Abstracts / Annals of Epidemiology 23 (2013) 581e598 589

only increased for non-asthmatics on lag day 2: RR¼1.003 (1.000-1.005).Risks for other pollutants often appeared higher for asthmatics but were lessconsistent.Conclusion: Asthmatics may be more susceptible to acute exposure totraffic-related pollutants, such as NOx and CO, which could trigger PTB.

P34-S. Impact of Aerial Insecticide Spraying on West Nile VirusDisease d North Texas, 2012

D. Ruktanonchai, S. Pillai, S. Stonecipher, N. Lindsey, K. Horiuchi, M. Delorey,B. Biggerstaff, T. Sidwa, J. Zoretic, J. McAllister, R. Nasci, M. Fischer, S. Hills. TXDSHS, Austin, TX

Purpose: West Nile virus (WNV) is the leading cause of mosquitobornedisease in the United States. During 2012, four north Texas counties reported>840 WNV cases, six times more than any previous year. In response, lar-viciding and ground-based adulticide spraying were performed variablythroughout the area and, for the first time in north Texas, aerial insecticidespraying was used for WNV control with two counties treated in August. Weevaluated aerial spraying's impact on WNV disease.Methods: We defined a case as a resident of one of the four counties who, in2012, had laboratory-confirmed WNV neuroinvasive disease using thenational surveillance case definition. Patients were categorized as livingwithin or outside the aerial-sprayed area. We calculated incidence rate ratios(IRRs) in treated and untreated areas by comparing incidence rates beforeand after spraying; for unsprayed areas, before and after periods weredefined by using spray dates from a corresponding sprayed area. We eval-uated aerial spraying's impact by using the ratio and 95% confidence intervals(CIs) of IRRs in treated and untreated areas.Results: In treated areas, the incidence before and after spraying was 7.47and 0.28 per 100,000 persons, respectively; the IRR was 27.00 (95% CI:12.70e57.41). In untreated areas, the before and after incidence was 4.80 and0.45 per 100,000 persons, respectively; the IRR was 10.57 (95% CI:6.11e18.29). The ratio of these IRRs was 2.55 (95% CI: 1.01e6.49).Conclusion: WNV neuroinvasive disease incidence decreased in the after-spray period in both areas, but the relative changewas significantly greater inaerial-sprayed areas.

P35. Associations Between Environmental Characteristics andWeight Status in Elementary School Children

R.R. Suminski, J.A. Wasserman, C.A. Mayfield, L.W. Segars, A. Glaros. KansasCity University of Medicine and Biosciences, Kansas City, MO

Purpose: In this cross-sectional study we examined associations betweenfood outlets and physical activity facilities and body mass index percentilerankings (BMIp).Methods: Trained investigators visited 43 elementary schools to collect dataon a sample (n¼6,939) of Hispanic (36.7%), Black (39.8%), and White (23.5%)boys (51.7%) and girls (mean age ¼ 8.3 y; mean BMIp ¼ 71.3) living in the zipcode areas of the schools (i.e., school neighborhoods). In addition, informa-tion about the number of convenience, fast food, and grocery stores and park,playground, and fitness facilities in the school neighborhoods was obtainedusing various search methods (e.g., Internet, in-person audits).Results: Hispanic had significantly higher BMIp than Whites and Blacks. Themulti-level regression analyses adjusted for school neighborhood (crimerate) and school (percent free/reduced lunch, PE offered) characteristics,indicated that higher BMIp were associated with fewer parks (Hispanic girls)and fitness facilities (Black boys) and more fast food stores (White andHispanic boys) (p<0.05).Conclusion: Environmental characteristics of the neighborhoodssurrounding elementary schools are associated with the weight status ofchildren attending and living near those schools. The associations varyaccording to the racial/ethnic background and gender of the child.

P36. Cumulative Neighborhood Risk and Allostatic Load inAdolescents

K.P. Theall, E.A. Shirtcliff, S.S. Drury. Department of Global CommunityHealth and Behavioral Sciences, Tulane University, New Orleans, LA

Purpose: We examine the impact of cumulative neighborhood risk on ALamong adolescents as a mechanism through which life stress, includingneighborhood conditions, may impact health and health inequities.Methods: Multilevel analyses were conducted, weighted for sampling andpropensity score matched, among 12-20 year-old adolescents in theNHANES, 1999-2006 (first level, n¼11,886) nested within family/household(second level, n¼6,696) and census tracts (third level, n¼2,191) to examinethe contextual effect of cumulative neighborhood risk environment on AL.Results: Approximately 35% of adolescents had 2 ormore biomarkers of AL. Asignificant amount of variance in AL was explained at the neighborhoodlevel. Even after taking into account household and other individual factors,the likelihood of having a high AL was approximately 10% higher for thoseliving in medium cumulative risk (adjusted OR ¼ 1.09, 95% CI ¼ 1.08, 1.09),30% higher those living in high (adjusted OR ¼ 1.28, 95% CI ¼ 1.27, 1.30), and69% higher for those living in very high risk neighborhoods (adjusted OR ¼1.69, 95% CI ¼ 1.68, 1.70) compared to those in low risk areas.Conclusion: These findings offer support for the hypothesis that neighbor-hood risksmay culminate in a range of biologically-mediated negative healthoutcomes detectable in adolescents.

Health Services

P37-S. Ethnicity, Gender, Need for Mental Health Care andInpatient Mental Health Care Utilization Among AmericanBlacks

Shervin Assari MD, MPH. University of Michigan School of Public Health

Purpose: To determine the effect of gender on the effect of having a definiteneed formental health care on use of inpatient mental health services amonga community sample of African Americans and Caribbean Blacks in theUnited States.Methods: Data came from National Survey of American Life, a nationalrepresentative data of noninstitutionalized African Americans (n¼3,123) andCaribbean Blacks (n¼1,319). Presence of lifetime psychiatric disorder wasindependent variable, determined by a modified version of the CompositeInternational Diagnostic Interview. Dependent variable was lifetime inpa-tient mental health care use. We tested main effects of gender and lifetimepsychiatric disorder and their interactions in logistic regressions specific foreach ethnic group. We also tested main effect and interactions of ethnicity,gender and any lifetime psychiatric disorder in the pooled sample.Results: Among African Americans (OR¼3.303; 95% CI¼ 1.015 to 10.753), butnot Caribbean Blacks (OR¼0.342; 95% CI¼0.009 to 12.488), male genderincreased the odds of inpatient mental health care utilization associated withany lifetime psychiatric disorder. Based on our pooled regression model, theeffect of male gender on inpatient mental health care use was larger forAfrican Americans than Caribbean Blacks (OR for interaction term¼ 4.5, 95%CI ¼ 1.3 to 15.8).Conclusion: Among African Americans with serious mental health need,male gender is associated with 3.3 times higher odds of inpatient mentalhealth care use. This gender disparity does not exist among Caribbean Blacks.

P38. The Influence of Surgical Subspecialty Training on In-Hospital Mortality for Cancer Procedures

P. Christos, M. Mazumdar, A. Mushlin. Department of Public Health, WeillCornell Medical College, New York, NY

Purpose: Patients operated on by surgeons with specialty training have beenshown to have lower mortality rates. The objective of this study was toevaluate the independent effect of surgical subspecialty training (training) onin-hospital mortality for cancer patients undergoing colectomy or gastrec-tomy surgical procedures.Methods: We studied all colectomy and gastrectomy (N¼62,719) dischargesfor cancer from the New York State Department of Health's StatewidePlanning and Research Cooperative System (SPARCS) database during 1998to 2006. Training was defined as membership in the Society of ColorectalSurgery or the Society of Surgical Oncology. In-hospital mortality rates werecompared for patients operated on by surgeons with and without training,adjusted for patient characteristics, surgeon volume, and hospital volume.Clustering by surgeon was explored with both generalized estimatingequations (GEE) and random effects (RE) modeling.