Skip to main content
Women's Health logoLink to Women's Health
. 2023 Apr 21;19:17455057231166822. doi: 10.1177/17455057231166822

Racial and ethnic disparities in postpartum weight retention: A narrative review mapping the literature to the National Institute on Minority Health and Health Disparities Research Framework

Jacqueline Kent-Marvick 1,, Kristin G Cloyes 1,2, Paula Meek 1, Sara Simonsen 1
PMCID: PMC10126608  PMID: 37082834

Abstract

Three out of four people who give birth retain excess weight at 1-year postpartum. This is concerning, as postpartum weight retention is associated with increased morbidity risk. People from racial and ethnic minority groups are disproportionately affected by postpartum weight retention; 80% of Black and 69.5% of Hispanic/Latina/o/x birthing people begin pregnancy overweight or obese compared to 55% of white, non-Hispanic birthing people. Black and Hispanic/Latina/o/x birthing people also may be more likely to experience postpartum weight retention. Investigating these risks in people from racially/ethnically diverse backgrounds may be an important way to address disparities in morbidity and mortality. This narrative review uses an intersectional approach to the investigation of U.S.-based racial and ethnic disparities in postpartum weight retention, applying both the framework of Reproductive Justice and the National Institute on Minority Health and Health Disparities Research Framework. The results illustrate the Levels and Domains of research in this field of investigation, revealing that efforts have been focused at the Level of the Individual (i.e. diet, activity). Mapping the literature to the National Institute on Minority Health and Health Disparities Research Framework reveals that gaps in research exist in areas recognized as key drivers of health and health disparities (e.g. the finding that no studies have investigated postpartum weight retention within the Healthcare System Domain). Furthermore, participant-driven insights into postpartum weight retention illuminated barriers to health behaviors encountered by birthing people. Among these insights is the need for postpartum weight retention efforts to address participants’ real-life circumstances and social settings so we may address structural factors that impact postpartum weight retention. Last, stakeholder engagement and further elucidation of the social-determinants-of-health contexts will be essential to the development of high-quality interventions. Researchers must consider how the intersections of the National Institute on Minority Health and Health Disparities Research Framework’s Levels and Domains can help to provide a route for understanding the complexities related to postpartum weight retention among minority-health and health-disparity populations.

Plain Language Summary

A Review of the Literature Using the National Institutes of Health, National Institute on Minority Health and Health Disparities (NIMHD) Research Framework to Create a Roadmap of the Studies Investigating Racial and Ethnic Disparities in Excess Weight Retained After Pregnancy

Why was this study done?

Three out of four people who give birth retain excess weight at 1-year post-pregnancy. This is concerning, as weight that is retained following pregnancy is associated with increased risk for the development of disease. People from racial and ethnic minority groups experience weight retention more frequently post-pregnancy. Black and Hispanic/Latina/o/x birthing people are more likely to begin pregnancy overweight or obese. They are also more likely to retain excess weight following pregnancy. Investigating these risks in people from racially/ethnically diverse backgrounds may be an important way to address disparities in excess weight retained post-pregnancy.

What did the researchers do?

This review of the literature used a tool called the National Institute on Minority Health and Health Disparities (NIMHD) Research Framework to map the literature to date on racial and ethnic disparities in excess weight retained post-pregnancy.

What did the researchers find?

We used the NIMHD Research Framework as a visual guide of the existing research about excess weight retained following pregnancy. Results illustrate the levels and domains at which research has been investigated. These results reveal that efforts have been focused at the individual level, with most attention given to diet and activity. Mapping the literature to the NIMHD Research Framework sheds light on gaps in the research.

What do the findings mean?

Mapping the literature has revealed a need for investigations that make connections between the levels and domains of the Framework, so that we may understand underlying factors that contribute to health disparities.

Keywords: health behaviors, health disparities, obesity, overweight, postpartum weight retention, women’s health

Introduction

Approximately three out of four people who give birth are heavier at 1-year postpartum than they were before pregnancy. Up to 50% of birthing people retain 10 pounds or more, and up to 25% retain more than 20 pounds. 1 This risk is magnified among people who enter pregnancy with an overweight or obese body mass index (BMI),2,3 as they are two times as likely to gain excess weight during pregnancy4,5 and have a three- to four-fold higher risk of postpartum weight retention (PPWR). 1 PPWR is defined as not returning to pre-pregnancy weight by one-year postpartum. 6 This is concerning, as PPWR is associated with morbidity risk such as cardiovascular disease7,8 and type 2 diabetes. 9

People from racial and ethnic minority groups are disproportionately affected by PPWR. Black and Hispanic/Latina/o/x people are more likely to begin pregnancy overweight or obese. Eighty percent (confidence interval (CI): 72.6–85.8) of Black women and 69.5% (CI: 63.5–74.9) of Hispanic women aged 20 to 39 years old are categorized as overweight or obese, compared to 55% (CI: 450–4.6) of non-Hispanic, white women. 10 In addition, Black and Hispanic/Latina/o/x birthing people may be more likely to experience PPWR, though evidence about racial and ethnic disparities of PPWR is sparse and somewhat conflicting.2,11,12 Thus, investigating these risks in birthing people from racially/ethnically diverse backgrounds may be an important way to understand root causes of disparities in morbidity and mortality by investigating why people from specific racial and ethnic minority groups are experiencing disparities in PPWR. Race and ethnicity are social constructions rooted in historical context with material, economic, and political implications for those categorized among minoritized racial and ethnic groups. 13 Because we know that there are differences in morbidity and mortality between U.S. birthing people from different racial and ethnic backgrounds, and because we know these differences are largely due to social determinants related to health and wellbeing, 14 an intersectional approach to investigating these disparities is essential.

Understanding the full range of people’s experiences is foundational to effectively addressing health disparities. Here, the Reproductive-Justice (RJ) framework and the National Institute on Minority Health and Health Disparities (NIMHD) Research Framework provide tools that allow us to do this. Reproductive Justice is a framework rooted in the reproductive-rights and social-justice movements. 15 The RJ movement was founded in 1994 by the Women of African Descent for Reproductive Justice. This group of Black women established the RJ movement as a means for advocating for marginalized birthing people, and their families and communities. The framework has been further developed by the SisterSong Women of Color Reproductive Justice Collective, and by Loretta J. Ross and Rickie Solinger in a primer on the topic. The framework outlines that in addition to birthing people’s right to have or not have a child, RJ is also concerned with people’s ability to parent their children in safe and healthy environments. Therefore, an RJ perspective allows us to view PPWR as it relates to the long-term health, interconception health and fertility, and caregiving of birthing people.

The National Institute on Minority Health and Health Disparities Research Framework

The NIMHD Research Framework was developed to help researchers design complex, multi-level approaches to investigate and address health disparities. 16 The Framework was introduced in 2017 as a product of a science-visioning process by the NIMHD and other National Institutes of Health (NIH). 17 The visioning process was spurred by the need to facilitate concerted efforts at addressing minority health and health disparities. The Framework is an amalgam of the National Institute on Aging (NIA) Health Disparities Framework and the Socioecological Model. 16 The fusion of these two models allows for phenomena of interest, as identified by NIMHD, to be investigated within the multiple domains (i.e. Biological, Behavioral, Physical/Built Environment, Sociocultural Environment, and Health Care System) and at the multiple levels (i.e. Individual, Interpersonal, Community, and Societal), resulting in a matrix of domains and levels that help to elucidate the complex nature of health disparities so that our research efforts may produce more complete knowledge. 18

Social categorization creates or exacerbates risk factors that are not as detrimental to people who are not minoritized 18 and social conditions (e.g. race/ethnicity, socioeconomic status, community resources, occupational health hazards, subjection to discrimination/racism) are closely linked to health outcomes (e.g. poorer maternal morbidity and mortality). For example, disparities in deaths and hospitalizations among people from racial and ethnic minority groups during the COVID-19 pandemic illustrated the additional burdens (e.g. disparities in comorbidities) and impacts of community contexts (e.g. populous living conditions, frontline public-facing occupations). 19 Therefore, research is needed that investigates factors at multiple levels and domains (e.g. those described for the NIMHD Research Framework in the previous paragraph) in order to understand the interactions at these intersections of domains and levels. Such research allows for more complete knowledge of the ways in which health disparities coalesce so that more effective interventions may be developed. 16 Thus, the Framework is a tool that facilitates appraisal of the real-life social and biological contexts of minority health and health disparities. Approaching minority health and health disparities phenomena in such a way aids in the identification of underlying mechanisms and provides a path for addressing still unanswered questions about health disparities. Moreover, research addressing only one domain, level, or singular box within the Framework’s matrix risks producing incomplete results because this type of research does not address the additive and interactive effects of intersecting determinants of health. 16

The goal of this narrative review was to map the literature to date on racial and ethnic disparities in PPWR and postpartum weight change onto the NIMHD Research Framework so as to identify gaps and opportunities in PPWR research.

Body

For this narrative review, the NIMHD Research Framework was used as a device for mapping the evidence to date on racial and ethnic disparities in PPWR and weight change (Table 1). The mapping procedure described by Alvidrez et al. 16 was used for this analysis of the literature. Using the Framework in this way illustrates how the research to date has been approached in this field of investigation. In addition, mapping the literature has elucidated the gaps and opportunities for future research investigating racial and ethnic disparities in PPWR.

Table 1.

Literature Mapped to the NIMHD Research Framework.

Levels of Influence
Individual Interpersonal Community Societal
Domains of influence (Over the life course) Biological BMI;12,2036
Genetics; 37 Gravidity/parity;12,2022,25,26,29,31,33,36,3843
GWG;11,12,2023,2527,29,30,32,33,4247
Postpartum weight change;20,26,31,39,40,44,45,48,49
PPWR;11,12,38,2124,2630,32,33,36,4143,46,50,51
Race/ethnicity: Asian,21,38
Black12,2027,2931,3436,39,40,42,43,48,5153 Hispanic12,21,25,28,3436,38,4042,44,45,48,51,53,54
Other race/ethnicity;21,24,25,30,40 Stress; 37
Offspring outcomes; 44
Behavioral Acculturation; 44
Alcohol;24,32,40,49 Breastfeeding;12,2022,27,29,30,3235,3842,44,45,48,50,51
Depression;28,30,3235,40,44,45,50,51 Diet;22,26,28,30,3335,3941,44,46,4951 Exercise;21,28,3035,39,40,41,4446,49,50 Knowledge;42,53
Perceived barriers to weight loss;52,53
Preferences for weight-loss interventions;52,53
Racism; 37
Self-esteem; 40
Self-efficacy;49,50 Sleep;28,30,32,40,44,45,50, Stress;28,37,40,49,50
Tobacco;21,23,24,3033,35,3841,44,45,49
Depression; 43
Diet; 54
Child care;53,54
Cultural norms;49,53,54
Exercise; 54
Family preferences; 54 Family/friend influence;53,54
Household income;53,54 Isolation; 54
Medical advice; 54
Social support;49,53,54
Weight-related issues 54
WIC 54
Physical/built environment SES; 37 Air pollution exposure; 28
Dietary offerings; 53
Neighborhood income;12,32 Neighborhood safety; 28 Neighborhood resources 54
Perceived barriers to weight loss 52
Sociocultural environment Attitudes on weight loss; 52 Depression; 21
Education;12,20,21,25,2933,38,4043 Employment;20,30,32,33,3840 Insurance;21,25
Language preference; 24
Perceived barriers to weight loss; 52
Socioeconomic status; 37
Stress 28
Acculturation;38,41,45
Acculturative stress; 38
Child attachment; 43
Cultural preference; 54
Diet;38,54
Household income;25,29,30,38,41,54 Isolation; 43
Linguistic isolation; 12
Marital status;20,21,25,27,29,33,42,43 Nutrition info. Sources; 42 Perceived barriers to weight loss; 52
Racism; 50
Social support;44,54
Stress28,43
Food insecurity;12,21,41
Social service use;12,21,22,25
Healthcare system
Health outcomes Individual health Family/
organizational health
Community health Population health

BMI: body mass index; GWG: gestational weight gain; PPWR: postpartum weight retention; WIC: women, infants, and children.

Searching the literature

ProQuest Dissertations & Theses Global, and PubMed, a resource maintained by the National Center for Biotechnology Information at the U.S. National Library of Medicine were searched. Medical Subject Headings search terms used for this review are available in Table 2. A total of 2956 articles underwent title-and-abstract screening. Reports that emphasized racial and ethnic disparities in PPWR or weight change among birthing people living in the United States or that focused on PPWR among a specific U.S. marginalized racial and/or ethnic category (i.e. non-white) were included for this review and mapping of the literature. Initially, a total of 32 articles and two dissertations20,38 met inclusion criteria. These articles were then full text-screened, and an additional nine articles were identified during the full-text stage and included within the final list for data extraction.11,12,2137,3946,4860Figure 1 Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram illustrates the identification of records and the screening process for the literature included in this review. Next, the qualified articles were organized according to the levels and domains of influence.

Table 2.

MeSH search terms and search strings.

MeSH terms Postpartum period; Women; Overweight; Obesity; Diet; Exercise; and Postpartum weight retention (branched under gestational weight gain)
Search strings “Gestational Weight Gain”[Mesh] OR “postpartum weight retention” [tiab] OR “maternal weight gain” [tiab] OR PPWR [tiab] OR “pregnancy weight gain” [tiab] OR “post-partum weight gain” [tiab]; (2) (“social network analysis” OR “Social Network Analysis”[Mesh] OR “Sociometric Techniques”[Mesh]) AND (obesity [mesh] OR obesity [tiab] OR obese [tiab]); (3) (“Social Support”[Mesh] OR “social support” [tiab]) AND (obesity [mesh] OR obesity [tiab] OR obese [tiab])

MeSH: Medical Subject Headings; PPWR: postpartum weight retention;

Figure 1.

Figure 1.

PRISMA flow diagram for literature screened.

Biological domain of influence

The Biological Domain of Influence at the individual level is focused on factors such as individual vulnerabilities and mechanisms (e.g. genetic risk). The Biological Domain of Influence at the Interpersonal Level is interested in factors such as caregiver-and-child interactions and the microbiome within the family setting. Within the Biological Domain of investigations on racial and ethnic disparities in postpartum weight, nearly all of the evidence is at the individual level, with just one other study accounting for offspring outcomes at the interpersonal level.

At the level of the individual, the following have been investigated: BMI (n = 18); genetics (n = 1); gravidity/parity (n = 16); gestational weight gain (GWG; n = 19); postpartum weight change (n = 9); PPWR (n = 21); stress (n = 1); and race/ethnicity. Racial and ethnic differences in PPWR and weight change have been investigated within the following groups: Asian (n = 2); Black (n = 23); Hispanic (n = 16); and other/multiracial/unknown race/ethnicity (n = 5; three of the five articles used the category of “other” and provided no additional details). No results were found at the Community and Societal Levels of the Biological Domain of Influence.

Most Individual-Level Biological-Domain factors have been investigated as predictors of PPWR and weight change. All reports describing racial and ethnic differences are descriptive investigations providing evidence that Hispanic and Black birthing people more often retain excess postpartum weight than their white counterparts. The data on PPWR and weight change among Hispanic birthing people are conflicting, however, providing evidence that Hispanic people may be at risk for retaining more21,24,25 or less 40 weight across studies.

Behavioral domain of influence

The behavioral domain of influence at the individual level is concerned with factors such as health behaviors, while the interpersonal level focuses on factors such as family functioning, and the societal level is concerned with policies and laws. Within the behavioral domain of investigations on racial and ethnic disparities in postpartum weight, most of the evidence is concentrated at the individual and interpersonal levels, with just one study at the societal level.

The majority of research found in the behavioral domain was at the individual level, and focused on the following areas: acculturation (n = 1); alcohol (n = 4); breastfeeding (n = 21); depression (n = 11); diet (n = 14); physical activity (n = 16); knowledge (n = 2); perceived barriers to weight loss (n = 2); preferences for weight-loss interventions (n = 2); racism (n = 1); self-esteem (n = 1); self-efficacy (n = 2); sleep (n = 7); stress (n = 5); and tobacco use (n = 15). At the interpersonal level, the following have been investigated: depression (n = 1); diet (n = 1); physical activity (n = 1); child care (n = 2); cultural norms (n = 3); family preferences (n = 1); family/friend influence (n = 2); household income (n = 2); isolation (n = 1); medical advice (n = 1); social support (n = 3); and weight-related issues (n = 1). At the societal level, just one record contributed knowledge within the Behavioral Domain, providing evidence that the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) restricts healthy diet options among families reliant on the program. 54

All PPWR intervention studies included in this review are represented within the Behavioral Domain of Influence,22,26,45,46,49,51 with three45,49,51 out of the six interventions reaching beyond the level of the individual to account for some aspect of the interpersonal level. Palnati et al. 45 intervention used culturally tailored diet and exercise to target healthy behavior change and weight loss among Hispanic women, and measured the acculturation (Psychological Acculturation Scale) of study participants in order to compare participants within intervention and control groups. Acculturation was not found to be a significant factor in the Palnati et al. 45 study, nor did the authors discuss acculturation in relation to their findings. Walker et al. 49 made ethnic-specific adaptations for their intervention with Black, Hispanic, and white participants, accounting for the cultural norms, dietary preferences, and social support of participants. Walker et al. intervention included education tailored for each racial and ethnic group that was presented at weekly meetings. Psychosocial and logistical barriers to healthy behavior change was discussed at the weekly meetings. Participants also received one-on-one diet personalization with a registered dietician. Wright et al. 51 developed their pilot intervention from qualitative work with key stakeholders. Their intervention used class sessions and home visits over one year to provide education and encouragement for breastfeeding, healthy eating, and increased physical activity, including incorporating their baby into activity. Overall, the six intervention studies have focused on Hispanic, Black, or a combination of Hispanic and Black and low-income birthing people, which also included white participants along with Black and Hispanic birthing people. Two of the interventions had no discussion about cultural tailoring of the programs to the samples,22,26 while the other four45,46,49,51 did state that the interventions were culturally and/or individually tailored to the participants’ preferences and needs. This tailoring, however, was discussed in varying degrees of transparency and often did not include stakeholder engagement. Interestingly, the two interventions22,26 that did not discuss cultural tailoring of their programs did report significant differences between intervention and control groups, while the other interventions did not find significant differences.45,46,49,51

Two qualitative studies54,53 provide insight into interpersonal-level factors that influence weight-related behaviors. These participant-driven insights include the importance of involving significant partners and children in intervention work, the need for tailoring physical activities to the home environment, and complexities related to social support, which facilitate and impede healthy behaviors. In addition, the qualitative study by Thornton et al., 54 which explored the role of social support on diet, weight, and beliefs and behaviors about physical activity, reported details about the ways in which WIC-program participation may restrict healthy diet options among women and their families who are reliant on the program.

Physical/Built Environment Domain of Influence

The Physical/Built Environment Domain of Influence at the individual level is focused on factors such as the individual’s personal environment, while the community level is concerned with factors such as community resources. Within the Physical/Built Environment Domain of Influence, investigations on racial and ethnic disparities in postpartum weight have primarily focused on the community level, with just one accounting for socioeconomic individual-level considerations. 37

At the level of the community, the following have been investigated: air-pollution exposure (n = 1; protocol article); dietary offerings (n = 1); neighborhood income (n = 2); neighborhood safety (n = 1; protocol article); neighborhood resources (n = 1); and perceived barriers to weight loss (n = 1). For example, Wright et al. 53 reported that the low-cost food and convenience offered by neighborhood fast-food restaurants impacted participants’ healthy eating behaviors. One participant stated that she could purchase fried chicken and French fries for her family for US$2.99 at the restaurant across the street from her residence, but that the cost of a single salad at the same establishment cost more than double that price (Wright et al., 53 p. 414).

Sociocultural Environment Domain of Influence

The Sociocultural Environment Domain of Influence at the individual level focuses on factors such as socio-demographics, language proficiency, and cultural identification. The Sociocultural Environment Domain of Influence at the interpersonal level is concerned with factors such as social networks and family and peer norms, while the community level is focused on factors such as community norms. Within the Sociocultural Environment Domain of investigations on racial and ethnic disparities in postpartum weight, available evidence is nearly evenly split at the individual and interpersonal levels, with five additional studies providing information at the community level.

At the level of the individual, the following have been investigated: attitudes on weight loss (n = 1); depression (n = 1); education (n = 14); employment (n = 7); insurance (n = 2); language preference (n = 1); perceived barriers to weight loss (n = 1); socioeconomic status (n = 1); and stress (n = 1). At the interpersonal level, the following have been investigated: acculturation (n = 3); acculturative stress (n = 1); child attachment (n = 1); cultural preferences (n = 1); diet (n = 2); household income (n = 6); isolation (n = 1); linguistic isolation (n = 1); marital status (n = 8); nutritional information sources (n = 1); perceived barriers to weight loss (n = 1); racism (n = 1); social support (n = 2); and stress (n = 2). At the level of the community, food insecurity (n = 3) and social service use (n = 4) have been investigated.

A qualitative report by Setse et al. 52 illustrates individual- and community-level impacts on postpartum weight. Participants shared desires for peer support in their weight-loss efforts. These participants expressed that peer-motivation networks would be key to their continued engagement in their weight-loss attempts. They also described opportunities for mentorship within peer networks, which could help them to problem-solve unhealthy dietary cultural norms and family preferences.

An important gap in the literature captured within this review is the absence of reports investigating the association between PPWR and paid family leave. To date, no U.S.-based studies have explored the impact of paid family leave on PPWR among racially and ethnically diverse birth people.

Healthcare system domain of influence

To date, no studies have investigated PPWR and weight change within the Healthcare System Domain. The Healthcare System Domain is pertinent to health disparities. This lack of investigation is notable and is underscored by the fact that the NIMHD Research Framework included the Healthcare System as a distinct domain of influence, rather than accounting for healthcare within the Sociocultural Environment Domain (e.g. through provider bias, or cultural humility and competence) and the Physical/Built Environment Domain (e.g. through access to care, and patient-provider concordance). 16

Locating the literature and elucidating gaps within the NIMHD research framework

Reports investigating disparities in PPWR have most often been descriptive in nature, describing racial and ethnic differences in postpartum weight, such as evidence that Hispanic and Black people more often retain excess postpartum weight than their white counterparts.21,2325,27,29,30,34,36,39,43 A potential discrepancy in this trend may relate to acculturation, with evidence that Hispanic people who have retained more of their cultural heritage are less likely to gain excessive gestational weight or retain excess weight postpartum. 41 Data are conflicting, however, with evidence that Hispanic people may be at risk for retaining more,21,24,25 or less weight 40 across studies. The “Latino Paradox” is a term that has been used to describe the association between lower acculturation scores and lower mortality rates among Hispanic/Latina/o/x immigrants.18,61 The exploration of acculturation may be a fruitful variable for future PPWR investigations, including the study of cultural strengths that could be harnessed within the context of PPWR interventions. A cautionary note relates to the investigation of race/ethnicity solely at the individual level. As race is an imperfect social construct, research that investigates race/ethnicity as a covariate without mining into the sociocultural layers that contextualize experiences of race, risks perpetuating the notion of race as biology, 18 and therefore risks contributing to structural racism by shoring up racist perceptions of racial inferiority.

Besides differences in race and ethnicity, these studies have often explored the association of common predictors of PPWR with weight outcomes, including GWG, parity, tobacco use, education, age, pre-pregnancy BMI, exercise, mood, and socioeconomic status. Less often have studies explicitly set out to investigate the social determinants of health (SDoH; specifically environmental and psychosocial factors) 28 and systemic racism. 50 Some factors that could be described as relating to SDoH and structural inequality include employment status;21,30,39,60 use of public assistance; 25 lower socioeconomic status; 30 lack of insurance; 30 sources of knowledge; 42 social support, influence and networks;52,54 acculturation;24,41 and life and parenting stressors. 43

The qualitative reports included in this review49,5254 provide participant-driven insights into perceived barriers to weight loss, healthy eating, and physical activity, as well as preferences for healthy lifestyle programs. Participants of these studies described parenting and postpartum challenges that complicated their ability to address health goals. In addition, these participants contextualized the numerous cultural, familial, and socioeconomic factors that influenced their day-to-day nutrition and ability to be physically active. Through these qualitative reports, participants were able to shed light on factors beyond the Individual Level that impacted their diet, activity, and ultimately their postpartum weight. As this review revealed, just three PPWR interventions have extended beyond the level of the Individual to also address an aspect of the interpersonal level. Participant-driven insights such as those identified in qualitative reports should help to guide the development of PPWR interventions. This will help to ensure that interventions are designed to address multi-level and dimensional factors that impact postpartum diet, activity, and weight, and participants’ ability to engage in healthy behavior change.

Gaps in the literature

No studies have investigated PPWR and weight change within the Healthcare System Domain of Influence. This domain holds promise as a rich area for acquiring knowledge about the quality of information birthing people are currently receiving from their providers, and offers opportunities to leverage the healthcare setting to prime birthing people for healthy GWG and postpartum weight loss, which reinforces nutritional and activity guidelines. 62 Some salient areas for future research within this domain relate to (1) postpartum people’s fears of harming themselves through physical activity during the postpartum period, 53 (2) receipt of guidance from healthcare providers, 54 and (3) encouragement from providers for weight-loss program participation. 49

Few studies have attempted to explore the effects of the SDoH on PPWR in racially and ethnically diverse birthing people. This includes exploration into the effects of participants’ social networks so that we may learn important ways that birthing people are impacted and influenced by their social relationships. Qualitative investigations included in this review revealed that participants did identify their relationships as impacting their motivation and health behaviors, yet only a single study has explicitly investigated these phenomena through the use of social network analysis. 63 An additional important gap in the literature related to the SDoH is the absence of studies investigating the impact of paid family leave on PPWR among birthing people from racially and ethnically diverse backgrounds.

Articles reviewed here sometimes revealed that weight differences between subgroups appeared to be caused by weight gain during the postpartum period. Studies were rarely able to capture the trajectory of postpartum weight change, though it appears that some postpartum people began gaining weight around 6 weeks postpartum. Weight that is gained during the postpartum period is an under-studied phenomenon that warrants qualitative investigation among racial and ethnic groups and communities. In addition, the interventional work predominantly was focused at the level of the individual and has been largely unsuccessful in assisting people with postpartum weight management. Last, community-based efforts and stakeholder involvement have not been consistent in this intervention work, and details of cultural tailoring vary in transparency.

Conclusion

This analysis provides a current bird’s-eye view of the literature to date explicitly investigating PPWR or postpartum weight change among birthing people from racially and ethnically diverse backgrounds. Among the limitations of this analysis is the exclusion of literature not captured through the title-and-abstract screening process, including literature that may have reported results on research conducted among racially and ethnically diverse samples, but that either did not report this in the abstract or did not report an aim for investigating racial/ethnic differences.

The use of the NIMHD Research Framework to chart the literature to date on racial and ethnic disparities in PPWR has provided a roadmap of the current PPWR-research territory, and a guide to where the gaps in the research remain. Importantly, mapping the literature to the Framework has revealed that these gaps exist in areas recognized as key drivers of health and health disparities. The Framework has illustrated that Hispanic and Black birthing people more often retain excess postpartum weight than their white counterparts. In addition, the intervention work targeting PPWR among racially and ethnically diverse participants has had limited success. The use of the NIMHD Research Framework has facilitated an equity perspective, prioritizing participant-driven insights into PPWR as a way to address barriers to healthy weight-related behaviors encountered by birthing people. Among these essential insights is the need for PPWR efforts to acknowledge and address participants’ real-life circumstances and social settings so we may address structural factors that impact PPWR. Focusing on these factors in PPWR investigations will likely illuminate structural disparities, which will require collaboration with community members, advocacy groups, and policymakers in order to effectively address the underlying disparities. Proceeding in this way underscores the premise that in order to fully address health inequities, we must also be ready to identify and address structural racism. 64

Finally, stakeholder engagement and further elucidation of SDoH contexts will be essential to the development of high-quality interventions. Researchers must consider how the intersections of the NIMHD Research Framework’s Levels and Domains can help to provide a route for understanding better the complexities related to PPWR among minority-health and health-disparity populations.

Acknowledgments

JKM would like to thank Dr. Ana Sanchez-Birkhead, who has been a tireless advocate within higher education for social justice. Dr. Sanchez-Birkhead’s mentorship in issues of health disparities and equity has been pivotal in JKM’s development as a scholar.

Footnotes

ORCID iD: Jacqueline Kent-Marvick Inline graphichttps://orcid.org/0000-0001-8850-2539

Declarations

Ethics approval and consent to participate: Not applicable. As this is a narrative review of the literature, no ethical approval is required.

Consent for publication: Not applicable.

Author contribution(s): Jacqueline Kent-Marvick: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Validation, Visualization, Writing—original draft, Writing—review & editing.

Kristin G. Cloyes: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Supervision, Validation, Visualization, Writing—review & editing.

Paula Meek: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Supervision, Validation, Visualization, Writing—review & editing.

Sara Simonsen: Conceptualization, Data curation, Formal analysis, Investigation, Project administration, Supervision, Validation, Visualization, Writing.

Funding: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Research reported in this publication was supported by the National Institute of Nursing Research of the National Institutes of Health under Award Number F31NR020431. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Availability of data and materials: Not applicable.

References

  • 1.Endres LK, Straub H, McKinney C, et al. Postpartum weight retention risk factors and relationship to obesity at 1 year. Obstet Gynecol 2015; 125(1): 144–152. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Branum AM, Kirmeyer SE, Gregory EC.Prepregnancy body mass index by maternal characteristics and state: data from the birth certificate, 2014. Natl Vital Stat Rep 2016; 65(6): 1–11. [PubMed] [Google Scholar]
  • 3.Begum F, Colman I, McCargar LJ, et al. Gestational weight gain and early postpartum weight retention in a prospective cohort of Alberta women. J Obstet Gynaecol Can 2012; 34(7): 637–647. [DOI] [PubMed] [Google Scholar]
  • 4.Gunderson EP, Murtaugh MA, Lewis CE, et al. Excess gains in weight and waist circumference associated with childbearing: the coronary artery risk development in young adults study (CARDIA). Int J Obes Relat Metab Disord 2004; 28(4): 525–535. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Gunderson EP.Childbearing and obesity in women: weight before, during, and after pregnancy. Obstet Gynecol Clin North Am 2009; 36(2): 317–332, ix. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Lipsky LM, Strawderman MS, Olson CM.Maternal weight change between 1 and 2 years postpartum: the importance of 1 year weight retention. Obesity 2012; 20(7): 1496–1502. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Kirkegaard H, Bliddal M, Støvring H, et al. Maternal weight change from prepregnancy to 18 months postpartum and subsequent risk of hypertension and cardiovascular disease in Danish women: a cohort study. PLoS MED 2021; 18(4): e1003486. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Calle EE, Thun MJ, Petrelli JM, et al. Body-mass index and mortality in a prospective cohort of U.S. Adults. N Engl J Med 1999; 341: 1097–1105. [DOI] [PubMed] [Google Scholar]
  • 9.Must A, McKeown NM. The disease burden associated with overweight and obesity. In: Feingold KR, Anawalt B, Boyce A, et al. (eds) Endotext. South Dartmouth, MA: Mdtext.com, Inc, 2021. [Google Scholar]
  • 10.Ogden CL, Carroll MD, Kit BK, et al. Prevalence of childhood and adult obesity in the United States, 2011-2012. JAMA 2014; 311: 806–814. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Headen IE, Davis EM, Mujahid MS, et al. Racial-ethnic differences in pregnancy-related weight. Adv Nutr 2012; 3(1): 83–94. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Widen EM, Whyatt RM, Hoepner LA, et al. Excessive gestational weight gain is associated with long-term body fat and weight retention at 7 y postpartum in African American and Dominican mothers with underweight, normal, and overweight prepregnancy BMI. Am J Clin Nutr 2015; 102(6): 1460–1467. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.López N, Gómez LE.Mapping “Race”: critical approaches to health disparities research. New Brunswick, NJ: Rutgers University Press, 2013. [Google Scholar]
  • 14.Marmot M, Allen JJ.Social determinants of health equity. Am J Public Health 2014; 104(Suppl. 4): S517–S519. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Ross L.Reproductive justice: an introduction. Oakland, CA: University of California Press, 2017. [Google Scholar]
  • 16.Alvidrez J, Castille D, Laude-Sharp M, et al. The national institute on minority health and health disparities research framework. Am J Public Health 2019; 109(S1): S16–S20. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Duran DG, Pérez-Stable EJ.Science visioning to advance the next generation of health disparities research. Am J Public Health 2019; 109(S1): S11–S13. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Dankwa-Mullan I, Perez-Stable EJ, Gardner K, et al. The science of health disparities research. Hoboken, NJ: John Wiley & Sons, 2021. [Google Scholar]
  • 19.Webb Hooper M, Nápoles AM, Pérez-Stable EJ. COVID-19 and racial/ethnic disparities. JAMA 2020; 323: 2466–2467. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Schneider CR.Associations of gestational weight gain and breastfeeding with postpartum weight change among African American women. Masters thesis, University of Alabama at Birmingham, Birmingham, AL, 2015. [Google Scholar]
  • 21.Archuleta J, Chao SM.Maternal characteristics that impact postpartum weight retention: results from the 2016 Los Angeles Mommy and Baby (LAMB) follow-up study. Matern Child Health J 2021; 25(1): 151–161. [DOI] [PubMed] [Google Scholar]
  • 22.Gross SM, Augustyn M, Henderson JL, et al. Integrating obstetrical care and WIC nutritional services to address maternal obesity and postpartum weight retention. Matern Child Health J 2018; 22(6): 794–802. [DOI] [PubMed] [Google Scholar]
  • 23.Groth SW, Holland ML, Kitzman H, et al. Gestational weight gain of pregnant African American adolescents affects body mass index 18 years later. J Obstet Gynecol Neonatal Nurs 2013; 42(5): 541–550. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Hackley B, Fennie K, Applebaum J, et al. The effect of language preference on prenatal weight gain and postpartum weight retention in urban Hispanic women. Ethn Dis 2010; 20(2): 162–168. [PubMed] [Google Scholar]
  • 25.Hernandez DC.Gestational weight gain as a predictor of longitudinal body mass index transitions among socioeconomically disadvantaged women. J Womens Health 2012; 21(10): 1082–1090. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Herring SJ, Cruice JF, Bennett GG, et al. Intervening during and after pregnancy to prevent weight retention among African American women. Prev Med Rep 2017; 7: 119–123. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Keppel KG, Taffel SM.Pregnancy-related weight gain and retention: implications of the 1990 Institute of Medicine guidelines. Am J Public Health 1993; 83(8): 1100–1103. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.O’Connor SG, Habre R, Bastain TM, et al. Within-subject effects of environmental and social stressors on pre- and post-partum obesity-related biobehavioral responses in low-income Hispanic women: protocol of an intensive longitudinal study. BMC Public Health 2019; 19: 253. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Parker JD, Abrams B.Differences in postpartum weight retention between black and white mothers. Obstet Gynecol 1993; 81(5(Pt. 1): 768–774. [PubMed] [Google Scholar]
  • 30.Siega-Riz AM, Herring AH, Carrier K, et al. Sociodemographic, perinatal, behavioral, and psychosocial predictors of weight retention at 3 and 12 months postpartum. Obesity 2010; 18(10): 1996–2003. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Smith DE, Lewis CE, Caveny JL, et al. Longitudinal changes in adiposity associated with pregnancy: the CARDIA study. JAMA 1994; 271: 1747–1751. [PubMed] [Google Scholar]
  • 32.van Poppel MN, Hartman MA, Hosper K, et al. Ethnic differences in weight retention after pregnancy: the ABCD study. Eur J Public Health 2012; 22(6): 874–879. [DOI] [PubMed] [Google Scholar]
  • 33.Waage CW, Falk RS, Sommer C, et al. Ethnic differences in postpartum weight retention: a Norwegian cohort study. BJOG 2016; 123(5): 699–708. [DOI] [PubMed] [Google Scholar]
  • 34.Walker L, Freeland-Graves JH, Milani T, et al. Weight and behavioral and psychosocial factors among ethnically diverse, low-income women after childbirth: II. Trends and correlates. Women Health 2004; 40(2): 19–34. [DOI] [PubMed] [Google Scholar]
  • 35.Walker LO, Freeland-Graves JH, Milani T, et al. Weight and behavioral and psychosocial factors among ethnically diverse, low-income women after childbirth: I. Methods and context. Women Health 2004; 40: 1–17. [DOI] [PubMed] [Google Scholar]
  • 36.Walker LO, Fowles ER, Sterling BS.The distribution of weight-related risks among low-income women during the first postpartum year. J Obstet Gynecol Neonatal Nurs 2011; 40(2): 198–205. [DOI] [PubMed] [Google Scholar]
  • 37.Davis EM, Stange KC, Horwitz RI.Childbearing, stress and obesity disparities in women: a public health perspective. Matern Child Health J 2012; 16(1): 109–118. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.LeCroy MN.Targeting the home food environment for obesity prevention in immigrant ethnic minorities. Dissertation, University of North Carolina at Chapel Hill, Chapel Hill, NC, 2018. [Google Scholar]
  • 39.Boardley DJ, Sargent RG, Coker AL, et al. The relationship between diet, activity, and other factors, and postpartum weight change by race. Obstet Gynecol 1995; 86(5): 834–838. [DOI] [PubMed] [Google Scholar]
  • 40.Gould Rothberg BE, Magriples U, Kershaw TS, et al. Gestational weight gain and subsequent postpartum weight loss among young, low-income, ethnic minority women. Am J Obstet Gynecol 2011; 204(1): 52.e1–e11. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Martin CL, Tate DF, Schaffner A, et al. Acculturation influences postpartum eating, activity, and weight retention in low-income Hispanic women. J Womens Health 2017; 26(12): 1333–1339. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Nuss H, Freeland-Graves J, Clarke K, et al. Greater nutrition knowledge is associated with lower 1-year postpartum weight retention in low-income women. J Am Diet Assoc 2007; 107(10): 1801–1806. [DOI] [PubMed] [Google Scholar]
  • 43.Whitaker K, Young-Hyman D, Vernon M, et al. Maternal stress predicts postpartum weight retention. Matern Child Health J 2014; 18(9): 2209–2217. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Chasan-Taber L, Marcus BH, Rosal MC, et al. Proyecto Mamá: a lifestyle intervention in overweight and obese Hispanic women: a randomised controlled trial—study protocol. BMC Preg Childbirth 2015; 15: 157. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Palnati M, Marcus BH, Pekow P, et al. The impact of a lifestyle intervention on postpartum weight retention among at-risk Hispanic women. Am J Prev Med 2021; 61(1): 44–54. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46.Peccei A, Blake-Lamb T, Rahilly D, et al. Intensive prenatal nutrition counseling in a community health setting: a randomized controlled trial. Obstet Gynecol 2017; 130(2): 423–432. [DOI] [PubMed] [Google Scholar]
  • 47.Ramón-Arbués E, Martínez Abadía B, Martín Gómez S.[Gestational weight gain and postpartum weight retention in a cohort of women in Aragon, Spain]. Nutr Hosp 2017; 34: 1138–1145. [DOI] [PubMed] [Google Scholar]
  • 48.Lederman SA, Alfasi G, Deckelbaum RJ.Pregnancy-associated obesity in black women in New York City. Matern Child Health J 2002; 6(1): 37–42. [DOI] [PubMed] [Google Scholar]
  • 49.Walker LO, Sterling BS, Latimer L, et al. Ethnic-specific weight-loss interventions for low-income postpartum women: findings and lessons. West J Nurs Res 2012; 34(5): 654–676. [DOI] [PubMed] [Google Scholar]
  • 50.Mendez DD, Sanders SA, Karimi HA, et al. Understanding pregnancy and postpartum health using ecological momentary assessment and mobile technology: protocol for the postpartum mothers mobile study. JMIR Res Protoc 2019; 8: e13569. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 51.Wright C, Mogul M, Acevedo G, et al. Preparing for a trial to test a postpartum weight retention intervention among low income women: feasibility of a protocol in a community-based organization. BMC Womens Health 2018; 18: 27. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 52.Setse R, Grogan R, Cooper LA, et al. Weight loss programs for urban-based, postpartum African-American women: perceived barriers and preferred components. Matern Child Health J 2008; 12(1): 119–127. [DOI] [PubMed] [Google Scholar]
  • 53.Wright C, Mogul M, Murray R, et al. The development of a postpartum weight management intervention for low-income women: end-user perspectives as groundwork. Prog Community Health Partnersh 2017; 11(4): 409–416. [DOI] [PubMed] [Google Scholar]
  • 54.Thornton PL, Kieffer EC, Salabarría-Peña Y, et al. Weight, diet, and physical activity-related beliefs and practices among pregnant and postpartum Latino women: the role of social support. Matern Child Health J 2006; 10(1): 95–104. [DOI] [PubMed] [Google Scholar]
  • 55.Gubrium A, Leckenby D, Harvey MW, et al. Perspectives of health educators and interviewers in a randomized controlled trial of a postpartum diabetes prevention program for Latinas: a qualitative assessment. BMC Health Serv Res 2019; 19: 357. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 56.Phillips T.An examination of postpartum African American adolescents’ sociocultural beliefs, perceptions of body weight, and weight control behaviors. ABNF J 2014; 25(1): 19–23. [PubMed] [Google Scholar]
  • 57.Phillips TM.Exploration of theoretical models: postpartum weight retention in african american adolescents. Nurs Sci Q 2014; 27(4): 308–314. [DOI] [PubMed] [Google Scholar]
  • 58.Walker LO.Managing excessive weight gain during pregnancy and the postpartum period. J Obstet Gynecol Neonatal Nurs 2007; 36(5): 490–500. [DOI] [PubMed] [Google Scholar]
  • 59.Walker LO, Sterling BS, Timmerman GM.Retention of pregnancy-related weight in the early postpartum period: implications for women’s health services. J Obstet Gynecol Neonatal Nurs 2005; 34(4): 418–427. [DOI] [PubMed] [Google Scholar]
  • 60.Wolfe WS, Sobal J, Olson CM, et al. Parity-associated body weight: modification by sociodemographic and behavioral factors. Obes Res 1997; 5(2): 131–141. [DOI] [PubMed] [Google Scholar]
  • 61.Abraído-Lanza AF, Chao MT, Flórez KR.Do healthy behaviors decline with greater acculturation? Implications for the Latino mortality paradox. Soc Sci Med 2005; 61(6): 1243–1255. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 62.Tully KP, Stuebe AM.Foreword: respectful, equitable, and supportive postpartum care. Clin Obstet Gynecol 2022; 65: 538–549. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 63.de la Haye K, Bell BM, Salvy SJ.The role of maternal social networks on the outcomes of a home-based childhood obesity prevention pilot intervention. J Soc Struct 2019; 20(3): 7–28. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 64.Phelan JC, Link BG.Is racism a fundamental cause of inequalities in health? Ann Rev Soc 2015; 41: 311–330. [Google Scholar]

Articles from Women's Health are provided here courtesy of SAGE Publications

RESOURCES