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Systematic scoping review of factors and measures of rurality: toward the development of a rurality index for health care research in Japan

BMC Health Services Research volume 21, Article number: 9 (2021) Cite this article

Abstract

Background

Rural-urban health care disparities are an important topic in health services research. Hence, developing valid and reliable tools to measure rurality is needed to support high quality research. However, Japan, has no index to measure rurality for health care research. In this study, we conducted a systematic scoping review to identify the important factors and methodological approaches to consider in a rurality index to inform the development of a rurality index for Japan.

Methods

For our review, we searched six bibliographic databases (MEDLINE, PubMed, CINAHIL, ERIC, Web of Science and the Grey Literature Report) and official websites of national governments such as Government and Legislative Libraries Online Publications Portal (GALLOP), from 1 January 1989 to 31 December 2018. We extracted relevant variables used in the development of rurality indices, the formulas used to calculate indices, and any measures for reliability and validity of these indices.

Results

We identified 17 rurality indices from 7 countries. These indices were primarily developed to assess access to health care or to determine eligibility for incentives for health care providers. Frequently used factors in these indices included population size/density and travel distance/time to emergency care or referral centre. Many indices did not report reliability or validity measures.

Conclusions

While the concept of rurality and concerns about barriers to access to care for rural residents is shared by many countries, the operationalization of rurality is highly context-specific, with few universal measures or approaches to constructing a rurality index. The results will be helpful in the development of a rurality index in Japan and in other countries.

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Background

Addressing rural-urban health care disparities is an important health system challenge. Numerous studies have reported that rural residents are more likely to have chronic diseases related to obesity, and less likely to engage in healthy behaviours, compared to urban residents [1,2,3,4]. Rural residents have poorer access to health care providers and have fewer visits to family physicians and specialists than urban residents [5, 6]. Moreover, living in a rural area is associated with lower physical/social functioning, mental health, self-reported health status [7], cancer survival [8], and overall quality of life [9]. Also, the recruitment and retention of the health care providers are major challenges in rural areas [10]. For example, Ontario, Canada originally developed the Rurality Index of Ontario (RIO) [11] in 2000 for policy purposes such as workforce incentives targeting physician recruitment and retention in rural areas [11]. Australia’s Modified Monash Model (MMM) [12] was based on Humphreys’s (2012) paper [13], and has been used to develop the recruitment and retention programs for health care providers [12]. However, a challenge for the development of rural indices is that many definitions of rurality exist as “rural” areas can include a wide range of community characteristics (e.g. level of affluence, degree of industrialization) [14, 15]. Yet most definitions of rurality focus on geographic characteristics (e.g., low population density or distance from health care resources) [14, 15], and not on social/cultural issues such as “way of life”, and “state of mind” associated with rural living that can affect health disparities [15]. Additionally, different methods have been used to calculate these indices. For example, the RIO used a sum of community population, travel time to nearest referral centre and travel time to nearest advanced referral centre to produce a continuous variable from 0 to 100 [11] while the MMM used a combination of population size and geographical remoteness to provide a 7-level classification with 1 representing a major city and 7 representing a high level of remoteness [12].

In Japan, researchers and policy makers do not have a rurality index. Japan has 6800 islands and 683,000 (0.5% of overall population) live on these islands [16]. Also, 11 million people live in rural areas called “depopulated areas” (11% of overall and the area is 58% of all areas) and 130,000 people live in “districts without a doctor (the areas are defined as the area over 50 residents within a radius of 4 km with limited access) [16]. Although the national government classified the “depopulated areas” based on the municipality’s income, demand and population trends, it is determined subjectively with no concrete definition or formula to consistently apply [17]. This existing index fails to capture the variation in health status and physician resources, ignores socio-cultural considerations, and is not widely accepted by primary care physicians [18].

In order to report comparisons between communities, researchers from various jurisdictions have developed indices to measure and categorize different degrees of rurality. Ensuring that a rurality index is valid and reliable is an integral step in promoting the widespread acceptance of the index, gathering high quality data, and developing strategies to tackle health and health workforce disparities [19].

The goal of this study is to identify the important factors and methods of measuring rurality for health services research and health policy. This scoping review is the first step in a project to develop a rurality index for Japan. The findings will also be useful for other countries and rural health researchers.

Aims

The aims of the scoping review are to 1) describe the publication characteristics of rurality indices, 2) identify factors commonly used in rurality indices, and 3) assess validity and reliability properties of published rurality indices.

Methods

Study design

A systematic scoping review.

A systematic scoping review is a review of existing literature to clarify a complex concept and refine subsequent research [20]. Usually, a systematic scoping review does not assess the quality of included studies, unlike a systematic review [20]. Also, a systematic scoping review is different from a narrative review because the scoping process requires analytical reinterpretation of the included literature [20]. A systematic scoping review is suitable for a discipline in which the shortage of randomized control trials makes it difficult for investigators to conduct a systematic review [20].

Arksey and O′Malley [21] presented a five-stage methodological framework to be used for scoping reviews that was further expanded by Levac et al. [20] The framework includes the following stages: identification of the research question; identification of relevant studies; selection of studies; charting of the data; collation, summarizing and reporting the results.

The systematic scoping review answers the research question: what are the factors, methods, and any measures for reliability and validity of rurality indices used in health care and health system related research.

Search strategy (identifying relevant studies)

We included articles and websites in English and Japanese. We searched the following bibliographic databases (MEDLINE, PubMed, CINAHIL, ERIC, Web of Science and the Grey Literature Report) to identify relevant papers. Also, we searched Government and Legislative Libraries Online Publications Portal (GALLOP), Registry of Canadian Government Information Digitization Projects, Canadian Research Index – Microlog, Municipal Information Network, Canadian Public Policy Collection, United Nations digital library, the US Census website and Organization for Economic Co-operation and Development (OECD) library to look identify rurality indices employed by national/local governments around the world. Moreover, we used Japanese databases, Ichushi-Web, an online Japanese literature searching system provided by the non-profit Japan Medical Abstracts Society. Ichushi-Web includes roughly 10 million medical papers from 6000 journals in Japan and is often used for Japanese literature searches [22]. We included studies that were published from 1 January 1989 to 31 December 2018 (the last 30 years) and websites. The most recent search date was 10th September 2019. The search strategy was based on the following title/abstract keywords in English and Japanese: “rurality” OR “rurality index” OR “index of rurality” OR “rurality measurement” OR “remoteness index” OR “accessibility index” OR “population density index”. Moreover, we added “develop” OR “create” OR “construct” OR “generate”. In addition, we used MESH term: “Rural Health Services/classification” OR “peripherality index”. We also reviewed the reference lists of relevant studies to identify research that might have been missed in the database search.

Inclusion/exclusion criteria (study selection)

Literature searches and study selection were independently conducted by two investigators (MK and RO) and any discrepancies were resolved by discussion.

We excluded articles and websites that used a previously developed rurality index.

Data extraction (charting data)

To report each study, we followed the approach of described in the PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation [23]. This checklist includes 22 essential reporting items that reflect on the title, abstract, introduction, methods, results, discussion and funding [23]. Based on an initial search of the literature, we developed an extraction template that included the following elements:

title of the article, name of authors, years of publication, name of the journal/website, name of the index, publication status (yes/no), peer review status (yes/no), citation index by Web of Science, country/province, unit of analysis (geographical jurisdiction/health care institution/individual), types of variable of rurality index (continuous/categorical), purpose of the index (for general purpose/for health care policy and research), study design, selection of factors included in the index, reported measures of reliability and validity.

We classified the unit of analysis into three categories: geographical jurisdiction, health care institution, or individual. The unit of analysis may vary depending on the purpose of the index. To assess rurality in specific areas, geographical jurisdiction is suitable for unit of analysis. Health care institution is employed for measurement of rurality from the viewpoint of each medical institution. Individual-level rurality is used for assessing each person’s accessibility to health care.

We categorize the purpose of the index into two categories: for general purpose and for health care policy and research. An index created for general purposes can be used for various situations. An index created for health care policy or research purposes is developed to measure rurality specific to health care.

Results

After searching through the titles and abstracts of 1850 publications, 17 eligible publications [11, 12, 24,25,26,27,28,29,30,31,32,33,34,35,36,37,38] were identified. Reasons for exclusion are shown in Fig. 1.

Fig. 1
figure 1

Flow diagram for the selection of studies in the systematic scoping review

Full size image

Publication characteristics of the rurality indices

As shown in Table 1, 14 (82%) of the 17 articles have been published since 2000. Table 2 shows that the majority (13; 76%) have been published in Australia, Canada and the US. Three indices were developed in Europe (Germany, Italy, and Scotland) and only one index was developed in Asia (China). Of 17 indices, 12 (71%) were published in a peer-reviewed journal and five were posted online on the web.

Table 1 Publication characteristics of the rurality indices
Full size table
Table 2 Description of purpose, types of factors included, and unit of analysis of rurality indices
Full size table

MSU Montana State University, GIS Geographic Information System, PHCWA Primary Health Care Worker Accessibility index, RRS Rural Ranking Scale, IRR Index of Relative Rurality

Purposes of and factors in rurality indices

Thirteen indices (76%) were developed for health care policy or research purposes and four (24%) were developed for general purpose (Table 2). The indices developed for health care policy or research were primarily designed to measure access to health care resources or to determine incentives for health care providers based on rurality. Fourteen indices (82%) measured rurality as a continuous score.

The unit of analysis in each study was determined by the purpose of the index (Table 2). Twelve indices (71%) employed geographical jurisdiction (such as statistical local area, county, state, or postal code) as a unit of analysis. Three focused on a medical institution (general practice) and two targeted individuals as the unit of analysis. The factors included in each rurality index are shown in Table 3. These factors were included in an index based on previous literature search and the availability of data related to the factor. The most frequently used factor was population (size or density) (n = 11: 65%). Travel distance and time to emergency care and/or referral centre were also often employed (n = 7: 41% and 3: 18%, respectively). In four indices (24%), resource availability expressed either as the number of physicians (both primary care and specialists) or as physician/population ratio was included in the index.

Table 3 Publication details and included factors of rurality indices
Full size table

MSU Montana State University, GIS Geographic Information System, PHCWA Primary Health Care Worker Accessibility index, RRS Rural Ranking Scale, IRR Index of Relative Rurality

The 14 indices (82%) that calculated a continuous rurality score used a mathematical formula: e.g. summing up the included variables, log transformation or a more complex operation (Table 4). The formulas measured rurality as a continuous variable, such as 0 to 1 or 0 to 100. Geographic Information System (GIS) was used in five studies (29%), of which two studies (12%) employed a two-step floating catchment area method to assess geographical accessibility.

Table 4 Validity and reliability properties of rurality measures
Full size table

MSU Montana State University, GIS Geographic Information System, PHCWA Primary Health Care Worker Accessibility index, RRS Rural Ranking Scale, IRR Index of Relative Rurality

Validity and reliability properties

Fifteen indices (88%) did not examine reliability and 12 indices (71%) did not examine validity (Table 4). In some studies, test/re-test and Cronbach’s alpha were used to assess reliability. Validity was confirmed by examining correlation of the index with other measures.

Discussion

The scoping systematic review found 17 rurality indices from seven countries. We found that these indices were designed specifically for health care research and policy purposes than general use. This review found that while the concept of rurality and concerns about barriers to access to care for rural residents is shared by many countries the approach to constructing an index was highly context specific. Although many indices were included, population size/density and travel time/distance to an advanced medical centre, none of the factors were used in all indices. These findings are consistent with earlier literature reviews that also found that a rurality index is generally based on population size or density and measures of distance such as travel time [39].

Although social, cultural, economic factors are associated with rurality [14, 15], none of the indices incorporated these factors. These factors may be relevant in the development of a rurality index for Japan. For example, the clinical peripherality index in Scotland accounted for local characteristics such as location on an island [29]. Similarly, Japan has many remote islands [16] and sometimes a patient can access a secondary hospital only by a ship or an airplane. The rurality index in Japan has to consider frequency/number of a round-trip flights or water transport. Additional travel related factors such as the quality of roads, availability of public transport, difficulty of the terrain, and weather (e.g. amount of annual snowfall) may be important considerations in the Japanese context.

In terms of reliability and validity, only 12 and 29% of all indices examined these measures, respectively. Reliability refers to the consistent interpretation and application. In terms of validity, content validity, such as face validity, may be more important than other forms of validity due to the highly contextual nature of the index [40]. Thus, gathering advice from health care providers and policy makers may be an important step in developing a rurality index for Japan.

Study strengths

To the best of our knowledge, this is the first systematic scoping review about the methods and measures used in the development of a rurality index. Given the variability in the definition of rural and uses of a rurality index, a systematic review may never be an appropriate review method. However, summarizing information from existing indices through a scoping review s helpful in the development of new rurality index.

Study limitations

This study has several limitations. First, we may have excluded potential indices, such as, an index developed for a specific research question or analysis that may not be generalizable or useful in developing a standardized rurality index. We also excluded classification schemes based on population or census area because these classifications do not take access to health care resources into account.

Conclusion

We identified 17 rurality indices by conducting the systematic scoping review. Although the operationalization of rurality is highly context specific, some variables were frequently employed in multiple countries/areas. The results will be helpful to develop a rurality index in Japan and other countries/areas.

Availability of data and materials

All data relevant to the study are included in the article.

Abbreviations

GALLOP:

Government and Legislative Libraries Online Publications Portal

MMM:

Modified Monash Model

OECD:

Organization for Economic Co-operation and Development

RIO:

Rurality Index of Ontario

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Acknowledgements

We thank David Le Sauvage, a retired member of Western Libraries Teaching and Learning Team and the Canadian Library of Family Medicine, for his assistance in the developing the search strategy, and Machiko Inoue, Department of Family and Community Medicine, Hamamatsu University School of Medicine, for the warm support in the planning the study. We also thank the members of the committee of rural and remote medicine in the Japan Primary Care Association.

Funding

This study was supported by the Grant-in-Aid for Young Scientists. The study sponsor had no role in the study design, data collection, analysis and interpretation, writing of the report, or the decision to submit the article for publication.

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Authors and Affiliations

  1. Primary Care Research Unit, Graduate School of Health Data Science, Yokohama City University, 22-2, Seto, Kanazawa-ku, Yokohama, Kanagawa, 236-0027, Japan

    Makoto Kaneko

  2. Department of Family and Community Medicine, Hamamatsu University School of Medicine, 1-20-1, Handayama, Higashi-ku, Hamamatsu, 431-3192, Japan

    Makoto Kaneko

  3. Department of Family Medicine, Schulich School of Medicine & Dentistry, Western Centre for Public Health and Family Medicine, London, Ontario, Canada

    Makoto Kaneko, Evelyn Vingilis, Maria Mathews & Thomas Robert Freeman

  4. Department of Community Care, Unnan City Hospital, 699-1221 96-1 Iida, Daito-Cho, Unnan City, Shimane, Japan

    Ryuichi Ohta

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Contributions

MK designed the study. MK and RO participated in the implementation, data collection and data analysis. MK took part in writing of the manuscript. MK also serves as the guarantor. EV, MM and TF contributed the design of the study and critically reviewed the manuscript. All authors had full access to the data and take responsibility for the integrity of the data and accuracy of the analysis. The author(s) read and approved the final manuscript.

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Correspondence to Makoto Kaneko.

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The study did not require ethical approval because the study was a review of the published articles and websites.

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Kaneko, M., Ohta, R., Vingilis, E. et al. Systematic scoping review of factors and measures of rurality: toward the development of a rurality index for health care research in Japan. BMC Health Serv Res 21, 9 (2021). https://doi.org/10.1186/s12913-020-06003-w

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