INTRODUCTION

Health-promoting behaviors are widely recognized as fundamental indicators of overall health status. They encompass a range of deliberate actions aimed at improving well-being and preventing disease [1]. As conceptualized by Pender et al. [2], these behaviors fall into 6 domains: nutrition, physical activity, stress management, health responsibility, interpersonal relationships, and spiritual growth. Together, these components foster healthy aging, enhance quality of life, and reduce rates of disability and premature mortality among older adults [3,4]. Adopting such behaviors, including reducing sodium intake, engaging in regular physical activity, and abstaining from tobacco and alcohol, can play a significant role in preventing or managing chronic diseases [5].

Chronic diseases such as cardiovascular disease, diabetes, hypertension, and chronic respiratory illnesses remain the leading causes of mortality worldwide, accounting for 31.2% of all deaths, with 78% occurring in low-income and middle-income countries [6,7]. As global populations age, the burden of chronic diseases and related complications is expected to rise, placing increasing strain on healthcare systems [8]. Studies have documented varying levels of health-promoting behaviors among older adults in Iran. For instance, Khami et al. [9] reported moderate overall adherence, with the lowest scores in physical activity and stress management subscales. This finding underscores the importance of enhancing health-promoting behaviors as a strategic approach to maintaining and improving the health of older adults. Beyond individual lifestyle choices, socio-demographic characteristics and social support significantly influence health behaviors in this population [8]. Social support, defined as the perceived or actual assistance received from one’s social network [10], plays a crucial role in initiating and sustaining health-promoting behaviors [11]. Evidence shows that higher levels of social support are associated with healthier dietary patterns [12], increased physical activity [13], and lower rates of tobacco and alcohol use [14], particularly among older adults. However, perceived support does not always translate into healthier behaviors [15]. This inconsistency may be influenced by factors such as the type and source of support, cultural expectations, individual motivation, and the quality of interpersonal relationships [16,17].

Given the increasing prevalence of lifestyle-related chronic conditions and the specific challenges faced by older adults—such as bereavement, financial constraints, and physical limitations [4]—identifying factors that promote healthy behaviors is essential. In this context, findings from the Fasa Cohort Study indicate that older adults in the region face substantial health challenges, including high rates of hypertension, diabetes, and chronic kidney disease, all of which are closely related to health-promoting behaviors [18,19].

Therefore, the present study aimed to examine the relationship between perceived social support and health-promoting behaviors among older adults in Fasa, Iran, in 2020. The findings are expected to inform the development of context-specific strategies to improve the health and well-being of aging populations.

METHODS

Study Design and Participants

This descriptive-analytical, cross-sectional study was conducted between May 2020 and June 2020 and included 300 older adults who attended the Vali-Asr (AJ) Specialty Hospital Clinic in Fasa. Participants were recruited through convenience sampling based on the following inclusion criteria: absence of physical limitations affecting activity; no history of psychiatric disorders or use of medications known to influence behavior; voluntary willingness to participate; and accurate completion of all study questionnaires.

The required sample size was calculated using the formula applied in the study by Seyfzadeh [20], assuming a type I error rate of 0.05 and statistical power of 90%. Based on these parameters, the minimum estimated sample size was 240 participants. To enhance statistical robustness and improve the generalizability of the findings, the final sample was increased to 300 individuals.

n=(z1-α2+z1-β0.5 ln(1+r1-r))2+3

Data Collection Instruments

Data were collected using a demographic information form and 2 standardized instruments: the Health-Promoting Lifestyle Profile II (HPLP-II) and the Perceived Social Support Scale. The demographic form captured variables such as age, gender, employment status, marital status, education level, and presence of chronic illness. Questionnaires were completed either through self-report or, when necessary, with the assistance of a trained interviewer to ensure accuracy and completeness.

Health-promoting behaviors were assessed using the HPLP-II, developed by Walker et al. [21]. For this study, the validated Persian version translated by Dr. Anahita Babak was employed. This version has demonstrated acceptable internal consistency, with a reported Cronbach’s alpha of 0.75 [21]. The HPLP-II consists of 52 items distributed across 6 subscales: spiritual growth (9 items), physical activity (8 items), nutrition (9 items), stress management (8 items), interpersonal relationships (9 items), and health responsibility (9 items). Each item is rated on a 5-point Likert scale, yielding total scores ranging from 52 to 208. Scores below 130 indicate an unfavorable lifestyle, whereas scores above 130 represent a favorable lifestyle [20].

Perceived social support was measured using the Perceived Social Support Scale, adapted from the original instrument developed by Canty-Mitchell and Zimet [22]. This 12-item questionnaire evaluates perceived support from 3 sources: family (items 5–8), friends (items 9–12), and significant others (items 1–4). Each item is rated on a 7-point Likert scale ranging from “strongly disagree” to “strongly agree.” Subscale scores range from 4 to 28, and the total score ranges from 12 to 84. The original scale demonstrated excellent internal consistency, with a Cronbach’s alpha of 0.91. In the present study, the Persian version of the instrument was used. Evidence for its reliability has been reported by Ezati et al. [23], who demonstrated a satisfactory reliability coefficient of 0.82. Notably, there were no missing data, as all participants completed the questionnaires in full.

Statistical Analysis

Data were analyzed using SPSS version 25 (IBM Corp., Armonk, NY, USA). Descriptive statistics, including mean, standard deviation (SD), frequency, and percentage, were calculated to summarize the characteristics of the study population. Inferential statistical tests were applied to examine associations between variables. These included Pearson correlation coefficients, one-way analysis of variance (ANOVA), the chi-square test, and multiple linear regression analysis. A p-value<0.05 was considered statistically significant. The normality of the data distribution was assessed using the Kolmogorov–Smirnov test and was confirmed prior to conducting parametric analyses.

Ethics Statement

This study was approved by the Ethics Committee of Fasa University of Medical Sciences (No. IR.FUMS.REC.1399.077). All participants were provided with detailed information about the study objectives and the confidentiality of their data. Written informed consent was obtained from each participant prior to enrollment, in accordance with ethical standards for human research.

RESULTS

Descriptive analysis showed that 56.6% of participants (n=170) were women, while 43.4% (n=130) were men. The mean±SD age of the participants was 68.9±7.8 years. Most were married (81.7%, n=245), and a smaller proportion were single (4.6%, n=14). A comprehensive summary of the participants’ demographic characteristics is provided in Table 1.

The mean score for health-promoting behaviors was 124.2± 31.3, indicating an overall unfavorable level of engagement in such behaviors. Among the 6 dimensions of the HPLP, the highest mean score was recorded in the domain of spiritual growth (22.2±4.3), whereas the lowest score was observed in physical activity (17.5±4.8). The mean score for perceived social support was 24.4±9.4, reflecting an overall inadequate level of social support among participants. Within the subdomains of perceived social support, the highest mean score was noted in the family dimension (9.9±3.9), while the lowest was found in the significant others dimension (7.1±2.7) (Table 2).

Analyses using ANOVA and the chi-square test demonstrated statistically significant associations between health-promoting behaviors and several demographic variables, including marital status (p=0.05), educational level (p=0.02), place of residence (p=0.04), and the presence of chronic illness (p=0.03). Similarly, perceived social support was significantly associated with educational level (p<0.01) and the presence of illness (p=0.02) (Table 3).

Pearson correlation analysis revealed a significant negative relationship between age and interpersonal relationships (r=−0.22, p=0.04). A positive and statistically significant correlation was observed between income and physical activity (r=0.15, p=0.05). In addition, educational level showed positive correlations with both nutrition (r=0.60, p=0.04) and health responsibility (r=0.12, p=0.03). Marital status demonstrated positive associations with health responsibility (r=0.23, p=0.01) and spiritual growth (r=0.47, p=0.02). Employment status also showed significant positive correlations with stress management (r=0.70, p<0.01), health responsibility (r=0.24, p<0.01), and spiritual growth (r=0.19, p<0.01).

Moreover, perceived social support exhibited significant positive correlations with stress management (r=0.33, p<0.01), health responsibility (r=0.36, p<0.01), and interpersonal relationships (r=0.30, p=0.03). Overall, a positive and statistically significant association was observed between total perceived social support and overall health-promoting behaviors (r=0.10, p=0.04) (Table 4).

Finally, multiple linear regression analysis identified perceived social support, gender, and educational level as significant predictors of health-promoting behaviors and their respective subscales. Together, these variables accounted for 34% of the variance in total health-promoting behavior scores (Table 5).

DISCUSSION

Engagement in health-promoting behaviors is widely recognized as one of the most vital and effective determinants for maintaining and improving health among older adults [23]. The present study aimed to examine the role of perceived social support in shaping health-promoting behaviors among the elderly population in southern Iran. The findings indicated that the mean score for health-promoting behaviors among participants was at an undesirable level. Among the subscales, spiritual growth received the highest mean score, whereas physical activity received the lowest. The elevated score for spiritual growth may reflect the cultural and religious fabric of Fasa, where spiritual and religious practices are deeply integrated into daily life. For many older adults in this region, spirituality offers a profound sense of peace, purpose, and meaning. In contrast, the low score for physical activity—despite its well-documented importance for aging populations—highlights the urgent need for targeted interventions that promote physical activity and mobility among older adults in Fasa.

The study further identified significant associations between health-promoting behaviors and several demographic variables, including marital status, educational level, place of residence, and the presence of chronic illness. These findings can be interpreted within the framework of Ecological Models of Health Behavior, which propose that health behaviors are influenced by interactions across multiple levels: individual, interpersonal, organizational, community, and policy. For example, individuals living in urban areas may benefit from environmental-level facilitators such as access to parks, sidewalks, and healthcare centers, whereas married individuals may receive interpersonal support that encourages engagement in healthier behaviors [24].

Previous studies by Han et al. [25] and Al Shammari et al. [26] have reported moderate levels of lifestyle quality and health-promoting behaviors among older adults in China and Saudi Arabia, respectively. Similarly, other research has found moderate levels of health-promoting behaviors among older adults in Iran, which contrasts with the findings of the present study [9,23,27]. This discrepancy may be due to the fact that these studies were conducted in larger urban centers with greater access to health and fitness resources, unlike the current study, which focused on a smaller, less resourced setting. Nevertheless, consistent with the present findings, several studies have reported that physical activity consistently receives the lowest scores among the subscales of health-promoting behavior [23,25,26]. Although physical activity ranked lowest in the current study, Khami et al. [9] identified stress management as the lowest-scoring domain, suggesting variability across populations. Differences in sample characteristics, regional resources, and cultural contexts may account for these inconsistencies.

Consistent with our findings, other studies have also reported significant associations between health-promoting behaviors and marital status [25,26,28]. It is plausible that married individuals benefit from the emotional, social, and instrumental support provided by their spouses, which in turn facilitates the adoption and maintenance of healthier lifestyles. Therefore, marital status should be considered an important factor in designing health promotion strategies for older adults.

Similarly, a significant association between educational attainment and health-promoting behaviors was observed in the present study, echoing the findings of Giena et al. [29] and several others [9,23,26–28]. Individuals with higher educational levels are more likely to have access to informational resources—such as books, journals, and credible health websites—that enhance their understanding of the benefits and barriers associated with healthy behaviors. Furthermore, those with higher educational attainment often possess greater economic and social capital, enabling them to adopt and sustain healthier lifestyles. In contrast, El Mokadem [30] did not find a significant relationship between educational level and health-promoting behaviors, a divergence that may be attributed to the high proportion of illiterate participants in their study.

In line with the current findings, previous studies have also demonstrated a significant association between the presence of chronic illness and engagement in health-promoting behaviors among older adults [26,27]. This association may reflect greater health awareness among individuals with chronic conditions, who may be more motivated to adopt healthier behaviors to manage their illnesses effectively and prevent further complications.

Moreover, the observed relationship between higher educational attainment and increased engagement in health-promoting behaviors underscores the pivotal role of education in fostering awareness and knowledge regarding healthcare and self-care practices. With respect to place of residence, the present findings corroborate those of Han et al. [25], who reported that older adults living in urban areas tend to engage more frequently in health-promoting behaviors. Urban residents generally benefit from superior access to healthcare facilities, support services, and reliable health information, reflecting disparities in infrastructure and resource allocation between urban and rural or peri-urban areas.

The present study revealed that the average score for perceived social support among participants was low. Among the subdomains assessed, family support received the highest score, whereas support from significant others received the lowest. Statistically significant associations were observed between perceived social support and both educational level and the presence of chronic illness.

In contrast to these findings, previous studies have reported higher levels of perceived social support among older adults [11,31,32]. This discrepancy may arise from differences in participant characteristics, such as variations in age distribution, or from the use of different instruments to measure social support. For instance, in the study conducted by Ezati et al. [23], the mean perceived social support score was higher, likely because participants were recruited from community health centers rather than from a specialized clinical population. In the present study, participants were selected from individuals seeking care at a specialty clinic, which may represent a population with more complex health needs and, consequently, lower levels of perceived support.

Consistent with our findings, Zareipour et al. [32] also reported that family support scored higher than support from non-family members among older adults. This observation aligns with the Buffering Hypothesis of Social Support, which posits that emotional and instrumental support can mitigate the adverse effects of stress and chronic illness [33]. Family support, as the most accessible and reliable form of assistance, likely serves a critical protective role by alleviating challenges faced by older adults and reducing psychological distress. This perspective not only explains the predominance of family support but also underscores the importance of incorporating family networks into the design of health-promotion interventions for the older adults. The pronounced role of family support observed in this study is likely influenced by the Iranian and Islamic cultural context, in which respect for older adults and intergenerational caregiving are deeply rooted values, reinforcing strong family-based support systems.

Regarding the associations between social support, education, and chronic illness, Ahmed and Mohamed [31] found that older adults living with chronic conditions reported lower levels of perceived support. Similarly, and consistent with the present study, Zareipour et al. [32] documented a significant relationship between perceived social support and educational attainment. Lower levels of education may restrict opportunities for social interaction and the development of supportive relationships, whereas higher education tends to expand social networks and enhance individuals’ capacity to both provide and receive support.

The results of the present study further demonstrated a significant positive association between social support and health-promoting behaviors, indicating that greater perceived support is linked to higher engagement in such behaviors. Prior studies by Han et al. [25] and Ahmadboukani et al. [34] reported that older adults who received adequate support exhibited greater adherence to dietary and medication regimens. According to Berkman’s conceptual model, receiving support from one’s social network can influence health outcomes through both behavioral and psychosocial mechanisms [16]. Furthermore, it is plausible that social support reinforces the health-promoting behaviors by strengthening individuals’ confidence in their ability to manage their health effectively [35].

The study also identified significant associations between certain demographic variables and specific domains of health-promoting behaviors. A noteworthy inverse relationship was found between age and interpersonal relationships, suggesting that social interactions tend to diminish with advancing age, possibly due to reduced social engagement, retirement, or physical limitations. A positive association between income and physical activity was also identified, implying that individuals with higher income levels may have greater access to recreational facilities and health-related resources. This finding highlights the need to address socioeconomic disparities in efforts to promote healthier lifestyles [36]. Additionally, a significant correlation was observed between educational level and nutritional practices, suggesting that higher education improves individuals’ understanding of dietary requirements and nutrient intake [37]. Education was also positively associated with health responsibility, as it fosters awareness, informed decision-making, and effective management of health resources [28]. Individuals with higher educational attainment are generally better equipped to set goals, evaluate information, and make sound health-related decisions, thereby cultivating a stronger sense of responsibility in managing their health, time, and available resources. However, although these associations were statistically significant, their effect sizes were small. Given the relatively large sample size, which increases the likelihood of detecting even minimal associations, the practical or clinical significance of these findings is likely limited. Therefore, while these statistical relationships merit acknowledgment, they may not represent meaningful or impactful real-world outcomes. This limitation should be considered carefully when interpreting the results and when designing or implementing potential interventions.

The observed relationships among marital status, health responsibility, and spiritual growth suggest that married individuals may lead more structured lives, which often encompass healthier dietary habits [27]. Moreover, they may experience enhanced spiritual development as a result of the emotional and psychological support provided by their spouses. These findings align with theoretical perspectives emphasizing the role of close interpersonal relationships in fostering spiritual well-being [38]. Additionally, the observed associations between stress management, health responsibility, spiritual growth, and occupational status indicate that friendships, collegial relationships, and workplace social support may facilitate the adoption of health-promoting behaviors among employed older adults. Supporting this view, Safavi et al. [28] likewise reported better stress management among older adults who remained in employment.

Importantly, the present study identified social support, gender, and educational level as significant predictors of health-promoting behaviors and their subdimensions, collectively accounting for 34% of the observed variance. Other studies have also underscored the predictive role of social support, reporting explained variances of 34% and 29%, respectively [9,39]. Consistent with our findings, previous research has repeatedly demonstrated that social support is the most influential predictor of health-promoting behaviors in older adults [22]. By fostering a sense of belonging, acceptance, and psychological security, social support may encourage the adoption of more positive health behaviors [9]. Regarding gender and education as additional predictors, Aygar et al. [40] found that several factors, including these variables, were significantly associated with engagement in health-promoting practices. The greater propensity among women to adopt such behaviors may stem from their more favorable attitudes toward health maintenance and their heightened sensitivity to illness symptoms [27].

Among the principal strengths of this study were the adequate sample size and the use of psychometrically validated, reliable questionnaires. Nevertheless, several limitations warrant consideration. First, because of the cross-sectional design, causal inferences cannot be drawn from the observed relationships. Second, although convenience sampling facilitated recruitment, this non-probability approach may have introduced selection bias, thereby limiting the representativeness of the sample. Additionally, the study population consisted solely of older adults residing in the city of Fasa (a geographically restricted setting) and excluded institutionalized or homebound elderly individuals, which may further constrain the external validity and generalizability of the findings. While some observed associations reached statistical significance, their effect sizes were relatively small and should therefore be interpreted with caution. These modest effects may reflect limited practical significance and highlight the need for further research to clarify the underlying mechanisms. Future investigations should consider contextual variables potentially related to social support and health-promoting behaviors—such as self-rated health and subjective well-being—and adopt longitudinal or mixed-methods designs that include older adults from more diverse populations, including those who are homebound or living in residential care facilities. Such approaches would facilitate a more comprehensive understanding of these associations.

Given the predictive significance of social support, gender, and educational attainment in influencing health-promoting behaviors and their dimensions among older adults, it is recommended that health promotion programs and interventions be strategically designed to enhance social support networks while also accounting for individual differences in gender and education. This targeted approach has the potential to improve both health outcomes and overall quality of life among the older adults. In light of the global demographic shift toward aging populations and the growing emphasis on preventive strategies in later life, the findings of this study offer valuable insights into the role of social networks and support systems in fostering healthy aging, particularly in low-income and middle-income contexts. These results may also inform national and regional health policies aimed at promoting active and healthy aging. Specifically, integrating social support components into community-based programs and tailoring interventions to reflect the cultural and educational characteristics of older adults may enhance both the effectiveness and sustainability of such initiatives within similar socio-cultural environments.

Notes

Conflict of Interest

The authors have no conflicts of interest associated with the material presented in this paper.

Funding

The authors express their sincere gratitude to the Vice Chancellor for Research at Fasa University of Medical Sciences (approval No. 97509) for financial and administrative support.

Acknowledgements

The authors also extend their heartfelt thanks to all elderly participants who generously contributed to this study.

Author Contributions

Conceptualization: Ghasemi A, Alinejad N, Hayati R, Hosseini Nejad Z. Data curation: Keshtkar M, Hayati R, Hosseini Nejad Z. Formal analysis: Khiyali Z, Dehghan A. Funding acquisition: Alinejad N, Ghasemi A. Methodology: Alinejad N, Dehghan A, Zandieh Z. Writing – original draft: Khiyali Z, Alinejad N, Ghasemi A. Writing – review & editing: Alinejad N, Zandieh Z, Khiyali Z.

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References

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