Abstract

Individuals with intellectual disability (ID) are at risk for obesity and physical inactivity. We analyzed a subset of 2009–2010 National Core Indicators (NCI) database to examine (1) the impact of three adulthood stages– younger (20–39 years), middle (40–59 years), and older (60 years and older) on Body Mass Index (BMI) and physical activity (PA); and (2) the relationship between social-environmental context (i.e., residence type, everyday choices, and community participation) and BMI and PA, with adjustment for individual characteristics of the adults with ID. Findings highlight the need to pay more attention to obesity by providing health education and emphasizing healthy choices. Results also suggest the importance of community participation as a way of promoting more physical activity.

Obesity and physical inactivity are a primary cause of most chronic diseases/conditions including metabolic syndrome, obesity, type 2 diabetes, cancer, loss of functional capacities, and premature mortality (Archer & Blair, 2011; Booth, Roberts, & Laye, 2012; Dixon, 2010). Physical inactivity was identified as the fourth leading risk factor for global mortality (World Health Organization, 2010). A secondary effect of obesity and physical inactivity is social economic burden as a result of increased lifetime medical care costs of those chronic diseases/conditions (Finkelstein, Trogdon, Cohen, & Dietz, 2009; Runge, 2007) and lost productivity (Finkelstein, Linnan, Tate, & Leese, 2009; Gifford, 2014). Compared to the general population, adults with intellectual disability (ID) have higher (Hsieh, Rimmer, & Heller, 2014; Rimmer, Yamaki, Lowry, Wang, & Vogel, 2010) or equal (Stancliffe et al., 2011) rates of overweight and obesity (ranging from 26.5% to 58.5%) and physical inactivity (Draheim, Williams, & McCubbin, 2002; McGuire, Daly, & Smyth, 2007; Temple, Frey, & Stanish, 2006). Meeting the recommended amount of physical activity can lead to a reduced risk of premature death and improved health outcomes including prevention of chronic health conditions and management of obesity (Warburton, Nicol, & Bredin, 2006). The World Health Organization, the U.S. Department of Health and Human Services, and other authorities recommend that for health benefits, adults should engage in at least 150 minutes of moderate-intensity or 75 minutes of vigorous-intensity physical activity each week (U.S. Department of Health and Human Services, 2008; World Health Organization, 2010). A systematic review indicated moderate to strong evidence that physical activity significantly improved balance, muscle strength, and quality of life in persons with ID (Bartlo & Klein, 2011). However, it was reported that 45% to 88% of adults with ID were physically inactive (Draheim et al., 2002; Robertson, Emerson, Gregory, Hatton, Turner, et al., 2000) which is much higher than the general population (Draheim et al., 2002; Finlayson et al., 2009; Frey, 2004; McGuire et al., 2007; Temple et al., 2006). None to 47% of individuals with ID were reported as meeting recommended physical activity guidelines (Draheim et al., 2002; Finlayson et al., 2009; Phillips & Holland, 2011; Robertson, Emerson, Gregory, Hatton, Turner, et al., 2000; Stanish, Draheim, & Taylor, 2005).

A large body of evidence indicates a link between physical activity and body weight, including studies of individuals with ID (Barnes, Howie, McDermott, & Mann, 2013; Hsieh et al., 2014). Given that adults with ID have high rates of overweight or obesity and physical inactivity, it is important to examine the underlying associated factors for higher than normal body mass index (BMI) and for not meeting the recommended amount of physical activity separately. The results will help us identify common associated factors between above normal BMI and not meeting the recommended amount of physical activity.

Both the noted disparities in obesity and in physical inactivity for adults with ID are in part due to individual characteristics. In regard to obesity, the associated individual characteristics include gender, race, severity of ID, ID-related diagnosis (e.g., Down syndrome, cerebral palsy; Hsieh et al., 2014; Rimmer & Yamaki, 2006; Stancliffe et al., 2011), and use of medication that might cause weight gain such as antipsychotics, antidepressants, antihypertensives, or diabetes-related medications (Bokszanska et al., 2003; Cohen, Glazewski, Khan, & Khan, 2001; Hellings, Zarcone, Crandall, Wallace, & Schroeder, 2001; Hsieh et al., 2014). In a recent literature review, it was reported that taking antipsychotic medication may reduce physical activity in the general population (Cuerda, Velasco, Merchan-Naranjo, Garcia-Peris, & Arango, 2014). Research findings report high rates of antipsychotic medication use in adults with ID (de Kuijper et al., 2010; Lunsky & Elserafi, 2012; Robertson, Emerson, Gregory, Hatton, Kessissoglou, et al., 2000). Studies also indicate that women with Down syndrome are more likely to be obese (Hsieh et al., 2014; Melville, Cooper, McGrother, Thorp, & Collacott, 2005), whereas adults with cerebral palsy are less likely to be obese than other ID-related groups (Bhaumik, Watson, Thorp, Tyrer, & McGrother, 2008). Individuals with behavior problems are often put on medication or secluded from their peers, consequently, they are less likely to engage in community activity or physical activity. Hence, the variable of behavior problems needs to be taken into account when investigating other factors related to BMI and physical activity.

Increasing age has been consistently found to have a positive association with BMI and obesity rates from early adulthood through 65 years in the general population (Bélanger-Ducharme & Tremblay, 2005; Flegal, Carroll, Kit, & Ogden, 2012). This pattern does not appear in studies of adults with ID (Emerson, 2005; Robertson, Emerson, Gregory, Hatton, Turner, et al., 2000; Stancliffe et al., 2011; Yamaki, 2005). In a recent study, compared to younger and older adults, the middle-aged adults with ID were more likely to be obese. Hence, adulthood stage might have an impact on BMI in adults with ID.

In addition to individual characteristics, health risk behaviors such as drinking sweetened soda, and engaging in insufficient physical activity were also significantly associated with obesity in adults with ID (Hsieh et al., 2014). As with obesity, various individual characteristics have been associated with low levels of physical activity in adults with ID. Amongst these factors are older age (Dixon-Ibarra, Lee, & Dugala, 2013; Emerson, 2005; Finlayson et al., 2009; Hilgenkamp, Reis, van Wijck, & Evenhuis, 2012; Robertson, Emerson, Gregory, Hatton, Turner, et al., 2000), and reduced mobility or immobility (Finlayson et al., 2009; Robertson, Emerson, Gregory, Hatton, Turner, et al., 2000). A large study in England found that physical inactivity was associated with age among men with ID. The percentage of physical inactivity among men with ID, excluding those unable to perform physical activity, increased with age from 83% to 100%. The same study reported that all of the young adults (16–24 years) and older adults (75 years and older) among women with ID were physically inactive (Emerson, 2005). One study that controlled for age to examine physical activity found adults with ID in the middle range of the spectrum (versus ID at the upper end of the spectrum) to be less physically active (Peterson, Janz, & Lowe, 2008). Therefore, the level of ID may be inversely associated with the amount of physical activity engagement. Additionally, although smoking has been negatively associated with physical activity in the general population (Trost, Owen, Bauman, Sallis, & Brown, 2002), it has not been examined in adults with ID. Given the low levels of physical activity in adults with ID, it is important to identify the associated factors and determinants for low levels of physical activity in order to better inform development of effective health promotion programs.

Beyond health behaviors and individual characteristics, both the weight and physical activity of adults with ID may also be influenced by social-environmental characteristics. Social-environmental context variables that have been identified as related to physical activity, food choice, and obesity rates include social support and social networks, socioeconomic position and income inequality, and neighborhood factors (e.g., neighborhood built environment, safety, public financial support, governmental policy etc.; (Booth et al., 2001; McNeill, Kreuter, & Subramanian, 2006). One of these social-environmental characteristics is living setting, or residence type which has been widely studied for adults with ID. These studies have consistently found that persons who live in less supervised (versus more supervised) settings are more likely to be obese (Lewis, Lewis, Leake, King, & Lindemann, 2002; Melville, Hamilton, Hankey, Miller, & Boyle, 2007; Rimmer, Braddock, & Marks, 1995; Rimmer & Yamaki, 2006; Robertson, Emerson, Gregory, Hatton, Turner, et al., 2000; Stancliffe et al., 2011). However, a recent study that adjusted for individual characteristics and demographics, did not find a significant impact of living settings on obesity (Hsieh et al., 2014). Another social-environmental factor that appears to have an impact on obesity and physical activity among adults with ID is community participation. One study found that greater social participation and friendship networks were related to higher BMI among adults with Down syndrome living with families (Fujiura, Fitzsimons, Marks, & Chicoine, 1997). Social connection has been positively associated with high level of physical activity among adults with ID (Temple, 2009).

In addition to residence type and community participation, a third social-environmental characteristic that may be related to obesity and physical activity is everyday choice-making. As living arrangements have shifted from institutional to community-living, choice-making in daily living and community participation have been increasingly promoted for adults with ID. Previous studies have suggested that the availability of choice of individuals with ID may relate to the level of obesity, physical activity, other health behaviors, and adaptive behavior (Hatton et al., 2004; Young, Ashman, Sigafoos, & Grevell, 2001). Engagement in physical activity, sport, and recreation is an important lifestyle choice. However, the impact of everyday choice on BMI has not been investigated; one study that included health behaviors and daily choice making of adults with ID did not find a significant association between these variables (McGuire et al., 2007).

It is crucial to understand the association of these social-environmental factors (e.g., residence type, community participation, everyday choice) with BMI and physical inactivity in order to inform the development of intervention programs to reduce or prevent obesity and promote active lifestyle from early to older adulthood. In the present study, the National Core Indicators data offers an opportunity to investigate this at the national level with large samples.

The purpose of the present study was to examine (1) the impact of the adulthood stages of younger (20–39 years), middle (40–59 years), and older (60 years and older) on body mass index and physical activity of individuals living in community settings; and (2) the relationship between social-environmental context (i.e., residence type, everyday choices, and community participation) and BMI and PA in addition to adulthood stage with adjustment for individual characteristics of the adults with ID. The findings of this research will help shed light on which adulthood stage should be the focus and the role of everyday choices and community participation in promoting healthy lifestyles in adults with ID.

Methods

Sampling

Participating states

The National Core Indictors (NCI) project is a collaborative effort between the National Association of State Directors of Developmental Disabilities Services (NASDDDS) and the Human Services Research Institute (HSRI). Data were drawn from 16 states, the District of Columbia, and one sub-state entity participating in the 2009–2010 NCI program. The participating states include Alabama, Arkansas, California (Orange County only), Georgia, Illinois, Kentucky, Louisiana, Maine, Missouri, North Carolina, New Jersey, New York, Ohio, Oklahoma, Pennsylvania, Texas, and Wyoming. Participating states were expected to interview adults with ID using the Adult Consumer Survey with a random sample of at least 400 individuals. The Adult Consumer Survey included background information and two interview sections (Section I and Section II. This study was limited to the background information and Section II. The background information included demographics, other disabilities, mobility, health status, preventive health care use, psychotropic medications, residence, employment, and behavioral supports, etc.). Section II of the survey's interview portion was for adults with ID who were receiving services and included questions on community participation, choices, and rights.

Study participant selection

The total NCI 2009–2010 database contained 11,599 cases. We analyzed a subset of NCI 2009–2010 database participants. We excluded subjects who were younger than 20 or missing data related to age (n  =  305); missing data on level of ID (n  =  974); missing race data or did not know their race (n  =  328); missing residence type data or individuals living in institutions, nursing homes, homeless, or other settings (n  =  2,331); and missing or invalid data on everyday choice or/and community participation (n  =  745). We also excluded 2,632 subjects who had missing data related to the outcome measures (i.e., PA and BMI). We examined whether missing data related to outcome measures were missing at random. The results showed there were no differences in gender and adulthood stages between those with and without missing data related to the outcome measures. Given the trend towards community living for people with ID and the high rates of obesity in those settings, we excluded individuals in institutions and nursing homes. A total of 4,282 individuals were included in the multivariate models for the outcome measures of above normal BMI and not meeting the physical activity recommendation.

Measures

All the data on measures were obtained from the background information and Section II (consumer interview) of the Adult Consumer Survey. The background section was completed by an agency staff, a case manager/service coordinator, a residential staff, or a family caregiver. For staff, they were encouraged to refer to agency records or use a computer system to obtain the best responses. Section II was based on the interview with the persons with ID or with suitable proxies (e.g., family, advocate, staff, but not the case manager or service coordinator).

Dependent variables

Above normal BMI

Data of body weight in pounds and height in feet and inches were collected from the background section. BMI was calculated using the formula: weight (lb) × 703/[height (ft)]2(Kuczmarski & Flegal, 2000). Following the current guidelines, BMI was dichotomized as above normal (1) and not above normal (0) using the cutoff value of 25 kg/m2 which represents individuals who are at risk for being overweight and/or obese (Expert Panel on the Identification, Evaluation, and Treatment of Overweight in Adults, 1998)

Not meeting physical activity (PA) recommendation

The amount of physical activity (PA) was obtained for the background information. Per the recommendation of the Physical Activity Guidelines for Americans (U.S. Department of Health and Human Services, 2008), PA was defined as engaging in any moderate PA for at least 30 minutes, five times or more per week.

Independent variables

Individual characteristic control variables included level of ID, cerebral palsy, Down syndrome, gender, race, ambulatory status, use of psychotropic medication, and behavioral support needs. Categorical individual characteristic variables included cerebral palsy, Down syndrome, gender, race, ambulatory status, and use of psychotropic medication. “0” was coded as reference in multivariate logistic models. Having a diagnosis of cerebral palsy or Down syndrome was determined by the question “What other disabilities are noted in this person's record?” Race was coded into three categories: White, Black, and Hispanics/Other. Mobility was coded into three categories: non-ambulatory and always needed assistance to move around, ambulatory with aids or used a wheelchair independently, and ambulatory without aids. Use of psychotropic medications was defined as using any medications for mood disorder, anxiety, behavior problems, or psychotic disorders. Level of ID and behavioral support needs were treated as continuous variables. Level of ID data was obtained from a single NCI item, and was coded from 1(mild or ID at the upper end of the spectrum) to 4 (profound or ID at the lowest end of the spectrum). Behavioral support needs were assessed by whether an individual needed support to manage self-injurious, disruptive, and destructive behavior. The level of each behavioral support was rated from 1 (no support needed) to 3 (extensive support needed). A mean of the three items was calculated.

Adulthood stage

The adulthood stage of the individual was examined for its possible moderating effect. Age was coded into three adulthood stages: younger (20–39 years, a reference group), middle (40–59 years), and older (60 years and older).

Social-environmental factors

Social-environmental factors included residence type, everyday choices, and community participation. For residence type, we included five categories: group home (a reference group, agency-operated apartment, independent home or apartment, family (parent's or relative's) home, and foster care/host home. We excluded individuals living in specialized institutions and nursing facilities, along with those who were homeless or residing in other settings which did not fit into the five previously identified residential settings. For everyday choices, we used the Everyday Choice scale collected in Section II (consumer interview), which was the sum score of three items including a daily schedule choice, how to spend free time, and what to buy with spending money (Lakin et al., 2008; Tichá et al., 2012). Each choice was coded from 0 to 2: 0  =  Someone else chose, 1  =  Person had some input, or 2  =  Person made the choice. The scaled score ranged from 0 to 6. Internal consistency was .79 (Standardized Cronbach's alpha). The third social-environmental factor of community participation (data collected from consumer interview) was calculated using the total number of engagement in seven community activities (i.e., shopping, running errands or appointments, entertainment, going to a restaurant or coffee shop, attending a religious service or spiritual practice, exercise, and vacationing) in the past month.

Statistical Analysis

Statistical analyses used the SPSS version 22.0 (IBM Corp, 2013). Descriptive statistics were employed for individual characteristics variables and a series of univariate logistic regressions was conducted on individual characteristic variables with each dependent variable (above normal BMI and not meeting PA recommendation) to identify potential confounding variables for the multivariate logistic models. We used a suggested p value cut-off point of 0.25 on the Wald test for univariate analysis to identify potential confounders including those that met the cut-off criteria in the multivariate models (Bendel & Afifi, 1977; Mickey & Greenland, 1989). As a result, none of the individual characteristic variables were excluded from the multivariate logistic regressions for the dependent variable above normal BMI. Down syndrome and behavioral support needs were excluded in the multivariate logistic regressions for the dependent variable not meeting PA recommendations. To examine the impact of adulthood stage on BMI and PA, adulthood stage was added to a separate multivariate logistic regression with adjustment for individual characteristics (Model I). In Model II, we added social-environmental factors to examine their association with above abnormal BMI and with not meeting the PA recommendation, adjusting for individual characteristics including adulthood stage. A significance level at a p value of .05 was used for all multivariate logistic regression models.

Results

Descriptive statistics indicated that there were more males than females (56.6% vs 43.4%), and that most participants were White (70.1%) and ambulatory (79.3%). Many participants had ID at the upper end of the spectrum (42.1%), used psychotropic medications (53.7%), and were middle aged (45.4%). Over 42% of participants lived in group homes, followed by 28.3% in family homes, 17.4% in independent homes or apartments, 7.1% in agency-operated apartments, and 4.5% in foster care/host homes. Nearly two thirds (63.6%) of the participants had an above normal BMI; more than four fifths (86.6%) of the participants did not meet the current physical activity recommendations. Means and standard deviations of behavioral support needs, everyday choices, and community participation are presented in Table 1. Chi squared tests indicated significant difference in overall distribution of above normal BMI between adulthood stage groups, x2(2, N  =  4282)  =  40.65, p  =  .000, and residence type groups, x2(4, N  =  4282)  =  28.82, p  =  .000. Adults with ID who were in the middle adulthood stage had a higher percentage of above normal BMI, than those who were in the older adulthood stage (68.5% vs. 56.7%). Adults with ID (72.8%) who lived in agency-operated apartments were more likely to have above normal BMI than those who lived in group homes (61.9%), family homes (60.8%), or foster care/host homes (60.9%). Chi squared tests indicated significant differences in the percentage of people with above normal body weight between adulthood stage groups who resided in the family home residence type, x2(2, N  =  1212)  =  34.05, p  =  .000, and among those who resided in the foster care/host home residence type, x2(2, N  =  192)  =  7.30, p  =  0.26. The middle group who lived in in foster care/host homes (72%) or in family homes (70.9%) had the highest percentage of above normal BMI. In contrast, the older age group living with parents or relatives had the lowest above normal BMI rate (33.3%). There were no significant differences in PA between adulthood stage or residence type groups (see Table 2).

Table 1

Participant Characteristics (N  =  4,282)

Participant Characteristics (N  =  4,282)
Participant Characteristics (N  =  4,282)
Table 2

Percentage of Adults Above Normal BMI and Not Meeting PA Recommendation by Adulthood Stage Within Residence Type

Percentage of Adults Above Normal BMI and Not Meeting PA Recommendation by Adulthood Stage Within Residence Type
Percentage of Adults Above Normal BMI and Not Meeting PA Recommendation by Adulthood Stage Within Residence Type

Model I: Adulthood Stage and Demographic Characteristics

A summary of results from the hierarchical regression analyses is presented in Tables 3 and 4. After adjusting for individual characteristics, a significant positive association with middle age and above normal BMI, AOR  =  1.35, 95% CI [1.17, 1.56] was noted. Significant individual characteristics included having Down syndrome, (AOR  =  1.91, 95% CI [1.48, 2.46]; being female, AOR  =  1.32, 95% CI [1.16, 1.51]); being Black, AOR  =  1.31, 95% CI [1.11, 1.54]; being ambulatory without aids, AOR  =  1.62, 95% CI [1.24, 2.10]; and using psychotropic medications, AOR  =  1.53, 95% CI [1.32, 1.77]. The severity of intellectual disability, AOR  =  0.69, 95% CI [0.65, 0.74], and having cerebral palsy, AOR  =  0.56, 95% CI [0.46, 0.68] had an inverse association with above normal BMI (Table 3).

Table 3

Summary of Hierarchical Multivariate Logistic Models for Above Normal BMI (N  =  4,282)

Summary of Hierarchical Multivariate Logistic Models for Above Normal BMI (N  =  4,282)
Summary of Hierarchical Multivariate Logistic Models for Above Normal BMI (N  =  4,282)
Table 4

Summary of Hierarchical Multivariate Logistic Models for Not Meeting PA Recommendation (N  =  4,282)

Summary of Hierarchical Multivariate Logistic Models for Not Meeting PA Recommendation (N  =  4,282)
Summary of Hierarchical Multivariate Logistic Models for Not Meeting PA Recommendation (N  =  4,282)

Regarding PA, adulthood stage had no impact after adjusting for individual characteristics. Significant individual characteristics included having a lower intellectual function, AOR  =  1.16, 95% CI [1.05, 1.28]; being female, AOR  =  1.29, 95% CI [1.07, 1.55]; and using psychotropic medications, AOR  =  1.20, 95% CI [1.001, 1.44]. Being Hispanic or other race, AOR  =  0.60, 95% CI [0.45, 0.80], and being ambulatory without, AOR  =  0.10, 95% CI [0.05, 0.24] or with aids, AOR  =  0.32, 95% CI [0.13, 0.78] had inverse associations with not meeting the PA recommendation (Table 4).

Model II: Social-Environmental Factors

When adjusting for individual characteristics, participants who were more likely to have above normal BMI were individuals who were middle-aged, AOR  =  1.34, 95% CI [1.15, 1.55]; living in agency-operated apartments, AOR  =  1.35, 95% CI [1.02, 1.80], or independent homes/apartments, AOR  =  1.26, 95% CI [1.04, 1.54]; and individuals with more everyday choices, AOR  =  1.05, 95% CI [1.01, 1.10]. Significant individual characteristics included having a higher intellectual function, AOR  =  0.73, 95% CI [0.68, 0.79]; not having cerebral palsy, AOR  =  0.56, 95% CI [0.46, 0.68]; having Down syndrome, AOR  =  1.99, 95% CI [1.54, 2.57]; being female, AOR  =  1.32 95% CI [1.16, 1.51]; being Black, AOR  =  1.29, 95% CI [1.09, 1.53]; being ambulatory without aids, AOR  =  1.58, 95% CI [1.21, 2.07]; and using psychotropic medications, AOR  =  1.55, 95% CI [1.33, 1.80] (Table 3).

Adults with ID who lived in family or relative homes, AOR  =  1.28, 95% CI [1.004, 1.63]; or in foster care or host homes,(AOR  =  1.67, 95% CI [1.01, 2.75]; and engaged in less community participation, AOR  =  0.86, 95% CI [0.81, 0.92] were more likely to not meet the PA recommendation. Significant individual characteristics related to not meeting physical activity recommendations included being female, AOR  =  1.28, 95% CI [1.06, 1.54]; not being Hispanic or other race, AOR  =  0.55, 95% CI [0.41, 0.74]; being non-ambulatory (ambulatory without aids) AOR  =  0.27, 95% CI [0.19, 0.40], (or ambulatory with aids) AOR  =  0.36, 95% CI [0.15, 0.89]; and using psychotropic medications, AOR  =  1.24, 95% CI [1.02, 1.50]; (Table 4).

Discussion

After adjusting for other demographics and characteristics, findings from the present study indicate that adulthood stage has an impact on above normal BMI but not on physical inactivity. Above normal BMI is more prevalent in middle age adulthood (40–59 years) than in other adulthood stages. The impact of middle adulthood stage on above normal BMI noted in this study concurs with findings from previous studies (Hsieh et al., 2014; Stancliffe et al., 2011). Middle-aged individuals with ID may be more at risk of developing above normal body weight than younger or older adults. Hence, health promotion programs targeting body weight management need to focus on this adulthood stage or start the programs in earlier adulthood to reduce the risk of developing obesity in middle age. Though we found adulthood stage related to above normal BMI, we did not find a similar relationship to physical activity. Only one previous study showed physical inactivity to be related to increasing age among men with ID (Emerson, 2005). One reason for this divergence could be that in this study, the majority of adults across different ages did not engage in sufficient physical activity. Only 13% of adults with ID in the present study met the PA recommendation. Therefore, a need exists for promoting physically active lifestyles across adulthood for this population.

With regard to social-environmental factors, our findings support previous studies indicating that persons with ID living in less supervised (versus more supervised) settings (e.g., independent homes or apartments) are more likely to have unhealthy weights (Lewis et al., 2002; Melville et al., 2007; Rimmer & Yamaki, 2006). Individuals with ID are especially at risk of developing above normal BMI when they are able to make more everyday choices. Our post hoc analysis indicates that individuals who have above normal BMI have significantly more choice making opportunity (56% vs. 45%). Hence, there is a need to further investigate how they choose to spend free time and what they choose to buy. Although adults with ID who live in more independent settings have more choices and control in their life, their obesity rates are also increased. Our findings highlight the importance of helping adults with ID make the right choices to adhere to healthy lifestyles while also promoting autonomy for people with ID. The information gained from this study can help tailor health promotion information for adults with ID as it points to the importance of more information on the need for health promotion and additional support for healthy behavior choices. One example of a curriculum that not only educates adults with ID regarding the need for physical activity, but also takes into account their personal desires and choices and their support systems is the Health Matters: Health Education Curriculum for Individuals With Intellectual and Developmental Disabilities Curriculum (Heller, Hsieh, & Rimmer, 2004; Marks, Sisirak, & Chang, 2013; Marks, Sisirak, & Heller, 2010), which has been shown to increase fitness and positive attitudes toward exercise.

The great need for physical activity programs is further supported by the exceptionally low prevalence of adults with ID participating in the recommended amount of physical activity. Current physical activity guidelines for Americans recommend that regardless of whether a disability is present, every adult should engage in moderate physical activity for at least 30 minutes, five times or more per week, in order to gain health benefits that reduce the risk for coronary artery disease, stroke, and obesity (U.S. Department of Health and Human Services, 2008). In this study however, less than 14% of the adults with ID met the recommended level of PA, demonstrating the existing gap between recommendation and practice. Preexisting disability-related conditions among persons with ID may limit their ability to perform or engage in physical activity. Further investigation on effective health promotion programs are needed to promote physical activity in adults by disability-related condition types.

Our findings also indicate that residence type and lack of community participation are associated with not meeting the PA recommendation. Adults with ID who lived in foster care/host homes or family homes and engaged in less community participation, were more likely to have insufficient physical activity. One possible explanation is that adults with ID who reside independently or with family, have less access to physical activity resources than those individuals living in group homes (Howie et al., 2012). Hence, it is important to include a supporting family member in health promotion programs for adults with ID living with family in order to promote a physically active lifestyle. If care providers or family caregivers do not have knowledge of the benefits of physical activity and skills to assist persons with ID then it is unlikely that efforts will be sustainable. For instance, including family members along with individuals with ID in a walking club, a group health promotion program, or joint membership in a fitness club might be a way to promote an active lifestyle. Unlike previous studies (Hatton et al., 2004; McGuire et al., 2007; Young et al., 2001), we did not find that daily choice related to physical activity engagement.

Social and environmental support plays an important role in initiating and maintaining a physically active lifestyle for adults with ID. In order to increase successful adherence to a physical activity program for adults with ID, activities that are highly enjoyable for the individual need to be incorporated into their routines (Rimmer, 2000). Walking is one common activity of community participation that can be a major contributor to increased physical activity. Including caregivers in health promotion programs to support individuals with ID as they engage in community participation and physical activity may help them meet the recommended levels of physical activity. Further research on physical activity interventions and healthy dietary habit formation is needed, and practice guidelines need to be developed.

The strength of the present study is the large-scale of the sample size across various residential settings. However, interpretations of the study's findings need to be made with caution due to several study limitations. This was a cross-sectional study; hence, a causal relationship cannot be established. Furthermore, our analysis of subjects' physical activity information was based on proxy responses about the duration and frequency with which subjects engaged in moderate physical activity. This is a limiting factor because proxies might have either underreported or overreported the intensity of physical activity. It is possible that a higher rate of not meeting recommendations of physical activity could be due to recall bias and hence is underreported. We are also aware that most of independent variables (except everyday choices and community participation) are proxy responses which could cause bias especially related to the use of psychotropic medications and behavioral support needs. It is possible that agency staff who have access to their client's health records may provide more accurate information about mediations and behavioral support needs. On the other hand, families may not have knowledge of types of medication their family members with ID are taking. Due to the nature of the study, some potential social-environmental factors such as, social support network, built environment, and public policy were not available for investigation. Also, data on dietary habits was lacking in the NCI dataset which would have been useful as a determinant of obesity. Last, because questions regarding community participation and everyday choices questions were completed by individuals with ID or proxies or a combination of both, it is possible that a discrepancy in the responses exists between individuals with ID and the proxy.

Conclusions

Obesity and physical inactivity are not only detrimental to the health of individuals, but they also contribute to escalating medical expenses and societal burden. Adults with ID are vulnerable to both obesity and physical inactivity. The present study examined BMI and physical activity among adults with ID. Results indicated that the majority of this population has an above-normal BMI and does not engage in sufficient physical activity levels to achieve optimum health benefits. Middle-aged adults with ID are more likely to have an above normal BMI. Our research also showed that daily choice-making plays a role in an individual's BMI level, just as community activity engagement contributes to physical activity levels. In conclusion, there is a need to pay more attention to weight management in individuals with ID, particularly in the middle-adulthood stage by providing health education emphasizing healthy lifestyle choices. The findings also suggest the importance of community participation as a way of promoting more physical activity across all adulthood stages.

Acknowledgments

This document was produced under Grant Nos. H133B080009 and H133B130007 awarded by the U.S. Department of Education's National Institute on Disability and Rehabilitation Research to the Rehabilitation Research and Training Center (RRTC) on Aging with Developmental Disabilities-Lifespan Health and Function (Grant No. H133B080009)and the RRTC on Developmental Disabilities and Health (Grant No. H133B130007) at the University of Illinois at Chicago. The contents of this article do not necessarily represent the policy of the U.S. Department of Education, and should not be assumed as being endorsed by the U.S. Federal Government. We also would like to acknowledge Charles Moseley, Ed.D., and the National Association of State Directors of Developmental Disabilities Services (NASDDDS) for their support.

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Author notes

Kelly Hsieh, University of Illinois at Chicago, U.S.; Tamar Heller, University of Illinois at Chicago, U.S.; Julie Bershadsky, Human Services Research Institute, Cambridge, MA, U.S.; and Sarah Taub, Human Services Research Institute, Cambridge, MA, U.S.