Introduction
Lonely people can be at increased risk of death (Elovainio et al., Reference Elovainio, Hakulinen, Pulkki-Råback, Virtanen, Josefsson, Jokela, Vahtera and Kivimäki2017). In many countries, loneliness has arisen in the last few years on the policy agenda as an important societal challenge, which was amplified by the COVID pandemic (Lampraki et al., Reference Lampraki, Hoffman, Roquet and Jopp2022). Moreover, socially and emotionally satisfying contacts can form a buffer against loneliness in later life when negative life events may occur (Switsers et al., Reference Switsers, Dierckx, Domènech-Abella, De Donder and Dury2021). Although loneliness in older adults is sometimes called a “silent epidemic,” estimates of loneliness prevalence differ widely across nations and across different assessment scales.
Perlman and Peplau defined loneliness in 1981 as “the unpleasant experience that occurs when a person’s network of social relations is deficient in some important way, either quantitatively or qualitatively” (Perlman & Peplau, Reference Perlman, Peplau, Duck and Gilmour1981, 31). De Jong Gierveld’s definition from 1987 adds that “this includes situations, in which the number of existing relationships is smaller than is considered desirable or admissible, as well as situations where the intimacy one wishes for has not been realized” (de Jong Gierveld, Reference de Jong Gierveld1987, 120). Both definitions describe loneliness as a negative and subjective feeling, which is in contrast to, e.g. social isolation, which refers to the objective situation and the absence of relationships with other people (De Jong Gierveld et al., Reference De Jong Gierveld, van Tilburg, Dykstra, Vangelisti and Perlman2006).
The WHO reports that there are no global assessments of the proportion of community-dwelling older people who are experiencing loneliness, but estimates that between 20% and 34% of older people in China, Europe, Latin America and the United States are lonely (World Health Organization, 2021). A recent meta-analysis based on prevalence data from 106 countries in 24 studies suggests that older adults (≥ 60 years; not explicitly community dwelling) in general have a higher prevalence of loneliness compared with their younger counterparts (i.e., young adults [18–29 years] and middle-aged adults [30–59 years]) (Surkalim et al., Reference Surkalim, Luo, Eres, Gebel, van Buskirk, Bauman and Ding2022).
Today, however, there is a high variability in loneliness prevalence (Surkalim et al., Reference Surkalim, Luo, Eres, Gebel, van Buskirk, Bauman and Ding2022). Possible explanations are differences in culture (Jylhä & Jokela, Reference Jylhä and Jokela1990), demography (Fokkema et al., Reference Fokkema, De Jong Gierveld and Dykstra2012), socioeconomic status (Hansen & Slagsvold, Reference Hansen and Slagsvold2016) or trust (Rapolienė & Aartsen, Reference Rapolienė and Aartsen2021). Another recent systematic review and meta-analysis on the prevalence of loneliness among older people in high-income countries (not explicitly community dwelling) hypothesizes that high variability between different prevalence studies could be influenced by differences in used measurement instruments and different modes of data collection (e.g., face-to-face, written questionnaires, etc.) (Chawla et al., Reference Chawla, Kunonga, Stow, Barker, Craig, Hanratty and Aslam2021). Today, the use of different measurement instruments is increasing (e.g., Awad et al., Reference Awad, Shamay-Tsoory and Palgi2023) using the De Jong Gierveld Loneliness Scale and Ost-Mor et al. (Reference Ost-Mor, Segel-Karpas, Palgi, Yaira, Mayan, Ben-Ezra and Greenblatt-Kimron2023) using the (University of California-Los Angeles (UCLA) Loneliness Scale, so the multidimensionality of loneliness is already widely recognized.
However, current research suggests that loneliness measures should be considered carefully in relation to the opposed research question(s) of a study and encourages researchers to include multiple measures in their studies to ensure robustness and to identify potential discrepancies among measures in existing and future research (Mund et al., Reference Mund, Maes, Drewke, Gutzeit, Jaki and Qualter2022). Su et al. (Reference Su, Rao, Li, Caron, D’Arcy and Meng2023) published a systematic review on the prevalence of loneliness and social isolation among older adults during the COVID-19 pandemic, but the influence of measurement instrument and mode of data collection were not treated. Through a systematic literature review and meta-analysis, this study reviews the prevalence of loneliness among community-dwelling older adults in countries worldwide and examines the study characteristics of these loneliness prevalence studies with specific attention to the influence of measurement instruments, mode of data collection, and the country where the study was conducted.
Methods
Search strategy and selection criteria
This study follows the recommendations of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement (Page et al., Reference Page, McKenzie, Bossuyt, Boutron, Hoffmann, Mulrow, Shamseer, Tetzlaff, Akl, Brennan, Chou, Glanville, Grimshaw, Hróbjartsson, Lalu, Li, Loder, Mayo-Wilson, McDonald, McGuinness, Stewart, Thomas, Tricco, Welch, Whiting and Moher2021). We screened seven electronic databases, i.e., Web of Science, PubMed, Sociological Abstracts, Social Services Abstracts, Embase, PsycINFO, and Cochrane Library, for eligible studies. The literature search included studies published between January 1, 1992 and October 31, 2021. We used “loneliness” as a search term in the title, “community-dwelling older adults” and “prevalence” as search terms in title and abstract, as well as possible variations, keywords and MeSH headings, if applicable for the database. The detailed search strategy can be found in Appendix 1 (published as supplementary material online attached to the electronic version of this paper at https://www.cambridge.org/core/journals/international-psychogeriatrics).
Authors HS and HC selected the studies derived from Web of Science and PubMed. HS and DD selected studies from Sociological Abstracts, Social Services Abstracts, PsycINFO, Embase, and Cochrane Library. After removing duplicates for both selection processes, a random sample of 10% was assessed by HS and HC for Web of Science and PubMed, and by HS and DD for the five other databases, to make sure the different authors selected studies based on the same benchmarks. To decide upon inclusion, the title, the abstract and eventually the full text of the study (if necessary) were screened. When one of the selection criteria was not met, the study was excluded without evaluating the other selection criteria. In case of doubt, HP, LDD, and ED decided together upon in- or exclusion. Reference lists from the included studies and studies citing our included studies were screened in the final stage to assure no further studies would be left unnoticed.
Studies were eligible if “loneliness” or “lonely” was mentioned in the title of English-language peer-reviewed studies and if data was reported on a non-clinical population of community-dwelling older adults where a minimum age of 60 years was specified. The definition of community-dwelling older people by Steultjens et al. (Reference Steultjens, Dekker, Bouter, Jellema, Bakker and van den Ende2004) was followed, stating that community-dwelling older people are “people aged 60 years or older living independently,” and therefore not living in institutionalized settings such as nursing homes, care homes or other types of residential care (Steultjens et al., Reference Steultjens, Dekker, Bouter, Jellema, Bakker and van den Ende2004). The final inclusion criterion was that studies should have as an explicit aim to estimate the loneliness prevalence, since clearly outlining the explicit purpose of the study contributes to a paper of better quality (Mack, Reference Mack2015). The primary objective of prevalence studies is to produce frequency estimates for the overall population, and sometimes population subgroups (Boyle, Reference Boyle1998). Altogether, prevalence studies about loneliness among community-dwelling older adults were selected for this study. Studies from all countries and world regions were included to get a complete image of existing prevalence studies and the corresponding loneliness measurement instruments and modes of data collection, since there are known differences between countries and cultures in terms of loneliness prevalence.
Data analysis
The following data were extracted: year of publication, year of data collection, was the study conducted pre- or during-COVID, sample size (of loneliness questions), percentage of women, type of sample, country (reclustered into region), level on which the study was conducted (national or regional), mode of data collection, data source (own or existing dataset), and used measurement instruments.
As part of the meta-analysis, the quality of the studies was appraised by HS and DD using the Joanna Briggs Institute (JBI) Critical Appraisal Checklist (Munn et al., Reference Munn, Barker, Moola, Tufanaru, Stern, McArthur, Stephenson and Aromataris2020). HS and DD first appraised all studies separately, and when no initial consensus was found, they decided together upon inclusion. Following JBI Checklist guidelines, studies included for review were given a quality cutoff score (Munn et al., Reference Munn, Barker, Moola, Tufanaru, Stern, McArthur, Stephenson and Aromataris2020), whereby studies with a “low-quality” score (0–3) were excluded and studies with moderate (4–6) and high (7–9) quality scores were included for the meta-analysis. We also excluded papers in the meta-analysis if they used data that had already been used in another paper or data that originated from the same wave in the same database, and included the most complete or recent studies.
For the meta-analysis, carried out by PS and HS, supervised by LS, uniform response options were needed, and therefore we dichotomized the loneliness answers of all the studies to include them in the meta-analysis; this means that studies with more than two categories were also dichotomized. Furthermore, for articles using the De Jong Gierveld loneliness scale, when other cut-off scores than the proposed scores of De Jong Gierveld & van Tilburg (De Jong Gierveld & van Tilburg, Reference De Jong Gierveld and van Tilburg1999) were used, we recalculated the prevalence percentages, using the original dataset received upon request from the original authors. For the UCLA loneliness scales, we did not do this, since the authors did not propose any cutoff scores and since they indicated that there are no diagnostic criteria for being lonely (Russell, Reference Russell1996). We therefore followed the cutoff that each of the studies proposed since we then had some clarity in who is considered as “lonely” in each of the studies.
In this review, all measurement instruments capture momentary loneliness, meaning that they measure loneliness as it is “now,” at the moment of measuring (Compernolle et al., Reference Compernolle, Finch, Hawkley and Cagney2021). The answers of the participants, both on the De Jong Gierveld Loneliness Scale as well as on the UCLA Loneliness Scale and the single-item questions, are subjective to how people feel at the moment of answering the question(s), even if they ask about loneliness, e.g., in the past week. Of all prevalence studies, none included a measurement tool that measured lifetime prevalence. This means that in this study, specifically point prevalences of loneliness are being studied. Therefore, it was appropriate to compare all the different prevalence percentages, since they all cover this momentary loneliness, mentioning a point prevalence percentage of loneliness.
Further information on the quality appraisal including the completed JBI Critical Appraisal Checklist for each study can be found in Appendix 2, as well as an overview of the classification (not/mildly lonely vs. lonely) that can be found in Appendix 3 (both published as supplementary material online attached to the electronic version of this paper at https://www.cambridge.org/core/journals/international-psychogeriatrics).
Following this, two steps were undertaken: the calculation of the pooled prevalence and a moderator analysis. First, a generalized linear mixed model (GLMM) was constructed. Such a model can directly model event counts with binomial likelihoods and fully account for within-study uncertainties (Lin & Xu, Reference Lin and Xu2020). This approach has several advantages over the two-step meta-analysis which typically uses the Freeman–Tukey double arcsine transformation (Lin & Xu, Reference Lin and Xu2020). In particular, we used a random intercept logistic regression model with a logit link function for the calculation of pooled prevalence rates (van Den Noortgate & Onghena, Reference van Den Noortgate and Onghena2003). The outcome thus was the prevalence of loneliness (individual proportions) measured as the number of lonely older adults among the sample. A three-level meta-analytic model was used to analyze the data (Assink & Wibbelink, Reference Assink and Wibbelink2016), modeling three sources of variance: sampling variance of the observed prevalence rates (Level 1), the variance between prevalence rates from the same study (Level 2), and variance between studies (Level 3) (Cheung, Reference Cheung2014; Van den Noortgate et al., Reference Van den Noortgate, López-López, Marín-Martínez and Sánchez-Meca2013). Results were back-transformed for easier interpretation.
Second, a multilevel random effects model was used for the moderator analyses to evaluate the impact of the measurement scale, the mode of data collection, and the country where a study was conducted on loneliness prevalence: the F-distribution was utilized to determine whether the pooled prevalence of loneliness was significantly affected by the moderators. Two separate one-tailed log-likelihood-ratio tests were conducted, comparing the deviance of the full model to the deviance of a model that excluded one of the variance parameters, to determine whether respectively the variance between prevalence rates within studies (Level 2) and the variance between studies (Level 3) was significant. All model parameters were estimated using the maximum likelihood estimation method. We considered p-values < 0.05 as statistically significant. The statistical analyses were carried out using the dmetar and metafor-packages (Viechtbauer, Reference Viechtbauer2010) in R (version 4.2.1).
To look at the effect of country, we used the six dimensions of Hofstede (Hofstede, Reference Hofstede2011), i.e., the Power Distance Index, Individualism, Motivation towards Achievement and Success, the Uncertainty Avoidance Index, Long-Term Orientation, and Indulgence. Despite the fact that there are some critiques on these dimensions now because of the idea of oversimplification and the static nature of cultures that these dimensions entangle (Chun et al., Reference Chun, Zhang, Cohen, Florea and Genc2021; Minkov, Reference Minkov2018), the Hofstede dimensions were used because they do provide a standardized way to compare cultures and they increase the awareness and sensitivity to cultural norms (Hofstede Insights, 2023). Moreover, this study is not necessarily about the precise meaning and labeling of the dimensions, but about comparing cultural aspects measured with the same scale in each individual country in the first place.
The Power Distance Index signifies a society’s acceptance of hierarchical power distribution – a higher score indicates a greater acceptance of inequality. Second, there is the spectrum of Individualism versus Collectivism, where higher scores suggest weaker interpersonal connections beyond the core “family,” and less responsibility for others’ actions. The dimension of Motivation towards Achievement and Success is about what motivates people: wanting to be the best (Decisive; high score) or liking what you do (Consensus-oriented; low score). A high score means that the society is driven by achievement, success, and competition, while a low score indicates a society that is driven by quality of life as a sign of success. The Uncertainty Avoidance Index measures a society’s inclination to control unpredictability. A higher score indicates a preference for predictability and control in life. Long-Term Orientation versus Short-Term Orientation reflects a society’s inclination toward pragmatism, modesty, and thriftiness with higher scores indicating a long-term focus. Finally, Indulgence versus Restraint explores how freely people gratify their desires and emotions – higher scores indicate a more permissive approach to enjoying life and expressing emotions.
Using the Country Comparison Tool of Hofstede (Hofstede Insights, 2023), we obtained a score for every included country for each of these dimensions between 0 and 100. These scores were gathered from survey responses over time, starting between 1967 and 1973 but still going on until today (Hofstede Insights, 2023). The dimension identification happens through factor analysis or other scaling methods, and next, normalization of factor scores is done to fit data from previous studies. The validity comes from correlations with dimensions of previous studies and national indices such as educational achievement or crime rates (Hofstede Insights, 2023).
We centered the continuous scores around the grand mean and used a multilevel approach, in which effect sizes are nested within studies (van Den Noortgate & Onghena, Reference van Den Noortgate and Onghena2003) and which enables using all effect sizes in the primary studies so that maximum statistical power is achieved (Assink et al., Reference Assink, Van Der Put, Hoeve, De Vries, Stams and Oort2015).
The protocol of this review was registered at the International Prospective Register of Systematic Reviews (PROSPERO) (registration number: CRD42021230197).
Results
The initial search provided 2,021 studies. After removing 925 duplicates and screening the other 1,096 records, 512 records were excluded based on title (n = 251) and abstract (n = 261); 568 records were assessed for eligibility (16 records could not be retrieved), 523 records were eventually excluded (based on language (n = 30), target group (n = 110) and the lack of a prevalence percentage (n = 383)), and 45 studies were included. After the backward and forward snowball search, 17 studies were added. Ultimately, 62 studies were included in the systematic review and 45 in the meta-analysis (17 studies were excluded due to quality appraisal and double data). The Prisma flowchart is added as Figure 1. In 33 studies (Anil et al., Reference Anil, Prasad and Puttaswamy2016; Bao et al., Reference Bao, Li and Zhong2021; Carrasco et al., Reference Carrasco, Fernández, Alexander and Herrera2021; Chokkanathan, Reference Chokkanathan2020; Dahlberg et al., Reference Dahlberg, Andersson, McKee and Lennartsson2015; Fokkema et al., Reference Fokkema, De Jong Gierveld and Dykstra2012; Gao et al., Reference Gao, Prina, Prince, Acosta, Luisa Sosa, Guerra, Huang, Jimenez-Velazquez, Llibre Rodriguez, Salas, Williams, Liu, Acosta Castillo and Mayston2021; Groarke et al., Reference Groarke, Berry, Graham-Wisener, McKenna-Plumley, McGlinchey, Armour and Murakami2020; Hansen & Slagsvold, Reference Hansen and Slagsvold2016; Huang et al., Reference Huang, Chi, Kuo, Wu and Chuang2021; Igbokwe et al., Reference Igbokwe, Ejeh, Agbaje, Umoke, Iweama and Ozoemena2020; Lay-Yee et al., 2021; Nicolaisen & Thorsen, Reference Nicolaisen and Thorsen2014; O’Shea et al., Reference O’Shea, Finlay, Kler, Joseph and Kobayashi2021; Paúl et al., Reference Paúl, Ayis and Ebrahim2006; Paúl & Ribeiro, Reference Paúl and Ribeiro2009; Peltzer & Pengpid, Reference Peltzer and Pengpid2020; Perissinotto et al., Reference Perissinotto, Stijacic Cenzer and Covinsky2012; Phaswana-Mafuya & Peltzer, Reference Phaswana-Mafuya and Peltzer2017; Rantakokko et al., Reference Rantakokko, Iwarsson, Vahaluoto, Portegijs, Viljanen and Rantanen2014; Rapolienė & Aartsen, Reference Rapolienė and Aartsen2021; Routasalo et al., Reference Routasalo, Savikko, Tilvis, Strandberg and Pitkälä2006; Srivastava et al., Reference Srivastava, Ramanathan, Dhillon, Maurya and Singh2020; Stickley et al., Reference Stickley, Koyanagi, Roberts, Richardson, Abbott, Tumanov, McKee and Mendelson2013; Theeke, Reference Theeke2010; Tomstad et al., Reference Tomstad, Dale, Sundsli, Saevareid and Söderhamn2017; Vozikaki et al., Reference Vozikaki, Papadaki, Linardakis and Philalithis2018; Yang & Victor, Reference Yang and Victor2008, Reference Yang and Victor2011; Zebhauser et al., Reference Zebhauser, Hofmann‐Xu, Baumert, Häfner, Lacruz, Emeny, Döring, Grill, Huber, Peters and Ladwig2014; Zhang et al., Reference Zhang, Xu, Li, Sun, Ding, Qin, Wang, Zhu, Yu and Xie2018; van den Broek, Reference van den Broek2017; van Tilburg, Reference van Tilburg2021), the answer to the loneliness question to obtain the prevalence percentages was dichotomized (yes vs. no), while 29 studies (Öztürk Haney et al., Reference Öztürk Haney, Bahar, Beşer, Açıl, Yardımcı and Çömez2017; Cheng et al., Reference Cheng, Jin, Sun, Tang, Zhang, Chen, Zhang, Zhang and Huang2015; Djukanović et al., Reference Djukanović, Sorjonen and Peterson2015; Gibney et al., Reference Gibney, Delaney, Codd and Fahey2017; Holmén et al., Reference Holmén, Ericsson, Andersson and Winblad1992; Kearns et al., Reference Kearns, Whitley, Tannahill and Ellaway2015; La Grow et al., Reference La Grow, Neville, Alpass and Rodgers2012; Losada et al., Reference Losada, Márquez-González, García-Ortiz, Gómez-Marcos, Fernández-Fernández and Rodríguez-Sánchez2012; Savikko et al., Reference Savikko, Routasalo, Tilvis, Strandberg and Pitkälä2005; Steed et al., Reference Steed, Boldy, Grenade and Iredell2007; Stickley et al., Reference Stickley, Koyanagi, Leinsalu, Ferlander, Sabawoon and McKee2015; Sundström et al., Reference Sundström, Fransson, Malmberg and Davey2009; Victor et al., Reference Victor, Scambler, Bowling and Bond2005, Reference Victor, Scambler, Marston, Bond and Bowling2006; Victor & Yang, Reference Victor and Yang2012; Victor & Bowling, Reference Victor and Bowling2012; Wang et al., Reference Wang, Snyder and Kaas2001, Reference Wang, Zhang, Wang, Li, Shen, Ge and Hang2011; Susheela et al., Reference Susheela, Valsaraj and Savitha2018; Chow et al., Reference Chow, Wong and Choi2021; Clark et al., Reference Clark, Bonnici and Azzopardi2021; Dahlberg et al., Reference Dahlberg, Agahi and Lennartsson2018; Devkota et al., Reference Devkota, Mishra and Shrestha2019; Ho et al., Reference Ho, Cheung, Lee, Lam and Kwan2021; Jia & Yuan, Reference Jia and Yuan2020; Joseph et al., Reference Joseph, Nalini and Santhi2020; Lee, Reference Lee2020; Li & Wang, Reference Li and Wang2020; Torres et al., Reference Torres, Braga, Moreira, Sabino Castro, Vaz, Andrade, Bof Andrade, Lima-Costa and Caiaffa2021) originally distinguished between different loneliness categories (e.g., never vs. seldom vs. sometimes vs. often lonely, etc.).
Figure 1. PRISMA flowchart of the included studies.
In our systematic review, most prevalence data (k = 125, 70.6%) spanned from 2006 to 2015, and a majority (k = 127, 71.8%) came from European countries. The majority of the data collection was done face-to-face (k = 114, 64.4%), and through single-item questions (k = 139, 78.5%). Table 1 shows an overview of the study characteristics of the included studies in both the systematic review and meta-analysis. Table S1 specifically shows an overview of the study characteristics related to the loneliness prevalence found in the studies. While we included 62 studies in our systematic review, several studies included prevalence percentages of different countries, with corresponding differences in, e.g., sample size and percentage of women (compared with men), leading to separate prevalence rates designated as “k” (k = 177 for the systematic review and k = 101 for the meta-analysis). Appendix 4 (published as supplementary material online attached to the electronic version of this paper at https://www.cambridge.org/core/journals/international-psychogeriatrics) gives an overview of the study characteristics per study.
Table 1. Summary of the research characteristics
n, number of studies (i.e., scientific articles) included; k, number of prevalence rates (separated by country) mentioned throughout the studies.
Calculation of the pooled prevalence of loneliness
A total of 45 studies were included in the meta-analysis reporting on n = 168 473 participants with valid prevalence percentages; n = 107 267 using single-item questions, n = 9795 using the UCLA 20-item scale, n = 13 668 using a shortened version of the UCLA scale, n = 37, 339 using the De Jong Gierveld (DJG) scale and n = 404 using a combination of different measures. Within these 45 studies, a total of 101 prevalence percentages were extracted. Descriptive information on the demographic and methodological characteristics is summarized in Table 1. The median of the included prevalence percentages was 26.0% (IQR 14.0% to 45.0%). Appendix 5 (published as supplementary material online attached to the electronic version of this paper at https://www.cambridge.org/core/journals/international-psychogeriatrics) presents four forest plots showing the prevalences of all the included studies in the meta-analysis, for each measurement instrument separately.
Table 2 presents the estimated pooled prevalence of loneliness among community-dwelling older adults based on the random-effects model. The pooled prevalence was 31.6% (95% CI 24.4–39.9) and it was statistically significant (p < .001). The results of the likelihood-ratio test showed there was significant within-study variance (at level 2, X ² (1) = 57.06, p < .001) as well as significant between-study variance (at level 3, X ² (1) = 6221.89, p < .001). From Table 2, 0.23% of the total variance could be attributed to variance at level 1 (i.e., sampling error variance), 28.03% of the total variance to differences between the prevalence of loneliness within studies at level 2 (i.e., within-study variance) and 71.74% of the total variance could be attributed to differences between studies at level 3 (i.e., between-study variance).
Table 2. Results for the overall pooled prevalence percentage
Moderator analysis
We performed moderator analyses to assess the effect of measurement instruments, the mode of data collection, and the country where the study was conducted on the pooled loneliness prevalence. The results of all univariate moderator analyses are presented in Table 3.
Table 3. Results for univariate moderator analysis
Measurement instrument was a statistically significant moderator of the overall prevalence of loneliness (F (3, 96) = 11.03, p < .001). A significantly lower pooled prevalence of 21.2% (95% CI 15.7–27.9) (p < .001) was observed for loneliness prevalence measured using 1-item questions, compared to the 20-item UCLA loneliness scale reporting the highest pooled prevalence of 59.3% (95% CI 43.9–73.0). For the De Jong Gierveld loneliness scale, the pooled prevalence was 55.4% (95% CI 38.6–71.1) which was significantly different from 1-item questions (p < .001). The variance between studies (level 3) decreased by 63% from 1.091 to 0.400 after adjusting for measurement instrument as moderator.
We also found moderating effects of the mode of data collection on the overall pooled prevalence (F (3, 96) = 3.23, p = .008). This implied there were significant differences between the pooled prevalence from the four data collection methods. The loneliness prevalence for face-to-face data collection was 39.4% (95% CI 30.0–49.6), being significantly higher than telephone and CATI (14.6% [95% CI 6.3–30.4]) and self-report (19.2% [95% CI 10.5–32.6]). However, this moderator explained the variability between studies only modestly as the level 3 variance decreased by only 8% (from 1.091 to 1.002).
Regarding the effect of country, four of the six dimensions of Hofstede were significant (p < .001). The prevalence of loneliness among community-dwelling older adults was significantly higher (compared to the initial 31.6% we found) in a country with the mean score of our sample on the Power Distance Index (32.5% [95% CI 25.5–40.4]), the Uncertainty Avoidance Index (35.9% (95% CI 27.4–45.4)) and the Indulgence index (34.0% [95% CI 26.9–41.9]). Countries with a mean score of our sample on the Individualism index had a significantly lower pooled prevalence of loneliness (30.6 [95% CI 23.8–38.4]). The dimension of Long-Term Orientation was not significant (p = .073), as well as the dimension of Motivation towards Achievement and Success (p = .152).
To check for residual heterogeneity, which is the remaining variability between the studies not accounted for by the moderators, we fitted a model with all the significant moderator variables. After adjusting for these variables, 0.34% of the total variance was attributed to the sampling error variance (level 1), 15.97% to differences within studies (level 2); and 83.69% of the total variance could be attributed to differences between studies (level 3).
Discussion
This systematic review and meta-analysis reports on the prevalence of community-dwelling older adults, as well as the impact of the used measurement instrument, mode of data collection, and country on reported prevalence percentages. Using 101 prevalence percentages from 45 studies, our study demonstrates that the pooled prevalence of loneliness among community-dwelling older adults is 31.6%. This percentage corresponds greatly to the percentage of a previous systematic review and meta-analysis on the prevalence of loneliness among older people in high-income countries (not explicitly community-dwelling), which was 28.5% (Chawla et al., Reference Chawla, Kunonga, Stow, Barker, Craig, Hanratty and Aslam2021). Our results show that the (level 3) variance of pooled loneliness prevalence that can be explained was 63% by differences in the used measurement instrument and 8% by data collection method.
The prevalence of loneliness is lower for single-item questions (21.2%) and shortened UCLA scales (25.0%), compared to the 20-item UCLA (59.3%) and the De Jong Gierveld loneliness scale (55.4%), where the loneliness rates are significantly higher. This might be a result of the fact that single-item questions, and by extension short measurement scales, may be more vulnerable to certain biases in interpretation and meaning as well as on social desirability, and that multiple-item scales are more prone to cover the whole range of a complex construct, such as, in this case, loneliness (Hoeppner et al., Reference Hoeppner, Kelly, Urbanoski and Slaymaker2011). Looking at the used measurement instruments, single-item questions are indeed more often used despite the existence of validated instruments and despite the critiques on single-item questions mentioning that these cannot capture a construct in all its complexity (Mund et al., Reference Mund, Maes, Drewke, Gutzeit, Jaki and Qualter2022).
For the mode of data collection, loneliness prevalence rates vary from 14.6% for telephone interviews (including CATI) to 39.8% for CAPI. A study specifically about the De Jong Gierveld loneliness scale suggests that data collection procedures indeed can have an impact on the motivation, accuracy, and self-disclosure of the participants while being subject to the data collection (van Tilburg & de Leeuw, Reference van Tilburg and de Leeuw1991), and this is thus also visible in our review.
Regarding the country, four of the six dimensions of Hofstede (Hofstede, Reference Hofstede2011) caused a significant increase (Power Distance Index, Uncertainty Avoidance Index, Indulgence) or a decrease (Individualism) in loneliness prevalence. Also here, we see that country, and more broadly, culture (Jylhä & Jokela, Reference Jylhä and Jokela1990), should be taken into account when making statements about loneliness prevalence among community-dwelling older adults.
The main strengths of this study are that the search strategy and the analyses were thoughtfully carried out and the choice of prevalence studies specifically on community-dwelling older people was made consciously, as we assessed the risk of bias very thoughtfully through our selection process. Moreover, despite the high heterogeneity of our pooled prevalence percentages, we assessed the quality of our studies carefully utilizing the JBI Critical Appraisal checklist (Munn et al., Reference Munn, Barker, Moola, Tufanaru, Stern, McArthur, Stephenson and Aromataris2020), so that a high quality of the included studies and their data collection methods and measures was ensured.
However, results from this study should also be viewed with caution in light of its limitations. First, although a comprehensive search is seen as a potential mechanism for minimizing bias (Cooper et al., Reference Cooper, Booth, Varley-Campbell, Britten and Garside2018), our selection criteria were rather strict. It is possible that because of this, certain percentages were excluded while they would have been included if the criteria were less rigorous. Another limitation is that the field of loneliness research is a rapidly evolving research area, certainly as a result of the COVID pandemic (Lampraki et al., Reference Lampraki, Hoffman, Roquet and Jopp2022). This means that we could have missed certain studies published since our search was conducted. Third, not all world regions were equally represented in our study: in our systematic review, a low number of prevalence percentages obtained in Africa (k = 2) and Oceania (k = 5) were included, mainly due to the lack of loneliness prevalence studies from these regions, in contrast to prevalence percentages originating in Europe (k = 127) or Asia (k = 31). To capture the diversity in the included countries, however, we used Hofstede’s dimensions (Hofstede, Reference Hofstede2011). Although we were aware of the prevailing criticisms surrounding this model (Chun et al., Reference Chun, Zhang, Cohen, Florea and Genc2021; Minkov, Reference Minkov2018), the standardized scores and the possibility of comparing countries were decisive to incorporate them in this study. Fourth, we split the UCLA scale into two groups in our analyses (i.e., the original and the shortened scale separately), but this was not done for the DJG due to an insufficient number of prevalence percentages in the two subcategories (i.e., the original vs. the shortened version) to be allowed to conduct separate statistical analyses. Possibly, more studies with the 11-item DJG could provide additional information on the differences between the original and the abbreviated scale. Furthermore, in our meta-analysis, we could not include several possible moderators because they were not consistently mentioned, such as the year of data collection (k = 11) or the percentage of men or women (k = 46), or because the sample size was relatively small (only k = 34 had a sample size of > 1000). Also, age was not included as a moderator because information on age in the studies was incomplete or too heterogeneous. For example, in some studies, the age classes of 60–69, 70–79, and 80+ were used, while 60–74 and 75+ were used in other studies. In addition, numerous studies simply give little or no information on age: several mention a general age range of their participants (e.g., 60–85), but there was no further information on the difference in loneliness prevalence for different ages or age groups.
Future prevalence studies are therefore recommended to comprehensively capture participants’ characteristics, including potential loneliness risk factors such as education, marital status, percentage of people living alone, etc., which were frequently absent in the current studies. Additionally, while existing studies differentiate types of loneliness (social, emotional, and existential), specific prevalence percentages for these types of loneliness are often lacking.
This study reviewed the prevalence of loneliness among community-dwelling older adults. Our results show that measurement instruments, mode of data collection, and country acted as moderator variables, leading to varying loneliness prevalence percentages. Nevertheless, considerable variation within and between studies suggests the influence of other factors, such as participant age and gender. Future prevalence studies should consider the contextual impact, including respondents’ personal and cultural characteristics, as well as study design, on reported loneliness prevalence rates.
Supplementary material
Supplementary material. The supplementary material for this article can be found at https://doi.org/10.1017/S1041610224000425.
Data availability
The extracted data that support the findings of this study are available upon reasonable request of researchers to the corresponding author (HS; hannelore.stegen@vub.be). The study protocol has been published on PROSPERO, https://www.crd.york.ac.uk/prospero/display_record.php?RecordID = 230197.
Conflict of interest
None.
Funding
This study was funded by the Research Foundation Flanders (FWO) (grant number: 11J7821N/11J7823N).
Description of author(s)’ roles
HS, DD, LDD, and ED conceived the study. HS, HC, and DD were involved in the data selection process, and DD conducted the critical appraisal together with HS. PS ran the statistical analyses, with the support of LS, and discussed them regularly with HS. HP and MA read the paper thoroughly and provided additional valuable comments. All authors had an important advisory voice in the paper writing process and provided critical comments on the manuscript.
Open access
