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It is reported that Facebook could be a key in mapping which geographical areas have the most overweight and obese people. Resea
It is reported that Facebook could be a key in mapping which geographical areas have the most overweight and obese people. Resea
admin
2021-08-12
58
问题
It is reported that Facebook could be a key in mapping which geographical areas have the most overweight and obese people. Researchers have found that the higher the percentage of people in a city or town with Facebook "interests" suggesting a healthy lifestyle, the lower that area’s obesity rate. At the same time, areas with a large percentage of Facebook users with television-related "interests" tend to have higher rates of obesity.
Researchers at Boston Children’s Hospital, in the US, drew these conclusions after comparing Facebook user data with data from national and New York City-focused health surveys. They looked at what Facebook users posted to their timeline, "liked" and shared with others. They then compared the percentage of users interested in healthy activities or television with details of Body Mass Index in the same area. The comparison revealed close geographic relationships between Facebook "interests" and obesity rates.
For instance, the obesity rate was 12 per cent lower in the region in the United States where the highest percentage of Facebook users expressed activity-related "interests", compared with that in the location with the lowest percentage.
Similarly, the obesity rate in the location with the highest percentage of users with television-related interests nationally was 3.9 per cent higher than the location with the lowest percentage.
The same correlation was reflected significantly in the New York City neighbourhood data as well, showing that the approach can scale from national to local-level data.
The obesity rate on Coney Island, which had the highest percentage of activity-related "interests" in the city, was 7.2 per cent lower than Southwest Queens, the neighbourhood with the lowest percentage. At the same time, the obesity rate in Northeast Bronx, the neighbourhood with the highest percentage of television-related "interests", was 27. 5 per cent higher than that in the neighbourhood with the lowest percentage—Greenpoint.
They now believe that people’s online "interests" could help public health researchers predict, tract and map obesity rates by area. The amount of data available from social networks like Facebook makes it possible to efficiently carry out research with cohorts of a size that was previously impossible. Dr. John Brownstein, from Boston Children’ s Hospital, explained: "Online social networks like Facebook represent a new high-value, low-cost data stream for looking at health at a population level. The tight correlation between Facebook users’ ’interests’ and obesity data suggests that this kind of social network and analysis could help generate real-time estimates of obesity levels in an area, target public health campaigns that would promote healthy behaviour change, and assess the success of those campaigns."
Complete the summary below with information from the passage, using no more than three words for each blank.
Recent research in a number of cities and neighbourhoods in the us has discovered a 【R1】_________between official figures for the number of people who are 【R2】_________and the type of leisure interests registered by users of Facebook in that area. In districts where Facebook users expressed a preference for sporting activities, 【R3】_________of obesity were recorded than cities where users had more passive interests like watching television. This close correlation between official 【R4】_________ and information collected from Facebook promises to facilitate research into 【R5】_________health patterns, and will, in turn, assist local authorities in targeting their public health programmes more strategically.
【R5】
选项
答案
regional
解析
文章第五段指出,同样的相关性也在纽约市的邻里数据中得到了显著的反映,表明这种方法可以从国家一级的数据扩展到地方一级的数据。由此可知,官方公共卫生数据和从脸书收集的信息之间的密切关联有望促进对区域卫生规划的研究。故空格处应填regional。
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本试题收录于:
C类竞赛(非英语专业本科)题库大学生英语竞赛(NECCS)分类
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C类竞赛(非英语专业本科)
大学生英语竞赛(NECCS)
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