Health-seeking delay and potential determinants among pulmonary tuberculosis patients: a retrospective survey in China

doi:10.21203/rs.3.rs-5308403/v1

Background

Understanding the health-seeking delay (HSD) in pulmonary tuberculosis (PTB) patients aids tailored strategies to curb transmission. This study aims to assess HSD and factors in China, considering the COVID-19 impacts.

Methods

Symptomatic PTB patients diagnosed from 2019 to 2022 were sampled using multistage stratified clustering. A semi-structured questionnaire was utilized to assess their HSD. Participants were divided to pre (2019) and epidemic (2020–2022) groups, the latter further categorized to 12 subgroups byⅠ–Ⅳstages and 3 levels of stringency in public health and social measures(PHSMs). Categorical variables were presented as counts (percentages), while continuous as median (Interquartile Range). The time between patient onset symptom and initial health facility visiting was defined as the health-seeking interval (HSI), HSIs of epidemic group and subgroups were compared with those of the 2019. Factors associated with HSD were analysed, univariable and multivariable analysis were performed by chi-square tests and binary logistic regression separately.

Results

Sum of 759 PTB patients, 391 diagnosed pre and 368 during the epidemic. HSI was 14 (7–30) days for all patients, with no significant difference between two groups [12 (7–30) days vs. 15 (6–30) days, P = 0.852]. Among the 12 subgroups, only under strict PHSMs in stage I and medium PHSMs in stage II showed significant differences in HSIs compared to 2019[10 (3–15) days vs. 20 (10–30) days, 10 (3–17.5) days vs. 20 (8.5–50) days] (P = 0.013, 0.038). HSD proportions were comparable between the two groups (48.1% vs. 51.6%, P = 0.328). Self-medication before seeking health was a common factor for HSD (AOR: 3.057/2.868, 95% CI: 1.888–4.950/1.718–4.787). During the epidemic, solely cough and expectoration were prone to HSD (AOR: 2.144, 95% CI: 1.288–3.569), and passive case-finding posed a higher HSD risk than active (AOR: 30.987, 95% CI: 3.904-245.932). Most patients with HSD misinterpreted PTB, while a few cited epidemic inconvenience and fear of COVID-19.

Conclusions

HSD among PTB patients remains prevalent, the COVID-19 epidemic exerted limited impact. Individual, epidemic and health provider factors mediated the HSD. Increasing PTB awareness, enhancing health services accessibility during epidemics, and expanding active case-finding are recommended to minimize the delays.

Tuberculosis

Lung

Delay

Health seeking

Risk factors

Tuberculosis (TB) continues to pose a significant public health concern, with a staggering 10.6 million new cases and 1.3 million deaths reported globally in 2022[1]. As a country with high TB burden, China holds the third largest share of global tuberculosis patients, with an estimated 748,000 new cases in 2022[1]. To effectively curb the tuberculosis epidemic, halting its transmission is undoubtedly a crucial and indispensable step[2]. Prompt health-seeking behaviour, timely diagnosis, and appropriate treatment by patients are vital in cutting off the transmission chain at the community level[3]. Notably, in countries with a high TB burden, shortening the health-seeking interval (HSI), the time between the onset of TB symptoms and the patient's initial medical consultation, has proven to be an effective strategy in reducing TB incidence[4]. However, health-seeking delay (HSD) poses a substantial obstacle to the progress of TB control initiatives.

HSIs within tuberculosis care cascades exhibit variation across countries[5] and even within different regions of the same country[6]. A systematic review (2017) included 40 studies involving 18,975 patients in low- and middle-income countries, revealed that HSIs ranged from 4 to 199 days [7]. Various factors contribute to HSD, including individual sociodemographic characteristics, clinical features, and health provider-related elements[8-10]. Since 2020, the impact of the sudden COVID-19 outbreak on HSD among pulmonary tuberculosis (PTB) patients has garnered increased attention. In summary, three primary reasons can lead to delays in health-seeking during the COVID-19 epidemic[11]. Firstly, public health and social measures (PHSMs) implemented to curb the spread of the novel coronavirus, such as traffic disruptions and city lockdowns, have restricted access to TB services. Secondly, resources dedicated to TB services have been redirected towards the prevention and control of COVID-19. Thirdly, patients have been hesitant to seek healthcare due to fear of contracting the novel coronavirus.

Extensive research has been conducted on domestic HSD and its determinants, primarily relying on tuberculosis surveillance data[12-15]. However, this approach limits the exploration of factors not captured by the surveillance system, such as patients' self-medication experiences prior to diagnosis, which can contribute to HSDs[16]. Furthermore, some studies have focused on subnational areas or specific groups[17-20], lacking nationwide representativeness. Additionally, while several studies have indicated that PHSMs prolonged HSI, they primarily concentrated on the early stages of the COVID-19 epidemic[21-23]. Between 2020 and 2022, the severity of the COVID-19 epidemic and the strictness of PHSMs fluctuated significantly across different periods in China[22]. Consequently, the overall situation and influencing factors of HSD throughout the nationwide implementation of PHSMs remain unclear.

The aforementioned research gaps necessitate updated data on the HSD of PTB patients. Therefore, the objectives of this study are to: 1) evaluate the duration of HSI and identify associated risk factors contributing to HSD among PTB patients in China, and 2) assess the influence of the COVID-19 epidemic on the health-seeking delay of PTB patients.

Study design and settings

From September to December 2023, a retrospective multicentre cross-sectional survey was conducted in 24 counties for HSD among patients with PTB. A multistage stratified clustering sampling method was employed to select PTB patients diagnosed between 2019–2022 and notified to the Chinese Tuberculosis Information Management System. The sampling process for the study settings is illustrated in Figure 1.

Considering the study objectives and the evolving policies for COVID-19 in China, we broadly categorized the period from January 2020 to October 2022 into four distinct stages[24].In Stage I, two provinces were randomly selected. In March 2020, the counties within these provinces were classified into three levels of strictness for public health and social measures (PHSMs): strict, medium, and mild. This classification was based on the Oxford COVID-19 Government Response Tracking System[25] and input from Chinese experts involved in COVID-19 prevention and control. Counties labeled "mild" consistently maintained this level throughout the month, while those labeled "medium" implemented medium measures but not strict ones during this period. One county was randomly selected from each category within each province. For Stages II-IV, the PHSMs levels of the counties were reassessed in January 2021, November 2021, and May 2022, respectively, using the same sampling method as in Stage I. No province was sampled more than once, ensuring a final study group of 24 counties from eight provinces.

Participants

For each county, 40 PTB patients were recruited, and half were diagnosed before the epidemic and half during the epidemic, PTB was diagnosed according to the current diagnostic criteria in China[26]. For stage I, starting from the first PTB patient registered in March 2020, 20 patients were consecutively contacted. If the patient had died, was missing, or refused participation, they were substituted in accordance with the registration number. Additionally, 20 patients who met the same criteria were selected from each county in March 2019 to represent the pre-epidemic group. For the remaining 18 counties in Stages II–IV, patients were selected at corresponding times: January 2021, November 2021, and May 2022, respectively. The methodologies used for selecting patients in these stages were consistent with those used for the six counties in Stage I. A total of 960 patients were included as participants, excluding those who had no PTB symptoms when diagnosed.

Sample size estimation

We set the HSI as a binary dependent variable with a cut-off value at 14 days and assumed that the proportion of HSI>14 days was 50% on the basis of a similar report[27,28]. In light of the study objective and referring to previous studies, we selected 12 variables a priori for inclusion in our model. To minimize bias in logistic regression analysis, 120 events are required to ensure 10 events per variable. A total of 240 symptomatic PTB patients need to be included. According to a previous survey, 56.9% of the PTB patients exhibited symptoms[29]. Consequently, we needed to contact at least 422 PTB patients separately before and during the epidemic to ensure an adequate sample size.

Data collection

Semi-structured questionnaire surveys were conducted to collect demographic and sociological information from the respondents, including sex, age, education level, occupation, marital status, and place of residence. Additionally, we collected data on the type and duration of symptoms experienced by the respondents before their initial medical care consultation. The surveys also inquired about their self-medication experiences prior to seeking medical attention, the reasons for encountering HSD, the type of health facility they initially contacted, and the case-finding method used. For respondents under the age of 15, or those with mental disabilities or communication disorders, their parents or guardians were asked to answer on their behalf.

A participant who had at least one of the following symptoms that were intermittent or persistent prior to the PTB diagnosis was defined as having PTB symptoms: cough and expectoration; haemoptysis; fever; chest pain; night sweats; fatigue; appetite loss; and weight loss.

Patients were found via two methods: active case-finding (ACF) and passive case-finding (PCF). ACF involves screening for active TB in certain population groups regardless of symptoms or clinical suspicion[30]. The PCF was where patients with PTB symptoms presented themselves to the health facility for PTB evaluation and diagnosis.

Operational definitions

Health-seeking interval

The HSI refers to the time interval between the date of a patient’s PTB symptom onset and the date of first contact with any health facility.

Health-seeking delay

In accordance with most previous domestic studies[31], in our study, HSD was defined as the time interval between a patient PTB symptom onset and the first contact with any health facility exceeding 14 days.

Self-medication

On the basis of other studies[32], we defined self-medication as a patient using any type of drug to treat PTB symptoms or to alleviate PTB suffering without a prescription before a health facility is contacted.

Data management and statistical analysis

The survey data were subjected to a double-entry process via Epidata 3.1 (The Epidata Association, Odense, Denmark) to ensure precision before being exported into a Microsoft Excel (version 2016; Microsoft Corporation, WA, USA) spreadsheet. Statistical analyses were carried out via SPSS 22.0^TM (IBM Corp. Released 2013. IBM SPSS Statistics for Windows, Version 22.0. Armonk, NY: IBM Corp.).

Categorical variables were summarized using counts (percentages) and analysed via chi-square tests. For continuous variables, the median (interquartile range [IQR]) was described, with comparisons conducted using the Mann–Whitney U test. The chi-square test was employed for univariable analysis to identify influencing factors of HSD, while multivariable binary logistic regression analysis was utilized to further explore these factors. The analysis encompassed sociodemographic characteristics, symptoms, self-medication practices, type of initial health facility visited, and case-finding methods. For patients diagnosed during the epidemic, additional variables such as epidemic stage and PHSMs level were included. Variables with a p-value ≤ 0.2 in the univariable analysis were selected for the multivariable model to estimate the adjusted Odds Ratio (AOR). The final model presented AOR with a 95% confidence interval (CI). A two-sided hypothesis test P value<0.05 was regarded as significant.

Participant characteristics

Ultimately, 759 symptomatic participants were surveyed and analysed, with 391 diagnosed before the epidemic and 368 during the epidemic. The majority of participants were male (526, representing 69.3% of the total). A total of 405 participants (53.4%) were aged between 35 and 64 years, with a median age of 49.1 years (range: 34-63), and only 5 participants (0.7%) were under 15 years old. Among them, 241 patients (31.7%) had completed at least senior middle school education. Additionally, 272 participants (35.8%) were agricultural labourers. The majority of patients, 566 (74.6%), were married or cohabiting. A total of 427 participants (56.3%) resided in urban areas. Regarding symptoms, 266 respondents (35.0%) reported only cough and expectoration, 208 (27.4%) had fever, 162 (21.3%) experienced chest pain, and 97 (12.8%) had haemoptysis. A significant number of patients, 512 (67.5%), used self-medication before the first health facility visiting. Over half of the patients chose comprehensive hospitals as their initial health facility. The sociodemographic characteristics and features mentioned above were not significantly different between patients diagnosed before and during the epidemic. However, a greater proportion of patients were identified through the ACF during the epidemic(Table 1).

Table 1 Comparison of characteristics of study participants diagnosed before and during the COVID-19 epidemic
Characteristics	Total (N=759)	Before epidemic (N=391)	During epidemic (N=368)	P
Sex				0.756
Male	526(69.3)	269(68.8)	257(69.8)
Female	233(30.7)	122(31.2)	111(30.2)
Age group(years)				0.269
0–34	193(25.4)	103(26.3)	90(24.5)
35–64	405(53.4)	198(50.6)	207(56.3)
65–	161(21.2)	90(23.0)	71(19.3)
Education level				0.344
Illiterate or semi-illiterate	81(10.7)	50(12.8)	31(8.4)
Primary school	179(23.6)	96(24.6)	83(22.6)
Junior high school	258(34.0)	128(32.7)	130(35.3)
High school/Technical	126(16.6)	62(15.9)	64(17.4)
Junior college	54(7.1)	28(7.2)	26(7.1)
University	61(8.0)	27(6.9)	34(9.2)
Occupation				0.094
Agricultural workers	272(35.8)	146(37.3)	126(34.2)
Industrial workers	139(18.3)	67(17.1)	72(19.6)
Cadre and staff^a	48(6.3)	29(7.4)	19(5.2)
Students	42(5.5)	20(5.1)	22(6.0)
Retiree	42(5.5)	25(6.4)	17(4.6)
Houseworkers and unemployed	138(18.2)	75(19.2)	63(17.1)
Others	78(10.3)	29(7.4)	49(13.3)
Marital status				0.069
Unmarried	129(17.0)	74(18.9)	55(14.9)
Married or cohabitate	566(74.6)	278(71.1)	288(78.3)
Divorce or widow	64(8.4)	39(10.0)	25(6.8)
Residence				0.561
Urban	427(56.3)	216(55.2)	211(57.3)
Rural	332(43.7)	175(44.8)	157(42.7)
Symptom				0.974
Others^b	509(67.1)	262(67.0)	247(67.1)
Only cough& Expectoration	250(32.9)	129(33.0)	121(32.9)
Self-medication				0.478
No	246(32.5)	268(68.5)	244(66.3)
Yes	512(67.5)	122(31.2)	124(33.7)
Initial contacted facility				0.517
TB dispensary	97(12.8)	56(14.3)	41(11.1)
Comprehensive hospital	394(51.9)	200(51.2)	194(52.7)
Others	268(35.3)	135(34.5)	133(36.1)
Case-finding				0.029
Active	38(5.0)	13(3.3)	25(6.8)
Passive	721(95.0)	378(96.7)	343(93.2)
Diagnosed stage				—
Stage Ⅰ			98(26.6)
Stage Ⅱ			94(25.5)
Stage Ⅲ			77(20.9)
Stage Ⅳ			99(26.9)
PHSMs level				—
Strict			124(33.7)
Medium			120(32.6)
Mild			124(33.7)
Data are presented as n(%) Abbreviation: PHSMs=Public health and social measures ^aIncluding teachers, medical staff, cadres and other brain-based labourers. ^bPatients with PTB symptoms except the ones with cough and expectoration only

Health-seeking interval

Among the 759 participants, the HSI was found to be 14 (7–30) days. Prior to the epidemic, the HSI was 12 (7–30) days, whereas during the epidemic, it increased slightly to 15 (6 –30) days. However, this difference was not statistically significant (P=0.852). In stage I, patients diagnosed under strict PHSMs exhibited a shorter HSI compared to those diagnosed before the epidemic [10(3–15) days vs. 20(10–30) days, P=0.013]. A similar phenomenon occurred in stage II, as medium PHSMs were adopted [10(3–17.5) days vs. 20(8.5–50) days, P=0.038]. In contrast, across the other 10 scenarios examined, no statistically significant differences were observed in the HSIs before and during the epidemic (Table 2).

Notably, 14 patients who were diagnosed during the epidemic recalled that, owing to fever symptom onset, they were concerned with primary health workers and were taken by ambulances to health facilities for chest CT scans/nucleic acid tests to rule out COVID-19, and their HSIs were no longer than 14 days.

Table 2 Health-seeking intervals of PTB patients diagnosed in different scenarios
Patients categories		Health-seeking intervals [Median (IQR)days]		P value
Patients categories		Before epidemic	During epidemic	P value
StageⅠ	Strict	20(10–30)	10(3–15)	0.013
	Medium	7(3–12)	14(7–29)	0.130
	Mild	15(5–30)	20(12.5–60)	0.129
StageⅡ	Strict	12.5(7–30)	15(7–30)	0.660
	Medium	20(8.5–50)	10(3–17.5)	0.038
	Mild	10(7–16)	10(7–20)	0.307
Stage Ⅲ	Strict	8.5(7–15)	7(3–15)	0.136
	Medium	7(3–29)	15(6–30)	0.334
	Mild	12.5(7–30)	11(3.5–60)	0.700
Stage Ⅳ	Strict	30(12–40)	30(17–60)	0.437
	Medium	8(3–30)	28(7–36.5)	0.192
	Mild	15(5–37.5)	15(7–30)	0.882
Total		12.0(7.0–30.0)	15.0(6.0–30.0)	0.852

Health-seeking delay and risk factors

Among all the participants, 378 (49.9%) experienced HSD. The HSD occurrence rate was not significantly different between patients diagnosed before and during the epidemic (48.1% vs. 51.6%, P=0.328).

Table 3 shows the outcomes of the univariable analysis for HSD-associated factors. Age and self-medication experience were both common factors influencing HSD among PTB patients diagnosed before and during epidemic, whereas education level and occupation were factors correlated to HSD in patients diagnosed before epidemic. Marriage status, symptoms, case-finding methods, and stage of diagnosis were factors associated with HSD during the epidemic.

After controlling for confounding effects, multivariable regression analysis revealed that self-medication prior to first health consultation was a significant factor associated with HSD (AOR: 3.057/2.868, 95% CI: 1.888–4.950/1.718–4.787) among patients diagnosed both before and during the epidemic. During the epidemic, patients experiencing only cough and expectoration had an increased risk of HSD (AOR: 2.144, 95% CI: 1.288–3.569) compared to those with other symptoms, and patients identified through PCF were more prone to HSD (AOR: 30.987, 95% CI: 3.904–245.932) than those identified by ACF (Table 4).

Table 3 Univariable analysis for HSD associated factors among PTB patients diagnosed before and during the COVID-19 epidemic
Variables	Before epidemic(n=391)			During epidemic(n=368)
Variables	HSI≤14 days	HSI>14 days	P	HSI≤14 days	HSI>14 days	P
Sex			0.145			0.541
Male	145(53.9)	124(46.1)		127(49.4)	130(50.6)
Female	58(47.5)	64(52.5)		51(45.9)	60(54.1)
Age group(years)			0.013			0.005
0–34	65(63.1)	38(36.9)		57(63.3)	33(36.7)
35–64	100(50.5)	98(49.5)		90(43.5)	117(56.5)
65–	38(42.2)	52(57.8)		31(43.7)	40(56.3)
Education level			0.001			0.152
Illiterate or semi-illiterate	18(36.0)	32(64.0)		15(48.4)	16(51.6)
Primary school	38(36.0)	58(64.0)		33(39.8)	50(60.2)
Junior high school	69(53.9)	59(46.1)		58(44.6)	72(55.4)
High school/Technical	40(64.5)	22(35.5)		36(56.2)	28(43.8)
Junior college	19(67.9)	9(32.1)		16(61.5)	10(38.5)
University	19(70.4)	8(29.6)		20(58.8)	14(41.2)
Occupation			0.005			0.296
Agricultural workers	59(40.4)	87(59.6)		61(48.4)	65(51.6)
Industrial workers	40(59.7)	27(40.3)		28(38.9)	44(61.1)
Cadre and staff^a	21(72.4)	8(27.6)		12(63.2)	7(36.8)
Students	14(70.0)	6(30.0)		14(63.6)	8(36.4)
Retiree	14(56.0)	11(44.0)		9(52.9)	8(47.1)
Houseworkers and unemployed	37(49.3)	38(50.7)		28(44.4)	35(55.6)
Others	18(62.1)	11(37.9)		26(53.1)	23(46.9)
Marital status			0.168			0.048
Unmarried	44(59.5)	30(40.5)		35(63.6)	20(36.4)
Married or cohabitate	43(51.4)	235(48.6)		132(45.8)	156(54.2)
Divorce or widow	16(41.0)	23(59.0)		11(44.0)	14(56.0)
Residence			0.071			0.843
Urban	121(56)	95(44.0)		103(48.8)	108(51.2)
Rural	82(46.9)	93(53.1)		75(47.8)	82(52.2)
Symptom			0.284			0.001
Others^b	141(53.8)	121(46.2)		134(54.3)	113(45.7)
Only cough &Expectoration	62(48.1)	67(51.9)		44(36.4)	77(63.6)
Self-medication			<0.001			<0.001
No	159(59.3)	109(40.7)		136(55.7)	108(44.3)
Yes	44(36.1)	78(63.9)		42(33.9)	82(66.1)
Initial contacted facility			0.700			0.911
TB dispensary	28(50.0)	28(50.0)		21(51.2)	20(48.8)
Comprehensive hospital	108(54.0)	92(46.0)		94(48.5)	100(51.5)
Others	67(49.6)	68(50.4)		63(47.4)	70(52.6)
Case-finding			0.066			<0.001
Active	10(76.9)	3(23.1)		24(96.0)	1(4.0)
Passive	193(51.1)	185(48.9)		154(44.9)	189(55.1)
Diagnosed stage						0.013
Stage Ⅰ				48(49.0)	50(51.0)
Stage Ⅱ				50(53.2)	44(46.8)
Stage Ⅲ				45(58.4)	32(41.6)
Stage Ⅳ				35(35.4)	64(64.6)
PHSMs hierarchy						0.881
Strict				60(48.4)	64(51.6)
Medium				60(50.0)	60(50.0)
Mild				58(46.8)	66(53.2)
Abbreviations: HSI= Health-seeking interval, PHSMs=Public health and social measures ^aIncluding teachers, medical staff, cadres and other brain-based labourers. ^bPatients with PTB symptoms except the ones with cough and expectoration only

Table 4 Multivariable analysis for associated factors with HSD among PTB patients diagnosed before and during the COVID-19 epidemic
Variables	Before epidemic(n=391)		During epidemic(n=368)
Variables	P	AOR(95%CI)	P	AOR(95%CI)
Sex
Male		1
Female	0.406	1.236(0.750–2.039)
Age group(years)
0–34		1		1
35–64	0.935	1.031(0.500–2.122)	0.395	1.372(0.662–2.845)
65–	0.851	1.091(0.438–2.719)	0.119	2.087(0.828–5.257)
Education level
Illiterate or semi-illiterate		1		1
Primary school	0.871	1.065(0.499–2.271)	0.283	1.695(0.647–4.443)
Junior high school	0.264	0.638(0.290–1.403)	0.412	1.510(0.565–4.040)
High school/Technical	0.093	0.443(0.172–1.144)	0.821	1.126(0.402–3.157)
Junior college	0.107	0.359(0.103–1.248)	0.679	1.310(0.364–4.714)
University	0.255	0.464(0.124–1.740)	0.781	1.191(0.347–4.086)
Occupation
Agricultural workers		1
Industrial workers	0.094	0.547(0.270–1.108)
Cadre and staff^a	0.220	0.473(0.143–1.564)
Students	0.188	0.423(0.117–1.521)
Retiree	0.604	0.769(0.284–2.080)
Houseworkers and unemployed	0.336	0.736(0.395–1.374)
Others	0.343	0.632(0.244–1.633)
Marital status
Unmarried		1		1
Married or cohabitate	0.724	0.875(0.416–1.841)	0.295	1.534(0.689–3.414)
Divorce or widow	0.978	1.015(0.357–2.885)	0.562	1.421(0.434–4.648)
Residence
Urban		1
Rural	0.895	0.968(0.599–1.565)
Symptom
Others^b				1
Only cough &Expectoration			0.003	2.144(1.288–3.569)
Self-medication
No		1		1
Yes	<0.001	3.057(1.888―4.950)	<0.001	2.868(1.718–4.787)
Case-finding
Active		1		1
Passive	0.201	2.435(0.623―9.520)	0.001	30.987(3.904–245.932)
Diagnosed stage
Stage Ⅰ				1
Stage Ⅱ			0.226	0.673(0.354–1.278)
Stage Ⅲ			0.066	0.524(0.263–1.045)
Stage Ⅳ			0.168	1.564(0.828–2.955)
Abbreviations: AOR=Adjusted Odds Ratio, CI= Confidence Interval, HSD= Health-seeking delay ^aIncluding teachers, medical staff, cadres and other brain-based labourers. ^bPatients with PTB symptoms except the ones with cough and expectoration only.

Reasons for health-seeking delay

Table 5 shows the reasons why the 378 participants experienced HSD. Before the COVID-19 epidemic, "Thinking it is a minor illness such as a cold, not taking it seriously" affected nearly 90% of patients who experienced HSD, followed by "Remote distance from residence to hospital" and "Too busy to see a doctor", with frequencies under 10%; "No money to see a doctor" (6.9%) was the fourth most common reason.

During each stage of the COVID-19 epidemic, mistaking PTB symptoms for a minor illness remains an absolutely vital cause of HSD. The proportion of patients who underwent HSD due to PHSMs ranged from 6.8% to 26.0%, and in stages Ⅰ–Ⅳ, the proportions of patients who were afraid of infection with the novel coronavirus during the health-seeking process were 8.0%, 2.3%, 9.4%, and 9.4%, respectively.

Table 5 The reasons for HSD of symptomatic participants diagnosed before COVID-19 epidemic and during different stages of epidemic
Reasons	Before epidemic(n=188)	During epidemic(n=190)
Reasons	Before epidemic(n=188)	Stage I(n=50)	Stage II(n=44)	Stage III(n=32)	Stage IV(n=64)
Thinking it is a minor illness such as a cold, not taking it seriously	168(89.4)	46(92.0)	39(88.6)	26(81.3)	50(78.1)
Inconvenient due to PHSMs	—	13(26.0)	3(6.8)	4(12.5)	14(21.9)
Fear of contracting the novel coronavirus during health seeking	—	4(8.0)	1(2.3)	3(9.4)	6(9.4)
Too busy to see a doctor	17(9.0)	4(8.0)	1(2.3)	8(25.0)	7(10.9)
Remote distance from residence to hospital	19(10.1)	8(16.0)	2(4.6)	1(3.1)	3(4.7)
No money to see a doctor	13(6.9)	3(6.0)	0(0.0)	0(0.0)	2(3.1)
Masked by other causes^a	4(2.9)	3(6.0)	0(0.0)	1(3.1)	3(4.7)
Other reasons	2(1.1)	0(0.0)	0(0.0)	0(0.0)	0(0.0)
Data are presented as n(%) Abbreviation: HSD=Health-seeking delay ^aLong-term respiratory symptoms caused by pneumoconiosis, bronchitis and smoking

Prompting timely health-seeking behaviour among PTB patients is paramount for controlling the spread of tuberculosis. This study presents an updated multicentre survey assessing HSD among PTB patients in China. Notably, half of the patients delay visiting a doctor for up to 14 days after symptom onset. During the COVID-19 epidemic, public health and social measures had limited impact on HSD among PTB patients. Factors associated with HSD included nonspecific symptoms such as cough and expectoration, prior self-medication before visiting health facility, and the use of passive case-finding methods.

According to the definition, asymptomatic patients do not experience HSD. Consequently, this study focused solely on symptomatic patients in its analysis of HSD. The survey conducted in China revealed that the HSI lasts for 14 (7–30) days. In comparison, a global study on tuberculosis patients' HSI in high-burden countries found that 14 low- and middle-income countries reported an HSI of 28 (20–30) days, while five high- and middle-income countries reported an HSI of 10 (10–20) days[33].This suggests that there is still potential to reduce HSI in China. Notably, the HSI observed in this study exceeds that reported in a survey conducted in Beijing, which found an HSI of 11 (5–26) days [34]. Furthermore, the Beijing study used the same 14-day cut-off value to define HSD and reported a lower percentage of HSD (41.71%) compared to the 49.9% reported in our survey. This discrepancy may be attributed to Beijing's status as a developed region, where patients generally have better economic conditions, higher education levels, and greater access to health services compared to the national average.

Although the value of the HSI was greater during the epidemic than before the epidemic, no significant difference was observed. Even for the HSIs presented separately in different patient diagnosis periods and under distinct PHSMs, only in two scenarios were the HSIs during the epidemic shorter than those before the epidemic. These HSIs are for stageⅠpatients diagnosed with strict PHSMs and for stage II patients diagnosed with medium PHSMs. The most plausible explanation for the former scenario is that, in March 2020, counties that implemented strict PHSMs took proactive COVID-19 quarantine measures to trace patients, and patients also paid more attention to their health status, reducing the delay in seeking health for symptomatic PTB patients, which is contrary to the results of domestic studies[21,23]. The reason for this discrepancy is that we conducted a more nuanced analysis by separately examining HSIs under different levels of PHSMs at the time of patient diagnosis.

We observed that PTB patients with cough and expectoration alone experienced greater HSDs than symptomatic patients did during the epidemic, which was in accordance with Lu’s study in Hubei[35] and Wang’s study in Shanghai[36]. The possible reason is that nonspecific cough and expectoration are usually mistaken by patients for minor diseases such as colds, and patients pay insufficient attention to them[37]. Patients suffer more discomfort, such as fever, chest pain, weight loss or haemoptysis, and their increased vigilance prompts them to seek health readily[38,39]. The reasons surveyed for HSD also indicate the prevalence of ignoring symptoms among PTB patients. It is necessary to reinforce TB health education, improve patients' ability to recognize symptoms, and promote early health seeking. Moreover, during the epidemic period, COVID-19 prevention and control agencies at all levels took fever as an important symptom in the quarantine of COVID-19[40], which promoted the health of PTB patients with fever symptoms but may have caused health providers and patients to ignore other symptoms, exacerbating the delay in seeking healthcare for patients with simple coughs and expectoration.

In agreement with reports from other countries[41–43], we found that self-medication prior to seeking healthcare prolonged the HSI. The explanation may be that self-medical treatment, especially antibiotics, can temporarily relieve patients' PTB symptoms[44], leading patients to think that the illness is over and to give up seeing a doctor. Self-medication accounts for nearly two-thirds of the PTB patients, although the proportion was much higher than that of patients in Zimbabwe (12.5%)[45], but it is not astonishing, as self-medication with over-the-counter medicines and prescription-only medicines are both pervasive in China[46]. Ge et al. [47]reported that the self-medication rate of Chinese adults was as high as 99.1%. In a report from southern China, antibiotics were almost universally prescribed for coughs. The primary reasons for opting for self-treatment over seeking medical care for perceived non-severe illnesses were cost and time savings[48,49]. Hence, offering health education and accessible services to these patients may help reduce the risk of health-seeking delay.

ACF is an effective method for early detection of pulmonary tuberculosis (PTB) patients and has been widely accepted and implemented globally[50,51]. This study further validated that during the COVID-19 epidemic, among the 25 patients identified through the ACF method, 14 patients with febrile symptoms experienced shortened HSIs. This finding suggests that in future PTB screening practices, attention should also be given to individuals with other PTB symptoms, beyond just chest symptoms. Among the patients diagnosed before the epidemic, ACF did not demonstrate a protective effect against HSD, which may be attributed to the small sample size (only 13 cases identified by ACF), thereby reducing the efficiency of testing.

Unlike the 2010 tuberculosis epidemiological survey[26], this study found that fewer PTB patients delayed seeking care due to medical expenses and transportation distance, with improved health service accessibility. However, a high proportion still disregarded PTB symptoms, leading to delays in seeking medical attention.

We found no significant difference in HSI or HSD between PTB patients diagnosed before and during the COVID-19 epidemic. During the epidemic, PTB case-finding services had positive effects, offsetting the impact of PHSMs. The proportion of patients found through ACF increased significantly, and quarantine measures facilitated the identification of febrile PTB cases. However, PHSMs negatively influenced some patients' health-seeking behaviour, prolonging consultation times due to fear of COVID-19. To prevent delays in future epidemics, it's crucial to intensify health education, conduct ACF, and implement multi-disease co-examinations.

Strengths and limitations

To our knowledge, this is the first multicentre study in China since 2020 to investigate HSD among PTB patients. It compares the durations of HSIs in different epidemic stages and under various stringency levels of PHSMs with those in the nonepidemic period, providing a comprehensive understanding of the current situation and influencing factors of HSD in China. The survey results offer new and crucial insights into PTB health-seeking delays in the country. However, the study has some limitations. Firstly, due to the significant time gap between when patients fell ill and when the survey was conducted, recall bias was inevitable. Secondly, due to difficulties in obtaining information such as patients' income and comorbidities, knowledge of PTB was excluded from the analysis, despite being identified as an influencing factor in previous studies. Lastly, only notified PTB patients were surveyed, excluding those who had not been diagnosed, potentially underestimating the extent of health-seeking delay.

The health-seeking delay for PTB patients in China remains high, with limited impact from the COVID-19 epidemic. Factors such as nonspecific cough, self-medication, and passive case-finding contribute to delays. Many patients mistake PTB for mild illnesses like colds. A few attribute delays to PHSMs during the epidemic. To reduce HSD, efforts should focus on enhancing public awareness of PTB symptoms, improving healthcare access, conducting active case-finding, and examining for multiple diseases during epidemics.

TB Tuberculosis

PTB Pulmonary tuberculosis

PHSMs Public health and social measures

HSI Health seeking interval

HSD Health seeking delay

ACF Active case-finding

PCF Passive case-finding

IQR Inter Quartile Range

AOR Adjusted Odds Ratio

CI Confidence Interval

Ethics approval and consent to participate

The study was approved by the Ethics Committee Review Board of the Chinese Center for Disease Control and Prevention (No. 202230). All participants were informed of the purpose of the study and provided written informed consent.

Consent for publication

Not applicable.

Competing interests

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as potential conflicts of interest.

Funding

This work was supported by the Research Project of the Chinese Center for Disease Control and Prevention (Grant no. JY22-3-13), and the Peking Union Medical College Education fund (Grant no. 20230221).

Author Contribution

Hui Zhang, Li Wang, and Mingkuan Fan conceived the study concept and design. Mingkuan Fan, Yushu Liu, Kui Liu, Yuhong Li and Xiaoqiu Liu collected data. The analysis was performed by Mingkuan Fan and Li Wang. Mingkuan Fan and Yushu Liu wrote the first draft of the manuscript. Hui Zhang, Li Wang, Tao Li and Canyou Zhang reviewed the manuscript and made substantial revisions. All authors reviewed the manuscript and approved the submitted version.

Acknowledgement

The authors acknowledge all participants in the study and thank the health staff in the CDC- and TB-designated facilities organizing and participating in the patient survey.

Data Availability

The datasets generated and analysed during the current study are available from the corresponding authors on reasonable request.

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No competing interests reported.

Health-seeking delay and potential determinants among pulmonary tuberculosis patients: a retrospective survey in China

Status:

Version 1

Abstract

Background

Methods

Results

Conclusions

Figures

Background

Methods

Results

Discussion

Conclusion

Abbreviations

Declarations

Ethics approval and consent to participate

Consent for publication

Competing interests

Funding

Author Contribution

Acknowledgement

Data Availability

References

Additional Declarations

Status:

Version 1