免费精品AB,亚洲日韩性欧美中文字幕,鲁丝无码一区二区三区,精品久久久久久成人AV,看av免费毛片手机播放,精品国际久久久久999波多野,又黄又爽又刺激又色的视频,亚洲无线码一区二区三区在线观看

        Chinese, American scientists identify seven measures to predict heart disease risk

        Source: Xinhua| 2019-06-03 02:50:44|Editor: Shi Yinglun
        Video PlayerClose

        WASHINGTON, June 2 (Xinhua) -- Chinese and American researchers have identified seven key measures of heart health that can help predict future risk of cardiovascular disease (CVD).

        The study, published in the latest journal JAMA Network Open, reported those indicators including four behaviors that people could have control over and three biometrics that should be kept at healthy levels.

        The behaviors include no smoking, maintaining a healthy weight, eating healthy and staying physically active, and the biometrics are blood pressure, cholesterol and blood sugar, according to the study.

        Researchers from China's Kailuan General Hospital, the Pennsylvania State University and Harvard University found that people who consistently scored well in the seven metrics had a lower chance of CVD than people who did not.

        They designed a scoring system with 0 for poor, 1 for intermediate and 2 for ideal and collected data from 74,701 Chinese adults. Then they evaluated the scoring data with five distinct patterns: maintaining high, medium or low scoring, as well as increasing and decreasing scoring over time.

        They found that different living patterns are associated with different risks for developing CVD in the future.

        About 19 percent of participants who maintained a better scoring over the four years had a 79-percent lower chance of developing heart disease than people who maintained a low cardiovascular health score, according to the study.

        Also, they found that the improvement of overall cardiovascular health over time was also related to lower chance of future CVD in this population, even for those with poor scoring at the beginning of the study.

        TOP STORIES
        EDITOR’S CHOICE
        MOST VIEWED
        EXPLORE XINHUANET
        010020070750000000000000011100001381113941