The severity and influencing factors of injuries among patients attending hospitals due to falls in China, 2018
-
摘要:
目的 了解中国因跌倒/坠落就诊病例流行特征和影响损伤严重程度的因素，为制定跌倒/坠落防控措施、政策提供依据。 方法 通过提取2018年中国伤害监测系统（national injury surveillance system，NISS）中跌倒/坠落病例数据，描述其流行特征，采用多因素Logistic回归分析模型分析损伤严重程度影响因素。 结果 共收集跌倒/坠落病例500 621例。损伤严重程度以轻度为主（76.00%），中、重度损伤所占比例为24.00%。单因素分析显示，性别、年龄、城乡、发生季节、发生时段、发生地点、发生时活动、发生前饮酒情况的跌倒/坠落病例损伤严重程度差异具有统计学意义（均有P＜0.001）。多因素分析显示，男性（OR=1.056，95% CI：1.041~1.071）；年龄为5~岁（OR=1.412，95% CI：1.366~1.460）、15~岁（OR=1.382，95% CI：1.337~1.427）、30~岁（OR=1.844，95% CI：1.787~1.903）、45~岁（OR=2.746，95% CI：2.666~2.829）、≥65岁（OR=4.524，95% CI：4.390~4.663）；夏季（OR=1.097，95% CI：1.077~1.118）、秋季（OR=1.110，95% CI：1.089~1.131）、冬季（OR=1.137，95% CI：1.116~1.159）；地点为家中（OR=1.169，95% CI：1.143~1.196）、学校与公共场所（OR=1.102，95% CI：1.069~1.136）、体育和运动场所（OR=1.066，95% CI：1.016~1.119）、工业和建筑场所（OR=1.800，95% CI：1.727~1.877）、农场/农田（OR=1.257，95% CI：1.196~1.320）；活动为步行（OR=1.084，95% CI：1.045~1.126）；发生前饮酒（OR=1.318，95% CI：1.257~1.381）是中重度损伤的危险因素。 结论 中国因跌倒/坠落就诊患者中重度损伤占一定比例，且影响因素较多，相关部门应开展针对性的防控工作。 Abstract:Objective To analyze the epidemiological characteristic and influencing factors of injury severity among patients attending hospitals due to falls in China, so as to provide the evidence for the work of preventing falls and the formulation of policies. Methods Descriptive analysis was applied by using the data from National Injury Surveillance System (NISS). Multivariate logistic regression was used for analysis on influencing factors of injury severity. Results In total, 500 621 cases of falls were collected by NISS. The injury severity was mainly mild (76.00%), and moderate and severe injury accounted for 24.00%. Results of univariate analysis showed that gender, age, urban-rural, season, time, places, drinking condition before falls, and activities when falls occurred were influencing factors of injury severity. The multivariate analysis showed that male (OR=1.056, 95% CI:1.041-1.071), age group of 5-years old (OR=1.412, 95% CI:1.366-1.460), 15-years old (OR=1.382, 95% CI:1.337-1.427), 30-years old (OR=1.844, 95% CI:1.787-1.903), 45-years old (OR=2.746, 95% CI:2.666-2.829) and 65 years old and older (OR=4.524, 95% CI:4.390-4.663), occurring in summer (OR=1.097, 95% CI:1.077-1.118), autumn (OR=1.110, 95% CI:1.089-1.131) and winter (OR=1.137, 95% CI:1.116-1.159), places where falls occurred were home (OR=1.169, 95% CI:1.143-1.196), school and school-related area (OR=1.102, 95% CI:1.069-1.136), sports and athletics area (OR=1.066, 95% CI:1.016-1.119), industrial and construction area (OR=1.800, 95% CI:1.727-1.877) and farm/farmland (OR=1.257, 95% CI:1.196-1.320), activity when falls occurred was walking (OR=1.084, 95% CI:1.045-1.126), and drinking condition before falls (OR=1.318, 95% CI:1.257-1.381) were risk factors of injury severity for falls. Conclusions Moderate and severe injuries account for a certain proportion of patients treated for falls and the influencing factors are various. Relevant departments should carry out targeted falls prevention and control. -
Key words:
- Falls /
- Severity /
- Surveillance /
- Influencing factors
-
表 1 多因素Logistic回归分析模型变量赋值说明
Table 1. Variable assignment description in multiple Logistic regression analysis
变量 赋值 中重度伤害 0=否，1=是 性别 0=女，1=男 年龄(岁) 0=0~，1=5~，2=15~，3=30~，4=45~，5=≥65 城乡 0=城市，1=农村 季节 0=春季，1=夏季，2=秋季，3=冬季 时间 0=1:00~，1=7:00~，2=13:00~，3=19:00~ 伤害发生地点 0=公共居住场所，1=家中，2=学校与公共场所，3=体育和运动场
所，4=公路/街道，5=贸易和服务场所，6=工业和建筑场所，7=农
场/农田，8=其他，9=不清楚伤害发生时活动 0=工作，1=家务，2=学习，3=体育活动，4=休闲活动，5=生命活动，
6=驾乘交通工具，7=步行，8=其他，9=不清楚发生前饮酒情况 0=未饮用，1=饮用，2=不清楚 
下载: 导出CSV
表 2 2018年全国伤害监测系统跌倒/坠落病例特征[n (%)]
Table 2. The characteristics of falls from the National Injury Surveillance System in 2018 [n (%)]
特征 总病例数 轻度伤害病例 中重度伤害病例 X2值a P值 性别 63.830 ＜0.001 女 212 893(42.53) 160 609(42.21) 52 284(43.52) 男 287 728(57.47) 219 872(57.79) 67 856(56.48) 年龄(岁) 20 468.066 ＜0.001 0~ 55 909(11.17) 48 780(12.82) 7 129(5.93) 5~ 72 551(14.49) 60 318(15.85) 12 233(10.18) 15~ 83 129(16.61) 68 838(18.09) 14 291(11.90) 30~ 90 510(18.08) 70 344(18.49) 20 166(16.79) 45~ 127 622(25.49) 89 698(23.57) 37 924(31.57) ≥65 70 900(14.16) 42 503(11.17) 28 397(23.64) 城乡 60.513 ＜0.001 城市 366 086(73.13) 279 274(73.40) 86 812(72.26) 农村 134 535(26.87) 101 207(26.60) 33 328(27.74) 季节 420.109 ＜0.001 春季 138 099(27.59) 107 561(28.27) 30 538(25.42) 夏季 128 067(25.58) 96 896(25.47) 31 171(25.95) 秋季 120 079(23.99) 90 748(23.85) 29 331(24.41) 冬季 114 376(22.85) 85 276(22.41) 29 100(24.22) 时间 453.146 ＜0.001 1：00~ 19 154(3.83) 14 007(3.68) 5 147(4.28) 7：00~ 191 138(38.18) 144 099(37.87) 47 039(39.15) 13：00~ 179 309(35.82) 135 498(35.61) 43 811(36.47) 19：00以上 111 020(22.18) 86 877(22.83) 24 143(20.10) 伤害发生地点 5 636.923 ＜0.001 公共居住场所 73 878(14.76) 57 947(15.23) 15 931(13.26) 家中 183 198(36.59) 136 245(35.81) 46 953(39.08) 学校与公共场所 53 936(10.77) 43 373(11.40) 10 563(8.79) 体育和运动场所 18 119(3.62) 14 392(3.78) 3 727(3.10) 公路/街道 104 949(20.96) 82 279(21.62) 22 670(18.87) 贸易和服务场所 20 470(4.09) 16 118(4.24) 4 352(3.62) 工业和建筑场所 28 376(5.67) 17 423(4.58) 10 953(9.12) 农场/农田 10 921(2.18) 7 227(1.90) 3 694(3.07) 其他 661(0.13) 469(0.12) 192(0.16) 不清楚 6 113(1.22) 5 008(1.32) 1 105(0.92) 发生时活动 5 713.943 ＜0.001 工作 4 9071(9.80) 32 889(8.64) 16 182(13.47) 家务 58 350(11.66) 41 882(11.01) 16 468(13.71) 学习 6 062(1.21) 4 972(1.31) 1 090(0.91) 体育活动 3 2157(6.42) 25 803(6.78) 6 354(5.29) 休闲活动 182 468(36.45) 146 545(38.52) 35 923(29.90) 生命活动 57 280(11.44) 43 560(11.45) 13 720(11.42) 驾乘交通工具 24 033(4.80) 18 672(4.91) 5 361(4.46) 步行 74 600(14.90) 53 823(14.15) 20 777(17.29) 其他 2 940(0.59) 2 239(0.59) 701(0.58) 不清楚 13 660(2.73) 10 096(2.65) 3 564(2.97) 发生前饮酒情况 123.070 ＜0.001 未饮用 480 759(96.03) 365 909(96.17) 114 850(95.60) 饮用 9 409(1.88) 6 703(1.76) 2 706(2.25) 不清楚 10 453(2.09) 7 869(2.07) 2 584(2.15)
下载: 导出CSV
表 3 跌倒伤害严重程度影响因素Logistic回归分析
Table 3. Logistic regression analysis of influencing factors for injury severity of falls
特征 β值 S值 wald χ2值 OR(95%CI)值 P值 性别 女 1.000 男 0.055 0.007 57.867 1.056 (1.041~1.071) ＜0.001 年龄(岁) 16 111.767 ＜0.001 0~ 1.000 5~ 0.345 0.017 416.155 1.412 (1.366~1.460) ＜0.001 15~ 0.323 0.017 375.681 1.382 (1.337~1.427) ＜0.001 30~ 0.612 0.016 1 454.166 1.844 (1.787~1.903) ＜0.001 45~ 1.010 0.015 4 444.713 2.746 (2.666~2.829) ＜0.001 ≥65 1.509 0.015 9 619.697 4.524 (4.390~4.663) ＜0.001 城乡 城市 1.000 农村 -0.047 0.008 36.013 0.954 (0.939~0.954 )＜0.001 季节 207.430 ＜0.001 春季 1.000 夏季 0.093 0.010 95.713 1.097 (1.077~1.118) ＜0.001 秋季 0.104 0.010 117.709 1.110 (1.089~1.131) ＜0.001 冬季 0.128 0.010 176.186 1.137 (1.116~1.159) ＜0.001 时间 270.949 ＜0.001 1:00~ 1.000 7:00~ -0.274 0.018 231.464 0.761 (0.734~0.788) ＜0.001 13:00~ -0.199 0.018 122.404 0.819 (0.791~0.849) ＜0.001 19:00以上 -0.219 0.019 139.192 0.804 (0.775~0.833) ＜0.001 伤害发生地点 2 177.042 ＜0.001 公共居住场所 1.000 家中 0.156 0.011 186.170 1.169 (1.143~1.196) ＜0.001 学校与公共场所 0.097 0.016 38.500 1.102 (1.069~1.136) ＜0.001 体育和运动场所 0.064 0.025 6.681 1.066 (1.016~1.119) 0.010 公路/街道 -0.178 0.013 189.740 0.837 (0.816~0.859) ＜0.001 贸易和服务场所 -0.110 0.021 28.076 0.896 (0.860~0.933) ＜0.001 工业和建筑场所 0.588 0.021 767.868 1.800 (1.727~1.877) ＜0.001 农场/农田 0.228 0.025 81.582 1.257 (1.196~1.320) ＜0.001 其他 0.245 0.089 7.644 1.277 (1.074~1.519) 0.006 不清楚 -0.426 0.039 117.096 0.653 (0.604~0.705) ＜0.001 发生时活动 1 304.030 ＜0.001 工作 1.000 家务 -0.237 0.020 140.673 0.789 (0.759~0.821) ＜0.001 学习 -0.205 0.039 28.143 0.814 (0.755~0.878) ＜0.001 体育活动 -0.073 0.025 8.242 0.930 (0.885~0.977) 0.004 休闲活动 -0.273 0.018 229.859 0.761 (0.735~0.788) ＜0.001 生命活动 -0.144 0.020 52.247 0.866 (0.833~0.900) ＜0.001 驾乘交通工具 -0.016 0.024 0.438 0.984 (0.938~1.032) 0.508 步行 0.081 0.019 18.031 1.084 (1.045~1.126) ＜0.001 其他 -0.096 0.047 4.085 0.909 (0.828~0.997) 0.043 不清楚 0.073 0.027 7.503 1.076 (1.021~1.133) 0.006 发生前饮酒情况 132.578 ＜0.001 未饮用 1.000 饮用 0.276 0.024 132.193 1.318 (1.257~1.381) ＜0.001 不清楚 -0.066 0.024 0.078 0.993 (0.948~1.041) 0.781
下载: 导出CSV
-
[1] Kyu HH, Abate D, Abate KH, et al. Global, regional, and national disability-adjusted life-years (DALYs) for 359 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990-2017:a systematic analysis for the global burden of disease study 2017[J]. Lancet, 2018, 392:1859-922. DOI: 10.1016/S0140-6736(18)32335-3. [2] James SL, Lucchesi LR, Bisignano C, et al. The global burden of falls:global, regional and national estimates of morbidity and mortality from the Global Burden of Disease Study 2017[J]. Injury Prev, 2020, 26(suppl 1):1-9. DOI: 10.1136/injuryprev-2019-043286. [3] 中国疾病预防控制中心慢病非传染病预防控制中心, 国家卫生和健康委统计信息中心.中国死因监测数据集2018[M].北京:中国科学技术出版社, 2019.National center for chronic and noncommunicable disease control and prevention, Chinese center for disease control and prevention, statistical information center of the national health commission. The national death surveillance data sets 2018[M]. Beijing:China science and technology press, 2019. [4] 中国疾病预防控制中心慢性非传染性疾病预防控制中心, Safe kids.中国青少年儿童伤害现状回顾报告[M].北京:人民卫生电子音像出版社, 2018.National center for chronic and noncommunicable disease control and prevention, Chinese center for disease control and prevention, Safe kids. Injury review of Chinese adolescent and children[M]. Beijing:People's health electronic audio-visual publishing house, 2018. [5] Gill TM, Munoz B, West SK, et al. Association of injurious falls with disability outcomes and nursing home admissions in community-living older persons[J]. Am J Epidemiol, 2013, 178(3):418-425. DOI: 10.1093/aje/kws554. [6] Haagsma JA, Graetz N, Bolliger I, et al. The global burden of injury:incidence, mortality, disability-adjusted life years and time trends from the Global Burden of Disease Study 2013[J]. Injury Prev, 2016, 22(1):3-18. DOI: 10.1136/injuryprev-2015-041616. [7] Florence CS, Bergen G, Atherly A, et al. Medical costs of fatal and nonfatal falls in older adults[J]. J Am Geriatr Soc, 2018, 66(4):693-698. DOI: 10.1111/jgs.15304. [8] 中国疾病预防控制中心慢性非传染性疾病预防控制中心.全国伤害医院监测数据集(2018)[M].北京:人民卫生电子音像出版社, 2020.National center for chronic and non-communicable disease control and prevention, Chinese center for disease control and prevention. National injury surveillance dataset (2018)[M]. Beijing:People's health electronic audio-visual publishing house, 2020. [9] 汪媛, 段蕾蕾, 纪翠蓉, 等. 2006-2012年全国伤害监测工作状况评估[J].中华流行病学杂志, 2015, 36(9):967-970. DOI: 10.3760/cma.j.issn.0254-6450.2015.09.013.Wang Y, Duan LL, Ji CR, et al. Evaluation of performance of national injury surveillance in China, 2006-2012[J]. Chin J Epidemiol, 2015, 36(9):967-970. DOI: 10.3760/cma.j.issn.0254-6450.2015.09.013. [10] World Health Organization. WHO global report on falls prevention in older age[R]. WHO Library Cataloguing in Publication Data, 2008. [11] 耳玉亮, 段蕾蕾, 汪媛, 等. 2008-2013年全国伤害监测系统中跌倒/坠落病例特征分析[J].中华流行病学杂志, 2015, 36(1):12-16. DOI: 10.3760/cma.j.issn.0254-6450.2015.01.004.Er YL, Duan LL, Wang Y, et al. Analysis on data from Chinese National Injury Surveillance System, 2008-2013 on the characteristics of Falls[J]. Chin J Epidemiol, 2015, 36(1):12-16. DOI: 10.3760/cma.j.issn.0254-6450.2015.01.004. [12] Kim SH. Risk factors for severe injury following indoor and outdoor falls in geriatric patients[J]. Arch Gerontol Geriatr, 2016, 62:75-82. DOI: 10.1016/j.archger.2015.10.003. [13] Christian F, Lars BL. The mechanism and severity of nonoccupational ladder fall injuries[J]. J Safety Research, 2001, 32:333-343. DOI: 10.1016/S0022-4375(01)00054-8. [14] Nelson HD, Haney EM, Dana T, et al. Screening for osteoporosis:an update for the US Preventive Services Task Force[J]. Ann Intern Med, 2010, 153(2):99-111. DOI: 10.7326/0003-4819-153-2-201007200-00262. [15] Hemenway D, Colditz GA. The effect of climate on fractures and deaths due to falls among white women[J]. Accid Anal Prev, 1990, 22(1):59-65. DOI: 10.1016/0001-4575(90)90007-8. [16] Vieira ER, Palmer RC, Chaves PH. Prevention of falls in older people living in the community[J]. BMJ, 2016, 28(353):i1419. DOI: 10.1136/bmj.i1419. [17] Bertocci GE, Pierce MC, Deemer E, et al. Influence of fall height and impact surface on biomechanics of feet-first free falls in children[J]. Injury, 2004, 35(4):417-424. DOI: 10.1016/S0020-1383(03)00062-7. -
