1. Minimizing bias and decreasing threats to internal validity is important to experimental designs. How will a researcher use the three criteria, manipulation, randomization, and control to minimize bias and decrease threats to internal validity?
2. Many times, researchers state that randomized clinical trials (RCT) provide the strongest level of evidence for an individual study when using an evidence-based model. As a researcher, why do you think this statement is true?
3. When conducting an experimental design, how will you as a researcher, use intervention fidelity to increase the strength and quality of the evidence provided by the findings of the study?
4. What is your cosmic question? (This is a question you ask your peers to respond to based on the chapter discussed in class this week i.e. Quantitative studies).
Resource
The Influence of Maternal-Fetal Attachment and Health Practices
on 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, Johns
Hopkins 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], and
Messiah College, Grantham, Pennsylvania
Phyllis W. Sharps, PhD, RN, CNE, FAAN [Professor]
Johns Hopkins University School of Nursing
Abstract
Maternal-fetal attachment (MFA) has been associated with health practices during pregnancy, but
less is known about this relationship in low-income women, and no identified studies have
examined this relationship to neonatal outcomes. This longitudinal descriptive study was
conducted to examine the relationships among MFA, health practices during pregnancy, and
neonatal outcomes in a sample of low-income, predominantly African-American women and their
neonates. MFA was associated with health practices during pregnancy and adverse neonatal
outcomes. Health practices during pregnancy mediated the relationships of MFA and adverse
neonatal outcomes. The results support the importance of examining MFA in our efforts to better
understand the etiology of health disparities in neonatal outcomes.
Keywords
maternal-fetal attachment; health-promoting behaviors; health disparities; African American; birth
outcomes
Disparities in neonatal outcomes between African-Americans and non-Latino White
Americans are one of the most concerning and chronic health disparities affecting our nation
(Alexander, Wingate, Bader, & Kogan, 2008). Many of the health disparities in preterm
birth, low birth weight (LBW) and other adverse pregnancy outcomes are more prevalent in
ethnic 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 restricted
neonates 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 40
times 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,
jalhuse1@son.jhmi.edu.
NIH Public Access
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Published in final edited form as:
Res Nurs Health. 2012 April ; 35(2): 112–120. doi:10.1002/nur.21464.
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morbidities including delays in cognitive development and growth, and heightened risk of
cardiovascular and respiratory disease (Goldenberg et al., 2007). A significant body of
research has been devoted to better understanding the reasons for persisting racial disparities
in neonatal outcomes, yet the causes remain largely unknown.
One factor known to influence neonatal outcomes is the health practices that a mother
engages in during pregnancy. Positive health practices include abstaining from tobacco,
alcohol, and other illegal substances; obtaining regular prenatal care; maintaining a
nutritionally-sound diet (Widen & Siega-Riz, 2010); obtaining adequate rest and sleep;
engaging in regular exercise (Stutzman et al., 2010); and learning about pregnancy and
childbirth (Feinberg, Jones, Kan, & Goslin, 2010). Several variables that correlate with
improved health practices during pregnancy include higher socioeconomic status, higher
levels 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). Cigarette
smoking is one of the most preventable risk factors associated with adverse perinatal
outcomes (Andres & Day, 2000).
Another factor thought to influence health practices during pregnancy is maternal-fetal
attachment (MFA). Cranley (1981) created the theoretical construct of MFA and defined it
as “the extent to which women engage in behaviours that represent an affiliation and
interaction with their unborn child” (Cranley, 1981, p.281). Higher levels of MFA correlate
with the aforementioned high-quality health practices (Lindgren, 2001, 2003). However,
studies of the associations between MFA and health practices during pregnancy have largely
excluded low-income, ethnic minorities (Alhusen, 2008). Furthermore, no longitudinal
studies were found of these variables in relation to neonatal outcomes.
An enhanced understanding of the role that MFA plays in neonatal outcomes of those
subject to disparities, by virtue of race or socioeconomic status, is necessary to improve
understanding 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 those
positive health practices.
This study was designed to examine the associations between MFA, health practices during
pregnancy, and neonatal outcomes in a highly vulnerable sample of predominantly African-
American pregnant women reporting low educational attainment and low socioeconomic
status. 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 the
following 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 during
pregnancy.
3. Improved health practices during pregnancy will be negatively related to adverse
neonatal outcomes.
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4. Health practices during pregnancy will mediate the relationship between MFA and
adverse neonatal outcomes.
Theoretical Model
The transition to motherhood is a major developmental life event. This transition requires
restructuring goals, behaviors and responsibilities. This study of factors that facilitated or
inhibited 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 for
the 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-term
implications of poor attachment (Mercer & Walker, 2006). A woman’s active involvement
in this stage has been consistently linked to engaging in healthier behaviors that benefit both
the woman and her unborn child (Lindgren, 2001, 2003). Women demonstrating higher
levels of MFA are presumed to be more vested in taking care of themselves during
pregnancy in an effort to improve both the health of their fetus and pregnancy outcomes.
Furthermore, researchers have suggested that prenatal attachment facilitates adaptation to
the 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 emotional
tie between the mother and unborn child as well as an innate desire to protect the unborn
child, later described as MFA (Cranley, 1981). This developmental and interactional process
occurs over time (Rubin, 1984). Maternal role attainment and subsequently BAM
acknowledge barriers and facilitators to this process, and were therefore ideal theories to
direct this study of MFA in a high-risk population where health disparities persist.
Methods
Sample
A convenience sample of pregnant women from three urban obstetrical clinics in the Mid
Atlantic region were recruited for the study. The three clinics were all affiliated with a major
university 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 singleton
pregnancies, and able to speak English. This gestational time frame was chosen as research
on MFA has demonstrated MFA increases as a pregnancy progresses, and this time period
marks the beginning of fetal viability thereby allowing for accurate assessment of neonatal
outcomes (Ramsay & Santella, 2010; Seri & Evans, 2008). Participants who met these initial
criteria 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 medical
condition (e.g. chronic hypertension, diabetes mellitus), or received an abnormal diagnostic
result (e.g. known fetal anomaly, abnormal results on first or second trimester screening
tests) during the current pregnancy. Additionally, women reporting a history of fetal
(spontaneous abortion after 24 weeks gestation) or infant death were excluded. These
exclusion criteria were selected given their known contribution to adverse neonatal
outcomes (Institute of Medicine, 1988;Mathews et al., 2011).
Of the 174 eligible pregnant women approached to participate, 167 (96%) completed the
study instruments. One participant delivered at an outside hospital, which precluded our
ability 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, and
100% by 24 weeks gestation. As seen in Table 1, the sample consisted of predominantly
poor, unmarried, African-American younger women.
Data Collection Procedures
Institutional Review Board approval was obtained prior to participant recruitment. Eligible
participants 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 to
complete study instruments prior to a scheduled appointment that between 24 and 28 weeks
gestation.
After a complete description of the study, informed consent was obtained from those women
who agreed to participate. Participants were interviewed in a private space at each of the
three study clinic sites. Interviews lasted approximately 30 minutes. The interviews were
conducted by the first author or one of two undergraduate nursing students who received
research compliance and study procedures training. Participants were compensated $15 for
their participation. Measures related to neonatal outcomes (i.e., birth weight and gestational
age) were extracted from electronic chart review within 48 hours after delivery. Measures
specific 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 event
these risk factors developed after the initial data collection (Bodnar, Ness, Markovic, &
Roberts, 2005; Catalano, Kirwan, Haugel-de Mouzon, & King, 2003).
Measures
Maternal-fetal attachment—MFA was measured with the Maternal-Fetal Attachment
Scale (MFAS; Cranley, 1981). The MFAS is a 24-item measure that asks women to respond
to questions or thoughts indicative of MFA. The scale contains 5-point Likert-type items
with response options ranging from 1 (definitely no) to 5 (definitely yes). Examples of
MFAS items include “I talk to my unborn baby” and “I do things to try to stay healthy that I
would not do if I were not pregnant.” The total score ranges from 24–120 with higher scores
indicative of higher levels of MFA. This instrument is one of the most frequently used
measures of MFA in prenatal studies and has been used in diverse populations including
samples 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 for
the 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 six
areas: balance of rest and exercise, safety measures, nutrition, avoiding use of harmful
substances, obtaining health care, and obtaining information. In addition, 1 item addresses
overall pregnancy health practices. Responses range from 1 (never) to 5 (always or daily) or
a 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 “Since
becoming pregnant I drink more than two caffeinated beverages in a day” and “Since
becoming pregnant I have smoked cigarettes.” The total score ranges from 34–170 with a
high 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 alpha
coefficient reported by Lindgren (2003) was .81 and for the current study was .90.
Neonatal outcomes—Neonatal outcomes were collected from electronic chart review by
the first author. Two undergraduate nursing students collected neonatal data on a random
25% sub-sample to assess inter-rater reliability. A kappa statistic of 1.0 was noted indicating
excellent agreement (Landis & Koch, 1977). Neonatal outcomes collected included the
neonate’s gestational age and birth weight. Small for gestational age (SGA) was calculated
using comprehensive reference values of birth weight at 22 through 44 completed weeks of
gestation that were established by Oken et al. (2003) based on a national sample of over 6
million infants. The presence of LBW (<2500 grams), preterm birth (<37 completed weeks
gestation), or SGA (<10th percentile weight adjusted for gestational age) was coded as an
adverse neonatal outcome during data collection.
Demographic and pregnancy background—A measure of demographic and
obstetrical 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 this
a planned pregnancy; is this pregnancy wanted, unwanted or ambivalent; number of
previous pregnancies, term births, number of therapeutic and/or spontaneous abortions, and
number of live children).
Data Analysis
Data were analyzed using PASW Statistics 18, Release Version 18.0.0 (SPSS: An IBM
Company). Data analysis began with descriptive and exploratory statistical analyses. Study
variables were examined to assess distributions, to identify outlying or extreme
observations, and to determine the need for transformation. There were no missing data. The
sample size was based on an a priori power analysis with a specified power of 80% to detect
a meaningful difference in MFA between participants delivering LBW neonates and
participants delivering neonates >2500 grams. Pearson correlation, and point biserial
correlation coefficients were calculated to address hypothesis 1–3. Mediation of the
relationship between MFA and adverse neonatal outcomes by health practices during
pregnancy was tested with an analytic approach specific to dichotomous outcomes, using the
bootstrap with biased-corrected confidence intervals (MacKinnon, Fairchild, & Fritz, 2007).
Separate logistic regression equations were conducted sequentially to first examine the
relationship between MFA and adverse neonatal outcome and then to determine the extent to
which 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 were
related to the outcome variable of an adverse neonatal outcome, they were included in
subsequent regression analyses to control for their potential confounding effects. Income
was dichotomized using the median of <$10,000 or >$10,000 total household income per
year. Pregnancy wantedness was dichotomized per participant’s response that the current
pregnancy was wanted or participant was ambivalent about current pregnancy. Additionally,
gestational diabetes and preeclampsia were controlled for in the regression models, given
their known contribution to adverse neonatal outcomes.
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Results
After initial data collection, 7.8% (n=13) of study participants were diagnosed with
preeclampsia, 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 2
demonstrates 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 was
83.5. 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 are
presented in Table 3. As hypothesized, there was a significant negative relationship between
MFA and adverse neonatal outcomes supporting our first hypothesis. Health practices
during pregnancy (mediator variable) was significantly related to MFA, the independent
variable, and adverse neonatal outcomes, the dependent variable thereby supporting
hypotheses 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 to
adverse neonatal outcome; the odds ratio for this equation indicated that a one point increase
in MFA was associated with a 9% decreased likelihood of an adverse neonatal outcome. In
the second model, health practices was regressed on adverse neonatal outcome while
controlling for MFA and health practices was noted to be significantly related to adverse
neonatal outcome , indicating that a one point increase in the health practices scale score
was associated with a 9% decreased likelihood of an adverse neonatal outcome. The
proportion of the total effect of MFA on adverse neonatal outcomes mediated by health
practices during pregnancy was 0.91. Additionally, the total indirect effect (−0.56) through
health practices was 10 times larger than the direct effect (−0.5) between MFA and adverse
neonatal outcomes. The total indirect effect through health practices remained significant
with bootstrap analysis, while direct effects between MFA and adverse neonatal outcomes
were non-significant, suggesting complete mediation through health practices. Thus, the
fourth hypothesis was also supported.
Discussion
To our knowledge, this is the first study that provides strong support for the role that MFA
plays both in health practices during pregnancy, and more importantly, in neonatal outcomes
in a highly vulnerable population of predominantly African-American women from a low-
income, urban community. Prior researchers found support for a relationship between MFA
and health practices among primarily Caucasian samples (Lindgren, 2001, 2003). However,
none have examined the longitudinal association between MFA and neonatal outcomes. The
findings of this study highlight the significance of MFA as a predictor of neonatal health and
wellbeing and, potentially, health care costs. Neonates born SGA or at LBW tend to have
longer post-partum hospitalizations and more chronic illnesses than infants born at normal
weight. Thus, MFA may be an important factor contributing to the increased health care
expenditures related to adverse neonatal outcomes noted in the United States.
In addition, our findings support the validity of MFA as in important health construct for
African-American, low-income women. Despite considerable resources devoted to
understanding and remediating the problem of perinatal health disparities, we understand
relatively little about the determinants of adverse neonatal outcomes. Great effort has been
focused 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 health
care, although the content and quality of care was not assessed. The impact of MFA in this
sample suggests that MFA is an important factor in our search for additional strategies
beyond prenatal care.
The mediating role of health practices on the relationship between MFA and adverse
neonatal outcomes was an important finding. Health practices such as assuring adequate
sleep, limiting caffeine consumption, practicing safe sex, seeking advice from health care
providers or social networks and engaging in relaxing behaviors receive less attention in the
literature in relation to birth outcomes than behaviors such as tobacco use, alcohol use, and
other illicit drug use. Given our knowledge that increased social support is correlated with
higher MFA and overall health practices during pregnancy, an enhanced understanding of
how social support may influence the aforementioned health behaviors could be important in
tailoring intervention programs (Cranley, 1984; Savage et al., 2007).
The high percentage of women whose neonates had an adverse outcome warrants special
attention. 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). In
this sample, 21% of neonates were classified as LBW demonstrating a higher prevalence
rate for LBW than previously reported though this sample was all low-income (Mathews et
al., 2011). The impact of income equality on neonatal outcomes is a critical area of inquiry
in 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 are
associated with adverse neonatal outcomes with the poorest neonates experiencing the worst
outcomes (Olson et al., 2010). This is particularly concerning given recent evidence that the
wealth gap between Whites and African-Americans is the largest it has been since the
government began publishing such data 25 years ago (Kochar, Fry, & Taylor, 2011). Further
research is necessary to better understand the contribution of income, income inequality, and
financial strain to both MFA and health practices.
This study has two important limitations. First, MFA and health practices were collected via
self-report measures in a cross-sectional manner making inference about their causal
relationships impossible. Tobacco use and substance use, factors known to contribute to
poor neonatal outcomes, may have been underreported. Second, these results are based on a
convenience sample and therefore cannot be generalized beyond this group of women.
Nonetheless, this study provides compelling evidence of an important relationship among
MFA, health practices, and adverse neonatal outcomes in a low-income, predominantly
African-American sample. Understanding risk factors for adverse neonatal outcomes is
essential to eliminate the disparities in perinatal health across racial and ethnic minorities. In
this sample of mainly poor, African-American women living in an urban environment,
women with higher MFA also noted better health practices and had better neonatal
outcomes. Birth outcomes were explained largely by actions taken during a woman’s
pregnancy (e.g., substance use, maintaining prenatal appointments, risky sexual behaviors).
Perhaps a more comprehensive examination of risk factors, including stress, emotional
health, 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. Future
research is needed to examine additional predictors of MFA, particularly in racial and ethnic
minorities at higher risk for disparate birth outcomes.
Finally, future researchers should test culturally-relevant interventions aimed at improving
the maternal-fetal relationship. Technological advances now allow women to detect their
pregnancies 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 genetic
screening, individuate the fetus from the expectant mother. Incorporating technology, with
an appropriate educational component, into an intervention may serve as the impetus for
adopting 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 adequate
preparation for motherhood. The limited research aimed at increasing MFA has not been
supported empirically, although the samples have been quite small and lacking ethnic and/or
racial diversity (Carter-Jessop, 1981; Davis & Akridge, 1987). As research on the
implications of poor MFA grows, there is a critical need for early identification and
appropriate intervention.
Conclusion
This study provides an important contribution to understanding the influence of MFA on
health practices during pregnancy, and ultimately neonatal outcomes, in a sample of urban,
low-income, predominantly African-American women. Women with lower MFA were less
likely to engage in health promoting practices during pregnancy, and consequently, more
likely to deliver neonates with adverse outcomes. Although significant strides have been
made in improving maternal and infant outcomes, continued concern is needed about the
widening gap in pregnancy outcomes. Continued research on the manner in which
individual, environmental, and societal factors interact to contribute to poor pregnancy
outcomes requires multidisciplinary research. Nurses are well positioned to lead the
challenge in ensuring every woman is afforded the same opportunity for favorable maternal
and neonatal outcomes.
Acknowledgments
Funding Received
This research was supported by funding from the National Institutes of Health (T32MH20014-08), National
Institute 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
a
The categories of adverse outcome are mutually exclusive
SGA = Small for Gestational Age
LBW = 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
a
Referent group was no adverse outcome
b
Referent group was pregnancy was wanted
c
Referent group was income <$10,000/yr
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Table 4
Summary of Logistic Regression Analyses Predicting Adverse Neonatal Outcomesa (n=166)
Predictor
Variable
Odds
Ratio
95%CI Adjusted
Odds Ratio*
95%CI
MFA .91 [.88,.94] .99 [.94, 1.05]
Health Practices .91 [.89,.94] .91 [.88,.96]
a
Referent group was no adverse outcome
*
Controlling for pregnancy wantedness, income, gestational diabetes and preeclampsia
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Example 1:
Crosbie et. al. (2018) conducted a quantitative study to see the relationship between colorectal cancer diagnosis for those below and above 50 years old (Crosbie et. al., 2018). The sample size that was used to conduct their study was a total of 181,909 cases between 35 years (Crosbie et. al., 2018). A convenience sampling of individuals was used in the New Jersey area that were diagnosed with colorectal cancer and were over the age of 20 (Crosbie et. al., 2018). Crosbie et. al. (2018) used the state cancer registry, the Center for Disease Control and Prevention (CDC) as well as the Surveillance, Epidemiology, and End Results (SEER) databases to gather their data (Crosbie et. al., 2018). These databases can be considered reliable because they are national and state databases that have up to date patient information regarding cancer statistics.
Example 2:
According to their findings, Wallace et. al. (2016) was able to identify a large
percentage of black individuals below the age of 50 years old with adenomas or polyps in their
colorectal canal. In addition, their findings indicated that black people under the age of 50 years
old had a similar risk for colorectal adenomas as those who were white, but were within the
recommended screening age of 50 – 64 years old. One of the limitations of this study that was
discussed was the small number of black individuals who were below 50 years old.
Consequently, the prevalence rate for colorectal cancer in African Americans below 50 years old
may have been overestimated within the study (Wallace et. al., 2016)
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