Bridging the Knowledge–Practice Gap in Hypertension Management: A Community-Engaged Systems Approach in Disadvantaged Rural Community

Highlights

Public health relevance—How does this work relate to a public health issue?

• Hypertension is a major cause of cardiovascular illness and premature death around the world, especially in low- and middle-income countries where control rates are low and health-care systems are underfunded.
• This study investigates challenges to hypertension control in disadvantaged communities, focusing on how socioeconomic factors, health system restrictions, and structural inequities associated with chronic illness management at the population level.

Public health significance—Why is this work of significance to public health?

• The study shows a strong knowledge-practice gap, in which patients are highly aware of hypertension but fail to transform this information into long-term lifestyle behaviors and effective self-care.
• The findings, which show that health worker counselling and engagement are major predictors of lifestyle adherence and self-management, provide evidence for improving hypertension control through community-based health education and primary health care treatments.

Public health implications—What are the key implications or messages for practitioners, policy makers and/or researchers in public health?

• Practitioners: Improving patient counselling and continuing engagement through primary health care professionals and community health workers may help with lifestyle adherence and hypertension self-management.
• Policymakers should address structural determinants of health such as poverty, transportation difficulties, and access to nutritious food, while also strengthening community-based health promotion activities. Future research should look into community-engaged and systems-based interventions, such as digital health and community health worker models, to improve long-term hypertension control in underserved groups.

Abstract

Background: Hypertension is a major contributor to cardiovascular morbidity and mortality globally, with particularly poor control in disadvantaged communities. Although awareness is generally high, sustaining lifestyle changes and treatment adherence remains difficult. This study examined socioeconomic, behavioural, and health system factors associated with hypertension management and explored the role of community-engaged health education in strengthening primary health care. Methods: A cross-sectional descriptive study was conducted among 107 adults with hypertension attending public primary health care facilities. Data were collected using structured questionnaires covering socioeconomic status, health system access, medication adherence, lifestyle practices, and knowledge and attitudes. Descriptive statistics summarized participant characteristics, while chi-square tests and multivariable logistic regression identified factors associated with clinic attendance, dietary adherence, lifestyle practices, and self-management. Results: Awareness of hypertension (86.9%) and trust in clinic care (91.6%) were high; however, a clear knowledge practice gap was evident. Although 79.4% acknowledged the importance of lifestyle changes, only 45.8% followed a hypertension-specific diet. Structural barriers included low income (39.3% earning <R3 000/month) and long distances to clinics (46.7% living ≥5 km away). Health worker advice strongly predicted dietary adherence (OR = 6.36, p = 0.001), lifestyle adherence (OR = 4.24, p = 0.006), and overall self-management (OR = 12.46, p = 0.024), whereas knowledge alone did not. Conclusions: Hypertension management is constrained more by structural and health system factors than by lack of awareness. Strengthening primary health care counselling and community-based health education may improve sustained lifestyle change and outcomes.

1. Introduction

Hypertension is one of the leading global risk factors for cardiovascular disease and premature mortality [1,2]. Despite the availability of effective treatments, control rates remain suboptimal in many low- and middle-income settings, particularly within disadvantaged communities where socioeconomic constraints and health system limitations complicate chronic disease management [3,4,5]. Rural populations often face barriers, including long travel distances to clinics, limited financial resources, and inconsistent access to medications and follow-up care [6,7,8]. In many contexts, public health interventions have focused primarily on increasing awareness of hypertension and promoting lifestyle modification. However, growing evidence suggests that awareness alone is insufficient to ensure sustained behavioural change [9,10]. Patients may possess adequate knowledge of hypertension but struggle to translate this knowledge into consistent practices such as dietary modification, physical activity, and medication adherence [11,12]. This phenomenon, often referred to as the knowledge–practice gap, highlights the importance of understanding how structural and relational factors influence chronic disease management.

Hypertension is a significant and growing public health burden in South Africa and across Sub-Saharan Africa. According to recent estimates, roughly 30–45% of individuals in South Africa suffer from hypertension, with prevalence increasing dramatically with age and disproportionately affecting socioeconomically disadvantaged populations. Despite this significant burden, awareness, treatment, and control rates remain low, resulting in a huge number of people with uncontrolled blood pressure [3,4].

Hypertension is a major cause of cardiovascular problems, such as stroke, myocardial infarction, heart failure, and chronic renal disease. Cardiovascular illnesses are a major cause of non-communicable disease morbidity and mortality in South Africa, with hypertension highlighted as a major modifiable risk factor. Stroke, in particular, remains one of the leading causes of mortality and disability, with high blood pressure accounting for a large proportion of occurrences [2].

The burden is similar in Sub-Saharan Africa, where hypertension prevalence is increasing at one of the fastest rates globally. More than 80% of people with hypertension live in low- and middle-income countries, especially Sub-Saharan Africa, where health-care system restrictions and socioeconomic inequities make effective disease control difficult [5]. As a result, hypertension contributes considerably to premature morbidity and mortality, with cardiovascular illnesses accounting for a growing share of deaths in the area. In South Africa, hypertension-related consequences contribute significantly to morbidity and mortality, with poor blood pressure control linked to more hospitalisations, a lower quality of life, and early death [4]. These findings highlight the critical need for stronger primary health care systems, better preventative efforts, and context-specific treatments that target both clinical management and the broader structural drivers of hypertension.

Rural and low-income neighborhoods face a variety of interconnected structural impediments that have a direct impact on hypertension management and serve as the foundation for this study’s measured predictors. Socioeconomic restrictions, notably low household income, impede people’s capacity to pay for transportation, access healthcare services, and follow suggested dietary practices, weakening continuity of care. Evidence suggests that financial constraints and a lack of insurance coverage are significant barriers to getting chronic disease care in low-resource settings [13,14]. Geographic limitations, such as significant distances to health facilities and insufficient transportation infrastructure, further limit access to routine follow-up and medication refills, sometimes deterring timely care-seeking behavior [15].

At the household level, conflicting activities such as caregiving and domestic duties may restrict time available for clinic attendance and treatment adherence, especially in resource-constrained contexts where individuals prioritise household requirements above personal health. Environmental and food system constraints in rural areas also limit access to healthy and inexpensive nutritional options, which contribute to poor adherence to lifestyle guidelines [16]. Health system problems such as inadequate healthcare infrastructure, workforce shortages, prolonged wait times, and uneven availability of medication and diagnostic services all contribute to poor continuity and quality of care [14,17]. Furthermore, these structural and systemic disadvantages are not only contextual barriers but also crucial variables in this study, such as household income, distance to clinic, carer position, health-care system access, and lifestyle choices. This alignment reflects a systems-oriented understanding of hypertension management, in which individual behaviours are shaped by broader socioeconomic, environmental, and health system determinants, particularly in rural and low- and middle-income settings where the burden of hypertension continues to rise [18].

Recent health systems research has emphasized the importance of community-engaged approaches to health promotion, particularly in settings characterized by socioeconomic disadvantage [19,20,21]. Community engagement involves collaborative partnerships between communities, health workers, and institutions to co-produce knowledge and develop locally relevant solutions to health challenges [22]. Such approaches align with broader frameworks of primary health care strengthening and participatory health promotion [23]. Within the African context, community engagement in health systems is often grounded in the philosophy of Ubuntu, which emphasizes relational interdependence and collective responsibility for wellbeing [24]. The Ubuntu ethic umuntu ngumuntu ngabantu (“a person is a person through others”) recognizes that health behaviours are shaped not only by individual choices but also by social relationships, community networks, and institutional structures [25]. Similarly, the concept of the reparative university highlights the responsibility of universities to engage collaboratively with communities in addressing social and health inequalities through participatory research and knowledge co-production [26,27,28]. Addressing hypertension in low-resource settings requires integrated approaches that combine behavioural, structural, and health system interventions.

This study examined barriers to hypertension management in disadvantaged communities while exploring the potential role of community-engaged health education in strengthening lifestyle practices and patient self-management. Specifically, the study aimed to identify socioeconomic and health system barriers associated with hypertension care, assess knowledge, attitudes, and practices related to hypertension treatment and lifestyle modification, evaluate predictors of hypertension self-management using multivariable statistical models, and develop a community-engaged conceptual framework to inform improved hypertension education and self-management within rural primary health care systems.

2. Materials and Methods

2.1. Study Design

A prospective cross-sectional descriptive study was conducted to investigate barriers to hypertension management in disadvantaged communities served by public primary healthcare facilities. Primary data were collected directly from participants using structured, self-administered questionnaires.

2.2. Study Population

The study included 107 adults diagnosed with hypertension who were receiving care through public primary health care services. Participants were recruited through community-based health engagement activities linked to primary health care clinics. Individuals aged 18 and older with a verified diagnosis of hypertension and active participation or linkage to care at participating primary health care clinics were eligible to participate.

Individuals who were unable to provide informed consent, had insufficient clinical or questionnaire data, or were not already receiving hypertension care at the time of data collection were excluded.

A non-probability convenience sampling method was utilised. Participants were recruited through community-based health engagement events and routine clinic visits, during which eligible persons were encouraged to participate in the study. This strategy was acceptable given the exploratory character of the study and the emphasis on obtaining information from people who are actively involved in primary health care services.

2.3. Variable Definitions and Operationalization

All variables (

Table 1. Summary of study variables, operational definitions, and roles in analysis.

Variable	Type	Operational Definition	Role in Analysis
Missed clinic appointment	Dichotomous (Yes/No)	Self-reported missed ≥1 clinic visit in past 6 months	Outcome
Dietary adherence	Dichotomous (Yes/No)	Self-reported adherence to low-salt/hypertension diet	Outcome
Lifestyle adherence (knowledge–practice gap outcome)	Dichotomous (Composite)	≥2 of diet, physical activity, salt monitoring	Outcome
Integrated self-management	Dichotomous (Composite)	≥3 of medication adherence, clinic attendance, BP monitoring, lifestyle adherence	Outcome
Knowledge–practice gap	Derived construct	Knowledge present without corresponding lifestyle adherence	Analytical construct
Household income	Categorical/Dichotomous	<R3 000 vs. ≥R3 000	Predictor
Employment status	Categorical	Employed/unemployed/self-employed	Predictor
Distance to clinic	Dichotomous	<5 km vs. ≥5 km	Predictor
Caregiver status	Dichotomous	Primary caregiver yes/no	Predictor
Health worker advice	Dichotomous	Received counselling on hypertension/lifestyle	Predictor
Waiting time perception	Dichotomous	Reasonable vs. not reasonable	Predictor
Medication availability (stock-outs)	Dichotomous	Experienced stock-outs yes/no	Predictor
Knowledge of lifestyle management	Dichotomous	Aware lifestyle controls hypertension	Predictor
Physical activity	Dichotomous	Regular activity yes/no	Predictor

) included in the analysis were derived from structured questionnaire items and categorized based on study objectives. Variables were defined, operationalized, and classified according to their role in the analysis as either dependent (outcome) or independent (predictor) variables.

2.4. Data Collection and Sample Size Calculation

Data were collected prospectively from adult patients attending the clinic during the study period using a structured questionnaire covering five key domains: socio-demographic characteristics, health system access and service delivery, medication adherence and clinic attendance, lifestyle practices, and knowledge and attitudes regarding hypertension. A sample size (n) of the study population will be calculated taking into account the following aspects:

Unkown proportion: P = 50%

Confidence level: 95%

e: The maximum error admitted by the researcher: e = 10%

n = (Z_∝² × P (100 − P))/e²

n = ([(1.96)]² × 50 (100 − 50))/100 = (3.84 × 2500)/100 = 96

All dimensional measurements were standardized and are reported using SI units, with units specified for each dimension (e.g., m × m for area and m × m for volume).

This sample size of 96 patients with hypertension is representative of the study population. To accommodate errors and confounding effects, 10% was added and rounded off to 106, with a minimum of 10% less calculated to be 86.

2.5. Ethical Consideration

This study was conducted in accordance with the principles of the Declaration of Helsinki. Ethical approval was obtained from the Walter Sisulu University Human Research Ethics Committee (HREC) (Protocol No.: WSU.HREC 150/2025), and permission to conduct the study was granted by the Eastern Cape Department of Health (Ref: EC_202510_023).

Written informed consent was obtained from all participants prior to data collection. The study involved direct participant engagement through prospective data collection, and no retrospective patient records were used.

Participants were assured of their right to withdraw from the study at any time without any consequences to their access to healthcare services. Confidentiality and anonymity were strictly maintained throughout the study. No personally identifiable information was collected, and all data were securely stored and accessible only to the research team. Data were analysed and reported in aggregate form to ensure that individual participants could not be identified.

2.6. Statistical Analysis

Data were analysed using IBM SPSS version 29. Chi-square tests were used to assess associations between categorical variables. Logistic regression analysis was performed to identify predictors of missed clinic appointments. Prior to conducting logistic regression analyses, key model assumptions were assessed. Multicollinearity among independent variables was evaluated using variance inflation factors (VIF), with no evidence of significant multicollinearity observed. The independence of observations was ensured by the study design. Model fit was assessed using the Hosmer–Lemeshow goodness-of-fit test. Additionally, confidence intervals were examined to assess the precision of estimates. All assumptions were considered adequately met. Multivariable logistic regression models were subsequently constructed to identify predictors of missed clinic appointments, examine factors associated with adherence to a hypertension-specific diet, evaluate the knowledge–practice gap in lifestyle adherence, and model integrated hypertension self-management behaviours. Effect sizes were reported as odds ratios (OR) with 95% confidence intervals (CI). Model performance and goodness-of-fit were assessed using likelihood ratio tests and pseudo-R² statistics.

Two additional multivariable logistic regression models were fitted to strengthen analytical inference. First, a knowledge–practice gap model evaluated whether knowledge that hypertension can be managed through lifestyle modification predicted a composite lifestyle adherence outcome (dietary modification, regular physical activity, and salt monitoring). Second, an integrated self-management model predicted a composite optimal hypertension self-management outcome incorporating medication-taking behavior, clinic attendance, blood pressure monitoring, and lifestyle adherence. Effect sizes are reported as odds ratios (OR) with 95% CI. Monetary values were converted from South African Rand (ZAR) to United States Dollars (USD) using an average exchange rate to facilitate international interpretation.

Although bivariate associations assessed using chi-square tests did not demonstrate statistically significant relationships for some variables, multivariable logistic regression analyses were conducted to account for potential confounding and to examine the independent effects of multiple predictors on hypertension management outcomes. This approach allows for a more comprehensive assessment of relationships within complex health systems, where interactions between variables may not be evident in unadjusted analyses.

3. Results

3.1. Participant Characteristics

A total of 107 participants were included in the analysis (

Table 2. Demographic characteristics of study participants (N = 107).

Variable	Category	Frequency, n (%)
Sex	Female	81 (75.7)
	Male	26 (24.3)
Employment status	Employed	52 (48.6)
	Unemployed	35 (32.7)
	Self-employed	19 (17.8)
Household income (ZAR/month)	<$55 (R1 000)	24 (22.4)
	$55–$165 (R1 000–R2 999)	18 (16.8)
	≥$165/month (R3 000) *	—
Distance to clinic	<5 km	57 (53.3)
	≥5 km	50 (46.7)

* Currency values were converted from South African Rand (ZAR) to United States Dollars (USD) using an approximate exchange rate of 1 USD = R18.5 for international comparability. Original values in ZAR are provided in parentheses.

). The sample was predominantly female (75.7%, n = 81), with males accounting for 24.3% (n = 26). Nearly half of respondents were employed (48.6%, n = 52), while 32.7% (n = 35) were unemployed and 17.8% (n = 19) self-employed. Household income varied, although a substantial proportion reported low income: 22.4% (n = 24) earned < R1 000 per month, and 16.8% (n = 18) earned R1 000–R2 999. Physical access to care was constrained for many respondents, with 46.7% (n = 50) living ≥5 km from the nearest clinic.

3.2. Socioeconomic, Cultural, and Systemic Barriers to Hypertension Management Socioeconomic Barriers

Economic constraints were frequently reported. More than one-third of participants were either unemployed or self-employed in low-income contexts (50.5%, n = 54), limiting their ability to afford transport, nutritious food, and time for clinic attendance. Low household income (<R3 000/month) was reported by 39.3% (n = 42) of participants.

While few respondents reported explicit cultural or religious barriers to clinic attendance, household roles and caregiving responsibilities were common. 38.3% (n = 41) identified as primary caregivers, reporting that caregiving duties often interfered with medication routines and clinic visits.

3.3. Systemic Barriers

System-level challenges were prominent. Many participants reported long waiting times, medication stock-outs, and infrequent blood pressure monitoring during clinic visits. These systemic constraints contributed to treatment interruptions and delayed follow-up, even among participants motivated to adhere to care.

Table 3. Socioeconomic and health system barriers to hypertension management (N = 107).

Domain	Indicator	Category	Frequency, n (%)
Socioeconomic barriers	Employment status	Employed	52 (48.6)
		Unemployed	35 (32.7)
		Self-employed	19 (17.8)
	Household income	<$165/month (R3 000)	42 (39.3)
Cultural/Household barriers	Caregiver responsibility	Yes	41 (38.3)
		No	66 (61.7)
Health system barriers	Distance to clinic	≥5 km	50 (46.7)
		<5 km	57 (53.3)
Knowledge and access context	Awareness of hypertension	Yes	93 (86.9)
	Trust in clinic care	Yes	98 (91.6)
Lifestyle practice (gap indicator)	Adherence to hypertension diet	Yes	49 (45.8)
		No	58 (54.2)

Currency values were converted from South African Rand (ZAR) to United States Dollars (USD) using an approximate exchange rate of 1 USD = R18.5. Original values in ZAR are provided in parentheses.

briefly highlights the contrast between high awareness/trust and lower lifestyle adherence, reinforcing the knowledge–practice gap described in the text.

Table 4. (A) Logistic regression predictors of missed clinic appointments. (B) Association between structural barriers and missed clinic appointments.

(A)
Variable	Odds Ratio (OR)	95% Confidence Interval	p-Value
Low household income (<R3 000)	0.22	0.05–1.09	0.064
Distance to clinic ≥ 5 km	0.54	0.14–1.99	0.350
Primary caregiver	0.36	0.10–1.33	0.125
(B)
Variable	Chi-Square (χ2)		p-Value
Household income	4.48		0.345
Distance to clinic	2.68		0.261
Caregiver status	2.31		0.128

A,B highlights a clear knowledge–practice gap, where high levels of awareness and positive attitudes toward hypertension management do not consistently translate into sustained lifestyle modification. Most participants reported having heard of hypertension (86.9%, n = 93) and understood its long-term health implications. A large proportion also recognized that hypertension could be managed through lifestyle modification (79.4%, n = 85), although 17.8% (n = 19) remained uncertain, indicating some gaps in health education. Attitudes toward treatment were largely positive, with nearly all participants expressing trust in clinic treatment recommendations (91.6%, n = 98), reflecting strong confidence in primary health care services despite reported system constraints.

In contrast, self-reported practices revealed notable challenges in maintaining recommended lifestyle behaviors. While the majority of participants reported not missing clinic appointments (87.9%, n = 94), 12.1% (n = 13) had missed at least one appointment in the preceding six months. Regular physical activity was reported by 69.2% (n = 74) of respondents; however, adherence to dietary recommendations was considerably lower, with fewer than half (45.8%, n = 49) following a low-salt or hypertension-specific diet. Additionally, 18.7% (n = 20) reported being unaware of appropriate dietary modifications.

To further examine structural influences on care continuity, a multivariable logistic regression model was conducted to evaluate whether socioeconomic and household factors were associated with missed clinic appointments among individuals receiving hypertension care (N = 107). The predictors included low household income (<R3 000), distance to the clinic (≥5 km), and primary caregiver status. Participants with low household income showed higher odds of missing clinic appointments compared with higher-income participants with low household income showed higher odds of missing clinic appointments compared with higher-income participants (OR = 0.22, 95% CI: 0.05–1.09, p = 0.064); however, this association did not reach statistical significance and should be interpreted cautiously. Distance to the nearest clinic was also not significantly associated with missed appointments (OR = 0.54, 95% CI: 0.14–1.99, p = 0.350). Similarly, participants who identified as primary caregivers demonstrated higher likelihood of missing clinic visits compared with non-caregivers, though the association was not statistically significant (OR = 0.36, 95% CI: 0.10–1.33, p = 0.125).

Overall, the model explained a modest proportion of the variance in clinic attendance (Pseudo R² = 0.07), suggesting that continuity of hypertension care in disadvantaged communities is influenced by a broader set of structural, behavioral, and health system factors beyond those included in the model.

Although chi-square analyses did not show statistically significant associations between structural variables and missed clinic attendance, these variables were included in multivariable models based on theoretical relevance and prior evidence. The regression analysis was therefore conducted to explore adjusted relationships and should be interpreted with caution, particularly where statistical significance was not achieved. These estimates should be interpreted with caution due to the relatively small sample size and the presence of wide confidence intervals, which may indicate reduced precision and potential model instability.

Chi-square analyses in

Table 5. Association between structural factors and missed clinic appointments.

Variable	Category	Missed Appointment n (%)	Did Not Miss n (%)	p-Value
Household income	<$54 (<R1 000)	2 (8.3)	22 (91.7)
	$54–$162 (R1 000–R2 999)	0 (0)	18 (100)
	$162–$270 (R3 000–R4 999)	4 (17.4)	19 (82.6)
	≥$270 (≥R5 000)	7 (17.1)	34 (82.9)	0.345
Distance to clinic	<5 km	9 (15.8)	48 (84.2)
	5–10 km	1 (3.6)	27 (96.4)
	>10 km	3 (13.6)	19 (86.4)	0.261

Note: Currency values were converted from South African Rand (ZAR) to United States Dollars (USD) using an approximate exchange rate of 1 USD = R18.5. Original values are presented in parentheses.

were conducted to explore associations between selected structural determinants and missed clinic appointments. No statistically significant association was observed between household income and missed clinic appointments (χ² = 4.48, p = 0.345). Similarly, distance to the nearest clinic was not significantly associated with missed appointments (χ² = 2.68, p = 0.261). Although these associations were not statistically significant, descriptive patterns suggested that participants residing farther from health facilities and those with lower income reported slightly higher proportions of missed appointments.

A multivariable logistic regression analysis in

Table 6. Logistic regression predicting missed clinic appointments.

Predictor	β Coefficient	Standard Error	p-Value	Odds Ratio
Distance ≥ 5 km	−0.87	0.65	0.179	0.42
Low income (<R3 000)	−1.48	0.80	0.066	0.23
Constant	−1.23	0.40	0.002	—

Model statistics: Pseudo R² = 0.07; Log-likelihood = −36.63; Likelihood ratio test p = 0.052.

was conducted to identify structural predictors of missed clinic appointments. The overall model demonstrated modest explanatory power (pseudo R² = 0.07) and approached statistical significance (p = 0.052). Participants with low household income (<R3 000/month) showed a higher likelihood of missing clinic appointments compared with higher-income participants (β = −1.48, p = 0.066), although this association did not reach conventional levels of statistical significance. Distance from the clinic (≥5 km) was not significantly associated with missed appointments (β = −0.87, p = 0.179).

3.4. Knowledge, Attitudes, and Practices Regarding Hypertension

Overall, the findings demonstrate a clear knowledge–practice gap, where high levels of awareness and generally positive attitudes toward treatment do not consistently translate into sustained lifestyle modification. Most participants had heard of hypertension (86.9%, n = 93) and recognized it as a chronic condition requiring ongoing management. A substantial proportion understood that hypertension can be controlled through both medication and lifestyle modification (79.4%, n = 85). However, 17.8% (n = 19) remained uncertain about lifestyle management, indicating residual gaps in health education. Attitudes toward treatment were largely positive. Nearly all respondents expressed trust in clinic treatment recommendations (91.6%, n = 98) and reported willingness to take prescribed medication. Nevertheless, frustrations related to health service challenges such as long waiting times and medication availability occasionally undermined confidence in long-term disease control.

Despite adequate knowledge and favorable attitudes, reported practices were often suboptimal. While most participants indicated that they had not missed clinic appointments (87.9%, n = 94), 12.1% (n = 13) reported missing at least one appointment in the previous six months. Regular physical activity was reported by 69.2% (n = 74), but adherence to dietary recommendations was considerably lower, with only 45.8% (n = 49) following a low-salt or hypertension-specific diet. Additionally, 18.7% (n = 20) reported being unaware of appropriate dietary modifications. Financial constraints and environmental barriers, including limited access to healthier food options and safe opportunities for physical activity, further constrained lifestyle practices.

Table 7. Knowledge, attitudes, and practices related to hypertension management (N = 107).

Domain	Indicator	Category	n (%)
Knowledge	Heard of hypertension	Yes	93 (86.9)
		No	14 (13.1)
	Aware of lifestyle management	Yes	85 (79.4)
		No/Unsure	22 (20.6)
Attitudes	Trust in clinic treatment	Yes	98 (91.6)
		No	9 (8.4)
Practices	Missed clinic appointment (past 6 months)	Yes	13 (12.1)
		No	94 (87.9)
	Regular physical activity	Yes	74 (69.2)
		No	33 (30.8)
	Adherence to hypertension diet	Yes	49 (45.8)
		No	58 (54.2)
	Awareness of dietary modification	Yes	87 (81.3)
		No	20 (18.7)

briefly describes the knowledge,, attitudes, and practices regarding hypertension.

3.5. Logistic Regression Analysis

A multivariable logistic regression analysis (

Table 8. Predictors of adherence to hypertension dietary recommendations.

Variable	Odds Ratio (OR)	95% CI	p-Value
Knowledge of lifestyle management	0.58	0.03–10.83	0.712
Trust clinic recommendations	7.25	0.69–75.87	0.098
Received health worker advice	6.36	2.10–19.28	0.001
Regular physical activity	2.79	0.85–9.11	0.089

) was conducted to examine factors associated with adherence to a hypertension-specific diet (low-salt or recommended dietary modification). Predictor variables included knowledge that hypertension can be managed with lifestyle changes, trust in clinic treatment recommendations, receipt of health worker advice on blood pressure control, and engagement in regular physical activity. Receiving advice from a health worker was strongly associated with adherence to a hypertension diet (OR = 6.36, 95% CI: 2.10–19.28, p = 0.001). Participants who engaged in regular physical activity were more likely to follow a recommended diet (OR = 2.79, 95% CI: 0.85–9.11, p = 0.089), although the association did not reach statistical significance. Trust in clinic treatment recommendations was also positively associated with dietary adherence (OR = 7.25, 95% CI: 0.69–75.87, p = 0.098). Knowledge that hypertension can be managed through lifestyle modification was not significantly associated with diet adherence (OR = 0.58, 95% CI: 0.03–10.83, p = 0.712).

3.6. Knowledge–Practice Gap Model

The analysis in

Table 9. Predictors of lifestyle adherence (knowledge–practice gap model).

Predictor	OR	95% CI	p-Value
Knowledge Yes	2.27	0.61–8.45	0.221
Advice	4.24	1.51–11.86	0.006
Low Income	1.41	0.54–3.63	0.481
Far Clinic	0.37	0.15–0.94	0.036
Caregiver	1.56	0.61–3.98	0.351

tested whether knowledge that hypertension can be managed with lifestyle change translated into actual lifestyle practice. The outcome was a composite lifestyle adherence index (following a hypertension diet + engaging in regular physical activity + monitoring salt intake). Predictors included knowledge, receipt of health worker advice, and key structural barriers. In the adjusted model, receiving advice from a health worker was independently associated with higher odds of lifestyle adherence (OR = 4.24, 95% CI: 1.51–11.86, p = 0.006). Knowledge alone was not significantly associated with lifestyle adherence after adjustment (OR = 2.27, 95% CI: 0.61–8.45, p = 0.221), supporting a measurable knowledge–practice gap. Living ≥5 km from the clinic was associated with lower odds of lifestyle adherence (OR = 0.37, 95% CI: 0.15–0.94, p = 0.036).

3.7. Integrated Multivariable Model Predicting Hypertension Self-Management

An integrated logistic regression model in

Table 10. Integrated predictors of optimal hypertension self-management.

Predictor	OR	95% CI	p-Value
Knowledge	9.27	0.81–106.29	0.074
Advice	12.46	1.38–112.07	0.024
Low Income	1.39	0.35–5.57	0.644
Far Clinic	0.39	0.11–1.35	0.138
Caregiver	3.39	0.91–12.60	0.068
Stockout	1.27	0.36–4.41	0.710
Wait Ok	3.28	0.93–11.56	0.064
Follow up	1.20	0.20–7.03	0.843
Med Avail Good	1.88	0.36–9.85	0.454

was constructed to predict optimal hypertension self-management. The outcome combined four essential self-management behaviors: (i) not reporting ‘never’ taking medication, (ii) not missing clinic appointments in the last six months, (iii) any blood pressure monitoring (excluding ‘not often’/‘not sure’), and (iv) lifestyle adherence (diet + physical activity + salt monitoring). Predictors included knowledge and counselling variables, structural barriers, and selected health system service delivery indicators. Receiving advice from a health worker remained the strongest independent predictor of optimal self-management (OR = 12.46, 95% CI: 1.38–112.07, p = 0.024). Knowledge of lifestyle management showed a positive but borderline association (OR = 9.27, 95% CI: 0.81–106.29, p = 0.074). Caregiving responsibilities and perceived reasonable waiting times also demonstrated borderline positive associations with self-management (caregiver OR = 3.39, p = 0.068; waiting time reasonable OR = 3.28, p = 0.064). Other structural and medicine access indicators did not show statistically significant associations in this sample.

4. Discussion

4.1. Participant Characteristics and Structural Context

This study examined hypertension management among adults receiving care in disadvantaged communities served by primary health care facilities. The findings of this study suggest that participants who received health worker advice demonstrated higher odds of improved hypertension self-management. However, this association did not reach statistical significance and should be interpreted with caution. The wide confidence intervals observed further indicate reduced precision of the estimates, likely reflecting the relatively small sample size. The observed association between counselling and self-management may be partially explained by confounding factors, including patient motivation, health-seeking behaviour, and differential access to healthcare services. As such, these findings do not imply a causal relationship between counselling and improved self-management outcomes. Nevertheless, counselling may play a supportive role within a broader set of behavioural and health system factors influencing hypertension management. This highlights the importance of considering counselling as part of a multifaceted, community-engaged approach rather than as a standalone determinant of behaviour change.

The study population was predominantly female (75.7%), with a substantial proportion of participants experiencing socioeconomic vulnerability, including unemployment or low household income. Similar patterns have been observed in other hypertension studies. For example, research conducted in Iran found that most hypertensive patients were women responsible for household duties, highlighting the important role women play in managing family health and dietary practices [29]. However, economic constraints can limit their ability to consistently implement recommended lifestyle modifications. Socioeconomic status has been widely identified as a key determinant of hypertension management. Individuals with lower income often face barriers such as limited access to healthy food, transportation challenges, and financial stress, which may reduce adherence to dietary and treatment recommendations. These structural barriers are particularly pronounced in disadvantaged communities. In the South African context, community-based health frameworks emphasise collective responsibility, patient empowerment, and culturally responsive care approaches, such as those informed by Ubuntu philosophy, to strengthen chronic disease management [23]. Nearly half of the respondents lived at least 5 km from the nearest clinic, highlighting potential geographic barriers to accessing routine hypertension care. Distance to health facilities is a well-recognized determinant of healthcare utilization in disadvantaged or rural communities, where transport options and financial resources are often limited. Longer travel distances increase both time and cost burdens, which may discourage regular clinic attendance and medication refills. Evidence from rural health research shows that while long travel distances may become normalized in underserved areas, they still significantly hinder access to preventive and chronic care services [8]. Geographic barriers can therefore contribute to missed appointments, reduced treatment adherence, and poorer hypertension control.

These findings reflect broader patterns reported in rural and resource-constrained settings, where chronic disease management is often shaped by structural inequalities and limited access to health services. In many low- and middle-income countries, hypertension disproportionately is associated with populations living in disadvantaged environments where health system capacity and service accessibility remain uneven [10]. Evidence suggests that more than 80% of the global burden of hypertension occurs in low- and middle-income regions, where disparities in healthcare infrastructure, economic resources, and preventive services complicate effective long-term disease management [10]. Economic hardship further constrains patients’ ability to adhere to recommended hypertension care. Financial limitations may reduce the capacity to afford transportation to healthcare facilities, purchase medications, or maintain healthier dietary practices. Studies examining adherence to chronic disease treatment show that out-of-pocket costs and limited insurance coverage are strongly associated with poor medication adherence and uncontrolled hypertension [9]. Additionally, transportation costs and other indirect treatment expenses can delay prescription refills or clinic visits, thereby undermining continuity of care [9]. Together, these socioeconomic and structural barriers highlight the importance of strengthening accessible primary health care systems and community-based interventions to support hypertension management in disadvantaged populations.

4.2. Socioeconomic, Household, and Health System Barriers to Care

Several structural barriers to hypertension management were identified. Low household income was reported by nearly 40% of participants, and over one-third identified as primary caregivers responsible for household duties. These caregiving responsibilities often interfered with medication routines and clinic attendance. Similar findings have been reported in other studies, where competing domestic responsibilities and financial constraints have been widely recognized as important barriers to effective chronic disease management. Individuals who serve as primary caregivers often prioritize household and family needs over their own health, which can disrupt medication routines and reduce the likelihood of attending scheduled clinic visits [30]. Economic hardship further compounds these challenges by limiting the ability to afford transportation, purchase recommended foods, or consistently access healthcare services [31]. In many disadvantaged communities, these socioeconomic pressures interact with broader structural inequalities that shape health behaviours and treatment adherence [32]. The systemic health service challenges, including long waiting times, medication stock-outs, and limited blood pressure monitoring during clinic visits, may further undermine effective hypertension control. Health-system-related barriers such as limited provider–patient interaction, inconsistent medication supply, and inadequate follow-up have been widely recognized as important contributors to poor medication adherence and uncontrolled hypertension in many settings [12].

Although chi-square analyses did not demonstrate statistically significant associations between structural variables and missed clinic appointments, descriptive patterns suggested that socioeconomic vulnerability and caregiving responsibilities may contribute to disruptions in hypertension care. Logistic regression results also indicated that lower household income was associated with increased likelihood of missing clinic visits, although the association approached but did not reach statistical significance.

The relatively low explanatory power of the regression model suggests that continuity of hypertension care is influenced by multiple interacting determinants, including structural, behavioural, and health system factors. These findings are consistent with previous public health research demonstrating that poverty, transport barriers, and competing household demands frequently disrupt chronic disease management in disadvantaged communities. In low- and middle-income settings, socioeconomic inequalities often limit patients’ ability to maintain regular clinic attendance, adhere to medication regimens, and implement recommended lifestyle changes. These challenges are further compounded by broader health system constraints, including limited resources and uneven access to preventive services. Evidence indicates that hypertension disproportionately affects populations in resource-limited environments, where structural barriers and health system weaknesses contribute to poor disease control and increased cardiovascular risk [1].

In addition to structural and health-care constraints, cultural and social norms have a significant impact on hypertension-related behaviours in underprivileged South African communities. In many sub-Saharan African cultures, greater body sizes are frequently culturally associated with health, prosperity, and social status, which may diminish the perceived urgency for weight control and contribute to the normalisation of overweight and obesity. These views can influence health-seeking behaviour and limit participation in weight control efforts, even among people who are aware of the hazards associated with hypertension. Dietary practices are similarly influenced by social and environmental factors. In low-resource contexts, dietary choices are usually influenced by affordability and availability, leading to a dependence on low-cost, energy-dense meals that are heavy in salt and fat [33]. High salt consumption continues to be a significant contributor to high blood pressure, and traditional and transitioning diets in many African contexts are frequently heavy in sodium, complicating hypertension management even further. Furthermore, access to healthy food options is frequently limited in rural and marginalised communities, impeding adherence to recommended dietary changes [34].

Moreover, physical activity patterns reflect contextual circumstances; purposeful or scheduled exercise is not always culturally acceptable or practicable. Physical activity is frequently incidental, resulting from occupational or domestic responsibilities such as long-distance walking, farming, or home chores rather than deliberate exercise [34]. Social conventions, gender roles, and community opinions all have an impact on physical activity, with family and social expectations influencing or discouraging certain types of exercise [34]. Furthermore, impediments such as hazardous environments, a lack of recreational infrastructure, and competing socioeconomic demands may impede regular physical activity. These interconnected cultural and socioeconomic elements contribute to the observed knowledge-practice gap in this study, demonstrating that hypertension management practices are driven not just by individual awareness but also by deeply established cultural norms and broader structural contexts.

4.3. Knowledge, Attitudes, and Practices: Evidence of a Knowledge–Practice Gap

Despite structural challenges, participants demonstrated high awareness of hypertension and positive attitudes toward treatment. These findings can be interpreted within established behavioural change frameworks, such as the Health Belief Model and Social Cognitive Theory, which emphasise the role of perceived barriers, self-efficacy, and social support in influencing health behaviours. Similarly, evidence from low- and middle-income countries indicates that effective hypertension self-management requires integrated approaches that address both individual behaviour and structural constraints, including access to care and health system responsiveness. The majority had heard of hypertension and understood that it requires long-term management, while most expressed trust in treatment recommendations provided by clinic staff. However, this awareness did not consistently translate into sustained lifestyle modification. Although most respondents recognized the importance of lifestyle management, fewer than half reported adherence to recommended dietary practices such as reducing salt intake. In a review study, South Africa was depicted as the only African country to have a national strategy to reduce average sodium intake with the aim of achieving the global target of 30% reduction of intake by 2021 [35]. In collaboration with our findings, a review study highlighting the effectiveness of nutritional support to improve treatment adherence reported significant improvement in treatment adherence among patients receiving support compared to those without support [36]. While regular physical activity was reported by a majority of respondents, dietary adherence remained relatively low, and nearly one-fifth reported uncertainty regarding appropriate dietary modifications. Comparably, a study in China reported low physical activity of less than 2 h and inadequate protein intake, suggesting the need to improve nutritional status among TB patients by developing nutritional screening and support plans as well as strengthening nutritional health education and interventions [37].

These findings highlight a clear knowledge–practice gap, where high levels of awareness and positive treatment attitudes do not necessarily result in consistent health behaviors. Lifestyle practices were frequently constrained by financial and environmental factors, including limited access to healthy foods and restricted opportunities for physical activity. Studies reveal that patients frequently struggle to purchase suggested nutritious diets or satisfy other basic needs during treatment, which is often associated with adherence to nutritional and lifestyle counseling provided by healthcare personnel. Moreover, environmental and structural hurdles, such as inadequate housing, restricted access to healthcare facilities, and inability to finance transportation, further hinder patients’ capacity to maintain healthy lives and seek TB therapies [38,39]. Such barriers illustrate how structural conditions can limit individuals’ ability to translate health knowledge into sustained behavior change.

4.4. Predictors of Lifestyle Adherence and the Role of Health Worker Engagement

Multivariable analysis examining adherence to hypertension dietary recommendations revealed that receiving advice from a health worker was strongly associated with lifestyle adherence. Similar findings have been reported in other studies examining hypertension self-management. Research conducted among hypertensive patients in Ethiopia found that individuals with better knowledge of their condition, often gained through counselling and education from health professionals, were significantly more likely to adhere to recommended lifestyle modifications, including dietary changes [40,41].

Participants who received counselling on blood pressure management were significantly more likely to follow recommended dietary practices. A study assessing abnormal blood pressure among individuals evaluated for TB infection reported a prevalence of hypertension among older age, with higher body mass index, and within the black community. The study further emphasized the need for public interventions, including pre-counselling, to reduce possible cardiovascular events [42]. These findings were echoed by Cox et al., emphasizing the need for dietary advice and nutritional management to improve patient-centered services and TB treatment outcomes [43]. Participants who received counselling on blood pressure management were significantly more likely to follow recommended dietary practices, underscoring the importance of health education delivered by healthcare professionals. Counselling provides patients with practical knowledge about lifestyle modification, including reducing salt intake, improving diet quality, and maintaining healthy behaviors necessary for blood pressure control. Evidence from hypertension management research shows that patient education and behavioral counselling are key components of effective cardiovascular risk reduction strategies, as they enhance patients’ understanding of disease management and encourage self-care practices [44]. Similarly, studies examining hypertension self-management have demonstrated that individuals who receive structured guidance from healthcare providers are more likely to adopt recommended lifestyle behaviors compared with those who receive limited or no counselling [40]. However, the effectiveness of counselling often depends on the frequency and quality of patient–provider interactions, as well as the patient’s broader social context. Continuous education, reinforcement, and supportive healthcare environments are therefore essential to sustain long-term adherence to dietary and lifestyle recommendations for hypertension control.

In contrast, knowledge that hypertension could be managed through lifestyle modification was not independently associated with dietary adherence. This finding suggests that behavior change is facilitated not simply through awareness but through relational engagement with health professionals who provide contextualized guidance and support [10]. The knowledge–practice gap model reinforced this interpretation. Receiving advice from a health worker remained independently associated with lifestyle adherence, whereas knowledge alone did not predict behavior change after adjustment. Distance to the clinic also emerged as a significant predictor, suggesting that physical access to health services may influence patients’ ability to sustain lifestyle practices. Together, these findings highlight the importance of counselling and ongoing patient–provider interactions in translating hypertension knowledge into behavioral change. While counselling is already entrenched in current evidence-based guidelines, it needs to be explicitly included as an organised, patient-centered intervention. We recommend that future modifications of South Africa’s hypertension management guidelines:

• Counselling should be clearly defined as a basic component of care, rather than an inferred activity in lifestyle adjustment.
• Provide established counselling protocols that include frequency, content (diet, salt intake, physical activity, medication adherence), and delivery methods.
• Encourage task-shifting initiatives, which allow nurses and community health workers to provide formal counselling in primary care settings.

Strengthening counselling within guidelines and practice may increase patient adherence, close the knowledge-practice gap, and, ultimately, improve hypertension management results in resource-limited settings.

4.5. Integrated Model of Hypertension Self-Management and Health System Implications

The integrated multivariable model provided a broader systems perspective on hypertension self-management. The composite outcome included medication adherence, clinic attendance, blood pressure monitoring, and lifestyle behaviors. Within this model, receiving advice from a health worker remained the strongest independent predictor of optimal hypertension self-management. Knowledge of lifestyle management demonstrated a positive but borderline association with self-management, suggesting that knowledge may contribute to behavior change when combined with counselling and health system support. Comparably, a health belief model-based motivational interview for treatment adherence and treatment success in TB patients highlighted the need for ongoing counselling training for TB program managers in order to have an in-depth understanding of the problems and needs of patients to overcome treatment barriers. It further emphasizes involving associated with families in counselling for constant self-efficacy [45]. Similarly, a study in Ethiopia highlighted the association of treatment support irregularities in treatment uptake and perceived self-efficacy towards adherence to anti-TB treatment [46]. Caregiving responsibilities and perceived reasonable waiting times also showed borderline associations with improved self-management, indicating that both household dynamics and health system efficiency may influence chronic disease management. Our findings correspond to a review that aimed to assess the effectiveness of family-based therapies, which emphasized the importance of family engagement in forming health behaviours and maintaining treatment adherence [47]. Our findings suggest that hypertension management should be understood within a broader systems framework, where structural determinants, health service delivery, and relational engagement interact to shape patient behaviors. Strengthening counselling services within primary health care, expanding the role of community health workers, and improving service delivery efficiency may therefore be critical components of effective hypertension control strategies in disadvantaged communities. From a health systems perspective, these findings support the need to strengthen primary healthcare through improved continuity of care, patient-centred approaches, and community engagement, particularly in resource-limited settings.

4.6. Community-Engaged Hypertension Education and Systems Approaches to Self-Management

This study provides important insights into the challenges of hypertension management in disadvantaged communities and highlights the need for community-engaged approaches to chronic disease education. Although most participants demonstrated high awareness of hypertension and expressed trust in primary health care services, a substantial knowledge–practice gap was observed. While many participants recognized that hypertension can be managed through lifestyle modification, fewer than half reported adherence to recommended dietary practices. Similar patterns have been reported in other low-resource settings, where awareness does not consistently translate into sustained behavior change due to contextual constraints on individuals’ daily lives [48]. Public health research further indicates that health behaviors are shaped not only by individual knowledge but also by broader social and environmental contexts that influence lifestyle choices and health-seeking behavior [49].

Structural barriers further limited participants’ ability to implement recommended lifestyle practices. Low household income, caregiving responsibilities, and distance to health facilities frequently restricted clinic attendance, dietary modification, and opportunities for regular physical activity. These findings align with research demonstrating that socioeconomic conditions strongly influence chronic disease management and may hinder individuals from translating health knowledge into practice [50,51]. Multivariable analyses supported this interpretation: knowledge alone was not significantly associated with lifestyle adherence, whereas engagement with health workers, particularly counselling and advice, was strongly associated with improved behavioral outcomes. Participants who received advice from health workers were significantly more likely to follow recommended dietary practices, suggesting that behavior change is facilitated through relational engagement rather than information alone.

From a community-engagement perspective, effective health education is relational, context-responsive, and embedded within the everyday realities of communities. Community health workers play a critical role in this process because they operate within the social environments of the populations they serve. Their proximity to community networks enables them to provide continuous counselling, reinforce medication adherence, and support lifestyle modification outside formal clinical settings. Evidence indicates that CHWs function as trusted intermediaries between health systems and communities, facilitating health education, improving access to care, and addressing cultural and social barriers to chronic disease management [52,53,54]. Community-engaged models emphasize that sustained behavioural change requires ongoing social support rather than isolated clinical encounters [55]. These approaches align with the WHO HEARTS framework, which promotes team-based care and community participation in cardiovascular disease prevention.

The findings also highlight the potential role of universities as community-embedded partners in health promotion. Community-engaged research frameworks demonstrate that academic institutions can collaborate with primary health care systems and community stakeholders to co-design culturally relevant health education strategies and strengthen implementation of evidence-based interventions [50,52]. Such partnerships facilitate the translation of research into practice by integrating local knowledge, strengthening dissemination pathways, and building sustainable community capacity [56]. Systems-science approaches further emphasize that cardiovascular health disparities are shaped by complex social, environmental, and structural determinants that require coordinated, multi-sectoral responses [57]. Therefore, improving hypertension outcomes in disadvantaged communities requires integrated strategies that strengthen primary health care systems, address structural determinants of health, and expand community-engaged health promotion initiatives.

The model in Figure 1 illustrates how hypertension control emerges from interactions between structural determinants, primary health care system functioning, and community engagement processes. Community-engaged health education, particularly through community health workers and university–community partnerships, facilitates relational knowledge exchange that supports behavioral self-management. This systems approach helps translate hypertension awareness into sustained practices such as medication adherence, dietary modification, and regular clinic attendance.

4.7. Strengths and Limitations

4.7.1. Strengths

This study contributes to the growing body of evidence on hypertension management in disadvantaged communities by integrating descriptive, behavioral, and multivariable statistical analyses. One key strength is the use of multiple analytical approaches, including chi-square tests and logistic regression models, to examine both structural and behavioral determinants of hypertension care. The inclusion of composite indicators of lifestyle adherence and integrated self-management behaviors provides a more comprehensive understanding of chronic disease management than single-behavior measures. Another important strength is the examination of the knowledge–practice gap, which allowed the study to assess whether awareness of hypertension translated into actual lifestyle modification. By incorporating health worker engagement variables into the analysis, the study was able to identify relational aspects of health care delivery that influence patient behavior. Finally, the study provides a systems-oriented perspective on hypertension management by considering structural, behavioral, and health system factors simultaneously. This approach offers valuable insights for strengthening primary health care and community-based chronic disease interventions.

4.7.2. Limitations

This study has several limitations that should be considered when interpreting the findings. The relatively small sample size may have limited the statistical power of the study and contributed to wide confidence intervals in the regression analyses, indicating reduced precision of estimates and potential model instability. As such, the findings from multivariable models should be interpreted as exploratory and hypothesis-generating rather than confirmatory. First, the study employed a cross-sectional design, which limits the ability to establish causal relationships between predictors and hypertension management outcomes. Second, the relatively small sample size may have reduced the statistical power to detect significant associations for some variables, particularly structural determinants such as income and geographic access to care. Third, behavioral variables such as medication adherence, physical activity, and dietary practices were based on self-reported data, which may be subject to recall bias or social desirability bias. Finally, the study was conducted within a specific community context, which may limit the generalizability of the findings to other settings with different socioeconomic or health system characteristics. Future studies with larger sample sizes are recommended to validate these findings. Despite these limitations, the study provides valuable insights into the complex interplay of structural, behavioral, and health system factors influencing hypertension management in disadvantaged communities.

4.7.3. Public Health Implications and Future Research

The findings of this study have important implications for strengthening hypertension control in disadvantaged and resource-constrained communities. Although awareness of hypertension was relatively high, a clear knowledge–practice gap was observed, indicating that awareness alone is insufficient to sustain lifestyle modification and effective self-management. Public health strategies should therefore move beyond information-based education toward relational and community-engaged approaches to chronic disease management. The strong association between health worker counselling and lifestyle adherence highlights the importance of patient–provider interactions within primary health care systems. Strengthening counselling during routine clinic visits and training health workers to provide culturally appropriate guidance on diet, physical activity, and self-monitoring may improve adherence to treatment and lifestyle recommendations. CHWs can further support hypertension management by reinforcing education, promoting medication adherence, and providing counselling within community and household settings. Expanding their role aligns with the WHO HEARTS framework, which promotes team-based care and community participation in cardiovascular disease prevention. The findings also emphasize the need to address structural determinants such as poverty, transport barriers, and caregiving responsibilities. Interventions integrating social support, community-based physical activity initiatives, and improved access to healthy food may help reduce these barriers. Future research should examine hypertension management across diverse populations and evaluate community-engaged and digital health interventions to support long-term adherence and blood pressure control.

5. Conclusions

This study achieved its aim of identifying key socioeconomic and health system barriers to hypertension care, while also assessing knowledge, attitudes, and practices related to treatment adherence and lifestyle modification in a rural primary healthcare setting. The findings highlight that, despite relatively high levels of awareness, significant gaps persist between knowledge and effective self-management practices, driven by structural constraints such as financial limitations, healthcare access challenges, and inconsistent follow-up.

Multivariable analysis further demonstrated that these factors, although not always statistically significant, show consistent directional influence on hypertension self-management, underscoring the complexity of care within resource-limited settings. Importantly, the study advances a community-engaged conceptual framework that integrates behavioural, structural, and health system dimensions, providing a practical foundation for strengthening hypertension education and self-management interventions.

Overall, the findings emphasise that improving hypertension outcomes requires a shift beyond individual-level interventions toward integrated, context-specific strategies that address systemic barriers and actively involve communities in care processes.

The findings suggest that knowledge alone may be insufficient to support effective self-management in resource-constrained settings. Instead, engagement with health workers, particularly through counselling and ongoing patient–provider interaction, was strongly associated with improved adherence to recommended practices. These results underscore the potential importance of relational and context-sensitive approaches to health education within primary health care systems. Structural challenges, including low income, caregiving responsibilities, and geographic barriers to care, were also identified as important contextual factors that may influence hypertension management behaviours. These findings highlight the need to consider broader social determinants of health when designing interventions aimed at improving chronic disease management in underserved populations. While causal inferences cannot be drawn due to the cross-sectional design, this study provides important insights into factors associated with hypertension self-management in disadvantaged settings. The findings may inform the development of integrated, community-engaged strategies that strengthen primary health care delivery, enhance patient support, and address structural barriers to care.

Future research is warranted to explore these associations in larger and longitudinal studies and to evaluate the implementation of contextually appropriate interventions, including community-based and health system strengthening approaches, to support sustained hypertension control.