ABSTRACT
Treatment adherence is a cornerstone of effective hypertension management. However, the dynamic patterns of adherence and their influencing factors among young Chinese adults with hypertension remain insufficiently understood. This study aimed to explore the trajectories of medication adherence and healthy lifestyle behaviors, as well as the associated influencing factors, in this population. A mixed methods design was employed. First, a prospective cohort of 89 young hypertensive patients was established. Adherence was assessed using guideline‐recommended questionnaires from the 2018 Chinese Hypertension Guidelines at the 3rd and 6th months of follow‐up. Medication adherence was categorized as low, moderate, or high. The healthy lifestyle adherence score encompassed six dimensions: diet, salt intake, alcohol consumption, smoking status, physical activity, and weight control. Second, semi‐structured interviews based on the Health Belief Model were conducted to identify factors influencing adherence. Qualitative data were coded accordingly. During follow‐up, 28.07% of participants exhibited a decline in medication adherence, whereas 19.30% showed improvement. For healthy lifestyle adherence, 46.07% declined and 22.47% improved. Baseline characteristics did not differ significantly across different adherence trajectory groups (p > 0.05). A total of 27 and 36 individuals participated in interviews regarding medication and lifestyle adherence, yielding 553 and 878 codes, respectively. Social, environmental, and patient‐related factors accounted for 73% and 85% of these codes, respectively. The most frequently reported influencing factors included reminders and encouragement from family members, childcare responsibilities, occupational demands, social obligations, and awareness of hypertension. In conclusion, young adults with hypertension commonly experience fluctuations in both medication and lifestyle adherence. These variations are predominantly influenced by a combination of social, environmental, and individual‐level factors.
Trial Registration: Chinese Clinical Trial Registry (https://www.chictr.org.cn/): ChiCTR2000033434
Keywords: adherence, hypertension, impact factors, interview, mixed method, young adult
1. Introduction
Hypertension is the leading cause of cardiovascular disease and mortality, affecting approximately one‐third of the adult population [1]. In developing countries such as China, young adults (aged 18–39 years) account for approximately 15% of individuals with hypertension [2]. Between 1991 and 2015, the prevalence of hypertension among young adults in China increased by 144%, a rise that surpasses the 25%–87% increase observed in middle‐aged and older populations over the same period [3]. A Chinese cohort study further demonstrated that the risk of cardiovascular mortality among young adults with hypertension (adjusted hazard ratio [aHR]: 4.87–7.98) is higher than that observed in middle‐aged (aHR: 2.54–6.48) and elderly individuals (aHR: 2.23–4.60) [4]. Persistent blood pressure elevation beginning in early adulthood is believed to contribute significantly to this heightened risk. Therefore, improving hypertension control in young adults is of critical importance.
Evidence indicates that poor treatment adherence—including both antihypertensive medication use and adherence to lifestyle recommendations—is a major contributor to suboptimal blood pressure control rates [5, 6]. Notably, treatment nonadherence among young adults ranges from 36% to 86%, which is significantly higher than that observed in older populations [7, 8, 9]. Numerous studies have investigated the factors influencing nonadherence in older hypertensive patients, such as financial barriers to healthcare, reliance on religious practices to enhance medication efficacy, the cultural use of salt for food preservation, and negative perceptions of weight loss [8, 10, 11, 12]. However, limited research has focused on the facilitators and barriers to adherence among young adults with hypertension, particularly in Asian populations [13]. Moreover, the rapid socioeconomic and cultural transitions occurring in developing countries may introduce additional external factors that uniquely impact treatment adherence in young adults [14]. Therefore, it is essential to better understand the fluctuating patterns and underlying determinants of adherence behaviors in this population.
Mixed methods research, regarded as the “third paradigm,” integrates both quantitative and qualitative approaches to provide a comprehensive understanding of complex research problems [15]. Within this framework, an explanatory sequential design is commonly employed to explore quantitative findings through qualitative inquiry, making it particularly suitable for research investigating the factors influencing treatment adherence [16]. According to the World Health Organization (WHO), factors affecting treatment adherence span five major domains: the social environment, healthcare system, disease‐related factors, treatment‐related factors, and patient‐related factors [17]. The Health Belief Model (HBM) is a widely adopted theoretical framework for explaining adherence behaviors, encompassing six key dimensions: perceived susceptibility to disease, perceived severity of disease, perceived benefits of treatment, perceived barriers to treatment, cues to action, and self‐efficacy [18]. Accordingly, the present study aimed to (1) quantify the trajectories of treatment adherence among young adults with hypertension using a prospective cohort design; and (2) identify qualitative factors contributing to changes in adherence based on interviews guided by HBM, and categorize them within the five domains outlined by WHO.
2. Methods and Materials
2.1. Study Design and Population
This study employed a mixed methods research design with an explanatory sequential approach [19]. It was conducted between July 2020 and January 2022 at the Comprehensive Management Clinic for Young Hypertensive Patients, West China Hospital, Sichuan University, and was implemented in two distinct phases. The first phase consisted of a quantitative, prospective cohort study. Young adults diagnosed with hypertension received standardized treatment based on the 2018 Chinese Guidelines for the Management of Hypertension [20], including both antihypertensive medications and lifestyle modification recommendations. Treatment adherence was assessed at the 3rd and 6th months of follow‐up. The second phase involved a qualitative study using semi‐structured interviews to explore the factors influencing adherence among patients with different adherence trajectories identified in the cohort study. The study was conducted in accordance with the ethical principles of the Declaration of Helsinki and received approval from the Ethics Committee of West China Hospital, Sichuan University (approval number: 2020261). Informed consent was obtained from all participants prior to enrollment.
The inclusion criteria for this study were as follows: (1) diagnosis of hypertension; (2) age between 18 and 40 years; (3) enrollment in the Comprehensive Management Service Package for Young Hypertensive Patients at West China Hospital, Sichuan University; and (4) willingness to participate and provide informed consent. Hypertension was defined as either: (a) systolic blood pressure (SBP) ≥ 140 mmHg and/or diastolic blood pressure (DBP) ≥ 90 mmHg on three separate office visits (non–same‐day sitting measurements); or (b) a prior diagnosis of hypertension with current use of antihypertensive medication. Exclusion criteria included (1) secondary hypertension; (2) pregnancy or lactation; (3) physical or cognitive impairments that significantly limited the ability to participate and comply with study procedures; (4) loss to follow‐up; and (5) voluntary withdrawal from the study for any reason. Ultimately, 89 participants were included in the quantitative phase of the study. For the qualitative phase, 27 and 36 participants were selected for interviews addressing factors related to medication adherence and healthy lifestyle adherence, respectively (Figure 1).
FIGURE 1.
Research flowchart.
The sample size for the quantitative analysis was determined based on hypothesis testing using a binomial distribution. It was anticipated that approximately 35% of participants would exhibit a moderate level of treatment adherence during the follow‐up period. Assuming a null hypothesis proportion ranging from 16.7% to 25%, the minimum required sample size was calculated to be 59 participants. For the qualitative phase, the sample size was determined according to the principle of information saturation [19]. Information saturation is defined as the point at which no new information emerges from subsequent interviews. Specifically, beginning with the second interviewee, if no novel information is obtained, one additional interview is conducted. If the additional interview also yields no new insights, data collection is considered complete. The generally recommended sample size for qualitative interviews is between 20 and 30 participants [15]. Participants for the qualitative phase were selected using stratified purposive sampling from the pool of quantitative participants. This approach ensured that the sample size for the quantitative study was at least twice that of the qualitative study, in line with best practices for mixed methods research design.
2.2. Baseline Data Collection
In this study, baseline data were collected through electronic structured questionnaires and standardized physical examinations. The collected information included demographic characteristics (such as age, sex, marital status, ethnicity, and educational level), clinical conditions (including current use of antihypertensive medications, duration of hypertension, history of diabetes, and history of dyslipidemia), as well as physical examination indicators, such as systolic and diastolic blood pressure, heart rate, height, weight, waist circumference, and hip circumference. In addition, social support was assessed using the validated Social Support Rating Scale (SSRS) [21], which has been widely used in Chinese populations to evaluate the level of perceived support from family, friends, and the broader social network.
2.3. Follow‐Up for Treatment Adherence
Patient medication adherence was measured via a scale recommended by the 2018 guidelines [20]. This scale demonstrated good reliability and validity, with a Cronbach's α coefficient of 0.736 and a content validity index (CVI) of 0.970. Based on the total score, medication adherence was categorized into three levels: low (< 6 points), moderate (≥ 6 and < 8 points), and high (8 points) (Table S1).
Following the recommendations of the 2018 guidelines [20], lifestyle adherence in this study was evaluated based on six key components: maintaining a healthy diet, salt restriction, weight control (or weight loss), nonsmoking, limited alcohol consumption, and adequate physical activity. Each item is worth 1 point, with a total score ranging from 0 to 6. In the 2018 guidelines, a healthy diet simultaneously meets the energy intake requirements of less than 20 kcal/kg for obese and overweight individuals and a fruit and vegetable intake of more than 500 g/day. The standard for salt restriction is 6 g/day. The standard for limiting alcohol consumption is 14 g/day. The standard for weight control is a body mass index (BMI) of < 24 kg/m2. The ideal weight loss rate is 5% and 10% at the 3rd and 6th month follow‐ups, respectively. The standard for adequate exercise is at least 150–300 min of moderate‐intensity activity or at least 75–150 min of vigorous‐intensity activity per week. The measurement of physical activity is conducted through the International Physical Activity Questionnaire Short Form [22]. The measurement of a balanced diet, salt restriction, and alcohol consumption is based on the modified Chinese semi‐quantitative food frequency questionnaire according to the “Chinese Residents' Dietary Guidelines” (Table S2) [23].
2.4. Semi‐Structured Interviews
This study initially constructed an interview outline based on HBM to explore the factors influencing treatment adherence among young patients with hypertension [18]. One cardiology expert and two methodological experts were subsequently invited to discuss and revise the interview outline. Finally, two young patients with hypertension were invited for a preinterview to refine ambiguous statements, resulting in the final version of the interview outline, as detailed in Table S3. Onsite interviews were conducted in a comfortable environment, where a moderate amount of snacks was provided to create a relaxed atmosphere and encourage participants to express themselves openly. Researchers actively facilitated the interviews by guiding the conversation, moderating the atmosphere, and adjusting the sequence of questions based on participants’ responses. Progression to subsequent questions only occurred after each question had been addressed twice without eliciting new insights. Each interview session aimed to include three participants representing diverse treatment adherence trajectories and lasted approximately 1 h. Following each interview, the audio recordings were transcribed verbatim into Word documents and subsequently cross‐checked for accuracy.
2.5. Statistical Analysis
Participants were categorized into three groups based on their adherence trajectories to medication and healthy lifestyle practices: increased, unchanged, and decreased adherence groups. Nonparametric data, such as the duration of hypertension, are presented as medians with interquartile ranges (25th and 75th percentiles) and were analyzed using the Mann–Whitney U test. Parametric data, including age, BMI, waist circumference, systolic blood pressure, diastolic blood pressure, and heart rate, are expressed as mean ± standard deviations and compared using one‐way analysis of variance (ANOVA). Categorical variables are reported as counts and percentages and were analyzed using the chi‐square test or Fisher's exact test, as appropriate. For the qualitative analysis, data were analyzed within the framework of treatment adherence factors proposed by WHO, which includes social environment, healthcare system, disease characteristics, treatment factors, and patient‐related factors [17]. Following this theoretical framework, the interview content was systematically coded, refined, and synthesized to identify subthemes and overarching themes, culminating in the construction of a matrix encompassing themes, subthemes, and corresponding codes. During the initial coding phase, an open coding approach was employed, using a line‐by‐line method to ensure close alignment with the raw data and maximize coding accuracy. Subsequently, themes and subthemes were inductively derived from the data and then deductively mapped onto the WHO framework. The final results were interpreted through the lens of HBM to provide a comprehensive understanding of the factors influencing treatment adherence.
3. Results
3.1. Trajectories of Medication and Healthy Lifestyle Adherence
This study included 89 young patients with hypertension, with a median age of 36 years (interquartile range, 32–38), of whom 55 (61.80%) were male. Changes in adherence over time among patients undergoing initial treatment were visualized using a Sankey diagram, where the left side represents adherence status at the 3‐month follow‐up and the right side represents the status at the 6‐month follow‐up. At 3 months, 11 (17.74%), 32 (51.61%), and 19 (30.64%) patients were classified into low‐, moderate‐, and high‐adherence groups, respectively. By the 6‐month follow‐up, 57 patients remained consistently adherent to their antihypertensive medication regimen. In Figure 2, the Sankey diagram visualized the trajectories of medication and healthy lifestyle adherence among young adults with hypertension. Among the 62 participants who demonstrated medication adherence at the 3‐month follow‐up, 16 (28.07%) exhibited a decline in adherence over time, whereas 11 (19.30%) showed an improvement. Similarly, lifestyle adherence scores decreased in 41 patients (46.07%) and increased in 20 patients (22.47%) during the same period.
FIGURE 2.
Trajectories of medication and healthy lifestyle adherence in young adult with hypertension. The Sankey diagram visualizes the changes in adherence among hypertensive patients undergoing initial treatment, 3‐month follow‐ups, and 6‐month follow‐ups, with the left side representing the earlier time point and the right side representing the later time point. The width of the lines corresponds to the number of patients transitioning between different adherence levels. (A) The entire population was divided into four groups: low, moderate, and high medication adherence groups and the non‐pharmacological treatment group. (B) The entire population was divided into seven groups on the basis of health lifestyle scores ranging from 0 to 6.
3.2. Baseline Characteristics of Participants With Different Trajectories of Adherence
As shown in Table 1, there were no statistically significant differences in age (p = 0.765), sex (p = 0.832), ethnicity (p = 0.513), education level (p = 0.979), comorbidities (p = 0.406), blood pressure (p = 0.844), heart rate (p = 0.117), BMI (p = 0.402), or level of social support (p = 0.837) among the three groups. However, the decreased medication adherence group had a significantly shorter hypertension course than the unchanged and increased medication adherence groups (p < 0.012). With respect to healthy lifestyle adherence, the three groups did not significantly differ in terms of baseline characteristics (Table 2).
TABLE 1.
Baseline characteristics of young adults with hypertension according to different trajectories of medication adherence.
| Characteristic | Decreased group | Unchanged group | Increased group | Not involved | p |
|---|---|---|---|---|---|
| (n = 16) | (n = 30) | (n = 11) | (n = 32) | ||
| Demographic variables | |||||
| Age, years | 34.56 ± 3.92 | 34.83 ± 4.13 | 35.55 ± 3.24 | 34.00 ± 5.28 | 0.765 |
| Male sex, n (%) | 9 (56.25) | 19 (63.33) | 8 (72.73) | 19 (59.38) | 0.832 |
| The Han nationality, n (%) | 15 (93.75) | 30 (100.00) | 10 (90.91) | 30 (93.75) | 0.513 |
| Solo living, n (%) | 1 (6.25) | 6 (20.00) | 0 (0.00) | 4 (12.50) | 0.293 |
| Education, n (%) | 0.979 | ||||
| ≤ 9 years | 1 (6.25) | 3 (10.00) | 1 (9.09) | 3 (9.38) | |
| >9 years | 15 (93.75) | 27 (90.00) | 10 (90.91) | 29 (90.62) | |
| Social support, n (%) | 0.837 | ||||
| Moderate level | 12 (75.00) | 23 (76.67) | 9 (81.82) | 27 (84.38) | |
| High level | 4 (25.00) | 7 (23.33) | 2 (18.18) | 5 (15.62) | |
| Chronic medical conditions | |||||
| Hypertension course, months | 8.5 (4–19.5) | 21 (12–33) | 20 (10–89) | 12.5 (7.5–22.75) | 0.012 |
| Diabetes mellitus, n (%) | 1 (6.25) | 2 (6.67) | 0 (0.00) | 0 (0.00) | 0.406 |
| Dyslipidemia, n (%) | 1 (6.25) | 3 (10.00) | 1 (9.09) | 6 (18.75) | 0.568 |
| Physiological and lab variables | |||||
| Body mass index, kg/m2 | 25.41 ± 3.85 | 25.17 ± 3.40 | 26.36 ± 4.35 | 25.23 ± 3.58 | 0.402 |
| Waist circumference, cm | 87.69 ± 11.46 | 86.35 ± 11.18 | 90.45 ± 15.90 | 84.88 ± 11.54 | 0.116 |
| Heart rate, n/min | 89.50 ± 15.03 | 82.07 ± 11.34 | 80.55 ± 13.71 | 88.03 ± 14.11 | 0.117 |
| Systolic blood pressure, mmHg | 147.62 ± 20.63 | 145.73 ± 22.53 | 147.41 ± 16.00 | 143.22 ± 12.87 | 0.844 |
| Diastolic blood pressure, mmHg | 96.16 ± 13.80 | 97.20 ± 14.69 | 95.32 ± 9.52 | 96.31 ± 12.62 | 0.979 |
TABLE 2.
Baseline characteristics of young adults with hypertension according to different trajectories of healthy lifestyle adherence.
| Characteristic | Decreased group | Unchanged group | Increased group | p |
|---|---|---|---|---|
| (n = 40) | (n = 28) | (n = 21) | ||
| Demographic variables | ||||
| Age, years | 34.45 ± 4.236 | 34.68 ± 5.15 | 34.67 ± 3.864 | 0.943 |
| Male sex, n (%) | 21 (52.50) | 21 (75.00) | 13 (61.90) | 0.171 |
| The Han nationality, n (%) | 39 (97.50) | 27 (96.43) | 19 (90.48) | 0.435 |
| Solo living, n (%) | 5 (12.50) | 4 (14.29) | 2 (9.52) | 0.881 |
| Education, n (%) | 0.466 | |||
| ≤ 9 years | 3 (7.50) | 4 (14.29) | 1 (4.76) | |
| >9 years | 37 (92.50) | 24 (85.71) | 20 (95.24) | |
| Social support, n (%) | 0.652 | |||
| Moderate level | 32 (80.00) | 21 (75.00) | 18 (85.71) | |
| High level | 8 (20.00) | 7 (25.00) | 3 (14.29) | |
| Chronic medical conditions | ||||
| Hypertension course, months | 11.5 (7.0–28.75) | 14 (9.25–28.5) | 19 (11–30) | 0.622 |
| Diabetes mellitus, n (%) | 0 (0.00) | 2 (7.14) | 1 (4.76) | 0.254 |
| Dyslipidemia, n (%) | 5 (12.50) | 4 (14.29) | 2 (9.52) | 0.881 |
| Physiological and lab variables | ||||
| Body mass index, kg/m2 | 25.17 ± 3.97 | 24.77 ± 3.48 | 26.60 ± 4.34 | 0.252 |
| Waist circumference, cm | 87.35 ± 13.38 | 85.54 ± 10.17 | 90.643 ± 13.68 | 0.370 |
| Heart rate, n/min | 84.98 ± 11.28 | 82.04 ± 14.94 | 90.52 ± 14.81 | 0.092 |
| Systolic blood pressure, mmHg | 147.04 ± 16.43 | 141.04 ± 15.65 | 148.00 ± 23.20 | 0.309 |
| Diastolic blood pressure, mmHg | 98.46 ± 11.02 | 92.80 ± 13.21 | 97.60 ± 15.79 | 0.197 |
3.3. Participant Recruitment for Interviews
To investigate factors influencing changes in medication adherence, purposeful stratified sampling was performed based on age, sex, disease duration, and adherence trajectory categories. Semi‐structured interviews were conducted with 27 and 36 young hypertensive patients regarding medication adherence and healthy lifestyle adherence, respectively. The baseline characteristics of these participants are summarized in Tables S4 and S5.
3.4. Coding of Adherence‐Influencing Factors
Open coding for medication and healthy lifestyle adherence accounted for 553 and 878 codes, respectively (Figure 3). For medication adherence, social environmental factors, healthcare factors, disease‐related factors, treatment factors, and patient‐related factors accounted for 69 (12.48%), 23 (4.16%), 12 (2.17%), 57 (10.31%), and 392 (70.89%) codes, respectively (Table 3). For healthy lifestyle adherence, the five subthemes accounted for 275 (31.32%), 8 (0.09%), 11 (1.25%), 112 (12.76%), and 472 (53.76%) codes, respectively (Table 4). The detailed quotes and thematic summaries of the interviewees are summarized in Tables S6 and S7.
FIGURE 3.
Theme‐coded distribution of factors associated with different trajectories of treatment adherence. (A) Impact factors of medication adherence. (B) Impact factors of healthy lifestyle adherence.
TABLE 3.
Impact factors influencing medication adherence in young adults with hypertension: themes, subthemes, and coding matrix.
| Themes | Subthemes | Coding matrix |
|---|---|---|
| Social and environmental factors | Family support | (+) Family encouragement (n = 10), (+) Family reminders (n = 11), (−) Family opposition (n = 3), (−) Childcare (n = 4) a |
| Social support | (+) Reasonable drug prices (n = 1), (−) Busy work (n = 12), (−) Many social engagements (n = 4), (−) COVID‐19 pandemic (n = 2), (−) Commuting restrictions (n = 1) | |
| Tool support | (+) Portable pillbox (n = 4) a , (+) Alarm reminder (n = 2), (+) Mobile phone medication tracking (n = 1) | |
| Healthcare factors | Doctor factors | (+) The importance of medication as informed by doctors (n = 10), (+) The authority of doctors (n = 1), (+) Proactive follow‐up by community doctors (n = 1), (−) Poor diagnostic and treatment skills of doctors (n = 1) |
| Medical system factors | (+) Convenient medication purchase (n = 3), (−) Inconvenient medication purchase (n = 1), (−) Difficult registration (n = 1) | |
| Disease factors | Symptoms of hypertension | (+) Experiencing symptoms of dizziness and headache (n = 9), (+) Experiencing symptoms of palpitations and chest pain (n = 2) a |
| Treatment factors | Blood pressure lowering effect | (+) Effective in lowering blood pressure (n = 16), (−) Drug resistance (n = 6) |
| Treatment side effects | (−) The drug has side effects (n = 8) | |
| Treatment complexity | (−) High complexity of medication regimen (n = 1) | |
| Patient factors | Perceived susceptibility to hypertension | (+) Irregular sleep–wake habits (n = 12), (+) High psychological stress (n = 14), (+) Lack of exercise (n = 8), (+) High‐salt and high‐fat diet (n = 16), (+) Alcohol consumption (n = 4), (+) Smoking (n = 3), (+) Genetic predisposition (n = 22), (+) Male gender (n = 1), (+) Overweight (n = 18), (+) Advanced age (n = 3) |
| Perceived severity of hypertension | (+) Hypertension is likely to lead to vision loss (n = 2) a , (+) Hypertension is likely to lead to atherosclerosis (n = 7), (+) Hypertension is likely to lead to stroke (n = 27), (+) Hypertension is likely to lead to kidney damage (n = 7), (+) Hypertension is likely to lead to heart disease (n = 27) | |
| Hypertension knowledge | (+) Possessing knowledge (n = 6) a , (−) Lack of knowledge (n = 11) a | |
| Treatment attitude | (+) Good blood pressure control is needed for family planning (n = 1), (+) Medication is the only choice (n = 5) a | |
| Healing skills | (+) Fixed medication times (n = 20) a , (+) Medication placed in conspicuous places (n = 21) | |
| Forgetful | (−) Forgot to bring medication (n = 6) a , (−) Forgot to take medication (n = 4) | |
| Psychological stress | (−) Emphasizing illness privacy (n = 2), (−) Unable to accept drug treatment (n = 2) |
Note: (+) indicates factors that promote medication adherence; (−) indicates factors that hinder medication adherence; n represents the number of patients with such influencing factors.
indicates that there are differences in impact factors among various groups (p < 0.05) according to the χ 2 test or Fisher's exact test.
TABLE 4.
Impact factors of lifestyle adherence in young adults with hypertension: themes, subthemes, and coding matrix.
| Themes | Subthemes | Coding matrix |
|---|---|---|
| Social and environmental factors | Family support | (+) Family encouragement (n = 25), (+) Family reminders (n = 12), (+) Friends' reminders (n = 8), (−) Childcare (n = 7), (−) Family preference for salty and greasy food (n = 8), (−) Family's lack of exercise (n = 5), (−) Heavy household chores (n = 1) |
| Social support | (+) Easy access to healthy food (n = 5), (+) Access to sports facilities everywhere (n = 5), (+) Popular science knowledge (n = 3), (+) Fitness coach reminders (n = 2), (−) Frequent socializing (n = 18), (−) Takeout (n = 7), (−) Regional high‐salt and high‐fat diet (n = 6), (−) COVID‐19 pandemic (n = 4), (−) Time‐consuming to cook healthy food (n = 2), (−) Inaccessibility to sports facilities (n = 3), (−) Unpalatable healthy food (n = 1), (−) High cost of healthy food (n = 1) a , (−) Fitness coach aggressively selling classes (n = 1) | |
| Tool support | (+) Sports apps (n = 4), (+) Sports watches (n = 3), (+) Weighing with a scale (n = 1) a , (+) Checking body shape in the mirror (n = 1) a , (+) Home blood pressure monitoring (n = 1), (+) Alarm reminders (n = 1) | |
| Support from affiliated units | (+) Regular health check‐ups arranged by the workplace (n = 1) a , (−) Busy work (n = 24), (−) Workplace canteen provides salty and greasy food (n = 2), (−) Subordinates find it difficult to propose healthy eating suggestions to leadership (n = 1) | |
| Natural environmental support | (+) Mild weather (n = 1) a , (−) Extremely hot or cold weather (n = 6) | |
| Healthcare factors | Patient education | (+) Doctors inform about the importance of a healthy lifestyle (n = 7), (−) Doctors do not clearly inform about a healthy diet plan (n = 1) a |
| Disease factors | Comorbidity | (+) Comorbid with other chronic diseases (n = 2) a |
| Sports injury | (−) Exercise causing physical discomfort (n = 5) | |
| Treatment factors | Weight loss | (+) Exercise aids in weight loss (n = 14), (+) Healthy diet aids in weight loss (n = 7) |
| Antihypertensive effect | (+) Blood pressure reduction is effective (n = 28), (−) Blood pressure reduction is not effective enough (n = 5) | |
| Beneficial to both mind and body | (+) Exercise is beneficial to physical and mental health (n = 14) | |
| Patient factors | Perception of hypertension susceptibility | (+) Irregular sleep–wake habits (n = 14), (+) High psychological stress (n = 19), (+) Lack of exercise (n = 9), (+) High‐salt and high‐fat diet (n = 22), (+) Alcohol consumption (n = 5), (+) Smoking (n = 3), (+) Genetic predisposition (n = 31), (+) Male gender (n = 1), (+) Overweight (n = 23), (+) Advanced age (n = 4) |
| Perceived seriousness of hypertension | (+) Hypertension can lead to sudden death (n = 5), (+) Hypertension can lead to vision loss (n = 2), (+) Hypertension can lead to atherosclerosis (n = 10), (+) Hypertension can lead to stroke (n = 36), (+) Hypertension can lead to kidney damage (n = 10), (+) Hypertension can lead to heart disease (n = 36) | |
| Hypertension knowledge | (+) Increased knowledge about hypertension (n = 13) a , (−) Lack of knowledge about hypertension (n = 2) a | |
| Treatment attitude | (+) Good blood pressure control is needed for family planning (n = 1) a , (−) Preference for salty and greasy food (n = 12), (−) Pursuit of a meaningful life (n = 1) a | |
| Treatment cognition | (+) Self‐reflection (n = 11) | |
| Treatment motivation | (−) Laziness (n = 18) | |
| Therapeutic skills | (+) Develop a habit of exercise (n = 3) a , (+) Set a fixed time for exercise (n = 5), (+) Take the initiative to make an exercise plan (n = 2), (+) Place healthy food in conspicuous places (n = 1) | |
| Psychological stress | (−) Binge eating to relieve stress (n = 5) a , (−) Lack of motivation to exercise due to stress (n = 3), (−) Valuing illness privacy (n = 1) |
Note: (+) indicates factors that promote lifestyle adherence; (−) indicates factors that hinder lifestyle adherence; n represents the number of patients with such influencing factors.
indicates that there are differences in impact factors among various groups (p < 0.05) according to the χ 2 test or Fisher's exact test.
3.5. Analysis of Factors Influencing Medication Adherence
Social and environmental factors: Family support impacts medication adherence. “My family fully supports my medication regimen; they are especially encouraging (P6).” “My wife asks every day: ‘Have you taken your medicine?’ (P9).” Four patients reported that taking care of their children and disapproving of their family hinder their medication adherence. “I have to get up early at 6:00 am to take kids to school; thus, I forget to take medicine (P8).” “My family, relatives, and friends tell me that I should not take Western medicine but traditional Chinese medicine instead (P4).” Social support is a key factor influencing medication adherence. “If a pill costs one or two hundred yuan, it might be unbearable. Now that the drug prices are quite low and affordable, I will definitely take them (P14).” “For our generation, especially those in business and sales, it is hard to avoid social events, such as late‐night drinking (P20).” Tool support is also important for medication adherence. “I set an alarm by 10 am daily, I naturally remember to take my medication (P10).” “I take three types of blood pressure meds, usually recorded on my phone to remind myself (P3).”
Healthcare factors: Physicians and healthcare systems are key subthemes. “The doctor stressed the importance of taking medication consistently, which I took to heart and followed diligently (P26).” “I have a special clinic appointment where community doctors remind me to visit monthly (P17).” “Many doctors are uncertain about blood pressure medication plans, which makes me doubt taking them. Therefore, the authority of the doctor is crucial; I definitely listen to expert advice (P14).” Another patient said, “Visiting West China Hospital is troublesome, so I buy the exact antihypertensives prescribed by the doctors online. It is very convenient (P26).” “While on a business trip in Singapore, the drugs I bring differ from local ones, so I do not know what medicine to take (P9).”
Disease factors: The key impact factor of medication adherence is hypertension symptoms: “I started taking medication due to frequent headaches; after taking it, the headaches decreased (P26).” “Before taking medication, I occasionally had heart pain and hard to breathe. I'm not sure if it was angina, but these symptoms stopped after I started my medication (P21).”
Treatment factors: Blood pressure control effectiveness is a factor influencing medication adherence. “I stopped taking medication for a week and found that my blood pressure was high, which returned to normal after I resumed taking the medication (P27)”. “I have changed many types of blood pressure medication. I'm worried that I may have developed a dependency on the medication, which is making it difficult to manage my blood pressure effectively. Occasionally, I have the idea of giving up (P6)”. Treatment complexity and side effects inhibit medication adherence. “I take two pills in the morning and one at night. My morning routine is more consistent, but not always the case at night. Sometimes I get back late, around midnight, and it is easy to forget (P14).” “As the old Chinese saying goes: ‘All medicines have 30% side effects,’ so antihypertensive drugs are not good for my health (P22 ).”
Patient factors: The perceived susceptibility of interviewees includes perceived irregular routines, high stress, a lack of exercise, a high‐salt and high‐fat diet, alcohol consumption, smoking, genetics, being male, being overweight, and advanced age, which predisposes them to hypertension. The majority of patients are aware of these risk factors. The perceived severity of disease included heart disease, stroke, atherosclerosis, kidney damage, and vision loss. Knowledge about hypertension affects adherence to medication. “I have been hearing a lot about the importance of managing high blood pressure from people around me, so I'm definitely committed to treating it (P22).” Treatment attitudes influence medication adherence. “Until I find a better method to lower my blood pressure, I will not give up my current medication regimen because there's no alternative (P26).” Medication adherence skills include setting a regular medication time and placing drugs in a visible spot. “I have made taking medication a morning routine, and it is become a conditioned reflex (P26).” Forgetfulness affects medication adherence in young hypertensive patients. “I forgot my medication, which felt truly risky; not taking it makes me feel terrible (P21).” Psychological stress from illness stigma and medication are barriers to adherence. “I do not want my family to know about my hypertension; I cannot leave medication at home or carry it with me (P12).”
3.6. Analysis of Factors Influencing Healthy Lifestyle Adherence
Like in medicine adherence, family, social, and instrumental support are influencing factors of healthy lifestyle adherence. In addition, the workplace and natural environmental support also seem to be crucial factors. “Our company will have a medical check‐up in the second half of the year. It is a way to encourage me to improve my unhealthy lifestyle (P36).” “I recently changed jobs, and the workload is much heavier now. I used to have time to exercise after work, but now I truly do not have any (P12).” “Our diet is not very healthy. We eat mainly in the cafeteria, and the food there is often high in oil and salt (P26 ).”
Healthcare factors: Patient education is considered a factor influencing lifestyle improvement. “The doctor told me that controlling my diet and exercising more are very important, and I will gradually do better (P19).” “The doctor only suggested a healthy diet but did not specify how to do it, so I did not pay much attention (P3).”
Disease factors: Comorbidities and sports injuries are considered factors influencing a healthy lifestyle. “Because I have not only hypertension but also diabetes, I do not focus on carbohydrates in my diet, and I have better control over my eating (P21).” “Because I had a knee problem after intense exercise before, which sometimes hurts on cloudy days, I may not exercise or exercise less (P14).”
Weight loss, blood pressure reduction, and mood improvement are considered factors that promote a healthy lifestyle. “When I was under review in the detention center, I exercised daily and ate a light diet. My weight dropped to approximately 50 kilograms. I no longer snored while sleeping, my blood pressure normalized, and all my indicators returned to normal (P32).” “I used to exercise less, but now I work out four times a week. I feel my blood pressure is well controlled (P29).” “Exercise brings me a unique kind of joy. I felt more relaxed and eager to experience this happiness (P35 ).”
Patient factors: Consistent with medicine adherence, perceived susceptibility, perceived severity, knowledge about hypertension, treatment attitude, skills, and psychological stress are considered key factors of healthy lifestyle adherence. Moreover, treatment awareness and motivation are also very important. “Every night before going to bed, I reflect on my health issues. I constantly remind myself which foods I should eat less of and which foods I should avoid (P32).” “My job is very flexible, and I have plenty of free time, but I'm just lazy and don't feel like doing anything (P14).”
4. Discussion
This study pioneers a mixed methods research approach using an explanatory sequential design to explore the dynamic factors influencing the trajectories of medication and healthy lifestyle adherence among young patients with hypertension. The concept of joint intervention for medication and behavior should be emphasized, and interviews should be conducted with patients who have experienced different trajectories of treatment adherence, with the aim of comprehensively identifying factors affecting treatment adherence in young hypertensive patients. Initially, quantitative prospective cohort research revealed that within a short time frame, the proportions of young hypertensive patients who changed their medication and lifestyle adherence reached as high as 47% and 69%, respectively. Among the different trajectory groups, a shorter hypertension course was correlated with decreased adherence. The potential reasons may involve insufficient disease awareness, denial and resistance psychology, lack of confidence in treatment, lack of social support, and unestablished behavioral habits according to previous research [24]. This finding suggests that the process through which hypertension patients' disease cognition and behavior change is long‐term. Clinicians need to enhance patient education and management in the early stages and continuously reinforce health awareness during follow‐up.
Other traditional factors did not significantly influence changes in treatment adherence among young hypertensive patients, highlighting the need to explore novel and previously unrecognized determinants. Accordingly, this study further investigated facilitators and barriers to changes in treatment adherence through qualitative interviews. The findings reveal that factors influencing medication adherence among young hypertensive patients span a wide range of dimensions, including social, familial, instrumental, therapeutic, disease‐related, psychological, cognitive, knowledge‐based, attitudinal, and personality aspects. These multifaceted influences can be broadly grouped into patient‐related factors and social environmental factors. Because these two overarching themes are closely linked to societal—including social, familial, occupational, and patient‐driven—attention to, accurate understanding of, accessibility to, and convenience of hypertension medication and lifestyle interventions, the study underscores the importance of future public health policies aimed at enhancing hypertension health education through social media platforms and professional health personnel.
The results of this study indicate that only 30.64% of young hypertensive patients in China have high medication adherence, which is significantly lower than that of the elderly population [7, 8, 9]. This finding is consistent with reports from the United States and South Korea [25, 26], and the potential reasons include a lack of symptoms, perceived side effects of medications, and poor understanding of the long‐term risks of uncontrolled hypertension, high costs of medications, lack of access to healthcare services, and competing life priorities. Additionally, a cohort study has shown that approximately 41% of hypertensive patients experience changes in their medication adherence [27]. Thus, it is important to address the factors influencing adherence in the younger population. We identified several patient factors that differ significantly from the perspectives of people in other countries, which are both intriguing and noteworthy. For example, in the same category of developing countries, hypertensive patients in rural Nigerian communities view Western drug therapy as a factor that enhances their adherence to treatment [10, 28]. However, in China, the entrenched cultural schema of traditional Chinese medicine (TCM) fundamentally shapes health epistemology. Rooted in Daoist philosophy, TCM emphasizes holistic balance (yin‐yang harmony) and gradual body regulation through herbal formulations, cultivating a therapeutic paradigm that strongly contrasts with the biochemical intervention approach of Western medicine. This philosophical divergence manifests in popular health narratives, where TCM is mythologized as “natural” and “harmonious”, whereas Western drugs are perceived as “invasive chemicals” that disrupt body equilibrium. Consequently, many populations influenced by this millennium‐old tradition mistakenly believe that TCM is free of side effects and can cure diseases. In accordance with TCM treatment logic, herbal regimens are typically prescribed for finite periods to restore balance, unlike chronic disease management, which requires perpetual medication [29]. Given the social stigma of chronic illness in collectivist cultures, young Chinese individuals view Western drug therapy as a barrier to adherence. Moreover, in a qualitative investigation examining patients' perspectives on hypertension at Lagos Hospital, individuals placed their trust in medical professionals, who were convinced that the doctors were best equipped to determine the optimal course of treatment for their conditions [30]. However, our study revealed that residents place their trust in physicians at large, comprehensive hospitals while questioning the professionalism of remote hospitals. This has a significant effect on the adherence of patients living in rural or relatively underdeveloped areas.
With respect to social and environmental factors, other studies conducted in Nigeria revealed that the accessibility of healthcare services, such as travel costs, clinic operating hours, waiting times, and difficulty in obtaining prescribed medications, may hinder medication adherence [10, 31]. This conclusion is similar to that of our study, and we found that online medication purchasing also plays a positive role in medication adherence. As in previous studies, medication adherence is positively correlated with family support [32]. However, middle‐aged and older individuals primarily receive support from their spouses and children, whereas young people mainly rely on support from their spouses and parents. Additionally, children often represent a burden for the younger population [33].
Consistent with previous studies, most patients recognized that maintaining a healthy lifestyle is beneficial for blood pressure control. However, this awareness alone was insufficient to sustain long‐term adherence, as treatment adherence is affected by a multitude of factors.
Our research indicates that social, environmental, and patient factors account for as much as 85% of the influence on the adherence to a healthy lifestyle among young hypertensive patients. Similar to previous studies [34], these factors involve complex interactions that influence patient adherence. In this study, family involvement was found to significantly influence patients’ confidence in achieving blood pressure control targets. Family reminders played a vital role in helping patients establish and maintain consistent medication routines, whereas opposition from family members toward Western medicine increased the psychological burden associated with medication adherence. These findings suggest that positive family support enhances patients’ self‐efficacy, whereas a lack thereof has detrimental effects. Additionally, cultural factors such as China's prevalent drinking culture contribute to young adults engaging frequently in social activities involving excessive alcohol consumption, unhealthy diets, smoking, and late‐night behaviors, which impede the adoption of healthy lifestyles. Furthermore, the age group of 20–40 years, often described as “emerging adulthood” in social psychology, faces unique challenges including limited time for meal preparation and exercise, as well as financial constraints that restrict access to high‐quality food and physical activity opportunities [33, 35].
Based on the key issues identified in this study, several recommendations are proposed. First, hypertension management should integrate Western medical approaches with TCM principles through targeted communication strategies, utilizing digital platforms to enhance reach and engagement. Training community health workers as “cultural brokers” can facilitate household‐level dialogues that address misconceptions regarding lifelong medication adherence by aligning biomedical concepts with traditional health beliefs. Second, family‐centered interventions should be developed, involving spouses, parents, and children, such as the implementation of smart medication dispensers that synchronize reminders with relatives’ devices and the establishment of intergenerational health contracts supported by incentive mechanisms. Third, workplace‐certified “hypertension‐friendly” social venues should be promoted, offering healthy banquet menus alongside blood pressure monitoring facilities to encourage healthier lifestyle choices within social and occupational settings.
This study has several notable strengths. First, it is the first to comprehensively analyze the factors influencing both medication and healthy lifestyle adherence, specifically among young patients with hypertension. Second, the explanatory mixed methods design employs stratified sampling from a prospective cohort to select participants with diverse adherence trajectories, enabling a dynamic investigation of influencing factors through qualitative research. Third, the interview framework is grounded in HBM, and the data categorization aligns with the WHO's standards, thereby ensuring the rigor and quality of the evidence provided. However, several limitations should be acknowledged. As a single‐center study, selection bias may exist due to patient recruitment from one hospital. Regional dietary preferences in Southwest China, characterized by a preference for spicy, numbing, salty, and oily foods as well as a vibrant night snack culture, may differ substantially from other regions, potentially impacting salt intake, weight management, and thus limiting the generalizability of the findings. Additionally, this study based its lifestyle adherence criteria on the Chinese hypertension guidelines, including six key factors. These differ from the American Heart Association's Life's Essential 8, which incorporates detailed metrics for both healthy behaviors (diet, exercise, sleep, smoking, weight control) and health factors (cholesterol, blood glucose, blood pressure control). Notably, Life's Essential 8 does not emphasize salt and alcohol intake, which are highlighted in the Chinese guidelines. Consequently, each healthy lifestyle item in this study was classified in a binary manner (yes/no) referencing prior research, without weighing the relative importance of each factor. Although this approach enhances the localization and relevance of the study, it may reduce its universal applicability and precision.
5. Conclusion
During the treatment period, young patients with hypertension frequently experience fluctuations in their adherence to medication and healthy lifestyle practices. These changes are primarily driven by social environmental factors and patient‐related factors. Among social environmental influences, key common factors affecting both medication and lifestyle adherence include reminders and encouragement from family members, responsibilities related to child care, work‐related busyness, and social obligations. Regarding patient factors, knowledge about hypertension emerges as a crucial shared determinant. Considering the distinctive perspectives and challenges faced by young hypertensive individuals, it is imperative that multiple stakeholders—including society, government, and healthcare institutions—collaborate to develop comprehensive strategies aimed at improving hypertension management in this population.
Ethics Statement
Ethics approval for this study was obtained from the Human Ethical Committee of the West China Hospital of Sichuan University (2020261). The experimental protocols were established according to the ethical guidelines of the Helsinki Declaration. Written informed consent was obtained from the participants.
Conflicts of Interest
The authors declare no conflicts of interests.
Supporting information
Supporting Table 1: Medication adherence scale.
Supporting Table 2: Consumption amount and frequency of the following foods over the past month.
Supporting Table 3: Interview outline of factors affecting treatment adherence in young adults with hypertension
Supporting Table 4: Characteristics of young hypertensive patients according to varying medication adherence.
Supporting Table 5: Characteristics of young hypertensive patients according to varying healthy lifestyle adherence.
Supporting Table 6: Impact factors influencing medication adherence in young adults with hypertension: themes, subthemes, and coding matrix
Supporting Table 7: Impact factors of lifestyle adherence in young adults with hypertension: themes, subthemes, and coding matrix.
Funding: This work was supported financially by grants from Noncommunicable Chronic Diseases‐National Science and Technology Major Project (No. 2023ZD0506101, 2023ZD0506100), Sichuan Science and Technology Program (No. 2024NSFSC0661, 2024NSFSC1534, 24ZDYF0065), Sichuan Provincial Health Commission (No. 2023‐103, 2024‐102), 135 Project for Disciplines of Excellence‐Clinical Research Incubation Project (No. 2023HXFH002) and Postdoctor Research Fund of West China Hospital, Sichuan University (No. 2024HXBH067), and CDHT Health Bureau (No. 2024004, 2024005).
Contributor Information
Rong Yang, Email: yangrong1567@gmail.com.
Can Shen, Email: shencan@wchscu.cn.
Xiaoyang Liao, Email: liaoxiaoyang@wchscu.cn.
Data Availability Statement
The data will be made available upon request.
References
- 1. Mills K. T., Bundy J. D., Kelly T. N., et al., “Global Disparities of Hypertension Prevalence and Control: A Systematic Analysis of Population‐Based Studies From 90 Countries,” Circulation 134, no. 6 (2016): 441–450, 10.1161/circulationaha.115.018912. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2. Wang C., Yuan Y., Zheng M., et al., “Association of Age of Onset of Hypertension With Cardiovascular Diseases and Mortality,” Journal of the American College of Cardiology 75, no. 23 (2020): 2921–2930, 10.1016/j.jacc.2020.04.038. [DOI] [PubMed] [Google Scholar]
- 3. Ma S., Yang L., Zhao M., Magnussen C. G., and Xi B., “Trends in Hypertension Prevalence, Awareness, Treatment and Control Rates Among Chinese Adults, 1991–2015,” Journal of Hypertension 39, no. 4 (2021): 740–748, 10.1097/hjh.0000000000002698. [DOI] [PubMed] [Google Scholar]
- 4. Qi Y., Han X., Zhao D., et al., “Long‐Term Cardiovascular Risk Associated With Stage 1 Hypertension Defined by the 2017 ACC/AHA Hypertension Guideline,” Journal of the American College of Cardiology 72, no. 11 (2018): 1201–1210, 10.1016/j.jacc.2018.06.056. [DOI] [PubMed] [Google Scholar]
- 5. Chowdhury R., Khan H., Heydon E., et al., “Adherence to Cardiovascular Therapy: A Meta‐Analysis of Prevalence and Clinical Consequences,” European Heart Journal 34, no. 38 (2013): 2940–2948, 10.1093/eurheartj/eht295. [DOI] [PubMed] [Google Scholar]
- 6. Carey R. M., Muntner P., Bosworth H. B., and Whelton P. K., “Prevention and Control of Hypertension: JACC Health Promotion Series,” Journal of the American College of Cardiology 72, no. 11 (2018): 1278–1293, 10.1016/j.jacc.2018.07.008. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. Adidja N. M., Agbor V. N., Aminde J. A., Ngwasiri C. A., Ngu K. B., and Aminde L. N., “Non‐Adherence to Antihypertensive Pharmacotherapy in Buea, Cameroon: A Cross‐sectional Community‐Based Study,” BMC Cardiovascular Disorders 18, no. 1 (2018): 150, 10.1186/s12872-018-0888-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8. Li Y., Jasani F., Su D., et al., “Decoding Nonadherence to Hypertensive Medication in New York City: A Population Segmentation Approach,” Journal of Primary Care and Community Health 10 (2019): 2150132719829311, 10.1177/2150132719829311. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9. Sung S. F., Lai E. C., Wu D. P., and Hsieh C. Y., “Previously Undiagnosed Risk Factors and Medication Nonadherence Are Prevalent in Young Adults With First‐Ever Stroke,” Pharmacoepidemiology and Drug Safety 26, no. 12 (2017): 1458–1464, 10.1002/pds.4250. [DOI] [PubMed] [Google Scholar]
- 10. Odusola A. O., Hendriks M., Schultsz C., et al., “Perceptions of Inhibitors and Facilitators for Adhering to Hypertension Treatment Among Insured Patients in Rural Nigeria: A Qualitative Study,” BMC Health Services Research 14 (2014): 624, 10.1186/s12913-014-0624-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Yao Y., Shen J., Luo J., Li N., Liao X., and Zhang Y., “Disagreements in Risk of Bias Assessment for Randomized Controlled Trials in Hypertension‐Related Cochrane Reviews,” Trials 25, no. 1 (2024): 405, 10.1186/s13063-024-08145-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12. Zhu L., Wu Y., Zhang Y., et al., “Copublication Promotes Dissemination Hypertension Guidelines: A Retrospective Cohort Study,” Hypertension Research 47, no. 2 (2024): 416–426, 10.1038/s41440-023-01470-0. [DOI] [PubMed] [Google Scholar]
- 13. Zou C., Deng L., Luo J., et al., “The Impact of Communication Training on the Clinical Care of Hypertension in General Practice: A Cluster Randomized Controlled Trial in China,” BMC Primary Care 25, no. 1 (2024): 98, 10.1186/s12875-024-02344-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14. Gore F. M., Bloem P. J., Patton G. C., et al., “Global Burden of Disease in Young People Aged 10–24 Years: A Systematic Analysis,” Lancet 377, no. 9783 (2011): 2093–2102, 10.1016/s0140-6736(11)60512-6. [DOI] [PubMed] [Google Scholar]
- 15. Gaglio B., Henton M., Barbeau A., et al., “Methodological Standards for Qualitative and Mixed Methods Patient Centered Outcomes Research,” BMJ 371 (2020): m4435, 10.1136/bmj.m4435. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16. Creswell J. W. and Hirose M., “Mixed Methods and Survey Research in Family Medicine and Community Health,” Family Medicine and Community Health 7, no. 2 (2019): e000086, 10.1136/fmch-2018-000086. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17. Burkhart P. V. and Sabaté E., “Adherence to Long‐Term Therapies: Evidence for Action,” Journal of Nursing Scholarship 35, no. 3 (2003): 207. [PubMed] [Google Scholar]
- 18. Jones C. L., Jensen J. D., Scherr C. L., Brown N. R., Christy K., and Weaver J., “The Health Belief Model As an Explanatory Framework in Communication Research: Exploring Parallel, Serial, and Moderated Mediation,” Health Communication 30, no. 6 (2015): 566–576, 10.1080/10410236.2013.873363. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19. Fetters M. D., Curry L. A., and Creswell J. W., “Achieving Integration in Mixed Methods Designs‐Principles and Practices,” Health Services Research 48, no. 6 Pt 2 (2013): 2134–2156, 10.1111/1475-6773.12117. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20. Liu J., “Highlights of the 2018 Chinese Hypertension Guidelines,” Clinical Hypertension 26 (2020): 8, 10.1186/s40885-020-00141-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21. Tang X., Li L., Yao K., et al., “Association Between Social Support and Mutual‐Support Needs Among the Rural Adults in China: A Cross‐Sectional Study,” Frontiers in Public Health 11 (2023): 1171046, 10.3389/fpubh.2023.1171046. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22. Lee P. H., Macfarlane D. J., Lam T. H., and Stewart S. M., “Validity of the International Physical Activity Questionnaire Short Form (IPAQ‐SF): A Systematic Review,” International Journal of Behavioral Nutrition and Physical Activity 8 (2011): 115, 10.1186/1479-5868-8-115. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23. Wang S. S., Lay S., Yu H. N., and Shen S. R., “Dietary Guidelines for Chinese Residents (2016): Comments and Comparisons,” Journal of Zhejiang University Science B 17, no. 9 (2016): 649–656, 10.1631/jzus.B1600341. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24. Peng X., Wan L., Yu B., and Zhang J., “The Link Between Adherence to Antihypertensive Medications and Mortality Rates in Patients With Hypertension: A Systematic Review and Meta‐Analysis of Cohort Studies,” BMC Cardiovascular Disorders 25, no. 1 (2025): 145, 10.1186/s12872-025-04538-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25. Kim H. C. and Cho M. C., “Korea Hypertension Fact Sheet 2018,” Clinical Hypertension 24 (2018): 13, 10.1186/s40885-018-0098-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26. Spikes T., Higgins M., Lewis T., and Dunbar S. B., “The Associations Among Illness Perceptions, Resilient Coping, and Medication Adherence in Young Adult Hypertensive Black Women,” Journal of Clinical Hypertension (Greenwich, Conn.) 21, no. 11 (2019): 1695–1704, 10.1111/jch.13712. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27. Unni E., Shiyanbola O. O., and Farris K. B., “Change in Medication Adherence and Beliefs in Medicines Over Time in Older Adults,” Global Journal of Health Sciences 8, no. 5 (2015): 39–47, 10.5539/gjhs.v8n5p39. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28. Osamor P. E. and Owumi B. E., “Factors Associated With Treatment Compliance in Hypertension in Southwest Nigeria,” Journal of Health, Population, and Nutrition 29, no. 6 (2011): 619–628, 10.3329/jhpn.v29i6.9899. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29. Zhao Q., Guo R., Fan Z., Hu L., Hu Z., and Liu Y., “Medical Conditions and Preference of Traditional Chinese Medicine: Results From the China Healthcare Improvement Evaluation Survey,” Patient Preference and Adherence 17 (2023): 227–237, 10.2147/ppa.S398644. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30. Taylor K. D., Adedokun A., Awobusuyi O., Adeniran P., Onyia E., and Ogedegbe G., “Explanatory Models of Hypertension Among Nigerian Patients at a University Teaching Hospital,” Ethnicity & Health 17, no. 6 (2012): 615–629, 10.1080/13557858.2013.771151. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31. Amira C. O. and Okubadejo N. U., “Factors Influencing Non‐Compliance With Anti‐Hypertensive Drug Therapy in Nigerians,” Nigerian Postgraduate Medical Journal 14, no. 4 (2007): 325–329. [PubMed] [Google Scholar]
- 32. Pan J., Hu B., Wu L., and Li Y., “The Effect of Social Support on Treatment Adherence in Hypertension in China,” Patient Preference and Adherence 15 (2021): 1953–1961, 10.2147/ppa.S325793. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33. Gooding H. and Johnson H. M., “The Unchartered Frontier: Preventive Cardiology Between the Ages of 15 and 35 Years,” Current Cardiovascular Risk Reports 10 (2016): 29, 10.1007/s12170-016-0509-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34. Feldman E. C. H., Durkin L. K., and Greenley R. N., “Family Support Is Associated With Fewer Adherence Barriers and Greater Intent to Adhere to Oral Medications in Pediatric IBD,” Journal of Pediatric Nursing 60 (2021): 58–64, 10.1016/j.pedn.2021.01.026. [DOI] [PubMed] [Google Scholar]
- 35. Howse E., Hankey C., Allman‐Farinelli M., Bauman A., and Freeman B., “‘Buying Salad Is a Lot More Expensive Than Going to McDonalds’: Young Adults' Views About What Influences Their Food Choices,” Nutrients 10, no. 8 (2018): 996, 10.3390/nu10080996. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Supporting Table 1: Medication adherence scale.
Supporting Table 2: Consumption amount and frequency of the following foods over the past month.
Supporting Table 3: Interview outline of factors affecting treatment adherence in young adults with hypertension
Supporting Table 4: Characteristics of young hypertensive patients according to varying medication adherence.
Supporting Table 5: Characteristics of young hypertensive patients according to varying healthy lifestyle adherence.
Supporting Table 6: Impact factors influencing medication adherence in young adults with hypertension: themes, subthemes, and coding matrix
Supporting Table 7: Impact factors of lifestyle adherence in young adults with hypertension: themes, subthemes, and coding matrix.
Data Availability Statement
The data will be made available upon request.