2015年中国十五省老年居民屏幕静坐时间及与肥胖的关联
Screen-based sedentary time and its association with obesity of elderly residents in 15 provinces of China in 2015
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摘要:
背景 静坐时间是肥胖的独立危险因素。
目的 了解我国老年居民屏幕静坐时间现状，分析其屏幕静坐时间与肥胖的关系，为指导老年人肥胖干预提供科学依据。
方法 研究资料来源于2015年“中国居民营养状况变迁的队列研究”数据，以该队列中我国十五省（直辖市、自治区）（后简称：十五省）的60岁及以上老年居民作为研究对象，通过问卷收集受访者过去一年平均每周的静坐时间（屏幕、非屏幕静坐时间）、身体活动情况，并测量其身高、体重、腰围等指标。采用方差分析法对不同性别、年龄、城乡、身体活动水平者的平均屏幕静坐时间差异进行比较。采用卡方检验对不同屏幕静坐时间水平者的性别、年龄、城乡、身体活动水平的分布差异进行分析。采用多元线性回归分析不同屏幕静坐时间水平与腰围、体重指数（BMI）的关系。采用多因素logistic回归分析不同屏幕静坐时间水平者的中心性肥胖及肥胖（BMI ≥28kg/m2）的患病风险。
结果 2015年中国十五省5047名60岁以上老年居民平均总屏幕静坐时间为（19.7±17.3）h/周，其中平均电视时间为（18.7±16.4）h/周，平均电脑时间为（1.0±5.3）h/周；非屏幕静坐时间为（1.2±5.3）h/周。总屏幕时间：男性（20.8±18.0）h/周高于女性（18.7±16.5）h/周（P < 0.001），随年龄升高而下降（P趋势=0.022），城市（21.4±17.8）h/周高于农村（18.4±16.8）h/周（P < 0.001）。老年居民的低、中、高水平屏幕静坐时间的构成比分别为40.4%、41.6%和18.0%。高水平屏幕静坐时间的比率：男性（20.6%）高于女性（15.6%）（P < 0.001），随年龄增加呈下降趋势（P趋势 < 0.001），城市（22.4%）高于农村（14.7%）（P < 0.001），随身体活动水平增加呈下降趋势（P趋势 < 0.001）。女性老年居民的腰围、中心性肥胖率与屏幕静坐时间水平呈正相关：与低水平屏幕静坐时间者相比，中、高水平屏幕静坐时间者的腰围分别增加1.316 cm（P=0.019）和1.708 cm（P=0.026），中心性肥胖的相对危险度OR及其95% CI分别为1.209（1.009~1.449）和1.316（1.024~1.691）。
结论 中国十五省老年居民的平均屏幕静坐时间、高水平屏幕静坐时间比率与性别、城乡、年龄相关，除此之外，高水平屏幕静坐时间比率还与身体活动水平相关。女性老年居民较高水平的屏幕静坐时间与腰围、中心性肥胖的患病风险呈正相关。
Abstract:Background Sedentary time is an independent risk factor for obesity.
Objective This study is designed to understand the status quo of screen-based sedentary time of elderly residents in China, analyze its relationship with obesity, so as to provide a scientific basis for making obesity intervention strategies for elderly residents.
Methods The data were derived from the China Nutritional Transition Cohort Study 2015, where elderly residents aged 60 years and above in 15 provinces (including municipalities and autonomous regions) (hereinafter referred to as 15 provinces) in China were selected as study subjects and were asked to complete a questionnaire on average weekly sedentary time (screenbased and non-screen-based) and physical activity in the past year, as well as anthropometric measurements such as height, weight, and waist circumference. Variance analysis was used to compare average screen-based sedentary time between different gender, age, residence, and physical activity level groups. Chi-square test was used to analyze the distribution differences in gender, age, residence, and physical activity level among subjects with different screen-based sedentary time. Multiple linear regression was used to analyze the relationship of screen-based sedentary time with waist circumference and body mass index (BMI). Multivariate logistic regression was used to analyze the risk of central obesity and obesity (BMI≥28kg/m2) at different screen-based sedentary time levels.
Results The average screen-based sedentary time of 5 047 elderly residents aged 60 years and above in 15 provinces of China in 2015 was (19.7±17.3) h/week, among which the average TV time was (18.7±16.4) h/week and the average computer time was (1.0±5.3) h/week; the average non-screen-based sedentary time was (1.2±5.3) h/week. The average screen-based sedentary time was higher in males (20.8±18.0) h/week than in females (18.7±16.5) h/week (P < 0.001), decreasing with older age (Ptrend=0.022), and higher in urban areas (21.4±17.8) h/week than in rural areas (18.4±16.8) h/week (P < 0.001). The proportions of low, middle, and high levels of screen-based sedentary time was 40.4%, 41.6%, and 18.0%, respectively. The proportion of high level of screen-based sedentary time was higher in males (20.6%) than in females (15.6%) (P < 0.001), decreasing with older age (Ptrend < 0.001), and higher in urban areas (22.4%) than in rural areas (14.7%) (P < 0.001), decreasing with higher physical activity level (Ptrend < 0.001). The waist circumference and central obesity rate of elderly female residents were positively correlated with screen-based sedentary time levels: compared with the low screen-based sedentary time level, the waist circumference of those with middle and high screen-based sedentary time levels increased by 1.316 cm (P=0.019) and 1.708cm (P=0.026) respectively, and the OR(95%CI) of central obesity was 1.209 (1.009-1.449) and 1.316 (1.024-1.691), respectively.
Conclusion The average screen-based sedentary time and the proportion of high-level screen-based sedentary time of elderly residents in 15 provinces of China are correlated with gender, residence, and age. In addition, the proportion of high-level screen-based sedentary time is also correlated with physical activity level. Higher levels of screen-based sedentary time in elderly female residents are positively correlated with increased waist circumference and the risk of central obesity.
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