The Influence of Maternal-Fetal Attachment and Health Practiceson Neonatal Outcomes in Low-Income, Urban Women
Jeanne L. Alhusen, PhD, CRNP, RN,Morton and Jane Blaustein Post-doctoral Fellow in Mental Health and Psychiatric Nursing, JohnsHopkins University School of Nursing, Baltimore, Maryland
Deborah Gross, DNSc, RN, FAAN [Professor],Johns Hopkins University School of Nursing
Matthew J. Hayat, PhD [Assistant Professor],College of Nursing, Rutgers University, Newark, NJ
Anne B. (Nancy) Woods, PhD, MPH, CNM [Associate Professor], andMessiah College, Grantham, Pennsylvania
Phyllis W. Sharps, PhD, RN, CNE, FAAN [Professor]Johns Hopkins University School of Nursing
AbstractMaternal-fetal attachment (MFA) has been associated with health practices during pregnancy, butless is known about this relationship in low-income women, and no identified studies haveexamined this relationship to neonatal outcomes. This longitudinal descriptive study wasconducted to examine the relationships among MFA, health practices during pregnancy, andneonatal outcomes in a sample of low-income, predominantly African-American women and theirneonates. MFA was associated with health practices during pregnancy and adverse neonataloutcomes. Health practices during pregnancy mediated the relationships of MFA and adverseneonatal outcomes. The results support the importance of examining MFA in our efforts to betterunderstand the etiology of health disparities in neonatal outcomes.
Keywordsmaternal-fetal attachment; health-promoting behaviors; health disparities; African American; birthoutcomes
Disparities in neonatal outcomes between African-Americans and non-Latino WhiteAmericans are one of the most concerning and chronic health disparities affecting our nation(Alexander, Wingate, Bader, & Kogan, 2008). Many of the health disparities in pretermbirth, low birth weight (LBW) and other adverse pregnancy outcomes are more prevalent inethnic minority and low-income populations (Patrick & Bryan, 2005). Poor and African-American women have twice the rates of preterm births and higher rates of growth restrictedneonates than most other women (Mathews, Minino, Osterman, Strobino, & Guyer, 2011).LBW is a major determinant of infant mortality, and LBW neonates die at rates up to 40times higher than the risk in normal birth weight neonates (Goldenberg & Culhane, 2007).Furthermore, LBW neonates are significantly more likely to have short and long-term
Corresponding Author, Jeanne L. Alhusen, PhD, CRNP, RN, 511 N. Washington Street, Balitmore, MD 21205, 443-848-6066,[email protected].
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morbidities including delays in cognitive development and growth, and heightened risk ofcardiovascular and respiratory disease (Goldenberg et al., 2007). A significant body ofresearch has been devoted to better understanding the reasons for persisting racial disparitiesin neonatal outcomes, yet the causes remain largely unknown.
One factor known to influence neonatal outcomes is the health practices that a motherengages in during pregnancy. Positive health practices include abstaining from tobacco,alcohol, and other illegal substances; obtaining regular prenatal care; maintaining anutritionally-sound diet (Widen & Siega-Riz, 2010); obtaining adequate rest and sleep;engaging in regular exercise (Stutzman et al., 2010); and learning about pregnancy andchildbirth (Feinberg, Jones, Kan, & Goslin, 2010). Several variables that correlate withimproved health practices during pregnancy include higher socioeconomic status, higherlevels of education (Rubio, Kraemer, Farrell, & Day, 2008; Webb, Siega-Riz, & Dole,2009), and increased social support (Savage, Anthony, Lee, Kappesser, & Rose, 2007).Conversely, negative health practices during pregnancy, such as tobacco and substance use,are higher among young, unmarried, low-income women (Phares et al., 2004). Cigarettesmoking is one of the most preventable risk factors associated with adverse perinataloutcomes (Andres & Day, 2000).
Another factor thought to influence health practices during pregnancy is maternal-fetalattachment (MFA). Cranley (1981) created the theoretical construct of MFA and defined itas “the extent to which women engage in behaviours that represent an affiliation andinteraction with their unborn child” (Cranley, 1981, p.281). Higher levels of MFA correlatewith the aforementioned high-quality health practices (Lindgren, 2001, 2003). However,studies of the associations between MFA and health practices during pregnancy have largelyexcluded low-income, ethnic minorities (Alhusen, 2008). Furthermore, no longitudinalstudies were found of these variables in relation to neonatal outcomes.
An enhanced understanding of the role that MFA plays in neonatal outcomes of thosesubject to disparities, by virtue of race or socioeconomic status, is necessary to improveunderstanding of the relationship between health practices and adverse neonatal outcomes.Extant literature supports the influence of maternal health practices on neonatal outcomes,but less is known about factors that contribute to a woman’s ability to engage in thosepositive health practices.
This study was designed to examine the associations between MFA, health practices duringpregnancy, and neonatal outcomes in a highly vulnerable sample of predominantly African-American pregnant women reporting low educational attainment and low socioeconomicstatus. Preterm birth and LBW are key predictors of neonatal complications and mortality(Halfon & Lu, 2010; Lu et al., 2010; Oken, Kleinman, Rich-Edwards, & Gillman, 2003).Thus, in this study neonatal measures of birth weight and gestational age were collected.This longitudinal study addressed a significant gap in the current literature by examining thefollowing hypotheses:
After controlling for income, pregnancy wantedness, preeclampsia, and gestational diabetes:
1. Higher MFA will be negatively related to adverse neonatal outcomes.
2. Higher MFA will be positively related to improved health practices duringpregnancy.
3. Improved health practices during pregnancy will be negatively related to adverseneonatal outcomes.
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4. Health practices during pregnancy will mediate the relationship between MFA andadverse neonatal outcomes.
Theoretical ModelThe transition to motherhood is a major developmental life event. This transition requiresrestructuring goals, behaviors and responsibilities. This study of factors that facilitated orinhibited this transition drew from Rubin’s (1967) theory of maternal role attainment (MRA)as well as Mercer’s expansion on this theory, which she termed “Becoming a Mother(BAM)” (Mercer, 2004). Although both theories largely focus on processes necessary forthe establishment of maternal identity that occur once the child is born, Mercer’s first stage,which entails a commitment and attachment to the unborn baby, recognizes the long-termimplications of poor attachment (Mercer & Walker, 2006). A woman’s active involvementin this stage has been consistently linked to engaging in healthier behaviors that benefit boththe woman and her unborn child (Lindgren, 2001, 2003). Women demonstrating higherlevels of MFA are presumed to be more vested in taking care of themselves duringpregnancy in an effort to improve both the health of their fetus and pregnancy outcomes.Furthermore, researchers have suggested that prenatal attachment facilitates adaptation tothe role of motherhood and may even act as a protective factor against perinatal depression(Brandon, Pitts, Denton, Stringer & Evans, 2009).
The successful attainment of a maternal identity includes the development of an emotionaltie between the mother and unborn child as well as an innate desire to protect the unbornchild, later described as MFA (Cranley, 1981). This developmental and interactional processoccurs over time (Rubin, 1984). Maternal role attainment and subsequently BAMacknowledge barriers and facilitators to this process, and were therefore ideal theories todirect this study of MFA in a high-risk population where health disparities persist.
MethodsSample
A convenience sample of pregnant women from three urban obstetrical clinics in the MidAtlantic region were recruited for the study. The three clinics were all affiliated with a majoruniversity health system and all served predominantly poor (>95% receiving Medicaid),African-American (>95%) inner-city populations. To be eligible for inclusion in the study,participants had to be 16 years or older, between 24–28 weeks gestation with singletonpregnancies, and able to speak English. This gestational time frame was chosen as researchon MFA has demonstrated MFA increases as a pregnancy progresses, and this time periodmarks the beginning of fetal viability thereby allowing for accurate assessment of neonataloutcomes (Ramsay & Santella, 2010; Seri & Evans, 2008). Participants who met these initialcriteria were excluded if prior to data collection they had been treated with tocolytic therapy,diagnosed with pre-eclampsia or gestational diabetes, diagnosed with a chronic medicalcondition (e.g. chronic hypertension, diabetes mellitus), or received an abnormal diagnosticresult (e.g. known fetal anomaly, abnormal results on first or second trimester screeningtests) during the current pregnancy. Additionally, women reporting a history of fetal(spontaneous abortion after 24 weeks gestation) or infant death were excluded. Theseexclusion criteria were selected given their known contribution to adverse neonataloutcomes (Institute of Medicine, 1988;Mathews et al., 2011).
Of the 174 eligible pregnant women approached to participate, 167 (96%) completed thestudy instruments. One participant delivered at an outside hospital, which precluded ourability to obtain accurate birth outcomes. Therefore, the final sample consisted of 166 low-income women (93% African-American) receiving prenatal care from one of the three
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participating clinics and their neonates, resulting in a 95.4% participation rate. Of note, 84%of the sample initiated prenatal care by 14 weeks gestation, 96% by 18 weeks gestation, and100% by 24 weeks gestation. As seen in Table 1, the sample consisted of predominantlypoor, unmarried, African-American younger women.
Data Collection ProceduresInstitutional Review Board approval was obtained prior to participant recruitment. Eligibleparticipants were approached about enrollment in the study during their prenatal care visits.If a woman expressed an interest in participating, but had not reached 24 weeks gestation,her contact information was obtained. The first author re-contacted her and met with her tocomplete study instruments prior to a scheduled appointment that between 24 and 28 weeksgestation.
After a complete description of the study, informed consent was obtained from those womenwho agreed to participate. Participants were interviewed in a private space at each of thethree study clinic sites. Interviews lasted approximately 30 minutes. The interviews wereconducted by the first author or one of two undergraduate nursing students who receivedresearch compliance and study procedures training. Participants were compensated $15 fortheir participation. Measures related to neonatal outcomes (i.e., birth weight and gestationalage) were extracted from electronic chart review within 48 hours after delivery. Measuresspecific to maternal physical health risk factors (i.e. preeclampsia and gestational diabetes)were also extracted from electronic chart review during the same time period, in the eventthese risk factors developed after the initial data collection (Bodnar, Ness, Markovic, &Roberts, 2005; Catalano, Kirwan, Haugel-de Mouzon, & King, 2003).
MeasuresMaternal-fetal attachment—MFA was measured with the Maternal-Fetal AttachmentScale (MFAS; Cranley, 1981). The MFAS is a 24-item measure that asks women to respondto questions or thoughts indicative of MFA. The scale contains 5-point Likert-type itemswith response options ranging from 1 (definitely no) to 5 (definitely yes). Examples ofMFAS items include “I talk to my unborn baby” and “I do things to try to stay healthy that Iwould not do if I were not pregnant.” The total score ranges from 24–120 with higher scoresindicative of higher levels of MFA. This instrument is one of the most frequently usedmeasures of MFA in prenatal studies and has been used in diverse populations includingsamples of culturally diverse and low SES adolescents (Ahern & Ruland, 2003; Hart &McMahon, 2006; Lindgren, 2003). Content validity was assessed by an expert panel review.In a study of MFA in ethnic minorities a content validity index of .91 was found (Ahern &Ruland, 2003). The Cronbach’s alpha coefficient reported by Cranley (1981) was .85 and forthe current study was .88.
Health practices—The Health Practices in Pregnancy Questionnaire-II (HPQ-II;Lindgren, 2005) is a 34-item measure designed to address adequacy of health practices in sixareas: balance of rest and exercise, safety measures, nutrition, avoiding use of harmfulsubstances, obtaining health care, and obtaining information. In addition, 1 item addressesoverall pregnancy health practices. Responses range from 1 (never) to 5 (always or daily) ora word or phrase that indicates the woman’s level of engagement in a specific activity (e.g.,1- No alcoholic drinks while pregnant to 5- More than 3 alcoholic drinks at one sitting).Negatively worded items were reverse coded. Examples of HPQ-II items include “Sincebecoming pregnant I drink more than two caffeinated beverages in a day” and “Sincebecoming pregnant I have smoked cigarettes.” The total score ranges from 34–170 with ahigh score indicating a higher quality of health practices. Content validity was established
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by clinical experts and pregnant women (Lindgren, 2001, 2005). The Cronbach’s alphacoefficient reported by Lindgren (2003) was .81 and for the current study was .90.
Neonatal outcomes—Neonatal outcomes were collected from electronic chart review bythe first author. Two undergraduate nursing students collected neonatal data on a random25% sub-sample to assess inter-rater reliability. A kappa statistic of 1.0 was noted indicatingexcellent agreement (Landis & Koch, 1977). Neonatal outcomes collected included theneonate’s gestational age and birth weight. Small for gestational age (SGA) was calculatedusing comprehensive reference values of birth weight at 22 through 44 completed weeks ofgestation that were established by Oken et al. (2003) based on a national sample of over 6million infants. The presence of LBW (<2500 grams), preterm birth (<37 completed weeksgestation), or SGA (<10th percentile weight adjusted for gestational age) was coded as anadverse neonatal outcome during data collection.
Demographic and pregnancy background—A measure of demographic andobstetrical data was developed for use in this study. Demographic data included age, race,marital status, insurance status, employment status, educational history, and income status.Pregnancy history included an assessment of current and previous pregnancies (e.g., was thisa planned pregnancy; is this pregnancy wanted, unwanted or ambivalent; number ofprevious pregnancies, term births, number of therapeutic and/or spontaneous abortions, andnumber of live children).
Data AnalysisData were analyzed using PASW Statistics 18, Release Version 18.0.0 (SPSS: An IBMCompany). Data analysis began with descriptive and exploratory statistical analyses. Studyvariables were examined to assess distributions, to identify outlying or extremeobservations, and to determine the need for transformation. There were no missing data. Thesample size was based on an a priori power analysis with a specified power of 80% to detecta meaningful difference in MFA between participants delivering LBW neonates andparticipants delivering neonates >2500 grams. Pearson correlation, and point biserialcorrelation coefficients were calculated to address hypothesis 1–3. Mediation of therelationship between MFA and adverse neonatal outcomes by health practices duringpregnancy was tested with an analytic approach specific to dichotomous outcomes, using thebootstrap with biased-corrected confidence intervals (MacKinnon, Fairchild, & Fritz, 2007).Separate logistic regression equations were conducted sequentially to first examine therelationship between MFA and adverse neonatal outcome and then to determine the extent towhich health practices mediated this relationship. The level of significance was set at α = .05.
Neonatal outcomes were dichotomized as adverse outcome or no adverse outcome;therefore, multiple logistic regression was used to test the relationships between MFA,health practices, and neonatal outcomes. Because income and pregnancy wantedness wererelated to the outcome variable of an adverse neonatal outcome, they were included insubsequent regression analyses to control for their potential confounding effects. Incomewas dichotomized using the median of <$10,000 or >$10,000 total household income peryear. Pregnancy wantedness was dichotomized per participant’s response that the currentpregnancy was wanted or participant was ambivalent about current pregnancy. Additionally,gestational diabetes and preeclampsia were controlled for in the regression models, giventheir known contribution to adverse neonatal outcomes.
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ResultsAfter initial data collection, 7.8% (n=13) of study participants were diagnosed withpreeclampsia, and 1.2% (n=2) were diagnosed with gestational diabetes. Forty-one percent(n=68) of study neonates were classified as having an adverse outcome. Table 2demonstrates the number of neonates born with adverse outcomes of LBW, preterm birth,SGA, or a combination thereof.
The mean score on the MFAS was 84.1 (SD = 14.2, range 52 – 116), and the median was83.5. Analysis of the HPQ-II scores revealed a mean score of 121.2 (SD = 19.6, range 78 –159), and the median was 122.0.
Bivariate correlations, and point biserial correlations among the main study variables arepresented in Table 3. As hypothesized, there was a significant negative relationship betweenMFA and adverse neonatal outcomes supporting our first hypothesis. Health practicesduring pregnancy (mediator variable) was significantly related to MFA, the independentvariable, and adverse neonatal outcomes, the dependent variable thereby supportinghypotheses two and three, respectively.
The results of the logistic regression are shown in Table 4. In univariate logistic regression,MFA was regressed on adverse neonatal outcome and MFA was significantly related toadverse neonatal outcome; the odds ratio for this equation indicated that a one point increasein MFA was associated with a 9% decreased likelihood of an adverse neonatal outcome. Inthe second model, health practices was regressed on adverse neonatal outcome whilecontrolling for MFA and health practices was noted to be significantly related to adverseneonatal outcome , indicating that a one point increase in the health practices scale scorewas associated with a 9% decreased likelihood of an adverse neonatal outcome. Theproportion of the total effect of MFA on adverse neonatal outcomes mediated by healthpractices during pregnancy was 0.91. Additionally, the total indirect effect (−0.56) throughhealth practices was 10 times larger than the direct effect (−0.5) between MFA and adverseneonatal outcomes. The total indirect effect through health practices remained significantwith bootstrap analysis, while direct effects between MFA and adverse neonatal outcomeswere non-significant, suggesting complete mediation through health practices. Thus, thefourth hypothesis was also supported.
DiscussionTo our knowledge, this is the first study that provides strong support for the role that MFAplays both in health practices during pregnancy, and more importantly, in neonatal outcomesin a highly vulnerable population of predominantly African-American women from a low-income, urban community. Prior researchers found support for a relationship between MFAand health practices among primarily Caucasian samples (Lindgren, 2001, 2003). However,none have examined the longitudinal association between MFA and neonatal outcomes. Thefindings of this study highlight the significance of MFA as a predictor of neonatal health andwellbeing and, potentially, health care costs. Neonates born SGA or at LBW tend to havelonger post-partum hospitalizations and more chronic illnesses than infants born at normalweight. Thus, MFA may be an important factor contributing to the increased health careexpenditures related to adverse neonatal outcomes noted in the United States.
In addition, our findings support the validity of MFA as in important health construct forAfrican-American, low-income women. Despite considerable resources devoted tounderstanding and remediating the problem of perinatal health disparities, we understandrelatively little about the determinants of adverse neonatal outcomes. Great effort has beenfocused on promoting prenatal care as a primary strategy for improving neonatal outcomes.
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Yet, this sample of women with a high rate of poor outcomes was receiving prenatal healthcare, although the content and quality of care was not assessed. The impact of MFA in thissample suggests that MFA is an important factor in our search for additional strategiesbeyond prenatal care.
The mediating role of health practices on the relationship between MFA and adverseneonatal outcomes was an important finding. Health practices such as assuring adequatesleep, limiting caffeine consumption, practicing safe sex, seeking advice from health careproviders or social networks and engaging in relaxing behaviors receive less attention in theliterature in relation to birth outcomes than behaviors such as tobacco use, alcohol use, andother illicit drug use. Given our knowledge that increased social support is correlated withhigher MFA and overall health practices during pregnancy, an enhanced understanding ofhow social support may influence the aforementioned health behaviors could be important intailoring intervention programs (Cranley, 1984; Savage et al., 2007).
The high percentage of women whose neonates had an adverse outcome warrants specialattention. In the United States, African-American women are nearly twice as likely as Non-Hispanic White women (13.7% vs. 7.2%) to have a LBW baby (Mathews et al., 2011). Inthis sample, 21% of neonates were classified as LBW demonstrating a higher prevalencerate for LBW than previously reported though this sample was all low-income (Mathews etal., 2011). The impact of income equality on neonatal outcomes is a critical area of inquiryin the United States, due to a widening gap between rich and poor (Olson, Diekema, Elliott& Renier, 2010). Researchers have demonstrated that income and income inequality areassociated with adverse neonatal outcomes with the poorest neonates experiencing the worstoutcomes (Olson et al., 2010). This is particularly concerning given recent evidence that thewealth gap between Whites and African-Americans is the largest it has been since thegovernment began publishing such data 25 years ago (Kochar, Fry, & Taylor, 2011). Furtherresearch is necessary to better understand the contribution of income, income inequality, andfinancial strain to both MFA and health practices.
This study has two important limitations. First, MFA and health practices were collected viaself-report measures in a cross-sectional manner making inference about their causalrelationships impossible. Tobacco use and substance use, factors known to contribute topoor neonatal outcomes, may have been underreported. Second, these results are based on aconvenience sample and therefore cannot be generalized beyond this group of women.
Nonetheless, this study provides compelling evidence of an important relationship amongMFA, health practices, and adverse neonatal outcomes in a low-income, predominantlyAfrican-American sample. Understanding risk factors for adverse neonatal outcomes isessential to eliminate the disparities in perinatal health across racial and ethnic minorities. Inthis sample of mainly poor, African-American women living in an urban environment,women with higher MFA also noted better health practices and had better neonataloutcomes. Birth outcomes were explained largely by actions taken during a woman’spregnancy (e.g., substance use, maintaining prenatal appointments, risky sexual behaviors).Perhaps a more comprehensive examination of risk factors, including stress, emotionalhealth, and financial strain, not only over the course of a pregnancy but from the pre-conception period, would reveal their influence on both MFA and birth outcomes. Futureresearch is needed to examine additional predictors of MFA, particularly in racial and ethnicminorities at higher risk for disparate birth outcomes.
Finally, future researchers should test culturally-relevant interventions aimed at improvingthe maternal-fetal relationship. Technological advances now allow women to detect theirpregnancies earlier, and they are able to view ultrasound images of their fetus at earlier
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dates. Advanced technology, such as fetal imaging, prenatal diagnostics, and geneticscreening, individuate the fetus from the expectant mother. Incorporating technology, withan appropriate educational component, into an intervention may serve as the impetus foradopting positive health practices at an earlier time period in pregnancy. More importantly,women at risk for poor MFA may benefit from this education thereby facilitating adequatepreparation for motherhood. The limited research aimed at increasing MFA has not beensupported empirically, although the samples have been quite small and lacking ethnic and/orracial diversity (Carter-Jessop, 1981; Davis & Akridge, 1987). As research on theimplications of poor MFA grows, there is a critical need for early identification andappropriate intervention.
ConclusionThis study provides an important contribution to understanding the influence of MFA onhealth practices during pregnancy, and ultimately neonatal outcomes, in a sample of urban,low-income, predominantly African-American women. Women with lower MFA were lesslikely to engage in health promoting practices during pregnancy, and consequently, morelikely to deliver neonates with adverse outcomes. Although significant strides have beenmade in improving maternal and infant outcomes, continued concern is needed about thewidening gap in pregnancy outcomes. Continued research on the manner in whichindividual, environmental, and societal factors interact to contribute to poor pregnancyoutcomes requires multidisciplinary research. Nurses are well positioned to lead thechallenge in ensuring every woman is afforded the same opportunity for favorable maternaland neonatal outcomes.
AcknowledgmentsFunding Received
This research was supported by funding from the National Institutes of Health (T32MH20014-08), NationalInstitute of Nursing Research (F31NR010957-01A) and the National Center for Research Resources(5KL2RR025006), a component of the National Institutes of Health, and the NIH Roadmap for Medical Research.
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Table 1
Demographic Characteristics of the Study Sample (n=166)
n %
Race African American 155 93
White non-Hispanic 9 5
Other 2 2
Education Less than High School 110 67
High School Graduate/GED 45 27
Some College/Trade School 5 3
College/Trade School Graduate 6 3
Marital Status Single 90 54
Partnered/Not Married 56 34
Married 17 10
Other 3 2
Employment Status Unemployed 127 77
Employed Full Time 25 15
Employed Part Time 14 8
Household Income Under $10,000 76 46
$10,001–$20,000 66 40
$20,001–$30,000 12 7
$30,001–$40,000 8 5
>$40,000 4 2
Gravidity Primigravida 54 32
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Table 2
Classification of Adverse Neonatal Outcomes (n= 68/166)
Adverse Outcomea n %
SGA 27 16.3
LBW and SGA 16 9.6
Preterm, LBW, and SGA 6 3.6
Preterm and LBW 13 7.8
Preterm 6 3.6
Total 68 41.0
aThe categories of adverse outcome are mutually exclusive
SGA = Small for Gestational AgeLBW = Low Birth Weight
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Table 3
Correlations among the Main Study Variables (n = 166)
Variable 1 2 3 4
1. MFA –
2. Health Practices .86* –
3. Adverse Neonatal Outcomea −.52* −.63* –
4. Pregnancy Wantednessb −.28* −.34* .19* –
5. Incomec .25* .31* −.23* −.18*
*p <.05
aReferent group was no adverse outcome
bReferent group was pregnancy was wanted
cReferent group was income <$10,000/yr
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Table 4
Summary of Logistic Regression Analyses Predicting Adverse Neonatal Outcomesa (n=166)
PredictorVariable
OddsRatio
95%CI AdjustedOdds Ratio*
95%CI
MFA .91 [.88,.94] .99 [.94, 1.05]
Health Practices .91 [.89,.94] .91 [.88,.96]
aReferent group was no adverse outcome
*Controlling for pregnancy wantedness, income, gestational diabetes and preeclampsia
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