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

• Published in: BioMed research international 2018-01, Vol.2018 (2018), p.1-31
• Main Authors: Li, Hong, Guo, Lei-lei, Zhang, Li-li, Li, Jin-long, Zhang, Lin, Li, Dan
• Format: Article
• Language: English
• Subjects: Age; Aged; Aged, 80 and over; Alcohol; Analysis; Antidiabetics; Antihypertensives; Asians; Blood Glucose - metabolism; Blood pressure; Blood Pressure - physiology; Blood Pressure Determination - methods; Body mass; Body Mass Index; Body size; Body weight; Cardiovascular agents; Cardiovascular disease; Cardiovascular diseases; China; Cholesterol; Cholesterol, HDL - blood; Cholesterol, LDL - blood; Confidence intervals; Correlation analysis; Correlation coefficient; Correlation coefficients; Cross-Sectional Studies; Diabetes; Diabetes mellitus; Drugs; Eating behavior; Education; Epidermal growth factor receptors; Exercise; Female; Food habits; GDP; Geriatrics; Glomerular filtration rate; Gross Domestic Product; High density lipoprotein; Households; Humans; Hypertension; Hypertension - blood; Hypertension - metabolism; Hypertension - physiopathology; Hypoglycemic agents; Lipoproteins; Liver; Liver diseases; Longitudinal Studies; Low density lipoprotein; Low density lipoproteins; Male; Marital status; Mathematical analysis; Meals; Medical laboratories; Men; Middle Aged; Obesity; Obesity - blood; Obesity - metabolism; Obesity - physiopathology; Older people; Overweight; Physical activity; Physical fitness; Pressure effects; Regression analysis; Regression models; Residential density; Retirement; Risk factors; Smoking; Statistical analysis; Synergistic effect; Systematic review; Therapy; Triglycerides; Triglycerides - blood; Triglycerides - metabolism; Uric acid; Uric Acid - blood; Womens health
• ISSN: 2314-6133; 2314-6141
• DOI: 10.1155/2018/8934534

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 cardiova