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ORIGINAL RESEARCH |
From the Division of Reproductive Health, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta; Children’s Healthcare of Atlanta, Atlanta; and TRW, Inc., Atlanta, Georgia.
Address reprint requests to: Indu B. Ahluwalia, MPH, PhD Division of Reproductive Health National Center for Chronic Disease Prevention and Health Promotion Centers for Disease Control and Prevention 4770 Buford Highway, NE Mailstop K-22 Atlanta, GA 30341-3717 E-mail: iahluwalia{at}cdc.gov
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Abstract |
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Methods: We used data from the Pregnancy Risk Assessment Monitoring System to conduct the research. Pregnancy Risk Assessment System is a population-based, mixed-mode surveillance system that collects information on maternal behaviors and experiences. We used data for 1997 from 13 (n = 19,331) states that had response rates of over 70%. We considered ten self-reported individual risk behaviors or exposures (eg, smoking, unintended pregnancy) and several demographic variables. The main outcome was SGA.
Results: Pregnant women engage in or are exposed to multiple risks and often these risks are inter-related. The occurrence of multiple risks appears to be associated with an increased likelihood of delivering an SGA infant. Compared with women with no reported risks or exposures, the adjusted odds ratios for delivering an SGA infant were as follows: 1.29 (95% confidence interval [CI] 0.69, 2.43) for one, 1.86 (95% CI 1.00, 3.44) for two, 1.67 (95% CI 0.90, 3.10) for three, 2.06 (95% CI 1.10, 3.89) for four, 3.53 (95% CI 1.71, 7.30) for five, and 3.82 (95% CI 1.97, 7.41) for six or more risks or exposures.
Conclusion: A large proportion of pregnant women engage in or are exposed to multiple risks. Women with a larger number of risks are at greater risk for delivering an SGA infant than women with fewer or no risks.
Pregnancy-related experiences and pregnancy outcomes are affected by various behavioral, psychosocial, demographic, and environmental factors.1–10 Maternal behaviors during pregnancy, such as tobacco and alcohol use, inadequate nutrition, and late entry into prenatal care, affect birth outcome and are known to affect the infant.2,9–13 Psychosocial factors that may influence pregnant women include their interactions with others, such as experiencing physical abuse, pregnancy intention, availability of social support, social stability, feelings of helplessness, social participation, and experiencing multiple stressful life events during pregnancy.8,14–20 Many studies have examined the individual effects of these behavioral risks, and a few studies have examined the occurrence of multiple risks simultaneously during pregnancy, which may affect both the pregnancy itself as well as the birth outcome and subsequently the infant.8,15–22 For example, several studies have reported that women who smoke cigarettes during pregnancy are more likely to use illicit drugs, experience stressful life events, experience physical violence, and report that their pregnancies were unplanned; women with unplanned pregnancies are less likely to recognize pregnancy-related signs and symptoms, which may delay their entry into prenatal care; and women who are living in impoverished environments may experience feelings of helplessness.10,17–22 These studies appear to suggest that multiple risks occur during pregnancy and that the risks may be inter-related, but no studies have examined the prevalence of multiple risks among pregnant women and their distribution or impact on small for gestational age (SGA) births on a population basis.
Women who engage in or are exposed to one risk behavior may be more likely to engage in or be exposed to other types of risks. Several behavioral and conceptual frameworks have outlined the influence of multiple risk factors and their interacting effects on determining the health status, and these range from individual behaviors to the social and physical environments in which they live.23,24 Behavioral and other frameworks are important in conceptualizing the various influences on women’s health during pregnancy.
Jessor’s problem behavior theory provided the framework for this study. This theory suggests that multiplerisk behaviors may occur as a function of a single behavioral syndrome.23 These risk behaviors may be clustered within certain groups of individuals, and this approach suggests that understanding the occurrence of an array of behaviors or exposures may give rise to and sustain intervention efforts that may improve pregnancy experiences and, potentially, birth outcomes of women. In addition to the risk exposures, one needs to consider the multiple influences of social environments and their impact on determining the health of pregnant women and their infants.23 Both theoretical and conceptual frameworks are important not only for examining the occurrence of multiple-risk behaviors but also for designing tailored and targeted interventions for pregnant women that take into account their circumstances, cultural background, environments in which they live, and resources/opportunities available to them. These factors may determine pregnant women’s predisposition for engagement in risky behaviors or exposures.
The purpose of this study was to examine the occurrence of both individual and multiple risks or exposures among women with recent deliveries and to examine their impact on birth outcome such as SGA.
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Materials and Methods |
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We developed measures to examine the specific risks women were engaged in or exposed to during pregnancy. Individual behaviors considered were cigarette smoking, alcohol use, inappropriate weight gain, late or no prenatal care, experience of physical abuse, unintended pregnancy, and experience with four different types of stressful life events such as partner-associated stress, traumatic stress, financial stress, and emotional stress. All of these items were from the Pregnancy Risk Assessment System survey. Although the Pregnancy Risk Assessment System survey was our primary source of data, we also used a selected set of variables from the birth certificates (eg, race/ethnicity, maternal education, parity, infant gender).
Responses to the questions on the survey were used to develop the study measures. Information on tobacco and alcohol use during pregnancy is collected within the context of the last 3 months of pregnancy on the Pregnancy Risk Assessment System survey. Cigarette smoking was defined dichotomously—a woman smoked or did not smoke during the last 3 months of pregnancy. Alcohol use was defined as any use compared with no use during the last 3 months of pregnancy. Weight gain appropriate for a woman’s BMI was defined by using the information on total weight gain during pregnancy and the woman’s prepregnancy weight and height.11 The BMI categories were underweight (BMI less than 19.8), normal (BMI 19.8–<26), overweight (BMI 26–29), and obese (BMI over 29). The recommended weight gain for each of these categories is 28–40 pounds for women with BMI less than 19.8; 25–35 pounds for women with BMI 19.8–26; 15–25 pounds for women with BMI 26–29; and 15 pounds for women with BMI over 29.11 If the weight gain was equal to or greater than the amount recommended for the BMI, then a woman was classified as having gained the recommended amount or more; otherwise, she was classified as having gained less than the recommended amount of weight for her BMI. Experience of physical abuse was categorized as a dichotomous variable; experience of physical abuse by anyone during pregnancy was classified as yes or no physical abuse; pregnancy was also defined as a dichotomous variable. Whether or not an unintended pregnancy was defined as a pregnancy for which the woman either did not want to be pregnant or desired to be pregnant later, and intended pregnancy meant that she wanted to be pregnant when she conceived.
Information on a woman’s experience with stressful life events 12 months before delivery was measured by using 13 individual items that were on the survey. These items were selected and evaluated by the Pregnancy Risk Assessment System team before inclusion into the survey, and these items were derived from an existing life event inventory list. Each item was coded as a yes-or-no variable. To develop meaningful constructs or to identify items that may be representing similar underlying experiences from the individual items, we performed principal component analysis. The purpose of principal component analysis is to identify items that are measuring the same underlying construct (eg, financial stress), and our analysis indicated that the 13 items loaded on four conceptually distinct constructs. The loadings refer to how the individual items correlated with other similar items in the empirically driven measure. It is an indication of the strength of the association among the items that may be related in some way, which individual items may not capture. Three items (partner did not want pregnancy, arguing with partner more than usual during pregnancy, and separation or divorce from a partner) with loadings of over 0.55 were defined as partner-associated stress; four items (woman or partner went to jail, woman was involved in a physical fight, woman became homeless, and someone close to the woman had a problem with alcohol or illicit drug use) with loadings of 0.49 were defined as traumatic stress; four items (woman lost her job despite wanting to work, woman had a lot of unpaid bills, husband or partner lost job, and woman moved to a new address) with loadings of 0.50 were defined as financial stress; and two items (family member ill or hospitalized and someone close died) with loadings of 0.80 or more were defined as emotional stress.
Once the four measures were developed, we examined the strength of association or 
level of each measure with multiple items. The levels for the four constructs were 0.53 for partner-associated stress, 0.49 for traumatic stress, 0.50 for financial stress, and 0.53 for emotional stress. The individual items in these domains were summed and then categorized as dichotomous variables (eg, emotional stress was present if any items were checked yes and was not present only if all items were checked as no) to be consistent with other risks that were categorized dichotomously.
We considered a number of demographic variables in the analysis, including mother’s age, race, education, marital status, parity from the birth certificate, and enrollment in the Special Supplemental Nutrition Program for Women, Infants, and Children and Medicaid from the survey. We divided age into five categories (under 20, 20–24, 25–29, 30–34, and 35 and over). We coded race as white, black, and other. Maternal education included three categories: less than high school, completion of high school, and more than high school. We coded marital status as married or not married, and we categorized parity into three groups (no previous live births, one previous live birth, and two or more previous live births). The two service-use variables, participation in programs such as the Special Supplemental Nutrition Program for Women, Infants and Children and Medicaid, were defined as dichotomous variables. We considered these variables to be proxy variables for low-income status as no consistent income data were available. In addition, we examined the state of the mother’s residency to assess whether the overall risk varied by geography, and we adjusted for the state in the multivariable analysis.
The outcome considered in this analysis was SGA deliveries. We used the clinically estimated date of delivery along with the date of the last menstrual period to estimate the length of pregnancy.26 The acceptable birth weight of infants was identified according to gender, ethnicity, gestational age, and the acceptable birth weight range reference.27 Once the acceptable birth weight and gestational age were identified, we categorized SGA infants as less than the 10th percentile of birth weight for gestational age by gender.28 The SGA variable based on the characteristics of the mother and the infant is a valid measure of pregnancy outcome and is increasingly used by researchers examining multiple psychosocial and lifestyle influences on birth outcomes.8,29
We investigated the association between SGA birth, demographic factors, and occurrence of individual and multiple risks or exposures. First, we used the Spearman rank correlation coefficient to examine the correlations among the ten risks and exposures. To examine the occurrence of multiple risks, we summed the ten individual risks (less than recommended weight gain, alcohol use, tobacco use, late or no entry into prenatal care, experience of physical abuse, having an unintended pregnancy, partner stress, emotional stress, traumatic stress, and financial stress). Inherent in this approach is an assumption that all risk behaviors have an equal value in determining the index score.
We used software for survey data analysis (SUDAAN Research Triangle Institute, Research Triangle Park, NC) to estimate percentages and standard errors, and to generate prevalence estimates, their standard errors, and to perform multivariable analysis. We used Statistical Analysis Software (SAS Institute, Cary, NC) to perform principal components and correlation analysis to develop measures from individual variables.
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Results |
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Examination of the individual risks and exposures showed approximately 14% of the women reported smoking cigarettes during the last 3 months of pregnancy, 6% reported drinking alcohol, 31% gained less than the recommended weight for their BMIs, 23% entered prenatal care after the first trimester or did not enter prenatal care at all, 45% reported the pregnancy was unintended at the time it occurred, 5% reported experiencing physical violence during pregnancy, 38% reported partner-associated stress, 36% experienced emotional stress, 23% experienced traumatic stress, and 57% experienced financial stress (Table 1
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). To fully understand the independent influence of maternal characteristics and behaviors or exposures, we examined the results of multiple logistic regression. These results with demographic and individual risks or exposures showed that the mother’s race or ethnicity, parity, maternal smoking, weight gain, and state of residence were significant predictors of SGA delivery.
Because the goal of this research was to investigate the occurrence of multiple risks and their collective influence on SGA deliveries, we first examined the correlation among the ten individual risks and exposures. Some variables were highly correlated and others were correlated moderately or not at all. The range of Spearman rank correlation coefficient varied from 0.001 indicating little or no correlation to 0.34 indicating moderate association. The range for the Spearman rank correlation coefficient for tobacco use was from 0.06 with emotional stress to 0.19 with traumatic stress; all values were statistically significant. Experience of physical abuse was correlated with partner-associated stress (Spearman rank correlation coefficient 0.22) and traumatic stress (Spearman rank correlation coefficient 0.32). Pregnancy intention was correlated with partner-associated stress (Spearman rank correlation coefficient 0.25), traumatic, and financial stress (Spearman rank correlation coefficient 0.16). After we examined the correlation coefficients for all ten variables, we created an index that ranged from zero risks to six or more risks with these measures. We had to truncate the index at six or more risks because there were small numbers in the categories above six. Approximately 10% of the women were in the zero risk category, 19% engaged in or were exposed to one risk, 21% had two risks, 19% had three risks, 14% had four risks, 10% were in the five-risk group, and 7% reported engaging in or exposure to six or more risk behaviors. Table 2 shows the distribution of multiple risks by demographic factors. Black women, women less than 25 years of age, women who had less than a high school education, unmarried women, women with two or more children, and women enrolled in the Special Supplemental Nutrition Program for Women, Infants, and Children and Medicaid were significantly more likely to report engaging in or being exposed to a greater number of risks.
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). Unadjusted estimates show there was an increase in the SGA births with an increasing number of risks or exposures, eg, women with four risks or exposures (OR 1.98, 95% CI 1.10, 3.57), five (OR 3.68, 95% CI 1.82, 7.43), and six or more (OR 4.18, 95% CI 2.26, 7.74) risks compared with women experiencing no risks or exposures (Table 3). The association was examined while adjusting for several demographic variables, and the results show that compared with women who were in the zero-risks or exposures category, women with four (OR 2.06, 95% CI 1.10, 3.89), five (OR 3.53, 95% CI 1.71, 7.30), and six or more risks (OR 3.82, 95% CI 1.97, 7.41) were significantly more likely to experience an SGA birth. Women in the one-to-three risk or exposure categories appear to have an elevated risk; however, the 95% CIs overlap one in these groups.
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Discussion |
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This study has several limitations. First, the findings are subject to recall bias because items on the Pregnancy Risk Assessment System survey were self-reported by women several months after delivery. Smoking status may be underestimated, and we did not have biomarkers to validate self-reports. Women’s reports of whether they smoked during pregnancy have been found to be accurate, but reports of the actual amount smoked may be somewhat less accurate.33 Second, the principal components analysis yielded moderate values (0.49–0.53) for the stressful experience variables, primarily because of the limited number of items capturing the underlying constructs of stress; therefore, these results may need to be interpreted with caution. Information about stressful life events covered the 12 months before delivery, and no information was available for changes that may have occurred during pregnancy or about the woman’s appraisal of these events and how she coped with the situations. Nonetheless, these measures are important to consider in terms of their associations with risk behaviors and exposures (smoking, adequate nutrition, appraisal of and coping with stressful situations, and adherence to medical advice), which directly and indirectly affect pregnancy and birth outcomes. Another potential limitation is the assumption that each item in the risk index is of equal value. We know from existing literature that smoking, for example, is one of the strongest predictors for adverse birth outcomes as compared to exposure to stressful life events, which may indirectly influence birth outcomes. Our research approach examined both issues and determined the independent predictors of SGA as well as multiple risk factors, including smoking, which may exert a cumulative effect. We believe that both approaches are useful ways of examining risk exposures during pregnancy.
Despite these limitations, the study has several strengths. The Pregnancy Risk Assessment System data set allowed us to examine a variety of risks and exposures among women with recent deliveries, and to establish the co-occurrence of multiple risks. This is one of the few studies to examine the effect of multiple risks on pregnancy outcome of SGA.
Our findings highlight the importance of examining individual as well as multiple risks or exposures during pregnancy. There may be a synergistic effect of multiple-risk behaviors that may not show up when one simply examines individual risks or exposures and their association with an outcome. We used a multivariable model to examine the individual predictors of SGA. The results showed that significant predictors of SGA were the mother’s race, parity, state of residence, smoking status, and weight gain. Although it is an important approach and has been used extensively to examine associations between risk factors and birth outcomes, it is equally important to develop a richer perspective on women’s predisposition during pregnancy by examining the co-occurrence of multiple risks or exposures. Our study has demonstrated that pregnant women are engaging in or are exposed to multiple risks that are often correlated with each other, and these risks affect SGA deliveries. For example, exposure to stressful situations may make it difficult for women to quit smoking, which directly affects birth outcomes and, potentially, a woman’s physical and mental health. The results indicate a need for care providers to assess an array of risks to devise appropriate and timely intervention strategies. Some risks, such as smoking cessation and adequate nutrition during pregnancy, may be more amenable to behavioral interventions, whereas other risks, such as those that involve a woman’s interactions with people in her social and cultural environment, may require counseling pregnant women to avoid harmful situations and/or linking women with community services, such as mental health, family planning, housing, nutrition, and support services. Some studies of low-income women have shown that enhanced services provided to at-risk pregnant women increased the use of prenatal care and other support services but they did not always result in improved birth outcomes.34–37 These studies focused on low-income women only, interventions varied, and they did not report on the pregnancy experiences of women, which also could be greatly affected by interventions targeting the risks women engage in or are exposed to during their pregnancies.
Our study suggests that women do engage in or are exposed to multiple risks during pregnancy and these have an impact on delivering an SGA infant. These findings indicate the occurrence of a behavioral syndrome in which multiple risks and exposures are common among pregnant women.22 These findings support the fact that a behavioral syndrome may be linked in some ways to the social environments in which pregnancy occurs.23 Likewise, our findings show that the occurrence of multiple risks and behaviors varies by race or ethnicity and a host of other demographic factors considered in this analysis, which further suggests that the social context in which pregnant women live influences their behaviors or exposures, and their behaviors or exposures in turn affect their social environments in which children are born. Constructs from specific theoretical frameworks such as Jessor’s problem behavior theory and others may be helpful in designing prenatal interventions that consider occurrence of multiple risk behaviors or exposures and their impact on birth outcomes such as SGA. Prenatal care providers have multiple opportunities to interact with pregnant women, and each opportunity can be used to assess women’s risks and their coping strategies/resources to further develop mutually acceptable and respectful strategies for dealing with their risks and exposures. Early recognition and assessment of not only individual behaviors but also multiple-risk behaviors and exposures are recommended along with strategies for targeting pregnant women in prenatal care and other health care settings to promote healthy pregnancies and better birth outcomes.
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Footnotes |
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Received August 23, 2000. Received in revised form December 12, 2000. Accepted January 12, 2001.
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References |
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