Abstract

Using the National Longitudinal Study of Adolescent to Adult Health (Add Health), we analyzed whether having any disability and having specific types of disabilities in adolescence were linked to the level of success in the attainment of five adulthood markers: college degree, employment, independent living, marriage, and parenthood. Using Poisson regression, we found a negative association between having a disability and the number of adulthood markers attained. However, disability type moderated this relationship: learning, intellectual, and multiple disabilities were associated with lower chances of attainment while no association was found for physical disability. Intellectual disability showed particularly strong associations. Similar results appeared when analyzing each marker separately in binary logistic regression models. Many previous studies showed disparities in these outcomes using samples that included adults of a wide age range, but the current results based on an adolescent sample show that disparities already exist in young adulthood. Current policies and programs aimed to reduce disparities between people with and without disabilities largely focus on individual efforts by people with disabilities. In light of the present results highlighting the extensive disparities, such policies should consider all key aspects of transitions and focus on institutional redesign.


In the U.S., the Americans with Disabilities Act (ADA) of 1990 aims to increase opportunities for persons with disabilities (PWD), but disparities between people with and without disabilities persist in major life spheres such as education, employment, residential community, and family. For example, PWD are half as likely to attend postsecondary school, compared to people without disabilities (PWoD), and the employment gap between the two groups has widened since enactment of the ADA (Kraus 2017; Wagner et al. 2005). Disability is usually defined as a deviation from established norms in body structure or function that restricts participation in normal daily activities (ADA 1990; Üstün et al. 2010), and PWD represent 26% of the adult population (Okoro et al. 2018) and 13% of the student population (NCES 2018). Disparities in major life spheres between people with and without disabilities have been widely documented, but few studies locate disparities that emerge during major life stage transitions.

The current study draws on the life course literature and conceptualizes these outcomes as a set of key markers for successful transition to adulthood. We then illustrate how disparities manifest during the transition to adulthood and how they vary by disability type. Studying adolescents' transition to adulthood is especially important because it can identify mechanisms that engender negative outcomes for PWD in later life stages (Shanahan 2000). Scholars typically conceptualize successful transition to adulthood as the attainment of five social markers including completion of college education, employment, independent living, marriage, and parenthood (Coleman 1974; Furstenberg, Rumbaut, and Settersten 2005; Shanahan 2000). Various studies document negative associations between disability and the transition to adulthood, but the current study extends the existing literature in several ways.

First, this article examines any type of disability and four types of disability separately (physical, learning, intellectual, and multiple disabilities), which extends existing scholarship that overlooks variation by disability type (e.g., Houtenville and Kalargyrou 2012; Shandra and Chowdhury 2012). A physical disability is a limitation in bodily functioning (e.g., respiratory disorders), a learning disability is a limitation in neurological processing (e.g., dyslexia), and an intellectual disability is a limitation in intellectual and adaptive functioning (e.g., Down syndrome). Multiple disabilities refer to the presence of two or more types of disabilities. Past research focused on one type of disability at a time when examining consequences for adulthood marker attainment (e.g., Rojas, Haya, Lazaro-Visa 2014), and the extent to which one can generalize these results to other types of disabilities remains unclear. Some studies combined all types of disability into one group without separating them (e.g., Holloway 2001), which was problematic because barriers to successful transition vary across disability types (Boman et al. 2015; Xiang et al. 2010).

Second, we reveal the utility of analyzing a total count of attained markers to assess overall progress of transition to adulthood and each marker separately to understand the nuances. The existing research tends to examine one transition marker at a time (e.g., MacInnes 2011). This precludes one from gaining a holistic view for the progress toward adulthood. Few studies have analyzed attainment of all markers simultaneously (notable exceptions include Erickson and Macmillan 2018; Janus 2009; Wells, Hogan, and Sandefur 2003). These studies examine the transition to adulthood using samples in their early to mid-20s. The current study goes beyond these past studies by examining the extent of disparities in the late 20's—a more meaningful time of measurement given first marriage and childbirth usually occur in the mid- to late 20s (CDC 2019; U.S. Census Bureau 2019).

Third, the current analysis provides nationally representative results by using data from The National Longitudinal Study of Adolescent to Adult Health (Add Health). This approach elevates the level of generalizability compared to previous studies, which typically used small, convenience samples (e.g. Galvin 2005; Saxton et al. 2011). Also, Add Health implements a longitudinal design, which facilitates interpretations of causal order and makes improvements from past cross-sectional studies (e.g. Brault 2010; Maroto and Pettinicchio 2014). Furthermore, Add Health includes a reference group (i.e. PWoD) unlike other datasets frequently used in the disability literature (e.g. The National Longitudinal Transition Study of students receiving special education services). The dataset therefore eliminates methodological problems arising from comparing to nonequivalent datasets (Levine and Nourse 1998).

THEORETICAL FRAMEWORK

The life course perspective conceptualizes individual lives as consisting of distinct stages characterized by unique sets of social roles and transitions between these stages (Elder 1974). Among several key transitions, our study focuses on the transition from adolescence to adulthood (Coleman 1961; Hogan and Astone 1986; Shanahan 2000). In recent decades, the transition to adulthood has become more elongated and flexible (Arnett 2003; Furstenberg et al. 2005; Shanahan 2000). Pathways to adulthood have also become more individualized, reflecting the diversity among adolescents in terms of gender, race, socioeconomic class, and sexual orientation (Arnett 2003; Settersten 2007; Ueno 2010). The current study reveals if the transition to adulthood differs for people with and without disabilities.

The transition to adulthood may be particularly challenging for PWD for two reasons. First, as PWD leave adolescence, they age out of government schooling programs, such as special education and mental health services. Although some of these government services are available through age 21, they are underfunded and only cover a portion of PWD in need (Osgood et al. 2005). Consequently, some young people abruptly lose much of the institutional support that they had as they become older. Second, compared to PWoD, PWD have less access to other types of support, such as family or higher education, which many young people rely on during the transition to adulthood (Furstenberg et al. 2005; Osgood et al. 2005). These factors may not only delay the transition to adulthood but also exacerbate the negative consequences of unsuccessful attainment.

A central principle of life course perspective is that socio-historical context profoundly affects individual lives although it recognizes the role of agency (Elder 1974). This idea resonates with the "social model of disability," which conceptualizes disability as a product of the social environment, as opposed to an individual attribute. It contends that activity and participation restrictions are caused by social context rather than the impairment itself (Oliver 1983; UPIAS 1976). According to the social model, PWD would experience more barriers in the transition to adulthood, compared to PWoD, because society has largely been organized for PWoD. Barriers can be physical, attitudinal, communicative, or political (CDC 2018), and they limit one's ability to participate in social institutions including schools, work organizations, and family. The social model of disability is compatible with life course perspective, which emphasizes that social structure creates disparities in the level of success in transition to adulthood across people in different social positions (Furstenberg et al. 2005; Shanahan 2000).

DISABILITY AND THE TRANSITION TO ADULTHOOD

PWD face more challenges in the transition to adulthood than those without disabilities although they have similar (or higher) expectations (Leiter 2012; Shandra 2011). Most notably, PWD have a higher likelihood of missing some or all markers by their early to mid-20's, compared to PWoD (Erickson and MacMillan 2018; Janus 2009). Still, marker attainment varies by disability type because society creates different barriers depending on disability type. Further, for a given type of disability, the severity of barriers varies across adulthood markers. Below, we discuss key findings on disability and each adulthood marker while noting various barriers by disability type.

Obtaining a College Degree

Once reserved for those of high socioeconomic status, higher education is now an important feature of the transition to adulthood because college degrees are vital in securing good jobs and economic stability (Settersten and Ray 2010). Compared to PWoD, PWD experience more barriers during their academic career (Morgan et al. 2008) as reflected in PWD's lower chance of obtaining college degrees, which is about half the rate of PWoD (Altman and Bernstein 2008). This attainment gap reflects PWD's reduced chance of admission as well as their reduced chance of completion once admitted (Sanford et al. 2011). Even when successfully admitted, it takes PWD twice as long to complete their college degree, compared to PWoD (NCD 2003).

Previous studies used qualitative data to document PWD's barriers to academic success. A main barrier is faculty's perception, behaviors, and lack of knowledge on disability (Abreu 2017; Leake and Stodden 2014). Another barrier is inaccessibility, including inaccessible website design (Quinn et al. 2019), lack of plain language, and distance between classrooms. Other barriers include physical demands (e.g., managing medical symptoms), emotional struggles (e.g., pressure to prove themselves as self-sufficient), and marginalization from peers (Holloway 2001; Hong 2015). These factors limit PWD's college experiences and academic performance, but they also hinder their willingness to seek disability services although accessing disability services can be a barrier within itself (Bessaha et al. 2020; Marshak et al. 2010). For example, obtaining and maintaining accommodations is burdensome because some universities require submission of medical documents to the disability services office every semester (Dolmage 2017). Further, accommodations are very limited (e.g., extra time on tests) and do not address persistent physical, intellectual, and social inaccessibility.

Looking at past findings together, PWD have lower rates of college attainment than PWoD, regardless of disability type (Brault 2010; Queirós et al. 2015), but the degree of disparity varies by disability type. Compared to people with other types of disabilities, people with intellectual and multiple disabilities are less likely to prepare for and attend postsecondary education (Grigal, Hart, and Migliore 2011; Lipscomb et al. 2017). People with learning and intellectual disabilities may have a particularly lower rate of college degree attainment because these disabilities directly impact academic performance in the current education system, which does not adequately consider their conditions.

Obtaining Employment

Even when PWDs graduate with a college degree, they are less likely to be employed than college graduates without disabilities (Stewart and Schwartz 2018; USBLS 2015). Among working-aged people, approximately 28% of PWD are employed, compared to 73% of PWoD (USBLS 2017). Many PWD desire to participate in the workforce, but they face barriers in the labor market including employer discrimination (Foster and Wass 2013; Friedman 2019). Employers have negative perceptions of PWD (e.g., unable to work and require costly accommodations) and assume supervisors will feel uncomfortable managing them (Houtenville and Kalargyrou 2012). These factors limit PWD's job opportunities and sort them into low-skilled jobs that require minimal levels of education and experience (Maroto and Pettinicchio 2014).

Looking at past findings together, PWD have lower rates of employment, but rates vary by disability type. People with physical (Queirós et al. 2015) and learning (Seo, Abbott, and Hawkins 2008) disabilities have similar rates of employment, compared to PWoD. Findings are mixed for people with intellectual disabilities. Some studies show their disadvantages (Kumin and Schoenbrodt 2016), and others show no such disadvantages (Queirós et al. 2015). People with multiple disabilities are most disadvantaged in employment rates (Newman et al. 2011), indicating that they face more serious barriers in the labor market and the workplace.

Establishing Independent Living

Developing independence from parents is an important element of transition to adulthood, and establishing independent residency is key in accomplishing this expectation (Rosenfeld 2007; Settersten and Ray 2010). Compared to PWoD, PWD are 15% less likely to establish independent living (Newman et al. 2011; also see Janus 2009). Barriers to PWD's independent living include the high cost of housing and assistive services, lack of government residential services (Braddock 2002; Larson et al. 2012), and building inaccessibility (Smith, Rayer, and Smith 2008). Less than 5% of housing units are accessible for people with moderate disabilities (HUD 2015). Further, many PWD must negotiate their ability to live independently with caregivers and disability staff (Reed et al. 2014). Even when PWD establish independent living, they may involuntarily move back home for a variety of reasons including mistreatment by personal assistants (Saxton et al. 2011).

Looking at past findings together, PWD have low rates of independent living although rates vary substantially (16% to 65%) by disability type (Newman et al. 2011). Learning disability is associated with higher levels of independent living, compared to intellectual and multiple disabilities. The present study is one of the first to examine whether a disparity in independent living exists between people with and without disabilities using data in which the two groups came from the same sampling frame.

Entering Marriage and Becoming a Parent

Transition to adulthood is also characterized by acquisition of two family roles—spouse and parent. Unsuccessful attainment of independent living means that the person continues to experience a lack of privacy, thereby reducing the person's likelihood of developing intimate relationships (Riddell et al. 2001; Rojas et al. 2014). PWD have lower rates of marriage and parenthood than PWoD (Janus 2009; Tumin 2016) although some studies find no differences for parenthood (Newman et al. 2011). Despite PWD's desire to find lifelong partners and become parents (Rojas et al. 2014; Shandra 2011), they experience barriers when trying to achieve these goals. PWD tend to be more socially isolated, which lowers their chance of meeting potential spouses (Hayden et al. 1992; Riddell et al. 2001). Further, PWoD often encounter social disapproval when developing intimate relationships with PWD (Milligan and Neufeldt 1998), which may lead to relationship dissolution. Such disapproval may come from family and caregivers (Leiter 2012; Martino and Perreault-Laird 2019).

Mainly relying on qualitative methods, the existing literature has identified two main reasons for PWD's lower sexual activity, which may lead to lower chances of parenthood: negative societal and self-perceptions. Negative societal perceptions include stereotypes that PWD are asexual, suffer from sexual dysfunction, and do not have the mental capability to make judgments regarding sexual activity (Milligan and Neufeldt 2001; Rojas et al. 2014). Such perceptions may lead to internalization resulting in lower sexual esteem and feelings of unattractiveness (Galvin 2005; Taleporos and McCabe 2001). Negative self-perceptions may discourage PWD from contacting or responding to potential spouses. Furthermore, there are legal barriers to parenthood for PWD, such as a lack of standard criteria and assessment tools for sexual consent capacity (Lyden 2007). When PWD have children, they often feel scrutinized by health professionals and are more likely to lose custody of their children (Frederick 2015; Mayes and Gwynnyth 2012).

Looking at past findings together, PWD have lower rates of marriage and parenthood, but the studies provide limited information about how these disparities vary by disability type. Compared to no disability, learning and multiple disabilities are associated with lower rates of marriage, but physical disability is not (MacInnes 2011). These patterns may be similar for parenthood. Some studies find lower rates of marriage among intellectual disability (May and Simpson 2003) while others do not (MacInnes 2011). Intellectual disability is associated with lower rates of parenthood (May and Simpson 2003).

Summary and Hypotheses

Overall, past studies have shown that PWD attain adulthood markers at lower rates than PWoD. However, the magnitude of the disparity depends on disability type and transition marker, indicating that the type and magnitude of barriers vary across people with different disabilities and across different transition markers. Comparing disability types, past findings suggest that disparities between people with and without physical disabilities are relatively small (MacInnes 2011; Queirós et al. 2015), but disparities between those with and without intellectual or multiple disabilities are large (Erickson and Macmillan 2018; Newman et al. 2011). These findings reflect more serious barriers that society creates for different types of disabilities.

Beyond these overall patterns, three issues remain unclear. First, some adulthood markers, mainly independent living and parenthood, are understudied. Consequently, little is known about the disparities between people with and without disabilities in these outcomes. Second, physical disability is studied less frequently, and findings regarding intellectual disability and marker attainment have been mixed across studies, which has limited the ability to make conclusions about how the magnitude of disparities varies across disability types. Third, most studies focused on one type of disability and one adulthood marker. Therefore, the differences across disability types and markers can only be inferred from a comparison across individual studies. To overcome these limitations, our analysis includes four types of disability and five types of adulthood markers.

Based on previous scholarship, we expect to find a negative relationship between disability and number of attained markers (H1). Similarly, we expect that disability will have a negative association with attainment of each adulthood marker (H2). However, we expect the association between disability and transition to adulthood to vary by disability type (H3). Past findings are sparse and highly dependent on methodological designs (e.g., sample size, measures), so they do not allow us to propose specific patterns of differences.

METHODS

Data and Sample

Data were obtained from Add Health, which is nationally representative of students who attended U.S. middle and high schools in 1994. A stratified, random sampling method was implemented in data collection. Participants provided informed consent for their participation. Add Health followed adolescents through early adulthood in four waves, and the sample included a sufficient number of PWD to maintain statistical power. For more information on the sampling method, see Harris et al. (2009).

We analyzed data collected at Wave 1 (1994/95), when respondents were 7th through 12th graders, and Wave 4 (2008/09), when most respondents were aged between 26 and 31 years. 2 We used data from in-home interviews with targeted adolescents at Wave 1, interviews with adolescents' parents (mostly mothers) at Wave 1, and in-home interviews with original participants at Wave 4. Wave 1 response rate was 70% (n=20,745), parental response rate was 85.4% (n=17,640), and wave 4 response rate was 80.3% (n=15,701). Respondents who were categorized as having a learning, intellectual, or multiple disabilities were less likely to participate at Wave 4 although physical disability was not associated with Wave 4 participation. Of the respondents who participated in all three interviews and were part of the core sample (n=12,794), 4.62% of respondents had missing data on at least one study variable. After deleting these cases with missing data listwise, the final operational sample consisted of 12,203 respondents.

Dependent Variables

We included measures for the five adulthood markers identified in the literature (Shanahan 2000). Attainment of College Degree was measured in Wave 4 and coded dichotomously (1=bachelor's degree or higher; 0=others). We decided to focus on this outcome, instead of college enrollment or high school completion, because higher education has expanded and college completion is becoming the new norm. Almost half of young adults today obtain a degree (NCES 2019). Further, completion of a college degree has important implications for occupational attainment and earnings (Day and Newburger 2002). In a supplemental analysis, we examined high school completion as the outcome and found results similar to the primary analysis based on college degree.

Employment was coded dichotomously (1=yes; 0=no) from the following Wave 4 question: "Have you ever worked full time at least 35 hours a week at a paying job while you were not primarily a student? The measure considered whether they had ever been employed full-time, rather than being part time or unemployed. In a supplemental analysis, we measured employment as "currently working for pay at least 10 hours a week" and obtained similar results. We focused on full-time employment in the primary analysis because getting a full time job marks an important transition although some people are unable or uninterested to sustain the status.

Independent Living was coded dichotomously from the following Wave 4 question: "Where do you live now [stay most often]?" Because successful attainment indicated voluntary, independent living from parents, those living at another person's home, their own place, dormitories, barracks, and communal homes were coded "1," representing successful attainment. Those living with their parents were coded "0," representing unsuccessful attainment. In addition, those living in group quarters, such as a halfway house, or those without a home were coded "0." Although these respondents lived away from parents, their living arrangement was likely involuntary and did not indicate independence. In a supplemental analysis, we measured independent living more narrowly as living at "their own place" and obtained similar results.

Marriage was measured at Wave 4 and coded dichotomously (1=have been married or currently married; 0=never married). We coded divorced people as "1" because marriage is a marker of adulthood regardless of whether it ends in divorce. Although cohabitation in the U.S. has been increasing (Cherlin 2004), people make distinctions between marriage and cohabitation in terms of commitment and responsibilities (Stanley, Whitton, Markman 2004). Further, marriage is a socially recognized relationship form that comes with legal privileges and obligations, and cohabitation is not widely recognized as a traditional adulthood marker, which is the focus of this article.

Becoming a Parent was coded dichotomously as having a son or daughter (biological, adopted, step, or foster) living in the respondent's household (coded 1) or otherwise (coded 0) at Wave 4. We included non-biological children because it requires certain responsibilities regardless of biological relationships.

Number of Attained Markers was constructed by summing all five adulthood markers into one count variable ranging from 0 to 5.

Independent Variables

Disability categories were not mutually exclusive. In an exploratory analysis, we used an alternative coding scheme that consisted of mutually exclusive categories, but the analysis generated random results, perhaps due to low frequencies of some categories. Thus, we concluded that using overlapping categories works the best for the current data.

Physical Disability was based on Wave 1 information from both adolescent and parent interviews. Adopting Cheng and Udry's (2002) strategy, we created a dichotomous variable using a series of four questions including: "Do you [does your child] have difficulties using limbs due to a permanent physical condition? Do you [does your child] use equipment such as a wheelchair, brace, or artificial limb due to a permanent physical condition?" If respondents or parents responded "yes" to any of the questions, respondents were classified as having a physical disability (coded 1). Everyone else was coded "0." A supplemental analysis using a stricter measure of physical disability, which required an affirmative response to both questions (Blum, Kelly, and Ireland 2001), yielded the same substantive results.

Learning Disability was measured using information from Waves 1 and 4. In Wave 1, parents were asked, "Does [your child] have a specific learning disability such as difficulties with attention, dyslexia, or some other reading, spelling, writing, or math disability? Did [your child] receive any type of special education services during the past twelve months?" If parents responded "yes" to both questions, respondents were classified as having a learning disability (Blum et al. 2001). At Wave 4, respondents were asked, "Has a doctor, nurse or other health care provider ever told you that you have or had attention problems with ADD or ADHD? How old were you when this happened?" This question was therefore based on respondents' retrospective self-reports of clinical diagnoses. Respondents who had a diagnosis in adolescence (before the age of 20) were also classified as having a learning disability.

Intellectual Disability was measured by the following question from the Wave 1 parent interview: "Is [your child] mentally retarded?" (MacInnes 2011). Responses were coded dichotomously (1=yes, 0=no).

Multiple Disabilities was created by considering all three types of disability. Respondents who had 2 or 3 disabilities were classified as having multiple disabilities (coded 1). Everyone else (1 or 0 disabilities) was coded as "0."

An overall dichotomous indicator, Any Disability was created by combining all three types of disability into one dichotomous measure (1=any disability, 0=no disability).

Control Variables

We controlled for a range of sociodemographic variables that were known to be associated with disability and the transition to adulthood (Arnett 2003; Xiang et al. 2010). Age at Wave 4 was measured in years. High school completion was measured at Wave 4 and coded dichotomously (1=high school degree or GED, 0=less than high school degree). Sex was measured at Wave 1 (adolescent interview) and coded dichotomously (male=1, female=0). Race was measured at Wave 1 (adolescent interview), and six dummy variables were created: "Hispanic," "non-Hispanic Black," "Asian or Pacific Islander," "American Indian or Native American," "non-Hispanic white," and "others." As an indicator for family socioeconomic status, parent's education was measured using Wave 1 parent interview. We created an ordinal variable that distinguished between parents with a college degree (coded 2), high school degree or GED (coded 1), and less than a high school degree (coded 0).

Analytic Technique

We used Poisson regression to analyze the association between disability and number of markers attained and binary logistic regression to assess the relationship between disability and each adulthood marker separately. In both the Poisson and logistic regression analyses, we ran five models. Model 1 specified the relationship between "any disability" and the outcome. Models 2 through 5 specified the relationship between specific types of disability (i.e., physical, learning, intellectual, and multiple disabilities) and the outcome. We entered each disability type in a separate model because entering them together in the same model produced random results, probably because the complex correlations among disability types and the low frequencies in certain disability types. Cell sizes were too small to conduct interactions between specific disability types. All analyses corrected for design effects of the sampling process (oversampling of certain demographic groups and sample stratification), using the "survey design" routine in Stata 13.1, which generated weighted estimates of model coefficients and linearized standard errors (Chantala and Tabor 2000).

RESULTS

Table 1 shows weighted means, proportions, and standard deviations for the sample by disability status. Approximately 16% of the sample had at least one type of disability, and about 2% of the sample had multiple disabilities with most common combinations of learning and intellectual disability (n=133) and physical and learning disability (n=100). Among individual types, learning disabilities were most common (11%), followed by physical disabilities (6%), and intellectual disabilities (1%). Men had higher rates of disability, compared to women (p < .001). Compared to PWoD, people with any disability were less likely to be Asian (p <.05), had lower rates of high school completion (p < .001), and their parents had lower education levels (p < .05).

On average, PWD attained 2.64 of five adulthood markers while PWoD attained 3.09 (p < .001). More specifically, approximately 13% of PWD obtained a college degree (34% PWoD; p < .001), 88% obtained employment (95% PWoD; p < .01), 78% established independent living (85% PWoD; p < .05), 44% entered marriage (50% PWoD; ns), and 41% became a parent (45% PWoD; ns). These results are generally consistent with past studies. One exception is the lack of difference in parenthood, which may be due to the sample age (mostly between 26 and 31 years).

Table 1. Descriptive Statistics by Disability Status
Variables Min-
Max
People with
Disabilities
(n=1,922)
People without
Disabilities
(n=10,281)
Diffference
Mean or Proportion Mean or Proportion
Dependent Variables
# of Attained Markers0,52.64 (1.17)3.09 (1.08)t=-3.35, p<.001
College Degree0,10.130.34F (1, 128)=114.06, p<.001
Full-Time Employment0,10.880.95F (1, 128)=6.86, p<.01
Independent Residency0,10.780.85F (1, 128)=4.48, p<.05
Marriage0,10.440.50F (1, 128)=3.53, ns
Parenthood0,10.410.45F (1, 128)=2.41, ns
Independent Variables
Any Disability0,10.160.84-
Physical Disability0,10.060.94-
Learning Disability0,10.110.89-
Intellectual Disability0,10.010.99-
Multiple Disabilities0,10.020.98-
Age24,34a28.36 (1.76)28.21 (1.81)t=1.72, ns
Sex (male)0,10.620.49F (1, 128)=40.50, p<.001
High School Graduate0,10.860.94F (1, 128)=55.25, p<.001
RaceF (4.2, 541.4)=2.41, p<.05
White0,10.710.67
Hispanic0,10.090.12
Black0,10.150.15
Asian0,10.010.03
Native American0,10.030.02
Other0,10.010.01
Parent's EducationF (1.7, 221.6)=3.61, p<.05
Less than HS0,10.190.16
High School Degree0,10.620.61
College Degree0,10.180.23
Note: n=12,203. Standard deviations in parenthesis. F = design-based F tests (an alternative to chi-square tests for analysis of complex survey data; StataCorp 2005).
a most respondents were aged between 26 through 31 years.

Table 2 presents results from the Poisson regression analysis. Consistent with Hypothesis 1, disability had a moderate, negative association with the number of attained markers. As shown in Model 1, having any disability decreased the expected number of markers by a factor of .87, compared to no disability, after controlling sociodemographic background (Incidence Rate Ratio [IRR] = 0.87, p < .01). Disability had a predicted count of 2.66 markers whereas no disability had a predicted count of 3.06 markers when all other variables were held at their means. Consistent with Hypothesis 3, this relationship depended on disability type: physical disability did not show a significant association (Model 2), but learning (IRR = 0.81, p < .01; Model 3), intellectual (IRR = 0.32, p < .01; Model 4), and multiple (IRR = 0.47, p < .01; Model 5) disabilities were negatively associated with the number of markers net of all other variables. More specifically, the predicted count of markers was 2.47 for learning disability, .97 for intellectual disability, and 1.42 for multiple disability, compared to approximately 3.04 for no disability, holding all other variables at their means. This analysis provided an overall association between disability and adulthood marker attainment, but the association could depend on specific markers. We explored the possibility using logistic regression models that predicted each adulthood marker.

Table 2. Incidence Rate Ratios from the Poisson Regression of the Number of Attained Markers (Attainment of 5 Adulthood Markers) on Selected Independent Variables
VariablesModel 1Model 2Model 3Model 4Model 5
Any Disability0.87**
(0.78, 0.96)
Physical Disability0.99
(0.95, 1.02)
Learning Disability0.81**
(0.70, 0.94)
Intellectual Disability0.32**
(0.15, 0.70)
Multiple Disabilities0.47**
(0.27, 0.82)
Age1.04***
(1.03, 1.05)
1.04***
(1.03, 1.05)
1.04***
(1.03, 1.05)
1.04***
(1.03, 1.05)
1.04***
(1.03, 1.05)
Sex (ref = male)0.88***
(0.86, 0.90)
0.87***
(0.85, 0.89)
0.88***
(0.86, 0.90)
0.87***
(0.85, 0.89)
0.87***
(0.85, 0.89)
High School Graduate1.06*
(1.01, 1.12)
1.08**
(1.03, 1.13)
1.05
(1.00, 1.11)
1.09***
(1.04, 1.14)
1.08**
(1.03, 1.13)
Race (ref = white)
Hispanic0.93**
(0.88, 0.97)
0.93**
(0.89, 0.98)
0.93**
(0.88, 0.97)
0.93**
(0.88, 0.97)
0.93**
(0.89, 0.98)
Black0.86***
(0.84, 0.89)
0.86***
(0.84, 0.89)
0.86***
(0.84, 0.89)
0.87***
(0.85, 0.90)
0.87***
(0.85, 0.90)
Asian0.90***
(0.86, 0.95)
0.91***
(0.87, 0.96)
0.90***
(0.86, 0.94)
0.90***
(0.86, 0.95)
0.90***
(0.86, 0.95)
Native American0.98
(0.92, 1.06)
0.98
(0.91, 1.06)
0.97
(0.90, 1.04)
0.97
(0.91, 1.04)
0.98
(0.91, 1.05)
Other0.92
(0.83, 1.02)
0.93
(0.84, 1.02)
0.91
(0.83, 1.01)
0.93
(0.84, 1.03)
0.93
(0.84, 1.02)
Parental Education (ref = less than high school)
High School Degree1.03
(0.99, 1.08)
1.04
(0.99, 1.08)
1.03
(1.00, 1.07)
1.02
(0.99, 1.05)
1.02
(0.99, 1.06)
College Degree1.09***
(1.04, 1.13)
1.09***
(1.05, 1.14)
1.08***
(1.04, 1.12)
1.07***
(1.03, 1.10)
1.07***
(1.04, 1.11)
Constant1.04
(0.85, 1.28)
1.03
(0.83, 1.26)
1.05
(0.86, 1.28)
0.99
(0.81, 1.19)
0.99
(0.82, 1.20)
Note: n=12,203. 95% confidence intervals in parenthesis. *p<.05; **p<.01; ***p<.001.

Table 3 presents results for obtaining a college degree. Any disability (Model 1), learning disability (Model 3), intellectual disability (Model 4), and multiple disabilities (Model 5) were negatively associated with obtaining a college degree, which was consistent with Poisson regression of attained marker count. Unlike the analysis of total marker counts, this analysis of college degree attainment showed that physical disability was negatively associated with obtaining a college degree. More specifically, physical disability was associated with 47% decreased odds of obtaining a college degree (odds ratio [OR] = 0.53, p < .001; Model 2). Overall, the magnitude of the educational disparities was greatest for multiple disabilities (OR = 0.12, p < .001; Model 5).

Table 3. Odds Ratios from the Logistic Regression Analysis of College Degree on Selected Independent Variables
VariablesModel 1Model 2Model 3Model 4Model 5
Any Disability0.31***
(0.24, 0.40)
Physical Disability0.53***
(0.40, 0.71)
Learning Disability0.21***
(0.15, 0.29)
Intellectual Disability0.16**
(0.04, 0.58)
Multiple Disabilities0.12***
Age1.01
(0.96, 1.06)
1.01
(0.96, 1.06)
1.01
(0.96, 1.06)
1.01
(0.96, 1.06)
1.01
(0.96, 1.06)
Sex (ref = male)0.69***
(0.61, 0.79)
0.66***
(0.58, 0.75)
0.71***
(0.62, 0.82)
0.66***
(0.58, 0.75)
0.66***
(0.58, 0.76)
High School Graduate66.92***
(20.02, 223.68)
72.75***
(21.89, 241.73)
66.02***
(19.71, 221.16)
73.72***
(22.21, 244.65)
73.22***
(22.03, 243.35)
Race (ref = white)
Hispanic0.75**
(0.61, 0.92)
0.78*
(0.63, 0.96)
0.76*
(0.62, 0.94)
0.79*
(0.64, 0.97)
0.79*
(0.64, 0.97)
Black0.62**
(0.47, 0.83)
0.64**
(0.48, 0.85)
0.63**
(0.47, 0.83)
0.65**
(0.48, 0.86)
0.65**
(0.48, 0.86)
Asian1.22
(0.76, 1.96)
1.31
(0.83, 2.08)
1.20
(0.77, 1.88)
1.30
(0.83, 2.03)
1.28
(0.82, 2.01)
Native American0.66
(0.35, 1.24)
0.66
(0.35, 1.23)
0.59
(0.31, 1.13)
0.61
(0.33, 1.15)
0.62
(0.33, 1.15)
Other0.80
(0.44, 1.45)
0.82
(0.45, 1.50)
0.78
(0.43, 1.41)
0.84
(0.46, 1.55)
0.84
(0.45, 1.55)
Parental Education (ref = less than high school)
High School Degree2.62***
(2.06, 3.32)
2.64***
(2.07, 3.36)
2.60***
(2.05, 3.31)
2.58***
(2.04, 3.27)
2.58***
(2.04, 3.27)
College Degree10.63***
(7.78, 14.53)
10.63***
(7.80, 14.49)
10.42***
(7.62, 14.24)
10.24***
(7.54, 13.89)
10.28***
(7.58, 13.95)
Note: n=12,203. 95% confidence intervals in parenthesis. *p<.05; **p<.01; ***p<.001.

Table 4 presents results for employment, and Table 5 presents results for independent living using logistic regression analyses. Any disability (Model 1), learning disability (Model 3), intellectual disability (Model 4), and multiple disabilities (Model 5) were negatively associated with attainment of these adulthood markers, which was consistent with Poisson regression results. Physical disability was not associated with independent living nor employment (Model 2). The magnitude of the disparity in employment (OR = 0.03, p < .001) and independent living (OR = 0.09, p < .001) was greatest for intellectual disability (Model 4).

Table 4. Odds Ratios from the Logistic Regression Analysis of Employment on Selected Independent Variables
VariablesModel 1Model 2Model 3Model 4Model 5
Any Disability0.31**
(0.13, 0.75)
Physical Disability0.76
(0.49, 1.20)
Learning Disability0.21**
(0.08, 0.55)
Intellectual Disability0.03***
(0.01, 0.12)
Multiple Disabilities0.04***
(0.01, 0.14)
Age1.06
(1.00, 1.13)
1.05
(0.98, 1.12)
1.06*
(1.00, 1.13)
1.09**
(1.03, 1.16)
1.09**
(1.03, 1.16)
Sex (ref = male)1.60***
(1.30, 1.98)
1.43***
(1.19, 1.72)
1.75***
(1.36, 2.24)
1.47***
(1.20, 1.81)
1.54***
(1.25, 1.89)
High School Graduate1.17
(0.68, 2.00)
1.37
(0.88, 2.13)
1.09
(0.62, 1.90)
1.62**
(1.13, 2.33)
1.41
(0.95, 2.11)
Race (ref = white)
Hispanic0.73
(0.42, 1.30)
0.80
(0.47, 1.37)
0.73
(0.42, 1.27)
0.82
(0.47, 1.42)
0.81
(0.46, 1.43)
Black0.66**
(0.51, 0.84)
0.68**
(0.53, 0.89)
0.66**
(0.51, 0.85)
0.74
(0.55, 1.01)
0.77
(0.57, 1.04)
Asian0.35***
(0.21, 0.59)
0.41***
(0.24, 0.69)
0.33***
(0.20, 0.56)
0.35***
(0.21, 0.57)
0.34***
(0.20, 0.57)
Native American2.17
(0.95, 4.96)
2.16
(0.96, 4.86)
1.92
(0.86, 4.25)
1.81
(0.83, 3.95)
2.34
(0.87, 6.24)
Other0.20**
(0.07, 0.54)
0.23**
(0.09, 0.59)
0.18**
(0.07, 0.50)
0.21**
(0.08, 0.58)
0.21**
(0.08, 0.56)
Parental Education (ref = less than high school)
High School Degree1.30
(0.86, 1.95)
1.32
(0.86, 2.02)
1.27
(0.86, 1.89)
1.08
(0.70, 1.66)
1.13
(0.75, 1.71)
College Degree1.34
(0.89, 2.01)
1.42
(0.92, 2.19)
1.27
(0.86, 1.87)
1.06
(0.69, 1.62)
1.14
(0.76, 1.71)
Note: n=12,203. 95% confidence intervals in parenthesis. *p<.05; **p<.01; ***p<.001.
Table 5. Odds Ratios from the Logistic Regression Analysis of Independent Living on Selected Independent Variables
VariablesModel 1Model 2Model 3Model 4Model 5
Any Disability0.65
(0.42, 1.01)
Physical Disability1.21
(0.87, 1.69)
Learning Disability0.53*
(0.31, 0.90)
Intellectual Disability0.09***
(0.04, 0.25)
Multiple Disabilities0.18***
(0.07, 0.47)
Age1.13***
(1.08, 1.18)
1.12***
(1.07, 1.18)
1.13***
(1.08, 1.18)
1.14***
(1.09, 1.19)
1.14***
(1.09, 1.19)
Sex (ref = male)0.76**
(0.64, 0.90)
0.73***
(0.62, 0.86)
0.77**
(0.65, 0.92)
0.72***
(0.62, 0.85)
0.74***
(0.63, 0.86)
High School Graduate1.20
(0.90, 1.60)
1.28
(0.98, 1.67)
1.17
(0.87, 1.56)
1.34*
(1.04, 1.73)
1.27
(0.98, 1.65)
Race (ref = white)
Hispanic0.53***
(0.40, 0.70)
0.55***
(0.42, 0.71)
0.52***
(0.40, 0.69)
0.54***
(0.41, 0.71)
0.54***
(0.41, 0.71)
Black0.49***
(0.40, 0.59)
0.49***
(0.40, 0.60)
0.48***
(0.39, 0.59)
0.50***
(0.40, 0.62)
0.51***
(0.41, 0.63)
Asian0.43***
(0.29, 0.64)
0.45***
(0.31, 0.66)
0.42***
(0.29, 0.62)
0.43***
(0.29, 0.62)
0.43***
(0.29, 0.62)
Native American0.94
(0.57, 1.56)
0.93
(0.56, 1.53)
0.90
(0.54, 1.49)
0.89
(0.55, 1.46)
0.95
(0.56, 1.62)
Other0.83
(0.39, 1.79)
0.87
(0.40, 1.88)
0.81
(0.38, 1.74)
0.87
(0.39, 1.94)
0.86
(0.39, 1.87)
Parental Education (ref = less than high school)
High School Degree1.24*
(1.02, 1.51)
1.25*
(1.02, 1.53)
1.23*
(1.01, 1.50)
1.16
(0.96, 1.40)
1.19
(0.98, 1.43)
College Degree1.73***
(1.36, 2.20)
1.77***
(1.38, 2.27)
1.70***
(1.34, 2.15)
1.60***
(1.28, 2.00)
1.65***
(1.32, 2.06)
Note: n=12,203. 95% confidence intervals in parenthesis. *p<.05; **p<.01; ***p<.001.

Table 6 presents results for marriage, and Table 7 presents results for parenthood. Learning disability (Model 3), intellectual disability (Model 4), and multiple disabilities (Model 5) were negatively associated with marriage and parenthood, but physical disability (Model 1) was not associated with marriage nor parenthood. These findings were similar with the Poisson regression of attained marker count. Unlike the analysis of marker counts, this analysis of marriage and parenthood showed no association between any disability (Model 1) and these outcomes. The disparity for marriage (OR = 0.09, p < .001) and parenthood (OR = 0.11, p < .001) was greatest for intellectual disability as shown in Model 4.

Table 6. Odds Ratios from the Logistic Regression Analysis of Marriage Selected Independent Variables
VariablesModel 1Model 2Model 3Model 4Model 5
Any Disability0.78
(0.58, 1.03)
Physical Disability1.00
(0.79, 1.27)
Learning Disability0.67*
(0.47, 0.97)
Intellectual Disability0.09***
(0.03, 0.27)
Multiple Disabilities0.19***
(0.07, 0.49)
Age1.27***
(1.21, 1.32)
1.26***
(1.21, 1.32)
1.27***
(1.21, 1.32)
1.27***
(1.22, 1.33)
1.27***
(1.22, 1.33)
Sex (ref = male)0.65***
(0.58, 0.73)
0.64***
(0.57, 0.72)
0.66***
(0.58, 0.74)
0.63***
(0.57, 0.71)
0.64***
(0.57, 0.72)
High School Graduate1.12
(0.84, 1.49)
1.16
(0.87, 1.53)
1.10
(0.83, 1.47)
1.19
(0.90, 1.57)
1.16
(0.87, 1.54)
Race (ref = white)
Hispanic0.74**
(0.61, 0.91)
0.75**
(0.62, 0.92)
0.74**
(0.61, 0.90)
0.76**
(0.62, 0.92)
0.75**
(0.62, 0.92)
Black0.31***
(0.26, 0.38)
0.32***
(0.26, 0.38)
0.31***
(0.26, 0.38)
0.32***
(0.27, 0.39)
0.32***
(0.27, 0.39)
Asian0.67*
(0.49, 0.91)
0.68*
(0.50, 0.93)
0.66**
(0.49, 0.90)
0.66**
(0.49, 0.90)
0.66**
(0.49, 0.90)
Native American0.87
(0.57, 1.31)
0.86
(0.57, 1.31)
0.85
(0.56, 1.28)
0.84(
0.56, 1.27)
0.86
(0.57, 1.31)
Other0.65
(0.37, 1.15)
0.67
(0.38, 1.17)
0.65
(0.37, 1.14)
0.67
(0.38, 1.18)
0.66
(0.37, 1.17)
Parental Education (ref = less than high school)
High School Degree0.97
(0.79, 1.18)
0.97
(0.79, 1.19)
0.96
(0.79, 1.17)
0.92
(0.77, 1.10)
0.93
(0.78, 1.12)
College Degree0.77*
(0.61, 0.96)
0.78*
(0.62, 0.98)
0.76*
(0.61, 0.95)
0.73**
(0.59, 0.90)
0.74**
(0.60, 0.91)
Note: n=12,203. 95% confidence intervals in parenthesis. *p<.05; **p<.01; ***p<.001.
Table 7. Odds Ratios from the Logistic Regression Analysis of Parenthood Selected Independent Variables
VariablesModel 1Model 2Model 3Model 4Model 5
Any Disability0.85
(0.64, 1.12)
Physical Disability1.25
(0.99, 1.58)
Learning Disability0.69*
(0.48, 1.00)
Intellectual Disability0.11***
(0.04, 0.27)
Multiple Disabilities0.25**
(0.10, 0.61)
Age1.20***
(1.15, 1.25)
1.19***
(1.15, 1.25)
1.20***
(1.15, 1.25)
1.21***
(1.16, 1.25)
1.20***
(1.16, 1.25)
Sex (ref = male)0.39***
(0.34, 0.44)
0.38***
(0.34, 0.43)
0.39***
(0.34, 0.45)
0.38***
(0.33, 0.43)
0.38***
(0.34, 0.43)
High School Graduate0.63***
(0.50, 0.81)
0.65***
(0.51, 0.83)
0.62***
(0.48, 0.79)
0.66***
(0.52, 0.84)
0.65***
(0.51, 0.82)
Race (ref = white)
Hispanic0.99
(0.80, 1.23)
1.01
(0.81, 1.25)
0.99
(0.80, 1.22)
1.01
(0.82, 1.24)
1.00
(0.81, 1.24)
Black1.17
(0.97, 1.40)
1.17
(0.97, 1.41)
1.17
(0.97, 1.40)
1.21*
(1.00, 1.46)
1.21*
(1.00, 1.45)
Asian0.75
(0.49, 1.16)
0.76
(0.49, 1.18)
0.74
(0.48, 1.14)
0.74
(0.48, 1.15)
0.74
(0.48, 1.15)
Native American1.16
(0.84, 1.61)
1.14
(0.82, 1.57)
1.14
(0.83, 1.57)
1.14
(0.82, 1.57)
1.16
(0.84, 1.61)
Other1.35
(0.76, 2.39)
1.36
(0.76, 2.42)
1.32
(0.74, 2.35)
1.37
(0.76, 2.46)
1.36
(0.76, 2.43)
Parental Education (ref = less than high school)
High School Degree0.77**
(0.64, 0.92)
0.78**
(0.64, 0.94)
0.77**
(0.64, 0.91)
0.73***
(0.62, 0.87)
0.74***
(0.63, 0.88)
College Degree0.38***
(0.30, 0.48)
0.38***
(0.30, 0.48)
0.38***
(0.30, 0.47)
0.36***
(0.29, 0.44)
0.36***
(0.29, 0.45)
Note: n=12,203. 95% confidence intervals in parenthesis. *p<.05; **p<.01; ***p<.001.

In sum, the logistic regression analysis of individual adulthood markers generated results similar to those of Poisson regression that predicted attained marker counts with two exceptions. First, any disability was not associated with entering marriage or parenthood. This result was contrary to Hypothesis 2, which stated any disability would be associated with all markers. Second, physical disability was negatively associated with attainment of college degree although it was not associated with attained marker count. Similar to Poisson regression results, learning, intellectual, and multiple disabilities were negatively associated with attainment of all markers. Still, the magnitude of these disparities varied across disability types: intellectual disability showed the greatest disparities followed by multiple disabilities and learning disability. These results support Hypothesis 3, which stated the association between disability and transition to adulthood would vary by disability type.

DISCUSSION

This study offers key insights about the relationship between disability status and adolescents' transition to adulthood. Previous studies have revealed various disadvantages that PWDs endure, but their scope is often limited by small or unrepresentative samples. Moreover, many studies of PWD lack comparisons to PWoD, thus hindering scholars from drawing conclusions about disparities. This article extends the literature by using a nationally representative, longitudinal dataset of people with and without disabilities. Further, the current study provides a holistic view of the transition to adulthood by examining four disability types and attainment of five adulthood markers.

Results show that PWD, as a group broadly defined as having any disability, had a predicted count of 2.66 attained markers whereas no disability had a predicted count of 3.06 attained markers, and the magnitude of attained marker counts varied by disability type. The pattern of disparities by disability type was largely consistent across individual markers. People with physical disabilities attained markers at similar rates to PWoD, with the exception of their lower rates in obtaining college degrees. Learning and intellectual disabilities were negatively associated with all markers. Beyond these individual disability types, having multiple disabilities was also negatively associated with all markers. The magnitude of disparity was greatest between people with and without intellectual disabilities. One may find this result unintuitive because the disparity was greater than that associated with multiple disabilities, but multiple disabilities include various combinations of disabilities. Some combinations may be linked with severer barriers, and others may not be. Overall, these results support the social model of disability by demonstrating that PWD experience more barriers in the transition to adulthood.

Previous similar studies examined marker attainment among respondents in their early to mid-20s (Erickson and Macmillan 2018; Janus 2009; Wells et al. 2003), and consequently, some respondents may have been in the process of attaining markers. Thus, the results could have indicated a delayed transition, rather than a permanent failure to make the transition. The current study examined marker attainment among respondents in their mid to late 20s and found similar results, which provides evidence against a delayed transition. Unlike previous studies that found few or no disparities between persons with and without physical disabilities (Erickson and Macmillan 2018; Janus 2009; Wells et al. 2003), the current study found disparities between people with and without physical disabilities in attainment of college degrees. Previous studies used latent class analysis, so they were unable to identify nuances among each marker. Extending from previous literature that did not examine independent living (Erickson and Macmillan 2018), we found disparities between people with and without disabilities in independent living with the exception of physical disability.

Intersectional life course perspective indicates that people with multiple marginalized identities experience more barriers (Collins 1990; Ferrer et al. 2017). In a supplemental analysis, we tested whether the relationship between disability types and the transition to adulthood varied by gender, race, and parental socioeconomic status (detailed results available upon request). Regarding socioeconomic status, we found that having parents with a college degree had a positive effect on marker attainment, but the results showed no other clear patterns of interactions. These results indicate that the association between disability and the transition to adulthood does not vary by the demographic variables. Alternatively, the results may reflect insufficient statistical power. Future research should oversample PWD with certain backgrounds (e.g., racial minority status) to further understand interactions.

In an additional supplemental analysis, we tested a variety of potential mediators including mental health, self-esteem, feelings of social acceptance, social relationships, and academic performance in high school. None of these mediators could fully explain the disparity in the transition to adulthood between people with and without disabilities. (Detailed results are available upon request.) Although surprising given the theoretical importance of each factor in the transition scholarship, these mediators are not exhaustive. For example, previous research has shown that self-determination improves transition to adulthood outcomes, including employment (Shogren et al. 2015; Wehmeyer and Palmer 2003) and independent living (Wehmeyer and Palmer 2003). The social model of disability emphasizes environmental factors (Oliver 1983), which the data also lacked. For example, discrimination (Beckett 2014; Foster and Wass 2013) and local policies on disability in schools and workplaces impact transition experiences and the extent of barriers that PWD face (Fulcher 2015). Future research should further investigate potential mediators.

The current result regarding PWDs transition to fewer adult roles suggests that PWD may face tradeoffs among adult roles. That is, making a successful transition to one role undermines their chance of transition to another role. Such a phenomenon has been observed for other marginalized populations, such as women (Han, Tumin, and Qian 2016), and may apply to PWD. In addition to tradeoffs among roles, whether people stay in each role (e.g. worker) is another important question. Future research could expand on adult role tradeoffs and length in adult roles to further understand the differences in the transition to adulthood between people with and without disabilities.

As emphasized in the life course literature, this study focused on traditional markers of adulthood based on role changes, but traditional markers rely on narrow definitions of success. Adopting broader definitions of success and rethinking what institutions define success could provide a better understanding about disparities between people with and without disabilities. For example, subjective markers may provide broader definitions of success because they provide more flexibility and allow individuals to define and assess their own success (Dalessandro 2019). Subjective markers have already been adopted by recent cohorts of young people with and without disabilities (Arnett 1997; Shanahan et al. 2005). For example, PWD reported social independence (Epp 2003) and accepting responsibility for one's actions (Leiter 2012) as important markers of achieved adulthood. Fewer PWD reported traditional markers as necessary to be considered adults (Rojas et al. 2014; Shandra 2011). However, the importance of subjective measures should not be overemphasized as it may mask objective challenges faced by PWD.

Drawing on the social model of disability, the present findings can be interpreted as an indication that major institutions, including education, employment, residential community, and family, systematically exclude PWD. For example, institutions of higher education create systematic exclusion by inherently valuing ability and stigmatizing intellectual weakness (Dolmage 2017). Policies and programs try to overcome PWD's systematic exclusion by providing specialized services. For example, the Individuals with Disabilities Education Act (IDEA) transition services (IDEA 2004) are designed to improve PWD's post-school activities (i.e. education, employment, adult services, independent living, and community participation). The services are "based on the individual child's needs, taking into account the child's strengths, preferences, and interests (IDEA 2004)." Given the persistence of disparities between people with and without disabilities as found in the present study, policy makers and program administrators should rethink the operation of transition services.

First, transition services should consider all key aspects of transition to adulthood including traditional and subjective markers. Currently, transition services focus on postsecondary education, employment, and to a lesser extent, independent living. They should also consider marriage, parenthood, and subjective markers, such as social independence. Second, transition services require coordination across social institutions, given that participation in one institution is closely linked to participation in another institution (Shanahan 2000). Transition services help PWD obtain accommodations, but accommodations usually apply to one space at a given time and place burdens on PWD (Dolmage 2017). For example, a worker must disclose and provide evidence of a disability to obtain a workplace accommodation. The accommodation will likely not be useful for other social institutions, such as residential community and family.

Third, transition services should shift their focus from relying on PWD's individual ability and efforts to redesigning social institutions. This recommendation aligns with the social model of disability, which emphasizes the role of environment for disparities between people with and without disabilities. Transition programs should focus on assessing and increasing institutional accessibility rather than finding institutions that "match" or accommodate the individual's ability. Transition services rely on PWD, family members, and caretakers to seek appropriate services to overcome specific barriers that social institutions create. Instead, greater efforts are necessary to make structural changes and prevent institutions from creating barriers to PWD's transition. Social institutions should be redesigned so that all bodies and minds can access them (Goldsmith 2012; Ronald Mace 1985).

LIMITATIONS

The present results need to be interpreted while keeping in mind the following features of the Add Health data. First, one limitation was sample representativeness of PWD. Add Health is a school-based survey and therefore excluded any people who did not attend schools or attended certain types of schools. Even when attending schools, students did not participate in the Add Health survey if their teachers or parents thought they were not capable of completing the questionnaire. Thus, people with the most severe disabilities may have been omitted from the sample. This would likely be the group to experience the most barriers in the transition to adulthood, and for this reason, the analysis may have underestimated the extent of disparities.

Further, persons with certain types of disabilities may be more likely to be excluded from the sample, and therefore, their disadvantages may have been underestimated in the analysis. For example, homeschooling has been increasing, and 6% of parents homeschooled because their child had a disability or other special needs (Bielick 2008). It is possible that children with intellectual and multiple disabilities are more likely to be homeschooled, compared to other types of disabilities. Adolescents that are homeschooled would not be included in the current sample, which may explain why the sample included only a small number of people with intellectual and multiple disabilities.

Second, due to a lack of adequate measures, severity and duration of disability were not considered even though past research suggests they hinder marker attainment (Jones 2011; Moin, Duvdevany, and Mazor 2009). Because Add Health did not include any measures of disability at Wave 4, we were unable to determine if respondents continued to experience the disability in young adulthood. In the US, however, learning and intellectual disabilities are usually lifelong labels, and results are likely not affected. Although the measure of physical disability captures aspects of mobility impairments, it does not capture other types of physical disability, such as chronic pain. The present findings cannot be generalized to other types of physical disabilities. These limitations of Add Health data need to be addressed in future research that uses a superior dataset.

CONCLUSION

Despite national (ADA 1990) and international (WHO 2013) attempts to improve opportunities for PWD, the current study reveals stark disparities in the transition to adulthood between people with and without disabilities in the U.S. These disparities are particularly pronounced for learning, intellectual, and multiple disabilities although disparities also exist in educational outcomes for physical disability. Current policies and programs are limited and largely focus on individual efforts of PWD. Reducing disparities between people with and without disabilities will require structural change and a redesign of major institutions, including education, employment, residential community, and family.

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Endnotes

  1. Add Health was designed by J. Richard Udry, Peter S. Bearman, and Kathleen Mullan Harris at the University of North Carolina at Chapel Hill. The project was funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development from 1994-2021, with cooperative funding from 23 other federal agencies and foundations. Add Health is currently directed by Robert A. Hummer; it was previously directed by Kathleen Mullan Harris (2004-2021) and J. Richard Udry (1994-2004). Information on obtaining Add Health data is available on the project website (https://addhealth.cpc.unc.edu). The Add Health Parent Study/Parents (2015-2017) data collection was funded by a grant from the National Institute on Aging (RO1AG042794) to Duke University, V. Joseph Hotz (PI) and the Carolina Population Center at the University of North Carolina at Chapel Hill, Kathleen Mullan Harris (PI).
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  2. Authors received approval from their institutional review board to conduct the present analysis.
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