The global burden of hypertension continues to increase, affecting approximately 2.64 billion people worldwide [1]. In China, young and middle-aged adults account for 67.5% of the estimated 244.5 million individuals with hypertension, and prevalence among the younger population is rising at rates two to three times higher than those observed among older adults [2, 3]. Hypertension remains the leading modifiable risk factor for cardiovascular disease (CVD) and all-cause mortality globally, with CVD accounting for more than 40% of all deaths in China [1, 4]. Despite this growing burden, younger adults demonstrate lower levels of hypertension awareness, treatment, and control compared with older populations. Accordingly, the 2024 updated Chinese hypertension guidelines emphasize the importance of addressing hypertension prevention and management among working-age adults [5].

Lifestyle modification is consistently recommended as a first-line strategy for hypertension management across major international and national guidelines [5, 6]. Nevertheless, evidence suggests that working-age adults with hypertension tend to maintain poorer lifestyle behavior than older adults. They are more likely to report unhealthy dietary patterns, insufficient physical activity, and higher levels of life stress related to work and family responsibilities, and they often participate in social activities in which alcohol consumption plays an important role [7, 8]. These patterns suggest that both individual circumstances and social environments may be associated with challenges in adopting guideline-recommended lifestyle behaviors in this population.

This perspective is consistent with the Individual and Family Self-Management Theory (IFSMT), a nursing-relevant theoretical framework that conceptualizes health behavior in chronic conditions as being shaped by contextual and self-management process factors [9]. Guided by the IFSMT, the present study focused on four independent variables that align with key theoretical domains and are amenable to nursing assessment and intervention. Life stress was conceptualized as a contextual factor, whereas hypertension knowledge, self-efficacy, and family relationship were conceptualized as self-management (SM) process factors. Lifestyle modification was defined as a proximal outcome within the IFSMT and served as the dependent variable in this study, which may be associated with both contextual and process-related factors.

Previous studies have reported that stress management is associated with better engagement in lifestyle modification behaviors among individuals with hypertension [10]. In addition, Chinese adults with hypertension have been shown to have limited knowledge regarding the development, prognosis, and complications of hypertension, and higher levels of hypertension-related knowledge have been associated with better adherence to lifestyle recommendations [11, 12]. Family-related factors have also been linked to self-management processes. For example, family encouragement and support have been associated with higher self-efficacy, which in turn has been associated with self-management behaviors in individuals with hypertension [13]. Similarly, positive family relationships have been associated with greater family support and healthier lifestyle behaviors [14-17]. Stable and supportive family relationships may facilitate healthier behavior adoption by shaping daily routines, emotional support, and shared health-related practices [18, 19].

Grounded in the IFSMT and supported by evidence that nursing interventions can enhance lifestyle modification behavior among individuals with hypertension [20, 21], examining the relationship between life stress, hypertension knowledge, self-efficacy, family relationships, and lifestyle modification represents an important preliminary step toward the development of theory-informed nursing interventions. However, prior studies examining factors associated with lifestyle modification in hypertension have largely focused on general or older adult populations, with limited attention to working-age adults and limited application of nursing theoretical frameworks such as the IFSMT [22].

In China, the rapid increase in hypertension prevalence among working-age adults, coupled with suboptimal prevention and control, highlights the need for focused investigation of lifestyle modification behaviors in this group. In rapidly developing cities such as Wenzhou, working-age adults constitute the core workforce and often face dual responsibilities to family and society, resulting in lifestyle patterns that differ from those of older adults. Given their longer anticipated life expectancy, understanding lifestyle modification and its associated factors in this population is particularly important. From a nursing perspective, assessing lifestyle modification level and its associated factors among working-age adults with hypertension is essential to inform targeted assessment, education, and supportive interventions aimed at reducing future chronic disease burden.

The purposes of this study are as follows: (1) To describe the level of lifestyle modification among adults with hypertension; and (2) To examine the association between life stress, hypertension knowledge, self-efficacy, family relationship, and lifestyle modification in the study population.

This study used a descriptive cross-sectional design to examine the association between psychosocial and cognitive factors and lifestyle modification among adults with hypertension. The cross-sectional approach allowed for the assessment of relationships among variables at a single point in time. Therefore, temporal sequencing and causal inference were not assumed. The study was guided by the IFSMT, in which life stress was conceptualized as a contextual factor, while hypertension knowledge, self-efficacy, and family relationship were conceptualized as self-management process factors. Lifestyle modification was defined as the proximal outcome.

Participants were recruited from the cardiovascular outpatient department of the First Affiliated Hospital of Wenzhou Medical University (WMU), a tertiary teaching hospital in China. Eligible participants were adults aged 18–59 years who had been diagnosed with essential hypertension for at least six months [23], defined as systolic blood pressure (SBP) ≥140 mm Hg and/or diastolic blood pressure (DBP) ≥90 mm Hg, and current use of antihypertensive medication. Additional inclusion criteria included the ability to read and communicate in Chinese and the absence of severe cognitive impairment, paralysis, or advanced comorbid conditions such as end-stage renal disease.

Simple random sampling was applied among eligible clinic attendees during the data collection period. Each day, identification numbers of eligible patients were placed in an opaque container, and participants were randomly selected until the target sample size was achieved. Restricting recruitment to outpatient clinic attendees may have resulted in a sample more engaged with healthcare services, and this should be considered when interpreting the findings.

The required sample size was calculated using G*Power 3.1 for multiple linear regression analysis. Assuming a medium effect size (f² = 0.15), an alpha level of 0.05, and a statistical power of 0.90 [24], and four independent variables, a minimum of 108 participants was required.

Validated self-report instruments were used to collect data on demographic characteristics, lifestyle modification, life stress, hypertension knowledge, self-efficacy, and family relationships. All instruments were administered with authorization from the original developers or copyright holders. Participants were instructed to respond based on their recent behavior and experience.

Lifestyle modification was assessed using the Chinese version of the Hypertension Self-Care Profile Behavior Scale, which assesses adherence to recommended health behaviors related to hypertension management. This scale was developed by Han et al. [25] and translated into Chinese by Ma et al., with a reported Cronbach’s α of 0.86 [26]. It comprises 20 items rated on a 4-point scale (4 = Always, 1 = Rarely/Never); items 15 and 16 are reverse-coded. Potential total scores range from 20 to 80, with higher scores indicating better lifestyle modifications. For descriptive purposes, mean subscale scores were converted to a 1-4 grading scale to facilitate comparison across lifestyle domains.

Life stress was assessed using the Chinese version of the Perceived Stress Scale-10. The scale was developed by Cohen et al. [27] and translated into Chinese by Wang et al., with a reported Cronbach’s α of 0.91 [28]. The scale includes ten items, of which six are negatively stated items and scored from 4 to 0 (4 = Very Often, 0 = Never); the four positively stated items are reverse-coded. The potential total scores range from 0 to 40, with a higher score indicating higher life stress.

Hypertension knowledge was assessed using the Chinese version of the Hypertension Knowledge-Level Scale. The scale was developed by Erkoc et al. [29] and translated into Chinese by You et al., with a Cronbach’s α of 0.71 [30]. It comprises 22 items, scored 1 for each correct response and 0 for each incorrect or unknown response, yielding a potential total score ranging from 0 to 22. Scores are converted to a percentage of the total and categorized into three levels: good (≥ 80%), fair (60%-79%), and poor (< 60%) [31].

Self-efficacy was assessed using the Chinese-translated version of the Hypertension Self-Efficacy Scale, which was developed by Warren-Findlow et al., with a reported Cronbach’s α of 0.81 [32], following forward and backward translation procedures based on the Brislin method to ensure semantic equivalence [33]. The instrument includes five items rated from 1 to 10 based on confidence level. The mean score was calculated and categorized into two levels: good (9-10 points) and poor (< 9 points) [32].

Family relationship was assessed using the Chinese version of the Brief Family Relationship Scale. The scale was developed by Fok et al. [16] and translated into Chinese by Huang et al., with a reported Cronbach’s α of 0.85 [34]. It comprises 16 items rated on a 3-point scale ranging from 0 to 2 (0 = Not at all, 2 = A lot); the Conflict subscale is reverse-coded. Potential total score ranges from 0 to 32, with a higher score indicating a better family relationship.

All instruments demonstrated acceptable internal consistency and reliability in the current sample, with Cronbach’s alpha coefficients ranging from 0.81 to 0.89.

Data were collected between April and June 2024. After providing written informed consent, participants completed the questionnaires privately prior to their physician visit. Anonymity and confidentiality were ensured, and participants were informed of their right to withdraw at any time without adverse consequences. Questionnaires were reviewed for completeness at the time of collection, and only fully completed questionnaires were included in the analysis.

The study protocol was approved by the Institutional Review Board of Burapha University, Thailand (G-HS132/2566), and the First Affiliated Hospital of WMU, China (KY2023-247).

Data were analyzed using IBM SPSS. Descriptive statistics were used to summarize participant characteristics and study variables. Pearson’s correlation analysis was conducted to examine bivariate associations between independent variables and lifestyle modification. Standard multiple regression analysis was performed to examine the association of life stress, hypertension knowledge, self-efficacy, and family relationships with lifestyle modification. Assumptions of linear regression-including normality, linearity, homoscedasticity, independence of errors, and multicollinearity-were examined and met prior to model estimation. Statistical significance was set at p < 0.05.

A total of 108 adults with hypertension participated in the study. Participants ranged in age from 25 to 59 years (M = 47.2, SD = 9.1). The sample consists predominantly of middle-aged adults, with a smaller proportion of younger adults. Most participants were male, married, employed, and living with family members. Approximately three-quarters reported no comorbid condition, and the majority had been diagnosed with hypertension for less than five years. Although most participants reported measuring blood pressure (BP) at home, fewer than half had achieved controlled BP levels at the time of data collection (Table 1).

Lifestyle modification scores ranged from 28 to 70 (possible range: 20-80), with a mean score of 44.04 (SD = 8.91) out of a possible 80.00. Among lifestyle domains, lower engagement was observed in stress reduction, physical activity, and healthy dietary practices, whereas higher scores were observed for nonsmoking and limiting alcohol consumption.

The mean perceived life stress score indicates a moderate level of stress among participants. Hypertension knowledge score reflects a fair level of knowledge overall, while the self-efficacy score indicates relatively low confidence in managing hypertension-related behaviors. Family relationship score suggests generally positive family functioning (Table 2).

Pearson’s correlation analysis demonstrated that lifestyle modification was negatively associated with life stress and positively associated with hypertension knowledge, self-efficacy, and family relationships. Life stress was also negatively correlated with self-efficacy and family relationship, whereas self-efficacy showed a moderate positive association with family relationship (Table 3).

Standard multiple regression analysis was conducted to examine the association between the four independent variables and lifestyle modification. The overall model explained 43.1% of the variance in lifestyle modification scores (adjusted R² = 0.431).

Higher levels of perceived life stress were significantly associated with lower lifestyle modification scores. In contrast, greater hypertension knowledge and higher self-efficacy were significantly associated with better lifestyle modification. Family relationship was not significantly associated with lifestyle modification after controlling for other variables in the model (Table 4).