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Abstract

The impact of Home- and Community-Based Services (HCBS) on the health of older adults has been a topic of concern for geriatric health and policy development. However, the existing studies have yielded inconsistent empirical findings. This meta-analysis aimed to assess the effectiveness of HCBS on the physical and mental health of older adults. We conducted a meta-analytic examination of 26 correlations in 11 separate studies, using random-effects meta-analysis to pool the data. The findings support a positive relationship between HCBS and the health of older adults, with a highly significant positive correlation with mental health (r = .532, 95% CI: [0.201, 0.864]) and a weak positive correlation with physical health (r = .076, 95% CI: [−0.171, 0.324]) in older adults. The study found high correlations between HCBS and well-being and depression relief, while the correlations between HCBS and self-rated health (SRH) and physical function were moderate and weak, respectively. Furthermore, the effects did not differ across different measurements of HCBS, duration of service, or country of investigation. These findings suggest that practitioners should develop precise integration of community care services with healthcare services, providing a full spectrum of services throughout the lifecycle to enhance the health and well-being of older adults.

Plain language summary

How home and community services affect the health of older adults: A comprehensive review of many studies

Researchers wanted to know how home and community services, such as in-home care and neighborhood programs, influence the health of older persons. Different studies produced inconsistent outcomes. Thus, this study collected data from existing related studies to produce clearer answers. We found that these services have a notable positive impact on the mental health of older adults, helping to relieve depression and improve overall well-being. Older adults feel better about their health condition when they receive these services. However, these services do not prevent physical function decline as people age. The study showed that the results remained consistent no matter how these services were measured, how long they were provided, or where the study took place. This suggests that combining community care services with healthcare can greatly improve the health and happiness of older adults. It is important for community to provide a full range of services to support older adults throughout their lives.

Keywords

HCBS meta-analysis physical health mental health older adults

Introduction

The worldwide population of older adults was 41.4 million, representing 13% of the total population in 2011; this proportion is predicted to increase to 33% by 2031 (Administration on Aging, 2013). The majority of older adults wish to age at home until the end of life (Productivity Commission, 2017; Ryan et al., 2009). Furthermore, the process of aging process often leads to a decline in functional performance and other health-rated behaviors (Verbrugge & Jette, 1994). Given the rising amount of older adults and their consequent increasing demand for supportive services provided to homebound older adults, many countries pay more attention to home- and community-based services (HCBS), which are primarily government-funded and aim to enable older adults to age in their communities rather than relocating to a care facility (Centers for Medicare & Medicaid Services, 2021).

In the United States, The HCBS program was initiated in 1973 and provided funding to states and territories depending on their proportion of the national population with an age of 60 and older (Administration for Community Living, 2014). With the accelerating process of population aging, HCBS has gained widespread adoption and development across numerous countries. These programs aim to meet the growing demand for services that address the daily living, medical, and social demands of older adults, thereby supporting the daily lives of older adults despite declining health and functioning (Kane, 2012). HCBS encompasses a variety of services specifically to address the daily living, medical, and social requirements of older adults (Watts et al., 2020; Wiles et al., 2009). Previous research defined HCBS as a range of services designed to meet the daily living, medical, and social needs of older adults. By providing these services, older adults could live independently in familiar environments such as their homes and communities (Alkema et al., 2006). In this study, we define HCBS as a form of socialized elderly care that simultaneously addresses the professional healthcare requirements and emotional support needs of older adults. HCBS is more cost-effective, flexible, and adaptable than nursing homes (Watts et al., 2020). In addition, the provision of health-related services contributes to the increase of the health stock of individuals by utilizing a specialized production function (Grossman, 1972). Older adults often experience frailty and live with complex co-morbid health conditions, which is an unavoidable reality. Declining health has become a prominent worry among older adults (Chamberlain et al., 2022). In this reality, promoting health is the fundamental responsibility of all nurses (Stievano & Tschudin, 2019). Thus, it is imperative to examine the impact of HCBS on the health of older adults.

HCBS can be categorized into several main types, including day services, home-based services, residential services, provision of equipment, respite care, and transportation (Borck et al., 2012; Shirk, 2006). Specific services encompass daycare centers, congregate meals, home-delivered meals, personal care (e.g., bathing, dressing, toileting), health promotion and disease prevention, transportation services, money management, case management, and home-making services (Centers for Medicare & Medicaid Services, 2021). In this study, the intervention was determined by whether the older adults received HCBS. If an older adult had received at least one type of HCBS, they were considered to have received the intervention. Conversely, if they had not received any HCBS, they were considered not to have received the intervention.

The term “health” has been extensively used in various disciplines, and its definition is complex, broad, and varied (Song & Kong, 2015; Williamson & Carr, 2009). The World Health Organization (1948) defines health as a condition of complete physical, mental, and social well-being rather than simply the absence of diseases and infirmity. Given that some services (i.e., health promotion and disease prevention) influence the decline of physical health and other services (i.e., daycare centers, bathing, and home-delivered meals) influence depression and well-being (i.e., satisfaction and quality of life), eventually will affect the mental health of older adults. Therefore, our research defines health as a combination of physical and mental health concepts. When it comes to physical health, numerous studies have regarded self-rated health (SRH) as a significant independent predictor of both morbidity and mortality (Idler & Benyamini, 1997; Kaplan & Camacho, 1983; Ocampo, 2010). SRH is also regarded as a subjective assessment of the physiological and functional condition of older adults (Kaplan et al., 1993). In past studies, the physical function of older adults frequently referred to the degree of functional limitation, impairment, and disability (Imanishi et al., 2017; Liu & Latham, 2009). Consequently, we use SRH and physical function as separate measures of physical health, with SRH representing a subjective physical health assessment and physical function representing an objective assessment. In previous research on mental health, past studies use varieties of subjective-feeling outcomes to reflect mental health, such as depression (Moussavi et al., 2007), anxiety (Scott et al., 2010), loneliness (McInnis & White, 2001), and well-being such as quality of life (QoL) and satisfaction (Imanishi et al., 2017; Querstret et al., 2020; Shapiro & Taylor, 2002; Zhang et al., 2018). Given the limited outcomes and concision of included studies, we use depression relief and well-being to reflect mental health in sub-group analysis.

As HCBS becomes increasingly prevalent, researchers have consistently examed how the utilization of HCBS affects the health of older adults. Existing articles have highlighted the benefits of HCBS for various health outcomes in older adults. HCBS can effectively improve physical health (Kato et al., 2009; Kim & Shiwaku, 2012) and mental health (Siegler et al., 2015) by increasing self-rated health (Duan et al., 2021), AIADL functio/IADL function (Chen et al., 2022), life satisfaction (Stancliffe et al., 2009), and reducing depression (Lam et al., 2014). According to Albert et al. (2005), older adults with impairments in activities of daily living had a lower mortality risk when they received HCBS, such as personal assistance, homemaking, and visiting nurses. When older adults receive HCBS, they can maintain their independence and remain in their own homes for an extended period. Even as their physical function declines, they still prefer to stay home. The ability of older adults to reside independently in their personal residences is a pivotal determinant influencing their quality of life (Angel & Angel, 1999). Moreover, HCBS can prevent hospitalization and delay institutionalization (Tomita et al., 2010; Wang et al., 2021). Existing research consistently demonstrates that HCBS positively impacts older adults’ subjective well-being, mental health, and subjective and objective physical health. However, there are suggestions that HCBS may have potential negative impacts on the health of older adults. These negative impacts are linked to prolonged homebound status among older adults receiving HCBS, which correlates with reduced physical activity compared to their counterparts not receiving HCBS. Consequently, this diminished physical activity may contribute to a decline in their physical functioning and overall health (Danilovich et al., 2017). Previous articles have indicated that homebound older adults are more likely to experience problems with their health (Wajnberg et al., 2013), lower functional status (Cohen-Mansfield et al., 2012), and higher levels of depression (Pepin et al., 2017). Qiu et al. (2010) indicated that homebound older adults have a higher likelihood of experiencing conditions such as arthritis of the spine, cardiovascular disease, and musculoskeletal morbidities. Kellogg and Brickner (2000) also found that homebound older adults frequently suffer from diseases with a high care burden, such as dementia, cancer, and depression. These conditions are linked to symptoms such as pain, nausea, shortness of breath, fatigue, and depression (Wajnberg et al., 2013). This situation can be attributed to the prolonged homebound status of older adults, which restricts their access to social support. Consequently, they frequently encounter challenges in receiving timely, high-quality care and locating suitably qualified and experienced professionals to handle the primary care requirements and heavy burdens (Agar et al., 2008; Gammel, 2005; Mor et al., 2007). Moreover, some studies suggest that the effectiveness of HCBS in enhancing the well-being and health of older adults is conditional and depends on their specific circumstances. When older adults receive informal support from spouses, family members, or friends, this informal support plays a more significant role in relieving depression compared to HCBS. However, HCBS is crucial in improving the mental health of older adults in the absence of informal support (Muramatsu et al., 2010).

Numerous research have investigated the correlation between HCBS and the health of older adults, yet the conclusions remain ambiguous. Existing research widely acknowledges that HCBS has a substantial influence on the physical and mental health of older adults. However, findings regarding the comparative effects of HCBS on physical and mental health outcomes between recipients and non-recipients are varied, leading to inconsistency in determining whether the influence is predominantly positive or negative. Therefore, this study aims to clarify this relationship through meta-analysis. To the best of our knowledge, there has been no systematic meta-analysis undertaken to examine the connection between HCBS and the health of older adults. Calculating the aggregated effect size will yield a reliable assessment of the actual correlation. Meta-analysis is crucial for reconciling inconsistencies and synthesizing existing data to yield more reliable and broadly applicable conclusions (Higgins & Green, 2011; Mulrow, 1994). Thus, this article conducts a meta-analysis to evaluate the impact of HCBS on the physical and mental health of older adults, intending to enhance understanding in this field. This study seeks to investigate the following research inquiries:

Does HCBS influence the health of older adults who receive these services?

To what extent does the utilization of HCBS impact the health of older adults who receive them?

Do moderator variables such as HCBS measurement, duration of intervention, and investigation country significantly affect health outcomes among older adults?

Method

We conducted this systematic review with meta-analysis with PRISMA principles (Moher et al., 2009). The review protocol was registered in the international prospective register of systematic reviews (PROSPERO). The registration ID is CRD42022383236 (https://www.crd.york.ac.uk/prospero/). Since our research is a systematic review based on previous publications, we do not need to provide ethical approval for this study.

Search Strategy

We conduct an electronic search using three databases (The Web of Science, Scopus, and PubMed) from the earliest date available until March 2, 2023. The search was limited to English literature. We use terms related to HCBS, health, and older adults. Our search terms were (“home- and community-based service*” OR “community-based supports and service*” OR “community-based service*” OR “community-based integrated service*”) AND (“old*” OR “elder*” OR “aged”) AND (“health” OR “well-being” OR “function*” OR “outcome*” OR “symptom*”). In addition, we look for additional articles by examining the reference lists of included publications and relevant systematic reviews.

Inclusion Criteria and Exclusion Criteria

The following inclusion criteria are used in the selection of the studies: (a) articles with full text written in English; (b) used quantitative methods; (c) recruited older adults who received at least one term of HCBS; (d) aged 60 or older; (e) considered results pertaining to physical or mental health assessed by quantitative methods; (f) examined the connection between the health of older adults and their use of HCBS; and (g) taken into account any impact assessments that employed quantitative or mixed methods, such as randomized, nonrandomized, and noncontrolled (single group) designs. There was no requirement for studies to include a control group. In addition, we considered both immediate and longitudinal impacts without imposing any temporality criteria. We excluded studies if they (a) were not written in English, (b) were review articles or qualitative studies, or (c) did not provide usable effect sizes.

Study Selection

All study data were recorded using a bibliographic management program (Endnote, version 20). We initially collected 2,230 articles (Web of Science = 909, Scopus = 1,061, and PubMed = 256) and subsequently removed 798 duplicates. Subsequently, two reviewers conducted assessments of the titles and abstracts of the remaining research independently, excluding any publications that lacked relevance to HCBS and the health of older adults. This process led to the deletion of 1,358 out of the 1,432 articles. After that, we obtained 74 articles for full-text evaluation. Two authors independently reviewed full texts and searched the reference list of included articles to identify any additional study that satisfied the specified criteria for inclusion. The two reviewers discussed and resolved their disagreements in a consensus meeting. Eventually, the meta-analysis included 11 studies that met the predetermined eligibility criteria (see Figure 1 and Supplemental Table 1).

Figure 1.

PRISMA flow diagram.

Data Extraction and Quality Assessment

We employed a pre-established data extraction form to collect information on the characteristics of the studies and participants, including authors names, publication year, research location, the overall size of the study sample, the average age of the study population, the distribution of females, the definition of the outcome, the measurement of HCBS, the duration of the investigation, and the estimations of effect size for each reported result. When the data was incomplete, we contacted the corresponding author to collect it. The transformation is done according to Cohen (1988), Rosenthal et al. (1994), and Lenhard and Lenhard (2016). Supplemental Table 2 shows the detailed transforming formulas for corrected correlations. We used the Agency for Healthcare Research and Quality (ARHQ) checklist (24) for cross-sectional studies and the Newcastle-Ottawa Scale (NOS) for cohort studies to evaluate the quality of potentially included studies. Supplemental Tables 3 and 4 show the detailed evaluations independently by two authors. The quality of all included articles are appropriate.

Statistical Analysis

A meta-analysis was conducted to evaluate the correlation between HCBS and the health of older adults, encompassing both their physical health and mental health. A small-sample adjustment was conducted because our meta-analysis included 26 effect sizes extracted from 11 studies (Tipton, 2015). We used Stata Statistical Software version 16.0 to conduct the analysis. All the corrected correlations from different studies were transformed into the value of Fisher’s Z. According to the heterogeneity test principle proposed by Hedges and Vevea (1998), random effects will be used if the effect values are heterogeneous (I² > 75%, Q-value > df(Q)) Conversely, fixed effects will be used when the effect values are homogeneous.

Catching what variables have a moderating effect on the effect size is an essential process for meta-analysis (Carpenter, 2020). As for the potential moderator variables, the subgroup analysis was conducted based on the data extractions. The type of HCBS measurement was divided into two types: dichotomy and continuum measure. Health includes physical health (SRH and physical function) and mental health (depression relief and well-being). The duration time of the investigation was divided into less than a year or more than a year. We also divided the investigation country of each study into U.S. or non-U.S. samples. Additionally, our research employed the Egger test and funnel plot to examine the presence of publication bias. The Egger test defined a significant publication bias with a p-value of <.05. As for the funnel plot, the distribution of plots was based on analyzing the publication bias (Stanley, 2008).

Results

Preliminary Analysis

The results of the homogeneity test show that the Q-value is larger than the degree of freedom (Q-value = 34,385.26, df(Q) = 25, p < .001), and the I² is larger than 75%, which means the heterogeneity is significantly high (see Table 1). The random effects analysis was conducted for the following meta-analysis (see Figure 2). Also, the heterogeneous effect suggests that additional factors could moderate the relationship between HCBS and health. Table 2 shows the results of HCBS on aggregate health in the random-effects model. The analysis reveals a moderate and significant HCBS effect on health (r = .305, p < .001, 95% confidence interval: [0.084, 0.527]).

Table 1.

The Results of the Homogeneity Test.

Random Effects Model	Studies	Heterogeneity				τ²
	Studies	Q-value	df(Q)	p-Value	I ²	τ²
Random effects	26	34,385.26	25	.000	99.93	0.3252

Figure 2.

The forest plot.

Table 2.

The Random Effects Analysis in the Relationship Between HCBS and Health.

Random Effects Model	Studies number	Effect size and 95% interval			Test of null (2-trial)
	Studies number	Point estimate	LL	UL	Z value	p
Random effects	26	0.305	0.084	0.527	2.70	.007

Note. LL = lower limit; UL = upper limit.

Subgroup Analysis

Table 3 shows that the effect of HCBS on mental health is significantly higher than on physical health (Q = 4.66, p = .031). The correlation between HCBS and physical health is 0.076. However, the relationship between HCBS and mental health is 0.532. Research by Lipsey and Wilson (2001) indicated that the correlation in meta-analysis is at a high level when r ≥ .4, a moderate relationship when .1 < r < .4, and a low level when r ≤ .1. According to the criterion, our analysis reveals a high and significant HCBS effect on mental health but a low-level effect on physical health. More specifically, we test subgroup analysis for more detailed categories of health. The effect sizes of HCBS on health (four categories) were sorted from high to low: well-being, depression relief, SRH, and physical function. In general, HCBS can improve the mental health of older adults but has a small impact on their physical health.

Table 3.

Subgroup Analysis for the Relationship Between HCBS and Health.

		N	k_e	Effect size and 95% interval			Heterogeneity
Variable		N	k_e	Point estimated	LL	UL	Q-value	df(Q)	p
HCBS measurement	Dichotomy	100,900	19	0.304	0.045	0.563	0.01	1	.986
HCBS measurement	Continuum	25,233	7	0.309	−0.151	0.768
Health	Physical health	91,029	13	0.076	−0.171	0.324	4.66	1	.031
Health	Mental health	35,104	13	0.532	0.201	0.864
Health categories	SRH	3,510	3	0.380	−0.173	0.934	6.79	3	.079
	Physical function	75,131	10	−0.011	−0.275	0.253
	Depression relief	28,948	8	0.469	0.021	0.916
	Well-being	6,156	5	0.633	0.102	1.164
Duration time	Less than a year	38,434	16	0.418	0.107	0.728	1.98	1	.159
Duration time	More than a year	75,392	10	0.122	−0.147	0.392
Country	USA	35,212	15	0.298	0.063	0.533	0.01	1	.931
Country	Non-USA	90,882	11	0.319	−0.108	0.746

Note. N = total sample size; ke = the number of effect sizes; LL = lower limit; UL = upper limit.

Furthermore, by employing the meta-analysis moderating test, the results show the robustness of the effect size among HCBS measurement, duration time, and investigation country (Figure 3). The results presented in Table 3 indicate that the effect of HCBS on health in total showed no significant difference between HCBS measurement (Q-value = 0.01, p = .986), duration time (Q-value = 1.98, p = .159), or even investigation country (Q-value = 0.01, p = .931), which increased the explanatory power of the meta-analysis.

Figure 3.

Subgroup forest plot.

Analysis of Publication Bias

The intercept’s Egger test yielded non-significant results (SE = 1.988, p = .707), indicating that there is no significant publication bias in our study. Then, we created the funnel plot to examine publication bias. The funnel plot illustrates that the majority of plots in the graph were spread around the mean effect size, with some deviation plots away from it. Given that both physical and mental health were encompassed in this research for meta-analysis, we believe the results are acceptable (see Figure 4).

Figure 4.

Funnel plot.

Discussion

This systematic literature review and meta-analysis provide insights into the correlation between HCBS and the health of older adults. Overall, this review finds that HCBS has a high and significant effect on improving mental health but only a little impact on improving physical health. These findings provide the support that HCBS can enhance well-being, relieve depression, and enhance SRH among older adults living in the community and their own homes, which is in line with earlier studies (Duan et al., 2021; Shippee et al., 2020; Stancliffe et al., 2009; Xu et al., 2023; Yu et al., 2022). This finding indicates that receiving HCBS enhances the subjective health perception of older adults and provides significant psychological comfort and emotional support. For example, facilities such as senior universities and government-established community activity centers provide older adults with various social interaction venues outside their homes, helping alleviate feelings of loneliness. This government-provided formal social support better satisfies and comforts the emotions of older adults, thereby helping to relieve depressive symptoms and enrich their well-being. However, the results indicate that HCBS may not be efficacious in preventing or slowing down a decline in physical function, which is consistent with previous conclusions drawn by Lewin and Vandermeulen (2010) and Imanishi et al. (2017). It is crucial to recognize that HCBS and medical services are not comparable. The decline in physical function among older adults is an inherent and inevitable phenomenon. Depending solely on elderly care services cannot reverse the gradual decline in physical function. HCBS has insurmountable limitations when it comes to improving the physical function of older adults. Achieving substantial strides in the physical well-being and health of older adults requires a comprehensive intervention involving medical services, health management, and personal lifestyle habits. To the best of our knowledge, this is the first systematic review and meta-analysis to demonstrate a significant positive association between HCBS utilization and health in older adults. Moreover, our research showed that there were no significant differences in health outcomes across different HCBS measurement methods, durations, or countries of investigation.

The results of this study have a significant influence on the inspiration for future research and application value in the field of gerontologic social work and healthcare systems. Firstly, recognizing the substantial value of HCBS in relieving the depression symptoms of older adults is crucial. Enhancing the accessibility, timeliness, and coverage of HCBS is essential to maximizing the health-promoting effect of HCBS. Ensuring that older adults can conveniently access supportive care, day services, emotional support, and other HCBS is vital for building an age-friendly society and is a fundamental requirement for implementing elder care services. Moreover, while the meta-analysis indicates that HCBS significantly impacts older adults’ well-being and mental health, it is still crucial to take into account the diversity of the population. Detailed classification and analysis of older adults based on the differences in economic status, social support, living arrangements, cultural background, and lifestyle habits can enhance comprehension of the heterogeneous impacts of HCBS on various health outcomes. This will enable the government to provide more tailored and refined HCBS interventions that effectively target the specific care requirements of vulnerable groups, such as older adults living alone, those with impairments in activities of daily living (ADL), or instrumental activities of daily living (IADL), and the oldest old. Furthermore, the provision of HCBS should not solely concentrate on resolving the existing care requirements of older adults but should also consider potential care needs and functional compensation arising from age-related health declines. This proactive approach can include the provision of lectures and training on disability prevention and rehabilitation care. Lastly, according to the conclusions drawn from this study, HCBS has not yet shown substantial improvements in the objective physical health of older adults. This could be attributed to the inadequate integration between HCBS and medical services. In practice, HCBS providers often prioritize daily care over coordination with medical care services. Therefore, future policy practices should emphasize the precise integration of community care services with healthcare services, providing a comprehensive range of services across the lifecycle, including disease prevention, health management, rehabilitation care, and long-term care. This approach attempts to address the multifaceted requirements of older adults and foster positive improvements in their objective physical health.

There are several limitations in this study. Firstly, because there were only a few studies that satisfied the inclusion criteria and quality assessment criteria, our meta-analysis primarily examines the overall impact of HCBS on health outcomes rather than conducting subgroup analyses for specific HCBS categories. Although multiple strategies were employed in this meta-analysis to avoid the “apples and oranges” issue (Carpenter, 2020), it would be valuable to explore further specific HCBS (e.g., daycare centers or personal care) when there are sufficient empirical studies available. Secondly, because of the scarcity of empirical research on this subject, while we have demonstrated the effectiveness of HCBS on the health of older adults, there are many specific patterns of HCBS. Further investigation is needed to determine the impact of diverse HCBS utilization patterns on the health of older adults. Thirdly, the long-term health outcomes of HCBS remain unclear as only five studies conducted the intervention over a year, whereas the majority of studies stopped intervention within 1 year. Considering that the effects of HCBS on health performance may not produce statistically significant differences immediately, future studies could benefit from employing longitudinal samples for more rigorous evaluation. This approach allows researchers to observe health outcomes over an extended duration, thereby facilitating a more thorough comprehension of the long-term impacts of HCBS on older adults. Moreover, this meta-analysis only contained articles written in English, which could be acknowledged as a potential constraint affecting the comprehensiveness of studies. Because of language barriers, it was difficult for us to incorporate studies in multiple languages, but we considered that English studies were generally representative. Future research could compare variations among studies in diverse languages to achieve a more exhaustive comprehension.

Although there are certain limitations, this study enhances the understanding of a substantial positive correlation between HCBS utilization and the health of older adults by synthesizing the conflicting results of prior studies through a meta-analysis. The study revealed that HCBS significantly relieved the depressive symptoms of older adults and improved their well-being and perceived physical health. However, it had a minimal impact on preventing their physical function from declining. Further empirical investigation is required to examine the impacts of various HCBS programs on the health of older adults and to analyze specific health outcomes, such as the number of chronic diseases, medication adherence, and hospitalization frequency. By filling these research gaps, we may improve our comprehension of the relationship between HCBS and the health of older adults, thereby informing policy and practice to promote healthy aging. Moreover, daily observations indicate that the impact of HCBS on the well-being and mental health of older adults is closely related to the heterogeneity of the elderly samples. For instance, older adults who have frequent interactions with their children or live with their spouses and thus receive strong family support tend to be less dependent on social support. Consequently, their demand for and perception of the effectiveness of HCBS is naturally lower compared to those who urgently need care, such as older adults who live alone, are the oldest old, or have ADL/IADL impairments. Therefore, future research needs to focus on the heterogeneity in the health-promoting effects of HCBS. Lastly, while the United States and Asian countries and regions have conducted several studies, other regions, such as Europe, Latin America, and Africa, still lack investigation into the connection between HCBS utilization and the health of older adults. Future research on this topic is essential to provide a deeper understanding of the global influence of HCBS on the health of older adults.

Conclusion

Based on our analysis, HCBS had a beneficial impact on the health of community-dwelling elderly residents, which remains consistent across diverse measurements of HCBS, varying durations of intervention, and distinct investigation countries. The outcomes unequivocally reveal that HCBS not only ameliorates their well-being and SRH but also significantly relieves depressive symptoms. It is noteworthy to mention that while heterogeneity is taken into account, our findings suggest that HCBS does not exhibit a significant efficacy in enhancing the physical health of community-dwelling elderly residents. Consequently, this study’s findings support HCBS as an efficacious care modality to enhance the mental health of community-dwelling elderly residents. Due to the scarcity of research on this topic, it is difficult to analyze the specific effects of patterns of HCBS on the health of older adults and the heterogeneous impact of HCBS on varied older adult populations. Subsequent studies should prioritize investigating the health-promoting effects of specific components of HCBS and exploring the variability of outcomes among older adults.

Supplemental Material

sj-docx-1-sgo-10.1177_21582440241285674 – Supplemental material for The Impact of Home- and Community-Based Services on the Health of Older Adults: A Meta-Analysis

Supplemental material, sj-docx-1-sgo-10.1177_21582440241285674 for The Impact of Home- and Community-Based Services on the Health of Older Adults: A Meta-Analysis by Xuanru Lyu and Yangyang Fan in SAGE Open

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research,authorship,and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research,authorship,and/or publication of this article: We acknowledge support from the Shanghai Philosophy and Social Science Planning Project (2023EGL010)

Ethical Approval

This study did not require any ethical approval as the data used have been published previously,and they are already in the public domain.

ORCID iDs

Xuanru Lyu

Yangyang Fan

Data Availability Statement

The data used to support the findings of this study are available from the corresponding author upon request.

Supplemental Material

Supplemental material for this article is available online.

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