Obesity Research & Clinical Practice (2013) 7, e308—e314
Comparison of lipid accumulation product with body mass index as an indicator of hypertension risk among Mongolians in China夽 Xin Gao a, Guiyan Wang a,b, Aili Wang a, Tan Xu a, Weijun Tong a, Yonghong Zhang a,∗ a
Department of Epidemiology, School of Public Health, Medical College of Soochow University, Suzhou, China b Department of Prevention and Care, Xiamen Municipal Maternity and Child Care Hospital, Xiamen, China Received 1 November 2011 ; received in revised form 5 February 2012; accepted 8 February 2012
KEYWORDS Lipid accumulation product; Body mass index; Waist circumference; Hypertension; Triglycerides
Summary Objective: To compare associations of lipid accumulation product (LAP) and body mass index (BMI) with risk of hypertension. Methods: Demographic characteristics, blood pressure and body measurements were obtained, blood lipids and fast plasma glucose were examined, BMI and LAP were calculated for 2589 Mongolians. Multiple linear model and covariance analysis was used to analyze the relationship between LAP and blood pressure levels, multivariate logistic analysis was used to analyze the association between BMI and LAP and hypertension. Results: LAP and BMI were all significantly higher in hypertensives than in normotensives in both genders. Multivariate adjusted mean levels of SBP and DBP increased with increased LAP and there was a linear association between LAP and blood pressure. LAP had a stronger association with risk of hypertension compared with BMI, linear trend between LAP and risks of hypertension was better than that between BMI and risks of hypertension in males. Compared to the first quartile, the odds ratios [95% confidence intervals (95% CIs)] of hypertension associated with the second, third and fourth quartiles of LAP were 1.85(1.23,2.79), 2.20(1.47,3.28), 4.21(2.78,6.38) in males; compared to the first quartile, the odds ratios (95% CIs) of hypertension associated with the second, third and fourth quartiles of BMI were 0.93(0.62,1.38), 1.23(0.83,1.84), 2.80(1.86,4.21) in males.
夽 We are deeply appreciative of the participants in the study, and thank Kezuohouqi Banner Center for Disease Prevention and Control, and Naiman Banner Center for Disease Prevention and Control for their support and assistance. This study was funded by National Natural Science Foundation of China (Grant No. 30972531) and the Priority Academic Program Development of Jiangsu Higher Education Institutions. ∗ Corresponding author at: Department of Epidemiology, School of Public Health, Medical College of Soochow University, 199 Renai Road, Industrial Park District, Suzhou 215123, China. Tel.: +86 512 6588 0078. E-mail address: [email protected] (Y. Zhang).
1871-403X/$ — see front matter © 2012 Asian Oceanian Association for the Study of Obesity. Published by Elsevier Ltd. All rights reserved.
doi:10.1016/j.orcp.2012.02.002
Comparison of LAP with BMI
e309 Conclusion: LAP was more closely associated with risk of hypertension than BMI in Mongolian males, this study suggested that LAP might be a preferred anthropometry measurement to predict risk of hypertension in males. Future prospective cohort studies should be conducted to test the causal relationship between LAP and the risk of hypertension in Mongolian population. © 2012 Asian Oceanian Association for the Study of Obesity. Published by Elsevier Ltd. All rights reserved.
Introduction Hypertension is a serious public health problem in the world because of its high prevalence and consequently increased risk of cardiovascular disease [1,2]. Increasing evidences suggested that obesity was significantly related to hypertension [3,4], especially central obesity [5,6]. Waist circumference (WC) was regarded as a simple measurement of central obesity. Furthermore, a prospective study reported a significant relationship between triglycerides (TG) and risk of hypertension [7]. Additionally, evidences have shown that the accumulation of TG was associated with increased WC [8]. Some studies suggested that simultaneous measurements of WC and TG could identify a syndrome of lipid overaccumulation associated with risk of metabolic syndrome and coronary artery disease [9,10]. Kahn firstly put forward a concept of lipid accumulation product (LAP) which combined WC with TG to estimate the lipid overaccumulation among adults [11], and found LAP was much superior to body mass index (BMI) for identifying adults with diabetes [12]. As we know, hypertension is a major risk factor of cardiovascular disease (CVD) and diabetes, but there were few studies on the relationship between LAP and prevalent hypertension, this study was to compare LAP with BMI as an indicator of hypertension risk in Inner Mongolians, China.
Methods Study participants We conducted a cross-sectional survey from 2002 to 2003. In this survey, two townships including 32 villages in Kezuohou Banner (county) and Naiman Banner in Inner Mongolia, China, were served as study fields. The two adjacent townships are 100 km from Tongliao, a prefecture-level city in eastern Inner Mongolia, China. Most of residents in the investigation fields are Mongolian who have lived there for many generations, they have been maintaining traditional manners and customs
of Mongolian ethnicity, their professions are either farmers or herdsmen, and their diet are high in fat and salt. There were a total of 3475 Mongolian people aged 20 or more in the 32 villages, among them, 2589 people who signed informed consent in the field, 886 did not signed informed consent and were not investigated because they were absent or refused to respond at the time of investigation.
Data collection and examination Data on demographic characteristics, lifestyle risk factors, family history of hypertension and medical history were obtained by using a standard questionnaire administered by trained staffs. Current cigarette smoker was defined as having smoked at least 1 cigarette per day for 1 year or more. The amount and type of alcohol consumed during the past year was collected, heavy alcohol consumption was defined as consuming at least 50 g alcohol per day for 1 year or more. Three blood pressure (BP) measurements were performed by 4 trained doctors while the study subjects were in the sitting position, using a standard mercury sphygmomanometer according to a standard protocol, after the subjects had been taking rest for 30 min. The first and fifth Korotkoff sounds were recorded as systolic blood pressure (SBP) and diastolic blood pressure (DBP), respectively, the mean of 3 BP measurements was used in the analysis. Hypertension was defined as SBP ≥ 140 mm Hg and/or DBP ≥ 90 mm Hg and/or use of antihypertensive medication in recent 2 weeks. Body weight and height were measured with subjects wearing light clothing and without shoes by trained staffs. The BMI was calculated as weight in kilograms divided by the square of the height in meters. The WC was measured at the level of 1 cm above the umbilicus. Fasting blood samples were collected in the morning after at least 8 h of fasting for all subjects, and frozen at −80 ◦ C for test. Fasting plasma glucose (FPG) was examined using a glucose meter (Roche, Basel, Switzerland) in the field. Total cholesterol (TC), high density lipoprotein cholesterol (HDL-C), and TG were analyzed enzymatically
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on a Beckman Synchrony CX5 Delta Clinical System (Beckman Coulter, Inc., Fullerton, CA, USA) using commercial reagents, and low density lipoprotein cholesterol (LDL-C) level was calculated by use of the Friedewald equation for the subjects. LAP was calculated by WC and TG concentration, LAP for men = [WC (cm) − 65] × [TG concentration (mmol/L)], LAP for women = [WC (cm) − 58] × [TG concentration (mmol/L)] [11].
Statistical analysis The means and standard deviations (SDs) of continuous variables and prevalence of categorical variables were calculated for characteristics of hypertensive and normotensive individuals. Differences in means were evaluated by t-test and differences in prevalence were evaluated by Chisquare test. For variables of laboratory examination and anthropometric measurements, the medians and interquartile ranges were calculated and p values were computed by using Wilcoxon rank-sum test for the medians comparison between the two groups. Age-adjusted and multivariable-adjusted mean levels and 95% confidence intervals (CIs) of SBP and DBP were calculated according to quartiles of LAP for males and females, respectively. Age, cigarette smoking, alcohol consumption, family history of hypertension, and FPG were adjusted in the multivariate models by using covariance analysis. The presence of a linear relationship between the medians of LAP in each quartile and SBP
Table 1
or DBP was tested in a linear model, in which the medians were treated as a continuous variable. Multivariable-adjusted odds ratios (ORs) were calculated using nonconditional multiple logistic regression models, and age, cigarette smoking, alcohol consumption, family history of hypertension and FPG were adjusted in the multivariate models. The liner association between the LAP, BMI or WC and the ORs of hypertension were tested using the medians of LAP, BMI or WC in each quartile as a continuous variable in the multivariate model by gender. All p values were two-tailed and a significance level of 0.05 was used. Statistical analysis was conducted using SPSS software (Version 16; SPSS, Chicago, IL).
Results Characteristics of the study population are shown in Table 1. A total of 2589 participants aged 20—84 years were finally included in the present analysis. There were 968 hypertensives and 1621 normotensives. Compared with normotensives, the hypertensives were more likely to be older, have alcohol drinking and cigarette smoking and higher levels of TC, TG, LDL-C, FPG, and more likely to have a family history of hypertension. No statistical difference of HDL-C was observed between the two groups. For the anthropometric measurements, WC, BMI and LAP were all significantly higher among hypertensives than normotensives both in males and females.
Characteristics of 2589 study participants according to hypertension status in Inner Mongolia, China.
Variables
Hypertensive
Normotensive
p-Value
Number of participants Age (years) Male (%) Cigarette smoking (%) Alcohol consumption (%) Family history of hypertension (%) Total cholesterol (mmol/L) Triglycerides (mmol/L) High-density lipoprotein cholesterol (mmol/L) Low-density lipoprotein cholesterol (mmol/L) Fasting plasma glucose (mmol/L) Waist circumference for male (cm) Waist circumference for female (cm) Body mass index for male (kg/m2 ) Body mass index for female (kg/m2 ) Lipid accumulation product for male Lipid accumulation product for female
968 52.03(12.05) 485(50.10) 467(48.20) 429(44.30) 239(24.70) 3.80(3.10,4.68) 1.12(0.78,1.78) 1.14(0.94,1.38) 2.33(1.72,3.13) 5.10(4.50,5.70) 83(77,90) 83(76,90) 21.90(19.81,24.80) 23.20(20.80,26.40) 20.66(11.39,43.95) 25.96(15.03,44.13)
1621 43.21(11.46) 579(35.70) 683(42.10) 437(27.00) 99(6.10) 3.48(2.89,4.17) 0.86(0.60,1.25) 1.14(0.96,1.36) 2.09(1.54,2.71) 4.70(4.20,5.30) 78(74,84) 77(72,84) 20.90(19.60,22.70) 21.51(19.57,23.90) 11.93(6.60,22.88) 15.30(8.47,26.06)
Comparison of lipid accumulation product with body mass index as an indicator of hypertension risk among Mongolians in China夽 Xin Gao a, Guiyan Wang a,b, Aili Wang a, Tan Xu a, Weijun Tong a, Yonghong Zhang a,∗ a
Department of Epidemiology, School of Public Health, Medical College of Soochow University, Suzhou, China b Department of Prevention and Care, Xiamen Municipal Maternity and Child Care Hospital, Xiamen, China Received 1 November 2011 ; received in revised form 5 February 2012; accepted 8 February 2012
KEYWORDS Lipid accumulation product; Body mass index; Waist circumference; Hypertension; Triglycerides
Summary Objective: To compare associations of lipid accumulation product (LAP) and body mass index (BMI) with risk of hypertension. Methods: Demographic characteristics, blood pressure and body measurements were obtained, blood lipids and fast plasma glucose were examined, BMI and LAP were calculated for 2589 Mongolians. Multiple linear model and covariance analysis was used to analyze the relationship between LAP and blood pressure levels, multivariate logistic analysis was used to analyze the association between BMI and LAP and hypertension. Results: LAP and BMI were all significantly higher in hypertensives than in normotensives in both genders. Multivariate adjusted mean levels of SBP and DBP increased with increased LAP and there was a linear association between LAP and blood pressure. LAP had a stronger association with risk of hypertension compared with BMI, linear trend between LAP and risks of hypertension was better than that between BMI and risks of hypertension in males. Compared to the first quartile, the odds ratios [95% confidence intervals (95% CIs)] of hypertension associated with the second, third and fourth quartiles of LAP were 1.85(1.23,2.79), 2.20(1.47,3.28), 4.21(2.78,6.38) in males; compared to the first quartile, the odds ratios (95% CIs) of hypertension associated with the second, third and fourth quartiles of BMI were 0.93(0.62,1.38), 1.23(0.83,1.84), 2.80(1.86,4.21) in males.
夽 We are deeply appreciative of the participants in the study, and thank Kezuohouqi Banner Center for Disease Prevention and Control, and Naiman Banner Center for Disease Prevention and Control for their support and assistance. This study was funded by National Natural Science Foundation of China (Grant No. 30972531) and the Priority Academic Program Development of Jiangsu Higher Education Institutions. ∗ Corresponding author at: Department of Epidemiology, School of Public Health, Medical College of Soochow University, 199 Renai Road, Industrial Park District, Suzhou 215123, China. Tel.: +86 512 6588 0078. E-mail address: [email protected] (Y. Zhang).
1871-403X/$ — see front matter © 2012 Asian Oceanian Association for the Study of Obesity. Published by Elsevier Ltd. All rights reserved.
doi:10.1016/j.orcp.2012.02.002
Comparison of LAP with BMI
e309 Conclusion: LAP was more closely associated with risk of hypertension than BMI in Mongolian males, this study suggested that LAP might be a preferred anthropometry measurement to predict risk of hypertension in males. Future prospective cohort studies should be conducted to test the causal relationship between LAP and the risk of hypertension in Mongolian population. © 2012 Asian Oceanian Association for the Study of Obesity. Published by Elsevier Ltd. All rights reserved.
Introduction Hypertension is a serious public health problem in the world because of its high prevalence and consequently increased risk of cardiovascular disease [1,2]. Increasing evidences suggested that obesity was significantly related to hypertension [3,4], especially central obesity [5,6]. Waist circumference (WC) was regarded as a simple measurement of central obesity. Furthermore, a prospective study reported a significant relationship between triglycerides (TG) and risk of hypertension [7]. Additionally, evidences have shown that the accumulation of TG was associated with increased WC [8]. Some studies suggested that simultaneous measurements of WC and TG could identify a syndrome of lipid overaccumulation associated with risk of metabolic syndrome and coronary artery disease [9,10]. Kahn firstly put forward a concept of lipid accumulation product (LAP) which combined WC with TG to estimate the lipid overaccumulation among adults [11], and found LAP was much superior to body mass index (BMI) for identifying adults with diabetes [12]. As we know, hypertension is a major risk factor of cardiovascular disease (CVD) and diabetes, but there were few studies on the relationship between LAP and prevalent hypertension, this study was to compare LAP with BMI as an indicator of hypertension risk in Inner Mongolians, China.
Methods Study participants We conducted a cross-sectional survey from 2002 to 2003. In this survey, two townships including 32 villages in Kezuohou Banner (county) and Naiman Banner in Inner Mongolia, China, were served as study fields. The two adjacent townships are 100 km from Tongliao, a prefecture-level city in eastern Inner Mongolia, China. Most of residents in the investigation fields are Mongolian who have lived there for many generations, they have been maintaining traditional manners and customs
of Mongolian ethnicity, their professions are either farmers or herdsmen, and their diet are high in fat and salt. There were a total of 3475 Mongolian people aged 20 or more in the 32 villages, among them, 2589 people who signed informed consent in the field, 886 did not signed informed consent and were not investigated because they were absent or refused to respond at the time of investigation.
Data collection and examination Data on demographic characteristics, lifestyle risk factors, family history of hypertension and medical history were obtained by using a standard questionnaire administered by trained staffs. Current cigarette smoker was defined as having smoked at least 1 cigarette per day for 1 year or more. The amount and type of alcohol consumed during the past year was collected, heavy alcohol consumption was defined as consuming at least 50 g alcohol per day for 1 year or more. Three blood pressure (BP) measurements were performed by 4 trained doctors while the study subjects were in the sitting position, using a standard mercury sphygmomanometer according to a standard protocol, after the subjects had been taking rest for 30 min. The first and fifth Korotkoff sounds were recorded as systolic blood pressure (SBP) and diastolic blood pressure (DBP), respectively, the mean of 3 BP measurements was used in the analysis. Hypertension was defined as SBP ≥ 140 mm Hg and/or DBP ≥ 90 mm Hg and/or use of antihypertensive medication in recent 2 weeks. Body weight and height were measured with subjects wearing light clothing and without shoes by trained staffs. The BMI was calculated as weight in kilograms divided by the square of the height in meters. The WC was measured at the level of 1 cm above the umbilicus. Fasting blood samples were collected in the morning after at least 8 h of fasting for all subjects, and frozen at −80 ◦ C for test. Fasting plasma glucose (FPG) was examined using a glucose meter (Roche, Basel, Switzerland) in the field. Total cholesterol (TC), high density lipoprotein cholesterol (HDL-C), and TG were analyzed enzymatically
e310
X. Gao et al.
on a Beckman Synchrony CX5 Delta Clinical System (Beckman Coulter, Inc., Fullerton, CA, USA) using commercial reagents, and low density lipoprotein cholesterol (LDL-C) level was calculated by use of the Friedewald equation for the subjects. LAP was calculated by WC and TG concentration, LAP for men = [WC (cm) − 65] × [TG concentration (mmol/L)], LAP for women = [WC (cm) − 58] × [TG concentration (mmol/L)] [11].
Statistical analysis The means and standard deviations (SDs) of continuous variables and prevalence of categorical variables were calculated for characteristics of hypertensive and normotensive individuals. Differences in means were evaluated by t-test and differences in prevalence were evaluated by Chisquare test. For variables of laboratory examination and anthropometric measurements, the medians and interquartile ranges were calculated and p values were computed by using Wilcoxon rank-sum test for the medians comparison between the two groups. Age-adjusted and multivariable-adjusted mean levels and 95% confidence intervals (CIs) of SBP and DBP were calculated according to quartiles of LAP for males and females, respectively. Age, cigarette smoking, alcohol consumption, family history of hypertension, and FPG were adjusted in the multivariate models by using covariance analysis. The presence of a linear relationship between the medians of LAP in each quartile and SBP
Table 1
or DBP was tested in a linear model, in which the medians were treated as a continuous variable. Multivariable-adjusted odds ratios (ORs) were calculated using nonconditional multiple logistic regression models, and age, cigarette smoking, alcohol consumption, family history of hypertension and FPG were adjusted in the multivariate models. The liner association between the LAP, BMI or WC and the ORs of hypertension were tested using the medians of LAP, BMI or WC in each quartile as a continuous variable in the multivariate model by gender. All p values were two-tailed and a significance level of 0.05 was used. Statistical analysis was conducted using SPSS software (Version 16; SPSS, Chicago, IL).
Results Characteristics of the study population are shown in Table 1. A total of 2589 participants aged 20—84 years were finally included in the present analysis. There were 968 hypertensives and 1621 normotensives. Compared with normotensives, the hypertensives were more likely to be older, have alcohol drinking and cigarette smoking and higher levels of TC, TG, LDL-C, FPG, and more likely to have a family history of hypertension. No statistical difference of HDL-C was observed between the two groups. For the anthropometric measurements, WC, BMI and LAP were all significantly higher among hypertensives than normotensives both in males and females.
Characteristics of 2589 study participants according to hypertension status in Inner Mongolia, China.
Variables
Hypertensive
Normotensive
p-Value
Number of participants Age (years) Male (%) Cigarette smoking (%) Alcohol consumption (%) Family history of hypertension (%) Total cholesterol (mmol/L) Triglycerides (mmol/L) High-density lipoprotein cholesterol (mmol/L) Low-density lipoprotein cholesterol (mmol/L) Fasting plasma glucose (mmol/L) Waist circumference for male (cm) Waist circumference for female (cm) Body mass index for male (kg/m2 ) Body mass index for female (kg/m2 ) Lipid accumulation product for male Lipid accumulation product for female
968 52.03(12.05) 485(50.10) 467(48.20) 429(44.30) 239(24.70) 3.80(3.10,4.68) 1.12(0.78,1.78) 1.14(0.94,1.38) 2.33(1.72,3.13) 5.10(4.50,5.70) 83(77,90) 83(76,90) 21.90(19.81,24.80) 23.20(20.80,26.40) 20.66(11.39,43.95) 25.96(15.03,44.13)
1621 43.21(11.46) 579(35.70) 683(42.10) 437(27.00) 99(6.10) 3.48(2.89,4.17) 0.86(0.60,1.25) 1.14(0.96,1.36) 2.09(1.54,2.71) 4.70(4.20,5.30) 78(74,84) 77(72,84) 20.90(19.60,22.70) 21.51(19.57,23.90) 11.93(6.60,22.88) 15.30(8.47,26.06)
