View in EDS HTML Full Text PDF Full Text

Student Debt and Healthcare Service Usage

Saved in:
Bibliographic Details
Title: Student Debt and Healthcare Service Usage
Language: English
Authors: Pearson, Blain, Lee, Jae Min
Source: Journal of Financial Counseling and Planning. 2022 33(2):183-193.
Availability: Association for Financial Counseling and Planning Education. 1500 West Third Avenue Suite 223, Columbus, OH 43212. Tel: 614-485-9650; Fax: 614-485-9621; Web site: https://connect.springerpub.com/content/sgrjfcp
Peer Reviewed: Y
Page Count: 11
Publication Date: 2022
Document Type: Journal Articles
Reports - Research
Descriptors: Debt (Financial), Access to Health Care, Student Loan Programs, Correlation, Health Behavior, Health Insurance, Student Characteristics
ISSN: 1052-3073
1947-7910
Abstract: This study investigated the association between student debt and healthcare service usage utilizing pooled data collected from the 2015 to 2018 waves of the National Financial Capability Study. The findings of this study suggest that, when compared to those without student debt, student debt holders have a lower likelihood of filling prescriptions for medicine, going to a doctor or clinic when they have a medical problem, and going to medical tests, treatments, and follow-up appointments. The findings and ensuing discussion add to the mounting evidence of the many challenges associated with student debt repayment.
Abstractor: As Provided
Entry Date: 2023
Accession Number: EJ1383266
Database: ERIC
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
    Url: https://content.ebscohost.com/cds/retrieve?content=AQICAHj0k_4E0hTGH8RJwT4gCJyBsGNe_WN95AvKlDbXJGqwxwEGZUlm7HZF1weSMulDhkkSAAAA4jCB3wYJKoZIhvcNAQcGoIHRMIHOAgEAMIHIBgkqhkiG9w0BBwEwHgYJYIZIAWUDBAEuMBEEDBzGzYs1aAbI1u42gQIBEICBmsZBTriZVLXzr46SYXqawSQr-3QOfsuwptJsDkPsSgBkIaYlZpmD8eJ6FVN4ti2wP-9ApiPP4vyUM-EVPYeNojMLn9RIgyRO75SPfkSO90h0g5DnENheUK4jZo8GjWeTvEPdwrAMvYMVG2cptYUE7E3C3xbCgjFasFchsNXOJKBLEHVZIZ7qFWckryWaHOZbB3DigdVFYIyKdCI=
Text:
  Availability: 1
  Value: <anid>AN0157892670;7e601jun.22;2022Jul12.05:12;v2.2.500</anid> <title id="AN0157892670-1">Student Debt and Healthcare Service Usage </title> <p>This study investigated the association between student debt and healthcare service usage utilizing pooled data collected from the 2015 to 2018 waves of the National Financial Capability Study. The findings of this study suggest that, when compared to those without student debt, student debt holders have a lower likelihood of filling prescriptions for medicine, going to a doctor or clinic when they have a medical problem, and going to medical tests, treatments, and follow-up appointments. The findings and ensuing discussion add to the mounting evidence of the many challenges associated with student debt repayment.</p> <p>Keywords: consumer theory; healthcare; personal finance; student debt; student loans</p> <p>Historically, a college education has offered the promise of a better and brighter tomorrow, and student debt has paved the path for many individuals to achieve their post-college dreams. In recent years, however, investing in a college education has been compared to investing in the lottery, where post-college financial uncertainty has younger individuals questioning whether or not college education warrants the monetary and time investments ([<reflink idref="bib6" id="ref1">6</reflink>]). Moreover, research has shown that many individuals regret taking out student debt to finance their college education ([<reflink idref="bib32" id="ref2">32</reflink>]; [<reflink idref="bib39" id="ref3">39</reflink>]).</p> <p>Student loan debt in the U.S. amounts to almost $1.6 billion in the third quarter of 2020 and accounts for the largest portion of household debt in the U.S., except for home mortgages ([<reflink idref="bib20" id="ref4">20</reflink>]). With U.S. aggregate student debt projected to reach $2 trillion by 2024 ([<reflink idref="bib18" id="ref5">18</reflink>]), heavy student debt burdens may increasingly affect other aspects of student debt holders' lives. Studies have found negative associations between student debt and homeownership ([<reflink idref="bib40" id="ref6">40</reflink>]; [<reflink idref="bib47" id="ref7">47</reflink>]), stock ownership ([<reflink idref="bib36" id="ref8">36</reflink>]), life satisfaction ([<reflink idref="bib34" id="ref9">34</reflink>]; [<reflink idref="bib37" id="ref10">37</reflink>]), financial self-efficacy ([<reflink idref="bib9" id="ref11">9</reflink>]), financial satisfaction ([<reflink idref="bib1" id="ref12">1</reflink>]; [<reflink idref="bib35" id="ref13">35</reflink>]; [<reflink idref="bib50" id="ref14">50</reflink>]), and financial difficulties and financial capability ([<reflink idref="bib13" id="ref15">13</reflink>]; [<reflink idref="bib38" id="ref16">38</reflink>]; [<reflink idref="bib43" id="ref17">43</reflink>]). However, the relationship between student debt and healthcare service usage has not received considerable attention in the prior literature.</p> <p>The relationship between student debt and healthcare service usage warrants research attention. The budget constraints imposed by student debt may place individuals in the vulnerable position of weighing the costs and benefits of student debt repayment and healthcare service usage. [<reflink idref="bib4" id="ref18">4</reflink>]) found that late student loan payments increased the likelihood of having unpaid medical bills by 41 percent. In cases where individuals' student debt is prevalent, individuals can be positioned to decide between spending on their healthcare and student debt repayment.</p> <hd id="AN0157892670-2">Literature Review and Hypothesis</hd> <p>Microeconomic theory posits that consumers are limited in healthcare service usage relative to their acquired capital, so-called budget constraints. Thus, factors creating dynamics within budget constraints, including the prices of substitutes for and complements of a commodity, affect the demand for the commodity, such as healthcare ([<reflink idref="bib25" id="ref19">25</reflink>]). An individual's healthcare service usage can be defined as the amount an individual consumes for medical care conglomerate services, such as drugs, hospitals, and physicians ([<reflink idref="bib21" id="ref20">21</reflink>]). Operating under the notion of healthcare as a commodity, in particular, [<reflink idref="bib53" id="ref21">53</reflink>]) utilized consumer theory to suggest that individuals are limited by their budget constraint and must make trade-offs between healthcare service usage and the service usage of alternative goods and services. Therefore, an individual's budget constraint necessitates that trade-offs must be made between healthcare service usage and the service usage of other goods and services. Empirical studies show that the amount of the desired spending on healthcare is constrained by income ([<reflink idref="bib8" id="ref22">8</reflink>]), and consumer choice entails a trade-off between the service usage of healthcare and other substitute goods and services ([<reflink idref="bib25" id="ref23">25</reflink>]).</p> <p>An individual's budget is constrained further by the introduction of debt repayment obligations ([<reflink idref="bib7" id="ref24">7</reflink>]; [<reflink idref="bib46" id="ref25">46</reflink>]). Increases in debt repayment obligations force trade-offs between service usage bundles, due to the resulting decrease in resources that can be allotted to the purchase of other goods. Thus, the trade-off between debt repayment and healthcare purchases may involve consumers weighing the costs and benefits of debt repayment or healthcare service usage. With respect to general debt obligations, this concept may help explain why consumer debts have been associated with poorer health, especially mental health ([<reflink idref="bib10" id="ref26">10</reflink>]; [<reflink idref="bib14" id="ref27">14</reflink>]; [<reflink idref="bib17" id="ref28">17</reflink>]; [<reflink idref="bib29" id="ref29">29</reflink>]; [<reflink idref="bib41" id="ref30">41</reflink>]).</p> <p>Of great concern are the recent and consistent increases in student debt ([<reflink idref="bib23" id="ref31">23</reflink>]; [<reflink idref="bib24" id="ref32">24</reflink>]; [<reflink idref="bib38" id="ref33">38</reflink>]). Student debt, more than other debt types, is associated with greater levels of financial anxiety and mental health challenges ([<reflink idref="bib3" id="ref34">3</reflink>]; [<reflink idref="bib5" id="ref35">5</reflink>]; [<reflink idref="bib26" id="ref36">26</reflink>]; [<reflink idref="bib49" id="ref37">49</reflink>]; [<reflink idref="bib54" id="ref38">54</reflink>]). With student debt continuing to climb ([<reflink idref="bib2" id="ref39">2</reflink>]; [<reflink idref="bib18" id="ref40">18</reflink>]; [<reflink idref="bib30" id="ref41">30</reflink>]; [<reflink idref="bib30" id="ref42">30</reflink>]; [<reflink idref="bib31" id="ref43">31</reflink>]), this places many individuals in the situation of foregoing healthcare purchases due to the budget constraints imposed by student debt.</p> <p>An individual's healthcare service usage has also been associated with other factors such as gender preferences, where females consume more than males ([<reflink idref="bib19" id="ref44">19</reflink>]; [<reflink idref="bib33" id="ref45">33</reflink>]; [<reflink idref="bib42" id="ref46">42</reflink>]), increases in income ([<reflink idref="bib48" id="ref47">48</reflink>]; [<reflink idref="bib51" id="ref48">51</reflink>]); race, where whites consume more than non-whites ([<reflink idref="bib33" id="ref49">33</reflink>]); increases in age ([<reflink idref="bib15" id="ref50">15</reflink>]); and the availability of substitute products, such as non-pharmaceutical interventions ([<reflink idref="bib22" id="ref51">22</reflink>]; [<reflink idref="bib45" id="ref52">45</reflink>]) and "alternative" medical practices ([<reflink idref="bib16" id="ref53">16</reflink>]; [<reflink idref="bib52" id="ref54">52</reflink>]). The authors posit that budget constraints resulting from student debt is related negatively to healthcare service usage.</p> <p>This study adds value to the current literature in two overarching ways. First, this study provides empirical evidence of the relationship between student debt and healthcare service usage, which has not been well-documented in the literature. Second, consumer theory focused on consumer decision-making under student-debt imposed budget constraints highlights the vulnerable position that many with student debt obligations face, with implications for borrowers, educators, researchers, practitioners, and policymakers.</p> <hd id="AN0157892670-3">Methods</hd> <p></p> <hd id="AN0157892670-4">Data and Sample Selection</hd> <p>Data from the National Financial Capability Study (NFCS) was utilized. The NFCS is sponsored by the Financial Industry Regulatory Authority (FINRA) Investor Education Foundation. Specifically, the 2015–2018 State-by-State Survey—Tracking Dataset is used. Respondent-level data from the 2015 to 2018 waves were utilized because these waves include the healthcare service usage data of interest.</p> <hd id="AN0157892670-5">Variables</hd> <p></p> <hd id="AN0157892670-6">Healthcare Variables</hd> <p>Three variables serve as proxies to estimate healthcare service usage. The questions from which the healthcare variables are constructed come from a series of questions in the NFCS. The NFCS participants were presented with the prompt, "In the last 12 months, was there any time when you..." and separately asked, "Did not fill a prescription for medicine because of the cost," "Skipped a medical test, treatment or follow-up recommended by a doctor because of the cost," and "Had a medical problem but DID NOT go to a doctor or clinic because of the cost." Participants could have answered "Yes," "No," "Don't know," or "Prefer not say." Participants who answered "Don't know" or "Prefer not say" were dropped from the sample. After missing observations were dropped, the sample size was (<emph>N</emph> = 24,806). The full set of questions related to the dependent variables can be found from the FINRA Foundatoin's website. <ulink href="http://www.usfinancialcapability.org/downloads.php">www.usfinancialcapability.org/downloads.php</ulink></p> <p>All healthcare variables are binary variables measuring whether healthcare costs prevented participants from filling a prescription for medicine (NoPills), going to a medical test/treatment/follow-up (NoTests), or going to a doctor or clinic when they had a medical problem (NoDoctor). If participants answered "yes" to any of the above, the variables were coded as a "1." The healthcare variables were coded as a "0," otherwise.</p> <hd id="AN0157892670-7">Student Debt Variable</hd> <p>The student debt variable is constructed based on the response to the question, "Do you currently have any student loans? If so, for whose education was this/were these loan(s) taken out?" Participants then could select a "Yes" response to each of the following: Yourself, Your spouse/partner, Your child(ren), Your grandchild(ren), and Other person. If participants answered "yes" to any of the above, the student debt was coded as a "1." The student debt was coded as a "0," otherwise.</p> <hd id="AN0157892670-8">Control Variables</hd> <p>The control variables examined include whether or not the survey participant is white, whether or not the survey participant is married, whether or not the survey participant has mortgage debt, and whether or not the survey participant has credit card debt. Other control measures include categorical measures for age, education, and income. Lastly, a binary control variable for the survey wave year is included as a control.</p> <hd id="AN0157892670-9">Analysis</hd> <p>To examine the association between student debt and healthcare service usage, three probit regression models are estimated:</p> <p> <ephtml> <math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mi mathvariant="italic">Pr</mi><mrow><mo stretchy="false">(</mo><msub><mrow><mi mathvariant="italic">Health</mi></mrow><mi>z</mi></msub><mo>=</mo><mn>1</mn><mo stretchy="false">)</mo></mrow><mo>=</mo><mi mathvariant="normal">Φ</mi><mrow><mo stretchy="false">{</mo><msub><mi>β</mi><mrow><mn>0</mn><mi>z</mi></mrow></msub><mo>+</mo><msub><mi>β</mi><mrow><mn>1</mn><mi>z</mi></mrow></msub><msub><mrow><mi mathvariant="italic">StudentDebt</mi></mrow><mi>z</mi></msub><msub><mrow><msub><mrow><mo>+</mo><msub><mi>β</mi><mrow><mn>2</mn><mi>z</mi></mrow></msub><msub><mrow><mi mathvariant="italic">HealthInsurance</mi></mrow><mi>z</mi></msub><mo>+</mo><mi>β</mi></mrow><mrow><mi mathvariant="italic">jz</mi></mrow></msub><mi>X</mi></mrow><mrow><mi mathvariant="italic">jz</mi></mrow></msub><mo>+</mo><msub><mi>e</mi><mi>z</mi></msub><mo stretchy="false">}</mo></mrow></mrow></math> </ephtml> </p> <p>Graph</p> <p>where <emph>Health<subs>z</subs></emph> represents the probability that a respondent limits healthcare service usage using three binary variables separately, <emph>NoPills<subs>z</subs></emph>, <emph>NoTests<subs>z</subs></emph>, and <emph>NoDoctor<subs>z</subs></emph>, coded as a "1" if costs prevented participants from filling a prescription for medicine (<emph>NoPills<subs>z</subs></emph>), going to a medical test/treatment/follow-up (<emph>NoTests<subs>z</subs></emph>), and going to a doctor or clinic when they had a medical problem (<emph>NoDoctor<subs>z</subs></emph>), respectively.</p> <p>Ф is the cumulative distribution function. A control for whether the participant has health insurance, <emph>HealthInsurance<subs>z</subs></emph>, enters the model as a binary variable. <emph>HealthInsurance<subs>z</subs></emph> was coded as a "1" if the respondent has health insurance and as a "0" otherwise.</p> <p>The <emph>X<subs>jz</subs></emph> is a vector of control variables, including white, married, mortgage debt, credit card debt, wave year, age, education, and income. The variables white, married, mortgage debt, and credit card debt enter the model as binary variables, coded as a "1" if the respondent is white, married, has mortgage debt, has credit card debt, respectively. The <emph>X<subs>jz</subs></emph> matrix also contains a binary variable for wave year, coded as a "1" for 2018 and a "0" for 2015. The age of the respondent enters the model as a categorical variable, with the reference group 18–24 serving as the reference group to which groups 25–34, 35–44, 45–54, 55–64, and 65+ are compared. Education is measured as a categorical variable with No High School (HS) serving as the reference group to which groups HS graduate (Diploma), HS graduate (GED), some college but no degree, Associate's degree, Bachelor's degree, and Post-graduate Degree are compared. Income is measured as a categorical variable with the group less than 15k serving as the reference group to which the other income groups, 15k–25k, 25k–35k, 35k–50k, 50k–75k, 75k–100k, 100k–150k, and 150k+, are compared. Survey weights are used. Marginal effects provide the magnitudes for each of the explanatory variables' effects on <emph>Health<subs>z</subs></emph>.</p> <hd id="AN0157892670-10">Results</hd> <p>Table 1 provides a correlation matrix showing the correlations between the three healthcare variables (NoPills, NoTests, NoDoctor). The NoPills and NoTests variables are positively correlated (<emph>r</emph> = 0.54). With respect to the NoDoctor variable, there is a positive correlation between NoPills (<emph>r</emph> = 0.52) and NoTests (<emph>r</emph> = 0.67).</p> <p>TABLE 1. Correlation Matrix Between Dependent and Explanatory Variables</p> <p> <ephtml> <table frame="hsides" rules="groups"><colgroup><col content-type="1" width="20%" /><col content-type="2" width="10%" /><col content-type="3" width="10%" /><col content-type="4" width="10%" /><col content-type="5" width="10%" /><col content-type="6" width="10%" /><col content-type="7" width="10%" /><col content-type="8" width="10%" /><col content-type="9" width="10%" /></colgroup><thead><tr><th /><th align="center">Did not fill prescription (nopills)</th><th align="center">Skipped medical test/treatment (notests)</th><th align="center">Did not go to doctor (nodoctors)</th><th align="center">Has student loan</th><th align="center">Spouse/partner student loan</th><th align="center">Child(ren) student loan</th><th align="center">Grandchild(ren) student loan</th><th align="center">Other person student loan</th></tr></thead><tbody><tr><td align="left">Did not fill prescription(nopills)</td><td align="center">1</td><td /><td /><td /><td /><td /><td /><td /></tr><tr><td align="left">Skipped medical test/treatment(notests)</td><td align="center">0.5366</td><td align="center">1</td><td /><td /><td /><td /><td /><td /></tr><tr><td align="left">Did not go to doctor(nodoctors)</td><td align="center">0.5188</td><td align="center">0.6712</td><td align="center">1</td><td /><td /><td /><td /><td /></tr><tr><td align="left">Has student loan</td><td align="center">0.2037</td><td align="center">0.2066</td><td align="center">0.2037</td><td align="center">1</td><td /><td /><td /><td /></tr><tr><td align="left">Spouse/partner student loan</td><td align="center">0.0751</td><td align="center">0.0913</td><td align="center">0.0875</td><td align="center">0.2308</td><td align="center">1</td><td /><td /><td /></tr><tr><td align="left">Child(ren) student loan</td><td align="center">0.034</td><td align="center">0.0489</td><td align="center">0.0363</td><td align="center">0.0012</td><td align="center">0.0219</td><td align="center">1</td><td /><td /></tr><tr><td align="left">Grandchild(ren) student loan</td><td align="center">0.0315</td><td align="center">0.0361</td><td align="center">0.0296</td><td align="center">0.0253</td><td align="center">0.0408</td><td align="center">0.0541</td><td align="center">1</td><td /></tr><tr><td align="left">Other person student loan</td><td align="center">0.0119</td><td align="center">0.0213</td><td align="center">0.0176</td><td align="center">0.021</td><td align="center">0.0078</td><td align="center">0.0078</td><td align="center">0.0735</td><td align="center">1</td></tr></tbody></table> </ephtml> </p> <p>1 <bold><emph>Note</emph></bold>. Data from the 2015 to 2018 National Financial Capability Study State-by-State Survey—Tracking Dataset are utilized. <emph>N</emph> = 24,806.</p> <p>Table 2 provides the means of the dependent variables and key explanatory variables. Healthcare costs prevented 12.98%, 16.16%, and 16.75% of participants from filling a prescription for medicine, going to a medical test/treatment/follow-up, or going to a doctor or clinic when they had a medical problem, respectively. On average, 24.22% had some form of student loan, with 14.63% having student loans on themselves, 7.59% having student loans for their spouses/partners, 5.75% having student loans for their child(ren), 0.17% having student loans for their grandchild(ren), and 0.16% having student loans for "other" person. The summation of the categorical means equals 28.27%, implying that 4.05% of the sample had more than one student loan type.</p> <p>TABLE 2. Descriptive Statistics</p> <p> <ephtml> <table frame="hsides" rules="groups"><colgroup><col content-type="1" width="50%" /><col content-type="2" width="25%" /><col content-type="3" width="25%" /></colgroup><thead><tr><th align="left">Variables</th><th align="center">Mean (%)</th><th align="center">Std. dev.</th></tr></thead><tbody><tr><td align="left">Did not fill prescription (nopills)</td><td align="center">0.1298</td><td align="center">0.3361</td></tr><tr><td align="left">Skipped medical test/treatment (notests)</td><td align="center">0.1616</td><td align="center">0.3681</td></tr><tr><td align="left">Did not go to doctor (nodoctors)</td><td align="center">0.1675</td><td align="center">0.3735</td></tr><tr><td align="left">Has student loan</td><td /><td /></tr><tr><td align="left"> On themselves</td><td align="center">0.1463</td><td align="center">0.3534</td></tr><tr><td align="left"> Spouse/partner student loan</td><td align="center">0.0759</td><td align="center">0.2648</td></tr><tr><td align="left"> Child(ren) student loan</td><td align="center">0.0572</td><td align="center">0.2322</td></tr><tr><td align="left"> Grandchild(ren) student loan</td><td align="center">0.0017</td><td align="center">0.0406</td></tr><tr><td align="left"> Other person student loan</td><td align="center">0.0016</td><td align="center">0.0396</td></tr><tr><td align="left">Health insurance (none as base)</td><td align="center">0.9480</td><td align="center">0.2220</td></tr><tr><td align="left">White (non-white as base)</td><td align="center">0.7857</td><td align="center">0.4103</td></tr><tr><td align="left">Married (non-married as base)</td><td align="center">0.7220</td><td align="center">0.4480</td></tr><tr><td align="left">Credit card debt (no debt as base)</td><td align="center">0.4523</td><td align="center">0.4977</td></tr><tr><td align="left">Mortgage debt (no debt as base)</td><td align="center">0.6344</td><td align="center">0.4816</td></tr><tr><td align="left">Wave (2015 as base)</td><td align="center">0.4894</td><td align="center">0.4999</td></tr><tr><td /><td align="center"><bold>Frequency</bold></td><td align="center"><bold>Percentage</bold></td></tr><tr><td align="left">Age</td><td /><td /></tr><tr><td align="left"> 18–24</td><td align="center">897</td><td align="center">3.62</td></tr><tr><td align="left"> 25–34</td><td align="center">3,699</td><td align="center">14.91</td></tr><tr><td align="left"> 35–44</td><td align="center">4,667</td><td align="center">18.81</td></tr><tr><td align="left"> 45–54</td><td align="center">5,503</td><td align="center">22.18</td></tr><tr><td align="left"> 55–64</td><td align="center">3,097</td><td align="center">12.48</td></tr><tr><td align="left"> 65+</td><td align="center">6,943</td><td align="center">27.99</td></tr><tr><td align="left">Education</td><td /><td /></tr><tr><td align="left"> No HS education</td><td align="center">215</td><td align="center">0.87</td></tr><tr><td align="left"> HS graduate (diploma)</td><td align="center">3,277</td><td align="center">13.21</td></tr><tr><td align="left"> HS graduate (GED)</td><td align="center">1,134</td><td align="center">4.57</td></tr><tr><td align="left"> Some college, no degree</td><td align="center">5,893</td><td align="center">23.76</td></tr><tr><td align="left"> Associate's degree</td><td align="center">2,814</td><td align="center">11.34</td></tr><tr><td align="left"> Bachelor's degree</td><td align="center">6,861</td><td align="center">27.66</td></tr><tr><td align="left"> Post-graduate degree</td><td align="center">4,612</td><td align="center">18.59</td></tr><tr><td align="left">Household income</td><td /><td /></tr><tr><td align="left"> Less than 15k</td><td align="center">578</td><td align="center">2.33</td></tr><tr><td align="left"> Between 15k and 25k</td><td align="center">1,070</td><td align="center">4.31</td></tr><tr><td align="left"> Between 25k and 35k</td><td align="center">1,597</td><td align="center">6.44</td></tr><tr><td align="left"> Between 35k and 50k</td><td align="center">3,026</td><td align="center">12.2</td></tr><tr><td align="left"> Between 50k and 75k</td><td align="center">5,746</td><td align="center">23.16</td></tr><tr><td align="left"> Between 75k and 100k</td><td align="center">5,076</td><td align="center">20.46</td></tr><tr><td align="left"> Between 100k and 150k</td><td align="center">5,035</td><td align="center">20.3</td></tr><tr><td align="left"> 150k+</td><td align="center">2,678</td><td align="center">10.8</td></tr></tbody></table> </ephtml> </p> <p>2 <bold><emph>Note</emph></bold>. Data from the 2015 to 2018 National Financial Capability Study State-by-State Survey—Tracking Dataset are utilized. <emph>N</emph> = 24,806.</p> <p>Table 2 also provides the descriptive statistics of the sample. An important consideration in analyzing whether survey participants healthcare service usage is whether or not they have health insurance, as health insurance can reduce the costs associated with filling prescription medicines, medical tests, and doctor visits. 94.80% of the sample has some form of health insurance. Other descriptive statistics of the sample show that 78.57% are white, 72.20% are married, 45.23% have credit card debt, 63.44% have mortgage debt, 40.47% have at least a four-year college degree, 46.25% are above the age of 55, and 74.72% have household income above $50,000.</p> <p>Table 3 provides the average marginal effects and standard errors from the probit regressions. The explanatory variable measuring whether the participant has a student loan, StudentDebt<subs>z</subs>, resultined in 0.0781, 0.0904, and 0.0836 average marginal effects for the regression models estimating whether costs prevented participants from filling a prescription for medicine (<emph>NoPills<subs>z</subs></emph>), going to a medical test/treatment/follow-up (<emph>NoTests<subs>z</subs></emph>), and going to a doctor or clinic when they had a medical problem (<emph>NoDoctor<subs>z</subs></emph>), respectively. The results are statistically significant (<emph>p</emph> <.001). The findings suggest that, when compared to those who do not have student debt, those who have student debt are more likely to experience budget constraints preventing them from filling a prescription for medicine, going to a medical test/treatment/follow-up, and going to a doctor or clinic.</p> <p>TABLE 3. Marginal Effects from Probit Regression</p> <p> <ephtml> <table frame="hsides" rules="groups"><colgroup><col content-type="1" width="22%" /><col content-type="2" width="13%" /><col content-type="3" width="13%" /><col content-type="4" width="13%" /><col content-type="5" width="13%" /><col content-type="6" width="13%" /><col content-type="7" width="13%" /></colgroup><thead><tr><th /><th colspan="2" align="center">Did not fill prescription (nopills)</th><th colspan="2" align="center">Skipped medical test/treatment (notests)</th><th colspan="2" align="center">Did not go to doctor (nodoctors)</th></tr><tr><th align="left">Variables</th><th align="center">Marginal effect</th><th align="center">S.E.</th><th align="center">Marginal effect</th><th align="center">S.E.</th><th align="center">Marginal effect</th><th align="center">S.E.</th></tr></thead><tbody><tr><td align="left">Has student loan</td><td align="center">0.0781<xref ref-type="table-fn" rid="tfn7">***</xref></td><td align="center">(0.0047)</td><td align="center">0.0904<xref ref-type="table-fn" rid="tfn7">***</xref></td><td align="center">(0.0051)</td><td align="center">0.0836<xref ref-type="table-fn" rid="tfn7">***</xref></td><td align="center">(0.0051)</td></tr><tr><td align="left">Health insurance (none as base)</td><td align="center">−0.0779<xref ref-type="table-fn" rid="tfn7">***</xref></td><td align="center">(0.0076)</td><td align="center">−0.1062<xref ref-type="table-fn" rid="tfn7">***</xref></td><td align="center">(0.0083)</td><td align="center">−0.1264<xref ref-type="table-fn" rid="tfn7">***</xref></td><td align="center">(0.0082)</td></tr><tr><td align="left">White (non-white as base)</td><td align="center">−0.0155<xref ref-type="table-fn" rid="tfn6">**</xref></td><td align="center">(0.0048)</td><td align="center">−0.0030</td><td align="center">(0.0053)</td><td align="center">0.0073</td><td align="center">(0.0054)</td></tr><tr><td align="left">Married (non-married as base)</td><td align="center">0.0149<xref ref-type="table-fn" rid="tfn6">**</xref></td><td align="center">(0.0049)</td><td align="center">0.0047</td><td align="center">(0.0052)</td><td align="center">0.0087</td><td align="center">(0.0053)</td></tr><tr><td align="left">Mortgage debt (no debt as base)</td><td align="center">0.0207<xref ref-type="table-fn" rid="tfn7">***</xref></td><td align="center">(0.0047)</td><td align="center">0.0325<xref ref-type="table-fn" rid="tfn7">***</xref></td><td align="center">(0.0052)</td><td align="center">0.0362<xref ref-type="table-fn" rid="tfn7">***</xref></td><td align="center">(0.0053)</td></tr><tr><td align="left">Credit card debt (no debt as base)</td><td align="center">0.0645<xref ref-type="table-fn" rid="tfn7">***</xref></td><td align="center">(0.0043)</td><td align="center">0.0735<xref ref-type="table-fn" rid="tfn7">***</xref></td><td align="center">(0.0047)</td><td align="center">0.0714<xref ref-type="table-fn" rid="tfn7">***</xref></td><td align="center">(0.0047)</td></tr><tr><td align="left">Wave (2015 as base)</td><td align="center">0.0144<xref ref-type="table-fn" rid="tfn7">***</xref></td><td align="center">(0.0041)</td><td align="center">0.0217<xref ref-type="table-fn" rid="tfn7">***</xref></td><td align="center">(0.0044)</td><td align="center">0.0214<xref ref-type="table-fn" rid="tfn7">***</xref></td><td align="center">(0.0044)</td></tr><tr><td colspan="2" align="left">Age (18–24 as base)</td><td /><td /><td /><td /><td /></tr><tr><td align="left">25–34</td><td align="center">0.0103</td><td align="center">(0.0130)</td><td align="center">0.0026</td><td align="center">(0.0142)</td><td align="center">0.0081</td><td align="center">(0.0147)</td></tr><tr><td align="left">35–44</td><td align="center">−0.0190</td><td align="center">(0.0128)</td><td align="center">−0.0317<xref ref-type="table-fn" rid="tfn5">*</xref></td><td align="center">(0.0141)</td><td align="center">−0.0339<xref ref-type="table-fn" rid="tfn5">*</xref></td><td align="center">(0.0145)</td></tr><tr><td align="left">45–54</td><td align="center">−0.0441<xref ref-type="table-fn" rid="tfn7">***</xref></td><td align="center">(0.0126)</td><td align="center">−0.0492<xref ref-type="table-fn" rid="tfn7">***</xref></td><td align="center">(0.0140)</td><td align="center">−0.0621<xref ref-type="table-fn" rid="tfn7">***</xref></td><td align="center">(0.0143)</td></tr><tr><td align="left">55–64</td><td align="center">−0.0746<xref ref-type="table-fn" rid="tfn7">***</xref></td><td align="center">(0.0132)</td><td align="center">−0.1118<xref ref-type="table-fn" rid="tfn7">***</xref></td><td align="center">(0.0144)</td><td align="center">−0.1277<xref ref-type="table-fn" rid="tfn7">***</xref></td><td align="center">(0.0147)</td></tr><tr><td align="left">65+</td><td align="center">−0.0837<xref ref-type="table-fn" rid="tfn7">***</xref></td><td align="center">(0.0125)</td><td align="center">−0.1104<xref ref-type="table-fn" rid="tfn7">***</xref></td><td align="center">(0.0137)</td><td align="center">−0.1363<xref ref-type="table-fn" rid="tfn7">***</xref></td><td align="center">(0.0141)</td></tr><tr><td colspan="3" align="left">Education (did not complete HS as base)</td><td /><td /><td /><td /></tr><tr><td align="left">HS graduate (Diploma)</td><td align="center">−0.0582<xref ref-type="table-fn" rid="tfn5">*</xref></td><td align="center">(0.0241)</td><td align="center">−0.0195</td><td align="center">(0.0241)</td><td align="center">−0.0266</td><td align="center">(0.0242)</td></tr><tr><td align="left">HS graduate (GED)</td><td align="center">−0.0256</td><td align="center">(0.0255)</td><td align="center">0.0093</td><td align="center">(0.0257)</td><td align="center">0.0016</td><td align="center">(0.0257)</td></tr><tr><td align="left">Some college, no degree</td><td align="center">−0.0473<xref ref-type="table-fn" rid="tfn5">*</xref></td><td align="center">(0.0239)</td><td align="center">−0.0185</td><td align="center">(0.0239)</td><td align="center">−0.0192</td><td align="center">(0.0239)</td></tr><tr><td align="left">Associate's degree</td><td align="center">−0.0658<xref ref-type="table-fn" rid="tfn6">**</xref></td><td align="center">(0.0242)</td><td align="center">−0.0267</td><td align="center">(0.0243)</td><td align="center">−0.0388</td><td align="center">(0.0243)</td></tr><tr><td align="left">Bachelor's degree</td><td align="center">−0.0743<xref ref-type="table-fn" rid="tfn6">**</xref></td><td align="center">(0.0239)</td><td align="center">−0.0468<xref ref-type="table-fn" rid="tfn5">*</xref></td><td align="center">(0.0239)</td><td align="center">−0.0465</td><td align="center">(0.0240)</td></tr><tr><td align="left">Post-graduate degree</td><td align="center">−0.0643<xref ref-type="table-fn" rid="tfn6">**</xref></td><td align="center">(0.0243)</td><td align="center">−0.0360</td><td align="center">(0.0243)</td><td align="center">−0.0385</td><td align="center">(0.0244)</td></tr><tr><td colspan="3" align="left">Household income (less than 15k as base)</td><td /><td /><td /><td /></tr><tr><td align="left">Between 15k and 25k</td><td align="center">0.0184</td><td align="center">(0.0189)</td><td align="center">−0.0027</td><td align="center">(0.0200)</td><td align="center">0.0125</td><td align="center">(0.0206)</td></tr><tr><td align="left">Between 25k and 35k</td><td align="center">0.0026</td><td align="center">(0.0177)</td><td align="center">−0.0123</td><td align="center">(0.0189)</td><td align="center">−0.0109</td><td align="center">(0.0194)</td></tr><tr><td align="left">Between 35k and 50k</td><td align="center">−0.0192</td><td align="center">(0.0166)</td><td align="center">−0.0307</td><td align="center">(0.0178)</td><td align="center">−0.0413<xref ref-type="table-fn" rid="tfn5">*</xref></td><td align="center">(0.0182)</td></tr><tr><td align="left">Between 50k and 75k</td><td align="center">−0.0569<xref ref-type="table-fn" rid="tfn7">***</xref></td><td align="center">(0.0161)</td><td align="center">−0.0586<xref ref-type="table-fn" rid="tfn6">**</xref></td><td align="center">(0.0174)</td><td align="center">−0.0731<xref ref-type="table-fn" rid="tfn7">***</xref></td><td align="center">(0.0178)</td></tr><tr><td align="left">Between 75k and 100k</td><td align="center">−0.0551<xref ref-type="table-fn" rid="tfn6">**</xref></td><td align="center">(0.0164)</td><td align="center">−0.0623<xref ref-type="table-fn" rid="tfn7">***</xref></td><td align="center">(0.0176)</td><td align="center">−0.0797<xref ref-type="table-fn" rid="tfn7">***</xref></td><td align="center">(0.0180)</td></tr><tr><td align="left">Between 100k and 150k</td><td align="center">−0.0915<xref ref-type="table-fn" rid="tfn7">***</xref></td><td align="center">(0.0164)</td><td align="center">−0.1163<xref ref-type="table-fn" rid="tfn7">***</xref></td><td align="center">(0.0176)</td><td align="center">−0.1320<xref ref-type="table-fn" rid="tfn7">***</xref></td><td align="center">(0.0180)</td></tr><tr><td align="left">150k+</td><td align="center">−0.1064<xref ref-type="table-fn" rid="tfn7">***</xref></td><td align="center">(0.0168)</td><td align="center">−0.1475<xref ref-type="table-fn" rid="tfn7">***</xref></td><td align="center">(0.0180)</td><td align="center">−0.1662<xref ref-type="table-fn" rid="tfn7">***</xref></td><td align="center">(0.0184)</td></tr></tbody></table> </ephtml> </p> <ulist> <item>3 <bold><emph>Note</emph></bold>. Data from the 2015 and 2018 National Financial Capability Study State-by-State Survey—Tracking Dataset are utilized. <emph>N</emph> = 24,806.</item> <item>4 Significance is defined as follows:</item> <item>5 *significant at <emph>p</emph> < 0.05;</item> <item>6 **significant at <emph>p</emph> < 0.01;</item> <item>7 ***significant at <emph>p</emph> < 0.001.</item> </ulist> <p>The average marginal effects for the HealthcareInsurance<subs>z</subs> variable for the <emph>NoPills<subs>z</subs></emph>, <emph>NoTests<subs>z</subs></emph>, and <emph>NoDoctor<subs>z</subs></emph> estimated models are −0.0779, −0.1062, and −0.1264, respectively. The results are statistically significant (<emph>p</emph> <.001). The findings suggest that, when compared to those who do not have health insurance, those who have health insurance are less likely to experience budget constraints preventing them from filling a prescription for medicine, going to a medical test/treatment/follow-up, and going to a doctor or clinic.</p> <p>The results for age, education level, and income level were negatively related to the probability of experiencing budget constraints preventing them from consuming healthcare service. For example, compared to those who did not complete high school, the other education groups were less likely to experience budget constraints preventing them from filling a prescription for medicine.</p> <hd id="AN0157892670-11">Discussions, Limitations, and Implications</hd> <p></p> <hd id="AN0157892670-12">Discussions</hd> <p>This study used the 2015 and 2018 NFCS to examine the association between holding student debt and healthcare service usage. Our probit analyses showed that, compared to those without student debt, student debt holders were less likely to consume healthcare measured in three ways, even when controlling for socio-demographic characteristics. The negative association between student debt and healthcare service usage raises concerns about the challenges student loan holders may experience, such as foregoing healthcare purchases.</p> <p>Demand for healthcare and other goods and services in the service usage bundle is a part of an individual's utility function, both directly as a source of current utility and indirectly as a capital or investment good ([<reflink idref="bib21" id="ref55">21</reflink>]; [<reflink idref="bib27" id="ref56">27</reflink>]; [<reflink idref="bib44" id="ref57">44</reflink>]). Student debt can affect dynamics in consumer decision-making under a budget constraint that represents all possible combinations of goods and services that a consumer can purchase, assuming the consumer exhausts all of their income during the analyzed period.Much like other household debt, such as a mortgage debt or an auto debt ([<reflink idref="bib13" id="ref58">13</reflink>]), student debt burdens can influence financial and non-financial decisions and outcomes ([<reflink idref="bib13" id="ref59">13</reflink>]) and have a negative effect on service usage levels (Bahadir & Gicheva, 2019). The potential increase in budget constraints resulting from student debt creates different consumer trade-offs between goods that can be consumed and how much can be consumed.In the context of healthcare, the findings of this study are aligned with the theoretical prediction, suggesting that student debt is associated negatively with healthcare service usage.</p> <p>Changes in the macro-economy have not helped the affordability of healthcare and higher education. The change in the Consumer Price Index (CPI) for healthcare costs increased by 638.6% ([<reflink idref="bib28" id="ref60">28</reflink>] and that of college tuition and fees increased by 1,298.5% between 1979 and 2019 ([<reflink idref="bib12" id="ref61">12</reflink>]). In comparison, according to the U.S. Census Bureau, the CPI for all Urban Consumers increased by 375.1% over the same time. With healthcare and college cost inflation increasing at a larger rate than the cost of all CPI items ([<reflink idref="bib12" id="ref62">12</reflink>]; [<reflink idref="bib28" id="ref63">28</reflink>]), student debt holders may increasingly find themselves making trade-off decisions between student debt repayment and healthcare purchases.</p> <hd id="AN0157892670-13">Limitations</hd> <p>Despite the findings and contributions, there are limitations to this study. First, due to the data availability, this study cannot measure the dollar amount of the survey participants' student debt or their repayment. A continuous measurement of the dollar amount of student debt, or the amount of required periodic student debt repayment, would provide further insight into how student debt burdens are related to healthcare service usage. On a related note, the data does not provide a continuous measure for healthcare expenditures. Having a continuous measure for healthcare expenditures would provide insight into the relative service usage of healthcare.</p> <p>Given the limited literature on the validity of limited healthcare service usage measures, future researchers could explore the validity or degree of measurement errors of "don't know" or "refused to answer" responses to limited healthcare service usage variables.</p> <p>Although this study is based on the assumptions from consumer theory, details of budget constraints can change. Potential dynamics of budget constraints can be further examined by future studies using a different study design, such as a panel study.</p> <hd id="AN0157892670-14">Implications for Financial Professionals</hd> <p>Unlike mortgage debt or auto debt, there is little that can be done to manage the debt and budget constraints imposed by student debt. In the case of a mortgage debt (auto debt), one option for individuals is to default on their debt, resulting in foreclosure (repossession). Another option for individuals is to sell their home (vehicle) and utilize the proceeds to alleviate the mortgage debt (auto debt). With regards to student debt, however, such options as repossession are not available, and other repayment options are limited.</p> <p>One of the few options that exist for student debt management is restructuring the repayment of the student debt. The Income Driven Repayment (IDR), Public Service Loan Forgiveness (PSLF), and Teacher Loan Forgiveness (TLF) are options for restructuring student debt repayment ([<reflink idref="bib38" id="ref64">38</reflink>]). Financial planners and counselors who work with clients who have student debt should be aware of the restructuring options that are available. In addition, financial planners and counselors should review the purchase patterns and budget components of their clients. Clearly, if student debt is preventing access to healthcare, there are potential benefits to restructuring their clients' student debt.</p> <p>A preventative practice proposed by [<reflink idref="bib11" id="ref65">11</reflink>]) is for financial aid professionals to collaborate with personal finance researchers to promote education initiatives for the responsible utilization of student debt. Their study showed that students who sought financial counseling had a greater likelihood in discontinuing college within the next year, ultimately suggesting early intervention for students who are self-funding their college education. Early intervention may serve as a roadblock for individuals from acquiring too much student debt, preventing the negative byproducts of too much student debt acquisition.</p> <p>Other preventative practices include the application of behavioral concepts. Financial aid professionals who place emphasis on framing student debt as an education access tool may aid in limiting debt acquisition, where student debt is framed as a tool to carry out a particular function, education. Framing student debt as an access tool may also aid in how student debt acquirers mentally account for the recently acquired funds, potentially viewing the recently acquired funds as having less discretionary spending power.</p> <hd id="AN0157892670-15">Disclosure</hd> <p>The authors have no relevant financial interest or affiliations with any commercial interests related to the subjects discussed within this article.</p> <hd id="AN0157892670-16">Funding</hd> <p>The author(s) received no specific grant or financial support for the research, authorship, and/or publication of this article.</p> <ref id="AN0157892670-17"> <title> References </title> <blist> <bibl id="bib1" idref="ref12" type="bt">1</bibl> <bibtext> Aboagye, J., & Jung, J. Y. (2018). Debt holding, financial behavior, and financial satisfaction. Journal of Financial Counseling and Planning, 29 (2), 208 – 218. https://doi.org/10.1891/1052-3073.29.2.208</bibtext> </blist> <blist> <bibl id="bib2" idref="ref39" type="bt">2</bibl> <bibtext> Addo, F. R., Houle, J. N., & Simon, D. (2016). Young, black, and (still) in the red: Parental wealth, race, and student loan debt. Race and Social Problems, 8 (1), 64 – 76. https://doi.org/10.1007/S12552-016-9162-0</bibtext> </blist> <blist> <bibl id="bib3" idref="ref34" type="bt">3</bibl> <bibtext> Andrews, B., & Wilding, J. M. (2004). The relation of depression and anxiety to life-stress and achievement in students. British Journal of Psychology, 95 (4), 509 – 521. https://doi.org/10.1348/0007126042369802</bibtext> </blist> <blist> <bibl id="bib4" idref="ref18" type="bt">4</bibl> <bibtext> Anong, S. T., & Henager, R. (2021). Student loans and health-related financial hardship. Journal of Student Financial Aid, 50 (2), 3.</bibtext> </blist> <blist> <bibl id="bib5" idref="ref35" type="bt">5</bibl> <bibtext> Archuleta, K. L., Dale, A., & Spann, S. M. (2013). College students and financial distress: Exploring debt, financial satisfaction, and financial anxiety. Journal of Financial Counseling and Planning, 24 (2), 50 – 62.</bibtext> </blist> <blist> <bibl id="bib6" idref="ref1" type="bt">6</bibl> <bibtext> Avery, C., & Turner, S. (2012). Student Loans: Do college students borrow too much-or not enough?. Journal of Economic Perspectives, 26 (1), 165 – 92. https://doi.org/10.1257/JEP.26.1.165</bibtext> </blist> <blist> <bibl id="bib7" idref="ref24" type="bt">7</bibl> <bibtext> Bechlioulis, A. P., & Brissimis, S. N. (2019). Consumer debt non-payment and the borrowing constraint: Implications for consumer behavior. Journal of Banking & Finance, 101, 161 – 172. https://doi.org/10.1016/J.JBANKFIN.2019.02.009</bibtext> </blist> <blist> <bibl id="bib8" idref="ref22" type="bt">8</bibl> <bibtext> Benzeval, M., Judge, K., & Shouls, S. (2001). Understanding the relationship between income and health: How much can be gleaned from cross-sectional data?. Social Policy and Administration, 35 (4), 376 – 396. https://doi.org/10.1111/1467-9515.00240</bibtext> </blist> <blist> <bibl id="bib9" idref="ref11" type="bt">9</bibl> <bibtext> Brady, S., Miller, J., Balmuth, A., D'Ambrosio, L. A., & Coughlin, J. F. (2021). Factors contributing to the financial self-efficacy of student loan borrowers. Journal of Financial Counseling and Planning, 32 (3), 493 – 506. https://doi.org/10.1891/JFCP-19-00067</bibtext> </blist> <blist> <bibtext> Bridges, S., & Disney, R. (2010). Debt and depression. Journal of Health Economics, 29 (3), 388 – 403. https://doi.org/10.1016/j.jhealeco.2010.02.003</bibtext> </blist> <blist> <bibtext> Britt, S. L., Ammerman, D. A., Barrett, S. F., & Jones, S. (2017). Student loans, financial stress, and college student retention. Journal of Student Financial Aid, 47 (1), 25 – 37.</bibtext> </blist> <blist> <bibtext> Bureau of Labor Statistics. (2021). Consumer price index. January 17, 2021, from https://beta.bls.gov/dataViewer/view/timeseries/CUSR0000SEEB01;jsessionid=B18F64F4381694F7337D7E7821C9023B</bibtext> </blist> <blist> <bibtext> Cho, S. H., Xu, Y., & Kiss, D. E. (2015). Understanding student loan decisions: A literature review. Family and Consumer Sciences Research Journal, 43 (3), 229 – 243. https://doi.org/10.1111/FCSR.12099</bibtext> </blist> <blist> <bibtext> Clayton, M., Liñares-Zegarra, J., & Wilson, J. O. (2015). Does debt affect health? Cross country evidence on the debt-health nexus. Social Science & Medicine, 130, 51 – 58. https://doi.org/10.1016/j.socscimed.2015.02.002</bibtext> </blist> <blist> <bibtext> Cylus, J., Hartman, M., Washington, B., Andrews, K., & Catlin, A. (2011). Pronounced gender and age differences are evident in personal health care spending per person. Health Affairs, 30 (1), 153 – 160. https://doi.org/10.1377/hlthaff.2010.0216</bibtext> </blist> <blist> <bibtext> Degner, L. F., Kristjanson, L. J., Bowman, D., Sloan, J. A., Carriere, K. C., O'neil, J., & Mueller, B. (1997). Information needs and decisional preferences in women with breast cancer. Journal of the American Medical Association, 277 (18), 1485 – 1492. https://doi.org/10.1001/JAMA.1997.03540420081039</bibtext> </blist> <blist> <bibtext> Drentea, P., & Lavrakas, P. J. (2000). Over the limit: The association among health, race and debt. Social Science & Medicine, 50 (4), 517 – 529. https://doi.org/10.1016/S0277-9536(99)00298-1</bibtext> </blist> <blist> <bibtext> Experian. (2020, June 24). Student loan debt climbs to $1.4 trillion in 2019. https://<ulink href="http://www.experian.com/blogs/ask-experian/state-of-student-loan-debt/#s1">www.experian.com/blogs/ask-experian/state-of-student-loan-debt/#s1</ulink></bibtext> </blist> <blist> <bibtext> Fan, J. X., Wen, M., Jin, L., & Wang, G. (2013). Disparities in healthcare utilization in China: Do gender and migration status matter?. Journal of Family and Economic Issues, 34 (1), 52 – 63. https://doi.org/10.1007/S10834-012-9296-1</bibtext> </blist> <blist> <bibtext> Federal Reserve Bank of New York. (2020). Quarterly report on household debt and credit. Federal Reserve Bank of New York. https://<ulink href="http://www.newyorkfed.org/microeconomics/hhdc.html">www.newyorkfed.org/microeconomics/hhdc.html</ulink></bibtext> </blist> <blist> <bibtext> Feldstein, P. J. (1966). Research on the demand for health services. The Milbank Memorial Fund Quarterly, 44 (3), 128 – 165.</bibtext> </blist> <blist> <bibtext> Flaxman, S., Mishra, S., Gandy, A., Unwin, H. J. T., Mellan, T. A., Coupland, H., & Bhatt, S. (2020). Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe. Nature, 584 (7820), 257 – 261. https://doi.org/10.1038/s41586-020-2405-7</bibtext> </blist> <blist> <bibtext> Fuinhas, J. A., Moutinho, V., & Silva, E. (2019). Delinquency and default in usa student debt as a proportional response to unemployment and average debt per borrower. Economies, 7 (4), 1 – 16. https://doi.org/10.3390/economies7040100</bibtext> </blist> <blist> <bibtext> Goldrick-Rab, S., & Steinbaum, M. (2020). What is the problem with student debt?. Journal of Policy Analysis and Management, 39 (2), 534 – 540. https://doi.org/10.1002/pam.22208</bibtext> </blist> <blist> <bibtext> Gan, L. L., & Frederick, J. R. (2010). The willingness to spend on healthcare: Evidence from Singapore. Review of Applied Economics, 6 (1), 13 – 27. https://doi.org/10.22004/AG.ECON.143266</bibtext> </blist> <blist> <bibtext> Grable, J. E., & Joo, S. H. (2006). Student racial differences in credit card debt and financial behaviors and stress. College Student Journal, 40 (2), 400 – 409.</bibtext> </blist> <blist> <bibtext> Grossman, M. (1972). On the concept of health capital and the demand for health. Journal of Political economy, 80 (2), 223 – 255. https://doi.org/10.1086/259880</bibtext> </blist> <blist> <bibtext> Health Resources ... Services Administration. (2020, June 24). Consumer Price Index (CPI) for medical care. https://<ulink href="http://www.hrsa.gov/get-health-care/affordable/hill-burton/cpi.html">www.hrsa.gov/get-health-care/affordable/hill-burton/cpi.html</ulink></bibtext> </blist> <blist> <bibtext> Hojman, D. A., Miranda, Á., & Ruiz-Tagle, J. (2016). Debt trajectories and mental health. Social Science & Medicine, 167, 54 – 62. https://doi.org/10.1016/j.socscimed.2016.08.027</bibtext> </blist> <blist> <bibtext> Houle, J. N. (2014). Disparities in debt: Parents' socioeconomic resources and young adult student loan debt. Sociology of Education, 87 (1), 53 – 69.</bibtext> </blist> <blist> <bibtext> Jackson, B. A., & Reynolds, J. R. (2013). The price of opportunity: Race, student loan debt, and college achievement. Sociological Inquiry, 83 (3), 335 – 368. https://doi.org/10.1111/SOIN.12012</bibtext> </blist> <blist> <bibtext> Johnson, C. L., O'Neill, B., Worthy, S. L., Lown, J. M., & Bowen, C. F. (2016). What are student loan borrowers thinking? Insights from focus groups on college selection and student loan decision making. Journal of Financial Counseling and Planning, 27 (2), 184 – 198. https://doi.org/10.1891/1052-3073.27.2.184</bibtext> </blist> <blist> <bibtext> Johnson-Lans, S., & Bellemore, F. (1997). Gender and race as factors in health care utilization. International Advances in Economic Research, 3 (2), 193 – 205. https://doi.org/10.1007/BF02294940</bibtext> </blist> <blist> <bibtext> Kim, J., & Chatterjee, S. (2019). Student loans, health, and life satisfaction of US households: Evidence from a panel study. Journal of Family and Economic Issues, 40 (1), 36 – 50. https://doi.org/10.1007/S10834-018-9594-3</bibtext> </blist> <blist> <bibtext> Kim, K. T., Lee, J. M., & Lee, J. (2021). Student loans and financial satisfaction: The moderating role of financial education. Journal of Financial Counseling and Planning, 32 (2), 266 – 279. https://doi.org/10.1891/JFCP-19-00002</bibtext> </blist> <blist> <bibtext> Korankye, T., & Guillemette, M. (2021). Student debt and stock-ownership decisions of US households. Applied Economics Letters, 28 (5), 387 – 390. https://doi.org/10.1080/13504851.2020.1757026</bibtext> </blist> <blist> <bibtext> Korankye, T., & Kalenkoski, C. M. (2021). The effect of households' student debt on life satisfaction. Journal of Family and Economic Issues, 1 – 16. https://doi.org/10.1007/S10834-021-09753-9</bibtext> </blist> <blist> <bibtext> Lee, J. M., Kim, K. T., & Hong, E. J. (2018). Exploring financial burdens of student loan holders in the United States. Family and Consumer Sciences Research Journal, 46 (4), 347 – 362. https://doi.org/10.1111/FCSR.12261</bibtext> </blist> <blist> <bibtext> Manton, E., & English, D. (2002). Do recent college graduates regret the amount of funds borrowed for educational purposes?. Education, 123 (1), 82 – 89.</bibtext> </blist> <blist> <bibtext> Mountain, T. P., Cao, X., Kim, N., & Gutter, M. S. (2020). Millennials' future homeownership and the role of student loan debt. Family and Consumer Sciences Research Journal, 49 (1), 5 – 23. https://doi.org/10.1111/FCSR.12374</bibtext> </blist> <blist> <bibtext> Nettleton, S., & Burrows, R. (1998). Mortgage debt, insecure home ownership and health: An exploratory analysis. Sociology of Health & Illness, 20 (5), 731 – 753. https://doi.org/10.1111/1467-9566.00127</bibtext> </blist> <blist> <bibtext> Osika Friberg, I., Krantz, G., Määttä, S., & Järbrink, K. (2016). Sex differences in health care service usage in Sweden: A register-based cross-sectional study. Scandinavian Journal of Public Health, 44 (3), 264 – 273. https://doi.org/10.1177/1403494815618843</bibtext> </blist> <blist> <bibtext> Pearson, B. (2020). Demographic variations in the perception of the investment services offered by financial advisors. Journal of Accounting and Finance, 20 (3), 127 – 139. https://doi.org/10.33423/jaf.v20i3.3014</bibtext> </blist> <blist> <bibtext> Pearson, B., & Guillemette, M. (2020). The association between financial risk and retirement satisfaction. Financial Services Review, 28 (4), 341 – 350.</bibtext> </blist> <blist> <bibtext> Pearson, B., & Kalenkoski, C. M. (2022). The association between retiree migration and retirement satisfaction. Journal of Financial Counseling and Planning, 33 (1), 56 – 65. <ulink href="http://doi.org/10.1891/JFCP-20-00064">http://doi.org/10.1891/JFCP-20-00064</ulink></bibtext> </blist> <blist> <bibtext> Pearson, B., Korankye, T., & Salehi, H. (2021). Comparative advantage in the household: Should one person specialize in a household's financial matters?. Journal of Family and Economic Issues, 1 – 11. https://doi.org/10.1007/s10834-021-09807-y</bibtext> </blist> <blist> <bibtext> Pearson, B., & Lacombe, D. (2021). The relationship between home equity and retirement satisfaction. Journal of Personal Finance, 20 (1), 40 – 51.</bibtext> </blist> <blist> <bibtext> Pevalin, D. J. (2007). Socio-economic inequalities in health and service utilization in the London Borough of Newham. Public health, 121 (8), 596 – 602. https://doi.org/10.1016/J.PUHE.2006.12.015</bibtext> </blist> <blist> <bibtext> Potter, D., Jayne, D., & Britt, S. (2020). Financial anxiety among college students: The role of generational status. Journal of Financial Counseling and Planning, 31 (2), 284 – 295. https://doi.org/10.1891/jfcp-17-00033</bibtext> </blist> <blist> <bibtext> Robb, C. A., Chatterjee, S., Porto, N., & Cude, B. J. (2019). The influence of student loan debt on financial satisfaction. Journal of Family and Economic Issues, 40 (1), 51 – 73. https://doi.org/10.1007/S10834-018-9599-Y</bibtext> </blist> <blist> <bibtext> Sauerborn, R., Nougtara, A., & Latimer, E. (1994). The elasticity of demand for health care in Burkina Faso: Differences across age and income groups. Health Policy and Planning, 9 (2), 185 – 192. https://doi.org/10.1093/HEAPOL/9.2.185</bibtext> </blist> <blist> <bibtext> Schuerger, N., Klein, E., Hapfelmeier, A., Kiechle, M., Brambs, C., & Paepke, D. (2019). Evaluating the demand for integrative medicine practices in breast and gynecological cancer patients. Breast Care, 14 (1), 35 – 40. https://doi.org/10.1159/000492235</bibtext> </blist> <blist> <bibtext> Wagstaff, A. (1986). The demand for health: Some new empirical evidence. Journal of Health Economics, 5 (3), 195 – 233. https://doi.org/10.1016/0167-6296(86)90015-9</bibtext> </blist> <blist> <bibtext> Walsemann, K. M., Gee, G. C., & Gentile, D. (2015). Sick of our loans: Student borrowing and the mental health of young adults in the United States. Social Science & Medicine, 124, 85 – 93. https://doi.org/10.1016/j.socscimed.2014.11.027</bibtext> </blist> </ref> <aug> <p>By Blain Pearson and Jae Min Lee</p> <p>Reported by Author; Author</p> </aug> <nolink nlid="nl1" bibid="bib32" firstref="ref2"></nolink> <nolink nlid="nl2" bibid="bib39" firstref="ref3"></nolink> <nolink nlid="nl3" bibid="bib20" firstref="ref4"></nolink> <nolink nlid="nl4" bibid="bib18" firstref="ref5"></nolink> <nolink nlid="nl5" bibid="bib40" firstref="ref6"></nolink> <nolink nlid="nl6" bibid="bib47" firstref="ref7"></nolink> <nolink nlid="nl7" bibid="bib36" firstref="ref8"></nolink> <nolink nlid="nl8" bibid="bib34" firstref="ref9"></nolink> <nolink nlid="nl9" bibid="bib37" firstref="ref10"></nolink> <nolink nlid="nl10" bibid="bib35" firstref="ref13"></nolink> <nolink nlid="nl11" bibid="bib50" firstref="ref14"></nolink> <nolink nlid="nl12" bibid="bib13" firstref="ref15"></nolink> <nolink nlid="nl13" bibid="bib38" firstref="ref16"></nolink> <nolink nlid="nl14" bibid="bib43" firstref="ref17"></nolink> <nolink nlid="nl15" bibid="bib25" firstref="ref19"></nolink> <nolink nlid="nl16" bibid="bib21" firstref="ref20"></nolink> <nolink nlid="nl17" bibid="bib53" firstref="ref21"></nolink> <nolink nlid="nl18" bibid="bib46" firstref="ref25"></nolink> <nolink nlid="nl19" bibid="bib10" firstref="ref26"></nolink> <nolink nlid="nl20" bibid="bib14" firstref="ref27"></nolink> <nolink nlid="nl21" bibid="bib17" firstref="ref28"></nolink> <nolink nlid="nl22" bibid="bib29" firstref="ref29"></nolink> <nolink nlid="nl23" bibid="bib41" firstref="ref30"></nolink> <nolink nlid="nl24" bibid="bib23" firstref="ref31"></nolink> <nolink nlid="nl25" bibid="bib24" firstref="ref32"></nolink> <nolink nlid="nl26" bibid="bib26" firstref="ref36"></nolink> <nolink nlid="nl27" bibid="bib49" firstref="ref37"></nolink> <nolink nlid="nl28" bibid="bib54" firstref="ref38"></nolink> <nolink nlid="nl29" bibid="bib30" firstref="ref41"></nolink> <nolink nlid="nl30" bibid="bib31" firstref="ref43"></nolink> <nolink nlid="nl31" bibid="bib19" firstref="ref44"></nolink> <nolink nlid="nl32" bibid="bib33" firstref="ref45"></nolink> <nolink nlid="nl33" bibid="bib42" firstref="ref46"></nolink> <nolink nlid="nl34" bibid="bib48" firstref="ref47"></nolink> <nolink nlid="nl35" bibid="bib51" firstref="ref48"></nolink> <nolink nlid="nl36" bibid="bib15" firstref="ref50"></nolink> <nolink nlid="nl37" bibid="bib22" firstref="ref51"></nolink> <nolink nlid="nl38" bibid="bib45" firstref="ref52"></nolink> <nolink nlid="nl39" bibid="bib16" firstref="ref53"></nolink> <nolink nlid="nl40" bibid="bib52" firstref="ref54"></nolink> <nolink nlid="nl41" bibid="bib27" firstref="ref56"></nolink> <nolink nlid="nl42" bibid="bib44" firstref="ref57"></nolink> <nolink nlid="nl43" bibid="bib28" firstref="ref60"></nolink> <nolink nlid="nl44" bibid="bib12" firstref="ref61"></nolink> <nolink nlid="nl45" bibid="bib11" firstref="ref65"></nolink>
CustomLinks:
  – Url: https://eric.ed.gov/contentdelivery/servlet/ERICServlet?accno=EJ1383266
    Name: ERIC Full Text
    Category: fullText
    Text: Full Text from ERIC
Header DbId: eric
DbLabel: ERIC
An: EJ1383266
AccessLevel: 3
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Student Debt and Healthcare Service Usage
– Name: Language
  Label: Language
  Group: Lang
  Data: English
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Pearson%2C+Blain%22">Pearson, Blain</searchLink><br /><searchLink fieldCode="AR" term="%22Lee%2C+Jae+Min%22">Lee, Jae Min</searchLink>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="SO" term="%22Journal+of+Financial+Counseling+and+Planning%22"><i>Journal of Financial Counseling and Planning</i></searchLink>. 2022 33(2):183-193.
– Name: Avail
  Label: Availability
  Group: Avail
  Data: Association for Financial Counseling and Planning Education. 1500 West Third Avenue Suite 223, Columbus, OH 43212. Tel: 614-485-9650; Fax: 614-485-9621; Web site: https://connect.springerpub.com/content/sgrjfcp
– Name: PeerReviewed
  Label: Peer Reviewed
  Group: SrcInfo
  Data: Y
– Name: Pages
  Label: Page Count
  Group: Src
  Data: 11
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2022
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<br />Reports - Research
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Debt+%28Financial%29%22">Debt (Financial)</searchLink><br /><searchLink fieldCode="DE" term="%22Access+to+Health+Care%22">Access to Health Care</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Loan+Programs%22">Student Loan Programs</searchLink><br /><searchLink fieldCode="DE" term="%22Correlation%22">Correlation</searchLink><br /><searchLink fieldCode="DE" term="%22Health+Behavior%22">Health Behavior</searchLink><br /><searchLink fieldCode="DE" term="%22Health+Insurance%22">Health Insurance</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Characteristics%22">Student Characteristics</searchLink>
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 1052-3073<br />1947-7910
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: This study investigated the association between student debt and healthcare service usage utilizing pooled data collected from the 2015 to 2018 waves of the National Financial Capability Study. The findings of this study suggest that, when compared to those without student debt, student debt holders have a lower likelihood of filling prescriptions for medicine, going to a doctor or clinic when they have a medical problem, and going to medical tests, treatments, and follow-up appointments. The findings and ensuing discussion add to the mounting evidence of the many challenges associated with student debt repayment.
– Name: AbstractInfo
  Label: Abstractor
  Group: Ab
  Data: As Provided
– Name: DateEntry
  Label: Entry Date
  Group: Date
  Data: 2023
– Name: AN
  Label: Accession Number
  Group: ID
  Data: EJ1383266
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1383266
RecordInfo BibRecord:
  BibEntity:
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 11
        StartPage: 183
    Subjects:
      – SubjectFull: Debt (Financial)
        Type: general
      – SubjectFull: Access to Health Care
        Type: general
      – SubjectFull: Student Loan Programs
        Type: general
      – SubjectFull: Correlation
        Type: general
      – SubjectFull: Health Behavior
        Type: general
      – SubjectFull: Health Insurance
        Type: general
      – SubjectFull: Student Characteristics
        Type: general
    Titles:
      – TitleFull: Student Debt and Healthcare Service Usage
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Pearson, Blain
      – PersonEntity:
          Name:
            NameFull: Lee, Jae Min
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2022
          Identifiers:
            – Type: issn-print
              Value: 1052-3073
            – Type: issn-electronic
              Value: 1947-7910
          Numbering:
            – Type: volume
              Value: 33
            – Type: issue
              Value: 2
          Titles:
            – TitleFull: Journal of Financial Counseling and Planning
              Type: main
ResultId 1