Abstract
Introduction
Women, especially in urban marginalized areas, face a set of challenges and limitations in the field of health promotion. Considering the key role of women in family and community health, and their vulnerability in marginalized conditions, this study aimed to examine health-promoting lifestyle in women living in urban marginalized areas, to identify their needs and provide a foundation for designing evidence-based interventions and effective policies to improve women’s health.
Methods
This cross-sectional, descriptive-analytical study was conducted in 2025 on 295 women living in a suburban area of Mashhad, northeastern Iran, using multi-stage sampling. After ethical approval and written informed consent, participants completed a demographic questionnaire and the Health-Promoting Lifestyle Profile II (HPLP-II), whose Persian version has confirmed validity and reliability in Iran (Cronbach’s alpha = 0.82). Data were analyzed in SPSS version 25 using descriptive and analytical statistics including Kruskal–Wallis, Mann–Whitney U, and Spearman correlation tests with a significance level of p < 0.05.
Results
The mean age of the women was 37.25 ± 10.63 years and mean total health-promoting lifestyle score was 127.87 ± 26.91, with the highest mean score in the spiritual growth dimension (26.02 ± 5.58). Analyses showed a significant inverse relationship between age, number of children, BMI, and lifestyle score (P < 0.05), and lower lifestyle scores among women with chronic diseases such as hypertension and hyperlipidemia (P < 0.05). A significant increase in lifestyle score with higher family income (P < 0.05), and differences in mean lifestyle scores based on marital status and educational level (P < 0.05).
Discussion and conclusion
The findings indicate that the overall level of health-promoting lifestyle among women living in marginalized areas is moderate and associated with various individual and social factors. These findings suggest that improving women’s health in such settings requires attention to both personal behaviors and broader economic and educational contexts. Further studies are recommended to design and assess interventions that effectively address these factors.
Keywords: Health Promotion, Life Style, Women, Suburban Population, Iran
Introduction
A health-promoting lifestyle is considered a cornerstone of a long and healthy life [1]. Walker et al. defined a health-promoting lifestyle as a multidimensional pattern of perceptions, emotions, and behaviors arising from an individual’s motivation to maintain and enhance health and achieve self-actualization [2–4]. This lifestyle encompasses six dimensions: health responsibility, physical activity, nutrition, stress management, spiritual growth, and interpersonal relationships [5, 6]. The importance of adopting such behaviors is also reflected in the goals of the World Health Organization’s “Health for All” program.
In recent decades, lifestyle-related changes have been recognized as major contributors to many health problems, including obesity, cardiovascular diseases, various cancers, and substance abuse, particularly in developed countries [7–10]. International evidence suggests that unhealthy lifestyle patterns significantly increase the risk of chronic diseases. For example, a comprehensive review of meta-analyses showed that healthy dietary patterns can significantly reduce the risk of type 2 diabetes, colorectal and breast cancers, and cardiovascular mortality, whereas unhealthy dietary habits increase these risks [11]. Similarly, a systematic review of 71 prospective studies demonstrated that adherence to a healthy lifestyle—characterized by balanced nutrition, regular physical activity, smoking cessation, and moderate alcohol consumption—is associated with a substantial reduction in cardiovascular disease and overall mortality [12].
Gender is one of the important factors influencing health-promoting lifestyles [13]. Women play a key role in shaping family health behaviors and often serve as role models for promoting healthy practices in the next generation [14]. Moreover, women constitute a fundamental pillar of family and community development, and their health is widely recognized as a public health priority [15]. Consequently, improving and maintaining women’s health has become a major focus of global health initiatives [16]. In Iran, evidence indicates that approximately 20% of women aged 15–54 years suffer from at least one chronic disease, such as diabetes, heart disease, or joint disorders. In addition, the crude annual mortality rate among women in Iran has been estimated at about 2.8 per 1,000 women [17].
Rapid urbanization and the exponential growth of urban populations have created numerous challenges, including the expansion of informal settlements characterized by high unemployment, poverty, limited access to urban services, and inadequate living conditions [18]. These conditions can create unfavorable environments that negatively affect public health and increase health inequalities [19].
Iran has also experienced rapid urbanization accompanied by the growth of informal settlements [20]. Mashhad, located in northeastern Iran and the capital of Razavi Khorasan Province, is the second-largest city in the country and one of the most important religious centers in the world due to the presence of the holy shrine of Imam Reza. Rapid population growth and migration to this metropolis over recent decades have contributed to the expansion of marginalized neighborhoods, making Mashhad one of the Iranian cities where the issue of informal settlements is particularly prominent [20].
Studies examining the social structure of marginalized areas have reported several challenges, including large household sizes, high migration rates, poor housing conditions, substandard infrastructure, low literacy levels, and limited access to health-care services [21]. Residents of these settlements are more likely to experience illness, injuries, and premature death compared with those living in non-marginalized areas, and the burden of disease and poverty in these communities often increases over time [22]. Despite the importance of this issue, relatively few studies have investigated the health and lifestyle of women living in disadvantaged urban or rural communities. Studies conducted in India and Nepal indicate that unhealthy behaviors—such as smoking, alcohol consumption, physical inactivity, low intake of fruits and vegetables, and excessive salt consumption—are prevalent among rural populations [23, 24]. Similarly, research in Ghana has shown that the general health status of rural women is significantly poorer than that of urban women [26].
However, most previous studies have focused on general urban populations or rural communities in other countries. Limited attention has been given to women living in marginalized urban settlements in Iran. In large cities such as Mashhad, where rapid urbanization, migration, and the expansion of informal settlements have created distinct social and environmental challenges, the lifestyle and health-related behaviors of marginalized women may differ substantially from those of other population groups. These differences may be related to socioeconomic deprivation, cultural and religious characteristics of the region, gender-related vulnerabilities, and disparities in education and access to health services among marginalized urban women.
Therefore, the present study aimed to examine health-promoting lifestyles among women living in marginalized areas of Mashhad. The findings of this study may help identify priority areas for targeted health promotion strategies and support the development of culturally appropriate interventions to improve women’s health in marginalized communities.
Materials and methods
Study design and participants
This descriptive-analytical cross-sectional study was conducted in 2025 in Mashhad, northeastern Iran. The target population consisted of women covered by a Comprehensive Health Services Center located in one of the marginalized neighborhoods of Mashhad.
A multi-stage sampling approach was used to select the study setting. In the first stage, Health Center No. 3 was randomly selected from among five health centers affiliated with Mashhad University of Medical Sciences. In the second stage, one comprehensive health services center located in a marginalized area under the supervision of Health Center No. 3 was randomly selected as the research site. Health Center No. 3 has the largest covered population among the five health centers in Mashhad, serving more than 1.5 million people. Therefore, this setting was considered appropriate for investigating health-promoting lifestyle behaviors among women living in marginalized urban areas.
Eligible participants were women who provided informed consent and had lived in the marginalized area for at least one year. Participants who left more than 10% of the questionnaire items unanswered were excluded from the final analysis.
Sample size
The sample size was calculated based on the results of the study by Hamzehgardeshi et al. (2024), in which the mean score of health-promoting lifestyle was reported as 127.02 ± 23.23 [25]. Considering a precision of 4, a type I error of 5%, and a test power of 80%, the required sample size was estimated to be 265 using the following formula:
 |
To compensate for a possible 10% dropout or incomplete responses, 300 women were initially recruited. After excluding participants who met the exclusion criteria, data from 295 women were included in the final analysis.
Sampling procedure and data collection
The study protocol was approved by the Ethics Committee of Mashhad University of Medical Sciences under the ethics code IR.MUMS.NURSE.REC.1404.041. Before data collection, the necessary permissions and coordination were obtained from the relevant health center authorities.
The researcher attended the selected health center over a six-month period. Participants were recruited using convenience sampling according to the inclusion and exclusion criteria. The researcher introduced herself to eligible women, explained the objectives and importance of the study, assured them of the confidentiality of their information, and obtained written informed consent.
Data were collected using two methods: paper-based questionnaires completed in person at the health center and online questionnaires completed through the Porsline platform. Participants were instructed on how to complete the questionnaires, and they were allowed to ask questions if any item was unclear.
Data collection instruments
Two instruments were used for data collection.
The first instrument was a demographic questionnaire consisting of 14 items assessing participants’ personal and socioeconomic characteristics, including age, marital status, number of children, history of physical and mental illnesses, education level, employment status, income, and tobacco and alcohol consumption. This questionnaire was previously used by Khani et al. (2021) [26].
The second instrument was the Health-Promoting Lifestyle Profile II (HPLP-II). This questionnaire enables researchers to assess health-promoting lifestyle patterns, determinants of health-related behaviors, and the effects of lifestyle modification interventions [5]. The HPLP-II has been widely used in previous studies [26–30]. It contains 52 items across six dimensions: nutrition, physical activity, health responsibility, spiritual growth, stress management, and interpersonal relationships.
Items are scored on a four-point Likert scale ranging from 1 to 4, where 1 indicates “never” and 4 indicates “always.” The total score ranges from 52 to 208, with higher scores indicating a healthier lifestyle. The Persian version of this instrument was validated by Mohammadi Zeidi et al. in Iran. The overall reliability of the questionnaire was reported as 0.82, and the reliability coefficients of its subscales ranged from 0.64 to 0.91 [25, 31].
Data analysis
After entering the data into SPSS version 25, data analysis was conducted using descriptive and analytical statistics. Descriptive statistics (frequency, percentage, mean, and standard deviation) were calculated. Since quantitative variables were not normally distributed, non-parametric tests including Kruskal-Wallis, Mann-Whitney U, and Spearman correlation coefficient were applied to compare and correlate the lifestyle score with demographic variables. A significant level of p < 0.05 was considered.
Results
The mean age of the participants was 37.25 ± 10.63 years. The mean number of children was 2.20 ± 1.21, and the mean body mass index (BMI) was 27.15 ± 11.48. Tables 1 and 2 present other demographic characteristics.
Table 1.
Demographic characteristics of women living in marginalized areas of Mashhad, Iran (n = 295)
| Variable | Number | Standard Deviation ±Mean | Minimum | Maximum | Median |
|---|---|---|---|---|---|
| Age (years) | 295 | 37.25 ± 10.63 | 16 | 83 | 36 |
| Weight (kg) | 295 | 66.64 13.19 |
35 | 111 | 68 |
| Height (cm) | 295 | 158.28 10.61 |
60 | 180 | 160 |
| Number of children | 295 | 2.20 1.21 |
0 | 6 | 2 |
| BMI (kg/m2) | 295 | 27.15 11.48 |
15.02 | 200 | 26.17 |
Table 2.
Demographic characteristics of women living in marginalized areas of Mashhad, Iran (n = 295)
| Variable | Level | Frequency | Percentage |
|---|---|---|---|
| BMI | Underweight | 13 | 4.40 |
| Normal | 108 | 36.60 | |
| Overweight | 106 | 35.90 | |
| Obesity | 60 | 20.40 | |
| Severe Obesity | 8 | 2.70 | |
| Chronic Disease Status | Yes | 105 | 35.60 |
| No | 190 | 64.40 | |
| Type of Chronic Disease | Diabetes | 26 | 8.80 |
| Hypertension | 31 | 10.50 | |
| Hyperlipidemia | 22 | 7.50 | |
| Mental Disorder | 17 | 5.80 | |
| Thyroid Disorder | 47 | 15.90 | |
| Cancer | 8 | 2.70 | |
| Other Disorders | 15 | 5.10 | |
| Marital Status | Single | 18 | 6.10 |
| Married | 239 | 81.30 | |
| Divorced | 18 | 6.10 | |
| Widowed | 20 | 6.80 | |
| Education Level | Illiterate | 24 | 8.10 |
| Primary | 70 | 23.70 | |
| Secondary | 87 | 29.50 | |
| Diploma | 88 | 29.80 | |
| Associate Degree | 8 | 2.70 | |
| Bachelor | 15 | 5.10 | |
| Master | 1 | 0.30 | |
| PhD and above | 2 | 0.70 | |
| Occupation | Housewife | 256 | 86.80 |
| Self-employed | 20 | 6.80 | |
| Employee | 6 | 2 | |
| Retired | 1 | 0.30 | |
| Worker | 7 | 2.40 | |
| Student | 5 | 1.70 | |
| Spouse’s Education Level | Illiterate | 68 | 23.10 |
| Primary | 63 | 21.40 | |
| Secondary | 73 | 24.70 | |
| Diploma | 64 | 21.70 | |
| Bachelor | 15 | 5.10 | |
| Master | 10 | 3.40 | |
| PhD and above | 2 | 0.70 | |
| Spouse’s Occupation | Self-employed | 117 | 39.70 |
| Employee | 10 | 3.40 | |
| Retired | 2 | 0.70 | |
| Worker | 94 | 31.90 | |
| Unemployed | 72 | 24.40 | |
| Household Income | Less than 5 million Tomans | 101 | 34.20 |
| 5–10 million Tomans | 88 | 29.80 | |
| 10–15 million Tomans | 73 | 24.70 | |
| 15–20 million Tomans | 29 | 9.80 | |
| More than 20 million Tomans | 4 | 1.40 | |
| Smoking | Yes | 8 | 2.70 |
| No | 287 | 97.30 | |
| Hookah Use | Yes | 30 | 10.20 |
| No | 265 | 98.80 | |
| Alcohol Consumption | Never | 287 | 97.30 |
| Rarely | 4 | 1.40 | |
| Sometimes | 3 | 1 | |
| Usually | 1 | 0.30 |
According to Table 3, the highest score for the women’s health-promoting lifestyle was observed in the spiritual growth dimension (26.02 ± 5.58), while the lowest score was observed in the physical activity dimension (15.08 ± 5.28). The overall score of the women’s health-promoting lifestyle was 127.87 ± 26.91. Based on the classification, 68 people (23.1%) were at an undesirable level, 181 people (61.4%) were at a moderate level, and 46 people (15.6%) were at an optimal level.
Table 3.
Mean and standard deviation of health-promoting lifestyle dimensions among women living in marginalized areas of Mashhad, Iran (n = 295)
| Dimension | N | Mean SD |
Min | Max | Median |
|---|---|---|---|---|---|
| Interpersonal Relations | 295 |
 5.19 |
11 | 36 | 24 |
| Nutrition | 295 | 22.83
|
9 | 36 | 23 |
| Health Responsibility | 295 |
 5.51 |
9 | 36 | 20 |
| Physical Activity | 295 |
 5.28 |
8 | 32 | 15 |
| Stress Management | 295 |
 4.39 |
8 | 32 | 20 |
| Spiritual Growth | 295 |
 5.58 |
12 | 36 | 26 |
| Total | 295 |
 26.91 |
63 | 208 | 127 |
Spearman’s correlation analysis showed a statistically significant inverse relationship between women’s age and the total lifestyle score and its dimensions, except for stress management and spiritual growth (r = −0.18, P = 0.001) (Table 4). As shown in Table 4, the number of children and BMI were significantly and inversely associated with the physical activity score (P = 0.03 and P = 0.04, respectively), and the number of children was also inversely associated with the stress management score (P = 0.02). Therefore, with increasing age, number of children, and women’s BMI, the lifestyle score in the aforementioned dimensions decreased.
Table 4.
Correlations between health-promoting lifestyle scores and age, number of children, and body mass index among women living in marginalized areas of Mashhad, Iran (n = 295)
| Variable | Statistics | Age | Number of children | BMI |
|---|---|---|---|---|
| Interpersonal Relations | r | −0.24 | −0.11 | −0.02 |
| p-value ^ | > 0.001 | 0.05 | 0.61 | |
| Nutrition | r | −0.22 | −0.07 | −0.01 |
| p-value | > 0.001 | 0.19 | 0.73 | |
| Health Responsibility | r | −0.14 | 0.00 | −0.05 |
| p-value | 0.01 | 0.99 | 0.36 | |
| Physical Activity | r | −0.21 | −0.12 | −0.11 |
| p-value | > 0.001 | 0.03 | 0.04 | |
| Stress Management | r | −0.09 | −0.12 | −0.06 |
| p-value | 0.09 | 0.02 | 0.29 | |
| Spiritual Growth | r | −0.08 | −0.03 | 0.008 |
| p-value | 0.14 | 0.53 | 0.89 | |
| Total | r | −0.18 | −0.08 | −0.04 |
| p-value | > 0.001 | 0.17 | 0.48 |
^ P-value < 0.05 was considered statistically significant
The results of the Mann-Whitney U test showed a statistically significant difference in the mean score of women’s health-promoting lifestyle based on chronic diseases such as hypertension and hyperlipidemia. Specifically, significant differences were observed according to hypertension (P = 0.001) and hyperlipidemia status (P < 0.001) (Table 5).
Table 5.
Comparison of health-promoting lifestyle scores and their dimensions according to demographic characteristics among women living in marginalized areas of Mashhad, Iran (n = 295)
| Variable | Count | Interpersonal Relationships (Mean ± SD) | Nutrition (Mean ± SD) | Health Responsibility (Mean ± SD) | Physical Activity (Mean ± SD) | Stress Management (Mean ± SD) | Spiritual Growth (Mean ± SD) | Total Score (Mean ± SD) |
|---|---|---|---|---|---|---|---|---|
| Chronic Disease* | ||||||||
| Yes | 105 | 22.27 ± 5.44 | 21.35 ± 6.02 | 19.98 ± 5.47 | 14.11 ± 5.25 | 19.19 ± 4.30 | 24.77 ± 5.66 | 121.88 ± 27.39 |
| No | 190 | 24.18 ± 4.93 | 23.64 ± 5.49 | 20.91 ± 5.52 | 15.62 ± 5.24 | 20.21 ± 4.41 | 26.71 ± 5.43 | 131.18 ± 26.13 |
| p-value^ | 0.002 | 0.004 | 0.15 | 0.01 | 0.09 | 0.003 | 0.006 | |
| Hypertension* | ||||||||
| Yes | 31 | 20.65 ± 5.78 | 18.74 ± 7.30 | 18.77 ± 6.23 | 12.48 ± 6.18 | 18.42 ± 5.00 | 24.13 ± 6.17 | 113.19 ± 32.82 |
| No | 264 | 23.83 ± 5.02 | 23.31 ± 5.39 | 20.75 ± 5.40 | 15.39 ± 5.09 | 20.02 ± 4.29 | 26.24 ± 5.48 | 129.59 ± 25.66 |
| p-value | 0.002 | < 0.001 | 0.03 | < 0.001 | 0.09 | 0.07 | 0.001 | |
| Hyperlipidemia* | ||||||||
| Yes | 22 | 19.64 ± 6.05 | 18.14 ± 7.35 | 17.86 ± 6.22 | 12.32 ± 6.41 | 17.41 ± 4.88 | 22.55 ± 6.17 | 107.91 ± 32.19 |
| No | 273 | 23.81 ± 5.00 | 23.21 ± 5.48 | 20.76 ± 5.41 | 15.31 ± 5.13 | 20.04 ± 4.30 | 26.30 ± 5.45 | 129.48 ± 25.85 |
| p-value | < 0.001 | 0.001 | 0.006 | 0.002 | 0.006 | 0.004 | < 0.001 | |
| Family Income Level# | ||||||||
| < 5 million Toman | 101 | 20.85 ± 5.77 | 19.44 ± 6.11 | 19.22 ± 6.03 | 13.91 ± 5.45 | 18.64 ± 4.71 | 24.01 ± 5.96 | 116.07 ± 29.73 |
| 5–10 million Toman | 88 | 23.83 ± 4.50 | 23.56 ± 4.97 | 20.53 ± 5.45 | 14.76 ± 5.48 | 19.89 ± 4.12 | 26.24 ± 5.09 | 128.98 ± 24.49 |
| 10–15 million Toman | 73 | 25.60 ± 3.88 | 25.38 ± 4.12 | 21.55 ± 4.65 | 16.49 ± 4.75 | 21.07 ± 4.07 | 27.89 ± 4.65 | 137.99 ± 20.36 |
| 15–20 million Toman | 29 | 26.28 ± 3.82 | 26.17 ± 4.95 | 22.41 ± 5.25 | 16.21 ± 4.37 | 21.00 ± 3.89 | 28.21 ± 5.26 | 140.28 ± 22.89 |
| > 20 million Toman | 4 | 24.50 ± 4.43 | 21.50 ± 3.00 | 22.25 ± 2.63 | 18.00 ± 5.59 | 18.75 ± 4.50 | 22.00 ± 6.97 | 127.00 ± 24.26 |
| p-value | < 0.001 | < 0.001 | 0.004 | 0.005 | 0.002 | < 0.001 | < 0.001 | |
| Marital status# | ||||||||
| Single | 18 | 23.33 ± 5.68 | 22.83 ± 7.18 | 20.83 ± 7.34 | 18.33 ± 6.72 | 20.50 ± 5.06 | 25.56 ± 6.99 | 131.39 ± 36.18 |
| Married | 239 | 23.87 ± 5.02 | 23.40 ± 5.56 | 20.67 ± 5.29 | 15.13 ± 5.06 | 19.92 ± 4.29 | 26.27 ± 5.37 | 129.31 ± 25.48 |
| Divorced | 18 | 22.67 ± 6.15 | 20.67 ± 5.15 | 21.22 ± 6.03 | 15.61 ± 5.42 | 20.39 ± 5.50 | 26.28 ± 7.16 | 126.83 ± 31.18 |
| Widowed | 20 | 20.00 ± 4.74 | 17.95 ± 5.18 | 18.10 ± 5.71 | 11.20 ± 4.29 | 17.90 ± 3.59 | 23.25 ± 4.70 | 108.40 ± 24.42 |
| p-value | 0.005 | < 0.001 | 0.10 | 0.001 | 0.17 | 0.09 | 0.006 | |
| Education Level# | ||||||||
| Illiterate | 24 | 18.00 ± 3.57 | 15.88 ± 5.86 | 16.50 ± 4.19 | 10.67 ± 4.84 | 16.71 ± 4.29 | 22.42 ± 5.40 | 100.17 ± 24.72 |
| Primary School | 70 | 22.37 ± 4.30 | 21.40 ± 5.58 | 19.71 ± 5.09 | 13.86 ± 5.32 | 19.49 ± 3.71 | 26.29 ± 4.90 | 123.56 ± 23.84 |
| Middle School | 87 | 23.99 ± 5.57 | 23.38 ± 5.25 | 20.61 ± 5.77 | 15.90 ± 5.53 | 20.05 ± 4.54 | 25.60 ± 5.51 | 129.33 ± 27.78 |
| Diploma | 88 | 24.85 ± 4.50 | 24.63 ± 4.75 | 22.03 ± 5.30 | 15.83 ± 4.40 | 20.65 ± 4.45 | 26.92 ± 5.72 | 134.91 ± 23.84 |
| Associate Degree | 8 | 24.50 ± 5.75 | 23.25 ± 6.29 | 20.63 ± 6.90 | 17.00 ± 6.27 | 19.63 ± 4.56 | 24.63 ± 8.19 | 129.63 ± 33.58 |
| Bachelor’s Degree | 15 | 26.33 ± 5.74 | 26.40 ± 5.52 | 22.13 ± 5.37 | 17.60 ± 4.40 | 21.13 ± 4.56 | 29.07 ± 4.51 | 142.67 ± 24.08 |
| Master’s Degree | 1 | 23.00 ± 0.00 | 29.00 ± 0.00 | 18.00 ± 0.00 | 11.00 ± 0.00 | 15.00 ± 0.00 | 26.00 ± 0.00 | 122.00 ± 0.00 |
| Doctorate and above | 2 | 23.00 ± 4.24 | 21.50 ± 3.53 | 18.50 ± 2.12 | 18.50 ± 2.12 | 20.00 ± 1.41 | 21.50 ± 4.95 | 123.00 ± 14.14 |
| p-value | < 0.001 | < 0.001 | < 0.001 | < 0.001 | 0.008 | 0.007 | < 0.001 | |
| Body Mass Index (BMI)# | ||||||||
| Underweight | 13 | 21.46 ± 4.89 | 20.31 ± 5.39 | 18.23 ± 6.09 | 14.92 ± 6.47 | 18.62 ± 3.38 | 24.38 ± 5.56 | 117.92 ± 26.93 |
| Normal | 108 | 23.78 ± 5.10 | 23.06 ± 5.76 | 20.95 ± 5.25 | 15.68 ± 5.33 | 20.21 ± 4.31 | 26.34 ± 5.07 | 129.87 ± 25.87 |
| Overweight | 106 | 24.22 ± 5.13 | 24.05 ± 5.70 | 21.27 ± 5.46 | 15.75 ± 5.17 | 20.58 ± 4.43 | 26.47 ± 5.80 | 132.34 ± 26.87 |
| Obese | 60 | 22.07 ± 5.27 | 20.83 ± 5.71 | 18.92 ± 5.54 | 13.00 ± 4.67 | 18.20 ± 4.22 | 24.87 ± 6.10 | 118.40 ± 26.54 |
| Severely Obese% | 8 | 24.25 ± 5.41 | 22.63 ± 4.17 | 21.25 ± 6.45 | 14.13 ± 5.46 | 19.63 ± 5.04 | 27.00 ± 4.62 | 128.88 ± 29.29 |
| p-value | 0.09 | 0.008 | 0.04 | 0.009 | 0.02 | 0.40 | 0.03 | |
* Mann–Whitney U test
# Kruskal-Wallis test
^ P-value < 0.05 was considered statistically significant
% Results for subgroups with very small sample sizes (e.g., severely obese) may be unstable and should be interpreted cautiously
According to the results of the Kruskal-Wallis test, women’s lifestyle scores increased significantly with increasing family income (P < 0.001). In addition, the scores for the interpersonal relationships and nutrition dimensions were significantly higher among married women than among other groups (P = 0.005 and P < 0.001, respectively). In contrast, the total lifestyle score and the physical activity dimension were significantly higher among single women than among other groups (P = 0.006 and P = 0.001, respectively). A statistically significant difference was also found in the mean lifestyle score and its dimensions based on women’s education level and BMI, except for the interpersonal relationships and spiritual growth dimensions (P < 0.05) (Table 5).
Discussion
The present study examined health-promoting lifestyle behaviors among women living in a marginalized area of Mashhad. The findings indicated that the mean total score of health-promoting lifestyle among the participants was at a moderate level. Among the lifestyle dimensions, spiritual growth had the highest mean score. This finding is consistent with the results reported by Abdelaziz et al. (2022), who investigated the relationship between health-promoting behaviors and sleep quality among postmenopausal women in Saudi Arabia, as well as Hosseini et al. (2024), who examined the association between health rigor, health-promoting lifestyle, and quality of life among adults. Similar findings were also reported by Ahmadi et al. (2020) in their study of health-promoting lifestyle among Afghan immigrant women in Iran [3, 32, 33].
Spiritual growth is considered one of the key components of holistic health because it provides meaning and direction in life and contributes to inner peace, emotional stability, and a sense of connection with oneself, others, and a higher power [34]. Previous research has shown that strengthening spiritual health can positively influence overall health status, disease progression, and mental well-being [35, 36]. For women living in marginalized communities characterized by economic hardship, social insecurity, and limited resources, spiritual beliefs may function as an important psychological coping resource and a source of resilience. Therefore, incorporating spiritual aspects into health promotion programs may enhance their effectiveness in such contexts.
Despite the high score observed in the spiritual growth dimension, stress management received a relatively low score. This finding is noteworthy because spirituality is theoretically associated with improved resilience and adaptive coping strategies [37]. However, inconsistent findings have been reported in the literature. For example, Saedmoucheshi et al. (2023) reported a significant negative correlation between spiritual health and levels of depression, anxiety, and stress among pregnant women [38]. In contrast, other studies have emphasized the role of spirituality in enhancing resilience and helping individuals cope with social stressors [39, 40].
The coexistence of high spiritual growth and low stress management scores in the present study may indicate that although women in marginalized areas rely on spiritual beliefs as a psychological resource, these beliefs may not always translate into practical coping strategies for managing daily stressors. This finding suggests the importance of integrating practical stress management skills with culturally appropriate spiritual practices in health promotion programs. Interventions such as stress management training, mindfulness practices, community support groups, and strengthening social support networks may help improve coping abilities among women in these communities.
Physical activity had the lowest mean score among the lifestyle dimensions in this study. This finding is consistent with the results of Mirghafourvand et al. (2015), who examined predictors of health-promoting behaviors among women of reproductive age. Several other studies have similarly reported low levels of physical activity among women [32, 41, 42]. Physical inactivity is considered one of the major risk factors for non-communicable diseases and contributes substantially to the global burden of disease [43]. Cultural norms, social expectations, economic constraints, and limited access to safe environments for exercise are among the factors that may reduce women’s participation in physical activity [44].
In marginalized urban areas, structural barriers such as the lack of safe public spaces, limited access to sports facilities, environmental insecurity, and financial constraints may further restrict opportunities for regular physical activity. These findings highlight the need for targeted public health interventions. Developing safe and accessible recreational environments, along with culturally appropriate educational programs, may help increase women’s engagement in physical activity.
Global evidence also indicates that physical activity levels are strongly influenced by environmental, social, and economic contexts. Studies have shown that access to supportive urban infrastructure, safe recreational spaces, and effective public health policies plays a crucial role in promoting physical activity, particularly among women [45, 46].
The findings of this study also revealed that more than half of the participants were overweight or obese (BMI > 25). This finding may partly reflect the low level of physical activity observed among participants. Previous studies suggest that the high prevalence of overweight and obesity in disadvantaged communities may be associated with dietary patterns characterized by low-cost, energy-dense foods [47]. Financial limitations and the relatively high cost of healthy foods may restrict access to nutritious dietary options among families living in marginalized areas [48].
In many low-income urban communities, the household food basket often relies on inexpensive carbohydrate-rich foods such as bread, rice, potatoes, and pasta, whereas the consumption of fruits, vegetables, lean proteins, and healthy fats may be relatively limited [49]. Combined with limited physical activity, such dietary patterns may contribute to increased body mass index among women in these settings. Improving access to affordable healthy foods, increasing nutritional awareness, and promoting healthy eating behaviors may therefore play an important role in addressing obesity in marginalized populations.
The results also showed a significant inverse relationship between age and health-promoting lifestyle scores, suggesting that engagement in health-promoting behaviors decreased with increasing age. This finding is consistent with the results reported by Ajam et al. (2022), who found a significant negative association between age and lifestyle score [50]. Similarly, Habibi et al. (2006) reported differences in health-promoting behaviors among different age groups of women [9].
However, some studies have reported contrasting findings, suggesting that older adults may adopt healthier lifestyles due to increased health awareness or greater contact with health services. For example, Bahrami et al. reported that some individuals modify their lifestyle after experiencing health problems or receiving medical advice [51]. Such inconsistencies across studies may be related to differences in socioeconomic status, health literacy, social support, and access to health care services.
In marginalized areas, older women may face additional barriers to maintaining healthy lifestyles, including limited mobility, reduced social support, and inadequate community infrastructure designed for aging populations. Therefore, developing interventions aimed at increasing motivation, improving self-efficacy, and providing supportive environments for healthy behaviors among older women appears necessary.
The results of this study also showed that women with chronic diseases such as hypertension and hyperlipidemia had lower lifestyle scores compared with women without these conditions. This finding is consistent with previous research indicating that individuals with chronic diseases may encounter greater challenges in maintaining healthy lifestyles due to physical limitations, persistent symptoms, and psychological stress [50].
Chronic conditions such as hypertension, diabetes, and hyperlipidemia often require long-term management and continuous lifestyle modification [52, 53]. In marginalized communities, barriers such as limited access to health services, high treatment costs, and delayed health-seeking behaviors may complicate disease management. Consequently, a cycle may develop in which chronic diseases and unhealthy lifestyle behaviors reinforce each other. Strengthening primary health care services, expanding screening programs, and implementing community-based health education may help improve disease prevention and management among women in these areas.
Nevertheless, some studies suggest that receiving a diagnosis of chronic disease may motivate individuals to adopt healthier lifestyles. For instance, Artinian et al. reported that individuals diagnosed with cardiovascular diseases may improve their dietary habits and physical activity levels after receiving medical advice [54]. Such differences may be influenced by factors such as disease severity, health literacy, and personal motivation. The present study also found that higher family income was significantly associated with better lifestyle scores. A review by Ghasemi et al. (2021) examining the social determinants of healthy lifestyle among Iranian women identified factors such as income, employment, education level, housing conditions, and social support as important determinants of lifestyle behaviors [55]. Similarly, Mirghafourvand et al. (2015) reported that demographic variables such as education and income significantly explained variations in lifestyle scores. Previous studies have also shown that higher income and healthier lifestyles are associated with reduced mortality risk, although lifestyle improvements alone cannot completely eliminate health inequalities related to socioeconomic status [12, 56].
Women living in marginalized areas often face limited employment opportunities and may rely primarily on domestic work or low-income informal jobs. Such structural conditions may make it more difficult to adopt healthy lifestyles. Therefore, effective health promotion strategies should address not only individual behaviors but also broader social determinants of health.
Furthermore, demographic data in this study indicated that a large proportion of women were housewives with relatively low education levels. The education and employment status of their spouses and the overall family income were also generally low. These conditions may limit access to health information and support resources. Research shows that low education level and poor economic status are major barriers to adopting healthy lifestyle and utilizing health services [56].
In marginalized communities, high school dropout rates among girls and early marriage are also common. Such circumstances may limit women’s access to health information and their ability to make informed decisions about their health and family life. Therefore, it is recommended that health promotion programs be designed and implemented with careful consideration of the cultural and economic characteristics of the target population to ensure greater acceptance and effectiveness.
Finally, it should be noted that the analyses in this study were primarily based on bivariate statistical methods, and the observed associations may be influenced by potential confounding variables. Factors such as age, income, education, and chronic diseases are interrelated, and their combined effects may influence lifestyle behaviors. Future studies are therefore recommended to apply multivariate statistical models to identify independent predictors of health-promoting lifestyle behaviors among women living in marginalized communities.
Conclusion
The findings of this study showed that the health-promoting lifestyle of women living in marginalized areas of Mashhad was at a moderate level. This finding suggests that although some health-promoting behaviors are practiced by women in these communities, there remains considerable room for improvement, particularly in dimensions that are strongly affected by social, economic, and environmental conditions.
Among the dimensions of health-promoting lifestyle, spiritual growth received the highest score. This may reflect the important role of religious beliefs, spirituality, and spiritual resources in the lives of women living in marginalized areas. However, the relatively lower score in stress management suggests that spiritual resources may not always be sufficient to support effective coping with psychological pressures arising from unfavorable living conditions, economic hardship, and social vulnerability.
Physical activity had the lowest score among the lifestyle dimensions. This finding, together with the high prevalence of overweight and obesity among participants, may indicate the influence of structural and environmental barriers in marginalized areas, such as limited access to safe recreational spaces, environmental insecurity, economic constraints, and unhealthy dietary patterns. Moreover, the observed associations between older age, higher number of children, higher BMI, chronic diseases, and lower health-promoting lifestyle scores highlight the need to pay greater attention to vulnerable subgroups of women in these communities.
The findings also suggest that socioeconomic factors, including income, educational level, marital status, employment conditions, and access to health-related resources, may play an important role in shaping health-promoting lifestyle behaviors among marginalized women. Therefore, interventions aimed at improving women’s health in marginalized areas should not focus solely on individual behavior change. Rather, they should also address broader social, economic, cultural, and environmental determinants of health.
Overall, the results of this study can help health policymakers, community health nurses, and primary health-care providers identify priority areas for health promotion among women living in marginalized urban communities. Given the descriptive and cross-sectional nature of the study, causal inferences cannot be made. Further longitudinal and interventional studies are recommended to design, implement, and evaluate culturally appropriate, community-based, and multi-level interventions to improve health-promoting lifestyles among marginalized women.
Study limitations
Several limitations should be considered when interpreting the findings of this study. First, data were collected using self-report questionnaires, which may be affected by recall bias and social desirability bias. This limitation may be particularly relevant in marginalized populations, where cultural norms, different levels of health literacy, and concerns about being judged may influence how participants understand questions or report their behaviors.
Second, the cross-sectional design of the study limits the ability to establish causal relationships between variables. Although significant associations were observed between health-promoting lifestyle scores and variables such as age, BMI, number of children, and chronic diseases, the temporal direction of these relationships cannot be determined. For example, it is not clear whether chronic diseases lead to poorer lifestyle behaviors or whether unhealthy lifestyle behaviors increase the likelihood of developing chronic conditions. Longitudinal studies are needed to clarify these relationships.
Third, participants were recruited using convenience sampling from one comprehensive health services center. Therefore, the findings may not be fully generalizable to all women living in marginalized areas of Mashhad or to women in other regions with different sociocultural and economic characteristics. Future studies with larger sample sizes, probability sampling methods, and recruitment from multiple health centers are recommended to improve the external validity of the findings.
Fourth, some subgroup analyses included categories with a small number of participants, such as the severely obese group. Therefore, the estimates related to these subgroups may be unstable and should be interpreted with caution.
Acknowledgements
This study was conducted with the financial support of Mashhad University of Medical Sciences [grant number 4040112]. The authors of this article express their gratitude to all those who collaborated in the various stages of this research. We would like to thank the health center officials and experts who provided the necessary conditions for the study and cooperated effectively with the study. We also sincerely appreciate the esteemed participants who played a key role in data collection by spending their time and providing accurate information.
Authors’ contributions
All authors contributed to the editing the manuscript and approved the final version for publication. FR, ND, and HRZT jointly designed and planned the study. FR identified and recruited potential participants. FR, ND, and HRZT contributed to the conceptualization and design of the study. FR and SN made significant contributions to the analysis and interpretation. All authors contributed to drafting the manuscript or critically revising it for important intellectual content. All authors read and approved the final manuscript.
Funding
This study was funded by Mashhad University of Medical Sciences.
Data availability
Datasets generated and/or analyzed during the present study are available from the corresponding author upon reasonable request.
Declarations
Ethics approval and consent to participate
This study was approved by the Ethics Committee of Mashhad University of Medical Sciences, Mashhad, Iran, under the ethics code IR.MUMS.NURSE.REC.1404.041. All procedures were conducted in accordance with the Declaration of Helsinki and relevant ethical guidelines and regulations. Eligible women were invited to participate after receiving information about the study objectives and procedures, and written informed consent was obtained from all participants prior to data collection.
Consent for publication
Not applicable.
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.
Data Availability Statement
Datasets generated and/or analyzed during the present study are available from the corresponding author upon reasonable request.