Diagnostic performance of waist-to-height ratio in identifying cardiovascular risk factors and metabolic syndrome among adult Saudis: A cross-sectional study

Rasmieh Alzeidan; Amel Fayed; Fatemeh Rabiee; Ahmad Hersi; Hala Elmorshedy

doi:10.15537/smj.2020.3.24915

References

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2. Koh GC,
3. Chen C,
4. Wong MT,
5. Fallows SJ
(2015) Comparison of body mass index (BMI), body adiposity index (BAI), waist circumference (WC), waist-to-hip ratio (WHR) and waist-to-height ratio (WHtR) as predictors of cardiovascular disease risk factors in an adult population in Singapore. PloS One 10:e0122985.
OpenUrl PubMed
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1. Owolabi EO,
2. Ter Goon D,
3. Adeniyi OV
(2017) Central obesity and normal-weight central obesity among adults attending healthcare facilities in Buffalo City Metropolitan Municipality, South Africa:a cross-sectional study. J Health Popul Nutr 36:54.
OpenUrl PubMed
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1. Ashwell M,
2. Gunn P,
3. Gibson S
(2012) Waist-to-height ratio is a better screening tool than waist circumference and BMI for adult cardiometabolic risk factors:systematic review and meta-analysis. Obes Rev 13:275–286.
OpenUrl CrossRef PubMed
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1. Irlbeck T,
2. Janitza S,
3. Poros B,
4. Golebiewski M,
5. Frey L,
6. Paprottka PM,
7. et al.
(2018) Quantification of adipose tissue and muscle mass based on computed tomography scans:Comparison of eight planimetric and diametric techniques including a step-by-step guide. Eur Surg Res 59:23–34.
OpenUrl
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1. Lee CM,
2. Huxley RR,
3. Wildman RP,
4. Woodward M
(2008) Indices of abdominal obesity are better discriminators of cardiovascular risk factors than BMI:a meta-analysis. J Clin Epidemiol 61:646–653.
OpenUrl CrossRef PubMed Web of Science
↵
1. Ashwell M,
2. Gibson S
(2016) Waist-to-height ratio as an indicator of 'early health risk':simpler and more predictive than using a 'matrix'based on BMI and waist circumference. BMJ Open 6:e010159.
OpenUrl Abstract/FREE Full Text
↵
1. Ashwell M,
2. Gibson S
(2014) A proposal for a primary screening tool:'Keep your waist circumference to less than half your height' BMC Med 12:207.
OpenUrl CrossRef PubMed
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1. Chen BD,
2. Yang YN,
3. Ma YT,
4. Pan S,
5. He CH,
6. Liu F,
7. et al.
(2015) Waist-to-height ratio and triglycerides/high-density lipoprotein cholesterol were the optimal predictors of metabolic syndrome in uighur men and women in Xinjiang, China. Metab Syndr Relat Disord 13:214–220.
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1. Boutayeb A,
2. Boutayeb S
(2005) The burden of non communicable diseases in developing countries. Int J Equity Health 4:2.
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1. Al-Rubean K,
2. Youssef AM,
3. AlFarsi Y,
4. Al-Sharqawi AH,
5. Bawazeer N,
6. AlOtaibi MT,
7. et al.
(2017) Anthropometric cutoff values for predicting metabolic syndrome in a Saudi community:from the SAUDI-DM study. Anna Saudi Med 37:21–30.
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1. Al-Hazzaa HM,
2. Abahussain NA,
3. Al-Sobayel HI,
4. Qahwaji DM,
5. Alsulaiman NA,
6. Musaiger AO
(2014) Prevalence of overweight, obesity, and abdominal obesity among urban Saudi adolescents:gender and regional variations. J Health Popul Nutr 32:634–645.
OpenUrl
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1. Memish ZA,
2. El Bcheraoui C,
3. Tuffaha M,
4. Robinson M,
5. Daoud F,
6. Jaber S,
7. et al.
(2014) Obesity and associated factors Kingdom of Saudi Arabia 2013. Prev chronic Dis 11:E174.
OpenUrl
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1. Alzeidan R,
2. Rabiee F,
3. Mandil A,
4. Hersi A,
5. Fayed A
(2016) Non-communicable disease risk factors among employees and their families of a Saudi University:An epidemiological study. PLoS One 11:e0165036.
OpenUrl
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1. World Health Organization
(2018) WHO STEPS Instrument (Core and Expanded) (World Health Organization, Geneva (SW)) Available from: https://www.who.int/ncds/surveillance/steps/STEPS_Instrument_v2.1.pdf.
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1. World Health Organization
(2018) Global database on body mass index (BMI) (World Health Organization, >Geneva (SW)) Available from: https://www.who.int/nutrition/databases/bmi/en/.
↵
1. Sherling DH,
2. Perumareddi P,
3. Hennekens CH
(2017) Metabolic Syndrome. J Cardiovasc Pharmacol Ther 22:365–367.
OpenUrl
↵
1. World Health Organization
(2011) Use of glycated haemoglobin (HbA1c) in the diagnosis of diabetes mellitus (World Health Organization, Geneva (SW)) Available from: https://www.who.int/diabetes/publications/report-hba1c_ 2011.pdf.
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1. 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
(2002) Circulation 106:3143–3421.
OpenUrl FREE Full Text
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1. Romero-Saldaña M,
2. Fuentes-Jiménez FJ,
3. Vaquero-Abellán M,
4. Álvarez-Fernández C,
5. Aguilera-López MD,
6. Molina-Recio G
(2019) Predictive capacity and cutoff value of waist-to-height ratio in the incidence of metabolic syndrome. Clin Nurs Res 28:676–691.
OpenUrl
↵
1. Hardy DS,
2. Stallings DT,
3. Garvin JT,
4. Gachupin FC,
5. Xu H,
6. Racette SB
(2017) Anthropometric discriminators of type 2 diabetes among White and Black American adults. J Diabetes 9:296–307.
OpenUrl
↵
1. Son YJ,
2. Kim J,
3. Park HJ,
4. Park SE,
5. Park CY,
6. Lee WY,
7. et al.
(2016) Association of Waist-Height Ratio with Diabetes Risk:A 4-Year Longitudinal Retrospective Study. Endocrinol Metab (Seoul) 31:127–133.
OpenUrl
↵
1. Zhang F,
2. Wan Q,
3. Cao H,
4. Tang L,
5. Li D,
6. Lü Q,
7. et al.
(2018) Identical anthropometric characteristics of impaired fasting glucose combined with impaired glucose tolerance and newly diagnosed type 2 diabetes:anthropometric indicators to predict hyperglycaemia in a community-based prospective cohort study in southwest China. BMJ Open 8:e019735.
OpenUrl Abstract/FREE Full Text
↵
1. Khader Y,
2. Batieha A,
3. Jaddou H,
4. El-Khateeb M,
5. Ajlouni K
(2019) The performance of anthropometric measures to predict diabetes mellitus and hypertension among adults in Jordan. BMC Public Health 19:1416.
OpenUrl
↵
1. Ononamadu CJ,
2. Ezekwesili CN,
3. Onyeukwu OF,
4. Umeoguaju UF,
5. Ezeigwe OC,
6. Ihegboro GO
(2017) Comparative analysis of anthropometric indices of obesity as correlates and potential predictors of risk for hypertension and prehypertension in a population in Nigeria. Cardiovasc J Afr 28:92–99.
OpenUrl
↵
1. Janghorbani M,
2. Aminorroaya A,
3. Amini M
(2017) Comparison of different obesity indices for predicting incident hypertension. High Blood Press Cardiovasc Prev 24:157–166.
OpenUrl
↵
1. Zeng Q,
2. He Y,
3. Dong S,
4. Zhao X,
5. Chen Z,
6. Song Z,
7. et al.
(2014) Optimal cut-off values of BMI, waist circumference and waist:height ratio for defining obesity in Chinese adults. Br J Nutr 112:1735–1744.
OpenUrl CrossRef PubMed
↵
1. Lee BJ,
2. Kim JY
(2014) A comparison of the predictive power of anthropometric indices for hypertension and hypotension risk. PloS One 9:e84897.
OpenUrl
↵
1. Kazlauskaite R,
2. Avery-Mamer EF,
3. Li H,
4. Chataut CP,
5. Janssen I,
6. Powell LH,
7. et al.
(2017) Race/ethnic comparisons of waist-to-height ratio for cardiometabolic screening:the study of women's health across the nation. Am J Hum Biol 29:22909.
OpenUrl
↵
1. Shen S,
2. Lu Y,
3. Qi H,
4. Li F,
5. Shen Z,
6. Wu L,
7. et al.
(2017) Waist-to-height ratio is an effective indicator for comprehensive cardiovascular health. Sci Rep 7:43046.
OpenUrl
↵
1. Corrêa MM,
2. Thumé E,
3. De Oliveira ER,
4. Tomasi E
(2016) Performance of the waist-to-height ratio in identifying obesity and predicting non-communicable diseases in the elderly population:A systematic literature review. Arch Gerontol Geriatr 65:174–182.
OpenUrl
↵
1. Rost S,
2. Freuer D,
3. Peters A,
4. Thorand B,
5. Holle R,
6. Linseisen J,
7. et al.
(2018) New indexes of body fat distribution and sex-specific risk of total and cause-specific mortality:a prospective cohort study. BMC Public Health 18:427.
OpenUrl CrossRef PubMed

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Keywords

[1] ↵
Lam BC,
Koh GC,
Chen C,
Wong MT,
Fallows SJ
(2015) Comparison of body mass index (BMI), body adiposity index (BAI), waist circumference (WC), waist-to-hip ratio (WHR) and waist-to-height ratio (WHtR) as predictors of cardiovascular disease risk factors in an adult population in Singapore. PloS One 10:e0122985.
OpenUrl PubMed

[2] Lam BC,

[3] Koh GC,

[4] Chen C,

[5] Wong MT,

[6] Fallows SJ

[7] ↵
Owolabi EO,
Ter Goon D,
Adeniyi OV
(2017) Central obesity and normal-weight central obesity among adults attending healthcare facilities in Buffalo City Metropolitan Municipality, South Africa:a cross-sectional study. J Health Popul Nutr 36:54.
OpenUrl PubMed

[8] Owolabi EO,

[9] Ter Goon D,

[10] Adeniyi OV

[11] ↵
Ashwell M,
Gunn P,
Gibson S
(2012) Waist-to-height ratio is a better screening tool than waist circumference and BMI for adult cardiometabolic risk factors:systematic review and meta-analysis. Obes Rev 13:275–286.
OpenUrl CrossRef PubMed

[12] Ashwell M,

[13] Gunn P,

[14] Gibson S

[15] ↵
Irlbeck T,
Janitza S,
Poros B,
Golebiewski M,
Frey L,
Paprottka PM,
et al.
(2018) Quantification of adipose tissue and muscle mass based on computed tomography scans:Comparison of eight planimetric and diametric techniques including a step-by-step guide. Eur Surg Res 59:23–34.
OpenUrl

[16] Irlbeck T,

[17] Janitza S,

[18] Poros B,

[19] Golebiewski M,

[20] Frey L,

[21] Paprottka PM,

[22] et al.

[23] ↵
Lee CM,
Huxley RR,
Wildman RP,
Woodward M
(2008) Indices of abdominal obesity are better discriminators of cardiovascular risk factors than BMI:a meta-analysis. J Clin Epidemiol 61:646–653.
OpenUrl CrossRef PubMed Web of Science

[24] Lee CM,

[25] Huxley RR,

[26] Wildman RP,

[27] Woodward M

[28] ↵
Ashwell M,
Gibson S
(2016) Waist-to-height ratio as an indicator of 'early health risk':simpler and more predictive than using a 'matrix'based on BMI and waist circumference. BMJ Open 6:e010159.
OpenUrl Abstract/FREE Full Text

[29] Ashwell M,

[30] Gibson S

[31] ↵
Ashwell M,
Gibson S
(2014) A proposal for a primary screening tool:'Keep your waist circumference to less than half your height' BMC Med 12:207.
OpenUrl CrossRef PubMed

[32] Ashwell M,

[33] Gibson S

[34] ↵
Chen BD,
Yang YN,
Ma YT,
Pan S,
He CH,
Liu F,
et al.
(2015) Waist-to-height ratio and triglycerides/high-density lipoprotein cholesterol were the optimal predictors of metabolic syndrome in uighur men and women in Xinjiang, China. Metab Syndr Relat Disord 13:214–220.
OpenUrl

[35] Chen BD,

[36] Yang YN,

[37] Ma YT,

[38] Pan S,

[39] He CH,

[40] Liu F,

[41] et al.

[42] ↵
Boutayeb A,
Boutayeb S
(2005) The burden of non communicable diseases in developing countries. Int J Equity Health 4:2.
OpenUrl CrossRef PubMed

[43] Boutayeb A,

[44] Boutayeb S

[45] ↵
Al-Rubean K,
Youssef AM,
AlFarsi Y,
Al-Sharqawi AH,
Bawazeer N,
AlOtaibi MT,
et al.
(2017) Anthropometric cutoff values for predicting metabolic syndrome in a Saudi community:from the SAUDI-DM study. Anna Saudi Med 37:21–30.
OpenUrl

[46] Al-Rubean K,

[47] Youssef AM,

[48] AlFarsi Y,

[49] Al-Sharqawi AH,

[50] Bawazeer N,

[51] AlOtaibi MT,

[52] et al.

[53] Al-Hazzaa HM,
Abahussain NA,
Al-Sobayel HI,
Qahwaji DM,
Alsulaiman NA,
Musaiger AO
(2014) Prevalence of overweight, obesity, and abdominal obesity among urban Saudi adolescents:gender and regional variations. J Health Popul Nutr 32:634–645.
OpenUrl

[54] Al-Hazzaa HM,

[55] Abahussain NA,

[56] Al-Sobayel HI,

[57] Qahwaji DM,

[58] Alsulaiman NA,

[59] Musaiger AO

[60] ↵
Memish ZA,
El Bcheraoui C,
Tuffaha M,
Robinson M,
Daoud F,
Jaber S,
et al.
(2014) Obesity and associated factors Kingdom of Saudi Arabia 2013. Prev chronic Dis 11:E174.
OpenUrl

[61] Memish ZA,

[62] El Bcheraoui C,

[63] Tuffaha M,

[64] Robinson M,

[65] Daoud F,

[66] Jaber S,

[67] et al.

[68] ↵
Alzeidan R,
Rabiee F,
Mandil A,
Hersi A,
Fayed A
(2016) Non-communicable disease risk factors among employees and their families of a Saudi University:An epidemiological study. PLoS One 11:e0165036.
OpenUrl

[69] Alzeidan R,

[70] Rabiee F,

[71] Mandil A,

[72] Hersi A,

[73] Fayed A

[74] ↵
World Health Organization
(2018) WHO STEPS Instrument (Core and Expanded) (World Health Organization, Geneva (SW)) Available from: https://www.who.int/ncds/surveillance/steps/STEPS_Instrument_v2.1.pdf.

[75] World Health Organization

[76] ↵
World Health Organization
(2018) Global database on body mass index (BMI) (World Health Organization, >Geneva (SW)) Available from: https://www.who.int/nutrition/databases/bmi/en/.

[77] World Health Organization

[78] ↵
Sherling DH,
Perumareddi P,
Hennekens CH
(2017) Metabolic Syndrome. J Cardiovasc Pharmacol Ther 22:365–367.
OpenUrl

[79] Sherling DH,

[80] Perumareddi P,

[81] Hennekens CH

[82] ↵
World Health Organization
(2011) Use of glycated haemoglobin (HbA1c) in the diagnosis of diabetes mellitus (World Health Organization, Geneva (SW)) Available from: https://www.who.int/diabetes/publications/report-hba1c_ 2011.pdf.

[83] World Health Organization

[84] ↵
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
(2002) Circulation 106:3143–3421.
OpenUrl FREE Full Text

[85] 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

[86] ↵
Romero-Saldaña M,
Fuentes-Jiménez FJ,
Vaquero-Abellán M,
Álvarez-Fernández C,
Aguilera-López MD,
Molina-Recio G
(2019) Predictive capacity and cutoff value of waist-to-height ratio in the incidence of metabolic syndrome. Clin Nurs Res 28:676–691.
OpenUrl

[87] Romero-Saldaña M,

[88] Fuentes-Jiménez FJ,

[89] Vaquero-Abellán M,

[90] Álvarez-Fernández C,

[91] Aguilera-López MD,

[92] Molina-Recio G

[93] ↵
Hardy DS,
Stallings DT,
Garvin JT,
Gachupin FC,
Xu H,
Racette SB
(2017) Anthropometric discriminators of type 2 diabetes among White and Black American adults. J Diabetes 9:296–307.
OpenUrl

[94] Hardy DS,

[95] Stallings DT,

[96] Garvin JT,

[97] Gachupin FC,

[98] Xu H,

[99] Racette SB

[100] ↵
Son YJ,
Kim J,
Park HJ,
Park SE,
Park CY,
Lee WY,
et al.
(2016) Association of Waist-Height Ratio with Diabetes Risk:A 4-Year Longitudinal Retrospective Study. Endocrinol Metab (Seoul) 31:127–133.
OpenUrl

[101] Son YJ,

[102] Kim J,

[103] Park HJ,

[104] Park SE,

[105] Park CY,

[106] Lee WY,

[107] et al.

[108] ↵
Zhang F,
Wan Q,
Cao H,
Tang L,
Li D,
Lü Q,
et al.
(2018) Identical anthropometric characteristics of impaired fasting glucose combined with impaired glucose tolerance and newly diagnosed type 2 diabetes:anthropometric indicators to predict hyperglycaemia in a community-based prospective cohort study in southwest China. BMJ Open 8:e019735.
OpenUrl Abstract/FREE Full Text

[109] Zhang F,

[110] Wan Q,

[111] Cao H,

[112] Tang L,

[113] Li D,

[114] Lü Q,

[115] et al.

[116] ↵
Khader Y,
Batieha A,
Jaddou H,
El-Khateeb M,
Ajlouni K
(2019) The performance of anthropometric measures to predict diabetes mellitus and hypertension among adults in Jordan. BMC Public Health 19:1416.
OpenUrl

[117] Khader Y,

[118] Batieha A,

[119] Jaddou H,

[120] El-Khateeb M,

[121] Ajlouni K

[122] ↵
Ononamadu CJ,
Ezekwesili CN,
Onyeukwu OF,
Umeoguaju UF,
Ezeigwe OC,
Ihegboro GO
(2017) Comparative analysis of anthropometric indices of obesity as correlates and potential predictors of risk for hypertension and prehypertension in a population in Nigeria. Cardiovasc J Afr 28:92–99.
OpenUrl

[123] Ononamadu CJ,

[124] Ezekwesili CN,

[125] Onyeukwu OF,

[126] Umeoguaju UF,

[127] Ezeigwe OC,

[128] Ihegboro GO

[129] ↵
Janghorbani M,
Aminorroaya A,
Amini M
(2017) Comparison of different obesity indices for predicting incident hypertension. High Blood Press Cardiovasc Prev 24:157–166.
OpenUrl

[130] Janghorbani M,

[131] Aminorroaya A,

[132] Amini M

[133] ↵
Zeng Q,
He Y,
Dong S,
Zhao X,
Chen Z,
Song Z,
et al.
(2014) Optimal cut-off values of BMI, waist circumference and waist:height ratio for defining obesity in Chinese adults. Br J Nutr 112:1735–1744.
OpenUrl CrossRef PubMed

[134] Zeng Q,

[135] He Y,

[136] Dong S,

[137] Zhao X,

[138] Chen Z,

[139] Song Z,

[140] et al.

[141] ↵
Lee BJ,
Kim JY
(2014) A comparison of the predictive power of anthropometric indices for hypertension and hypotension risk. PloS One 9:e84897.
OpenUrl

[142] Lee BJ,

[143] Kim JY

[144] ↵
Kazlauskaite R,
Avery-Mamer EF,
Li H,
Chataut CP,
Janssen I,
Powell LH,
et al.
(2017) Race/ethnic comparisons of waist-to-height ratio for cardiometabolic screening:the study of women's health across the nation. Am J Hum Biol 29:22909.
OpenUrl

[145] Kazlauskaite R,

[146] Avery-Mamer EF,

[147] Li H,

[148] Chataut CP,

[149] Janssen I,

[150] Powell LH,

[151] et al.

[152] ↵
Shen S,
Lu Y,
Qi H,
Li F,
Shen Z,
Wu L,
et al.
(2017) Waist-to-height ratio is an effective indicator for comprehensive cardiovascular health. Sci Rep 7:43046.
OpenUrl

[153] Shen S,

[154] Lu Y,

[155] Qi H,

[156] Li F,

[157] Shen Z,

[158] Wu L,

[159] et al.

[160] ↵
Corrêa MM,
Thumé E,
De Oliveira ER,
Tomasi E
(2016) Performance of the waist-to-height ratio in identifying obesity and predicting non-communicable diseases in the elderly population:A systematic literature review. Arch Gerontol Geriatr 65:174–182.
OpenUrl

[161] Corrêa MM,

[162] Thumé E,

[163] De Oliveira ER,

[164] Tomasi E

[165] ↵
Rost S,
Freuer D,
Peters A,
Thorand B,
Holle R,
Linseisen J,
et al.
(2018) New indexes of body fat distribution and sex-specific risk of total and cause-specific mortality:a prospective cohort study. BMC Public Health 18:427.
OpenUrl CrossRef PubMed

[166] Rost S,

[167] Freuer D,

[168] Peters A,

[169] Thorand B,

[170] Holle R,

[171] Linseisen J,

[172] et al.

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Diagnostic performance of waist-to-height ratio in identifying cardiovascular risk factors and metabolic syndrome among adult Saudis

A cross-sectional study

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Diagnostic performance of waist-to-height ratio in identifying cardiovascular risk factors and metabolic syndrome among adult Saudis

A cross-sectional study

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