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© Borgis - New Medicine 2/2012, s. 45-51
*Andrea Fogarasi-Grenczer1, Ildikó Rákóczi2, Péter Balázs3, Kristie L. Foley4
Socioeconomic factors and health risks among smoking women prior to pregnancy in Hungary
1Semmelweis University, Faculty of Health Sciences, Institute of Health Promotion and Clinical Methodology, Department of Family Care and Methodology, Hungary
Head of Institute: Gyula Domján, MD, PhD
2University of Debrecen, Health Care Faculty, Institute of Health Sciences, Department of Family Care Methodology and Public Health, Hungary
Head of Department: Zsigmond Kósa, MD, PhD
3Semmelweis University, Faculty of General Medicine, Institute of Public Health, Hungary
Head of Institute: Anna Tompa, MD, PhD
4Medical Humanities Program, Davidson College, North Carolina, USA
Director: Lance K. Stell, PhD
Summary
Aim. To assess the social and economic factors that influence tobacco smoking prior to pregnancy.
Material and methods. This research was conducted among mothers who gave birth to babies in the two least developed counties in Hungary (Borsod-Abaúj-Zemplén and Szabolcs-Szatmár-Bereg) in 2009. Data were obtained from medical records of obstetrical wards and structured interviews conducted by local maternity and child service. There were 7,877 women with complete data on smoking habits among 9,040 women in the study. This represents 9.4% of total live births in Hungary and 71.1% of all live births in the two counties.
Results. The overall prevalence of smoking prior to pregnancy was 46.0%. Smoking women were typically less than 18 years old, underweight, with the lowest levels of education, those living in non-contractual cohabitation, and those with unhealthy dietary habits (p<0.001), further living in deep poverty (p < 0.05).
Conclusions. While planning preventive actions to reduce female tobacco use in gestational age, the socioeconomic situation must be considered.



Introduction
While male tobacco smoking has levelled off in most of the developed countries, the frequency of smoking among women is on the rise. The European average is near 34%. Hungary is comparable to Greece, Portugal, Bosnia, Spain, and the United Kingdom. Only in Austria and Serbia is the frequency of smoking among women higher than in Hungary (1). Young girls start smoking very early and are often addicted smokers by the time they reach young adulthood. The prevalence of tobacco smoking among women aged 18-44 is 30.8% in Hungary (2). The level of education and the mother’s active employment influence smoking cessation (3). Tobacco use and exposure to secondhand smoking is extremely dangerous for the mother and the foetus. Smoking contributes to premature birth (< 37 weeks gestation), low birth weight (< 2500 grams) (4). In 2009 Hungary’s preterm births (PTB) and low birth weight (LBW) frequency (8.7% and 8.4%) was well-above the average of the European Union (EU), which was 6% (4, 5). In addition, 85% of the morbidity among newborn babies is due to PTB and/or LBW. The frequency of developmental disorders, stillbirth and other infant conditions (6), and the incidence of SIDS are growing (7).
In our study we aimed to identify socioeconomic factors that predicted smoking prior to pregnancy among mothers who gave birth to babies in the two least developed counties in Hungary (Borsod-Abaúj-Zemplén = BAZ, and Szabolcs-Szatmár-Bereg = Szabolcs) in 2009.
Material and methods
Our research was approved by the Ethical Committee of Semmelweis University. In the two countries mentioned above, mothers who gave birth to live babies between January 1, 2009 and December 31, 2009 were invited to participate in our research. The final sample was 9,040 mothers, which represents 71.1% of all mothers (N = 12,732) of live birth cases in these two counties. It means 9.4% of all live births (96,442) in Hungary during 2009. Mothers were informed about the aims of the research and the method we applied, and they provided formal consent to participate.
Data were obtained from medical records of obstetrical wards and through in-person interviews administered by the local maternity and child service.
Demographic, Social and Economic status: we measured the mothers’ age groups (years < 18, 18-34, 35-40, 41+), ethnicity (self-admitted as Roma or non-Roma), body mass index (BMI = kg/m2) converted to a categorical variable (underweight = <18.49, normal weight = 18.5-24.9, overweight = 25-29.9, obese = 30 or greater), level of education (less than 8 grades of primary school, completed 8 grades, secondary education, college and/or university), employment status (employed, unemployed, varia as students, disabled, on social benefit), marital status (married, non-contractual cohabitation, separated or divorced, single or widowed), number of children converted also to 3 categories (1-2, 3-6, 7-13), and dwelling circumstances (full, partial amenities and without basic amenities [running water, indoor plumbing, and heat]). Level of income/capita was determined by comparing the self-reported family income with data of the Central Statistical Office (CSO). Thus, the upper limit of deep poverty is reached if there are two children and two employed adults in the family and the income per capita is less than half of the average income per capita of the relevant year (8, 9). Poverty means 50-80%, at poverty level 80-120%, sufficient 120-170% and wealthy above 170% of this level.
Health Behaviours: dietary habits related to fresh fruits, vegetables, dairy and meat products in 4 categories of consumption were measured (at least once a day, every other day, once or twice a week, less than once a week). Coffee and alcohol (wine and beer) consumption were measured in 3 categories (coffee: at least every other day, 1-2 times a week and seldom or never, alcohol: at least once a week, less than per week, and never).
Descriptive statistics (means, standard deviations, 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 socioeconomic and health behavior status to smoking prior to pregnancy. Results are reported in odds ratios (ORs) and 95% confidence interval (CI). All data were analysed using SSPS (19.0) statistical program.
Results

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Piśmiennictwo
1. Shafey O, Eriksen M, Ross H, Mackay J: The Tobacco Atlas. 3rd edition. (Table A The Demographics of Tobacco). The American Cancer Society, Atlanta 2009. 2. Tombor I, Paksi B, Urbán R et al.: Dohányzás elterjedtsége a Magyar felnőtt lakosság körében. (Prevalence of Smoking among the Hungarian Adult Population). Népegészségügy 2010; 88 (2): 131-136. 3. Foley KL, Balázs P, Grenczer A, Rákóczi I: Factors Associated with Quit Attempts and Quitting among Eastern Hungarian Women who Smoked at the Time of Pregnancy Cent Eur J Public Health 2011; 19 (2): 63-66. 4. Élveszületési adatok az anya tényleges lakóhelye szerint, (Livebirth Data Based on the Real Residence of the Mother), KSH, Tájékoztatási adatbázis, Népességstatisztika, Népmozgalmi adatok, 2009. http://statinfo.ksh.hu/Statinfo/themeSelector.jsp?page=1&theme=WD (2011.11.28). 5. Perinatal Statistics in the Nordic Countries, http://www.stakes.fi/EN/tilastot/statisticsbytopic/reproduction/perinatalreproductionsummary.htm (2011.11.28). 6. Páll G, Valek A, Szabó M: Neonatalis Intenzív Centrumok tevékenysége 2005-2009 között. (The Actions of NICU between 2005 and 2009). Budapest, Országos Gyermekegészségügyi Intézet 2011. 7. Wisborg K, Kesmodel U, Henriksen TB et al.: Prospective Study of Smoking during Pregnancy and SIDS. Arc Dis Child 2000; 83(3): 203-206. 8. A Kormány 321/2008. (XII. 29.) Korm. Rendelete a Kötelező Legkisebb Munkabér (minimálbér) és a Garantált Bérminimum Megállapításáról (Government of Hungary: Regulation on Guaranteed Minimal Income), Munkaügyi Fórum, http://www.munkaugyiforum.hu/archivum/minimalber-2009 (2012.01.15.). 9. KSH: Létszám és kereset a nemzetgazdaságban, gyorstájékoztató, (Number of Employees and Wages and Salaries in National Economics) Budapest, 2009. január–december. http://portal.ksh.hu/pls/ksh/docs/hun/xftp/gyor/let/let20912.pdf. 10. Csépe P: Hátrányos helyzetű csoportok egészségfelmérése és egészségfejlesztése különös tekintettel a roma populációra. (The Measurement of the Health Status and Health Development of Disadvantaged Groups). PhD. Dissertation, Budapest, Central Library of the Semmelweis University, 2010. 11. Janky B: A korai gyermekvállalást meghatározó tényezők a cigány nők körében (Factors Determining Early Willingness to have Children among Roma Women). Andorka Rudolf Emlékkonferencia BCE, Budapest 2006. október 10. 12. Balázs P, Foley KL, Grenczer A, Rákóczi I: Roma és nem-roma népesség egyes demográfiai és szocioökonómiai jellemzői a 2009. évi szülészeti adatok alapján (Hungary’s Roma and Non-Roma Population in Obstetrical Statistics in 2009: Demographic and Socioeconomic Characteristics) – Magyar Epidemiológia, 2011; 8: 67-75. 13. Foley KL, Balázs P: Social Will for Tobacco Control among the Hungarian Public Health Workforce. Cent Eur J Public Health 2010; 18(1): 25-30.
otrzymano: 2012-05-07
zaakceptowano do druku: 2012-05-25

Adres do korespondencji:
*Andrea Fogarasi-Grenczer
Semmelweis University Faculty of Health Sciences
17 Vas St. 1088 – Budapest, Hungary
tel.: +36 1 284 2792
e-mail: grenczera@gmail.com

New Medicine 2/2012
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