142nd APHA Annual Meeting and Exposition

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Trends in upstate NY adult health indicators: Longitudinal county- level results, 1997-2012

142nd APHA Annual Meeting and Exposition (November 15 - November 19, 2014): http://www.apha.org/events-and-meetings/annual
Sunday, November 16, 2014

Dana Olzenak, PT, DPT , Department of Public Health Sciences, University of Rochester, Rochester, NY
Ann M. Dozier, RN, PhD , Public Health Sciences/Social and Behavioral Sciences, University of Rochester, Rochester, NY
Ann Kern , Monroe County Department of Public Health, Rochester, NY
Kelly Thevenet-Morrison, MS , Public Health Sciences, University of Rochester, Rochester, NY
Amina Alio, PhD , Department of Public Health Sciences, University of Rochester, Rochester, NY
Holly Widanka, MS , Public Health Sciences, University of Rochester, Rochester, NY
Hazel Adekunle, MLA , Public Health Sciences, University of Rochester, Rochester, NY
Byron Kennedy, MD, PhD , Monroe County Health Department, Rochester, NY
Nancy Bennett, MD, MS , Center of Community Health, University of Rochester, Rochester, NY
Background. Understanding racial/ethnic disparities at the local level is limited by lack of timely, actionable data. Furthermore analyses rarely control for key covariates. We report on analyses of longitudinal population level data collected over 15 years in an upstate New York community.

Methods. Secondary data analyses compared 4 cross-sectional surveys (collected in 1997, 2000, 2006, 2012) to study acial/ethnic disparities across five health outcomes (BMI, insurance coverage, smoking, mental health and self-reported health). Data from cross-sectional telephone surveys, items adapted from national surveys, were designed to provide valid representation of prevalence estimates of adult health status and behavior indicators. Survey questions changed over time; variables were collapsed or recoded to allow for longitudinal analyses; missing observations were excluded. Sample sizes across survey years varied (1579 to 2272). Raking was performed to appropriately weight and report population level outcomes. Covariates included age, gender, education and residence (city/suburb).

Results. Results presented for two outcomes.
Current Smoker: Despite declines from 1997 to 2012 in overall prevalence and among non-Hispanic (NH) Blacks and Hispanics, disparities persisted (2012: NH-Whites:  12.4%, NH-Blacks: 23.9%; Hispanics: 16.5%). Unadjusted ORs: 1.8[95%CI:1.1,2.9] and 1.3[95%CI:0.4,1.1] (NH-Black and Hispanic (vs. NH-White)) changed dramatically after covariate adjustment: 0.6[95%CI:0.4,1.1] and 0.5[95%CI:0.3,1.1] respectively.
BMI: Despite increases overall and among Blacks and Hispanics, rates of overweight were similar for NH-Blacks and NH-Whites (ranging from 31.1-38.1% over the four surveys). Hispanics’ rates were generally >5% lower.
Obesity prevalence rates among NH-Blacks were approximately twice those of NH-Whites over all surveys (e.g. 1997: obese: 30.8% vs. 14.2%; 2012: obese:  46.3% vs. 27.9%). Obesity rates among Hispanics were similar to NH-Whites in 1997, but approached those of NH-Blacks by 2012.

For NH-Blacks vs. NH-Whites, after adjustment, ORs showed only slight differences (e.g. 2012: overweight: crude OR: 1.4[95%CI: 0.8,2.5]; adjOR: 1.8[95%CI:1.0,3.3]; obese: crude OR: 1.9[95%CI:1.2,3.2]; adjOR: 1.4[95%CI:0.8,2.5]). Comparisons between crude and adjusted ORs for Hispanics vs. NH-Whites also showed few differences.

Conclusions. Observed racial/ethnic disparities may be better understood after accounting for other covariates. Using local data and accounting for covariates in disparity analyses identifies areas of greater or lesser impact and opportunities to focus programs and target funding.

Learning Areas:

Chronic disease management and prevention

Learning Objectives:
Discuss data collection methods, disparity analysis and use of longitudinal community level data for planning and evaluation.

Keyword(s): Health Disparities/Inequities, Data Collection and Surveillance

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I am the Lead Evaluator for the project from which the data in this presentation are drawn. I helped design the survey and interpret the findings. I am an PhD prepared nurse and an Associate Professor in Public Health Sciences
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.