Race/Ethnicity Modifies the Relationship Between Diet Quality at the Home- and Individual-Levels and Weight Status Among African American and Hispanic/Latinx Households With Preschool-Age Children

Abstract

Background:

Higher obesity prevalence and poorer diet quality disproportionately impacting groups based on income and race/ethnicity may be partially attributed to the home food environment. This study examined home- and individual-level diet quality with weight status among racially/ethnically diverse households.

Methods:

This cross-sectional study included African American (AA) and Hispanic/Latinx (H/L) households with preschool-age children (n = 97). Home-level diet quality was based on comprehensive home food inventories and individual-level diet quality was based on 24-hour dietary recalls; scores were estimated with the Healthy Eating Index. Child and adult appropriate weight categories based on BMI were estimated with measured heights and weights. Multiple linear regression models (independent variable: weight status, outcome: diet quality scores) with an interaction term for weight status and race/ethnicity and adjusting for potential confounding factors were used to estimate adjusted mean diet quality scores. Postestimation pairwise comparisons of these scores were used to look for within and between group differences by weight status and race/ethnicity.

Results:

Home-level diet quality scores were significantly higher among H/L households compared to AA counterparts regardless of weight status. AA parents with BMI <30 and AA children with BMI <85th percentile had poorer individual-level diet quality scores compared to AA parents and children of lower weight status and all H/L parents and children.

Conclusions:

These findings offer evidence that race/ethnicity modifies the relationship between diet quality and weight among AA and H/L households. Future research needs to examine the distinctive ways race/ethnicity shapes the relationship between weight and diet quality in these households.

Introduction

Diet quality is a prominent contributor to health outcomes^1–3 including obesity.^4,5 Lower-income households and some racial/ethnic groups are disproportionately burdened with poorer quality diets and higher rates of obesity even in children as young as 2–5 years.^6–10 One approach to address this disparity is to impact diet quality by targeting home food availability (HFA). Previous research has consistently shown that HFA is associated with consumption of both healthful (fruits, vegetables) and unhealthful foods (sweetened beverages, sugar, and high fat snacks) among young children, including African American (AA) and Hispanic/Latinx (H/L) children from low-income households.^11–16

While the relationship between HFA and dietary intake is well established, its relationship to weight is less conclusive. In a study of predominantly non-Hispanic white (NHW) children and adolescents, availability of unhealthy high-calorie nutrient poor foods was not related to overweight among children.¹⁷ Similarly, no HFA items were correlated with child BMI in a racially/ethnically diverse sample.¹⁴ However, in a national sample of US adults, greater fruit and vegetable (F/V) availability was associated with lower odds of having overweight or obesity,¹⁸ and similarly, vegetable availability was less common among families who had preschoolers with obesity.¹⁹ This study further investigates the relationship between HFA and weight status. Given the potential for racial/ethnic differences observed by previous home food environment studies among racially/ethnically diverse samples,^16,20–22 this study examined diet quality scores at the home- and individual-levels across categories of weight and race/ethnicity.

Methods

The Study on Children's Home Food Availability using TechNology was a cross-sectional study that examined the home food environments of AA and H/L households with preschool-age children. As previously described, data were collected between November 2014 and March 2016 from parent–child dyads residing in Chicago, Illinois.¹⁶ Our earlier article examined the relationship between individual-level diet quality (based on 24-hour diet recalls) and home-level diet quality (based on observed home food inventories) among AA and H/L households.¹⁶ This study builds on earlier findings and looks specifically at home- and individual-level diet quality with weight status across racial/ethnic groups.

Sample and Setting

We enrolled 97 AA and H/L parent–child dyads. Flyers were placed in settings that assisted low-income families with young children such as Head Start and the Special Supplemental Nutrition Program for Women, Infant, and Children to purposefully recruit households with lower income who had a preschool-age child (2–5 years). Eligibility criteria also included parents who self-identified as either AA or H/L, currently resided in Chicago, IL, and were fluent in English or Spanish. The Institutional Review Board at the University of Illinois Chicago approved the study protocol (No. 2014-0555, approved March 6, 2014), and written informed consent was obtained from all parents participating in the study.

Home Visits

Two home visits were conducted with each household. During the first visit, data on sociodemographics, food security status,²³ family meals,^24–26 and measured heights and weights were obtained. Comprehensive food inventories and 24-hour diet recalls were conducted at both home visits.

Anthropometrics

Weight was assessed using a digital weight scale (SECA, Hanover, MD), and height was measured with a BWB-800 stadiometer (Tanita Corp., Arlington Heights, IL) during the first home visit. Measurements were taken twice and averaged. A third measurement was taken if there was a 0.5 cm difference between height measurements or a 0.2 kg difference in weight measurements. BMI was calculated as weight (kg)/[height (m)]². Obesity status for adults was defined as a BMI ≥30 kg/m.²⁷ Child's weight status was estimated with age- and sex-specific percentiles. A BMI at the 85th percentile and less than 95th percentile is defined as overweight, and a BMI at or above the 95th percentile is defined as obese.²⁸ For this study, the overweight and obese categories were combined to form the higher weight group (i.e., BMI ≥85th percentile) for children.

Dietary Intake

Twenty-four hour recalls were collected from parents at both home visits about their own intake and their child's intake (one per person at each home visit). Most meals (>90%) consumed by children in the study sample were observed by parents, but if a child was in child care during the recall period, parents collected information from the provider regarding food offered and consumed. Data collectors used an automated, multipass approach guided by Nutrition Data for Research (NDSR) software (Version 2014, University of Minnesota) and standardized portion booklets (English and Spanish) to obtain recalls.

Home Food Inventories

Data collection staff completed two in-person home food inventories approximately 2 weeks apart. The process involved conducting comprehensive food inventories in the homes of study participants, which has been extensively described previously.¹⁶ In brief, foods with universal product codes (UPCs) were inventoried with a commercially available mobile application that captured the following: (1) product name, (2) net weight, (3) quantity, and (4) calories per/serving. Research staff later entered these foods into NDSR. Foods without UPCs were photographed and details (food name, net weight, quantity) about the food items were documented in a log. Food item descriptions and the corresponding digital photo assisted in the data entry of those food items in NDSR.

Diet Quality

Diet quality was assessed at two levels and was fully detailed previously.¹⁶ In brief, home-level diet quality was based on two home food inventories, and individual-level diet quality was based on two 24-hour diet recalls. These data were entered into NDSR and diet quality scores were estimated with the Healthy Eating Index 2010 (HEI-2010), which measures adherence to the Dietary Guidelines for Americans.²⁹ Total HEI score equals the sum of all components (total fruit, whole fruit, total vegetables, greens and beans, whole grains, dairy, total protein foods, seafood, plant proteins, fatty acids, refined grains, sodium, and empty calories), with a maximum value of 100, with higher scores indicating better diet quality. Foods were disaggregated into component ingredients and were then assigned to corresponding food groups, which were then converted into food pattern equivalents. The simple scoring algorithm was used to estimate scores.³⁰

Statistical Analyses

Descriptive data were presented as means with standard deviation or proportions. Chi-square or t-tests were used, where appropriate, to test for differences. Home-level diet quality was based on average HEI scores of two home food inventories, and individual-level diet quality used average HEI scores of two 24-hour diet recalls (per parent and child) conducted approximately 2 weeks apart. To estimate adjusted mean diet quality scores, weight status (independent variable) and diet quality (dependent variable) at the home- and individual-levels, respectively, were entered into multiple linear regression models that included an interaction term for weight status and race/ethnicity to examine diet quality differences across weight status categories by race/ethnicity.

The following strata were created in models for diet quality at the home-level and for parents at the individual-level (also referred to as “parent-level diet quality”): H/L parents with BMI <30 kg/m², AA parents with BMI <30 kg/m², H/L parents with BMI ≥30 kg/m², and AA parents with BMI ≥30 kg/m². The following strata were created for models examining individual-level diet quality among children (also referred to as “child-level diet quality): H/L children with BMI <85th percentile, AA children with BMI <85th percentile, H/L children with BMI ≥85th percentile, and AA children with BMI ≥85th percentile. Models controlled for household income, marital status, household size, food security, Special Nutrition Assistance Program participation (yes or no), and family meals from fast-food restaurants.

Postestimation pairwise comparison analyses were used to examine mean differences in diet quality scores between groups (weight status by race/ethnicity); no adjustments for multiple comparisons were made. Statistical tests were two-sided with an alpha of <0.05. Adjusted means with 95% confidence intervals are presented. Analyses were performed using STATA version 14.2 (StataCorp LLC, College Station, TX).

Results

Table 1 displays participant characteristics by parent weight status (BMI <30 kg/m² and BMI ≥30 kg/m²). Participants were similar across all characteristics except for child weight status. The percentage of children with a BMI ≥85th percentile was significantly higher among parents with a BMI ≥30 kg/m² compared to parents with a BMI <30 kg/m² (15.7% vs. 50%; p < 0.001) (Table 1).

Table 1.

Characteristics of Study Participants by Parent Weight Status

	BMI <30 (n = 51), % (n)^*	BMI ≥30 (n = 46), % (n)^*
Age in years
Parent age mean (SD)	32.5 (7.4)	34.4 (8.6)
Child age mean (SD)	3.9 (1.3)	4.0 (1.3)
Race/ethnicity
Hispanic/Latinx	51 (26)	46 (21)
African American	49 (25)	54 (25)
Female
Parent	100 (51)	96 (44)
Child	39 (20)	35 (16)
Educational status
High school/GED or less	57 (29)	37 (17)
Annual income
<$20,000	71 (36)	65 (30)
Marital status
Married or living with a partner	41 (21)	50 (23)
Employment status
Not employed	64.7 (33)	71.7 (66)
Household size
Total adults/children in home mean (SD)	4.3 (2.1)	4.5 (1.5)
Food assistance use
Receiving SNAP	73 (37)	87 (40)
Receiving WIC	57 (29)	65 (30)
Food security status
High or marginal	51 (26)	59 (27)
Low or very low	49 (25)	41 (19)
Family meals from fast food
One time/week or more	60.8 (31)	71.7 (33)
Child BMI percentile^**
≥85th percentile^**	15.7 (8)	50 (23)

Data are presented as % (n) unless otherwise specified.

p-Value <0.001, based on Pearson's chi square.

GED, General Education Developmental Test; SD, standard deviation; SNAP, Supplemental Nutrition Assistance Program; WIC, Special Supplemental Nutrition Program for Women, Infant, and Children.

Adjusted mean total HEI-2010 scores at the home- and individual-levels (i.e., parent-level, child-level) stratified by weight status and race/ethnicity are in Table 2 and component scores are reported in the Supplementary Table S1. Home-level total HEI-2010 scores were significantly lower among AA households compared to all H/L households. There were no significant differences in home-level diet quality scores by weight status within racial/ethnic groups. The adjusted mean home-level total HEI-2010 score for AA households of higher weight status (BMI ≥30 kg/m²) was 48.0, which was significantly lower than H/L households of lower weight status (BMI <30 kg/m²; mean score: 57.8; diff: −9.8 points; p = 0.003) and H/L households of similar weight (mean score: 58.4; diff: −10.4 points; p = 0.003) (Table 2).

Table 2.

Adjusted Mean Diet Quality Scores (Home-Level, Parent-Level, Child-Level) Stratified by Weight Status and Race/Ethnicity

Total HEI score (max: 100)	Home		Parent		Child
Total HEI score (max: 100)	Adj mean	95% CI	Adj mean	95% CI	Total HEI score (max: 100)	Adj mean	95% CI
BMI <30 H/L	57.8^a,b	44.5–71.0	65.8^a,b	51.2–80.5	BMI <85th H/L	68.7^f	53.9–83.5
BMI <30 AA	50.6^a,c	36.5–64.7	38.8^a,c,e	23.2–54.4	BMI <85th AA	52.7^f,g,h	36.8–68.6
BMI ≥30 H/L	58.4^c,d	45.4–71.4	63.5^c,d	49.2–77.9	BMI ≥85th H/L	61.6^h	50.3–81.5
BMI ≥30 AA	48.0^b,d	34.4–61.6	51.5^b,d,e	36.5–66.5	BMI ≥85th AA	65.9^g	50.3–81.5

Adult weight status: BMI <30 kg/m² and BMI ≥30 kg/m²; child weight status: BMI <85th percentile and ≥85th percentile. Means were derived from multiple linear regression models that included an interaction of weight status and race/ethnicity (parent) and adjusted for the following: food assistance participation (SNAP), food security status, income, marital status, number in the household, and family meals prepared away from home. Adult weight status was included in models for home- and parent-level diet quality. Child weight status was included in models for child-level diet quality. Pairwise comparisons tested for differences in HEI-2010 scores between groups. These differences were statistically significant at an alpha of p < 0.05.

BMI <30 H/L vs. BMI <30 AA. ^bBMI <30 H/L vs. BMI ≥30 AA. ^cBMI >30 H/L vs. BMI <30 AA. ^dBMI ≥30 H/L vs. BMI ≥30 AA. ^eBMI ≥30 AA vs. BMI <30 AA. ^fBMI <85th H/L vs. BMI <85th AA. ^gBMI <85th AA vs. BMI ≥85th AA. ^hBMI <85th AA vs. BMI ≥85th H/L.

AA, African American; Adj, adjusted; CI, confidence interval; HEI, Healthy Eating Index; H/L, Hispanic/Latinx; max, maximum.

Similarly, the home-level total HEI-2010 score for AA households of lower weight status (BMI <30 kg/m²) was 50.6, which was significantly lower than H/L households of higher weight status (diff: −7.8 points; p = 0.036) and H/L households of similar weight (diff: −7.2 points; p = 0.039) (Table 2).

Among parents, individual-level total HEI-2010 scores were lowest among AA parents with BMI <30 kg/m². This group had significantly lower diet quality scores compared to all other groups. Specifically, the total individual-level HEI-2010 score for AA parents with BMI <30 was 38.8, which was 27 points lower than H/L parents of similar weight (mean score: 65.8; diff: −27.0 points; p < 0.0001), ∼25 points lower than H/L parents of higher weight status (mean score: 63.5; diff: −24.7 points; p < 0.0001), and ∼13 points lower than AA parents of higher weight status (mean score: 51.5; diff: −12.7; p < 0.0001) (Table 2). The total HEI-2010 score of AA parents of higher weight was 51.5, which was significantly lower than H/L parents of lower weight (diff: −14.3 points; p = 0.002) and H/L parents of similar weight (diff: −12.0 points; p = 0.002).

Among children, AA children with BMI <85th percentile had significantly lower HEI-2010 scores compared to all other groups. Specifically, the total HEI-2010 score of this group was 52.7, which was significantly lower than H/L children of higher weight status (mean score: 61.6; diff: −8.9 points; p = 0.031), H/L children of similar weight status (mean score: 68.7; diff: −16 points; p < 0.0001), and AA children of higher weight status (mean score: 65.9; diff: −13.2 points; p = 0.002) (Table 2).

Discussion

This study examined diet quality at both the home-level (based on comprehensive in-home food inventories) and at the individual-level (based on dietary recalls) with weight status in a racially/ethnically diverse sample. We found some differences in home- and individual-level diet quality scores by weight status, but this was modified by race/ethnicity. Specifically, home-level diet quality scores were higher among H/L households compared to AA households across weight categories. H/L households also had higher individual-level diet quality scores compared to their AA counterparts, but no within group differences were observed among H/L households by weight. Individual-level diet quality scores were poorest among AA parents and children of lower weight status compared to all parents and children in the study sample.

Data from UDSA's National Food Acquisition and Purchase Survey (FoodAPs), which commonly reports HEI scores using “food at home” (FAH) purchase data (e.g., groceries) from nationally representative sample, found no differences in HEI-2010 scores (based on FAH) among households who had a child with obesity compared to households who did not.³¹ However, those findings were not stratified by race/ethnicity. In our study, home-level HEI scores only differed significantly when we compared AA with H/L households regardless of weight. A more recent FoodAPs study reported that non-Hispanic Black households classified as obese had an average HEI score (based on FAH) of 48.8, which is consistent with the average home-level HEI score (score: 48) we found among AA households with BMI ≥30.³² In contrast, we did not find a significant difference in HEI score by weight status among AA households. However, our findings for H/L households were similar in that there was no significant difference in HEI-scores by weight among H/L households.³²

In our study, individual-level HEI scores were significantly lower among AA parents compared to H/L parents regardless of weight status. Previous studies, consisting of nationally representative samples and low-income households, also found AA groups with lower diet quality scores compared to their H/L counterparts.^33–35 The higher diet quality scores of H/L households in our study may be partially explained by acculturation, which has been shown to be inversely associated with diet quality scores among Mexican Americans based on National Health and Nutrition Examination Survey (NHANES) data.³⁶ This is consistent with our study sample of H/L parent–child dyads who are less acculturated and primarily of Mexican descent.¹⁶

AA children with BMI <85th percentile had poorer diet quality scores compared to AA children of higher weight (BMI ≥85th percentile) and all H/L children. A previous study based on NHANES data (2009–2014) found lower diet quality scores among AA children compared to H/L children within similar weight categories.³⁷ Our findings contrast in that AA children with BMI <85th percentile had poorer diet quality scores compared to H/L and AA children of higher weight status. AA parents of lower weight status also had poorer diet quality scores than their higher weight counterparts. It was unexpected that diet quality scores were poorest among AA parents and children in the lower weight categories compared to all other groups in this sample, including AA parents and children of higher weight status. Further examination of component scores (Supplementary Table S1) allowed us to determine that both adequacy and moderation components contributed to poor total diet quality among lower weight AA parents and children. AA parents had significantly lower scores in 6 of 9 adequacy components (total vegetables, total fruits, whole fruits, whole grains, dairy, seafood, and protein). Their moderation scores were lower, relative to other groups; however, a statistically significant difference was only seen with empty calories. Similarly, lower weight AA children also scored significantly lower in 6 of 9 adequacy components (greens and beans, total fruits, whole fruits, whole grains, dairy, fatty acids) and 2 of 3 moderation components (refined grains and sodium). Fewer differences were observed at the home-level, but scores for whole fruits and empty calories were significantly lower among lower weight households compared to their counterparts.

Factors within the home food environment may explain some of the racial/ethnic differences observed in this study. Prior research has demonstrated that the types of fruits and vegetables available in the home (fresh, canned, frozen) vary by race/ethnicity,^38,39 with H/L households being twice as likely to have fresh fruits and three times as likely to have fresh vegetables compared to AA households.³⁸ The variations in F/V availability in the home may be due to cultural factors as H/L households attempt to maintain their traditional diets.^40,41 Research has shown that H/L adults consistently report higher F/V consumption than AA adults,^42,43 which may explain why in the present study, H/L parents had higher total diet quality scores than AA parents regardless of weight status. H/L households may be more physically and socially supportive of healthier diets (e.g., fresh fruit displayed in the open),^17,38,44 which may translate to a healthier home food environment resulting in better diet quality for all household members.^17,20,45,46 Previous research also proposes that H/L individuals exhibit higher levels of “nutrition resilience.”⁴⁷ This term suggests that there are groups which, despite being constrained by socioeconomic status or other disadvantages, exhibit positive food-related attitudes that may translate to better quality diets. However, more research is needed to understand factors that explain nutrition resilience in H/L groups and whether it varies by acculturation.

Still, a clearer understanding of factors explaining racial/ethnic differences and the mechanisms driving the relationship between home-level diet quality and weight are still needed. Given that race/ethnicity is a social construct, we cannot fully understand how to reduce inequities until we recognize the critical social determinants driving disparities in diet quality and weight. Use of multilevel, health equity frameworks should be used to gather contextual data (social, economic, environmental),⁴⁸ which may help us understand which factors determine how AA and H/L families to attain and maintain higher-quality diets.

A main strength of this study includes using an objective method to measure and assess the home food environment of two populations at greater risk for obesity and related comorbidities. Since nearly all foods in the home are captured, this approach makes it possible to evaluate diet quality of the home food environment using the HEI, which is a validated and commonly used index for diet quality. Limitations of the present study include the inclusion of only AA and H/L households with young children in a large urban setting, limiting the ability to generalize findings to other populations. Even though dietary intake assessed with multiple 24-hour recalls are less biased than other dietary assessment methods (e.g., food frequency questionnaires), all self-reported dietary assessment methods are prone to errors (e.g., random and systematic).⁴⁹ In addition, recalls were scheduled and not assessed at random which could have affected parents' recall of their children's diets⁵⁰ and had to rely on multiple proxies (parent, child care provider) for a small sample of participants. Another potential limitation is that these data only reflect diet quality during a specified period of time (2014–2016); however, trend data from NHANES suggest that diet quality scores tend to be fairly stable over time.⁵¹ For instance, HEI scores only decreased over time (from 2011 to 2018) among non-Hispanic white US adults, but not in other racial/ethnic groups.⁵¹ Finally, the present study is cross-sectional, and therefore, causal inferences between diet quality and weight status cannot be made.

Conclusions

Home- and individual-level diet quality in relationship to weight are modified by race/ethnicity. Future research should use approaches appropriate for examining contextual factors that may be critical determinants of diet quality and obesity. This information could be used in developing interventions and policies that would help racially/ethnically diverse households equitably access and maintain healthful diets.

Impact Statement

These findings provide evidence of the modifying effect of race/ethnicity on diet quality and weight. Given that race is socially constructed, addressing disparities in racially/ethnically diverse populations require a better understanding of the contextual factors (e.g., social, environmental, economic) that may be driving the relationship between diet quality and obesity.

Footnotes

Acknowledgments

We thank all research assistants and study participants for their time and support in this project.

Authors' Contributions

A.K. and M.F. designed the study and A.K. directed all aspects of study implementation and data collection. L.S. managed and prepared the data for analyses. A.K. and C.H. analyzed the data. A.K. and J.S.F. prepared the article and all authors contributed to and approved the final version of the article.

Disclaimer

This article's content is solely the authors' responsibility and does not necessarily represent the official views of the National Institutes of Health.

Ethics Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board of University of Illinois, Chicago (protocol no. 2014-0055; March 6, 2014), for studies involving humans.

Informed Consent Statement

Written informed consent was obtained from all parents involved in the study.

Data Availability Statement

The data used to support the findings of this study are available from the corresponding author upon request.

Funding Information

This study was funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development at the National Institutes of Health (Grant No. R21HD080157). Dr. Sanchez-Flack was supported by a training grant from the National Cancer Institute (T32CA057699) and by the Chicago Cancer Health Equity Collaborative (ChicagoCHEC) grants: U54CA202995, U54CA202997, U54CA203000 provided by the NCI U54 Comprehensive Cancer Partnership to Advance Cancer Health Equity.

Author Disclosure Statement

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the article; or in the decision to publish the results.

Supplementary Material

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