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

^*Corresponding author for this work

10 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 ± 6.0 kg m⁻², 84.0 ± 11.3 cm and 0.52 ± 0.1 respectively. Optimal WC cut-off for discriminating MetS and diabetes was 83 cm in females and 85 cm in males, and 82 cm in females and 89 cm 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
Journal	Diabetes and Metabolic Syndrome: Clinical Research and Reviews
Volume	10
Issue number	3
Pages (from-to)	121-127
Number of pages	7
ISSN	1871-4021
DOIs	https://doi.org/10.1016/j.dsx.2016.01.001
Publication status	Published - 1 Jul 2016

Keywords

Diabetes
Metabolic syndrome
Sub-Sahara Africa
Waist circumference
Waist-to-height ratio

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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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

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 › Journal article › Research › peer-review

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

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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 ± 6.0 kg m−2, 84.0 ± 11.3 cm and 0.52 ± 0.1 respectively. Optimal WC cut-off for discriminating MetS and diabetes was 83 cm in females and 85 cm in males, and 82 cm in females and 89 cm 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.}",

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",

number = "3",

}

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.

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 ± 6.0 kg m−2, 84.0 ± 11.3 cm and 0.52 ± 0.1 respectively. Optimal WC cut-off for discriminating MetS and diabetes was 83 cm in females and 85 cm in males, and 82 cm in females and 89 cm 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 ± 6.0 kg m−2, 84.0 ± 11.3 cm and 0.52 ± 0.1 respectively. Optimal WC cut-off for discriminating MetS and diabetes was 83 cm in females and 85 cm in males, and 82 cm in females and 89 cm 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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U2 - 10.1016/j.dsx.2016.01.001

DO - 10.1016/j.dsx.2016.01.001

M3 - Journal article

C2 - 26907969

AN - SCOPUS:84958581172

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

Abstract

Keywords

UN SDGs

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