Adapting a Health at Every Size Intervention to Obstetric Care
OB-HAES
3 other identifiers
interventional
10
1 country
1
Brief Summary
Perinatal mental health disorders occur in 1 in 5 pregnancies and have significant negative intergenerational consequences including being the leading cause of overall and preventable mortality during pregnancy and the first year postpartum. Perinatal mental health disorders impact not only the individual but can also have adverse effects on immediate and long-term child and family wellbeing. Untreated mental health disorders in pregnancy are associated with preterm birth, low birth weight, impaired bonding and lead to issues with neonatal neurodevelopment. Interventions to prevent perinatal mental health disorders are of the utmost importance in helping to improve maternal and child health outcomes in the United States. In Massachusetts, almost a quarter of pregnant people have a BMI \>30 kg/m2. Rates of perinatal mental health disorders are higher among individuals with elevated body mass index (BMI) \> 30 kg/m2 compared to people with BMI \< 30 kg/m2. People with BMI \> 30 are 50% more likely to have antenatal depression, 40% more likely to have postpartum depression, and 25% more likely to develop postpartum anxiety compared to those with BMI \<30 kg/m2. The etiology for the increased risk for perinatal mental health disorders among persons with a higher BMI has not been extensively investigated. However, some postulate this could be due to an increase in the medicalization of pregnancy, along with complications for the birthing person or with fetal/neonatal health. Over the last few years, some researchers have begun to hypothesize that weight stigma may also play a significant role in the development of perinatal mental health disorders in this population. Weight stigma - the social rejection and devaluing of people who live in bodies which do not conform to the societal standards of weight - is associated with the development of depression among people with BMI \>30. Weight stigma has been demonstrated through many fields of healthcare. Many providers hold beliefs regarding people with elevated BMIs, including that they are lazy and unintelligent. Providers may also blame individuals for their medical complications and are less likely to offer them interventions including surgery. This leads to worse outcomes and people avoiding care. Additionally, external weight stigma can lead to weight bias internalization, where individuals accept and self-direct negative stereotypes toward themselves. Weight stigma leads to a cycle of internalized bias which is then compounded by traumatic experiences of stigmatization by healthcare providers. This may lead patients to avoid care and be at increased risk for adverse health outcomes (include adverse mental health outcomes). In fact, the American Association of Endocrinology recommends incorporating the experience of bias and stigmatization into the diagnosis and staging of obesity. Therefore, one could postulate that weight stigma and weight bias internalization likely contribute to the high prevalence of perinatal mental health conditions among individuals with elevated BMI. In order to combat weight stigma and weight bias internalization in people seeking healthcare, the Association for Size Diversity and Health created the Health at Every Size (HAES) intervention. HAES characterizes health as a continuum that is specific to the individual and varies with time and circumstance. HAES has five principles including weight inclusivity, health enhancement, eating for well-being, respectful care, and life enhancing movement. Previously studied HAES interventions consist of a number of group sessions led by trained clinicians that are based on these principles. The sessions range in topics from nutrition, physical activity, self-efficacy and acceptance in order to decrease internalization of weight bias. Previous data from the primary care literature demonstrates the efficacy of HAES interventions on improving overall well-being, decreasing rates of depression and other mental health disorder symptoms, and even in improving cardiovascular and lipid profiles. Despite these findings, HAES has not yet been adapted for use in an obstetric context despite the traditional model for prenatal care being highly focused on weight. Patients are weighed at each prenatal visit, and the amount of "appropriate" weight gain is calculated based on BMI. People with an elevated BMI receive extra laboratory testing, ultrasounds and fetal monitoring. This almost extreme perseverance on weight during pregnancy causes individuals in larger bodies to experience significant weight stigma during their prenatal care. Obstetric providers and perinatal people are interested in interventions to assist in the provision of sensitive care for people who experience weight stigma. This project aims to utilize patient and expert input to adapt a HAES intervention to an obstetric context (OB-HAES).
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at below P25 for not_applicable
Started Jul 2025
Shorter than P25 for not_applicable
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
April 2, 2025
CompletedFirst Posted
Study publicly available on registry
April 9, 2025
CompletedStudy Start
First participant enrolled
July 1, 2025
CompletedPrimary Completion
Last participant's last visit for primary outcome
December 31, 2025
CompletedStudy Completion
Last participant's last visit for all outcomes
May 1, 2026
CompletedJuly 22, 2025
July 1, 2025
6 months
April 2, 2025
July 17, 2025
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
Acceptability Questionnaire
Eleven item questionnaire adapted from Sekhon et al (BMC Health Service Research 2022). This questionnaire will ask participants to rate the acceptability of the intervention including how comfortable they were participating, how what they learned may help them, as well as identify areas for improvement in the intervention and roadblocks.
Within 2 weeks of completion of each group session.
Secondary Outcomes (1)
Qualitative Interviews
within 6 weeks of final session
Study Arms (1)
OBHAES Intervention
EXPERIMENTALIndividuals will be invited to participate in 5 group sessions in pregnancy and the postpartum period. The sessions include education on pregnancy, mental health, nutrition, and self-advocacy.
Interventions
Individuals are invited to participate in 5 group sessions during pregnancy and the postpartum period. The sessions will last 2-2.5 hours each and will include education on pregnancy, mental health, nutrition, movement, and self-advocacy. The sessions will be administered by an OBGYN/MFM physician and psychologist and include discussion with doulas, registered dieticians with pregnancy and disordered eating experience, and prenatal yoga instructors.
Eligibility Criteria
You may qualify if:
- Individuals who are between 18 and 50 years of age, have a BMI \>30 kg/m2, and are in the first trimester of their first pregnancy.
- English speaking
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
UMass Memorial Medical Center
Worcester, Massachusetts, 01605, United States
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
Anna Whelan, MD
UMass Chan Medical School
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- NA
- Masking
- NONE
- Purpose
- OTHER
- Intervention Model
- SINGLE GROUP
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Assistant Professor in Obstetrics and Gynecology
Study Record Dates
First Submitted
April 2, 2025
First Posted
April 9, 2025
Study Start
July 1, 2025
Primary Completion
December 31, 2025
Study Completion
May 1, 2026
Last Updated
July 22, 2025
Record last verified: 2025-07
Data Sharing
- IPD Sharing
- Will not share
This data would be identifiable as there are so few planned participants.