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Several previous studies have found that healthy behaviors substantially reduce non-communicable disease incidence and mortality. The present study was performed to estimate the prevalence of four modifiable healthy behaviors and a healthy lifestyle among Korean adults according to socio-demographic and regional factors.
We analyzed data from 199 400 Korean adults aged 19 years and older who participated in the 2010 Korean Community Health Survey. We defined a healthy lifestyle as a combination of four modifiable healthy behaviors: non-smoking, moderate alcohol consumption, regular walking, and a healthy weight. We calculated the prevalence rates and odds ratios of each healthy behavior and healthy lifestyle according to socio-demographic and regional characteristics.
The prevalence rates were as follows: non-smoking, 75.0% (53.7% in men, 96.6% in women); moderate alcohol consumption, 88.2% (79.7% in men, 96.9% in women); regular walking, 45.0% (46.2% in men, 43.8% in women); healthy weight, 77.4% (71.3% in men, 73.6% in women); and a healthy lifestyle, 25.5% (16.4% in men, 34.6% in women). The characteristics associated with a low prevalence of healthy lifestyle were male gender, younger age (19 to 44 years of age), low educational attainment, married, living in a rural area, living in the Chungcheong, Youngnam, or Gwangwon-Jeju region, and poorer self-rated health.
Further research should be implemented to explore the explainable factors of disparities for socio-demographic and regional characteristics to engage in the healthy lifestyle among adults.
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This study estimated the association of cardiovascular health behaviors with the risk of all-cause and cardiovascular disease (CVD) mortality in middle-aged men in Korea.
In total, 12 538 men aged 40 to 59 years were enrolled in 1993 and followed up through 2011. Cardiovascular health metrics defined the following lifestyle behaviors proposed by the American Heart Association: smoking, physical activity, body mass index, diet habit score, total cholesterol, blood pressure, and fasting blood glucose. The cardiovascular health metrics score was calculated as a single categorical variable, by assigning 1 point to each ideal healthy behavior. A Cox proportional hazards regression model was used to estimate the hazard ratio of cardiovascular health behavior. Population attributable risks (PARs) were calculated from the significant cardiovascular health metrics.
There were 1054 total and 171 CVD deaths over 230 690 person-years of follow-up. The prevalence of meeting all 7 cardiovascular health metrics was 0.67%. Current smoking, elevated blood pressure, and high fasting blood glucose were significantly associated with all-cause and CVD mortality. The adjusted PARs for the 3 significant metrics combined were 35.2% (95% confidence interval [CI], 21.7 to 47.4) and 52.8% (95% CI, 22.0 to 74.0) for all-cause and CVD mortality, respectively. The adjusted hazard ratios of the groups with a 6-7 vs. 0-2 cardiovascular health metrics score were 0.42 (95% CI, 0.31 to 0.59) for all-cause mortality and 0.10 (95% CI, 0.03 to 0.29) for CVD mortality.
Among cardiovascular health behaviors, not smoking, normal blood pressure, and recommended fasting blood glucose levels were associated with reduced risks of all-cause and CVD mortality. Meeting a greater number of cardiovascular health metrics was associated with a lower risk of all-cause and CVD mortality.
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The aim of this study was to evaluate and quantify the risk of both individual and combined health behaviors on premature mortality in middle aged men in Korea.
In total, 14 533 male subjects 40 to 59 years of age were recruited. At enrollment, subjects completed a baseline questionnaire, which included information about socio-demographic factors, past medical history, and life style. During the follow-up period from 1993 to 2008, we identified 990 all-cause premature deaths using national death certificates. A Cox proportional hazard regression model was used to estimate the hazard ratio (HR) of each health risk behavior, which included smoking, drinking, physical inactivity, and lack of sleep hours. Using the Cox model, each health behavior was assigned a risk score proportional to its regression coefficient value. Health risk scores were calculated for each patient and the HR of all-cause premature mortality was calculated according to risk score.
Current smoking and drinking, high body mass index, less sleep hours, and less education were significantly associated with all-cause premature mortality, while regular exercise was associated with a reduced risk. When combined by health risk score, there was a strong trend for increased mortality risk with increased score (
Modifiable risk factors, such as smoking, drinking, and regular exercise, have considerable impact on premature mortality and should be assessed in combination.
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