{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,19]],"date-time":"2026-09-19T12:45:12Z","timestamp":1789821912833,"version":"4.0.1"},"reference-count":103,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2025,2,11]],"date-time":"2025-02-11T00:00:00Z","timestamp":1739232000000},"content-version":"vor","delay-in-days":41,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":["alz-journals.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["A&amp;amp;D Transl Res &amp;amp; Clin Interv"],"published-print":{"date-parts":[[2025,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:label\/>\n                    <jats:p>The rising age of the global population has made Alzheimer's disease and related dementias (ADRD) a critical public health problem, with significant health\u2010related disparities observed between rural and urban areas. However, no previous reviews have examined the scope and determinant factors contributing to rural\u2013urban disparities of ADRD\u2010related health outcomes. This study aims to systematically collate and synthesize peer\u2010reviewed articles on rural\u2013urban disparities in ADRD, identifying key determinants and research gaps to guide future research. We conducted a systematic search using key terms related to rural\u2013urban disparities and ADRD without restrictions on geography or study design. Five search engines\u2014MEDLINE, CINAHL, Web of Science, PubMed, and Scopus\u2014were used to identify relevant articles. The search was performed on August 16, 2024, and included English\u2010language articles published from 2000 onward. Sixty\u2010three articles met the eligibility criteria for data extraction and synthesis. Most articles were published after 2010 (85.7%) and were concentrated in the United States, China, and Canada (66.7%). A majority had cross\u2010sectional (58.7%) or cohort study designs (23.8%), primarily examining prevalence (41.3%) or incidence (11.1%). Findings often indicated a higher prevalence and incidence in rural areas, although inconsistent rural\u2013urban classification systems were noted. Common risk factors included female sex, lower education level, lower income, and comorbidities such as diabetes and cerebrovascular diseases. Environmental (12.7%) and lifestyle (14.3%) factors for ADRD have been less explored. The statistical methods used were mainly traditional analyses (e.g., logistic regression) and lacked advanced techniques such as machine learning or causal inference methods. The gaps identified in this review emphasize the need for future research in underexplored geographic regions and encourage the use of advanced methods to investigate understudied factors contributing to ADRD disparities, such as environmental, lifestyle, and genetic influences.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Highlights<\/jats:title>\n                    <jats:p>\n                      <jats:list list-type=\"bullet\">\n                        <jats:list-item>\n                          <jats:p>Few studies on rural\u2013urban ADRD disparities focus on low\u2010 and middle\u2010income\u00a0countries.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>Common risk factors include female sex, low education attainment, low income, and comorbidities.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>Inconsistent definitions of \u201crural\u201d complicate cross\u2010country comparisons.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>Environmental and lifestyle factors affecting ADRD are underexplored.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>Advanced statistical methods, such as machine learning and causal inference, are recommended.<\/jats:p>\n                        <\/jats:list-item>\n                      <\/jats:list>\n                    <\/jats:p>\n                  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