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. 2026 Apr 17;105(16):e48374. doi: 10.1097/MD.0000000000048374

Oral health-related quality of life in systemic disease patients: A bibliometric analysis and visualization from 2001 to 2024

Linxin Jiang a, Simin Li b, Daniel R Reissmann a, Deborah Kreher c, Gerhard Schmalz c, Xianda Hu d,*
PMCID: PMC13095243  PMID: 41995536

Abstract

Background:

Oral health-related quality of life (OHRQoL) serves as a key measure for understanding how systemic health conditions affect oral health and daily functioning. This study aims to systematically analyze the research on the relationship between OHRQoL and systemic diseases using scientometric methods, with the goal of uncovering research trends, hotspots, and frontiers.

Methods:

Publications from the Web of Science were analyzed using GraphPad Prism, Bibliometrix, VOSviewer, and CiteSpace. Results were visualized.

Results:

A total of 441 documents (2001–2024) were included. Publication output steadily increased, with a surge in 2020. Core authors, journals, and institutions were mainly from developed countries. Frequent keywords included “OHRQoL,” “oral health,” “impact,” “validation,” and “periodontal disease.” Twelve keyword clusters were identified: “oral cancer,” “oral squamous cell carcinoma,” “breast neoplasms,” “oral health,” and “dental care” were key hotspots. “Osteoporosis” and “benign mucous membrane” emerged as novel themes, while “consensus,” “older people,” “2017 World Workshop,” and “dry mouth” showed strong bursts.

Conclusions:

Research has advanced significantly, with developed countries as key contributors. Cancer, periodontitis, and the validation tools are central topics. Aging populations, and systemic or oral diseases in older adults are expected to shape future directions.

Keywords: bibliometrics, dental research, oral health, oral health-related quality of life, systemic disease

1. Introduction

Oral health-related quality of life (OHRQoL) is a critical indicator for assessing the impact of oral health on daily life, encompassing multiple dimensions such as oral function, orofacial pain, orofacial appearance, and psychosocial impact.[1-3] Additionally, OHRQoL serves as a vital bridge for understanding the association between oral health and systemic health, demonstrating a significant correlation with HRQoL.[4,5] Its applications extend widely across public health surveillance, therapeutic evaluation, and clinical practice.[6] For instance, questionnaires developed based on OHRQoL principles have been employed to enhance communication between dentists and patients, thereby improving the quality of dental care.[7]

The adverse effects of systemic diseases – such as diabetes, cardiovascular diseases, and rheumatic conditions – on oral health have been extensively studied. The systemic diseases influence patients’ OHRQoL by impairing oral health and inducing physical and psychological challenges. For example, metabolic diseases like diabetes can exacerbate periodontal tissue damage by amplifying inflammatory responses.[8] Patients with rheumatoid arthritis often experience oral symptoms such as reduced salivary flow and oral ulcers.[9] With the rapid progression of global aging[10] and the rising burden and prevalence of systemic diseases,[11-13] the impact of systemic disease on OHRQoL has become increasingly significant. Thus, a deeper exploration of the relationship between systemic diseases and OHRQoL is not only crucial for a comprehensive understanding but also provides a theoretical foundation for designing effective interventions to enhance patients’ quality of life.

Bibliometric analysis, as a quantitative tool for analyzing research trends and knowledge structures, has demonstrated unique advantages across various multidisciplinary fields in recent years.[14,15] Existing systematic review have individually summarized research on OHRQoL and systemic diseases.[16-19] However, there is no bibliometric analysis focusing on the relationship between systemic diseases and OHRQoL. Therefore, conducting this study holds significant academic value in addressing this research gap.

This study aims to systematically analyze the current research landscape on the relationship between OHRQoL and systemic diseases using bibliometric methods, identifying research trends, hotspots, and frontiers to provide scientific guidance for future studies. Based on the research background, the study proposes the following hypotheses: current research exhibits broad geographical distribution, but international collaboration remains insufficient; research hotspots and trends are shaped by global contexts, such as population aging and burden of systemic diseases, which are emerging as central topics of focus.

2. Materials and methods

2.1. Data sources and search strategy

The Web of Science (WoS) is a highly regarded academic database that spans multiple disciplines, indexing high-quality journal literature. It provides comprehensive data essential for bibliometric analysis, including titles, authors, journals, countries/regions, institutions, keywords, and citations. This study utilized the SCI-EXPANDED database within the WoS Core Collection, exporting plain text files for analysis. The search was completed on December 31, 2024, with the search strategy outlined in Figure 1. The inclusion criteria were limited to publications in English and document types categorized as articles or reviews. No restrictions were applied to the publication time span. Exclusions included conference proceedings, early access publications, and editorial materials. Data preprocessing involved deduplication and cross-checking conducted independently by 2 researchers (LX J and SM L).

Figure 1.

Figure 1.

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Search strategy and analytical methodology flowchart.

2.2. Data analysis and visualization

The data analysis and visualization in this study were performed using GraphPad Prism (version 8.0.2), Bibliometrix,[20] VOSviewer (version 1.6.20),[21] and CiteSpace (version 6.4.R1),[22] respectively.

GraphPad Prism was employed to organize and visualize the annual publication trends.

Bibliometrix is a comprehensive R package designed for bibliometric analysis, offering robust tools for visualizing publications output and citations.

VOSviewer facilitated the analysis of collaboration networks among authors, journals, countries/regions, and institutions, as well as keyword co-occurrence relationships. Its collaboration network analysis, based on social network theory, connects nodes (e.g., authors, journals, countries/regions, or institutions) with edges (representing collaboration), uncovering patterns of scientific collaboration and academic influence. Keyword co-occurrence analysis, built on word frequency statistics and co-occurrence relationships, identifies research hotspots and the structural knowledge of the field through the analysis of high-frequency keywords and their associations in the literature.

CiteSpace was utilized to examine the knowledge structure and research dynamics within academic literature. The keyword clustering analysis, based on co-occurrence relationships, categorized high-frequency keywords into distinct clusters, revealing research hotspots and subthemes in the field. Keyword cluster in time line view demonstrated the evolution of various topics over time, offering insights into the developmental trend of the field. Burst keyword analysis, leveraging an algorithm for detecting sudden increases in frequency, identified keywords with significant temporal frequency changes, highlighting emerging hotspots and frontiers of research.

3. Results

3.1. Annual publication trend

A total of 441 articles were ultimately included in this study (Fig. 2). The overall publication trend shows an increase over the years, which can be categorized into 3 distinct stages. From 2001 to 2016, the field was a nascent stage, with annual publication counts generally below 10, except for brief increases in 2013 (12 articles) and 2015 (17 articles). The period from 2016 to 2019 was a developmental stage, with publications steadily rising from 21 to 33 articles per year. The third stage saw rapid growth, with a sharp increase to 55 articles in 2020 and a peak of 60 articles in 2024.

Figure 2.

Figure 2.

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The annual publication output trend from 2001 to 2024.

3.2. Collaboration or co-citation network analysis of authors, journals, countries/regions, and institutions

The study included a total of 2340 authors, with 39 authors included in the co-citation network analysis (with a minimum co-citation frequency of 20). In the co-citation network analysis, Slade, GD is the most influential author (Fig. 3 and Table S1, Supplemental Digital Content, https://links.lww.com/MD/R692). Meanwhile, the clustering algorithm grouped documents based on their co-citation frequency, resulting in 4 clusters. Slade, GD (the USA); Atchison, KA (the USA); Thomson, WM (New Zealand); and Locker, D (Canada) were identified as core authors within the 4 clusters.

Figure 3.

Figure 3.

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Co-citation network of authors. The size of nodes is proportional to the citation frequency, and the thickness of the edges corresponds to the co-citation strength.

The study included a total of 3539 journals, with a citation threshold of 20. Using co-citation network analysis, 179 journals were included. The core journals, with the highest citation counts in the field, were Community Dentistry and Oral Epidemiology (Denmark), Journal of Clinical Periodontology (Denmark), Journal of Dental Research (the USA), Gerodontology (the UK), and Journal of Periodontology (the USA; Fig. 4A and Table S2, Supplemental Digital Content, https://links.lww.com/MD/R692). The top 5 journals in terms of publication output were BMC Oral Health (the UK), Clinical Oral Investigations (Germany), International Journal of Environmental Research and Public Health (Switzerland), Journal of Oral Rehabilitation (the UK), and Supportive Care in Cancer (Germany). Journal of Oral Rehabilitation had the highest publication output during the 2000s and 2010s, while BMC Oral Health had an increase in output around 2020 and subsequently became the leading journal (Fig. 4B).

Figure 4.

Figure 4.

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(A) Co-citation network of journals. The size of nodes is proportional to the citation frequency, and the thickness of the edges corresponds to the co-citation strength. (B) The annual publication output trend of journals from 2001 to 2024.

The study included a total of 64 countries/regions. By setting the minimum publication threshold at 5 articles, 33 countries/regions were included in the collaboration network analysis. The United States is a core country in the collaboration network (Fig 5B, C). And India, Japan, Sweden, the USA, Germany, Spain, and Norway serve as the core countries in each cluster (Table S3, Supplemental Digital Content, https://links.lww.com/MD/R692). Although Canada, China, Australia, and France did not achieve the publication volume or collaboration intensity of the core countries, they rank among the top ten in terms of citation counts, indicating their high impact (Fig. 5A).

Figure 5.

Figure 5.

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(A) The top ten most-cited countries/regions. (B) Collaboration network of countries/regions. The size of nodes is proportional to the number of publications, and the thickness of the edges corresponds to the collaboration intensity. (C) Collaboration map of countries/regions.

The analysis included 827 institutions, with a minimum publication threshold set at 3, and 82 institutions were included in the collaboration network analysis. University of Leipzig (Germany) is the core institution in the network. And these institutions were classified into 6 clusters, with the core institutions of each cluster being the University of Western Cape (South Africa), University of Minnesota (USA), University Medical Center Hamburg Eppendorf (Germany), Federal University of Minas Gerais (Brazil), University of Leipzig (Germany), and University of Bergen (Norway; Fig. 6A and Table S4, Supplemental Digital Content, https://links.lww.com/MD/R692). Most of the core institutions emerged primarily in the later stages of the study period (Fig. 6B).

Figure 6.

Figure 6.

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(A) Collaboration network of institutions. (B) Time-based overlay visualization of institutional collaboration networks. The size of nodes is proportional to the number of publications, and the thickness of the edges corresponds to the collaboration intensity.

3.3. Keyword co-occurrence analysis

The minimum number of occurrences for a keyword was set at 5, resulting in 151 keywords being selected from a total of 1613 for inclusion in the co-occurrence network analysis (Fig. 7). The keywords were categorized into 7 clusters, with the most frequent terms in each cluster being “population,” “oral health,” “validation,” “periodontal disease,” “xerostomia,” “oral health-related quality of life,” and “impact,” which represent the hotpots of the research. Among these, “oral health-related quality of life,” “oral health,” “impact,” “validation,” and “periodontal disease” exhibited the strongest link strengths, serving as central bridging elements within the research network.

Figure 7.

Figure 7.

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Co-occurrence network of keywords. The size of the nodes is proportional to the co-occurrence frequency of the keywords, while the thickness of the edges corresponds to the strength of their association.

3.4. Keyword clustering analysis

Modularity Q = 0.5486 indicates that the network is reasonably divided into loosely coupled clusters, and the mean Silhouette score = 0.8016 indicates that the homogeneity of the clusters is significant on average.

A total of 12 keyword clusters were identified (Fig. 8 and Table S5, Supplemental Digital Content, https://links.lww.com/MD/R692), including: 0# oral cancer, 1# oral squamous cell carcinoma, 2# breast neoplasms, 3# dental caries, 4# oral health, 5# glycemic control, 6# osteoporosis, 7# dental care, 8# photobiomodulation therapy, 9# oral health-related quality of life, 10# health variables, and 11# benign mucous membrane.

Figure 8.

Figure 8.

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Keyword co-occurrence clustering map. The size of the bubbles represents the occurrence frequency of the keywords.

3.5. Temporal analysis of keyword clusters

Figure 9 illustrates that clusters 0, 1, 2, 4, and 7 have consistently been research hotspots. The surges in studies related to clusters 9 and 10 were primarily concentrated in the 2000s and 2010s, respectively. Meanwhile, clusters 3, 5, and 8 garnered increasing attention around the 2010s and have remained active research topics. Clusters 6 and 11 have emerged as novel areas of focus in recent years.

Figure 9.

Figure 9.

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Temporal keyword clustering map: (A) Timeline view, (B) landscape view, and (C) heatmap view.

3.6. Keyword burst detection analysis

Figure 10 illustrates that the keyword “neck cancer” exhibited the longest burst duration, while “dental caries” demonstrated the highest burst strength. Emerging hotspots since 2022 include the keywords “consensus,” “older people,” “2017 World Workshop,” and “dry mouth.”

Figure 10.

Figure 10.

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Burst Detection Analysis of Top 25 Keywords. The green line segments represent the occurrence periods, and the red line segments represent the burst periods.

4. Discussion

This study systematically evaluated research on OHRQoL in patients suffering from systemic diseases using bibliometric analysis. In the beginning, this research received limited attention until a noticeable increase in publication volume emerged in 2016, and culminated in a substantial surge in 2020. This trend is corroborated by collaboration network, showing that core institutions contributing predominantly appeared during the later years of the studied period. Furthermore, the journal with the highest publication, BMC Oral Health, also gained prominence starting in 2020. These shifts may be linked to broader global trends. Firstly, the analysis of burst keywords identified “older people” as a frontier topic. As the global disease burden intensified with aging population, systemic diseases among the elderly pose significant public health and economic challenges.[23] The World Health Organization (WHO) has emphasized the importance of healthy aging, and launched the “Decade of Healthy Ageing 2020–2030” initiative.[24] These factors may have driven growing research interest in this domain, contributing to the rapid increase in publications. Additionally, the COVID-19 pandemic, spurred numerous studies examining the pandemic’s impact on oral health and systemic diseases, such as anxiety, challenges in healthcare access, and adverse vaccine reactions.[25-28]

In terms of primary contributors, including authors, journals, countries/regions, and institutions, most originate from developed countries/regions. However, it is noteworthy that China, as a developing country, ranks fifth among the most-cited countries/regions. This indicates that despite fewer publications and collaborations, developing countries/regions still exert considerable influence. Given the significant regional disparities in disease prevalence and trends, with systemic diseases being more severe in developing countries/regions.[29,30] Future research should focus on fostering collaboration among developed and developing countries/regions to enhance the global applicability of findings.

Key research hotspots in this field include the study of cancer patients as the most extensively examined group with systemic diseases. Oral cancer is a type of head and neck cancer.[31] Oral squamous cell carcinoma accounts for over 90% of oral cancers[32,33] and significantly impairs patients’ oral function and aesthetics,[34] leading to a decline in OHRQoL.[35] Breast cancer, the most prevalent cancer among women worldwide,[36] has also been identified as a long-term research hotpot. Cancer patients often experience a significant decline in HRQoL,[37] which may be positively correlated with OHRQoL,[4] making it a potential factor influencing OHRQoL. Besides, Cancer treatments such as surgery, radiotherapy, and chemotherapy can lead to acute or chronic oral toxicities, including xerostomia, taste alterations, oral ulcers, periodontal disease, and radiation-induced caries,[38] further diminishing OHRQoL.[39] Strategies to improve cancer patients’ OHRQoL, such as preventive tooth extractions, smoking cessation, dietary recommendations, follow-up dental care, and oral hygiene practices, have been proposed.[40] However, evidence-based research in this area remains insufficient, and dental professionals’ education on this topic needs further enhancement.[40,41] Second, periodontal disease is one of the most prevalent and severe oral diseases.[42] Substantial evidence has demonstrated that periodontitis and systemic diseases, such as diabetes, cardiovascular disease, obesity and cancer, are interconnected through a bidirectional relationship. This association is attributed to mechanisms including immune response, bacteremia, oxidative stress, and proinflammatory states.[43] Periodontal medicine has experienced remarkable growth in research over the past 2 decades. The impact of periodontitis on systemic diseases has garnered significant attention from researchers, emerging as one of the key hotpots in the field.[44] In 2017, the American Academy of Periodontology and the European Federation of Periodontology released a consensus report on periodontitis, providing detailed classifications, treatment protocols, and future research recommendations,[45] which represents an identified research frontier. Thirdly, the use of scales or questionnaires such as the Cancer Quality of Life Questionnaire Head and Neck-specific module (EORTC QLQ-H&N35), Oral Cancer Quality-of-Life Questionnaire, and Oral Health Impact Profile to evaluate the impact of systemic diseases on OHRQoL has been a persistent research hotpot too.[35,46,47] This is accompanied by studies validating the reliability and validity of those tools.[48-51]

Emerging research frontiers include domains on systemic and oral diseases. First, osteoporosis, a common aging-related systemic disease that imposes a substantial economic burden on healthcare systems.[52-54] Due to the correlation between systemic bone loss and alveolar bone resorption, osteoporosis patients often experience more severe periodontal disease, reducing OHRQoL.[55] Second, other frontiers are benign mucous membrane and dry mouth. For example, dry mouth, such as xerostomia, commonly arises as a side effect of radiotherapy in cancer patients, with salivary gland dysfunction appearing as early as 1 week after treatment and potentially causing permanent damage.[56] Hypertension medications, diabetes, and Parkinson’s disease are other common causes of dry mouth,[57] which lead to various oral health issues, such as caries and oral candidiasis, as well as impair speech and eating functions.[57] Current research has proposed interventions including immunosuppressants, specialized toothpaste, artificial saliva, and oral care to alleviate symptoms.[57]

In summary, this study might suggest the following recommendations for future research: focusing on the impacts of aging population and global public health events. Enhancing research influence and fostering international collaboration. Pursuing stronger evidence for improving cancer patients’ OHRQoL and validation of OHRQoL measurement tools. Expanding frontiers such as managements of periodontal disease, osteoporosis, and dry mouth.

Additionally, it might be recommendable to build research networks to evaluate superordinate topics related to OHRQoL, potentially affecting the oral care situation of patients with systemic diseases. One example might be the “response shift” in oral health perception of individuals with systemic diseases, affecting oral health behavior and thus the oral care situation.[58] A better understanding of those topics might help to develop more patient-centered dental care strategies for those patients, making research on OHRQoL of systemically diseased promising for future research.

5. Limitations

Several limitations of this study should be acknowledged. First, although the WoS is a widely recognized authoritative academic database, the exclusion of other databases may result in some relevant literatures being excluded, affecting the comprehensiveness of the study. Second, the selection of keywords in the search strategy was based on existing literature and aimed to be as comprehensive as possible. However, some relevant studies may have been missed due to the inherent limitations of keyword selection. Third, restricting the inclusion criteria to English-language articles and reviews may introduce language and publication biases, particularly for research in a global context. Fourth, in order to focus on the research focus, this study did not include treatments related to the systemic diseases, which may also have an impact on oral health-related quality of life. The effects of disease treatments, such as medication, surgery, and other interventions, could potentially alter the findings related to OHRQoL. Fifth, the selection of minimum publication or citation thresholds might exclude influential but less prolific authors, journals, countries/regions, and institutions, thereby biasing the results toward more established contributors. Lastly, while this study aims for objective interpretation of the analysis results, subjective bias remains.

6. Conclusions

Research on OHRQoL and systemic diseases has seen significant advancements over the past 4 years. Authors, journals, and institutions from developed countries/regions have made main contributions to this field. Key research hotspots include cancer, periodontitis, and the validation of OHRQoL measurement tools. Future research frontiers are expected to focus on elderly populations, osteoporosis, and dry mouth.

Acknowledgments

The authors would like to acknowledge that Gerhard Schmalz and Xianda Hu are co-corresponding authors of this article.

Author contributions

Conceptualization: Linxin Jiang, Simin Li, Gerhard Schmalz, Xianda Hu.

Data curation: Deborah Kreher.

Formal analysis: Linxin Jiang.

Funding acquisition: Linxin Jiang.

Methodology: Linxin Jiang, Simin Li, Deborah Kreher.

Supervision: Daniel R. Reissmann, Gerhard Schmalz, Xianda Hu.

Visualization: Linxin Jiang.

Writing – original draft: Linxin Jiang, Simin Li.

Writing – review & editing: Daniel R. Reissmann, Gerhard Schmalz, Xianda Hu.

Supplementary Material

medi-105-e48374-s001.pdf (335.5KB, pdf)

Abbreviations:

OHRQoL
oral health-related quality of life
WoS
Web of Science

Linxin Jiang received doctoral study support from the China Scholarship Council (CSC; CSC No. 202408440099) at University of Leipzig.

This study used data from publicly available database and published literature. No ethical approval and consent were required.

The authors have no conflicts of interest to disclose.

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

Supplemental Digital Content is available for this article.

How to cite this article: Jiang L, Li S, Reissmann DR, Kreher D, Schmalz G, Hu X. Oral health-related quality of life in systemic disease patients: A bibliometric analysis and visualization from 2001 to 2024. Medicine 2026;105:16(e48374).

Contributor Information

Linxin Jiang, Email: linxin.jiang@uni-leipzig.de.

Simin Li, Email: simin.li.dentist@gmail.com.

Daniel R. Reissmann, Email: Daniel.reissmann@medizin.uni-Leipzig.de.

Deborah Kreher, Email: Deborah.kreher@mhb-fontane.de.

Gerhard Schmalz, Email: Gerhard.Schmalz@mhb-fontane.de.

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