Study of the epidemiological profile of type 2 diabetes and associated pathologies in the Nador City, Morocco

¹Laboratory of Natural Resources and Sustainable Development, Department of Biology, Ibn Tofail University, Kenitra, Morocco, ²Laboratory of Biology and Health, Department of Biology, Ibn Tofail University, Kenitra, Morocco, ³Statistics Unit, the Provincial Hospital Center of Tan-Tan, Nador, Morocco

^&Corresponding author
Ikram Kenfaoui, Laboratory of Natural Resources and Sustainable Development, Department of Biology, Ibn Tofail University, Kenitra, Morocco

Introduction    

Diabetes, classified as a non-communicable disease, is acknowledged by the United Nations as a global health threat [1], with infectious epidemics like malaria, tuberculosis, and AIDS [2]. By 2021, diabetes is projected to affect more than 537 million people worldwide [3], equivalent to approximately 1 in 10 individuals, with 61 million cases concentrated in Europe [4]. The prevalence of diabetes is estimated to increase from 8.3% to 9.9% of the world's population by 2030 [5]. Type 2 diabetes, also known as "Non-insulin-dependent Diabetes Mellitus" (NIDDM) or "diabetes mellitus", is characterized by chronic hyperglycemia, exposing individuals to risks of acute complications such as hyperglycemia, ketoacidosis, and hyperosmolar syndrome [6]. Long-term hyperglycemia can lead to various severe degenerative complications. Over 95% of diabetes cases are attributed to type 2 diabetes, mainly affecting adults [7]. Preventive measures against type 2 diabetes involve maintaining a healthy diet, engaging in regular physical activity, maintaining a normal weight, and avoiding tobacco consumption [8]. Managing chronic conditions like diabetes often involves dealing with psychological and psychosocial aspects that can impact blood glucose levels, personal effectiveness, and overall quality of life [9]. Stress, for instance, may elevate blood sugar levels or exacerbate existing hyperglycemia in diabetics [10], while also increasing the risk of anxiety and making it challenging to achieve a balance.

Diabetes, a major contributor to global mortality rates, places a significant burden on healthcare systems worldwide. Numerous studies have sought to investigate the patterns of diabetes prevalence, awareness, treatment, and control. For instance, a study focused on Iranians aged 25 to 65 over a 12-year duration, utilizing data from a national population-based survey known as the STEPwise approach to surveillance (STEPS) for non-communicable diseases (NCDs). This study encompassed four survey rounds conducted in 2004, 2007, 2011, and 2016. The analysis involved secondary data, with sample sizes of 89,404, 29,991, 12,103, and 30,541 individuals across both urban and rural areas [11]. Descriptive statistics and logistic regression models were applied, with odds ratios calculated at significance levels below 5%, without adjustments for age and sex [12]. The logistic regression explored sociodemographic factors linked to awareness, treatment, and control levels of diabetes. Over the four survey rounds, diabetes prevalence increased from 8.4% to 13.2%. Awareness among those with diabetes rose from 53.5% to 82.2%, treatment rates ranged from 35.9% to 46%, and rates of adequate glycemic control ranged from 14.5% to 20.4%. Multivariable logistic regression analyses unveiled noteworthy connections between diabetes prevalence and factors like female gender, age over 40, urban residency, higher wealth quintile, and possession of health insurance. Female participants exhibited heightened awareness, and older individuals were more likely to undergo treatment and maintain glycemic control [13].

Furthermore, numerous studies have highlighted that the prevalence of diabetes continues to rise. Despite the heightened awareness of the disease, both the receipt of treatment and the achievement of effective disease control remain below optimal levels. Although various national policies have been introduced in recent years to enhance diabetes screening and care, there are still significant gaps in disease detection and treatment, indicating that challenges persist in this area [14]. For instance, Diabetes Mellitus (DM) has emerged as an epidemic in the USA, ranking among the primary causes of death over the last few decades. Despite the notable prevalence of diagnosed DM cases, nearly half of all individuals with DM are unaware of their condition. The risk of developing type 2 DM is shaped by a complex interplay of genetic and metabolic factors. Patients with type 2 DM face an increased risk of death due to cardiovascular causes compared to individuals without diabetes. The mortality rates associated with cardiovascular disease linked to DM vary across different ethnic and gender groups. In addition to its adverse impact on individual health, DM also places an economic burden on both affected individuals and households, as well as on the healthcare system [15].

In Morocco, approximately 80% of diabetes cases are classified as type 2 diabetes, and this prevalence is likely influenced by lifestyle and dietary factors [16]. Despite the establishment of the Regional Directorates of the Ministry of Health (MS) in 2010/2011, there is still a lack of sufficient statistical data regarding this condition within healthcare centers [17]. The Eastern Mediterranean region is particularly affected and according to WHO [18] estimates, the prevalence rate of diabetes in the adult population is 12.4% [19]. This pathology is the cause of more than 12,000 deaths per year and is the cause of 32,000 additional deaths, attributable to complications due to high blood glucose levels [20]. Conversely, there is a notable scarcity of studies on the epidemiology of diabetes in southern Morocco. Consequently, the objective is to create the epidemiological profile of type 2 diabetes and explore its influence on the emotional well-being of patients in the city of Nador, situated in the north-east region of Morocco. This research is particularly significant in Nador, where diabetes has emerged as a significant public health concern.

Methods     

Study area

The study area is called Nador, and it is a Moroccan coastal city, the capital of the Nador province, which forms part of the eastern region, located on the Mediterranean Sea in the north of the country [21,22]. The city is located 150 km away from Al Hoceïma, 80 km from the province of Berkane to the east, 110 km from the provinces of Taourirt and Guercif to the south, the province of Driouch to the west and the Mediterranean Sea to the north [21]. It also borders on the presidency of Melilla. Covering an area of 3,221 km², or 3.6% of the total area of the Oriental region (90,130 km²) [23], the province of Nador extends over approximately 88 km from north to south and approximately 85 km from 'East to West (Figure 1). Given its geographical position, the province of Nador is characterized by a Mediterranean climate marked by low rainfall and very significant temperature differences [24]. According to the results of the last General Census of Population and Housing 2014, the total population of the province is 565,426 inhabitants, or 24.4% of the total population of the Oriental region [25]. The urban population of the province amounts to 392,623 inhabitants, registering an urbanization rate of nearly 70%. The 6 population density of Nador is very high, i.e. 175.5 inhabitants/Km² [26].

Data collection

The epidemiological in this study was conducted at a private medical analysis laboratory in Nador, spanning from October 1, 2018, to October 1, 2019. The study involved a total of 830 male and female participants aged 18 years and above, all of whom were residents of Nador. To initiate the study, we sought permission to conduct our research at the private medical analysis laboratory in Nador. Upon receiving approval, we explained the study's objectives to the laboratory's biologist. The subjects included in the study were individuals diagnosed with type 2 diabetes, who visited the laboratory for blood glucose level checks, and their blood glucose levels were found to be equal to or greater than 1.26g/l (7 mmol/l) on two separate occasions. Data for the research were gathered from data sheets encompassing various clinical characteristics such as age, sex, duration of diabetes, marital status, educational level, and Body Mass Index (BMI). Additionally, the data sheets include questions pertaining to drug treatment, insulin therapy, diet, and a question related to sensation [27]. Additionally, we performed necessary anthropometric measurements and biological assays using specialized equipment, which was conducted in a designated room dedicated to the participants (Figure 2). We employed the following procedures for data collection:

Subject selection: we enrolled participants who had fasted for 12 hours before blood collection, and who have given their consent to participate in the study.

Blood collection: venipuncture at the elbow was utilized to draw two vials of venous blood from each participant. A loose tourniquet was applied, and single-use needles were inserted into the patient's vein to collect blood, which was then transferred into vacuum-sealed tubes.

Blood sample types: two types of tubes were used for blood collection. The first was a dry tube containing lithium heparin, a glass vacuum blood collection tube used for fasting blood glucose determination. The second was an Ethylene-diamine-tetra-acetic Acid (EDTA) tube employed for determining glycated hemoglobin levels. The blood sample collection was carried out by a laboratory nurse.

Blood glucose determination: fasting blood glucose levels were determined using an automated biochemistry system after 5 minutes of decantation and 10 minutes of centrifugation.

HbA1c determination: whole blood samples underwent analysis through High-Performance Liquid Chromatography (HPLC) to ascertain the level of glycated hemoglobin (HbA1c).

Complications and treatment data: data on diabetes-related complications and treatment specifics were extracted from the patient's admission record.

Prescription and data entry: following validation with the patient, the secretary inputted prescription data directly into the software system to ensure traceability. This process involved recording the patient's clinical information, associated pathologies, treatments, and doses, with a printed bench sheet containing all relevant patient details.

Anthropometric characteristics: body mass index (BMI) is calculated by dividing a person's weight in kilograms by the square of their height in meters. The BMI categories approved by the World Health Organization are as follows: 18.5 or less (underweight), 18.6 to 24.9 (normal weight), 25.0 to 29.9 (overweight), and 30.0 or more (obese). To measure anthropometric parameters such as weight, height, BMI, waist circumference (TT), hip circumference (TH), and the waist-to-hip ratio (TT/TH) in adults, we used a measuring tape and a SECA mechanical scale.

For weight measurement, the patient was asked to stand upright, motionless, barefoot, and wearing light clothing on a SECA mechanical scale. The weight was recorded to an accuracy of 0.5 Kg. Waist measurement was conducted using a fixed wall-mounted height gauge. The person being measured stood unshod with their heels together and legs straight, while the back of their head, shoulder blades, buttocks, calves, and heels touched the wall. The individual being measured was instructed to look straight ahead during the measurement process. Following these standardized procedures ensures accurate and consistent anthropometric measurements, which are essential for assessing and categorizing BMI and other related health parameters.

The Depression, Anxiety and Stress Scale - 21 items (DASS-21) is a set of three self-report scales designed to measure the emotional states of depression, anxiety and stress. It has been used to assess patients' psychological state. Each of the three DASS-21 scales contains 7 items, divided into subscales with similar content. The depression scale assesses dysphoria, hopelessness, devaluation of life, self-deprecation, lack of interest / involvement, anhedonia and inertia. The anxiety scale assesses autonomic arousal, skeletal muscle effects, situational anxiety, and subjective experience of anxious affect. The stress scale is sensitive to levels of chronic nonspecific arousal. It assesses difficulty relaxing, nervous arousal, and being easily upset/agitated, irritable/over-reactive and impatient. Scores for depression, anxiety and stress are calculated by summing the scores for the relevant items.

Data processing and analysis

The data for our study were gathered from data sheets containing various clinical characteristics, including age, sex, duration of diabetes, marital status, educational level, body mass index (BMI), as well as questions related to medication, insulin therapy, diet, and sensation. After collecting the data, we entered it into Excel for organization and initial processing. We then applied filtering and coding to ensure data quality. Next, the data was transferred to the statistical analysis software, SPSS (Statistical Package for Social Sciences) version 23.0, for further analysis.

Quantitative variables were presented as means ± standard deviation, allowing us to understand the average values and the variability within the data. On the other hand, qualitative variables were expressed as frequencies and percentages, providing a clear understanding of the distribution and proportions of different categorical variables. To test hypotheses and compare means, we employed Student's T-test, while the Chi-2 test of independence was used to compare proportions. These statistical tests enabled us to draw meaningful conclusions and identify any significant differences between groups or variables.

Since this is a cross-sectional study subject to bias, and to neutralize biases that may affect the validity of the results. A number of precautions were taken: firstly, random sampling was carried out among subjects who had given their consent to take part in the study; secondly, with regard to biases linked to recall, objective measures were used for nutritional status, records in patients' medical files for associated pathologies, and the DASS-21 questionnaire for assessment of psychological condition.

Results     

Sociodemographic characteristics of patients: according to the results of the Table 1, indicate that all selected variables are significantly associated with gender (p < 0.05). Among patients aged over 40, the prevalence of female type 2 diabetics was 74.49% (n = 549) compared to 25.51% among males. Furthermore, within the entire sample of diabetics (n = 830), a significant proportion, 90.24% (n= 749), were functionally impaired, and among them, more than 75% (n= 565) were women. Similarly, among patients with no formal education (n = 699), a majority of 74.53% (n = 521) were female. However, among those who were married (n= 717), 86.38% (n= 539) were women. The average age of diabetes onset in the population was found to be 7.50 ± 0.14 years, with the duration of the disease ranging from a minimum of 1 year to a maximum of 21 years. Notably, 72.79% (n= 305) of patients who had suffered from the disease for a duration of 5 to 10 years, and 74% for more than 10 years, were women. These findings suggest a significant gender disparity in the prevalence and impact of type 2 diabetes among the studied population, with a higher proportion of female patients in various age groups and disease durations.

Anthropometric characteristics of patients: the distribution of respondents based on body mass index (BMI) reveals an average BMI of 30.13 ± 0.24 for the entire sample. When analyzed by gender, the average BMI for females was 30.44 ± 0.28, while for males, it was 29.28 ± 0.42. The Fisher's test indicated a significant difference between the BMI values of males and females (F= 4.77; p < 0.929). The distribution of BMI was found to be normal, with a skewness coefficient of 0.36 and a kurtosis of 0.14. Examining the distribution of type 2 diabetic patients according to BMI categories, the findings were as follows: 1) Underweight: 2.77% (n= 23) of the diabetic patients were underweight, including 20 women. 2) Normal Weight: 22.41% (n= 186) of diabetic patients were categorized as having a normal build. 3) Overweight: 27.23% of diabetic patients were overweight, with 69.91% (n= 158) of them being female. 4) Obese: the majority, 47.59%, of diabetic patients were obese, with 76.96% (n= 304) of them being female.

These results demonstrate the distribution of type 2 diabetic patients across various BMI categories, revealing a significant number of females in the overweight and obese categories. It is noteworthy that a considerable proportion of diabetic patients were classified as obese, particularly among female individuals (Table 2). Disease-related pathologies: the table presents the prevalence of complications associated with type 2 diabetes in the study population, classified by gender. The results are as follows: Dyslipidemia: the prevalence of dyslipidemia is 14.82%, with a complication rate of 17.94% in men and 13.67% in women. The attributable risk is 4.27% in favor of males. Diabetic foot: The prevalence of diabetic foot is 7.23%, with an attributable risk of -0.68% in favor of women. Hypertension: the prevalence of hypertension is 17.23%, with a rate of 18.35% in men and 16.8% in women. The attributable risk is 1.59% in favor of men. Diabetic Ketoacidosis (DKA): the prevalence of DKA is 14.58%, with a rate of 10.76% in men and 15.98% in women. The attributable risk is -5.22% in favor of women. Cataracts: the prevalence of cataracts is 10.12% in favor of males. Renal failure: The prevalence of renal failure is 18.07%, with a rate of 19.73% in men and 17.46% in women. The attributable risk is 2.27% in favor of males. Skin involvement: the prevalence of skin involvement is 2.77% in favor of males. Thyroid Dysfunction: The prevalence of thyroid dysfunction is 10.86%, with a rate of 9.42% in men and 11.37% in women. The attributable risk is -1.95% in favor of females. Overall, the prevalence of associated pathologies varies from a minimum of 2.77% for skin disorders to a maximum of 18.07% and 17.23% for renal failure and high blood pressure, respectively. The chi-square test indicated no significant effect of gender on the occurrence of these complications, although the attributable risk favored males for hypertension, cataracts and renal failure. These results highlight the prevalence of various complications associated with type 2 diabetes in the study population and provide insights into the gender-specific patterns of these complications (Table 3).

Distribution by patient's psychological state: Figure 3 displays the distribution of patients based on their psychological state and gender. It shows that 80.48% (n= 668) of the patients were in a state of stress, out of which 73.05% (n= 488) were women. However, the chi-square test did not reveal any significant relationship between gender and psychological state. The other hand, 19.52% of the patients experienced other psychological manifestations, such as anxiety, which affected 18.43% of the total population (114 women and 39 men). Additionally, depression were also observed among the patients with a prevalence of 1.08% (5 males and 4 females). These findings highlight that women are more susceptible to experiencing psychological distress in response to the implications of the disease. The data suggests that the impact of type 2 diabetes may have a greater psychological toll on female patients compared to male patients.

Global analysis: Multiple Correspondence Analysis (MCA) allowed us to conduct an overall analysis and classify the modalities into three distinct groups: Group 1: this group is situated on the positive side of Axis 1 and includes female diabetic patients aged over 70, who have been living with the disease for more than 10 years. These individuals generally fall into the obese category and suffer from renal insufficiency, along with symptoms of diabetic foot complications. Group 2: positioned on the positive side of Axis 1, this group comprises married diabetic women aged 55 to 70. Patients in this group exhibited symptoms of depression, anxiety, stress, and hypertension. Group 3: this group is located on the negative side of Axis 1 and consists of single male patients under 40 years of age. These patients presented with skin disorders and symptoms of nervous tiredness. By utilizing MCA, we were able to identify these distinct groups of diabetic patients with specific characteristics and related complications. This analysis provides valuable insights into the patterns and relationships between various factors affecting patients with type 2 diabetes, facilitating a comprehensive understanding of their health conditions and psychological states (Figure 4).

Discussion     

The main subject of our study is to analyze the epidemiological profile of type 2 diabetic patients residing in the city of Nador. The presence of a chronic disease like diabetes often leads to psychological repercussions. In our population, we observed two major psychopathological disorders: stress and anxiety [28]. Our findings align with previous research that depicts diabetes as a manageable but not curable condition, impacting patients' mood, anxiety levels, depression, and even eating habits [29].

The influence of psychological stress on blood sugar levels in individuals with type 2 diabetes has been confirmed by a Canadian study [30]. Moreover, high blood pressure (hypertension) and type 2 diabetes are common coexisting conditions [31]. Our sample showed a hypertension rate of 17.23% among type 2 diabetic patients, which is significantly lower than rates reported in other regions, such as black Africa, where hypertension prevalence reached as high as 72.18%. Similar trends were found in other studies conducted in Tunisia, where obesity was associated with type 2 diabetes and its prevalence was higher in women compared to men [32].

Furthermore, we identified other associated pathologies in our sample, including dyslipidemia, which involves abnormal lipid concentrations in the blood [33]. The prevalence of dyslipidemia in our study reached 14.82%. Another significant finding in our population was the prevalence of Chronic Kidney Disease (CKD), with a rate of 18.07%. Diabetes is the leading cause of end-stage CKD globally, and the second leading cause in France, after hypertension [34]. Our study provides valuable insights into the epidemiological characteristics and associated conditions of type 2 diabetic patients in Nador, contributing to the overall understanding of diabetes-related complications and their implications for patient management and care.

The present study provided a psychological and epidemiological profile of diabetics in the Nador population. However, it cannot establish whether the psychological state causes a health outcome or whether the two are simply associated, so further investigations should be carried out to determine other risk factors and their mechanisms of action, such as genetic or environmental factors. Furthermore, the generalizability of the results to the entire Moroccan population is likely to be biased, and further confirmatory studies on a national scale should be carried out.

Conclusion     

Type 2 diabetes is a significant source of stress, and the psychological conflicts arising from this condition can disrupt the glycemic balance of diabetic patients. However, this type of diabetes can be effectively managed through a treatment plan that involves a balanced diet, regular physical activity, and medical interventions. In Morocco, the prevalence of diabetes is increasing each year, and as a result, it is crucial for the medical authorities and appropriate health insurance programs to prioritize the care of diabetics. This study has identified specific sociodemographic and anthropometric characteristics, as well as various issues affecting the diabetic population. The findings reveal that the diabetic population studied is generally elderly, with an average age of 59.06 ± 14.51 years. The age range is broad, spanning from 18 to 97 years, indicating a diverse and heterogeneous population. The study highlights the prevalence of obesity, particularly in the female population, with 36.9% of women having a BMI greater than 30. It also suggests that female gender and advanced age are sociodemographic risk factors for type 2 diabetes, while waist circumference and BMI are anthropometric risk factors. Further in-depth investigations are necessary to comprehensively address the various challenges associated with managing diabetes in the elderly population within the Moroccan context. Improved understanding and management of these issues will lead to more effective and tailored diabetes treatments for this age group. In conclusion, this study provides valuable insights into the characteristics and risks associated with type 2 diabetes in the Moroccan population. It emphasizes the importance of personalized care and interventions, especially for the elderly, to better manage diabetes and improve the overall well-being of diabetic patients in the country.

Competing interests     

The authors declare no competing interests.

Authors' contributions     

Conceptualization: Ikram Kenfaoui, Hanae Marjaa, Siham Daouchi; methodology: Ikram Kenfaoui, Hanae Marjaa and Said Bouchefra; software: Abderrahim Benzakour and Said Bouchefra; validation. Ikram Kenfaoui; original draft preparation: Ikram Kenfaoui and Said Bouchefra; writing - review and editing: Siham Daouchi; visualization: Ikram Kenfaoui and Siham Daouchi; supervision: Mohammed Ouhssine. All authors have read and agreed to the final version of the manuscript.

Acknowledgments     

Our thanks go to all those who contributed directly or indirectly to the realization of this work. We would like to express my gratitude to the professional and attentive team of the medical analysis laboratory and especially Dr Imad Taibi, the biologist.

Tables and figures      

Table 1: sociodemographic characteristics of respondents

Table 2: anthropometric characteristics of respondents

Table 3: distribution of type 2 diabetes patients according to associated pathologies

Figure 1: location of Nador City

Figure 2: inclusion and exclusion criteria of study area

Figure 3: population distribution by psychological state

Figure 4: arrhythmogenic cardiomyopathy presentation of the modalities of the sociodemographic-anthropometric and psychic variables

References