Defining Obesity Cut Points in a Multiethnic Population
Background— Body mass index (BMI) is widely used to assess risk for cardiovascular disease and type 2 diabetes. Cut points for the classification of obesity (BMI >30 kg/m 2 ) have been developed and validated among people of European descent. It is unknown whether these cut points are appropriate...
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| Published in | Circulation (New York, N.Y.) Vol. 115; no. 16; pp. 2111 - 2118 |
|---|---|
| Main Authors | , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Hagerstown, MD
Lippincott Williams & Wilkins
24.04.2007
|
| Subjects | |
| Online Access | Get full text |
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| Abstract | Background—
Body mass index (BMI) is widely used to assess risk for cardiovascular disease and type 2 diabetes. Cut points for the classification of obesity (BMI >30 kg/m
2
) have been developed and validated among people of European descent. It is unknown whether these cut points are appropriate for non-European populations. We assessed the metabolic risk associated with BMI among South Asians, Chinese, Aboriginals, and Europeans.
Methods and Results—
We randomly sampled 1078 subjects from 4 ethnic groups (289 South Asians, 281 Chinese, 207 Aboriginals, and 301 Europeans) from 4 regions in Canada. Principal components factor analysis was used to derive underlying latent or “hidden” factors associated with 14 clinical and biochemical cardiometabolic markers. Ethnic-specific BMI cut points were derived for 3 cardiometabolic factors. Three primary latent factors emerged that accounted for 56% of the variation in markers of glucose metabolism, lipid metabolism, and blood pressure. For a given BMI, elevated levels of glucose- and lipid-related factors were more likely to be present in South Asians, Chinese, and Aboriginals compared with Europeans, and elevated levels of the blood pressure–related factor were more likely to be present among Chinese compared with Europeans. The cut point to define obesity, as defined by distribution of glucose and lipid factors, is lower by ≈6 kg/m
2
among non-European groups compared with Europeans.
Conclusions—
Revisions may be warranted for BMI cut points to define obesity among South Asians, Chinese, and Aboriginals. Using these revised cut points would greatly increase the estimated burden of obesity-related metabolic disorders among non-European populations. |
|---|---|
| AbstractList | Background—
Body mass index (BMI) is widely used to assess risk for cardiovascular disease and type 2 diabetes. Cut points for the classification of obesity (BMI >30 kg/m
2
) have been developed and validated among people of European descent. It is unknown whether these cut points are appropriate for non-European populations. We assessed the metabolic risk associated with BMI among South Asians, Chinese, Aboriginals, and Europeans.
Methods and Results—
We randomly sampled 1078 subjects from 4 ethnic groups (289 South Asians, 281 Chinese, 207 Aboriginals, and 301 Europeans) from 4 regions in Canada. Principal components factor analysis was used to derive underlying latent or “hidden” factors associated with 14 clinical and biochemical cardiometabolic markers. Ethnic-specific BMI cut points were derived for 3 cardiometabolic factors. Three primary latent factors emerged that accounted for 56% of the variation in markers of glucose metabolism, lipid metabolism, and blood pressure. For a given BMI, elevated levels of glucose- and lipid-related factors were more likely to be present in South Asians, Chinese, and Aboriginals compared with Europeans, and elevated levels of the blood pressure–related factor were more likely to be present among Chinese compared with Europeans. The cut point to define obesity, as defined by distribution of glucose and lipid factors, is lower by ≈6 kg/m
2
among non-European groups compared with Europeans.
Conclusions—
Revisions may be warranted for BMI cut points to define obesity among South Asians, Chinese, and Aboriginals. Using these revised cut points would greatly increase the estimated burden of obesity-related metabolic disorders among non-European populations. BACKGROUND: Body mass index (BMI) is widely used to assess risk for cardiovascular disease and type 2 diabetes. Cut points for the classification of obesity (BMI >30 kg/m super(2)) have been developed and validated among people of European descent. It is unknown whether these cut points are appropriate for non-European populations. We assessed the metabolic risk associated with BMI among South Asians, Chinese, Aboriginals, and Europeans. METHOD:S: and Results- We randomly sampled 1078 subjects from 4 ethnic groups (289 South Asians, 281 Chinese, 207 Aboriginals, and 301 Europeans) from 4 regions in Canada. Principal components factor analysis was used to derive underlying latent or "hidden" factors associated with 14 clinical and biochemical cardiometabolic markers. Ethnic-specific BMI cut points were derived for 3 cardiometabolic factors. Three primary latent factors emerged that accounted for 56% of the variation in markers of glucose metabolism, lipid metabolism, and blood pressure. For a given BMI, elevated levels of glucose- and lipid-related factors were more likely to be present in South Asians, Chinese, and Aboriginals compared with Europeans, and elevated levels of the blood pressure-related factor were more likely to be present among Chinese compared with Europeans. The cut point to define obesity, as defined by distribution of glucose and lipid factors, is lower by approximately 6 kg/m super(2) among non-European groups compared with Europeans. CONCLUSIONS: Revisions may be warranted for BMI cut points to define obesity among South Asians, Chinese, and Aboriginals. Using these revised cut points would greatly increase the estimated burden of obesity-related metabolic disorders among non-European populations. Body mass index (BMI) is widely used to assess risk for cardiovascular disease and type 2 diabetes. Cut points for the classification of obesity (BMI >30 kg/m2) have been developed and validated among people of European descent. It is unknown whether these cut points are appropriate for non-European populations. We assessed the metabolic risk associated with BMI among South Asians, Chinese, Aboriginals, and Europeans. We randomly sampled 1078 subjects from 4 ethnic groups (289 South Asians, 281 Chinese, 207 Aboriginals, and 301 Europeans) from 4 regions in Canada. Principal components factor analysis was used to derive underlying latent or "hidden" factors associated with 14 clinical and biochemical cardiometabolic markers. Ethnic-specific BMI cut points were derived for 3 cardiometabolic factors. Three primary latent factors emerged that accounted for 56% of the variation in markers of glucose metabolism, lipid metabolism, and blood pressure. For a given BMI, elevated levels of glucose- and lipid-related factors were more likely to be present in South Asians, Chinese, and Aboriginals compared with Europeans, and elevated levels of the blood pressure-related factor were more likely to be present among Chinese compared with Europeans. The cut point to define obesity, as defined by distribution of glucose and lipid factors, is lower by approximately 6 kg/m2 among non-European groups compared with Europeans. Revisions may be warranted for BMI cut points to define obesity among South Asians, Chinese, and Aboriginals. Using these revised cut points would greatly increase the estimated burden of obesity-related metabolic disorders among non-European populations. Body mass index (BMI) is widely used to assess risk for cardiovascular disease and type 2 diabetes. Cut points for the classification of obesity (BMI >30 kg/m2) have been developed and validated among people of European descent. It is unknown whether these cut points are appropriate for non-European populations. We assessed the metabolic risk associated with BMI among South Asians, Chinese, Aboriginals, and Europeans.BACKGROUNDBody mass index (BMI) is widely used to assess risk for cardiovascular disease and type 2 diabetes. Cut points for the classification of obesity (BMI >30 kg/m2) have been developed and validated among people of European descent. It is unknown whether these cut points are appropriate for non-European populations. We assessed the metabolic risk associated with BMI among South Asians, Chinese, Aboriginals, and Europeans.We randomly sampled 1078 subjects from 4 ethnic groups (289 South Asians, 281 Chinese, 207 Aboriginals, and 301 Europeans) from 4 regions in Canada. Principal components factor analysis was used to derive underlying latent or "hidden" factors associated with 14 clinical and biochemical cardiometabolic markers. Ethnic-specific BMI cut points were derived for 3 cardiometabolic factors. Three primary latent factors emerged that accounted for 56% of the variation in markers of glucose metabolism, lipid metabolism, and blood pressure. For a given BMI, elevated levels of glucose- and lipid-related factors were more likely to be present in South Asians, Chinese, and Aboriginals compared with Europeans, and elevated levels of the blood pressure-related factor were more likely to be present among Chinese compared with Europeans. The cut point to define obesity, as defined by distribution of glucose and lipid factors, is lower by approximately 6 kg/m2 among non-European groups compared with Europeans.METHODS AND RESULTSWe randomly sampled 1078 subjects from 4 ethnic groups (289 South Asians, 281 Chinese, 207 Aboriginals, and 301 Europeans) from 4 regions in Canada. Principal components factor analysis was used to derive underlying latent or "hidden" factors associated with 14 clinical and biochemical cardiometabolic markers. Ethnic-specific BMI cut points were derived for 3 cardiometabolic factors. Three primary latent factors emerged that accounted for 56% of the variation in markers of glucose metabolism, lipid metabolism, and blood pressure. For a given BMI, elevated levels of glucose- and lipid-related factors were more likely to be present in South Asians, Chinese, and Aboriginals compared with Europeans, and elevated levels of the blood pressure-related factor were more likely to be present among Chinese compared with Europeans. The cut point to define obesity, as defined by distribution of glucose and lipid factors, is lower by approximately 6 kg/m2 among non-European groups compared with Europeans.Revisions may be warranted for BMI cut points to define obesity among South Asians, Chinese, and Aboriginals. Using these revised cut points would greatly increase the estimated burden of obesity-related metabolic disorders among non-European populations.CONCLUSIONSRevisions may be warranted for BMI cut points to define obesity among South Asians, Chinese, and Aboriginals. Using these revised cut points would greatly increase the estimated burden of obesity-related metabolic disorders among non-European populations. |
| Author | Anand, Sonia S. Jacobs, Ruby McQueen, Matthew Shannon, Harry Yusuf, Salim Razak, Fahad Vuksan, Vladimir Davis, Bonnie Teo, Koon K. |
| Author_xml | – sequence: 1 givenname: Fahad surname: Razak fullname: Razak, Fahad organization: From the Population Health Research Institute (F.R., S.S.A., K.K.T., M.M., S.Y.), Department of Medicine (S.S.A., K.K.T., M.M., S.Y.), and Department of Clinical Epidemiology and Biostatistics (S.S.A., K.K.T., M.M., S.Y.), McMaster University, Hamilton, Canada; Faculty of Medicine (F.R.) and Department of Medicine (V.V.), University of Toronto, Toronto, Canada; and Six Nations Health Services (B.D., R.J.), Ohsweken, Ontario, Canada – sequence: 2 givenname: Sonia S. surname: Anand fullname: Anand, Sonia S. organization: From the Population Health Research Institute (F.R., S.S.A., K.K.T., M.M., S.Y.), Department of Medicine (S.S.A., K.K.T., M.M., S.Y.), and Department of Clinical Epidemiology and Biostatistics (S.S.A., K.K.T., M.M., S.Y.), McMaster University, Hamilton, Canada; Faculty of Medicine (F.R.) and Department of Medicine (V.V.), University of Toronto, Toronto, Canada; and Six Nations Health Services (B.D., R.J.), Ohsweken, Ontario, Canada – sequence: 3 givenname: Harry surname: Shannon fullname: Shannon, Harry organization: From the Population Health Research Institute (F.R., S.S.A., K.K.T., M.M., S.Y.), Department of Medicine (S.S.A., K.K.T., M.M., S.Y.), and Department of Clinical Epidemiology and Biostatistics (S.S.A., K.K.T., M.M., S.Y.), McMaster University, Hamilton, Canada; Faculty of Medicine (F.R.) and Department of Medicine (V.V.), University of Toronto, Toronto, Canada; and Six Nations Health Services (B.D., R.J.), Ohsweken, Ontario, Canada – sequence: 4 givenname: Vladimir surname: Vuksan fullname: Vuksan, Vladimir organization: From the Population Health Research Institute (F.R., S.S.A., K.K.T., M.M., S.Y.), Department of Medicine (S.S.A., K.K.T., M.M., S.Y.), and Department of Clinical Epidemiology and Biostatistics (S.S.A., K.K.T., M.M., S.Y.), McMaster University, Hamilton, Canada; Faculty of Medicine (F.R.) and Department of Medicine (V.V.), University of Toronto, Toronto, Canada; and Six Nations Health Services (B.D., R.J.), Ohsweken, Ontario, Canada – sequence: 5 givenname: Bonnie surname: Davis fullname: Davis, Bonnie organization: From the Population Health Research Institute (F.R., S.S.A., K.K.T., M.M., S.Y.), Department of Medicine (S.S.A., K.K.T., M.M., S.Y.), and Department of Clinical Epidemiology and Biostatistics (S.S.A., K.K.T., M.M., S.Y.), McMaster University, Hamilton, Canada; Faculty of Medicine (F.R.) and Department of Medicine (V.V.), University of Toronto, Toronto, Canada; and Six Nations Health Services (B.D., R.J.), Ohsweken, Ontario, Canada – sequence: 6 givenname: Ruby surname: Jacobs fullname: Jacobs, Ruby organization: From the Population Health Research Institute (F.R., S.S.A., K.K.T., M.M., S.Y.), Department of Medicine (S.S.A., K.K.T., M.M., S.Y.), and Department of Clinical Epidemiology and Biostatistics (S.S.A., K.K.T., M.M., S.Y.), McMaster University, Hamilton, Canada; Faculty of Medicine (F.R.) and Department of Medicine (V.V.), University of Toronto, Toronto, Canada; and Six Nations Health Services (B.D., R.J.), Ohsweken, Ontario, Canada – sequence: 7 givenname: Koon K. surname: Teo fullname: Teo, Koon K. organization: From the Population Health Research Institute (F.R., S.S.A., K.K.T., M.M., S.Y.), Department of Medicine (S.S.A., K.K.T., M.M., S.Y.), and Department of Clinical Epidemiology and Biostatistics (S.S.A., K.K.T., M.M., S.Y.), McMaster University, Hamilton, Canada; Faculty of Medicine (F.R.) and Department of Medicine (V.V.), University of Toronto, Toronto, Canada; and Six Nations Health Services (B.D., R.J.), Ohsweken, Ontario, Canada – sequence: 8 givenname: Matthew surname: McQueen fullname: McQueen, Matthew organization: From the Population Health Research Institute (F.R., S.S.A., K.K.T., M.M., S.Y.), Department of Medicine (S.S.A., K.K.T., M.M., S.Y.), and Department of Clinical Epidemiology and Biostatistics (S.S.A., K.K.T., M.M., S.Y.), McMaster University, Hamilton, Canada; Faculty of Medicine (F.R.) and Department of Medicine (V.V.), University of Toronto, Toronto, Canada; and Six Nations Health Services (B.D., R.J.), Ohsweken, Ontario, Canada – sequence: 9 givenname: Salim surname: Yusuf fullname: Yusuf, Salim organization: From the Population Health Research Institute (F.R., S.S.A., K.K.T., M.M., S.Y.), Department of Medicine (S.S.A., K.K.T., M.M., S.Y.), and Department of Clinical Epidemiology and Biostatistics (S.S.A., K.K.T., M.M., S.Y.), McMaster University, Hamilton, Canada; Faculty of Medicine (F.R.) and Department of Medicine (V.V.), University of Toronto, Toronto, Canada; and Six Nations Health Services (B.D., R.J.), Ohsweken, Ontario, Canada |
| BackLink | http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=18716400$$DView record in Pascal Francis https://www.ncbi.nlm.nih.gov/pubmed/17420343$$D View this record in MEDLINE/PubMed |
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Body mass index (BMI) is widely used to assess risk for cardiovascular disease and type 2 diabetes. Cut points for the classification of obesity... Body mass index (BMI) is widely used to assess risk for cardiovascular disease and type 2 diabetes. Cut points for the classification of obesity (BMI >30... BACKGROUND: Body mass index (BMI) is widely used to assess risk for cardiovascular disease and type 2 diabetes. Cut points for the classification of obesity... |
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| Title | Defining Obesity Cut Points in a Multiethnic Population |
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