2013―2022年自贡市结核病患者就诊延迟情况及影响因素分析

卓凌云; 曹洪; 杜柯楠; 张雨; 张越; 雷立健

doi:10.16462/j.cnki.zhjbkz.2024.11.007

2013―2022年自贡市结核病患者就诊延迟情况及影响因素分析

doi: 10.16462/j.cnki.zhjbkz.2024.11.007

卓凌云¹,
曹洪²,
杜柯楠²,
张雨³,
张越^{1, 4},
雷立健^{1, 4, ,}

1.
山西医科大学公共卫生学院流行病学教研室，太原 030001
2.
自贡市疾病预防控制中心，自贡 643000
3.
山西医科大学公共卫生学院劳动卫生学教研室，太原 030001
4.
煤炭环境致病与防治教育部重点实验室，太原 030001

基金项目:

山西省高等教育“百亿工程”科技引导专项 BYBLD002

详细信息

通讯作者:
雷立健，E-mail: wwdlijian@sxmu.edu.cn

中图分类号: R521
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- 被引次数: 0
出版历程
- 收稿日期: 2024-05-13
- 修回日期: 2024-07-28
- 网络出版日期: 2024-12-23
- 刊出日期: 2024-11-10

Delay on care-seeking and related influencing factors among tuberculosis patients in Zigong, 2013-2022

ZHUO Lingyun¹,
CAO Hong²,
DU Kenan²,
ZHANG Yu³,
ZHANG Yue^{1, 4},
LEI Lijian^{1, 4
, ,}

1.
Department of Epidemiology, School of Public Health, Shanxi Medical University, Taiyuan 030001, China
2.
Zigong Centre for Disease Control and Prevention, Zigong 643000, China
3.
Department of Occupational Health, School of Public Health, Shanxi Medical University, Taiyuan 030001, China
4.
MOE Key Laboratory of Coal Environmental Pathogenicity and Prevention, Shanxi Medical University, Taiyuan 030001, China

Funds:

Shanxi Province Higher Education "Billion Project" Science and Technology Guidance Project BYBLD002

More Information

Corresponding author: LEI Lijian, E-mail: wwdlijian@sxmu.edu.cn

摘要

摘要: 目的了解自贡市结核病就诊延迟情况，分析其影响因素，为该地区制定相关政策及采取针对性措施提供依据。方法通过中国疾病预防控制信息系统中的结核病信息管理系统，收集2013―2022年自贡市14 807例结核病患者的病案信息，拟合Joinpoint回归模型，分析2013―2022年就诊延迟率变化趋势，采用非条件多因素logistic回归分析模型对结核病患者就诊延迟影响因素进行分析。结果自贡市结核病患者就诊延迟率总体呈上升趋势，不同性别就诊延迟率变化均呈上升趋势，20~ < 60岁和≥60岁年龄组就诊延迟率变化均呈上升趋势。多因素logistic回归分析模型分析结果显示，2020―2022年，患者来源为追踪、直接就诊、推介、其他来源，以及结核性胸膜炎的结核病患者就诊延迟风险更高(均P < 0.05)。学生、家政及待业、工人及民工、主动发现、病原学结果阴性、富顺县、贡井区的结核病患者就诊延迟风险更低(均P < 0.05)。结论 2013―2022年自贡市结核病患者就诊延迟率总体呈上升趋势，自贡市结核病患者就诊延迟可能与职业类型、患者来源、诊断分型、病原学结果和年份有关，应针对上述因素实施有效的干预措施。
- 结核病 /
- 疾病监测 /
- 就诊延迟 /
- Joinpoint回归
Abstract: Objective To understand the situation of delay in tuberculosis care-seeking in Zigong, analyze the related influencing factors, and provide a reference for the future formulation of relevant policies and adoption of targeted measures in the region. Methods The medical record information of 14 807 tuberculosis patients in Zigong from 2013 to 2022 was collected through the "tuberculosis information management system", a subsystem of the China disease prevention and control information system. The Joinpoint regression model was used to analyze the trend of the delay rates over this period. Additionally, The influencing factors of delayed visits of tuberculosis patients were analyzed using the unconditional multivariate logistic regression model. Results The delayed rate of tuberculosis patients in Zigong City showed an overall increasing trend. And the delayed rate of different genders showed an upward trend. And the delay rates for patients aged 20 to 59 and ≥60 also showing an upward trend. Multivariate logistic regression analysis showed that in 2020-2022, the sources of patients include follow-up, direct treatment, promotion, other sources, and tuberculosis pleurisy had a higher risk of delayed TB treatment (all P < 0.05). The risk of delay in care-seeking was lower for patients who were students, domestic workers and unemployed, workers and migrant workers, as well as patients whose sources were actively detected, and whose pathogenetic results were negative, or belonged to areas such as Fushun County and Gongjing District (all P < 0.05). Conclusions The delay rate of tuberculosis patients in Zigong City showed an overall upword trend from 2013 to 2022. The delay of tuberculosis patients in Zigong City may be related to occupational type, patient source, diagnosis type, etiology results and registration year. It is crucial to implement effective intervention strategies to address the above factors.
- Tuberculosis /
- Disease surveillance /
- Care-seeking delay /
- Joinpoint regression

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图 1 2013―2022年自贡市结核病患者就诊延迟率变化趋势

Figure 1. Trend of delayed rate of tuberculosis patients in Zigong, 2013-2022

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图 2 2013―2022年自贡市结核病患者各年龄组就诊延迟率变化趋势

Figure 2. Trend of medical care-seeking delay in tuberculosis patients in different age groups in Zigong, 2013-2022

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表 1 2013―2022年自贡市结核病就诊延迟率的Joinpoint回归分析

Table 1. Joinpoint regression analysis of medical care-seeking delay of tuberculosis patients in Zigong, 2013―2022

变量 Variable	指标 Index	时间段/年 Time period/year	变化值Change value/% (95% CI)	t值 value	P值 value
总体 Total	APC/%	2013―2022	4.3(2.1~6.6)	4.534	0.002
	AAPC/%
性别 Gender
男性 Male	APC/%	2013―2022	4.5(2.4~6.6)	5.012	0.001
	AAPC/%
女性 Female	APC/%	2013―2022	3.7(1.1~6.4)	3.287	0.011
	AAPC/%
年龄组/岁 Age group/years
< 20	APC/%	2013―2022	3.4(-0.8~7.8)	1.869	0.098
	AAPC/%
20~ < 40	APC/%	2013―2022	4.2(1.3~7.2)	3.310	0.011
	AAPC/%
40~ < 60	APC/%	2013―2022	4.9(2.9~7.0)	5.727	< 0.001
	AAPC/%
≥60	APC/%	2013―2022	3.7(1.5~5.9)	3.929	0.004
	AAPC/%
注：APC，年度变化百分比；AAPC，平均年度变化百分比。 Note: APC, the annual percentage change; AAPC, the average annual percentage change.

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表 2 2013―2022年自贡市结核病就诊延迟影响因素分析

Table 2. Analysis of influencing factors on medical care-seeking delay for tuberculosis patients in Zigong, 2013-2022

因素 Factors	患者数 Number of patients^①	就诊延迟 Health-care seeking delay^①		单因素分析 Univariate analysis		多因素分析 Multifactorial analysis
因素 Factors	患者数 Number of patients^①	否 No	是 Yes	χ²值 value	P值 value	OR值value (95% CI)	P值 value
年份/年 Year				91.789	< 0.001
2013―2019	11 176(75.48)	4 886(43.72)	6 290(56.28)			1.000
2020―2022	3 631(24.52)	1 260(36.70)	2 371(63.30)			1.396(1.273~1.531)	< 0.001
年龄组/岁 Age group/years				36.336	< 0.001
< 20	585(3.95)	304(51.97)	281(48.03)			1.000
20~ < 40	2 845(19.21)	1 221(42.92)	1 624(57.08)			1.147(0.901~1.460)	0.266
40~ < 60	5 650(38.16)	2 347(41.54)	3 303(58.46)			1.230(0.966~1.566)	0.093
≥60	5 727(38.68)	2 274(39.71)	3 453(60.29)			1.261(0.989~1.608)	0.061
性别 Gender				0.466	0.495
男性 Male	11 185(75.54)	4 625(41.35)	6 560(58.65)			―
女性 Female	3 622(24.46)	1 521(41.99)	2 101(58.01)			―
民族 Ethnic group				0.024	0.877
汉族 Han	14 741(99.55)	6 118(41.50)	8 623(58.50)			―
少数民族 Ethnic minorities	66(0.45)	28(42.42)	38(57.58)			―
户籍 Household register				0.104	0.747
本地 Locality	13 793(93.15)	5 730(41.54)	8 063(58.46)			―
非本地 Non-locality	1 014(6.85)	416(41.02)	598(58.98)			―
职业类型 Occupation				141.466	< 0.001
农民 Farmer	8 984(60.67)	3 761(41.86)	5 223(58.14)			1.000
学生 Student	442(2.99)	242(54.75)	200(45.25)			0.640(0.486~0.844)	0.002
家政及待业 Housekeeping and unemployment	3 330(22.49)	1 270(38.14)	2 060(61.86)			0.892(0.814~0.976)	0.013
工人及民工 Worker and migrant labourer	794(5.36)	438(55.16)	356(44.84)			0.805(0.685~0.976)	0.009
专业技术人员 Technical professionals	328(2.22)	135(41.16)	193(58.84)			0.868(0.681~1.105)	0.249
其他职业 Other occupations^②	929(6.27)	300(32.29)	629(67.70)			1.170(0.997~1.371)	0.054
患者来源 Patient source				185.689	< 0.001
转诊 Referral	7 077(47.79)	2 882(40.72)	4 195(59.28)			1.000
追踪 Trace	2 068(13.97)	832(40.23)	1 236(59.77)			1.341(1.202~1.495)	< 0.001
直接就诊 Active visiting	4 891(33.03)	2 237(45.74)	2 654(54.26)			1.124(1.027~1.231)	0.011
推介 Urge medical treatment	213(1.44)	28(13.15)	185(86.85)			0.319(0.197~0.517)	< 0.001
主动发现 Proactive discovery	77(0.52)	50(64.94)	27(35.06)			3.501(2.332~5.257)	< 0.001
其他来源 Other sources^③	481(3.25)	117(24.32)	364(75.68)			6.017(4.805~7.536)	< 0.001
诊断分型 Diagnosis and classification				38.293	< 0.001
继发型 Secondary type^④	1 4401(97.26)	6 034(41.90)	8 367(58.10)			1.000
结核性胸膜炎 Tuberculous pleurisy	290(1.96)	70(24.14)	220(75.86)			2.202(1.656~2.930)	< 0.001
其他分型 Other classification^⑤	116(0.78)	42(36.21)	74(63.79)			1.267(0.847~1.896)	0.225
治疗分类 Treatment classification				17.752	< 0.001
初治 Initial treatment	13 999(94.54)	5 868(41.92)	8 131(58.08)			1.000
复治 Repeated treatment	808(5.46)	278(34.41)	530(65.59)			1.079(0.920~1.267)	0.348
病原学结果 Pathogenetic results				61.484	< 0.001
阳性 Positivity	6 062(40.94)	2 285(37.69)	3 777(62.31)			1.000
阴性 Negativity	8 745(59.06)	3 861(44.15)	4 884(55.85)			0.899(0.832~0.972)	0.007
地区 Areas				1 079.150	< 0.001
大安区 Da′an District	2 067(13.96)	672(32.51)	1 395(67.49)			1.000
富顺县 Fushun County	4 639(31.33)	2 818(60.75)	1 821(39.25)			0.264(0.235~0.298)	< 0.001
贡井区 Gojing District	1 440(9.73)	589(40.90)	851(59.10)			0.715(0.620~0.824)	< 0.001
荣县 Rong County	3 033(20.48)	965(31.82)	2 068(68.18)			1.020(0.898~1.158)	0.760
沿滩区 Yantan District	1 710(11.55)	511(29.88)	1 199(70.12)			1.148(0.996~1.322)	0.057
自流井区 Ziliujing District	1 918(12.95)	591(30.81)	1 327(69.19)			0.980(0.967~1.293)	0.094
注：“―”未纳入多因素分析。 ①以人数(占比/%)表示；②其他职业包括商业服务、食品餐饮业、公共场所服务员、牧民、长途驾驶员以及其他无法界定的职业；③其他来源为病案信息中来源不详的患者；④继发型包括继发于尘肺病、糖尿病、HIV等疾病；⑤其他分型包括原发型、血行播散型、其他肺外结核。 Note: “―” the indicator was not included in the multifactorial analysis. ① Number of people(proportion/%); ② Other occupations include business services, food and catering industry, public place service staff, herdsmen, long-distance drivers, and other undefined occupations; ③ Other sources refer to patients with unspecified origins in medical records; ④ Secondary types include those secondary to diseases such as pneumoconiosis, diabetes, HIV, etc; ⑤ Other types include primary forms, hematogenous dissemination, and other extrapulmonary tuberculosis.

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参考文献(20)

[1]	World Health Organization. Global tuberculosis report 2023-1. 1 TB disease burden [EB/OL]. (2023-11-07)[2024-02-25]. https://www.who.int/teams/global-tuberculosis-programme/tb-reports/global-tuberculosis-report-2023/tb-disease-burden.
[2]	Tong YQ, Guan XH, Hou SY, et al. Determinants of health care-seeking delay among tuberculosis patients in rural area of central China [J]. Int J Environ Res Public Health, 2018, 15(9): 1998. DOI: 10.3390/ijerph15091998.
[3]	全国第五次结核病流行病学抽样调查技术指导组, 全国第五次结核病流行病学抽样调查办公室. 2010年全国第五次结核病流行病学抽样调查报告[J]. 中国防痨杂志, 2012, 34(8): 485-508. The Technical Guidance Group of the Fifth National TB Epidemiological Survey, The Office of the Fifth National TB Epidemiological Survey. The fifth national tuberculosis epidemiological survey in 2010 [J]. Chin J Antituberc, 2012, 34(8): 485-508.
[4]	龙莹, 宁柱, 汪川, 等. 2018-2021年四川省自贡市结核病流行病学特征分析[J]. 解放军医学杂志, 2022, 59(8): 1-12. DOI: 10.11855/j.issn.0577-7402.0943.2022.1017. Long Y, Ning Z, Wang C, et al. Epidemiological characterisation of tuberculosis in Zigong City, Sichuan Province, 2018-2021 [J]. Med J Chin PLA, 2022, 59(8): 1-12. DOI: 10.11855/j.issn.0577-7402.0943.2022.1017.
[5]	Ranzani OT, Rodrigues LC, Bombarda S, et al. Long-term survival and cause-specific mortality of patients newly diagnosed with tuberculosis in São Paulo state, Brazil, 2010-15: a population-based, longitudinal study [J]. Lancet Infect Dis, 2020, 20(1): 123-132. DOI: 10.1016/S1473-3099(19)30518-3.
[6]	中华人民共和国国家卫生和计划生育委员会. 结核病分类: WS 196―2017 [S]. 北京: 中国标准出版社, 2017: 2. National Health and Family Planning Commission of the People′s Republic of China. Classification of tuberculosis: WS 196-2017 [S]. Beijing: Standards Press of China, 2017: 2.
[7]	Jiang YL, Luo L, Gui M, et al. Duration and determinants of delayed diagnosis with tuberculosis in Shenzhen, China: a cross-sectional study [J]. Risk Manag Healthc Policy, 2022, 15: 1473-1481. DOI: 10.2147/RMHP.S367998.
[8]	Alene M, Assemie MA, Yismaw L, et al. Patient delay in the diagnosis of tuberculosis in Ethiopia: a systematic review and meta-analysis [J]. BMC Infect Dis, 2020, 20(1): 797. DOI: 10.1186/s12879-020-05524-3.
[9]	王晓君, 付谦, 张正斌, 等. 武汉市2008-2017年结核病患者就诊延迟情况及影响因素分析[J]. 中华流行病学杂志, 2019, 40(6): 643-647. DOI: 10.3760/cma.j.issn.0254-6450.2019.06.008. Wang WJ, Fu Q, Zhang ZB, et al. Analysis of delay in consultation and factors affecting tuberculosis patients in Wuhan from 2008 to 2017 [J]. Chin J Epidemiol, 2019, 40(6): 643-647. DOI: 10.3760/cma.j.issn.0254-6450.2019.06.008.
[10]	Lestari BW, McAllister S, Hadisoemarto PF, et al. Patient pathways and delays to diagnosis and treatment of tuberculosis in an urban setting in Indonesia [J]. Lancet Reg Health West Pac, 2020, 5: 100059. DOI: 10.1016/j.lanwpc.2020.100059.
[11]	Getnet F, Demissie M, Assefa N, et al. Delay in diagnosis of pulmonary tuberculosis in low-and middle-income settings: systematic review and meta-analysis [J]. BMC Pulm Med, 2017, 17(1): 202. DOI: 10.1186/s12890-017-0551-y.
[12]	Chiposi L, Cele LP, Mokgatle M. Prevalence of delay in seeking tuberculosis care and the health care seeking behaviour profile of tuberculous patients in a rural district of KwaZulu Natal, South Africa [J]. Pan Afr Med J, 2021, 39: 27. DOI: 10.11604/pamj.2021.39.27.26717.
[13]	Jia YF, Jiang WX, Xiao X, et al. Patient delay, diagnosis delay, and treatment outcomes among migrant patients with tuberculosis in Shanghai, China, 2018-2020: a mixed-methods study [J]. BMJ Open, 2024, 14(10): e082430. DOI: 10.1136/bmjopen-2023-082430.
[14]	Seid A, Metaferia Y. Factors associated with treatment delay among newly diagnosed tuberculosis patients in Dessie city and surroundings, Northern Central Ethiopia: a cross-sectional study [J]. BMC Public Health, 2018, 18(1): 931. DOI: 10.1186/s12889-018-5823-9.
[15]	Tattevin P, Che D, Fraisse P, et al. Factors associated with patient and health care system delay in the diagnosis of tuberculosis in France [J]. Int J Tuberc Lung Dis, 2012, 16(4): 510-515. DOI: 10.5588/ijtld.11.0420.
[16]	程冬梅, 陶然. 2015-2019年太原市肺结核患者就诊延误情况及影响因素分析[J]. 预防医学论坛, 2021, 27(2): 110-112, 117. DOI: 10.16406/j.pmt.issn.1672-9153.2021.02.010. Cheng DM, Tao R. Analysis on the situation and influencing factors of treatment delay of pulmonary tuberculosis patients, Taiyuan city, 2015-2019 [J]. Prev Med Trib, 2021, 27(2): 110-112, 117. DOI: 10.16406/j.pmt.issn.1672-9153.2021.02.010.
[17]	Li Y, Ehiri J, Tang SL, et al. Factors associated with patient, and diagnostic delays in Chinese TB patients: a systematic review and meta-analysis [J]. BMC Med, 2013, 11: 156. DOI: 10.1186/1741-7015-11-156.
[18]	傅丽娟, 汪业胜, 朱文龙, 等. 湖州市2008―2018年肺结核患者就诊延迟情况及影响因素[J]. 中华疾病控制杂志, 2021, 25(2): 235-239. DOI: 10.16462/j.cnki.zhjbkz.2021.02.022. Fu LJ, Wang YS, Zhu WL, et al. Consultation delay and influencing factors among pulmonary tuberculosis patients in Huzhou City from 2008 to 2018 [J]. Chin J Dis Control Prev, 2021, 25(2): 235-239. DOI: 10.16462/j.cnki.zhjbkz.2021.02.022.
[19]	Long Q, Jiang WX, Dong D, et al. A new financing model for tuberculosis (TB) care in China: challenges of policy development and lessons learned from the implementation [J]. Int J Environ Res Public Health, 2020, 17(4): 1400. DOI: 10.3390/ijerph17041400.
[20]	Pang Y, An J, Shu W, et al. Epidemiology of extrapulmonary tuberculosis among inpatients, China, 2008-2017 [J]. Emerg Infect Dis, 2019, 25(3): 457-464. DOI: 10.3201/eid2503.180572.