1. 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 Data were obtained from two sources: 1) Medical records of obstetrical wards and 2) In-person interviews
Data were analyzed by SPSS ( ) 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,
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
[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 TW 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