METHODS:
The Nulliparous Pregnancy Outcomes Study: Monitoring mothers-to-be (nuMoM2b) is a geographically diverse, prospective, observational cohort study in which 10,038 nulliparous individuals with singleton pregnancies were enrolled between October 2010 and September 2013. Individuals were eligible for enrollment if they were nulliparous (no prior delivery at 20 weeks or later gestational age), had a viable singleton gestation, had an estimated gestational age of pregnancy between 60–136 weeks, and intended to deliver at a participating clinical site. The study protocol included three study visits during pregnancy and a final visit at the time of delivery. Maternal characteristics and other covariates were ascertained from baseline clinical assessments, medical record abstraction, and standardized questionnaires by trained personnel. Details of the study procedures have been described elsewhere. 11 Each institutional review board approved the study, and all participants gave written informed consent.
A follow-up study, nuMoM2b-Heart Health Study (HHS), included nuMoM2b participants 2 to 7 years after the nuMoM2b index pregnancy. 4508 HHS participants completed an in-person cardiovascular risk factor evaluation. HHS participants had not withdrawn from the primary parent study, had pregnancy outcome data available, and agreed to follow-up contact at 6 month intervals beginning at least 6 months after delivery of the index pregnancy. After the in-person study CVD visit, participants agreed to be contacted at an interval of every 12 months. Biometric data, measurements, questionnaires, and bio-specimens were obtained at the in-person nuMoM2b-HHS visit. Further details on the methods of the HHS have been described elsewhere. 12
This study was a secondary analysis of the nuMoM2b-HHS cohort. We excluded participants for whom the index pregnancy ended in fetal demise < 20 weeks or termination. Participants with missing 1st trimester index pregnancy biomarker measurements, details of APOs, preexisting diabetes, chronic diabetes and other missing delivery details at index pregnancy were excluded from the primary analysis. Chronic hypertension and preexisting diabetes at the index pregnancy, were exclusion criteria from the primary analysis, but were included in analyses of secondary outcomes MD and incident HTN, respectively.
Allostatic load biomarkers were processed from stored urine or serum samples, collected in the first trimester during the nuMoM2b index pregnancy. Samples were stored at -80oC at a central core biorepository. Assays were completed at the HHS core laboratory (Lundquist Institute, Torrance, CA) using standard protocols on a Beckman AU480.
This study’s definition of allostatic load modifies the NHANES13, 14 commonly used risk biomarkers by adding triglycerides, insulin and glucose. Based on available data and assays, allostatic load was defined using: clinically-measured (systolic blood pressure (SBP) diastolic blood pressure (DBP), and body mass index (BMI) (kg/m2)), serum-measured (cholesterol (mg/dL), low-density lipoprotein (LDL) (mg/dL), high-density lipoprotein (HDL) (mg/dL), high sensitivity C-reactive protein (hsCRP) (mg/dL), triglycerides (mg/dL), insulin (ulU/mL), and glucose (mg/dL)) and urine-measured (creatinine (mg/dL) and albumin (mg/dL)). Numerous variations and definitions of allostatic load that have been used, and one is not clearly superior to another [14]. We decided to use biomarkers that were available in our dataset and had been used in other definitions of allostatic load commonly utilized in studies of health disparities. These biomarkers exemplify organ and tissue damage within the following physiological systems: cardiovascular, inflammation, metabolic, and immune.14-16
A high allostatic load score was defined as four or more out of 12 biomarkers in the worst quartile; the ’worst’ quartile was lowest for HDL and albumin and highest for the rest. 17 For each biomarker, if values were at or above the worst quartile (high risk), that biomarker received a value score of ”1.” Values not in the worst quartile were characterized as ”low risk” and given a value score of ”0”. 13 The total allostatic load score was summed for an allostatic load index ranging from 0 to 12. Low allostatic load was reported as an allostatic load index of 4 or less, and high allostatic load was an allostatic load index of more than 4 since this threshold has been discriminatory. 17
The study’s primary outcome, a composite CVD-related outcome, consisted of hypertension (HTN), and metabolic disorder (MD) newly diagnosed in the 2 to 7 years after the index pregnancy. The diagnostic threshold for HTN was based on confirmed elevated or high clinical measurements of blood pressure (SBP ≥ 120 mm Hg, DBP ≥ 80 mm Hg) or antihypertensive medication use. The diagnostic threshold for MD consisted of diabetes as diagnosed by a health care provider, fasting glucose levels >= 100 mg/dL, or medication use for glucose control. Individually, HTN and MD were assessed as secondary outcomes and were chosen due to their strong associations with CVD risk and mortality.12 Definitions for these outcomes were standard and previously reported in detail. 18
Obstetric, medical history, clinical features of pregnancy, maternal demographic, and health behavior characteristics, all measured during the index pregnancy, were evaluated as risk factors for CVD. Obstetric and medical history included: gravida, prior miscarriages, and previous abdominal surgery. Clinical features of pregnancy included bleeding in the first trimester. Maternal demographic and health behavior characteristics included maternal age, education, smoking, federal poverty level, and health insurance status. We report time between index pregnancy and HHS visit.
Non-Hispanic black race has been associated with chronic stress and allostatic load. 32 Thus, although race is a social construct, we evaluated it as a proxy for social experience, systematic, racism, and other unmeasured social determinants of health that potentially manifest through chronic stress. Outcomes were compared between people of self-reported non-Hispanic Black race, and non-Hispanic White, Hispanic, Asian, Native American, Native Hawaiian, Multiracial, and additional racial backgrounds. It was not possible to analyze some groups separately due to small numbers.
Risk factors associated with the composite outcome were identified by testing differences in percentages with chi-square between individuals with and without composite outcome. Unadjusted and adjusted odds ratios (ORs) and 95% confidence interval (CIs) were calculated from bi-variable logistic regression models between individuals with and without composite outcome.
Our primary analysis assessed the association between allostatic load and composite outcome. Unadjusted odds ratios (ORs) and 95% confidence interval (CIs) for the association of high allostatic load with composite outcome were calculated from bi-variable logistic regression models. As secondary outcomes, we evaluated each component of composite outcome in a separate model using a similar methodology. For multivariable modeling of composite outcome, maternal age, smoking status, gravidity, the time between index pregnancy, bleeding at the first trimester, and health insurance status were chosen either a priori based on reported associations19, 20 or were risk factors with an association with the outcome of P-value <0.10. The same covariates were used in the HTN model with the addition of preexisting diabetes and in the MD model with the addition of chronic hypertension. As an additional exploratory analysis, we modeled each of the twelve individual allostatic load component with three outcomes for a total of 36 comparisons. A sensitivity analysis of the primary outcome was performed excluding blood pressure and insulin from the allostatic load definition, and similarly for each secondary outcome allostatic load was redefined excluding blood pressure and insulin separately.
To test whether allostatic load is a pathway that contributes to racial disparities in CVDs, we conducted a four-step mediation analysis to test whether allostatic load is a mediator of the relationship between self-reported race and composite outcome. We first examined the association of maternal race on composite outcome (path c, Figure 2).21-23 Second, we examined the impact of maternal race on allostatic load (path a, Figure 2). 21-23 Third, we report the association between allostatic load with composite outcome (path b, Figure 2). 21-23 In the final step, we assessed whether the race-composite outcome relationship was mediated by allostatic load (path c’, Figure 2). We conducted a sensitivity analysis of the mediation examining the association between allostatic load and composite outcome, limiting the analytical population to individuals of non-Hispanic Black and non-Hispanic White race and ethnicity. This was repeated for secondary outcomes.
As an exploratory analysis, we tested whether there’s an effect modification by race between allostatic load and composite outcome. In unadjusted and adjusted models of composite outcome, we tested for an interaction between race (non-Hispanic Black vs. “Non-Hispanic White, Hispanic, Asian, Native American, and Native Hawaiian, multiracial and additional racial backgrounds”.) and high allostatic load. A significant interaction would demonstrate a difference in the association between high allostatic load and CVD outcomes for people of non-Hispanic Black race compared to people of “Non-Hispanic White, Hispanic, Asian, Native American, and Native Hawaiian, multiracial and additional racial backgrounds”. (i.e., moderation). We conducted a sensitivity analysis of the exploratory moderation examining the association, limiting the analytical population to individuals of non-Hispanic Black and non-Hispanic White race and ethnicity. This was repeated for secondary outcomes.
Data analyses were conducted using SAS 9.4 software (SAS Institute Inc., Cary, NC, USA). All tests were performed at a significance level of p < 0.05, and all single degrees of freedom tests were 2-sided.