Relationship Between Physical Activity, Fitness, and CHD Risk Factors in Middle-Age Chinese

Transcription

1 Journal of Physical Activity and Health, 2005, 3, Human Kinetics Publishers, Inc. Relationship Between Physical Activity, Fitness, and CHD Risk Factors in Middle-Age Chinese Stanley S.C. Hui, Neil Thomas, and Brian Tomlinson Background: The impact of physical activity, aerobic fitness, and body composition on coronary heart disease (CHD) risk factors in Hong Kong Chinese adults has not been previously investigated. Methods: The study surveyed 707 randomly selected middle-age Hong Kong Chinese by telephone for Physical Activity Rating (PAR). Three hundred and sixteen respondents (age: 45.1 ± 8.1 y) participated in subsequent aerobic fitness testing (VO 2max ) and CHD risk factor screening. Results: More than 70% of respondents did not have sufficient levels of physical activity. Fifty percent of the men and 19.5% of the women had two or more CHD risk factors. PAR correlated poorly with VO 2max and CHD risk factors. VO 2max showed significant associations with CHD risk factors. The adjusted odds ratios of having CHD risk factors for unfit participants ranged from 1.11 to 6.61 as compared to fit participants. Obese but fit individuals demonstrated lower odds of CHD risk factors than the obese and unfit individuals. WC was found to be a stronger predictor for CHD risk factors than BMI. Conclusions: The prevalence of CHD risk factors in middle-age Chinese in Hong Kong was high and was related to levels of aerobic fitness and obesity. Key Words: preventive medicine, public health, epidemiology, aerobic fitness, body composition Heart disease is the most important cause of mortality in the US, and is the second most important in Hong Kong, accounting for 16.3% of the total mortality in 2000, 1 which represents more than 5000 deaths annually. Of all deaths from heart disease, coronary heart disease (CHD) accounted for 65.1% in 2000, compared to 59.4% in 1992, 55.1% in 1982, and 38.6% in Mild to moderate levels of physical activity 2,3,4,5,6 and moderate levels of physical fitness 7,8,9,10,11 have been shown to significantly lower the risk of CHD. There is limited data, however, describing physical activity, physical fitness, and CHD risk factors in Chinese adult populations. The importance of physical activity or physical fitness for health is poorly recognized by Hui is with the Dept of Sports Science & Physical Education, the Chinese University of Hong Kong, Shatin, N.T. Hong Kong. Thomas is with the Dept of Community Medicine, the University of Hong Kong. Tomlinson is with the Dept of Medicine and Therapeutics, the Chinese University of Hong Kong. 307

2 308 Hui et al. the public in Hong Kong. One major reason is that there is limited documentation to support these associations in Asian populations. Donnan et al. reported that the incidence of acute myocardial infarction in four Hong Kong hospitals correlated with cigarette smoking, history of hypertension, diabetes, body fatness, and physical activity levels. 12 They found that the association between physical activity and the incidence of acute myocardial infarction was significant and was similar to levels reported in other studies. Woo et al. also evaluated the association between CHD mortality and physical activity in Chinese age 70 y and over, 13 and found that the overall mortality from stroke and ischemic heart disease was negatively associated with participation in physical activity. These 2 studies presented the relationship between physical activity and CHD without addressing CHD risk factors. To our knowledge, no study has included an evaluation of physical fitness and CHD risk factors for Hong Kong Chinese adults. From a recent cross-sectional physical activity survey in Hong Kong, Hui and Morrow found that middle-age Chinese in Hong Kong were less active than their younger and older counterparts. 14 Evidence that an active lifestyle and improved physical fitness is associated with lower levels of CHD in Hong Kong Chinese could support the development of a territory-wide health promotion policy. The purpose of this study was to examine traditional CHD risk factors in middle-age Chinese in Hong Kong, and to determine the impact of physical activity and fitness on the CHD risk factors. Physical Activity Survey Methods In 2002 we conducted a citywide randomized telephone survey of middle-age Hong Kong adults using the Telephone Survey Research Laboratory of the Hong Kong Institute of the Asia-Pacific Studies Center. A total of 6400 random telephone calls were made, and 880 target respondents (age 35 to 65 y) were identified. Of the 880 target respondents, 707 answered the telephone survey successfully, a success rate of 80.3%. The survey asked the subjects to determine their physical activity level in terms of average weekly activity on a scale from 1 (least active) to 8 (most active) in the past year. The physical activity rating (PAR) was adopted from the National Survey of Physical Activity Practice 15 and was translated into Chinese (Appendix A). The list of physical activities describes eight different levels of physical activity in a progression of different combinations of frequencies, durations, and intensities of activity. The reliability and validity of the PAR have been reported in other sources. 14,15 Laboratory Testing Respondents who answered the telephone survey were invited to attend the Clinical Pharmacology Studies Unit of the Prince of Wales Hospital for testing that included a submaximal treadmill exercise test for estimating maximal oxygen uptake (VO 2max ), blood pressure measurement, fasting blood chemistry analysis, body-mass index (BMI) for general obesity, and waist circumference (WC) for central obesity. Physical Fitness Measurement. A single-stage submaximal treadmill test as recommended by Shephard 16 was used to measure aerobic fitness. Mahar et al. 17

3 CHD Risk Factors in Chinese 309 reported that the accuracy of the single-stage model is similar to that of the multistage model. The criterion-related validity of the single-stage model on treadmill exercise was r = 0.72 (SEE = 1.8 METs). 17 The subject was required to walk on a treadmill at a self-selected moderate pace (approximately 3.0 mph) for 5 min as a warm-up procedure. After the warm-up walk, the subject was asked to walk or jog for one more stage to obtain steady-state heart rate above 60% of age-predicted HR max. The second workload was a self-selected moderate walking/jogging pace at a 4% gradient for 3 min. In cases of a steady-state heart rate lower than 60% of HR max, the subject was requested to walk/jog for another 3 min with the same speed but the elevation was increased to 8%. Once a steady-state exercise heart rate of 60% of HR max was achieved, this heart rate was used to estimate VO 2max using the single-stage equation suggested by Shephard. 16 Exercise heart rate was monitored continuously using a Polar heart rate monitor. CHD Risk Factor Measurement. Prior to the submaximal treadmill test, subjects were invited to go through a blood screening procedure after a 12 h fast. Subjects reported to the laboratory of the university-affiliated hospital between 8 and 9 AM. Blood chemistry analyses included total, LDL-, and HDL-cholesterol, triglycerides, and glucose following an overnight fast, as described previously. 18 Plasma glucose was measured using a standard glucose oxidase method and total HBA 1 by electrophoresis (Ciba Corning Diagnostics, Palo Alto, CA; normal range: 6.5 to 8.5%). Plasma total cholesterol and triglycerides were measured enzymatically (Centrichem Chemistry System, Baker Instruments Co., Allentown, PA). The long-term imprecision of the assay was 3% at 3.3 mmol/l and 2.2% at 6.8 mmol/l for total cholesterol and 6.9% at 1.02 mmol/l and 4.6% at 2.18 mmol/l for triglycerides. HDL-cholesterol was determined following fractional precipitation with dextran sulphate-mgcl 2 and LDL-cholesterol was calculated using Friedewald s formula. CHD risk factors were determined by blood pressure and blood chemistry tests, smoking habits, family CHD history, and anthropometric measurements. Three seated blood pressure measures were obtained after a 15 min rest period, and the average of the 3 measures was used for analysis. History of smoking and family CHD background were collected using a questionnaire. Anthropometric measurements included weight, height, and waist and hip circumferences. The definitions for CHD risk factors (Appendix B) were adopted from the criteria published by the ACSM 19 except for obesity. According to recent Asian standards published by the WHO, 20 obesity was defined as a BMI 25 kg/m 2 or waist circumference > 90 cm for men and > 80 cm for women. Subjects were requested not to exercise on the day of and the day before testing. Subjects were also requested to refrain from smoking and not take any medication before the blood testing. All subjects signed the informed consent form. The research procedures were approved by the Clinical Research Ethics Committee of the Chinese University of Hong Kong. Of the 707 respondents from the telephone survey, 316 attended the laboratory testing, and 263 satisfactorily completed the fitness measurement and blood analysis. Statistical Analysis Basic descriptive statistics (mean and standard deviation) and proportion (in terms of percentage) were computed to describe the distributions of demographic

4 310 Hui et al. information, physical activity levels, and the CHD risk factors. Age-adjusted Pearson correlations between PAR, estimated VO 2max, and CHD risk factors were computed to determine the association between them. PAR levels of subjects were divided into either inactive (PAR = 1 to 4) or active (PAR = 5 to 8) groups according to the well-established criterion of sufficient physical activity to achieve health benefits. 6 Similarly, fitness levels of subjects were also classified into either unfit (bottom half of fitness levels) and fit (upper half of fitness levels) according to the age and gender specific VO 2max cut-off values. MANOVA was conducted to determine the differences in CHD risk factors between the two activity groups and the two fitness groups. Subsequent univariate ANOVA were carried out when significant MANOVA was found. Logistic regressions, using various CHD risk factors (either risk or no risk) as dependent variables and activity groups, age, gender, smoking habits, family CHD history, and educational attainment as independent variables, were conducted to determine the odds ratio for showing CHD likelihood for the inactive group as compared to the active group. The same strategy was used to examine the odds ratio for having CHD likelihood for the unfit group as compared to the fit group. Subjects who had metabolic syndrome were also identified using the National Cholesterol Education Program (NCEP) ATP III Panel criteria, 21 which defined metabolic syndrome as the presence of three or more of the following indicators: increased waist circumference, high triglycerides ( 1.7 mmol/l), low HDL-cholesterol (< 1.0 mmol/l in men and < 1.3 mmol/l in women), high blood pressure ( 130/ 85 mmhg), and impaired fasting glucose ( 6.1 mmol/l). 21 For the waist circumference, the new WHO obesity standards for Asians was used. 20 Logistic regression analyses examined the odds ratios of having the metabolic syndrome for the unfit group as compared to the fit group. The logistic regression analyses of fitness and CHD risk factors were also assessed by different obesity levels (lean and obese). Results Respondents from the telephone survey included 337 men (47.7%) and 370 women (52.3%) with a mean age of 45.1 ± 8.1 y and a male/female ratio similar to the Hong Kong middle-age population in the year 2000 census. For the PAR level, 32.6% had no physical activity (ratings of 1 to 2), 36.1% took irregular physical activity (ratings of 3 to 4), and only 31.3% were active enough to derive substantial health benefits (at least 5 d moderate level of activities or 2.5 h exercise weekly, ratings of 5 to 8). Of the 707 individuals surveyed, 316 attended the laboratory testing. The distributions of age, gender, physical activity level, education, work status, and industry background of the surveyed sample and the laboratory sample are presented in Table 1. The demographic characteristics and physical activity levels of the 316 laboratory subjects were similar to the original 707 telephone respondents. The CHD risk factors for the 316 men and women who submitted to laboratory testing are summarized in Table 2. A large proportion of men and women were obese (two-fifths of the sample), and almost as many demonstrated undesirable blood screening profiles (high total and LDL-cholesterol, high glucose). Table 3 summarizes the number of CHD risk factors (total number of positive risk factors minus the number of negative risk factors) by gender from the risk factors listed in

5 CHD Risk Factors in Chinese 311 Table 1 Demographic Information of the Survey and Laboratory Samples Survey sample (N = 707) Laboratory sample (N = 316) Age (y) (mean ± SD) 45.1 ± ± 8.2 Gender Men 47.7% 49.4% Women 52.3% 50.6% Activity level Inactive (PAR = 1 & 2) 32.6% 29.7% Some active (PAR = 3 & 4) 36.1% 41.9% Active (PAR = 5 8) 31.3% 28.4% Education Primary or less 22.9% 17.7% Secondary 60.7% 63.7% Tertiary or higher 16.4% 18.6% Work status Full-time 55.8% 57.9% Part-time/student 7.3% 7.1% Retired/unemployed 13.5% 12.5% Household work 23.5% 22.5% Industry Blue collar 12.7% 12.6% White collar 46.9% 34.9% Other/no response 40.4% 52.5% Table 2. Physical inactivity from the PAR, however, is not included in the number of CHD risk factors because the influence of physical activity on CHD odds was analyzed separately. As can be seen in Table 3, 19.5% of women had two or more CHD risk factors and 5.7% of women had three or more CHD risk factors. For men, 50.0% had two or more CHD risk factors, 17.9% had three or more CHD risk factors. When inactivity was taken into account, the figures for having two or more CHD risk factors increased to 38.4% and 68.0% for women and men, respectively. The correlation between age and total CHD risk scores for women was low but significant (r = 0.29, P < 0.05); for men, the correlation between age and total CHD risk factors was very low (r = 0.08, P > 0.05). For aerobic fitness of the 263 Chinese subjects, the mean estimated VO 2max for men was 35.8 ± 6.5 ml kg 1 min 1 (range: 19.8 to 56.9 ml kg 1 min 1 ), and for women was 32.6 ± 6.1 ml kg 1 min -1 (range: 17.5 to 62.1 ml kg 1 min 1 ). Out of 132 women, only 61 (46.2%) met the minimal VO 2max health criterion (32.5 ml kg 1 min 1 ), whereas 71 of 131 men (54.20%) met the minimal VO 2max health criterion (35 ml kg 1 min 1 ). 22 The correlations between age and estimated VO 2max were r = 0.22 in women and r = 0.37 in men (P < 0.05).

6 312 Hui et al. Table 2 CHD Risk Factors of Laboratory Participants (N = 316) Men (N = 156) Women (N = 160) Physically inactive (completely sedentary) Cumulative: 1 through 2 on PAR 31.4% 28.0% Not active enough Cumulative: 1 through 4 on PAR 71.3% 72.0% Obesity 41.7% 40.0% Hypertension 24.4% 6.9% Smoking 24.4% 0.6% Family history 15.4% 10.6% Impaired blood glucose 7.7% 5.6% High cholesterol 48.1% 33.1% High LDL-cholesterol (> 3.4 mmol/l) 43.1% 32.5% High triglycerides (> 2.4 mmol/l) 13.5% 3.8% Low HDL (< 0.9 mmol/l) 4.5% 0.0% High HDL-cholesterol (> 1.6 mmol/l) A negative risk factor and beneficial for heart health 17.3% 53.8% Table 3 Number of Positive CHD Risk Factors (excluding inactivity risk factor) Men (N = 156) Women (N = 160) Number of CHD risk factors % Accumulated % % Accumulated % 5 1.2% 1.2% 0% 0% 4 1.3% 2.5% 1.9% 1.9% % 17.9% 3.8% 5.7% % 50.0% 13.8% 19.5% % 77.6% 23.1% 42.6% % 94.9% 31.2% 73.9% 1 5.1% 100% 26.2% 100% Association Between PAR, Fitness, and CHD Risk Factors The associations between PAR, aerobic fitness, body composition, and CHD risk factors were analyzed in the 263 adults. The age-adjusted correlation between PAR and VO 2max was r = 0.30 (P < 0.01) for women and r = 0.01 for men (P > 0.05). The age-adjusted correlations between PAR and all CHD risk factors ranged from r = 0.17 to 0.15 for women and r = 0.16 to 0.07 for men, and were all nonsignificant (P > 0.05). Age-adjusted correlations between VO 2max and all CHD risk factors were also low, but significant for triglycerides in men (r = 0.20, P < 0.05) and significant for systolic blood pressure (r = 0.22, P < 0.05), glucose (r = 0.23, P < 0.01), and triglycerides (r = 0.26, P < 0.01) in women (Table 4).

7 CHD Risk Factors in Chinese 313 Table 4 Age-adjusted Correlation Between Physical Activity Rating, VO 2max, and CHD Risk Factors Physical Activity Rating VO 2max Men Women Men Women Body-mass index (kg/m 2 ) Waist circumference (cm) Systolic blood pressure (mmhg) * Diastolic blood pressure (mmhg) Plasma glucose (mmol/l) ** Total cholesterol (mmol/l) LDL-cholesterol (mmol/l) Triglycerides (mmol/l) * 0.26** HDL-cholesterol (mmol/l) Note: *significant at 0.05 level; **significant at 0.01 level. When PAR of subjects was divided into the active and inactive groups (inactive: PAR = 1 to 4; and active: PAR = 5 to 8), MANOVA tests comparing all CHD risk measures (total, LDL- and HDL-cholesterol, triglycerides, glucose, BMI, waist circumference, and blood pressure) between the two activity groups were not significant for both men (P > 0.05) and women (P > 0.05). ANOVA tests comparing the number of elevated CHD risk factors between the two activity groups were also not significant for both men (P > 0.05) and women (P > 0.05). Logistic regression analyses, however, found that the inactive subjects (PAR = 1 to 4, n = 184) tended to have higher odds (adjusted for age, gender, smoking habits, family history, and educational levels) of having high blood pressure (OR = 1.26, 95% CI: 0.51 to 3.13), obesity (OR = 1.41, 95% CI: 0.79 to 2.53), and glucose (OR = 2.20, 95% CI: 0.53 to 9.19) compared to active subjects (PAR = 5 to 8, n = 73, Figure 1); however, 95% CI indicated that none of these odds ratios reached significance. For aerobic fitness and CHD risk factors in women, VO 2max showed a significant negative relationship (age-adjusted) with blood pressure (r = 0.22, P < 0.05), glucose (r = 0.23, P < 0.01) and triglycerides (r = 0.26, P < 0.01). Moreover, BMI also significantly correlated (age-adjusted) with glucose (r = 0.25, P < 0.01), triglycerides (r = 0.24, P < 0.01), and HDL-cholesterol (r = 0.38, P < 0.001). Compared with BMI, however, WC showed stronger correlations with triglycerides (r = 0.27, P < 0.01) and HDL-cholesterol (r = 0.45, P < 0.001). For age-adjusted correlations between VO 2max and CHD risk factors in men, significant negative relationships were found for triglycerides (r = 0.20, P < 0.05). In addition, significant age-adjusted correlations between BMI and systolic blood pressure (SBP) (r = 0.27, P < 0.01), DBP (r = 0.21, P < 0.05), HDL-cholesterol (r = 0.26, P < 0.01), and triglycerides (r = 0.34, P < 0.001), as well as between WC and SBP (r = 0.30, P < 0.001), DBP (r = 0.26, P < 0.05), HDL-cholesterol (r = 0.31, P < 0.001), and triglycerides (r = 0.33, P < 0.001) were found. Most correlations for WC were higher than those for BMI.

8 314 Hui et al. Figure 1 Age, gender, smoking habits, family CHD history, and education level adjusted odds ratios of CHD odds for inactive group (PAR = 1 to 4, n = 184) as compared to the active group (PAR = 5-8, n = 73). TGL, triglycerides; CHL, total cholesterol; LDL, low-density lipoprotein cholesterol; HDL, high-density lipoprotein cholesterol; BP, blood pressure; GLU, glucose. The range in the brackets describes the 95% CI of the odds ratio. The aerobic fitness level of the sample was divided into two fitness categories (unfit: bottom half; and fit: top half) according to their age and gender specific cutoff values for further analyses. The age and gender specific VO 2max cut-off values are shown in Table 5. MANOVA (P < 0.01) and subsequent univariate ANOVA found significant differences in blood pressure (P < 0.05), glucose (P < 0.05), triglycerides (P < 0.05), and HDL-cholesterol (P < 0.01) levels between the two fitness groups in women (Table 6). The higher the fitness level, the lower the CHD risk profiles were in women. On the other hand, MANOVA found nonsignificant differences (P > 0.05) in all CHD risk measures between the two fitness groups in men, although triglycerides were significantly lower in the fit group as compared to the unfit group (Table 6). Results of the logistic regression analysis comparing the elevated CHD risk factors of unfit and fit groups are presented in Figures 2 and 3. Figure 2 shows that the odds of having high triglycerides were almost four times higher in the unfit group than the fit group (OR = 3.92, 95% CI: 1.24 to 12.37). Furthermore, the odds for high glucose for the unfit group was more than six times (OR = 6.61, 95% CI: 1.37 to 31.81) than the fit group, whereas, the odds of having high HDL-cholesterol for the unfit group was less than half of the fit group (OR = 0.47, 95% CI: 0.27 to 0.84). From Figure 3, the odds of having two or more CHD risk factors for the unfit group was 47% (OR = 1.47, 95% CI: 0.82 to 2.65) more than the fit group.

9 CHD Risk Factors in Chinese 315 Table 5 VO 2max Cut-off Values (ml kg 1 min 1 ) for Classifying High Fit (Top Half) and Low Fit (Bottom Half) Groups Age groups (y) Men (N = 131) Women (N = 132) Table 6 ANOVA Comparing CHD Risk Profiles Between Low Fit and High Fit Participants Women (N = 132) Men (N = 131) Unfit Fit P Unfit Fit P Body-mass index (kg/m 2 ) Waist circumference (cm) Systolic blood pressure (mmhg) * Diastolic blood pressure (mmhg) Plasma glucose (mmol/l) * Total cholesterol (mmol/l) LDL-cholesterol (mmol/l) Triglycerides (mmol/l) * * HDL-cholesterol (mmol/l) ** Note: *significant at 0.05 level; **significant at 0.01 level. Similarly, the odds of having three or more CHD risk factors for the unfit group was five times greater (OR = 5.04, 95% CI: 1.42 to 17.98) than the fit group. The age, gender, smoking habits, family CHD history, and education adjusted odds ratio for having the metabolic syndrome for the unfit individuals was 2.69 (95% CI: 1.02 to 7.21). The odds ratios of having different components of the metabolic syndrome are shown in Figure 4. Fitness Versus Fatness To further examine the influence of body composition on the relation of fitness and CHD risk factors, subjects were divided into either the fit-lean, fit-obese, unfit-lean, or unfit-obese groups according to the specific fitness and obesity cut-off values as described previously. Using the fit-lean group as reference, the odd ratios of

10 316 Hui et al. Figure 2 Age, gender, smoking habits, family history, and educational level adjusted odds ratios of CHD odds for unfit group as compared to fit group. HDL, high-density lipoprotein cholesterol; BP, blood pressure; LDL, low-density lipoprotein cholesterol; CHL, total cholesterol; TGL, triglycerides; GLU, glucose. The range in the brackets describes the 95% CI of the odds ratio. Figure 3 Age, gender, smoking habits, family history, and educational level adjusted odds ratios of the number of CHD odds for unfit group as compared to fit group. The range in the brackets describes the 95% CI of the odds ratio.

11 CHD Risk Factors in Chinese 317 Figure 4 Age, gender, smoking habits, family history, and educational level adjusted odds ratios of the number of metabolic syndrome risk factors for unfit group as compared to fit group. The range in the brackets describes the 95% CI of the odds ratio. Table 7 Comparison of Odds Ratios (Age, Gender, Smoking Habits, Family CHD History, and Education Level Adjusted) of CHD Risk Among the Fit-Obese, Unfit-Lean, and Unfit-Obese Groups Using the Fit-Lean Group as the Reference Group Fit-lean vs. fit-obese Fit-lean vs. unfit-lean Fit-lean vs. unfit-obese OR 95% CI OR 95% CI OR 95% CI High blood pressure High plasma glucose ---# * High total cholesterol High LDL-cholesterol High triglycerides * High HDL-cholesterol 0.18* * * Note: #There were less than 2 cases of high glucose subjects in the fit-obese group, therefore no odds ratio was computed; *indicates significant odds ratio at 95% CI. demonstrating CHD risk factors for the fit-obese, unfit-lean, and unfit-obese groups were computed. As can be seen in Table 7, the unfit-obese group had nearly 20 times the odds of having high blood glucose (OR = 19.98, 95% CI: 1.90 to ), and 14 times the odds of having high triglycerides (OR = 13.96, 95% CI: 2.74 to 68.46) as compared to the fit-lean group. For the fit-obese and unfit-lean groups, however, all odds for CHD risk factors were not significant except for high-hdl-cholesterol. Compared with the fit-lean group, the other 3 groups demonstrated significantly lower odds for having high HDL-cholesterol (OR range: 0.09 to 0.41).

12 318 Hui et al. Discussion Similar to previous studies, 14,23 the present study found that 70% of Hong Kong middle-age adults are not physically active enough to achieve health benefits from daily activities. Two-fifths of men and women were obese according to the Asian criteria. Furthermore, approximately half of the men and one-third of the women possessed adverse cholesterol (high LDL-cholesterol, or low HDL-cholesterol) or triglycerides levels. When all the measured CHD risk factors were considered, onefifth of the women and one-half of the men had two or more risk factors (Table 3). These findings revealed that the odds for having CHD risk factors in Chinese men is much greater than in Chinese women. The above observations indicate that the CHD risk of Hong Kong middle-age adults is high. A large-scale CHD survey in Hong Kong conducted by Janus in 1995 reported that, when only risk factors of diabetes, hypertension, high cholesterol, and smoking were considered, for the same age group as the present study, 58.1% of middle-age men and 33.5% of middle-age women had at least one CHD risk factor. 24 Using the same four risk factors for calculation, the present study found 76.9% of men 38.7% of women had at least one CHD risk factor, suggesting the prevalence of cardiovascular risk factors might be increasing. In contrast to aerobic fitness and CHD risk factors, this study shows poor correlation between physical activity and aerobic fitness, as well as CHD risk factors. One possible reason is the lack of sensitivity of the PAR scale used in this study. A more objective measure of physical activity, such as activity counts from motion sensors or measurement of energy expenditure, might produce a clearer association. In addition to CHD risk factors, assessment of hard endpoints, such as heart disease morbidity and mortality is likely to provide a more direct evaluation of the beneficial effects of regular physical activity. 25 Such measurements, however, would be very costly in terms of both time and resources. Consistent with a number of previous studies conducted in North American and Japanese populations, 8,22,25,26,27,28 aerobic fitness seems to be an important factor influencing CHD risk in middle-age Chinese. Of all CHD risk factors, glucose and triglycerides were the most closely related to aerobic fitness. In 1664 law enforcement trainees, McMurray et al. reported that aerobic fitness appears to have more of an influence on CHD risk factors than PA levels. 27 Compared to the lowest tertile of fitness, the fit trainees had reduced relative risks (RR) of elevated cholesterol (RR = 0.56, 95% CI: 0.36 to 0.88), blood pressure (RR = 0.31, 95% CI: 0.15 to 0.62), and obesity (RR = 0.09, 95% CI: 0.06 to 0.12), whereas only subtle associations were found for physical activity. 27 In 4360 middle-age Americans residing in Utah, LaMonte et al. found significant inverse associations between fitness (quintile) and all CHD risk factors except glucose among men, and SBP and triglycerides among women. 26 In another sample of 222 Japanese adults, aerobic fitness was more closely related to CHD risk factors than physical activity measured using motion sensors. 28 The results from the present study suggest that higher aerobic fitness is associated with beneficial lower glucose and triglyceride levels, particularly in women. As shown in Figure 2, the odds for high glucose for unfit individuals was more than six times greater than that of fit individuals; the odds for high triglycerides was approximately four times greater. Regarding the impact of obesity level on the relationship between aerobic fitness and CHD risk factors (Table 7), using the fit-lean group as reference, the

13 CHD Risk Factors in Chinese 319 obese and unfit individuals clearly demonstrated increased odds for having high glucose (20 times) and triglycerides (14 times). The odds for the fit-obese group and unfit-lean group were similar, however. These results suggest that being obese but fit, or being unfit but lean would reduce the level of risk towards that of the fit and lean individuals, but not entirely as seen from the significantly lower ORs for HDL-cholesterol in the lean-fit group compared to each of the other groups. Therefore, in obese individuals, being fit would help to lower the odds of having the CHD risk factors, and similarly for unfit individuals, being lean would help to reduce risk. Both fitness and obesity levels therefore appear to be important determinants for the presence of CHD risk factors, but overall the data indicates that being both fit and lean will result in the greatest benefit for the HDL-cholesterol profile. As can be seen in Figures 3 and 4, unfit individuals appeared to have five times the odds of having three or more of the CHD risk factors compared to the fit group (Figure 3) and close to three times the odds of having the metabolic syndrome (Figure 4). All these results suggest that improving aerobic fitness might attenuate the development of CHD risk factors and the metabolic syndrome. Furthermore, the effects of aerobic fitness are most evident in the obese individuals, such that an aerobically fit obese individual appears to have lower cardiovascular risk than unfit obese individuals. Although the importance of physical activity, in terms of PAR, in lowering CHD risk factors of Chinese middle-age adults cannot be confirmed in the present cross-sectional study, the relationship between aerobic fitness and lower CHD risk factors and the metabolic syndrome is evident. One effective means to improve aerobic fitness is through increased physical activity with an intensity sufficient (e.g., 60% HR max ) to stimulate changes in the cardiovascular system. 19 Another important finding is that obesity is one of the most important factors influencing glucose, triglycerides, and HDL-cholesterol levels of middle-age Hong Kong adults, with the strongest association being found for HDL-cholesterol. In a 6-y prospective study of 2856 Chinese adults of northeastern China, CHD risk factors increased with increasing BMI. 29 Compared to a BMI of 21 kg/m 2, the CHD odds for a BMI of 23.0 to 24.9 kg/m 2 was double and for a BMI of 25.0 to 26.9 kg/m 2 was tripled. 29 Results from the present study also confirmed that central obesity (WC) is a more important factor than general obesity (BMI) in influencing CHD odds. 20,29 Li et al. recommended that a WC of 85 cm for Chinese men and 80 cm for Chinese women be suitable cut-off points. From these observations, it is suggested that one of the most effective ways to lower the risk of CHD is to reduce obesity levels. 29 This study has several limitations. First, as described previously, the failure to identify the association between the PAR and CHD risk factors might result from the lack of sensitivity of the instrument. Second, compared to other large-scale studies, the relatively small sample size in this study might also contribute to the nonsignificant association between PAR and CHD risk factors. As a result of the small number of individuals who had high blood glucose levels, odds ratios could not be determined. Third, this study was cross-sectional and thus the actual impact of physical activity and aerobic fitness on CHD mortality and morbidity remain to be confirmed. It is suggested that a longitudinal study that examines the long term CHD health outcomes, as well as adopting a more objective measure of physical activity be conducted for the Chinese adult population in the future.

14 320 Hui et al. Conclusions The prevalence of CHD risk factors in middle-age Chinese in Hong Kong was high and was related to levels of aerobic fitness and obesity. Reduced odds of diabetes and hypertriglyceridemia are associated with greater aerobic fitness. Lower obesity levels, particularly central obesity, was associated with lower levels of hypercholesterolemia in these middle-age Chinese subjects. These data tend to suggest that middle-age Hong Kong adults should try to maintain or improve aerobic fitness to reduce the likelihood of cardiovascular disease, possibly by engaging in a regular aerobic exercise training program. Acknowledgments This project was funded by the Hong Kong Sports Development Board Research Fund and was partly supported by Fitness Concept Ltd. References 1. Hong Kong Dept of Health. Annual Departmental Report by Director of Health Hong Kong: Hong Kong Dept of Health, 2001: Berlin JA, Colditz GA. A meta-analysis of physical activity in the prevention of coronary heart disease. Am J Epidemiol. 1990;132: Morris JN, Everitt MG, Pollard R, Chase SPW, Semmence AM. Vigorous exercise in leisure-time: protection against coronary heart disease. Lancet, 1980;2: Paffenbarger RS Jr, Hale WE. Work activity and coronary heart mortality. N Engl J Med. 1975;292: Young DR, Steinhardt MA. The importance of physical fitness versus physical activity for coronary artery risk factors: a cross-sectional analysis. Res Q Exerc Sport. 1993;64: US Dept of Health and Human Services. Physical Activity and Health: A Report of the Surgeon General. Atlanta, GA: US Dept of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, 1996: Blair SN, Kohl HW, Paffenbarger RS Jr, Clark DG, Cooper KH, Gibbons LW. Physical fitness and all-cause mortality: a prospective study of healthy men and women. JAMA 1989;262: Cooper KH, Pollock ML, Martin RP, White SR, Linnerud AC, Jackson A. Physical fitness levels vs. selected coronary risk factors: a cross-sectional study. JAMA 1976;236: Ekelund LG, Haskell WL, Johnson JL, Whaley FS, Criqui MH, Sheps DS. Physical fitness as a predictor of cardiovascular mortality in asymptomatic North American men: The Lipid Research Clinics Mortality Follow-up Study. N Engl J Med. 1988;319: Lakka T, Venalainen J, Rauramaa R, Salonen R, Tuomilehto J, Salonen J. Relation of leisure-time physical activity and cardiorespiratory fitness to the risk of acute myocardial infarction in men. N Eng J Med. 1994;330: Sallis JF, Haskell WL, Fortmann SP, Wood PD, Vranizan KM. Moderate-intensity physical activity and cardiovascular risk factors: The Stanford Five-City Project. Prev Med. 1986;15:

15 CHD Risk Factors in Chinese Donnan SP, Ho SC, Woo J, Wong SL, Woo KS, Tse CY, Chan KK, Kay CS, Cheung KO, Mak KH. Risk factors for acute myocardial infarction in a southern Chinese population. Ann Epidemiol. 1994;4(1): Woo J, Ho SC, Yuen YK, Yu LM, Lau J. Cardiovascular risk factors and 18-month mortality and morbidity in an elderly Chinese population aged 70 years and over. Gerontology 1998;44(1): Hui SC, Morrow JR Jr. Level of participation and knowledge of physical activity in Hong Kong Chinese adults and their association with age. J Aging Phys Act. 2001;9(4): Morrow JR Jr, Blair SN. Promoting the Surgeon General s report on physical activity and health: activities of the NCPPA. Quest, 1999;51(2): Shephard RJ. Alive Man: The Physiology of Physical Activity. Springfield, IL: Charles C. Thomas, 1972: Mahar MT, Jackson AS, Ross RM, Pivarnik JM, Pollock ML. Predictive accuracy of single and double stage submax treadmill work for estimating aerobic capacity. Med Sci Sports Exerc. 1985;17: Thomas GN, Critchley JAJH, Tomlinson B, Anderson PJ, Lee ZSK, Chan JCN. Obesity, independent of insulin resistance, is a major determinant of blood pressure in normoglycaemic Hong Kong Chinese. Metabolism 2000;49: American College of Sports Medicine. ACSM s Guidelines for Exercise Testing and Prescription (6th ed.). Baltimore, MD: Lippincott Williams & Wilkins, 2000:24, World Health Organization. The Asia-Pacific Perspective: Redefining Obesity and Its Treatment. WHO: Western Pacific Region, 2000: Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults: Executive Summary of the Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). JAMA. 2001; 285: Blair SN, Kampert JB, Kohl HW, Barlow CE, Macera CA, Paffenbarger RS Jr, Gibbons LW. Influences of cardiorespiratory fitness and other precursors on cardiovascular disease and all-cause mortality in men and women. JAMA. 1996;276(3): Hui SC, Morrow JR Jr, Leung WC. Comparison of the physical activity levels between American adults and Hong Kong Chinese adults. Med Sci Sports Exerc. 1999;31(5): S165, # Janus ED. Epidemiology of cardiovascular risk factors in Hong Kong. Clin Exp Pharmacol Physiol. 1997;24(12): Blair SN. Physical Activity, physical fitness, and health. Res Q Exerc Sport 1993;64: Lamonte MJ, Eisenman PA, Adams TD, Shultz BB, Ainsworth BE, Yanowitz FG. Cardiovascular fitness and coronary heart disease risk factors: The LDS Hospital Fitness Institute cohort. Circulation 2000;102: McMurray RG, Ainsworth BE, Harrell JS, Griggs TR, Williams OD. Is physical activity or aerobic power more influential on reducing cardiovascular disease risk factors? Med Sci Sports Exerc. 1998;30: Suzuki I, Yamada H, Sugiura T, Kawakami N, Shimizu H. Cardiovascular fitness, physical activity and selected coronary heart disease risk factors in adults. J Sports Med Phys Fitness. 1998;38: Li G, Chen X, Jang Y, Wang J, Xing X, Yang W, Hu Y. Obesity, coronary heart disease risk factors and diabetes in Chinese: an approach to the criteria of obesity in the Chinese population. Obes Rev. 2002;3:

16 322 Hui et al. Physical Activity Rating Scale Appendix A I am going to read some statements about your level of activity. For these statements, keep the following in mind: The word VIGOROUS refers to activities that require significant physical effort like basketball, jogging, running, fast cycling, aerobics class, swimming laps, singles tennis, racquetball, etc. The word MODERATE refers to less intense activities like brisk walking, gardening, slow cycling, dancing, or hard work around the house. Please tell me which ONE OF THE FOLLOWING best identifies your current level of exercise. Please STOP me when I describe your current level of exercise. (Interviewer: Begin to read the list below) 1. I don t exercise/walk regularly now, and don t intend to start in the near future. 2. I don t exercise or walk regularly, but I have been thinking to start in the near future. 3. I m trying to start to exercise or walk, or I exercise or walk infrequently. 4. I m doing vigorous exercise < 3 times/wk or moderate exercise < 5 times/wk. 5. I ve been doing moderate exercise > 5 times/wk (or > 2.5 h/wk) for the last 1-6 months. 6. I ve been doing moderate exercise > 5 times/wk (or > 2.5 h/wk) for > 7 months. 7. I ve been doing vigorous exercise 3-5 times/wk for 1-6 months. 8. I ve been doing vigorous exercise 3-5 times/wk for 7 or more months.

17 CHD Risk Factors in Chinese 323 Appendix B Definitions of Coronary Heart Disease Risk Factors Risk factors Positive Family history Smoking Hypertension Hypercholesterolemia Impaired fasting glucose Obesity Negative High HDL-cholesterol Defining criteria Myocardial infarction, coronary revascularization, or sudden death before age 55 y in father or other male first-degree relative, or before age 65 in mother or other female first-degree relative Current cigarette smoker or those who quit within the previous 6 months Resting systolic blood pressure of 140 mmhg or diastolic 90 mmhg LDL-cholesterol > 3.4 mmol/l, or triglycerides > 2.4 mmol/l, or HDL-cholesterol < 0.9 mmol/l Fasting blood glucose of 6.1 mmol/l Body mass index 25 kg/m 2 or waist circumference > 90 cm for men and > 80 cm for women HDL-cholesterol > 1.6 mmol/l