Maximum accuracy obesity indices for screening metabolic syndrome in Nigeria: A consolidated analysis of four cross-sectional studies

Victor M Oguoma; Ezekiel U Nwose; Ifeoma I Ulasi; Adeseye A Akintunde; Ekene E Chukwukelu; Matthew A Araoye; Andrew E Edo; Chinwuba K Ijoma; Innocent C Onyia; Innocent I Ogbu; Joel C Onyeanusi; Kester A Digban; Obinna D Onodugo; Olufemi Adediran; Oladimeji G Opadijo; Phillip T Bwititi; Ross S Richards; Timothy C Skinner

doi:10.1016/j.dsx.2016.01.001

Maximum accuracy obesity indices for screening metabolic syndrome in Nigeria: A consolidated analysis of four cross-sectional studies

Victor M Oguoma, Ezekiel U Nwose, Ifeoma I Ulasi, Adeseye A Akintunde, Ekene E Chukwukelu, Matthew A Araoye, Andrew E Edo, Chinwuba K Ijoma, Innocent C Onyia, Innocent I Ogbu, Joel C Onyeanusi, Kester A Digban, Obinna D Onodugo, Olufemi Adediran, Oladimeji G Opadijo, Phillip T Bwititi, Ross S Richards, Timothy C Skinner

Research output: Contribution to journal › Article › peer-review

11 Citations (Scopus)

Abstract

BACKGROUND: In sub-Saharan Africa, there is no precise use of metabolic syndrome (MetS) definitions and risk factors screening indices in many clinical and public health services. Methods proposed and used in Western populations are adopted without validation within the local settings. The aim of the study is to assess obesity indices and cut-off values that maximise screening of MetS and risk factors in the Nigerian population.

METHOD: A consolidated analysis of 2809 samples from four population-based cross-sectional study of apparently healthy persons≥18 years was carried out. Optimal waist circumference (WC) and waist-to-height ratio (WHtR) cut points for diagnosing MetS and risk factors were determined using Optimal Data Analysis (ODA) model. The stability of the predictions of the models was also assessed.

RESULTS: Overall mean values of BMI, WC and WHtR were 24.8±6.0kgm(-2), 84.0±11.3cm and 0.52±0.1 respectively. Optimal WC cut-off for discriminating MetS and diabetes was 83cm in females and 85cm in males, and 82cm in females and 89cm in males, respectively. WC was stable in discriminating diabetes than did WHtR and BMI, while WHtR showed better stability in predicting MetS than WC and BMI.

CONCLUSION: The study shows that the optimal WC that maximises classification accuracy of MetS differs from that currently used for sub-Saharan ethnicity. The proposed global WHtR of 0.50 may misclassify MetS, diabetes and hypertension. Finally, the WC is a better predictor of diabetes, while WHtR is a better predictor of MetS in this sample population.

Original language	English
Pages (from-to)	121-127
Number of pages	7
Journal	Diabetes and Metabolic Syndrome: Clinical Research and Reviews
Volume	10
Issue number	3
DOIs	https://doi.org/10.1016/j.dsx.2016.01.001
Publication status	Published - 1 Jul 2016
Externally published	Yes

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10.1016/j.dsx.2016.01.001

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Oguoma, V. M., Nwose, E. U., Ulasi, I. I., Akintunde, A. A., Chukwukelu, E. E., Araoye, M. A., Edo, A. E., Ijoma, C. K., Onyia, I. C., Ogbu, I. I., Onyeanusi, J. C., Digban, K. A., Onodugo, O. D., Adediran, O., Opadijo, O. G., Bwititi, P. T., Richards, R. S., & Skinner, T. C. (2016). Maximum accuracy obesity indices for screening metabolic syndrome in Nigeria: A consolidated analysis of four cross-sectional studies. Diabetes and Metabolic Syndrome: Clinical Research and Reviews, 10(3), 121-127. https://doi.org/10.1016/j.dsx.2016.01.001

@article{db95ea2954b842259c71ca604b95b2eb,

title = "Maximum accuracy obesity indices for screening metabolic syndrome in Nigeria: A consolidated analysis of four cross-sectional studies",

abstract = "BACKGROUND: In sub-Saharan Africa, there is no precise use of metabolic syndrome (MetS) definitions and risk factors screening indices in many clinical and public health services. Methods proposed and used in Western populations are adopted without validation within the local settings. The aim of the study is to assess obesity indices and cut-off values that maximise screening of MetS and risk factors in the Nigerian population.METHOD: A consolidated analysis of 2809 samples from four population-based cross-sectional study of apparently healthy persons≥18 years was carried out. Optimal waist circumference (WC) and waist-to-height ratio (WHtR) cut points for diagnosing MetS and risk factors were determined using Optimal Data Analysis (ODA) model. The stability of the predictions of the models was also assessed.RESULTS: Overall mean values of BMI, WC and WHtR were 24.8±6.0kgm(-2), 84.0±11.3cm and 0.52±0.1 respectively. Optimal WC cut-off for discriminating MetS and diabetes was 83cm in females and 85cm in males, and 82cm in females and 89cm in males, respectively. WC was stable in discriminating diabetes than did WHtR and BMI, while WHtR showed better stability in predicting MetS than WC and BMI.CONCLUSION: The study shows that the optimal WC that maximises classification accuracy of MetS differs from that currently used for sub-Saharan ethnicity. The proposed global WHtR of 0.50 may misclassify MetS, diabetes and hypertension. Finally, the WC is a better predictor of diabetes, while WHtR is a better predictor of MetS in this sample population.",

keywords = "Diabetes, Metabolic syndrome, Sub-Sahara Africa, Waist circumference, Waist-to-height ratio",

author = "Oguoma, {Victor M} and Nwose, {Ezekiel U} and Ulasi, {Ifeoma I} and Akintunde, {Adeseye A} and Chukwukelu, {Ekene E} and Araoye, {Matthew A} and Edo, {Andrew E} and Ijoma, {Chinwuba K} and Onyia, {Innocent C} and Ogbu, {Innocent I} and Onyeanusi, {Joel C} and Digban, {Kester A} and Onodugo, {Obinna D} and Olufemi Adediran and Opadijo, {Oladimeji G} and Bwititi, {Phillip T} and Richards, {Ross S} and Skinner, {Timothy C}",

note = "Funding Information: This particular research report is part of an ongoing international collaboration programme on prediabetes and cardiovascular complications studies (PACCS). The assistance of Prof. Paul Yarnold of Optimal Data Analysis LLC USA in guiding with the use of ODA commands and timely response to queries is highly appreciated. VMO is supported by the Prestigious International Research Training Scholarship (PIRTS) and University Postgraduate Research Scholarship (UPRS) from the Charles Darwin University (CDU), Northern Territory, Australia. Publisher Copyright: {\textcopyright} 2016 Diabetes India",

year = "2016",

month = jul,

day = "1",

doi = "10.1016/j.dsx.2016.01.001",

language = "English",

volume = "10",

pages = "121--127",

journal = "Diabetes and Metabolic Syndrome: Clinical Research and Reviews",

issn = "1871-4021",

publisher = "Elsevier BV",

number = "3",

}

Oguoma, VM, Nwose, EU, Ulasi, II, Akintunde, AA, Chukwukelu, EE, Araoye, MA, Edo, AE, Ijoma, CK, Onyia, IC, Ogbu, II, Onyeanusi, JC, Digban, KA, Onodugo, OD, Adediran, O, Opadijo, OG, Bwititi, PT, Richards, RS & Skinner, TC 2016, 'Maximum accuracy obesity indices for screening metabolic syndrome in Nigeria: A consolidated analysis of four cross-sectional studies', Diabetes and Metabolic Syndrome: Clinical Research and Reviews, vol. 10, no. 3, pp. 121-127. https://doi.org/10.1016/j.dsx.2016.01.001

Maximum accuracy obesity indices for screening metabolic syndrome in Nigeria: A consolidated analysis of four cross-sectional studies. / Oguoma, Victor M; Nwose, Ezekiel U; Ulasi, Ifeoma I et al.
In: Diabetes and Metabolic Syndrome: Clinical Research and Reviews, Vol. 10, No. 3, 01.07.2016, p. 121-127.

Research output: Contribution to journal › Article › peer-review

TY - JOUR

T1 - Maximum accuracy obesity indices for screening metabolic syndrome in Nigeria

T2 - A consolidated analysis of four cross-sectional studies

AU - Oguoma, Victor M

AU - Nwose, Ezekiel U

AU - Ulasi, Ifeoma I

AU - Akintunde, Adeseye A

AU - Chukwukelu, Ekene E

AU - Araoye, Matthew A

AU - Edo, Andrew E

AU - Ijoma, Chinwuba K

AU - Onyia, Innocent C

AU - Ogbu, Innocent I

AU - Onyeanusi, Joel C

AU - Digban, Kester A

AU - Onodugo, Obinna D

AU - Adediran, Olufemi

AU - Opadijo, Oladimeji G

AU - Bwititi, Phillip T

AU - Richards, Ross S

AU - Skinner, Timothy C

N1 - Funding Information: This particular research report is part of an ongoing international collaboration programme on prediabetes and cardiovascular complications studies (PACCS). The assistance of Prof. Paul Yarnold of Optimal Data Analysis LLC USA in guiding with the use of ODA commands and timely response to queries is highly appreciated. VMO is supported by the Prestigious International Research Training Scholarship (PIRTS) and University Postgraduate Research Scholarship (UPRS) from the Charles Darwin University (CDU), Northern Territory, Australia. Publisher Copyright: © 2016 Diabetes India

PY - 2016/7/1

Y1 - 2016/7/1

N2 - BACKGROUND: In sub-Saharan Africa, there is no precise use of metabolic syndrome (MetS) definitions and risk factors screening indices in many clinical and public health services. Methods proposed and used in Western populations are adopted without validation within the local settings. The aim of the study is to assess obesity indices and cut-off values that maximise screening of MetS and risk factors in the Nigerian population.METHOD: A consolidated analysis of 2809 samples from four population-based cross-sectional study of apparently healthy persons≥18 years was carried out. Optimal waist circumference (WC) and waist-to-height ratio (WHtR) cut points for diagnosing MetS and risk factors were determined using Optimal Data Analysis (ODA) model. The stability of the predictions of the models was also assessed.RESULTS: Overall mean values of BMI, WC and WHtR were 24.8±6.0kgm(-2), 84.0±11.3cm and 0.52±0.1 respectively. Optimal WC cut-off for discriminating MetS and diabetes was 83cm in females and 85cm in males, and 82cm in females and 89cm in males, respectively. WC was stable in discriminating diabetes than did WHtR and BMI, while WHtR showed better stability in predicting MetS than WC and BMI.CONCLUSION: The study shows that the optimal WC that maximises classification accuracy of MetS differs from that currently used for sub-Saharan ethnicity. The proposed global WHtR of 0.50 may misclassify MetS, diabetes and hypertension. Finally, the WC is a better predictor of diabetes, while WHtR is a better predictor of MetS in this sample population.

AB - BACKGROUND: In sub-Saharan Africa, there is no precise use of metabolic syndrome (MetS) definitions and risk factors screening indices in many clinical and public health services. Methods proposed and used in Western populations are adopted without validation within the local settings. The aim of the study is to assess obesity indices and cut-off values that maximise screening of MetS and risk factors in the Nigerian population.METHOD: A consolidated analysis of 2809 samples from four population-based cross-sectional study of apparently healthy persons≥18 years was carried out. Optimal waist circumference (WC) and waist-to-height ratio (WHtR) cut points for diagnosing MetS and risk factors were determined using Optimal Data Analysis (ODA) model. The stability of the predictions of the models was also assessed.RESULTS: Overall mean values of BMI, WC and WHtR were 24.8±6.0kgm(-2), 84.0±11.3cm and 0.52±0.1 respectively. Optimal WC cut-off for discriminating MetS and diabetes was 83cm in females and 85cm in males, and 82cm in females and 89cm in males, respectively. WC was stable in discriminating diabetes than did WHtR and BMI, while WHtR showed better stability in predicting MetS than WC and BMI.CONCLUSION: The study shows that the optimal WC that maximises classification accuracy of MetS differs from that currently used for sub-Saharan ethnicity. The proposed global WHtR of 0.50 may misclassify MetS, diabetes and hypertension. Finally, the WC is a better predictor of diabetes, while WHtR is a better predictor of MetS in this sample population.

KW - Diabetes

KW - Metabolic syndrome

KW - Sub-Sahara Africa

KW - Waist circumference

KW - Waist-to-height ratio

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UR - http://www.mendeley.com/catalogue/maximum-accuracy-obesity-indices-screening-metabolic-syndrome-nigeria-consolidated-analysis-four-cro

U2 - 10.1016/j.dsx.2016.01.001

DO - 10.1016/j.dsx.2016.01.001

M3 - Article

C2 - 26907969

SN - 1871-4021

VL - 10

SP - 121

EP - 127

JO - Diabetes and Metabolic Syndrome: Clinical Research and Reviews

JF - Diabetes and Metabolic Syndrome: Clinical Research and Reviews

IS - 3

ER -

Maximum accuracy obesity indices for screening metabolic syndrome in Nigeria: A consolidated analysis of four cross-sectional studies

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