Methods

The present report is a part of the results of a broad study titled, “Development of Mother’s Lifestyle Scale during Pregnancy with an Approach to Social Determinants of Health and communicative model between Mother’s Lifestyle during Pregnancy with Low Birth Weight”. Two methods were used in this study: methodology for the purpose of designing the instrument, and case-control for determining and presenting the correlation model. Within four stages, the study was performed on 750 mothers of infants with birth weight lower than 4000 g using the multistage sampling method.

In the first step of the study, the researchers designed an instrument for measuring lifestyle factors from the perspective of determinants of health and examined their psychometrics through face, content, criterion, and construct (exploratory factor analysis) validity. The questionnaire consisted of 132 items in 10 parts. Three parts were related to general specifications, history of the pregnancy, and laboratory results in medical records. The remaining seven parts included physical activity, occupation, nutrition, control of stress, self-care, social relations, and inappropriate health-related behaviors. The questionnaire was scored using the Likert scale (1–5) and metabolic equivalent of task (MET), and its high internal consistency was confirmed upon calculation of the Cronbach’s alpha (0.76).24

The participants of this study were Iranian pregnant women who went to selected hospitals for delivery between May 2012 and March 2013. They were aged 15–45 years, and were at a gestational age of 37–42 weeks based on their first day of last menstruation (LMP) or ultrasound. The inclusion criteria of the study were as follows: being willing to participate in the study, having no medical conditions (such as multiple fetuses, cardiovascular diseases, diabetes, renal diseases, thyroid diseases, pulmonary diseases, autoimmune diseases, preeclampsia, placental abruption, premature rupture of membranes during or after delivery, hepatitis, AIDS, and TORCH syndrome), using no medications that could affect birth weight, and giving birth to a living and normal infant weighing less than 4000 g.

Tehran was divided into five regions (North, South, East, West, and Central), one hospital (affiliated with a university or the Social Security Organization) was selected randomly in each region. Then, a total of 750 participants were selected proportionate to the delivery statistics of each hospital.

The researchers started the study upon receiving permission from the authorities of the university and selected hospitals, providing necessary explanations to the participants, and gaining their consent. The questionnaire was completed by a trained team. To do so, mothers with inclusion criteria in the delivery ward were identified and monitored up to delivery. The researcher or a questioner was present in the delivery room during delivery and recruited the mother if the infant did not have any medical problems and his/her weight was less than 4000 g according to the scale in the delivery room. Once the mother was transferred to the postpartum ward, informed consent was received from her if she was in a suitable condition and was willing to participate in the study. Then, questions related to laboratory results, ultrasound results, and the mother’s medical history were completed using her medical records. Questions on demographic specifications and lifestyle were completed via an interview with the mother. During the 11 months of sampling, all deliveries at the selected hospitals (851 in total) were examined. Some deliveries were excluded [Figure 2], and sampling was stopped when the sample size reached 750.

In this study, the fit of the theoretical model determining the correlation of concurrent structural determinants and mothers’ lifestyles during pregnancy with LBW [Figure 1] was examined using path analysis.

Path analysis is a generalization of the conventional regression analysis, which shows the indirect effects beside the direct effects and the effect of each variable on dependent variables. The results of path analysis can be used to provide a reasonable interpretation of relationships and correlations observed between variables of the study. The data were analyzed in SPSS Statistics (SPSS Inc. Released 2007. SPSS for Windows, Version 16.0. Chicago, SPSS Inc.) and Lisrel software version 8.8 (Lincolnwood, IL: Scientific Software International, Inc.) using logistic regression, T-test, and path analysis.

Results

The two groups (the control group of 500 mothers with infants weighing 2500–4000 g, and the case group of 250 mothers with infants weighing less than 2500 g) were not significantly different in terms of the following variables: mean age, gestational age, birth spacing, age at marriage, history of having a LBW infant, miscarriage and stillbirth, mean weight before pregnancy, body mass index (BMI), hemoglobin (HB), and hematocrit (HCT). The groups were matched in terms of the above variables. However, the two groups were significantly different when considering the mother’s mean weight gain during pregnancy (p = 0.002), educational level (p = 0.030), family size (p = 0.002), number of pregnancies (p = 0.007), husband’s support during pregnancy (p < 0.001), and husband’s occupation (p < 0.001) [Table 1]. In this respect, the logistic regression was used to determine the correlation between dimensions of lifestyle and birth weight in the presence of the above variables.

Based on the results, the most influential dimensions of lifestyle were the occupational lifestyle and social relations of mothers, as an increase in the score of a mother’s occupational lifestyle by one point resulted in an increase in the risk of LBW by 2.01 (p < 0.001). However, an increase in the score of a mother’s social relations by one point resulted in a decrease in risk of the LBW by -0.08 (p < 0.001) [Table 2].

Bivariate analyses were used to examine the correlation between variables for path analysis. According to the results, birth weight significantly and directly correlated with educational level, weight gain, nutrition, self-care, and mother’s social relations. There was a significant and indirect correlation with husband’s support, the level of activity at home, the total level of activity, occupational lifestyle, and mother’s stress level (p < 0.050) [Table 3].

The path analysis examined the effect of sociodemographic variables (structural determinants) and lifestyle dimensions (an intermediate determinant) on the birth weight [Figure 3].

According to the path diagram, the mothers’ weight gain (β = 0.17) and education level socioeconomic factor were the most influential structural determinants of birth weight. Of the lifestyle dimensions, occupational lifestyle, stress, self-care, and social relations were influential in birth weight both directly and indirectly. Occupational lifestyle (β = -0.263) and social relations (β = 0.248) had the highest effect on birth weight. In this regard, an unfavorable occupational lifestyle during pregnancy decreased birth weight, and favorable social relations increased birth weight. Nutrition
(β = 0.30), inappropriate health-related behaviors
(β = -0.002), and self-care (β = -0.015) were influential in birth weight indirectly from one path. In the proposed model, 42% of the variance of LBW was justified by the variables affecting birth weight [Table 4].

The fitted model did not differ from the conceptual model significantly, and fit indexes of the model showed the desirability, high fit of the model, and reasonable relationships of the variables adjusted on the basis of the conceptual model [Table 5].

Table 5: Goodness of fit indices, n = 750.

RMSEA: root mean square error of approximation; GFI: goodness of fit index; NFI: normed fit index; CFI: comparative fit index; IFI: incremental fit index; df: degrees of freedom; X2: chi-square.

Discussion

A mother’s occupational lifestyle showed the maximum effect in reducing birth weight among other factors that both, directly and indirectly, affect birth weight. Occupational lifestyle indirectly affected birth weight in that it affected the stressful conditions and, subsequently, the inappropriate health-related behaviors, nutrition, and mothers’ weight gain during pregnancy. In other words, if mothers’ occupational conditions are unfavorable, they will be influenced directly by the occupational problems and indirectly by the risk of increased stress and are more likely to give birth to LBW infants. Therefore, the occupational lifestyle is not only a risk factor but also a very powerful determinant of LBW because it affects birth weight both directly and indirectly and through other intermediate factors. Other studies also stated that a mother’s occupation and its relevant factors correlated to the adverse outcomes of pregnancy, including LBW.25–28 The occupation type and working conditions depend on the socioeconomic status of the family, skills, reputation, and mother’s social class. People with lower skill levels or education, or lower social class are more exposed to unfavorable working conditions, including the physical pressures, low occupational control, noise, air pollution, work shifts, fatigue, long working hours, lifting loads, standing, and heavy physical work. Moreover, these mothers make less income than those working at better jobs and men. The material deprivations and economic inequalities due to unfavorable work conditions including poor nutrition, poverty, and inappropriate housing conditions and income, impact the incidence of chronic and mental diseases through psychosocial factors, lifestyle behaviors, and physiopathological changes.29

A mothers’ social relations during pregnancy were another factor with the highest total effect on birth weight. Social relations affected birth weight indirectly through reducing the stressful conditions and increasing self-care. In their study, Soogheh et al,30 found that poor social relations during pregnancy increased the risk of LBW babies as much as four-times. The researchers accepted two theories regarding the effect of social relations on health: control of stress and the model of major effect. In the model of major effect, social relations directly affect health with protective and preventive effects. For example, biological effects and emotional behaviors that are not explicitly considered as a supporter help, directly affect health. In the stress-buffering model, favorable social relations (e.g., such as feeling happy and satisfied, feeling worthwhile, perceived sympathy, and compatibility with others) affect people’s health indirectly. Therefore, social relations affect health directly and indirectly.31,32

Among the structural determinants of birth weight, the underlying factor of mothers’ weight gain and the socioeconomic factor of mothers’ education influenced birth weight the most.

Inappropriate weight gain during pregnancy reflects the deficiency of nutrients essential for the fetus. Mothers are the only source of nutrition for a fetus, and if mothers do not have favorable nutrition for any reason, their fetus does not receive essential nutrients for their growth. Regardless of genetic factors, mothers’ weight gain during pregnancy leads to an increase in infants’ birth weight, that is, there is a direct correlation between mothers’ weight gain during pregnancy and birth weight.33 This variable is under the influence of different factors, including poor socioeconomic conditions of mothers.34 Adlshoar et al,10 found that mothers in low-income families did not have good nutrition because they could not buy the necessary foods, and this situation interfered with mothers’ weight gain during pregnancy and resulted in more LBW infants.

The educational level is considered the most fundamental socioeconomic factor because it affects future occupational opportunities and income. This variable can prevent the adverse outcomes of pregnancy through educational experiences and skills, such as improving the home environment, nutrition, self-care, and cognitive stimulation. Thus, it is considered a very important determinant of birth outcomes.35 The immediate results conformed to that of many studies. Kehinde et al,36 found that mothers’ educational level was more influential in LBW than fathers’ educational level.

One of the strengths of this study was matching the study groups for confounding factors, including gestational age, mothers’ age, birth spacing, age at marriage, history of having a LBW infant, miscarriage and stillbirth, mean weight before pregnancy, BMI, HB, and HCT. Mothers, especially those with natural delivery, are admitted to hospitals for a short time, and this resulted in the collection of data in a short time after delivery in the postpartum ward. Therefore, mothers’ fatigue and forgetting some things over time might have affected their answers and was a limitation of this study.

Conclusion

The review of lifestyle dimensions showed that all of the dimensions directly, indirectly, or both affected birth weight. Thus, given the importance and the role of lifestyle as an important determinant affecting birth weight, attention, and training interventions are important to promote healthy lifestyles in pregnant women.

Disclosure

The authors declared no conflicts of interest. No funding was received for this study.

Acknowledgements

The present study was approved by the Ethics Committee of the University of Social Welfare and Rehabilitation on December 4, 2011. We would like to thank the research deputy of the university, the head of the research center for social determinants of health, and all the participants for their cooperation.

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