Yu‐Hung Chang

875 total citations
18 papers, 684 citations indexed

About

Yu‐Hung Chang is a scholar working on Physiology, Public Health, Environmental and Occupational Health and Psychiatry and Mental health. According to data from OpenAlex, Yu‐Hung Chang has authored 18 papers receiving a total of 684 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Physiology, 5 papers in Public Health, Environmental and Occupational Health and 5 papers in Psychiatry and Mental health. Recurrent topics in Yu‐Hung Chang's work include Nutrition and Health in Aging (5 papers), Dementia and Cognitive Impairment Research (4 papers) and Nutritional Studies and Diet (3 papers). Yu‐Hung Chang is often cited by papers focused on Nutrition and Health in Aging (5 papers), Dementia and Cognitive Impairment Research (4 papers) and Nutritional Studies and Diet (3 papers). Yu‐Hung Chang collaborates with scholars based in Taiwan, Australia and United States. Yu‐Hung Chang's co-authors include Mark L. Wahlqvist, Meei-Shyuan Lee, Chih-Cheng Hsu, Meei‐Shyuan Lee, Yuan‐Ting C. Lo, I‐Chien Wu, Chao A. Hsiung, Yu‐Chun Lin, Chih‐Cheng Hsu and Ren‐Hua Chung and has published in prestigious journals such as Journal of the American Geriatrics Society, Journal of Epidemiology & Community Health and Journal of Medical Internet Research.

In The Last Decade

Yu‐Hung Chang

18 papers receiving 663 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Yu‐Hung Chang Taiwan 9 320 183 134 121 90 18 684
Bertha Hidalgo United States 16 382 1.2× 54 0.3× 120 0.9× 92 0.8× 70 0.8× 48 866
Phillip Tuso United States 9 107 0.3× 172 0.9× 131 1.0× 124 1.0× 135 1.5× 21 798
M.J. Stampfer United States 10 170 0.5× 247 1.3× 195 1.5× 141 1.2× 43 0.5× 18 939
Sanjeev Budhathoki Japan 16 173 0.5× 156 0.9× 198 1.5× 52 0.4× 41 0.5× 30 741
Vanessa Gordon-Dseagu United States 10 86 0.3× 163 0.9× 241 1.8× 65 0.5× 55 0.6× 21 735
Anlan Cao United States 9 86 0.3× 130 0.7× 213 1.6× 114 0.9× 53 0.6× 18 756
Irina Bondarenko United States 12 163 0.5× 165 0.9× 183 1.4× 393 3.2× 36 0.4× 24 1.1k
Jian Su China 15 83 0.3× 130 0.7× 134 1.0× 59 0.5× 32 0.4× 80 628
Laura Rosana Aballay Argentina 15 77 0.2× 95 0.5× 225 1.7× 87 0.7× 50 0.6× 41 616
Juan Sun China 16 170 0.5× 78 0.4× 118 0.9× 22 0.2× 88 1.0× 68 726

Countries citing papers authored by Yu‐Hung Chang

Since Specialization
Citations

This map shows the geographic impact of Yu‐Hung Chang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Yu‐Hung Chang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yu‐Hung Chang more than expected).

Fields of papers citing papers by Yu‐Hung Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yu‐Hung Chang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Yu‐Hung Chang. The network helps show where Yu‐Hung Chang may publish in the future.

Co-authorship network of co-authors of Yu‐Hung Chang

This figure shows the co-authorship network connecting the top 25 collaborators of Yu‐Hung Chang. A scholar is included among the top collaborators of Yu‐Hung Chang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yu‐Hung Chang. Yu‐Hung Chang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
1.
Chang, Yu‐Hung, Xing Lü, I‐Chien Wu, et al.. (2025). Use of Artificial Intelligence, Internet of Things, and Edge Intelligence in Long-Term Care for Older People: Comprehensive Analysis Through Bibliometric, Google Trends, and Content Analysis. Journal of Medical Internet Research. 27. e56692–e56692. 3 indexed citations
2.
Chuang, Shu‐Chun, Yu‐Hung Chang, I‐Chien Wu, et al.. (2024). Impact of physical activity on disability‐free and disabled life expectancies in middle‐aged and older adults: Data from the healthy aging longitudinal study in Taiwan. Geriatrics and gerontology international. 24(S1). 229–239. 3 indexed citations
3.
Chang, Yu‐Hung, et al.. (2023). Exploring concepts and trends in informal caregiver burden: systematic review using citation network and content analysis. Aging Clinical and Experimental Research. 35(12). 2873–2885. 8 indexed citations
4.
Chang, Yu‐Hung, et al.. (2023). Country-Level Factors Associated With Nurse Salaries: Empirical Evidence From Organisation for Economic Co-operation and Development Countries and Taiwan. Journal of Nursing Research. 31(6). e303–e303. 1 indexed citations
5.
Hsu, Yu‐Chin, et al.. (2022). A multilevel analysis of the determinants of the attitude toward separate cycle paths in Taiwan. Social Science Quarterly. 103(7). 1732–1749. 2 indexed citations
6.
Chang, Yu‐Hung, I‐Chien Wu, & Chao A. Hsiung. (2020). Reading activity prevents long-term decline in cognitive function in older people: evidence from a 14-year longitudinal study. International Psychogeriatrics. 33(1). 63–74. 35 indexed citations
8.
Lin, Yu‐Chun & Yu‐Hung Chang. (2020). Poor Appetite and Eating Difficulties Can Predict the Long-Term Risk of Falling: A Longitudinal Study in Middle-Aged and Older Adults. Journal of Applied Gerontology. 40(11). 1465–1474. 3 indexed citations
9.
Lin, Yu‐Chun, et al.. (2020). Urinary incontinence and its association with socioeconomic status among middle‐aged and older persons in Taiwan: A population‐based study. Geriatrics and gerontology international. 21(2). 245–253. 4 indexed citations
10.
Lo, Yuan‐Ting C., et al.. (2016). Combined Effects of Chewing Ability and Dietary Diversity on Medical Service Use and Expenditures. Journal of the American Geriatrics Society. 64(6). 1187–1194. 9 indexed citations
11.
Wu, I‐Chien, Chao A. Hsiung, I‐Shou Chang, et al.. (2014). Personal mastery, multisystem physiological dysregulation and risk of functional decline in older adults: A prospective study in Taiwan. Geriatrics and gerontology international. 15(6). 707–714. 5 indexed citations
12.
Chang, Yu‐Hung, et al.. (2013). Planning and evaluation in health workforce development: Projection for the pharmacy workforce in Taiwan. Journal of the Formosan Medical Association. 112(12). 733–734. 1 indexed citations
13.
Chang, Yu‐Hung, et al.. (2012). Increased Medical Costs in Elders With the Metabolic Syndrome are Most Evident With Hospitalization of Men. Gender Medicine. 9(5). 348–360. 3 indexed citations
14.
Chang, Yu‐Hung, et al.. (2011). Dietary quality may enhance survival related to cognitive impairment in Taiwanese elderly. Food & Nutrition Research. 55(1). 7387–7387. 27 indexed citations
15.
Chang, Yu‐Hung, et al.. (2011). Frequent shopping by men and women increases survival in the older Taiwanese population. Journal of Epidemiology & Community Health. 66(7). e20–e20. 27 indexed citations
17.
Lo, Yuan‐Ting C., Yu‐Hung Chang, Meei‐Shyuan Lee, & Mark L. Wahlqvist. (2011). Dietary diversity and food expenditure as indicators of food security in older Taiwanese. Appetite. 58(1). 180–187. 68 indexed citations
18.
Lee, Meei-Shyuan, et al.. (2011). Cooking frequency may enhance survival in Taiwanese elderly. Public Health Nutrition. 15(7). 1142–1149. 84 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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