Subject and design
A cross-sectional study was conducted. The medical records of 306 participants, who underwent a health check-up at the Health Examination Management Center of Third Xiangya Hospital from November 1, 2018, to August 31, 2019, were included. The inclusion criteria were males between 45 and 59 years old (WHO-recommended middle-aged group) underwent endothelial function examination. The exclusion criteria were symptomatic cardiovascular disease. The present study was conducted according to the principles expressed in the Declaration of Helsinki, and approved by the Ethics Committee of Third Xiangya Hospital. The consent form was signed by each participant.
Definitions And Measures
Systolic and diastolic blood pressure (SBP and DBP) was measured between 8 AM and 10 AM, following the guidelines from the American Health Association17. All measurements were conducted using an automatic digital BP monitor (Omron 9020). The participants were measured after a 10-minute rest period, with their feet straight upon the ground and their back and arm supported, and with the antecubital fossa at the level of the heart. The maximum cuff inflation was calculated by adding 30 mmHg to the pulse obliteration pressure, and the cuff was deflated at a constant rate of 2–4 mmHg per second. Venous blood was collected in the morning after overnight fasting. The serum samples were stored at 4 °C, and were subjected to testing (Hitachi 7170s autoanalyzer) within two days, according to the instruction of the analyzer. Fasting blood glucose (FBG), TG, and HDL-c were measured using the enzymatic method with the full-automatic biochemical analyser (Hitachi 7170s). The investigators chose to analyze five cardio-metabolic components of the metabolic syndrome as categorical risk factors: Body mass index (BMI), TG,HDL-c and FBG were categorized into three groups, according to the standards of the Guidelines for prevention and control of overweight and obesity in Chinese adults (2004), and the Guidelines on prevention and treatment of blood lipid abnormality in Chinese adults (2018): BMI (< 24༌24–28༌≥28 kg/m2), TG (< 1.70, 1.70–2.25, ≥ 2.26 mmol/L), HDL-c (< 1.04, 1.04–1.55, ≥ 1.55 mmol/L), FBG (< 6.1, 6.1-7.0, > 7.0 mmol/L or taking antidiabetic medication). Blood pressure was binary categorized as < 140/90 mmmHg, ≥ 140/90 mmHg/or taking antihypertensive medication.
Data concerning diet, physical activity and sleep quality on the past one year were extracted from the "self-rated health measurement scale in health check-up" recommended by the Chinese Health Management Association18. This questionnaire was designed and administered by medical professionals, who collected data on the previous year. Physical activity was defined as moderate-intensity aerobic exercise, including fast walking, running, bicycle riding, rope skipping and swimming. All participants were assigned to categories, according the activity frequency per week (0 time, 1–2 times, 3–5 times, and > 5 times) and average duration each time (0 minute, < 30 minutes, and ≥ 30 minutes). Subjective evaluation of sleep quality was categorized into levels of poor, medium and excellent, according to the their own state of difficulty of falling sleep, early awakening, dreaminess, easily awaken, and shortened sleep duration. The 12 diet items in the scale included common diet behavior and diet habits: Anticipating dinner party per week (1.≤1 time, 2. 2–3 times, 3. 4–5 times, and 4. ≥5 times); Midnight snack per week (1.never, 2. ≤1 time, and 3.>1 time); Three meals on time per week (1.everytime, 2.failed 2–3 times, and 3. failed > 3 times); Times of milk and alcoholic drink per week (1.never, 2. 1–2 times, 3. 3–5 times, and 4. ≥6 times); Fruit, eggs and legume product per week (1.≤2 times, 2. 3–5 times, and 3. ≥6 times); Vegetable per day (1.<100 g, 2. 100–200 g, 3. >200 g); Meat per day (1.<50 g, 2. 50–100 g, and 3. >100 g); Sugary beverage and coffee per week (1.never, 2. 1–2 times, and 3. ≥3 times).
ED was measured using the ENDOPATTM2000 device (Itamar Medical Ltd. Caesarea, Israel), which recorded the digital pulsatile volume changes without involving painful and risky invasive procedures. Micro-arterial tonometry signals were obtained from participants resting in the supine position in a quiet, temperature-controlled room after overnight fasting. Subjects were refrained from smoking and vigorous activity for 12 hours before the examination. Two finger probes were placed on one finger of each hand. The baseline pulse amplitude was recorded during the first five minutes, followed by the 5-minute induction of ischemia induced by inflating upper-arm blood pressure cuff to 60 mmHg above systolic BP, with the opposite arm serving as a control, and the occlusion of blood flow was confirmed by the reduction of the ENDOPAT tracing to zero. After five minutes, the cuff was deflated, and the pulsatile tracing was recorded for another five minutes. RHI was automatically calculated using the computer algorithm of the ratio of the hyperemia and baseline pulse amplitude after control-arm correction. RHI < 1.67 was defined as ED.
Exploratory Factor Analysis (EFA)
EFA was first used to explore the latent construct of diet on 50% randomly selected responders. Principal Component Analysis followed by orthogonal Varimax rotation was conducted to estimate the factor loading, and determine the category and component of latent variables. Items of food and dietary habit with absolute factor loading of ≥ 0.30 entered the corresponding latent variable group. Only latent variables constructed with three or more items could be selected for further analysis to reduce measurement errors.
Confirmatory Factor Analysis (CFA)
Another 50% responders were analyzed. CFA was introduced to test the underlying construction of the food groups, and verify the latent construct explored by EFA.
Structural Equation Model (SEM)
Path analysis and structural modeling approach were used. First, the conceptual model that specified the correlations among dependent and independent variables is shown in Fig. 1. The apriori paths emanating from the measured univariate and unmeasured latent variables potentially direct or indirect affecting RHI-measured ED were constructed. The possible two-way correlation that implied two factors that were mutually connected were also given consideration. The SEM was fitted by the Maximum Likelihood Estimation method, the goodness-of-fit of the CFA and SEM. The chi-squared test (X2), normed chi-square test (X2/df), root mean square error of approximation (RMSEA), goodness-of-fit statistic (GFI), the adjusted goodness-of-fit statistic (AGFI), and the comparative fit index (CFI) were also evaluated to guarantee that the proposed model can be used. All analyses were conducted using IBM SPSS Statistics 21.0 and Amos version 23.0. P-values < 0.05 were considered statistically significant.
Chi-square tests were used to compare the frequency distribution of categorical data for metabolic risk factors. The factor score for each dietary pattern were calculated by weighting the consumption of each food item with the corresponding factor loading, and summing the resulting values. Then, the comparison between two groups evaluated by the factor score were made using student t-test.