Abstract
Background:
Approximately one in every eight mothers experience symptoms of postpartum depression (PPD) in the United States.1 Existing literature lacks an in-depth exploration of the social context from which symptoms of PPD arise. The objectives of this study were to (1) determine the prevalence of postpartum depressive symptoms (PDS) among new mothers and to explore relationships between selected social determinants of health (SDOH) and the likelihood of experiencing PDS.
Materials and Methods:
Data were from the Pregnancy Risk Assessment Monitoring System (PRAMS) 2016 and 2017 Questionnaires. Measured SDOH included socioeconomic status, social network support, psychosocial stress, and availability of resources to meet basic daily needs. Outcome measurement included a combination of two symptom indicator questions. Univariate analyses yielded weighted frequencies of descriptive statistics according to PDS status, and bivariate and multivariate logistic regression analyses yielded odds of reporting PDS.
Results:
The prevalence of self-reported PDS was 3.5%. Among mothers with PDS, most (54%) lived at or below the federal poverty guideline. Mothers who experienced psychosocial stress (e.g., intimate partner violence) during pregnancy had the highest likelihood of reporting PDS (adjusted odds ratio [aOR] = 3.60; confidence interval [95% CI], 2.12–6.12). Mothers who considered their most recent pregnancy unintended or mistimed were more likely to report PDS (aOR = 1.36; 95% CI, 1.01–1.82), (aOR = 1.65; 95% CI, 1.19–2.27), respectively.
Conclusion:
Results demonstrate that several social and psychosocial risk factors significantly impact the likelihood of experiencing PDS. The risk of PDS was particularly significant among lower socioeconomic status mothers, especially those with inadequate social network support. Public health efforts to mitigate potentially harmful social factors should focus on transforming public policies and social programs and increasing screening opportunities.
Keywords: postpartum depression, postpartum depressive symptoms, PRAMS, social determinants of health
Introduction
Postpartum depression (PPD) is a dangerously prevalent condition that affects approximately one in every eight new mothers in the United States.1 That number can be as high as one in five, depending on the state in which the mother lives.1 Given its burden and potentially long-term implications for mothers and their infants, it is critical for research to not only identify individual-level risk factors for experiencing depressive symptoms during the postpartum period but also to address the societal contexts from which these symptoms derive.
Following childbirth, levels of estrogen and progesterone in a mother's body decrease rapidly.2 This abrupt hormonal shift leads to changes in her brain that may trigger fluctuations in mood, and such changes are expected. However, persistent feelings of extreme sadness, loss of interest in usually enjoyable activities, or difficulty bonding with the baby indicates PPD.2
Ever-increasing evidence implies that the postpartum period has substantial and long-lasting implications for mothers, their children, and their families.3,4 Mothers with PPD are less likely to initiate and sustain breastfeeding and use safe sleep practices.5,6 Depression adversely impacts the mother–infant dyad by limiting the mother's ability to respond emotionally and bond with the infant.7 The quality of the mother–infant dyad plays a critical role in the infant's social, cognitive, and behavioral development.4,7,8
Psychological risk factors such as antenatal depression (i.e., depression during pregnancy) have been well-established as a powerful predictor of PPD.9,10 In addition to biological risk factors, previous research has demonstrated that experiencing stressful life events (e.g., financial hardship and intimate partner violence [IPV]) before and during pregnancy increase the risk of developing PPD,11–14 the existing literature lacks an in-depth exploration of the social context from which such stressful life events might arise. Examining the associations between social determinants of health (SDOH) and postpartum depressive symptoms (PDS) is critical to developing supportive public health policies and social programs to reduce the burdensome symptoms of PPD among new mothers.
According to the U.S. Department of Health and Human Services, SDOH are the conditions in the environments where people are born, live, learn, work, play, worship, and age that affect a wide range of health, functioning, and quality-of-life outcomes and risks.15 SDOH can be grouped into five domains: economic stability, education access and quality, health care access and quality, neighborhood and built environment, and social and community context.15 SDOH significantly impact people's health, well-being, and quality of life. Examples of SDOH include safe housing, transportation, racism, violence, education, job opportunities, income, and social cohesion. Recent literature has demonstrated that maternal health outcomes are markedly worse when pregnant and postpartum women are housing insecure, hungry, face financial instability, lack workplace protections and benefits, or are repeatedly exposed to crime and violence, including sexual assault and intimate partner violence.16
For this study, the social context surrounding each mother was measured by her socioeconomic status (e.g., education, income, and occupation), social network (e.g., marital status, IPV), psychosocial stress (e.g., pregnancy intendedness, IPV), and availability of resources to meet basic daily needs (e.g., prenatal care health insurance, Women, Infants, and Children [WIC] eligibility).
Materials and Methods
Study design and participants
This secondary cross-sectional study analyzed data collected in utilized data from the 2016 and 2017 Pregnancy Risk Assessment Monitoring System (PRAMS). PRAMS is an ongoing state-based surveillance system conducted annually by the Centers for Disease Control and Prevention's (CDC) Division of Reproductive Health in collaboration with state health departments. PRAMS is designed to identify and monitor maternal behaviors, emotions, and experiences before, during, and following a live birth. PRAMS uses a complex survey design to capture adequate information from vulnerable populations.17 Participating states utilize birth certificate records as the sampling frame for identifying a representative sample of between 100 and 250 new mothers each month. Mothers' survey responses are linked to extracted birth certificate variables, yielding data that contain a wealth of demographic information.
Currently, PRAMS surveillance represents ∼83% of all live births in the United States.17 All women who delivered a live infant during the surveillance period (2016 and 2017) and reported their most recently born infant as alive at the time of survey completion were eligible for inclusion (N = 64,421).
Measures
Data were from 30 participating states*, which met the response threshold requirement while implementing the PRAMS Phase 8 Core Questionnaire.
Postpartum depressive symptoms
PPD may begin at any time after childbirth but commonly begins between 1 and 4 weeks after delivery.2,3 PRAMS participants are sampled and complete the questionnaire between 2 and 6 months after birth. Knowing that the expected changes in a new mother's emotional state are likely to be resolved within a few weeks postpartum, any depressive symptoms that have persisted until the time of questionnaire completion are highly suggestive of PPD. The PRAMS questionnaire includes core questions implemented by all participating states and state-specific questions chosen or developed by individual states to supplement the core questionnaire. From 2016 to the present, the core questionnaire has included two questions relating to symptoms of PPD.
The outcome of interest was defined by participants' responses to both the symptom indicator questions related to self-assessed experience with symptoms of PPD. Mothers were asked, “Since your new baby was born, how often have you felt down, depressed, or hopeless?” to which they were asked to rate the frequency of experiencing the feeling as always, almost always, or often, sometimes, rarely, or never. Next, mothers were asked, “How often have you had little interest or little pleasure in doing things you usually enjoyed?” to which they were asked to rate the frequency with the same response choices as the previous indicator question. To remain consistent with the methodology of existing literature,1 mothers indicating they “always” or “almost always” experienced both symptoms were classified as experiencing PDS; those reporting that they sometimes, rarely, or never experienced both symptoms were classified as not experiencing PDS.
Social determinants of health
Determining which and how to measure SDOH was complex and cumbersome. Each of the five SDOH domains includes many related variables, and each has varying degrees of influence on maternal mental health outcomes. In addition to young age and low socioeconomic status, single marital status (i.e., unwed or separated/divorced) and low educational attainment have increased women's risk for PPD.18–20 A contributor to the association between single marital status and PPD could be a lack of sufficient father involvement during pregnancy and in parenting after birth.21,22 For this study, predictor or SDOH variables were limited to the scope of the questionnaire. Every attempt was made to measure SDOH similarly to previous studies for consistency and reproducibility.
Thus, the social context surrounding each mother was measured by her socioeconomic status (e.g., education, income, and occupation), social network (e.g., marital status, IPV), psychosocial stress (e.g., pregnancy intendedness, IPV), and availability of resources to meet basic daily needs (e.g., prenatal care health insurance, WIC eligibility).
Socioeconomic status
Socioeconomic status is typically characterized along the following three dimensions: education, income, and occupation.23 Maternal education was classified as less than high school, high school graduate/GED, and greater than high school. Income was a self-reported value that referred to total household income before taxes in the 12 months that preceded delivery. Income ranges were created for classification purposes and to distinguish mothers living at or below the Federal Poverty Guidelines (FPG) established by the U.S. Department of Health and Human Services. For a family of 2 in 2016 and 2017, 100% of the FPG was $16,020 and $16,240, respectively.24 Furthermore, 138% of the FPG (considered eligible for Medicaid) for a family of 2 in 2016 and 2017 was $22,108 and $22,411, respectively.24
While the scope of the questionnaire allowed for simple assessments of education and income, measuring occupation was more challenging. In lieu of employment status data, occupation and occupational network support during the postpartum period were measured by breastfeeding and pumping status. Adherence to breastfeeding is contingent mainly on the quantity and quality of maternal occupational leave time and an accommodating occupational environment with a suitable location and policies that allow time for pumping. Work-related issues have been cited as a major reason for noninitiation25–31 and early cessation of breastfeeding.25–27,32
Social network
Measuring the mother's social network was challenging due to the limitations of the questionnaire. Thus, marital status was a proxy for spousal support during the postpartum period. Participants reported being married or unmarried. Single marital status (i.e., unwed or separated/divorced) has been found to increase a woman's risk for PPD.18–20 A contributor to the association between single marital status and PPD could be a lack of sufficient father involvement during pregnancy and in parenting after birth.21,22 The quantity of previous full-term pregnancies (i.e., parity) indicated how many dependents each mother had in her social network before her most recently delivered. Previous research has demonstrated that women with multiparity had a higher risk of PPD, especially if their social support was low.33–35 It is plausible that multiparity could increase maternal stress and depressive symptoms because of multiple dependents' increased physical, emotional, and financial demands.
Whether or not the participant experienced IPV during her most recent pregnancy served as a measure of the quality of her social network and an indicator of psychosocial stress. Intimate partner violence during pregnancy presents a risk for maternal mental health problems, preterm birth, and having a low birth weight infant.36 A 2012 meta-analysis by Beydoun et al. demonstrated a 1.5–2-fold increased risk of elevated PDS and PPD among women exposed to IPV relative to nonexposed women.37
Availability of resources to meet daily needs
Insurance status can affect whether a pregnant woman seeks medical care and how often, the services and facilities available to her, and ultimately her health and that of her infant.38 Both cross-sectional studies and natural experiments provide evidence of the influence of insurance status on prenatal care.38 At the time of prenatal care, health insurance type was reported as private, Medicaid, self-pay, or no prenatal care. Pregnancy intendedness served as an additional measure of psychosocial stress and socioeconomic status. It has been estimated that nearly half of all pregnancies in the United States are unintended, and poorer women are disproportionately affected.39,40 Limited access to family planning services (e.g., condoms, pharmaceutical contraceptives) increases rates of unintended pregnancies.39 Pregnancy intention was classified as intended, mistimed, and unintended.39
Recent literature has indicated that WIC participants are at significantly higher risk for PDS than ineligible women.41 This is likely due to WIC participation being a proxy for household income and socioeconomic status. Participants indicated whether they were eligible for WIC supplemental nutritional assistance during pregnancy.
Statistical analyses
Survey procedures with SAS version 9.4 (Cary, NC) were utilized to account for the complex survey weights while conducting statistical analyses. PRAMS data were weighted to ensure that the sample represented all women who had a live birth in the United States between 2016 and 2017. Participants were excluded from analyses if data were missing for one or both symptom indicator questions. Descriptive statistics were used to summarize weighted frequencies of baseline sociodemographic characteristics by PDS status. Using bivariate regression models, unadjusted odds ratios (ORs) were calculated to predict the odds of experiencing PDS. Mothers with a history of depression during pregnancy were significantly more likely to report PDS. Thus, for a final subanalysis, mothers who experienced PDS were stratified by antenatal depression status.
Using multivariate logistic regression models to control for the confounding effects of maternal age, race, and ethnicity, adjusted ORs (aORs) were calculated to predict the odds of experiencing PDS among mothers with different socioeconomic circumstances.
Results
Among the 66,232 mothers who completed the PRAMS Phase 8 Core Questionnaire, 64,421 completed both the symptom indicator questions and were included in the analysis. The prevalence of self-reported PDS was 3.5%. The highest state-specific prevalence of PDS (6.8%) was among Arkansan mothers, a notable 3.3% higher than the average. Mothers in New York City reported the lowest prevalence (1.5%) of PDS.
Among mothers who reported PDS, most were unmarried (54.3%), 20 to 29 years old (58.8%), not currently breastfeeding (57.6%), had annual household incomes of less than $24,000 (51.2%), and utilized Medicaid as their source of health insurance to access prenatal care (52.9%) (Table 1). Among mothers who did not report PDS, most were married (63.2%), 20 to 29 years old (47.5), currently breastfeeding (60.2%), had annual household incomes of greater than $60,000 (34.2%), and utilized a private source of health insurance to access prenatal care (44.0%) (Table 1). Approximately 62% of mothers experiencing PDS reported having a clinical visit for depression during their most recent pregnancy (Table 1).
Table 1.
Sociodemographic Characteristics of Pregnancy Risk Assessment Monitoring System Participants by Postpartum Depressive Symptoms, 2016 to 2017 (N = 64,421)
| Characteristicsa | PDS (n = 2,242) |
No PDS (n = 62,179) |
|---|---|---|
| n (weighted %) | n (weighted %) | |
| Maternal age, years | ||
| 19 and younger | 151 (6.4) | 3,076 (4.7) |
| 20–29 | 1,260 (58.8) | 29,835 (47.5) |
| 30–39 | 779 (33.0) | 27,177 (44.5) |
| 40 and older | 52 (1.8) | 2,090 (3.3) |
| Race | ||
| White | 1,367 (72.6) | 36,872 (70.2) |
| Black | 456 (15.2) | 11,512 (14.4) |
| Otherb | 398 (12.2) | 13,101 (15.4) |
| Ethnicity | ||
| Non-Hispanic | 1,916 (84.7) | 49,814 (80.0) |
| Hispanic | 322 (15.3) | 12,007 (20.0) |
| Education | ||
| Less than high school | 305 (12.3) | 8,196 (12.7) |
| High school graduate/GED | 701 (32.0) | 14,802 (23.8) |
| Greater than high school | 1,215 (55.7) | 38,550 (63.5) |
| Annual household incomec | ||
| $0–$16,000 | 709 (32.6) | 11,681 (20.9) |
| $16,001–$24,000 | 381 (18.6) | 8,206 (15.3) |
| $24,001–$32,000 | 193 (10.7) | 5,203 (9.6) |
| $32,001–$48,000 | 205 (12.2) | 5,994 (11.3) |
| $48,001–$60,000 | 152 (8.2) | 4,500 (8.7) |
| $60,001 and greater | 309 (17.7) | 15,465 (34.2) |
| Marital status | ||
| Unmarried | 1,219 (54.3) | 24,310 (36.8) |
| Married | 1,019 (45.7) | 37,817 (63.2) |
| Prenatal health insurance | ||
| Private | 555 (28.9) | 23,770 (44.0) |
| Medicaid | 1,206 (52.9) | 24,475 (36.2) |
| Otherd | 275 (13.7) | 3,145 (5.6) |
| Self-pay or no prenatal care | 105 (4.5) | 8,174 (14.1) |
| Parity | ||
| 0 | 751 (35.1) | 24,347 (38.8) |
| 1 | 697 (33.1) | 19,497 (33.0) |
| 2 | 424 (17.4) | 10,268 (16.5) |
| 3 to 5 | 321 (13.1) | 7,246 (10.7) |
| 6 or more | 40 (1.3) | 682 (1.0) |
| Currently breastfeeding/pumping | ||
| No | 1,059 (57.6) | 22,809 (39.8) |
| Yes | 814 (42.4) | 32,294 (60.2) |
| Pregnancy intention | ||
| Intended | 622 (30.0) | 26,778 (45.3) |
| Mistimed | 716 (33.0) | 20,861 (34.0) |
| Unsure/unintended | 872 (37.0) | 13,536 (20.7) |
| IPV during pregnancy | ||
| No | 1,982 (88.2) | 60,346 (98.0) |
| Yes | 239 (11.8) | 1,410 (2.0) |
| WIC during pregnancy | ||
| No | 1,018 (49.1) | 36,692 (63.1) |
| Yes | 1,190 (50.9) | 24,585 (36.9) |
| Depression during pregnancye | ||
| No | 896 (37.8) | 54,234 (89.7) |
| Yes | 1,346 (62.2) | 7,110 (10.3) |
Information on annual household income and breastfeeding was missing in ∼17% and 12% of participants, respectively.
Other includes American Indian/Alaska Native, Asian, Native Hawaiian, mixed, and others.
Annual total household income before taxes during the 12 months before birth.
Other includes Health Insurance Marketplace and other state-specific options.
Self-reported having a clinical visit for depression during their most recent pregnancy.
IPV, intimate partner violence; PDS, postpartum depressive symptoms; WIC, Women, Infants, and Children.
Without adjusting for confounding variables, teen moms were significantly more likely to report PDS compared with their older counterparts (OR = 1.82; 95% confidence interval [CI], 1.35–2.47) (Table 2). A positive dose–response relationship was observed between annual household income during the 12 months that preceded delivery and PDS, as the odds of mothers reporting PDS increased as income decreased. Mothers who lived at or below 100% of the FPG during the year before delivery were significantly more likely to experience PDS (OR = 1.66; 95% CI, 1.26–2.18) compared with their maternal counterparts who reported an income of between $48,000 and $60,000 (reference) (Table 2). In addition, unmarried mothers were significantly more likely to experience PDS (OR = 2.04; 95% CI, 1.78–2.22) compared with their married counterparts (reference) (Table 2).
Table 2.
Unadjusted Odds of Reporting Symptoms of Postpartum Depression Among Pregnancy Risk Assessment Monitoring System Participants, 2016 to 2017 (N = 64,421)
| Characteristics | uOR | 95% CI limits |
|---|---|---|
| Maternal age, years | ||
| 19 and younger | 1.82 | 1.35–2.47 |
| 20–29 | 1.67 | 1.44–1.93 |
| 30–39 | 1.00 | Reference |
| 40 and older | 0.75 | 0.48–1.15 |
| Race | ||
| White | 1.00 | Reference |
| Black | 1.02 | 0.85–1.22 |
| Other | 0.77 | 0.63–0.93 |
| Ethnicity | ||
| Non-Hispanic | 1.00 | Reference |
| Hispanic | 0.72 | 0.59–0.89 |
| Education | ||
| Less than high school | 0.72 | 0.58–0.90 |
| High school graduate/GED | 1.00 | Reference |
| Greater than high school | 0.65 | 0.56–0.76 |
| Annual household income | ||
| $0 - $16,000 | 1.66 | 1.26–2.18 |
| $16,001–$24,000 | 1.29 | 0.96–1.74 |
| $24,001–$32,000 | 1.18 | 0.84–1.66 |
| $32,001–$48,000 | 1.15 | 0.83–1.58 |
| $48,001–$60,000 | 1.00 | Reference |
| $60,001 and greater | 0.55 | 0.41–0.74 |
| Marital status | ||
| Unmarried | 2.04 | 1.78–2.33 |
| Married | 1.00 | Reference |
| Prenatal health insurance | ||
| Private | 1.00 | Reference |
| Medicaid | 2.22 | 1.90–2.60 |
| Other | 1.47 | 1.16–1.87 |
| Self-pay or no prenatal care | 1.23 | 0.87–1.73 |
| Parity | ||
| 0 | 0.90 | 0.76–1.07 |
| 1 | 1.00 | Reference |
| 2 | 1.05 | 0.87–1.28 |
| 3 to 5 | 1.22 | 0.99–1.51 |
| 6 or more | 1.29 | 0.77–2.17 |
| Currently breastfeeding/pumping | ||
| No | 2.06 | 1.77–2.38 |
| Yes | 1.00 | Reference |
| Pregnancy intention | ||
| Intended | 1.00 | Reference |
| Mistimed | 1.47 | 1.23–1.75 |
| Unsure/unintended | 2.70 | 2.28–3.19 |
| IPV during pregnancy | ||
| No | 1.00 | Reference |
| Yes | 6.44 | 5.08–8.17 |
| WIC during pregnancy | ||
| No | 1.00 | Reference |
| Yes | 1.78 | 1.55–2.03 |
| Depression during pregnancy | ||
| No | 1.00 | Reference |
| Yes | 14.33 | 12.43–16.52 |
CI, confidence interval; IPV, intimate partner violence; uOR, unadjusted odds ratios.
Similarly, mothers who were not breastfeeding/pumping at the time of survey completion were approximately two times (OR = 2.06; 95% CI, 1.77–2.38) as likely as mothers who were breastfeeding/pumping (reference) to experience PDS (Table 2). Furthermore, mothers who reported their most recent pregnancy to be mistimed (i.e., too soon or too late) or unintended were significantly more likely to experience PDS (OR = 1.47; 95% CI, 1.23–1.75) (OR = 2.70; 95% CI, 2.28–3.19), respectively, compared with mothers who reported their pregnancy to be both intended and well-timed (Table 2). The odds of reporting PDS among mothers who experienced IPV during pregnancy were six times (OR = 6.44; 95% CI, 5.08–8.17) as likely as their maternal counterparts who did not experience violence during pregnancy (reference) to report experiencing depressive symptoms (Table 2).
Of the 2,217 mothers who self-reported having a clinical visit for depression during their most recent pregnancy, 60.7% experienced PDS. After stratifying by depression status during pregnancy and controlling for the confounding effects of maternal age, race, and ethnicity, aORs for the associations between select social determinants and PDS are presented in Table 3. Mothers ages 20–29 years who did not experience depression during pregnancy were most likely to report experiencing PDS (OR = 1.52; 95% CI, 1.14–2.02) (Table 3). Among mothers who did not have antenatal depression, those of Hispanic ethnicity were less likely to report experiencing PDS compared with the non-Hispanic referent group (OR = 0.72; 95% CI, 0.47–1.09) (Table 3). The dose–response effect between income and PDS was no longer observable.
Table 3.
Adjusted Odds of Reporting Symptoms of Postpartum Depression Among Pregnancy Risk Assessment Monitoring System Participants With and Without a Clinical History of Depression During Pregnancy, 2016 to 2017 (N = 2,242)
| PDS among those with depression during pregnancy(n = 1,346) |
PDS among those without depression during pregnancy(n = 896) |
|||
|---|---|---|---|---|
| aOR | 95% CI limits | aOR | 95% CI limits | |
| Maternal age, years | ||||
| 19 and younger | 0.87 | 0.52–1.47 | 1.22 | 0.64–2.32 |
| 20–29 | 1.22 | 0.93–1.60 | 1.52 | 1.14–2.02 |
| 30–39 | 1.00 | Reference | 1.00 | Reference |
| 40 and older | 1.05 | 0.51–2.16 | 0.76 | 0.34–1.69 |
| Race | ||||
| White | 1.00 | Reference | 1.00 | Reference |
| Black | 0.78 | 0.56–1.08 | 0.75 | 0.51–1.11 |
| Other | 0.82 | 0.58–1.17 | 1.08 | 0.77–1.51 |
| Ethnicity | ||||
| Non-Hispanic | 1.00 | Reference | 1.00 | Reference |
| Hispanic | 0.87 | 0.61–1.24 | 0.72 | 0.47–1.09 |
| Annual household income | ||||
| $0–$16,000 | 0.67 | 0.43–1.04 | 1.21 | 0.72–2.04 |
| $16,001–$24,000 | 0.66 | 0.42–1.04 | 1.20 | 0.68–2.11 |
| $24,001–$32,000 | 0.65 | 0.37–1.11 | 1.27 | 0.73–2.23 |
| $32,001–$48,000 | 0.80 | 0.49–1.30 | 1.54 | 0.91–2.62 |
| $48,001–$60,000 | 1.00 | Reference | 1.00 | Reference |
| $60,001 and greater | 0.74 | 0.47–1.17 | 1.14 | 0.70–1.85 |
| Marital status | ||||
| Unmarried | 1.22 | 0.91–1.62 | 1.03 | 0.71–1.48 |
| Married | 1.00 | Reference | 1.00 | Reference |
| Currently breastfeeding/pumping | ||||
| No | 1.41 | 1.09–1.82 | 1.27 | 0.95–1.71 |
| Yes | 1.00 | Reference | 1.00 | Reference |
| Pregnancy intention | ||||
| Intended | 1.00 | Reference | 1.00 | Reference |
| Mistimed | 1.16 | 0.87–1.53 | 0.99 | 0.73–1.35 |
| Unsure/unintended | 1.36 | 1.01–1.82 | 1.65 | 1.19–2.27 |
| IPV during pregnancy | ||||
| No | 1.00 | Reference | 1.00 | Reference |
| Yes | 2.44 | 1.68–3.55 | 3.60 | 2.12–6.12 |
aOR, adjusted odds ratios; adjusted for maternal age, race, ethnicity.
Irrespective of depression status during pregnancy, unmarried mothers were slightly more likely to report PDS than their married counterparts; however, this result was nonsignificant (Table 3). Similarly, mothers who were not breastfeeding remained more likely to report PDS. The odds of reporting PDS among mothers with antenatal depression who were not breastfeeding were significantly greater than their breastfeeding counterparts (OR = 1.41; 95% CI, 1.09–1.82). Factors such as pregnancy intendedness and intimate partner violence remained significant predictors for experiencing PDS, irrespective of the mothers' antenatal depression status. Mothers who considered their pregnancy to be unintended or were unsure about the intendedness were significantly more likely (OR = 1.36; 95% CI, 1.01–1.82), (OR = 1.65; 1.19–2.27) to report PDS, respectively, when compared with their maternal counterparts with intended, well-timed pregnancies (reference) (Table 3).
Among mothers who were depressed and experienced IPV during pregnancy, the odds of experiencing PDS were nearly 2.5 times (OR = 2.44; 95% CI, 1.68–3.55) as likely as those of mothers who were depressed during pregnancy and had not experienced IPV (Table 3). The odds of experiencing PDS among mothers who were not depressed but had experienced IPV during pregnancy were nearly four times (OR = 3.60; 95% CI, 2.12–6.12) as likely as those of mothers who were both not depressed and had not experienced IPV during pregnancy (Table 3).
Discussion
In a review of relevant literature, biological or psychological risk factors for PPD have been well-established, while research exploring relationships between SDOH and maternal mental health continues to grow.9,10 This study presents insight into the prevalence of mothers experiencing PDS and the social contexts from which this outcome derives.
Studies conducted in 2001 and 2004 by Beck and Robertson et al., respectively, demonstrated that depression before and during pregnancy to be a significant risk factor for developing PPD.42,43 The results of our study are in agreement with such findings, as mothers with a history of antenatal depression were significantly more likely to experience symptoms of PDS when compared with mothers without a history of depression during pregnancy. In addition, our findings were also in agreement with those of Beck, who found thirteen predictors of PPD, including unintended pregnancy, social network support, and psychosocial stress.42 Lastly, the findings of our study lend support to the results of a 2012 meta-analysis completed by Beydoun et al. that demonstrated a twofold increased risk of symptoms of PDS and PPD among women who experienced IPV compared with women who did not experience IPV.37
The PRAMS data set adjusts for underrepresentation and overrepresentation, which increases the discernibility of results to the U.S. population of new mothers. The findings in this study are subject to several limitations. First, PRAMS is a cross-sectional questionnaire; thus, causality cannot be established. Results only represent women with a recent live birth in the PRAMS sites* included in the report. Women who reside in any site that did not meet the response threshold were excluded, as well as women with a recent miscarriage, stillbirth, or spontaneous abortion. Symptoms of PPD were self-reported and are not indicative of a clinical diagnosis of depression. Results may not capture symptoms that resolved before or began after survey completion.
Furthermore, the complexities of a mother's social network were challenging to measure using the core questionnaire and birth certificate data. Since this study's data were collected, the CDC developed and implemented a PRAMS module that includes measures to assess housing and food security, education, financial stability, and health care access.44 Lastly, this study did not measure all factors associated with experiencing PDS. Factors such as complications during pregnancy or delivery and birth outcomes should be considered in future research. Despite these limitations, PRAMS continues to be an invaluable source of maternal and child health data due to its standardized collection methodology. Only data from states that have met the relatively high response rate threshold are included in the sample, representing ∼83% of all live births in the United States. The potential for reporting bias is minimal due to PRAMS survey responses being anonymous.
Our results further demonstrate the importance of public policies (e.g., legislation that mandates education on and screening for PDS) and multifaceted social programs that assist new mothers during the prenatal and postpartum periods.45 An example of a multifaceted social program is the WIC program, which integrates a PPD screening into their everyday practice while collaborating with community-based behavioral health services to provide referrals and treatment.41 The 2022 White House Blueprint for Addressing the Maternal Health Crisis includes expanding the National Maternal Mental Health Hotline for new mothers to increase access to behavioral health care.16 The Blueprint also called for expanding the capability to screen, treat, and refer for PPD and integrating behavioral health supports in community settings (e.g., school-based health centers and community-based organizations).16
Employing the power of health policy and programs to increase opportunities for maternal mental health screenings would be ineffective without addressing the stigmatization new mothers feel when they speak honestly about their emotional journeys during the postpartum period. To reduce this societal stigma, the 2022 White House Blueprint for Addressing the Maternal Health Crisis included a plan for the U.S. Department of Health and Human Services to facilitate a media campaign to increase knowledge and raise awareness for women, families, and the public about PPD.16
Conclusion
In the last decade, there has been an increasing awareness of the importance of addressing SDOH as a comprehensive strategy for improving health, particularly among groups disproportionally affected by SDOH. While access to quality health care is essential, social risk factors are estimated to drive as much as half of health outcomes. This study demonstrates that in addition to a history of antenatal depression, several SDOH significantly impact the likelihood of experiencing depressive symptoms postpartum. The likelihood of experiencing PDS is particularly significant among lower socioeconomic status mothers, especially those with inadequate social network support.
Acknowledgments
The researchers would like to thank all mothers who responded to the 2016–2017 PRAMS questionnaire.
The PRAMS Working Group: Alabama—Albert Woolbright, PhD; Alaska—Kathy Perham-Hester, MS, MPH; Arkansas—Mary McGehee, PhD; Colorado—Alyson Shupe, PhD; Delaware—George Yocher, MS; Florida—Marie Bailey, MA, MSW, MPH; Georgia—Carol Hoban, PhD, MS, MPH; Hawaii—Mark Eshima, MA; Illinois—Theresa Sandidge, MA; Louisiana—Joan Wightkin; Maine—Tom Patenaude; Maryland—Diana Cheng, MD; Massachusetts—Hafsatou Diop, MD, MPH; Michigan—Violanda Grigorescu, MD, MSPH; Minnesota—Judy Punyko, PhD, MPH; Mississippi—Marilyn Jones, M.Ed; Missouri—Venkata Garikapaty, MSc, MS, PhD, MPH; Montana—JoAnn Dotson; Nebraska—Brenda Coufal; New Jersey—Lakota Kruse, MD; New Mexico—Eirian Coronado, MPH; New York State—Anne Radigan-Garcia; New York City—Candace Mulready-Ward, MPH; North Carolina—Paul Buescher, PhD; North Dakota—Sandra Anseth; Ohio—Connie Geidenberger; Oklahoma—Alicia Lincoln, MSW, MSPH; Oregon—Kenneth Rosenberg, MD; Pennsylvania—Tony Norwood; Rhode Island—Sam Viner-Brown, PhD; South Carolina—Mike Smith.
South Dakota Tribal—Christine Rinki, MPH; Texas—Kate Sullivan, PhD; Tennessee—David Law, PhD; Utah—Laurie Baksh; Vermont—Peggy Brozicevic; Virginia—Marilyn Wenner; Washington—Linda Lohdefinck; West Virginia—Melissa Baker, MA; Wisconsin—Katherine Kvale, PhD; Wyoming—Angi Crotsenberg; CDC PRAMS Team, Applied Sciences Branch, Division of Reproductive Health.
Abbreviations Used
- aOR
adjusted odds ratio
- CDC
Centers for Disease Control and Prevention
- CI
confidence interval
- FPG
Federal Poverty Guidelines
- IPV
intimate partner violence
- ORs
odds ratios
- PDS
postpartum depressive symptoms
- PPD
postpartum depression
- PRAMS
Pregnancy Risk Assessment Monitoring System
- SDOH
social determinants of health
Authors' Contributions
S.O'C.: Conceptualization (lead); writing—original draft (lead); formal analysis (lead); methodology (equal); and writing—review and editing (equal). L.J.S.: Conceptualization (supporting); formal analysis (supporting); methodology (equal); supervision (lead); and writing—review and editing (equal).
Disclaimer
The findings and conclusions described in this article are those of the authors and do not necessarily represent the official position of the CDC or any other organization.
Compliance with Ethical Standards
Ethical approval was waived since the analysis was determined to be nonhuman subject research by the University of Arkansas for Medical Sciences Institutional Review Board.
Data Availability Statement
Data analyzed in this study were a secondary analysis of existing data, which are openly available at locations cited in the Reference section.13 Further documentation about data processing is available at the CDC's PRAMS website at www.cdc.gov/prams/prams-data/researchers.htm
Author Disclosure Statement
No competing financial interests exist.
Funding Information
No funding was received for this article.
Cite this article as: O'Connor S, Su LJ (2023) Postpartum depressive symptoms: an analysis of social determinants using the Pregnancy Risk Assessment Monitoring System, Women's Health Reports 4:1, 584–593, DOI: 10.1089/whr.2023.0050.
The 30 sites included Alaska, Arkansas, Colorado, Connecticut, Delaware, Illinois, Iowa, Louisiana, Maine, Maryland, Massachusetts, Michigan, Missouri, Nebraska, New Hampshire, New Jersey, New Mexico, New York, New York City, Oklahoma, Pennsylvania, Rhode Island, Utah, Vermont, Virginia, Washington, West Virginia, Wisconsin, and Wyoming.
References
- 1. Bauman BL, Ko JY, Cox S, et al. Vital signs: Postpartum depressive symptoms and provider discussions about perinatal depression—United States, 2018. MMWR Morb Mortal Wkly Rep 2020;69:575–581; doi: 10.15585/mmwr.mm6919a2 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2. NIMH. Perinatal Depression. 2020. Available from: https://www.nimh.nih.gov/health/publications/perinatal-depression [Last accessed: April 8, 2023].
- 3. Meltzer-Brody S. New insights into perinatal depression: Pathogenesis and treatment during pregnancy and postpartum. Dialog Clin Neurosci 2011;13(1):89–100; doi: 10.31887/DCNS.2011.13.1/smbrody [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4. Brummelte S, Galea LAM. Postpartum depression: Etiology, treatment and consequences for maternal care. Horm Behav 2016;77:153–166; doi: 10.1016/j.yhbeh.2015.08.008 [DOI] [PubMed] [Google Scholar]
- 5. Wouk K, Stuebe AM, Meltzer-Brody S. Postpartum mental health and breastfeeding practices: An analysis using the 2010–2011 Pregnancy Risk Assessment Monitoring System. Matern Child Health J 2017;21(3):636–647; doi: 10.1007/s10995-016-2150-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6. Field T. Postpartum depression effects on early interactions, parenting, and safety practices: A review. Infant Behav Dev 2010;33(1):1–6; doi: 10.1016/j.infbeh.2009.10.005 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. Stein A, Gath DH, Bucher J, et al. The relationship between post-natal depression and mother–child interaction. Br J Psychiatry 1991;158(1):46–52; doi: 10.1192/bjp.158.1.46 [DOI] [PubMed] [Google Scholar]
- 8. Seng JS, Sperlich M, Low LK, et al. Childhood abuse history, posttraumatic stress disorder, postpartum mental health, and bonding: A prospective cohort study. J Midwifery Women's Health 2013;58(1):57–68; doi: 10.1111/j.1542-2011.2012.00237.x [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9. Ghaedrahmati M, Kazemi A, Kheirabadi G, et al. Postpartum depression risk factors: A narrative review. J Educ Health Promot 2017;6:60; doi: 10.4103/jehp.jehp_9_16 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Lancaster CA, Gold KJ, Flynn HA, et al. Risk factors for depressive symptoms during pregnancy: A systematic review. Am J Obstet Gynecol 2010;202(1):5–14; doi: 10.1016/j.ajog.2009.09.007 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Burns ER, Farr SL, Howards PP. Stressful life events experienced by women in the year before their infants' births—United States, 2000–2010. MMWR Morb Mortal Wkly Rep 2015;64(9):247–251. [PMC free article] [PubMed] [Google Scholar]
- 12. Salm Ward T, Kanu FA, Robb SW. Prevalence of stressful life events during pregnancy and its association with postpartum depressive symptoms. Arch Women's Mental Health 2017;20(1):161–171; doi: 10.1007/s00737-016-0689-2 [DOI] [PubMed] [Google Scholar]
- 13. Kingston D, Tough S, Whitfield H. Prenatal and postpartum maternal psychological distress and infant development: A systematic review. Child Psychiatry Hum Dev 2012;43(5):683–714; doi: 10.1007/s10578-012-0291-4 [DOI] [PubMed] [Google Scholar]
- 14. Qobadi M, Collier C, Zhang L. The effect of stressful life events on postpartum depression: Findings from the 2009–2011 Mississippi Pregnancy Risk Assessment Monitoring System. Matern Child Health J 2016;20(S1):164–172; doi: 10.1007/s10995-016-2028-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15. HP2030. Healthy People 2030: Social Determinants of Health: Office of Disease Prevention and Health Promotion. U.S. Department of Health and Human Services; 2020. Available from: https://health.gov/healthypeople/objectives-and-data/browse-objectives/social-and-community-context [Last accessed: April 8, 2023].
- 16. White House. White House Blueprint for Addressing the Maternal Health Crisis. June 2022. Available from: https://www.whitehouse.gov/wp-content/uploads/2022/06/Maternal-Health-Blueprint.pdf [Last accessed: April 8, 2023].
- 17. Shulman HB, D'Angelo DV, Harrison L, et al. The Pregnancy Risk Assessment Monitoring System (PRAMS): Overview of design and methodology. Am J Public Health 2018;108(10):1305–1313; doi: 10.2105/ajph.2018.304563 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18. Stampfel C. Life Course Indicator: Postpartum Depression. Washington, D.C.; 2014. Contract No.: LC-44. Available from: https://amchp.org/wp-content/uploads/2022/02/LC-44_Postpartum-Depression_Final_8-1-2014.pdf [Last accessed: April 8, 2023]. [Google Scholar]
- 19. Chaudron LH. Postpartum depression: What pediatricians need to know. Pediatr Rev 2003;24(5):154–161; doi: 10.1542/pir.24-5-154 [DOI] [PubMed] [Google Scholar]
- 20. Beck CT. Revision of the postpartum depression predictors inventory. J Obstet Gynecol Neonatal Nurs 2002;31(4):394–402; doi: 10.1111/j.1552-6909.2002.tb00061.x [DOI] [PubMed] [Google Scholar]
- 21. Séjourné N, Vaslot V, Beaumé M, et al. The impact of paternity leave and paternal involvement in child care on maternal postpartum depression. J Reprod Infant Psychol 2012;30(2):135–144; doi: 10.1080/02646838.2012.693155 [DOI] [Google Scholar]
- 22. Fagan J, Lee Y. Perceptions and satisfaction with father involvement and adolescent mothers' postpartum depressive symptoms. J Youth Adolesc 2010;39(9):1109–1121; doi: 10.1007/s10964-009-9444-6 [DOI] [PubMed] [Google Scholar]
- 23. Glymour MM, Avendano M, Kawachi I.. Social Epidemiology: Socioeconomic Status and Health, 2nd ed: Oxford University Press; 2014; doi: 10.1093/med/9780195377903.001.0001 [DOI] [Google Scholar]
- 24. DHHS U. Poverty Guidelines Computations. 2016–2017. Available from: https://aspe.hhs.gov/index.php/topics/poverty-economic-mobility/poverty-guidelines/prior-hhs-poverty-guidelines-federal-register-references/2017-poverty-guidelines/2017-poverty-guidelines-computations [Last accessed: April 8, 2023].
- 25. Ogbuanu C, Glover S, Probst J, et al. Balancing work and family: Effect of employment characteristics on breastfeeding. J Hum Lact 2011;27(3):225–238; doi: 10.1177/0890334410394860 [DOI] [PubMed] [Google Scholar]
- 26. Ahluwalia IB, Morrow B, Hsia J. Why do women stop breastfeeding? Findings from the Pregnancy Risk Assessment and Monitoring System. Pediatrics 2005;116(6):1408–1412; doi: 10.1542/peds.2005-0013 [DOI] [PubMed] [Google Scholar]
- 27. Taylor JS, Risica PM, Cabral HJ. Why primiparous mothers do not breastfeed in the United States: A national survey. Acta Paediatr 2003;92(11):1308–1313; doi: 10.1080/08035250310006467 [DOI] [PubMed] [Google Scholar]
- 28. Khoury AJ, Moazzem SW, Jarjoura CM, et al. Breast-feeding initiation in low-income women: Role of attitudes, support, and perceived control. Women's Health Issues 2005;15(2):64–72; doi: 10.1016/j.whi.2004.09.003 [DOI] [PubMed] [Google Scholar]
- 29. Arora S, McJunkin C, Wehrer J, et al. Major factors influencing breastfeeding rates: Mother's perception of father's attitude and milk supply. Pediatrics 2000;106(5):E67; doi: 10.1542/peds.106.5.e67 [DOI] [PubMed] [Google Scholar]
- 30. Guttman N, Zimmerman DR. Low-income mothers' views on breastfeeding. Soc Sci Med 2000;50(10):1457–1473; doi: 10.1016/s0277-9536(99)00387-1 [DOI] [PubMed] [Google Scholar]
- 31. Ogbuanu CA, Probst J, Laditka SB, et al. Reasons why women do not initiate breastfeeding: A southeastern state study. Women's Health Issues 2009;19(4):268–278; doi: 10.1016/j.whi.2009.03.005 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32. Kimbro RT. On-the-job moms: Work and breastfeeding initiation and duration for a sample of low-income women. Matern Child Health J 2006;10(1):19–26; doi: 10.1007/s10995-005-0058-7 [DOI] [PubMed] [Google Scholar]
- 33. Cho H, Lee K, Choi E, et al. Association between social support and postpartum depression. Sci Rep 2022;12(1):3128; doi: 10.1038/s41598-022-07248-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34. Nakamura Y, Takeishi Y, Ito N, et al. Comfort with motherhood in late pregnancy facilitates maternal role attainment in early postpartum. Tohoku J Exp Med 2015;235(1):53–59; doi: 10.1620/tjem.235.53 [DOI] [PubMed] [Google Scholar]
- 35. Sagami A, Kayama M, Senoo E. The relationship between postpartum depression and abusive parenting behavior of Japanese mothers: A survey of mothers with a child less than one-year-old. Bull Menninger Clin 2004;68(2):174–187; doi: 10.1521/bumc.68.2.174.35951 [DOI] [PubMed] [Google Scholar]
- 36. D'Angelo DV, Bombard JM, Lee RD, et al. Prevalence of experiencing physical, emotional, and sexual violence by a current intimate partner during pregnancy: Population-based estimates from the Pregnancy Risk Assessment Monitoring System. J Fam Violence 2022;38(1):117–126; doi: 10.1007/s10896-022-00356-y [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37. Beydoun HA, Beydoun MA, Kaufman JS, et al. Intimate partner violence against adult women and its association with major depressive disorder, depressive symptoms, and postpartum depression: A systematic review and meta-analysis. Soc Sci Med 2012;75(6):959–975; doi: 10.1016/j.socscimed.2012.04.025 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38. Institute of Medicine (IOM). Health-Related Outcomes for Children, Pregnant Women, and Newborns. Health Insurance is a Family Matter. National Academies Press (US): Washington (DC); 2002; doi: 10.17226/10503 [DOI] [Google Scholar]
- 39. Gauthreaux C, Negron J, Castellanos D, et al. The association between pregnancy intendedness and experiencing symptoms of postpartum depression among new mothers in the United States, 2009 to 2011: A secondary analysis of PRAMS data. Medicine (Baltimore) 2017;96(6):e5851; doi: 10.1097/md.0000000000005851 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40. Finer LB, Zolna MR. Declines in Unintended Pregnancy in the United States, 2008–2011. N Engl J Med 2016;374(9):843–852; doi: 10.1056/NEJMsa1506575 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41. Pooler J, Perry DF, Ghandour RM. Prevalence and risk factors for postpartum depressive symptoms among women enrolled in WIC. Matern Child Health J 2013;17(10):1969–1980; doi: 10.1007/s10995-013-1224-y [DOI] [PubMed] [Google Scholar]
- 42. Beck CT. Predictors of postpartum depression: An update. Nurs Res 2001;50(5):275–285; doi: 10.1097/00006199-200109000-00004. [DOI] [PubMed] [Google Scholar]
- 43. Robertson E, Grace S, Wallington T, et al. Antenatal risk factors for postpartum depression: A synthesis of recent literature. Gen Hosp Psychiatry 2004;26(4):289–295; doi: 10.1016/j.genhosppsych.2004.02.006 [DOI] [PubMed] [Google Scholar]
- 44. Hacker K, Auerbach J, Ikeda R, et al. Social determinants of health-an approach taken at CDC. J Public Health Manag Pract 2022;28(6):589–594; doi: 10.1097/phh.0000000000001626 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45. Wisner KL, Chambers C, Sit DKY. Postpartum depression: A major public health problem. JAMA 2006;296(21):2616–2618; doi: 10.1001/jama.296.21.2616 [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
Data analyzed in this study were a secondary analysis of existing data, which are openly available at locations cited in the Reference section.13 Further documentation about data processing is available at the CDC's PRAMS website at www.cdc.gov/prams/prams-data/researchers.htm