The influence of multiple disadvantages on capabilities for healthy diet and activity

Ferrer, Robert Louis; Burge, Sandra K.; Cruz, Inez (2018). 'The influence of multiple disadvantages on capabilities for healthy diet and activity' Paper presented at the annual conference of the HDCA, Buenos Aires, Argentina 2018.

Abstract

One of the important human capabilities is that of enjoying good health, free of preventable illness. The capabilities and functionings necessary to live a healthy life are central to the social determinants of health paradigm, although SDoH scholars have historically not operationalized their analyses in the terminology and framework of  the capability approach (CA). The CA is well-aligned with SDoH, however, providing guidance on both normative and empirical matters. 

In recent studies, we have been examining the obesity epidemic through the lens of capability, evaluating what practical opportunities for healthy patterns of diet and physical activity are available to a disadvantaged Latino population in our city. Beginning with qualitative work, we developed and validated measures of resources and conversion factors for healthy diet and activity. We then applied a structural equation model to demonstrate that the capability measures predict intentions for healthy diet and activity, which in turn predict body mass index (BMI), diet quality, and weekly physical activity minutes.

In this paper, we present data on clustering of disadvantage in capabilities for diet and activity. Our sample consists of 746 patients recruited from a community health center in San Antonio, Texas, USA who sought care for obesity or type 2 diabetes mellitus. Respondents completed a 25-item instrument measuring resources and conversion factors for diet and activity. Examples of survey topics include ability to afford food, availability of healthy shopping, knowledge of food preparation, community safety for walking, and competing household obligations.

 To visually examine person-level clustering of disadvantages, we created a set of radar plots depicting diet and activity resources and conversion factors for respondents in each income group. 

We operationalized clustered disadvantage by identifying which quartile each respondent fell into on each of the 4 capability scales and then summing the quartile ranks for each respondent (e.g. respondents in the bottom quartile for each of 4 scales would score a 4; those in the top quartile for each scale would score 16.) Clustered disadvantage was strongly associated with monthly income category; (Kruskal Wallace chi-sq, 6 df = .0001)). Clustered disadvantage was also strongly associated with higher BMI (ANOVA; F=7.16; p<.0001) over a predicted range from 26 to 38 kg/m2, a span that is very clinically meaningful. Finally, even after controlling for age, sex, race/ethnicity, and income, clustered disadvantage was a strong predictor of physical and mental health status.

These analyses illustrate potential applications of the capability approach to better understanding clustered health disadvantages and their implications. Many of the measured health capability items are actionable at both individual and policy levels, and could point to novel approaches to conceptualizing and improving the personal, social, and environmental contexts for health.

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