Pregnancy Intention and Health Behaviors: Results from the Central Pennsylvania Women's Health Study Cohort

Cynthia H. Chuang; Carol S. Weisman; Marianne M. Hillemeier; Eleanor Bimla Schwarz; Fabian T. Camacho; Anne-Marie Dyer


Matern Child Health J. 2010;14(4):501-510. 

In This Article


Study Design and Sample

The Central Pennsylvania Women's Health Study (CePAWHS) includes a population-based cohort study of reproductive-age women residing in Central Pennsylvania, a region that includes urban as well as rural and semirural areas. The primary objective of the CePAWHS longitudinal survey was to provide estimates of the prevalence of risk factors for preterm birth and low birthweight in the region and to assess how these risks change over time and are related to pregnancy outcomes.[8] The current study uses these longitudinal data to evaluate prevalence and patterns of change in participants' health behaviors, and determine whether they are affected by pregnancy intention as measured at baseline. CePAWHS was approved by the Institutional Review Board of the Penn State College of Medicine and conducted in accordance with prevailing ethical principles.

The baseline CePAWHS survey was a random-digit dial telephone survey of 2002 women ages 18–45, residing in a 28-county region of Central Pennsylvania, who were either English or Spanish-speaking. The sample was highly representative of the target population with respect to age, race/ethnicity, educational level, and poverty status. Details of the sampling methodology, response rate, and representativeness have been previously published.[8] At the time of the baseline survey, 90% of participants consented to future follow-up interviews; of these, 1,420 women completed a 2-year follow-up telephone survey for a response rate of 79%. The main reason for loss to followup was failure to locate women who had changed residence; only 5% refused the interview. Women were more likely to respond to the follow-up survey if they were older (ages 35–45), college educated, married or partnered, not in poverty, and non-Hispanic white; there was no significant difference in response by location of residence along the rural–urban continuum.

The analytic sample for this paper includes a subset of the respondents to the follow-up survey: non-pregnant women who had reproductive capacity at both baseline and follow-up. Thus, women were excluded if they were pregnant at baseline (n = 54), reported hysterectomy or tubal sterilization either before or during the study (n = 439), or reported infertility at the baseline interview (n = 75). These exclusions were necessary because these women would not be planning for a future pregnancy. An additional five women were excluded because they were missing either pregnancy intention or follow-up pregnancy data. This resulted in 847 women for this analysis.

Hypotheses and Definition of Variables

The CePAWHS survey instrument was developed from previously validated surveys on women's health, modified to meet the objectives of the CePAWHS project. Data on pregnancy history and future pregnancy intention, health status, health care utilization, sociodemographics, and health behaviors were among the survey measures. The main hypothesis was that future pregnancy intention is associated with positive longitudinal health behaviors; more specifically, women considering pregnancy in the next year would be improving health behavior (or maintaining healthy behavior). Secondary hypotheses were that prior experience with pregnancy, better health status, more contact with the health care system, and higher socioeconomic status are associated with positive longitudinal health behaviors.

The outcome variables were measures of health behaviors that have been shown to impact pregnancy outcomes, such as nutrition (fruit and vegetable consumption), folic acid supplementation, physical activity, alcohol use, smoking, and vaginal douching. The rationale for inclusion of each of the seven health behaviors and how healthy levels of behavior were defined is described here. Proper nutrition prior to conception and during pregnancy has been shown to improve pregnancy outcomes,[9–14] and daily fruit and vegetable consumption is recommended by the American Dietetic Association for preconceptional and pregnant women.[15] Thus, we considered consumption of fruit and vegetables at least once daily as healthy preconception behaviors. Folic acid supplementation has been shown to reduce the risk of neural tube defects.[16,17] The March of Dimes,[18] the American Academy of Pediatrics and the American College of Obstetricians and Gynecologists (AAP/ACOG),[19] the Institute of Medicine,[20] and the U.S. Public Health Service[21] recommend daily use of a multivitamin containing 400 mcg of folic acid in women capable of reproduction; we thus considered daily consumption of a multivitamin with folic acid as a healthy preconception behavior. Physical activity in the preconception period is important for achieving and maintaining a healthy weight, as maternal obesity is associated with numerous pregnancy-related complications.[22] Exercise has also been shown to decrease the risk of postpartum weight retention.[23] For healthy women before, during, and after pregnancy, ACOG recommends exercise at least 30 min a day on most, if not all, days of the week;[23] we thus used these guidelines as our definition of healthy preconception physical activity. Adverse effects of alcohol likely occur early in pregnancy (before a woman realizes she's pregnant) and no established safe level of alcohol consumption during pregnancy has been established. Alcohol is associated with preterm birth, miscarriage, growth retardation, and the fetal alcohol syndrome, making it the leading preventable cause of birth defects and developmental disabilities in the United States.[24–27] In view of the high prevalence of binge drinking (five or more drinks on an occasion) in the sample, we defined the absence of binge drinking in the past month as a healthy preconception behavior. Smoking has also been associated with numerous maternal and fetal complications, such as low birthweight, preterm birth, and intrauterine growth retardation;[28–31] we thus considered abstinence from smoking as a healthy preconception behavior. Vaginal douching was included since evidence suggests an association with preterm birth and adverse pregnancy outcomes.[32,33] No douching in the past 12 months was considered a healthy preconception behavior. For each of the seven behaviors, it was determined whether women were engaging in healthy levels of behavior at the baseline and follow-up time points.

For each of the seven health behaviors, we assessed whether the women were engaging in positive longitudinal behavior, defined as sustained healthy levels of behavior at both baseline and follow-up, or improved health behavior between baseline and follow-up (even if healthy levels were not met). For example, if a woman was not taking any folic acid supplements at baseline but was taking them twice a week at follow-up, that was considered positive longitudinal behavior for folic acid (even though she was not taking them daily, the recommended amount). Negative longitudinal behavior was behavior that remained unchanged at below healthy levels or declined from healthy to below healthy levels. Table 1 shows the longitudinal pattern for each of the seven health behaviors; overall, the most negative longitudinal behavior occurred for physical activity and folic acid supplementation, and the most positive longitudinal behavior occurred for binge drinking, vaginal douching, and smoking.

The main independent variable was pregnancy intention at the time of the baseline survey. Participants were asked, "Are you considering becoming pregnant within the next year, at some other time in the future, or not at all?" Future pregnancy intention was categorized as a three-level variable as per these responses.

Covariates included variables that were expected to influence the health behaviors of reproductive-age women. Pregnancy-related variables were reproductive life stage (preconceptional indicating never been pregnant and interconceptional indicating at least one previous pregnancy; women with a previous pregnancy were hypothesized to be more likely to engage in healthy behaviors); perceived severity of preterm birth/low birthweight for a baby's health (very serious risk versus somewhat serious/somewhat small/very small risk; those perceiving higher risk were hypothesized to be more likely to engage in healthy behaviors); and incident pregnancy occurring during the 2-year study (pregnant women were hypothesized to engage in healthier behaviors).

We included several health status variables to test our hypothesis that better health status would be associated with better longitudinal health behaviors. Baseline health status variables included overall self-rated health status as measured using the first item from the SF-12v2 Health Survey,[34] comparing those who report their overall health as excellent or very good versus good, fair, or poor. We included a measure for obesity (defined as a body mass index of 30 kg/m[2] or greater) and a chronic condition measure indicating whether the woman had received a diagnosis of diabetes, hypertension, or heart disease in the past 5 years. The Psychosocial Hassles Scale was used as a measure of psychosocial stress; this 12-item scale measures the degree to which common hassles (e.g., money worries, problems with friends) are perceived as stressful during the past 12 months. The scale was adapted from the Prenatal Psychosocial Profile Hassles Scale, which referred to stress during pregnancy, used by Misra et al.,[35] which in turn was adapted from the stress subscale of the Prenatal Psychosocial Profile developed by Curry et al.[36] For this analysis, the scale was dichotomized at the median value to indicate higher and lower measures of psychosocial stress. Depressive symptoms were measured using a 6-item scale assessing frequency of symptoms in the past week, based on the Center for Epidemiologic Studies Depression Scale;[37] the scale score was dichotomized to indicate high risk versus low risk for depression.[38]

We hypothesized that greater access to the health care system would be related to improved healthy behaviors. Baseline health care utilization variables were whether the participant had seen an obstetrician-gynecologist in the 2 years preceding the baseline survey, and whether she had received counseling by a doctor or other health professional in the past 12 months for none, 1–2, or 3–6 of the following health topics: smoking, diet, weight, exercise, alcohol, or planning for pregnancy.

Finally, we included sociodemographic variables to test our hypothesis that higher socioeconomic status is associated with better health behaviors. Baseline sociodemographic measures were age group (18–24, 25–34, or 35–45), race/ethnicity (non-Hispanic White versus other race/ethnicity), education (high school graduate or less versus some college or more), marital status (married or living with partner versus not partnered) and poverty status (defined as in poverty, near poverty, or not in poverty using U.S. Census definitions based on household income and composition). A proportion of participants (12%) had missing income data, either because they did not know, were not sure, or refused to report their household income. Further examination of the women with missing income data revealed that they were similar to women in the poverty and near poverty groups in terms of educational attainment and type of health insurance. This group of women who did not report their household incomes was treated as a separate category in the poverty status variable.

Statistical Analysis

Frequencies of the study variables were determined. Bivariate tests of the association of intention for future pregnancy with positive longitudinal behaviors were determined using Chi-square tests and simple logistic regression analysis. Multivariable logistic regression models were fit to predict the likelihood of engaging in positive longitudinal behavior for each of the seven behaviors, with baseline pregnancy intention as the independent variable of interest. The pregnancy-related variables, health status, health care utilization, and sociodemographic variables described above were also included in the models. We checked for multicollinearity among the independent variables. Likelihood ratio test P-values testing for overall significance are reported for each of the regression models (P-values#0.05 suggest the model is predictive of the outcome). All statistical analyses were performed on unweighted data using SAS software, Version 9.0 of the SAS System for Windows (SAS Institute Inc., Cary, NC, USA).


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