PRAMS8 Maternal Health Dataset - Bivariate Analyses
We conducted bivariate analyses using the chi-square hypothesis test to determine which variables in the PRAMS dataset were statistically associated with maternal health depression. Variables were selected based on hypothesized relationships laid out in the structural equation model framework developed by the PI. Variable selection was also informed by updated findings from the univariate analyses.
Variables Selected for Bivariate Analysis
Direct Effect Model Components and Variables to Model Social Inequality
Socio-Economic Status/Education: Education (MAT_ED), Income (income.label), MARRIED
Indirect Effect Model Components and Variables to Model Social Context
Variables above including
Discrimination, which was replaced with History of Interpersonal Violence variables: IPV_Husband, IPV_Exhusband, IPV_Family Member, and IPV_NonFamilyMember after univariate analyses (e.g., one-way frequency count tables and bar plots) found no viable observations to support inclusion of a Discrimination variable.
Health Insurance Status: (Employer, Parental, Health Exchange, Medicaid, Military/TRICARE, IHS/Tribal Services, Other, Uninsured, CHIP, Other Government Assistance, which will be transformed for modeling as one health insurance variable with four levels: Private, Public, Other, or Uninsured.
Social Support, which may be replaced with Resource Environment to conceptualize mothers who receive WIC (MAT_WIC) as a model variable.
Pregnancy Intent (PGINTENT), which was added to the model after univariate analysis and literature review which supported adding this variable into our model to understand the relationship between a mother’s intent to become pregnant and post-partum maternal depression.
History of Pre-Pregnancy Depression and symptoms of post-partum mental health depression (BGP_DEPRS82, MH_PPINT2)
Substance Use expressed as history of smoking cigarettes (SMK2YRS2, SMK63B_A2) and history of and frequency of alcohol use (DRK_2YRS2 and DRK8_3B2).
Key Takeaways - Relationships of Selected Variables to Post-Partum Maternal Depression
Pregnancy Intentions, reported PPD symptoms, history of depression before pregnancy, and income have both a statistically significant relationship with post-partum maternal depression and medium-to-strong association with post-partum maternal depression compared to all other variables as indicated by test statistics, p-values, and calculated effect sizes.
Pregnancy intention has the strongest association with post-partum maternal depression in this dataset.
Other variables with statistically significant relationships and detectable effect sizes include marital status and substance use (i.e., smoking in the past 2 years, smoking at all pre-pregnancy, and drinking in the past 2 years).
Age, drinking frequency, and history of interpersonal violence had negligible effects but statistically significant relationships.
Race and insurance did not have a statistically significant relationship or observable effect on post-partum maternal depression.
Interpreted Bivariate Analysis Results
Variable
Chi-Square
p-value
Statistically Significant?
Cramer’s V
Effect Size Interpretation
DF = 2
Race/Ethnicity
X2 = 0
p = 1
No
0
No association with PPD
Marital Status
X2 = 1677.5,
p = >0.005
Yes
0.09
Small association with PPD
Age
X2 = 233.33
p = >0.005
Yes
0.03
Negligible association with PPD
Income
X2 = 21124
p = >0.005
Yes
0.22
Medium association with PPD
Insurance
X2 = 0
p = 1
No
0
No association with PPD
Smoking History - Past 2 Years
X2 = 2898.5
p = >0.005
Yes
0.12
Small association with PPD
Smoking History Pre-Pregnancy at All
X2 = 2677.07
p = >0.005
Yes
0.11
Small association with PPD
Drinking History - Past 2 Years
X2 = 1178.5
p = >0.005
Yes
0.07
Small association with PPD
Drinking History - Frequency
X2 = 1457.4
p = >0.005
Yes
0.06
Small association with PPD
History of Interpersonal Violence
X2 = 32.057
p = >0.005
Yes
0.004
Negligible association with PPD
Intent to Become Pregnant
X2 = 190111
p = >0.005
Yes
0.66
Largest association with PPD
History of Depression Before Pregnancy
X2 = 20334
p = 0.005
Yes
0.30
Medium association with PPD
Reports PPD Symptoms
X2 = 53548
p = 0.005
Yes
0.49
Large association with PPD
Hypothesis Testing with Chi-Square and Effect Size Calculation with Cramer’s V
The chi-square test was used to confirm the hypothesized relationship between our predictor variables and post-partum maternal health depression. The null hypothesis asserts that there is no relationship between our variables and maternal health depression, while the alternative hypothesis supports a rejection of the null in favor of evidence that there is a relationship between our variables and maternal health depression.
Cramer’s V was used to measure the effect size between variables we hypothesize to be associated with maternal post-partum depression. The larger the effect size, the stronger the association between two variables. While the hypothesis test can be used to test which variables are related in our dataset, the effect size can also tell us how big or small the association is between those variables. Further, some survey items in the PRAM dataset may have less responses than others, and since sample sizes can change between two variables due to variations in responses across respondents, then the effect size can be a more robust measure of the hypothesized relationship between two variables compared to the p-value of statistical significance, which is less likely to detect stastically significant relationships for smaller samples.
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