Metabolomic data presents challenges for epidemiological meta-analysis: a case study of childhood body mass index from the ECHO consortium.

INTRODUCTION: Meta-analyses across diverse independent studies provide improved confidence in results. However, within the context of metabolomic epidemiology, meta-analysis investigations are complicated by differences in study design, data acquisition, and other factors that may impact reproducibility. OBJECTIVE: The objective of this study was to identify maternal blood metabolites during pregnancy (> 24 gestational weeks) related to offspring body mass index (BMI) at age two years through a meta-analysis framework. METHODS: We used adjusted linear regression summary statistics from three cohorts (total N = 1012 mother-child pairs) participating in the NIH Environmental influences on Child Health Outcomes (ECHO) Program. We applied a random-effects meta-analysis framework to regression results and adjusted by false discovery rate (FDR) using the Benjamini-Hochberg procedure. RESULTS: Only 20 metabolites were detected in all three cohorts, with an additional 127 metabolites detected in two of three cohorts. Of these 147, 6 maternal metabolites were nominally associated (P < 0.05) with offspring BMI z-scores at age 2 years in a meta-analytic framework including at least two studies: arabinose (Coefmeta = 0.40 [95% CI 0.10,0.70], Pmeta = 9.7 × 10-3), guanidinoacetate (Coefmeta = - 0.28 [- 0.54, - 0.02], Pmeta = 0.033), 3-ureidopropionate (Coefmeta = 0.22 [0.017,0.41], Pmeta = 0.033), 1-methylhistidine (Coefmeta = - 0.18 [- 0.33, - 0.04], Pmeta = 0.011), serine (Coefmeta = - 0.18 [- 0.36, - 0.01], Pmeta = 0.034), and lysine (Coefmeta = - 0.16 [- 0.32, - 0.01], Pmeta = 0.044). No associations were robust to multiple testing correction. CONCLUSIONS: Despite including three cohorts with large sample sizes (N > 100), we failed to identify significant metabolite associations after FDR correction. Our investigation demonstrates difficulties in applying epidemiological meta-analysis to clinical metabolomics, emphasizes challenges to reproducibility, and highlights the need for standardized best practices in metabolomic epidemiology.

Using multiple imputation by super learning to assign intent to nonfatal firearm injuries.

The number of nonfatal firearm injuries in the US by intent (e.g., due to assault) is not reliably known: First, although the largest surveillance system for hospital-treated events, the Healthcare Cost and Utilization Project Nationwide Emergency Department Sample (HCUP-NEDS), provides accurate data for the number of nonfatal firearm injuries, injury intent is not coded reliably. Second, the system that reliably codes intent, the CDC's National Electronic Injury Surveillance System - Firearm Injury Surveillance Study (NEISS-FISS), while large enough to produce stable estimates of the distribution of intent, is too small to produce stable estimates of the number of these events. Third, a large proportion of cases in NEISS-FISS, notably in early years of the system, are coded as of "undetermined intent." Trends in the proportion of nonfatal firearm injuries by intent in NEISS-FISS thus depend on whether these cases are treated as a distinct category, or, instead, can be re-classified through imputation. We contrast the distributions of nonfatal firearm injury by intent generated using multiple imputation with those generated using complete-case analyses and analyses that consider "undetermined intent" as a distinct category. We produce estimates of the annual number of firearm injuries by intent in a two-step process. First, we impute intent for cases coded as "undetermined" using Multiple Imputation by Super Learning (MISL). Second, we apply MISL-derived distributions to aggregate count data from HCUP-NEDS. The proportion of non-fatal firearm assaults appears to increase over time when injuries coded as undetermined are included as a category. By contrast, the proportion of assaults remains relatively constant over time in complete-case and multiply imputed analyses. Differences between complete-case and multiple imputation approaches become apparent in subgroup analyses. Trends in the number of nonfatal firearm injuries by intent, 2006-2016, derived in our two-step process, are relatively flat. Multiple imputation strategies recovered intent distribution trends that differed from trends derived using methods that are not designed to account for the multiple complex relationships of missingness present in NEISS - FISS data. When applied to NEISS - FISS, MISL imputation produces plausible distributional estimates of firearm injury by intent.

Reprint of "Using multiple imputation by super learning to assign intent to nonfatal firearm injuries".

The number of nonfatal firearm injuries in the US by intent (e.g., due to assault) is not reliably known: First, although the largest surveillance system for hospital-treated events, the Healthcare Cost and Utilization Project Nationwide Emergency Department Sample (HCUP-NEDS), provides accurate data for the number of nonfatal firearm injuries, injury intent is not coded reliably. Second, the system that reliably codes intent, the CDC's National Electronic Injury Surveillance System - Firearm Injury Surveillance Study (NEISS-FISS), while large enough to produce stable estimates of the distribution of intent, is too small to produce stable estimates of the number of these events. Third, a large proportion of cases in NEISS-FISS, notably in early years of the system, are coded as of "undetermined intent." Trends in the proportion of nonfatal firearm injuries by intent in NEISS-FISS thus depend on whether these cases are treated as a distinct category, or, instead, can be re-classified through imputation. We contrast the distributions of nonfatal firearm injury by intent generated using multiple imputation with those generated using complete-case analyses and analyses that consider "undetermined intent" as a distinct category. We produce estimates of the annual number of firearm injuries by intent in a two-step process. First, we impute intent for cases coded as "undetermined" using Multiple Imputation by Super Learning (MISL). Second, we apply MISL-derived distributions to aggregate count data from HCUP-NEDS. The proportion of non-fatal firearm assaults appears to increase over time when injuries coded as undetermined are included as a category. By contrast, the proportion of assaults remains relatively constant over time in complete-case and multiply imputed analyses. Differences between complete-case and multiple imputation approaches become apparent in subgroup analyses. Trends in the number of nonfatal firearm injuries by intent, 2006-2016, derived in our two-step process, are relatively flat. Multiple imputation strategies recovered intent distribution trends that differed from trends derived using methods that are not designed to account for the multiple complex relationships of missingness present in NEISS - FISS data. When applied to NEISS - FISS, MISL imputation produces plausible distributional estimates of firearm injury by intent.

Long-term nitrogen dioxide exposure and cause-specific mortality in the U.S. Medicare population.

BACKGROUND: Since 1971, the annual National Ambient Air Quality Standard (NAAQS) for nitrogen dioxide (NO2) has remained at 53 ppb, the impact of long-term NO2 exposure on mortality is poorly understood. OBJECTIVES: We examined associations between long-term NO2 exposure (12-month moving average of NO2) below the annual NAAQS and cause-specific mortality among the older adults in the U.S. METHODS: Cox proportional-hazard models were used to estimate Hazard Ratio (HR) for cause-specific mortality associated with long-term NO2 exposures among about 50 million Medicare beneficiaries living within the conterminous U.S. from 2001 to 2008. RESULTS: A 10 ppb increase in NO2 was associated with increased mortality from all-cause (HR: 1.06; 95% CI: 1.05-1.06), cardiovascular (HR: 1.10; 95% CI: 1.10-1.11), respiratory disease (HR: 1.09; 95% CI: 1.08-1.11), and cancer (HR: 1.01; 95% CI: 1.00-1.02) adjusting for age, sex, race, ZIP code as strata ZIP code- and state-level socio-economic status (SES) as covariates, and PM2.5 exposure using a 2-stage approach. NO2 was also associated with elevated mortality from ischemic heart disease, cerebrovascular disease, congestive heart failure, chronic obstructive pulmonary disease, pneumonia, and lung cancer. We found no evidence of a threshold, with positive and significant HRs across the range of NO2 exposures for all causes of death examined. Exposure-response curves were linear for all-cause, supra-linear for cardiovascular-, and sub-linear for respiratory-related mortality. HRs were highest consistently among Black beneficiaries. CONCLUSIONS: Long-term NO2 exposure is associated with elevated risks of death by multiple causes, without evidence of a threshold response. Our findings raise concerns about the sufficiency of the annual NAAQS for NO2.

Preterm birth and PM2.5 in Puerto Rico: evidence from the PROTECT birth cohort.

BACKGROUND: Preterm birth (PTB, birth before 37 weeks of gestation) has been associated with adverse health outcomes across the lifespan. Evidence on the association between PTB and prenatal exposure to air pollutants is inconsistent, and is especially lacking for ethnic/racial minority populations. METHODS: We obtained data on maternal characteristics and behaviors and PTB and other birth outcomes for women participating in the Puerto Rico Testsite for Exploring Contamination Threats (PROTECT) cohort, who lived in municipalities located along the North Coast of Puerto Rico. We assessed pre-natal PM2.5 exposures for each infant based on the nearest US Environmental Protection Agency monitor. We estimated prenatal phthalate exposures as the geometric mean of urinary measurements obtained during pregnancy. We then examined the association between PM2.5 and PTB using modified Poisson regression and assessed modification of the association by phthalate exposure levels and sociodemographic factors such as maternal age and infant gender. RESULTS: Among 1092 singleton births, 9.1% of infants were born preterm and 92.9% of mothers had at least a high school education. Mothers had a mean (standard deviation) age of 26.9 (5.5) years and a median (range) of 2.0 (1.0-8.0) pregnancies. Nearly all women were Hispanic white, black, or mixed race. Median (range) prenatal PM2.5 concentrations were 6.0 (3.1-19.8) µ g/m3. Median (interquartile range) prenatal phthalate levels were 14.9 (8.9-26.0) and 14.5 (8.4-26.0), respectively, for di-n-butyl phthalate (DBP) and di-isobutyl phthalate (DiBP). An interquartile range increase in PM2.5 was associated with a 1.2% (95% CI 0.4, 2.1%) higher risk of PTB. There was little difference in PTB risk in strata of infant sex, mother's age, family income, history of adverse birth outcome, parity, and pre-pregnancy body mass index. Pregnancy urinary phthalate metabolite levels did not modify the PM2.5-PTB association. CONCLUSION: Among ethnic minority women in Puerto Rico, prenatal PM2.5 exposure is associated with a small but significant increase in risk of PTB.

Corrections for measurement error due to delayed onset of illness for case-crossover designs.

Epidemiologic studies of the short-term effects of ambient particulate matter (PM) on the risk of acute cardiovascular or cerebrovascular events often use data from administrative databases in which only the date of hospitalization is known. A common study design for analyzing such data is the case-crossover design, in which exposure at a time when a patient experiences an event is compared to exposure at times when the patient did not experience an event within a case-control paradigm. However, the time of true event onset may precede hospitalization by hours or days, which can yield attenuated effect estimates. In this article, we consider a marginal likelihood estimator, a regression calibration estimator, and a conditional score estimator, as well as parametric bootstrap versions of each, to correct for this bias. All considered approaches require validation data on the distribution of the delay times. We compare the performance of the approaches in realistic scenarios via simulation, and apply the methods to analyze data from a Boston-area study of the association between ambient air pollution and acute stroke onset. Based on both simulation and the case study, we conclude that a two-stage regression calibration estimator with a parametric bootstrap bias correction is an effective method for correcting bias in health effect estimates arising from delayed onset in a case-crossover study.

The impact of long-term PM2.5 exposure on specific causes of death: exposure-response curves and effect modification among 53 million U.S. Medicare beneficiaries.

BACKGROUND: The shape of the exposure-response curve for long-term ambient fine particulate (PM2.5) exposure and cause-specific mortality is poorly understood, especially for rural populations and underrepresented minorities. METHODS: We used hybrid machine learning and Cox proportional hazard models to assess the association of long-term PM2.5 exposures on specific causes of death for 53 million U.S. Medicare beneficiaries (aged ≥65) from 2000 to 2008. Models included strata for age, sex, race, and ZIP code and controlled for neighborhood socio-economic status (SES) in our main analyses, with approximately 4 billion person-months of follow-up, and additionally for warm season average of 1-h daily maximum ozone exposures in a sensitivity analysis. The impact of non-traffic PM2.5 on mortality was examined using two stage models of PM2.5 and nitrogen dioxide (NO2). RESULTS: A 10 µg /m3 increase in 12-month average PM2.5 prior to death was associated with a 5% increase in all-cause mortality, as well as an 8.8, 5.6, and 2.5% increase in all cardiovascular disease (CVD)-, all respiratory-, and all cancer deaths, respectively, in age, gender, race, ZIP code, and SES-adjusted models. PM2.5 exposures, however, were not associated with lung cancer mortality. Results were not sensitive to control for ozone exposures. PM2.5-mortality associations for CVD- and respiratory-related causes were positive and significant for beneficiaries irrespective of their sex, race, age, SES and urbanicity, with no evidence of a lower threshold for response or of lower Risk Ratios (RRs) at low PM2.5 levels. Associations between PM2.5 and CVD and respiratory mortality were linear and were higher for younger, Black and urban beneficiaries, but were largely similar by SES. Risks associated with non-traffic PM2.5 were lower than that for all PM2.5 and were null for respiratory and lung cancer-related deaths. CONCLUSIONS: PM2.5 was associated with mortality from CVD, respiratory, and all cancer, but not lung cancer. PM2.5-associated risks of CVD and respiratory mortality were similar across PM2.5 levels, with no evidence of a threshold. Blacks, urban, and younger beneficiaries were most vulnerable to the long-term impacts of PM2.5 on mortality.

Associations between a safety prequalification survey and worker safety experiences on commercial construction sites.

BACKGROUND: While assessment of subcontractors' safety performance during project bidding processes are common in commercial construction, the validation of organizational surveys used in these processes is largely absent. METHODS: As part of a larger research project called Assessment of Contractor Safety (ACES), we designed and tested through a cross-sectional study, a 63-item organizational survey assessing subcontractors' leading indicators of safety performance. We administered the ACES Survey to 43 subcontractors on 24 construction sites. Concurrently, we captured the safety climate of 1426 workers on these sites through worker surveys, as well as injury rates, for the duration of the project. RESULTS: At the worksite level, higher average ACES scores were associated with higher worker safety climate scores (P < .01) and lower rates of injury involving days away (P < .001). Within subcontracting companies, no associations were observed between ACES and worker safety climate scores and injuries. CONCLUSIONS: These results suggest the overall and collective importance of the construction project and its worksite in mediating worker experiences, perhaps somewhat independent of the individual subcontractor level.

Daily ambient temperature is associated with biomarkers of kidney injury in older Americans.

BACKGROUND: Increases in ambient temperature have recently been associated with increased emergency department visits and hospital admissions for acute renal failure. However, potential biological mechanisms through which short-term ambient temperature affects kidney function are not known. METHODS: We used multiple regression models to evaluate the association between 1- and 3-day average, ambient temperature levels and two biomarkers of kidney injury (neutrophil gelatinase-associated lipocalin (NGAL) and adiponectin), among 3377 individuals over 57 years of age enrolled in the National Social Life, Health, and Aging Project. Ambient temperature was estimated on a 6-km grid covering the conterminous United States using ambient temperature measurements obtained from the National Climatic Data Center (NCDC). NGAL and adiponectin levels were measured from whole blood collected for each participant. All health effect models were adjusted for a number of demographics, socioeconomic, health behavior, medical history variables, with non-linear exposure-response relationships examined using natural cubic splines. RESULTS: The relationship between 1- and 3-day average temperature and both NGAL and adiponectin levels was significant and non-linear, with largely null associations below 10 °C, and positive association for temperatures >10 °C. In fully adjusted, linear multiple regression models restricted to >10 °C, NGAL and adiponectin levels increased by 1.89% (95% CI: 0.77, 3.91) and 2.51% (95% CI: 1.34, 3.69), respectively, for a 1 °C increase in daily average temperature. Additionally, every 1 °C increase in temperature over 10 °C was associated with a 1.83% increased odds of having plasma NGAL levels consistent with acute kidney injury (>150 µg/L). CONCLUSIONS: In a cohort of older men and women in the United States, our study is the first to observe that short-term ambient temperature exposures were significantly associated with biomarkers of kidney injury. These associations suggest that ambient temperature exposures could be an important risk factor for renal pathology.

Testing the associations between leading and lagging indicators in a contractor safety pre-qualification database.

BACKGROUND: Safety prequalification assessing contractors' safety management systems and safety programs lack validation in predicting construction worker injuries. METHODS: Safety assessments of leading indicators from 2198 construction contractors, including Safety Management Systems (SMS), Safety Programs (e.g., falls, hearing protection), and Special Elements (drug testing, return to work) scales as well as the history of citations from the Occupational Safety and Health Administration (OSHA) were compared to contractors' lagging indicators of recordable injury case rates (RC) and rates of injuries involving days away, restricted, or transferred (DART). RESULTS: Increased SMS scores were related to lower injury rates. Each one-point increase in SMS values was associated with 34% reduced odds of a recordable case rate greater than zero (Odds ratio (OR): 0.66, 95% Confidence Interval (CI): (0.57, 0.79)), and a 9% reduced recordable case rate, if one occurs (Risk Ratio (RR): 0.91, 95% CI: (0.88, 0.94)). A one-point increase in SMS was associated with 28% reduced odds of a DART (OR = 0.72, 95%CI (0.56, 0.91)), and 9% reduced DART rate, if one occurs (RR = 0.91, 95%CI (0.87, 0.95)). Safety programs did not show consistent associations with injury outcomes. Having additional Special Elements related to drug and alcohol programs was associated with lower injury rates while the Special Element related to return to work showed no consistent associations with injury. Having more OSHA Citations was associated with lower injury rates for companies with injuries. CONCLUSIONS: These results support pre-qualification methods based on SMS and suggest the need for safety management systems in contractors.

Use of predicted vital status to improve survival analysis of multidrug-resistant tuberculosis cohorts.

BACKGROUND: Multidrug-resistant tuberculosis (MDR-TB) cohorts often lack long-term survival data, and are summarized instead by initial treatment outcomes. When using Cox proportional hazards models to analyze these cohorts, this leads to censoring subjects at the time of the initial treatment outcome, instead of them providing full survival data. This may violate the non-informative censoring assumption of the model and may produce biased effect estimates. To address this problem, we develop a tool to predict vital status at the end of a cohort period using the initial treatment outcome and assess its ability to reduce bias in treatment effect estimates. METHODS: We derive and apply a logistic regression model to predict vital status at the end of the cohort period and modify the unobserved survival outcomes to better match the predicted survival experience of study subjects. We compare hazard ratio estimates for effect of an aggressive treatment regimen from Cox proportional hazards models using time to initial treatment outcome, predicted vital status, and true vital status at the end of the cohort period. RESULTS: Models fit from initial treatment outcomes underestimate treatment effects by up to 22.1%, while using predicted vital status reduced this bias by 5.4%. Models utilizing the predicted vital status produce effect estimates consistently stronger and closer to the true treatment effect than estimates produced by models using the initial treatment outcome. CONCLUSIONS: Although studies often use initial treatment outcomes to estimate treatment effects, this may violate the non-informative censoring assumption of the Cox proportional hazards model and result in biased treatment effect estimates. Using predicted vital status at the end of the cohort period may reduce this bias in the analyses of MDR-TB treatment cohorts, yielding more accurate, and likely larger, treatment effect estimates. Further, these larger effect sizes can have downstream impacts on future study design by increasing power and reducing sample size needs.

Associations of long-term fine particulate matter exposure with prevalent hypertension and increased blood pressure in older Americans.

BACKGROUND: Hypertension is a highly prevalent cardiovascular risk factor. It is possible that air pollution, also an established cardiovascular risk factor, may contribute to cardiovascular disease through increasing blood pressure. Previous studies evaluating associations between air pollution and blood pressure have had mixed results. METHODS: We examined the association between long-term (one-year moving average) air pollutant exposures, prevalent hypertension and blood pressure in 4121 older Americans (57+ years) enrolled in the National Social Life, Health, and Aging Project. We estimated exposures to PM2.5 using spatio-temporal models and used logistic regression accounting for repeated measures to evaluate the association between long-term average PM2.5 and prevalence odds of hypertension. We additionally used linear regression to evaluate the associations between air pollutants and systolic, diastolic, mean arterial, and pulse pressures. Health effect models were adjusted for a number of demographic, health and socioeconomic covariates. RESULTS: An inter-quartile range (3.91 µg/m3) increase in the one-year moving average of PM2.5 was associated with increased: Odds of prevalent hypertension (POR 1.24, 95% CI: 1.11, 1.38), systolic blood pressure (0.93 mm Hg, 95% CI: 0.05, 1.80) and pulse pressure (0.89 mm Hg, 95% CI: 0.21, 1.58). Dose-response relationships were also observed. CONCLUSIONS: PM2.5 was associated with increased odds of prevalent hypertension, and increased systolic pressure and pulse pressure in a cohort of older Americans. These findings add to the growing evidence that air pollution may be an important risk factor for hypertension and perturbations in blood pressure.

Association of neighborhood greenness with self-perceived stress, depression and anxiety symptoms in older U.S adults.

BACKGROUND: Neighborhood environment, such as green vegetation, has been shown to play a role in coping with stress and mental ill health. Yet, epidemiological evidence of the association between greenness and mental health is inconsistent. METHODS: We examined whether living in green space is associated with self-perceived stress, depressive and anxiety symptoms in a nationally representative, longitudinal sample of community-dwelling older adults (N = 4118; aged 57-85 years) in the United States. We evaluated perceived stress, depression and anxiety symptoms using the Cohen's Perceived Stress Scale, the Center for Epidemiological Studies - Depression, and the Hospital Anxiety and Depression Scale - anxiety subscale, respectively. Greenness was assessed for each participant using the Normalized Difference Vegetation Index at 250-m resolution, as well as a buffer of 1000-m. We conducted longitudinal analyses to assess the associations between greenness and mental health upon adjusting for confounders (e.g., education), and to examine potential mediation and effect modification. RESULTS: An interquartile range (0.25 point) increase in contemporaneous greenness was significantly associated with 0.238 unit (95% CI: - 0.346, - 0.130) and 0.162 unit (95% CI: - 0.271, - 0.054) decrease in the perceived stress in base and multivariable models, respectively. The magnitude of the association was similar or even stronger when examining summer (- 0.161; 95% CI: - 0.295, - 0.027) and annual average of greenness (- 0.188; 95% CI: - 0.337, - 0.038), as well as greenness buffer of 1000-m. The greenness-stress association was partially mediated by physical activity (15.1% mediated), where increased greenness led to increased physical activity and less stress, and by history of respiratory diseases (- 3.8% mediated), where increased greenness led to increased respiratory disease and more stress. The association was also significantly modified by race, social support, physical function, socioeconomic status, and region. While greenness was not significantly associated with anxiety and depressive scores across all participants, significant inverse associations were found for Whites participants, and for individuals with higher socioeconomic status, who were physically active, as compared to their counterparts. CONCLUSION: We found a direct association of greenness with perceived stress among older adults, and an indirect association mediated through physical activity and respiratory disease history. Our study findings warrant further examination of the mediation and modification of the greenness-mental health association.

Long-Term PM2.5 Exposure and Respiratory, Cancer, and Cardiovascular Mortality in Older US Adults.

The impact of chronic exposure to fine particulate matter (particulate matter with an aerodynamic diameter less than or equal to 2.5 µm (PM2.5)) on respiratory disease and lung cancer mortality is poorly understood. In a cohort of 18.9 million Medicare beneficiaries (4.2 million deaths) living across the conterminous United States between 2000 and 2008, we examined the association between chronic PM2.5 exposure and cause-specific mortality. We evaluated confounding through adjustment for neighborhood behavioral covariates and decomposition of PM2.5 into 2 spatiotemporal scales. We found significantly positive associations of 12-month moving average PM2.5 exposures (per 10-µg/m3 increase) with respiratory, chronic obstructive pulmonary disease, and pneumonia mortality, with risk ratios ranging from 1.10 to 1.24. We also found significant PM2.5-associated elevated risks for cardiovascular and lung cancer mortality. Risk ratios generally increased with longer moving averages; for example, an elevation in 60-month moving average PM2.5 exposures was linked to 1.33 times the lung cancer mortality risk (95% confidence interval: 1.24, 1.40), as compared with 1.13 (95% confidence interval: 1.11, 1.15) for 12-month moving average exposures. Observed associations were robust in multivariable models, although evidence of unmeasured confounding remained. In this large cohort of US elderly, we provide important new evidence that long-term PM2.5 exposure is significantly related to increased mortality from respiratory disease, lung cancer, and cardiovascular disease.

Erectile dysfunction and exposure to ambient Air pollution in a nationally representative cohort of older Men.

BACKGROUND: Little is known about the association between air pollution and erectile dysfunction (ED), a disorder occurring in 64% of men over the age of 70, and to date, no studies have been published. To address this significant knowledge gap, we explored the relationship between ED and air pollution in a group of older men who were part of the National Social Life, Health, and Aging Project (NSHAP), a nationally representative cohort study of older Americans. METHODS: We obtained incident ED status and participant data for 412 men (age 57-85). Fine particulate matter (PM2.5) exposures were estimated using spatio-temporal models based on participants' geocoded addresses, while nitrogen dioxide (NO2) and ozone (O3) concentrations were estimated using nearest measurements from the Environmental Protection Agency's Air Quality System. The association between air pollution and incident ED (newly developed in Wave 2) was examined and logistic regression models were run with adjusted models controlling for race, education, season, smoking, obesity, diabetes, depression, and median household income of census tract. RESULTS: We found positive, although statistically insignificant, associations between PM2.5, NO2, and O3 exposures and odds of incident ED for each of our examined exposure windows, including 1 to 7 year moving averages. Odds ratios (OR) for 1 and 7 year moving averages equaled 1.16 (95% CI: 0.87, 1.55) and 1.16 (95% CI: 0.92, 1.46), respectively, for an IQR increase in PM2.5 exposures. Observed associations were robust to model specifications and were not significantly modified by any of the examined risk factors for ED. CONCLUSIONS: We found associations between PM2.5, NO2, and O3 exposures and odds of developing ED that did not reach nominal statistical significance, although exposures to each pollutant were consistently associated with higher odds of developing ED. While more research is needed, our findings suggest a relationship between air pollutant exposure and incident cases of ED, a common condition in older men.

Identifying Hotspots of Multidrug-Resistant Tuberculosis Transmission Using Spatial and Molecular Genetic Data.

BACKGROUND: We aimed to identify and determine the etiology of "hotspots" of concentrated multidrug-resistant tuberculosis (MDR-tuberculosis) risk in Lima, Peru. METHODS: From 2009 to 2012, we conducted a prospective cohort study among households of tuberculosis cases from 106 health center (HC) areas in Lima, Peru. All notified tuberculosis cases and their household contacts were followed for 1 year. Symptomatic individuals were screened by microscopy and culture; positive cultures were tested for drug susceptibility (DST) and genotyped by 24-loci mycobacterial interspersed repetitive units-variable-number tandem repeats (MIRU-VNTR). RESULTS: 3286 individuals with culture-confirmed disease, DST, and 24-loci MIRU-VNTR were included in our analysis. Our analysis reveals: (1) heterogeneity in annual per-capita incidence of tuberculosis and MDR-tuberculosis by HC, with a rate of MDR-tuberculosis 89 times greater (95% confidence interval [CI], 54,185) in the most-affected versus the least-affected HC; (2) high risk for MDR-tuberculosis in a region spanning several HCs (odds ratio = 3.19, 95% CI, 2.33, 4.36); and (3) spatial aggregation of MDR-tuberculosis genotypes, suggesting localized transmission. CONCLUSIONS: These findings reveal that localized transmission is an important driver of the epidemic of MDR-tuberculosis in Lima. Efforts to interrupt transmission may be most effective if targeted to this area of the city.

Spatial measurement errors in the field of spatial epidemiology.

BACKGROUND: Spatial epidemiology has been aided by advances in geographic information systems, remote sensing, global positioning systems and the development of new statistical methodologies specifically designed for such data. Given the growing popularity of these studies, we sought to review and analyze the types of spatial measurement errors commonly encountered during spatial epidemiological analysis of spatial data. METHODS: Google Scholar, Medline, and Scopus databases were searched using a broad set of terms for papers indexed by a term indicating location (space or geography or location or position) and measurement error (measurement error or measurement inaccuracy or misclassification or uncertainty): we reviewed all papers appearing before December 20, 2014. These papers and their citations were reviewed to identify the relevance to our review. RESULTS: We were able to define and classify spatial measurement errors into four groups: (1) pure spatial location measurement errors, including both non-instrumental errors (multiple addresses, geocoding errors, outcome aggregations, and covariate aggregation) and instrumental errors; (2) location-based outcome measurement error (purely outcome measurement errors and missing outcome measurements); (3) location-based covariate measurement errors (address proxies); and (4) Covariate-Outcome spatial misaligned measurement errors. We propose how these four classes of errors can be unified within an integrated theoretical model and possible solutions were discussed. CONCLUSION: Spatial measurement errors are ubiquitous threat to the validity of spatial epidemiological studies. We propose a systematic framework for understanding the various mechanisms which generate spatial measurement errors and present practical examples of such errors.

Length of time spent working on a commercial construction site and the associations with worker characteristics.

BACKGROUND: Construction workers move frequently from jobsite to jobsite, yet little is documented about length of stay on-site and associations with worker characteristics. METHOD: Using cross-sectional data, we investigated associations between worker characteristics (including trade and musculoskeletal pain) and length of stay on-site (dichotomized as < 1 month, n = 554, and ≥ 1 month, n = 435). RESULTS: Approximately, 56% of workers remained on the worksite for at least 1 month. Length of stay was significantly associated with workers' race/ethnicity, union status, title, trade, and musculoskeletal pain (P-values < 0.05). Trades associated with longer length of stay included pipefitters and plumbers. Trades associated with shorter length of stay included operators and piledrivers. Workers with single-location pain had 2.21 times (95%CI: 1.52, 3.19) the odds of being short-term versus long-term, adjusting for trade, title, and race/ethnicity. CONCLUSION: The length of stay and associated characteristics provide important insight into how workers come and go on construction sites and the methodological challenges associated with traditional intervention evaluations.

Agreement between child self-report and parent-proxy report for functioning in pediatric chronic pain.

PURPOSE: Accurate assessment of chronic pain and functional disability in children and adolescents is imperative for guiding pain management interventions. Parents have multifaceted roles in their child's pain experience and frequently provide parent-proxy reports of pain-related functioning. However, cross-informant variance is often observed with limited understanding of contributing factors. This study aims to examine the degree of alignment between child and parent-proxy reports for Patient-Reported Outcomes Measurement Information System (PROMIS) pain interference domain among children with chronic pain and to identify factors associated with improved child-parent agreement. METHODS: This study includes a sample of 127 youth (66.1% female) with mixed etiology chronic pain, ranging in age from 8 to 17 (M = 12.24; SD = 1.598), and their parent. Data was collected at an interdisciplinary pediatric pain clinic and online peer support groups. Measures of demographic, pain intensity, and functioning were collected. RESULTS: Means of parent-proxy reports were significantly lower than child self-reports on the PROMIS (p < 0.05). A statistically significant association between child's pain intensity (ß = 0.953, P < 0.05) and the difference between child self-reported and parent-proxy reported PROMIS functional interference scores was found. CONCLUSION: Parents underestimated pain-related functional disability relative to children's self-reports. The difference between the paired child self-report and parent-proxy report of functional disability was significantly associated with greater child self-reported pain intensity. Although parent-proxy reports in pediatric chronic pain is often used in research and practice, findings underscore the importance of incorporating child and adolescent self-report, when possible, to comprehensively capture the child's pain experience and best inform clinical interventions.

Impact of a protocol advocating dexmedetomidine over propofol sedation after robotic-assisted direct coronary artery bypass surgery on duration of mechanical ventilation and patient safety.

BACKGROUND: Controversy remains whether propofol or dexmedetomidine is the preferred sedative following cardiac surgery. Dexmedetomidine may offer advantages over propofol among patients undergoing robotic-assisted, minimally invasive, direct coronary artery bypass (MIDCAB) surgery given the rapidity with which this population is usually extubated after surgery. OBJECTIVE: To measure the impact of a surgery protocol advocating use of dexmedetomidine rather than propofol after MIDCAB surgery on discontinuation of mechanical ventilation and patient safety. METHODS: The records on consecutive adults undergoing MIDCAB surgery who received postoperative sedation with propofol or dexmedetomidine at a 508-bed academic medical center were analyzed before and after implementation of a post-MIDCAB surgery protocol advocating dexmedetomidine use. RESULTS: Seventy-three propofol patients were compared with 53 dexmedetomidine patients. The groups were similar, except propofol patients were older (p = 0.002) and more likely to have underlying heart failure that was either moderate or severe (New York Heart Association class III or IV) (p = 0.0001). Time (median [interquartile range]) to extubation (hours) was shorter in the dexmedetomidine group (5.0 [3.6-7.0] vs 9.8 [5.0-16.3]; p = 0.0001). A Cox proportional hazards model revealed that patient age (p = 0.001) and duration of surgery (p = 0.003) influenced time to extubation between the dexmedetomidine and propofol groups but the presence of moderate or severe heart failure (p = 0.438), the number of coronary vessels operated on (p = 0.130), use of an opioid (p = 0.791), or the total dose of morphine administered (p = 0.215) did not. During sedation administration, more propofol-treated patients experienced 1 or more episodes of hypotension (systolic blood pressure ≤80 mm Hg, 11.6% vs 0%; p = 0.02), tachycardia (heart rate ≥120 beats/min, 8.6% vs 0%; p = 0.04), and unarousability (Sedation Agitation Scale score ≤2, 30.0% vs 9.4%; p = 0.03). CONCLUSIONS: Use of a protocol promoting dexmedetomidine, rather than propofol sedation, after MIDCAB surgery facilitates faster discontinuation of mechanical ventilation and is associated with greater hemodynamic stability and arousability.