Justin Manjourides

Association of Ambient Air Pollution with Depressive and Anxiety Symptoms in Older Adults: Results from the NSHAP Study.

Background: Ambient fine particulate matter (PM2.5) is among the most prevalent sources of environmentally induced inflammation and oxidative stress, both of which are implicated in the pathogenesis of most mental disorders. Evidence, however, concerning the impact of PM2.5 on mental health is just emerging. Objective: We examined the association between PM2.5 and current level of depressive and anxiety symptoms using a nationally representative probability sample (n = 4,008) of older, community-dwelling individuals living across the United States (the National Social Life, Health and Aging project). Methods: Mental health was evaluated using validated, standardized questionnaires and clinically relevant cases were identified using well-established cutoffs; daily PM2.5 estimates were obtained using spatiotemporal models. We used generalized linear mixed models, adjusting for potential confounders, and explored effect modification. Results: An increase in PM2.5 was significantly associated with anxiety symptoms, with the largest increase for 180-days moving average (OR = 1.61; 95% CI: 1.35, 1.92) after adjusting for socioeconomic measures (SES); PM2.5 was positively associated with depressive symptoms, and significantly for 30-day moving average (OR = 1.16; 95% CI: 1.05, 1.29) upon SES adjustment. The observed associations were enhanced among individuals who had low SES and history of comorbidity. When considering mental health as chronic conditions, PM2.5 was significantly associated with incident depressive symptoms for all exposure windows examined, but with incident anxiety symptoms only for shorter exposure windows, which may be due to a drop in power resulting from the decreased between-subject variability in chronic PM2.5 exposure. Conclusion: PM2.5 was associated with depressive and anxiety symptoms, with associations the strongest among individuals with lower SES or among those with certain health-related characteristics. Citation: Pun VC, Manjourides J, Suh H. 2017. Association of ambient air pollution with depressive and anxiety symptoms in older adults: results from the NSHAP study. Environ Health Perspect 125:342–348; http://dx.doi.org/10.1289/EHP494

Identifying multidrug resistant tuberculosis transmission hotspots using routinely collected data

In most countries with large drug resistant tuberculosis epidemics, only those cases that are at highest risk of having MDRTB receive a drug sensitivity test (DST) at the time of diagnosis. Because of this prioritized testing, identification of MDRTB transmission hotspots in communities where TB cases do not receive DST is challenging, as any observed aggregation of MDRTB may reflect systematic differences in how testing is distributed in communities. We introduce a new disease mapping method, which estimates this missing information through probability-weighted locations, to identify geographic areas of increased risk of MDRTB transmission. We apply this method to routinely collected data from two districts in Lima, Peru over three consecutive years. This method identifies an area in the eastern part of Lima where previously untreated cases have increased risk of MDRTB. This may indicate an area of increased transmission of drug resistant disease, a finding that may otherwise have been missed by routine analysis of programmatic data. The risk of MDR among retreatment cases is also highest in these probable transmission hotspots, though a high level of MDR among retreatment cases is present throughout the study area. Identifying potential multidrug resistant tuberculosis (MDRTB) transmission hotspots may allow for targeted investigation and deployment of resources.

Effects of Latitude and Longitude on the Population Structure of Culex pipiens s.l., Vectors of West Nile Virus in North America

We assessed the structure and latitudinal selection that might result in sensitivities to critical day-lengths that trigger diapause between Culex pipiens populations distributed along North-South and East-West axes in eastern North America. Strong population structure between Cx. p. pipiens and Cx. p. quinquefasciatus existed. Among Cx. p. pipiens, a 100-km increase in the latitudinal change resulted in an increased square root of F(ST) by 0.002. A 100-km increase in the longitudinal change caused an increased square root of F(ST) by 0.035. A lack of latitudinal influence on the structure between Cx. p. pipiens populations suggests a uniform signal using the 12 microsatellite markers, which might increase the risk of West Nile virus (WNV) transmission toward northern areas because of longer breeding season, extend host-seeking period, and larger population size. Northern Cx. p. pipiens may have undergone additional generations before diapause is triggered, magnifying population size when WNV amplification is peaking.

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.

Associations between long-term exposure to air pollution, glycosylated hemoglobin and diabetes

BACKGROUND Air pollution exposures have been shown to adversely impact health through a number of biological pathways associated with glucose metabolism. However, few studies have evaluated the associations between air pollution and glycosylated hemoglobin (HbA1c) levels. Further, no studies have evaluated these associations in US populations or investigated whether associations differ in diabetic as compared to non-diabetic populations. To address this knowledge gap, we investigated the associations between airborne fine particulate matter (PM2.5) and nitrogen dioxide (NO2) and HbA1c levels in both diabetic and non-diabetic older Americans. We also examined the impact of PM2.5 and NO2 on prevalent diabetes mellitus (DM) in this cohort. METHODS We used multilevel logistic and linear regression models to evaluate the association between long-term average air pollutant levels and prevalence of DM and HbA1c levels, respectively, among 4121 older (57+ years) Americans enrolled in the National Social Life, Health, and Aging Project between 2005 and 2011. All models adjusted for age, sex, body mass index, smoking status, race, household income, education level, neighborhood socioeconomic status, geographic region, urbanicity and diabetic medication use. We estimated participant-specific exposures to PM2.5 on a six-kilometer grid covering the conterminous U.S. using spatio-temporal models, and to NO2 using nearest measurements from the Environmental Protection Agencys Air Quality System. HbA1c levels were measured for participants in each of two data collection waves from dried blood spots and log-transformed prior to analysis. Participants were considered diabetic if they had HbA1c values≥6.5% or reported taking diabetic medication. RESULTS The prevalence of diabetes at study entry was 22.2% (n=916) and the mean HbA1c was 6.0±1.1%. Mean one-year moving average PM2.5 and NO2 exposures were 10.4±3.0μg/m3 and 13.1±7.0 ppb, respectively. An inter-quartile range (IQR, 3.9μg/m3) increase in one-year moving average PM2.5 was positively associated with increased diabetes prevalence (prevalence odds ratio, POR 1.35, 95% CI: 1.19, 1.53). Similarly, an IQR (8.6 ppb) increase in NO2 was also significantly associated with diabetes prevalence (POR 1.27, 95% CI: 1.10, 1.48). PM2.5 (1.8%±0.6%, p<0.01) and NO2 (2.0%±0.7%, p<0.01) exposures were associated with higher HbA1c levels in diabetic participants, while only NO2 was significantly associated with HbA1c in non-diabetic participants (0.8%±0.2%, p<0.01). Significant dose response relationships were identified for both pollutants in diabetic participants and for NO2 in non-diabetic participants. CONCLUSIONS/INTERPRETATIONS In a cohort of older men and women in the United States, PM2.5 and NO2 exposures were significantly associated with prevalence of DM and increased HbA1c levels among both non-diabetic and diabetic participants. These associations suggest that air pollution could be a key risk factor for abnormal glucose metabolism and diabetes in the elderly.

Improving the power of chronic disease surveillance by incorporating residential history

We present a global test for disease clustering with power to identify disturbances from the null population distribution which accounts for the lag time between the date of exposure and the date of diagnosis. Location at diagnosis is often used as a surrogate for the location of exposure; however, the causative exposure could have occurred at a previous address in a cases residential history. We incorporate models for the incubation distribution of a disease to weight each address into the residential history by the corresponding probability of the exposure occurring at that address. We then introduce a test statistic which uses these incubation-weighted addresses to test for a difference between the spatial distribution of the cases and the spatial distribution of the controls, or the background population. We follow the construction of the M statistic to evaluate the significance of these new distance distributions. Our results show that gains in detection power when residential history is accounted for are of such a degree that it might make the qualitative difference between the presence of spatial clustering being detected or not, thus making a strong argument for the inclusion of residential history in the analysis of such data.

A permutation test for determining significance of clusters with applications to spatial and gene expression data

Hierarchical clustering is a common procedure for identifying structure in a data set, and this is frequently used for organizing genomic data. Although more advanced clustering algorithms are available, the simplicity and visual appeal of hierarchical clustering has made it ubiquitous in gene expression data analysis. Hence, even minor improvements in this framework would have significant impact. There is currently no simple and systematic way of assessing and displaying the significance of various clusters in a resulting dendrogram without making certain distributional assumptions or ignoring gene-specific variances. In this work, we introduce a permutation test based on comparing the within-cluster structure of the observed data with those of sample datasets obtained by permuting the cluster membership. We carry out this test at each node of the dendrogram using a statistic derived from the singular value decomposition of variance matrices. The p-values thus obtained provide insight into the significance of each cluster division. Given these values, one can also modify the dendrogram by combining non-significant branches. By adjusting the cut-off level of significance for branches, one can produce dendrograms with a desired level of detail for ease of interpretation. We demonstrate the usefulness of this approach by applying it to illustrative data sets.

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.

Linking Surveillance with Action against Drug-Resistant Tuberculosis

The speed at which most countries with high burdens of multidrug-resistant tuberculosis (MDRTB) have scaled up their capacity to diagnose and treat individuals with these forms of TB has failed to keep pace with the problem. Limited availability of drug susceptibility testing, high costs and inefficiencies in the supply of second-line drugs, and inadequate capacity for the management of patients with MDRTB have contributed to the wide gap between the estimated need for and the delivery of MDRTB treatment. The most recent global estimates indicate that only about 1 in 20 individuals with incident MDRTB will be properly diagnosed; fewer still receive quality-assured treatment. As policy makers confront the threat of growing levels of drug-resistant TB, there is a clear role for improved surveillance methods that can facilitate more effective public health responses. In countries that cannot yet test all incident cases for drug resistance, analysis of programmatic data and use of periodic, efficient surveys can provide information to help prioritize the use of limited resources to geographic areas or population subgroups of greatest concern. We describe methods for the analysis of routinely collected data and alternative surveys that can help tighten the link between surveillance activities and interventions.

Cognitive impacts of ambient air pollution in the National Social Health and Aging Project (NSHAP) cohort

BACKGROUND Pathways through which air pollution may impact cognitive function are poorly understood, particularly with regard to whether and how air pollution interacts with social and emotional factors to influence cognitive health. OBJECTIVE To examine the association between air pollutant exposures and cognitive outcomes among older adults participating in the National Social Life, Health, and Aging Project (NSHAP) cohort study. METHODS Measures of cognitive function, social connectedness, and physical and mental health were obtained for each NSHAP participant starting with Wave 1 of the study in 2005. Cognitive function was assessed using the Chicago Cognitive Function Measure (CCFM) for 3377 participants. Exposures to fine particles (PM2.5) were estimated for each participant using GIS-based spatio-temporal models, and exposures to nitrogen dioxide (NO2) were obtained from the nearest EPA monitors. RESULTS In adjusted linear regression models, IQR increases in 1 to 7year PM2.5 exposures were associated with a 0.22 (95% CI: -0.44, -0.01) to a 0.25 (95% CI: -0.43, -0.06) point decrease in CCFM scores, equivalent to aging 1.6years, while exposures to NO2 were equivalent to aging 1.9years. The impacts of PM2.5 on cognition were modified by stroke, anxiety, and stress, and were mediated by depression. The impacts of NO2 were mediated by stress and effect modification by impaired activities of daily living for NO2 was found. CONCLUSIONS Exposures to long-term PM2.5 and NO2 were associated with decreased cognitive function in our cohort of older Americans, and individuals who experienced a stroke or elevated anxiety were more susceptible to the effects of PM2.5 on cognition. Additionally, mediation results suggest that PM2.5 may impact cognition through pathways related to mood disorders.