Abstract
Introduction
High body mass index (BMI) is associated with adverse pregnancy outcomes, but it is not a direct measure of cardiovascular health (CVH) and misclassifies many. As CVH is a lead determinant of lifelong morbidity and mortality, we aimed to evaluate the association between BMI ≥30 and adverse pregnancy outcomes stratified by CVH.
Methods
Secondary analysis of the nuMoM2b multicenter cohort of nulliparas, excluding people with pregestational diabetes (GDM) and chronic hypertension. We used American Heart Association's Life's Simple 7 to assess CVH. Metrics included smoking, physical activity, healthy diet pattern, total cholesterol, and blood pressure. We omitted BMI given our objective, and we added triglycerides as these are a marker of CVH in pregnancy. We assigned 0 points for Poor category, 1 for Intermediate, and 2 for Ideal for each metric, with a maximum total score of 14. Total score was categorized as Poor (1–7), Intermediate (8–11), or Ideal (12–14). Outcomes included adverse perinatal outcomes previously linked to BMI. Association between exposures and outcomes was calculated via logistic regression.
Results
A total of 2381 participants were included, of which 445 (20.0%) had BMI ≥30, 134 (5.4%) had Poor CVH, 1733 (72.8%) had Intermediate CVH, and 514 (21.6%) had Ideal CVH. Overall, BMI ≥30 was associated with increased hypertensive disease of pregnancy (HDP, 38.7% vs. 19.6%; odds ratio [OR], 2.6; 95% confidence interval [CI], 2.1–3.2), severe preeclampsia (8.3 vs. 3.1%; OR, 2.8; 95% CI, 1.9–4.3), large for gestational age (LGA, 10.6% vs. 4.3%; OR, 2.6; 95% CI, 1.8–3.8), GDM (7.4% vs. 2.6%; OR, 3.0; 95% CI, 1.9–4.6), and cesarean birth (37.0% vs. 22.4%; OR, 2.0; 95% CI, 1.6–2.5). However, when stratified by CVH category, these associations were attenuated. In the Ideal CVH category, BMI ≥30 was only associated with LGA and GDM. Poor CVH was associated with an elevated risk of HDP regardless of BMI.
Conclusion
Relying on BMI alone to assess pregnancy risk appears to overestimate the risk of BMI ≥30 in those with otherwise Ideal CVH and underestimate in those with BMI 18.5–29.9 but Poor CVH. A more comprehensive assessment of CVH could result in a more accurate risk stratification.
Keywords: adverse pregnancy outcomes, body mass index, cardiovascular health, hypertensive disease of pregnancy
1. INTRODUCTION
Cardiovascular disease is the leading cause of pregnancy‐related mortality in the United States [1]. Poor cardiovascular health (CVH) is prevalent among reproductive‐age individuals and can have significant implications for both the pregnant person and her offspring. Elevated body mass index (BMI) is associated with many pregnancy morbidities, including gestational diabetes (GDM), preeclampsia, cesarean, and stillbirth [2]. Thus, clinicians often use BMI as a cardiometabolic screening tool for allocation of care. For example, many clinicians perform an additional growth ultrasound for people with elevated BMI, and the American College of Obstetricians & Gynecologists recommends antenatal fetal surveillance for those with BMI ≥35 [3]. However, BMI is not a direct measure of health, cardiovascular or otherwise.
BMI is simply a measure of body size and proportions: weight in kilograms divided by the square of height in meters. This fails to account for body composition such as muscle mass and lifestyle behaviors that contribute to health. Whereas BMI is not a direct measure of health, we do have direct measures available clinically. Such measures include blood pressure, exercise tolerance, serum assessments of insulin resistance and lipids, among others. There is a growing acknowledgment from the medical field that BMI is a poor marker of health. The American Medical Association recently recommended against its routine use [4], although general clinical guidelines and billing practices have yet to change.
In nonpregnant populations, it is clear that cardiovascular/cardiorespiratory fitness and health behaviors matter far more than BMI in predicting future mortality and cardiovascular mortality [5]. “Fit” people tend to have the same risk across BMI categories, as do “unfit” people [6]. In fact, the risk of low physical activity in “normal” weight populations is greater than the risk of high BMI. It is possible that this finding is present in pregnancy as well. If so, clinicians may be ascribing inaccurate levels of pregnancy risk to people with high BMI who are also “fit.”
We hypothesize that when CVH is high, BMI will have a weaker impact on pregnancy outcomes than in an unselected population. Our objective was to (1) describe frequencies of pregnancy morbidity among varying levels of CVH and BMI categories and (2) to evaluate the association between BMI ≥30 and adverse pregnancy outcomes (APOs) in different cohorts of CVH status.
2. METHODS
This is a secondary analysis of the prospective cohort study “Nulliparous Pregnancy Outcomes Study: Monitoring Mothers‐to‐Be (nuMoM2b).” This multisite cohort study of 10,038 nulliparous pregnant people was conducted from 2010 to 2015. Participants underwent data collection at up to three study visits (6–13 6/7 weeks, 16–21 6/7 weeks, and 22–29 6/7 weeks) and at delivery. At each study visit, medical information, physical activity, nutrition inventory, and serum samples were obtained. A subset of the population had first‐trimester biomarkers of cardiometabolic health obtained as part of the nuMoM2b Heart Health follow‐up cohort study. Pregnancy terminations were excluded from the study population. For this analysis, we included participants with (1) delivery outcome information available, (2) tobacco use recorded, (3) first‐trimester assessment of physical activity, (4) first‐trimester nutrition inventory, and (5) first‐trimester biomarkers of cardiometabolic health available. We excluded participants with a known diagnosis of pregestational diabetes and/or chronic hypertension, as people with these conditions by definition have complications of cardiometabolic health that are likely to dominate the risk profile. We also excluded those with BMI <18.5, as there is increased pregnancy risk associated with this group (10 participants excluded from analysis).
CVH status was determined using a modified application of the American Heart Association's Life's Simple 7 [7]. The standard Life's Simple 7 evaluates tobacco use, diet, physical activity, BMI, blood pressure, cholesterol, and insulin resistance as both risk factors for cardiometabolic conditions and targets for intervention and risk reduction. For our modified approach, we omitted weight as a risk factor given our goal of evaluating the impact of BMI on different tiers of CVH. Instead, we substituted triglycerides, as these have been associated with APOs. Also, we substituted random glucose for fasting based on the availability of specimens. Random glucose has been shown to demonstrate an association with CVD [8, 9]. Each CVH risk variable was scored as poor, intermediate, or ideal and coded as 0, 1, or 2, respectively (Table 1). All variables were added together for a total CVH risk score ranging from 0 to 14. Higher score indicated healthier risk profile. These scores were then categorized as Poor (1–7 points), Intermediate (8–11 points), or Ideal (12–14 points). Tobacco use was ascertained from patient interviews. Physical activity was based on a survey. Diet pattern scores were based on Food Frequency Questionnaires completed by participants. Diet pattern score consisted of 1 point for each of the following: ≥4.5 cups/day of fruits and vegetables, ≥2 servings/week fish, ≥3 servings/day whole grains, no more than 36 oz/week of sugar‐sweetened beverages, and <1500 mg/day of sodium. Blood pressure was based on the first‐trimester blood pressure measurement recorded by study staff. Cholesterol, triglycerides, and glucose are based on the first‐trimester serum obtained as part of the original study and analyzed as part of the subsequent Heart Health follow‐up [10].
TABLE 1.
Risk categories of variables in modified CVH risk score.
| Variable | Poor—0 points | Intermediate—1 point | Ideal—2 points |
|---|---|---|---|
| Tobacco use | Use in early pregnancy | Prior use, not during pregnancy | No tobacco use |
| Physical activity | None | Some but <150 min/week | ≥150 min/week |
| Diet pattern score | 0–1 | 2–3 | 4–5 |
| Total cholesterol, mg/dL | ≥240 | 200–239 | <200 |
| Triglycerides, mg/dL | ≥200 | 150–199 | <150 |
| Blood pressure, mmHg | ≥140/90 | 120/80–139/89 | <120/80 |
| Random glucose, mg/dL | ≥120 | 100–119 | <100 |
Abbreviation: CVH, cardiovascular health.
Individual APOs evaluated included those previously linked to higher BMI. These individual outcomes included any hypertensive disease of pregnancy (HDP), preterm birth (PTB) prior to 37 weeks, small for gestational age (SGA) with birthweight < 10th percentile, large for gestational age (LGA) with birthweight ≥90th percentile, GDM, and cesarean birth. HDP was defined by the standard American College of Obstetricians & Gynecologists definitions [11]. Birthweight percentiles were based on Oken norms [12].
Descriptive data were reported as mean (standard deviation [SD]) or median (interquartile ratio [IQR]), as appropriate. BMI was dichotomized as 18.5–29.9 and ≥30. Demographics were reported by BMI category and the difference between categories was determined via the Wilcoxon rank‐sum test or the chi‐squared test, as appropriate. Frequencies of individual APOs were reported by CVH and BMI category along with confidence intervals (CIs). The following categories were generated: (1) Ideal CVH with BMI 18.5–29.9, (2) Ideal CVH with BMI ≥30, (3) Intermediate CVH with BMI 18.5–29.9, (4) Intermediate CVH with BMI ≥30, (5) Poor CVH with BMI 18.5–29.9, and (6) Poor CVH with BMI ≥30. Associations between BMI ≥30 and APOs were determined within each CVH category via log binomial regression with BMI 18.5–29.9 as the referent group. The association between BMI ≥30 and each APO was also calculated to provide a within‐population reference. This part of the analysis queries if elevated BMI remains a risk factor within each CVH risk group. Finally, the association between each category and APO was evaluated overall using the Ideal CVH with BMI 18.5–29.9 group as the reference. RRs were adjusted by maternal age and use of government‐funded insurance because these variables are linked to higher BMI, worse CVH, and APOs. Original study site's local Institutional Review Board approved the original nuMoM2b protocol and procedures, and informed consent was obtained from participants as part of this.
3. RESULTS
There were 2554 participants who had all key components of our modified Life's Simple 7 CVH risk score. After excluding 1 individual who underwent termination of pregnancy, 36 with pregestational diabetes, 55 with chronic hypertension, 71 with missing BMI information, and 65 with BMI < 18.5, 2381 remained for secondary analysis (Figure 1). A total of 475 (19.9%) participants had BMI ≥30. The median CVH risk score was 10 (IQR, 9–11). There were 134 (5.6%) in the overall Poor category, 1733 (72.8%%) in the Intermediate category, and 514 (21.6%) in the Ideal category. Demographic information by BMI category is shown in Table 2. While people with BMI ≥30 made up a larger portion of the Poor CVH group than the Ideal CVH group, 9.5% (45 out of 475) of people with BMI ≥30 had Ideal CVH, and 3.7% (70 out of 1916) of people with BMI 18.5–29.9 had Poor CVH, highlighting that BMI alone does not determine CVH status.
FIGURE 1.
Population included in analysis. BMI, body mass index; CVH, cardiovascular health.
TABLE 2.
Demographic information by BMI category.
| Variable | BMI 18.5–29.9 | BMI ≥30 | p value |
|---|---|---|---|
| Age at first study visit | 29 (25–32) | 27 (23–31) | 0.001 |
| Race | <0.001 | ||
| American Indian/Alaska Native | 2 (0.1%) | 3 (0.6%) | |
| Asian | 73 (3.8%) | 8 (1.7%) | |
| Native Hawaiian/Other Pacific | 4 (0.2%) | 0 (0.0%) | |
| Islander | |||
| Black/African American | 130 (6.8%) | 78 (16.4%) | |
| White | 1533 (80.0%) | 306 (64.4%) | |
| More than one race | 92 (4.8%) | 43 (9.1%) | |
| Not reported | 82 (4.3%) | 37 (7.8%) | |
| Hispanic ethnicity | 193 (10.1%) | 78 (16.4%) | <0.001 |
| Public insurance | 307 (16.1%) | 118 (24.9%) | <0.001 |
| Previous pregnancies | 0.023 | ||
| 0 | 1486 (77.6%) | 340 (71.6%) | |
| 1 | 329 (17.2%) | 104 (21.9%) | |
| 2 or more | 101 (5.3%) | 31 (6.5%) | |
| Household income as percentage of 2013 federal poverty level | 448 (234–640) | 346 (177–453) | <0.001 |
| CVH Category | <0.001 | ||
| Poor | 70 (3.7%) | 64 (13.5) | |
| Intermediate | 1367 (71.7%) | 366 (77.1%) | |
| Ideal | 469 (24.6%) | 45 (9.5%) |
Note: Continuous data presented as median (interquartile range).
Abbreviations: BMI, body mass index; CVH, cardiovascular health.
Overall, as previously described, BMI ≥30 was associated with increased frequency of HDP (adjusted risk ratio [aRR], 2.0; 95% CI, 1.7–2.3), LGA (aRR, 2.5; 95% CI, 1.8–3.5), GDM (aRR, 2.8; 95% CI, 1.9–4.3), and cesarean (RR, 1.6; 95% CI, 1.4–1.9) when compared to BMI 18.5–29.9. However, when participants were first grouped by CVH category, some of these associations were attenuated. In the Ideal CVH category, BMI ≥30 only remained associated with LGA and GDM (Table 3). When compared to BMI 18.5–29.9/Ideal CVH group, risk of HDP was elevated in the BMI 18.5–29.9/Intermediate CVH (aRR, 1.4; 95% CI, 1.1–1.8), BMI ≥30/Intermediate CVH (aRR, 2.7; 95% CI, 2.1–3.5), and BMI ≥30/Poor CVH (aRR, 3.0; 95% CI, 2.2–4.3) groups. Figure 2 displays the ORs and 95% CIs for the outcomes of HDP, LGA, GDM, and cesarean according to CVH and BMI categories when the Ideal CVH and BMI <30 group is used as reference. Figure 3 displays the frequencies of these outcomes across CVH and BMI categories. See supplementary table for 95% confidence intervals of group outcome frequencies (Table S1).
TABLE 3.
Association of BMI ≥30 and adverse pregnancy outcomes within each CVH category.
| Poor CVH score (1–7) | Intermediate CVH score (8–11) | Ideal CVH score (12–14) | All CVH groups | |||||
|---|---|---|---|---|---|---|---|---|
| Adverse pregnancy outcome | BMI 18.5–29.9N (%)Ref N = 70 |
BMI ≥30 N (%) RR (95% CI) aRR (95% CI) N = 64 |
BMI 18.5–29.9 N (%) Ref N = 1367 |
BMI ≥30 N (%) RR (95% CI) aRR (95% CI) N = 366 |
BMI 18.5–29.9 N (%) N = 469 |
BMI ≥30 N (%) RR (95% CI) aRR (95% CI) N = 45 |
BMI 18.5–29.9 N (%) Ref N = 1906 |
BMI ≥30 N (%) RR (95% CI) aRR (95% CI) N = 475 |
| Hypertensive disease of pregnancy | 17 (24.3%) | 29 (45.3%) | 287 (21.1%) | 146 (40.0%) | 69 (14.8%) | 8 (18.2%) | 373 (19.7%) | 183 (38.7%) |
| 1.9 (1.1–3.1) | 1.9 (1.6–2.2) | 1.2 (0.6–2.4) | Ref | 2.0 (1.7–2.3) | ||||
| 2.0 (1.2–3.3) | 1.9 (1.6–2.2) | 1.2 (0.6–2.4) | 2.0 (1.7–2.3) | |||||
| Preterm birth | 4 (5.7%) | 5 (7.8%) | 87 (6.4%) | 35 (9.6%) | 39 (8.3%) | 2 (4.4%) | 130 (6.8%) | 42 (8.8%) |
| * p = 0.736 | 1.5 (1.03–2.2) | * p = 0.564 | 1.3 (0.9–1.8) | |||||
| 1.4 (0.98–2.1) | 1.2 (0.9–1.7) | |||||||
| SGA | 5 (7.3%) |
6 (9.4%) 1.3 (0.4–4.0) 1.0 (0.3–2.9) |
115 (8.5%) |
25 (6.9%) 0.8 (0.5–1.2) 0.8 (0.5–1.2) |
40 (8.7%) |
3 (7.0%) * p > 0.999 |
160 (8.5%) |
34 (7.2%) 0.9 (0.6–1.2) 0.8 (0.6–1.1) |
| LGA | 3 (4.4%) | 8 (12.5%) | 60 (4.4%) | 34 (9.3%) | 18 (3.9%) | 6 (13.6%) | 81 (4.3%) | 48 (10.2%) |
| * p = 0.118 | 2.1 (1.4–3.2) | 3.5 (1.5–8.3) | 2.4 (1.7–3.3) | |||||
| 2.2 (1.5–3.3) | 3.8 (1.6–9.0) | 2.5 (1.8–3.5) | ||||||
| Gestational diabetes | 8 (11.4%) | 6 (9.4%) | 41 (3.0%) | 26 (7.1%) | 1 (0.2%) | 3 (6.7%) | 50 (2.6%) | 35 (7.4%) |
| 0.8 (0.3–2.2) | 2.4 (1.5–3.8) | * p = 0.002 | 2.8 (1.8–4.3) | |||||
| 0.8 (0.3–2.3) | 2.4 (1.5–3.9) | 2.8 (1.9–4.3) | ||||||
| Cesarean | 20 (28.6%) | 27 (42.2%) | 315 (23.1%) | 136 (37.3%) | 91 (19.5%) | 12 (27.3%) | 426 (22.4%) | 175 (37.0%) |
| 1.5 (0.9–2.4) | 1.6 (1.4–1.9) | 1.4 (0.8–2.3) | 1.6 (1.4–1.9) | |||||
| 1.7 (1.0–2.7%) | ** | 1.4 (0.8–2.4) | ** | |||||
Abbreviations: aRR, adjusted risk ratio; BMI, body mass index; CI, confidence interval; CVH, cardiovascular health; LGA, large for gestational age; RR, risk ratio; SGA, small for gestational age.
*Fisher's exact p value listed instead of OR due to ≤5 events. ** no aRR due to failed convergence of log‐binomial model.
FIGURE 2.
Risk ratio of HDP, LGA, GDM, and cesarean according to CVH and BMI category. BMI, body mass index; CI, confidence interval; CVH, cardiovascular health, GDM, gestational diabetes; HDP, hypertensive disease of pregnancy; LGA, large for gestational age; SGA, small for gestational age.
FIGURE 3.
Frequencies of HDP, LGA, GDM, and cesarean according to CVH and BMI category. BMI, body mass index; CI, confidence interval; CVH, cardiovascular health, GDM, gestational diabetes; HDP, hypertensive disease of pregnancy; LGA, large for gestational age; SGA, small for gestational age.
4. CONCLUSIONS
Our findings suggest that BMI alone, used to assess risk of APOs, overestimated the risk of HDP and cesarean in those with BMI ≥30 and otherwise Ideal CVH. In contrast, relying on BMI alone underestimates the risk of HDP in those with BMI < 30 and Poor CVH. People with Ideal CVH and BMI ≥30 have a similar risk of HDP as allcomers with BMI 18.5–29.9. These findings are likely because BMI is not a direct measure of health.
BMI has long been used as a surrogate for health in medicine, but it is losing legitimacy. BMI originated as the Quetelet Index by a 19th‐century statistician, astronomer, and sociologist [13, 14, 15]. The Quetelet Index was never intended to be a measure of individual health, but rather a population estimate of desirable aesthetics. It was based on white, European men. It also does not separate weight due to muscle from weight due to visceral fat. As such, many have argued that the use of BMI in other populations and as a measure of health is inappropriate. Due to its pervasiveness and convenience, BMI has long been used as a predictor in all fields of medicine including obstetrics. However, we now have better direct measures of health. In nonpregnant patients, BMI is not predictive of mortality if markers of CVH are included in the prediction [5]. As discussed previously, one of the strongest predictors of mortality in nonpregnant populations is low cardiorespiratory fitness, far stronger than high BMI [6, 16]. While BMI is not a strong measure of health, higher BMI is more common in the poor CVH group and less common in the ideal CVH group. This likely reflects both the interplay between fat mass and physical activity and nutrition, as well as the cardiovascular harms of exposure to weight stigma [17, 18, 19, 20, 21, 22, 23] and weight cycling [24, 25], which are independent risk factors for poor health.
Accurate risk assessment in pregnancy is important to avoid contributing to obstetric weight stigma. Weight stigma is pervasive in medicine and obstetrics [19]. Patients with high BMIs report high levels of experiencing weight stigma during pregnancy, with the most common source being from obstetricians [20]. Some examples of such stigma include the assumption that someone with a high BMI is destined to develop an APO and expressions of surprise if they have a healthy, low‐risk pregnancy. Qualitative work highlights the harmful effects of blame from providers and overemphasis on high‐risk status, with many endorsing a feeling of victory when their pregnancy resulted in an uncomplicated birth [20, 26, 27, 28]. Much of this stems from presumptions of poor health in people with high BMIs, even when all direct measures of health are reassuring. While our findings are preliminary, given the small numbers in some exposure groups, we can reassure patients with BMI ≥30 and otherwise Ideal CVH that their overall absolute risk of APOs is close to the population level. Providers should not be surprised when their pregnancies go well.
We must also avoid missing elevated risk in people with BMI 18.5–29.9 and otherwise poor CVH. This population had an increased risk of HDP, but would not qualify for prophylactic low‐dose aspirin for preeclampsia prevention unless they also had additional risk factors beyond nulliparity [29]. None of the variables in Life's Simple 7 or our modified version is currently an indication for prophylactic low‐dose aspirin. This population also would not qualify for additional growth ultrasounds or fetal monitoring. A similar analysis using the Life's Essential 8 CVH profile found that a Poor Behaviors/Normal BMI & BP group had 1.5 times the odds of HDP (95% CI, 1.2–1.8) [30], similar to our findings. Evaluation of CVH may permit improved care for this population that is currently allocated to low‐risk care.
The primary strength of our work is the evaluation of CVH independent of BMI in a pregnant population. As with the original Life's Simple 7, BMI is typically aggregated with other variables in evaluating CVH. Our goal was to better understand the contributions of BMI and CVH to adverse pregnancy outcomes to best inform patient counseling. Access to multiple variables of CVH permitted this analysis, and we used multiple analytic methods to demonstrate relationships. Both risk ratios, to demonstrate effect size, and frequencies are important to understand absolute risk. Certainly, further work with direct measures of aerobic fitness or body composition would provide additional insight.
This analysis is limited by the population numbers available. Due to smaller numbers in the Poor and Ideal CVH groups, it is possible that the lack of association is due to a lack of power in some comparisons. However, regardless of this, the descriptive statistics remain useful. Overall outcomes in those with BMI ≥30 and Ideal CVH are optimistic. The study population is also exclusively nulliparous and lacks sufficient diversity, thus limiting generalizability. We were also limited by the available laboratory assays in this existing cohort. For example, a fasting glucose, a 2‐h oral glucose tolerance test, or a hemoglobin A1c would have been a preferred measure of insulin resistance compared to a random glucose.
A comprehensive assessment of CVH could result in a more comprehensive pregnancy risk determination by including known metabolic factors that contribute to adverse cardiometabolic outcomes. Moreover, further individualizing risk prediction may effectively allocate appropriate resources to optimize pregnancy health. Both are important to avoid undue harm and to improve patient‐centered communication.
AUTHOR CONTRIBUTIONS
Amy M. Valent: Conceptualization; methodology; writing—review and editing. Karen J. Gibbins: Conceptualization; methodology; software; formal analysis; writing—review and editing; visualization; validation; writing—original draft. Nicole E. Marshall: Conceptualization; methodology; writing—review and editing.
CONFLICT OF INTEREST STATEMENT
The authors declare no conflicts of interest.
FUNDING INFORMATION
The authors received no specific funding for this work.
Supporting information
Supporting Information
This work was previously presented at the Society for Maternal‐Fetal Medicine Pregnancy Meeting, January 2025 in Denver, Colorado.
DATA AVAILABILITY STATEMENT
The data that support the findings of this study are available by request in the NICHD Data and Specimen Hub.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Supporting Information
Data Availability Statement
The data that support the findings of this study are available by request in the NICHD Data and Specimen Hub.