Abstract
Background
Hypertension has significant socioeconomic consequences and adversely affects the health-related quality of life (HRQOL) of people living with hypertension. In Cameroon, although one-third of adults have hypertension, no study has previously examined its impact on the HRQoL of individuals. This study aimed to assess the effect of hypertension on the HRQoL of people living with hypertension followed up in three health facilities in the Dschang Health District.
Methodology
We carried out a comparative analytical cross-sectional study to compare people with a confirmed diagnosis of hypertension (exposed group) with age-, sex-, and location-matched participants without hypertension (unexposed group). Data were collected through face-to-face interviews via a standardized questionnaire including the Health Utilities Index Mark 3 (HUI3) to assess HRQoL. Data were analysed using SPSS software, and the significance threshold was set at 5%. Comparisons between the two groups were performed using multivariable linear regression for continuous HUI3 scores and logistic regression for binary HRQoL outcomes.
Results
A total of 196 participants were enrolled in this study, with 98 in each group. The median age of the subjects was 66 years (IQR: 60-73.25), and most of the participants were females (62.2%). Among chronic comorbidities, diabetes was significantly more common among participants with hypertension (OR = 30.961 [6.87-139.51], p value = 0.001). Compared with those without hypertension, people with hypertension had significantly poorer HRQoL (a difference of 0.2017 in the overall mean HUI score, p < 0.001), and this difference was more than 6 times greater than the clinically important difference of 0.03. Neither a longer duration of hypertension since diagnosis nor the overall burden of comorbidities was associated with a reduction in HRQoL.
Conclusion
These findings underscore the importance of integrating routine HRQoL assessment and comprehensive management of hypertension into hypertension care programs. They also support continued investment in health promotion and primary prevention strategies aimed at reducing the burden of hypertension and diabetes in Cameroon and other low- and middle-income settings.
Keywords: Hypertension, HRQoL, Comorbidities, Duration of hypertension, Dschang West Region of Cameroon
Background
Since the second half of the 20th century, the global epidemiological transition has been characterized by the rise of noncommunicable diseases (NCDs), driven by population aging, rapid urbanization, changes in dietary habits, sedentary lifestyles, and widespread smoking and alcohol use. These trends have led to the development of major cardiovascular risk factors, including obesity, dyslipidaemia, diabetes, and hypertension. Cardiovascular diseases remain the leading cause of death globally, accounting for approximately 17.7 million deaths annually, with hypertension being the primary contributor [1, 2]. Also, according to the global burden of disease study in 2019, NCDs are increasingly imposing a greater disease and economic burden globally and accounts for nine out of the top 10 drivers of increasing disability-adjusted life years (DALYs) [3].
Hypertension is a major public health concern and the leading cause of cardiovascular disease and premature death worldwide. It affects 1.28 billion people aged 30–79 years worldwide, with the majority (two-thirds) living in low- and middle-income countries [4]. By 2025, the global prevalence is projected to reach approximately 60% of adults, approximately 1.56 billion [5]. Sub-Saharan African (SSA) countries are also affected; in 2018, the prevalence ranged from 16% to 40% for adults aged 18 years and over and more than 18% for adults aged 65 years and over [6]. In Cameroon, the overall prevalence is 30.9% (95% CI: 27.0–34.8), with variations by sex (34.3% in men vs. 31.3% in women), place of residence (31.4% in urban vs. 25.4% in rural areas), agroecological zones (35.1% in the tropical highlands vs. 28% in the Guinean savannah), and subnational regions (36.3% in the West to 17.1% in the south) [7]. In 2023, a study conducted in the Dschang Heath District, of Cameroon reported a hypertension prevalence of 57.6% [8].
Hypertension has serious consequences for health, the economy, and society, significantly affecting the quality of life (QoL) of people living with this condition. Hypertension represents a significant economic burden for patients and governments in sub-Saharan Africa. The main cost drivers were combination chemotherapy, hospitalization, and comorbidities such as diabetes [9]. Also, it is important to note that the current outbreak of non-communicable diseases (hypertension, diabetes) is affecting health services in Africa. Not only is this putting pressure on national budgets, on individuals and families, but it is also having a significant negative impact on the quality of life of the people living with these diseases. Due to the lack of adequate care systems, many families are sometimes forced to provide long-term palliative care for their loved ones living with NCDs [10]. Moreover, evidence suggests that comorbidities in people with hypertension reduce the effectiveness of treatment and further decrease health-related quality of life (HRQoL) [11].These comorbidities can be divided into three groups: diseases related to hypertension (overweight and obesity, diabetes, hyperthyroidism, chronic kidney disease), complications of hypertension (atherosclerosis, ischaemic heart disease, myocardial infarction, heart failure, stroke) and conditions unrelated to hypertension (degenerative disc disease, neurotic disorders, chronic obstructive pulmonary disease, and asthma, peptic ulcer disease) [6]. Interestingly, some studies have also shown that hypertension is associated with dengue fever, malaria, and leishmaniasis [12].
Several studies worldwide have documented the impact of hypertension on HRQoL. In Brazil, HRQoL was examined in people with and without hypertension. The study revealed that people with hypertension had a poorer HRQoL, with lower scores in seven of the eight domains of the SF-36 than individuals without hypertension did. A study of the Swedish population also concluded that people living with hypertension had lower perceived HRQoL than normotensive individuals did [13]. In addition, studies conducted in Ethiopia have shown that long-term hypertension and other factors (such as the presence of comorbidities) are associated with decreased quality of life in people living with hypertension [14].
Given the increasing prevalence of hypertension and its growing burden on national budgets, as well as the cost incurred by individuals and families, assessing HRQoL in people with hypertension has become essential. Furthermore, over 74% of African countries, including Cameroon, lack comprehensive national guidelines for the management of hypertension [15].Cameroon also lacks reliable estimates for adequate national surveillance despite the country’s high prevalence of hypertension. However, no study has comprehensively evaluated the impact of hypertension on HRQoL using a validated instrument. Therefore, this study aimed to assess the HRQoL of people living with hypertension attending three health facilities in the Dschang health district compared with that of normotensive subjects and identify potential predictors of the QoL. The findings of this study are expected to provide evidence to support policy makers in developing cost-effective hypertension prevention and management strategies both at the individual and community levels, thereby reducing the burden of hypertension on national budgets, individuals and families.
Methods
Study Design
We carried out a comparative analytical cross-sectional study in three health facilities in the town of Dschang. Exposed group were defined as any person aged 21 and over, diagnosed with hypertension for at least three months, and followed as outpatients in one of the study facilities. Unexposed were people aged 21 and over without hypertension matched to the exposed group according to age, sex, and residential location and recruited in the community. The study was conducted over a period of ten months (from September 2023 to July 2024), with data collection occurring from April to May 2024.
Study Site and Study Population
This study was carried out in three health facilities in the Dschang Health District: the Dschang Regional Annex Hospital (a third-category health facility and the main referral hospital in the District), Saint Vincent de Paul’s Catholic Hospital of Dschang (a faith-based health facility located in the Siteu Health Area), and our Ladies of Lord Batsintgla’a Hospital (also a faith-based health facility located in the Doumbouo Health Area, a rural zone). These three health facilities are the only facilities responsible for the follow-up of people living with hypertension in the town of Dschang.
This study included adults aged 21 years and over who were divided into two groups: patients who were diagnosed with hypertension and those who were followed up at one of the three health facilities. The unexposed group was constituted by people without hypertension who were recruited from the same community as the patients.
Sample Size and Sampling Technique
The sample size was calculated via the Fleiss formula for comparing two independent groups. In the absence of baseline data on the exposure factor, we assumed that 50% of people with hypertension would have a perceived poor HRQoL. Using a 95% confidence level, a 5% margin of error, an estimated prevalence of hypertension of 30% in Cameroon, and a 1:1 ratio between exposed and unexposed participants, the minimum required sample size was 196 participants (98 per group). An exhaustive sampling strategy was applied, including all eligible individuals who met the inclusion criteria and provided informed consent. Exposed and unexposed participants were matched by age, sex, and residential area.
Recruitment Procedures
After obtaining ethical clearance and administrative authorization, people living with hypertension followed in these three health facilities were approached. Signed informed consent was obtained from each participant after the objectives and procedures of the study were explained.
Inclusion Criteria
Patients
Adults aged ≥ 21 years with a confirmed diagnosis of hypertension of more than three months, followed in one of the selected hospitals of the study, who were able to respond and who provided written consent. Eligible exposed participants were identified from a series of patients coming for consultation in the hospitals targeted by the study. Those willing to take part in the study were interviewed immediately or at a later agreed upon time and place, with contact details collected.
Unexposed Group
Adults aged ≥21 years, of the same sex and age range (± 5 years) as the matched exposed participants, who lived in the same residential areas as the exposed participants, without a confirmed diagnosis of hypertension, were able to respond, provided written consent, and were able to respond.
Exclusion Criteria
Both in exposed and unexposed groups, we excluded individuals with known diagnosis of cancer; those who withdrew from the study before completion; and participants with incomplete information for variables of interest.
Variables
The dependent variable was the HRQoL score, whereas the independent variables included socio-démographique variables (age, sex, marital status, occupation, education level, monthly revenue and number of people per household) and clinical variables (Duration since diagnosis of hypertension, smoking, alcohol, alcohol index, type of treatment, duration of treatment, target organ complications and comorbidities).
Data Collection Instrument
Data were collected via a structured interviewer-administered questionnaire. HRQoL was measured via the standardized Health Utilities Index Mark 3 (HUI3), which analyses eight attributes: vision, hearing, speech, mobility, dexterity, emotion, pain, and discomfort. Each attribute reflects a functional capacity [16], and the eight attributes are combined into a single score via the multiattribute utility function:
| u = 1.371* (b1* b2* b3* b4* b5* b6* b7* b8) - 0.371 |
where u is the HUI3 overall score and bi is the single attribute score.
The HUI3 scale ranges from − 0.36 to 1.00, where 0.0 represents death, negative scores indicate health states considered worse than death, and 1.00 represents the highest level of functioning. Differences of 0.03 or more in overall HUI3 scores are considered to be clinically significant [16]. The participants were also categorized into disability levels based on HUI score: 1.00 for normal, 0.89–0.99 for mild, 0.70–0.88 for moderate and < 0.70 for severe. The questions referred to the “last 7 days”.
Operational Terms
People Living with Hypertension
People with a physician confirmed diagnosis of hypertension for more than 3 months at any stage of hypertension, with or without complication/comorbidity, who were taking an antihypertensive drug and attending the out-patient health facilities targeted for the study.
Comorbidities/Health Problems
Classified into two subgroups: conditions of temporal duration and long-term conditions.
Health-related Quality of Life
HRQoL is the extent to which one’s usual or expected physical, emotional, and social well-being are affected by a medical condition or its treatment [17]. Good or poor health-related quality of life was defined according to the HUI3 scoring system (scale ranges from − 0.36 to 1.00, where 0.0 represents death, negative scores indicate health states considered worse than death, and 1.00 represents the highest level of functioning).
Long Diagnosis Duration of Hypertension
Clinical studies often define longstanding hypertension as a chronic condition lasting 5, 10, or more years, which significantly increases the risk of heart disease and stroke. A long duration of hypertension in this study was considered as living with hypertension for 10 years or more [18].
Statistical Analysis
The collected data were entered into an input mask designed via Cs-Pro software and subsequently exported into SPSS version 20 software for statistical analysis. Age was summarized using the median and interquartile range (IQR) because of its non-normal distribution. The HUI3 utility score was summarized using the mean and standard deviation to facilitate comparison with previous studies. Differences in age and HUI3 utility scores between participants with and without hypertension were assessed using the Mann–Whitney U test, whereas categorical variables were compared using the Chi-square test or Fisher’s exact test, as appropriate. Multivariable linear regression was used to assess the association between hypertension status and the continuous HUI3 utility score. In addition, multivariable logistic regression was performed as a secondary analysis when HRQoL was dichotomized into good and poor HRQoL. All statistical tests were two-sided, and a p-value < 0.05 was considered statistically significant.
Ethical Considerations
Ethical approval was obtained from the Regional Human Health Ethics Committee of the West Region (Reference N° 2024/CE/CRESH-OU/VP). Prior authorization for the research was obtained from the directors of the Dschang Regional Annex Hospital Saint Paul’s Hospital or Our Ladies of Lords Hospital Batsingla’a. Additionally, permission to use the HUI3 questionnaire was obtained. This study was carried out in strict compliance with the declaration of Helsinki: respondents’ rights to withdraw from the study, confidentiality, participant privacy, risks and benefits involved in the study were duly explained to participants, comprising 98 people with hypertension (exposed group) and 98 people without hypertension (unexposed group).
Results
A total of 215 people approached, of whom 200 agreed to participate, yielding a participation rate of 93%. After excluding four participants because of for incomplete data for variables of interest, 196 participants were included in the final analysis, comprising 98 people with hypertension (exposed group) and 98 people without hypertension (unexposed group).
Socio-demographic Characteristics
The two study groups were homogenous in terms of age, sex, level of education, occupation, number of people living in a whole house, monthly income, and smoking status (all p > 0.05). The median age of the participants was 66 (IQR: 60–73.25) years, with 66.54 (IQR: 60–70.6) years for people with hypertension and 65.63 (IQR: 59.57–71) years for people without hypertension. The age range spanned from 32 to 90 years. Most of the participants were females (62.2%), and more than two-thirds of the participants were married (68.87%). The average number of people living in a household was 4.85 ± 3.08. In terms of education, most of the participants had completed primary school (77.5%). With respect to income, approximately 80% of households earn less than one minimum wage (41,000 CFA francs, equivalent to USD 67.71). A detailed comparison of socio-demographic characteristics between people with and without hypertension is presented in Table 1.
Table 1.
Sociodemographic characteristics of the participants in the study
| Features | Modalities | HTN + n (%) |
HTN - n (%) |
p value |
|---|---|---|---|---|
|
Age range (years) |
< 40 | 2 (2.0) | 2 (2.0) | 0.842 |
| [40–64] | 38 (38.8) | 42 (42.9) | ||
| 65+ | 58 (59.2) | 54 (55.1) | ||
| Sex | Male | 37 (37.8) | 37 (37.8) | 1.00 |
| Female | 61 (62.2) | 61 (62.2) | ||
| Marital status | Bachelor | 1 (1.0) | 7 (7.1) | 0.070 |
| Married | 65 (66.3) | 70 (71.4) | ||
| Divorce | 4 (4.1) | 2 (2.0) | ||
| Widower (widow) | 28 (28.6) | 19 (19.4) | ||
| Cohabitation | 0 (0.0) | 0 (0.0) | ||
| Level of education | Never been to school | 18 (18.4) | 14 (14.3) | 0.660 |
| Primary | 40 (40.8) | 36 (36.7) | ||
| Secondary | 32 (32.7) | 40 (40.8) | ||
| Superior | 8 (8.20) | 8 (8.20) | ||
| Occupation | Working | 60 (61.2) | 68 (69.4) | 0.230 |
| Not working | 38 (38.8) | 30 (30.6) | ||
| Monthly income | < 41000frs | 65 (66.3) | 72 (73.5) | 0.311 |
| 41000-100,000frs | 23 (23.5) | 22 (22.4) | ||
| 100,000-250,000frs | 6 (6.1) | 4 (4.1) | ||
| 250,000-500,000frs | 2 (2.0) | 0 (0.0) | ||
| 500,000-1000,000frs | 2 (2.2) | 0 (0.0) | ||
| > 1000,000frs | 0 (0.0) | 0 (0.0) | ||
| Smoking status | Nonsmoker | 94 (95.9) | 98 (100.0) | 0.121 |
| Smoking | 4 (4.10) | 0 (0.0) | ||
| Alcohol consumption | Nonconsumer | 76 (77.6) | 96 (98.0) | 0.0001 |
| Consumer | 22 (22.4) | 2 (2.0) |
HTN+ people living with hypertension, HTN- people without hypertension
Clinical Characteristics of People Living with Hypertension
Among people with participants, fewer than half (44 participants, 46.3%) reported living with hypertension for less than 5 years. The duration of hypertension since diagnosis ranged from 5 months to 40 years, with a mean follow-up period of 8.6 years. Monotherapy was the most frequently prescribed treatment regimen, used by 61.2% of the participants. Table 2 summarizes the clinical characteristics of the participants living with hypertension.
Table 2.
Clinical characteristics of people living with hypertension
| Variable | Modality | Frequency | Percentage |
|---|---|---|---|
| Duration since diagnosis of hypertension (years) | < 5 | 44 | 46.3 |
| [5–10] | 25 | 26.3 | |
| > 10 | 26 | 27.4 | |
| Treatment duration | < 5 | 46 | 46.9 |
| [5–10] | 24 | 24.5 | |
| > 10 | 28 | 28.6 | |
| Type of treatment | Monotherapy | 60 | 61.2 |
| Dual therapy | 17 | 17.3 | |
| Triple therapy | 21 | 21.4 |
Distribution of Health Problems Among People Living with Hypertension Compared with People Without Hypertension
Among the participants, the most common acute illnesses were cough and malaria, with no significant difference between participants with and without hypertension. In terms of chronic diseases, notable differences were observed; lower back pain was more prevalent among participants without hypertension (42.9%) than among those with hypertension (19.4%); conversely, leg ulcers, chronic kidney disease, diabetes (39.2%), and obesity were reported exclusively among participants with hypertension.
Association Between Hypertension and HRQoL
HRQoL scores in people living with hypertension versus those without hypertension
Table 3 presents the comparison of HRQoL between people with hypertension and those without hypertension, expressed via the HUI3 score. After adjustment for potential confounders, people living with hypertension had poorer HRQoL scores in seven of the eight HUI attributes, except for speech. They also had a significantly lower overall HUI3 utility score than participants without hypertension. The adjusted mean difference in the overall HUI3 score between the two groups was 0.202, which exceeded the clinically important difference of 0.03 by more than six fold. A statistically significant difference in the overall HUI3 score was observed between men and women (p < 0.05). Regarding the severity of impairment, 61.1% of people with hypertension were severe disability, compared with 35% of those without hypertension.
Table 3.
Mean scores and regression coefficients for the associations between hypertension and HUI3 scores
| Measures | HTN+ Mean ± SD |
HTN- Mean ± SD |
P value* | β- coefficients [95% CI] Adjusted | p value** |
|---|---|---|---|---|---|
| Vision | 0.897 ± 0.133 | 0.959 ± 0.067 | 0.0001 | 0.835 [0.779,0.890] | 0.001 |
| Hearing | 0.993 ± 0.044 | 0.999 ± 0.007 | 0.399 | 0.987 [0.966,1.000] | 0.001 |
| Speech | 1.086 ± 0.910 | 1.00 ± 0.001 | 0.562 | 1.173 [ 0.976,1.594] | 0.331 |
| Mobility | 0.947 ± 0.120 | 0.982 ± 0.054 | 0.043 | 0.912 [0.860,0.957] | 0.001 |
| Dexterity | 0.824 ± 0.930 | 1.00 ± 0.0001 | 0.0001 | 0.997 [0.989,1.00] | 0.001 |
| Emotion | 0.969 ± 0.973 | 1.000 ± 0.0001 | 0.0001 | 0.939 [0.899,0.976] | 0.001 |
| Memory | 0.876 ± 0.154 | 0.862 ± 0.162 | 0.857 | 0.891 [0.812,0.956] | 0.001 |
| Pain | 0.899 ± 0.124 | 0.962 ± 0.055 | 0.000 1 | 0.838 [0.783,0.884] | 0.001 |
| Average total score | 0.5107 ± 1.14 | 0.712 ± 0.24 | 0.001 | 0.239[-0.039,0.37] | 0.03 |
HUI 3 health utility index score 3, HTN + people living with hypertension, HTN- normotensive individuals, β linear regression coefficient, p* unadjusted p value from the Mann‒Whitney test, p** adjusted p value from linear regression
Risk of poor HRQoL among people living with hypertension
More than half of the population with a poor QoL had hypertension (53%), whereas 47% of the population without hypertension didn’t. Living with hypertension increased the odds of having a poor QoL by approximately 8.43 times (ORa 8.43 [95% CI 1.79–39.68]; p < 0.007). The binary logistic model confirmed that living with hypertension significantly increased the likelihood of having a poor HRQoL.
Association Between Duration of hypertension Since Diagnosis and HRQoL
No significant association was found between the duration of hypertension since diagnosis and poor QoL (OR 0.36 [95% CI: 0.022–6.103]; p = 0.475). Among the 98 people living with hypertension included in this study, more than half (54.2%) reported having at least one chronic disease. Among the respondents, 17.1% lived with hypertension alone, and 28.1% had two or more comorbid conditions. All chi-square tests and logistic regression models examining the associations between comorbidity status (one, 2 or more comorbidities) and HRQoL did not find any associations.
Variables included in the multivariable linear regression model were selected based on their significance in the bivariate analysis (p < 0.05) and their established clinical relevance as potential predictors of HRQoL among individuals with hypertension. Specifically, diabetes, obesity, chronic kidney disease, leg ulcer, back pain, age ≥ 65years, revenue was included in the model because they were significantly associated with HUI3 scores in the bivariate analysis and are recognized in the literature as important factors that may influence HRQoL. Their inclusion in the multivariable model allowed adjustment for potential confounders and identification of variables independently associated with HUI3 scores. After the logistic regression model was applied, a statistically significant association was observed between diabetes and QoL. Hence, the presence of this condition in people living with hypertension alters their HRQoL. These results are presented in Tables 4 and 5 below.
Table 4.
Bivariate analysis between the duration of hypertension since diagnosis and HRQoL
| Variable | Modality | Quality of life | OR c [95% CI] | p value | |
|---|---|---|---|---|---|
| Bad n (%) | Good n (%) | ||||
| Duration since diagnosis of hypertension | < 5 years | 44 (47.3) | 0 (0.0) | - | - |
| 5–10years | 24 (25.8) | 1 (50.0) | 0.348[0.02–5.780] | 0.459 | |
| > 10 years | 25 (26.9) | 1 (50.0) | 0.368[0.022–6.103] | 0.475 | |
ORc crude odds ratio, ORa adjusted odds ratio
Table 5.
Association between chronic comorbidities and health-related quality of life in people living with hypertension
| Variable | Modality | ORc [95% CI] | p value | OR a [95% CI] | p value |
|---|---|---|---|---|---|
| Chronic health problems | Chronic Kidney disease | 16.16 [2.08–125.54] | 0.001 | - | 0.99 |
| Obesity | 2.08 [1.79–2.40] | 0.014 | - | 0.99 | |
| Diabetes | 30.91 [7.19–132.90] | 0.001 | 30.96 [6.87–139.51] | 0.001 | |
| Depression | 1.71 [1.47–1.98] | 0.01 | 0.01 [0.01–0.03] | 0.99 | |
| Low back pain | 0.32 [0.16–0.79] | 0.001 | 0.11 [0.03–0.39] | 0.001 |
ORccrude odds ratio, ORaadjusted odds ratio
Discussion
Health-related quality of life (HRQoL) reflects how people perceive the impact of their health status on daily life. It is a concept that includes physical, mental, and social well-being. Our findings show that individuals with hypertension had significantly poorer HRQoL across seven of the eight attributes of the HUI3 and the overall utility index than did people without hypertension. Moreover, diabetes and low back pain were associated with low HRQoL in people with hypertension. Nevertheless, neither the duration of hypertension nor the treatment was associated with reduced HRQoL in this population.
These results are consistent with several studies conducted across diverse settings around the world [2, 19–24], confirming the detrimental impact of hypertension on the HRQoL of people living with hypertension; these studies have assessed HRQoL in people with hypertension compared with people without hypertension. In contrast, some studies conducted in Mekelle, North Ethiopia, Shaanxi, China, and Nigeria have focused on within-group determinants rather than comparisons with people living without hypertension. Both approaches are complementary: while comparative studies demonstrate the additional burden imposed by hypertension, within-group analyses reveal specific risk factors that might be targeted for tailored interventions.
Our study also reported a significant association between older age (≥ 65 years) and poor HRQoL in individuals with hypertension, echoing findings from Brazil, China, and Nepal n [24–26]. Ageing causes multiple psychological, mental, and social changes that can amplify the negative impact of chronic conditions such as hypertension [26]. Possible explanations include the presence of other comorbidities, cognitive impairment associated with aging, and financial constraints due to postretirement, which can limit access to proper health care and a healthy lifestyle. Addressing these issues through a comprehensive approach that considers social and psychological support and an integrated care approach could improve the QoL and overall health outcomes of older people living with hypertension.
With respect to lifestyle risk factors, we did not observe significant associations between smoking, alcohol consumption, and HRQoL in either group. This result contrasts with those of other authors [2, 25, 27], who reported that smoking and alcohol consumption had a negative effect on HRQoL. This difference could be explained by several factors. First, the majority of our participants were older adults (median age of 66 years compared with 50–59 years in the other studies), which may reduce the impact of lifestyle risk factors on HRQoL. Second, alcohol consumption was relatively uncommon in our population, with only 24% reporting alcohol use. Similarly, only four participants were smokers, limiting our ability to detect an effect. Finally, the smaller sample size of our study compared with the much larger samples in previous studies (672, 3509, and 919 participants, respectively) may have reduced the statistical power to identify significant associations. Together, these factors could mask or underestimate a possible relationship between smoking, alcohol consumption, and HRQoL.
Interestingly, a long duration of hypertension (defined as ≥ 10 years since diagnosis) was not associated with poorer HRQoL. This finding should, however, be interpreted with caution, as categorizing hypertension duration may have reduced our ability to detect potential dose-response relationships. Studies with larger sample sizes should explore this association using more detailed duration categories. This finding aligns with studies from Nigeria and others from Lebanon [2, 28–30]. One possible explanation is that people with long-term hypertension adapt over time, which might help maintain HRQoL despite the long duration. This implies that instead of focusing only on disease duration, interventions should target factors that directly affect HRQoL, such as lifestyle modifications and mental health support. Additionally, health programs should emphasize primary prevention (early detection) and management.
Comorbidities were common among participants with hypertension, with more than half (54.2%) reporting at least one chronic condition. However, comorbidities (except diabetes) were not significantly associated with poorer HRQoL in our study. These findings are different from those of previous studies conducted in Shanghai, China, Turkey, Croatia, and Northeast Ethiopia, where comorbidities might have had a significant impact on HRQoL [19, 23, 31, 32]. Possible explanations for our findings include effective management of chronic conditions, stronger family or community support, or specific sample characteristics.
Although this study provides novel insights as the first to formally assess the health-related quality of life (HRQoL) of people living with hypertension compared with individuals without hypertension in our context in Cameroon, it has some limitations that should be considered. First, because of its comparative cross-sectional design, the study does not allow conclusions about causal relationships between hypertension and HRQoL. Second, this was a facility-based study in which people living with hypertension were consecutively recruited from three health facilities. Consequently, the findings may not be fully representative of all people living with hypertension in the community, particularly those who do not seek healthcare. In addition, although participants were matched by age, sex, and place of residence, the influence of unmeasured confounding factors cannot be completely ruled out. Recall bias may also have occurred because some questionnaire items required participants to report events that had taken place several weeks earlier. Finally, the wide confidence intervals observed for some estimates were likely attributable to the small number of participants in certain subgroups, particularly those with hypertension who reported good HRQoL, reducing the precision of the estimated odds ratios.
Conclusion
This study demonstrated that hypertension is associated with a substantial reduction in HRQoL among adults in the Dschang Health District. Compared with people without hypertension, people living with hypertension reported poorer scores across most HUI3 attributes and a significantly lower overall utility index. Although the overall burden of comorbidities was not independently associated with HRQoL, diabetes, chronic kidney disease, and low back pain were identified as significant predictors of poor HRQoL. These findings underscore the importance of integrating routine HRQoL assessment and comprehensive management of hypertension and coexisting chronic conditions into hypertension care programs. They also support continued investment in health promotion and primary prevention strategies aimed at reducing the burden of hypertension and diabetes in Cameroon and other low- and middle-income settings.
Acknowledgements
The authors would like to thank the participants for their time and information for this study. We are also grateful to the healthcare staff working at the Dschang Regional Annex Hospital, Saint Vincent de Paul’s Catholic Hospital of Dschang, and Our Lady of the Lord’s Hospital, Batsintgla’a, for their generous support during the study. We are equally grateful to Health Utilities, Inc., Ontario, Canada, for granting us the licence to use the Health Utility Mark 3 questionnaire as a tool for our study.
Author Contributions
OSN was involved in study design, data collection, statistical analyses, and drafting the manuscript; CMT & SRSJ were involved in study design, data collection and analysis supervision, and manuscript revision. ZTT contributed to the statistical analyses and revised the manuscript; FGY was involved in data collection; SPC and GCMN critically revising the manuscript for important intellectual content. All the authors approved the final version of the submitted manuscript.
Funding
This study was conducted without external funding or grant.
Data Availability
The dataset supporting the conclusions of this article is available upon request.The Health Utilities Index Mark 3 (HUI3) questionnaire used as a tool for this study is available from Health Utilities Inc., Dundan Ontario, Canada, but restrictions apply to the availability of these data, which were used under licence for the current study and are not publicly available. Data are, however, available from the authors upon reasonable request and with permission from [Health Utilities Inc., Dundan Ontario, Canada].
Declarations
Ethics Approval
Ethical approval was obtained from the Regional Ethics Committee of research for Human Health of the West Region, Cameroon (Reference N° 2024/CE/CRESH-OU/VP) which belongs to the National Ethics Committee of Research for Human Health.
Consent for Publication
Not applicable (N/A).
Competing Interests
The authors declare that they have no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The dataset supporting the conclusions of this article is available upon request.The Health Utilities Index Mark 3 (HUI3) questionnaire used as a tool for this study is available from Health Utilities Inc., Dundan Ontario, Canada, but restrictions apply to the availability of these data, which were used under licence for the current study and are not publicly available. Data are, however, available from the authors upon reasonable request and with permission from [Health Utilities Inc., Dundan Ontario, Canada].