Physical activity and body mass index inequities among adult women in the United States: An application of intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy (I-MAIHDA)

Using intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy (I-MAIHDA) on 2015-2020 NHANES data, this study reveals that physical activity and body mass index inequities among US adult women are significantly shaped by the intersection of race/ethnicity, age, education, nativity, and work status, with specific subgroups such as Black and Asian women and those with lower educational attainment facing the greatest disparities.

The Gist

Imagine your health as a garden. Two of the most important plants in this garden are Physical Activity (how much you move and exercise) and Body Mass Index (a measure of your weight relative to your height). For women in the United States, these two plants are crucial because they determine how strong the "heart tree" in the center of the garden will grow.

However, not every garden gets the same amount of sunlight or water. Some women's gardens are thriving, while others are struggling. This study asked a big question: Why are some gardens doing better than others?

The "Recipe" for Inequality

Usually, researchers look at one ingredient at a time. They might ask, "Does race matter?" or "Does age matter?" or "Does your job matter?"

But this study realized that life isn't a single ingredient; it's a complex recipe. A woman isn't just "Black" or just "older"; she is a unique mix of many things at once: her race, her age, how much schooling she has, where she was born, and whether she works.

The researchers used a special, high-tech kitchen tool called I-MAIHDA. Think of this tool as a super-magnifying glass that can look at all these ingredients mixed together at the same time. Instead of seeing just "race" or just "age," it sees the specific "flavor" of being, for example, a 40-year-old Black woman born in another country with a high school diploma.

What Did They Find?

The researchers looked at data from over 4,500 women (like tasting a huge batch of soup to see what's in it) and discovered a few key things:

1. The "Secret Sauce" is Mostly Social: They found that about 97% to 99% of the differences in how active women are and what their weight is, comes down to these social ingredients (race, age, education, where you were born, and your job). It's not just bad luck or biology; it's the "recipe" of your life circumstances.
2. Who is Struggling the Most?
   • Physical Activity: The "gardens" with the least movement tended to belong to Asian and Black women, those between 35 and 49 years old, women born outside the US, and those who didn't finish high school. Imagine these women trying to run a race while carrying a heavy backpack full of extra responsibilities.
   • Body Weight: The "gardens" with the highest weight tended to belong to Black and Hispanic/Latino women, and those under 64 years old.

The Big Takeaway

Think of the study's conclusion as a map for a better future.

The researchers are saying, "We can't just tell everyone to 'eat better and move more' with a generic instruction manual." That doesn't work because everyone's garden has different soil and weather.

Instead, we need tailored strategies. If we want to help women grow healthy hearts, we need to understand the specific "recipe" of their lives. We need to design health programs that fit the unique experiences of a young immigrant woman with a high school diploma, or an older Black woman with a college degree.

By understanding these specific intersections, we can stop treating all women the same and start giving the right kind of sunlight and water to the gardens that need it most.

Technical Summary

Problem Statement

Physical activity (PA) and Body Mass Index (BMI) are critical determinants of cardiovascular risk, particularly among women in the United States. While existing literature acknowledges disparities in these metrics, there is a significant gap in research regarding how intersectional social axes (the complex interplay of multiple social identities) jointly shape inequities in PA and BMI. Traditional approaches often examine single demographic factors in isolation, failing to capture the unique experiences of women situated at the intersections of race/ethnicity, age, education, nativity, and work status. This study aims to address this gap by quantifying how these intersecting identities contribute to health disparities.

Methodology

The study employed a rigorous quantitative approach using data from the 2015–2020 National Health and Nutrition Examination Survey (NHANES).

• Sample: The analysis focused on adult women, with sample sizes of $n=4,591$ for Physical Activity and $n=4,596$ for BMI.
• Statistical Framework: The researchers utilized Intersectional Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (I-MAIHDA). This advanced technique allows for the examination of variance across intersectional strata (combinations of social categories) rather than just main effects.
• Variables:
  • Outcomes: Physical Activity (PA) and Body Mass Index (BMI).
  • Intersectional Strata: Defined by five key axes: Race/Ethnicity, Age, Education, Nativity (place of birth), and Work Status.
• Modeling: Linear models were used to estimate additive fixed effects and quantify the contribution of specific strata to the observed variance in health outcomes.

Key Contributions

• Application of I-MAIHDA: This study is notable for applying the I-MAIHDA framework to PA and BMI inequities among US women, a method that effectively disentangles individual heterogeneity from group-level discrimination.
• Intersectional Granularity: By defining strata through the combination of five social axes, the study moves beyond single-axis analyses to provide a nuanced view of how overlapping identities create unique health profiles.
• Variance Decomposition: The study explicitly quantifies the proportion of variance explained by the intersectional strata versus the residual variance, offering a clear metric of how much social identity drives health disparities.

Key Results

• Variance Explanation:
  • In the null model, the intersectional strata collectively explained 4.6% of the variance in Physical Activity inequities and 13.8% of the variance in BMI inequities.
  • The remaining variance was attributed to the individual axes (age, race/ethnicity, education, nativity, and occupation status), which accounted for 99.2% of PA variance and 97.5% of BMI variance.
• Predicted Means for Physical Activity (Lowest PA):
  • Asian and Black women
  • Women aged 35–49 years
  • Women born outside the US (non-US natives)
  • Women with less than a high school diploma
• Predicted Means for BMI (Highest BMI):
  • Black and Hispanic/Latino women
  • Women younger than 64 years

Significance and Implications

The findings demonstrate that while individual demographic factors (like age and race) explain the vast majority of variance, the specific intersectional combinations of these factors are critical in identifying the most vulnerable subgroups.

• Targeted Interventions: The identification of specific high-risk strata (e.g., foreign-born Asian women with low education) allows for the development of tailored health promotion strategies rather than one-size-fits-all approaches.
• Policy Relevance: The study provides empirical evidence to support policy-informed strategies that address the structural and social determinants of health. By understanding how lived experiences shaped by these social identities influence PA and BMI, public health initiatives can be better designed to reduce cardiovascular risk inequities among US women.