Diabetic Polyneuropathy and Associated Factors in a Population of Type 2 Diabetic Patients in Garoua, Cameroon ()
1. Introduction
Diabetes is a chronic disease characterized by impaired carbohydrate metabolism. It is a leading cause of mortality and reduces life expectancy [1]. Over the past decade, the prevalence of diabetes mellitus has increased significantly, mainly due to the continuing rise in the incidence of type 2 diabetes [2]. According to the International Diabetes Federation, approximately 537 million people worldwide will be living with diabetes in 2021 [1]. Due to socio-cultural transitions mainly the growing urbanisation and the sedentarisation of the population, Africa has not been spared from this increase. In 2021, 24 million people in Africa will have diabetes, with a prevalence of 4.5% [2]. In Cameroon, the number of diabetics in 2023 is estimated at 2.5 million [3]. In parallel with this rise in the incidence of diabetes, there is an increase in chronic complications affecting patients’ quality of life.
Diabetic polyneuropathy (DPN) is one of the most prevalent chronic complications, affecting approximately 50% of type 2 diabetic patients [4]. A multitude of studies have investigated the prevalence of DPN, with estimates ranging from approximately 50% in France, 26% in the UK, 43% in Belgium, and 34% in Saudi Arabia [4]-[7]. Similar figures have been documented on the African continent: 56.7% in Tunisia and 49% in Morocco [8] [9]. In Cameroon, Simo et al. found a prevalence of 31.4% in 2020 [10] and Dehayem et al. in 2010 found 44.1% in the cities of Douala and Yaoundé respectively [11]. The main risk factors incriminated by the Cameroonian studies were age, female gender, long-standing diabetes, albuminuria, HIV infection, glycemic imbalance, urban residence and hepatitis C virus infection [10]-[12]. However, data from northern Cameroon are scarce. We therefore considered it necessary to assess the prevalence of DPN and the factors associated in Garoua.
2. Methodology
2.1. Study Design and Population
This multicenter cross-sectional study was conducted over a five-month period from January 1 to May 31, 2024, in the diabetology units of Garoua Regional Hospital and Garoua General Hospital. This two referral hospitals in Garoua have functional diabetology services, including therapeutic education units, nutrition services, outpatient consultation units, and inpatient wards. However, due to its status as a first-category facility within Cameroonian healthcare pyramid, Garoua General Hospital receives more socioeconomically diverse patients compared to Garoua Regional Hospital. All type 2 diabetic patients aged 35 or over who had given informed consent to participate in the study were included. Patients with a non-diabetic cause of peripheral polyneuropathy (alcoholism, chemotherapy, anticonvulsants, psychotropic, antiretrovirals drugs, anti-tuberculosis drugs…) were excluded.
2.2. Sampling
For this in-hospital study, we used consecutive, non-probability, exhaustive sampling.
2.3. Data Collection
We obtained ethical clearance (N˚004/CERSH/NO/2024) and administrative authorizations (N˚2562/23/L/HRG/CM and N˚23-0005/AR/MSP/HGG/DG) prior to the start of the survey. Recruitment of participants began at the Garoua Regional Hospital, as this was the busiest in terms of patient attendance. Outpatients were approached by the principal investigator. After obtaining informed consent, a pre-established electronic questionnaire, prepared using Epi Data Entry 4.0.6.0 software, was administered to patients during a face-to-face exchange, enabling direct data capture during the survey. The following data were collected:
Sociodemographic data: gender, region of origin, marital status, residence (urban, semi-urban or rural), level of education, occupation, income, religion and ethnicity.
Diabetes data: type of diabetes, date and mode of diagnosis, family history of diabetes, diabetes control (glycated hemoglobin level), follow-up visits frequency, type of treatment, complications of diabetes (diabetic retinopathy, chronic kidney disease).
Other cardiovascular risk factors: hypertension, smoking, alcoholism, sedentary lifestyle, dyslipidemia, chronic kidney disease, hyperuricemia/gout.
Clinical exam: weight, height, abdominal circumference, and blood pressure measured using standardized procedures.
Neurological foot examination: assessment began with checking for subjective neurological symptoms and their duration, followed by evaluation of superficial sensation (pain [pin-prick], light touch [cotton wool], temperature [hot/cold]). All exams were performed by the same examiner.
Paraclinical data: glycated hemoglobin (A1c), capillary blood glucose, serum creatinine, lipid profile, and funduscopy.
2.4. Assessment of Diabetic Polyneuropathy
We assessed DPN using the DN-4 questionnaire, a validated screening tool for diabetic polyneuropathy. It consists of 10 items across four domains (pain characteristics, associated symptoms, pain location, and triggers): 7 interview-based and 3 physical exam-based items: 7 questioning items and 3 physical examination items scored by 0 or 1 according to the absence or presence of symptoms. A total score ≥ 4 indicated DPN, with a sensitivity of 80% and a specificity of 92% (Table 1) [13].
Table 1. DN-4 questionnaire.
|
|
Yes = 1 |
No = 0 |
QUESTION 1 |
Does the pain have one or more of the following characteristics: |
|
Burning |
|
|
Painful cold sensation |
|
|
Electrical discharges |
|
|
QUESTION 2 |
Is the pain associated in the same area with one or more of the
following symptoms: |
|
Tingling |
|
|
Tickling |
|
|
Numbness |
|
|
Itching |
|
|
QUESTION 3 |
Is the pain located in a territory where the examination reveals: |
|
Hypoesthesia to touch |
|
|
Hypoesthesia to prick |
|
|
QUESTION 4 |
Is the pain provoked or increased by: |
|
Friction |
|
|
2.5. Statistical Analysis
Data collected on Epi Data 4.0.6.0 were exported to IBM SPSS version 23 for statistical analysis. Frequencies and percentages were calculated for qualitative variables. Mean [standard deviation (SD)] and median [interquartile range (IQR)] were used for quantitative variables based on data distribution. For comparison of continuous variables, we used Student’s t test or its non-parametric equivalent. Proportions were compared using the Chi2 test. The prevalence [95% confidence interval (95% CI)] of diabetic peripheral polyneuropathy was calculated as the proportion of cases of diabetic sensitive polyneuropathy over the total number of diabetic patients tested. We used Logistic regression to investigate factors associated with DPN (age, gender, duration of diabetes, diabetes control, comorbidities, chronic complications). Univariate analysis variables with p < 0.05 were entered into a single multinomial logistic regression model to determine independent factors associated to DPN. The threshold of significance in this multivariate analysis was set at 0.05. The strength of the association was estimated using the adjusted odds ratio (ORa) and its 95% CI.
3. Results
Out of 247 patients seen in the diabetology clinics, 44 were excluded due to exclusion criteria, resulting in 203 patients definitively included in the study (Figure 1).
Figure 1. Study population flow diagram.
3.1. Socio-Demographic Data
The study included 64 (31.5%) men and 139 (68.5%) women, with a male-to-female sex ratio of 0.46. The median age (IQR) of patients was 56 (48 - 63) years ranging from 35 to 80 years. The most represented age group was 51 - 60 years (35.50%). A large proportion of patients had no formal education 81 (39.90%) while only 17 (8.37%) patients had university-level education. Nearly half of the participants (45.3%) had a monthly income below 50,000 FCFA (Table 2).
Table 2. Sociodemographic characteristics of the study population.
Variable |
Total N = 203 |
DPN |
ORa |
95% CI |
p value |
Present
N = 93 (%) |
Absent
N = 110 (%) |
Sex |
Female |
139 |
73 (52.5) |
66 (47.5) |
2.43 |
[1.30 - 4.54] |
0.005 |
Male |
64 |
20 (31.2) |
44 (68.8) |
|
|
Age |
≥60 years |
84 |
57 (40.4) |
27 (59.6) |
4.87 |
[2.66 - 8.88] |
<0.001 |
<60 years |
119 |
36 (30.3) |
83 (69.7) |
|
|
Level of education |
No schooling |
81 |
40 (49.4) |
41 (50.6) |
1.27 |
[0.72 - 2.23] |
0.692 |
Educated |
122 |
53 (43.4) |
69 (56.6) |
|
|
|
Salary income |
<50,000 Fcfa |
92 |
44 (47.8) |
48 (52.2) |
1.16 |
[0.66 - 2.02] |
0.275 |
≥50,000 Fcfa |
111 |
49 (44.1) |
62 (55.9) |
|
|
|
3.2. Clinical Data
The median diabetes duration (IQR) was 5 (2 - 9) years. Almost half (47.29%) of the patients had had diabetes for less than 5 years, while 21.18% had diabetes for 10 years or more.
In our study population, 170 (83.74%) patients had performed a glycated hemoglobin within the last 3 months. The median (IQR) A1c was 8.80% (7.50% - 10.6%). Among these, only 14.71% had controlled diabetes (A1c < 7%), while 22.94% had moderately uncontrolled diabetes (A1c 7% - 8%), and 62.35% had poorly controlled diabetes (A1c ≥ 8%).
Table 3. Clinical characteristics of the study population.
Variable |
Total |
DPN |
ORa |
95% CI |
p value |
Present
N = 93 (%) |
Absent
N = 110 (%) |
Age of diabetes |
≥10 years |
43 |
31 (72.1) |
12 (27.9) |
4.08 |
[1.95 - 8.54] |
<0.001 |
<10 years |
160 |
62 (38.8) |
98 (61.2) |
|
|
A1c |
≥7% |
145 |
79 (54.5) |
66 (45.5) |
|
|
|
<7% |
25 |
6 (24.0) |
19 (76.0) |
3.79 |
[1.43 - 10.04] |
0.005 |
Dietary and hygienic measures |
Not complied |
70 |
35 (50.0) |
35 (50.0) |
1.29 |
[0.72 - 2.31] |
0.385 |
Adhered to |
133 |
58 (43.6) |
75 (56.4) |
|
|
|
Treatment |
Insulin therapy |
25 |
10 (40.0) |
15 (60.0) |
0.73 |
[0.35 - 1.79] |
0.388 |
Others |
178 |
83 (46.6) |
95 (53.4) |
|
|
|
Diabetic retinopathy |
Yes |
13 |
12 (92.3) |
1 (7.7) |
14.16 |
[1.77 - 112.72] |
0.002 |
No |
109 |
50 (45.8) |
59 (54.2) |
|
|
|
Chronic kidney disease |
Yes |
26 |
24 (92.3) |
2 (7.7) |
16.90 |
[3.79 - 75.27] |
<0.001 |
No |
106 |
44 (41.5) |
62 (58.5) |
|
|
|
Most patients (65.22%) reported adhering to dietary recommendations and 50.74% practiced regular physical activity. Oral antidiabetic drugs were used by 72.41% of the patients.
Fundus examination was performed in 60.10% of the sample. Among them, 13 patients (10.66%) had diabetic retinopathy. Of the 158 patients with serum creatinine measured, 19.7% had an estimated creatinine clearance < 60 ml/min (Cockcroft formula) (Table 3).
3.3. Cardiovascular Risk Factors
With regard to cardiovascular risk factors, 43.8% of patients had arterial hypertension. A total of 11.3% of patients reported regular alcohol consumption. Only 2.9% of patients were tobacco smokers, while 1.4% had quit smoking at least 3 years previously (Table 4).
Table 4. Cardiovascular risk factors.
Variable |
Total |
DPN |
ORa |
95% CI |
p value |
Present
N = 93 (%) |
Absent
N = 110 (%) |
Arterial hypertension |
Yes |
89 |
50 (56.2) |
39 (43.8) |
2.11 |
[1.20 - 3.72] |
0.009 |
No |
114 |
43 (37.7) |
71 (62.3) |
|
|
Alcoholism |
Yes |
23 |
12 (40.0) |
11 (60.0) |
1.33 |
[0.56 - 3.18] |
0.516 |
No |
180 |
81 (45.0) |
99 (50.0) |
|
|
|
Smoking |
Yes |
6 |
4 (66.7) |
2 (33.3) |
2.42 |
[0.43 - 13.56] |
0.298 |
No |
197 |
89 (45.2) |
108 (54.8) |
|
|
|
Overweight |
Yes |
115 |
64 (55.7) |
51 (44.3) |
2.55 |
[1.43 - 4.54] |
0.001 |
No |
88 |
29 (32.9) |
59 (67.1) |
|
|
|
Sedentary lifestyle |
Yes |
100 |
58 (58.0) |
42 (42.0) |
2.68 |
[1.51 - 4.74] |
0.001 |
No |
103 |
35 (33.9) |
68 (66.1) |
|
|
|
Abdominal obesity |
Yes |
97 |
57 (58.7) |
40 (41.3) |
2.77 |
[1.57 - 4.90] |
<0.001 |
No |
106 |
36 (34.0) |
70 (66.0) |
|
|
|
Total cholesterol (g/L) |
≥2 |
35 |
19 (54.2) |
16 (45.8) |
1.12 |
[0.52 - 2.77] |
0.682 |
<2 |
66 |
33 (50.0) |
33 (50.0) |
|
|
|
Triglycerides (g/L) |
≥1.5 |
63 |
37 (58.7) |
26 (41.3) |
2.18 |
[0.96 - 4.96] |
0.061 |
<1.5 |
38 |
15 (39.4) |
23 (60.6) |
|
|
|
LDL (g/L) |
≥1.6 |
10 |
5 (50.0) |
5 (50.0) |
0.94 |
[0.25 - 3.45] |
0.921 |
<1.6 |
91 |
47 (51.6) |
44 (48.4) |
|
|
|
HDL (g/L) |
<0.4 (if Male) <0.5 (if Female) |
66 |
40 (60.6) |
26 (39.4) |
2.94 |
[1.25 - 6.93] |
0.012 |
≥0.4 (if Male) ≥0.5 (if Female) |
35 |
12 (34.2) |
23 (65.8) |
|
|
|
3.4. Anthropometric Parameters
Table 5 summarizes the anthropometric parameters of our study population. The median waist circumference (IIQ) in our sample was 91 cm (82 - 102 cm). Women had a median waist circumference (IIQ) of 89 cm (78 - 98 cm) and men 99 (92 - 107 cm).
Participants’ median BMI (IIQ) was 26.51 (22.75 - 30.83) kg/m2 and 56.65% patients had a BMI ≥ 25 kg/m2.
Using the American NCEP-ATP III classification for the gender distribution of our sample, we note that 47.7% of patients were android obese (Table 5).
Table 5. Anthropometric parameters
Variable |
Median |
IQI |
Minimum |
Maximum |
Weight (kg) |
72 |
[63 - 86] |
45 |
131 |
Height (m) |
1.65 |
[1.60 - 1.70] |
1.50 |
1.89 |
Waist circumference (cm) |
91 |
[82 - 102] |
61 |
120 |
BMI (kg/m2) |
26.51 |
[22.75 - 30.83] |
16.30 |
45.87 |
BMI: Body mass index.
3.5. Clinical Signs of DPN
Burning was the main symptom, with a frequency of 90.3% in the DPN population. Followed by tingling sensation, present in 80.6% of patients (Table 6).
Table 6. Clinical signs of DPN.
|
Number (N = 93) |
Frequency (%) |
Symptoms |
|
|
Burning |
84 |
90.32 |
Painful cold |
23 |
24.73 |
Electric discharge |
41 |
44.10 |
Tingling |
75 |
80.64 |
Tickling |
58 |
62.37 |
Numbness |
61 |
65.59 |
Itching |
32 |
34.41 |
Objective sensory disorders |
Hypoesthesia to touch |
75 |
80.66 |
Hypoesthesia to sting |
27 |
29.01 |
3.6. Prevalence and Associated Factors to DPN
The prevalence (95% CI) of DPN in our study population was 45.81% (38.82 - 52.96)%.
Multivariate analysis was carried out on a sample of 101 patients, due to the fact that some of our patients did not undergo complementary examinations. The independent factors associated [ORa (95% CI), p] with DPN were female gender [3.65 (1.62 - 8.23), p = 0.037]; age ≥ 60 years [4.57 (2.11 - 9.86), p = 0.048]; duration of diabetes progression [2.93 (1.16 - 7.45), p = 0.006]; hyperglycemic imbalance with HbA1c ≥ 7% [3.99 (1.25 - 5.72), p = 0.043] and chronic renal failure [4.79 (2.22 - 7.54), p = 0.009] (Table 7).
Table 7. Associated factors to DPN.
Variables |
Ajusted OR |
95% CI |
Ajusted p |
Female gender |
3.65 |
[1.62 - 8.23] |
0.037 |
Age ≥ 60 years |
4.57 |
[2.11 - 9.86] |
0.048 |
Dyslipidemia |
2.40 |
[0.71 - 8.07] |
0.071 |
Diabetes duration ≥ 10 years |
2.93 |
[1.16 - 7.45] |
0.006 |
A1c ≥ 7% |
3.99 |
[1.25 - 5.72] |
0.043 |
Diabetic retinopathy |
2.94 |
[1.10 - 7.25] |
0.065 |
Chronic kidney disease |
4.79 |
[2.22 - 7.54] |
0.009 |
4. Discussion
The aim of our study was to identify the factors associated with diabetic peripheral polyneuropathy in patients with type 2 diabetes in the city of Garoua. We included 203 patients and the main findings were:
1) The prevalence of DPN was high;
2) The main identified risk factors were female gender, age over 60, duration of diabetes over 10 years, chronic hyperglycemic imbalance and chronic kidney disease.
4.1. Prevalence of Diabetic Polyneuropathy
In our study, the prevalence (95% CI) of DPN was 45.81 (38.82 - 52.96)%. This result is similar to the results reported by Dehayem et al. in Cameroon on a sample of 376 patients and Aynaou et al. in Morocco on a cohort of 391 patients, which were 44.1% and 40% respectively. Both used the same diagnostic tool, the DN-4 questionnaire [8] [11].
Studies using other diagnostic criteria reported higher prevalence rates. Using the Michigan Neuropathy Screening Instrument (MNSI), Elleuch et al. found a prevalence of 57.8% [4]. Conversely, studies that employed electroneuromyography (ENMG) found lower rates. Mojaddidi et al. reported a prevalence of 16.4% in Saudi Arabia using ENMG, identifying subclinical DPN [14].
Thus, diagnostic tools significantly influence reported prevalence rates. This was confirmed in a 2022 Saudi Arabian meta-analysis by Owolabi et al., which included 12 studies using different diagnostic methods. Studies relying on questionnaires and clinical exams showed a pooled prevalence of 48% [46% - 50%], while those using nerve conduction studies reported a prevalence of 26% [15% - 36%] [6].
4.2. Factors Associated with Diabetic Polyneuropathy
The study of associated factors with DPN concluded that the female sex is involved. Many authors reported similar results. These include Hode et al. (p = 0.022) and Halawa et al. (p = 0.001) [15] [16]. However, some studies reported opposite results. Sani et al. found an association between male sex and DPN in their study (p = 0.017), explained by the predominantly male prevalence in their population [17].
We noted a significant relationship between advanced age (60 years) and DPN. This has also been reported by Sani et al. and Halawa et al. [16] [17].
In univariate analysis, both overweight and abdominal obesity were significantly associated with DPN, likely due to sensory dysfunction in small nerve fibers [18]. However, in multivariate analysis, BMI and waist circumference were not independent predictors.
Long-standing diabetes is a well-established major associated factor. Moreover, there was a positive correlation between the duration of diabetes and DPN, with a clearer correlation from 10 years onwards. This was demonstrated by logistic regression. The correlation has been confirmed by several studies, notably those by Bassanguen et al. and Halawa et al. [16] [19].
The role of hyperglycemia is clearly established in the onset and aggravation of DPN. Vinik et al. have demonstrated that poor glycemic control (A1c ≥ 7%) increases the risk of developing DPN by more than fivefold. According to our work, hyperglycemic imbalance is linked to the occurrence of DPN, with an aOR = 3.99, in case of A1c ≥ 7%. Similar results reported by Hode et al. [15].
In our study, chronic kidney disease was a significant predictor of the occurrence of DPN. Bassanguen et al. and Sani et al. highlighted this relationship, which is similar to our data [17] [19].
4.3. Study Limitations
Many patients faced financial barriers to completing certain paraclinical investigations. Thus, almost all the data collected was based on a pre-established questionnaire, completed during the consultation, with all the hazards inherent to this environment, notably the often stressful hospital atmosphere, which could alter the quality of patients’ answers. Screening for DPN using this questionnaire was based on subjective responses, influenced by the patient’s psychic disposition at the time of the interview.
The exclusive use of the DN-4 questionnaire to diagnose DPN could be responsible for overestimating the prevalence of DPN. The use of nerve conduction studies, even on a sub-sample of participants, would have improved diagnostic accuracy and strengthened the validity of the results.
5. Conclusion
Diabetic polyneuropathy is a highly prevalent complication of diabetes that significantly impacts patient quality of life. This study showed that almost half of our patients were affected by this complication. The identified independent associated factors in multivariate analysis were female gender, age ≥ 60 years, diabetes duration more than 10 years, poor glycemic control (A1c ≥ 7%) and chronic kidney disease.