Diet Quality of Midwest Adolescents and Young Adults With Intellectual Disabilities and Overweight/Obesity Differs by Diagnosis but Not by Weight Category

Abstract

Background

Poor diet may contribute to high rates of overweight/obesity (OW/OB) in adolescents and young adults with intellectual disabilities (IDs).

Objective

The purpose of this study was to examine diet quality as assessed by Healthy Eating Index 2015 (HEI-2015) scores in adolescents and young adults with IDs and OW/OB and to compare diet quality by ID diagnosis and weight.

Design

Three-day image-assisted food records from baseline assessments in an 18-month weight-loss trial for adolescents and young adults with IDs and OW/OB were used to calculate HEI-2015 scores, which were compared between ID diagnoses and weight categories.

Participants/setting

A total of 102 adolescents and young adults (aged 13 to 21 years) with IDs (48 with Down syndrome [DS], 40 with autism, and 14 with other/unspecified IDs) and OW/OB at a Midwestern academic medical center completed valid food records from November 2015 to November 2019.

Main outcome measures

Outcome measures included HEI-2015 scores, energy intake (kcal/d), macronutrient intake as percentage of energy, energy intake per kilogram body weight, and grams protein per kilogram body weight.

Statistical analyses performed

Differences in HEI-2015 scores and additional dietary measures by weight category and ID diagnosis were examined with analysis of variance or Kruskal–Wallis tests.

Results

Participants with DS had a significantly higher mean ± SD HEI-2015 score (53.9 ± 8.4) compared with participants with autism (49.1 ± 9.6; P = .047). Compared with those with autism, participants with DS had a higher percentage of energy from protein, higher energy intake per kilogram body weight, and higher grams of protein intake per kilogram body weight. For HEI-2015 components, participants with DS had higher scores than participants with autism for total fruits, whole fruits, total vegetables, greens and beans, and total protein foods, but lower scores for sodium. Diet quality was not observed to differ by weight classification.

Conclusions

Adolescents and young adults with autism had lower overall diet quality scores compared with those with DS. Diet quality was not found to be related to OW/OB. Understanding dietary differences by ID diagnosis may inform intervention strategies.

Intellectual disabilities (ids) originate in early life and are characterized by substantial limitations in both intellectual functioning (IQ <75) and adaptive behaviors, typically manifesting before age 22 years.¹ IDs are present in approximately 33% of children with autism spectrum disorder²; are a prominent feature of Down syndrome (DS)³; and may co-occur with other developmental disabilities, including cerebral palsy and fetal alcohol syndrome.¹ People with IDs experience numerous disparities in health,⁴ including lifestyle-related conditions, such as obesity. Adolescents and young adults with IDs experience overweight and obesity (OW/OB) up to 1.8 times the rate of their typically developing peers.⁵ Prevalence of OW/OB in this population ranges from approximately 60% in children and adolescents with DS to approximately 42% among adolescents with autism.^6–8 OW/OB contributes to the increased prevalence of sleep apnea and cardiovascular disease^9–11 and elevated risk of developing type 2 diabetes¹² observed in individuals with IDs, and may limit opportunities for employment and lead to social stigma.¹³ Without aggressive efforts toward prevention and treatment, adolescent OW/OB frequently carries over into adulthood.^14,15 Thus, adolescence is a critical period in which to intervene on weight-related behaviors.^16,17

Diet is a primary contributor to OW/OB in adolescents and young adults with IDs.¹⁸ In the general population, adolescents begin to have more autonomy and control over dietary choices, may acquire lifelong dietary habits,¹⁹ and typically have the lowest diet quality of any age group throughout the lifespan.²⁰ However, adolescents and young adults with IDs have additional barriers to healthy diet beyond the typical adolescent diet. For instance, those with autism frequently experience food sensitivity and selectivity,²¹ with approximately 90% of children with autism experiencing feeding difficulties and 70% described as selective eaters.^22–24 Furthermore, those with high levels of autistic traits (eg, social and communication deficits, restricted interests, or behavioral patterns) have even poorer diet quality and lower food variety, making them a nutritionally vulnerable group.²⁵ For those with DS, dietary intake may be impacted by the presence of celiac disease, which affects 5% to 6% of the DS population compared with 0.5% to 1% of the general population,^26,27 and oral motor difficulties from a young age, which may affect chewing and swallowing behaviors.²⁷ These early feeding difficulties may require calorie supplementation²⁸ or alterations in feeding, such as increased caloric or thickened liquid intake,²⁹ which, if they persist into adolescence and adulthood,³⁰ may contribute to the high obesity rates across the lifespan in individuals with DS.³¹ Understanding how diet quality is associated with the unique characteristics and health profiles in individuals with different ID diagnoses could potentially inform personalized clinical and targeted community-level interventions in this population.

As a critical driver of weight and other health outcomes, diet remains a modifiable factor that may have a long-lasting impact on the development and treatment of OW/OB in adolescents and young adults with IDs, and deserves further exploration. Previous studies have reported on the diet quality of adolescents with IDs,^21,32,33 however, we are unaware of research that has examined diet quality by ID diagnosis (ie, DS, autism, or other) in adolescents with IDs and OW/OB. The purposes of the current study were to 1) describe the overall and specific components of diet quality in adolescents and young adults with ID and OW/OB; 2) compare overall diet quality and components of diet quality across individuals with common types of ID, including DS, autism, and other/unspecified ID; and 3) compare diet quality by weight category.

METHODS

This study was a secondary analysis of baseline diet data from an 18-month randomized controlled weight-loss trial for adolescents and young adults with IDs and OW/OB, described in detail elsewhere.³⁴ The trial, approved by the University of Kansas Medical Center Institutional Review Board and registered at ClinicalTrials.gov (Number: NCT02561754), was conducted in the United States at an academic medical center in the Midwest with data used for this analysis collected between November 2015 and November 2019. All outcomes were collected during a single study visit, which was conducted at each participant’s home.

Participants

Participants were adolescents and young adults (aged 13 to 21 years) with mild-to-moderate IDs (IQ range, 40 to 74), as verified by a primary care physician and with OW defined as a body mass index (BMI; calculated as kg / m²) ≥85th percentile on Centers for Disease Control and Prevention growth charts³⁵ for those aged ≤19 years, BMI ≥25 for those aged ≥19 years, or waist-to-height ratio >0.5, which indicates excess central adiposity in children and adolescents.^36–39 In addition, inclusion criteria included caregiver-reported sufficient functional ability to understand directions and communicate through spoken language, living at home with a parent or guardian, and with internet access in the home. Participants were excluded if they had caregiver-reported type 1 diabetes or type 2 diabetes treated with insulin; Prader-Willi syndrome; participated in a weight-management program involving diet and physical activity in the past 6 months; or an eating disorder, serious food allergies, or inability to participate in moderate-to-vigorous physical activity. Participants were recruited through local community programs serving adolescents with IDs and using print and web advertisements in the target area. Participant and guardian assent/consent was obtained for all participants.

Outcomes

Demographics Characteristics.

Basic demographic information was collected from caregivers, including age, sex, race, ethnicity, primary ID diagnosis, and level of support needed (mild or moderate).

Anthropometrics.

Weight was calculated as the mean of duplicate measurements to the nearest 0.1 kg using a calibrated digital scale (Model #PS6600, Belfour). Participants wore shorts and a t-shirt. Standing height without shoes was calculated as the mean of duplicate measurements to the nearest 0.1 cm with a portable stadiometer (Model IP0955, Invicta Plastics Limited). For those aged 13 to 19 years, BMI z scores were calculated using the Centers for Disease Control and Prevention growth charts,³⁵ as BMI is not an accurate measure for adolescents younger than 20 years of age due to their nonlinear growth trajectories.⁴⁰ For those 20 to 21 years of age, weight and height were used to calculate BMI.

Dietary Intake.

Dietary intake was assessed using 3-day image-assisted food records. This method has demonstrated acceptable reliability in a comparable sample of adolescents with ID and estimates energy intake within 9% of total daily energy expenditure measured by doubly labeled water.⁴¹ To complete the image-assisted food records, the participant, with caregiver help as needed, was asked to fill out a hard-copy food record for the 3 consecutive days (including 2 weekdays/1 weekend day) before the home study visit. Participants were also asked to take before and after digital images of all foods and beverages consumed using an iPad (Apple Inc) provided by the study. The hard-copy food record accounted for food and beverage type and estimated portion size and additional details that would not be discernable from digital images (eg, nonfat vs whole milk). During the home visits, study staff reviewed the food record and digital images, with both the participant and a parent (if needed), clarifying any ambiguous or conflicting information. Data from the food record were used when digital images of a meal were not available (eg, meals at school). Nutrient content was determined using the Nutrition Data System for Research, version 2017, developed by the Nutrition Coordinating Center, University of Minnesota.⁴² Data were entered by research staff and checked by a registered dietitian with at least 1 year of experience using the Nutrition Data System for Research. Before analysis, diet outcome data were reviewed for plausibility and accuracy by the study team (eg, records were excluded if they did not represent a typical day (eg, holiday), the participant forgot 1 or more meals, or if the mean daily energy intake across the 3 days was <500 kcal/d). Records were included if they had 1, 2, or 3 days of valid data.

Diet Quality.

Data obtained from the food records were used to calculate diet quality index scores using the 2015 Healthy Eating Index (HEI-2015). In 1995, the US Department of Agriculture published the first HEI, with subsequent versions reflecting updates to the Dietary Guidelines for Americans (DGA).⁴³ The HEI-2015 assesses conformance to the 2015-2020 DGA.^16,44 The HEI-2015 assesses the following 13 different dietary components: adequacy of intake of total fruit (including 100% fruit juice), whole fruit (excludes juice), total vegetables, dark green vegetables and beans, whole grains, dairy, total protein foods, seafood and plant proteins, and fatty acids, and the moderation of intake of refined grains, sodium, added sugars, and saturated fats. The HEI-2015 provides a point value (up to either 5 or 10 points per component) based on how well a person meets the DGA.⁴⁴ Point values for all categories are summed to obtain the total HEI-2015 with a maximum value of 100; higher scores for adequacy components indicate higher intake, whereas higher scores for moderation components indicate lower intake. Higher overall scores correspond with better diet quality. The HEI-2015 simple scoring algorithm method was applied to describe mean diet quality for the sample.⁴⁵

Dietary Measures.

In addition to diet quality, food records were also used to determine mean energy intake (kcal/d), percent macronutrient intake, energy intake per kilogram body weight, and grams protein per kilogram body weight.

Analysis

Means ± SD are used to describe diet quality overall and of the 13 dietary components. Normality of the distribution of each outcome was determined by Shapiro-Wilk test. Analysis of variance or Kruskal–Wallis tests were used to examine differences in HEI-2015 scores, energy intake, percentage of macronutrient intake, energy intake per kilogram body weight (kcal/kg/d), and grams protein per kilogram body weight (g/kg/day) by diagnostic category (autism, DS, and other/not-specified IDs).

To examine the relationship between HEI-2015 and weight status, differences in HEI-2015 scores by weight category were examined with analysis of variance tests. Five weight categories were determined using current guidelines from Centers for Disease Control and Prevention and American Academy of Pediatrics⁴⁶ in order to combine the weight status of the adolescents with that of young adults. These categories were determined by BMI percentile for those aged 13 to 19 years and by BMI for those aged 20 to 21 years. All analyses were performed using IBM SPSS Statistics, version 27,⁴⁷ with statistical significance at P < .05.

RESULTS

A total of 102 (of 110 enrolled) adolescents and young adults (aged 13 to 21 years) with IDs completed 1 to 3 days of valid food records. The sample included 48 participants with DS, 40 with autism, and 14 with other/unspecified IDs.

Demographic and anthropometric characteristics are described in Table 1.

Table 1.

Descriptive characteristics and dietary intake from baseline data of an 18-month randomized controlled weight-loss trial with 102 adolescents and young adults with intellectual disabilities and overweight or obesity at a Midwestern academic medical center from 2015 to 2019

Characteristic	Data
Age (y), mean ± SD	16.7 ± 2.3
Sex, female, n (%)	53 (52)
Diagnosis, n (%)
Autism	40 (39.2)
Down syndrome	48 (47.1)
Other/not specified	14 (13.7)
Support level, n (%)
Mild intellectual disability	60 (58.8)
Moderate intellectual disability	42 (41.2)
Race, n (%)
White	89 (87.3)
Black	7 (6.9)
2 or more races	6 (5.9)
Ethnicity, n (%)
Hispanic/Latino	7 (6.9)
No. of days of valid food records, n (%)
1	4 (3.9)
2	9 (8.8)
3	89 (87.3)
BMIa (ages 20-21 y), mean ± SD	37.3 ± 10.2
BMI z score (ages 13-19 y), mean ± SD	1.9 ± 0.5
Energy intake (kcal/d), mean ± SD	1933 ± 569
Energy intake per kilogram body weight (kcal/kg/d), mean ± SD	24.8 ± 8.0
Protein per kilogram body weight (g/kg/d), mean ± SD	0.99 ± 0.4
HEI-2015b total score, mean ± SD	51.3 ± 9.5

^aBMI = body mass index; calculated as kg / m².

^bHEI-2015 = Healthy Eating Index 2015.

Differences in Diet Quality by Diagnosis

Overall, adolescents and young adults with IDs had a mean ± SD HEI-2015 score of 51.3 ± 9.5, with mean 35.3% of energy intake from fat, 48.4% of energy intake from carbohydrates, and 16.3% of energy intake from protein, and mean ± SD energy intake of 1933 ± 569 kcal/d. Those with DS had a mean ± SD HEI-2015 score of 53.9 ± 8.4, which was significantly higher compared with those with autism (49.1 ± 9.6; P = .047), but not unspecified IDs (48.9 ± 11.1; P = .19). Those with DS also had higher energy intake per kilogram body weight (27.4 ± 8.2 kcal/kg/d) compared with those with autism (22.4 ± 7.6; P = .009), and had higher protein intake per kilogram body weight (1.16 ± 0.4 g/kg/d) compared with those with autism (0.83 ± 0.3; P < .001) or other ID (0.9 ± 0.4; P = .03). Significant differences between diagnostic groups were observed for percent energy intake per day from protein and for the following HEI-2015 component scores: total fruits, whole fruits, total vegetables, greens and beans, total protein foods, and sodium. Post-hoc analyses indicated that, compared with those with autism, participants with DS had a significantly higher percent of energy intake from protein (P = .006), and significantly higher HEI-2015 component scores on total fruits (P = .002), whole fruits (P = .001), total vegetables (P = .01), greens and beans (P = .03), and total protein foods (P = .003), but significantly lower diet quality in sodium intake (P = .048). Those with DS also had significantly higher scores on total vegetables and lower diet quality on sodium intake compared with those with other/unspecified IDs (all, P < .05). Table 2 describes the overall dietary outcomes and outcomes by diagnosis.

Table 2.

Dietary intake and quality in 102 adolescents and young adults with overweight and obesity and intellectual disabilities from baseline data of an 18-month randomized controlled weight-loss trial at Midwestern academic medical center from 2015 to 2019

Variable	Overall (N = 102)	Autism (n = 40)	DSa (n = 48)	Other IDb (n = 14)	F test or Kruskal–Wallis statistic	P valuec	Tukey’s post-hocd (P valuec)
	mean ± SD
HEI-2015e total score (0-100)	51.3 ± 9.5	49.1 ± 9.6	53.9 ± 8.4	48.9 ± 11.1	3.43	.036	DS > autism (.047)
Energy intake (kcal/d)	1933 ± 569	2025 ± 710	1870 ± 463	1887 ± 429	0.47f	.79	—
Energy intake/kg body weight (kcal/kg/d)	24.8 ± 8.0	22.4 ± 7.6	27.4 ± 8.2	23.0 ± 5.6	5.09	.008	DS > autism (.009)
Protein/kg body weight (g/kg/d)	0.99 ± 0.4	0.83 ± 0.3	1.16 ± 0.4	0.90 ± 0.4	17.58f	<.001	DS > autism (<.001)  DS > other (.03)
Percent daily energy intake from macronutrients
Fat	35.3 ± 5.9	34.6 ± 6.2	35.6 ± 5.7	36.2 ± 5.6	0.46	.63	—
Carbohydrate	48.4 ± 7.3	50.1 ± 7.4	47.1 ± 7.0	48 ± 7.7	2.00	.14	—
Protein	16.3 ± 3.9	15.2 ± 4.2	17.3 ± 3.4	15.8 ± 4.2	10.05f	.007	DS > autism (.006)
HEI-2015 component scores
Adequacy components
Total fruits (0-5)	2.33 ± 1.5	1.70 ± 1.5	2.84 ± 1.4	2.38 ± 1.5	12.18f	.002	DS > autism (.002)
Whole fruits (0-5)	2.56 ± 1.6	1.83 ± 1.7	3.14 ± 1.4	2.67 ± 1.5	13.84f	.001	DS > autism (.001)
Total vegetables (0-5)	2.71 ± 1.37	2.36 ± 1.5	3.20 ± 1.2	2.03 ± 1.2	12.31f	.002	DS > autism (.01) DS > other (.02)
Greens and beans (0-5)	1.28 ± 1.62	0.92 ± 1.4	1.77 ± 1.8	0.58 ± 1.1	10.07f	.011	DS > autism (.03)
Whole grains (0-10)	3.80 ± 2.9	4.13 ± 3	3.62 ± 2.9	3.51 ± 3	1.21f	.55	—
Dairy (0-10)	6.77 ± 2.5	7.03 ± 2.3	6.87 ± 2.6	5.66 ± 2.5	3.62f	.16	—
Total protein foods (0-5)	3.95 ± 1.1	3.50 ± 1.2	4.42 ± 0.7	3.61 ± 1.2	12.09f	.002	DS > autism (.003)
Seafood/plant proteins (0-5)	1.10 ± 1.4	0.89 ± 1.3	1.27 ± 1.4	1.11 ± 1.3	2.08f	.35	—
Fatty acids (0-10)	5.19 ± 2.7	4.98 ± 3	5.15 ± 2.5	5.93 ± 2.6	1.39f	.52	—
Moderation componentsg
Refined grains (0-10)	5.66 ± 2.6	5.43 ± 2.6	5.92 ± 2.5	5.44 ± 3.0	1.09f	.58	—
Sodium (0-10)	3.85 ± 2.4	4.34 ± 2.4	3 ± 1.9	5.25 ± 2.7	11.57f	.004	DS < autism (.048) DS < other (.009)
Added sugars (0-10)	6.9 ± 2.2	6.66 ± 2	7.28 ± 2.3	6.31 ± 2.5	3.79f	.14	—
Saturated fats (0-10)	5.22 ± 2.8	5.32 ± 2.9	5.36 ± 2.8	4.45 ± 2.5	2.43f	.3	—

^aDS = Down syndrome.

^bID = intellectual disability.

^cBold type indicates statistical significance.

^dPost-hoc tests include correction for multiple tests.

^eHEI-2015 = Healthy Eating Index 2015.

^fKruskal–Wallis test.

^gModeration components are reversed-scored, such that a higher score indicates lower intake.

Association of Diet Quality With Energy Intake and Weight

Table 3 indicates that no differences in HEI-2015 overall scores by weight category were observed in the total sample (all, P > .05).

Table 3.

Diet quality by weight and diagnostic categories of 102 Midwest adolescents and young adults with overweight/obesity and intellectual disabilities from 2015 to 2019

Variable	Healthy weighta	Overweightb	Obesity class			ANOVAf results
			1c	2d	3e
	mean ± SD (n)
HEI-2015g total scores (all participants)	46.6 ± 13 (7)	52 ± 9 (25)	52.3 ± 8.9 (36)	53.8 ± 10 (16)	48.1 ± 9.2 (18)	F(4,97) = 1.37, P = .25
Autism	43.4 ± 10 (4)	53.1 ± 10.1 (5)	46.8 ± 7.8 (11)	53.7 ± 10.8 (10)	47.3 ± 9 (10)	—h
Down syndrome	48.5 ± 0 (1)	52.9 ± 8.5 (18)	55.6 ± 8.1 (18)	53.9 ± 9.5 (6)	52.2 ± 10 (5)	—h
Other intellectual disability	52.3 ± 24.6 (2)	40.8 ± 3 (2)	52.6 ± 9.1 (7)	—h	43.6 ± 9.2 (3)	—h

^aHealthy weight: <85th percentile or body mass index (BMI) <25 but waist-to-height ratio >0.5.

^bOverweight: 85th percentile to <95th percentile or BMI 25 to <30.

^cObesity class 1: ≥95th percentile to <120% of 95th percentile or BMI 30 to <35.

^dObesity class 2: ≥120% to <140% of 95th percentile or BMI 35 to <40.

^eObesity class 3: ≥140% of 95th percentile or BMI ≥40.

^fANOVA = analysis of variance.

^gHEI-2015 = Healthy Eating Index 2015.

^hGroups too small for analysis.

DISCUSSION

Overall diet quality in the sample was low, with an HEI-2015 score of 51.3 of a potential 100. A recent analysis of 3281 adolescents aged 12 to 18 years reported that adolescents had a mean HEI-2015 total score of 52,²⁰ which is only slightly higher than the mean total score (51.3) in this sample. Diet quality was highest in participants with DS and significantly higher compared with participants with autism. Diet quality did not differ by weight in this sample.

Although diet quality was low overall, those with DS had significantly better diet quality scores than those with autism, including higher percent of energy intake from protein and better component scores for total fruits, whole fruits, total vegetables, and greens and beans, although worse sodium scores. Poor diet quality is often found in children and adolescents with autism who have unique sensory issues around foods²¹ and express food selectivity and sensitivity.^48,49 An analysis including 4092 children with autism found that higher autistic traits scores were associated with lower intake of fruits, vegetables, whole grains, and fish, indicating that those with higher support needs may be particularly at risk of having poorer diet quality.⁵⁰ Similar to the current findings, a study of 154 children with autism by Mathew and colleagues⁵¹ found that those with higher autistic traits had lower protein intake and higher percentage of simple carbohydrate intake. Understanding components of diet quality in those with autism may help researchers and clinicians identify ways to improve diet quality for this population.

Results of analyses of the National Health and Nutrition Examination Survey demonstrated that diet quality typically declines in adolescence compared with earlier childhood.^52–54 Compared with typically developing adolescents, previous research suggests that adolescents with DS have higher diet quality than typically developed peers, and those with autism have lower diet quality. For example, a study comparing 143 adolescents with DS to 100 typically developed adolescents found better diet quality in those with DS who scored 52.7 on the HEI-2015 compared with 45.1 in those without DS (P < .0001).³³ This study also determined that adolescents with DS had higher total fruits and greens and beans HEI component scores compared with typically developing adolescents.³³ A smaller study (n = 12) found that children and adolescents (aged 8 to 18 years) with DS had higher HEI-2010 overall scores and vegetable and greens and beans component scores compared with typically developed peers.⁵⁵ In contrast, a study of 41 youth with autism matched with typically developing youth found those with autism had lower HEI-2015 component scores for whole fruits, total vegetables, dairy, and total protein foods.²¹ These results seem to be consistent with the current findings related to diet quality in adolescents with DS and autism. Although in the current study those with DS had diet quality superior to those with autism and other IDs, overall scores were still inadequate, thus strategies to improve diet quality in adolescents and young adults with DS are warranted.

In typically developed adolescents, poorer diet quality appears to be associated with higher risk of developing obesity, as indicated by higher BMI percentile, increased percent body fat, increased waist circumference z score,⁵⁶ and higher risk of metabolic syndrome.⁵⁷ In the overall sample, HEI-2015 scores were lowest in those with healthy weight (but high waist-to-height ratio) and those with obesity class 3 or higher; however, these findings were not statistically significant. Several studies have reported that those with autism are at greater risk for both overweight and obesity compared with typically developing adolescents^51,58,59; however, few studies have looked specifically at diet quality in relation to this risk. For those with autism in the sample, participants in the lowest weight category with waist-to-height ratio of >0.5 had a mean ± SD HEI-2015 score of only 43.4 ± 10, indicating that lower weight may also be a risk of poor diet quality. However, small group sizes prohibited us from making definitive conclusions. Larger studies are needed to understand the link between diet quality and weight in the ID population.

Strengths of this study include measuring energy intake, overall dietary quality, and specific components of dietary quality in an understudied population using a dietary assessment method validated in adolescents and young adults with ID. Limitations of this study include small subgroup sizes and limited variability in the BMI of the study sample due to the inclusion criteria that all participants have OW/OB or high waist-to-height ratio at baseline. Additional inclusion criteria also limited generalizability to those who met study requirements. Three-day food records and the simple scoring algorithm method for HEI-2015 are limited in describing usual dietary intake in populations⁴⁵; however, these methods were selected a priori because the 3-day image-assisted food record is one of the few dietary assessments validated in this population, and the simple scoring method allowed us to compare means between groups. Larger studies with more representative samples are needed to build on these findings.

CONCLUSIONS

Dietary quality in this sample of adolescents and young adults with IDs was similar to population estimates of adolescent dietary quality. Those with DS scored significantly higher than those with autism or other IDs. Overall HEI-2015 scores and scores of diagnostic subgroups did not indicate a significant relationship between diet quality and OW/OB level. Understanding differences in dietary intake between those with differing ID diagnoses will help researchers and clinicians make more targeted dietary recommendations and interventions for those with IDs who are often intervened upon as a collective group.

RESEARCH SNAPSHOT.

Research Question:

Does the diet quality of adolescents and young adults with intellectual disabilities and overweight/obesity differ by intellectual disability diagnosis or weight category?

Key Findings:

Results of this cross-sectional secondary analysis of 102 adolescents and young adults with intellectual disabilities showed that overall diet quality as assessed by the Healthy Eating Index 2015 did not differ significantly by weight classification, but that overall diet quality (mean ± SD Healthy Eating Index 2015 score) of those with Down syndrome (53.9 ± 8.4) was significantly higher than diet quality of those with autism (49.1 ± 9.6).