Diabetes Miletus (DM) is a group of metabolic diseases characterized by hyperglycemia resulting from defects in insulin secretion, insulin action, or both. The chronic hyperglycemia of DM is associated with long-term damage, dysfunction, and failure of different organs, especially the eyes, kidneys, nerves, heart, and blood vessels. (Richard, 2013; American Diabetes Association, 2004). It is a metabolic condition characterized by elevated blood glucose due to insufficient insulin production (type 2) or inability to produce insulin (type 1), and/or peripheral tissue resistance to the action of insulin (Dall et al. 2019). The underlying causes of the DM are genetic and environmental factors, such as urbanization and industrialization, as well as increased longevity and changes in lifestyle from a traditional healthy and active life to a modern, sedentary, stressful life and over-consumption of energy-dense foods (Katrina et.al, 2002). Traditional rural communities have a low prevalence of 1 to 2% of DM whereas 1 to 13% or more adults are reported in urban areas (Motala et.al, 2003). 

Diabetes Miletus(DM) is spiking on the African continent (Asmelash and Asmelash, 2019), the prevalence of DM is increasing throughout the world as a consequence of growing rates of obesity, metabolic syndrome, and westernization of lifestyle (Bernadette 2019). DM are of three types; type 1 diabetes, type 2 diabetes mellitus, and gestational diabetes mellitus (Pouya et al 2019) which as of 2017 had 425 million adult patients and projected to 629 million by 2045 (IDF, 2017). It's a serious public health concern affecting millions of families globally with a projected health expenditure burden of 490 billion US Dollars in 2030 (Khushk et.al, 2010; Zhang et al.  2010;  Pouya et al 2019).  Geographical 

space is heterogeneous with an uneven interacting constituent (Halas et al., 2014) such that phenomena from one section can influence the other (Ullman, 1980) in terms of human, material, and financial horizontal flows (Halas et al., 2014). For example, China (116 million), India (77 million), and the USA (31 million) accounted for the highest prevalence in 2019 and by 2030 are projected to have 140, 101, and 34 million diabetes patients. By 2045 diabetes patients will be highest in China, India, and Pakistan, with 147, 134, and 37 million (Pouya et al. 2019). The prevalence and exacerbation of Diabetes in sub-Saharan Africa are largely caused by poor blood glucose control and late diagnosis in African Population. Of significance are the paucity of data which has made the understanding of the epidemiology, the true burden of diabetes, and the effective screening and management of the diseases with limited resources a challenge (Atun et al., 2017). According to the International Federation of Diabetes Africa report (2019), 19.4 million cases of diabetes were reported in 2019 and projected in 2030 to 28.6 million and 47.1 million in 2045. Diabetes rates in terms of Disability Adjusted Life Years (DALY), Years of Life Lost (YLL), Years of Life Lived with Disability (YLD) rates in sub-Saharan Africa increased by 126.4% between 1990 to 2017 (Gouda et al., 2019). 

According to the WHO (2018) noncommunicable disease profile report for Nigeria, 29% of mortality is caused by non-communicable disease, and Diabetes accounts for 1% of the total mortality. In 2013 DM accounted for 105,091 mortality cases (IDF, 2013), and 3 to 15% cases of medical admission (Agoucha et.al, 2013), which was as a result of a lack of self-monitoring of blood glucose level reported in 73% of DM patients (Chinenye et.al, 2008). DM has been increasing in Nigeria in the last 4 decades (Nyenwe et.al, 2003) and accounts for the highest DM burden in Africa followed by South Africa (2.6 million), Ethiopia (1.9 million), and Tanzania with 1.7 million (Oputa and Chinenye, 2015). The International Diabetes Federation (2009) puts the national prevalence of diabetes in Nigeria at 3.9 %, while in 2004, the Nigeria Diabetes Association estimated over 10 million DM patients (Ogbera et al. 2005). Urbanization is a precursor to the spread of type 2 DM (Ramachandran et.al, 1999) and urban life is characterized with variation in behavioural lifestyle (Van Dieren et.al, 2010) and as such this study is focused on the spread of DM in the city of Makurdi with the view to unraveling the underlining causes.

Study Area

Makurdi is situated in Benue State and located between Latitude 6° 251 and 8° 81 north and Longitude 7° 471 and 10° 01 east. It is bounded to the North by Nasarawa state, to the West by Kogi State, to the East by Taraba state and the Republic of Cameroun, and to the South by Cross-River and Enugu states. Benue state has an aerial extent of 30,955km2 and bifurcated into three (3) senatorial districts namely: Benue north, Benue central and Benue south, and twenty-three local governments areas. Benue State has a projected population of 4, 138, 166(culled from the 2006 NPC Census). The landmass is well-drained and defined by the River Benue and its tributaries which derived its source from the Cameroun Mountain. The State experiences a temperature of between 23°C to 34°C annually with a mean annual rainfall of between 150mm to 180mm (Ojanuga, and Ekwoanya, 1994). The ethnic groups are diverse and are; Tiv, Idoma, Igede, Etulo, Jukun, Hausa, Abakwa, etc. 

Benue state stretches across the transition belt between the forest and savannah vegetation, covering a vast and fertile landmass. Most of the inhabitants are farmers and fishermen. Major crops cultivated in the state are root crops such as yam, cassava, sweet potatoes, groundnuts, etc, grains e.g. rice, beans, benniseed, sorghum, and fruits e.g. oranges, banana, plantain, etc. Health care delivery is hierarchical in the state and they are primary, secondary, and tertiary levels. Primary health centers are the first point of call for the sick and injured persons. They are meant to treat common ailments such as cold, cough, malaria, etc. secondary healthcare centers are specialized healthcare centers such as the General Hospitals and the tertiary healthcare centers are the most specialized in terms of personnel and equipment. A specialist like a psychiatrist, pediatrician, cardiologist, thoracic surgeon, radiologist, etc. are present. The Federal Medical Centre (FMC) is a classic example.

Data Types

Secondary data was used for this study which includes medical records of the Federal Medical Centre and General Hospital in Makurdi, Benue State. Medical records were accessed after approval was granted from the ethics committees of both hospitals. Records sought were the year 2016 cases of Diabetes Miletus and other demographics such as an address, gender, age, ethnicity, religion, and occupation, locational information were linked to their corresponding streets. A total of 199 cases was used from the 226 recorded cases, this is as a result of the replicability of the residential addresses and non-recording of address in some of the case files. The addresses of patients were geocoded using Goggle Earth and later imported into ArcGIS 10.4 application for digitization. Global positioning system (GPS) was used to obtain the geographic coordinates of each hospital and entered into ArcGIS version 10.4 to map out the spatial location of the hospitals. Data collected from the two hospitals were grouped according to the various wards in Makurdi metropolis. See Table 1 and Figures 1 and 2 below.

Table 1: Political Wards in Makurdi Metropolis

Figure 1: Location Map of the Study area.

Source: Ministry of Lands and Survey Makurdi, 2017

Figure 2: Location Map of Study Area Showing Sampled Hospitals

Source: Field Survey (2017)

Table. 2: Spatial distribution of DM incidence across political wards (N=199)

Source: Medical Records (2016).

Spatial Pattern of DM Incidence Across Political Wards

From Table 2 and Figure 3, A total number of 226 cases of DM were extracted from hospital records of the Federal Medical Centre and General hospital. Out of the total number, only 199 cases were used for analysis. The remaining 27 cases were recorded as missing cases because of the non-existent addresses in their case files. Table 3.1 presents the frequency distribution of DM incidence across wards in the study area. Bar ward had the highest number of DM incidence 19.1%, Wailomayo ward amounted to 18.6% while Fiidi had 18.1%. Clerks/Market ward had 2%. Agan and Mbalagh wards had no incidence of DM. The result from  this

Figure 3: Spatial Distribution of DM across political wards

Source: Field Survey (2017)

Figure 4: Distribution of DM according to types

table shows that out of the total number of DM patients in the study area (199), Bar ward had the highest number (38) of DM patients.

Findings from this study in Figure 4 revealed that type 2 DM had the highest incidence at 95% while cases for type 1 DM accounted for 4.5%. Gestational DM accounted for 0.5% of the total incidence. This shows that the incidence rate of type 2 DM is the highest. Results from this study agree with a study carried out by Ojobi et.al (2016) on mortality among type 2 diabetic in-patients in a Nigerian tertiary hospital. According to findings, One-tenth (10%) of all the admissions within five years of the study were individuals living with diabetes. The overwhelming majority of 96% had type 2 diabetes, the predominant type of the disease regionally and globally. Also, Oputa and Chinenye (2015) in their study on Diabetes in Nigeria pointed out that more than 95% of cases of diabetes in Nigeria are type 2 DM. The high rate of type 2 DM is as a result of unhealthy diet (fast food, excess refined sugar, excess salt, low fiber), overweight/obesity, lack of regular physical exercise, excessive use of alcohol, advancing age, hypertension, family history, history of previously impaired glucose tolerance (IGT) or impaired fasting glucose (IFG), dyslipidemia, and history of gestational diabetes.

Nearest Neighbour Analysis of the Spatial Distribution of DM

The distribution of DM as shown in Table 3 and figure 5 in Makurdi metropolis is clustered with less than 1%  likelihood

Table 3: Nearest Neighbour Analysis of the Spatial Distribution of DM

Source: Field survey, (2017)

 

Figure 5: Nearest Neighbour showing DM Incidence in Makurdi

Source: Field Survey, (2017)

Figure 6: DM incidence across Hospitals

Source: Field Survey (2017)

that the clustered pattern could be a result of random chance. From the reported cases of DM across the eleven wards of the metropolis, DM is concentrated in Bar (19.1%), Wailomayo (18.6%), and Fiidi (18.1%) wards. The reason for this clustered pattern of DM could be as a result of the high rate of alcohol consumption from numerous beer parlour outlets in these wards. Federal Medical Centre (FMC) shown in figure 6 had a DM incidence of 63% while General hospital had 37% of DM patients.

Table 4 which shows DM incidence across political wards revealed that Fiidi ward recorded the highest number of incidences from the Federal Medical Centre (83.3%) and North bank ward I recorded the highest cases of DM for General hospital (79.2%). This shows that the most patronized hospital is the Federal Medical Centre (FMC).

Table 4: Incidence of DM Across Political Wards by Hospitals

Source: Field Survey, (2017)

Figure 7: DM incidence across residential densities

Source: Field Survey (2017)

From Figure 7. Above 73.9% of patients resides in high-density areas, 10.6% in medium-density while 15.6% are domiciled in low-density residence. The disparity across the wards in Figure 8 revealed the following: Both Bar and Ankpa/Wadata ward did not register patients from the low-density residence. In Ankpa/wadata ward, 14.3% of patients came from medium residential density and 85.7% of patients from high residential density. Bar ward recorded 26.3% of patients for medium density and 73.7% from high density. Fiidi ward had 69.4% patients for low density, 13.9% from medium density, and 16.7% from high residential density. Central/South mission ward had 16.7% for low density, 33.3% patients for medium density, and 50% for high residential density. Clerks/market ward presented 25% case for the medium density and 75% cases for the high residential density. Modern Market ward had 25% of patients from low density and 75% of patients from high density. North bank ward I and II recorded 100% cases from high residential density. Wailomayo ward had 5.41% of patients from low density and 94.6% of patients from high residential density and non from both Agan and Mbalagh wards. The highest number of patients from high residential areas reside in Wailomayo ward at 94.6%, Central/South mission ward had the highest number of patients residing in a medium at 33.3% while Fiidi ward recorded the highest number of patients in low residential density at 699.4%.

Figure 8: The pattern of DM incidence among political wards across residential densities

Source: Field Survey (2017)

Figure 8: Variations in DM incidence across residential densities in Makurdi

Source: Ministry of Lands and Survey Makurdi (2017)

Table 5:      Variation in DM Incidence across different residential densities in Makurdi metropolis

Source: Field Survey (2017)

One Way Analysis of Variance (ANOVA) results in Table 5. revealed that there is a significant variation in the incidence of DM across different residential densities in Makurdi metropolis (F2, 196 = 3.341; p<0.05). This implies that the observed significance value for the cases of DM recorded confirms the existence of spatial variation across the different residential densities in Makurdi metropolis.

Diabetes Miletus (DM) has become an African urgency due to its spiking cases as a result of genetic and environmental factors e.g. urbanization and industrialization, increased longevity, modern sedentary lifestyles, and over-consumption of energy-dense foods.

Bar ward had the highest number of DM incidence at 19.1%, Wailomayo ward 18.6%, and Fiidi had 18.1%. Type 2 DM had the highest incidence at 95% while type 1 DM accounted for 4.5% and gestational DM accounted for 0.5% of the total incidence. The high rate of type 2 DM is a result of an unhealthy diet (fast food, excess refined sugar, excess salt, low fiber), overweight/obesity, lack of regular physical exercise, excessive use of alcohol, advancing age, hypertension, family history, etc.

The distribution of DM in Makurdi metropolis is clustered in Bar (19.1%), Wailomayo (18.6%), and Fiidi (18.1%) wards and across the major hospitals in the city which are the Federal Medical Centre (FMC) and the General Hospital (GM), 63% of DM incidence was reported at FMC with Fidi ward having 83.3% of the cases while 37% of DM patients reported at GM had 79.2% cases from North Bank I. One Way Analysis of Variance (ANOVA) result revealed that there is a significant variation in the incidence of DM across different residential densities in Makurdi metropolis (F2, 196 = 3.341; p<0.05).

Conflict of Interest

The authors all declared a conflict of no interest.

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