Prevalence of cardio-metabolic syndrome in Nigeria: a systematic review

Share Embed

Descrição do Produto

p u b l i c h e a l t h 1 2 9 ( 2 0 1 5 ) 4 1 3 e4 2 3

Available online at

Public Health journal homepage:

Review Paper

Prevalence of cardio-metabolic syndrome in Nigeria: a systematic review V.M. Oguoma a, E.U. Nwose b,c,*, R.S. Richards b a

School of Psychological and Clinical Sciences, Charles Darwin University, NT, Australia School of Community Health, Charles Sturt University, NSW, Australia c Department of Public and Community Health, Novena University, Ogume, Nigeria b

article info


Article history:

Objective: This is a systematic review of the distribution of cardiometabolic syndrome (CMS)

Received 24 March 2014

in Nigeria, the clinical definitions widely used and how it affects the proposition of a na-

Received in revised form

tional prevalence of CMS that will advise management interventions.

17 January 2015

Study design: Systematic review of literature.

Accepted 20 January 2015

Methods: To present a comprehensive report of the distribution of CMS in Nigeria, extensive

Available online 28 February 2015

searches was carried out on PubMed, African Journals Online (AJOL), SCOPUS, EBSCOhost (CINAHL Plus), Google Scholar and Science Direct using terms: Nigeria, metabolic syn-


drome, cardio-metabolic syndrome, syndrome X, World Health Organization, International

Cardiometabolic syndrome

Diabetic Federation, National Cholesterol Education Program Adult Treatment Panel III,


European Group for study on Insulin Resistance, American Association of Clinical Endo-


crinologist, American Heart Association/National Heart, Lung and Blood Institute. All


published data between January 2002 and December 2013 were collated into a database.


Information gathered and recorded for each source were the population sampled, age and


number of population, locality, clinical definition used, longitude and latitude, and period of the study. Results: Out of 32 studies, 9 (28.1%) adopted the WHO classification, 19 (59.4%) used the ATPIII definition, while the remaining 10 (31.3%) studies used the IDF definitions. Twenty (62.5%) were hospital-based studies on diabetic, hypertensive, HIV, asthmatic and thyroid disorder patients. The remaining 12 (37.5%) studies were population-based studies in urban, suburb and rural settings. The mean overall prevalence of CMS in Nigeria is 31.7%, 27.9% and 28.1% according to the WHO, ATPIII and IDF definitions, respectively. Most of the studies were from the Southern region. Age groups mostly studied were those from 35 years. Conclusion: The report of this review provides an essential overview on the current distribution of CMS in Nigeria. It provides an insight to direct future studies such as the need to (1) study rural communities where lifestyles are not westernized as in the urban areas, and

* Corresponding author. School of Community Health, Charles Sturt University, Leeds Parade Orange, Orange, NSW 2800, Australia. Tel.: þ61 2 63657282. E-mail address: [email protected] (E.U. Nwose). 0033-3506/Crown Copyright © 2015 Published by Elsevier Ltd on behalf of The Royal Society for Public Health. All rights reserved.


p u b l i c h e a l t h 1 2 9 ( 2 0 1 5 ) 4 1 3 e4 2 3

(2) young adults, as well as (3) develop a consensus on the definition of CMS among the Sub-Saharan African populations. Crown Copyright © 2015 Published by Elsevier Ltd on behalf of The Royal Society for Public Health. All rights reserved.



Cardiometabolic syndrome (CMS) is a complex cluster of risk factors for cardiovascular disease (CVD) and diabetes.1 Independent risk factors implicated in both clinical and public health perspectives includes hyperglycaemia, dyslipidaemia, hypertension and obesity. Individuals with the CMS are at increased risk of developing diabetes mellitus and CVD as well as increased mortality from CVD and all causes.2 The CMS is believed to affect at least one in five adults worldwide and carries a high risk of CVD.3 However, the actual prevalence in rural communities of Nigeria, as an example of low-mid income country (LIMC), need to be reviewed for the purpose of public health planning. The mechanism underlying the relationship between CMS and CVD lies between the concept of endothelial injury and dysfunction; the deposition of low density lipoprotein cholesterol; and the recruitment, migration and proliferation of monocytes in smooth muscle cells in the artery wall. These are central to the initiation and progression of artherosclerosis.4,5 CMS was first mentioned by Gerald Reaven as Syndrome X or the Insulin Resistance Syndrome.6 Following Reaven in 1988, several clinical definitions have been proposed: the World Health Organization definition (WHO),7 the European Group for Study of Insulin Resistance, the National Cholesterol Education program e Third Adult Treatment Panel (NCEP ATP-III),8 the American Association of Clinical Endocrinologists (AACE), the International Diabetes Federation (IDF),9 and the American Heart Association/National Heart, Lung and Blood Institute (AHA/NHLBI) definitions.10 This has led to some confusion on the part of clinicians regarding how to identify patients with the syndrome.1 In order to salvage the situation, IDF and AHA/NHLBI representatives held discussion to attempt to resolve the remaining differences between definitions of CMS, which led to the recent consensus on harmonizing the definition of CMS.1 It would be interesting to know how this is utilized in the developing parts of SubSaharan Africa and other LIMC health systems. These individual risk factors have been reported in Nigeria.11e15 However, despite the increase in reporting, the prevalence of CMS has not been clearly defined partly due to unresolved clinical definitions and resource constraints. Nigeria is currently undergoing rapid epidemiological transition to increasing number of metabolic disorders,16 and some authors have implicated demographic changes such as ageing, and the undesirable risk factors such as obesity and sedentary life as the cause.17e20 Based on the rising reporting of the prevalence of CMS in Nigeria over the last decade, the objective of this study is to assess overall distribution of CMS in Nigeria and the clinical definitions employed; as well as age group of the population covered in studies.

Study design This is a systematic review of prevalence studies of CMS in Nigeria following the PRISMA guideline (S1). Two reviewers, VMO and EUN, extracted data independently using standardized data extraction forms. Consensus was reached between the reviewers in case of initial disagreement. Characteristics of studies extracted were the study location, type of population, number of population, age, and clinical definition of CMS used.

Study area Nigeria is a Federation made up of 36 States and a Federal Capital Territory (FCT), Abuja; with 774 Local Government Areas. The states are grouped into six geo-political zones; namely the North Central, North East, North West, South East, SoutheSouth and South West.21 The main latitude and longitude of Nigeria is 10 North and 8 East respectively.22 Nigeria is approximately 923,768 sq km, located in West Africa with a population of 175.6 million people. Estimated 50.4% of this population live in the rural areas, while the remaining 49.6% live in the urban areas.23

Data sources and searches A systematic collation of published data over the period of January 2002 to December 2013 on CMS was retrieved between August and December 2013 to develop a comprehensive distribution of CMS in Nigeria. A final search was done in January 2015. The search was carried out using electronic searches in online bibliographic archives: PubMed, African Journals Online (AJOL), SCOPUS, EBSCOhost (CINAHL Plus), Google Scholar and Science Direct. Search terms include: Nigeria, metabolic syndrome, cardio-metabolic syndrome, syndrome X, World Health Organization, International Diabetic Federation, National Cholesterol Education Program Adult Treatment Panel III, European Group for study on Insulin Resistance, American Association of Clinical Endocrinologist, American Heart Association/National Heart, Lung and Blood Institute were used. Many articles were identified through this method. Articles that could not be obtained online were sourced from the Library of Charles Darwin University. Suggested academics, experts and researchers that have published widely in the subject area in Nigeria were also contacted with request for other publications not indexed in any of the search database as well as other grey literature.

p u b l i c h e a l t h 1 2 9 ( 2 0 1 5 ) 4 1 3 e4 2 3

Validation of search results and study selection All search results from different search engines/databases were combined in Endnote and duplicates removed. In order to avoid publication bias, quality related criterion for these articles were not performed. This was to avoid further restriction of the number of articles selected using the inclusion criteria. However, comments about limitations/weaknesses in selected studies are highlighted where appropriate. A total of 3758 potential articles were indicated in the initial literature search (Fig. 1). Out of these, 89 studies were done in Nigeria; which were retrieved and assessed for eligibility. Of the studies retrieved, 31 plus one additional article retrieved through a hand search of references from published studies met the inclusion criteria and were included in the review. The remaining 58 were excluded because they did not identify a known clinical definition of CMS or were studies on one of the components of the CMS. Eligible studies were prospective or cross-sectional studies published in English Language (official language of the nation) on CMS and/or the independent components carried out in Nigeria; studies that identified the use of known definitions of CMS based on any or combination of the WHO, ATPIII, AACE, IDF, or AHA/NHLBI definitions; and subjects of age range of 15 years old. The use of known definitions of CMS as inclusion criteria is to assess how these definitions


were used in Nigerian studies over the last 12 years, though the joint scientific statement currently recommends the IDF for Sub-Saharan's. More so, the inclusion of studies from 15 years old is to understand how CMS occurs in younger adults since most risk assessment models targets subject of 40 years. Ineligible studies were those looking at CMS in individuals of 15 years of age and studies without a universally accepted definition of CMS. Studies on individual CVD risk factors and those done outside Nigeria but probably within the SubSaharan African were excluded from the review.

Data extraction and analysis Each study location were geo-referenced using the latitude and longitude coordinates obtained by crosschecking the names of the study location with the Distance Calculator Database.24 Degree/minutes/seconds were converted into decimal degrees. All the relevant information was entered into an Excel spreadsheet and data analysis was performed using SPSS (Version 17 for Windows, SPSS Inc., Chicago, IL). Mean prevalence of CMS based on all eligible hospital-based and population-based studies in urban, suburban and rural settings were calculated for each definition of CMS used. All data were mapped using the Epi-Info geographical mapping software (Version 7.1 CDC, Atlanta).

Fig. 1 e Flow diagram of studies included in the systematic review.


p u b l i c h e a l t h 1 2 9 ( 2 0 1 5 ) 4 1 3 e4 2 3

Results All studies that met the final selection were only crosssectional studies published from 2002 to 2013 and had sample sizes ranging from 93 to 1458 subjects, as there was no longitudinal study identified. The prevalence of CMS in these studies ranged from 6.3% among apparently healthy population,25 to 86% in a study of patients with type 2 diabetes mellitus.26 In Nigeria, three clinical definitions are widely used (Table 1). Of the 32 studies (n ¼ 10,854) included in this review,16,25e55 nine studies employed the WHO model; nineteen used the ATP-III and ten IDF definitions. Two studies used all three models; one study used both ATP-III and IDF definitions; another study used WHO and ATP-III. In dichotomous categorization of the 32 selected reports,16,25e55 20 (62.5%) were hospital-based studies on diabetic, hypertensive, HIV, asthmatic and thyroid disorder patients. The remaining 12 (37.5%) studies are population-based studies from urban, suburban or rural settings. All of the hospital-based studies were located in urban health institutions. Amongst the hospital based sub-population studies, 12 (60%) were carried out on diabetic patients, 4 (20%) on hypertensive patients, 1 (5%) each were carried out on HIV, asthmatic, thyroid disorder and undisclosed ill-health patients, respectively (Table 2). Mean prevalence of CMS over the 12 year period for hospital-based studies was 41.8% (WHO), 38.4% (ATPIII) and 40.8% (IDF). In population-based studies carried out in urban, suburban and rural settings, mean prevalence of CMS was 8.2% (WHO), 18.3% (ATPIII) and 15.3% (IDF). The mean overall prevalence of CMS in Nigeria was 31.7%, 27.9% and 28.1% according to the WHO, ATPIII and IDF definitions, respectively (Table 3). Fig. 2A and B shows the geographical distribution of the CMS, and the distribution of the use of the three diagnostic criteria over the 12 year period in Nigeria. Fig. 3A and B shows the prevalence of CMS in Nigeria according to each clinical definition. It reveals that CMS is predominantly in Nigeria irrespective of the scarce data available in the literature. Of the 36 states plus FCT, only 15 states were found to be represented in all the eligible studies. Lagos state had the highest with eight studies retrieved on CMS, followed by Oyo State with four studies. Osun and Enugu State have three

studies each. FCT, Anambra and Rivers State have two studies each, while the remaining eight States have one study each on CMS (Table 2, Fig. 2B). The age group of subjects in the 32 studies ranged from 14 years in patients with thyroid disorders43 and asthma44 to 105 years apparently healthy individuals in the rural community (Table 2). The age groups sampled were predominantly from >30 years. Only one study sampled apparently healthy subjects from 18 years in rural communities.48 Three definitions of CMS were identified in all of the qualified studies for the systematic review: the WHO, ATPIII and IDF definitions. Of the 32 studies, 9 (28.1%) adopted use of the WHO classification, 19 (59.4%) used the ATPIII definition, while the remaining 10 (31.3%) studies used the IDF definitions (Table 3). There was an overlap in four studies, where 2 (n ¼ 877) assessed the three definitions, and 1 (n ¼ 291) study assessed the ATPIII and IDF definitions, the remaining 1 (n ¼ 338) study assessed the WHO and ATPIII definitions (Table 2).

Discussion This systematic review was designed to estimate the overall distribution of CMS in Nigeria based on three themes, which are the (1) clinical definitions being explored, (2) age group of populations studied and (3) type of population studied. Three definitions of CMS were identified in all of the qualified studies for the systematic review: WHO,7 ATPIII8 and IDF9 definitions. Although these three definitions were debuted since the years 1999, 2001 and 2005, respectively in addition to the 2009 consensus statement,1 there is current disagreement and debate regarding their use in clinical practice occasioned by the disparities of results as evidenced from this review. According to the ATPIII, IDF and WHO definitions, the overall prevalence of CMS in Nigeria is 27.9%, 28.1% and 31.7% respectively. These are higher than the reported prevalence of 19.1% using ATPII criteria in Canada,56 and comparable to prevalence of 33.5% in Australia according to the IDF definition57 and unadjusted prevalence of 34.1% in the USA based on the ATPIII criteria. Over the 12 year period, hospital-based studies recorded mean prevalence's of 41.8%, 38.4% and 40.8% for the three different definitions. Also, the prevalence of CMS is highly

Table 1 e Three definitions of cardiometabolic syndrome based on different criteria. Clinical components Criteria for diagnosis Obesity

Triglyceride HDL-C

Blood pressure Blood glucose Others

WHO (1999) IGT, IFG, T2DM, or low insulin sensitivity, plus any two of the below listed features Men: WHR > 0.90 Women: WHR > 0.85 and or BMI > 30 kg/m2 150 (1.7 mmol/L) Men: 35 (0.9 mmol/L) Women: 39 (1.0 mmol/L) 140/90 mmHg IFG (fast >110) IGT (2 h > 140) Microalbuminuria

ATP-III (2001)

IDF (2005)

Any three of the five features listed below WC  102 cm in men WC  88 cm in women

Central obesity plus any two of the below listed features Increased WC (ethic specific)

150 (1.7 mmol/L) Men: 40 (1.03 mmol/L) Women: 50 (1.29 mmol/L)

150 (1.7 mmol/L) or on TG therapy Men: 40 (1.03 mmol/L) Women: 50 (1.29 mmol/L) or on HDL-C therapy 130/85 mmHg IFG (fast 100) T2DM

140/90 mmHg IFG (fast >110) T2DM

Table 2 e Studies that reported CMS prevalence rates e showing definition used, age group, population and location of study in the 12 years. s/n

Author, year 27


Ogbera, 2010 Alebiosu and Odusan, 200428 Adediran et al., 200729 Akande et al., 200730 Isezue and Ezunu, 200531 Udenze et al., 201326 Puepet et al., 200932 Osuji et al., 201233 Ogbera et al., 201134 Unadike et al., 200935 Ogbera, 201136 Ogbera and Azenabor, 201037 Akintunde et al., 201138 Osuji and Omejua, 201239 Ojji et al., 201240 Akintunde et al., 201041

17 18 19 20 21 22 23 24 25 26 27

Ayodele et al., 201242 Ogbera et al., 201243 Adeyeye et al., 201244 Siminialayi et al., 200945 Siminialayi & Emem-chioma, 200825 Adedoyin et al., 201346 Adegoke et al., 201047 Charles-Davis et al., 201248 Ulasi et al., 201049 Chukwukelu et al., 201350 Adediran et al., 201216

Diabetic patients Diabetic patients Diabetic patients Diabetic patients Diabetic patients Diabetic patients Diabetic patients Diabetic patients Diabetic patients Diabetic patients Diabetic patients Diabetic patients Hypertensive patients Hypertensive patients Hypertensive patients Hypertensive vs non-hypertensive patients HIV patients Thyroid disorders Asthma patients Patients (undisclosed) Rural Rural Rural Rural Semi-urban vs rural Urban vs rural Rural vs urban

28 29 30 31 32

Ijeh et al., 201051 Ogbu and Chukwukelu, 201352 Sani et al., 201053 Ghazali and Sanusi, 201054 Odenigbo et al., 200955

Urban Urban Urban Urban Urban

35e85 52 ± 5.8 30e70 37e78 35e80 57 ± 10.8 54.2 ± 9.1 24e84 40e85 50.8 ± 11 30e86 34e91 55.14 ± 10.83 24 51.80 ± 11.63 55.14 ± 10.83 vs 54.67 ± 10.89 18 14e76 14e78 18 40.55 ± 0.99 30e70 58.6 ± 16.9 18e105 25e64 35 42.3 ± 14.4 vs 44.1 ± 13.2 22e84 35e85 18e75 25e73 29e58



WHO (%)


963 218 408 121 254 100 634 93 201 240 203 601 210 250 362 140 vs 70


GH Gbagada & LASUTH, Lagos OOUTH, Sagamu, Ogun State b LUTH, Lagos State b UITH, Ilorin, Kwara State b UDUTH, Sokoto State b LASUTH, Lagos, Lagos State b JUTH, Jos, Plateau State b NAUTH, Nnewi, Anambra State b LASUTH, Lagos, Lagos State b UUTH, Uyo, Akwa Ibom State b GH Gbagada, Lagos State b GH Gbagada & LASUTH, Lagos b LAUTECH, Osogbo, Osun State b NAUTH, Nnewi, Anambra State b UATH, Gwagwalada, Abuja FCT b LAUTECH, Osogbo, Osun State

e 25.2 51.0 23.9 59.1 86.0 e e e e

86 e e e e e e 66.7 69.0 62.5

34.5 e 13.0

35.0 31.2 e 31.4 vs 15.7

291 112 158 250 300 100 132 534 972 vs 486 103 vs 102 342 vs 325


LAUTECH, Ogbomosho, Osun State LASUTH, Lagos, Lagos State b LASUTH, Lagos State b Okrika General Hosp. Rivers State a Odufor, Etche LGA, Rivers State a Ilora community, Oyo State a Ife North LGA, Osun State a Badija, Ibadan, Oyo State a Ujo Nike, Enugu State a,b Enugu, Enugu State a,b FCT, Abuja

e e

12.7 28.0

e e e e e e

31.6 6.3 e 12.1 e e 20.4 vs 12.7 3.7 vs 13.7

199 342 300 338 400


e e e 23.7



Umuahia, Abia State Nsukka Urban, Enugu State b Katsina city, Katsina State b UI and UCHI, Ibadan, Oyo State b Asaba, Delta State b

0 vs 0.9

30.8 23.4 22.0 36.7 20

IDF (%) e e e e e e 63.6 e e e 44 60 42.5 e e

17.2 e 17.7 e e 25.0 e 16.3 18.0 vs 10.0

p u b l i c h e a l t h 1 2 9 ( 2 0 1 5 ) 4 1 3 e4 2 3

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16


7.7 vs 14.9 e e e

Key: LAUTECH: Ladoke Akintola University of Technology Teaching Hospital, GH: General Hospital, LASUTH: Lagos State University Teaching Hospital, OOUTH: Olabisi Onabanjo University Teaching Hospital, LGA: Local Government Area, LUTH: Lagos University Teaching Hospital, FCT: Federal Capital Territory, UITH: University of Ilorin Teaching Hospital, UDUTH: Usmanu Danfodiyo University Teaching Hospital, NAUTH: Nnamdi Azikiwe University Teaching Hospital, UATH: University of Abuja Teaching Hospital, JUTH: Jos University Teaching Hospital, UUTH: University of Uyo Teaching Hospital, UI: University of Ibadan, UCHI: University College Hospital Ibadan. a Indicate studies that were carried out in rural settings. b Indicate studies in urban settings.



p u b l i c h e a l t h 1 2 9 ( 2 0 1 5 ) 4 1 3 e4 2 3

Table 3 e Mean prevalence of CMS among hospital-based studies and population-based studies in rural/urban settings based on three clinical definitions. Population Hospital

Urban/suburban/ rural




Mean prevalence Standard error Mean prevalence Standard error Mean prevalence Standard error

41.81429 9.532237 8.2 7.754354 31.73 8.530912

ATPIII 38.38 6.46412 18.34545 2.99986 27.88571 4.039397

IDF 40.83333 8.148974 15.31667 2.505915 28.075 5.596172

distributed among diabetic and hypertensive patients.26e35,38e40 Within the sub-population of hospital-based studies, greater attention has been concentrated on diabetic patients where 12 (60%) of the studies assessed the prevalence of CMS in type 2 diabetic patients.26e34 One of the studies indicate that prevalence of CMS in non-diabetic patients are as high as 35%.38 This indeed has huge implications for increased morbidity and mortality resulting from cadiovascular complications, especially in a population of low-mid income countries such as Nigeria. In population-based studies carried out in urban, suburban and rural settings, this review recorded mean CMS prevalence of 8.2% (WHO), 18.3% (ATPIII) and 15.3% (IDF). More so, studies that assessed the prevalence of CMS in semi-urban and rural communities found prevalences of 18% vs 10%, 6.3%, 7.7%, 12.1%, 23.4%, 16.3% and 25%,16,25,46e49,52 which shows a sizeable prevalence of these cardiovascular risk factors in the rural settings. However, more increase in the prevalence rate is anticipated with increased reporting, which is envisaged to compensate for the unaccounted CMS morbidity and mortality in these rural settings that is popularly attributed to malaria. Clinical definitions being explored: the ATPIII definition appears to be the most widely used in Nigerian studies. How these definitions contribute to the management of CMS in SubSaharan Africa have not been understood considering the fragile health systems in this part of the world. The two studies that assessed all the three definitions opined that there seemed no marked significant difference in the prevalence projections by each of the definitions.16,38 However, one study found that the IDF definition resulted in a higher frequency because of the lower cut-off for waist circumference (WC) used for identification of viseral obesity,38 while in the other study, the IDF criteria was opined to seem more relevant because of its ethnic-specific definition for viseral obesity.16 In a different report that compared the prevalence of CMS using the ATPIII and the IDF guidelines in two American and one German population samples, the prevalence of CMS was higher when the IDF criteria were used in the German sample, but the IDF criteria had lower predictive power for coronary events.58 However, such CVD predictive power of any of the clinical definitions of CMS was not found in any of the studies in this review. The diagnostic efficacy of these definitions have not been studied extensively in Nigerian and other Sub-Saharan

nations, thus the reason why there is no precision in the use of the diagnostic definitions albeit a joint scientific statement recommended the IDF for the Sub-Saharans.1 Longitudinal studies exploring the diagnostic efficacies of these definitions and their CVD predictive power should be envisaged in Nigeria, especially studies evaluating the reliability of the Europid WC cut-off points, which the concensus statement have recommended for Sub-Saharans. The mechanism in which the CMS interrelate has yet to be clearly elucidated,1 but there is suggestion that CMS is a prediabetic state.10 Interestingly, epidemiological evidence suggests that the relationship between diabetes and CVD begins earlier in progression from prediabetes to diabetes.59 This should rekindle attention on assessment of these cardiovascular risk factors, including consensus agreed definition of CMS for Sub-Saharan population, for early identification and intervention at the stage where the morbid conditions can be modified. Age group of populations studied: a greater number of studies in this review assessed the CMS in subjects of 35 years of age and above. It is pertinent to note that this is a stage where thresholds for prehypertension and prediabetes (subclinical hypertension and diabetes) may have outpassed.60 Whether the indices of CMS is a predictive tool for future occurrence of diabetes and CVD is still an issue for debate. In San Anthonio Study,61 receiver operating characteristics (ROC) analyses data showed that the Framingham risk score is a better screening tool for CVD than the CMS, while in the Artherosclerosis risk in communities (ARIC) cohort, the CMS was found to be predictive of cardiovascular events but did not improve the coronary risk prediction beyond that achieved by the Framingham risk score.5 However, in resource constrained settings, the CMS might be a better predictive tool for cardiovascular events than the available risk scores owing to the fact that most risk scores target subjects of 40 years of age e a stage where overt conditions may have been established. In young asymptomatic individuals and women, these traditional CVD risk tools seem to underestimate the CVD risk.62 With the growing opinion that CMS is a prediabetic state, authors have hypothesized a risk assessment chart for prediabetes.63 More so, there is call to assess the potential of possible screening of individuals less than 40 years old.64 Type of studies and subpopulations studied: each of the 32 studies assessed revealed significant prevalence of CMS in Nigeria. However, no longitudinal study was found on the CMS studies done in Nigeria. It is worthy of note that longterm prospective studies are needed in the Sub-Saharan ethnic group to reach more reliable waist circumference cut points. Based on the recent consensus statement, the waist circumference cut point of the ATP-III definition is strictly prescribed for the Americans, while that currently recommended for the Sub-Saharan ethnic group is that which is of Europid ethnicity.1 This infers that the real representation of results from studies in this review may not be the true morbid state of these CVD risk factors in these proportion of the Nigerian population studied over the last 12 years. It is glaring that studies among the apparently healthy individuals within the Sub-urban and rural communities are below average. Most of the studies were done in the urban settings. All of the

p u b l i c h e a l t h 1 2 9 ( 2 0 1 5 ) 4 1 3 e4 2 3


Fig. 2 e A: Geo-distribution of CMS in Nigeria, B: Distribution of CMS and use of the three clinical definitions in Nigeria.


p u b l i c h e a l t h 1 2 9 ( 2 0 1 5 ) 4 1 3 e4 2 3

Fig. 3 e A: Prevalence of CMS in hospital-based studies, B: Prevalence of CMS in population-based studies in urban, semi-urban and rural settings.

hospital-based study settings are tertiary health institutions located in the urban areas of major cities. These in addition to the study on apparently healthy individuals in the urban areas indicates that health status of those in the rural and remotes areas are not well taken care of, thereby predisposing them to a very high rate of morbidity and mortality resulting from CMS most of which are undetected. This study corroborates with the fact that there is inadequate prevalence studies on CMS in

Sub-Saharan Africa, however, evidence shows that Nigeria has the highest frequency of CMS among the Sub-Saharans as a result of the growing economic strength and the degree of western influence on both communities.16 This reflects the impact of increasing urbanization and reduced physical activity. The review has also shown that studies are lacking in the Northern region of the country as compared to the Southern part. This is in relation to the wealth and economic

p u b l i c h e a l t h 1 2 9 ( 2 0 1 5 ) 4 1 3 e4 2 3

stability which are indicators of urbanization. The southern region outweighs the Northern counterpart in terms of the level of westernization.

Limitation of studies in the review The review could not determine the variability of prevalence rates in relation to the age group studied since the studies employed different clinical diagnostic criteria for CMS. Studies, especially those carried out in hospitals/health facilities did not describe appropriate method of sample size and power determination to justify the reliability of the prevalence projections. None of the studies tried to ascertain the cardiovascular disease predictive power of the different clinical definitions of CMS in the Nigerian subjects.

Conclusion A significant prevalence of CMS exists in Nigeria, although available studies are inadequate. More studies, especially longitudinal studies exploring the association between WC thresholds, prediabetes and CMS to risk of CVD and type 2 diabetes are envisaged. Rural communities and young adults are yet to be studied. There should be a rekindled attention on assessment of these cardiovascular risk factors for at least two reasons; including (1) a consensus on the definition of CMS for African population, and (2) for early identification and intervention at the stage where the morbid conditions can be modified.

Author statements Acknowledgements The authors appreciate Prof. Timothy Skinner for his input towards the intellectual context of this article. Honia Medical Diagnostic and Research Laboratory, Nigeria is also acknowledged for the support provided at the proposal phase of this work.

Ethical approval This study is part of VMO's doctorate research, which was approved by the Ethics Committee of the Charles Darwin University, Northern Territory, Australia (HREC Reference:H14003).

Funding VMO is a recipient of the Prestigious International Research Training Scholarship (PIRTS) and University Postgraduate Research Scholarship (UPRS) from the Charles Darwin University, NT, Australia. The funding body played no role in conducting the study, drafting the manuscript and the decision to publish.

Competing interests None declared.



1. Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, Fruchart JC, James WP, Loria CM, Smith SC Jr. International Diabetes Federation Task Force on, Epidemiology, Prevention; Hational Heart, Lung, Blood, Institute; American Heart Association; World Heart Federation; International Atherosclerosis, Society; and International Association for the Study of Obesity. Circulation 2009;120:1640e5. n B, Lahti K, Nisse  n M, 2. Isomaa B, Almgren P, Tuomi T, Forse Taskinen M, Groop L. Cardiovascular morbidity and mortality associated with the metabolic syndrome. Diabetes Care 2001;24:683e9. 3. Magliano DJ, Shaw JE, Zimmet PZ. How to best define the metabolic syndrome. Ann Med 2006;38:34e41. 4. Ross R. The pathogenesis of atherosclerosis: a perspective for the 1990s. Nature 1993;362:801e9. 5. Qiao Q, Gao W, Zhang L, Nyamdorj R, Tuomilehto J. Metabolic syndrome and cardiovascular disease. Ann Clin Biochem 2007;44:232e63. 6. Reaven GM. Banting lecture 1988: role of insulin resistance in human disease. Diabetes 1988;37:1595e607. 7. Alberti KG, Zimmet PZ. Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes mellitus provisional report of a WHO consultation. Diabet Med 1998;15:539e53. 8. NCEP. Third report of the National Cholesterol Education Program (NCEP) expert panel on detection, evaluation, and treatment of high blood cholesterol in adults (Adult Treatment Panel III) final report. Circulation 2002;106:3143e421. 9. Alberti KG, Zimmet P, Shaw JIDF Epidemiology Task Force Consensus Group. The metabolic syndromeea new worldwide definition. Lancet 2005;366:1059e62. 10. Babu A, Fogelfeld L. Metabolic syndrome and prediabetes. Dis Mon 2006;52:55e144. 11. Ahaneku GI, Osuji CU, Anisiuba BC, Ikeh VO, Oguejiofor OC, Ahaneku JE. Evaluation of blood pressure and indices of obesity in a typical rural community in eastern Nigeria. Ann Afr Med 2011;10:120e6. 12. Akpa M, Emem-Chioma P, Odia O. Current epidemiology of hypertension in Port Harcourt metropolis, Rivers State, Nigeria. P H Med J 2008;2:218e23. 13. Azinge N, Anizor C. Diabetes mellitus screening and prevalence in a rural community in Delta State, SoutheSouth Nigeria. Niger J General Pract 2012;10:15e7. 14. Bakari AG, Onyemelukwe GC, Sani BG, Aliyu IS, Hassan SS, Aliyu TM. Obesity overweight and underweight in suburban northern Nigeria. Int J Diabetes Metab 2007;15:68e9. 15. Ejike CE, Ugwu CE, Ezeanyika LU. Nutritional status, prevalence of some metabolic risk factors for cardiovascular disease and BMI-metabolic-risk sub-phenotypes in an adult Nigerian population. Biokemistri 2009;21. 16. Adediran O, Akintunde AA, Edo AE, Opadijo OG, Araoye AM. Impact of urbanization and gender on frequency of metabolic syndrome among native Abuja settlers in Nigeria. J Cardiovasc Dis Res 2012;3:191e6. 17. Flegal KM, Graubard BI, Williamson DF, Gail MH. Excess deaths associated with underweight, overweight, and obesity. JAMA 2005;293:1861e7. 18. Mokdad AH, Marks JS, Stroup DF, Gerberding JL. Actual causes of death in the united states, 2000. JAMA 2004;291:1238e45. 19. Kengne AP, Amoah AGB, Mbanya JC. Cardiovascular complications of diabetes mellitus in Sub-Saharan Africa. Circulation 2005;112:3592e601.


p u b l i c h e a l t h 1 2 9 ( 2 0 1 5 ) 4 1 3 e4 2 3

20. Sobngwi E, Mauvais-Jarvis F, Vexiau P, Mbanya JC, Gautier JF. Diabetes in Africans. Part 1: epidemiology and clinical specificities. Diabete Metab 2001;27:628e34. 21. Olsen H. The potential of community based health care in a community undergoing societal transitions; the case of old Igbo people [Master thesis]. University of Oslo. accessed 17.01.15. Available online from:, handle/10852/36103/HeidixOlsen.pdf?sequence¼1; 2013. 22. Iloeje NP. A new geography of Nigeria. Longman Nigeria PLC; 2001. 23. CIA. The world factbook: Nigeria [cited 2013 December]; Available from:; 2013. 24. Softusevista Inc. Distance calculator [accessed online 30.10.13]; Available from: 25. Siminialayi IM, Emem-Chioma PC. Metabolic syndrome in a rural Nigerian community: is central obesity always the key determinant? Niger Health J 2008;8:48e51. 26. Udenze IC, Azinge EC, Arikawe AP, Egbuagha EU, Onyenekwu C, Ayodele O, Adizua UC. The prevalence of metabolic syndrome in persons with type 2 diabetes at the Lagos University Teaching Hospital, Lagos, Nigeria. West Afr J Med 2013;32:126e32. 27. Ogbera AO. Prevalence and gender distribution of the metabolic syndrome. Diabetol Metab Syndr 2010;2:1e5. 28. Alebiosu CO, Odusan BO. Metabolic syndrome in subjects with type-2 diabetes mellitus. J Natl Med Assoc 2004;96:817e21. 29. Adediran O, Edo A, Jimoh A, Ohwovoriole A. Prevalence of the metabolic syndrome among Nigerians with type 2 diabetes. Diabetes Int 2007;15:13e4. 30. Akande AA, Jimoh AK, Akinyinka OA, Olarinoye GO. Serum uric acid level as an independent component of the metabolic syndrome in type 2 diabetic blacks. Niger J Clin Pract 2007;10:137e42. 31. Isezuo SA, Ezunu E. Demographic and clinical correlates of metabolic syndrome in Native African type-2 diabetic patients. J Natl Med Assoc 2005;97:557e63. 32. Puepet F, Uloko A, Akogu I, Aniekwensi E. Prevalence of the metabolic syndrome among patients with type 2 diabetes mellitus in urban North-Central Nigeria. Afr J Endocrinol Metab 2009;8:12e4. 33. Osuji CU, Nzerem BA, Dioka CE, Onwubuya EI. Metabolic syndrome in newly diagnosed type 2 diabetes mellitus using NCEP-ATPIII, the Nnewi experience. Niger J Clin Pract 2012;15:475e80. 34. Ogbera A, Fasanmade O, Kalra S. Menopausal symptoms and the metabolic syndrome in Nigerian women with type 2 diabetes mellitus. Climacteric 2011;14:75e82. 35. Unadike B, Akpan N, Peters E, Essien I, Essien O. Prevalence of the metabolic syndrome among patients with type 2 diabetes mellitus in Uyo, Nigeria. Afr J Endocrinol Metab 2009;8:9e11. 36. Ogbera A. Relationship between serum testosterone levels and features of the metabolic syndrome defining criteria in patients with type 2 diabetes mellitus. West Afr J Med 2011;30:277e81. 37. Ogbera AO, Azenabor AO. Hyperuricaemia and the metabolic syndrome in type 2 DM. Diabetol Metab Syndr 2010;2:24. 38. Akintunde AA, Ayodele OE, Akinwusi PO, Opadijo GO. Metabolic syndrome: comparison of occurrence using three definitions in hypertensive patients. Clin Med Res 2011;9:26e31. 39. Osuji CU, Omejua EG. Prevalence and characteristics of the metabolic syndrome among newly diagnosed hypertensive patients. Indian J Endocr Metab; 2012::104e9. 40. Ojji DB, Ajayi SO, Mamven MH, Alabi P. Prevalence of metabolic syndrome among hypertensive patients in Abuja, Nigeria. Ethn Dis 2012;22:1e4. 41. Akintunde A, Ayodele O, Akinwusi P, Peter J, Opadijo O. Metabolic syndrome among newly diagnosed non-diabetic















56. 57.



hypertensive Nigerians: prevalence and clinical correlates. SA J Diabetes Vasc Dis 2010;7:107e10. Ayodele OE, Akinboro AO, Akinyemi SO, Adepeju AA, Akinremi OA, Alao CA, Popoola AA. Prevalence and clinical correlates of metabolic syndrome in Nigerians living with human immunodeficiency virus/acquired immunodeficiency syndrome. Metab Syndr Relat Disord 2012;10:373e9. Ogbera AO, Kuku S, Dada O. The metabolic syndrome in thyroid disease: a report from Nigeria. Indian J Endocr Metab 2012;16:417e22. Adeyeye OO, Ogbera AO, Ogunleye OO, Brodie-Mens AT, Abolarinwa FF, Bamisile RT, et al. Understanding asthma and the metabolic syndromeea Nigerian report. Int Arch Med 2012;5:1e7. Siminalayi I, Emem-Chioma P, Odia O. relative risk of metabolic syndrome components in Nigerians: the adult treatment panel III definition. P H Med J 2009;3. Adedoyin RA, Afolabi A, Adegoke OO, Akintomide AO, Awotidebe TO. Relationship between socio-economic status and metabolic syndrome among Nigerian adults. Diabetes Metab Syndr 2013;7:91e4. Adegoke OA, Adedoyin RA, Balogun MO, Adebayo RA, Bisiriyu LA, Salawu AA. Prevalence of metabolic syndrome in a rural community in Nigeria. Metab Syndr Relat Disord 2010;8:59e62. Charles-Davies MA, Arinola O, Fasanmade A, Olaniyi J, Oyewole O, Owolabi M, Hassan OO, Ajobo MT, Adigun K, Akinlade KS. Indices of metabolic syndrome in 534 apparently healthy Nigerian traders. J US-China Med Sci 2012;9:91e100. Ulasi II, Ijoma CK, Onodugo OD. A community-based study of hypertension and cardio-metabolic syndrome in semi-urban and rural communities in Nigeria. BMC Health Serv Res 2010;10:71. Chukwukelu E, Ogbu I, Onyeanusi C. Prevalence of metabolic syndrome in some urban and rural communities in Enugu state, Nigeria. Internet J Lab Med 2013;5. Ijeh II, Okorie U, Ejike C. Obesity, metabolic syndrome and BMI-metabolic-risk sub-phenotypes: a study of an adult Nigerian population. J Med Med Sci 2010;1:254e60. Ogbu I, Chukwukelu E. The prevalence of the metabolic syndrome among normal weight Nigerians. J Coll Med 2013;17:43e54. Sani MU, Wahab KW, Yusuf BO, Gbadamosi M, Johnson OV, Gbadamosi A. Modifiable cardiovascular risk factors among apparently healthy adult Nigerian population e a cross sectional study. BMC Res Notes 2010;3:1e7. Ghazali S, Sanusi R. Waist circumference, waist to hip ratio, and body mass index in the diagnosis of metabolic syndrome in Nigerian subjects. Niger J Physiol Sci 2013;25:187e95. Odenigbo U, Odenigbo C, Oguejiofor O, Oguejiofor C. Prevalence of metabolic syndrome in healthy professionals in Asaba, SoutheSouth Nigeria. J Biomed Investig 2009;7. Riediger ND, Clara I. Prevalence of metabolic syndrome in the Canadian adult population. CMAJ 2011;183:E1127e34. Tanamas SK, Magliano DJ, Lynch B, Sethi P, Willenberg L, Polkinghorne KR, Chadban S, Dunstan D, Shaw JE. The Australian diabetes, obesity and lifestyle study (AusDiab). Bak IDI; 2012:34e38. Assmann G, Guerra R, Fox G, Cullen P, Schulte H, Willett D, Grundy SM. Harmonizing the definition of the metabolic syndrome: comparison of the criteria of the adult treatment panel III and the International Diabetes Federation in United States American and European populations. Am J Cardiol 2007;99:541e8. Deedwania PC, Fonseca VA. Diabetes, prediabetes, and cardiovascular risk: shifting the paradigm. Am J Med 2005;118:939e47.

p u b l i c h e a l t h 1 2 9 ( 2 0 1 5 ) 4 1 3 e4 2 3

60. Lin T, Liu JC, Chang LY, Lee TM. Association of metabolic syndrome and diabetes with subclinical coronary stenosis and plaque subtypes in middle-aged individuals. Diabet Med 2011;28:493e9.  lez-Villalpando C, Hunt KJ, 61. Stern MP, Williams K, Gonza Haffner SM. Does the metabolic syndrome improve identification of individuals at risk of type 2 diabetes and/or cardiovascular disease? Diabetes Care 2004;27:2676e81. 62. Nasir K, Michos ED, Blumenthal RS, Raggi P. Detection of high-risk young adults and women by coronary calcium and


National Cholesterol Education Program Panel III guidelines. J Am Coll Cardiol 2005;46:1931e6. 63. Nwose EU, Richards RS, Cann NG, Butkowski E. Cardiovascular risk assessment in prediabetes: a hypothesis. Med Hypotheses 2009;72:271e5. 64. Nwose EU, Richards RS, Digban K, Bwititi PT, Ennis G, Yee KC, Oguoma VM, Liberato S. Cardiovascular risk assessment in prediabetes and undiagnosed diabetes mellitus study: international collaboration research overview. North Am J Med Sci 2013;5:625e30.

Lihat lebih banyak...


Copyright © 2017 DADOSPDF Inc.