Abstract
Background
Motivation to engage in physical activities is a multifaceted phenomenon influenced by numerous individual, social, and environmental factors. Understanding these factors in the older adults, as a group with specific needs, is particularly crucial. This study aims to determine the relationship between lifestyle and participation motivation in physical activity among the older adults.
Methods
This cross-sectional study was conducted from January 2023 to June 2024. A total of 263 older adults visiting comprehensive health centers and day care centers participated in the study. Data were collected using “the Participation Motivation Questionnaire of Older Adults in Physical Activity“(PMQOA) and “Lifestyle older adults” questionnaires. Data were analyzed using univariable and multivariable logistic regression analyses performed in STATA. Odds ratios (ORs) were calculated with 95% confidence intervals (CI).
Results
The mean score (standard deviation) for motivation to participate in physical activities was 110.3 (19.2) with a (95% CI: 107.9 to 112.6). The mean lifestyle score (standard deviation) was 154.2 (25.4) with a (95% CI: 151.1 to-157.3). The logistic regression results indicated that lifestyle had a positive and significant effect on motivation for physical activities (OR = 1.18, 95% CI: 1.08 to 1.29, p < 0.001), with each unit increase in lifestyle score associated with an average 18% increase in motivation for physical activity. Additionally, older men and those with higher education had greater motivation for physical activity (p < 0.05).
Conclusion
The results indicate that older adults with a healthier lifestyle have greater motivation to engage in physical activities. It is recommended to implement lifestyle-enhancing interventions among older adults to increase their motivation for physical activity participation and improve their health.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12913-026-14061-9.
Keywords: Motivation, Physical activity, Life style, Older adults
Background
As life expectancy increases, the global older adult’s population is on the rise [1]. According to a World Health Organization report, the number of individuals over the age of 65 worldwide is projected to double over the next forty years. Consequently, 52% of this population will reside in Asian countries, and 40% in developed countries [2]. By 2050, it is anticipated that the older adults will comprise over 20% of Iran’s population [3].
Successful aging is defined by three factors: the absence of disease, adaptation to life, and maintaining physical and mental health [4]. Based on these factors, the United States Health Services emphasizes regular exercise, proper nutrition, and immunization to enhance the health of the older adults [5]. Regular participation in physical activities helps older adults maintain muscle strength and endurance, improving their balance and coordination. Conversely, a decrease in physical activity can lead to feelings of loneliness and isolation [6]. Despite the importance of physical activities for the older adults, studies show that over 80% of seniors are inactive, and 30% are unwilling to participate in exercise programs [7–9]. A study of Iranian seniors revealed that 50% to 70% of individuals over the age of 60 do not engage in any physical activity during the week [10].
Motivation is a crucial topic in sports psychology, influencing the extent and intensity of performance. People participate in sports and physical activities for various reasons and are motivated in different ways and context [11]. In this context, the results of the study by Mouratidis et al. demonstrated that creating exercise conditions associated with positive emotions enhances self-efficacy and motivation [12]. The findings of Bathgate et al. (2017) showed that motivation for continued activity depends on individuals’ psychological experiences [13]. Another study indicated that fear of falling and the inability to perform tasks reduce the older adults’ motivation to participate in physical activitie [14]. Additionally, another study identified access to equipment, time, and motivation as factors influencing physical activity motivation (Meredith et al., 2023). Other significant factors affecting motivation to participate in physical activities include lifestyle choices [15, 16].
A healthy lifestyle, which aims to maintain health and prevent disease, encompasses a range of behaviors that generally contribute to health maintenance and improvement. Typically, a health-promoting lifestyle is divided into six dimensions: nutrition, exercise, health responsibility, stress management, social support, and personal growth [17].
Motivation to engage in physical activities is a multifaceted phenomenon influenced by numerous individual, social, and environmental factors. Understanding these factors in the older adults, as a group with specific needs, is particularly crucial. By identifying and enhancing motivational factors and addressing existing barriers, we can significantly increase older adults’ participation in physical activities, thereby improving their quality of life and health. Current studies have qualitatively examined factors influencing motivation to engage in physical activities or identified factors affecting the quantity of physical activity among individuals. Given the differences in service delivery structures in Iran, the factors influencing older adults’ participation in physical activities may differ from those in other cultures. Also most literature compared benefits of physical activity, with being sedentary, for measured survival and years free of impairment in older adults from different age groups. In addition, little is known about the relationship between lifestyle and participation motivation in physical activity among the older adults. Therefore, this study aims to determine the relationship between lifestyle and participation motivation in physical activity among the older adults.
Materials and methods
Study design
This multi-center, cross-sectional, descriptive-analytical study was conducted in Mazandaran Province, northern Iran, from January 2023 to June 2024. The manuscript was prepared in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines for reporting cross-sectional studies.
Participants
In this cross-sectional study, 263 older adults over the age of 60 who visited comprehensive health centers and day care centers in Ramsar, Mazandaran, participated. Sampling was done through convenience sampling. The sample size was determined to be 263 using the sample size calculation formula, considering an alpha of 0.05, an estimated variance (S² = 62), and an acceptable error margin (d = 1). Inclusion criteria included being aged 60 to 74 years, having the ability to understand and speak Persian, and not having movement disorders such as rheumatism, Parkinson’s disease, or any form of plegia. Participants who scored at least 7 on the Abbreviated Mental Test (AMT) were included. Those who did not complete more than one-third of the questionnaire were excluded from the study.
Data collection
To access individuals over the age of 60, a list of potential participants was prepared and contacted via telephone. If they expressed interest in participating in the study, face-to-face interviews using standard and researcher-made questionnaires were conducted. Before commencing the interview, participants were fully informed about the study’s objectives and the confidentiality of their information. Upon obtaining informed consent, the questionnaires were completed. To ensure proper comprehension of the questions, the researcher assisted participants as needed. Additionally, cognitive ability was assessed using AMT. For those unwilling to participate in face-to-face interviews, telephone-based questionnaire completion was also available. All interviews were conducted by two trained researchers. The following instruments were used for data collection:
Data collection form (Demographic information)
This includes age, gender, marital status, employment, residence, financial status, educational level, and history of chronic diseases (such as diabetes, hypertension, cancer, chronic obstructive pulmonary disease, etc.), Alcohol consumption, sleep duration.
The abbreviated mental test scale (AMT)
This scale comprises 10 items, with total scores ranging from 0 to 10. Lower total scores indicate more severe cognitive impairments. The validity and reliability of this scale were confirmed by Foroughan et al. (2017) with a Cronbach’s alpha of 90% and a cut-off point of 7. In the present study, older adults with scores of 7 and above were considered to have no cognitive impairments [18].
The Participation Motivation Questionnaire of Older Adults in Physical Activity (PMQOA)
This Questionnaire was developed by Benam et al. (2014) in Iran. In Benam’ study, construct validity was examined using exploratory factor analysis, and reliability was assessed using Cronbach’s alpha and test-retest methods. Cronbach’s alpha for the three domains—intrapersonal, interpersonal, and social were 0.75, 0.70, and 0.76, respectively, and 0.81 for the overall scale [19]. This 35-item scale encompasses three domains: intrapersonal (15 items), interpersonal (8 items), and social (7 items). It is scored on a five-point Likert scale ranging from “strongly disagree” (1) to “strongly agree” (5), with total scores ranging from 35 to 175. Scores between 35 and 70 indicate weak motivation, scores between 70 and 105 indicate moderate motivation, and scores above 105 indicate strong motivation among the older adults to participate in activities. Participants were asked to respond to each statement based on their personal perspective. The advantage of this Questionnaire over others lies in its simplicity, clarity, and brevity.
Older adults lifestyle questionnaire
This 46-item scale encompasses five domains: prevention (15 items), physical activity, exercise, and recreation (5 items), healthy nutrition (14 items), stress management (5 items), and social and interpersonal relationships (7 items). The face and content validity of the scale were assessed by Es-Haghi et al. (2009), with reliability confirmed by a Cronbach’s alpha of 0.76. The reliability of the scale was further evaluated by Dorvishzadeh (2015) for each dimension, with Cronbach’s alpha coefficients of 0.83 for prevention, 0.91 for physical activity, exercise, and recreation, 0.88 for healthy nutrition, 0.86 for stress management, and 0.89 for social and interpersonal relationships, resulting in an overall lifestyle questionnaire reliability of 0.89 [20].
This Questionnaire, given the small number of questions, simplicity, and good validity and reliability, is suitable for use in the older adults and can be utilized to assess their lifestyle.
Statistical analyses
In the data preprocessing stage, the collected information was entered into STATA software version 17. After performing data cleaning operations, the data were prepared for statistical analysis.
Categorical variables were reported as frequency distributions and percentages along with a 95% CI. The Pearson Chi-square test was used to compare distributions between groups. Quantitative variables were reported as means, standard deviations, and 95% CI. An independent t-test was used to compare the means of two independent groups. Prior to the test, the normality of the variable distributions was assessed and confirmed using the Shapiro-Wilk test, QQ plot, and PP plot.
To identify the relationship between motivation to participate in physical activities and other primary study variables, univariable and multivariable logistic regression models were utilized. The assumptions of the logistic regression test were thoroughly examined and confirmed in this study. To control for the confounding effects of residential area and sleep duration, a multivariable logistic regression model was used. Three adjusted logistic regression models were established. Model 1, the crude model, did not control for any variables. In Model 2, the effect of the residential area was controlled. Finally, in Model 3 (the full model), the impact of sleep duration was examined. The strength of the relationship between the independent and dependent variables in the regression model was measured using the OR with a 95% CI [21].
To control for Type I error in multiple statistical tests, the Bonferroni correction was applied. All statistical tests were two-tailed and considered significant at a p-value less than 0.05 [22].
Missing data in both quantitative and qualitative variables were analyzed using statistical tests. The mean differences in quantitative variables were less than 20% of the standard deviation, and the frequency differences in qualitative variables were less than 10%, indicating inconsiderable differences between groups with and without missing data [23].
Results
Data from 263 older adults who fully completed the research instruments were analyzed in this study (Fig. 1). The age range of participants was 60 to 74 years, with a mean age of 66.7 (2.4) years. Women comprised 53.2% (n = 140) of the sample. The mean body mass index (BMI) of participants was 28.8 kg/m² (4.2), ranging from 20.1 to 43.2 kg/m². Women were significantly more inclined than men to participate in group physical activities (p < 0.001). There was a significant association between residential area and motivation for physical activity (p = 0.006). However, no significant associations were found between education level (p = 0.089) and economic status (p = 0.20) with motivation for physical activity (Table 1).
Fig. 1.
Flow chart of study. *AMT: the Abbreviated Mental Test
Table 1.
Characteristics of study participants according to motivation group to participate in physical activity groups
| Variables | Motivation to participate in physical activity* | p-value | |
|---|---|---|---|
| Moderate group N = 109 |
Excellent group N = 154 |
||
| Age (years), mean ± SD | 66.5 ± 4.4 | 66.6 ± 4.2 | 0.812 |
| BMI (kg/m2), mean ± SD | 28.4 ± 4.6 | 29.1 ± 3.9 | 0.175 |
| Sex n (%) | < 0.001 | ||
| Male | 26 (23.9) | 97 (63.0) | |
| Female | 83 (76.1) | 57 (37.0) | |
| Marital status, n (%) | 0.601 | ||
| Single | 6 (5.5) | 5 (3.26) | |
| Married | 80 (72.72) | 121 (79.09) | |
| Widowed | 20 (18.18) | 22 (14.4) | |
| Divorced | 2 (1.8) | 4 (2.6) | |
| Missing information | 2 (1.8) | 1 (0.65) | |
| BMI category n (%) | 0.019 | ||
| Normal (18.5–24.9 kg/m2) | 28 (25.7) | 20 (13.0) | |
| Overweight (25–29.9 kg/m2) | 50 (45.9) | 73 (47.4) | |
| Obese (> 30 kg/m2) | 31 (28.4) | 61 (39.6) | |
| Living area n (%) | 0.006 | ||
| Urban | 40 (36.7) | 83 (53.9) | |
| Rural | 69 (63.3) | 71 (46.1) | |
| Education n (%) | 0.089 | ||
| Primary school | 23 (21.7) | 21 (13.4) | |
| Diploma | 48 (45.3) | 62 (39.5) | |
| Bachelor and above | 35 (33) | 67 (42.7) | |
| Missing information | 0 (0) | 7 (4.4) | |
| Employment n (%) | 0.593 | ||
| Administrative staff | 8 (7.3) | 15 (9.7) | |
| Farmer | 45 (42.2) | 60 (39.0) | |
| Unemployed | 32 (29.4) | 37 (24.7) | |
| Retired | 22 (21.1) | 41 (26.6) | |
| Chronic disease n (%) | 0.294 | ||
| Yes | 79 (72.5) | 99 (64.3) | |
| No | 30 (27.5) | 54 (35.1) | |
| Smoker n (%) | 0.263 | ||
| Yes | 23 (21.05 | 43 (27.92) | |
| No | 81 (74.34) | 109 (70.76) | |
| Missing | 5 (4.61) | 2 (1.32) | |
| Alcohol consumption n (%) | 0.121 | ||
| Yes | 5 (4.36) | 15 (10.14) | |
| No | 101 (87.82) | 126 (85.14) | |
| Missing information | 9(7.82) | 7 (4.72) | |
| Sleep duration n (%) | 0.171 | ||
| ≤ 6 h | 21 (19.30) | 45 (29.20) | |
| 6–8 h | 80 (73.40) | 97 (63.00) | |
| ≥ 9 h | 8 (7.30) | 12 (7.80) | |
| Sport n (%) | 0.202 | ||
| Yes | 43 (39.43) | 74 (48.05) | |
| No | 62 (56.91) | 77 (50) | |
| Missing information | 4 (3.66) | 3 (1.95) | |
Motivation to participate in physical activity was measured by a 35-item scale: Scores between 35 and 70 indicate “Weak” motivation, scores between 70 and 105 indicate “Moderate” motivation, and scores above 105 indicate “Excellent” motivation among the older adults. Given that none of the older adults fell into the weak motivation group, they were classified into two groups: moderate and excellent motivation for physical activity
BMI was calculated by calculating the ratio of weight to the square of height (weight (kg) / height2(m)); Normal (18.5–24.9 kg/m2); Overweight (25–29.9 kg/m2), Obese (> 30 kg/m2)
The results showed that the mean score (standard deviation) for older adults motivation to participate in physical activities was 110.3 (19.2) (CI: 95%; 107.9 to 112.6). The range of scores obtained by the older adults was from 71 to 175. Given that none of the older adults fell into the weak motivation group, they were classified into two groups: moderate and excellent motivation for physical activity. Of these, 83 women were in the moderate group, and 97 men were in the excellent motivation group (Fig. 2).
Fig. 2.
Participation Motivation in physical activity. Note: Scores between 35 and 70 from the physical activity motivation questionnaire indicate “Weak” motivation, scores between 70 and 105 indicate “Moderate” motivation, and scores above 105 indicate “Excellent” motivation among the older adults
The mean score for the older adults’ lifestyle was 154.2 (25.4) (CI 95% 151.1 to 157.3). The range of scores obtained by the older adults was from 99 to 222. Given that none of the older adults fell into the unhealthy lifestyle group, they were classified into two groups: moderate and healthy lifestyle. 88 women were in the moderate group, and 52 men were in the healthy group (Fig. 3).
Fig. 3.
The correlation between participation motivation in physical activity and lifestyle. Note: The range of scores, using lifestyle questionnaire, obtained by the older adults was from 99 to 222. Given that none of the older adults fell into the unhealthy lifestyle group, they were classified into two groups: moderate and healthy lifestyle. 88 women were in the moderate group, and 52 men were in the healthy group. The mean overall motivation score in older adults with a healthy lifestyle was significantly higher in all motivational dimensions compared to those with a moderate lifestyle (p < 0.001)
The results indicated that the mean overall participation motivation score in older adults individuals with a healthy lifestyle was significantly higher in all motivational dimensions (interpersonal, intrapersonal, and social) compared to those with a moderate lifestyle (p < 0.001) (Table 2).
Table 2.
Characteristics of study participants according to motivation to participate in physical activity
| Variable | Scores of Motivation to participate in physical activity mean ± SD |
p-value | |
|---|---|---|---|
| Moderate group (n = 109) |
Excellent group (n = 154) |
||
| Participation Motivation | 94.0 ± 9.1 | 121.9 ± 15.8 | < 0.001 |
| Interpersonal | 39.8 ± 8.8 | 55.7 ± 10.4 | < 0.001 |
| Intrapersonal | 22.2 ± 4.8 | 28.0 ± 6.6 | < 0.001 |
| Social | 32.1 ± 6.5 | 38.1 ± 8.2 | < 0.001 |
Note: Motivation to participate in physical activity measured by a 35-item scale: Scores between 35 and 70 indicate “Weak” motivation, scores between 70 and 105 indicate “Moderate” motivation, and scores above 105 indicate “Excellent” motivation among the older adults
SD: Standard Deviation
The results showed that the mean overall lifestyle score in the dimensions of nutrition, exercise, stress management, and relationships was significantly higher in the older adults group with a healthy lifestyle compared to those with a moderate lifestyle. Although no significant difference was observed in the prevention dimension between the two groups, overall, older adults with a healthy lifestyle had higher motivation for physical activities (Table 3).
Table 3.
Characteristics of study participants according to lifestyle
| Variable | Lifestyle category*, mean ± SD | p-value | |
|---|---|---|---|
|
Moderate group n = 109 |
Healthy group n = 154 |
||
| Life style | 147.9 ± 20.8 | 158.8 ± 27.4 | < 0.001 |
| Prevention | 48.0 ± 9.8 | 49.5 ± 9.7 | 0.220 |
| Nutrition | 44.9 ± 8.5 | 48.2 ± 11.2 | 0.011 |
| Exercise | 16.8 ± 4.4 | 18.1 ± 4.6 | 0.020 |
| Stress management | 16.2 ± 4.0 | 17.6 ± 4.9 | 0.015 |
| Relationship | 21.9 ± 5.7 | 25.4 ± 5.7 | < 0.001 |
*The range of scores, using lifestyle questionnaire, obtained by the older adults was from 99 to 222. Given that none of the older adults fell into the unhealthy lifestyle group, they were classified into two groups: moderate and healthy lifestyle
SD: Standard Deviation
The logistic regression results indicated that lifestyle had a positive and significant effect on motivation for physical activities (OR = 1.18, 95% CI: 1.08 to 1.29, P < 0.001).
This finding indicates that with each unit increase in the lifestyle variable, participation motivation for physical activity increases by an average of 18%. This result suggests that lifestyle can be considered an important predictor of participation motivation in physical activity.
The results of the logistic regression analysis indicated that men have significantly higher motivation to engage in physical activity compared to women (OR = 5.43, 95% CI: 3.13 to 9.41, p < 0.001). Additionally, individuals with a normal BMI are more motivated to engage in physical activities compared to obese individuals (OR = 2.75, 95% CI: 1.34 to 5.65, p = 0.001). Furthermore, individuals with university education were more motivated to engage in physical activities compared to those with primary education (OR = 2.16; p = 0.088). However, this difference was not statistically significant (Table 4).
Table 4.
Multivariable logistic regression associated between of motivation to physical activity in elders referring to emergency department and main variables
| Variable | cOR (95% CI) | aOR* (95% CI) | aOR† (95% CI) |
|---|---|---|---|
| Life style | 1.02 (1.01–1.03) | 1.05 (0.98–1.36) | 1.02 (1.01–1.03) |
| Gender | |||
| Female | Reference | - | - |
| Male | 5.43 (3.13–9.41) | 1.74 (1.01–2.9) | 1.04 (0.34–3.21) |
| BMI category | |||
| Normal (18.5–24.9 kg/m2) | 2.75 (1.34–5.65) | 3.21 (1.53–6.76) | 2.85 (1.37–5.92) |
| Over weight (25–29.9 kg/m2) | 2.04 (1.03–4.02) | 2.28 (1.13–4.58) | 2.19 (1.10–4.37) |
| Obese (≥ 30 kg/m2) | Reference | - | - |
| Education | |||
| Primary school | Reference | - | - |
| Diploma | 1.51 (1.06–4.39) | 1.51 (0.75–3.07) | 1.51 (0.74–3.05) |
| Bachelor and above | 2.16 (0.74–3.01) | 1.97 (0.95–4.04) | 2.28 (1.12–4.67) |
aOR: adjusted odds ratio; BMI: Body Mass Index; CI: Confidence Interval; cOR: crude odds ratio; kg/m2: kilogram/meter2
*Adjusted for living area; †Adjusted for sleep duration
Discussion
This study was designed and conducted to determine the relationship between motivation to participate in physical activities, lifestyle, and individual and clinical variables in the older adults. The results showed that older adults with a better lifestyle have greater motivation to engage in physical activities. This study confirms that a healthy lifestyle plays an important role in the health and well-being of the older adults. Seniors with a more active lifestyle generally have better physical and mental health, and as a result, experience a higher quality of life. Healthy nutrition, regular exercise, stress management, and strong social relationships are key factors that contribute to the health and well-being of the older adults. It can be stated that the positive effects of a healthy lifestyle on health status (such as weight reduction, physical fitness, blood sugar regulation, cholesterol level management, and blood pressure control) motivate adherence to healthy lifestyle behaviors. Among the healthy lifestyle behaviors, engaging in physical activity is particularly notable due to its direct and favorable impact on health. Thus, the connection between lifestyle and motivation to participate in physical activities can be justified.
According to the results, for each unit increase in the lifestyle score, the motivation to engage in physical activities increases by approximately 18%. In this context, a study found that positive or negative recommendations from doctors and health service providers regarding lifestyle modifications and the necessity of physical activity play a significant role in motivating older adults to engage in physical activities [13]. Other studies have shown that understanding the health benefits of physical activity within the lifestyle of the older adults is a crucial motivational factor for engaging in physical activities [24, 25].
The results showed that the overall lifestyle scores in the dimensions of nutrition, exercise, stress management, and relationships were higher in the older adults group with an excellent lifestyle compared to those with a moderate lifestyle. These findings suggest that maintaining a healthy lifestyle positively impacts various aspects of lifestyle, including engaging in physical activity among the older adults. The study findings indicated that gender and education level independently influence the motivation to engage in physical activities among the older adults [26, 27]. One possible explanation for this finding is that women may have less motivation for physical activities due to the limitations caused by chronic restrictive diseases such as osteoarthritis, which are more prevalent among women. Additionally, individuals with higher education levels and greater income may have more awareness of the benefits of physical activity. These results are comparable to previous studies emphasizing the importance of social and psychological factors in motivation for physical activity [28, 29].
The study by Ntoumanis et al. (2021) showed that motivation for sustained activity is dependent on individuals’ psychological experiences [30]. Future studies could confirm these findings and further clarify the underlying mechanisms of these connections by examining mediating variables such as social support and self-efficacy. Naderi et al. (2018) also found that positive perceptions of physical activity, positive self-perceptions, and habitual physical activity were motivators, while negative self-perceptions, health problems, lack of interest, and time management issues were deterrents to physical activity among the older adults [31]. Therefore, it was suggested that sports service providers could facilitate participation in physical activity by employing motivating factors and addressing barriers, thereby improving their physical and mental health [15].
The findings of Poda et al. (2019) indicate that a vegetarian diet, multiple medications, comorbidities, dysphagia, and lifestyle factors such as smoking, alcohol consumption, and sleep duration of 6 to 8 h are risk factors for malnutrition in the older adults [32]. These factors, by causing physical weakness, were identified as barriers to physical activity among the older adults. Other studies identified access to equipment, time, and motivation as factors influencing physical activity motivation, which differ from the findings of the present study [33]. The reason for this difference may lie in the cultural context and the life priorities of older adults in various societies. Each individual’s priorities vary, leading to a preference for certain beneficial activities over those less impactful on health.
The limitations of the ongoing study are: (a) not conducting an exploratory factor analysis due to the lack of access to more subjects, (b) filling out the questionnaire as a self-report, (c) possible influence of participants’ physical, mental and psychological condition of the participants in answering the items, (d) limiting the sampling to one geographical region of Iran, and (e) limiting the sampling to an age group (older adults).
Conclusion
The present study revealed that older adults with a better lifestyle have greater motivation to engage in physical activities. Therefore, it is recommended that lifestyle improvement interventions be implemented among the older adults to enhance motivation for physical activity participation and improve their health. The findings also indicated that gender and education level independently affect the motivation for physical activity among the older adults. Thus, it is suggested that educational and supportive interventions be provided to old women and those with primary education to increase their motivation to participate in physical activities.
Supplementary Information
Below is the link to the electronic supplementary material.
Acknowledgements
The authors would like to acknowledge the research deputy at Babol University of medical sciences for their support. We have no funding support.
Abbreviations
- OR
Odds ratio
- CI
Confidence interval
- SD
Standard deviation
- AMT
Abbreviated mental test
- STROBE
Strengthening the reporting of observational studies in epidemiology
- BMI
Body mass index
- SD
Standard deviation
- aOR
adjusted odds ratio
- cOR
crude odds ratio
Author contributions
Planning the structure and methodology of the study-Zahra Fotokian, Fatemeh Larijani, Data Acquisition: Ali Pourhabib, Fatemeh Mohammad-khah, Leyla Taslimi, Data Analysis: Ali Pourhabib, Data Interpretation: Zahra Fotokian, Ali Pourhabib, Fatemeh LarijaniWriting the Manuscript: Zahra Fotokian, Ali Pourhabib, Revising the Manuscript: Zahra Fotokian, Ali Pourhabib.
Funding
No funding was received for this article.
Data availability
The data that support the findings of this study are available from Partnership for Research and Action for Health (PRAH), but restrictions apply to the availability of these data. While the dataset is not publicly available due to sensitivity concerns, de-identified data can be shared upon reasonable request and with the permission of PRAH by emailing to corresponding author.
Declarations
Ethical approval and consent to participate
Data were collected after obtaining approval from the Ethics Committee of Babol University of Medical Sciences (IR.MUBABOL.REC.1401.047) and complied with the Declaration of Helsinki; informed consent has been obtained from the subjects. The study’s purpose and importance were explained to participants, who met the inclusion criteria, and they signed the written informed consent form. All collected data were anonymized and stored in a secure folder, accessible solely to the principal investigator. All methods were performed in accordance with the relevant guidelines and regulations, which are aligned with the Declaration.
Consent for publication
Not applicable. This study does not include any individual-level identifying images or personal or clinical details of participants that compromise anonymity.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The data that support the findings of this study are available from Partnership for Research and Action for Health (PRAH), but restrictions apply to the availability of these data. While the dataset is not publicly available due to sensitivity concerns, de-identified data can be shared upon reasonable request and with the permission of PRAH by emailing to corresponding author.