Patterson Freda, Lozano Alicia, Huang Liming, Perkett Mackenzie, Beeson Jacqueline, Hanlon Alexandra
Department of Behavioral Health and Nutrition, University of Delaware, Newark, Delaware, USA.
School of Nursing, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
BMJ Open. 2018 Jul 6;8(7):e019639. doi: 10.1136/bmjopen-2017-019639.
In response to a call from the American Heart Association to more clearly identify the demographic factors associated with sedentary behaviours, this study aimed to identify the hierarchy of demographic characteristics associated with the sedentary behaviours of television viewing, recreational computer use and driving.
Cross-sectional analysis of baseline data collected as part of the UK Biobank. The UK Biobank is a population cohort recruited from 22 centres across the UK. Participants aged between 37 and 73 years were recruited between 2006 and 2010.
Decision tree models were generated for the sedentary behaviour outcomes of hours/day spent television viewing, recreational computer use and all driving; a sum of time spent in these sedentary behaviours ('overall') was computed. Age, sex, race, college attendance, employment, shift-work, urban versus rural residence as well as physical activity were considered as predictors.
The analytic sample comprised 415 666 adults who were mostly female (54.2%), white (95.2%), non-college attendee (64.5%), employed (61.7%), lived in an urban centre (85.5%), with a mean age of 56.6 (SD=8.1) years. Television viewing was most common sedentary behaviour (2.7 hour/day vs 1.1 for recreational computer use and 1.0 for all driving). Males (tier 1), who did not attend college (tier 2) were the highest risk group for overall sedentary time. Adults with no college attendance (tier 1) and were retired (tier 2) were the most high-risk demographic group for television viewing. College attendees (tier 1) were highest risk for recreational computer use. Adults who were employed (tier 1), male (tier 2) and did not attend college (tier 3) were most at risk for driving CONCLUSIONS: Daily time spent in different sedentary behaviours varies by sex, employment status and college attendance status. The development of targeted interventions to reduce sedentary behaviour in different demographic subgroups is needed.
为响应美国心脏协会关于更明确地识别与久坐行为相关的人口统计学因素的呼吁,本研究旨在确定与看电视、休闲使用电脑和驾驶等久坐行为相关的人口统计学特征层次结构。
对作为英国生物银行一部分收集的基线数据进行横断面分析。英国生物银行是一个从英国22个中心招募的人群队列。2006年至2010年期间招募了年龄在37岁至73岁之间的参与者。
针对每天看电视时长、休闲使用电脑时长和所有驾驶时长等久坐行为结果生成决策树模型;计算了这些久坐行为所花费时间的总和(“总计”)。将年龄、性别、种族、大学学历、就业情况、轮班工作、城乡居住情况以及身体活动作为预测因素。
分析样本包括415666名成年人,其中大多数为女性(54.2%)、白人(95.2%)、未上过大学(64.5%)、有工作(61.7%)、居住在城市中心(85.5%),平均年龄为56.6岁(标准差=8.1)。看电视是最常见的久坐行为(每天2.7小时,而休闲使用电脑为1.1小时,所有驾驶为1.0小时)。男性(第一层)、未上过大学(第二层)是久坐总时长风险最高的群体。未上过大学(第一层)且已退休(第二层)的成年人是看电视风险最高的人口统计学群体。上过大学的人(第一层)休闲使用电脑风险最高。有工作(第一层)、男性(第二层)且未上过大学(第三层)的成年人驾驶风险最高。结论:不同久坐行为的每日时长因性别、就业状况和大学学历状况而异。需要制定有针对性的干预措施来减少不同人口亚组的久坐行为。