The protective effects between combined healthy lifestyle factor as lifestyle score and the risk of CVD had evidence in previous studies, especially in American and
European race. However, it is unclear in Asia population whether adherence to healthy lifestyle score could further lead to the reduction in the lifetime risk of CVD and the magnitude of population attribution fraction of healthy lifestyle score on the incidence of CVD. Further, the non-weighted healthy lifestyle score assumed all lifestyle factors with the same magnitude of effect and potentially leaded to the misclassification bias. A demonstration of beneficial influence of weighted healthy lifestyle score from the reducing CVD risk has important clinical implication. Healthy lifestyle score from the recommendation of WCRF/AICR has been shown to
favorably influence of cancer risk but little evidence about CVD risk. Therefore, to exam the impact of a healthy lifestyle score from WCRF/ACIR on CVD risk is of particular interest. In addition, beside combined healthy lifestyle factors and healthy lifestyle score from WCRF/ACIR, healthy lifestyle score from American Heart Association namely Life's Simple 7 has been proposed the inverse association of CVD risk. However, we were particularly interested in the predictive performance of CVD among combined healthy lifestyle factors, healthy lifestyle score from
WCRF/AICR and Life's Simple 7. Finally, age as a potential effect modifier on the association between healthy lifestyle score and CVD has been studied in a secondary data but no validation in primary analysis. Further evidence was lack whether
targeting younger adult for primordial prevention of CVD would be more feasible compared with older adults in clinical studies.
Accordingly, the current study sought to assess whether a healthy lifestyle score, as captured by a combination of non-obesity BMI, healthy dietary quality, physical activity, non-smoking and adequate drinking is associated with CVD risk in a representative cohort of Taiwan adults from the Taiwanese Survey on Hypertension, Hyperglycemia, and Hyperlipidemia. Furthermore, we weighted each lifestyle factor according to its independent magnitude of effect on CVD and estimate the impact.
In additional, we evaluated the performance ability of different healthy lifestyle score on predicting the CVD risk.
Chapter Two：Materials and Method 2.1 Study design and participants
We conducted analyses in Taiwan’s Hypertensive, Hyperglycemia, Hyperlipidemia Survey, 2002. (Taiwan’s Triple High Survey, 2002,TwSHHH) 44, a prospective cohort of 6706 participants (age>= 15 years old )in 2002. The protocol was reviewed and approved by the Research Ethics Committee of National Taiwan University Hospital. The committee was organized under and operated in accordance with the Good Clinical Practice Guidelines (NTUH-REC Number: 201901103W [Institutional Review Board reference, IRB]). Taiwan’s Triple High Survey, 2002 was using face-to-face questionnaire interviews during March 11.2002 to August 10, 2002 and recruited 7578 random sample from Taiwan National Health Interview Survey.45-46 Participants enrolled in Taiwan’s Triple High Survey, 2002 provided information on medical history, lifestyle factors and blood drawing data. In 2007, the follow-up of the Triple High cohort was done again as Taiwan’s Triple High Survey, 2007. With the informed consent of eligible participants, the Taiwan's triple high cohort were linked to the National Health Insurance Research Database from January 1, 2000 to
December 31, 2015. The National Health Insurance program is a universal, single-payer, and compulsory health insurance system that covers 99% of the 23 million residents in Taiwan. The National Health Insurance included ambulatory care,
inpatient care, dental service, prescription drugs, registration file, and scrambled identification numbers released for public access and International Classification of Disease-9 and 10 (ICD-9 and ICD-10) codes of discharge diagnosed. In the current investigation, the Taiwan’s Triple High Survey, 2002 was used as baseline
information. All eligible participants in this study were excluded if prior to the enrollment date of 2002 Taiwan’s Triple High Survey (1) they hadn’t been 20 years old (2) they had pregnancy within 1 year (3) they had records of coronary artery disease and ischemic stroke from National Health Insurance (4) their identical numbers linking to Taiwan National Health Interview Survey or National Health Insurance Research Database were missing.
2.2 Assessment of health lifestyle factors
We considered five lifestyle factors: ideal body mass index (BMI) (table 2), alternative Mediterranean diet pattern (table 3), achievement of the physical active goal (table 4), non-smoking status (table 5), and healthy alcohol consumption (table 6). BMI was calculated as weight in kilograms divided by the square of height in meters from self-reported data in 2002 but the measurement from trained
questionnaire staff in 2007 and categorized as non-obesity (BMI < 27) and obesity (BMI≧27) according to Taiwan Recommendation (table 2). Data used to generate the
healthy diet patterns were derived from a simplified food frequency questionnaire with 20 items of food. We used the alternative Mediterranean diet score as our healthy dietary score. The alternative Mediterranean diet included 11 of the 17 primary
criteria contained in the Mediterranean dietary score (table 3): fresh vegetables, legumes, fresh fruits, dairy products (milk, goat's milk, fermented milk, cheese, yogurt, Yakult), grains (rice or noodle), meat (beef, pork, goat, chicken), fish, eggs, sweets (cookies, candies, chocolate, cakes, bread, ice cream, milkshake), nonalcoholic beverages (cola, soda or sweet-beverage), saturated lipid (burger, French frizzed, pizza). The alternative Mediterranean diet score was calculated by the frequency of intake and summed across all 11 components. Participants with an alternative Mediterranean diet score less than 6 points were assigned to non-adherence of
alternative Mediterranean diet as zero point. Those with an alternative Mediterranean diet score of six or more than six points were assigned to adherence of alternative Mediterranean diet score as 1 point.
Physical activity during the past 2 weeks were categorized as adequate active (1~50, 51~100, 101~150 minutes/week) and non-optimal active including inactive (0 minute/week) or overactive (> 150 minutes/week) (table 4). Smoking status was categorized as current Smoking≧20 year, current smoking < 20 year, quit smoking < 1 year, quit smoking≧1 year and never smoking (table 5). The participants were
questioned about the usually drinking status and categorized as frequency alcohol consumption (dinking every day with undrunk, half-drunk or drunk; drinking per 2 days with half-drunk or drunk; drinking once a week with drunk) or few (drinking less than once a week or drinking per 2 days with undrunk ) or non-alcohol consumption (table 6). A detailed description of the questions and definition on ideal BMI, healthy diet, adequate physical activity, non-smoking status and frequency alcohol
consumption was based on the current literature, recommended guidelines but also on levels realistically obtainable within the general population.
2.3 Simple Taiwan healthy lifestyle scores
We created a simple pragmatic combined healthy lifestyle score. We created a healthy lifestyle score to sum each dichotomous lifestyle factor as "optimal" versus
"nonoptimal" as follows: normal BMI (BMI < 25 kg/m2) versus obese (BMI >=25 kg/m2), alternative Mediterranean diet 6 or higher points versus less than 6 points, ideal physical activity versus unideal physical activity , never smoking versus current or quit smoking and healthy drinking versus no drinking (table 7). The participants received 1 point for each optimal criterion met, and points were summed to obtain a HL-score ranging from 0 (nonoptimal) to 5 (optimal). Participants scored one point for each of the following health lifestyle criterion met: healthy diet, non-harmful
alcohol, non-obesity, adequate physical activity and non-current smoking. Participants could therefore have a total health lifestyle score ranging from 0-5 and were divided into five lifestyle groups: unhealthy lifestyle (none, one; 0–1), intermediate unhealthy lifestyle (two healthy lifestyle factors; 2), intermediate lifestyle (three healthy lifestyle factors; 3) intermediate healthy lifestyle (four healthy lifestyle factors; 4) healthy lifestyle (five healthy lifestyle factors; 5).
2.4 Weighted Taiwan healthy lifestyle score
A weighted healthy lifestyle-score named the Taiwan healthy lifestyle score also was created, where each dichotomous lifestyle factor was first weighted according to its independent magnitude of effect (ex: beta coefficient adjusted for the other
dichotomized lifestyle factors) on cardiovascular disease risk (table 8). Taiwan healthy lifestyle score was obtained from the sum of the weighted points attained by each individual, which range from 0 (Nonoptimal) to 17 (optimal). Taiwan healthy lifestyle score was classified into 4 groups for analyzing as quintile of people for comparing with healthy lifestyle score.
2.5 The World Cancer Research Fund International/ American Institute for Cancer Research (WCRF/AICR) lifestyle score
In accordance with WCRF/AICR 2018 definition, the WCRF/AICR lifestyle score was created which was a composite numerical measure of the adherence of health lifestyle and consisting of 7 main components, with each scored based on a 0, 0.25, 0.5 and 1 scale (0 point = least healthy; 10 points = most healthy) (table 9). According to recommendation of be a healthy weight, BMI was categorized as 18.5–24.9 kg/m2, 25–29.9 kg/m2 and either <18.5 or ≥30 kg/m2 for analyses. For being physically active, total moderate-vigorous physical activity was categorized as ≥150 mins/week, 75–<150 mins/week and <75 mins/week. For health dietary habits, fruits and
vegetables were categorized according to the frequency of intake as one of them every day, one of them 1~5 times per week or both of them less than once/week; the
frequency of bean intake was categorized as intake of bean every day , 1~5 times per week or less than 1 time per week. For limited consumption of “fast foods” and other processed foods high in fat, starches or sugars, the frequency of French fried or pizza intake was representative ultra-processed foods (aUPFs) and categorized tertiles. For limited consumption of red and processed meat, the frequency of pork, beef, goat, chicken and burger intake were representative and categorized tertiles, too. Limited consumption of sugar-sweetened drinks was defined by no intake of cola, soda and other sweetened drinks, < 3 times per week or ≧3 times per week. Participants was categorized into no drinking, few drinking and frequency drinking for the
recommendation of limited alcohol consumption. All points of 7 components was sumed as WCRF/AICR healthy lifestyle score .
2.6 Life’s Simple 7 score
Based on the 2019 AHA update criteria of cardiovascular health, the Life's Simple 7 score in our study included core health behaviors (weight, diet, physical activity and smoking) and health factors (cholesterol, blood pressure and glucose control). We defined the health heart participants with body mass index of >= 30, 25~29.9 and < 25 kg/m2 as poor health, intermediate health and ideal health (table 10). We categorized achievement of the alternative ideal health diet (table 11) of Life's Simple 7: >= 7 times per week of fruits and vegetables; >= 1 times per week of fish; >= 1 cup per day of grains (rice and noodles); >= 7 times per week of legumes; < 1 time per week of sugar-sweetened beverages (cola, soda and other sweetened beverages); < 1 time per week of processed meat (beef, pork, goat, and burgers) and < 1 time per week of saturated fat (French fried and pizza). We calculated the frequency of intake and summed across all food items. Participants with an alternative ideal health diet of Life's Simple 7 scoring 0~2, 3~4 and 5~7 points had poor health, intermediate health and ideal health, respectively. The weekly time of physical activity were derived from interview. We calculated the frequency of bouts of exercise by multiplying the times
of each bouts by the frequency in previous two weeks and summed across all exercise. The achievement of physical active goal were categorized according to Life's Simple 7 (poor health: 0 min/week; Intermediate health: 0~149 min/week moderate intensity or 0~74 min/week vigorous intensity; ideal health: >=150
moderate intensity or >=75 vigorous intensity or combination). Participants who had still currently smoking were defined as poor health. Former smokers but had quit within previous 12 months as intermediate level and those who had never smoked or quit more than 12 months were defined as optimal level.
We categorized poor health, intermediate health and ideal health in 3 cardiovascular health metric including total cholesterol(poor health: <200 mg/dL; intermediate health: 200-240 mg/dL ; ideal health: >240 mg/dL), blood pressure (poor health:
systolic blood pressure(sbp) ≥140mm Hg or diastolic blood pressure (dbp)≥ 90 mm Hg ; intermediate health: sbp: 120-139mm Hg or dbp: 80-89 mm Hg ; ideal health:
sbp<120mm Hg and dbp<80 mm Hg ), fasting plasma glucose (poor health: <100 mg/dL; intermediate health: 100-126 mg/dL; ideal health: >126 mg/dL).
Life's Simple 7 score were summed of each health heart behavior and factors, giving 2 points for an ideal metric, 1 point for an intermediate metric and 0 points for a poor
metric. Overall Life's Simple 7 score ranged 0 and 14 was devided into 4 categories as follows: 0-6, 7-9, 10-12, 13-14.
2.7 Measurements of blood pressure, weight and height measurement
According to American Heart Association recommendation, the measurement of blood pressure was obtained twice by certified interviewers. After the participants seated at rest for 5-10 min without walking, running or lifting heavy objects, the blood pressure was measured twice with arm raised to the same height as the heart using of a calibrated mercury sphygmomanometer and cuffs of the appropriate size. If the difference between twice was more than 10 mmHg, a third time of blood pressure measurement was taken and the average of blood pressure between two closet measurement were used in our study. Body mass index was calculated from weight and height measures obtained at clinical examination using a calibrate stadiometer.
2.8 Measurement of biochemistry markers
We performed the biochemical measurements once in the baseline 2002. The procedures involved in blood sample collection were previously reported. (citation.
Uric acid concentration as a risk marker for blood pressure progression and incident hypertension: A Chinese cohort study) Briefly, after a 9-12 hour overnight fast, all
venous blood samples were drawn into an EDTA anticoagulant tube, immediately refrigerated, and transported within 4 hours to central laboratory with an automatic multichannel chemical analyzer (TBA-200FR, Toshiba Corporation, Tokyo, Japan).
Serum samples were stored at -20℃before conducting batch assays to determine the levels of total cholesterol, triglycerides, and high density lipoprotein cholesterol (HDL-C) with blinded quality control specimens. Serum cholesterol and triglycerides were analyzed by the standard enzymatic methods. Both high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C) were performed by electrophoresis. Hexokinase glucose-6 phosphate dehydrogenase procedure was used for the measurement of plasma glucose and high-performance liquid chromatographic (HPLC) method was for the determination of HbA1c. Non-high-density lipoprotein cholesterol level was derived from the simplified equation as (total cholesterol in mg/dL) - (high-density lipoprotein cholesterol in mg/dL). The inter- and intra-assay coefficients of variation of these measurements were
approximately 5%.
2.9 Important covariates
At baseline, participants reported on socio-demographic factors and medical history including educational level, monthly income, marital status, menopause status, history
of estrogen exposure and parental history of cardiovascular disease (table 12).
Educational level was classified as compulsory school education (<=9 years) and 12-year school, university or college (> 9 12-years). The systolic blood pressure and diastolic blood pressure were obtained twice after 5 min of rest and the mean of the two measurements at clinical examinations. The value of fasting glucose, hemoglobin A1c, triglyceride, total cholesterol and non-high-density lipoprotein were measured by blood samples drawing in the morning after overnight fasting and serum level were analyzed using enzymatic methods.
Diabetes at baseline was defined as a fasting serum glucose >= 126 mg/dL and hemoglobin A1c >= 6.5 mg/dL or records with twice diagnosis of diabetes by ICD-9 or prescription of anti-diabetes drugs more than 12 weeks from NHIRD prior to enrolled date. Hypertension was defined as systolic blood pressure >= 140 mmHg or diastolic >= 90 mmHg or records with twice diagnosis of hypertension or prescription of anti-hypertensive drugs more than 12 weeks from NHIRD prior to enrolled date.
Data on the use of lipid-lowering agent and aspirin were obtained from drug register and defined as yes while prescriptions were more than 12 weeks prior to the enrolled date. Abdominal obesity was indicated as waist circumflex ≧ 80 cm in women and
>= 90 cm in men.
2.10 Outcome ascertainment and prospective follow-up
Follow-up information was from the national health insurance research database and the Taiwan Cause of Death Register for fatal outcomes by record linkage using the personal identification numbers assigned to every citizen on Taiwan. The
International Classification of Disease 9(ICD-9) codes were used to identify coronary artery disease or ischemic stroke in the above-mentioned. (Table 13) Coronary artery disease was defined as ICD-9 codes 410-411, 414 and V45.81-82. Ischemic stroke was defined as ICD-9 codes 434-436, 4371, 4379. We ascertained incident cast of coronary artery disease and ischemic stroke using National Health Insurance Research Database with the first hospitalization with the diagnosis of above interest events and the event date defined as the first date of hospitalization. We ascertained the coronary artery disease and stroke related death using death certificate registration. All
participants were flagged for death at the department of Household Registration, and coded death certificates using the international classification of disease (ICD), revision 9. The diagnoses of coronary artery disease and ischemic stroke were made by the treating physicians, based on a clinical assessment and examinations as considered relevant by the clinician in charge of treatment.
2.11 Statistical Analyses
Person-years at risk were calculated from the baseline date to the diagnosis of a CVD
event, date of death, loss to follow-up, or end of follow-up (December 31, 2015), whichever occurred first.
Participants were categorized into 4 group among each healthy lifestyle scores, based on the numbers of adherence to Mediterranean diet related healthy lifestyle score, Taiwan healthy lifestyle score, WCRF/AICR healthy lifestyle score and Life's Simple 7 score. The continuous variables are presented by mean, standard deviation, or median levels; categorical data are presented in contingency table with ANOVA to test for differences among quintiles. Relationships between individually healthy lifestyle factor and 4 combined healthy lifestyle scores were examined by the age- and gender-adjusted Spearman's partial correlation coefficients.
We used Cox proportional hazards models to determine the hazard ratio (HR) and 95% confidence interval (CI) of the association between health lifestyle factors, either individually or as their combined health lifestyle score, and the risk of coronary artery disease and ischemic stroke during the follow-up. Multivariate Cox regression models were constructed for combined health lifestyle scores with the lowest score category as the reference category with age as the underlying time scale, and stratified jointly by age at baseline in 20 -year intervals and sex.
We made multivariate adjustments to examine how far the effect of combined health lifestyle score might be explained by known cardiovascular factors. We adjusted for age and sex in model A; age, sex, educational level, monthly income, marital status, menopause, estrogen exposure, and parental history of cardiovascular disease in model B; And as for model B with the addition of history of hypertension, diabetes, the, lower lipid agent use and aspirin used, fasting glucose, hemoglobin A1c, systolic blood pressure, diastolic blood pressure, triglyceride and non- high density
lipoprotein-cholesterol in model C.
The linear trend test for individual factors was performed by the specific median to each category and then modeling this as a continuous variable in a separate model; for combined lifestyle factors, the test was performed by treating the number of low-risk factors as a continuous variable. Proportional hazard assumption was note rejected in these Cox models by plotting the log(-log(survival time)) versus log of survival time and including time dependent covariates.
The population attributable risk (PAR), proportion of CVD hypothetically prevented if whole population with the highest number of healthy lifestyle factors, was
estimated using hazard ratio (HRs) obtained from the different Cox regression models in our cohort. The Wacholder et al. method was performed to generate 95%
confidence intervals (CI) for robust estimation according to sex, age, education years, marriage status, income level, parental histories of heart attack or stroke, menopause status, hormone replacement therapy, baseline hypertension, diabetes and
hyperlipidemia, blood pressure, fasting glucose, hemoglobin A1c, triglyceride and non-HDL-C. We tested potential effect modifiers of sex and age category (20-39.9, 40-39.9, >=60) by using the likelihood ratio test comparing models with and without a cross-product term.
To further investigate the role of combined healthy lifestyle factors to predict the cardiovascular risk, we compared the 4 model with healthy lifestyle score (simple and
To further investigate the role of combined healthy lifestyle factors to predict the cardiovascular risk, we compared the 4 model with healthy lifestyle score (simple and