Factors associated with poor glycemic control in patients with type 2 diabetes at the Bafoussam Regional Hospital: a preliminary cross-sectional study at the Bafoussam Regional Hospital (Cameroon)

Introduction

Diabetes is a group of metabolic diseases characterized by hyperglycemia resulting from abnormalities in insulin secretion, insulin action or both (1). It is classified into several subtypes namely type 1 diabetes (the least frequent, accounting for less than 10%), type 2 diabetes (T2D) (much more frequent between 90% to 95% of cases and currently representing one of the health emergencies in the world), secondary diabetes and gestational diabetes (1). Rapid socio-economic transition with urbanization and industrialization are the main causes of the global diabetes epidemic (2). In 2021, International Diabetes Federation (IDF) estimated that there were 537 million diabetes patients aged 20–79 years worldwide with an estimated prevalence of 9.3%, which is expected to reach 10.2% (643 million) by 2030 and 10.9% (784 million) by 2045. Moreover, 240 million adults living with diabetes are undiagnosed (3).

Prevalence is higher in urban areas than in rural areas with the highest rise has been noted in low- and middle-income countries (4). Diabetes accounted for at least $966 billion in expenditure in 2021. Africa is expected to experience the largest increase in the number of diabetes cases worldwide, from 24 million cases in 2021 to 55 million in 2045 (3). The prevalence (and burden) of T2D is rapidly increasing; according to IDF, this prevalence was estimated at 4.5% in 2021 in Africa, with 4.8% of cases in Cameroon where a local study estimated the prevalence of diabetes in Cameroon in 2018 at 5.8% (5). Moreover, the prevalence of undiagnosed diabetes in Africa in the same year was estimated at 53.6%. In 2021, an estimated 6.7 million deaths among adults aged 20 to 79 were attributed to diabetes; and diabetes contributed to 11.3% of global deaths (4). These deaths are mainly related to complications of diabetes, although all-cause mortality is higher among diabetes patients (6,7). Diabetes-related complications explain the increase in morbidity, disability and mortality and pose a threat to the economies of all countries, particularly developing countries (8). Vascular complications of diabetes result from unsatisfactory long-term glycaemic control. They can be classified according to the size of the vessels involved as micro-vascular (such as diabetic retinopathy, nephropathy and neuropathy) or macrovascular (such as cerebrovascular, coronary and peripheral arterial diseases) (8).

Large-scale global clinical studies of diabetes complications have widely evaluated glycated hemoglobin (HbA1c) as an indicator of good glycaemic control (9). In addition, HbA1c is a valuable indicator of treatment effectiveness (10) and should be measured at least every 3 months when blood glucose targets are not met and when diabetes treatment is adjusted or modified (11). Many trials recommend that glycaemic targets be individualized according to the fragility or functional dependence of the individual and his life expectancy; hence a range of HbA1c values between 7–8.5% (12,13), with a 7% average target to reduce the risk of complications (14). In developing countries, glycaemic control in people with T2D has remained suboptimal (15).

The reasons for poor glycaemic control in T2D patients are complex and multiple (12). In Western countries, the most common factors associated with poor glycaemic control are: prolonged duration of diabetes, poor adherence to treatment, low level of education, presence of comorbidities, poor management of self-medication care, smoking, physical inactivity, type of treatment, cost of care, age between 40 and 60 years, co-existence of factors in the same subject (16-19). Numerous studies targeted factors associated with poor glycaemic control in sub-Saharan Africa, but to the best of our knowledge there are no data in Cameroon, and in its West Region in particular, that has assessed the factors associated with poor glycaemic control (20-27).

Methods

Study design

A cross-sectional study was carried out over 6 months (January to June 2022) at the Bafoussam Regional Hospital. The data collected using a data sheet were transferred Microsoft Office Excel 2013 and analyzed by the Epi info software version 7.2.2.16. This study targeted patients with T2D attending the Endocrinology Department of the Bafoussam Regional Hospital.

Study setting

Our study took place at the Bafoussam Regional Hospital, created in 1953, located in the West Region of Cameroon, MIFI department, Bafoussam II district and the TYO-city district. It covers an area of 10,000 m², it is a 3rd category hospital and 2nd reference hospital. It consists of 8 departments, 17 buildings, 256 beds and 260 staff. Specialized endocrinology consultations are held twice a week. The Endocrinology and Diabetology Department has an endocrinologist, a general practitioner, a nutritionist and 8 nurses with 15 beds.

Study population

This study targeted patients with T2D attending the Endocrinology and Diabetology Department of the Bafoussam Regional Hospital. Patients with T2D were freely approached during their stay in the department and those consenting to participate were included in the study.

Sample

The sample size was calculated using Lorenz’s formula (Stat Calc of EPI Info Software). Using the national prevalence of 4.8% in Cameroon and a 5% accepted margin of error, the minimal sample size estimated was 70 participants.

Recruitment: patients with diabetes coming spontaneously for consultation or follow-up were approached for their recruitment. At first contact, an explanation session was conducted on the purpose, procedure, advantages and disadvantages of participation in the study. Participants could then express all their concerns. The informed consent form was submitted to them for careful reading, after which everyone was free to sign or not.

Inclusion and exclusion criteria

Inclusion criteria included: patients with T2D, aged over 21 years of age, followed at the Bafoussam Regional Hospital, who had an HbA1c measurement (<3 months) and whose informed consent to carry out this study had been obtained.

Exclusion criteria excluded: pregnant women, those with an acute illness, participants with incomplete data or who withdrew their consent during the study.

Data collection

Data collection took place from February to June 2022, after obtaining administrative authorization and ethical clearance. We obtained the informed consent from these participants following an explanation of the study’s purpose. Later on, a pre-designed and pre-tested questionnaire was administered by the principal investigator in a face-to-face interview lasting 10 minutes on average.

Collected variables included:

• Socio-demographic (age, sex, education level, income).
• Clinical characteristics (duration of diabetes since diagnosis, type of treatment, adherence to lifestyle and diet measures, cost of care, type of complications).
• Physical examination data [measurement of weight in kg, height in cm, body mass index (BMI), waist circumference in cm, arterial pressure measurement].
• HbA1c levels.

Operational definitions:

• Patients with T2D: fasting glucose 126 mg/dL (7.0 mmol/L) twice, or random glucose 200 mg/dL (11.1 mmol/L) in the context of signs of hyperglycemia, or plasma glucose concentration at 2 hours 200 mg/dL (11.1 mmol/L) after 75 g of anhydrous glucose in an oral glucose tolerance test (OGTT) or HbA1c greater than 6.5% by high-performance liquid chromatography (HPLC) method; according to the criteria defined by the American Diabetes Association (1). People who had already been diagnosed or treated for diabetes were also considered diabetic.
• Poor glycemic control: was defined by HbA1c above or equal to 7% (28).
• Hypertension: systolic blood pressure (SBP) 140 mmHg and/or diastolic BP (DBP) 90 mmHg. People who had already been diagnosed or treated for hypertension were also considered hypertensive.
• Obesity: BMI ≥30 kg/m²; overweight BMI between 25 and 29.9 kg/m².
• Sedentary: absence of any physical activity or activity less than 5 times a week for a minimum of 30 minutes.
• Android obesity: waist circumference >94 cm in men or 80 cm in women.
• Current excessive alcohol consumption: consumption of more than 30 g/day in men and 20 g/day in women.
• Current smoking: consumption of at least one cigarette per day.
• Low socio-economic level: a monthly income below 167 USD defines a low social class. Other social classes are classified on average (by income between 167 and 334 USD) and high (by income above this amount) (29).
• Regular follow-up: at least one medical visit per quarter.

Data analysis

The data collected using a data sheet were entered and analyzed by Epi info software version 7.2.2.16 and Microsoft Office Excel 2013. The Khi Two Statistical Test and the Fisher Exact Test were used to look for the association between qualitative variables with a significance threshold set at 5%. Multiple logistic regression was used to identify associated factors independent of poor glycemic control.

Ethics approval and consent to participate

The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by the West Regional Ethics Committee (No. 2022/06/016/CE/CRERSH-OU/VP) and the Bafoussam Regional Hospital (No. 443/L/MINSANTE/SG/DRSPO/HRB/D). Patients were free to participate in the study without any external constraints. Informed consent was obtained from all individual participants.

Results

Participants

We included 70 participants with T2D (Figure 1) with a median age was 63.5 (45–87) years among which 60% were women against 40% men, with a sex ratio of 0.67. Patients were mostly retired (18.57%) and housewives (17.14%). They lived mainly in urban areas (51.43%). Many of them were married (57.14%) and Christian (81.43%) with a monthly income of less than 100,000 FCFA (168.0 USD) (75.71%) (Table 1).

Figure 1 Participants flow chart.

Main data (factors associated with poor blood glucose control)

A total of 48 (68.6%) participants had poor glycaemic control (Figure 2). In bivariate analysis, factors associated with poor glycaemic control in patients with diabetes were female gender (P=0.03), a monthly income 100,000 FCFA (168.0 USD) (P<0.001), a primary education level (P=0.007), among those not regularly followed up (P<0.001), among those not regularly self monitoring their glycemia (P=0.02) and those not regularly followed up (P<0.001), the use of herbal medicine (P<0.001), dietary measures (P=0.001), DBP (P=0.02), SBP (P=0.02), comorbidities (P=0.02) and complications (P<0.001) (Table 1). After multiple logistic regression, it appears that the risk of poor glycaemic control was greater in participants not regularly followed-up [adjusted odds ratio (aOR) =14; 95% confidence interval (CI): 1.16–169; P=0.04]. However, it was very low in patients using phytotherapy (aOR =0.06; 95% CI: 0.01–0.42; P=0.004), in those with a monthly income of more than 100,000 FCFA (168.0 USD) (aOR =0.04; 95% CI: 0.002–0.82; P=0.03) and those observing treatment (aOR =0.07; 95% CI: 0.012–0.38; P=0.002) relative to others (Table 2).

Figure 2 Glycemic control among patients with type 2 diabetes.

Discussion

The general objective of our work was to identify factors associated with poor glycaemic control among patients with diabetes followed up at the Bafoussam Regional Hospital. Specifically, we aimed to identify socio-demographic characteristics, to determine the level of glycaemic control and to identify the factors associated with poor glycemic control in patients with diabetes followed at the Bafoussam Regional Hospital. We found an elderly population, predominantly female, living mainly in urban areas and on low incomes. More than two-thirds of participants had poor glycaemic control. The factors associated with poor glycaemic control were: irregular follow-up, use of herbal medicine, low income and treatment adherence.

The study population had a median age of 63.5 years with female predominance. This result is similar to that of Simeni Njonnou et al. conducted in Cameroon in 2020 which had recruited 80 patients with 67% women, a median age at 62.4 years (extreme 39–82 years), the dominant age group was 56–65 years (30). T2D mellitus imposes a considerable economic burden that most directly affects patients in low- and middle-income countries. Our results suggest that a high socio-economic status above 168.0 USD improves glycaemic control in patients with diabetes. Established studies on the subject corroborate our results (31). Diabetes is a serious handicap to the economy and quality of life of patients, due to the enormous costs of medical and therapeutic care, which is why many patients are unable to pay the exorbitant cost of care. It is with this in mind, that Afroz et al., in 2018 in Australia, estimated that the average annual cost (direct and indirect) per person for the treatment of T2D ranged from 29.91 USD to 237.38 USD, direct costs ranged from 106.53 USD to 293.79 USD and indirect costs ranged from 1.92 USD to 73 USD. Hospitalization costs were the main contributor to direct costs, followed by drug costs (32).

More than two-thirds of participants had suboptimal glycaemic control. This was higher than Simeni Njonnou et al. findings in 2020 in an urban center of Cameroon (41.3%) (30). This rate of poor glycaemic control was similar to that in Ethiopia (ranging from 63.8% to 66.1%) but lower than that found in Guinea and Nigeria (74% and 83.3% respectively) (21,25,26,28,33). This discrepancy in the HbA1c results could be due to the type of treatment centers, the type of HbA1c assays, or the impact of each country’s health policies.

In our study, insufficient regular follow-up exposed 14 times more to poor glycemic control. Several research on the subject corroborates our findings, such as that of Jafarian-Amirkhizi et al. made in Iran in 2018 (34). We can probably attribute this risk to obstacles such as the high cost of care, the scarcity of health personnel, the quality of service delivery, and poverty. A recent study in Tanzania, of 248 participants, showed that non-regular follow-up was associated with poor glycaemic control (35).

This study found some protective factors. The use of herbal medicine was identified as protective against poor glycemic control. Its use in the management of diabetes is not well established because of the diversity of plants used and ambiguous scientific knowledge on the issue. However, even though many participants used it in our study and data showed a reduction of poor glycemic control in people using it, we cannot say with certainty that herbal medicine is a protective factor against poor glycemic control, as we could not identify the different types of plants consumed by them. We can explain this massive use by the advantage that traditional pharmacopeia has uncontrolled access and low cost. Despite the large amount of literature available, the actual clinical efficacy of medicinal plants in glycaemic control remains controversial and there is a critical need for stronger evidence (36). Therapeutic non-adherence is the main difficulty that patients with diabetes encounter, thus promoting poor glycaemic control. In our analysis, poor adherence was a factor associated with insufficient glycaemic control as indicated in the literature. These data are similar to many studies, such as those of Aminde et al. conducted in Cameroon in 2019 (37) and Waari et al. conducted in Kenya in 2018 (38). Similarly, Jodan et al. in an Indian survey [2022] found that non-adherence to drugs in patients with T2D is significantly associated with drug cost, drug unavailability, and the long-term use of drugs (39). This non-adherence is also associated with psychosocial and interpersonal factors that may play a role in the non-adherence to diabetes treatment (40). In addition, the simplification of a complex drug regimen for patients with diabetes should be sought by physicians and pharmacists to improve adherence to drugs and subsequent improvement in glycaemic control (41).

We had several limitations in this study. The first and main difficulty encountered was the limited access to the HbA1c assay due to its high cost, which justifies our small sample size. The second limit was the use by laboratories of different types of HbA1c assays (mainly enzymatic assays). This can give a heterogeneity of results. The third limitation was due to our sample, as it was low, which reduced the power of our statistical analysis.

Conclusions

The prevalence of poor glycemic control in the population of T2D followed-up at the Bafoussam Regional Hospital was high (68.6%). The factors associated with poor glycemic control in this population on multivariate analysis are monthly income less than 100,000 FCFA (168.0 USD), irregular follow-up, poor adherence, the consumption of herbal medicine. There is a need to confirm these findings on a large population scale.

Acknowledgments

We thank the participants of this study as well as the staff of the diabetology unit of the Bafoussam Regional Hospital.

Funding: None.

Footnote

Data Sharing Statement: Available at https://jxym.amegroups.com/article/view/10.21037/jxym-23-30/dss

Peer Review File: Available at https://jxym.amegroups.com/article/view/10.21037/jxym-23-30/prf

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jxym.amegroups.com/article/view/10.21037/jxym-23-30/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by the West Regional Ethics Committee (No. 2022/06/016/CE/CRERSH-OU/VP) and the Bafoussam Regional Hospital (No. 443/L/MINSANTE/SG/DRSPO/HRB/D). Patients were free to participate in the study without external constraints. Informed consent was obtained from all individual participants.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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