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R-3: Relation of Sociodemographics and Local Characteristics 
to Community Participation and Community Living


Background

Individual, household and local environmental characteristics are likely to influence community participation and community living for people with disabilities. The complex interactions of individual (disability, age, race, gender, and education), residential (housing structure, composition) and local environmental factors (location of residence, available services) influence the level to which people with disabilities are able to participate in their communities.


Although the literature has documented the existence of these barriers, the studies have typically included only small samples and people in non-institutional settings, or focused on a small subset of the disability population. In addition, they have typically only examined a minimal number of the factors without assessing the complex interactions between socio-demographic, residential and local environmental levels. 

The project will add to the existing literature by (1) pioneering the use of the American Community Survey (ACS) as a tool for understanding people with disabilities, and (2) using a nationally representative database to examine and document the complex interaction between personal, socio-demographic, and local characteristics on community participation and community living. The ACS is an ongoing statistical survey conducted by the U.S. Census Bureau that samples a small percentage of the population every year.

Purpose of the Study 
Focusing on working age adults with and without disabilities, this project investigates the association of community participation and community living with:

  • Socio-demographic factors, including but not limited to race, ethnicity, income, education, and household composition,
  • Traits of the housing physical structure, including but not limited to age of the structure, number of stories, structure type (e.g., single family home, mobile home, apartment building),
  • Local characteristics, including but not limited to urban/rural location and availability of public transportation, state and local policies and programs (e.g., proximity to an independent living center, access to community services), topography, climate, and
  • The nature of an individual’s disability (i.e., disability type and severity).
     

The ACS does not provide direct measures of community participation (with the exception of employment). However, it does ask, “Because of a physical, mental, or emotional condition, does this person have difficulty doing errands alone such as visiting a doctor’s office or shopping?” The Census Bureau calls this an “independent living difficulty.”  Note that this question does not askwhether an individual participates in a task or activity, but rather asks about the perceived difficulty in going outside the home alone.  Not all people with disabilities (as measured by the ACS-disability questions related to vision, hearing, mobility, and cognition) report an independent living difficulty.  In using this variable, this study will examine factors associated with perceiving errands outside the home as difficult, rather than the extent to which people actually perform the errands.  

With regard to community living, the Census Bureau provides information about whether an individual lives in an institution (which includes correctional facilities and others).  For this project, we are interested in institutional living based on disability.  We will compare community living with institutional living, define institutional living as whether an individual resides in one of the following: a nursing facility/skilled-nursing facility, a mental (psychiatric) hospital or psychiatric unit in other hospital, or a residential school for people with disabilities. 

We will estimate the effect of individual and location characteristics on independent living difficulty, using multi-level mixed effects models; a.k.a., hierarchical linear modeling (HLM).  The same approach will be used for community living. These models ensure that the coefficients and standard errors of individual-level variables are estimated correctly.  Initially, community participation and community living will be modeled separately. We will estimate ordered logic models with the dependent variable being equal to zero for those with no independent living difficulty and not living in a disability-related institution, one for those with an independent living difficulty and not living in a disability-related institution, and two for those living in a disability-related institution.

Anticipated Benefits
We anticipate results from this study can affect change in policy and practice by informing policymakers about the impact of environmental characteristics on their programs and services.  This information can then support their efforts to assess and address changes to support more widespread participation by persons with disabilities in their communities. 

Identifying and classifying environmental characteristics, including traits of housing physical structures, urban/rural location, and proximity to local programs with person-level characteristics should provide important new information regarding the association between these factors and perceived difficulty in going outside the home without assistance, a key factor in achieving community participation.  

This innovative method of analysis as applied to the ACS enhances the ACS’s overall value to the disability research community and programs and practices impacting the lives of people with disabilities.

Methods and Hypotheses
This project will use restricted-access data from the American Community Survey to test the hypothesis that individual and environmental characteristics in the local physical and social environments influence participation. 

While research has demonstrated that personal, residential and environmental factors affect the participation of people with disabilities, to date the literature on the local effects on participation is underdeveloped. This is likely due to the lack of quality disability data linked to geocodes with sufficient sample sizes. These limitations are remediated by the restricted-access ACS.

The extremely large sample size and sampling design of the ACS allows for precise local-level estimates. The restricted-access data, available via Restricted Data Centers (RDCs), provides zip code level identifiers (upon which local characteristics from other data sources will be merged) and the type of institution for those not living in the community, neither of which are available in the public-use microdata (PUMS) files. 

Social models of disability provided the theoretical underpinnings of this project—the Nagi disability model, the IOM disablement model, and the ICF.  In general, these models hold that an individual’s participation in a social role is influenced by the complex interaction of his/her underlying health condition, personal characteristics, mitigating factors, and the physical/social environment.  This leads us to investigate whether community participation/community living are influenced by this complex interaction.

Specifically, we will examine the following hypotheses: 

1.    The community participation/living of individuals with disabilities is related to the individual’sunderlying health conditions, holding personal/household and environmental characteristics constant.

2.    The community participation/living of individuals with disabilities is related to the individual’s personal/household, holding underlying health conditions and characteristics of the environment constant.

3.    The community participation/living of individuals with disabilities is related to the characteristics of the local environment, holding the individual’s underlying health conditions and personal/household characteristics constant.

More information about the design of the research: 
Sample, Data Collection and Measurement, Data Analysis


Principal Investigator: Andrew Houtenville, PhD



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