Prevalence and Risk Factors for Diabetes Mellitus in an Apparently Healthy Population in the Niger Delta Region of Southern Nigeria


Article views count

 2,265 total views,  6 views today

Greener Journal of Medical Sciences

Vol. 11(2), pp. 190-200, 2021

ISSN: 2276-7797

Copyright ©2021, the copyright of this article is retained by the author(s)

Prevalence and Risk Factors for Diabetes Mellitus in an Apparently Healthy Population in the Niger Delta Region of Southern Nigeria

Amaewhule M N1, Daka I R2, Wekhe C3

1Department of Internal Medicine, Rivers State University Teaching Hospital, Port-harcourt, Nigeria

2Department of Pharmacology, Rivers State University Teaching Hospital, Port-harcourt, Nigeria

3Department of Radiology, Rivers State University Teaching Hospital, Port-harcourt, Nigeria

Article No.: 110821115

Type: Research

Full Text: HTML;EPUB

Introduction: Diabetes Mellitus is a chronic progressive metabolic disorder due to a lack of or resistance of body tissues to the action of insulin leading to persistent hyperglycemia and subsequent target organ damages. The prevalence of Diabetes is on the rise in this part of the world mainly as a result of adoption of Western lifestyle and diet.

Materials and Methods: This was a cross-sectional descriptive study involving 107 voluntary participants in 2 suburban communities in Rivers State, Southern Nigeria. The participants were first administered a structured questionnaire after which their biometric measurements and blood pressure was taken. Thereafter, blood specimen was taken for blood sugar sugar and lipid profile. Data was analysed with the SPSS version 23.0. A p-value of 0.05 was taken to be statistically significant.

Results: The prevalence of Diabetes Mellitus in this study was found to be 16.8%. Diabetes was more common in females, those aged 40 years and above, married and low income earners. Although no risk factor had any statistically significant association with Diabetes Mellitus in this study, there was a higher preponderance of Diabetes in smokers, non-drinkers, high salt consumers, the physically inactive, hypertensives, those with a family history of Diabetes and those with dyslipidemia.

Conclusion: This study revealed a high prevalence of Diabetes Mellitus in the population studied. The higher preponderance of Diabetes in participants with known risk factors for the disease, calls for appropriate intervention targeting such risk factors in order to curb its rising prevalence.

Accepted: 10/11/2021

Published: 15/11/2021

*Corresponding Author

Dr. Daka IR

E-mail: nnendamary@

Phone: +2348036723644

Keywords: Diabetes; Risk Factors; suburban population


Diabetes .mellitus is a chronic metabolic disorder characterized by persistent hyperglycemia. It results from either insufficient production of insulin by the pancreas or the inability of the body to effectively utilize the insulin produced.

Type 1 DM results from insufficient production of insulin by the pancreas while type 2 DM results from ineffective use insulin produced by the pancreas. Other less common types of DM include- gestational DM, maturity onset diabetes of the young, steroid induced diabetes, latent autoimmune diabetes in adults, type 3C diabetes, etc. Majority of cases of DM worldwide (90%) are Type 21. Predisposing factors to type 2 DM are obesity and lack of exercise.

DM is a disease that has a worldwide burden and its prevalence has continued to increase over the years. It rose from4.5% in1980 to 8.5% in 20142. It is a major cause of blindness3, stroke, heart disease and kidney disease4, as well as non-traumatic lower limb amputation.

Type 2 DM used less common in non-Western countries where the diet contains less calories with a higher daily caloric expenditure. However, with the adoption of a western lifestyle (westernization) in these countries, and subsequent development of obesity, the incidence of Type 2 DM has continued to rise. Here in Nigeria, DM affects all parts of the country. The highest prevalence is in the south-south geo-political zone where the Niger Delta is located. Urban dwelling, physical inactivity, advancing age and unhealthy diets are some of the important risk factors for Type 2 DM in Nigeria5.

The World Health Organization (WHO) estimated a 4.3% prevalence of DM in Nigeria in 20166. A recent study reported about 4.7million Nigerians had type 2 DM7.

Type 2 DM accounts for >90% of total cases of DM in Nigeria8,9. Majority of people living with DM (about 2/3) are undiagnosed and therefore untreated. This majority may later present with complications like stroke, myocardial infarction, kidney disease or even death due to untreated DM.

In 2015, more than 40,000 Nigerians died from DM complications10. These deaths were primarily due to the poor state of health care delivery in the country, as well as ignorance, poverty and superstitious beliefs on the part of the patients that prevent them from seeking access to orthodox medical care. It is for this reason that it is recommended that governments make provision for proper screening and diagnosis of DM and ensure adequate health education and care for the diabetic patients in order to reduce the burden of this life-threatening disease.


This was a cross-sectional, descriptive, community-based study that was carried out between October and November 2020. A total of 107 adults were enrolled in this study which took place in Amadi-ama and Fimie communities in Port-Harcourt City Local Government Area of Rivers state, in Southern Nigeria. Ethical approval for this study was obtained from the Ethics Committee of the Rivers State Ministry of Health, Port-Harcourt.

Study participants were all apparently healthy adults aged between 20-80 years and were chosen via convenience sampling. Participation in this study was voluntary. Prior to the study, the communities were sensitized via town criers and church announcements and those that met the inclusion criteria were told to meet in church halls for screening. The inclusion criteria for participation include being >18yearsof age with no previous history of hypertension or diabetes. Individuals that gave their consent were included in the study. Pregnant and lactating women as well as those who are obviously ill or wheel-chair bound were excluded from the study. Strict Covid-19 prevention protocols were also adhered to.

A structured screening questionnaire was given to participants to collect data on their socio-demographic variables, behavioral characteristics, as well as medical history. Thereafter, well trained examiners measured the anthropometric indices and participants were required to wear light, thin clothing and no shoes.

The indices measured were:

a) BMI (Body mass index) which is the body weight/square of height, and the unit is in kg/metre 2.

b)Waist circumference

c) Blood pressure

d) Blood sugar

e) Lipid profile

The body weight was measured using an analogue medical scale while the height was measured with a standard stadiometer. They were measured to the nearest 0.1kg and 0.1cm respectively.

The classes of BMI reported by WHO are:




Classes of obesity include: Class I – 30-34kg/m2, Class II- 35-39.9kg/m2, and Class III- >40Kg/m.2

Blood pressure was measured with a clinically validated electronic sphygmomanometer – OMRON digital fully automated blood pressure monitor. Values were obtained after resting for 5mins in a seated position, with 30 seconds interval between cuff inflation.

Assessments were performed in a dedicated room, with optimum temperature and lighting while respecting privacy.

Blood pressure values were categorised as follows:

(1) Normal: <120/80mm/hg

(2) Pre-hypertension: 120-139/80-89mm/hg

(3) Stage 1: 140-159/90-99mm/hg

(4) Stage 2: > 160/100mm/hg

Biochemical measurements- Blood sugar was assessed using a Finetest glucometer and strip which uses a capillary blood sample which is set to plasma serum standard. Capillary blood is obtained by pricking the participant’s thumb and then placing the drop of blood on the glucometer strip after which the value is read. The diagnosis of diabetes was based on the American Diabetes Association (ADA) Criteria viz : A fasting blood glucose level of 7.0mmol/l or higher or a random blood glucose level of 11.1 mmol/l or higher. The lipid levels were obtained using a 5ml syringe and needle to collect at least 5mls of venous blood into a heparin containing bottle and samples sent to the chemical pathology laboratory for analysis.

Data were analysed using the IBM SPSS Version 23.0



1. Socio-demographic characteristics

A total of 107 respondents were studied, 80 (74.8%) were females, 79 (73.8%) were above 40 years of age (mean age was 49.4 years and standard deviation was 13.7 years), 87 (81.3%) were currently married or had been married before and 43 (40.2%) had tertiary level of education. Close to half of the respondents (46.7%) were self-employed and the monthly income of 67 (62.6%) was low (table 1).

Table 1: Socio-demographic Characteristics

  Frequency (n=107) Percent
Male 27 25.2
Female 80 74.8
Age group    
≤40 28 26.2
>40 79 73.8
Mean Age (SD) 49.4 (13.7)  
Marital status    
Never married 20 18.7
Ever married 87 81.3
Level of education    
Non-formal 5 4.7
Primary 27 25.2
Secondary 32 29.9
Tertiary 43 40.2
Self-employed 50 46.7
Unemployed 19 17.8
Student 7 6.5
Others 24 22.4
Civil servant 5 4.7
Retired 2 1.9
Monthly income    
Low 67 62.6
Medium 20 18.7
High 20 18.7

SD=Standard deviation


2. Life style characteristics/Medical history

Only 11 (10.3%) of the respondents’ smoke tobacco and were all previous smokers, 28 (26.2%) currently drink alcohol, 84 (78.5) do not consume adequate amount of fruits and vegetables, 16 (15.0%) add extra salt to their meal and 51 (47.7%) do no engage in physical activities. Thirty-five (32.7%) of the respondents reported history of hypertension while 43 (40.2%) reported family history of hypertension, similarly, 14 (13.1%) reported history of diabetes while 19 (17.8%) reported family history of diabetes (table 2).

Table 2: Life style characteristics/medical history

  Frequency (n=107) Percent
Tobacco Use    
Never Smoked 96 89.7
Previous Smoker 11 10.3
Alcohol Consumption    
Current Drinker 28 26.2
Previous Drinker 31 29.0
Never Drank 48 44.9
Fruit and Vegetable Consumption    
Adequate 23 21.5
Inadequate 84 78.5
Salt Consumption    
High 16 15.0
Normal 91 85.0
Engage in Physical Activity    
Yes 56 52.3
No 51 47.7
History of Hypertension    
Yes 35 32.7
No 72 67.3
Family History of Hypertension    
Yes 43 40.2
No 64 59.8
History of Diabetes    
Yes 14 13.1
No 93 86.9
Family History of Diabetes    
Yes 19 17.8
No 88 82.2

3. Prevalence of Diabetes

The prevalence of Diabetes was 16.8% (n=18) among the study population (figure 1).

Figure 1: Prevalence of diabetes among study population

The prevalence of diabetes did not show any statistically significant relationship with the socio-demographic characteristics of respondents (p>0.05). See table 3.

Also, diabetes prevalence did not show any statistically significant relationship with life style characteristics of respondents (p>0.05). See table 4.


Table 3. Prevalence of Diabetes by Socio-demographic Characteristics

  Not diabetic (n=89) Diabetic (n=18)    
  Frequency Percent Frequency Percent ꭓ2 p-value
Marital status            
Never married 19 95.0% 1 5.0% 2.457 0.117
Ever married 70 80.5% 17 19.5%    
Age group (years)            
≤40 25 89.3% 3 10.7% 1.011 0.315
>40 64 81.0% 15 19.0%    
Male 23 85.2% 4 14.8% 0.104 0.747
Female 66 82.5% 14 17.5%    
Level of education            
Non-formal 4 80.0% 1 20.0% 2.497 0.476
Primary 20 74.1% 7 25.9%    
Secondary 27 84.4% 5 15.6%    
Tertiary 38 88.4% 5 11.6%    
Self-employed 40 80.0% 10 20.0% 3.436 0.633
Unemployed 15 78.9% 4 21.1%    
Student 7 100.0% 0 0.0%    
Others 20 83.3% 4 16.7%    
Civil servant 5 100.0% 0 0.0%    
Retired 2 100.0% 0 0.0%    
Monthly income            
Low 54 80.6% 13 19.4% 1.032 0.597
Medium 18 90.0% 2 10.0%    
High 17 85.0% 3 15.0%    

*=Statistically significant


Table 4. Prevalence of Diabetes by Life Style Characteristics

  Not diabetic (n=89) Diabetic (n=18)    
  Frequency Percent Frequency Percent ꭓ2 p-value
Tobacco use            
Never smoked 80 83.3% 16 16.7% 0.016 0.899
Previous smoker 9 81.8% 2 18.2%    
Alcohol consumption            
Current drinker 26 92.9% 2 7.1% 3.160 0.206
Previous drinker 26 83.9% 5 16.1%    
Never drank 37 77.1% 11 22.9%    
Fruit and vegetable consumption            
Adequate 18 78.3% 5 21.7% 0.506 0.477
Inadequate 71 84.5% 13 15.5%    
Salt consumption            
High 12 75.0% 4 25.0% 0.899 0.343
Normal 77 84.6% 14 15.4%    
Engage in physical activity            
Yes 47 83.9% 9 16.1% 0.047 0.828
No 42 82.4% 9 17.6%    
History of hypertension            
Yes 27 77.1% 8 22.9% 1.354 0.245
No 62 86.1% 10 13.9%    
Family history of hypertension            
Yes 37 86.0% 6 14.0% 0.423 0.516
No 52 81.3% 12 18.8%    
History of diabetes            
Yes 10 71.4% 4 28.6% 1.589 0.207
No 79 84.9% 14 15.1%    
Family history of diabetes            
Yes 14 73.7% 5 26.3% 1.488 0.223
No 75 85.2% 13 14.8%    

*=Statistically significant


Physical and biochemical measurements of the population

Physical measures of the population

Thirty-four (31.8%) of the respondents had normal waist circumference. The mean waist circumference was 89.0±12.5cm for males and 91.7±16.2cm for females. Seven (6.5%) of the respondents were underweight, 38 (35.5%) had normal weight, 31 (29.0%) were overweight, and another 31 (29.0%) were obese. The mean BIM, weight and height were 27.9±8.9Kgm2, 70.3±16.8Kg and 160.6±12.0cm respectively. It was also shown that 46 (43.0%). The mean SBP and DBP were 143.2±32.4mmHg and 87.1±18.3mmHg respectively.

Biochemical measures of the population

The study also found that 38 (35.5%) of the respondents had normal total cholesterol level (mean±SD=5.5±1.0mmol/l), 101 (94.4%) had triglyceride level (mean±SD=0.9±0.3mmol/l), 105 (98.1%) had normal high-density lipoprotein (mean±SD=0.94±0.2mmol/l) and 23 (21.5%) had low-density lipoprotein (mean±SD=4.14±0.9mmol/l). See table 5 below.


Table 5: Physical and biochemical measurements of the population

  Frequency (n=107) Percent
Physical parameter    
Waist circumference    
Normal 34 31.8
Abnormal 73 68.2
Mean waist circumference (SD)    
Male (n=27) 89.0 (12.5)  
Female (n=80) 91.7 (16.2)  
BMI Category    
Underweight 7 6.5
Normal weight 38 35.5
Overweight 31 29
Obese 31 29
Mean BMI (SD) 27.9 (8.9)  
Mean weight (SD) 70.3 (16.8)  
Mean height (SD) 160.6 (12.0)  
Blood pressure status    
Normal 46 43
High 61 57
Mean SBP (SD) 143.2 (32.4)  
Mean DBP (SD) 87.1 (18.3)  
Biochemical parameter    
TC Category    
Normal 38 35.5
High 69 64.5
Mean TC (SD) 5.5 (1.0)  
TG Category    
Normal 101 94.4
High 6 5.6
Mean TG (SD) 0.9 (0.3)  
HDL Category    
Abnormal 105 98.1
Normal 2 1.9
Mean HDL (SD) 0.94 (0.2)  
LDL Category    
Normal 23 21.5
Abnormal 84 78.5
Mean LDL (SD) 4.14 (0.9)  

*=Statistically significant


Prevalence of Diabetes by physical and biochemical characteristics

There was no statistically significant difference in the prevalence of diabetes across respondent’s physical measures such as waist circumference, BMI and blood pressure status; and across respondent’s biochemical measures such as total cholesterol, triglyceride, HDL and LDL levels (p>0.05). See table 6 below.

Table 6. Prevalence of Diabetes by physical and biochemical characteristics

  Not diabetic (n=89) Diabetic (n=18)    
  Frequency Percent Frequency Percent ꭓ2 p-value
Physical measures
Waist circumference            
Normal 30 88.2% 4 11.8% 0.911 0.340
Abnormal 59 80.8% 14 19.2%    
BMI Category            
Underweight 6 85.7% 1 14.3% 1.142 0.767
Normal weight 33 86.8% 5 13.2%    
Overweight 24 77.4% 7 22.6%    
Obese 26 83.9% 5 16.1%    
Blood pressure status            
Normal 40 87.0% 6 13.0% 0.823 0.364
High 49 80.3% 12 19.7%    
Biochemical measures
TC Category            
Normal 31 81.6% 7 18.4% 0.108 0.743
High 58 84.1% 11 15.9%    
TG Category            
Normal 85 84.2% 16 15.8% 1.238 0.265
High 4 66.7% 2 33.3%    
HDL Category            
Abnormal 88 83.8% 17 16.2% 1.603 0.309
Normal 1 50.0% 1 50.0%    

*=Statistically significant


This study assessed the prevalence and risk factors for diabetes mellitus in a suburban community in the Niger Delta region of Southern Nigeria.

The prevalence of diabetes in the studied population was found to be 16.8%. This figure is higher than that obtained from previous studies on the prevalence of diabetes in Nigeria which ranged from 2-12%. 11-14 However, a previous study done in the South-south region of this country revealed a higher prevalence of 13.9%15. These figures are all lower than that noted in this study.

This increase in prevalence is most likely due to population growth and aging, urbanization, increasing prevalence of obesity as well as inadequate exercise being experienced worldwide. This is also in keeping with the predicted global increase in diabetes globally, including Africa 16-18.

In this study, there was no socio-demographic characteristic that was significantly associated with diabetes mellitus, however, diabetes had a higher preponderance in the participants who are married, >40 years of age, females, have only primary level of education, unemployed, and low income earners. Other studies done previously have reported a lower prevalence of diabetes mellitus in married people, in contrast to this study 19,20 ; however, the lower preponderance of diabetes mellitus noted in the married participants in this study may be attributable to the fact that married persons (esp. females) in this part of the country tend to become obese 21 .

Another, well known risk factor for diabetes mellitus is advancing age. In this study, participants that are above 40 years of age had a higher preponderance of diabetes mellitus. This is in keeping with other studies done elsewhere 8,22. The increase in diabetes mellitus ith increasing age is mainly due to the fact that aging induces a decrease in insulin sensitivity as well as inadequate compensation of beta cell functional mass despite increasing insulin insulin resistance 23. There is also a correlation between aging and reduction in beta cell proliferation and also increased sensitivity to apoptosis 24.

Female participants were also found to have a higher preponderance of diabetes mellitus in this study. Although, this is not statistically significant, it is in keeping with other studies done in this part of the country 25,26. These studies also reported a higher number of females than males with diabetes mellitus. However, worldwide, more males than females have been reported to have diabetes mellitus 27. This contrast with the global picture may be attributable to the cultural practice in this part of the country that encourages obesity in women, especially the practice of the ‘fattening room’ that is prevalent in the Niger Delta region of Southern Nigeria 28.

None of the lifestyle characteristics studied has any statistically significant association with diabetes mellitus. This may be due to the small sample size used in this study.

Overweight and obese individuals were also found to have a higher preponderance of diabetes mellitus in this study. This is in keeping with other studies that have emphasized the link between diabetes mellitus and obesity. Obesity is a well known risk factor for diabetes mellitus 29-31.

Diabetes mellitus also has a higher prevalence in participants who are hypertensive. Other previous studies have noted a similar trend 32,33. This may be explained by the common pathways shared by both diseases which may ultimately lead to the development of the metabolic syndrome 34.

Participants with abnormally high levels of triglycerides also had a higher prevalence of diabetes mellitus. This is not surprising as hypertriglyceridaemia has been noted to be a risk factor for type 2 diabetes mellitus 35,36.

Low HDL-cholesterol and high total cholesterol are both known risk factors for the development of type 2 diabetes mellitus 37-39. However, the reverse is the case in this study. This may be due to the possible presence of other confounding risk factors for diabetes mellitus in this study.


This study revealed a high prevalence of Diabetes Mellitus in a suburban region of the Niger Delta area of Southern Nigeria. There was no statistically significant risk factor associated with diabetes, however there was a higher preponderance of Diabetes in participants who are above 40 years of age, married, smokers, consume excess salt, physically inactive, hypertensive, and have dyslipidemia. This result may be attributed to the small sample size used in this study. In view of the findings in this study, appropriate intervention targeting these risk factors will go a long way to curb the rising prevalence of Diabetes in this part of the world.


1) IDF Diabetes Atlas, 9th edition, 2019, page 14

2) Emerging Risk Factors Collaboration, Sarwar N, Gao P, Seshasai SR, Gobin R, Kaptoge S, Di Angelantonio E, Ingelsson E, Lawlor DA, Selvin E, Stampfer M, Stehouwer CD, Lewington S, Pennells L, Thompson A, Sattar N, White IR, Ray KK, Danesh J. Diabetes mellitus, fasting blood glucose concentration, and risk of vascular disease: a collaborative meta-analysis of 102 prospective studies. Lancet. 2010 Jun 26;375(9733):2215-22.

3) Bourne RR, Stevens GA, White RA, Smith JL, Flaxman SR, Price H, Jonas JB, Keeffe J, Leasher J, Naidoo K, Pesudovs K, Resnikoff S, Taylor HR; Vision Loss Expert Group. Causes of vision loss worldwide, 1990-2010: a systematic analysis. Lancet Glob Health. 2013 Dec;1(6):e339-49.

4) Saran R, Li Y, Robinson B, Ayanian J, Balkrishnan R, Bragg-Gresham J, Chen JT, Cope E, Gipson D, He K, Herman W, Heung M, Hirth RA, Jacobsen SS, Kalantar-Zadeh K, Kovesdy CP, Leichtman AB, Lu Y, Molnar MZ, Morgenstern H, Nallamothu B, O’Hare AM, Pisoni R, Plattner B, Port FK, Rao P, Rhee CM, Schaubel DE, Selewski DT, Shahinian V, Sim JJ, Song P, Streja E, Kurella Tamura M, Tentori F, Eggers PW, Agodoa LY, Abbott KC. US Renal Data System 2014 Annual Data Report: Epidemiology of Kidney Disease in the United States. Am J Kidney Dis. 2015 Jul;66(1 Suppl 1):Svii, S1-305.

5) Motala AA, Omar MA, Pirie FJ. Diabetes in Africa. Epidemiology of type 1 and type 2 diabetes in Africa. J Cardiovasc Risk. 2003 Apr;10(2):77-83.

6) Muhammad F. Diabetes: A Silent Killer in Nigeria, Jundishapur J Chronic Dis Care. 9(4): e105702.doi: 10.5812/jjcdc.105702.12668904.

7) Uloko AE, Musa BM, Ramalan MA, Gezawa ID, Puepet FH, Uloko AT, Borodo MM, Sada KB. Prevalence and Risk Factors for Diabetes Mellitus in Nigeria: A Systematic Review and Meta-Analysis. Diabetes Ther. 2018 Jun;9(3):1307-1316.

8) Uloko AE, Ofoegbu EN, Chinenye S, Fasanmade OA, Fasanmade AA, Ogbera AO, Ogbu OO, Oli JM, Girei BA, Adamu A. Profile of Nigerians with diabetes mellitus – Diabcare Nigeria study group (2008): Results of a multicenter study. Indian J Endocrinol Metab. 2012 Jul;16(4):558-64. doi:

9) Leive A, Xu K. Coping with out-of-pocket health payments: empirical evidence from 15 African countries. Bull World Health Organ. 2008 Nov;86(11):849-856.

10) Muanya C. 1.6m Nigerians live with diabetes as disease kills over 40,000. 2016, [cited 2020 Apr 27]. Available from:

11) Nyenwe EA, Odia OJ, Ihekwaba AE, Ojule A, Babatunde S. Type 2 diabetes in adult Nigerians: a study of its prevalence and risk factors in Port Harcourt, Nigeria. Diabetes Res Clin Pract. 2003 Dec;62(3):177-85.

12) Puepet FH, Ohwovoriole AE. Prevalence of risk factors for diabetes mellitus in a non-diabetic population in Jos, Nigeria. Niger J Med. 2008 Jan-Mar;17(1):71-4.

13) Sabir, A.A., Isezuo, S.A. and Ohwovoriole, A.E. (2011) Dysglycaemia and Its Risk Factors in an Urban Fulani Population of Northern Nigeria. West African Journal of Medicine, 30, 325-330.

14) Gezawa I D, Puepet F H, Mubi B M, Uloko A E, Bakki B, Talle M A, Haliru I. Socio-demographic and Anthropometric risk factors for Type 2 diabetes in Maiduguri, North-Eastern Nigeria. Sahel Med J 2015;18, Suppl S1:1-7

15) Egbi, Oghenekaro & Ahmed, Sulaiman. (2020). Prevalence of Diabetes Mellitus in a Rural, Agrarian Community in South-South Nigeria. Research Journal of Health Sciences. 8. 201-208. 10.4314/rejhs.v8i3.6.

16) International Diabetes Federation Diabetes Atlas, 9 th edition. Brussels, Belgium: Interntional Diabetes Fed.2019;107843.

17) Saeedi P, Petersohn I, Salpea P, Malanda B, Karuranga S, Unwin N, Colagiuri S, Guariguata L, Motala AA, Ogurtsova K, Shaw JE, Bright D, Williams R; IDF Diabetes Atlas Committee. Global and regional diabetes prevalence estimates for 2019 and projections for 2030 and 2045: Results from the International Diabetes Federation Diabetes Atlas, 9th edition. Diabetes Res Clin Pract. 2019 Nov;157:107843. doi: 10.1016/j.diabres.2019.107843. Epub 2019 Sep 10. PMID: 31518657.

18) NCD Risk Factor Collaboration (NCD-RisC) – Africa Working Group. Trends in obesity and diabetes across Africa from 1980 to 2014: an analysis of pooled population-based studies. Int J Epidemiol. 2017 Oct 1;46(5):1421-1432. doi: 10.1093/ije/dyx078. PMID: 28582528; PMCID: PMC5837192.

19) de Oliveira CM, Viater Tureck L, Alvares D, Liu C, Horimoto ARVR, Balcells M, de Oliveira Alvim R, Krieger JE, Pereira AC. Relationship between marital status and incidence of type 2 diabetes mellitus in a Brazilian rural population: The Baependi Heart Study. PLoS One. 2020 Aug 3;15(8):e0236869. doi: 10.1371/journal.pone.0236869. PMID: 32745127; PMCID: PMC7398527.

20) Flor LS, Campos MR. The prevalence of diabetes mellitus and its associated factors in the Brazilian adult population: evidence from a population-based survey. Rev Bras Epidemiol. 2017 Jan-Mar;20(1):16-29. Portuguese, English. doi: 10.1590/1980-5497201700010002. PMID: 28513791.

21) Unamba N, Unamba B. Prevalence of metabolic syndrome and its components in an adult Nigerian population attending a tertiary hospital. The Nigerian Health Journal,vol 17,No 3 (2017) p105-118.

22) Kasia BE, Oyeyemi AS, Opubiri I, Azonobi RI. Prevalence and Risk Factors of Diabetes Mellitus and Pre-diabetes in Rural Communities in Bayelsa State, Niger Delta Region of Nigeria. Nig Del Med J 2020; 4: 14-24

23) Meneilly GS, Elliott T. Metabolic alterations in middle-aged and elderly obese patients with type 2 diabetes. Diabetes Care. 1999 Jan;22(1):112-8. doi: 10.2337/diacare.22.1.112. PMID: 10333911.

24) Maedler K, Schumann DM, Schulthess F, Oberholzer J, Bosco D, Berney T, Donath MY. Aging correlates with decreased beta-cell proliferative capacity and enhanced sensitivity to apoptosis: a potential role for Fas and pancreatic duodenal homeobox-1. Diabetes. 2006 Sep;55(9):2455-62. doi: 10.2337/db05-1586. Retraction in: Diabetes. 2020 Mar;69(3):494. PMID: 16936193.

25) Ekpenyong, Christopher, Akpan, U., Ibu, John , Nyebuk Daniel. (2011). Gender and age specific prevalence and associated risk factors of type 2 diabetes mellitus in Uyo metropolis, South Eastern Nigeria. Diabetol Croat. 41.November 2011

26) Chukwunonso ECC, Nnamdi KU. Diabetes and pre-diabetes in adult Nigerians: prevalence, and correlations of blood glucose concentrations with measures of obesity. Afr J Biochem Res. 2015;9(3):55–60.

27) International Diabetes Federation (2013) IDF Diabetes Atlas. 6th Edition, International Diabetes Federation, Brussels.

28) Enang, Ofem. (2009). The fattening rooms of Calabar- a breeding ground for diabesity. DiabetesVoice. May 2009. Vol 54. Special issue. P 40-41.

29) American Society for Metabolic and Bariatric Surgery; Type 2 Diabetes and Metabolic Surgery.October 2018.Accessed March 6 2021.

30) Mayer-Davis EJ, Costacou T. Obesity and sedentary lifestyle: modifiable risk factors for prevention of type 2 diabetes. Curr Diab Rep. 2001 Oct;1(2):170-6. doi: 10.1007/s11892-001-0030-x. PMID: 12643113.

31) Lieberman LS. Dietary, evolutionary, and modernizing influences on the prevalence of type 2 diabetes. Annu Rev Nutr. 2003;23:345-77.

32) Ogunmola OJ, Ajani GO, Olabinri EO (2019) Prevalence of Diabetes Mellitus in Outpatients with Essential Hypertension in a Rural Tertiary Hospital. Int J Diabetes Clin Res 6:115.

33) Emdin CA, Anderson SG, Woodward M, Rahimi K. Usual Blood Pressure and Risk of New-Onset Diabetes: Evidence From 4.1 Million Adults and a Meta-Analysis of Prospective Studies. J Am Coll Cardiol. 2015 Oct 6;66(14):1552-1562.

34) Movahed MR, Sattur S, Hashemzadeh M. Independent association between type 2 diabetes mellitus and hypertension over a period of 10 years in a large inpatient population. Clin Exp Hypertens. 2010 May;32(3):198-201.

35) Aynalem SB, Zeleke AJ. Prevalence of Diabetes Mellitus and Its Risk Factors among Individuals Aged 15 Years and Above in Mizan-Aman Town, Southwest Ethiopia, 2016: A Cross Sectional Study. Int J Endocrinol. 2018 Apr 26;2018:9317987.

36) Perry IJ, Wannamethee SG, Walker MK, Thomson AG, Whincup PH, Shaper AG. Prospective study of risk factors for development of non-insulin dependent diabetes in middle aged British men. BMJ. 1995 Mar 4;310(6979):560-4.

37) Schmidt MI, Duncan BB, Bang H, Pankow JS, Ballantyne CM, Golden SH, Folsom AR, Chambless LE; Atherosclerosis Risk in Communities Investigators. Identifying individuals at high risk for diabetes: The Atherosclerosis Risk in Communities study. Diabetes Care. 2005 Aug;28(8):2013-8.

38) Wilson PW, Meigs JB, Sullivan L, Fox CS, Nathan DM, D’Agostino RB Sr. Prediction of incident diabetes mellitus in middle-aged adults: the Framingham Offspring Study. Arch Intern Med. 2007 May 28;167(10):1068-74.

39) Rhee E-J, Han K, Ko S-H, Ko K-S, Lee W-Y (2017) Increased risk for diabetes development in subjects with large variation in total cholesterol levels in 2,827,950 Koreans: A nationwide population-based study. PLoS ONE 12(5): e0176615.

Cite this Article: Amaewhule MN; Daka IR; Wekhe C (2021). Prevalence and Risk Factors for Diabetes Mellitus in an Apparently Healthy Population in the Niger Delta Region of Southern Nigeria. Greener Journal of Medical Sciences, 11(2): 190-200.


Loader Loading...
EAD Logo Taking too long?

Reload Reload document
| Open Open in new tab

Download [417.40 KB]

 2,263 total views,  4 views today

Leave a Reply

Your email address will not be published. Required fields are marked *

× Chat on Whatsapp?