THE IMPACT OF SOCIAL FACTORS ON TOBACCO SMOKING DURING PREGNANCY 5th Annual NIDA International Poster Session at the Society for Prevention Research (SPR) 20th Annual Meeting in Washington, DC, May 29–June 1, 2012. THE IMPACT OF SOCIAL FACTORS ON TOBACCO SMOKING DURING PREGNANCY A. Fogarasi-Grenczer1, I. Rákóczi2, K. L. Foley PhD.3, P. Balázs MD. PhD4 1. Semmelweis University, Faculty of Health Sciences, Institute of Health Promotion and Clinical Methodology, Department of Family Care Methodology, Hungary. 2. University of Debrecen, Health Care Faculty, Institute of Health Sciences, Deptartment of Family Care Methodology and Public Health, Hungary, 3. Medical Humanities Program, Davidson College, North Carolina, USA, 4. Semmelweis University, Faculty of General Medicine, Institute of Public Health, Hungary. Introduction Health risks associated with prenatal exposure to tobacco smoking are well- established. Maternal smoking influences not only the perinatal period of the neonate, but also it may have long-term consequences, such as behavioral disorders and pulmonary diseases in childhood. The aim of our research was to study tobacco use and its correlates (socio-economic background, demographic status and other lifestyle factors) among expectant mothers as well as birth outcomes. The results of our research will be applied to the training of health care personnel active in field prevention in the maternal and child health service in Hungary Objectives to assess relationships among socio-economic factors and preterm birth and/or /low birth weight to measure the frequency of expectant mothers’ smoking and identification of factors contributing to regular smoking to understand the impact of smoking on the infants’ biometric measures and adaptation. Methods Our research was conducted among mothers with live-born babies in two counties of Hungary. We reached 9,040 mothers, which represents 71% of the pregnant population and 9.4% of all live births in Hungary in 2009. Data were obtained from two sources: 1) Medical records of obstetrical wards and 2) In-person interviews Data were analyzed by SPSS (15.0-19.0) statistical program Descriptive statistics (means, sd, ranges and frequencies) were used to describe the sample. Bivariate associations were calculated on all variables and their relationship to smoking status using the Pearson’s Chi-square test. Logistic regression analyses were computed to assess the relationship of socio-economic status to smoking versus non-smoking. Results are reported in odds ratios (ORs) at 95 % confidence interval (CI). Results The rate of smoking during pregnancy is very high in the two measured counties. Smoking is more frequent among mothers who live in poverty and deep poverty. Low level of education, unemployment, ethnicity, and family status influence significantly the frequency of smoking. Conclusions Smoking attitudes and health status depend on level of education, socio-economic position, and social relationships. There is a need for cooperation of health care, education and civil and governmental organizations in order to reduce tobacco use among expectant mothers. As there are equality problems while accessing health care services, setting up available facilities at primary and secondary level in rural and underdeveloped regions would also be necessary in providing the necessary cessation services for expectant mothers. Table I. Population and birth outcomes in Hungary (2010) # of live births in Hungary and per thousand Average age of woman at the birth of the first child Preterm birth (PTB) Low birth weight (LBW) (<2500gr) Infant mortality per thousand liveborns Total fertility rate (2010) 96,442 9.6 27.92 yrs 8.7 % 8.4 % 5.1 ‰ 1.26 Hungarian smoking habits Male smoking is 40,6% (incidence of lung cancer is the highest in Hungary) Female smoking is 31,7% Smoking during pregnancy is 15%, but in disadvantaged counties 25% Incidence of smoking among 11-year-old students is the highest in Hungary Incidence of smoking among 13-year-old students is 6% Incidence of smoking among 17-year-old students is 30% Effect of smoking during pregnancy Ectopic pregnancy Spontaneous abortion Premature birth IUGR [intrauterine growth restiction] Abruptio placentae, placenta praevia Stillbirth, Congenital malformation Table II. Smoking habits during pregnancy related to demo-graphic, socioeconomic and other characteristics of smoking (n=3506) and non-smoking (n=4844) mothers (N=8350) with live born babies in 2 north-eastern counties in Hungary in 2009. Variables Overall (N) Smokers non-Smokers p-value Ethnicity (n,%) 7330 3065 4265 <0.001 Roma 2261 1269 (41.4) 992 (23.3) non-Roma 5069 1796 (58.6) 3273(76.7) Age categories (n,%) <18 308 139 (4) 169 (3.5) 18-34 6823 2919 (83.3) 3904 (80.6) 35-40 1045 375 (10.7) 670 (13.8) 41+ 174 73 (2.1) 101 (2.1) BMI categories (n,%) Underweight 1158 626 (19) 532 (11.5) Normal 4753 1951 (59.1) 2802 (60.7) Overweight 1292 470 (14.2) 722 (17.8) Obesity 714 254 (7.7) 460 (10) Education (n,%) 8309 3494 4815 <8 grades 790 492 (14.1) 298 (6.2) Completed 8 grades** 2397 1322 (37.8) 1075 (22.3) Secondary 3620 1434 (41) 2186 (45.4) University/college 1502 246 (7) 1256 (26.1) Employment (n,%) 8306 3490 4816 Employed 3405 1049 (30.1) 2356 (48.9) Unemployed 2001 1072 (30.7) 929 (19.3) Varia*** 2900 1369 (39.2) 1531 (31.8) Marital Status (n, %) 8315 4825 Married 4345 1333 (38.2) 3012 (62.4) Cohabitation 3539 1908 (54.7) 1631 (33.8) Separated/divorced 138 70 (2.0) 58 (1.2) Single/Widowed 303 179 (5.1) 124 (2.6) # Children (x, (sd) ) min-max 2.3 (1.5) 1-13 2.5 (1.7) 2.1 (1.3) Income/capita (n,%) 7989 3401 4588 Deep poverty Varia**** 3742 4247 2076 (61.0) 1325 (39) 1666 (36.3) 2922 (63.7) Housing conditions (n,%) 7827 3284 4543 Full amenities 4683 1564 (47.6) 3119 (68.7) Partial amenities 1450 715 (21.8) 735 (16.2) Without amenities 1694 1005 (30.6) 689 (15.2) ETS (n, % Yes) 4013 2339 (67.2) 1674 (35.8) Table III: Multivariable logistic regression model of women’s smoking during pregnancy versus non- smoking (N=8350) by demographic, socio-economic characteristics in 2 Eastern Hungarian counties. Variables OR 95% CI <p-value families with non-deep poverty vs. deep poverty 1,208 ,910 1,604 N.A. towns and incorporated towns with medical services vs. rural 1,429 1,005 2,032 ,047 ETS (non-smoker husband) vs. smoker husband 2,503 1,953 3,208 ,000 full or partial amenities vs. without amenities 1,317 ,957 1,812 employed before labour vs. unemployed ,753 ,555 1,023 education ( secondary)   <8 grades and 8 grades (primary school) ,420 ,285 ,619 trade school ,557 ,403 ,770 university/college 1,589 1,037 2,436 ,034 family status: married vs. non-contractual cohabitation ,605 ,477 ,766 single or separated or divorced ,821 ,444 1,518 did not do manual work vs. did manual work regularly during pregnancy 2,003 1,307 3,072 ,001 non-Roma vs. Roma 1,432 1,045 1,961 ,025 References [1] S. Cnattingius: The epidemiology of smoking during pregnancy: Smoking prevalence, maternal characteristics, and pregnancy outcomes, Nic.Tob.Res. Vol. 6, Supplement 2, apr. 2004. [2] M. Eriksen, J. Mackay, H. Ross: The Tobacco Atlas 4th edition, 2012 [3] Tombor I, Paksi B, Urban R, Kun B, et al.: Prevalence of smoking among the Hungarian adult population, Népegészségügy 2010. [4] Source: Hungarian CSO database ACKNOWLEDGEMENT: This publication was made possible by Grant Number 1 R01 TW007927-01 from the Fogarty Inter-national Center, the National Cancer Institute, and the National Institutes on Drug Abuse, within the National Institutes of Health (NIH).  Its contents are solely the responsibility of the authors and do not necessarily represent the official view of the NIH. *t-probe, all other p-values were processed by the Pearson’s chi-square test **Primary school ***Disabled, student, etc. ****Poverty, At poverty level, Sufficient/Wealthy