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 Table of Contents  
ORIGINAL ARTICLE
Year : 2019  |  Volume : 6  |  Issue : 1  |  Page : 26-30

Beta-cell function and insulin resistance among First-Degree relatives of persons with type 2 diabetes in a Northwestern Nigerian Population


1 Department of Internal Medicine, Federal Medical Centre, Azare, Bauchi State, Nigeria
2 Department of Internal Medicine, Ahmadu Bello University Teaching Hospital, Zaria, Nigeria
3 Department of Internal Medicine, College of Health Sciences, University of Abuja, Abuja, Nigeria

Date of Submission09-Dec-2018
Date of Acceptance23-Jan-2019
Date of Web Publication30-Apr-2019

Correspondence Address:
Dr. Yakubu Lawal
Federal Medical Centre, Azare, Bauchi State
Nigeria
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jhrr.jhrr_52_18

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  Abstract 


Background and Aims: Pancreatic beta-cell deficit and insulin resistance (IR) form two major factors in the etiopathogenesis of type 2 diabetes. The aim of this study is to assess beta-cell function and IR among first-degree relatives (FDRs) of persons with type 2 diabetes in a Northwestern Nigerian population. Other objectives include assessing the relationships among HOMA-%B, HOMA-IR, plasma glucose levels, and some obesity indices and to determine whether beta cell function, IR, and some obesity indices are independent determinants of glucose intolerance in the studied population. Materials and Methods: A total of 200 individuals and 200 controls were recruited through cluster sampling from their respective communities after due consent. The relevant biodata was documented and appropriate examinations including anthropometric measurements were carried out. Oral glucose tolerance test was carried out and fasting plasma insulin levels were also measured. IR and beta-cell function were calculated using homeostasis model assessment (HOMA) method. Results: Mean HOMA-IR was higher while HOMA-% B lower among FDRs compared to controls. Significant independent determinants of glucose intolerance with odds ratio (OR) and confidence interval (CI) included age (OR = 1.9, CI 1.9–2.0, P = 0.002), body mass index (OR = 1.9, CI 1.8–2.0, P = 0.032), waist circumference (OR = 2.0, CI 1.9–2.0, P = 0.043), waist-to-hip ratio (OR = 1.1, CI 1.0–15.7, P = 0.022), HOMA-IR (OR = 3.0, CI 2.3–3.3, P < 0.001), and HOMA-B (OR = 0.43, CI 0.24–0.65, P < 0.001) which means HOMA-%B is protective against glucose intolerance with inverse OR of 1/0.43 = 2.3. Conclusions: IR was higher and beta cell functions lower among FDRs compared to controls. IR (HOMA-IR) and some obesity indices were significant determinants of glucose intolerance while HOMA-%B was protective against glucose intolerance in this study.

Keywords: Beta-cell function, diabetes mellitus, glucose intolerance, insulin resistance


How to cite this article:
Lawal Y, Bello F, Anumah FE, Bakari AG. Beta-cell function and insulin resistance among First-Degree relatives of persons with type 2 diabetes in a Northwestern Nigerian Population. J Health Res Rev 2019;6:26-30

How to cite this URL:
Lawal Y, Bello F, Anumah FE, Bakari AG. Beta-cell function and insulin resistance among First-Degree relatives of persons with type 2 diabetes in a Northwestern Nigerian Population. J Health Res Rev [serial online] 2019 [cited 2024 Mar 28];6:26-30. Available from: https://www.jhrr.org/text.asp?2019/6/1/26/257483




  Introduction Top


Pancreatic beta-cell dysfunction and insulin resistance (IR) form 2 major factors in the etiopathogenesis of type 2 diabetes.[1],[2] Beta-cell dysfunction occurs when the beta cells are unable to produce optimum insulin concentration needed to maintain glucose homeostasis while IR is a state in which a given concentration of insulin produces a less-than expected biological effect.[1],[2] Pathophysiologically, persistent IR will eventually result in beta-cell dysfunction when the maximum insulin produced by the beta cells is no longer enough to surmount IR.[2] There are several methods of assessing beta cell function and IR including the homeostasis model assessment (HOMA)-%B and HOMA-IR, respectively.[1],[2]

Varied degrees of IR and beta cell dysfunction have been reported by various authors as the cause of glucose intolerance in different populations of the world.[1],[2],[3],[4],[5],[6],[7],[8] Kim et al.,[1] Grobusch et al.,[5] and Meeks et al.[9] emphasized the involvement of both IR and beta-cell dysfunction in the pathogenesis of diabetes in sub-Saharan Africans and South-East Asians. In a study involving different segments of Nigerian population, Awofisoye et al.[10] and Bakari and Onyemelukwe[11] reported predominant IR among type 2 diabetes mellitus (DM) patients. IR was also implicated by several other authors as the predominant defect in obese individuals with or without type 2 DM.[12],[13],[14]

Our aim is to assess beta cell function and IR among first-degree relatives (FDRs) of persons with type 2 diabetes in a Northwestern Nigerian population. Other objectives include assessing the relationship among HOMA-%B, HOMA-IR, plasma glucose levels, and some obesity indices and to determine whether HOMA-%B, HOMA-IR, and some obesity indices are independent determinants of glucose intolerance in the studied population. Furthermore, there are not many studies on beta-cell function and IR in Northern Nigeria also justifying the need for this research.


  Materials and Methods Top


This was a cross-sectional observational study carried out in Zaria, Northern Nigeria over a period of 1 year. Zaria is a major city in Kaduna State of Northern Nigeria. The predominant occupation of the men includes farming and trading while the women are mainly homemakers who engage in domestic works.

This study was approved by the Ethics Committee of Ahmadu Bello University Teaching Hospital Zaria (certificate number ABUTH/HREC/TRG/36) and is in accordance with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. Informed consents were taken from the participants. Two hundred FDRs of persons with type 2 diabetes and 200 controls who satisfied the inclusion criteria were enrolled. Inclusion criteria included individuals who were not previously known to have diabetes within the age of 18–70 years while exclusion criteria included individuals known to have DM, individuals on medications that affect glucose metabolism such as steroids, thiazides, beta blockers or HIV protease inhibitors, and individuals who declined consent.

The sample selection was achieved by random sampling from some communities. The essence and procedures of the study were explained to each subject and consent subsequently obtained before enrolment.

The World Health Organization (WHO)-3 steps pro forma[15] modified to suit the peculiarities of this study was used for data collection. These included history, measurement of some anthropometric indices, and laboratory investigation results (fasting plasma glucose 26, 2 h postprandial plasma glucose [PPG], and fasting insulin level).

Anthropometric measurements were carried out by the researcher with the help of a trained assistant and in the presence of a chaperone. Standing height was measured using a stadiometer (Seca 213 portable stadiometer, Seca North America, USA). Each subject's head was positioned in the Frankfort horizontal plane (i.e., when the horizontal line from the ear canal to the lower border of the orbit is parallel to the floor and perpendicular to the vertical backboard), then the height was measured to the nearest 0.1 cm.[16]

Individuals were then, weighed in kilograms using a beam balance (Seca 700 series, Seca North America, USA). They were asked to wear only light clothings/undergarments, stand in the center of the scale platform with hands at the sides, looking straight ahead, and weight evenly distributed. The weight was then recorded in kilograms to the nearest 0.5 kg. Waist circumference (WC) was measured using a measuring tape (NON 171330, 72”, Medline industries Inc., USA). Each subject was instructed to cross the arms and place the hands on opposite shoulders. The WC was measured to the nearest 0.1 cm midway between the iliac crest and the costal margin along the midaxillary line. Values >94 cm for male individuals and >80 cm for female individuals were used to define abdominal obesity.[16]

Each subject was asked to stand up with feet together and weight evenly distributed on both feet, the hip circumference was then measured to the nearest 0.1 cm with a measuring tape placed around the hip at the level of the greater trochanters. If the greater trochanter was not palpable, the largest horizontal girth around the buttocks was used.[16]

Subsequently, oral glucose tolerance test was performed for each subject. Individuals were asked to take normal diet with no carbohydrate restriction 72 h before test. They then fasted for 8–12 h overnight before test day (water was allowed). At 0900 h, blood sample for FPG and fasting insulin levels were drawn from each subject's antecubital vein.

Each subject was then given a 75 g anhydrous glucose load in 250 mL of water to drink within 5 min. Two hours after the oral glucose load, venous blood from each subject was again drawn for plasma glucose determination using the glucose oxidase method. The WHO criteria were used in the diagnosis of impaired fasting glucose (FPG >6.1 mmol/L), impaired glucose tolerance (2 h PPG >7.8 mmol/L), and DM (FPG >7.0 mmol/L and/or 2 h PPG >11.1 mmol/L).

Fasting insulin level was determined using insulin Elisa kit (Cortez Diagnostics with detection range of 0–600 U/L, sensitivity 4.6 U/ml). The homeostasis model assessment of insulin resistance (HOMA-IR) was calculated as fasting plasma insulin (mIU/L) × FPG (mmol/L) divided by 22.5. A value of <2.2 was taken as normal; and above 2.2 as IR. Homeostasis model assessment beta cell function (HOMA-%B) was calculated as (20 × fasting plasma insulin) divided by (FPG – 3.5).[17],[18]

Statistical analysis

Microsoft excel was used for data entry and statistical package for social sciences (SPSS) version 19 software by IBM, SPSS Inc., New York, USA was used for data analysis. Results were expressed as means ± standard deviation at 95% confidence interval (CI).

Students t-test was used to compare continuous variables and Chi-square for categorical variables. Spearman's correlation was used to test for association among HOMA-%B, HOMA-IR, plasma glucose levels, body mass index (BMI), WC, and waist-hip ratio (WHR). Logistic regression was used to assess whether HOMA-%B, HOMA-IR, and some obesity indices were independent determinants of glucose intolerance. P value was considered as statistically significant when ≤0.05.


  Results Top


This study was carried out to assess beta cell function and IR among FDRs of persons with type 2 diabetes and to determine whether HOMA-%B, HOMA-IR, and some obesity indices were significant independent determinants of glucose intolerance in a Northwestern Nigerian population. At the beginning of this study, 200 FDRs and 200 controls were enrolled out of which four respondents were excluded from analysis due to incomplete laboratory results. Response rate was 99% with a male:female ratio of 1–1.1 and peak age of 31–50 years.

The mean age (years) of FDRs and controls was 40.2 ± 10.1 and 40.6 ± 10.7, respectively. The mean HOMA-IR of FDRs (5.45 ± 3.0) was higher than that of controls (1.8 ± 1.2) while the mean HOMA-B (%) of FDRs (85.0 ± 10.3) was lower than that of controls (109.5 ± 34.8). The mean BMI, WC, and WHR of FDRs were higher than that of controls [Table 1].
Table 1: Some obesity indices and laboratory results of individuals

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The mean age (years) of female individuals was (41.3 ± 11.2) while that of male individuals was 39.5 ± 9.4. The mean HOMA-IR of female individuals (2.56 ± 1.36) was higher than that of male individuals (2.28 ± 1.26) while the mean HOMA-B (%) of female individuals (97.1 ± 30.6) was lower than that of male individuals (99.1 ± 34.7). The mean BMI, WC for sex, WHR for sex of the female individuals were higher than those of the male individuals [Table 2].
Table 2: Sex distribution of obesity indices and laboratory results among individuals

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There were significant positive correlations between FPG and the following variables: HOMA-IR (P < 0.001), BMI (P < 0.001), WC (P < 0.001), and WHR (P < 0.001), however FPG was significantly but inversely correlated with HOMA-B (P < 0.001). Similar correlation pattern was also found between 2 h PPG and the following variables: HOMA-IR (P < 0.001), BMI (P < 0.001), WC (P < 0.001), WHR (P < 0.001), and HOMA-B (P < 0.001) [Table 3].
Table 3: Spearman's correlation of obesity indices and laboratory results

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Following logistic regression analysis, significant independent determinants of glucose intolerance with their odds ratio (OR) and CI included age (OR = 1.9, CI 1.9–2.0, P = 0.002), BMI (OR = 1.9, CI 1.8–2.0, P = 0.032), WC (OR = 2.0, CI 1.9–2.0, P = 0.043), WHR (OR = 1.1, CI 1.0–15.7, P = 0.022), HOMA-IR (OR = 3.0, CI 2.3–3.3, P < 0.001), HOMA-B (OR = 0.43, CI 0.24–0.65, P < 0.001). Since the OR of HOMA-%B is <1, it therefore means HOMA-%B is protective against glucose intolerance with OR of 1/0.43 = 2.3 [Table 4].
Table 4: Logistic regression showing determinants of glucose intolerance among individuals

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  Discussion Top


This study was carried out to assess beta-cell function (HOMA-B) and (HOMA-IR) among FDRs of persons with type 2 diabetes. The mean HOMA-B was lower among FDRs compared to controls while the mean HOMA-IR was higher among FDRs. This shows that beta-cell deficit and IR are twin characteristics of FDRs of the population studied. This is similar to reports by Grobusch et al.[5] in a sub-Saharan African population and Nyenwe et al.[7] among ethnic nationalities in the US.

Sex distribution of data showed that female individuals had higher mean HOMA-IR but slightly lower mean HOMA-%B. Therefore, the higher mean plasma glucose levels among the female individuals may be due predominantly to IR than beta cell dysfunction. This reflects the higher mean BMI, WC for sex, and WHR for sex among the female individuals compared to male subjects. These higher mean values of obesity indices among the female individuals may not be unconnected with the sedentary lifestyle of these women who are mainly homemakers and hardly venture out of their homes. This agrees with similar report by Bakari and Onyemelukwe[11] in the same region.

Spearman's correlational studies showed a strong inverse correlation between HOMA-IR and HOMA-B. This may be explained by the pathogenetic assertion that progressive IR eventually gives rise to beta cell dysfunction. Although both HOMA-IR and HOMA-%B showed significant direct and inverse correlations respectively to all the obesity indices analyzed, HOMA-IR showed stronger correlation further supporting a twin (IR and beta cell dysfunction) but predominantly IR defect. This is in agreement with reports by Kim et al.[1] and Meeks et al.[9] in a South-East Asian and sub-Saharan African population, respectively.

The logistic regression showed that BMI, WC, WHR, and HOMA-IR were significant independent determinants of glucose intolerance. However, HOMA-%B showed a protective OR against glucose intolerance, this was lower than the risk OR of HOMA-IR which means IR was the major factor in the causation of glucose intolerance in this population. This is in keeping with the assertion that the initial defect in type 2 DM is IR and with progressive IR, beta-cell deficit sets in. This agrees with the works of several authors.[1],[8],[9],[10],[11],[12],[13]

Limitations of this research include the nonassay of plasma lipids and lack of genetic studies which is an important causation factor in type 2 DM. Larger sample size would have yielded better results too.


  Conclusions Top


FDRs of persons with type 2 diabetes had lower mean values of HOMA-%B and higher mean values of HOMA-IR, plasma glucose levels, and some obesity indices compared to controls. HOMA-IR and some obesity indices were significant independent determinants of glucose intolerance while HOMA-%B was protective against glucose intolerance. However, IR was found to be the strongest determinant of glucose intolerance in this population. It is hereby recommended that HOMA-IR and HOMA-%B studies be done periodically on high risk individuals such as FDRs and obese persons. This will help to detect those on the pathogenetic ladder to glucose intolerance and manage them appropriately in order to roll back the incidence and prevalence of type 2 diabetes.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

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Kim CH, Kim HK, Kim EH, Bae SJ, Choe J, Park JY, et al. Longitudinal changes in insulin resistance, beta-cell function and glucose regulation status in prediabetes. Am J Med Sci 2018;355:54-60.  Back to cited text no. 1
    
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Baynes HW. Classification, pathophysiology, diagnosis, and management of diabetes mellitus. J Diabetes Metab 2015;6:541.  Back to cited text no. 2
    
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Mohandas C, Bonadonna R, Shojee-Moradie F, Jackson N, Boselli L, Alberti KG, et al. Ethnic differences in insulin secretory function between black African and white European men with early type 2 diabetes. Diabetes Obes Metab 2018;20:1678-87.  Back to cited text no. 3
    
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Dagogo-Jack S. imperative Primary prevention of type 2 diabetes: An for developing countries. In: Dagogo-Jack S, editors. Diabetes Mellitus in Developing Countries and Undeserved Communities. Cham: Springer; 2017.  Back to cited text no. 4
    
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Grobusch FP, Osei K, Matthias B. The role of insulin resistance and beta-cell dysfunction in impaired fasting glucose among Sub-Saharan Africans. Diabetologia 2017;60:854-64.  Back to cited text no. 5
    
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Hwang YC, Fujimoto WY, Kahn SE, Leonetti DL, Boyko EJ. Predictors of incident type 2 diabetes mellitus in Japanese Americans with normal fasting glucose level. Diabetes Metab J 2018;42:198-206.  Back to cited text no. 6
    
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Nyenwe E, Owei I, Wan J, Dagogo-Jack S. Parental history of type 2 diabetes abrogates ethnic disparities in key glucoregulatory indices. J Clin Endocrinol Metab 2018;103:514-22.  Back to cited text no. 7
    
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Moon JH, Roh E, Oh TJ, Kim KM, Moon JH, Lim S, et al. Increased risk of metabolic disorders in healthy young adults with family history of diabetes: From the Korea National Health and Nutrition Survey. Diabetol Metab Syndr 2017;9:16.  Back to cited text no. 8
    
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Meeks KA, Stronks K, Adeyemo A, Addo J, Bahendeka S, Beune E, et al. Peripheral insulin resistance rather than beta cell dysfunction accounts for geographical differences in impaired fasting blood glucose among Sub-Saharan African individuals: Findings from the RODAM study. Diabetologia 2017;60:854-64.  Back to cited text no. 9
    
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Awofisoye O, Okpiabhele R, Esan A, Adeleye J. Insulin resistance, obesity indices and lipid profile in Nigerian patients with type 2 diabetes. Endocr Abstr 2016;44:117.  Back to cited text no. 10
    
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Bakari AG, Onyemelukwe GC. Insulin resistance in type 2 diabetic Nigerians. Int J Diabet Metab. 2005;13:24-27.  Back to cited text no. 11
    
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Zou X, Zhou X, Ji L, Yang W, Lu J, Weng J, et al. The characteristics of newly diagnosed adult early-onset diabetes: A population-based cross-sectional study. Sci Rep 2017;7:46534.  Back to cited text no. 12
    
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Elochukwu AC, Opara UC, Chinyere NA, Jeremiah OS, Chukwuma OO. Evaluation of tumor necrosis factor alpha, insulin, and homeostasis model assessment of insulin resistance among obese participants living in Calabar, Nigeria. Trop J Med Res 2017;20:45-52.  Back to cited text no. 13
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Young EE, Okafor CN, Iroezindu MO, Agbalu IS. Insulin resistance, metabolic syndrome, and lipids in African women. Niger J Clin Pract 2016;19:793-8.  Back to cited text no. 14
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Centers for Disease Control and Prevention. National Health and Nutrition Examination Survey III; Anthropometry Procedures Manual. Georgia, USA: Centers for Disease Control and Prevention; 2016. Available from: http://www.cdc.gov/nchs/data/nhanes/nhanes_15_16/manual_an.pdf171. [Last accessed on 2017 Mar 15].  Back to cited text no. 16
    
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Lee CH, Shih AZ, Woo YC, Fong CH, Leung OY, Janus E, et al. Optimal cut-offs of homeostasis model assessment of insulin resistance (HOMA-IR) to identify dysglycemia and type 2 diabetes mellitus: A 15-year prospective study in Chinese. PLoS One 2016;11:e0163424.  Back to cited text no. 17
    
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Shashaj B, Luciano R, Contoli B, Morino GS, Spreghini MR, Rustico C, et al. Reference ranges of HOMA-IR in normal-weight and obese Young Caucasians. Acta Diabetol 2016;53:251-60.  Back to cited text no. 18
    



 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4]


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