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基于随机森林分析广西地区20~39岁青年人超重及肥胖的影响因素

彭迎春 莫海娟 赖银娟 黄志碧 罗茜倩 韦瑜群

彭迎春, 莫海娟, 赖银娟, 黄志碧, 罗茜倩, 韦瑜群. 基于随机森林分析广西地区20~39岁青年人超重及肥胖的影响因素[J]. 中华疾病控制杂志, 2021, 25(6): 734-738. doi: 10.16462/j.cnki.zhjbkz.2021.06.020
引用本文: 彭迎春, 莫海娟, 赖银娟, 黄志碧, 罗茜倩, 韦瑜群. 基于随机森林分析广西地区20~39岁青年人超重及肥胖的影响因素[J]. 中华疾病控制杂志, 2021, 25(6): 734-738. doi: 10.16462/j.cnki.zhjbkz.2021.06.020
PENG Ying-chun, MO Hai-juan, LAI Yin-juan, HUANG Zhi-bi, LUO Qian-qian, WEI Yu-qun. Influential factors of overweight and obesity in young adults aged 20 to 39 in Guangxi based on random forest algorithm[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2021, 25(6): 734-738. doi: 10.16462/j.cnki.zhjbkz.2021.06.020
Citation: PENG Ying-chun, MO Hai-juan, LAI Yin-juan, HUANG Zhi-bi, LUO Qian-qian, WEI Yu-qun. Influential factors of overweight and obesity in young adults aged 20 to 39 in Guangxi based on random forest algorithm[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2021, 25(6): 734-738. doi: 10.16462/j.cnki.zhjbkz.2021.06.020

基于随机森林分析广西地区20~39岁青年人超重及肥胖的影响因素

doi: 10.16462/j.cnki.zhjbkz.2021.06.020
基金项目: 

广西中青年教师科研基础能力提升项目 2020KY26008

详细信息
    通讯作者:

    莫海娟,E-mail:mo18729026426@163.com

  • 中图分类号: R723.14

Influential factors of overweight and obesity in young adults aged 20 to 39 in Guangxi based on random forest algorithm

Funds: 

The Project of Improving the Basic Scientific Research Ability of Young and Middle-aged Teachers in Guangxi 2020KY26008

More Information
  • 摘要:   目的  探讨广西地区20~39岁青年人的交通方式、工作状态、闲暇时间的活动对超重和肥胖的影响,为提高全民身体素质水平提供参考意见。  方法  对广西14个地市的国民体质监测中心监测点的20~39岁青年人进行随机整群抽样,共纳入7 534例研究对象。将其分成20~<30岁、30~39岁两组资料过采样处理后建立随机森林分类模型。  结果  根据基尼指数的下降幅度对变量重要性排序结果显示:20~<30岁青年超重和肥胖的影响因素主要为骑摩托车、电动车时长,读书、用电脑等时长,看电视、听广播时长,以静坐伏案为主时长,轻家务劳动时长;30~39岁青年超重和肥胖的影响因素主要为骑摩托车或电动车时长,看电视、听广播时长,读书、用电脑等时长,轻家务劳动时长,以静坐伏案为主时长。  结论  人们要尽量缩短静坐行为的持续时间。短距离路程尽量选择骑自行车和步行,工作方式与闲暇活动方面避免久坐,增加科学规律的体育锻炼。
  • 图  1  20~<30岁的变量个数、树的数量调整的袋外错误率

    Figure  1.  OOB error of mtry and ntree adjustment in 20- < 30 years of age

    图  2  30~39岁变量个数、树的数量调整的袋外错误率

    Figure  2.  OOB error of mtry and ntree adjustment in 30-39 years of age

    图  3  广西地区20~<30岁青年超重与肥胖影响因素重要性的排序

    Figure  3.  Ranking of influencing factors of overweight and obesity in 20- < 30 years in Guangxi

    图  4  广西地区30~39岁青年超重与肥胖影响因素重要性的排序

    Figure  4.  Ranking of influencing factors of overweight and obesity in 30-39 years in Guangxi

    表  1  研究对象样本构成[n(%)]

    Table  1.   The composition of the research object sample [n(%)]

    年龄(岁) 体重正常 超重、肥胖 χ2 P
    20~<30 2 851(55.36) 846(35.49) 257.519 < 0.001
    30~39 2 299(44.64) 1 538(64.51)
    下载: 导出CSV

    表  2  体重影响指标的代码

    Table  2.   Codes for the weight impact indicators

    类别 代码
    交通方式
      乘车(船) BUS
      自驾私家车 DRIVE
      骑摩托车、电动车 MOTO
      骑自行车 BIKE
      步行 WALK
    工作时状态
      以静坐伏案为主 SED
      工作中静坐并伴有上肢活动或以站为主 ULM
      以走为主 AMB
      搬运、举重物或挖掘 CARRY
    闲暇时活动
      看电视、听广播 TV
      下棋、打牌等 CHESS
      读书、用电脑等 READ
      散步 STROLL
      轻家务劳动 LHW
      重家务劳动 HHW
    下载: 导出CSV

    表  3  各个年龄段训练集和测试集的模型评估结果

    Table  3.   Model evaluation results of training sets and test sets for each age group

    年龄(岁) 数据集 实际情况 预测体重正常(人) 预测超重、肥胖(人) 准确率(%)
    20~<30 训练集 体重正常 1 746 242 92.59
    超重、肥胖 53 1 940
    测试集 体重正常 727 136 68.65
    超重、肥胖 217 46
    30~39 训练集 体重正常 1 169 409 78.89
    超重、肥胖 257 1 319
    测试集 体重正常 547 174 58.02
    超重、肥胖 315 129
    全年龄段 训练集 体重正常 2 850 718 85.32
    超重、肥胖 330 3 240
    测试集 体重正常 1 243 339 60.68
    超重、肥胖 578 172
    下载: 导出CSV
  • [1] Guglielmi V, Sbraccia P. Obesity phenotypes: depot-differences in adipose tissue and their clinical implications[J]. Eat Weight Disord, 2018, 23(1): 3-14. DOI: 10.1007/s40519-017-0467-9.
    [2] Yang T, Yu L, Barnett R, et al. Contextual influences affecting patterns of overweight and obesity among university students: a 50 universities population-based study in China[J]. Int J Health Geogr, 2017, 16(1): 18. DOI: 10.1186/s12942-017-0092-x.
    [3] Bray GA, Frühbeck G, Ryan DH, et al. Management of obesity[J]. Lancet, 2016, 387(10031): 1947-1956. DOI: 10.1016/s0140-6736(16)00271-3.
    [4] Alghamdi M, Al-Mallah M, Keteyian S, et al. Predicting diabetes mellitus using SMOTE and ensemble machine learning approach: The Henry Ford ExercIse Testing (FIT) project[J]. PLoS One, 2017, 12(7): e0179805. DOI: 10.1371/journal.pone.0179805.
    [5] 吕红燕, 冯倩. 随机森林算法研究综述[J]. 河北省科学院学报, 2019, 36(3): 37-41. DOI: 10.16191/j.cnki.hbkx.2019.03.005.

    Lyu HY, Feng Q. A review of random forests algorithm[J]. Journal of the Hebei Academy of Sciences, 2019, 36(3): 37-41. DOI: 10.16191/j.cnki.hbkx.2019.03.005.
    [6] Kanerva N, Erkkola M, Nevalainen J, et al. Random forest analysis in identifying the importance of obesity risk factors[J]. European Journal of Public Health, 2013, 23(Supplement): 1. DOI: 10.1093/eurpub/ckt124.042.
    [7] 中国肥胖问题工作组. 中国成人超重和肥胖症预防与控制指南(节录)[J]. 营养学报, 2004(1): 1-4. https://www.cnki.com.cn/Article/CJFDTOTAL-YYXX200401004.htm

    Working Group of Obesity in China. Guidelines for the prevention and control of overweight and obesity in Chinese adults (excerpt)[J]. Acta Nutr Sin, 2004(1): 1-4. https://www.cnki.com.cn/Article/CJFDTOTAL-YYXX200401004.htm
    [8] 唐蓉. 基于随机森林回归的青年人体质影响因素研究[D]. 南昌: 华东交通大学, 2016.

    Tang R. Research on influence factors of young people physical fitness based on random forest regression[D]. Nanchang: East China Jiaotong University, 2016.
    [9] 闫慈, 田翔华, 阿拉依·阿汗, 等. 基于重采样技术在医学不平衡数据分类中的应用研究[J]. 中国卫生统计, 2018, 35(2): 177-180, 185. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGWT201802004.htm

    Yan C, Tian XH, Alayi AH, et al. Application of the resampling technology in the classification of imbalanced medical datasets[J]. Chin J Heal Stat, 2018, 35(2): 177-180, 185. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGWT201802004.htm
    [10] Janitza S, Hornung R. On the overestimation of random forest's out-of-bag error[J]. PLoS One, 2018, 13(8): e0201904. DOI: 10.1371/journal.pone.0201904.
    [11] Biddle SJH, García Bengoechea E, Pedisic Z, et al. Erratum to: screen time, other sedentary behaviours, and obesity risk in adults: a review of reviews[J]. Curr Obes Rep, 2017, 6(3): 352. DOI: 10.1007/s13679-017-0267-6.
    [12] Tumin R, Anderson SE. Television, home-cooked meals, and family meal frequency: associations with adult obesity[J]. J Acad Nutr Diet, 2017, 117(6): 937-945. DOI: 10.1016/j.jand.2017.01.009.
    [13] Al-Hanawi MK, Chirwa GC, Pemba LA, et al. Does prolonged television viewing affect body mass index? A case of the Kingdom of Saudi Arabia[J]. PLoS One, 2020, 15(1): e0228321. DOI: 10.1371/journal.pone.0228321.
    [14] Goh EK, Kim OY, Jeon HJ. Depression is a mediator for the relationship between physical symptom and psychological well-being in obese people[J]. Clin Nutr Res, 2017, 6(2): 89-98. DOI: 10.7762/cnr.2017.6.2.89.
    [15] 栗华, 张敬一, 张中朝, 等. 河北省成年居民超重肥胖流行特征及相关因素的调查分析[J]. 实用预防医学, 2007, 14(2): 283-286. DOI: 10.3969/j.issn.1006-3110.2007.02.009.

    Li H, Zhang JY, Zhang ZC, et al. Investigation on epidemiological characteristics and related factors of overweight and obesity among adult residents in Hebei Province[J]. Pract Prev Med, 2007, 14(2): 283-286. DOI: 10.3969/j.issn.1006-3110.2007.02.009.
    [16] Yang L, Hu L, Hipp JA, et al. Cross-sectional associations of active transport, employment status and objectively measured physical activity: analyses from the National Health and Nutrition Examination Survey[J]. J Epidemiol Community Health, 2018, 72(9): 764-769. DOI: 10.1136/jech-2017-210265.
    [17] 熊荣, 袁丽凤, 杨进刚, 等. 自行车拥有状况与体力活动、静坐时间及超重或肥胖的关系研究[J]. 中国循环杂志, 2018, 33(3): 251-255. DOI: 10.3969/j.issn.1000-3614.2018.03.010.

    Xiong R, Yuan LF, Yang JG, et al. Correlation study between bicycle ownership status and physical activity, time of sitting, overweight or obesity[J]. Chin Circ J, 2018, 33(3): 251-255. DOI: 10.3969/j.issn.1000-3614.2018.03.010.
    [18] Nam JY, Kim J, Cho KH, et al. Associations of sitting time and occupation with metabolic syndrome in South Korean adults: a cross-sectional study[J]. BMC Public Health, 2016, 16: 943. DOI: 10.1186/s12889-016-3617-5.
    [19] Drenowatz C, Hand GA, Shook RP, et al. The association between different types of exercise and energy expenditure in young nonoverweight and overweight adults[J]. Appl Physiol Nutr Metab, 2015, 40(3): 211-217. DOI: 10.1139/apnm-2014-0310.
    [20] Jiang Y, Wang J, Wu S, et al. Association between take-out food consumption and obesity among Chinese university students: a cross-sectional study[J]. Int J Environ Res Public Health, 2019, 16(6): 1071. DOI: 10.3390/ijerph16061071.
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出版历程
  • 收稿日期:  2020-11-23
  • 修回日期:  2021-02-04
  • 刊出日期:  2021-06-10

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