重庆市机关事业单位慢性病高风险人群吸烟干预效果

陈婷; 白雅敏; 丁贤彬

doi:10.16462/j.cnki.zhjbkz.2019.11.016

重庆市机关事业单位慢性病高风险人群吸烟干预效果

doi: 10.16462/j.cnki.zhjbkz.2019.11.016

1.
400042 重庆, 重庆市疾病预防控制中心慢性病非传染性疾病预防控制所
2.
100050 北京, 中国疾病预防控制中心慢性非传染性疾病预防控制中心

基金项目:

全国慢性病高风险人群健康管理项目 MBGY-2017-003

详细信息

通讯作者:
丁贤彬, E-mail: 784702780@qq.com

中图分类号: R163
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- 被引次数: 0
出版历程
- 收稿日期: 2019-02-25
- 修回日期: 2019-06-01
- 刊出日期: 2019-11-10

Effectiveness of tobacco-control intervention program among high risk population of chronic non-communicable diseases in institutions from Chongqing

1.
Institute of Non-communicable Disease Prevention and Control, Chongqing Center for Disease Prevention and Control, Chongqing 400042, China
2.
National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China

Funds:

National Health Management Project for High Risk Populations of Chronic Non-communicable Diseases MBGY-2017-003

More Information

Corresponding author: DING Xian-bin, E-mail: 784702780@qq.com

摘要

摘要: 目的探讨分类管理干预模式对机关事业单位慢性病高风险人群吸烟状况的干预效果，为慢性病高风险人群管理工作提供科学依据。方法对重庆市四个区县机关事业单位的职工进行整群抽样，筛查出的慢性病高风险人群分别纳入干预组和对照组，干预组根据危险因素进行分级管理，对照组不主动采取任何形式的干预活动，评估采取一年的干预措施后干预组和对照组吸烟和吸烟危害认知的变化情况。结果利用倍差法回归模型分析干预措施的净效果得到，干预措施可以使研究对象吸烟率、现在吸烟率、现在每日吸烟率降低（OR=0.32，95% CI：0.21~0.49；OR=0.31，95% CI：0.20~0.48；OR=0.34，95% CI：0.21~0.54），同时，干预措施可以使研究对象对吸烟会造成严重疾病、吸烟会造成中风、吸烟会造成肺癌的知晓率提高（OR=2.19，95% CI：1.08~4.42；OR=1.73，95% CI：1.17~2.57；OR=2.17，95% CI：1.25~3.77），差异均有统计学意义（均有P < 0.05）。结论对机关事业单位慢性病高风险人群采取分类管理的干预模式可以有效地提高研究对象吸烟危害的认识水平，进而降低慢性病高风险人群的吸烟率，该干预模式是一种值得推广和应用的干预模式。
- 慢性病 /
- 高风险人群 /
- 烟草危害 /
- 认知 /
- 干预研究
Abstract: Objective To explore the effect of the classified management intervention model on the smoking status of high risk population of chronic non-communicable diseases in institutions from Chongqing, so as to provide scientific basis for the management of high risk population of chronic non-communicable diseases. Methods Workers from governments and institutions of four districts in Chongqing were sampled by cluster sampling. High risk population of non-communicable disease were screened and enrolled into the intervention group and control group. The intervention group were intervened by classified management. And the control group weren't intervened. To evaluate the change of smoking and smoking hazard cognition in intervention group and control group after one year intervention. Results The result of analysis of the net effect of intervention measures using difference in difference regression model showed that the intervention measures could reduce the smoking rate, the current smoking rate and the daily smoking rate in subjects (OR=0.32, 95% CI: 0.21-0.49; OR=0.31, 95% CI: 0.20-0.48; OR=0.34, 95% CI: 0.21-0.54). The intervention measures could increase the awareness rates of smoking causing serious diseases, stroke and lung cancer in subjects (OR=2.19, 95% CI: 1.08-4.42; OR=1.73, 95% CI: 1.17-2.57; OR=2.17, 95% CI: 1.25-3.77), the difference was statistically significant (all P < 0.05). Conclusion The intervention model of classified management for high risk population of chronic non-communicable diseases in institutions can effectively improve the awareness rate of smoking hazards among the subjects, and then reduce the smoking rate. Therefore, this intervention model is worth popularizing and applying.
- Chronic non-communicable diseases /
- Population with high risk /
- Tobacco hazards /
- Cognition /
- Intervention study

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表 1 研究人群基线人口学特征[n(%)]

Table 1. Baseline demographic characteristics of the study population[n(%)]

变量	干预组 (n=380)	对照组 (n=576)	χ²值	P值
年龄(岁)			7.372	0.061
20~	43(11.31)	88(15.28)
30~	113(29.74)	183(31.77)
40~	136(35.79)	207(35.94)
50~	88(23.16)	98(17.01)
性别			7.246	0.007
男性	182(47.89)	327(56.77)
女性	198(52.11)	249(43.23)
民族			1.478	0.224
汉族	376(98.95)	564(97.92)
其他	4(1.05)	12(2.08)
文化程度			5.327	0.255
小学及以下	11(2.89)	9(1.56)
初中	14(3.69)	36(6.25)
高中/中专/技校	48(12.63)	67(11.63)
大专	96(25.26)	154(26.74)
本科及以上	211(55.53)	310(53.82)
婚姻状况			5.713	0.017
已婚	312(82.11)	505(87.67)
其他	68(17.89)	71(12.33)
慢性病高风险因素(个)			0.002	0.965
1~	323(85.00)	489(84.90)
3~	57(15.00)	87(15.10)

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表 2 干预对研究对象吸烟及吸烟危害认知情况改变的净效果

Table 2. Net effect of intervention on the changes of smoking and smoking hazard cognition

变量	β_E	s_x^-	Wald值	OR(95% CI)值	P值
吸烟	-1.15	0.22	26.58	0.32(0.21~0.49)	< 0.001
现在吸烟	-1.16	0.22	27.19	0.31(0.2~0.48)	< 0.001
现在每日吸烟	-1.09	0.24	20.91	0.34(0.21~0.54)	< 0.001
吸烟会造成严重的疾病	0.78	0.36	4.74	2.19(1.08~4.42)	0.030
吸烟造成中风	0.55	0.20	7.46	1.73(1.17~2.57)	0.006
吸烟造成心脏病发作	0.27	0.20	1.91	1.31(0.89~1.93)	0.167
吸烟造成肺癌	0.77	0.28	7.52	2.17(1.25~3.77)	0.006

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参考文献(14)

[1]	杨焱, 南奕, 屠梦吴, 等. 《2015中国成人烟草调查报告》概要[J]. 中华健康管理学杂志, 2016, 10(2): 85-87. DOI: 10.3760/cma.j.issn.1674-0815.2016.02.002. Yang Y, Nan Y, Tu MW, et al. Major finding of 2015 China adults tobacco survery[J]. Chin J Health Manage, 2016, 10(2): 85-87. DOI: 10.3760/cma.j.issn.1674-0815.2016.02.002.
[2]	中华人民共和国卫生部. 中国吸烟危害健康报告[M]. 北京: 人民卫生出版社, 2012: 19-20. Ministry of Health of the People's Republic of China. Report on health hazards of smoking in China[M]. Beijing: People's Health Publishing House, 2012: 19-20.
[3]	高静, 丁贤彬, 陈婷, 等. 重庆市机关事业单位慢性病高风险人群吸烟现状及影响因素分析[J]. 中国慢性病预防与控制, 2018, 26(6): 405-408. DOI: 10.16386/j.cjpccd.issn.1004-6194.2018.06.002. Gao J, Ding XB, Chen T, et al. Investigation on smoking status and influencing factors in population with high risk of chronic non-communicable diseases of institutions in Chongqing[J]. Chin J Prev Contr Chron Dis, 2018, 26(6): 405-408. DOI: 10.16386/j.cjpccd.issn.1004-6194.2018.06.002.
[4]	杨天, 倪文庆. 深圳市福田区慢性病高风险人群吸烟行为现状及所致健康危害认知情况分析[J]. 慢性病学杂志, 2016, 17(5): 487-480. DOI: 10.16440/j.cnki.1674-8166.2016.05.004. Yang T, Ni WQ. Investigationon status of smoking behaviors and knowledge on tobacco harm among high-risk group of chronic non-communicable diseases in Futian District of Shenzhen City[J]. Chronic Pathematology J, 2016, 17(5): 487-480. DOI: 10.16440/j.cnki.1674-8166.2016.05.004.
[5]	卫生部疾病预防控制局. 全国慢性病预防控制工作规范[M]. 北京: 人民卫生出版社, 2011: 28-31. Department of Disease Prevention and Control, Ministry of Health. National code for the prevention and control of chronic diseases[M]. Beijing: People's Health Publishing House, 2011: 28-31.
[6]	马吉祥, 楚洁, 郭晓雷, 等. 生活方式干预对农村居民慢病及相关知识、态度、及行为的影响[J]. 中国预防医学杂志, 2010, 11(11): 1108-1112. DOI: 10.16506/j.1009-6639.2010.11.003.1108. Ma JX, Chu J, Guo XL, et al. Impact of lifestyle intervention on knowledge, attitude and behavior of chronic diseases and their risk factors in rural residents[J]. Chin Prev Med, 2010, 11(11): 1108-1112. DOI: 10.16506/j.1009-6639.2010.11.003.1108.
[7]	王健, 马军. 健康教育[M]. 北京: 高等教育出版社, 2004: 160-611. Wang J, Ma J. Health Education[M]. Beijing: Higher Education Press, 2004: 160-611.
[8]	杨华凤, 陈旭鹏, 戚圣香, 等. 南京市中小学教职工控烟干预效果分析[J]. 中国学校卫生, 2016, 37(2): 181-183. DOI: 10.16835/j.cnki.1000-9817.2016.02.007. Yang HF, Chen XP, Qi SX, et al. Effectiveness of tobacco-control intervention program among primary and secondary school staff in Nanjing[J]. Chin J Sch Health, 2016, 37(2): 181-183. DOI: 10.16835/j.cnki.1000-9817.2016.02.007.
[9]	耿梅云, 林鹏, 贾晓蓉, 等. 青岛市无烟企业创建干预效果评估[J]. 中国健康教育, 2017, 33(10): 902-905. DOI: 10.16168/j.cnki.issn.1002-9982.2017.10.009. Geng MY, Lin P, Jia XR, et al. Effect evaluation on intervention in tobacco free enterprises in Qingdao[J]. Chinese Journal of Health Education, 2017, 33(10): 902-905. DOI: 10.16168/j.cnki.issn.1002-9982.2017.10.009.
[10]	王亚莎, 肖箫, 方涛, 等. 代谢综合征患者综合干预效果研究[J]. 中华疾病控制杂志, 2017, 21(8): 784-788. DOI: 10.16462/j.cnki.zhjbkz.2017.08.008. Wang YS, Xiao X, Fang T, et al. The effect of comprehensive interventions for metabolic syndrome patients[J]. Chin J Dis Control Prev, 2017, 21(8): 784-788. DOI: 10.16462/j.cnki.zhjbkz.2017.08.008.
[11]	Lindenauer PK, Remus D, Roman S, et al. Public reporting and pay for performance in hospital quality improvement[J]. N Engl J Med, 2007, 356(5): 486-496. DOI: 10.1056/NEJMsa064964.
[12]	Jha AK, Joynt KE, Orav EJ, et al. The long-term effect of premier pay for performance patient outcomes[J]. N Engl J Med, 2012, 366(17): 1606-1615. DOI: 10.1056/NEJMsa1112351.
[13]	徐浩, 王婉宜, 肖川, 等. 倾向得分法与倍差法在我国卫生政策评估领域的应用[J]. 中国预防医学杂志, 2016, 17(6): 451-454. DOI: 10.16506/j.1009-6639.2016.06.012. Xu H, Wang WY, Xiao C, et al. Application of tendency score method and difference in difference method in health policy assessment in China[J]. Chin Prev Med, 2016, 17(6): 451-454. DOI: 10.16506/j.1009-6639.2016.06.012.
[14]	王海鹏, 孟庆跃. 应用匹配倍差法评估城镇居民医疗保险对医疗服务利用的影响[J]. 中国卫生经济, 2013, 32(6): 8-10. DOI: 10.7664/CHE20130602. Wang HP, Meng QY. Evaluating the effects of urban resident basic medical insurance on medical service utilization based on matching DID model[J]. Chinese Health Economics, 2013, 32(6): 8-10. DOI: 10.7664/CHE20130602.