# Association and Interaction Analysis of Body Mass Index and Triglycerides Level with Blood Pressure in Elderly Individuals in China

Authors: Lin Zhang; Jin-long Li; Li-li Zhang; Lei-lei Guo; Hong Li; Dan Li
Journal: BioMed Research International
 (2018)

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## Abstract

Objectives. To assess the extent of interaction between body mass index (BMI) and triglyceride (TG) level and its effects on blood pressure (BP) in elderly individuals in China.Design. Cross-sectional study.Setting. Data were taken from a cross-sectional study called the China Health and Retirement Longitudinal Study.Participants. The analytic sample included 3629 subjects aged 45 to 96 years.Main Outcome Measurements. Data were obtained from the China Health and Retirement Longitudinal Study, which is a cross-sectional study. Age-adjusted partial Pearson’s correlation test was used to compare various characteristics and BP. Adjusted associations were first used as linear regression models, as appropriate. Then, general linear models adjusted for related potential confounders were used to examine the synergistic effects of BMI and TG level on BP. Finally, a binary logistic regression model adjusted for confounding factors was used to examine the association between BMI or TG level and hypertension.Results. Age-adjusted partial Pearson’s correlation coefficient showed that the TG level was positively correlated with both systolic blood pressure (SBP) and diastolic blood pressure (DBP) in both men and women with BMI < 24.0 kg/m2; however, TG level was positively correlated with DBP in women with BMI ≥ 24.0 kg/m2 but not with DBP in men with BMI ≥ 24.0 kg/m2. Multiple linear regression analysis showed that BMI level was significantly and positively associated with both SBP and DBP in men and women with BMI < 24.0 kg/m2, and TG level was significantly and positively associated with SBP in women with BMI < 24.0 kg/m2, independent of other confounding factors. A general linear model analysis with adjustment for confounding factors (age, educational level, marital status, current residence, smoking, eating habits, taking activities, antidiabetic medication, antihypertensive therapy, fasting plasma glucose [FPG], low-density lipoprotein cholesterol [LDL-C], estimated glomerular filtration rate [eGFR], and serum uric acid [SUA]) showed no interaction between BMI and TG level and SBP (men, β = 0.572,P = 0.845; women, β = 0.122,P= 0.923) and DBP (men, β = -0.373,P= 0.810; women, β = 0.272,P= 0.828). A binary logistic regression model analysis with adjustment for confounding factors (age, educational level, marital status, current residence, smoking, drinking, eating habits, taking activities, major accidental injury, physical activity, history of cardiovascular disease, history of liver disease, antilipidemic medication, antidiabetic medication, antihypertensive therapy, FPG, LDL-C, high-density lipoprotein cholesterol [HDL-C], eGFR, and SUA) showed that overweight and obese men and women were more likely to have hypertension (men: odds ratio [OR] = 1.781, 95% confidence interval [CI] = 1.393–2.277; women: OR = 1.653, 95% CI = 1.330–2.055) and women with high TG were more likely to have hypertension (OR = 1.558, 95% CI = 1.219–1.992).Conclusion. An interactive effect of BMI and TG level on BP was not observed in either men or women; however, independent effects of BMI on BP were observed in both men and women, and an association between TG level and hypertension was observed in women.


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## Body

## 1. Introduction

The prevalence of hypertension has dramatically increased in the past few years in China[1, 2]; furthermore, the rate of hypertension is disproportionately high among elderly individuals in this country[3–5]. Hypertension is defined as a diastolic blood pressure (DBP) of ≥ 90 mmHg and/or systolic blood pressure (SBP) of ≥ 140 mmHg based on the evidence of modestly increasing risk[6–8] and incidence of cardiovascular disease (CVD)[9–11].Hypertension is a complex disease, and patients with the condition suffer from an economic, psychosocial, and physical burden. Recently, hypertension has become an important global public health challenge [12]. Therefore, an effective strategy to prevent hypertension and determine its associated risks should be carefully implemented. Numerous studies[13–20] have been conducted to determine the risk factors for hypertension, such as aging, overweight, central obesity, lifestyle, family history of hypertension, history of diabetes and dyslipidemia, lack of physical activity, smoking, alcohol consumption, low-density lipoprotein cholesterol (LDL-C) level, triglycerides (TG) level, and high-density lipoprotein cholesterol (HDL-C) level. Lipid abnormalities have been shown to increase the risk factors for hypertension [21]. For example, Teng [22] found an additive effect of TG on DBP. Brennan [23] conducted a study to investigate the effects of body weight on TG and SBP in individuals aged 20 to 49 years and found that, in men, significant correlations with BMI were found for all variables, while in women younger than 40, only the correlation with BP was significant. TG level has been associated with BP since TG level itself can lead to endothelial dysfunction [24, 25], arterial stiffness [26], and loss of vasomotor reactivity [27]. However, it is also important to understand the interrelationships among various risk factors for hypertension. In particular, the association between TG level and risk of hypertension and the effects of obesity on this association are of considerable interest, and an interactive effect between body mass index (BMI) and TG level on BP may also be considered.No consistent recognition of the association and interaction analysis between BMI and TG level and BP in elderly individuals exists. Thus, the present study particularly aimed to determine the prevalence of normotension and hypertension and their association with BMI, TG level, and other confounding factors based on sex, using cross-sectional data from community-dwelling individuals aged ≥ 60 years in China.


## 2. Methods

### 2.1. Study Design and Setting

Data for this cross-sectional study were taken from the China Health and Retirement Longitudinal Study (CHARLS), a biennial and nationally representative longitudinal survey conducted by the China Centre for Economic Research at Peking University [28]. The baseline survey had a four-stage, stratified, cluster probability sampling design.In the first stage, all counties in China were stratified by region, rural/urban status, and gross domestic product per capita. A random sample of 150 counties was selected to represent the socioeconomic and geographic pattern of all the counties. In the second stage, three primary sampling units (PSUs) were selected in each county with the probability of inclusion of each county in the sample proportional to their population size. In the third stage, all households in each selected PSU were mapped, and a random sample of 24 households was selected among all the households with residents aged ≥ 45 years within each PSU. Finally, for each selected household, one resident aged ≥ 45 years was randomly selected as a participant in the survey. From the 2011 CHARLS Wave1, we included a total of 3629 individuals in our study.


### 2.2. Information on Demographic Characteristics and Self-Reported Risk Factors

Data including age, education, marital status, current residence, smoking, drinking, eating habits, taking activities, accidental injury, physical exercise, history of cardiovascular disease, history of liver disease, antilipidemic medication, antidiabetic medication, and antihypertensive therapy were obtained using a self-reported questionnaire. (1) Median age was 68 years, and age was categorized as < 68 years and ≥ 68 years. (2) Educational levels were classified into illiterate, less than elementary school, high school, and above vocational school. (3) Marital status was classified into married and single. (4) Current residence was classified into rural and urban. (5) Smoking status was never smoked, ex-smoker, and current smoker. (6) Alcohol consumption was classified into more than non-drinker, less than once a month, and once a month. (7) Eating habits were categorized into 2 meals per day or fewer, 3 meals per day, and 4 meals per day or more. (8) Activity status was dichotomized into at least once a month versus never. (9) Major accidental injury information was obtained by asking the participant whether he/she suffered from any type of major accidental injury and received medical treatment; the answer was “yes” or “no.” (10) Regular physical exercise was defined as exercising at least 3 days per week and more than 30 minutes per day, including moderate to vigorous physical activity and walking. (11) History of CVD, history of liver disease, antilipidemic medication, antidiabetic medication, and antihypertensive therapy were defined as a history of receiving treatment for the respective diseases; the answer was “yes” or “no.”


### 2.3. Glucose, LDL, HDL, Triglycerides, eGFR, BP, and Uric Acid Measurement

Venous blood samples were obtained at the Centers for Disease Control and Prevention (CDC) station, then immediately stored and frozen at −20°C, and transported within 2 weeks to the Chinese CDC in Beijing, where they were placed in a deep freezer and stored at −80°C until the relevant assay was performed at the China Medical University laboratory. (1) Fasting plasma glucose (FPG), LDL, HDL, and TG levels were analyzed at the Youanmen Center for Clinical Laboratory at Capital Medical University using the enzymatic colorimetric tests, and serum uric acid (SUA) levels were analyzed using the urinalysis (UA) plus method. We classified TG levels into 2 categories: ≥ 150 mg/dL and < 150 mg/dL, a categorization widely used in previous studies [29, 30]. (2) BP was measured 3 times at intervals of 45 seconds with a sphygmomanometer. The value of BP was determined based on the mean of the 3 measurements. Normotension was defined as absence of antihypertensive therapy with an SBP of < 140 mmHg and DBP of < 90 mmHg, while hypertension was defined as an SBP of ≥140 mmHg and/or DBP of ≥ 90 mmHg; this categorization has been widely used in previous studies. (3) Estimated glomerular filtration rate (eGFR) was calculated using the CKD-EPI creatinine-cystatin equations [31]: (1) in men, serum creatinine (Scr) ≤ 0.9, serum cystatin C(Scys) ≤ 0.8, eGFR = 135∗ (Scr/0.9)−0.207∗ (Scys/0.8)−0.375∗0.995age; Scr≤ 0.9, Scys> 0.8, eGFR = 135∗ (Scr/0.9)−0.207∗ (Scys/0.8)−0.711∗0.995age; Scr> 0.9, Scys≤ 0.8, eGFR=135∗ (Scr/0.9)−0.601∗ (Scys/0.8)−0.375∗0.995age; Scr> 0.9, Scys> 0.8, eGFR = 135∗ (Scr/0.9)−0.601∗ (Scys/0.8)−0.711∗0.995age; (2) in women, Scr ≤ 0.7, Scys ≤ 0.8, eGFR = 130∗(Scr/0.7)−0.248∗(Scys/0.8)−0.375∗0.995age; Scr≤ 0.7, Scys> 0.8, and eGFR = 130∗(Scr/0.7)−0.248∗(Scys/0.8)−0.711∗0.995age; Scr> 0.7, Scys≤ 0.8, eGFR = 130∗ (Scr/0.7)−0.601∗(Scys/0.8)−0.375∗0.995age; Scr> 0.7, Scys> 0.8, and eGFR = 130∗ (Scr/0.7)−0.601∗ (Scys/0.8)−0.711∗0.995age.


### 2.4. Measurement of Body Mass Index

Weight and height were measured using a weight and height measurement instrument. BMI was calculated based on the measured weight and height of the participants, who were classified into four categories: underweight (BMI, ≤ 18.5 kg/m2), normal weight (18.5–24 kg/m2), overweight (24–28 kg/m2), and obese (> 28 kg/m2)[32].


### 2.5. Statistical Analysis

Our data are represented as mean ± standard deviation (SD; continuous data) and number and percentage (categorical data). Differences between normotension and hypertension, or between normal weight individuals and those with underweight or adiposity, were evaluated using the t-test or chi-square test, followed by Bonferroni adjustment. Correlations between various characteristics and BP were compared using the age-adjusted partial Pearson’s correlation test. The adjusted associations between various characteristics and BP were first compared using linear regression models, as appropriate. Then, general linear models adjusted for related potential confounders (age, educational level, marital status, current residence, smoking, drinking, eating habits, taking activities, major accidental injury, physical activity, history of CVD, history of liver disease, antilipidemic medication, antidiabetic medication, antihypertensive therapy, FPG, LDL-C, HDL-C, eGFR, and SUA) [33] were constructed to examine the synergistic effect of BMI and TG level on BP. A binary logistic regression model adjusted for related potential confounders was used to examine the association between BMI or TG and hypertension. AP-value of 0.05 was considered significant. All data were analyzed using the SPSS version 17.0 (IBM Corp., Armonk, NY, USA).


### 2.6. Patient and Public Involvement Statement

Consent from the respondents was obtained by the CHARLS. The data information obtained from the study was public, and patients were not involved.


## 2.1. Study Design and Setting

Data for this cross-sectional study were taken from the China Health and Retirement Longitudinal Study (CHARLS), a biennial and nationally representative longitudinal survey conducted by the China Centre for Economic Research at Peking University [28]. The baseline survey had a four-stage, stratified, cluster probability sampling design.In the first stage, all counties in China were stratified by region, rural/urban status, and gross domestic product per capita. A random sample of 150 counties was selected to represent the socioeconomic and geographic pattern of all the counties. In the second stage, three primary sampling units (PSUs) were selected in each county with the probability of inclusion of each county in the sample proportional to their population size. In the third stage, all households in each selected PSU were mapped, and a random sample of 24 households was selected among all the households with residents aged ≥ 45 years within each PSU. Finally, for each selected household, one resident aged ≥ 45 years was randomly selected as a participant in the survey. From the 2011 CHARLS Wave1, we included a total of 3629 individuals in our study.


## 2.2. Information on Demographic Characteristics and Self-Reported Risk Factors

Data including age, education, marital status, current residence, smoking, drinking, eating habits, taking activities, accidental injury, physical exercise, history of cardiovascular disease, history of liver disease, antilipidemic medication, antidiabetic medication, and antihypertensive therapy were obtained using a self-reported questionnaire. (1) Median age was 68 years, and age was categorized as < 68 years and ≥ 68 years. (2) Educational levels were classified into illiterate, less than elementary school, high school, and above vocational school. (3) Marital status was classified into married and single. (4) Current residence was classified into rural and urban. (5) Smoking status was never smoked, ex-smoker, and current smoker. (6) Alcohol consumption was classified into more than non-drinker, less than once a month, and once a month. (7) Eating habits were categorized into 2 meals per day or fewer, 3 meals per day, and 4 meals per day or more. (8) Activity status was dichotomized into at least once a month versus never. (9) Major accidental injury information was obtained by asking the participant whether he/she suffered from any type of major accidental injury and received medical treatment; the answer was “yes” or “no.” (10) Regular physical exercise was defined as exercising at least 3 days per week and more than 30 minutes per day, including moderate to vigorous physical activity and walking. (11) History of CVD, history of liver disease, antilipidemic medication, antidiabetic medication, and antihypertensive therapy were defined as a history of receiving treatment for the respective diseases; the answer was “yes” or “no.”


## 2.3. Glucose, LDL, HDL, Triglycerides, eGFR, BP, and Uric Acid Measurement

Venous blood samples were obtained at the Centers for Disease Control and Prevention (CDC) station, then immediately stored and frozen at −20°C, and transported within 2 weeks to the Chinese CDC in Beijing, where they were placed in a deep freezer and stored at −80°C until the relevant assay was performed at the China Medical University laboratory. (1) Fasting plasma glucose (FPG), LDL, HDL, and TG levels were analyzed at the Youanmen Center for Clinical Laboratory at Capital Medical University using the enzymatic colorimetric tests, and serum uric acid (SUA) levels were analyzed using the urinalysis (UA) plus method. We classified TG levels into 2 categories: ≥ 150 mg/dL and < 150 mg/dL, a categorization widely used in previous studies [29, 30]. (2) BP was measured 3 times at intervals of 45 seconds with a sphygmomanometer. The value of BP was determined based on the mean of the 3 measurements. Normotension was defined as absence of antihypertensive therapy with an SBP of < 140 mmHg and DBP of < 90 mmHg, while hypertension was defined as an SBP of ≥140 mmHg and/or DBP of ≥ 90 mmHg; this categorization has been widely used in previous studies. (3) Estimated glomerular filtration rate (eGFR) was calculated using the CKD-EPI creatinine-cystatin equations [31]: (1) in men, serum creatinine (Scr) ≤ 0.9, serum cystatin C(Scys) ≤ 0.8, eGFR = 135∗ (Scr/0.9)−0.207∗ (Scys/0.8)−0.375∗0.995age; Scr≤ 0.9, Scys> 0.8, eGFR = 135∗ (Scr/0.9)−0.207∗ (Scys/0.8)−0.711∗0.995age; Scr> 0.9, Scys≤ 0.8, eGFR=135∗ (Scr/0.9)−0.601∗ (Scys/0.8)−0.375∗0.995age; Scr> 0.9, Scys> 0.8, eGFR = 135∗ (Scr/0.9)−0.601∗ (Scys/0.8)−0.711∗0.995age; (2) in women, Scr ≤ 0.7, Scys ≤ 0.8, eGFR = 130∗(Scr/0.7)−0.248∗(Scys/0.8)−0.375∗0.995age; Scr≤ 0.7, Scys> 0.8, and eGFR = 130∗(Scr/0.7)−0.248∗(Scys/0.8)−0.711∗0.995age; Scr> 0.7, Scys≤ 0.8, eGFR = 130∗ (Scr/0.7)−0.601∗(Scys/0.8)−0.375∗0.995age; Scr> 0.7, Scys> 0.8, and eGFR = 130∗ (Scr/0.7)−0.601∗ (Scys/0.8)−0.711∗0.995age.


## 2.4. Measurement of Body Mass Index

Weight and height were measured using a weight and height measurement instrument. BMI was calculated based on the measured weight and height of the participants, who were classified into four categories: underweight (BMI, ≤ 18.5 kg/m2), normal weight (18.5–24 kg/m2), overweight (24–28 kg/m2), and obese (> 28 kg/m2)[32].


## 2.5. Statistical Analysis

Our data are represented as mean ± standard deviation (SD; continuous data) and number and percentage (categorical data). Differences between normotension and hypertension, or between normal weight individuals and those with underweight or adiposity, were evaluated using the t-test or chi-square test, followed by Bonferroni adjustment. Correlations between various characteristics and BP were compared using the age-adjusted partial Pearson’s correlation test. The adjusted associations between various characteristics and BP were first compared using linear regression models, as appropriate. Then, general linear models adjusted for related potential confounders (age, educational level, marital status, current residence, smoking, drinking, eating habits, taking activities, major accidental injury, physical activity, history of CVD, history of liver disease, antilipidemic medication, antidiabetic medication, antihypertensive therapy, FPG, LDL-C, HDL-C, eGFR, and SUA) [33] were constructed to examine the synergistic effect of BMI and TG level on BP. A binary logistic regression model adjusted for related potential confounders was used to examine the association between BMI or TG and hypertension. AP-value of 0.05 was considered significant. All data were analyzed using the SPSS version 17.0 (IBM Corp., Armonk, NY, USA).


## 2.6. Patient and Public Involvement Statement

Consent from the respondents was obtained by the CHARLS. The data information obtained from the study was public, and patients were not involved.


## 3. Results

The 2011 CHARLS Wave1 sample (N=3629) consists of 49.88% men (Age: Mean = 68.86 years; SD = 6.30; range, 60–93 years) and 50.12% women (Age: Mean = 68.55 years; SD = 6.82; range, 60–96 years). Among men, the mean SBP and DBP were 128.93 mmHg and 72.28 mmHg, respectively, and among women, the mean SBP and DBP were 133.66 mmHg and 73.00 mmHg, respectively. In men, 10.94%, 60.66%, 21.60%, and 6.80% were underweight, normal weight, overweight, and obese, respectively, whereas in women 10.34%, 49.04%, 29.08%, and 11.54% were underweight, normal weight, overweight, and obese, respectively. The mean and SD of TG level were 112.79 ± 83.55 mg/dL in men and 140.14 ± 94.12 mg/dL in women. Tables1 and 2 present the baseline characteristics of the sample for all variables, and most variables were based on our previous research [32].Table 1
Various characteristics of participants categorized by BMI in male (N=1810).
Variables BMI≤18.5(n=198) BMI18.5-24 (n=1098) BMI 24-28 (n=391) BMI>28 (n=123) t/χ2 P Age(years) 71.49±6.31 69.17±6.4 67.35±5.71 66.7±5.22 25.817 <0.001 Education Illiterate 52(26.26) 256(23.32) 44(11.25) 20(16.26) 42.976 <0.001 Less than elementary school 130(65.66) 773(70.40) 306(78.26) 90(73.17) High school 6(3.03) 17(1.55) 5(1.28) 4(3.25) Above vocational school 10(5.05) 52(4.74) 36(9.21) 9(7.32) Marital status Single 29(14.65) 179(16.30) 30(7.67) 13(10.57) 19.2333 <0.001 Married 169(85.35) 919(83.70) 361(92.33) 110(89.43) Current residence Rural 152(76.77) 791(72.04) 213(54.48) 65(52.85) 60.303 <0.001 Urban 46(23.23) 307(27.96) 178(45.52) 58(47.15) Smoke NO 118(59.60) 632(57.56) 163(41.69) 48(39.02) 43.161 <0.001 Former smoke 36(18.18) 199(18.12) 105(26.85) 33(26.83) Current smoke 44(22.22) 267(24.32) 123(31.46) 42(34.15) Drinking NO 115(58.08) 543(49.45) 202(51.66) 65(52.85) 197.72 <0.001 Less than once a month 13(6.57) 94(8.56) 33(8.44) 14(11.38) More than once a month 70(35.35) 461(41.99) 156(39.9) 44(35.77) Eating meals ≤2 meals per day 31(15.66) 174(15.85) 43(11.00) 10(8.13) 15.580 0.016 3 meals per day 162(81.82) 905(82.42) 345(88.24) 113(91.87) ≥4 meals per day 5(2.53) 19(1.73) 3(0.77) 0(0.00) Taking activities No 119(60.10) 593(54.01) 175(44.76) 62(50.41) 15.198 0.002 Yes 79(39.90) 505(45.99) 216(55.24) 61(49.59) Ever been in major accidental injury No 173(87.37) 976(88.89) 349(89.26) 111(90.24) 0.743 0.863 Yes 25(12.63) 122(11.11) 42(10.74) 12(9.76) Having regular physical exercises No physical exercise 122(61.62) 701(63.84) 247(63.17) 69(56.1) 5.204 0.518 Less than regular physical exercises 39(19.70) 183(16.67) 60(15.35) 23(18.70) Regular physical exercises 37(18.69) 214(19.49) 84(21.48) 31(25.20) History of CVD No 178(89.90) 965(87.89) 323(82.61) 87(70.73) 33.007 <0.001 Yes 20(10.10) 133(12.11) 68(17.39) 36(29.27) History of liver diseases No 194(97.98) 1055(96.08) 375(95.91) 114(92.68) 5.576 0.134 Yes 4(2.02) 43(3.92) 16(4.09) 9(7.32) Antilipidemic medication No 194(97.98) 1063(96.81) 366(93.61) 104(84.55) 43.969 <0.001 Yes 4(2.02) 35(3.19) 25(6.39) 19(15.45) Anti-diabetic medication No 195(98.48) 1069(97.36) 365(93.35) 104(84.55) 54.001 <0.001 Yes 3(1.52) 29(2.64) 26(6.65) 19(15.45) Anti-hypertensive therapy No 186(93.94) 1036(94.35) 359(91.82) 114(92.68) 3.345 0.341 Yes 12(6.06) 62(5.65) 32(8.18) 9(7.32) Fasting plasma glucose(mg/dl) 105.00±28.94 109.16±36.00 118.37±41.50 119.64±41.26 9.994 <0.001 LDL Cholesterol (mg/dl) 105.37±32.12 110.54±32.35 118.02±35.30 119.42±34.05 9.701 <0.001 HDL Cholesterol (mg/dl) 60.04±16.14 53.83±15.90 44.00±13.320 42.9±12.28 74.457 <0.001 eGFR(ml/min/1.73m2) 71.56±16.22 74.92±16.53 75.57±16.32 75.13±16.23 2.868 0.035 Serum uric acid(mg/dl) 4.79±1.29 4.98±1.31 5.37±1.34 5.27±1.29 12.990 <0.001 Systolic blood pressure(mmHg) 128.93±21.56 132.59±24.29 139.25±25.58 143.94±19.85 23.845 <0.001 Diastolic blood pressure(mmHg) 72.28±12.34 74.59±12.78 78.65±12.37 81.69±12.29 17.079 <0.001 Body mass index(kg/m2) 17.24±0.90 21.25±1.53 25.65±1.12 30.71±4.3.00 2126.849 <0.001 Triglycerides (mg/dl) 84.34±34.71 101.52±59.33 146.98±129.67 150.5±92.37 47.962 <0.001Table 2
Various characteristics of participants categorized by BMI in female (N=1819).
Variables BMI≤18.5(n=188) BMI18.5-24 (n=892) BMI 24-28 (n=529) BMI>28 (n=210) t/χ2 P Age (years) 71.41±7.07 68.77±6.99 67.64±6.32 67.34±6.25 17.169 <0.001 Education Illiterate 133(70.74) 530(59.42) 269(50.85) 111(52.86) 35.807 <0.001 Less than elementary school 55(29.26) 342(38.34) 236(44.61) 97(46.19) High school 0(0.00) 6(0.67) 9(1.70) 0(0.00) Above vocational school 0(0.00) 14(1.57) 15(2.84) 2(0.95) Marital status Single 72(38.30) 291(32.62) 131(24.76) 49(23.33) 20.478 <0.001 Married 116(61.70) 601(67.38) 398(75.24) 161(76.67) Current residence Rural 150(79.79) 588(65.92) 309(58.41) 107(50.95) 43.911 <0.001 Urban 38(20.21) 304(34.08) 220(41.59) 103(49.05) Smoke NO 151(80.32) 783(87.78) 479(90.55) 190(90.48) 20.377 <0.001 Former smoke 6(3.19) 30(3.36) 15(2.84) 8(3.81) Current smoke 31(16.49) 79(8.86) 35(6.62) 12(5.71) Drinking NO 164(87.23) 781(87.56) 462(87.33) 194(92.38) 7.632 0.266 Less than once a month 10(5.32) 32(3.59) 27(5.10) 6(2.86) More than once a month 14(7.45) 79(8.86) 40(7.56) 10(4.76) Eating meals ≤2 meals per day 48(25.53) 143(16.03) 58(10.96) 18(8.57) 32.785 <0.001 3 meals per day 139(73.94) 732(82.06) 463(87.52) 189(90.00) ≥4 meals per day 1(0.53) 17(1.91) 8(1.51) 3(1.43) Taking activities No 113(60.11) 490(54.93) 241(45.56) 100(47.62) 19.191 <0.001 Yes 75(39.89) 402(45.07) 288(54.44) 110(52.38) Ever been in major accidental injury No 173(92.02) 830(93.05) 490(92.63) 197(93.81) 0.573 0.903 Yes 15(7.98) 62(6.95) 39(7.37) 13(6.19) Having regular physical exercises No physical exercise 134(71.28) 569(63.79) 322(60.87) 132(62.86) 9.032 0.172 Less than regular physical exercises 25(13.30) 172(19.28) 99(18.71) 36(17.14) Regular physical exercises 29(15.43) 151(16.93) 108(20.42) 42(20.00) History of CVD No 160(85.11) 757(84.87) 428(80.91) 158(75.24) 13.931 0.003 Yes 28(14.89) 135(15.13) 101(19.09) 52(24.76) History of liver diseases No 183(97.34) 864(96.86) 504(95.27) 203(96.67) 3.289 0.349 Yes 5(2.66) 28(3.14) 25(4.73) 7(3.33) Antilipidemic medication No 185(98.40) 854(95.74) 474(89.60) 178(84.76) 49.744 <0.001 Yes 3(1.60) 38(4.26) 55(10.40) 32(15.24) Anti-diabetic medication No 187(99.47) 863(96.75) 490(92.63) 188(89.52) 33.154 <0.001 Yes 1(0.53) 29(3.25) 39(7.37) 22(10.48) Anti-hypertensive therapy No 171(90.96) 838(93.95) 495(93.57) 191(90.95) 33.154 <0.001 Yes 17(9.04) 54(6.05) 34(6.43) 19(9.05) Fasting plasma glucose (mg/dl) 105.18±22.29 110.63±40.95 118.34±48.98 116.55±35.01 6.659 <0.001 LDL Cholesterol (mg/dl) 115.41±33.67 122.84±34.65 127.66±38.90 128.45±41.61 6.511 <0.001 HDL Cholesterol (mg/dl) 60.31±16.04 54.55±15.13 47.67±13.02 45.26±11.70 62.326 <0.001 eGFR (ml/min/1.73m2) 72.49±16.54 75.97±16.10 77.40±15.8 75.16±18.06 4.396 0.004 Serum uric acid (mg/dl) 3.83±1.14 4.06±1.12 4.30±1.14 4.62±1.22 21.304 <0.001 Systolic blood pressure (mmHg) 133.66±24.74 136.74±23.69 141.83±30.53 146.33±38.15 19.704 <0.001 Diastolic blood pressure (mmHg) 73.00±12.26 75.01±11.77 78.61±12.06 79.54±12.23 10.742 <0.001 Body mass index (kg/m2) 17.13±1.42 21.43±1.50 25.73±1.15 30.90±4.33 2202.200 <0.001 Triglycerides (mg/dl) 103.17±50.81 128.46±82.33 158.53±100.30 176.54±128.24 33.113 <0.001Tables1 and 2 show the various characteristics of participants categorized on basis of BMI. The participants comprised 1,810 men aged 68.86 ± 6.30 (range: 60–93) years and 1,819 women aged 68.55 ± 6.82 (range, 60–96) years. According to the modified Chinese criteria for BMI [34], the mean BMI in men was 22.41 kg/m2 (SD, 3.71), with 10.94% underweight (BMI, < 18.5 kg/m2), 60.66% normal weight (BMI, 18.5–24 kg/m2), 21.60% overweight, and 6.80% obese (BMI, ≥ 28 kg/m2), whereas the mean BMI in women was 23.33 kg/m2 (SD, 4.23), with 10.34% underweight (BMI, < 18.5 kg/m2), 49.04% normal weight (BMI, 18.5–24 kg/m2), 29.08% overweight, and 11.54% obese (BMI, ≥ 28 kg/m2). Table 1 shows the background characteristics of male participants categorized based on BMI. Levels of FPG, LDL-C, TG, eGFR, SUA, SBP, and DBP were significantly higher in the high BMI group than in the low BMI group, whereas HDL-C level was higher in the low BMI group than in the high BMI group. However, between-group differences in the prevalence of major accidental injury, regular physical exercise, history of liver disease, and antihypertensive therapy were not observed. In women, levels of FBG, LDL-C, TG, eGFR, SUA, SBP, and DBP were significantly higher in the high BMI group than those in the low BMI group, but HDL-C level was higher in the low BMI group than in the high BMI group. However, between-group differences in categories of alcohol drinking, major accidental injury, physical activity, and history of liver disease were not observed (Table 2).Tables3 and 4 show the characteristics of participants categorized by BMI and BP status. First, in the hypertensive group with a BMI < 24.0 kg/m2 in men, levels of glucose, LDL-C, BMI, SUA, SBP, and DBP were significantly higher than those in the hypertensive group, but eGFR level was significantly higher than that in the normotensive group. Second, in the hypertensive group with a BMI ≥ 24.0 kg/m2 in men, levels of SUA, SBP, and DBP were also significantly higher, but eGFR level was significantly lower than that in the normotensive group (shown in Table 3). Third, in the hypertensive group with a BMI < 24.0 kg/m2 in women, levels of TG, SUA, SBP, DBP, and the prevalence of antilipidemic medication were significantly higher than those in the normotensive group, but eGFR level was significantly lower. Lastly, in the hypertensive group with a BMI ≥ 24.0 kg/m2 in women, the prevalence of CVD, antilipidemic medication, and antidiabetic medication were significantly higher, as were levels of glucose, TG, SBP, and DBP (Table 4).Table 3
Characteristics of participants categorized by BMI and blood pressure status in male (N=1810).
Variables BMI24(n=1296) t/χ2 P BMI≥24 (n=514) t/χ2 P Normotension(n=866) Hypertension(n=430) Normotension(n=276) Hypertension(n=238) Age(years) 68.99±6.42 70.53±6.33 -4.080 <0.001 66.84±5.47 67.55±5.71 -1.439 0.151 Education Illiterate 200(23.09) 108(25.12) 6.278 0.099 37(13.41) 27(11.34) 0.776 0.855 Less than elementary school 600(69.28) 303(70.47)   211(76.45) 185(77.73) High school 20(2.31) 3(0.70)   4(1.45) 5(2.10) Above vocational school 46(5.31) 16(3.72)   24(8.70) 21(8.82) Marital status Single 122(14.09) 86(20.00) 7.454 0.006 20(7.25) 23(9.66) 0.974 0.324 Married 744(85.91) 344(80.00)   256(92.75) 215(90.34) Current residence Rural 638(73.67) 305(70.93) 1.090 0.296 155(56.16) 123(51.68) 1.032 0.310 Urban 228(26.33) 125(29.07)   121(43.84) 115(48.32) Smoke NO 487(56.24) 263(61.16) 2.980 0.225 103(37.32) 108(45.38) 3.691 0.158 Former smoke 165(19.05) 70(16.28)   81(29.35) 57(23.95) Current smoke 214(24.71) 97(22.56)   92(33.33) 73(30.67) Drinking NO 441(50.92) 217(50.47) 0.051 0.975 139(50.36) 128(53.78) 0.599 0.741 Less than once a month 72(8.31) 35(8.14)   26(9.42) 21(8.82) More than once a month 353(40.76) 178(41.4)   111(40.22) 89(37.39) Eating meals ≤2 meals per day 116(13.39) 89(20.70) 11.939 0.003 29(10.51) 24(10.08) 0.233 0.890 3 meals per day 735(84.87) 332(77.21)   245(88.77) 213(89.50) ≥4 meals per day 15(1.73) 9(2.09)   2(0.72) 1(0.42) Taking activities No 477(55.08) 235(54.65) 0.021 0.884 120(43.48) 117(49.16) 1.334 0.248 Yes 389(44.92) 195(45.35)   156(56.52) 121(50.84) Ever been in major accidental injury No 760(87.76) 389(90.47) 2.091 0.148 243(88.04) 217(91.18) 1.741 0.187 Yes 106(12.24) 41(9.53)   33(11.96) 21(8.82) Having regular physical exercises No physical exercise 563(65.01) 260(60.47) 2.957 0.228 170(61.59) 146(61.34) 1.743 0.418 Less than regular physical exercises 139(16.05) 83(19.30)   49(17.75) 34(14.29) Regular physical exercises 164(18.94) 87(20.23)   57(20.65) 58(24.37) History of CVD No 772(89.15) 376(87.44) 0.947 0.330 222(80.43) 183(76.89) 0.760 0.383 Yes 94(10.85) 54(12.56)   54(19.57) 55(23.11) History of liver diseases No 832(96.07) 417(96.98) 0.634 0.426 260(94.20) 229(96.22) 1.122 0.290 Yes 34(3.93) 13(3.02)   16(5.80) 9(3.78) Antilipidemic medication No 839(96.88) 418(97.21) 0.105 0.746 253(91.67) 217(91.18) 0.039 0.843 Yes 27(3.12) 12(2.79)   23(8.33) 21(8.82) Anti-diabetic medication No 841(97.11) 423(98.37) 1.891 0.169 252(91.30) 217(91.18) 0.003 0.959 Yes 25(2.89) 7(1.63)   24(8.70) 21(8.82) Anti-hypertensive therapy No 866(100.00) 356(82.79) 154.880 <0.001 276(100.00) 197(82.77) 49.347 <0.001 Yes 0(0.00) 74(17.21)   0(0.00) 41(17.23) Fasting plasma glucose(mg/dl) 106.7±33.3 112.26±38.38 -2.678 0.007 116.83±37.59 120.62±45.51 -1.029 0.304 LDL Cholesterol (mg/dl) 108.4±32.03 112.4±33.07 -2.089 0.037 117.46±34.23 119.22±35.95 -0.565 0.572 HDL Cholesterol (mg/dl) 54.94±16.53 54.59±15.34 0.364 0.716 44.02±12.93 43.18±13.00 0.735 0.463 eGFR(ml/min/1.73m2) 75.95±15.97 71.69±17.21 4.396 <0.001 77.54±16.00 73.21±16.46 3.011 0.003 Serum uric acid(mg/dl) 4.83±1.25 5.15±1.38 -4.246 <0.001 5.22±1.32 5.49±1.31 -2.278 0.023 Systolic blood pressure(mmHg) 119.36±12.22 157.19±21.46 -25.143 <0.001 124.62±10.54 158.37±23.28 -15.737 <0.001 Diastolic blood pressure(mmHg) 69.02±9.26 84.54±12.44 -40.141 <0.001 72.72±8.41 86.95±11.89 -21.480 <0.001 Body mass index(kg/m2) 20.53±2.05 20.84±2.04 -2.604 0.009 26.80±3.76 26.88±2.08 -0.280 0.780 Triglycerides (mg/dl) 95.95±54.77 104.34±59.81 -2.510 0.012 147.99±135.77 147.86±104.59 0.012 0.990Table 4
Characteristics of participants categorized by BMI and blood pressure status in female (N=1819).
Variables BMI24(n=1080) t/χ2 P BMI≥24 (n=739) t/χ2 P Normotension(n=660) Hypertension(n=420) Normotension(n=362) Hypertension(n=377) Age(years) 67.87±6.60 71.12±7.30 -7.518 <0.001 66.27±5.54 68.71±6.70 -5.352 <0.001 Education Illiterate 385(58.33) 278(66.19) 7.660 0.054 168(46.41) 212(56.23) 11.887 0.008 Less than elementary school 260(39.39) 137(32.62)   178(49.17) 155(41.11) High school 5(0.76) 1(0.24)   8(2.21) 1(0.27) Above vocational school 10(1.52) 4(0.95)   8(2.21) 9(2.39) Marital status Single 189(28.64) 174(41.43) 18.823 <0.001 82(22.65) 98(25.99) 1.120 0.290 Married 471(71.36) 246(58.57)   280(77.35) 279(74.01) Current residence Rural 450(68.18) 288(68.57) 0.018 0.893 207(57.18) 209(55.44) 0.228 0.633 Urban 210(31.82) 132(31.43)   155(42.82) 168(44.56) Smoke NO 574(86.97) 360(85.71) 0.444 0.801 330(91.16) 339(89.92) 0.925 0.630 Former smoke 22(3.33) 14(3.33)   9(2.49) 14(3.71) Current smoke 64(9.70) 46(10.95)   23(6.35) 24(6.37) Drinking NO 575(87.12) 370(88.10) 1.172 0.556 318(87.85) 338(89.66) 1.871 0.392 Less than once a month 29(4.39) 13(3.10)   20(5.52) 13(3.45) More than once a month 56(8.48) 37(8.81)   24(6.63) 26(6.90) Eating meals ≤2 meals per day 112(16.97) 79(18.81) 0.599 0.741 40(11.05) 36(9.55) 0.611 0.737 3 meals per day 537(81.36) 334(79.52)   316(87.29) 336(89.12) ≥4 meals per day 11(1.67) 7(1.67)   6(1.66) 5(1.33) Taking activities No 366(55.45) 237(56.43) 0.099 0.753 171(47.24) 170(45.09) 0.342 0.559 Yes 294(44.55) 183(43.57)   191(52.76) 207(54.91) Ever been in major accidental injury No 610(92.42) 393(93.57) 0.510 0.475 333(91.99) 354(93.90) 1.030 0.310 Yes 50(7.58) 27(6.43)   29(8.01) 23(6.10) Having regular physical exercises No physical exercise 417(63.18) 286(68.10) 4.349 0.114 223(61.60) 231(61.27) 0.840 0.657 Less than regular physical exercises 133(20.15) 64(15.24)   62(17.13) 73(19.36) Regular physical exercises 110(16.67) 70(16.67)   77(21.27) 73(19.36) History of CVD No 561(85.00) 356(84.76) <0.001 0.985 293(80.94) 293(77.72) 0.979 0.322 Yes 99(15.00) 64(15.24)   69(19.06) 84(22.28) History of liver diseases No 640(96.97) 407(96.90) 0.004 0.952 342(94.48) 365(96.82) 1.912 0.167 Yes 20(3.03) 13(3.10)   20(5.52) 12(3.18) Antilipidemic medication No 641(97.12) 398(94.76) 3.912 0.048 329(90.88) 323(85.68) 4.822 0.028 Yes 19(2.88) 22(5.24)   33(9.12) 54(14.32) Anti-diabetic medication No 644(97.58) 406(96.67) 0.785 0.375 343(94.75) 335(88.86) 8.466 0.004 Yes 16(2.42) 14(3.33)   19(5.25) 42(11.14) Anti-hypertensive therapy No 660(100.00) 349(83.10) 116.690 <0.001 362(100.00) 324(85.94) 52.732 <0.001 Yes 0(0.00) 71(16.90)   0(0.00) 53(14.06) Fasting plasma glucose(mg/dl) 107.94±38.43 112.33±38.69 -1.816 0.070 111.30±31.47 123.61±54.14 -3.727 <0.001 LDL Cholesterol (mg/dl) 121.38±33.16 121.89±36.31 -0.235 0.814 126.38±37.50 129.47±41.91 -1.046 0.296 HDL Cholesterol (mg/dl) 56.09±15.43 54.71±15.29 1.429 0.153 47.60±12.33 46.48±13.09 1.183 0.237 eGFR(ml/min/1.73m2) 77.62±15.26 72.13±17.03 5.486 <0.001 78.07±15.97 75.73±16.73 1.935 0.053 Serum uric acid(mg/dl) 3.92±1.10 4.17±1.16 -3.510 <0.001 4.30±1.12 4.46±1.21 -1.950 0.052 Systolic blood pressure(mmHg) 120.81±12.07 159.88±17.31 -20.347 <0.001 123.15±10.88 161.97±35.55 -17.786 <0.001 Diastolic blood pressure(mmHg) 69.57±8.82 82.44±11.75 -43.348 <0.001 71.98±8.39 85.32±11.53 -19.691 <0.001 Body mass index(kg/m2) 20.6±2.20 20.85±2.19 -1.796 0.073 26.97±2.92 27.43±3.84 -1.810 0.071 Triglycerides (mg/dl) 119.69±73.83 130.67±83.99 -2.243 0.025 150.58±87.77 174.89±122.44 -3.067 0.002Table5 shows the various characteristics of participants categorized by age. SUA and SBP levels were significantly higher in the older age group than in the younger age group in men, whereas levels of HDL-C, eGFR, DBP, BMI, and TG were lower in the older age group than in the younger age group. However, between-group differences in categories of current residence, eating habits, taking activities, major accidental injury, regular physical exercise, history of liver disease, antidiabetic medication, antihypertensive therapy, FPG, and LDL-C were not observed. In women, SUA and SBP levels were significantly higher in the older age group than in the younger age group, but eGFR and BMI levels were lower in the older age group than in the younger age group. However, between-group differences in categories of current residence, drinking, eating habits, activity, major accidental injury, history of CVD, history of liver disease, antidiabetic medication, and antihypertensive therapy, FPG, LDL-C, HDL-C, DBP, and TG were not observed.Table 5
Characteristics of participants categorized by age in male and female (N=3629).
Male(n=1810) Female(n=1819) Variables Age <68 years (n=807) Age≥68 years (n=1003) t/χ2 P Age <68 years (n=887) Age≥68 years (n=932) t/χ2 P Education Illiterate 94(11.65) 278(27.72) 73.763 <0.001 409(46.11) 634(68.03) 94.734 <0.001 Less than elementary school 652(80.79) 647(64.51)   457(51.52) 273(29.29) High school 16(1.98) 16(1.60)   8(0.90) 7(0.75) Above vocational school 45(5.58) 62(6.18)   13(1.47) 18(1.93) Marital status Single 69(8.55) 182(18.15) 34.471 <0.001 138(15.56) 405(43.45) 168.901 <0.001 Married 738(91.45) 821(81.85)   749(84.44) 527(56.55) Current residence Rural 538(66.67) 683(68.10) 0.416 0.519 580(65.39) 574(61.59) 2.831 0.092 Urban 269(33.33) 320(31.90)   307(34.61) 358(38.41) Smoke NO 201(24.91) 275(27.42) 10.454 0.005 791(89.18) 812(87.12) 13.584 0.001 Former smoke 145(17.97) 228(22.73)   15(1.69) 44(4.72) Current smoke 461(57.13) 500(49.85)   81(9.13) 76(8.15) Drinking NO 366(45.35) 559(55.73) 19.444 <0.001 777(87.6) 824(88.41) 1.095 0.578 Less than once a month 79(9.79) 75(7.48)   41(4.62) 34(3.65) More than once a month 362(44.86) 369(36.79)   69(7.78) 74(7.94) Eating meals ≤2 meals per day 107(13.26) 151(15.05) 1.687 0.430 119(13.42) 148(15.88) 2.586 0.275 3 meals per day 686(85.01) 839(83.65)   752(84.78) 771(82.73) ≥4 meals per day 14(1.73) 13(1.3)   16(1.8) 13(1.39) Taking activities No 412(51.05) 537(53.54) 1.108 0.292 448(50.51) 496(53.22) 1.339 0.247 Yes 395(48.95) 466(46.46)   439(49.49) 436(46.78) Ever been in major accidental injury No 723(89.59) 886(88.33) 0.715 0.398 825(93.01) 865(92.81) 0.027 0.869 Yes 84(10.41) 117(11.67)   62(6.99) 67(7.19) Having regular physical exercises No physical exercise 509(63.07) 630(62.81) 3.842 0.146 530(59.75) 627(67.27) 11.203 0.004 Less than regular physical exercises 148(18.34) 157(15.65)   181(20.41) 151(16.2) Regular physical exercises 150(18.59) 216(21.54)   176(19.84) 154(16.52) History of CVD No 712(88.23) 841(83.85) 6.902 0.009 741(83.54) 762(81.76) 0.977 0.323 Yes 95(11.77) 162(16.15)   146(16.46) 170(18.24) History of liver diseases No 769(95.29) 969(96.61) 2.154 0.142 858(96.73) 896(96.14) 0.450 0.503 Yes 38(4.71) 34(3.39)   29(3.27) 36(3.86) Antilipidemic medication No 759(94.05) 968(96.51) 6.177 0.013 811(91.43) 880(94.42) 6.206 0.013 Yes 48(5.95) 35(3.49)   76(8.57) 52(5.58) Anti-diabetic medication No 769(95.29) 964(96.11) 0.739 0.390 838(94.48) 890(95.49) 0.911 0.320 Yes 38(4.71) 39(3.89)   49(5.52) 42(4.51) Anti-hypertensive therapy No 755(93.56) 940(93.72) 0.002 0.888 823(92.78) 872(93.56) 0.433 0.511 Yes 52(6.44) 63(6.28)   64(7.22) 60(6.44) Fasting plasma glucose(mg/dl) 113.22±40.77 109.94±34.06 1.864 0.062 112.89±44.91 113.09±38.18 -0.104 0.917 LDL Cholesterol (mg/dl) 113.49±35.56 111.15±31.42 1.489 0.137 123.2±36.32 125.00±37.35 -1.041 0.298 HDL Cholesterol (mg/dl) 50.53±15.8 52.53±16.25 2.633 0.009 51.62±14.61 52.5±15.33 -1.252 0.211 eGFR(ml/min/1.73m2) 81.50±14.52 69.24±15.88 16.964 <0.001 82.21±14.6 69.97±15.68 17.211 <0.001 Serum uric acid(mg/dl) 4.97±1.28 5.14±1.35 -2.682 0.007 4.08±1.13 4.26±1.19 -3.350 0.001 Systolic blood pressure(mmHg) 132±21.28 136.32±26.41 -3.748 <0.001 134.43±25.74 143.46±29.58 -6.885 <0.001 Diastolic blood pressure(mmHg) 77.38±12.52 74.33±12.96 5.036 <0.001 76.83±12.3 75.95±11.98 1.534 0.252 Body mass index(kg/m2) 23.06±3.61 21.88±3.70 6.853 <0.001 23.78±3.86 22.90±4.51 4.428 <0.001 Triglycerides (mg/dl) 121.17±99.74 106.04±67.08 3.843 <0.001 142.91±90.84 137.51±97.13 1.223 0.222In addition to their direct associations, we observed the effect between BMI category and TG levels on BP in Figure1. TG correlated positively with both SBP and DBP. Analysis of covariance showed that three regression lines in each graph were not different from those in the other groups (male: SBP, F=0.028,P=0.867 and DBP, F= 0.194, andP =0.660; female: SBP, F=0.783,P=0.376 and DBP, F=0.005, andP =0.941; respectively).Figure 1
(a, b) Correlation between serum uric acid and blood pressure status of participants categorized by body mass index in male. (c, d) Correlation between triglycerides and blood pressure status of participants categorized by body mass index in female.
(a) (b) (c) (d)Tables6 and 7 show the relationship between various characteristics and BP status of participants categorized by BMI (< 24.0 kg/m2 and ≥ 24.0 kg/m2). Age-adjusted partial Pearson’s correlation coefficient showed that TG level was positively correlated with both SBP and DBP in men with a BMI < 21.0 kg/m2 (Table 6). In women, the TG level was significantly correlated with SBP and DBP in subjects with a BMI < 21.0 kg/m2 and positively correlated with DBP in those with a BMI ≥ 24.0 kg/m2, but there was no correlation with SBP in women with a BMI ≥ 24.0 kg/m2 (Table 7).Table 6
Age-adjusted relationship between various characteristics and blood pressure status of participants categorized by BMI in male (N=1810).
Variables BMI<24(n=1296) BMI≥24 (n=514) Systolic blood pressurepartial r(P-value) Diastolic blood pressurepartial r(P-value) Systolic blood pressurepartial r(P-value) Diastolic blood pressurepartial r(P-value) Education(0= Illiterate, 1= Less than elementary school, 2= High school, 3= Above vocational school) -0.024(0.392) 0.013(0.647) -0.009(0.848) -0.042(0.344) Marital status(0= Single,1= Married) -0.105(<0.001) -0.092(0.001) 0.011(0.807) -0.011(0.798) Current residence(0= Rural,1= Urban) 0.044(0.117) 0.032(0.249) 0.113(0.011) 0.059(0.187) Smoke(0= NO,1= Former smoke,2= Current smoke) 0.06(0.033) 0.009(0.752) 0.066(0.140) 0.016(0.727) Drinking(0= NO,1= Less than once a month,2= More than once a month) 0.015(0.602) 0.020(0.480) -0.066(0.139) -0.003(0.944) Eating meals(0= ≤2 meals per day,1=3 meals per day,2= ≥4 meals per day) -0.061(0.031) -0.083(0.003) -0.014(0.759) -0.056(0.21) Taking activities(0= No,1= Yes) 0.014(0.623) 0.031(0.268) 0.091(0.040) 0.118(0.008) Ever been in major accidental injury(0= No,1= Yes) -0.028(0.320) -0.019(0.505) -0.035(0.429) -0.007(0.871) Having regular physical exercises(0= No physical exercise,1= Less than regular physical exercises,2= Regular physical exercises) 0.034(0.23) 0.006(0.833) 0.011(0.803) 0.011(0.814) History of CVD(0= No,1= Yes) 0.019(0.497) 0.028(0.327) -0.009(0.833) 0.008(0.854) History of liver diseases(0= No,1= Yes) 0.009(0.760) 0.013(0.631) -0.023(0.613) 0.028(0.526) Antilipidemic medication(0= No,1= Yes) -0.008(0.787) 0.019(0.504) 0.002(0.973) 0.027(0.546) Anti-diabetic medication(0= No,1= Yes) 0.002(0.955) 0.007(0.806) 0.043(0.339) -0.012(0.796) Anti-hypertensive therapy(0= No,1= Yes) 0.140(<0.001) 0.109(<0.001) 0.047(0.291) 0.127(0.004) Fasting plasma glucose(mg/dl) 0.075(0.007) 0.046(0.098) 0.068(0.126) 0.065(0.147) LDL Cholesterol (mg/dl) 0.063(0.024) 0.052(0.067) 0.063(0.157) 0.024(0.585) HDL Cholesterol (mg/dl) -0.005(0.848) 0.005(0.870) -0.042(0.344) -0.003(0.942) eGFR(ml/min/1.73m2) -0.076(0.007) -0.043(0.124) -0.157(<0.001) -0.107(0.016) Serum uric acid(mg/dl) 0.108(<0.001) 0.06(0.032) 0.056(0.212) 0.067(0.130) Body mass index(kg/m2) 0.121(<0.001) 0.093(0.001) 0.062(0.163) 0.048(0.279) Triglycerides (mg/dl) 0.069(0.014) 0.058(0.04) 0.074(0.097) 0.047(0.288)Table 7
Age-adjusted relationship between various characteristics and blood pressure status of participants categorized by BMI in female (N=1819).
Variables BMI<24(n=1080) BMI≥24(n=739) Systolic blood pressurepartial r(P-value) Diastolic blood pressurepartial r(P-value) Systolic blood pressurepartial r(P-value) Diastolic blood pressurepartial r(P-value) Education(0= Illiterate, 1= Less than elementary school, 2= High school, 3= Above vocational school) -0.053(0.086) -0.07(0.024) -0.002(0.957) -0.041(0.270) Marital status(0= Single,1= Married) -0.097(0.002) -0.077(0.012) -0.066(0.076) -0.015(0.687) Current residence(0= Rural,1= Urban) -0.01(0.745) -0.039(0.211) 0.039(0.294) 0.035(0.344) Smoke(0= NO,1= Former smoke,2= Current smoke) 0.035(0.255) 0.021(0.503) -0.025(0.508) 0.007(0.844) Drinking(0= NO,1= Less than once a month,2= More than once a month) -0.016(0.608) 0.015(0.630) -0.022(0.549) -0.02(0.584) Eating meals(0= ≤2 meals per day,1=3 meals per day,2= ≥4 meals per day) -0.021(0.505) -0.075(0.015) -0.026(0.483) -0.069(0.064) Taking activities(0= No,1= Yes) -0.036(0.251) -0.034(0.266) 0.027(0.474) 0.027(0.472) Ever been in major accidental injury(0= No,1= Yes) -0.01(0.745) 0.014(0.640) -0.041(0.274) -0.042(0.259) Having regular physical exercises(0= No physical exercise,1= Less than regular physical exercises,2= Regular physical exercises) -0.008(0.799) -0.008(0.803) -0.015(0.692) 0.031(0.401) History of CVD(0= No,1= Yes) 0.036(0.239) 0.001(0.986) -0.014(0.700) -0.021(0.582) History of liver diseases(0= No,1= Yes) 0.005(0.868) 0.003(0.934) -0.047(0.213) -0.103(0.006) Antilipidemic medication(0= No,1= Yes) 0.065(0.034) 0.054(0.082) 0.054(0.151) 0.032(0.399) Anti-diabetic medication(0= No,1= Yes) 0.013(0.686) -0.029(0.356) 0.122(0.001) 0.046(0.214) Anti-hypertensive therapy(0= No,1= Yes) 0.110(<0.001) 0.037(0.029) 0.128(<0.001) 0.102(<0.001) Fasting plasma glucose(mg/dl) 0.049(0.115) 0.043(0.161) 0.021(0.577) 0.158(<0.001) LDL Cholesterol (mg/dl) 0.028(0.362) 0.011(0.725) 0.049(0.189) -0.005(0.886) HDL Cholesterol (mg/dl) -0.087(0.005) -0.06(0.051) -0.039(0.293) -0.050(0.184) eGFR(ml/min/1.73m2) -0.069(0.025) -0.045(0.147) 0.067(0.075) 0.020(0.600) Serum uric acid(mg/dl) 0.126(<0.001) 0.074(0.016) -0.018(0.627) 0.011(0.764) Body mass index(kg/m2) 0.105(0.001) 0.093(0.002) 0.021(0.583) 0.075(0.045) Triglycerides (mg/dl) 0.123(<0.001) 0.091(0.003) 0.046(0.218) 0.097(0.010)Tables8 and 9 show the relationship between various characteristics and BP status of participants categorized by age (< 68 years and ≥ 68 years). TG level was positively correlated with both SBP and DBP in both men and women with age < 68 years and ≥ 68 years.Table 8
Relationship between various characteristics and blood pressure status of participants categorized by age in male (N=1810).
Variables Age <68 years(n=807) Age≥68 years(n=1003) Systolic blood pressurepartial r(P-value) Diastolic blood pressurepartial r(P-value) Systolic blood pressurepartial r(P-value) Diastolic blood pressurepartial r(P-value) Age 0.052(0.146) -0.011(0.763) 0.05(0.116) -0.096(0.002) Education(0= Illiterate, 1= Less than elementary school, 2= High school, 3= Above vocational school) 0.013(0.720) -0.016(0.646) -0.019(0.544) 0.043(0.173) Marital status(0= Single,1= Married) -0.064(0.070) -0.086(0.015) -0.074(0.020) -0.033(0.295) Current residence(0= Rural,1= Urban) 0.072(0.042) 0.039(0.274) 0.102(0.001) 0.096(0.003) Smoke(0= NO,1= Former smoke,2= Current smoke) 0.018(0.616) 0.017(0.633) 0.042(0.184) -0.023(0.462) Drinking(0= NO,1= Less than once a month,2= More than once a month) -0.028(0.425) -0.015(0.679) -0.006(0.856) 0.037(0.244) Eating meals(0= ≤2 meals per day,1=3 meals per day,2= ≥4 meals per day) -0.065(0.067) -0.098(0.006) -0.026(0.420) -0.050(0.114) Taking activities(0= No,1= Yes) -0.036(0.315) -0.040(0.255) 0.022(0.495) 0.042(0.189) Ever been in major accidental injury(0= No,1= Yes) -0.044(0.212) -0.053(0.137) -0.026(0.416) -0.001(0.975) Having regular physical exercises(0= No physical exercise,1= Less than regular physical exercises,2= Regular physical exercises) -0.001(0.987) -0.005(0.89) 0.046(0.147) 0.022(0.489) History of CVD(0= No,1= Yes) 0.055(0.123) 0.06(0.089) 0.009(0.786) 0.027(0.396) History of liver diseases(0= No,1= Yes) -0.033(0.357) -0.019(0.598) 0.024(0.448) 0.056(0.078) Antilipidemic medication(0= No,1= Yes) 0.060(0.092) 0.06(0.088) -0.018(0.561) 0.021(0.502) Anti-diabetic medication(0= No,1= Yes) 0.038(0.281) -0.002(0.945) 0.041(0.198) 0.045(0.157) Anti-hypertensive therapy(0= No,1= Yes) 0.131(<0.001) 0.122(0.001) 0.103(0.001) 0.118(<0.001) Fasting plasma glucose(mg/dl) 0.122(0.001) 0.092(0.009) 0.069(0.031) 0.048(0.131) LDL Cholesterol (mg/dl) 0.096(0.007) 0.067(0.056) 0.061(0.054) 0.054(0.087) HDL Cholesterol (mg/dl) -0.102(0.004) -0.077(0.028) -0.049(0.122) -0.026(0.405) eGFR(ml/min/1.73m2) -0.119(0.001) -0.084(0.017) -0.117(<0.001) -0.016(0.618) Serum uric acid(mg/dl) 0.143(<0.001) 0.122(0.001) 0.104(0.001) 0.049(0.123) Body mass index(kg/m2) 0.252(<0.001) 0.218(<0.001) 0.146(<0.001) 0.140(<0.001) Triglycerides (mg/dl) 0.091(0.010) 0.091(0.010) 0.105(0.001) 0.083(0.009)Table 9
Relationship between various characteristics and blood pressure status of participants categorized by age in female (N=1819).
Variables Age <68 years(n=887) Age≥68 years(n=932) Systolic blood pressurepartial r(P-value) Diastolic blood pressurepartial r(P-value) Systolic blood pressurepartial r(P-value) Diastolic blood pressurepartial r(P-value) Age 0.067(0.048) -0.032(0.348) 0.117(<0.001) -0.039(0.244) Education(0= Illiterate, 1= Less than elementary school, 2= High school, 3= Above vocational school) -0.033(0.335) -0.020(0.546) -0.034(0.308) -0.051(0.124) Marital status(0= Single,1= Married) -0.073(0.031) -0.028(0.409) -0.104(0.002) -0.035(0.292) Current residence(0= Rural,1= Urban) 0.034(0.320) 0.028(0.410) 0.021(0.536) -0.007(0.822) Smoke(0= NO,1= Former smoke,2= Current smoke) 0.043(0.203) 0.024(0.481) -0.040(0.230) -0.024(0.471) Drinking(0= NO,1= Less than once a month,2= More than once a month) -0.017(0.605) -0.008(0.818) -0.028(0.391) 0.001(0.970) Eating meals(0= ≤2 meals per day,1=3 meals per day,2= ≥4 meals per day) -0.053(0.118) -0.07(0.039) 0.013(0.700) -0.041(0.221) Taking activities(0= No,1= Yes) 0.022(0.509) 0.053(0.115) -0.002(0.956) -0.049(0.142) Ever been in major accidental injury(0= No,1= Yes) -0.018(0.589) 0.012(0.719) -0.034(0.300) -0.032(0.330) Having regular physical exercises(0= No physical exercise,1= Less than regular physical exercises,2= Regular physical exercises) -0.016(0.638) 0.025(0.460) -0.011(0.735) 0.007(0.834) History of CVD(0= No,1= Yes) 0.079(0.020) 0.074(0.028) -0.032(0.332) -0.057(0.084) History of liver diseases(0= No,1= Yes) 0.019(0.574) 0.011(0.746) -0.054(0.104) -0.088(0.008) Antilipidemic medication(0= No,1= Yes) 0.095(0.005) 0.075(0.027) 0.058(0.081) 0.046(0.161) Anti-diabetic medication(0= No,1= Yes) 0.125(<0.001) 0.061(0.069) 0.057(0.087) -0.004(0.896) Anti-hypertensive therapy(0= No,1= Yes) 0.096(0.004) 0.060(0.073) 0.135(<0.001) 0.076(0.022) Fasting plasma glucose(mg/dl) 0.061(0.072) 0.159(<0.001) 0.031(0.344) 0.055(0.097) LDL Cholesterol (mg/dl) 0.048(0.157) 0.028(0.404) 0.05(0.132) 0.014(0.668) HDL Cholesterol (mg/dl) -0.137(<0.001) -0.118(<0.001) -0.063(0.058) -0.085(0.010) eGFR(ml/min/1.73m2) -0.039(0.248) -0.007(0.836) -0.025(0.455) -0.011(0.743) Serum uric acid(mg/dl) 0.084(0.012) 0.083(0.013) 0.092(0.005) 0.054(0.100) Body mass index(kg/m2) 0.161(<0.001) 0.253(<0.001) 0.116(<0.001) 0.116(<0.001) Triglycerides (mg/dl) 0.155(<0.001) 0.148(<0.001) 0.069(0.037) 0.096(0.004)Tables10 and 11 show the multivariate-adjusted relationship between various characteristics and BP status in participants categorized by BMI (< 24.0 kg/m2 and ≥ 24.0 kg/m2). Multiple linear regression analysis showed that TG level was significantly and positively associated with SBP in women with a BMI < 24.0 kg/m2, independent of other confounding factors; however, TG level was not significantly associated with BP in men.Table 10
Multivariate-adjusted relationship between various characteristics and blood pressure status of participants categorized by BMI in male (N=1810).
Variables BMI<24(n=1296) BMI≥24 (n=514) Systolic blood pressureβ(P-value) Diastolic blood pressureβ (P-value) Systolic blood pressureβ (P-value) Diastolic blood pressureβ (P-value) Age (years) 0.117(<0.001) -0.108(0.001) — -0.199(<0.001) Education (0= Illiterate, 1= Less than elementary school, 2= High school, 3= Above vocational school) — — — — Marital status (0= Single,1= Married) -0.101(<0.001) -0.092(0.001) — — Current residence (0= Rural,1= Urban) — — 0.119(0.009) — Smoke (0= NO,1= Former smoke,2= Current smoke) 0.060(0.033) — 0.104(0.023) — Drinking (0= NO,1= Less than once a month,2= More than once a month) — — — — Eating meals (0=≤2 meals per day,1=3 meals per day,2= ≥4 meals per day) -0.056(0.041) -0.085(0.002) — — Taking activities (0= No,1= Yes) — — -0.108(0.016) -0.116(0.01) Ever been in major accidental injury (0= No,1= Yes) — — — — Having regular physical exercises (0= No physical exercise,1= Less than regular physical exercises,2= Regular physical exercises) — — — — History of CVD (0= No,1= Yes) — — — — History of liver diseases (0= No,1= Yes) — — — — Antilipidemic medication (0= No,1= Yes) — — — — Anti-diabetic medication (0= No,1= Yes) — — — — Anti-hypertensive therapy (0= No,1= Yes) 0.130(<0.001) 0.103(<0.001) — 0.113(0.011) Fasting plasma glucose (mg/dl) 0.072(0.016) — — — LDL Cholesterol (mg/dl) 0.056(0.042) — 0.091(0.048) — HDL Cholesterol (mg/dl) — — — — eGFR (ml/min/1.73m2) — — -0.172(0.002) — Serum uric acid (mg/dl) 0.068(0.029) — — — Body mass index (kg/m2) 0.106(<0.001) 0.076(0.009) — — Triglycerides (mg/dl) — — — — R2 0.098(<0.001) 0.054(<0.001) 0.087(0.003) 0.089(0.0002)Table 11
Multivariate-adjusted relationship between various characteristics and blood pressure status of participants categorized by BMI in female (N=1819).
Variables BMI<24(n=1080) BMI≥24 (n=739) Systolic blood pressureβ(P-value) Diastolic blood pressureβ (P-value) Systolic blood pressureβ (P-value) Diastolic blood pressureβ (P-value) Age (years) 0.168(<0.001) — 0.191(<0.001) 0.191(<0.001) Education (0= Illiterate, 1= Less than elementary school, 2= High school, 3= Above vocational school) — -0.072(0.030) — — Marital status (0= Single,1= Married) -0.106(0.001) -0.084(0.013) -0.082(0.034) -0.082(0.034) Current residence (0= Rural,1= Urban) — — — — Smoke (0= NO,1= Former smoke,2= Current smoke) — — — — Drinking (0= NO,1= Less than once a month,2= More than once a month) — — — — Eating meals (0= ≤2 meals per day,1=3 meals per day,2= ≥4 meals per day) — -0.075(0.016) — — Taking activities (0= No,1= Yes) — — — — Ever been in major accidental injury (0= No,1= Yes) — — — — Having regular physical exercises (0= No physical exercise,1= Less than regular physical exercises,2= Regular physical exercises) — — — — History of CVD (0= No,1= Yes) — — — — History of liver diseases (0= No,1= Yes) — — — — Antilipidemic medication (0= No,1= Yes) — — — — Anti-diabetic medication (0= No,1= Yes) — — 0.138(0.001) 0.138(0.001) Anti-hypertensive therapy(0= No,1= Yes) 0.12(<0.001) — 0.129(0.001) 0.129(0.001) Fasting plasma glucose(mg/dl) — — — — LDL Cholesterol (mg/dl) — — — — HDL Cholesterol (mg/dl) — — — — eGFR(ml/min/1.73m2) — — — — Serum uric acid(mg/dl) 0.084(0.016) — — — Body mass index(kg/m2) 0.082(0.009) 0.086(0.008) — — Triglycerides (mg/dl) 0.078(0.025) — — — R2 0.119(<0.001) 0.046(0.001) 0.089(<0.001) 0.072(<0.001)Tables12 and 13 show the multivariate-adjusted relationship between various characteristics and BP status in participants categorized by age (< 68 years and ≥ 68 years). Multiple linear regression analysis showed that TG level was significantly and positively associated with SBP in women with age of < 68 years, independent of other confounding factors. In contrast, TG level was significantly associated with SBP in men with age of ≥ 68 years.Table 12
Multivariate-adjusted relationship between various characteristics and blood pressure status of participants categorized by age in male (N=1810).
Variables Age<68 years (n=807) Age≥68 years (n=1003) Systolic blood pressureβ(P-value) Systolic blood pressureβ(P-value) Systolic blood pressureβ(P-value) Systolic blood pressureβ(P-value) Age — — — -0.085(0.015) Education(0= Illiterate, 1= Less than elementary school, 2= High school, 3= Above vocational school) — — — — Marital status(0= Single,1= Married) 0.078(0.024) 0.1(0.004) 0.074(0.020) — Current residence(0= Rural,1= Urban) — — 0.105(0.002) 0.084(0.014) Smoke(0= NO,1= Former smoke,2= Current smoke) — — 0.078(0.016) — Drinking(0= NO,1= Less than once a month,2= More than once a month) — — — — Eating meals(0= ≤2 meals per day,1=3 meals per day,2= ≥4 meals per day) -0.070(0.039) -0.103(0.003) — -0.071(0.025) Taking activities(0= No,1= Yes) -0.077(0.027) — — — Ever been in major accidental injury(0= No,1= Yes) — — — — Having regular physical exercises(0= No physical exercise,1= Less than regular physical exercises,2= Regular physical exercises) — — — — History of CVD(0= No,1= Yes) — — — — History of liver diseases(0= No,1= Yes) — — — — Antilipidemic medication(0= No,1= Yes) — — — — Anti-diabetic medication(0= No,1= Yes) — -0.078(0.046) — — Anti-hypertensive therapy(0= No,1= Yes) 0.09(0.009) 0.090(0.010) 0.111(<0.001) 0.114(<0.001) Fasting plasma glucose(mg/dl) 0.09(0.022) — — — LDL Cholesterol (mg/dl) — — — — HDL Cholesterol (mg/dl) — — — — eGFR(ml/min/1.73m2) -0.078(0.040) — — — Serum uric acid(mg/dl) 0.088(0.024) 0.08(0.042) — — Body mass index(kg/m2) 0.229(<0.001) 0.213(<0.001) 0.137(<0.001) 0.105(0.003) Triglycerides (mg/dl) 0.024(0.545) 0.03(0.452) 0.096(0.009) 0.063(0.088) R2 0.136(<0.001) 0.115(<0.001) 0.087(<0.001) 0.065(<0.001)Table 13
Multivariate-adjusted relationship between various characteristics and blood pressure status of participants categorized by age in female (N=1819).
Variables Age <68 years(n=887) Age≥68 years(n=932) Systolic blood pressureβ(P-value) Systolic blood pressureβ(P-value) Systolic blood pressureβ(P-value) Systolic blood pressureβ(P-value) Age — — 0.105(0.005) — Education (0= Illiterate, 1= Less than elementary school, 2= High school, 3= Above vocational school) — — — — Marital status (0= Single,1= Married) 0.071(0.035) — 0.103(0.003) 0.071(0.043) Current residence (0= Rural,1= Urban) — — — — Smoke (0= NO,1= Former smoke,2= Current smoke) — — — — Drinking (0= NO,1= Less than once a month,2= More than once a month) — — — — Eating meals (0= ≤2 meals per day,1=3 meals per day,2= ≥4 meals per day) — -0.08(0.015) — — Taking activities (0= No,1= Yes) — — — — Ever been in major accidental injury (0= No,1= Yes) — — — — Having regular physical exercises (0= No physical exercise,1= Less than regular physical exercises,2= Regular physical exercises) — — — — History of CVD (0= No,1= Yes) — — — -0.069(0.048) History of liver diseases (0= No,1= Yes) — — — -0.076(0.023) Antilipidemic medication (0= No,1= Yes) — — — — Anti-diabetic medication (0= No,1= Yes) 0.105(0.004) — — — Anti-hypertensive therapy (0= No,1= Yes) 0.085(0.012) — 0.153(<0.001) 0.089(0.008) Fasting plasma glucose (mg/dl) — 0.128(<0.001) — — LDL Cholesterol (mg/dl) — — — — HDL Cholesterol (mg/dl) — — — — eGFR (ml/min/1.73m2) — — — — Serum uric acid (mg/dl) — — — — Body mass index (kg/m2) 0.11(0.003) 0.23(<0.001) 0.097(0.007) 0.105(0.004) Triglycerides (mg/dl) 0.087(0.031) 0.056(0.159) 0.046(0.270) 0.072(0.090) R2 0.087(<0.001) 0.110(<0.001) 0.079(<0.001) 0.057(<0.001)Table14 shows the interaction between BMI and TG level and BP status in men and women. A general linear model with the following confounding factors (age, educational level, marital status, current residence, smoking, eating habits, taking activities, antidiabetic medication, antihypertensive therapy, FPG, LDL-C, eGFR, and SUA) was used to assess the statistical significance of the synergistic relationship between BMI and SUA level. Evidence of interaction between BMI and SUA level on SBP (men, β = 0.572,P = 0.845; women, β = 0.122, andP= 0.923) and DBP (men, β = -0.373,P= 0.810; women, β = 0.272, andP= 0.828) levels was not observed.Table 14
Interaction between body mass index and uric acid on blood pressure status in male and female (N=3629).
Characteristics Male(n=1810) Female(n=1819) Systolic blood pressureβ(P-value) Diastolic blood pressureβ(P-value) Systolic blood pressureβ(P-value) Diastolic blood pressureβ(P-value) Age(years) 0.337(0.001) -0.240(<0.001) -0.092(0.042) -0.113(0.013) Education(0= Illiterate, 1= Less than elementary school, 2= High school, 3= Above vocational school) — — — -1.119(0.019) Marital status(0= Single,1= Married) -5.660(0.001) -2.494(0.004) -1.503(0.024) -1.453(0.029) Current residence(0= Rural,1= Urban) 3.574(0.003) — — — Smoke(0= NO,1= Former smoke,2= Current smoke) 1.864(0.005) — — — Eating meals(0=≤2 meals per day,1=3 meals per day,2= ≥4 meals per day) 2.978(0.045) 2.483(0.002) — 2.193(0.003) Taking activities(0= No,1= Yes) — — — — Anti-diabetic medication(0= No,1= Yes) — — — — Anti-hypertensive therapy(0= No,1= Yes) 10.228(<0.001) 5.745(<0.001) 3.292(0.003) — Fasting plasma glucose(mg/dl) 0.039(0.011) — — — LDL Cholesterol (mg/dl) 0.049(0.004) — — — eGFR(ml/min/1.73m2) -0.123(0.003) — — — Serum uric acid(mg/dl) 0.948(0.047) — — — Body mass index -8.004(0.002) -4.125(0.002) -3.668(<0.001) -4.102(<0.001) Triglycerides -3.962(0.076) -1.482(0.203) -2.140(0.017) -2.319(0.009) Body mass index∗ Triglycerides 0.572(0.845) -0.373(0.810) 0.122(0.923) 0.272(0.828)Table15 shows the interaction between BMI and TG on BP status of participants categorized by age in men and women. A general linear model with the following confounding factors (age, educational level, marital status, current residence, smoking, eating habits, activity, physical activity, antilipidemic medication, antidiabetic medication, antihypertensive therapy, FPG, eGFR, and SUA) was used to assess the statistical significance of the synergistic relationship between BMI and SUA level. Evidence of interaction between BMI and SUA level on SBP (men with age of < 68 years, β = -1.075, andP = 0.760; men with age of ≥ 68 years, β = 2.138, andP = 0.654; women with age of < 68 years, β = -1.345, andP= 0.718; women with age of ≥ 68 years, β = -4.192, andP = 0.334) and DBP (men with age of < 68 years, β = -0.095, andP = 0.964; men with age of ≥ 68 years, β = -0.931, andP = 0.691; women with age of < 68 years, β = 2.410,P= 0.170; women with age of ≥ 68 years β = -3.386, andP = 0.439) was not observed.Table 15
Interaction between body mass index and uric acid on blood pressure status of participants categorized by age in male and female (N=3629).
Characteristics Age <68 years(n=807) Age≥68 years(n=1003)  Male Systolic blood pressureβ(P-value) Diastolic blood pressureβ(P-value) Systolic blood pressureβ(P-value) Diastolic blood pressureβ(P-value)  Marital status (0= Single,1= Married) -6.913(0.009) -5.237(0.001) -5.876(0.007) Current residence (0= Rural,1= Urban)   5.232(0.004) 2.164(0.015) Smoke (0= NO,1= Former smoke,2= Current smoke)   1.917(0.05) Eating meals (0= ≤2 meals per day,1=3 meals per day,2= ≥4 meals per day) 3.746(0.058) 3.227(0.006)  2.239(0.036) Taking activities (0= No,1= Yes) -2.747(0.057) Antilipidemic medication (0= No,1= Yes)  -1.651(0.423) Anti-hypertensive therapy (0= No,1= Yes) 9.032(0.002) 5.343(0.002) 11.982(<0.001) 6.384(<0.001) Fasting plasma glucose (mg/dl) 0.040(0.030) eGFR (ml/min/1.73m2) -0.122(0.024) Serum uric acid(mg/dl) 1.454(0.022) 0.957(0.006) Body mass index -8.409(0.006) -4.837(0.008) -8.347(0.048) -3.042(0.142) Triglycerides -0.135(0.958) -0.587(0.695) -7.960(0.035) -1.478(0.427) Body mass index∗ Triglycerides -1.075(0.760) -0.095(0.964) 2.138(0.654) -0.931(0.691)  Female Age <68 years(n=887) Age≥68 years(n=932) Systolic blood pressureβ(P-value) Diastolic blood pressureβ(P-value) Systolic blood pressureβ(P-value) Diastolic blood pressureβ(P-value)  Age — — 0.626(0.001) — Education (0= Illiterate, 1= Less than elementary school, 2= High school, 3= Above vocational school) — — — — Marital status (0= Single,1= Married) 5.866(0.012) — 5.481(0.007) 7.504(<0.001) Eating meals (0= ≤2 meals per day,1=3 meals per day,2= ≥4 meals per day) — 2.821(0.009) — — History of CVD (0= No,1= Yes) — — — -3.837(0.123) Antilipidemic medication (0= No,1= Yes) — — — — Anti-diabetic medication (0= No,1= Yes) 11.822(0.002) — — — Anti-hypertensive therapy (0= No,1= Yes) 8.946(0.006) — 17.459(<0.001) 17.254(<0.001) Fasting plasma glucose (mg/dl) — 0.035(<0.001) — Body mass index -5.696(0.062) -6.621(<0.001) -4.726(0.187) -5.152(0.155) Triglycerides -4.716(0.063) -2.716(0.024) -1.573(0.622) -2.147(0.507) Body mass index∗ Triglycerides -1.345(0.718) 2.410(0.170) -4.192(0.334) -3.386(0.439)Table16 shows relationships between BMI or TG level and hypertension in men and women. After adjusting for age, educational level, marital status, current residence, smoking, drinking, eating habits, activity, major accidental injury, physical activity, history of CVD, history of liver disease, antilipidemic medication, antidiabetic medication, antihypertensive therapy, FPG, LDL-C, HDL-C, eGFR, and SUA, compared with their counterparts with BMI < 24.0 kg/m2, both elderly men and women with a BMI ≥ 24.0 kg/m2 were more likely to have high BP (men: odds ratio [OR] = 1.781, 95% confidence interval [CI] = 1.393–2.277; women: OR = 1.653, 95% CI = 1.330–2.055). Among women, compared to those with TG < 150 mg/dL, individuals with a high TG level were more likely to have high BP (OR = 1.558, 95% CI = 1.219–1.992).Table 16
Adjusting ORs and 95%CI for BMI or TG and hypertension in male and female.
Male Female BMI and hypertension TG and hypertension BMI and hypertension TG and hypertension OR 95 % CI P OR 95 % CI P OR 95 % CI P OR 95 % CI P Age(years) 1.027 (1.007,1.047) 0.007 1.021 (1.002,1.041) 0.029 1.056 (1.037,1.076) <0.001 1.054 (1.035,1.073) <0.001 education Illiterate 1.000   1.000   1.000   1.000 Less than elementary school 1.066 (0.817,1.391) 0.636 1.086 (0.834,1.415) 0.538 0.875 (0.703,1.088) 0.229 0.876 (0.705,1.089) 0.233 High school 0.649 (0.271,1.553) 0.331 0.662 (0.279,1.567) 0.348 0.169 (0.037,0.777) 0.022 0.178 (0.038,0.823) 0.027 Above vocational school 0.817 (0.493,1.352) 0.431 0.837 (0.508,1.379) 0.485 0.671 (0.304,1.484) 0.325 0.704 (0.319,1.557) 0.387 Marital status Single 1.000   1.000   1.000   1.000 Married 0.693 (0.515,0.933) 0.016 0.726 (0.540,0.975) 0.033 0.833 (0.660,1.052) 0.126 0.854 (0.676,1.077) 0.183 Current residence Urban 1.000   1.000   1.000   1.000 Rural 1.281 (1.021,1.608) 0.033 1.327 (1.058,1.663) 0.014 1.028 (0.826,1.278) 0.807 1.057 (0.851,1.314) 0.616 Smoke NO smoke 1.000   1.000   1.000   1.000 Former smoke 0.892 (0.660,1.204) 0.454 0.906 (0.672,1.221) 0.518 0.914 (0.523,1.599) 0.753 0.844 (0.482,1.476) 0.551 Current smoke 1.309 (1.019,1.682) 0.035 1.235 (0.964,1.582) 0.095 1.155 (0.810,1.648) 0.427 1.106 (0.777,1.573) 0.577 Drinking NO 1.000   1.000   1.000   1.000 Less than once a month 1.030 (0.823,1.289) 0.796 1.051 (0.841,1.313) 0.663 1.060 (0.733,1.533) 0.758 1.045 (0.722,1.513) 0.814 More than once a month 1.134 (0.772,1.665) 0.523 1.141 (0.780,1.671) 0.496 0.696 (0.416,1.164) 0.167 0.716 (0.429,1.196) 0.202 Eating meals ≤2 meals per day 1.000   1.000   1.000   1.000 3 meals per day 0.898 (0.381,2.117) 0.806 0.832 (0.355,1.953) 0.673 0.777 (0.328,1.837) 0.565 0.782 (0.330,1.851) 0.575 ≥4 meals per day 0.658 (0.494,0.875) 0.004 0.682 (0.513,0.906) 0.008 0.983 (0.739,1.308) 0.909 1.050 (0.790,1.396) 0.737 Taking no activities No 1.000   1.000   1.000   1.000 Yes 0.916 (0.744,1.127) 0.407 0.930 (0.756,1.142) 0.487 1.021 (0.834,1.250) 0.840 1.035 (0.846,1.266) 0.738 Ever been in major accidental injury NO 1.000   1.000   1.000   1.000 Yes 0.746 (0.535,1.041) 0.085 0.754 (0.542,1.049) 0.094 0.864 (0.584,1.279) 0.4660 0.871 (0.588,1.290) 0.491 Having regular physical exercises No physical exercise 1.000   1.000   1.000   1.000 Less than regular physical exercises 1.199 (0.927,1.550) 0.168 1.220 (0.945,1.576) 0.127 0.975 (0.748,1.270) 0.849 0.959 (0.736,1.250) 0.756 Regular physical exercises 1.282 (0.972,1.690) 0.079 1.292 (0.981,1.701) 0.068 0.919 (0.705,1.197) 0.530 0.922 (0.708,1.201) 0.546 History of CVD NO 1.000   1.000   1.000   1.000 Yes 1.170 (0.869,1.575) 0.300 1.247 (0.930,1.673) 0.141 0.982 (0.750,1.286) 0.896 0.986 (0.753,1.290) 0.916 History of liver diseases NO 1.000   1.000   1.000   1.000 Yes 0.640 (0.369,1.110) 0.112 0.654 (0.379,1.129) 0.128 0.795 (0.466,1.355) 0.399 0.837 (0.491,1.429) 0.515 Antilipidemic medication NO 1.000   1.000   1.000   1.000 Yes 0.984 (0.601,1.612) 0.949 1.027 (0.629,1.679) 0.914 1.711 (1.127,2.596) 0.012 1.783 (1.177,2.701) 0.006 Anti-diabetic medication NO 1.000   1.000   1.000   1.000 Yes 0.549 (0.312,0.965) 0.037 0.586 (0.334,1.030) 0.063 1.421 (0.846,2.387) 0.184 1.540 (0.919,2.581) 0.101 Anti-hypertensive therapy NO 1.000   1.000   1.000   1.000 Yes 2.448 (1.635,3.665) <0.001 2.522 (1.690,3.766) <0.001 2.097 (1.416,3.105) <0.001 2.154 (1.457,3.186) <0.001 Fasting plasma glucose(mg/dl) 1.005 (1.002,1.008) <0.001 1.005 (1.002,1.008) 0.001 1.004 (1.001,1.007) 0.005 1.004 (1.001,1.006) 0.017 LDL Cholesterol (mg/dl) 1.004 (1.001,1.007) 0.014 1.004 (1.001,1.008) 0.004 1.001 (0.998,1.004) 0.585 1.001 (0.999,1.004) 0.316 HDL Cholesterol (mg/dl) 0.998 (0.991,1.005) 0.614 0.995 (0.988,1.002) 0.158 0.997 (0.990,1.004) 0.383 0.999 (0.991,1.006) 0.708 Egfr (ml/min/1.73m2) 0.993 (0.986,1.001) 0.089 0.993 (0.986,1.001) 0.091 0.998 (0.990,1.005) 0.566 0.997 (0.990,1.005) 0.455 Serum uric acid(mg/dl) 1.160 (1.064,1.265) 0.001 1.175 (1.077,1.282) <0.001 1.122 (1.017,1.238) 0.022 1.118 (1.013,1.234) 0.027 Body mass index (kg/m2) BMI <24 1.000      1.000 BM I≥24 1.781 (1.393,2.277) <0.001    1.653 (1.330,2.055) <0.001 Triglycerides (mg/dl) <150    1.000      1.000 ≥150    1.169 (0.882,1.548) 0.277    1.558 (1.219,1.992) <0.001Tables17 and 18 show relationships between BMI or TG and hypertension categorized by age in men and women. After adjusting for age, educational level, marital status, current residence, smoking, drinking, eating habits, taking activities, major accidental injury, physical activity, history of CVD, history of liver disease, antilipidemic medication, antidiabetic medication, antihypertensive therapy, FPG, LDL-C, HDL-C, eGFR, and SUA, compared to individuals with a BMI < 24.0 kg/m2, both elderly men and women with a BMI ≥ 24.0 kg/m2 were more likely to have high BP (men with age of < 68 years, OR=1.805, and 95% CI=1.249-2.610; men with age of ≥ 68 years, OR = 1.796, and 95% CI = 1.275–2.529; women with age of < 68 years, OR = 1.936, and 95% CI = 1.404–2.668; women with age of ≥ 68 years, OR = 1.506, and 95% CI = 1.108–2.047). Among women, compared to those with TG < 150 mg/dL, individuals with a high TG level were more likely to have high BP (women with age of < 68 years, OR = 1.629, and 95% CI = 1.149–2.309; women with age of ≥ 68 years, OR = 1.596, and 95% CI = 1.113–2.288).Table 17
Adjusting ORs and 95%CI for BMI or TG and hypertension categorized by age in male.
Age <68 years (n=807) Age≥68 years (n=1003) BMI and hypertension TG and hypertension BMI and hypertension TG and hypertension OR 95 % CI P OR 95 % CI P OR 95 % CI P OR 95 % CI P Age(years) 1.009 (0.937,1.088) 0.806 1.006 (0.934,1.083) 0.877 1.021 (0.988,1.055) 0.212 1.015 (0.982,1.048) 0.383 education Illiterate 1.000   1.000   1.000   1.000 Less than elementary school 0.805 (0.487,1.330) 0.397 0.850 (0.516,1.401) 0.523 1.171 (0.852,1.609) 0.330 1.182 (0.862,1.621) 0.299 High school 1.212 (0.353,4.157) 0.760 1.201 (0.352,4.092) 0.770 0.303 (0.080,1.158) 0.081 0.321 (0.086,1.207) 0.093 Above vocational school 0.687 (0.288,1.641) 0.399 0.749 (0.316,1.774) 0.511 0.809 (0.424,1.543) 0.519 0.802 (0.423,1.521) 0.499 Marital status Single 1.000   1.000   1.000   1.000 Married 0.501 (0.283,0.885) 0.017 0.548 (0.311,0.967) 0.038 0.762 (0.535,1.085) 0.132 0.785 (0.552,1.116) 0.177 Current residence Urban 1.000   1.000   1.000   1.000 Rural 1.183 (0.834,1.680) 0.346 1.244 (0.880,1.759) 0.216 1.413 (1.037,1.925) 0.028 1.459 (1.072,1.986) 0.016 Smoke NO smoke 1.000   1.000   1.000   1.000 Former smoke 0.894 (0.538,1.486) 0.666 0.897 (0.541,1.486) 0.672 0.905 (0.617,1.327) 0.609 0.927 (0.634,1.356) 0.696 Current smoke 1.337 (0.893,2.000) 0.158 1.219 (0.820,1.810) 0.327 1.322 (0.953,1.836) 0.095 1.274 (0.921,1.763) 0.144 Drinking NO 1.000   1.000   1.000   1.000 Less than once a month 0.971 (0.681,1.386) 0.873 0.996 (0.699,1.418) 0.980 1.049 (0.778,1.413) 0.755 1.064 (0.791,1.431) 0.681 More than once a month .908 (0.504,1.636) 0.747 0.918 (0.512,1.645) 0.774 1.459 (0.863,2.469) 0.159 1.469 (0.872,2.475) 0.148 Eating meals ≤2 meals per day 1.000   1.000   1.000   1.000 3 meals per day 0.093 (0.011,0.803) 0.031 0.090 (0.011,0.756) 0.027 3.274 (0.921,11.630) 0.067 3.131 (0.884,11.09) 0.077 ≥4 meals per day 0.624 (0.396,0.983) 0.042 0.644 (0.408,1.016) 0.058 0.657 (0.452,0.955) 0.028 0.684 (0.472,0.992) 0.045 Taking no activities No 1.000   1.000   1.000   1.000 Yes 0.748 (0.541,1.035) 0.080 0.764 (0.554,1.054) 0.101 1.053 (0.798,1.389) 0.717 1.065 (0.808,1.403) 0.657 Ever been in major accidental injury NO 1.000   1.000   1.000   1.000 Yes 0.640 (0.363,1.128) 0.122 0.606 (0.344,1.065) 0.082 0.781 (0.510,1.197) 0.256 0.809 (0.530,1.234) 0.325 Having regular physical exercises No physical exercise 1.000   1.000   1.000   1.000 Less than regular physical exercises 0.959 (0.626,1.468) 0.846 0.978 (0.641,1.494) 0.919 1.397 (1.000,1.952) 0.050 1.418 (1.017,1.978) 0.039 Regular physical exercises 1.185 (0.776,1.809) 0.432 1.225 (0.805,1.864) 0.344 1.432 (0.983,2.084) 0.061 1.422 (0.978,2.066) 0.065 History of CVD NO 1.000   1.000   1.000   1.000 Yes 1.355 (0.821,2.238) 0.235 1.478 (0.902,2.424) 0.121 1.063 (0.725,1.557) 0.755 1.132 (0.777,1.650) 0.518 History of liver diseases NO 1.000   1.000   1.000   1.000 Yes 0.630 (0.283,1.399) 0.256 .624 (0.283,1.378) 0.244 0.595 (0.270,1.309) 0.197 0.640 (0.293,1.395) 0.261 Antilipidemic medication NO 1.000   1.000   1.000   1.000 Yes 1.135 (0.568,2.269) 0.720 1.142 (0.574,2.273) 0.706 0.861 (0.407,1.821) 0.695 0.911 (0.433,1.902) 0.807 Anti-diabetic medication NO 1.000   1.000   1.000   1.000 Yes 0.476 (0.194,1.173) 0.107 0.520 (0.210,1.285) 0.156 0.655 (0.308,1.393) 0.272 0.683 (0.323,1.447) 0.320 Anti-hypertensive therapy NO 1.000   1.000   1.000   1.000 Yes 2.277 (1.242,4.174) 0.008 2.299 (1.258,4.202) 0.007 2.681 (1.536,4.681) 0.001 2.748 (1.577,4.791) <0.001 Fasting plasma glucose(mg/dl) 1.004 (1.000,1.008) 0.075 1.004 (1.000,1.009) 0.071 1.007 (1.002,1.011) 0.003 1.006 (1.002,1.011) 0.005 LDL Cholesterol (mg/dl) 1.007 (1.003,1.011) 0.002 1.008 (1.003,1.012) 0.001 1.001 (0.996,1.005) 0.817 1.001 (0.997,1.005) 0.655 HDL Cholesterol (mg/dl) 0.993 (0.982,1.004) 0.227 0.989 (0.977,1.000) 0.053 1.002 (0.993,1.011) 0.691 0.998 (0.989,1.008) 0.743 eGFR(ml/min/1.73m2) 0.987 (0.976,0.999) 0.040 0.988 (0.976,1.000) 0.048 0.998 (0.988,1.008) 0.692 0.998 (0.988,1.008) 0.682 Serum uric acid(mg/dl) 1.171 (1.020,1.344) 0.025 1.184 (1.028,1.364) 0.019 1.185 (1.056,1.331) 0.004 1.205 (1.074,1.353) 0.002 Body mass index(kg/m2) BMI<24 1.000      1.000 BMI≥24 1.805 (1.249,2.610) 0.002    1.796 (1.275,2.529) 0.001 Triglycerides (mg/dl) <150    1.000      1.000 ≥150    1.140 (0.754,1.722) 0.535    1.098 (0.733,1.643) 0.651Table 18
Adjusting ORs and 95%CI for BMI or TG and hypertension categorized by age in female.
Age <68 years (n=807) Age≥68 years (n=1003) BMI and hypertension TG and hypertension BMI and hypertension TG and hypertension OR 95 % CI P OR 95 % CI P OR 95 % CI P OR 95 % CI P Age(years) 1.077 (1.008,1.105) 0.029 1.071 (1.003,1.144) 0.040 1.055 (1.022,1.089) 0.001 1.053 (1.020,1.087) 0.001 education Illiterate 1.000   1.000   1.000   1.000 Less than elementary school 0.807 (0.596,1.093) 0.166 0.803 (0.593,1.087) 0.155 0.966 (0.698,1.337) 0.834 0.972 (0.702,1.345) 0.863 High school 0.231 (0.027,1.980) 0.181 0.277 (0.032,2.410) 0.245 0.121 (0.014,1.046) 0.055 0.116 (0.013,1.003) 0.050 Above vocational school 0.798 (0.227,2.805) 0.725 0.820 (0.239,2.809) 0.752 0.668 (0.234,1.907) 0.451 0.726 (0.252,2.086) 0.552 Marital status Single 1.000   1.000   1.000   1.000 Married 0.681 (0.457,1.017) 0.060 0.717 (0.482,1.066) 0.100 0.891 (0.663,1.196) 0.441 0.904 (0.674,1.214) 0.502 Current residence Urban 1.000   1.000   1.000   1.000 Rural 1.118 (0.810,1.543) 0.499 1.191 (0.864,1.643) 0.286 1.003 (0.739,1.362) 0.984 1.009 (0.743,1.369) 0.955 Smoke NO smoke 1.000   1.000   1.000   1.000 Former smoke 2.322 (0.771,6.998) 0.134 2.228 (0.743,6.681) 0.153 0.715 (0.367,1.391) 0.323 0.649 (0.333,1.267) 0.206 Current smoke 1.502 (0.905,2.494) 0.116 1.383 (0.840,2.277) 0.203 0.888 (0.535,1.473) 0.644 0.858 (0.517,1.424) 0.553 Drinking NO 1.000   1.000   1.000   1.000 Less than once a month 0.917 (0.518,1.622) 0.765 0.963 (0.547,1.695) 0.896 1.107 (0.668,1.837) 0.693 1.057 (0.635,1.758) 0.831 More than once a month 0.938 (0.464,1.897) 0.859 0.894 (0.443,1.803) 0.755 0.508 (0.235,1.100) 0.086 0.559 (0.257,1.214) 0.142 Eating meals ≤2 meals per day 1.000   1.000   1.000   1.000 3 meals per day 0.843 (0.264,2.689) 0.773 0.861 (0.269,2.754) 0.800 0.637 (0.176,2.302) 0.492 0.646 (0.179,2.332) 0.505 ≥4 meals per day 0.744 (0.486,1.140) 0.174 0.801 (0.524,1.225) 0.306 1.213 (0.822,1.790) 0.330 1.297 (0.879,1.914) 0.190 Taking no activities No 1.000   1.000   1.000   1.000 Yes 0.950 (0.705,1.280) 0.737 0.984 (0.732,1.323) 0.917 1.117 (0.8400,1.486) 0.446 1.115 (0.838,1.482) 0.456 Ever been in major accidental injury NO 1.000   1.000   1.000   1.000 Yes 0.888 (0.491,1.604) 0.693 0.906 (0.501,1.639) 0.744 0.831 (0.485,1.423) 0.499 0.820 (0.477,1.408) .472 Having regular physical exercises No physical exercise 1.000   1.000   1.000   1.000 Less than regular physical exercises 1.037 (0.709,1.517) 0.852 1.024 (0.701,1.496) 0.904 0.851 (0.581,1.246) 0.407 0.826 (0.564,1.210) .327 Regular physical exercises 0.978 (0.669,1.432) 0.911 0.953 (0.652,1.393) 0.804 0.924 (0.627,1.361) 0.688 0.944 (0.640,1.391) .770 History of CVD NO 1.000   1.000   1.000   1.000 Yes 1.563 (1.062,2.300) 0.023 1.586 (1.079,2.331) 0.019 0.640 (0.435,0.942) 0.023 0.640 (0.435,0.940) 0.023 History of liver diseases NO 1.000   1.000   1.000   1.000 Yes 1.100 (0.495,2.446) 0.815 1.190 (0.533,2.654) 0.671 0.645 (0.309,1.345) 0.242 0.671 (0.322,1.398) 0.286 Antilipidemic medication NO 1.000   1.000   1.000   1.000 Yes 1.487 (0.869,2.544) 0.148 1.587 (0.930,2.708) 0.090 2.127 (1.051,4.301) 0.036 2.174 (1.082,4.368) 0.029 Anti-diabetic medication NO 1.000   1.000   1.000   1.000 Yes 1.613 (0.806,3.229) 0.177 1.728 (0.865,3.454) 0.122 1.318 (0.594,2.925) 0.498 1.429 (0.648,3.147) 0.376 Anti-hypertensive therapy NO 1.000   1.000   1.000   1.000 Yes 2.039 (1.187,3.502) 0.010 2.031 (1.185,3.479) 0.010 2.260 (1.241,4.113) 0.008 2.409 (1.321,4.396) 0.004 Fasting plasma glucose(mg/dl) 1.003 (1.000,1.007) 0.077 1.003 (0.999,1.007) 0.108 1.005 (1.001,1.009) 0.027 1.004 (1.000,1.008) 0.081 LDL Cholesterol (mg/dl) 0.999 (0.995,1.003) 0.686 1.000 (0.996,1.004) 0.836 1.002 (0.998,1.006) 0.331 1.002 (0.998,1.006) 0.245 HDL Cholesterol (mg/dl) 0.997 (0.986,1.008) 0.629 0.998 (0.986,1.010) 0.745 0.995 (0.985,1.005) 0.344 0.998 (0.987,1.008) 0.688 eGFR(ml/min/1.73m2) 1.001 (0.990,1.012) 0.845 1.001 (0.990,1.012) 0.922 0.996 (0.985,1.006) 0.436 0.995 (0.984,1.005) 0.331 Serum uric acid(mg/dl) 1.132 (0.979,1.310) 0.095 1.117 (0.965,1.294) 0.137 1.103 (0.961,1.265) 0.163 1.099 (0.958,1.262) 0.179 Body mass index(kg/m2) BMI<24 1.000      1.000 BMI≥24 1.936 (1.404,2.668) <0.001    1.506 (1.108,2.047) 0.009 Triglycerides (mg/dl) <150    1.000      1.000 ≥150    1.629 (1.149,2.309) 0.006    1.596 (1.113,2.288) 0.011


## 4. Discussion

The effects of BMI and TG level on BP varied in elderly individuals. In the present study, we determined the prevalence of hypertension and its association with BMI and TG level. Our findings show that the prevalence of hypertension was 36.91% (668/1810) in men, 43.82% (797/1819) in women, and 40.37% (1465/3629) overall. After stratification by age, the prevalence of hypertension was 39.20% (481/1227) in men (age ≥ 65 years), 49.91% (576/1154) in women (age ≥ 65 years), and 44.39% (1057/2381) overall. In a sample collected from the Korea National Health and Nutrition Examination Survey (2007) in the elderly Korean population (age ≥ 65 years)[35], the prevalence of hypertension was 62.0%; the prevalence of hypertension in the Japan Gerontological Evaluation Survey[36], conducted in a population aged 65 or older, was 59.54%. The prevalence of hypertension in our study was lower than that observed in the Korean and Japanese studies. Moreover, men with hypertension had a higher prevalence of risk factors, such as age, marital status, eating habits, FPG, LDL-C, TG, eGFR, BMI, and SUA level, than those with normotension. Age, marital status, antilipidemic medication, FPG, TG, eGFR, and SUA level were significantly associated with BP among women. Furthermore, TG levels were positively associated with SBP and DBP in men with BMI < 24 kg/m2; however, TG levels were positively associated with both SBP and DBP in women with a BMI < 24 kg/m2 and also positively associated with DBP in women with a BMI ≥ 24 kg/m2.Studies [37, 38] have explored the association and/or interaction analysis between BMI and SUA level and BP. Lyngdoh et al. [37] reported that adiposity substantially decreased the association between SUA level and BP in young adults, and BP was independently associated with SUA level in women. Kawamoto et al. [38] concluded that BMI changes the association between SUA level and BP status among community-dwelling men. In other studies [39, 40], the association of TG and SUA levels has been persistent after full adjustment in a multiple logistic model, suggesting that TG levels correlate independently with SUA level, with TG levels having the most influence on SUA. However, there were no previous studies on the interactive effect between BMI and TG level on BP.As our general linear models adjusting for 13 related potential confounders showed, interaction between BMI and TG on BP was not observed. In our investigation of the relationships between BMI or TG and hypertension, we made several observations. First, we found that overweight and obese men and women were more likely to have hypertension. We also observed that women with high TG were more likely to experience hypertension. Thirdly, no association between TG and hypertension was found in men. Lastly, the relative results in relations between BMI or TG and hypertension categorized by age in both men and women are the same as those above. Furthermore, age differences in relations between BMI or TG and hypertension were found. Specifically, individuals with age ≥ 68 years experienced lower effects of BMI or TG level on BP. Similar evidence has been found in Brazil, in a study based on 287 men and women aged between 18 and 88 years, in which Pimenta [41] found that central obesity and TG level were independent risk factors for hypertension according to multivariate analysis. However, several studies have reported divergent findings regarding the association between obesity and hypertension. Some studies have suggested an increased risk of hypertension with higher BMI, waist circumference (WC), and waist-to-hip ratio (WHR) [42, 43], whereas other studies found that the association was not significant [44–46]. Zhou [47] conducted the first meta-analysis of cohort studies to quantify the relationship between obesity and the incidence of hypertension and found a positive association between the risk of hypertension and BMI, WC, and WHR. Arabshahi [48] conducted the first meta-analysis of cross-sectional studies to investigate the relationship between BMI or WC and hypertension, and concluded that the risk of hypertension was associated with adiposity. Jayedi [49] conducted a meta-analysis of prospective cohort studies to report the risk estimates of hypertension for abdominal adiposity (BMI, WC, and WHR) and found that the risk of hypertension increased with a somewhat steeper trend with increasing BMI, in comparison with WC and WHR. Such discrepancies between our findings and the null studies may be a result of methodological differences in design, measurement of obesity, and populations. Moreover, TG level has been associated with BP since TG level itself can cause endothelial dysfunction [24, 25], arterial stiffness [26], and the loss of vasomotor reactivity [27]. Such pathophysiology induced by increased TG and FPG levels and low HDL-C level may be greater than that of SUA. To explore the extent of the effects of TG level on blood pressure, we controlled for SUA and the related confounders, such as LDL-C and HDL-C [38]. The findings showed that TG level and hypertension were observed in women, but no independent effect was observed in men. Sanchez-Inigo [50] conducted a cohort study to identify the association of TG with the incidence of hypertension in Spain and found that the incidence of hypertension was associated with TG level in both men and women independent of adiposity. Tohidi [51] found that high TG independently predicted incidence of hypertension in Middle Eastern women.The mechanisms that lead to hypertension in participants with high BMI or TG levels have not been completely understood. Current studies may provide insight into the pathogenic mechanisms of BMI/TG that induce hypertension. The present study suggests that TG level may play an important role in hypertension in women. We speculate that sex-specific factors may also play an important role. TG levels are higher in women than in men, which partially explains the underlying mechanism that accounts for sex difference based on hormone levels. Additionally, body fat, sex steroids, and their interaction in elderly participants may also be associated with hypertension. As an important sex hormone, estrogen may also affect BP. Elderly women have lower concentrations of estrogen, which may affect the level of TG and result in a smaller protective effect.


## 5. Strengths and Limitations of the Study

There are several limitations of our study. First, the association and interaction of BMI and serum TG on blood pressure become seriously more complex; we only consider the confounders as possible as we can, but there are some unknown factors. Secondly, the relationship should be studied prospectively. Our study investigated BP in the elderly participant through a cross-sectional study. Follow-up study was relatively short to comprehensively observe changes in the next step. Last, more research is needed to observe the result. Several strengths could be found in our study. Firstly, the study was based on a nationwide survey. Secondly, we conducted the analyses according to gender.


## 6. Conclusions

An interactive effect of BMI and TG level on BP was not observed in either men or women; however, independent effects of BMI on BP were observed in both men and women, and an association between TG level and hypertension was observed in women.



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*Source: 8934534-2018-11-22.xml*