1. Michelle Jiménez de Tavárez, MD; Flavia C. D. Andrade, PhD Department of Kinesiology and Community Health, College of Applied Health Sciences, University of Illinois at Urbana-Champaign Impact of Education in Tobacco Use and Alcohol Consumption in the Dominican Republic: A Social Gradient Perspective Acknowledgements The authors would like to thank DHS MEASURE and the Demography of Health and Aging Laboratory writing group. References 1.Marmot M. The Status Syndrome: How Social Standing Affects Our Health and Longevity. New York, Times Books, 2004. 319 pp. 2.Yusuf S, Hawken S, Ôunpuu S, Dans T, Avezum A, Lanas F, et al. Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case-control study. The Lancet. 2004; 364(9438):937-952. 3.Cowell AJ. The relationship between education and health behavior: Some empirical evidence. Health Economics. 2006; 15:125-146. 4.Yeon Kang J, Young Lee J, Hee Sung S, Mi Paek Y, In Choi T. The Comparison of Nutrient Intakes and Patterns of Alcohol Consumption According to Social Status in Workers. [Abstract] Epidemiology. 2011; 22(1):S164. Doi: 10.1097/01.ede.0000392178.94629.87 5.Pampel FC, Denney JT. Cross-National Sources of Health Inequality: Education and Tobacco Use in the World Health Survey. Demography 2011:1-22. 6.Harper S, Lynch J, Davey-Smith G. Social determinants and the decline of cardiovascular diseases: understanding the links. Annu Rev Public Health. 2011; 32:39-69. 7.Heller RF, McElduff P, & Edwards R. Impact of upward social mobility on population mortality: Analysis with routine data. BMJ. 2002; 325(7356), 134-137 8.http://legacy.measuredhs.com/accesssurveys/data_collection.cfmhttp://legacy.measuredhs.com/accesssurveys/data_collection.cfm 9.Centro de Estudios Sociales y Demográficos (CESDEM) y Macro International Inc. Encuesta Sociodemográfica y sobre VIH/SIDA en los bateyes Estatales de la República Dominicana 2007. Santo Domingo, República Dominicana y Calverton, Maryland: CESDEM y Macro International Inc.; 2008. (Original in Spanish). Aims 1.To assess the impact of educational attainment on tobacco use, alcohol consumption, concurrent use of tobacco and alcohol among adults in the DR.  We explore whether these relationships differ between the bateyes (sugar cane plantations) residents and the general population in the DR.  We also explore gender differences. Introduction  According to the social gradient socioeconomic status (SES) shape individual’s health and life expectancy.  SES is associated with cardiovascular disease (CVD) and CVD risk factors, such as cigarette smoking and alcohol consumption. 2  Studies have indicated that education is negatively associated with smoking. Inequalities in tobacco use, mainly among males and young individuals increase social inequalities in health. 2-5  In contrast, higher educational attainment is associated with higher and heavier daily alcohol consumption and drinking problems, mainly among women and older individuals. 5  Evidence supports that the impact of education level on smoking 6, 7 and alcohol consumption 5 differs by gender and by residential location. 3, 4  Little is known about the impact of educational attainment on tobacco use and alcohol consumption in the Dominican Republic (DR). Methods Data  We analyzed data from the Demographic and Health Surveys (DHS) collected in the DR in 2007. 8 Sample selection  Sampling process: cluster randomization  Eligibility criteria: all women aged 15-49 years and men aged 15-59 years who agreed to be interviewed  Final sample for data analysis  n=57,178 Measurements  Educational attainment: no education (ref.), incomplete primary, complete primary, incomplete secondary, complete secondary, and higher  Tobacco use (Do you smoke?) : yes vs. no (ref.)  Alcohol (Have you drunk alcohol?): yes vs. no (ref.)  Concurrent use: both smoking and drinking vs. none smoking or drinking (ref.) Data analysis STATA SE version 12.0 was used in the analysis. Descriptive statistics were assessed and logistic regressions were conducted to estimate the impact of educational attainment on tobacco use, alcohol consumption, and concurrent use. All regression analyses included age, sex, and residential location (bateyes vs. general population). Results  Most participants were aged 30 to 34 years.  Residents in bateyes were less educated than the general population.  Women had higher levels of educational achievement than men in the general population.  There were gender differences on educational attainment among the general population (chi2=3 986; p<0.001), but not among the bateyes (chi2=156; p=0.204).  Tobacco use was higher among men than among women (p<0.001) regardless the residential location.  Tobacco use among the bateyes’ residents was higher than in the general population (p<0.001).  Alcohol consumption was higher in the general population than in the bateyes (p<0.001).  Reported drinking alcohol was higher among men than women (p<0.001) for both locations.  The concurrent use of tobacco and alcohol was reported in 30.5% of all cases and was more frequent among the bateyes residents than the general population (p<0.001) and among men than women (p<0.001).. Discussion  Our findings support that: There is a social gradient in tobacco use in the DR: a higher educational attainment reduces the likelihood of smoking. However, alcohol-related social gradient was negatively associated with educational attainment. Higher educational attainment is negatively associated with the use of both tobacco and alcohol. Being female is a protective factor for both using tobacco or consuming alcohol. Living is the bateyes increases the likelihood of using tobacco but not alcohol. Our findings reinforce the need for gender-specific, social class-targeted interventions that are tailored to the circumstances of specific communities to prevent tobacco use and alcohol consumption in the DR. Figure 1. Percentage of adults using tobacco by gender and residential location in the DR. DHS 2007. Figure 2. Percentage of adults using alcohol by gender and residential location in the DR. DHS 2007. a Odds ratios; b Reference group: no education. c Reference group: males. d Reference group: general population Tobacco use n= 57, 178 Alcohol Consumption n= 57, 178 Concurrent use n= 16, 574 OR a P-value95%CIOR a P-value95%CIOR a P-value95%CI Educational attainment b Incomplete primary 0.64<0.0010.58 - 0.721.97<0.0011.79 - 2.161.210.0121.04 - 1.41 Complete primary 0.52<0.0010.44 - 0.622.38<0.0012.11 - 2.681.140.2270.92 - 1.41 Incomplete secondary 0.39<0.0010.33 - 0.452.73<0.0012.47 - 3.021.020.8060.85 - 1.23 Complete secondary 0.30<0.0010.25 - 0.352.82<0.0012.49 - 3.180.730.0030.59 - 0.89 Higher 0.22<0.0010.19 - 0.263.08<0.0012.75 - 3.450.63<0.0010.51- 0.77 Age 1.06<0.0011.05 - 1.061.00 0.5271.00 - 1.001.06<0.0011.06 - 1.07 Females c 0.64 0.0020.59 - 0.680.30<0.0010.28 - 0.310.18<0.0010.16 - 0.20 Bateyes d 1.23<0.0011.08 - 1.410.94 0.2950.85 - 1.051.120.2190.94 - 1.34 Table 2. Logistic regression results for tobacco use and alcohol consumption in DR, DHS 2007 Figure 3. Percentage of concurrent use of tobacco and alcohol by gender and residential location in the DR. DHS 2007 Contact information: Michelle Jimenez mjimenez@illinois.edu Table 1. Educational attainment by gender and residential location in DR, DHS 2007 ***