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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Int J Public Health</journal-id>
<journal-title>International Journal of Public Health</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Int J Public Health</abbrev-journal-title>
<issn pub-type="epub">1661-8564</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="publisher-id">1605325</article-id>
<article-id pub-id-type="doi">10.3389/ijph.2023.1605325</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Public Health Archive</subject>
<subj-group>
<subject>Original Article</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Inequalities in the Access to Health Services Among Older Migrants: Evidence From the China Migrant Dynamic Monitoring Survey</article-title>
<alt-title alt-title-type="left-running-head">Long et al.</alt-title>
<alt-title alt-title-type="right-running-head">Vulnerable Older Migrant Workers</alt-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Long</surname>
<given-names>Chengxu</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Chen</surname>
<given-names>Fangfei</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Ye</surname>
<given-names>Yisheng</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Ji</surname>
<given-names>Lu</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Xu</surname>
<given-names>Xinyin</given-names>
</name>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Tang</surname>
<given-names>Shangfeng</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="corresp" rid="c001">&#x2a;</xref>
<uri xlink:href="https://loop.frontiersin.org/people/996349/overview"/>
</contrib>
</contrib-group>
<aff id="aff1">
<sup>1</sup>
<institution>School of Medicine and Health Management</institution>, <institution>Tongji Medical College</institution>, <institution>Huazhong University of Science and Technology</institution>, <addr-line>Wuhan</addr-line>, <country>China</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Department of Global Health and Social Medicine</institution>, <institution>School of Global Affairs</institution>, <institution>Faculty of Social Science and Public Policy</institution>, <institution>King&#x2019;s College London</institution>, <addr-line>London</addr-line>, <country>United Kingdom</country>
</aff>
<aff id="aff3">
<sup>3</sup>
<institution>Department of Health Service and Population Research</institution>, <institution>Institute of Psychiatry, Psychology and Neuroscience</institution>, <institution>King&#x2019;s College London</institution>, <addr-line>London</addr-line>, <country>United Kingdom</country>
</aff>
<aff id="aff4">
<sup>4</sup>
<institution>Department of Chronic Noncommunicable Disease Control and Prevention</institution>, <institution>Sichuan Center for Disease Control and Prevention</institution>, <addr-line>Chengdu</addr-line>, <country>China</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>
<bold>Edited by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1046709/overview">Afona Chernet</ext-link>, Swiss Tropical and Public Health Institute, Switzerland</p>
</fn>
<fn fn-type="edited-by">
<p>
<bold>Reviewed by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1041264/overview">Hyo Lee</ext-link>, Dongseo University, Republic of Korea</p>
</fn>
<corresp id="c001">&#x2a;Correspondence: Shangfeng Tang, <email>sftang2018@hust.edu.cn</email>
</corresp>
<fn fn-type="other" id="fn001">
<p>This Original Article is part of the IJPH Special Issue &#x201c;Migration Health Around the Globe&#x2014;A Construction Site With Many Challenges&#x201d;</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>07</day>
<month>04</month>
<year>2023</year>
</pub-date>
<pub-date pub-type="collection">
<year>2023</year>
</pub-date>
<volume>68</volume>
<elocation-id>1605325</elocation-id>
<history>
<date date-type="received">
<day>16</day>
<month>08</month>
<year>2022</year>
</date>
<date date-type="accepted">
<day>28</day>
<month>03</month>
<year>2023</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2023 Long, Chen, Ye, Ji, Xu and Tang.</copyright-statement>
<copyright-year>2023</copyright-year>
<copyright-holder>Long, Chen, Ye, Ji, Xu and Tang</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<p>
<bold>Objectives:</bold> To identify differences in healthcare use between older migrant workers (OMWs) and older migrants (OMs) and explore associated factors and paths of healthcare use.</p>
<p>
<bold>Methods:</bold> The data came from the 2015 China Migrant Dynamic Monitoring Survey (CMDMS). CMDMS used a multi-stage stratified probability proportionate to size method as the sampling technique and conducted a desk review. The samples include OMWs, OMs for caring offspring (N &#x3d; 4,439), and OMs for receiving care from family (N &#x3d; 4,184). We built logistic regression and path analysis models to analyze the data.</p>
<p>
<bold>Results:</bold> Social health insurance (SHI) in current place of residence is associated with less expenditure among all subgroups. OMWs and OMs for receiving care from family with SHI in current place of residence are more likely to use healthcare.</p>
<p>
<bold>Conclusion:</bold> OMWs are particularly vulnerable in healthcare use and socioeconomic status. Having SHI registered in current place of residence helps decrease expenditure among OMs. We urge policymakers to consider a united health financing scheme across OMWs and other urban employees and streamline policies for migrants to enroll in SHI in current place of residence.</p>
</abstract>
<kwd-group>
<kwd>rural-to-urban migrants</kwd>
<kwd>older migrant workers</kwd>
<kwd>access to health services</kwd>
<kwd>social health insurance</kwd>
<kwd>health equity</kwd>
</kwd-group>
<contract-num rid="cn001">2022YFE0133000</contract-num>
<contract-num rid="cn002">72004073</contract-num>
<contract-num rid="cn003">20YJC630134</contract-num>
<contract-sponsor id="cn001">National Science and Technology Major Project<named-content content-type="fundref-id">10.13039/501100018537</named-content>
</contract-sponsor>
<contract-sponsor id="cn002">National Natural Science Foundation of China<named-content content-type="fundref-id">10.13039/501100001809</named-content>
</contract-sponsor>
<contract-sponsor id="cn003">Humanities and Social Science Fund of Ministry of Education of China<named-content content-type="fundref-id">10.13039/501100013139</named-content>
</contract-sponsor>
</article-meta>
</front>
<body>
<sec sec-type="intro" id="s1">
<title>Introduction</title>
<p>The global community has been concerned with the rising prevalence of migrants and population aging. Migrants form a growing proportion of the population in many countries. The economic, social, and cultural differences that exist in the gap between the urban area and rural area inspire rural-to-urban migrants to transfer from agriculture to industry (<xref ref-type="bibr" rid="B1">1</xref>). In low- and middle-income countries (LMICs), rural surplus labor&#x2019;s migration to cities has been fuelled by the rapid progress of urbanization (<xref ref-type="bibr" rid="B2">2</xref>). Rapid aging is expected to put new pressure on the migrant issue. Although older migrants (OMs) have worse health status and higher health needs, due to low socioeconomic status and existing policies which create barriers to accessing public welfare benefits, older rural-to-urban migrants are particularly vulnerable to healthcare access and at an increased risk of insufficient receipt of health services (<xref ref-type="bibr" rid="B3">3</xref>).</p>
<p>As time goes by, rural-to-urban migrant Chinese workers, a crucial portion of labor, are facing the stage of aging and have transited to a special labor group in the last 2&#xa0;decades, namely, older migrant workers (OMWs). In China, the coverage and benefits of health insurance programs are not varied by the subgroups of OMs but vary across rural and urban areas (<xref ref-type="bibr" rid="B4">4</xref>). Due to low socioeconomic status and poor working conditions, OMWs may be at a higher risk of unmet health needs (<xref ref-type="bibr" rid="B5">5</xref>). Urban health financing schemes provide higher reimbursement rates than the rural health insurance scheme (<xref ref-type="bibr" rid="B6">6</xref>). Health and the availability of health services are highly variable between rural-to-urban migrants and urban employees (<xref ref-type="bibr" rid="B7">7</xref>). Although the health services coverage within health financing models was extended in the 2019 medical reform (<xref ref-type="bibr" rid="B8">8</xref>), the gap between rural and urban health insurance schemes still exists: the co-payment for Urban Employee Insurance (UEI) beneficiaries (24.4%) was still lower than the Urban-Rural Resident Medical Insurance (URRMI) which covers rural and urban residents without formal employment (40.3%) (<xref ref-type="bibr" rid="B9">9</xref>). A large number of rural-to-urban migrants usually register in their place of origin rather than their current place of residence, who are covered by URRMI or the rural health insurance scheme and excluded from UEI (<xref ref-type="bibr" rid="B10">10</xref>); this may be even worse for OMWs. Chinese OMWs often experience significant access barriers to healthcare as their insurance program usually only reimburses health visits that take place in their hometown (<xref ref-type="bibr" rid="B11">11</xref>).</p>
<p>The National Health Commission in China (<xref ref-type="bibr" rid="B12">12</xref>) stated that OMWs, OMs for looking after offspring, and OMs for receiving care from family constituted the main three subgroups of OM. Researchers have used the China Migrant Dynamic Monitoring Survey to investigate the association between these three reasons for migration and healthcare use with this dataset (<xref ref-type="bibr" rid="B13">13</xref>), but they did not go far into the details of the differences among these three subgroups and the pathways of associated factors on healthcare use. Simultaneously, compare with other OMs, OMWs have the dual characteristics of the older population and migrant workers (<xref ref-type="bibr" rid="B14">14</xref>), which means they are more inherently disadvantaged and at higher risk of social inequities (<xref ref-type="bibr" rid="B13">13</xref>). Therefore, they may face greater challenges in access to health services. These barriers to accessing health services could adversely affect the wellbeing and health outcomes of OMWs (<xref ref-type="bibr" rid="B15">15</xref>, <xref ref-type="bibr" rid="B16">16</xref>). In addition, although multiple studies have documented migrant workers&#x2019; barriers to accessing public services, there is scant research examining the inequalities in access to healthcare between OMWs and other OMs (<xref ref-type="bibr" rid="B17">17</xref>&#x2013;<xref ref-type="bibr" rid="B19">19</xref>). Moreover, prior studies had not specified the paths of how the SHI registration place is associated with health services use across different OMs.</p>
<p>Therefore, this study aims to examine the differences in health services use among OMWs and other OMs (for looking after offspring and for receiving care from family) and explore the associated factors and paths of using health services use among subgroup OMs. Given that there has been an increase in migrants both within countries and internationally, targeted measures will shed light on the global community and inform policymakers who face similar challenges. Empirical strategies based on the differences among subgroups will contribute to identifying the vulnerable population and improving the accessibility of care delivery. The analyses of associated factors and paths offer insights to understand the relationship between health services use and the SHI registration place. Based on the above discussion, this study aims to answer two research questions as followed:<list list-type="simple">
<list-item>
<p>1) Are there differences in health services use between OMWs and other OMs?</p>
</list-item>
<list-item>
<p>2) What is the relationship between the registration place of SHI and health services use among OMWs and other OMs?</p>
</list-item>
</list>
</p>
<sec id="s1-1">
<title>Conceptual Framework</title>
<p>Anderson&#x2019;s Behavioral model (ABM) focuses on explaining the individual and contextual determinants of healthcare utilization (<xref ref-type="bibr" rid="B20">20</xref>), which serves as a conceptual framework for our study to investigate the impact of SHI on healthcare use among OMs. Visiting doctors is suggested as the proxy for healthcare use to assess the availability of care delivery, illustrating whether the individual&#x2019;s health needs are met (<xref ref-type="bibr" rid="B21">21</xref>). Andersen and Newman&#x2019;s seminal model (<xref ref-type="bibr" rid="B20">20</xref>) proposed three major components of the determinants of healthcare use: predisposing, enabling, and need factors.</p>
<p>First, predisposing factors refer to the characteristics indicating the propensity for receiving healthcare, such as age and migration duration. Second, enabling factors refer to the conditions that enable individuals to seek healthcare (<xref ref-type="bibr" rid="B20">20</xref>). Health insurance is an essential enabling factor for health services use. Insurance coverage supplies financial resources which enable migrants to access health services and facilitate the receipt of care when needed (<xref ref-type="bibr" rid="B22">22</xref>). SHI in China plays a critical role in reducing financial barriers to accessing needed services and alleviating the economic burden of disease (<xref ref-type="bibr" rid="B22">22</xref>). The association between insurance and healthcare use may differ by the services coverage and co-payment. Rural-urban area of residence is another enabling factor critical for healthcare use highlighted by previous research (<xref ref-type="bibr" rid="B20">20</xref>). As noted in the Case Study, the insurance benefits differ across urban and urban health insurance programs. Additionally, health expenditures also indicate the individual&#x2019;s capability to fend off the negative influences from other stressors on health status and the resources that enable individuals to seek healthcare (<xref ref-type="bibr" rid="B20">20</xref>). However, excessive expenditures would adversely affect health services use, especially for patients from low socioeconomic backgrounds (<xref ref-type="bibr" rid="B23">23</xref>). Insured older adults are less worried about health expenditure and have a higher receipt of care compared with the uninsured (<xref ref-type="bibr" rid="B24">24</xref>). Third, need factors, i.e., perceived and evaluated illness, capture the immediate cause of healthcare use (<xref ref-type="bibr" rid="B20">20</xref>). As individuals&#x2019; health status go worse, they are more likely to have greater health needs. Self-assessed health, which indicates the individual&#x2019;s subjective assessment, is categorized as a need factor and used as the control variable in this study.</p>
</sec>
<sec id="s1-2">
<title>Case Study of China</title>
<p>This study chooses China as the case study country as China has developed a population management scheme based on household registration and an established SHI scheme (<xref ref-type="bibr" rid="B25">25</xref>). Previous research has identified better employment opportunities as a key reason for migration when economic disparities in earnings and livelihoods manifest (<xref ref-type="bibr" rid="B26">26</xref>). Simultaneously, existing literature supports social and cultural motivations behind migrations, such as family ethics, health needs, and social network (<xref ref-type="bibr" rid="B27">27</xref>).</p>
<p>In China, prices and healthcare quality control do vary between OMWs and other OMs, but inequalities in benefits exist across OMs insured through the urban and rural health insurance schemes (<xref ref-type="bibr" rid="B6">6</xref>). The SHI in China includes the New Rural Cooperative Medical Scheme (NCMS), Urban Resident Insurance (URI), and Urban Employee Insurance (UEI). Altogether these schemes cover rural residents, urban employees, and urban residents who do not have formal employment (<xref ref-type="bibr" rid="B28">28</xref>). Since 2016, the Urban-Rural Resident Medical Insurance (URRMI) was implemented in stages by combing URI and NCMS (<xref ref-type="bibr" rid="B28">28</xref>); however, this did not change the fact that the urban health financing program, UEI, provides higher reimbursement rates than URRMI (<xref ref-type="bibr" rid="B6">6</xref>). Similarly, China carried out a new round of medical reform in 2019, which raised the government subsidy and services coverage for the insured and extend the coverage of the direct reimbursement for seeking cross-province inpatient services healthcare (<xref ref-type="bibr" rid="B8">8</xref>). However, the co-payment of inpatient services for UEI beneficiaries was still much lower than those enlisted in URRMI (24.4% vs. 40.3%) (<xref ref-type="bibr" rid="B9">9</xref>).</p>
<p>One crucial objective of this study is to examine whether visiting doctors during times of illness among OMs with SHI in their current place of residence is different from those without. SHI in the current place of residence here refers to two health insurance schemes in urban areas: URRMI registered in the urban area and UEI. The &#x201c;territorial principle&#x201d; has been the primary principle of population management policy in China&#x2014;residents were under localized management in the registration area (<xref ref-type="bibr" rid="B29">29</xref>). SHI was also under localized management in the registration area. Although URRMI covers both rural and urban residents, the majority of rural-to-urban migrants enlisted in URRMI are registered in their hometowns&#x2014;mostly rural areas (<xref ref-type="bibr" rid="B13">13</xref>). To enroll in URRMI in the current place of residence, they need to hold a non-agricultural <italic>Hukou</italic> (<xref ref-type="bibr" rid="B30">30</xref>). Furthermore, the UEI enrolment conditions mainly involve having formal employment and a non-agricultural <italic>Hukou</italic> (<xref ref-type="bibr" rid="B4">4</xref>). Even if these criteria have been met, rural-to-urban migrants need to go through a complex and time-consuming before enrolling in SHI in the current place of residence. Therefore, a large number of rural-to-urban OMs usually register in their place of origin rather than their current place of residence. A piece of research shows that, in China, a considerable proportion of OMs, especially for OMWs, are still covered by SHI registered in rural areas and benefit less than urban residents, which results in insufficient receipts of needed healthcare (<xref ref-type="bibr" rid="B29">29</xref>).</p>
</sec>
</sec>
<sec sec-type="methods" id="s2">
<title>Methods</title>
<sec id="s2-1">
<title>Data and Sample</title>
<p>Data are drawn from the 2015 wave of the China Migrant Dynamic Monitoring Survey (CMDMS) (<xref ref-type="bibr" rid="B31">31</xref>). CMDMS is a nationally representative interview survey of internal migrants in China, which. aims to investigate the health, healthcare, migration, and demographic information of people migrating within China (<xref ref-type="bibr" rid="B32">32</xref>, <xref ref-type="bibr" rid="B33">33</xref>). This survey used the multi-stage stratified probability proportionate to size (<xref ref-type="bibr" rid="B13">13</xref>) method as the sampling technique (<xref ref-type="bibr" rid="B13">13</xref>), with a highly representative of national migrant data in China. Based on the PPS sampling technique, CMDMS selected communities and cities from 32 provincial-level units in China; then, this survey randomly recruited individuals in the selected communities (<xref ref-type="bibr" rid="B13">13</xref>). CMDMS has conducted the desk review and this sampling strategy was compiled based on the migrant statistics in the 2014 annual report of the China National Health Commission and the latest statistics of each provincial health commission (<xref ref-type="bibr" rid="B31">31</xref>).</p>
<p>The latest CMDMS specifically targeted OMs was merely conducted in 2015, and there is no alternative for nationally representative surveys on OMs in China. The 2015 CMDMS collected information on socio-demographic characteristics, health, and health services use among older people within migrating families. As noted before, the gap in coverage and benefits between rural and urban health insurance schemes still exists after the 2019 medical reform (<xref ref-type="bibr" rid="B9">9</xref>). Prior studies (<xref ref-type="bibr" rid="B34">34</xref>, <xref ref-type="bibr" rid="B35">35</xref>) also used this 2015 dataset to investigate the relationship between health insurance, household registration, and health services use among OMs in China after the 2019 medical reform. In this regard, 2015 nationally representative CMDMS may be the most available dataset for research on Chinese OMs and well serves our aim of this study. Hence, we draw the data from the 2015 CMDMS dataset and the sample encompasses individuals who were aged above 60&#xa0;years and migrated within the mainland of China. Guided by a report from the China National Health Commission (<xref ref-type="bibr" rid="B12">12</xref>), looking after offspring, seeking better employment opportunities, and to live close to their adult children constitute the main reasons for migration among older migrants. Prior research also investigated the healthcare use among Chinese OMs across these reasons for migration (<xref ref-type="bibr" rid="B13">13</xref>). In addition, as noted in the introduction, OMWs could be particularly vulnerable among the subgroups. Therefore, we divided the subjects into three categories: OMs for better employment opportunities (OMW, N &#x3d; 3,050), OM for looking after children (N &#x3d; 4,439), and OMs for receiving care from family (N &#x3d; 4,184). <xref ref-type="table" rid="T1">Table 1</xref> summarized the weighted statistics summary.</p>
<table-wrap id="T1" position="float">
<label>TABLE 1</label>
<caption>
<p>Weighted descriptive statistics of older migrants (China. 2015).</p>
</caption>
<table>
<thead valign="top">
<tr>
<th rowspan="2" align="left">Variables</th>
<th align="center">OMWs</th>
<th align="center">OMs for looking after offspring</th>
<th align="center">OMs for receiving care from family</th>
</tr>
<tr>
<th colspan="3" align="center">Mean (SD)/Percentages</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">Visiting doctors (%)</td>
<td align="center">42.22%</td>
<td align="center">53.58%</td>
<td align="center">53.17%</td>
</tr>
<tr>
<td align="left">SHI in current place of residence</td>
<td align="center">9.99%</td>
<td align="center">4.02%</td>
<td align="center">7.15%</td>
</tr>
<tr>
<td align="left">Age (years old)</td>
<td align="center">63.62 (0.12)</td>
<td align="center">65.30 (0.12)</td>
<td align="center">70.18 (0.25)</td>
</tr>
<tr>
<td align="left">Male (%)</td>
<td align="center">72.11%</td>
<td align="center">43.18%</td>
<td align="center">48.47%</td>
</tr>
<tr>
<td colspan="4" align="left">Highest educational level (%)</td>
</tr>
<tr>
<td align="left">&#x2003;No education</td>
<td align="center">14.25%</td>
<td align="center">17.74%</td>
<td align="center">22.11%</td>
</tr>
<tr>
<td align="left">&#x2003;Primary/secondary education</td>
<td align="center">74.96%</td>
<td align="center">65.3%</td>
<td align="center">57.39%</td>
</tr>
<tr>
<td align="left">&#x2003;High school or above</td>
<td align="center">10.79%</td>
<td align="center">16.96%</td>
<td align="center">20.51%</td>
</tr>
<tr>
<td align="left">MHEPA (CNY)</td>
<td align="center">1040.30 (24.28)</td>
<td align="center">1396.35 (24.44)</td>
<td align="center">1274.72 (33.41)</td>
</tr>
<tr>
<td colspan="4" align="left">Marital status (%)</td>
</tr>
<tr>
<td align="left">&#x2003;Unmarried</td>
<td align="center">0.62%</td>
<td align="center">0.05%</td>
<td align="center">0.17%</td>
</tr>
<tr>
<td align="left">&#x2003;Married</td>
<td align="center">92.00%</td>
<td align="center">81.53%</td>
<td align="center">73.05%</td>
</tr>
<tr>
<td align="left">&#x2003;Divorced/widowed</td>
<td align="center">7.38%</td>
<td align="center">18.42%</td>
<td align="center">26.78%</td>
</tr>
<tr>
<td align="left">&#x2003;Migration duration (years)</td>
<td align="center">7.74 (0.22)</td>
<td align="center">5.77 (0.13)</td>
<td align="center">6.80 (0.17)</td>
</tr>
<tr>
<td colspan="4" align="left">Self-assessed health (%)</td>
</tr>
<tr>
<td align="left">&#x2003;Healthy</td>
<td align="center">63.08%</td>
<td align="center">53.99%</td>
<td align="center">37.53%</td>
</tr>
<tr>
<td align="left">&#x2003;Generally healthy</td>
<td align="center">32.37%</td>
<td align="center">41.77%</td>
<td align="center">45.88%</td>
</tr>
<tr>
<td align="left">&#x2003;Unhealthy but can self-care</td>
<td align="center">4.26%</td>
<td align="center">4.13%</td>
<td align="center">13.55%</td>
</tr>
<tr>
<td align="left">&#x2003;Cannot self-care</td>
<td align="center">0.29%</td>
<td align="center">0.11%</td>
<td align="center">3.04%</td>
</tr>
<tr>
<td align="left">
<italic>N</italic>
</td>
<td align="center">3,050</td>
<td align="center">4,439</td>
<td align="center">4,184</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>OMW, older migrant workers; OM, older migrants; SHI, social health insurance; SD, standard deviation; MHEPA, monthly household expenditure <italic>per capita</italic>. Percentages are shown for categorical variables, and Mean is shown for continuous variables. Migrant Dynamic Monitoring Survey, China, 2015.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s2-2">
<title>Variables</title>
<p>Based on existing literature and data availability (<xref ref-type="bibr" rid="B13">13</xref>, <xref ref-type="bibr" rid="B32">32</xref>), the outcome of interest is visiting doctors. CMDMS collected information on this variable by asking: &#x201c;How do you deal with the illness when you are sick.&#x201d; This study aggregated this answer to create a dichotomized variable (visiting doctors): coded as 1 &#x3d; yes (visiting doctors) and 0 &#x3d; no (no medical treatment/self-treatment) (<xref ref-type="bibr" rid="B36">36</xref>). The key variable of interest is SHI in the current place of residence, a dichotomized variable coded as 1 &#x3d; yes (SHI registered in the current place of residence), 0 &#x3d; no (SHI registered in hometown/else areas).</p>
<p>Regarding the binary logistic regression analyses, this study controlled for a set of variables: age, gender, highest educational level, monthly household expenditure <italic>per capita</italic> (MHEPA), marriage, migration duration, and self-rated health status. Age is a categorical variable, coded as 1 &#x3d; 60&#x2013;70&#xa0;years, 2 &#x3d; 70&#x2013;80&#xa0;years, and 3 &#x3d; 80&#xa0;years or above (the reference group). Gender is a binary variable with &#x201c;female&#x201d; set as the reference category. The highest educational level is a categorial variable: no formal education (the reference group), primary or secondary education, and high school or above. Marriage has three categories: unmarried, married (the reference group), and divorced/widowed. MHEPA is a continuous variable, and we winsorized this variable in 0.5% quantile on both sides to rule out the impact of the extreme values and then logarithmically transformed it. Migrating duration is a continuous variable measured by years, winsorized in 0.5% quantile on both sides. Self-rated health is a categorical variable, coded as 1 &#x3d; healthy, 2 &#x3d; generally healthy, 3 &#x3d; unhealthy but can self-care, and 4 &#x3d; cannot self-care.</p>
<p>Based on the results of binary logistic models and existing literature (<xref ref-type="bibr" rid="B13">13</xref>, <xref ref-type="bibr" rid="B32">32</xref>, <xref ref-type="bibr" rid="B37">37</xref>), the measurement in path analysis models involves visiting doctors, age, monthly household expenditure <italic>per capita</italic> (MHEPA), migrating duration, and self-rated health status.</p>
</sec>
<sec id="s2-3">
<title>Statistical Analysis</title>
<p>To explore the first research question, individual weights with non-respondent adjustment were applied for the sample statistics of visiting doctors among the three subgroups. To answer the second research question, firstly, this study employed binary logistic regression models to identify the associated factors of visiting doctors as the following equation:<disp-formula id="equ1">
<mml:math id="m1">
<mml:mrow>
<mml:mi mathvariant="normal">y</mml:mi>
<mml:mo>&#x3d;</mml:mo>
<mml:mi mathvariant="normal">l</mml:mi>
<mml:mi mathvariant="normal">o</mml:mi>
<mml:mi mathvariant="normal">g</mml:mi>
<mml:mi mathvariant="normal">i</mml:mi>
<mml:mi mathvariant="normal">t</mml:mi>
<mml:mrow>
<mml:mfenced open="(" close=")" separators="&#x7c;">
<mml:mrow>
<mml:mi mathvariant="normal">p</mml:mi>
</mml:mrow>
</mml:mfenced>
</mml:mrow>
<mml:mo>&#x3d;</mml:mo>
<mml:msub>
<mml:mi mathvariant="normal">&#x3b2;</mml:mi>
<mml:mn>0</mml:mn>
</mml:msub>
<mml:mo>&#x2b;</mml:mo>
<mml:msub>
<mml:mi mathvariant="normal">&#x3b2;</mml:mi>
<mml:mn>1</mml:mn>
</mml:msub>
<mml:mo>&#xd7;</mml:mo>
<mml:msub>
<mml:mi mathvariant="normal">P</mml:mi>
<mml:mi mathvariant="normal">m</mml:mi>
</mml:msub>
<mml:mo>&#x2b;</mml:mo>
<mml:mrow>
<mml:mstyle displaystyle="true">
<mml:msubsup>
<mml:mo>&#x2211;</mml:mo>
<mml:mrow>
<mml:mi mathvariant="normal">m</mml:mi>
<mml:mo>&#x3d;</mml:mo>
<mml:mn>7</mml:mn>
</mml:mrow>
<mml:mi mathvariant="normal">m</mml:mi>
</mml:msubsup>
</mml:mstyle>
<mml:mrow>
<mml:mfenced open="(" close=")" separators="&#x7c;">
<mml:mrow>
<mml:msub>
<mml:mi mathvariant="normal">&#x3b2;</mml:mi>
<mml:mi mathvariant="normal">m</mml:mi>
</mml:msub>
<mml:mo>&#xd7;</mml:mo>
<mml:msub>
<mml:mi mathvariant="normal">C</mml:mi>
<mml:mi mathvariant="normal">m</mml:mi>
</mml:msub>
</mml:mrow>
</mml:mfenced>
</mml:mrow>
</mml:mrow>
</mml:mrow>
</mml:math>
</disp-formula>Where y refers to the probability model of the visiting doctors in a certain exposure of the independent factors. P<sub>m</sub> denotes SHI in the current place of residence. C<sub>m</sub> denotes control variables. &#x3b2;<sub>0</sub> is the constant term. &#x3b2;<sub>m</sub> are the coefficients of the respective regressors.</p>
<p>Based on the results of binary logistic regression analyses, significantly associated factors (SHI in current place of residence, age, MHEPA, migrating duration, and self-rated health status) were involved in the path analysis models. This study performed path analysis models for the three subgroup OMs. We first used path analysis to understand the relationship among the registration place of SHI, visiting doctors, and other variables among OMWs. The second part and the third part used the same path analysis to model the associations among OMs for looking after children and OMs for receiving care from family, respectively. The maximum likelihood method was used in the estimation. As shown in <xref ref-type="table" rid="T1">Table 1</xref>, the criteria to evaluate the model fitness were suggested by Deng Z (<xref ref-type="bibr" rid="B38">38</xref>): a value of &#x3c7;<sup>2</sup>/df less than 3 and the root mean square error of approximation (RMSEA) less than 0.05 denote a well-fitted model for the data; the comparative fit index (CFI), normed fit index (NFI), Tucker-Lewis Coefficient (TLI), and incremental fit index over 0.90 show good fit indexes (<xref ref-type="bibr" rid="B38">38</xref>). Furthermore, to check the robustness of the result, a categorical variable, age, was replaced by a continuous variable measured by years in the three path analysis models.</p>
</sec>
</sec>
<sec sec-type="results" id="s3">
<title>Results</title>
<p>
<xref ref-type="table" rid="T1">Table 1</xref> shows the weighed sample statistics of the three subgroup OMs. The rate of visiting doctors in OMWs (42.22%) was lower than that in OMs for looking after children (53.58%) and OMs for receiving care from family (53.17%). OMWs had a higher proportion of receiving formal education, longer migration duration, being male, married, and healthy than the other two subgroups, whereas OMWs had lower monthly household expenditure <italic>per capita</italic>.</p>
<p>
<xref ref-type="table" rid="T2">Table 2</xref> shows the results of binary logistic models to identify the factors associated with visiting doctors. Having SHI registered in the current place of residence is associated with increased odds of visiting doctors among OMWs and OMs for receiving care from family. In addition, greater monthly household expenditure <italic>per capita</italic> is related to an increased probability of doctor visits, whereas longer migration duration is associated with a decreased occurrence of this seeking health services behavior among OMWs. OMs who migrated to receive care from family and were unable to take care of themselves were less likely to visit doctors when they were sick than their healthy counterparts.</p>
<table-wrap id="T2" position="float">
<label>TABLE 2</label>
<caption>
<p>Binary logistic regression investigating the relationship between social health insurance in registration place of residence and visiting doctors among older migrants (China. 2015).</p>
</caption>
<table>
<thead valign="top">
<tr>
<th rowspan="2" align="left">Variables</th>
<th align="center">OMWs</th>
<th align="center">OMs for looking after children</th>
<th align="center">OMs for receiving care from family</th>
</tr>
<tr>
<th align="center">OR <sup>P</sup> (SE)</th>
<th align="left"/>
<th align="left"/>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">SHI in registration place of residence (Ref: SHI in hometown/other areas)</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;current place of residence</td>
<td align="center">1.76&#x2a;(0.41)</td>
<td align="center">0.77 (0.21)</td>
<td align="center">1.48&#x2a;(0.28)</td>
</tr>
<tr>
<td align="left">Age (Ref: &#x2265;80&#xa0;years old)</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;60&#x2013;70</td>
<td align="center">2.05 (1.92)</td>
<td align="center">0.93 (0.52)</td>
<td align="center">0.96 (0.22)</td>
</tr>
<tr>
<td align="left">&#x2003;70&#x2013;80</td>
<td align="center">2.19 (2.15)</td>
<td align="center">1.09 (0.61)</td>
<td align="center">0.91 (0.20)</td>
</tr>
<tr>
<td align="left">Gender (Ref: female)</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;Male</td>
<td align="center">0.88 (0.15)</td>
<td align="center">1.11 (0.14)</td>
<td align="center">1.09 (0.14)</td>
</tr>
<tr>
<td align="left">Education (Ref: no formal education)</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;Primary or secondary education</td>
<td align="center">1.13 (0.25)</td>
<td align="center">1.15 (0.25)</td>
<td align="center">1.04 (0.23)</td>
</tr>
<tr>
<td align="left">&#x2003;High school or above</td>
<td align="center">2.84&#x2a;&#x2a;(0.89)</td>
<td align="center">1.07 (0.17)</td>
<td align="center">1.00 (0.17)</td>
</tr>
<tr>
<td align="left">&#x2003;MHEPA (CNY)</td>
<td align="center">1.35&#x2a;(0.20)</td>
<td align="center">1.02 (0.12)</td>
<td align="center">1.05 (0.14)</td>
</tr>
<tr>
<td align="left">Marital status (Ref: married)</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;Unmarried</td>
<td align="center">0.44 (0.37)</td>
<td align="center">&#x2014;</td>
<td align="center">5.86 (6.39)</td>
</tr>
<tr>
<td align="left">&#x2003;Divorced/widowed</td>
<td align="center">1.52 (0.40)</td>
<td align="center">1.02 (0.18)</td>
<td align="center">1.41&#x2a;(0.22)</td>
</tr>
<tr>
<td align="left">&#x2003;Migration duration (years)</td>
<td align="center">0.97&#x2a;&#x2a;(0.01)</td>
<td align="center">1.01 (0.01)</td>
<td align="center">0.98 (0.01)</td>
</tr>
<tr>
<td align="left">Self-assessed health (Ref: healthy)</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;Generally healthy</td>
<td align="center">0.93 (0.15)</td>
<td align="center">1.00 (0.13)</td>
<td align="center">0.91 (0.13)</td>
</tr>
<tr>
<td align="left">&#x2003;Unhealthy but can self-care</td>
<td align="center">0.94 (0.32)</td>
<td align="center">1.35 (0.41)</td>
<td align="center">0.72 (0.15)</td>
</tr>
<tr>
<td align="left">&#x2003;Cannot self-care</td>
<td align="center">1.53 (1.68)</td>
<td align="center">1.52 (1.64)</td>
<td align="center">0.33&#x2a;(1.15)</td>
</tr>
<tr>
<td align="left">&#x2003;Constant</td>
<td align="center">0.05&#x2a;(0.08)</td>
<td align="center">0.86 (0.89)</td>
<td align="center">0.94 (1.93)</td>
</tr>
<tr>
<td align="left">
<italic>N</italic>
</td>
<td align="center">3,050</td>
<td align="center">4,439</td>
<td align="center">4,184</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>OMW, older migrant workers; OM, older migrants; SHI, social health insurance; SE, standard error; MHEPA, monthly household expenditure <italic>per capita</italic>. &#x2a;<italic>p</italic> &#x3c; 0.05, &#x2a;&#x2a;<italic>p</italic> &#x3c; 0.01, &#x2a;&#x2a;&#x2a;<italic>p</italic> &#x3c; 0.001. Migrant Dynamic Monitoring Survey, China, 2015.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>
<xref ref-type="table" rid="T3">Table 3</xref> reports the model fit of the path analysis models. All fit indices met the criteria, indicating acceptable model fitness between the hypothetic model and the data. <xref ref-type="fig" rid="F1">Figure 1</xref> shows the base case path analysis models for the three subgroups. Above all, a significant association of having SHI in the current place of residence with less household expenditure <italic>per capita</italic> was discovered in all three subgroup OMs. SHI in the current place of residence is significantly associated with increases in the occurrence of doctor visits among OMs for looking after children and OMs for receiving care from family, whereas this association is not observed in OMs for better employment. We also found a significant association between worse self-rated health and greater household expenditure <italic>per capita</italic> and an association between longer migration duration and having SHI in the current place of residence in all the subgroups. It is noted that worse self-assessed health was associated with a lower probability of visiting doctors among OMWs and OMs for receiving care from family. Additionally, regarding OMs for receiving care from family, household expenditure <italic>per capita</italic> demonstrated a positive association with visiting doctors.</p>
<table-wrap id="T3" position="float">
<label>TABLE 3</label>
<caption>
<p>Summary of the fit indices (China. 2015).</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="left">Fit indices</th>
<th align="center">&#x3c7;<sup>2</sup>/df</th>
<th align="center">RMSEA</th>
<th align="center">CFI</th>
<th align="center">NFI</th>
<th align="center">TLI</th>
<th align="center">IFI</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">Recommended value</td>
<td align="center">&#x3c;3</td>
<td align="center">&#x3c;0.08</td>
<td align="center">&#x3e;0.90</td>
<td align="center">&#x3e;0.90</td>
<td align="center">&#x3e;0.90</td>
<td align="center">&#x3e;0.90</td>
</tr>
<tr>
<td colspan="7" align="left">Base case analysis</td>
</tr>
<tr>
<td align="left">&#x2003;OMWs</td>
<td align="center">1.411</td>
<td align="center">0.012</td>
<td align="center">0.997</td>
<td align="center">0.991</td>
<td align="center">0.970</td>
<td align="center">0.997</td>
</tr>
<tr>
<td align="left">&#x2003;OMs for looking after children</td>
<td align="center">1.234</td>
<td align="center">0.007</td>
<td align="center">0.999</td>
<td align="center">0.993</td>
<td align="center">0.985</td>
<td align="center">0.999</td>
</tr>
<tr>
<td align="left">&#x2003;OMs for receiving care from family</td>
<td align="center">0.768</td>
<td align="center">&#x3c;0.001</td>
<td align="center">1.000</td>
<td align="center">0.997</td>
<td align="center">1.011</td>
<td align="center">1.001</td>
</tr>
<tr>
<td colspan="7" align="left">Robustness check</td>
</tr>
<tr>
<td align="left">&#x2003;OMWs</td>
<td align="center">1.561</td>
<td align="center">0.014</td>
<td align="center">0.996</td>
<td align="center">0.991</td>
<td align="center">0.963</td>
<td align="center">0.997</td>
</tr>
<tr>
<td align="left">&#x2003;OMs for looking after children</td>
<td align="center">2.194</td>
<td align="center">0.016</td>
<td align="center">0.993</td>
<td align="center">0.989</td>
<td align="center">0.931</td>
<td align="center">0.994</td>
</tr>
<tr>
<td align="left">&#x2003;OMs for receiving care from family</td>
<td align="center">0.933</td>
<td align="center">&#x3c;0.001</td>
<td align="center">1.000</td>
<td align="center">0.996</td>
<td align="center">1.003</td>
<td align="center">1.000</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>CFI, the comparative fit index; NFI, normed fit index; TLI, Tucker-Lewis Coefficient; IFI, incremental fit index; OMW, older migrant workers; OM, older migrants. Migrant Dynamic Monitoring Survey, China, 2015.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<fig id="F1" position="float">
<label>FIGURE 1</label>
<caption>
<p>Path analysis models toward three subgroups of older migrants (China. 2015). SHI, social health insurance. &#x2a;, <italic>p</italic> &#x3c; 0.05; &#x2a;&#x2a;, <italic>p</italic> &#x3c; 0.01; &#x2a;&#x2a;&#x2a;, <italic>p</italic> &#x3c; 0.001. Migrant Dynamic Monitoring Survey, China, 2015.</p>
</caption>
<graphic xlink:href="ijph-68-1605325-g001.tif"/>
</fig>
<p>In the robustness check, this study changed the categorical variable, age, into a continuous variable measured by years. <xref ref-type="table" rid="T4">Table 4</xref> compares the test statistics for the specific paths between the main models and robustness checks. The results of the robustness check, reported in the lower panel of <xref ref-type="table" rid="T4">Table 4</xref>, were in line with the results of the main models in the upper panel.</p>
<table-wrap id="T4" position="float">
<label>TABLE 4</label>
<caption>
<p>Path coefficients in path analysis models among older migrants (China. 2015).</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="left">Base case analysis</th>
<th align="center">OMWs</th>
<th align="center">OMs for looking after children</th>
<th align="center">OMs for receiving care from family</th>
</tr>
<tr>
<th align="left">Path</th>
<th colspan="3" align="center">Coefficients <sup>P</sup> (SE)</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">&#x2003;Visiting doctors &#x3c;- Health status</td>
<td align="center">&#x2212;0.053&#x2a;&#x2a;&#x2a;(0.015)</td>
<td align="center">&#x2212;0.006 (0.012)</td>
<td align="center">&#x2212;0.035&#x2a;&#x2a;&#x2a;(0.010)</td>
</tr>
<tr>
<td align="left">&#x2003;Visiting doctors &#x3c;- SHI in current place of residence</td>
<td align="center">0.043 (0.027)</td>
<td align="center">0.099&#x2a;&#x2a;&#x2a;(0.030)</td>
<td align="center">0.120&#x2a;&#x2a;&#x2a;(0.026)</td>
</tr>
<tr>
<td align="left">&#x2003;Visiting doctors &#x3c;-Expenditure</td>
<td align="center">0.021 (0.015)</td>
<td align="center">0.004 (0.013)</td>
<td align="center">0.028&#x2a;(0.014)</td>
</tr>
<tr>
<td align="left">&#x2003;Visiting doctors &#x3c;- Age</td>
<td align="center">0.041 (0.034)</td>
<td align="center">0.047&#x2a;&#x2a;(0.017)</td>
<td align="center">0.043&#x2a;&#x2a;&#x2a;(0.011)</td>
</tr>
<tr>
<td align="left">&#x2003;Expenditure &#x3c;- SHI in current place of residence</td>
<td align="center">&#x2212;0.131&#x2a;&#x2a;&#x2a;(0.033)</td>
<td align="center">&#x2212;0.305&#x2a;&#x2a;&#x2a;(0.035)</td>
<td align="center">&#x2212;0.195&#x2a;&#x2a;&#x2a;(0.029)</td>
</tr>
<tr>
<td align="left">&#x2003;Expenditure &#x3c;- Health status</td>
<td align="center">&#x2212;0.060&#x2a;&#x2a;&#x2a;(0.018)</td>
<td align="center">&#x2212;0.094&#x2a;&#x2a;&#x2a;(0.001)</td>
<td align="center">&#x2212;0.097&#x2a;&#x2a;&#x2a;(0.011)</td>
</tr>
<tr>
<td align="left">&#x2003;Expenditure &#x3c;- Migrating duration</td>
<td align="center">0.001 (0.002)</td>
<td align="center">&#x2212;0.004&#x2a;&#x2a;(0.002)</td>
<td align="center">&#x2212;0.008&#x2a;&#x2a;&#x2a;(0.002)</td>
</tr>
<tr>
<td align="left">&#x2003;Expenditure &#x3c;- Age</td>
<td align="center">0.016 (0.041)</td>
<td align="center">&#x2212;0.065&#x2a;&#x2a;(0.020)</td>
<td align="center">&#x2212;0.025&#x2a;(0.012)</td>
</tr>
<tr>
<td align="left">&#x2003;SHI in current place of residence &#x3c;- Migration duration</td>
<td align="center">0.010&#x2a;&#x2a;&#x2a;(0.001)</td>
<td align="center">0.006&#x2a;&#x2a;&#x2a;(0.001)</td>
<td align="center">0.005&#x2a;&#x2a;&#x2a;(0.001)</td>
</tr>
<tr>
<td align="left">&#x2003;Health status &#x3c;-SHI-in current place of residence</td>
<td align="center">0.012 (0.035)</td>
<td align="center">0.106&#x2a;&#x2a;(0.036)</td>
<td align="center">0.047 (0.039)</td>
</tr>
<tr>
<td align="left">&#x2003;Health status &#x3c;- Age</td>
<td align="center">0.267&#x2a;&#x2a;&#x2a;(0.041)</td>
<td align="center">0.186&#x2a;&#x2a;&#x2a;(0.001)</td>
<td align="center">0.226&#x2a;&#x2a;&#x2a;(0.017)</td>
</tr>
<tr>
<td align="left">&#x2003;Migrating duration &#x3c;- Age</td>
<td align="center">2.302&#x2a;&#x2a;&#x2a;(0.489)</td>
<td align="center">0.951&#x2a;&#x2a;&#x2a;(0.114)</td>
<td align="center">0.808&#x2a;&#x2a;&#x2a;(0.125)</td>
</tr>
<tr>
<td align="left">&#x2003;Migrating duration &#x3c;- Health status</td>
<td align="center">1.762&#x2a;&#x2a;&#x2a;(0.218)</td>
<td align="center">0.070 (0.129)</td>
<td align="center">0.157 (0.114)</td>
</tr>
<tr>
<td align="left">Robustness check</td>
<td align="center">OMWs</td>
<td align="center">OMs for looking after children</td>
<td align="center">OMs for receiving care from family</td>
</tr>
<tr>
<td align="left">&#x2003;Visiting doctors &#x3c;- Health status</td>
<td align="center">&#x2212;0.055&#x2a;(0.015)</td>
<td align="center">&#x2212;0.007 (0.012)</td>
<td align="center">&#x2212;0.036&#x2a;&#x2a;&#x2a;(0.010)</td>
</tr>
<tr>
<td align="left">&#x2003;Visiting doctors &#x3c;- SHI in current place of residence</td>
<td align="center">0.042 (0.027)</td>
<td align="center">0.098&#x2a;&#x2a;(0.030)</td>
<td align="center">0.120&#x2a;&#x2a;&#x2a;(0.026)</td>
</tr>
<tr>
<td align="left">&#x2003;Visiting doctors &#x3c;-Expenditure</td>
<td align="center">0.022 (0.015)</td>
<td align="center">0.003 (0.013)</td>
<td align="center">0.029&#x2a;(0.014)</td>
</tr>
<tr>
<td align="left">&#x2003;Visiting doctors &#x3c;- Age</td>
<td align="center">0.004 (0.003)</td>
<td align="center">0.004&#x2a;&#x2a;(0.002)</td>
<td align="center">0.005&#x2a;&#x2a;&#x2a;(0.001)</td>
</tr>
<tr>
<td align="left">&#x2003;Expenditure &#x3c;- SHI in current place of residence</td>
<td align="center">&#x2212;0.131&#x2a;&#x2a;&#x2a;(0.033)</td>
<td align="center">&#x2212;0.304&#x2a;&#x2a;&#x2a;(0.035)</td>
<td align="center">&#x2212;0.195&#x2a;&#x2a;&#x2a;(0.029)</td>
</tr>
<tr>
<td align="left">&#x2003;Expenditure &#x3c;- Health status</td>
<td align="center">&#x2212;0.056&#x2a;&#x2a;(0.018)</td>
<td align="center">&#x2212;0.095&#x2a;&#x2a;&#x2a;(0.014)</td>
<td align="center">&#x2212;0.097&#x2a;&#x2a;&#x2a;(0.011)</td>
</tr>
<tr>
<td align="left">&#x2003;Expenditure &#x3c;- Migrating duration</td>
<td align="center">0.001 (0.002)</td>
<td align="center">&#x2212;0.004&#x2a;&#x2a;(0.002)</td>
<td align="center">&#x2212;0.008&#x2a;&#x2a;&#x2a;(0.002)</td>
</tr>
<tr>
<td align="left">&#x2003;Expenditure &#x3c;- Age</td>
<td align="center">&#x2212;0.004 (0.003)</td>
<td align="center">&#x2212;0.005&#x2a;(0.002)</td>
<td align="center">&#x2212;0.002&#x2a;(0.001)</td>
</tr>
<tr>
<td align="left">&#x2003;SHI in current place of residence &#x3c;- Migration duration</td>
<td align="center">0.010&#x2a;&#x2a;&#x2a;(0.001)</td>
<td align="center">0.006&#x2a;&#x2a;&#x2a;(0.001)</td>
<td align="center">0.005&#x2a;&#x2a;&#x2a;(0.001)</td>
</tr>
<tr>
<td align="left">&#x2003;Health status &#x3c;-SHI-in current place of residence</td>
<td align="center">0.011 (0.023)</td>
<td align="center">0.101&#x2a;&#x2a;(0.036)</td>
<td align="center">0.049 (0.039)</td>
</tr>
<tr>
<td align="left">&#x2003;Health status &#x3c;- Age</td>
<td align="center">0.024&#x2a;&#x2a;&#x2a;(0.004)</td>
<td align="center">0.019&#x2a;&#x2a;&#x2a;(0.002)</td>
<td align="center">0.024&#x2a;&#x2a;&#x2a;(0.002)</td>
</tr>
<tr>
<td align="left">&#x2003;Migrating duration &#x3c;- Age</td>
<td align="center">0.219&#x2a;&#x2a;&#x2a;(0.037)</td>
<td align="center">0.112&#x2a;&#x2a;&#x2a;(0.016)</td>
<td align="center">0.079&#x2a;&#x2a;&#x2a;(0.012)</td>
</tr>
<tr>
<td align="left">&#x2003;Migrating duration &#x3c;- Health status</td>
<td align="center">1.704&#x2a;&#x2a;&#x2a;(0.218)</td>
<td align="center">0.033 (0.129)</td>
<td align="center">0.140 (0.114)</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>OMW, older migrant workers; OM, older migrants; SE, standard error; SHI, social health insurance. &#x2a;<italic>p</italic> &#x3c; 0.05, &#x2a;&#x2a;<italic>p</italic> &#x3c; 0.01, &#x2a;&#x2a;&#x2a;<italic>p</italic> &#x3c; 0.001. Migrant Dynamic Monitoring Survey, China, 2015.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec sec-type="discussion" id="s4">
<title>Discussion</title>
<p>This study offers four novel contributions to the existing research on older migrants. First, the analysis suggested that OMWs were the particularly vulnerable population in visiting doctors, and SHI, compared with other OMs. The results indicate that OMWs are more disadvantaged in using health services and socioeconomic status. OMWs had the least rate of visiting doctors in times of sickness, the least household expenditure, and the largest proportion of receiving secondary education or below among the three subgroups. Besides, given OMWs are still employed in their current place of residence after retirement to support their family, they are more likely to be from a low socioeconomic background and have unmet health needs. Previous research also evidenced the existence of significant unmet healthcare needs in Chinese rural-to-urban migrant workers (<xref ref-type="bibr" rid="B39">39</xref>).</p>
<p>Second, the negative relationship between worse health status and visiting doctors in OMs might be related to their disadvantages in low socioeconomic status. The path analyses demonstrate OMWs and OMs for receiving care from family who had worse health status are less likely to visit doctors, and worse health status was associated with less household expenditure. Disposable income and chronic disease might explain this finding. The CMDMS data indicate that the average monthly household disposable income <italic>per capita</italic> of OMWs and OMs for receiving care from family was merely CNY 1068 and CNY 1027 per month, while the figure was CNY 1363 among OMs for caring offspring. OMs for looking after children are more likely to live with their adult children who have formal employment and stable income resources. This is consistent with the broad body of literature which shows the role of income in using health services among older adults (<xref ref-type="bibr" rid="B40">40</xref>, <xref ref-type="bibr" rid="B41">41</xref>). Simultaneously, the CMDMS data suggest that the prevalence of hypertension or diabetes in OMs for looking after offspring (24.6%) was higher than that of OMWs (12.5%). Due to the longstanding disease course, chronic diseases require regular healthcare and have more rigid demand, which is less influenced by socioeconomic status, and might incur increases in medical expenses. Research also shows that the price elasticity for older patients with high chronic diseases is higher than those without (<xref ref-type="bibr" rid="B42">42</xref>).</p>
<p>Third, a significant association between having SHI in the current place of residence and less expenditure was discovered in all three sub-group OMs. Moreover, regarding OMs for looking after offspring and OMs for receiving care from family, the expenditure reduced by the SHI in the current place of residence further increased the probability of visiting doctors. These findings might imply that addressing the inequalities in the reimbursement of health expenses among different types of SHI <italic>via</italic> unifying all types of health financing schemes into a single-payer program might be considered as a future approach. Due to the fragmented SHI schemes, rural and urban health insurance schemes are separately operated, and a gap exists in healthcare delivery between rural-to-urban migrants and urban residents (<xref ref-type="bibr" rid="B43">43</xref>). Although the Chinese government has implemented the Urban-Rural Resident Medical Insurance (URRMI) since 2016 by combing URI and NCMS (<xref ref-type="bibr" rid="B28">28</xref>), there are still 130 million Chinese people covered by NCMS in 2018 (<xref ref-type="bibr" rid="B6">6</xref>). On the one hand, since SHI is linked with the household registration scheme, a large number of rural-to-urban OMs is still covered by NCMS due to a lack of non-agricultural <italic>Hukou</italic> in urban area (<xref ref-type="bibr" rid="B29">29</xref>). Rural-to-urban OMs with SHI in their current place of residence benefit more from the reimbursement of healthcare expenses, in comparison to those without (<xref ref-type="bibr" rid="B4">4</xref>, <xref ref-type="bibr" rid="B44">44</xref>). UEI which targets urban employees is evidence to be more effective in improving access to health services by providing higher financial protection, compared with other types of SHI (<xref ref-type="bibr" rid="B4">4</xref>). On the other hand, for those migrants who enrolled in URRMI, they still had a higher co-payment than urban employees enrolling in UEI (<xref ref-type="bibr" rid="B6">6</xref>). The high reimbursement of the urban health financing scheme could be a vital factor in the decision for OMs to seek health services (<xref ref-type="bibr" rid="B41">41</xref>). With a higher reduction in out-of-pocket health expenses benefiting from urban health financing schemes (<xref ref-type="bibr" rid="B45">45</xref>), OMs for receiving care from their family who have SHI in their current place of residence may be more likely to visit doctors during times of illness.</p>
<p>Fourth, OMWs with a longer migrating duration are more likely to have SHI in their current place of residence. This finding is in line with previous research that shows as the duration extends, rural-to-urban migrants are more likely to be eligible for urban health financing schemes (<xref ref-type="bibr" rid="B29">29</xref>). In the short run, rural-to-urban OMWs face policy barriers and discrimination in seeking employment and healthcare expenses reimbursement in their current place of residence. As time goes by, rural-to-urban migrants could undergo elaborate procedures in their current place of residence under transfer policies. OMWs might benefit from a long service for local employers (<xref ref-type="bibr" rid="B3">3</xref>, <xref ref-type="bibr" rid="B46">46</xref>) to get enrolled in urban health financing schemes and other public welfare.</p>
<p>The following policy implications could be derived from the above analyses. First, policymakers are suggested to further promote the URRMI by combining the NCMS and UEI across rural residents and urban residents. Second, streamlined transfer policies for rural-to-urban migrants covered by NCMS to enroll in URRMI and improved elaborate procedures for OMWs to enroll in UEI are worthwhile. More efforts on community-based education or counseling on the transfer procedure on SHI in the current place of residence are needed. Third, we also suggest policymakers consider unifying all types of health insurance programs into a single-payer program to address the gap between existing URRMI and UEI. Fourth, the Chinese government has announced nationwide direct reimbursement for seeking cross-provincial inpatient expenses, but this reimbursement for outpatient expenses across provinces is still limited in pilot areas after the medical reform in 2019. We suggest the government to future extend the coverage of direct reimbursement for seeking cross-province outpatient services. Fifth, simply improving health services use among OMs <italic>via</italic> existing SHI is insufficient. We suggest policymakers in LMICs to consider a more generous public welfare scheme. Further programs targeting OMWs needed to be better designed to guarantee wage payment, pension, and other public benefits and improve access to health services. Sixth, to improve the awareness of active health-seeking behaviors during times of illness, social media and family members need to guide OMs to face their health needs and understand the importance of their health to the family.</p>
<sec id="s4-1">
<title>Limitations</title>
<p>The limitations need to be given due attention. First, given that the last national survey that investigated Chinese OMs was in 2015, the data merely reflected the status in 2015, and it could not explore the causal effects of cross-sectional data. Finally, although this study controlled for essential associated factors, restricted by method availability and the large sample size&#x2019;s sensitivity, this study could not detect potential associations regarding other variables.</p>
</sec>
<sec id="s4-2">
<title>Conclusion</title>
<p>OMWs are the particularly vulnerable population in using health services and socioeconomic status, in comparison to other OMs. OMWs and OMs for receiving care from their family who had worse health status were less likely to visit doctors during times of illness and were more likely to have less household expenditure, which might be related to the disadvantages in socioeconomic status and SHI. Having SHI in the current place of residence may help reduce household expenditure for OMs. As the migration duration extends, OMs are more likely to enroll in SHI registered in their current place of residence, which may increase the occurrence of doctor visits. Public policies in LMICs are worthy of consideration when more universal to cover OMWs. We urge the government to future promote URRMI across rural and urban areas. We suggest policymakers consider unifying all types of health financing schemes into a single-payer program by adjusting the approaches of existing URRMI and UEI. More efforts are needed to streamline transfer policies for rural-to-urban migrants to enroll in URRMI in the current place of residence or UEI.</p>
</sec>
</sec>
</body>
<back>
<sec id="s5">
<title>Author Contributions</title>
<p>CL wrote the first draft. ST, FC, YY, LJ, and XX reviewed and approved the final article.</p>
</sec>
<sec id="s6">
<title>Funding</title>
<p>This study was supported by the National Key R&#x26;D Program of China from the Ministry of Science and Technology of China (grant number 2022YFE0133000), the National Science Foundation of China (grant number 72004073), and the Chinese Ministry of Education of Humanities and Social Science project (grant No. 20YJC630134). This study also is supported by King&#x2019;s-China Scholarship Council Program.</p>
</sec>
<ack>
<p>We gratefully appreciate the helpful comments received from Dr. Wei Yang at King&#x2019;s College London. </p>
</ack>
<sec sec-type="COI-statement" id="s7">
<title>Conflict of Interest</title>
<p>The authors declare that they do not have any conflicts of interest.</p>
</sec>
<ref-list>
<title>References</title>
<ref id="B1">
<label>1.</label>
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Nikoloski</surname>
<given-names>Z</given-names>
</name>
<name>
<surname>Zhang</surname>
<given-names>A</given-names>
</name>
<name>
<surname>Hopkin</surname>
<given-names>G</given-names>
</name>
<name>
<surname>Mossialos</surname>
<given-names>E</given-names>
</name>
</person-group>. <article-title>Self-reported Symptoms of Depression Among Chinese Rural-To-Urban Migrants and Left-Behind Family Members</article-title>. <source>Jama Netw Open</source> (<year>2019</year>) <volume>2</volume>(<issue>5</issue>):<fpage>e193355</fpage>. <pub-id pub-id-type="doi">10.1001/jamanetworkopen.2019.3355</pub-id>
</citation>
</ref>
<ref id="B2">
<label>2.</label>
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Ye</surname>
<given-names>J</given-names>
</name>
<name>
<surname>Wang</surname>
<given-names>C</given-names>
</name>
<name>
<surname>Wu</surname>
<given-names>H</given-names>
</name>
<name>
<surname>He</surname>
<given-names>C</given-names>
</name>
<name>
<surname>Liu</surname>
<given-names>J</given-names>
</name>
</person-group>. <article-title>Internal Migration and Left-Behind Populations in China</article-title>. <source>J Peasant Stud</source> (<year>2013</year>) <volume>40</volume>(<issue>6</issue>):<fpage>1119</fpage>&#x2013;<lpage>46</lpage>. <pub-id pub-id-type="doi">10.1080/03066150.2013.861421</pub-id>
</citation>
</ref>
<ref id="B3">
<label>3.</label>
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Zhu</surname>
<given-names>Y</given-names>
</name>
<name>
<surname>Hu</surname>
<given-names>X</given-names>
</name>
<name>
<surname>Yang</surname>
<given-names>B</given-names>
</name>
<name>
<surname>Wu</surname>
<given-names>G</given-names>
</name>
<name>
<surname>Wang</surname>
<given-names>Z</given-names>
</name>
<name>
<surname>Xue</surname>
<given-names>Z</given-names>
</name>
<etal/>
</person-group> <article-title>Association between Migrant Worker Experience, Limitations on Insurance Coverage, and Hospitalization for Schizophrenia in Hunan Province, China</article-title>. <source>Schizophrenia Res</source> (<year>2018</year>) <volume>197</volume>:<fpage>93</fpage>&#x2013;<lpage>7</lpage>. <pub-id pub-id-type="doi">10.1016/j.schres.2017.11.026</pub-id>
</citation>
</ref>
<ref id="B4">
<label>4.</label>
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Meng</surname>
<given-names>Q</given-names>
</name>
<name>
<surname>Fang</surname>
<given-names>H</given-names>
</name>
<name>
<surname>Liu</surname>
<given-names>X</given-names>
</name>
<name>
<surname>Yuan</surname>
<given-names>B</given-names>
</name>
<name>
<surname>Xu</surname>
<given-names>J</given-names>
</name>
</person-group>. <article-title>Consolidating the Social Health Insurance Schemes in China: Towards an Equitable and Efficient Health System</article-title>. <source>Lancet</source> (<year>2015</year>) <volume>386</volume>(<issue>10002</issue>):<fpage>1484</fpage>&#x2013;<lpage>92</lpage>. <pub-id pub-id-type="doi">10.1016/S0140-6736(15)00342-6</pub-id>
</citation>
</ref>
<ref id="B5">
<label>5.</label>
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Liem</surname>
<given-names>A</given-names>
</name>
<name>
<surname>Wang</surname>
<given-names>C</given-names>
</name>
<name>
<surname>Wariyanti</surname>
<given-names>Y</given-names>
</name>
<name>
<surname>Latkin</surname>
<given-names>CA</given-names>
</name>
<name>
<surname>Hall</surname>
<given-names>BJ</given-names>
</name>
</person-group>. <article-title>The Neglected Health of International Migrant Workers in the COVID-19 Epidemic</article-title>. <source>Lancet Psychiatry</source> (<year>2020</year>) <volume>7</volume>(<issue>4</issue>):<fpage>E20</fpage>. <pub-id pub-id-type="doi">10.1016/S2215-0366(20)30076-6</pub-id>
</citation>
</ref>
<ref id="B6">
<label>6.</label>
<citation citation-type="book">
<collab>Statistical Bulletin on the Development of National Basic Medical Security in 2018</collab>. <source>China National Healthcare Security Administration</source> (<year>2019</year>). <comment>Available from: <ext-link ext-link-type="uri" xlink:href="http://www.nhsa.gov.cn/art/2019/6/30/art_7_1477.html">http://www.nhsa.gov.cn/art/2019/6/30/art_7_1477.html</ext-link> (Accessed January 19, 2022)</comment>.</citation>
</ref>
<ref id="B7">
<label>7.</label>
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Campbell</surname>
<given-names>LJ</given-names>
</name>
</person-group>. <article-title>Age, Gender, Socioeconomic, and Ethnic Differences in Patients&#x27; Assessments of Primary Health Care</article-title>. <source>Qual Health Care</source> (<year>2001</year>) <volume>10</volume>(<issue>2</issue>):<fpage>90</fpage>&#x2013;<lpage>5</lpage>. <pub-id pub-id-type="doi">10.1136/qhc.10.2.90</pub-id>
</citation>
</ref>
<ref id="B8">
<label>8.</label>
<citation citation-type="book">
<collab>Reply to Recommendation No</collab>. <source>7432 of the Second Session of the 13th National People&#x27;s Congress</source>. <publisher-loc>China</publisher-loc>: <publisher-name>China National Healthcare Security Administration</publisher-name> (<year>2019</year>). <comment>Available from: <ext-link ext-link-type="uri" xlink:href="http://www.nhsa.gov.cn/art/2019/7/30/art_26_1581.html">http://www.nhsa.gov.cn/art/2019/7/30/art_26_1581.html</ext-link> (Accessed May 17, 2022)</comment>.</citation>
</ref>
<ref id="B9">
<label>9.</label>
<citation citation-type="book">
<collab>Statistical Bulletin on the Development of National Basic Medical Security in 2019</collab>. <source>China National Healthcare Security Administration</source> (<year>2020</year>). <comment>Available from: <ext-link ext-link-type="uri" xlink:href="http://www.nhsa.gov.cn/art/2020/6/24/art_7_3268.html">http://www.nhsa.gov.cn/art/2020/6/24/art_7_3268.html</ext-link> (Accessed March 6, 2023)</comment>.</citation>
</ref>
<ref id="B10">
<label>10.</label>
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Tang</surname>
<given-names>S</given-names>
</name>
<name>
<surname>Long</surname>
<given-names>C</given-names>
</name>
<name>
<surname>Wang</surname>
<given-names>R</given-names>
</name>
<name>
<surname>Liu</surname>
<given-names>Q</given-names>
</name>
<name>
<surname>Feng</surname>
<given-names>D</given-names>
</name>
<name>
<surname>Feng</surname>
<given-names>Z</given-names>
</name>
</person-group>. <article-title>Improving the Utilization of Essential Public Health Services by Chinese Elderly Migrants: Strategies and Policy Implication</article-title>. <source>J Glob Health</source> (<year>2020</year>) <volume>10</volume>(<issue>1</issue>):<fpage>010807</fpage>. <pub-id pub-id-type="doi">10.7189/jogh.10.010807</pub-id>
</citation>
</ref>
<ref id="B11">
<label>11.</label>
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Chen</surname>
<given-names>S</given-names>
</name>
<name>
<surname>Chen</surname>
<given-names>Y</given-names>
</name>
<name>
<surname>Feng</surname>
<given-names>Z</given-names>
</name>
<name>
<surname>Chen</surname>
<given-names>X</given-names>
</name>
<name>
<surname>Wang</surname>
<given-names>Z</given-names>
</name>
<name>
<surname>Zhu</surname>
<given-names>J</given-names>
</name>
<etal/>
</person-group> <article-title>Barriers of Effective Health Insurance Coverage for Rural-To-Urban Migrant Workers in China: A Systematic Review and Policy Gap Analysis</article-title>. <source>BMC Public Health</source> (<year>2020</year>) <volume>20</volume>(<issue>1</issue>):<fpage>408</fpage>. <pub-id pub-id-type="doi">10.1186/s12889-020-8448-8</pub-id>
</citation>
</ref>
<ref id="B12">
<label>12.</label>
<citation citation-type="book">
<collab>Summary of the China Migrant Population Development Report 2016</collab>. <source>Materials for the Special Press Conference on October 19, 2016: Summary of "China Migrant Population Development Report 2016"</source>. <publisher-loc>Beijing, China</publisher-loc>: <publisher-name>National Health Commission of China</publisher-name> (<year>2020</year>). <comment>Available from: <ext-link ext-link-type="uri" xlink:href="http://www.nhc.gov.cn/xcs/s3574/201610/58881fa502e5481082eb9b34331e3eb2.shtml">http://www.nhc.gov.cn/xcs/s3574/201610/58881fa502e5481082eb9b34331e3eb2.shtml</ext-link> (Accessed March 6, 2023)</comment>.</citation>
</ref>
<ref id="B13">
<label>13.</label>
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Zhang</surname>
<given-names>X</given-names>
</name>
<name>
<surname>Yu</surname>
<given-names>B</given-names>
</name>
<name>
<surname>He</surname>
<given-names>T</given-names>
</name>
<name>
<surname>Wang</surname>
<given-names>P</given-names>
</name>
</person-group>. <article-title>Status and Determinants of Health Services Utilization Among Elderly Migrants in China</article-title>. <source>Glob Health Res Pol</source> (<year>2018</year>) <volume>3</volume>(<issue>3</issue>):<fpage>8</fpage>. <pub-id pub-id-type="doi">10.1186/s41256-018-0064-0</pub-id>
</citation>
</ref>
<ref id="B14">
<label>14.</label>
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Li</surname>
<given-names>D</given-names>
</name>
<name>
<surname>Zhou</surname>
<given-names>Z</given-names>
</name>
<name>
<surname>Shen</surname>
<given-names>C</given-names>
</name>
<name>
<surname>Zhang</surname>
<given-names>J</given-names>
</name>
<name>
<surname>Yang</surname>
<given-names>W</given-names>
</name>
<name>
<surname>Nawaz</surname>
<given-names>R</given-names>
</name>
</person-group>. <article-title>Health Disparity between the Older Rural-To-Urban Migrant Workers and Their Rural Counterparts in China</article-title>. <source>Int J Environ Res Public Health</source> (<year>2020</year>) <volume>17</volume>(<issue>3</issue>):<fpage>955</fpage>. <pub-id pub-id-type="doi">10.3390/ijerph17030955</pub-id>
</citation>
</ref>
<ref id="B15">
<label>15.</label>
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Kluge</surname>
<given-names>HHP</given-names>
</name>
<name>
<surname>Jakab</surname>
<given-names>Z</given-names>
</name>
<name>
<surname>Bartovic</surname>
<given-names>J</given-names>
</name>
<name>
<surname>D&#x27;Anna</surname>
<given-names>VSS</given-names>
</name>
</person-group>. <article-title>Refugee and Migrant Health in the COVID-19 Response</article-title>. <source>Lancet</source> (<year>2020</year>) <volume>395</volume>(<issue>10232</issue>):<fpage>1237</fpage>&#x2013;<lpage>9</lpage>. <pub-id pub-id-type="doi">10.1016/S0140-6736(20)30791-1</pub-id>
</citation>
</ref>
<ref id="B16">
<label>16.</label>
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Chen</surname>
<given-names>F</given-names>
</name>
<name>
<surname>Tao</surname>
<given-names>S</given-names>
</name>
<name>
<surname>Zhang</surname>
<given-names>J</given-names>
</name>
</person-group>. <article-title>Status of Social Health Insurance of Migrants and its Impact on Long-Term Residence Intention (In Chinese)</article-title>. <source>World Surv Res</source> (<year>2017</year>) <volume>11</volume>:<fpage>37</fpage>&#x2013;<lpage>42</lpage>. <pub-id pub-id-type="doi">10.13778/j.cnki.11-3705/c.2017.11.006</pub-id>
</citation>
</ref>
<ref id="B17">
<label>17.</label>
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Miltiades</surname>
<given-names>HB</given-names>
</name>
</person-group>. <article-title>Factors Affecting Physician Visits in Chinese and Chinese Immigrant Samples</article-title>. <source>Soc Sci Med</source> (<year>2008</year>) <volume>66</volume>(<issue>3</issue>):<fpage>704</fpage>&#x2013;<lpage>14</lpage>. <pub-id pub-id-type="doi">10.1016/j.socscimed.2007.10.016</pub-id>
</citation>
</ref>
<ref id="B18">
<label>18.</label>
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Xi</surname>
<given-names>S</given-names>
</name>
<name>
<surname>Song</surname>
<given-names>Y</given-names>
</name>
<name>
<surname>Li</surname>
<given-names>X</given-names>
</name>
<name>
<surname>Li</surname>
<given-names>M</given-names>
</name>
<name>
<surname>Lu</surname>
<given-names>Z</given-names>
</name>
<name>
<surname>Yang</surname>
<given-names>Y</given-names>
</name>
<etal/>
</person-group> <article-title>Local&#x2010;Migrant Gaps in Healthcare Utilization between Older Migrants and Local Residents in China</article-title>. <source>J Am Geriatr Soc</source> (<year>2020</year>) <volume>68</volume>(<issue>7</issue>):<fpage>1560</fpage>&#x2013;<lpage>7</lpage>. <pub-id pub-id-type="doi">10.1111/jgs.16421</pub-id>
</citation>
</ref>
<ref id="B19">
<label>19.</label>
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Ma</surname>
<given-names>Y</given-names>
</name>
<name>
<surname>Guo</surname>
<given-names>H</given-names>
</name>
<name>
<surname>Guo</surname>
<given-names>S</given-names>
</name>
<name>
<surname>Jiao</surname>
<given-names>T</given-names>
</name>
<name>
<surname>Zhao</surname>
<given-names>C</given-names>
</name>
<name>
<surname>Ammerman</surname>
<given-names>BA</given-names>
</name>
<etal/>
</person-group> <article-title>Association of the Labor Migration of Parents with Nonsuicidal Self-Injury and Suicidality Among Their Offspring in China</article-title>. <source>Jama Netw Open</source> (<year>2021</year>) <volume>4</volume>(<issue>11</issue>):<fpage>e2133596</fpage>. <pub-id pub-id-type="doi">10.1001/jamanetworkopen.2021.33596</pub-id>
</citation>
</ref>
<ref id="B20">
<label>20.</label>
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Andersen</surname>
<given-names>R</given-names>
</name>
<name>
<surname>Newman</surname>
<given-names>JF</given-names>
</name>
</person-group>. <article-title>Societal and Individual Determinants of Medical Care Utlization in United-States</article-title>. <source>Milbank Memorial Fund Quarterly-Health Soc</source> (<year>1973</year>) <volume>51</volume>(<issue>1</issue>):<fpage>95</fpage>&#x2013;<lpage>124</lpage>. <pub-id pub-id-type="doi">10.2307/3349613</pub-id>
</citation>
</ref>
<ref id="B21">
<label>21.</label>
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Ma</surname>
<given-names>S</given-names>
</name>
<name>
<surname>Zhou</surname>
<given-names>X</given-names>
</name>
<name>
<surname>Jiang</surname>
<given-names>M</given-names>
</name>
<name>
<surname>Li</surname>
<given-names>Q</given-names>
</name>
<name>
<surname>Gao</surname>
<given-names>C</given-names>
</name>
<name>
<surname>Cao</surname>
<given-names>W</given-names>
</name>
<etal/>
</person-group> <article-title>Comparison of Access to Health Services Among Urban-To-Urban and Rural-To-Urban Older Migrants, and Urban and Rural Older Permanent Residents in Zhejiang Province, China: A Cross-Sectional Survey</article-title>. <source>BMC Geriatr</source> (<year>2018</year>) <volume>18</volume>:<fpage>174</fpage>. <pub-id pub-id-type="doi">10.1186/s12877-018-0866-4</pub-id>
</citation>
</ref>
<ref id="B22">
<label>22.</label>
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Xu</surname>
<given-names>J</given-names>
</name>
<name>
<surname>Zhang</surname>
<given-names>Y</given-names>
</name>
<name>
<surname>Qiu</surname>
<given-names>C</given-names>
</name>
<name>
<surname>Cheng</surname>
<given-names>F</given-names>
</name>
</person-group>. <article-title>Global and Regional Economic Costs of Dementia: A Systematic Review</article-title>. <source>Lancet</source> (<year>2017</year>) <volume>390</volume>:<fpage>S47</fpage>. <pub-id pub-id-type="doi">10.1016/s0140-6736(17)33185-9</pub-id>
</citation>
</ref>
<ref id="B23">
<label>23.</label>
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Zheng</surname>
<given-names>A</given-names>
</name>
<name>
<surname>Fang</surname>
<given-names>Q</given-names>
</name>
<name>
<surname>Zhu</surname>
<given-names>Y</given-names>
</name>
<name>
<surname>Jiang</surname>
<given-names>C</given-names>
</name>
<name>
<surname>Jin</surname>
<given-names>F</given-names>
</name>
<name>
<surname>Wang</surname>
<given-names>X</given-names>
</name>
</person-group>. <article-title>An Application of ARIMA Model for Predicting Total Health Expenditure in China from 1978-2022</article-title>. <source>J Glob Health</source> (<year>2020</year>) <volume>10</volume>:<fpage>010803</fpage>. <pub-id pub-id-type="doi">10.7189/jogh.10.010803</pub-id>
</citation>
</ref>
<ref id="B24">
<label>24.</label>
<citation citation-type="book">
<collab>China National Health Development Research Centre</collab>. <source>National Health and Family Planning Commission: China National Health Accounts 2014 Report</source>. <publisher-name>China National Health Development Research Centre</publisher-name>: <publisher-loc>Beijing</publisher-loc> (<year>2015</year>).</citation>
</ref>
<ref id="B25">
<label>25.</label>
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Yang</surname>
<given-names>W</given-names>
</name>
<name>
<surname>Li</surname>
<given-names>D</given-names>
</name>
<name>
<surname>Gao</surname>
<given-names>J</given-names>
</name>
<name>
<surname>Zhou</surname>
<given-names>X</given-names>
</name>
<name>
<surname>Li</surname>
<given-names>F</given-names>
</name>
</person-group>. <article-title>Decomposing Differences in Depressive Symptoms between Older Rural-To-Urban Migrant Workers and Their Counterparts in Mainland China</article-title>. <source>BMC Public Health</source> (<year>2020</year>) <volume>20</volume>:<fpage>1442</fpage>. <pub-id pub-id-type="doi">10.1186/s12889-020-09374-1(1)</pub-id>
</citation>
</ref>
<ref id="B26">
<label>26.</label>
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Mohabir</surname>
<given-names>N</given-names>
</name>
<name>
<surname>Jiang</surname>
<given-names>Y</given-names>
</name>
<name>
<surname>Ma</surname>
<given-names>R</given-names>
</name>
</person-group>. <article-title>Chinese Floating Migrants: Rural-Urban Migrant Labourers&#x27; Intentions to Stay or Return</article-title>. <source>Habitat Int</source> (<year>2017</year>) <volume>60</volume>:<fpage>101</fpage>&#x2013;<lpage>10</lpage>. <pub-id pub-id-type="doi">10.1016/j.habitatint.2016.12.008</pub-id>
</citation>
</ref>
<ref id="B27">
<label>27.</label>
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Bakewell</surname>
<given-names>O</given-names>
</name>
</person-group>. <article-title>Some Reflections on Structure and Agency in Migration Theory</article-title>. <source>J Ethnic Migration Stud</source> (<year>2010</year>) <volume>36</volume>(<issue>10</issue>):<fpage>1689</fpage>&#x2013;<lpage>708</lpage>. <pub-id pub-id-type="doi">10.1080/1369183x.2010.489382</pub-id>
</citation>
</ref>
<ref id="B28">
<label>28.</label>
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Tan</surname>
<given-names>SY</given-names>
</name>
<name>
<surname>Wu</surname>
<given-names>X</given-names>
</name>
<name>
<surname>Yang</surname>
<given-names>W</given-names>
</name>
</person-group>. <article-title>Impacts of the Type of Social Health Insurance on Health Service Utilisation and Expenditures: Implications for A Unified System in China</article-title>. <source>Health Econ Pol L</source> (<year>2019</year>) <volume>14</volume>(<issue>4</issue>):<fpage>468</fpage>&#x2013;<lpage>86</lpage>. <pub-id pub-id-type="doi">10.1017/S174413311800018X</pub-id>
</citation>
</ref>
<ref id="B29">
<label>29.</label>
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Zhou</surname>
<given-names>Q</given-names>
</name>
<name>
<surname>Liu</surname>
<given-names>G</given-names>
</name>
</person-group>. <article-title>The Difference of Benefits from Health Insurance: Based on the Study of the Local Population and Migrants (In Chinese)</article-title>. <source>Nankai Econ Stud</source> (<year>2016</year>) <volume>4</volume>(<issue>1</issue>):<fpage>77</fpage>&#x2013;<lpage>94</lpage>. <pub-id pub-id-type="doi">10.14116/j.nkes.2016.01.005</pub-id>
</citation>
</ref>
<ref id="B30">
<label>30.</label>
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Zhu</surname>
<given-names>Y</given-names>
</name>
<name>
<surname>Oesterle</surname>
<given-names>A</given-names>
</name>
</person-group>. <article-title>Rural-urban Disparities in Unmet Long-Term Care Needs in China: The Role of the Hukou Status</article-title>. <source>Soc Sci Med</source> (<year>2017</year>) <volume>191</volume>:<fpage>30</fpage>&#x2013;<lpage>7</lpage>. <pub-id pub-id-type="doi">10.1016/j.socscimed.2017.08.025</pub-id>
</citation>
</ref>
<ref id="B31">
<label>31.</label>
<citation citation-type="book">
<collab>Data Application of National Internal Migrant Dynamic Monitoring Survey</collab>. <source>Migrant Population Service Center of China</source> (<year>2022</year>). <comment>Available from: <ext-link ext-link-type="uri" xlink:href="https://www.chinaldrk.org.cn/wjw/#/application/index">https://www.chinaldrk.org.cn/wjw/&#x23;/application/index</ext-link> (Accessed Februray 2, 2022)</comment>.</citation>
</ref>
<ref id="B32">
<label>32.</label>
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Chen</surname>
<given-names>W</given-names>
</name>
<name>
<surname>Zhang</surname>
<given-names>Q</given-names>
</name>
<name>
<surname>Renzaho</surname>
<given-names>AMN</given-names>
</name>
<name>
<surname>Zhou</surname>
<given-names>F</given-names>
</name>
<name>
<surname>Zhang</surname>
<given-names>H</given-names>
</name>
<name>
<surname>Ling</surname>
<given-names>L</given-names>
</name>
</person-group>. <article-title>Social Health Insurance Coverage and Financial Protection Among Rural-To-Urban Internal Migrants in China: Evidence from A Nationally Representative Cross-Sectional Study</article-title>. <source>BMJ Glob Health</source> (<year>2017</year>) <volume>2</volume>(<issue>4</issue>):<fpage>e000477</fpage>. <pub-id pub-id-type="doi">10.1136/bmjgh-2017-000477</pub-id>
</citation>
</ref>
<ref id="B33">
<label>33.</label>
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Proust-Lima</surname>
<given-names>C</given-names>
</name>
<name>
<surname>Philipps</surname>
<given-names>V</given-names>
</name>
<name>
<surname>Liquet</surname>
<given-names>B</given-names>
</name>
</person-group>. <article-title>Estimation of Extended Mixed Models Using Latent Classes and Latent Processes: The R Package Lcmm</article-title>. <source>J Stat Softw</source> (<year>2017</year>) <volume>78</volume>(<issue>2</issue>):<fpage>1</fpage>&#x2013;<lpage>56</lpage>. <pub-id pub-id-type="doi">10.18637/jss.v078.i02</pub-id>
</citation>
</ref>
<ref id="B34">
<label>34.</label>
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Tang</surname>
<given-names>D</given-names>
</name>
<name>
<surname>Wang</surname>
<given-names>J</given-names>
</name>
</person-group>. <article-title>Basic Public Health Service Utilization by Internal Older Adult Migrants in China</article-title>. <source>Int J Environ Res Public Health</source> (<year>2021</year>) <volume>18</volume>:<fpage>270</fpage>. <pub-id pub-id-type="doi">10.3390/ijerph18010270</pub-id>
</citation>
</ref>
<ref id="B35">
<label>35.</label>
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Xie</surname>
<given-names>D</given-names>
</name>
</person-group>. <article-title>Household Registration, Migration Reasons and Long-Term Residence Intention of Older Adults: Based on 2015 China Migrant Dynamic Monitoring Survey (In Chinese)</article-title>. <source>World Surv Res</source> (<year>2019</year>) <volume>03</volume>:<fpage>37</fpage>&#x2013;<lpage>42</lpage>. <pub-id pub-id-type="doi">10.13778/j.cnki.11-3705/c.2019.03.008</pub-id>
</citation>
</ref>
<ref id="B36">
<label>36.</label>
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Xie</surname>
<given-names>Y</given-names>
</name>
<name>
<surname>Guo</surname>
<given-names>Q</given-names>
</name>
<name>
<surname>Meng</surname>
<given-names>Y</given-names>
</name>
</person-group>. <article-title>The Health Service Use of Aged Rural-To-Urban Migrant Workers in Different Types of Cities in China</article-title>. <source>BMC Health Serv Res</source> (<year>2021</year>) <volume>21</volume>(<issue>1</issue>):<fpage>606</fpage>. <pub-id pub-id-type="doi">10.1186/s12913-021-06638-3</pub-id>
</citation>
</ref>
<ref id="B37">
<label>37.</label>
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Long</surname>
<given-names>C</given-names>
</name>
<name>
<surname>Wang</surname>
<given-names>R</given-names>
</name>
<name>
<surname>Feng</surname>
<given-names>D</given-names>
</name>
<name>
<surname>Ji</surname>
<given-names>L</given-names>
</name>
<name>
<surname>Feng</surname>
<given-names>Z</given-names>
</name>
<name>
<surname>Tang</surname>
<given-names>S</given-names>
</name>
</person-group>. <article-title>Social Support and Health Services Use in People Aged over 65 Years Migrating within China: A Cross-Sectional Study</article-title>. <source>Int J Environ Res Public Health</source> (<year>2020</year>) <volume>17</volume>:<fpage>4651</fpage>. <pub-id pub-id-type="doi">10.3390/ijerph17134651(13)</pub-id>
</citation>
</ref>
<ref id="B38">
<label>38.</label>
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Deng</surname>
<given-names>Z</given-names>
</name>
<name>
<surname>Lu</surname>
<given-names>Y</given-names>
</name>
<name>
<surname>Wei</surname>
<given-names>KK</given-names>
</name>
<name>
<surname>Zhang</surname>
<given-names>J</given-names>
</name>
</person-group>. <article-title>Understanding Customer Satisfaction and Loyalty: An Empirical Study of Mobile Instant Messages in China</article-title>. <source>Int J Inf Manage</source> (<year>2010</year>) <volume>30</volume>(<issue>4</issue>):<fpage>289</fpage>&#x2013;<lpage>300</lpage>. <pub-id pub-id-type="doi">10.1016/j.ijinfomgt.2009.10.001</pub-id>
</citation>
</ref>
<ref id="B39">
<label>39.</label>
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Lu</surname>
<given-names>CH</given-names>
</name>
<name>
<surname>Luo</surname>
<given-names>ZC</given-names>
</name>
<name>
<surname>Wang</surname>
<given-names>JJ</given-names>
</name>
<name>
<surname>Zhong</surname>
<given-names>JH</given-names>
</name>
<name>
<surname>Wang</surname>
<given-names>PX</given-names>
</name>
</person-group>. <article-title>Health-Related Quality of Life and Health Service Utilization in Chinese Rural-To-Urban Migrant Workers</article-title>. <source>Int J Environ Res Public Health</source> (<year>2015</year>) <volume>12</volume>(<issue>2</issue>):<fpage>2205</fpage>&#x2013;<lpage>14</lpage>. <pub-id pub-id-type="doi">10.3390/ijerph120202205</pub-id>
</citation>
</ref>
<ref id="B40">
<label>40.</label>
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Shao</surname>
<given-names>S</given-names>
</name>
<name>
<surname>Wang</surname>
<given-names>M</given-names>
</name>
<name>
<surname>Jin</surname>
<given-names>G</given-names>
</name>
<name>
<surname>Zhao</surname>
<given-names>Y</given-names>
</name>
<name>
<surname>Lu</surname>
<given-names>X</given-names>
</name>
<name>
<surname>Du</surname>
<given-names>J</given-names>
</name>
</person-group>. <article-title>Analysis of Health Service Utilization of Migrants in Beijing Using Anderson Health Service Utilization Model</article-title>. <source>BMC Health Serv Res</source> (<year>2018</year>) <volume>18</volume>:<fpage>462</fpage>. <pub-id pub-id-type="doi">10.1186/s12913-018-3271-y</pub-id>
</citation>
</ref>
<ref id="B41">
<label>41.</label>
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Huang</surname>
<given-names>R</given-names>
</name>
<name>
<surname>Ghose</surname>
<given-names>B</given-names>
</name>
<name>
<surname>Tang</surname>
<given-names>S</given-names>
</name>
</person-group>. <article-title>Effect of Financial Stress on Self-Rereported Health and Quality of Life Among Older Adults in Five Developing Countries: a Cross Sectional Analysis of WHO-SAGE Survey</article-title>. <source>BMC Geriatr</source> (<year>2020</year>) <volume>20</volume>(<issue>1</issue>):<fpage>288</fpage>. <pub-id pub-id-type="doi">10.1186/s12877-020-01687-5</pub-id>
</citation>
</ref>
<ref id="B42">
<label>42.</label>
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Yang</surname>
<given-names>CJ</given-names>
</name>
<name>
<surname>Tsai</surname>
<given-names>YC</given-names>
</name>
<name>
<surname>Tien</surname>
<given-names>JJ</given-names>
</name>
</person-group>. <article-title>The Impacts of Persistent Behaviour and Cost-Sharing Policy on Demand for Outpatient Visits by the Elderly: Evidence from Taiwan&#x27;s National Health Insurance</article-title>. <source>Geneva Pap Risk Insurance Issues Pract</source> (<year>2017</year>) <volume>42</volume>:<fpage>31</fpage>&#x2013;<lpage>52</lpage>. <pub-id pub-id-type="doi">10.1057/s41288-016-0022-3</pub-id>
</citation>
</ref>
<ref id="B43">
<label>43.</label>
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Meng</surname>
<given-names>Q</given-names>
</name>
<name>
<surname>Xu</surname>
<given-names>K</given-names>
</name>
</person-group>. <article-title>Progress and Challenges of the Rural Cooperative Medical Scheme in China</article-title>. <source>Bull World Health Organ</source> (<year>2014</year>) <volume>92</volume>(<issue>6</issue>):<fpage>447</fpage>&#x2013;<lpage>51</lpage>. <pub-id pub-id-type="doi">10.2471/BLT.13.131532</pub-id>
</citation>
</ref>
<ref id="B44">
<label>44.</label>
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Qiu</surname>
<given-names>P</given-names>
</name>
<name>
<surname>Yang</surname>
<given-names>Y</given-names>
</name>
<name>
<surname>Zhang</surname>
<given-names>J</given-names>
</name>
<name>
<surname>Ma</surname>
<given-names>X</given-names>
</name>
</person-group>. <article-title>Rural-to-urban Migration and its Implication for New Cooperative Medical Scheme Coverage and Utilization in China</article-title>. <source>BMC Public Health</source> (<year>2011</year>) <volume>11</volume>:<fpage>520</fpage>. <pub-id pub-id-type="doi">10.1186/1471-2458-11-520</pub-id>
</citation>
</ref>
<ref id="B45">
<label>45.</label>
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Liu</surname>
<given-names>K</given-names>
</name>
<name>
<surname>Wu</surname>
<given-names>Q</given-names>
</name>
<name>
<surname>Liu</surname>
<given-names>J</given-names>
</name>
</person-group>. <article-title>Examining the Association between Social Health Insurance Participation and Patients&#x27; Out-Of-Pocket Payments in China: The Role of Institutional Arrangement</article-title>. <source>Soc Sci Med</source> (<year>2014</year>) <volume>113</volume>:<fpage>95</fpage>&#x2013;<lpage>103</lpage>. <pub-id pub-id-type="doi">10.1016/j.socscimed.2014.05.011</pub-id>
</citation>
</ref>
<ref id="B46">
<label>46.</label>
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Van Hear</surname>
<given-names>N</given-names>
</name>
<name>
<surname>Bakewell</surname>
<given-names>O</given-names>
</name>
<name>
<surname>Long</surname>
<given-names>K</given-names>
</name>
</person-group>. <article-title>Push-pull Plus: Reconsidering the Drivers of Migration</article-title>. <source>J Ethnic Migration Stud</source> (<year>2018</year>) <volume>44</volume>(<issue>6</issue>):<fpage>927</fpage>&#x2013;<lpage>44</lpage>. <pub-id pub-id-type="doi">10.1080/1369183x.2017.1384135</pub-id>
</citation>
</ref>
</ref-list>
</back>
</article>