Hypertension is a public health problem with serious social, economic, and health consequences. The World Health Organization (WHO) estimates that 1 in 3 adults worldwide suffers from hypertension. In Cameroon, the prevalence of hypertension is estimated at 35%, with nearly 17,000 deaths recorded each year. This study aimed to determine the factors associated with the occurrence and complications of hypertension at the Sangmelima Referral Hospital (SRH). A total of 528 patients treated in the cardiology department of the SRH were identified between January and December 2023. The data were analyzed using SPSS 28 software. Binary logistic regression determined the odds ratios and 95% confidence intervals associated with each variable. Differences were statistically significant for a p-value < 0.05. At the SRH, the annual incidence of hypertension was 16.13%. Hypertension was present in 78.8% of patients. The factors associated with the occurrence and complications of hypertension were age (OR=1.028; p=0.003 ), level of education (OR=15.49; p=0.023), marital status (OR=3.859; p=0.04), hypercholesterolemia (OR=2.856; p=0.01), monthly income (OR=0.882; p=0.026), number of dependents (OR=1.231; p=0.025), food security (OR=16.666; p p<0.001), tobacco consumption (OR=8.592; p=0.041), fruit and vegetable consumption (OR=0.027; p=0.031), salt/sugar consumption (OR=8.129; p<0.001), place of residence (OR=4.794; p=0.005), access to essential technologies (OR=8.851; p=0.002), and use of traditional care (OR=3.137; np=0.032). HTA at the HRS is associated with several factors. In order to limit the impact of hypertension, it is crucial to emphasize improving socioeconomic and health conditions.

Hypertension is one of the leading causes of premature death and disability worldwide. It contributes to over 10 million preventable deaths annually, primarily through complications such as stroke, heart failure, myocardial infarction and kidney disease [1-3]. Although once considered a condition of high-income countries, hypertension now disproportion-ately affects low- and middle-income countries (LMICs), where nearly two-thirds of cases are found [4]. Sub-Saharan Africa is particularly affected, with recent estimates suggesting that 25% to 35% of adults aged 25 to 64 are hypertensive [5,6]. Yet awareness, diagnosis, and control rates remain unacceptably low [7].

The growing burden of hypertension in Africa is largely driven by a complex interplay of factors, including population aging, rapid urbanization, lifestyle transitions, and structural weaknesses in health systems. Dietary shifts toward processed foods high in salt and sugar, physical inactivity, increased alcohol and tobacco consumption, and poor health literacy all contribute to the epidemic [8–10]. At the same time, limited access to essential diagnostic tools, preventive care, and affordable medications hampers early detection and long-term control [11].

In Cameroon, national surveys have documented a rising trend in hypertension prevalence — from 18.5% in 1998 to 29.7% in recent years [12-14]. Almost 35% of the adult population is affected; however, regional disparities persist [14-16]. In the southern region, particularly in towns like Sangmelima, socioeconomic hardship, limited dietary diversity, and reliance on traditional medicine remain common. These conditions may increase vulnerability to both hypertension and its complications, yet data on risk factors in such semi-urban settings are sparse.

Since the arrival of a cardiologist at the Sangmelima Referral Hospital (SRH) in 2018, the number of detected cases of hypertension and cardiovascular disease has markedly increased from 157 cases in 2018 to 625 cases in 2023 [17]. This shift offers a valuable opportunity to explore the individual and contextual determinants of hypertension in a high-risk population.

This study aimed to identify the sociodemographic, clinical, behavioral, environmental, and systemic factors associated with hypertension and its complications among patients treated at the SRH, in order to inform more targeted prevention and management strategies.

This was a retrospective cohort study conducted at the Cardiology Department of the SRH, South Cameroon. The study population consisted of 528 patients managed for cardiovascular conditions between January and December 2023.

Data collection was carried out in two complementary phases. The first (passive) phase involved a review of patient medical records to extract sociodemographic, clinical, behavioral, socioeconomic, environmental, and health-related data. In the second (active) phase, structured telephone interviews were conducted with patients or caregivers to collect additional information not available in the records.

Data were entered and analyzed using SPSS version 28. Descriptive statistics were used to summarize the characteristics of the population. Associations between variables and hypertension were assessed using Chi-square tests and Cramer’s V. Binary logistic regression was performed to identify independent factors associated with the occurrence and complications of hypertension. A p-value < 0>

Ethical approval for the study was obtained from the Institutional Ethics Committee of the School of Health Sciences, Catholic University of Central Africa (Ref: 2024/020641/CEIRSH/ESS/MSP). The authoriz-ation for data collection was obtained from the Director of the Hospital. Verbal informed consent was also obtained from all p articipants prior to data collection. Data collection lasted 03 months from January 2024.

3.1. Univariate Descriptive Analysis

3.1.1. Sociodemographic factors

A total of 528 patients were included, with a mean age of 59.5 ± 15.4 years (range: 13–92 years). Women represented 58% of the sample, and 62.7% had only primary level education. Most participants (50.6%) were married, with an average of six dependents per household (Table 1, Figures 1, 2, 3 and 4).

     Note: Values are presented as frequencies and percentages of the study population (n = 528).

Table 1: Distribution of sociodemographic factors in the study population.

Figure 1: Age distribution of the study population.

Figure 2: Weight distribution of the study population.

Figure 3: Weight distribution of the study population.

Figure 4: Distribution of the study population’s number of people in charge.

3.1.2. Clinical and metabolic factors

Clinically and metabolically, 78.8% of the participants were hypertensive, 20.6% were obese, 10% were diabetic, and 18% had hypercholesterolemia (Table 2).

Table 2: Distribution of clinical and metabolic factors in the study population. Note: Values are presented as frequencies and percentages of the study population (n = 528),

3.1.3. Socioeconomic factors

Socioeconomically, 84.8% of patients reported food insecurity, and 54.7% had a very low monthly income between 50,000 and 100,000 FCFA (Table 3).

                Note: Values are presented as frequencies and percentages of the study population (n = 528).

Table 3: Distribution of clinical and metabolic factors in the study population. Note: Values are presented as frequencies and percentages of the study population (n = 528),

3.1.4. Behavioral factors 

Behaviorally, 5.7% were regular smokers, 33.7% regularly consumed alcohol, 26.1% practiced sports weekly, 22.3% consumed fruits and vegetables regularly,

                Note: Values are presented as frequencies and percentages of the study population (n = 528).

Table 4: Distribution of behavioral factors in the study population,

3.1.5. Environmental and cultural factors

Regarding environment and culture, 75.8% of participants live in urban areas, 95.5% of patients are Christian, and 81.3?long to the Fang-Beti cultural area (Table 5).

                Note: Values are presented as frequencies and percentages of the study population (n = 528).

Table 5: Distribution of environmental and cultural factors in the study population.,

3.1.6. Heath factors

In terms of health system access, 83.1% lacked access to essential technologies, and 17.4% reported using traditional medicine. The most common hypertension-related complications were hypertensive heart disease (48.5%), ischemic heart disease (25.2%), heart failure (10.3%), and stroke (4.9%). Housekeepers aged around 60, with primary education, were the most affected by hypertension (Table 6).

                Note: Values are presented as frequencies and percentages of the study population (n = 528).

Table 6: Distribution of health factors in the study population.,

Overall, hypertension is present in 78.8% of participants. 84.8% of these participants live in unfavorable socioeconomic conditions in urban areas (75.8%), and 62.3% regularly consume salty or sugary foods. 78.6% of diseases are detected late and 17.4% recourse to traditional care.

3.2. Bivariate Analysis

3.2.1. Sociodemographic factors

Sociodemographically, age was strongly associated with the onset of hypertension, while marital status, level of education, and gender were weakly associated with hypertension among the study population (Figure 5).

Figure 5: Strength of association between hypertension and sociodemographic factors (A value of Cramer’s V between 0 and 0.1 indicates a weak association; between 0.1 to 0.3 a moderate association, and above 0.3 a strong association).

3.2.2. Clinical and metabolic factors

In clinical and metabolic terms, there was a weak association between hypertension, diabetes, and hypercholesterolemia, respectively among the study population (Figure 6).

Figure 6: Strength of association between hypertension and clinical & metabolic factors (A value of Cramer’s V between 0 and 0.1 indicates a weak association; between 0.1 to 0.3 a moderate association, and above 0.3 a strong association).

3.2.3. Socioeconomic factors

Regarding socioeconomic status, there was a moderate association between hypertension and profession and a weak association between hypertension and participants’ income and food security among the study population (Figure 7).

Figure 7: Strength of association between hypertension and socioeconomic factors (A value of Cramer’s V between 0 and 0.1 indicates a weak association; between 0.1 to 0.3 a moderate association, and above 0.3 a strong association).

3.2.4. Behavioral factors

At the behavioral level, there was a weak association between hypertension and smoking, physical activity and fruit and vegetable consumption, and a moderate association between hypertension and salt or sugar consumption among the study population (Figure 8).

Figure 8: Strength of association between hypertension and socioeconomic factors (A value of Cramer’s V between 0 and 0.1 indicates a weak association; between 0.1 to 0.3 a moderate association, and above 0.3 a strong association).

3.2.5. Environmental and cultural factors

Regarding the physical and socio-cultural environment, there was no association between hypertension and independent variables tested among the study population. 

3.2.6. Health factors

Regarding health, there was a moderate association between hypertension, access to essential technologies, and access to essential medicines, respectively, and a weak association between hypertension and access to therapeutic education among the participants identified (Figure 9).

Figure 9: Strength of the association of hypertension with the health environment (A value of Cramer’s V between 0 and 0.1 indicates a weak association; between 0.1 to 0.3 a moderate association, and above 0.3 a strong association).

Finally, bivariate analysis revealed moderate associations between hypertension and variables such as age, occupation, salt/sugar intake, and access to health technologies. Weaker associations were observed with factors like education level, marital status, income, hypercholesterolemia, and smoking.

3.3. Multivariate Analysis

A binary logistic regression was performed to identify factors independently associated with known hypertension. The full model was significant, χ² (26, N = 528) = 352.51, p < 0>

The following variables were independently associated with hypertension (p < 0 OR=1.028), OR=3.859), OR=15.494), OR=2.856), OR=1.231), OR=16.666), OR=8.592), OR=8.129), OR=0.027), OR=4.794), OR=8.851), OR=3.137). OR=0.882)>

Note: Only significant variables (p < 0 xss=removed xss=removed>< 0>

Table 7: Multivariate logistic regression analysis of factors associated with hypertension.

The final binary logistic regression model predicting the probability p that an individual is hypertensive is: 

logit (p) = − 5.333 + 0.028 x age + 2.740 x level education + 1.351 x marital status + 1.049 x level cholesterol + 0.208 x number dependents + 2.812 x food security + 2.150 x smoking + 2.096 x salt/sugar intake + 1.568 x residence + 2.181 x access health technologies + 1.144 x traditional medicine use − 3.612 x fruit/vegetable consumption − 0.126 x monthly income

Where:

• logit(p) = ln (p / (1 - p)) ;
• p = probability of being hypertensive;
• Binary variables are coded; 1 = presence of the characteristic, 0 = absence;
• The β coefficients correspond to the natural logarithm of the adjusted ORs calculated in the multivariate model.

This equation makes it possible to calculate, for a given individual, the probability of known hypertension based on their sociodemographic, clinical, and behavioral characteristics.