Skip to main content
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2018 Oct 1.
Published in final edited form as: Disabil Health J. 2017 Feb 12;10(4):542–547. doi: 10.1016/j.dhjo.2017.02.001

Caregivers’ Effect on Weight Management in Adults with Intellectual and Developmental Disabilities

LT Ptomey a, CA Gibson b, J Lee c, DK Sullivan d, RA Washburn a, AM Gorczyca a, JE Donnelly a
PMCID: PMC5554465  NIHMSID: NIHMS853437  PMID: 28215627

Abstract

Introduction

Caregivers of adults with IDD often play a large role in the ability of adults with IDD to lose weight.

Objective

The purpose of this study was to determine to examine the effects of the caregivers’ perceived burdens and self-efficacy and their relationship to an individual (family member or paid staff) on weight changes across an weight management intervention for adults with IDD.

Methods

Overweight/obese adults with mild to moderate IDD, along with assigned caregivers who served as their study partner, were randomized to an 18-month weight management intervention. The living environment and caregiver relationship were assessed at baseline. Caregivers completed questionnaires regarding perceived hassles, uplifts, and self-efficacy in helping the participant follow a weight management intervention.

Results

147 adults with IDD (~57% women and ~16% minorities) were included in data analysis. After 18 months, there were no differences in weight loss between participants who had a family member as their study partner and those who had a paid assistant as their study partner (−5.5 ± 5.2 % vs. −5.6 ± 5.3% p = 0.16). However, paid assistants reported more hassles with following the diet intervention at 6 months (p < 0.05). Participants who had a paid assistant as their study partner were more likely to have multiple study partners during the study, which was correlated with smaller weight loss.

Conclusion

While caregivers are important for weight management of adults with IDD, the caregiver’s relationship to the participant does not affect weight change in an intervention.

Keywords: Caregiver, intellectual and development disabilities, adults, weight management, family

INTRODUCTION

Approximately 1–3% of the US population is diagnosed with an intellectual or developmental disability (IDD). IDD is defined as a disability, originating before the age of 10, characterized by significant limitations in both intellectual functioning (IQ < 75) and 2 or more adaptive behaviors (1).

As adults with IDD have left institutional care to live in group homes or supported living arrangements, they have adopted the physical activity (2, 3) and dietary characteristics (46) of the general population and in turn have shown increased rates of overweight and obesity (7, 8). The prevalence of obesity among individuals with IDD is approximately twice that in the general population, with up to 55% of adults with IDD considered obese (BMI >30 kg/m2) (911). This high rate of obesity combined with a lower level of fitness and poor diet quality has resulted in an increased risk of heart disease, diabetes, hypertension, and osteoporosis (3, 12, 13).

Adults with IDD live in a variety of different living environments: at home with parents or family, in group homes with live-in staff, and independently with occasional staff or parental support (14). While the living situations may vary, all have some type of caregiver support, typically either a family member or paid staff. The role of caregivers has been recognized as an important factor in meeting the needs of individuals with IDD (15). This is also true in providing support for weight management. While data is limited, previous studies have reported that support from family or paid caregivers may have a positive impact on weight loss for overweight and obese adults with IDD (16, 17). Including caregivers in the realm of health promotion could provide an avenue for increasing physical activity and reducing energy intake (11). Bergstrom et al. (18) found that adults with IDD living in supported living homes had increases in physical activity after a weight management intervention.

It is unlikely that adults with IDD can effectively implement the components of a weight management intervention without social support from caregivers (19). However, caregivers experience many barriers to providing support for weight management to adults with IDD. Spanos et al. (20) identified staffing issues (e.g. constant turnover and lack of communication between staff members) and lack of caregiver knowledge on diet and physical activity as the two greatest barriers to providing successful weight management support. Matthews et al.(21) completed a process evaluation of a walking intervention in adults with IDD and found that low morale for staff and increased demands in family caregivers were a few reasons for the lack of effectiveness in the trial. Thus, adults with IDD who live at home or in environments with one consistent care provider may have better support for weight management and therefore be more successful in a weight management intervention than those who live in homes with multiple staff.

Previous weight loss interventions in adults with IDD have generally involved small samples (n < 25) and been conducted over a relatively short time frame (8–12 weeks) (22), thus there has not been the opportunity to examine the association between caregiver relationship and weight change in a long-term weight management intervention. Data from a recently completed 18-month weight management intervention in 149 adults with IDD afforded an opportunity to examine the effects of the caregivers’ perceived burdens and self-efficacy and their relationship to an individual (family member or paid staff) on weight change.

Methods

Study Overview

This was a secondary analysis of the data collected in an 18-month effectiveness study with adults with IDD that compared two intervention approaches for weight management. All study participants who completed 1 month of the intervention were included in the current investigation. A detailed description of the rationale, design, and methods of this study has been previously published (23). In brief, 149 overweight/obese adults with mild to moderate IDD and their study partners were randomized to either an enhanced Stop Light Diet (eSLD) (24) or a Conventional calorie-restriction Diet (CD) (25). Following a 6-month weight loss period, both groups were encouraged to continue following their diet for 12 months at a level of energy intake estimated to result in weight maintenance.

The caregiver relationship (defined as family member or paid staff), living environment (independent living, group, or parent’s home), and number of roommates were assessed at baseline using a demographic questionnaire completed by each participant’s legal guardian (if applicable) or caregiver. The caregiver (staff) turnover and changes were tracked during the study, and a designated caregiver completed a nutrition hassles questionnaire at 0, 6, and 18 months of the study to determine their barriers, uplifts, and self-efficacy for helping the participant be successful in the intervention. This study was approved by the Institutional Review Board at the University of Kansas.

Participants

The study was conducted between July 2011 and May 2014. All participants lived within ~50 miles of Lawrence, KS, United States of America, which includes the greater Kansas City Metropolitan. Participants were men and women, 18 years of age or older, with a diagnosis of mild to moderate IDD as determined by a Community Service Provider operating in Kansas under the auspices of a Community Developmental Disability Organization (CDDO). To be included in the study, participants had to reside in a supported living condition either at home or with no more than 1–4 residents and have a caregiver (parent or staff) who assisted with food shopping, meal planning, and meal preparation. Participants had to be overweight or obese (BMI > 25 kg/m2), able to walk, and have a clearance from their physician to participate. Potential participants also must have had the ability to communicate preferences (e.g., foods liked and disliked), wants (e.g., more to eat, drink), and needs (e.g., assistance with food preparation) through spoken language, sign language, or augmentative and alternative communication systems, such as voice output communication aides. Individuals were excluded if they had uncontrolled insulin dependent diabetes, hypertension, severe heart disease, cancer, or HIV. Individuals were also excluded if they had participated in physical activity and weight reduction programs within the past 6 months or were being treated for an eating disorder. If a female participant was or became pregnant, she was excluded/terminated from the study.

All participants were required to have a caregiver, defined as a parent/guardian whom the participant lived with or a direct care support staff who had primary responsibility for managing the house where the participant resided. The caregiver was referred to as the participant’s “study partner.” The study partner agreed to participate in each of the monthly meetings with the participant and to support the participant in following the intervention. Study partners were not asked to follow the diet or to increase their own physical activity. When study partners who were unable to complete their partner role (e.g., they changed jobs, they were no longer able to commit to attending the monthly meetings, participants moved out of their care, etc.), they were replaced. New caregivers were provided training that was identical to that received by the original caregiver.

Recruitment Procedure

Participants were recruited through community and home visits. Written informed consent was obtained from either participants (self as guardian) or their legal guardian, and the caregiver.

Intervention Overview

At baseline, participants and study partners attended a 90-minute, at-home diet orientation session conducted by their assigned health educator, and subsequently participated in monthly at-home education sessions during the 18-month intervention with the same health educator. During a 6-month weight loss period, participants followed one of two different diet prescriptions, eSLD or CD. Following the weight loss period, both groups were encouraged to continue following their diet prescription for 12 months but at a level of energy intake designed to provide weight maintenance. Both groups were asked to wear a step counter and record steps walked with an eventual goal of 150 minutes per week.

Weight Loss Diets (Months 0–6)

eSLD

The original Stop Light Diet developed by Epstein (26) for use in children was enhanced (eSLD) with the addition of fruits and vegetables minimum recommendations (≥ 5 servings/day) and high-volume, low-energy portion controlled meals (PCMs) consisting of 2 entrées and 2 shakes per day. The PCMs consisted of pre-packaged, pre-portioned food products that were low in calorie but high in nutritional content, and intended to take the place of regular meals or snacks. Non-caloric beverages were allowed ad libitum. Participants were instructed to consume 2 entrées and 2 shakes per day, and if they were still hungry or were unable to consume an entrée or shake, they could pick foods from the Stop Light Diet picture guide. Participants were instructed to choose green or yellow foods and to avoid red foods. Shakes were provided to participants during the weight loss phase, and participants were instructed to purchase their own approved entrees.

CD

Participants in the CD diet were educated to consume a nutritionally balanced, high-volume, lower fat diet as recommended by the United States Department of Agriculture (27). Participants’ energy needs were estimated using the equation of Mifflin-St Jeor (28) multiplied by 1.4 to 1.6 to account for physical activity. A deficit of 500–700 kcal/day was prescribed; however, prescriptions never recommended less than 1,200 kcals/day. Consumption of five servings of fruits and vegetables per day was recommended. Participants were provided examples of meal plans based on the 2010 MyPlate guidelines (27), each consisted of suggested servings of grains, proteins, fruits, vegetables, dairy, and fats based on their energy needs, and was counseled on appropriate portion sizes using three-dimensional food models.

Weight Maintenance Diets (Months 7 to 18)

Energy intake for weight maintenance was estimated separately for the eSLD and CD diets was estimated using the equation of Mifflin-St Jeor (28) multiplied by 1.4 to 1.6 to account for physical activity. Participants in the eSLD diet were encouraged, but not required, to continue to consume 14 PCMS per week and 5 servings of fruits and vegetables per day. Participants in the CD diet were provided examples of meal plans based on their energy needs for weight maintenance.

Weekly Tracking and Monthly Meetings

Participants, with assistance from their study partners, were asked to complete weekly data recording cards that were specific to their diet group (eSLD/CD) during the 18-month intervention. All participants were visited once a month by their assigned health educator. During the monthly home visits, the health educator assessed body weight and compliance with the intervention, provided feedback to the participant, answered any questions the participant or caregiver had, and resolved any issues related to following the diet or physical activity goals.

Outcomes Assessments

Overview

Demographic information including living environment was obtained at baseline. Anthropometric measurements (i.e., weight, height, BMI, waist circumference) and a nutritional hassles questionnaire were completed at baseline, following at 6 months during the weight loss period and at 12 and 18 months during the weight maintenance period. Study partner changes were monitored and documented monthly over the study. All outcomes were assessed at the participant’s home during a single visit by study staff blinded to the intervention.

Living environment

At baseline, the participant’s legal guardian or caregiver completed a form to determine if the participant lived at home or out of the home, the number of individuals who resided in the home, the number of staff who provided support in the home each week, and how many individuals in the home participated in the program. It was also determined if the study partner was a parent/family member or paid staff.

Anthropometrics

Participants were weighed in a hospital gown between 8:00 and 10:00 AM, in duplicate, on a calibrated scale (Model #PS6600, Belfour, Saukville, WI) to the nearest 0.25 kg, following an overnight fast (~12 hours). Standing height was measured in duplicate with a portable stadiometer (Model #IP0955, Invicta Plastics Limited, Leicester, UK). BMI was calculated as weight (kg)/height (m2). Waist circumference, as a surrogate for abdominal adiposity, was assessed using the procedures described by Lohman et al. (29). Three measurements were taken, resulting in anthropometric outcomes recorded as the average of the closest 2 values.

Nutritional Hassles Questionnaire

A nutrition hassles questionnaire was administered to study partners in order to assess hassles, uplifts, and self-efficacy that might influence their ability to help others in a weight management intervention. To create this questionnaire, the Hassles Scale (30), Hassles and Uplifts Scale (31), and Nutrition Hassles Questionarie (32) were modified into 26 items that measure three constructs (Hassles, Uplifts, and Self-efficacy) with adequate psychometric properties. All three subscales (constructs) showed acceptable reliability, with Cronbach’s alpha values of .90–.93 for Hassles, .78–.85 for Uplifts, and .93–.95 for Self-efficacy across three measurements (0, 6, and 18 months). The convergent validity of the questionnarie was assessed by the composite reliability (CR) and average variance extracted (AVE) estimated from longitudinal confirmatoy factor analysis. The CR values were more than acceptable (i.e., > .70), with .89–.92 for Hassles, .88–.91 for Uplifts, and .93–.96 for Self-efficacy across three measurements. The discriminant validity of the questionnaire was also evaluated by comparing each construct’s AVE value against squared correlations that the construct has other two constructs (33). The discriminant validity was fully supported as the AVE values were always greater than the squared correlations.

The hassles subscale included 10 items regarding minor annoyances to major problems or difficulties, such as planning meals, preparing meals, and grocery shopping. The hassle items were rated on a 3-point scale from 1 (somewhat severe) to 3 (extremely severe). If the item was not considered a hassle by the caregiver, it was scored as 0. The uplifts subscale included six different events that increase positive feelings, such as eating out or cooking for someone else. Study partners indicated how often an uplifting event has occurred in the last month using a scale from 1 (somewhat often) to 3 (extremely often). If the item was not considered an uplifting event by the caregiver, it was scored as 0. The self-efficacy subscale included 10 items designed to determine how confident study partners feel in their ability to perform different healthy nutrition behaviors, such as “identify appropriate food for meals and snacks,” “help to limit portion size,” and “prepare recipes using a variety of cooking methods.” Ratings ranged from 1 (not at all confident) to 5 (very confident). The questionnaire took approximately 10 minutes to complete.

Statistical Analysis

Participant demographics and all study outcomes (anthropometrics, hassles, uplifts, and self-efficacy) were summarized using descriptive statistics and bivariate analysis. Independent-samples t-test (with Satterthwaite approximation, if necessary) was conducted to examine group differences between participants who were supported by a family member and those who were supported by a paid assistant. In addition, general mixed modeling for repeated measures was utilized to estimate overall group difference (i.e., group effect), linear or quadratic change from 0 to 18 months (i.e., time effect), and group difference in this change (i.e., group-by-time interaction) for each outcome, accounting for age, sex, race, education level, and support level. All analyses were conducted using SAS 9.4 (SAS Institute, 2002–2012).

Results

Participants

A total of 149 adults with IDD were participated in the study. Of those, 147 completed at least one month of the intervention and were included for analysis — 124 completed the 6-month weight loss and 101 completed the full 18-month intervention. There were no differences in demographic characteristics and study outcomes at baseline (anthropometrics; hassles, uplifts, and self-efficacy) between those who completed the study and those who did not, indicating a minimal or no bias due to the sample attrition. Full baseline demographic data for the 147 participants are presented in Table 1. This sample comprised ~57% women and ~16% minorities, with a mean age of ~36 years and BMI of ~37 kg/m2.

Table 1.

Demographic data of adults with IDD enrolled in a weight loss program.

All (n = 147) Family member (n = 38) Paid assistant (n = 108)

Variable n % n % n % p
Age (yr) (M ± SD) 147 36.4 ± 12.1 38 32.7 ± 10.3 108 37.8 ± 12.5 0.027a
Gender 0.196
Male 63 42.9% 13 34.2% 50 46.3%
Female 84 57.1% 25 65.8% 58 53.7%
Race 0.619
White 123 83.7% 33 86.8% 89 82.4%
Black or African American 19 12.9% 3 7.9% 16 14.8%
Pacific Islander 0 0.0% 0 0.0% 0 0.0%
Asian 2 1.4% 1 2.6% 1 0.9%
American Indian/Alaska Native 1 0.7% 0 0.0% 1 0.9%
Two or more races 2 1.4% 1 2.6% 1 0.9%
Ethnicity 0.962
Hispanic 4 2.7% 1 2.6% 3 2.8%
Non-Hispanic 143 97.3% 37 97.4% 105 97.2%
Education level 0.715
>9th grade 4 2.8% 1 2.6% 3 2.8%
9th–12th grade 20 13.9% 5 13.2% 15 13.9%
High school graduate/GED 91 63.2% 22 57.9% 71 65.7%
Post graduate classes 29 20.1% 10 26.3% 19 17.6%
Support level 0.004b
Mild 74 50.3% 27 71.1% 47 43.5%
Moderate 73 49.7% 11 28.9% 61 56.5%
BMI (kg/m2) (M ± SD) 147 36.9 ± 8.0 34 36.6 ± 7.1 97 37.1 ± 8.4 0.726
a

Significant difference between groups at p<0.05

b

Significant difference between groups at p<0.01

Weight Change in Diet Groups

Percent change in weight during the 18-month intervention was not significantly different between the eSDL and CD diets (−7.4% ± 8.0 vs. −6.7% ± 8.2; p = 0.68).

Study Partner Relationship

At baseline, 38 participants had a family member as their study partner, and 108 participants had a paid assistant as their study partner. Participants whose study partner was a paid assistant were older (p < 0.05) and had a greater severity of IDD (p < 0.01) compared to those whose study partner was a family member (Table 1). There were no significant differences in % weight change between participants who were supported by a family member and those who were supported by paid assistant during the 6-month weight loss period (−5.5 ± 5.2 vs. −5.6 ± 5.3, p = 0.97) or the entire 18-month study (−6.3 ± 10.2 vs −7.5 ± 8.4, p = 0.14). There were also no significant differences in change in weight (kg), BMI, and waist circumference during the 6-month weight loss period or the entire 18-month study (all p > 0.05). Mixed modeling revealed that participants achieved significant reductions in weight (kg; p < 0.05 for quadratic change), BMI (p < 0.05 for quadratic change), and waist circumference (p < 0.001 for linear change) over the 18-month period, but the change patterns did not differ between those whose study partner was a family member and those whose study partner was a paid assistant (i.e., no significant group effect or group-by-time interaction). When looking at hassles, uplifts, and self-efficacy for helping participants with the intervention (Table 2), the only significant finding was that study partners who were a paid assistant reported more hassles with following the diet at 6 months compared to those who were a family member (p < 0.05). However, there were no significant differences at 18 months. Mixed modeling also indicated that neither group effect nor group-by-time interaction was significant for hassles, uplifts, and self-efficacy. Significant increases over time were found only in self-efficacy (p < 0.05 for linear change).

Table 2.

Hassles, uplifts, and study partner self-efficacy related to helping the participant with the diet for adults with IDD whose study partner was a family member or a paid assistant.

Family member (n = 38) Paid assistant (n = 108)

Variable n M SD n M SD p d
Hassles score
Month 0 34 0.7 0.8 97 0.7 0.7 0.814 0.047
Month 6 26 0.4 0.5 76 0.8 0.6 0.015a 0.564
Month 18 23 0.6 0.6 65 0.8 0.7 0.243 0.285
Change from months 0 to 6 23 −0.1 0.8 76 0.1 0.7 0.208 0.306
Change from months 6 to 18 23 0.2 0.7 65 0.1 0.7 0.674 0.110
Uplifts score
Month 0 34 1.4 0.8 97 1.3 0.8 0.576 0.112
Month 6 26 1.5 0.8 76 1.6 0.7 0.709 0.085
Month 18 23 1.7 0.7 65 1.5 0.9 0.450 0.184
Change from months 0 to 6 26 0.2 0.9 76 0.3 1.1 0.853 0.045
Change from months 6 to 18 23 0.0 1.0 65 −0.1 1.1 0.585 0.143
Confidence score
Month 0 34 3.4 1.2 97 3.5 1.4 0.697 0.078
Month 6 26 3.6 1.3 76 3.7 0.9 0.749 0.086
Month 18 23 3.8 1.2 65 3.9 1.0 0.837 0.050
Change from months 0 to 6 26 0.0 1.4 76 0.1 1.5 0.864 0.041
Change from months 6 to 18 23 0.2 2.0 65 0.1 1.2 0.825 0.072
a

Significant difference between groups at p<0.05

Relationships of Hassles, Uplifts, and Self-Efficacy to Weight Change

Study partners’ reported hassles, uplifts, and self-efficacy were not significantly associated with participants’ weight and % weight change at 6 months (all p > 0.05). However, hassles were positively correlated with weight (kg) at 18 months (r = 0.30, p < 0.01), and self-efficacy change and % weight change from 6 to 18 months were negatively correlated (r = −0.20, p < 0.05). Self-efficacy were negatively correlated with hassles at 0, 6, and 18 months (r =−0.39, −0.30, and −0.38, respectively; all p < 0.01).

Number of Study Partners

Sixty-two percent of participants had 1 study partner, 27% had 2, and 11% had 3 or more during the 18-month study. The total number of study partners had no impact on weight change in kg during the 6-month weight loss period or the entire 18-month study; however, during the 6-month weight loss period, % weight loss was significantly greater among participants who had 1 study partner compared to those with 3 or more study partners (−6.5 ± 5.0% vs. −2.5 ± 6.3%; p<0.05; Table 3). The number of people living with the participant and the total number of support staff during the week were not significantly correlated with weight change (in either kg or %) during the study.

Table 3.

Impact of multiple study partners on weight across the 18-month study

1 study partner 2 study partners 3 or more study partners Group difference (p)

Variable n M SD n M SD n M SD 1v2 1v3 2v3
Weight (kg)
Baseline 91 96.0 22.7 40 98.1 22.2 18 112.8 32.5 0.653 0.007 b 0.033a
6 months 74 89.4 21.5 32 91.4 25.0 18 109.9 31.4 0.422 0.001 c 0.018 a
18 months 60 88.6 22.2 27 88.9 22.7 14 105.0 34.4 0.501 0.015 a 0.079
Weight Loss (kg)
0 – 6 months 74 −6.2 5.5 32 −4.5 4.9 18 −3.0 6.8 0.250 0.077 0.448
0 – 18 months 60 −6.6 8.1 27 −5.2 6.7 14 −8.6 12.6 0.484 0.517 0.282
Weight Loss (%)
0 – 6 months 74 −6.5 5.0 32 −5.0 4.7 18 −2.5 6.3 0.311 0.028 a 0.214
0 – 18 months 60 −6.9 8.5 27 −5.5 6.9 14 −7.3 10.7 0.443 0.915 0.653
a

Significant difference between groups at p<0.05

b

Significant difference between groups at p<0.01

c

Significant difference between groups at p<0.001

DISCUSSION

Caregivers’ involvement is considered to be an essential component of health promotion efforts for adults with IDD (15). In the context of weight management, caregivers play a pivotal and potentially supportive role in assisting with decisions regarding meal planning, food shopping, and meal preparation, as well as assisting with scheduling and participating in appropriate physical activity, a task which can be difficult without encroaching on the autonomy of the adult they are caring for. This study sought to find out how much the caregiver and living environment influenced the ability of adults with IDD to lose and maintain weight loss during an 18-month weight management intervention.

We observed no significant differences in weight loss between adults with IDD who received care from a family member or from paid staff. Nevertheless, those who had a paid assistant did experience greater staff turnover and changes in study partners across the study. Our results showed that individuals who had a consistent study partner had greater % weight loss during the 6-month weight loss period compared to those who had 3 or more study partners. While multiple study partners did not impact weight loss during the entire 18-month study, this finding still suggests that adults with IDD may benefit from having a consistent caregiver during a weight management intervention. Similarly, Spanos et al. (20) reported that participants who are in homes with multiple staff would benefit from having consistent shift patterns and more one-on-one time allocated with the person they support.

Study partners’ reported hassles (e.g., planning meals, getting individuals to eat what is prepared, and finding time to prepare healthy foods) and self-efficacy (e.g., the ability to limit portion size, prepare low-fat meals, and choose low calorie snacks) did not impact participants’ weight during the 6-month weight loss phase but did influence weight at the end of the 18-month intervention. Participants who had study partners that reported more hassles had higher weights at the end of the 18-month study, and those who had study partners who reported higher self-efficacy had greater weight loss at the end of the study. This is in agreement with previous research (17, 20, 34) that suggests a successful weight management intervention needs to reduce barriers for not only the participants but also for their caregivers. Spanos et al. (20) suggests that, in order to reduce caregiver barriers, weight management interventions need to incorporate small, established staff teams that can follow the weight loss plan consistently and to establish better communication and cooperation between the staff within the same support team.

Strengths of the current study include the use of a randomized controlled trial with a weight management intervention over 18 months, a relatively large sample, the inclusion of both males and females, and a rigorous assessment of body weight and validated measures of hassles, uplifts, and self-efficacy. However, while the results are encouraging, this study should be considered in the context of certain limitations. First, the main intervention was not specifically designed or powered to detect between- or within-group differences of weight or hassles, uplifts, and self-efficacy between the caregiver groups. Next, study partners’ hassles, uplifts, and self-efficacy were obtained using self-report, which might have introduced some responder bias (35). However, to limit potential socially desirable responses, study partners completed the questionnaires in private and were told that their responses would not be shared. There were also unequal numbers of participants who had a family member and who had a paid assistant as their study partner. However, such unequal group sizes reduced power to detect group differences by only 3.4% on average. Finally, demographic information about the caregivers was not obtained, so it is unknown if there are certain characteristics (e.g., age, sex, education level) that may influence the ability of a caregiver to successfully support adults with IDD during a weight management intervention. The current trial did not specifically evaluate the impact of the caregiver on weight loss/maintenance. However, we observed no significant differences in weight loss between adults with IDD who received care from a family member or from paid staff, or who had two or more different study partners during the 18-month trial. Although in need of confirmation, these results suggest that adults with IDD can achieve clinically relevant weight loss under a variety of supportive situations. Innovative strategies to improve caregiver training and to provide support for caregivers in their efforts to assist adults with IDD in weight management warrant investigation.

Acknowledgments

Funding: The National Institute of Diabetes and Digestive and Kidney Disease (R01- DK83539). We acknowledge HMR for providing the pre-packaged meals.

Footnotes

Conflict of Interest: No authors report any conflicts of interest.

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

References

  • 1.American Association on Intellectual and Developmental Disabilities. Definition of Intellectual Disabilities. Washington, D.C: 2012. [cited 2012 April 16th]. Available from: http://www.aaidd.org/content_100.cfm?navID=21. [Google Scholar]
  • 2.Draheim CC, Williams DP, McCubbin JA. Prevalence of physical inactivity and recommended physical activity in community based adults with mental retardation. Ment Retard. 2002;40(6):436–44. doi: 10.1352/0047-6765(2002)040<0436:POPIAR>2.0.CO;2. [DOI] [PubMed] [Google Scholar]
  • 3.Beange H, McElduff A, Baker W. Medical disorders of adults with mental retardation: a population study. Am J Ment Retard. 1995;99(6):595–604. [PubMed] [Google Scholar]
  • 4.Mercer KC, Ekvall SW. Comparing the diets of adults with mental retardation who live in intermediate care facilities and in group homes. J Am Diet Assoc. 1992;92(3):356–8. [PubMed] [Google Scholar]
  • 5.Robertson J, Emerson E, Gregory N, Hatto C, Turner S, Kessissoglou S, Hallam A. Lifestyle related risk factors for poor health in residential settings for people with intellectual disabilities. Research in developmental disabilities. 2000;21(6):469–86. doi: 10.1016/s0891-4222(00)00053-6. [DOI] [PubMed] [Google Scholar]
  • 6.Ptomey L, Goetz J, Lee J, Donnelly J, Sullivan D. Diet quality of overweight and obese adults with intellectual and developmental disabilities as measured by the healthy eating index-2005. Journal of developmental and physical disabilities. 2013;25(6):625–36. doi: 10.1007/s10882-013-9339-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Rimmer JH, Yamaki K. Obesity and intellectual disability. Ment Retard Dev Disabil Res Rev. 2006;12(1):22–7. doi: 10.1002/mrdd.20091. [DOI] [PubMed] [Google Scholar]
  • 8.Melville CA, Hamilton S, Hankey CR, Miller S, Boyle S. The prevalence and determinants of obesity in adults with intellectual disabilities. Obesity Reviews. 2007;8(3):223–30. doi: 10.1111/j.1467-789X.2006.00296.x. [DOI] [PubMed] [Google Scholar]
  • 9.Rimmer JH, Wang E. Obesity prevalence among a group of Chicago residents with disabilities. Archives of physical medicine and rehabilitation. 2005;86(7):1461–4. doi: 10.1016/j.apmr.2004.10.038. Epub 2005/07/09. [DOI] [PubMed] [Google Scholar]
  • 10.Yamaki K. Body weight status among adults with intellectual disability in the community. Ment Retard. 2005;43(1):1–10. doi: 10.1352/0047-6765(2005)43<1:bwsaaw>2.0.co;2. Epub 2005/01/05. [DOI] [PubMed] [Google Scholar]
  • 11.Hsieh K, Heller T, Bershadsky J, Taub S. Impact of adulthood stage and social-environmental context on body mass index and physical activity of individuals with intellectual disability. Intellectual and developmental disabilities. 2015;53(2):100–13. doi: 10.1352/1934-9556-53.2.100. [DOI] [PubMed] [Google Scholar]
  • 12.Hensrud DD. Dietary treatment and long-term weight loss and maintenance in type 2 diabetes. Obes Res. 2001;9(Suppl 4):348S–53S. doi: 10.1038/oby.2001.141. [DOI] [PubMed] [Google Scholar]
  • 13.Draheim CC, Williams DP, McCubbin JA. Physical activity, dietary intake, and the insulin resistance syndrome in nondiabetic adults with mental retardation. Am J Ment Retard. 2002;107(5):361–75. doi: 10.1352/0895-8017(2002)107<0361:PADIAT>2.0.CO;2. [DOI] [PubMed] [Google Scholar]
  • 14.Kozma A, Mansell J, Beadle-Brown J. Outcomes in different residential settings for people with intellectual disability: a systematic review. Journal Information. 2009;114(3) doi: 10.1352/1944-7558-114.3.193. [DOI] [PubMed] [Google Scholar]
  • 15.NHS Health Scotland. People with Learning Disabilities in Scotland. Clifton House; 2004. [Google Scholar]
  • 16.Hamilton S, Hankey CR, Miller S, Boyle S, Melville CA. A review of weight loss interventions for adults with intellectual disabilities. Obes Rev. 2007;8(4):339–45. doi: 10.1111/j.1467-789X.2006.00307.x. Epub 2007/06/21. [DOI] [PubMed] [Google Scholar]
  • 17.Melville CA, Hamilton S, Miller S, Boyle S, Robinson N, Pert C, Hankey CR. Carer Knowledge and Perceptions of Healthy Lifestyles for Adults with Intellectual Disabilities. Journal of Applied Research in Intellectual Disabilities. 2009;22(3):298–306. doi: 10.1111/j.1468-3148.2008.00462.x. [DOI] [Google Scholar]
  • 18.Bergstrom H, Hagstromer M, Hagberg J, Elinder LS. A multi-component universal intervention to improve diet and physical activity among adults with intellectual disabilities in community residences: a cluster randomised controlled trial. Research in developmental disabilities. 2013;34(11):3847–57. doi: 10.1016/j.ridd.2013.07.019. Epub 2013/09/12. [DOI] [PubMed] [Google Scholar]
  • 19.Mitchell F, Melville C, Stalker K, Matthews L, McConnachie A, Murray H, Walker A, Mutrie N. Walk well: a randomised controlled trial of a walking intervention for adults with intellectual disabilities: study protocol. BMC public health. 2013;13(1):1. doi: 10.1186/1471-2458-13-620. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Spanos D, Hankey CR, Boyle S, Koshy P, Macmillan S, Matthews L, Miller S, Penpraze V, Pert C, Robinson N, Melville CA. Carers’ perspectives of a weight loss intervention for adults with intellectual disabilities and obesity: a qualitative study. J Intellect Disabil Res. 2013;57(1):90–102. doi: 10.1111/j.1365-2788.2011.01530.x. Epub 2012/03/01. [DOI] [PubMed] [Google Scholar]
  • 21.Matthews L, Mitchell F, Stalker K, McConnachie A, Murray H, Melling C, Mutrie N, Melville C. Process evaluation of the Walk Well study: a cluster-randomised controlled trial of a community based walking programme for adults with intellectual disabilities. BMC public health. 2016;16(1):527. doi: 10.1186/s12889-016-3179-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Spanos D, Melville CA, Hankey CR. Weight management interventions in adults with intellectual disabilities and obesity: a systematic review of the evidence. Nutr J. 2013;12:132. doi: 10.1186/1475-2891-12-132. Epub 2013/09/26. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Donnelly JE, Saunders RR, Saunders M, Washburn RA, Sullivan DK, Gibson CA, Ptomey LT, Goetz JR, Honas JJ, Betts JL, Rondon MR, Smith BK, Mayo MS. Weight management for individuals with intellectual and developmental disabilities: rationale and design for an 18 month randomized trial. Contemporary clinical trials. 2013;36(1):116–24. doi: 10.1016/j.cct.2013.06.007. Epub 2013/07/03. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Saunders RR, Saunders MD, Donnelly JE, Smith BK, Sullivan DK, Guilford B, Rondon MF. Evaluation of an approach to weight loss in adults with intellectual or developmental disabilities. American journal on intellectual and developmental disabilities. 2011;49(2):103–12. doi: 10.1352/1934-9556-49.2.103. [DOI] [PubMed] [Google Scholar]
  • 25.Seagle HM, Strain GW, Makris A, Reeves RS. Position of the American Dietetic Association: weight management. J Am Diet Assoc. 2009;109(2):330–46. doi: 10.1016/j.jada.2008.11.041. Epub 2009/02/28. [DOI] [PubMed] [Google Scholar]
  • 26.Epstein L, Squires S. The Stoplight Diet for Children: An Eight-Week Program for Parents and Children. Boston: Little Brown & Co; 1988. [Google Scholar]
  • 27.U.S. Department of Agriculture. Choose MyPlate. Washington DC: 2013. Available from http://www.choosemyplate.gov. [Google Scholar]
  • 28.Mifflin MD, St Jeor ST, Hill LA, Scott BJ, Daugherty SA, Koh YO. A new predictive equation for resting energy expenditure in healthy individuals. The American journal of clinical nutrition. 1990;51(2):241–7. doi: 10.1093/ajcn/51.2.241. Epub 1990/02/01. [DOI] [PubMed] [Google Scholar]
  • 29.Lohman TG, Roche AF, Martorell R. Anthropometric Standardization Reference Manual. Champaign, Ill: Human Kinetics Books; 1988. [Google Scholar]
  • 30.Kanner AD, Coyne JC, Schaefer C, Lazarus RS. Comparison of two modes of stress measurement: Daily hassles and uplifts versus major life events. Journal of behavioral medicine. 1981;4(1):1–39. doi: 10.1007/BF00844845. [DOI] [PubMed] [Google Scholar]
  • 31.Lazarus RS, Folkman S. Transactional theory and research on emotions and coping. European Journal of personality. 1987;1(3):141–69. [Google Scholar]
  • 32.Hatton DC, Haynes RB, Oparil S, Kris-Etherton P, Pi-Sunyer FX, Resnick LM, Stern J, Clark S, McMahon M, Morris C. Improved quality of life in patients with generalized cardiovascular metabolic disease on a prepared diet. The American journal of clinical nutrition. 1996;64(6):935–43. doi: 10.1093/ajcn/64.6.935. [DOI] [PubMed] [Google Scholar]
  • 33.Fornell C, Larcker DF. Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research. 1981:39–50. [Google Scholar]
  • 34.Ptomey LT, Gibson CA, Willis EA, Taylor JM, Goetz JR, Sullivan DK, Donnelly JE. Parents’ perspective on weight management interventions for adolescents with intellectual and developmental disabilities. Disabil Health J. 2016;9(1):162–6. doi: 10.1016/j.dhjo.2015.07.003. Epub 2015/08/19. [DOI] [PubMed] [Google Scholar]
  • 35.Podsakoff PM, MacKenzie SB, Podsakoff NP. Sources of method bias in social science research and recommendations on how to control it. Annual review of psychology. 2012;63:539–69. doi: 10.1146/annurev-psych-120710-100452. [DOI] [PubMed] [Google Scholar]

RESOURCES