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National Estimates and Complex Sampl...

Sang, Hilla I.

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National Estimates and Complex Sample Regression Modeling of the Financial Burden of Health Care Among the U.S. Nonelderly Population.

Record Type:	Electronic resources : Monograph/item
Title/Author:	National Estimates and Complex Sample Regression Modeling of the Financial Burden of Health Care Among the U.S. Nonelderly Population./
Author:	Sang, Hilla I.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2019,
Description:	149 p.
Notes:	Source: Dissertations Abstracts International, Volume: 81-02, Section: B.
Contained By:	Dissertations Abstracts International81-02B.
Subject:	Public health. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=27534876
ISBN:	9781085658904

National Estimates and Complex Sample Regression Modeling of the Financial Burden of Health Care Among the U.S. Nonelderly Population.
Sang, Hilla I.

National Estimates and Complex Sample Regression Modeling of the Financial Burden of Health Care Among the U.S. Nonelderly Population. - Ann Arbor : ProQuest Dissertations & Theses, 2019 - 149 p.

Source: Dissertations Abstracts International, Volume: 81-02, Section: B.

Thesis (Ph.D.)--Kent State University, 2019.

This item must not be sold to any third party vendors.

This study is a modified replication of Banthin and Bernard's (2006) study that provided national estimates of health care financial burden (FB) and highlighted disparities among different segments of the U.S. nonelderly population. Using Banthin and Bernard's (2006) study as a point of comparison, the current study used data from 2015 to calculate national estimates of FB for different population segments and utilizes complex samples logistic regression (CSLR) to identify parsimonious models predicting two types of FB. This study utilized PSID data, data that provides a reliable approximation of health measures and consumption expenditures and has an excellent response rate of 97%. The sample (n=11,434) includes individuals aged 18 to 64, participants with disposable income of $100 or more and participants identified as Head or Spouse/Partner within the United States.Finding suggest that persons with private non-group insurance and employer-sponsored insurance incurred the highest increases in FB. CSLR results indicated that the parsimonious models for both types of financial burden were similar. Sex, urbanicity, and the presence of limitation in Activities of Daily Living (ADL) were not statistically significant predictors of FB, whereas age, race, income level, health insurance type, chronic conditions and Instrumental Activities of Daily Living (IADL) limitations predict FB among U.S. nonelderly adults. Future research needs to be conducted to identify mechanisms of the association between the predictor variables and FB and to reduce the prevalence of FB in the U.S. population. The findings from this study may inform future policy directions, programs and interventions that benefit U.S. individuals and households who disproportionately experience FB.

ISBN: 9781085658904Subjects--Topical Terms:

534748
Public health.
Subjects--Index Terms:

Financial burden

National Estimates and Complex Sample Regression Modeling of the Financial Burden of Health Care Among the U.S. Nonelderly Population.
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