic variants can be obscured by using a one-SNP-at-a-time analysis when in fact multiple biological pathways and multiple genes jointly influence etiology. These examples highlight the need for better methods for gene-by-environment and gene-by-gene analyses.
Habitual moderate alcohol consumption is associated with a lower risk of acute myocardial infarction (MI) whereas heavy (binge) drinking is associated with higher cardiovascular risk. However, less is known about the immediate effects of alcohol consumption on the risk of acute MI and whether any association differs by beverage type or usual drinking patterns.
We conducted a case-crossover analysis of 3,869 participants from the Determinants of Myocardial Infarction Onset Study who were interviewed during hospitalization for acute MI in one of 64 medical centers across the United States in 1989–1996. We compared the observed number of times that each participant consumed wine, beer or liquor in the hour preceding MI symptom onset with the expected frequency based on each participant’s control information, defined as the number of times the participant consumed alcohol in the past year.
Among 3869 participants, 2119 (55%) reported alcohol consumption in the past year, including 76 within 1 hour before acute MI onset. The incidence rate of acute MI onset was elevated 1.72-fold (95% confidence interval [CI]=1.37–2.16) within 1 hour after alcohol consumption. The association was stronger for liquor than for beer or wine. The higher rate was not apparent for daily drinkers. For the 24 hours after consumption, there was a 14% lower rate (relative risk=0.86 [95% CI=0.79–0.95]) of MI compared with periods with no alcohol consumption.
Alcohol consumption is associated with an acutely higher risk of MI in the subsequent hour among people who do not typically drink alcohol daily.
Stress has been shown to suppress ovulation in experimental models, but its effect on human reproduction at the population level is unclear.
Healthy women (n=259), aged 18–44 years from Western New York, were followed for two menstrual cycles (2005–2007). Women completed daily perceived stress assessments, a 4-item Perceived Stress Scale (PSS-4) up to four times each cycle, and a 14-item PSS at baseline. Mixed model analyses were used to assess effects of stress on log reproductive hormone concentrations and sporadic anovulation.
High versus low daily stress was associated with lower estradiol (-9.5%; 95% confidence interval (CI)= -15.6% to -3.0%), free estradiol (-10.4% [-16.5% to -3.9%]), and LH (-14.8% = [-21.3% to -7.7%]), and higher FSH (6.2% [2.0% to 10.5%]) after adjusting for age, race, percent body fat, depression score, and time-varying hormones and vigorous exercise. High versus low daily stress was also associated with lower luteal progesterone (-10.4% [-19.7% to -0.10%]) and higher odds of anovulation (adjusted OR = 2.2 [95% CI=1.0 to 4.7]). For each unit increase in daily stress level, women had a 70% higher odds of an anovulatory episode (OR=1.7 [1.1 to 2.4]). Similar but attenuated results were found for the association between the PSS-4 and reproductive hormones, while null findings were found for the baseline PSS.
Daily perceived stress does appear to interfere with menstrual cycle function among women with no known reproductive disorders, warranting further research to explore potential population-level impacts and causal biologic mechanisms.
In nonrandomized studies of comparative effectiveness of medications, the prescriber may be the most important determinant of treatment assignment, yet the majority of analyses ignore the prescriber. Via Monte Carlo simulation, we evaluated the bias of 3 approaches that utilize the prescriber in analysis compared against the default approach that ignores the prescriber. Prescriber preference instrumental variable (IV) analyses were unbiased when IV criteria were met, which required no clustering of unmeasured patient characteristics within prescriber. In all other scenarios, IV analyses were highly biased, and stratification on the prescriber reduced confounding bias at the patient or prescriber levels. Including a prescriber random intercept in the propensity score model reversed the direction of confounding from measured patient factors and resulted in unpredictable changes in bias. Therefore, we recommend caution when using the IV approach, particularly when the instrument is weak. Stratification on the prescriber may be more robust and warrants additional research.
comparative effectiveness; epidemiologic methods; instrumental variable; prescriber; propensity score; random effects; simulation
This study aimed to estimate the magnitude of geographical variation in dementia rates and suggest explanations for this variation. Small-area studies are scarce, and none has adequately investigated the relative contribution of genetic and environmental factors to the distribution of dementia.
We present two complementary small-area hierarchical Bayesian disease mapping studies using the comprehensive Swedish Twin Registry (n=27,680) and the 1932 Scottish Mental Survey cohort (n=37,597). The twin study allowed us to isolate the area in order to examine the effect of unshared environmental factors. The Scottish Mental Survey study allowed us to examine various epochs in the life course – approximately age 11 years and adulthood.
We found a 2-to 3- fold geographical variation in dementia odds in Sweden, after twin random effects – likely to capture genetic and shared environmental variance – were removed. In Scotland we found no variation in dementia odds in childhood but substantial variation, following a broadly similar pattern to Sweden, by adulthood.
There is geographical variation in dementia rates. Most of this variation is likely to result from unshared environmental factors that have their effect in adolescence or later. Further work is required to confirm these findings and identify any potentially modifiable socio-environmental risk factors for dementia responsible for this geographical variation in risk. However, if these factors do exist and could be optimized in the whole population, our results suggest that dementia rates could be halved.
Cosmic radiation and circadian disruption are potential reproductive
hazards for flight attendants.
Flight attendants from 3 US airlines in 3 cities were interviewed for
pregnancy histories and lifestyle, medical, and occupational covariates. We
assessed cosmic radiation and circadian disruption from company records of 2
million individual flights. Using Cox regression models, we compared
respondents (1) by levels of flight exposures and (2) to teachers from the
same cities, to evaluate whether these exposures were associated with
Of 2654 women interviewed (2273 flight attendants and 381 teachers),
958 pregnancies among 764 women met study criteria. A hypothetical pregnant
flight attendant with median firsttrimester exposures flew 130 hours in 53
flight segments, crossed 34 time zones, and flew 15 hours during her
home-base sleep hours (10 pm–8 am), incurring 0.13 mGy absorbed dose
(0.36 mSv effective dose) of cosmic radiation. About 2% of flight attendant
pregnancies were likely exposed to a solar particle event, but doses varied
widely. Analyses suggested that cosmic radiation exposure of 0.1 mGy or more
may be associated with increased risk of miscarriage in weeks 9–13
(odds ratio = 1.7 [95% confidence interval = 0.95–3.2]). Risk of a
first-trimester miscarriage with 15 hours or more of flying during home-base
sleep hours was increased (1.5 [1.1–2.2]), as was risk with high
physical job demands (2.5 [1.5–4.2]). Miscarriage risk was not
increased among flight attendants compared with teachers.
Miscarriage was associated with flight attendant work during sleep
hours and high physical job demands and may be associated with cosmic
Short-term fine particulate matter (PM2.5) exposure has been linked with increased QT interval duration, a marker of ventricular repolarization and a risk factor for cardiac arrhythmia and sudden death, in several studies. Only one previous study evaluated whether long-term PM exposure is related to the QT interval. We aim to evaluate whether sub-chronic and long-term exposure to PM2.5 at home is linked with QT duration in an elderly cohort.
We measured heart-rate corrected QT interval duration among 404 participants from the Greater Boston area between 2003 and 2011. We modeled residential PM2.5 exposures using a hybrid satellite- and land use-based model. We evaluated associations between moving averages of short-term (1–2 day), sub-chronic (3–28 day) and long-term (1 year) pollutant exposures and corrected QT duration using linear mixed models. We also evaluated effect modification by oxidative stress genetic score using separated regression models and interaction terms.
We observed positive associations between sub-chronic and long-term PM2.5 exposure and corrected QT duration, with the strongest results for longer-term exposures. For example, a 1 standard deviation increase in 1-year PM2.5 was associated with a 6.3 ms increase in corrected QT (95% confidence interval: 1.8, 11). We observed somewhat greater effects among subjects with higher (8.5 ms) rather than lower (3.1 ms) oxidative stress allelic profiles (p-interaction=0.25).
PM2.5 was associated with increased corrected QT duration in an elderly cohort. While most previous studies focused on short-term air pollution exposures, our results suggest that longer-term exposures are associated with cardiac repolarization.
Both CD4 count and viral load in HIV infected persons are measured with error. There is no clear guidance on how to deal with this measurement error in the presence of missing data.
We used multiple overimputation, a method recently developed in the political sciences, to account for both measurement error and missing data in CD4 count and viral load measurements from four South African cohorts of a Southern African HIV cohort collaboration. Our knowledge about the measurement error of lnCD4 and log10 viral load is part of an imputation model that imputes both missing and mismeasured data. In an illustrative example we estimate the association of CD4 count and viral load with the hazard of death among patients on highly active antiretroviral therapy by means of a Cox model. Simulation studies evaluate the extent to which multiple overimputation is able to reduce bias in survival analyses.
Multiple overimputation emphasizes more strongly the influence of having a high baseline CD4 counts compared to a complete case analysis and multiple imputation (hazard ratio for >200 cells/mm3 vs. <25 cells/mm3: 0.21 [95%CI: 0.18;0.24] vs. 0.38 [0.29;0.48] and 0.29 [0.25;0.34] respectively). Similar results are obtained when varying assumptions about the measurement error, when using p-splines, and when evaluating time-updated CD4 count in a longitudinal analysis. The estimates of the association with viral load are slightly more attenuated when using multiple imputation instead of multiple overimputation. Our simulation studies suggest that multiple overimputation is able to reduce bias and mean squared error in survival analyses.
Multiple overimputation, which can be used with existing software, offers a convenient approach to account for both missing and mismeasured data in HIV research.
In occupational cohort mortality studies, epidemiologists often compare the observed number of deaths in the cohort to the expected number obtained by multiplying person-time accrued in the study cohort by the mortality rate in an external reference population. Interpretation of the result may be difficult due to non-comparability of the occupational cohort and reference population. We describe an approach to estimate an adjusted standardized mortality ratio (aSMR) to control for bias due to unmeasured differences between the occupational cohort and the reference population. The approach draws on methods developed for the use of negative control outcomes. Conditions necessary for unbiased estimation are described, as well as looser conditions necessary for bias reduction. The approach is illustrated using data on bladder cancer mortality among male Oak Ridge National Laboratory workers. The SMR for bladder cancer was elevated among hourly-paid males (SMR=1.90; 1.27, 2.72) but not among monthly-paid males (SMR=0.96; 0.67, 1.33). After indirect adjustment using the proposed approach, the mortality ratios were similar in magnitude among hourly- and monthly-paid men (aSMR=2.22; 1.52, 3.24; and, aSMR=1.99; 1.43, 2.76, respectively). The proposed adjusted SMR offers a complement to typical standardized mortality ratio analyses.
cohort studies; mortality study; occupational diseases
In a previous study, we provided evidence that a decline in fine particulate matter (PM2.5) air pollution during the period between 2000 and 2007 was associated with increased life expectancy in 545 counties in the United States. In this article, we investigated which chemical constituents of PM2.5 were the main drivers of the observed association.
We estimated associations between temporal changes in seven major components of PM2.5 (ammonium, sulfate, nitrate, elemental carbon matter, organic carbon matter, sodium, and silicon) and temporal changes in life expectancy in 95 counties between 2002 and 2007. We included US counties that had adequate chemical components of PM2.5 mass data across all seasons. We fitted single pollutant and multiple pollutant linear models, controlling for available socioeconomic, demographic, and smoking variables and stratifying by urban and nonurban counties.
In multiple pollutant models, we found that: (1) a reduction in sulfate was associated with an increase in life expectancy; and (2) reductions in ammonium and sodium ion were associated with increases in life expectancy in nonurban counties only.
Our findings suggest that recent reductions in long-term exposure to sulfate, ammonium, and sodium ion between 2002 and 2007 are associated with improved public health.
Military service has been suggested to be associated with an increased risk of amyotrophic lateral sclerosis (ALS), but only one prospective study—of a volunteer cohort—has examined this question.
We prospectively assessed the relation between service in the military and ALS mortality among participants in the National Longitudinal Mortality Study, a population-representative cohort of U.S. men and women surveyed from 1973 through 2002. Participant follow-up was conducted from 1979 through 2002 for ALS mortality. There were 696,743 men and 392,571 women who were 25 years old or more with military service data. In this group, there were 375 male ALS deaths and 96 female ALS deaths. Adjusted hazard ratios (HRs) were calculated using Cox proportional hazards.
Men who served in the military had an increased adjusted ALS death rate [HR: 1.23; 95% confidence interval (CI): 0.98, 1.53] compared with those who did not serve. An increase in ALS mortality was found among those who served during World War II (HR: 1.47; 95% CI: 1.13, 1.91) but not during other time periods. This pattern of results was similar for women, but with larger confidence intervals (HR for military service: 1.26; 95% CI: 0.29, 5.59; HR for service during World War II: 2.03; 95% CI: 0.45, 9.05).
Military personnel have an increased risk of ALS, which may be specific to certain service periods although there was no data on actual deployment. Because of the longer follow-up time for World War II veterans, we cannot rule out that increased risk for those who served during other periods would be seen with further follow-up.
Supplemental Digital Content is available in the text.
We investigated the incidence of ischemic heart disease (IHD) in relation to accumulated exposure to particulate matter (PM) in a cohort of aluminum workers. We adjusted for time varying confounding characteristic of the healthy worker survivor effect, using a recently introduced method for the estimation of causal target parameters.
Applying longitudinal targeted minimum loss-based estimation, we estimated the difference in marginal cumulative risk of IHD in the cohort comparing counterfactual outcomes if always exposed above to always exposed below a PM2.5 exposure cut-off. Analyses were stratified by sub-cohort employed in either smelters or fabrication facilities. We selected two exposure cut-offs a priori, at the median and 10th percentile in each sub-cohort.
In smelters, the estimated IHD risk difference after 15 years of accumulating PM2.5 exposure during follow-up was 2.9% (0.6%, 5.1%) using the 10th percentile cut-off of 0.10 mg/m3. For fabrication workers, the difference was 2.5% (0.8%, 4.1%) at the 10th percentile of 0.06 mg/m3. Using the median exposure cut-off, results were similar in direction but smaller in size. We present marginal incidence curves describing the cumulative risk of IHD over the course of follow-up for each sub-cohort under each intervention regimen.
The accumulation of exposure to PM2.5 appears to result in higher risks of IHD in both aluminum smelter and fabrication workers. This represents the first longitudinal application of targeted minimum loss-based estimation, a method for generating doubly robust semi-parametric efficient substitution estimators of causal parameters, in the fields of occupational and environmental epidemiology.
Supplemental Digital Content is available in the text.
The relationship between arsenic and birth weight is not well understood. The objective was to evaluate the causal relationship between prenatal arsenic exposure and birth weight considering the potential mediation effects of gestational age and maternal weight gain during pregnancy using structural equation models.
A prospectively enrolled cohort of pregnant women was recruited in Bangladesh from 2008 to 2011. Arsenic was measured in personal drinking water at the time of enrollment (gestational age <16 weeks, N = 1,140) and in toenails collected ≤1 month postpartum (N = 624) using inductively coupled plasma mass spectrometry. Structural equation models estimated the direct and indirect effects of arsenic on birth weight with gestational age and maternal weight gain considered as mediating variables.
Every unit increase in natural log water arsenic was indirectly associated with decreased birth weight (β = −19.17 g, 95% confidence interval [CI]: −24.64, −13.69) after adjusting for other risk factors. This association was mediated entirely through gestational age (β = −17.37 g, 95% CI: −22.77, −11.98) and maternal weight gain during pregnancy (β = −1.80 g, 95% CI: −3.72, 0.13). When exposure was modeled using toenail arsenic concentrations, similar results were observed. Every increase in natural log toenail arsenic was indirectly associated with decreased birth weight (β = −15.72 g, 95% CI: −24.52, −6.91) which was mediated through gestational age (β = −13.59 g, 95% CI: −22.10, −5.07) and maternal weight gain during pregnancy (β = −2.13 g, 95% CI: −5.24, 0.96).
Arsenic exposure during pregnancy was associated with lower birth weight. The effect of arsenic on birth weight appears to be mediated mainly through decreasing gestational age and to a lesser extent by lower maternal weight gain during pregnancy.
Studies of weight and mortality sometimes state that the mortality relative risks for obesity from non-smokers are valid estimates of the relative risks for obesity in both smokers and non-smokers. Extending this idea, several influential articles have used relative risks for obesity from non-smokers and attributable fraction methods for unadjusted risks to estimate attributable fractions of deaths in the entire population (smokers and non-smokers combined). However, stratification by smoking is a form of adjustment for confounding. Simplified examples show that the use of relative risks from only one stratum to estimate attributable fractions, without incorporating data on the stratification variable, gives incorrect results for the entire population. Even if the mortality relative risks for obesity from non-smokers are indeed valid in both smokers and non-smokers, these relative risks nonetheless need to be treated as adjusted relative risks for the purpose of calculating attributable fractions for the whole sample.
Children may have differing susceptibility to ambient air pollution concentrations depending on various background characteristics of the children.
Using emergency department (ED) data linked with birth records from Atlanta, Georgia, we identified ED visits for asthma or wheeze among children aged 2–16 years from 1 January 2002 through 30 June 2010 (n=109,758). We stratified by preterm delivery, term low birth weight, maternal race, Medicaid status, maternal education, maternal smoking, delivery method, and history of a bronchiolitis ED visit. Population-weighted daily average concentrations were calculated for 1-hour maximum carbon monoxide and nitrogen dioxide; 8-hour maximum ozone; and 24-hour average particulate matter less than 10 microns in diameter, particulate matter less than 2.5 microns in diameter (PM2.5), and the PM2.5 components sulfate, nitrate, ammonium, elemental carbon, and organic carbon, using measurements from stationary monitors. Poisson time-series models were used to estimate rate ratios for associations between three-day moving average pollutant concentrations and daily ED visit counts and to investigate effect-measure modification by the stratification factors.
Associations between pollutant concentrations and asthma exacerbations were larger among children born preterm and among children born to African American mothers. Stratification by race and preterm status together suggested that both factors affected susceptibility. The largest estimated effect size (for an interquartile-range increase in pollution) was observed for ozone among preterm births to African American mothers: rate ratio=1.138 (95% confidence interval=1.077–1.203). In contrast, the rate ration for the ozone association among full-term births to mothers of other races was 1.025 (0.970–1.083).
Results support the hypothesis that children vary in their susceptibility to ambient air pollutants.
Because ambient air pollution exposure occurs as mixtures, consideration of joint effects of multiple pollutants may advance our understanding of air pollution health effects.
We assessed the joint effect of air pollutants in selected combinations (representative of oxidant gases, secondary, traffic, power plant, and criteria pollutants; constructed using combinations of criteria pollutants and fine particulate matter (PM2.5) components) on pediatric asthma emergency department (ED) visits in Atlanta during 1998–2004. Joint effects were assessed using multi-pollutant Poisson generalized linear models controlling for time trends, meteorology and daily non-asthma upper respiratory ED visit counts. Rate ratios (RR) were calculated for the combined effect of an interquartile-range increment in each pollutant’s concentration.
Increases in all of the selected pollutant combinations were associated with increases in warm-season pediatric asthma ED visits [e.g., joint effect rate ratio=1.13 (95% confidence interval 1.06–1.21) for criteria pollutants (including ozone, carbon monoxide, nitrogen dioxide, sulfur dioxide, and PM2.5)]. Cold-season joint effects from models without non-linear effects were generally weaker than warm-season effects. Joint effect estimates from multi-pollutant models were often smaller than estimates calculated based on single-pollutant model results, due to control for confounding. Compared with models without interactions, joint effect estimates from models including first-order pollutant interactions were largely similar. There was evidence of non-linear cold-season effects.
Our analyses illustrate how consideration of joint effects can add to our understanding of health effects of multi-pollutant exposures, and also illustrate some of the complexities involved in calculating and interpreting joint effects of multiple pollutants.
Several epidemiological cross-sectional studies have found positive associations between serum concentrations of lipids and perfluorooctanoic acid (PFOA, or C8). A longitudinal study should be less susceptible to biases from uncontrolled confounding or reverse causality.
We investigated the association between within-individual changes in serum PFOA and perfluorooctanesulfonic acid (PFOS) and changes in serum lipid levels (low-density lipoprotein [LDL] cholesterol, high-density lipoprotein cholesterol, total cholesterol, and triglycerides) over a 4.4-year period. The study population consisted of 560 adults living in parts of Ohio and West Virginia where public drinking water had been contaminated with PFOA. They had participated in a cross-sectional study in 2005–2006, and were followed up in 2010, by which time exposure to PFOA had been substantially reduced.
Overall serum concentrations of PFOA and PFOS fell by half from initial geometric means of 74.8 and 18.5 ng/mL, respectively, with little corresponding change in LDL cholesterol (mean increase 1.8%, standard deviation 26.6%). However, there was a tendency for people with greater declines in serum PFOA or PFOS to have greater LDL decrease. For a person whose serum PFOA fell by half, the predicted fall in LDL cholesterol was 3.6% (95% confidence interval = 1.5–5.7%). The association with a decline in PFOS was even stronger, with a 5% decrease in LDL (2.5–7.4%).
Our findings from this longitudinal study support previous evidence from cross-sectional studies of positive associations between PFOA and PFOS in serum and LDL cholesterol.
Phenols interact with nuclear receptors implicated in growth and adipogenesis regulation. Only a few studies have explored their effects on growth in humans.
We studied the associations of maternal exposure to phenols during pregnancy with prenatal and postnatal growth of male newborns.
Within a cohort of women recruited during pregnancy, we selected 520 mother–son pairs and quantified 9 phenols in spot urine samples collected during pregnancy. We used ultrasonography during pregnancy, together with birth measurements, to assess fetal growth. We modeled individual postnatal growth trajectories from repeated measures of weight and height in the first 3 years of life.
Triclosan concentration was negatively associated with growth parameters measured at the third ultrasound examination but not earlier in pregnancy. At birth, this phenol tended to be negatively associated with head circumference (−1.2 mm for an interquartile range [IQR] increase in ln-transformed triclosan concentration [95% confidence interval = −2.6 to 0.3]) but not with weight or height. Parabens were positively associated with weight at birth. This positive association remained for 3 years for methylparaben (β = 193 g [−4 to 389]) for an IQR increase in ln-transformed concentrations.
We relied on only 1 spot urine sample to assess exposure; because of the high variability in phenol urinary concentrations reported during pregnancy, using only 1 sample may result in exposure misclassification, in particular for bisphenol A. Our study suggested associations between prenatal exposure to parabens and triclosan and prenatal or early postnatal growth.
Scant research has analyzed the health impact of abolition of Jim Crow (ie, legal racial discrimination overturned by the US 1964 Civil Rights Act).
We used hierarchical age–period–cohort models to analyze US national black and white premature mortality rates (death before 65 years of age) in 1960–2009.
Within a context of declining US black and white premature mortality rates and a persistent 2-fold excess black risk of premature mortality in both the Jim Crow and non-Jim Crow states, analyses including random period, cohort, state, and county effects and fixed county income effects found that, within the black population, the largest Jim Crow-by-period interaction occurred in 1960–1964 (mortality rate ratio [MRR] = 1.15 [95% confidence interval = 1.09–1.22), yielding the largest overall period-specific Jim Crow effect MRR of 1.27, with no such interactions subsequently observed. Furthermore, the most elevated Jim Crow-by-cohort effects occurred for birth cohorts from 1901 through 1945 (MRR range = 1.05–1.11), translating to the largest overall cohort-specific Jim Crow effect MRRs for the 1921–1945 birth cohorts (MRR ~ 1.2), with no such interactions subsequently observed. No such interactions between Jim Crow and either period or cohort occurred among the white population.
Together, the study results offer compelling evidence of the enduring impact of both Jim Crow and its abolition on premature mortality among the US black population, although insufficient to eliminate the persistent 2-fold black excess risk evident in both the Jim Crow and non-Jim Crow states from 1960 to 2009.