Determinants of active aging and quality of life among older adults: systematic review

Introduction: Population demography across the globe shows an increasing trend in the aging population due to better healthcare, improved nutrition, advanced health-related technology, and decreased fertility rate. Despite these advancements, there remains a knowledge gap in understanding the association between active aging determinants and quality of life (QoL) among older adults, particularly within diverse cultural contexts, which has not been adequately explored in previous research. Therefore, understanding the association between active aging determinants and QoL can help policymakers plan early interventions or programs to assist future older adults in both aging actively and optimizing their quality of life (QoL), as these two factors have a bidirectional relationship.

Objective: This study aimed to review evidence regarding the association between active aging and quality of life (QoL) among older adults and to determine the most widely used study designs and measurement instruments in studies conducted between 2000 and 2020.

Methods: Relevant studies were identified by a systematic search of four electronic databases and cross-reference lists. Original studies examining the association between active aging and QoL in individuals aged 60 years or older were considered. The quality of the included studies and the direction and consistency of the association between active aging and QoL were assessed.

Results: A total of 26 studies met the inclusion criteria and were included in this systematic review. Most studies reported a positive association between active aging and QoL among older adults. Active aging had a consistent association with various QoL domains including physical environment, health and social services, social environment, economic, personal, and behavioral determinants.

Conclusion: Active aging had a positive and consistent association with several QoL domains among older adults, backing the notion that the better the active aging determinants, the better the QoL among older adults. Considering the broader literature, it is necessary to facilitate and encourage the active participation of older adults in physical, social, and economic activities for the maintenance and/or improvement of QoL. Identifying other possible determinants and enhancing the methods to improve those determinants may help improve the QoL among older adults.

Introduction

Population demography across the globe shows an increasing trend in the aging population due to better healthcare, improved nutrition, advanced health-related technology, and decreased fertility rate (1). By the year 2050, the global population of older adults is expected to increase by approximately 20.6%, resulting in an estimated 2 billion older adults worldwide. Most of these older adults will live in low- and middle-income countries [LMICs; (2)]. Due to this rapid demographic transition, there will be a potential shortage of the productive young population in the coming decades (2). Therefore, it is essential to develop strategies by which older people can be actively engaged to promote their wellbeing and that of their families. In contrast to previous studies in this area (3–5), which primarily focused on specific disease conditions or were conducted in developed regions, our study adopted a comprehensive approach to examine the association between active aging determinants and quality of life (QoL) among community-dwelling older adults from diverse cultural contexts. This broader perspective provides valuable insights for early intervention programs and policies aimed at enhancing the lives of older adults (6, 7).

The novel findings of our study are crucial for understanding the various factors that contribute to QoL in older adults across different cultural settings, thus supporting their wellbeing and helping them age actively and healthily. By extending our analysis beyond specific health conditions and incorporating a wider range of geographical regions, we hope to inform the development of more inclusive and effective policies and interventions for older adults around the world. The World Health Organization (WHO) as part of its Aging and Life Course Program has developed the “Active aging: a policy framework” to address this problem (8). The framework intends to inform and guide discussion and formulation of action plans that foster healthy and active aging.

The concept of active aging was defined by the WHO as “the process of optimizing opportunities for health, participation, and security to enhance quality of life as people age” (9). Active aging emerges as a strategy to achieve QoL, permeated and influenced by six determinants: physical environment, health and social services, social environment, economic, personal, and behavioral determinants (10). This multidimensional definition implies that this concept intersects with others, such as productive aging, healthy aging, and successful aging (11–13).

Although active aging and QoL have some overlap, by definition, active aging is considered a dynamic process, whereas the QoL is a “state of being” (9). A study has noted that elements that compose the active aging index also relate to the elements that define life satisfaction/life happiness as measured for QoL (6). Furthermore, another study, using a sample from 27 European countries, examined QoL among older adults as a subset of active aging (7).

Within this broad framework of active aging and QoL, engaging in social activities, along with better physical health, financial condition, and security, are the essential aspects of QoL as defined by older adults themselves (14, 15). The concept of QoL is at times used conversely with active aging but is mainly considered as an outcome or the proxy measure of active aging (1, 7, 16–18).

Previous studies have reported the association of QoL with regard to diseases and clinical conditions among older adults (3–5), but none have investigated the association of active aging determinants with QoL. In this study, we aimed to fill the knowledge gap by investigating the association between active aging determinants and quality of life (QoL) among older adults. Our research stands out from previous studies that mainly focused on the association of QoL with diseases and clinical conditions among older adults (3–5). By examining the association between active aging determinants and QoL, our study offers a more comprehensive understanding of these factors and their role in promoting active aging and better QoL for older adults. Understanding the association of active aging determinants and QoL may help policymakers plan an early intervention or program to assist the future older adult in aging actively by optimizing their quality of life. Ultimately, this will help in the comprehensive support of the aging population in physical, mental, social, and financial wellbeing. Thus, this study aims to demonstrate the association of active aging with QoL, describing the need for more all-inclusive and broader measures designed to incorporate these unique factors influencing healthcare, health outcomes, longevity, and overall QoL in older age.

Methodology

Protocol and registration

This systematic review of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P) guidelines (19) and the study protocol were registered in the International Prospective Register of Systematic Reviews (PROSPERO): CRD42020186740.

Eligibility criteria

Only studies published in the English language were considered in this review. Studies were included based on a series of predefined inclusion and exclusion criteria as follows:

Inclusion and exclusion criteria

The study used the following inclusion criteria: (i) published original articles that assessed the association between active aging (AA) components and QoL domains; (ii) studies published between 1 January 2000 and 31 July 2020; (iii) having individuals aged 60 years or older as the study sample; and (iv) interventional, cross-sectional, and longitudinal study designs. For QoL assessment, we considered studies that used self-reported QoL questionnaires and wellbeing scales containing QoL or Health-Related Quality of Life (HRQoL) domains (life satisfaction, wellbeing, and self-rated health) and specific domains that include QoL or HRQoL (physical, cultural, social, psychological, mental, and spiritual domains). In addition, we included studies that utilized other relevant QoL assessment tools, such as CASP, SF EQ5D, and VAS, due to their established validity in evaluating active aging and QoL. We decided not to limit the study search to those that assess QoL using only generic instruments (WHOQoL-100 or SF-36). As a result, we also included key intervention and cohort studies that assessed the association between elements of AA and QoL domains.

Search strategy

We searched for relevant articles from various electronic databases, including MEDLINE/PubMed, EMBASE and Cochrane via OVID and Open Gray, LILACS, and CINAHL. We used keywords for active aging (health, participation, and security) and the population of interest (geriatrics, older adults, elderly, aged people, and seniors), in combination with the keyword for QoL (quality of life). Keywords were combined using the Boolean operators “AND” and “OR”. All identified articles were screened independently by two reviewers (RM and SS) (Appendix 1).

Data selection and collection process

The identified articles from the search were screened by two independent researchers/authors (RM and SS). At first, titles and abstracts of identified articles were assessed, and then eligible articles with full texts were retrieved and screened in full against the eligibility criteria mentioned above. All disagreements that arose were solved via discussion with a third reviewer (PKM, DM, or TTS). A flowchart detailing the study inclusion and exclusion process is included (Figure 1).

FIGURE 1

Figure 1. PRISMA flow chart for the inclusion and exclusion process.

Data extraction

Data were independently extracted by two reviewers (RM and SS) using a standardized data extraction template designed for this purpose. The following data and information were extracted from each of the included studies: country, study setting, sample type, and size, participants' age and gender, QoL measurement instruments (both generic and specific scales related to health, security, and participation), and active aging measures/definition. Disagreements at this stage were also solved via discussion with a third party/reviewer where necessary.

Quality assessment

The quality of included studies was examined, independently, by two authors (RM and PK) using the Newcastle–Ottawa Quality Assessment Scale (NOS) of cross-sectional and cohort studies (20). Here, we determined the quality of selection, comparability, exposure, and outcome of each study participant, using a scoring system (maximum 9 points). The qualities of included studies were categorized into three: (1) high (score of 7–9); (2) moderate (score of 4–6); and (3) low (score of 0–3) qualities.

The Joanna Briggs Institute (JBI) Critical Appraisal Tool (21) was used to examine the methodological quality of interventional studies and the extent to which a study addressed the possibility of bias in its design, conduct, and analysis. The qualities of assessed studies were divided into three categories: (+) Yes implying low-risk bias; (?) unclear; and (–) No, implying high-risk bias. Disagreements were resolved through discussion to reach the final agreed score.

Results

Study selection process

Figure 1 presents the study selection process, which was divided into four key stages:

(i) Identification: In July 2020, a database search was done through Central, Embase, Medline via OVID (2,502 articles), CINAHL (3 articles), LILAC, and Open Gray (5 articles), and bibliographic search of systematic literature reviews (SLRs) (4 articles). Thus, the initial search yielded 2,514 articles identified from the online databases. However, 929 were removed because they were duplicates.

(ii) Screening: In total, 1,585 titles and abstracts were screened for eligibility. A total of 1,484 studies were removed because they did not meet the eligibility criteria such as population out of scope, intervention not of interest, relevant outcomes not reported, and study design and publication type not of interest.

(iii) Eligibility: At this stage, 101 full-text articles were assessed. Of these, 75 studies were excluded after a full-text review because the population was out of scope, relevant outcomes were not reported, and study design was not of interest.

(iv) Included: In total, 26 studies were considered to be eligible for inclusion in this systematic review.

General characteristics of the studies

There were 22 cross-sectional, three longitudinal, and one quasi-experimental design studies—all studies composed exclusively of the older people (60 years or older) of both sexes (Table 2). Of the 26 studies, 14 studies were from seven Asian countries (China, India, Korea, Japan, Malaysia, Turkey, and Egypt). Two studies were conducted in the Latin American region (Brazil and Mexico) and four European regions (Austria, Ireland, UK, and Israel). One study each was conducted in Canada, Australia, and Nigeria.

Two contexts of the living arrangement were considered; community-based dependent older people and older people living in residential aged-care facilities. Eighteen studies included community-dwelling participants (22–26, 31, 32, 36–38, 41–48) and four studies included participants from residential aged care facilities (30, 34, 35, 39), while four studies did not report the kind of living arrangement (28, 29, 33, 40).

Quality of studies

The qualities of cross-sectional and longitudinal studies were assessed through the NOS scale (Table 1). Based on the proposed cutoff points, 15 studies were classified as high-quality (22, 25, 28–31, 33, 38–42, 44–47) and 10 studies of medium quality (23, 24, 26, 28, 32, 35–37, 43, 48). The Joanna Briggs Institute (JBI) was used to evaluate the quality of the quasi-experimental study and scored 8/9 (88%) low risk of bias (34).

TABLE 1

Table 1. Quality of studies assessed through the newcastle–ottawa quality assessment scale.

Table 2 summarizes the instruments used to measure the QoL in the selected 26 studies. The concept of AA was measured, considering the three pillars of AA: participation, health, and security. The current study analyzed the active aging of the older population through their level of participation in physical, social, and cultural leisure activities about their socio-demographic characteristics and QoL dimensions in old age. In addition to participation, the health and security statuses have been also investigated in relation to QoL among older adults. The most widely used questionnaire to assess QoL is the World Health Organization Quality of Life Assessment–Module for Older Adults (WHOQoL-Old) (8 studies) (30, 36, 38, 39, 41, 42, 44, 45), followed by the WHOQOL–Abbreviated Version (WHOQoL-Bref) (6 studies) (35, 36, 42, 44, 46, 48) and the Short Form-36 (SF-36) (5 studies) (22, 23, 30, 31, 34). The European Quality of Life-5 Dimension (EQ-5D) (26, 40), Control, Autonomy, Self-Realization, and Pleasure (CASP-19) (28, 43), and visual analog scale (VAS) (32, 33) were used in two studies each. The following instruments were used in one study each: The Satisfaction with Life Scale (SWLS) (24), CASP-12 (25), SF-12 (47), WHO-5 (29), and CASP-16 (37).

TABLE 2

Table 2. Summary study characteristics.

The selected studies in the present systematic review used different questionnaires for assessing active aging. We observed that the questionnaire assessed different determinants of active aging. For example, the WHOQoL–OLD and WHOQoL–BREF assessed the personal, social, behavioral, environment, health and social services, physical environment, and economic aspects of aging; while CASP-12, CASP-16, CASP-19, SF-12, SF-36, and EQ5D measured the three aspects of active aging, namely personal, behavioral, and social aspects. Similarly, VAS was used to assess the personal and behavioral aspects and SWLS and WHO-5 measured personal aspects only (Table 3).

TABLE 3

Table 3. Similarities and differences of the questionnaires/instruments used.

Association of active aging determinants and QoL

Table 4 summarizes the key findings on the association between elements of AA and QoL domains. Various instruments were used to ascertain QoL scores, thus allowing a wide variety of QoL domains to be evaluated in the analyzed studies. The most examined QoL domains included physical health, mental health, functional capacity, psychological, emotional, social relationships, environment, pain, overall health, general QoL, and vitality concerning social participation and engagement in reading, art, and leisure activities.

TABLE 4

Table 4. Association of active aging determinants and quality of life.

Six out of six studies using WHQOL-Bref showed that social participation and other activities such as reading, art, and physical activities significantly influence the QoL (35, 36, 42, 44, 46, 48). Seven out of eight studies using WHOQOL-Old demonstrated the consistent positive influence of activities including social participation, participating in art activities, reading, etc. on the QoL (30, 38, 39, 41, 42, 44, 45). Three out of five studies employing SF-36 showed that social or community participation is a relevant factor influencing the QoL (23, 30, 31). Two studies using CASP-19 showed that social participation and interaction significantly influence QoL (28, 43).

Discussion

This systematic review synthesized evidence on the investigation of the association of active aging with QoL determinants among older adults. To date, most of the studies targeting QoL are focused mainly on clinical conditions, and thus the association of active aging determinants and QoL is uncharted. Our systematic review shows that different types of assessment tools have been used for the evaluation of QoL considering different components of AA, which varied with sex, settings, and study design, and resulted in a wide variation in association of QoL and active aging determinants. Due to the importance of AA, as it could interfere with personal as well as relatives' life, the understanding of determinants that affect AA is essential. This review has enhanced our knowledge of active aging in context to the quality of life that may prove crucial in understanding how the QoL can be maintained simultaneously with active living among older adults. In summary, our study supports the notion that the better the active aging determinants, the better the QoL among older adults.

Among the selected 26 studies in the current systematic review, QoL was assessed using different tools. We observed that the use of different QoL questionnaires resulted from the inclusion of different active aging determinants (Table 4) and therefore, variable determinants have been studied in different studies. For instance, some studies investigate the influence of personal determinants only, while some consider physical factors and some considered multiple factors such as physical activity, social participation, and mental health. Although this discrepancy among the investigated determinants is due to the use of variable questionnaires, the most commonly used questionnaire in various studies was the World Health Organization Quality of Life Assessment–Module for Older Adults (WHOQoL-Old) followed by WHOQOL–Abbreviated Version (WHOQoL-Bref) and the Short Form-36 (SF-36) (5 studies). Similarly, the European Quality of Life-5 Dimension (EQ-5D), Control, Autonomy, Self-Realization, and Pleasure (CASP-19), and visual analog scale (VAS) were used in two studies each. While the Satisfaction with Life Scale (SWLS), SF-12, CASP-12, CASP-16, and WHO-5 were used in one study each.

In examining the relation between active aging determinants and QoL, our study emphasizes that QoL is higher with the better status of active aging determinants, although some contrary findings are observed. It is noticed from many listed studies that social participation and other activities, including reading, art, and physical activities, have a positive impact on QoL (23, 28, 30, 31, 35, 36, 38, 39, 41–46, 48), despite different questionnaires such as WHOQOL-Old, CASP-19, and WHOQoL-Bref were used. Sampaio et al. (42) showed that social activity has the most significant impact on WHOQOL-Old, ensued by reading and writing (42). Similarly, our systematic review also showed that financial security and ensuring care positively influenced the QoL (48). In addition to that, Rugbeer et al. (34) demonstrated that mental and social benefits could be achieved regardless of exercise frequency (34).

The recent study by López-Ortega and Konigsberg (22) considered multiple outcome measures using an SF-36 questionnaire and reported the positive influence of socioeconomic and social, educational, and marital statuses on HRQoL (22), but there was no effect on HRQoL. In addition, there was no effect on HRQoL concerning the number of family members and those having chronic disease conditions. In contrast, another study conducted in the same year in the Shaanxi province of China reported the effect of a chronic condition on physical and mental HRQoL (23). On the contrary, we also acknowledge that not all the possible active aging determinants were associated with QoL among the selected studies. The study by Top and Dikmetaş (39) did not observe a significant association between gender and overall QoL (39). Notably, Onunkwor et al. (35), conducted a study on 203 older adults aged >60 years and failed to associate multiple factors such as pension, ethnicity, marital status, and smoking and alcohol status with any of the domains of QoL (35). Another study by Gureje et al. (46) also did not observe any association between gender, marital status, educational level, and residence and the physical domain of QoL (46). However, one of the studies showed no impact of the recipient of a national pension on QoL among middle-high and high household income levels and wealth (32). Considering most of the studies are based on associations, we support the concept that the higher the score in active aging determinants, the better QoL among older adults. We compared our findings to those of previous studies that investigated the relationship between active aging and QoL (49–52). Our results were consistent with these studies, supporting the notion that higher scores in active aging determinants lead to better QoL among older adults. This finding underlines the importance of promoting active aging to achieve improved QoL outcomes for older adults. Furthermore, a study by Ahmad Bahuri et al. (51) focused on active aging awareness and QoL among pre-elder Malaysian public employees, emphasizing the need to promote active aging in this population to ensure better QoL outcomes (51). Ooi and Ong (52) investigated active aging, psychological wellbeing, and QoL among older adults and pre-older adults Malaysians during movement control periods. Their findings suggest that even in challenging situations like movement control periods, promoting active aging can contribute to improved psychological wellbeing and overall QoL (52).

Our study, therefore, suggests that QoL among older adults is higher among individuals who are advancing well in different active aging components such as health, participation, and security. Our study compiling the previous studies suggests that there is a necessity to manage active aging determinants for the maintenance of QoL properly. Identifying other possible determinants and enhancing the methods to improve those determinants may help improve the QoL among older adults.

Strength and limitations

The main strength of our review is that this is the first study collating information on the association between AA determinants and QoL. Furthermore, stringent search strategy was used in the current study to identify the relevant areas and thus strengthen our interpretation that physical, social, and health determinants are closely associated with QoL. However, as with most of the reviews, our study also has some limitations. Our search was limited to the English language; therefore, any studies published in other languages might have been omitted. Additionally, our literature screening time frame was limited to 2000–2020 as the active aging concept was developed from 2002 onward. Therefore, there might be the possibility of missing any articles that have been published before 2002. Our study's generalizability and interpretation may be affected by factors such as small sample sizes, geographically limited scope, unclear sampling schemes, and imbalanced gender distribution. We recommend future studies prioritize nationally representative studies, detailed sampling schemes, and balanced gender distributions to address these limitations.

Conclusion

The maintenance of QoL in advancing age among older adults is necessary from individual to family, society, and healthcare perspectives. Thus, the elucidation of the related active aging determinants associated with an individual's QoL among older adults is paramount. QoL is multifaceted and is affected by several factors. Previous studies mainly highlighted QoL and clinical condition association; however, the specific aging determinants' association with QoL remains unknown. This review identified and systematically compiled the associated determinants of active aging and QoL. While relatively few studies have been identified, suggesting AA determinants, promising findings pointing to more extensive associations exist. To conclude, the findings from this study could help to further illuminate which AA determinants are essential in the maintenance of QoL. A future study could evaluate the cost necessity to improve the associated active aging determinants of QoL to improve/maintain the overall QoL in a better state.

Author contributions

RM, TS, DM, and PM contributed to conception and design of the study. RM, PK, and SS organized the database. RM, TS, DM, PM, PK, and SS performed the statistical analysis and wrote sections of the manuscript. RM, TS, DM, PM, PK, and SS wrote sections of the manuscript. All authors contributed to manuscript revision, read, and approved the submitted version.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpubh.2023.1193789/full#supplementary-material

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