Diabetes Ther (2018) 9:1307–1316 https://doi.org/10.1007/s13300-018-0441-1 ORIGINAL RESEARCH Prevalence and Risk Factors for Diabetes Mellitus in Nigeria: A Systematic Review and Meta-Analysis . . . Andrew E. Uloko Baba M. Musa Mansur A. Ramalan . . . Ibrahim D. Gezawa Fabian H. Puepet Ayekame T. Uloko Musa M. Borodo Kabiru B. Sada Received: April 9, 2018 / Published online: May 14, 2018 The Author(s) 2018 MeSH headings, the terms ‘‘diabetes mellitus,’’ ABSTRACT ‘‘risk factors,’’ ‘‘prevalence,’’ and ‘‘Nigeria’’ as well as variations thereof were searched for. The Introduction: There has been no nationwide last search was performed on 26 November health (diabetes) survey in Nigeria since 1992, 2017. We only included studies that utilized the when a diabetes mellitus (DM) prevalence of random plasma glucose test, the fasting plasma 2.2% was reported. We aimed to determine the glucose test, the oral glucose tolerance test prevalence of and risk factors for DM in Nigeria (OGTT), or HbA1c to diagnose DM. A total of 23 by performing a systematic review and meta- studies (n = 14,650 persons) were evaluated. A analysis. random effects model was used to estimate the Methods: We searched Medline, EMBASE, pooled prevalence of DM. We estimated the PubMed, PapersFirst, the Cochrane Library, overall pooled prevalence of DM and subgroup- Scopus, Bioline, African Journals Online, Insti- speciﬁc DM prevalences while accounting for tute of Scientiﬁc Information, and Google inter-study and intra-study variability/ Scholar from the year 1990 to 2017. Using heterogeneity. Results: The overall pooled prevalence of DM Enhanced Digital Features To view enhanced digital was 5.77% (95% CI 4.3–7.1). The pooled features for this article go to https://doi.org/10.6084/ m9.ﬁgshare.6216518. prevalences of DM in the six geopolitical zones of Nigeria were 3.0% (95% CI 1.7–4.3) in the A. E. Uloko (&) B. M. Musa M. A. Ramalan north-west, 5.9% (95% CI 2.4–9.4) in the north- I. D. Gezawa M. M. Borodo east, 3.8% (95% CI 2.9–4.7) in the north-central Department of Medicine, Aminu Kano Teaching zone, 5.5% (95% CI 4.0–7.1) in the south-west, Hospital Kano, Bayero University Kano, Kano, 4.6% (95% CI 3.4–5.9) in the south-east, and Nigeria e-mail: email@example.com 9.8% (95% CI 7.2–12.4) in the south-south zone. Risk factors for the pooled prevalence of F. H. Puepet DM were a family history of DM (4.6%; 95% CI Department of Medicine, Jos University Teaching 3.5–5.6); urban dwelling (6.0%; 95% CI Hospital Jos, University of Jos, Jos, Nigeria 4.3–7.8); unhealthy dietary habits (8.0%; 95% A. T. Uloko CI 5.4–10.5); cigarette smoking (4.4%; 95% CI Department of Pharmacy, Aminu Kano Teaching 1.3–10.2); older age (6.6%; 95% CI 4.5–8.7); Hospital Kano, Kano, Nigeria physical inactivity (4.8%; 95% CI 3.2–6.4); and K. B. Sada obesity (5.3%; 95% CI 3.8–6.9). Department of Medicine, Federal Medical Centre, Gusau, Nigeria 1308 Diabetes Ther (2018) 9:1307–1316 Conclusion: There has been an increase in the 12% across the country in recent years [4–7]. prevalence of DM in Nigeria. All regions of the The last time a nationwide population estimate country have been affected, with the highest of DM was undertaken in Nigeria was during the prevalence seen in the south-south geopolitical 1992 Nigerian National Non-communicable zone. Urban dwelling, physical inactivity, Diseases (NCD) survey, where DM was said to advanced age, and unhealthy diet are important occur in 2.2% of the population . There has risk factors for DM among Nigerians. A national been no nationwide health (diabetes) survey in diabetes care and prevention policy is highly Nigeria since then. However, it is important to recommended. determine the actual burden of DM in Nigeria to facilitate appropriate health resource alloca- tion, advocacy, and planning. Thus, in the work Keywords: Diabetes prevalence; Meta-analysis; reported in the present paper, we aimed to Nigeria; Risk factors; Systematic review determine the prevalence of and risk factors for DM in Nigeria using a systematic review and INTRODUCTION meta-analysis. Diabetes mellitus (DM) is a metabolic disorder METHODS of chronic hyperglycemia characterized by dis- turbances to carbohydrate, protein, and fat Data Search metabolism resulting from absolute or relative insulin deﬁciency with dysfunction in organ We searched Medline, EMBASE, PubMed, systems . This disease has shown a tremen- dous increase in prevalence with a demographic PapersFirst, the Cochrane Library, Scopus, Bio- line, African Journals Online, the Institute of transition in its epidemiology in recent years. Populations previously unaffected or minimally Scientiﬁc Information, and Google Scholar from the year 1990 to 2016. Using MeSH headings, affected by DM are now reporting soaring the terms ‘‘diabetes mellitus,’’ ‘‘risk factors,’’ prevalence ﬁgures, which poses a real challenge ‘‘prevalence,’’ and ‘‘Nigeria’’ as well as variations to health ﬁnancing by governments and non- thereof were searched for. We contacted the governmental organizations. The latest preva- authors of articles in journals that were not lence ﬁgure published by the International available online. The last search was performed Diabetes Federation (IDF) is 425 million persons living with DM worldwide, with nearly 50% of on 26 November 2017. Studies included in the meta-analysis were those that utilized the oral these undiagnosed . The developing econo- mies of Africa and Asia contribute a signiﬁcant glucose tolerance test (OGTT), the random plasma glucose (RPG) test, the fasting plasma fraction of this ﬁgure. There is also a rising burden from the complications of DM alongside glucose (RPG) test, or glycated hemoglobin (HbA1c) to diagnose DM. In all, a total of 23 the ever-increasing prevalence of the disease . studies involving 14,650 persons were We now see high rates of DM-related amputa- evaluated. tions, cerebrovascular disease, heart-related problems, and kidney disease in populations that were not previously known for these chal- Inclusion Criteria lenging health problems. In Nigeria, the current prevalence of DM Only population-based studies that were exe- among adults aged 20–69 years is reported to be cuted between 1990 and 2017 and in which 1.7% . It is widely perceived that prevalence FPG, RPG, OGTT, or HbA1C was used to diag- ﬁgures reported by the IDF grossly under-report nose DM were included in the meta-analysis. the true burden of DM in Nigeria, given that they are derived through the extrapolation of data from other countries. Various researchers have reported prevalences ranging from 2% to Diabetes Ther (2018) 9:1307–1316 1309 Exclusion Criteria that diminish red blood cell survival, the HPLC platform adequately and accurately provides HbA1c values. In this meta-analysis, only stud- Clinic/hospital-based studies and those per- ies that utilized the HPLC platform to evaluate formed before 1990 or after 2017 were excluded HbA1c were included. from the meta-analysis. Quality of the Studies Included Compliance with Ethics Guidelines Two authors separately assessed the quality of This review and meta-analysis is based on pre- the studies included using the NIH Quality viously conducted studies and does not involve Assessment Tool for Observational Cohort and any study with human participants or animals Cross-Sectional Studies . The studies were performed by the authors. assessed with questions appropriate to the study design. We graded the quality of the study as Data Extraction good (G) if its rating was at least 70%, fair (F) if its rating was at least 50%, and poor (P) if its Various data were extracted from eligible stud- rating was less than 50%. ies, such as the prevalence of DM, risk factors for DM, method of diagnosing DM, study design, Statistical Analyses and Nigerian geopolitical zone in which the study was carried out. A summary of the data The primary outcome measure was the preva- extracted is shown in Table 1. We coded the lence of DM. The standard error in the preva- data based on the name of the ﬁrst author of the lence was estimated using the binomial study and the year that the study was published. probability distribution. A random effects Multiple coder agreement was assessed using model based on the DerSimonian-Laird  Cohen’s kappa . method was used to estimate the pooled prevalence of DM and the conﬁdence interval Operational Deﬁnitions via weighted least squares (weighting was based on the reciprocal sum of the between- and DM was diagnosed based on the 1999 WHO within-study variances). The inter-study diagnostic criteria for DM or the ADA 2010 heterogeneity was evaluated using Cochran’s diagnostic criteria for DM [1, 10]. According to Q test . We deﬁned low, medium, and high the 1999 WHO diagnostic criteria , the cut- heterogeneity a priori as Cochrane Q values of off plasma glucose values for diagnosing DM are 25%, 50%, and 75%, respectively. We estimated as follows: the overall pooled prevalence of DM and the • Fasting plasma glucose C 7.0 mmol/L subgroup-speciﬁc prevalences accounting for • Random plasma glucose C 11.1 mmol/L the inter-study and intra-study variability/ • Plasma glucose 2-h post-glucose load heterogeneity. An assessment of risk factors was (75 g) C 11.1 mmol/L undertaken. The 2010 ADA diagnostic criteria  for DM Publication bias was appraised using Begg’s states that a glycated hemoglobin (HbA1c)  rank correlation methods and Egger’s  value of C 6.5% is diagnostic of DM if the assay weighted regression test. All analyses were per- technique is based on high-performance liquid formed using the STATA software (version 11). chromatography (HPLC). The HPLC assay A level of signiﬁcance of 0.05 was adopted for technique potentially adjusts for hemoglobi- Cochran’s Q test. nopathies and provides information on hemo- The null hypothesis of this study assumed globin variants. In populations such as the that all of the studies reported the same preva- Nigerian population, where there is a high lence in the various populations studied. prevalence of hemoglobinopathies and factors 1310 Diabetes Ther (2018) 9:1307–1316 Table 1 Studies included in the meta-analysis S/ Author Geopolitical Year of Study design Method used to Prevalence Quality no. zone publication of diagnose DM of DM (%) grading study 1 Nyenwe et al. South-south 2003 Cross-sectional RBS 6.8 F  prospective 2 Puepet et al. North-central 2008 Cross-sectional OGTT 4.0 F  prospective 3 Sabir et al.  North-central 2011 Cross-sectional OGTT 4.61 G prospective 4 Gezawa et al. North-east 2015 Prospective FBS 7.0 F  5 Kyari et al.  Pan-Nigeria 2013 Cross-sectional RBS 3.30 F 6 Omorogiuwa South-south 2010 Cross-sectional FPG and RBS 9.0 F et al.  7 Ekpeyong et al. South-east 2012 Cross-sectional RBS 10.0 F  8 Oyegbade et al. South-west 2007 Cross-sectional RBS 5.0 F  9 Opeodu et al. South-west 2013 Cross-sectional RBS 4.40 F  10 Gabriel et al. South-east 2013 Cross-sectional FBS 5.0 F  11 Dahiru et al. Pan-Nigeria 2008 Review RBS 2.0 F  12 Anzaku et al. North-central 2012 Cross-sectional OGTT 8.3 G  prospective 13 Adeniyi et al. North-west 2010 Cross-sectional RBS 2.0 F  14 Etukumana North-central 2014 Cross-sectional FBS 4.1 G et al.  prospective 15 Nwafor et al. South-south 2001 Cross-sectional RBS, FBS 23.1 F  prospective 16 Sabir et al.  North-west 2013 Cross-sectional RBS 0.81 F prospective 17 Chukwunonso South-east 2015 Cross-sectional FBS 3.0 G et al.  18 Bakari et al. North-west 1999 Cross-sectional OGTT 8.0 G  Diabetes Ther (2018) 9:1307–1316 1311 Table 1 continued S/ Author Geopolitical Year of Study design Method used to Prevalence Quality no. zone publication of diagnose DM of DM (%) grading study 19 Isara et al.  South-south 2015 Cross-sectional RBS 5.0 F 20 Enang et al. South-south 2014 Cross-sectional OGTT 7.0 F  21 Ramalan et al. North-west 2016 Prospective OGTT 8.0 G  22 Ramalan et al. North-west 2016 Prospective A1C 10.0 F  23 Olamoyegun South-west 2014 Prospective FBS 7.0 F et al.  DM diabetes mellitus, RBS random blood sugar, FBS fasting blood sugar; OGTT oral glucose tolerance test, F fair, G good, A1c glycated hemoglobin by diagnostic method are shown in Fig. 2. Fig- RESULTS ure 3 shows the pooled prevalence of DM in each of the six geopolitical zones of Nigeria, The total number of records initially identiﬁed which indicates that the highest prevalence during the database searches was 149, but only occurred in the south–south zone (9.8%; 95% 23 studies (total number of persons: 14,650) CI 7.2–12.4) and the lowest in the north-west were eventually found to be eligible for inclu- zone (3.0%; 95% CI 1.7–4.3). Assessment of the sion in the meta-analysis, as shown in Fig. 1. risk factors for DM (see Fig. 4) revealed that The overall pooled prevalence of DM was 5.77% unhealthy dietary habits (8.0%; 95% CI (95% CI 4.3–7.1). The overall prevalence and 5.4–10.5), older age (6.6%; 95% CI 4.5–8.7), and the prevalences of DM in subgroups categorized urban dwelling (6.0%; 95% CI 4.3–7.8) were the leading risk factors for DM in Nigeria. DISCUSSION The United Nation estimates that the popula- tion of Nigeria as of September 2017 was 193.3 million . The pooled DM prevalence of 5.77% observed in our meta-analysis suggests that 11.2 million Nigerians (1 out of every 17 adults) are living with the disease. Regional differences in the prevalence of DM, with the highest rate observed in the south–south zone and the lowest rate seen in the north-western zone, mirror a similar ﬁnding for obesity, which Fig. 1 Flow diagram of the studies included in the meta- is a major risk factor for type 2 diabetes . analysis 1312 Diabetes Ther (2018) 9:1307–1316 Fig. 2 Forest plot showing the overall prevalence of diabetes and the prevalences of diabetes in subgroups categorized by method of diagnosis Fig. 3 Prevalence of diabetes in each geopolitical zone of Nigeria Diabetes Ther (2018) 9:1307–1316 1313 Fig. 4 Prevalences of risk factors for diabetes mellitus To the best of our knowledge, this is the ﬁrst that sub-Saharan Africa has one of the fastest study to determine the prevalence of and risk annual rates of change in the number of urban factors for diabetes in Nigeria using a systematic dwellers in the world . Studies have reported review and meta-analysis. The pooled DM a two- to ﬁvefold increase in the risk of diabetes prevalence of 5.77% found in our study is quite and pre-diabetes in association with urban res- similar to the 2013 IDF estimate derived from idence [20, 21]. Urbanization is also associated extrapolations from populations with similar with decreased physical activity energy expen- sociodemographic characteristics . Our diture (PAEE), an independent risk factor for diagnostic methods also differ from those of the metabolic syndrome . IDF, which mainly promotes the use of the The modest improvement in living standards OGTT. Although the OGTT is the gold standard witnessed over the past few years in Nigeria has for the diagnosis of DM, FPG and RPG are also resulted in the aging of its populace. Insulin good tools that are cheaper and easier to apply, resistance tends to worsen with advancing age even in remote settings where an OGTT may . This, coupled with decreased physical not be feasible. In 2010, the ADA recommended activity among the aged, increases the risk of the use of the glycosylated hemoglobin (HbA1c) type 2 diabetes. Among the risk factors for DM test in the diagnosis of DM . We found only found in our study, unhealthy dietary habits one study that used HbA1c measured using was the most prevalent, which is not surprising high-performance liquid chromatography considering the proliferation of fast food outlets (HPLC) to diagnose DM based on a cutoff of in many cities across the country. An unhealthy C 6.5%. diet consisting mainly of high-fat, energy-dense Compared with the 1992 NCD population foods contributes to the development of obesity estimate of 2.2% , the prevalence of DM and DM. obtained in this meta-analysis suggests a 2.6- The strength of our study is that it is the ﬁrst fold increase in prevalence over the past two to determine the prevalence of and risk factors and half decades. We found urban dwelling, for diabetes in Nigeria based on a systematic physical inactivity, advancing age, and an review of the literature and meta-analyses. In unhealthy diet to be the leading risk factors for addition, the selected studies cover the six DM among Nigerians. It has been demonstrated geopolitical zones of Nigeria, making it possible 1314 Diabetes Ther (2018) 9:1307–1316 to pinpoint regional differences in the preva- Compliance with Ethics Guidelines. This lence of DM. meta-analysis is based on previously conducted Limitations of our study include the cross- studies and does not contain any studies with sectional design of the selected studies, making human participants or animals performed by causal associations between diabetes and the any of the authors. identiﬁed risk factors difﬁcult. Our study also Data Availability. The datasets obtained did not consider other potential risk factors for during and/or analyzed during the current diabetes, such as gender and socioeconomic study are available from the corresponding status. Finally, the fact that we selected studies author on reasonable request. which used different screening methods for the diagnosis of diabetes means that some people Open Access. This article is distributed with the disease could have been missed. under the terms of the Creative Commons Attribution-NonCommercial 4.0 International CONCLUSIONS License (http://creativecommons.org/licenses/ by-nc/4.0/), which permits any noncommercial There has been a signiﬁcant increase in the use, distribution, and reproduction in any prevalence of DM in Nigeria, affecting all medium, provided you give appropriate credit regions of the country, with the highest preva- to the original author(s) and the source, provide lence noted in the south-south geopolitical a link to the Creative Commons license, and zone. Urban dwelling, physical inactivity, indicate if changes were made. advancing age, and unhealthy diet are impor- tant risk factors for DM among Nigerians. A national diabetes care and prevention policy is REFERENCES highly recommended. 1. WHO. Deﬁnition, diagnosis and classiﬁcation of diabetes mellitus and its complications, part 1. ACKNOWLEDGEMENTS Geneva: WHO; 1999. 2. 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