Epidemiological characteristics of pulmonary tuberculosis in patients with pneumoconiosis based on its social determinants and risk factors in China: a cross-sectional study from 27 provinces : Chinese Medical Journal

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Original Article

Epidemiological characteristics of pulmonary tuberculosis in patients with pneumoconiosis based on its social determinants and risk factors in China: a cross-sectional study from 27 provinces

Wang, Huanqiang1; Dai, Huaping2,3; He, Jiayu1; Lyu, Xiangpei1; Zhang, Xinran2,4; Li, Tao1

Editor(s): Wei, Peifang

Author Information
Chinese Medical Journal ():10.1097/CM9.0000000000002486, December 29, 2022. | DOI: 10.1097/CM9.0000000000002486

Abstract

Introduction

Pneumoconiosis is a group of heterogeneous occupational interstitial lung diseases caused by inhaling mineral dust into the lungs, leading to lung dysfunction. It is China's most common and severe occupational disease and imposes a significant economic and social burden.[1] By the end of 2021, a total of 915,000 cumulative cases of pneumoconiosis had been reported in China,[2] with an average of 13,000 newly diagnosed patients annually in the past 10 years. China bears the most significant burden of pneumoconiosis across the world. Pulmonary tuberculosis (PTB) is a respiratory infectious disease caused by Mycobacterium tuberculosis (M. tuberculosis) infection, which seriously endangers people's health. It is one of the leading causes of morbidity and death worldwide and is listed as a significant infectious disease in China.[3] China is one of the 30 countries with a high burden of tuberculosis globally and has a high incidence of tuberculosis. In 2020, there were 842,000 new tuberculosis cases (including organs other than the lung) in China, accounting for 8.5% of the total new tuberculosis cases worldwide. The incidence was 59/100,000, of which 95% were PTB.[4]

In China, PTB is the most common comorbidity of pneumoconiosis and the leading cause of premature death of patients with pneumoconiosis. In the late 1980s and early 1990s, China conducted the first national pneumoconiosis epidemiological survey and identified 314,160 cases of various types of pneumoconiosis. The PTB incidence in all the pneumoconiosis patients was 15.82%, and was 14.82%, 14.74%, and 34.60% in the patients with stage I, stage II, and stage III pneumoconiosis.[5] During the past two decades, the incidence of PTB has dropped by more than half,[6] and the incidence of pneumoconiosis complicated with PTB has also decreased significantly.[7] However, there has been no sizeable population-based survey regarding PTB's prevalence in pneumoconiosis cases.

In 2019, China issued “the National Action Plan to Stop Tuberculosis (2019–2022)”, which requires strengthening active screening in critical populations, maximizing the detection of patients, and improving the accessibility of diagnosis and treatment services.[8] Epidemiological studies have found that high-risk populations for PTB included those in close contact with pathogen-positive patients, older adults (>65 years old), workers with high mobility, manual workers, patients with pneumoconiosis, patients with diabetes, and human immunodeficiency virus-infected or acquired immunodeficiency syndrome patients.[9,10] There are >23 million dust-exposed workers[11] and >450,000 living patients with pneumoconiosis in China, as well as a considerable number of suspected patients with pneumoconiosis, most of them born in rural areas, with high mobility and older age, and therefore have higher risk factors for PTB. They are the key population for the prevention and control of active PTB. Consequently, it is necessary to understand the prevalence and main risk factors of PTB in the current patients with pneumoconiosis in China.

The World Health Organization (WHO) Commission on Social Determinants of Health (CSDH) believes that health inequity caused by inequitable social status and resource allocation is the most fundamental cause of social determinants affecting society's health status.[12] PTB has the “exposure-infection-disease-adverse outcome” spectrum and should be monitored for social determinants and risk factors.[13] There are still no reports for pneumoconiosis complicated with PTB based on the CSDH framework.

To understand the disease progression of patients with pneumoconiosis and their utilization of medical services, relying on the occupational health emergency service project supported by the national financial funds in 2018 and the pneumoconiosis prevention research project funded by the Chinese Academy of Engineering in 2019, we conducted a cross-sectional survey on patients with pneumoconiosis in 27 provinces (autonomous regions, municipalities) in China in the first phase, and planned to conduct the follow-up survey every 2 years to establish a cohort study. In this article, we analyzed the prevalence of PTB and its social determinants and risk factors in patients with pneumoconiosis from the baseline data of the first phase and calculated the population attributable fractions (PAFs) of significant risk factors.

Methods

Ethics approval

Ethics approval was obtained from the Ethics Committee of the Institute for Occupational Health and Poisoning Control of the Chinese Center for Disease Control and Prevention (No. 201720). All participants provided their written informed consent.

Study design and participants

A face-to-face questionnaire survey was conducted by trained and qualified occupational disease physicians and nurses. Associated social determinants and individual risk factors were investigated. Baseline survey items included demographic and sociological characteristics, history of exposure to dust, working conditions, lifestyle, economic status, symptoms, stage and complications of pneumoconiosis, quality of life, health literacy, medical service utilization, social security, support, etc. During the survey, the progression and complications of pneumoconiosis, as well as the changes in the patients’ health-seeking behavior, were investigated. Limited by funding and human resources, we adopted the approach of collecting baseline data successively. The surveys were conducted in 5 to 7 provinces yearly, and each region contained 200 to 600 patients with pneumoconiosis. Considering the mobility of patients with pneumoconiosis and the distribution of medical resources, we selected cooperative institutions from the list of national occupational disease diagnostic institutions and occupational health inspection institutions. We carried out patient recruitment and surveys in local, municipal, and county-level occupational disease prevention and control institutions and township health service centers in each province. At the same time, door-to-door surveys were also conducted in towns where patients were concentrated. Considering that some patients had no certification of occupational disease diagnosis, in addition to those diagnosed through occupational disease diagnostic procedures, the survey participants also included clinically diagnosed patients with pneumoconiosis. According to the medical institutions and survey methods, survey participants had inpatient cases, outpatient cases from occupational disease clinics, screening cases identified during an occupational health examination, and household survey cases. Stratified random and convenience sampling was used, respectively, according to the different survey objects. There were more inpatient cases, and stratified random sampling was used in these patients after grouping and numbering the patients by pneumoconiosis stage and severity and work-related injury insurance (WRII). Outpatient and screening cases were fewer, and case data were collected on a rolling basis. The household survey was conducted in towns and villages where pneumoconiosis cases were concentrated according to the information provided by institutions and patients. Exclusion criteria included: (1) mental and behavioral disorders; (2) those who could not understand the contents of the questionnaire well for various reasons; and (3) patients without informed consent.

From December 2017 to June 2021, a total of 11,181 questionnaires were collected in 27 provinces (autonomous regions, municipalities) except Tianjin, Shanghai, Hainan, Tibet, Hongkong, Macao and Taiwan, because pneumoconiosis cases had been rarely diagnosed or reported in Hainan and Tibet, the number of pneumoconiosis cases was deficient in Tianjin and Shanghai, and no suitable medical institutions were available to cooperate with our study. There were 378 repeated questionnaires obtained from patients who received the questionnaire in different regions or hospitals or the same hospital but at other times. There were 180 subjects who were patients under medical surveillance. These patients had some lung lesions, but the profusion of small opacities did not reach the current criteria of stage I pneumoconiosis, as revealed by chest X-ray imaging and needed to undergo further medical surveillance. There were 486 questionnaires that missed essential items and could not be supplemented in the follow-up visits. After excluding these 1044 questionnaires, 10,137 questionnaires were included in the study, accounting for 90.7% of all questionnaires. The present study was cross-sectional, and the baseline survey data were analyzed.

Outcome: pneumoconiosis and tuberculosis

The pneumoconiosis cases included in the study required official occupational disease diagnostic certificates or were clinically diagnosed by physicians qualified for pneumoconiosis diagnosis. According to the GBZ 70-2015 Diagnosis of Occupational Pneumoconiosis, the diagnosis was made.[14] Patients needed a clear history of exposure to mineral dust and a chest X-ray showing abnormal appearance in the posteroanterior view with some related symptoms. Other pulmonary diseases needed to be differentially diagnosed and excluded. A series of close comparative reads with standard images of pneumoconiosis were required for pneumoconiosis diagnosis. Silicosis and coal workers’ pneumoconiosis (CWP) were major diseases, accounting for 47.7% (n = 4834) and 43.8% (n = 4444) of the total of 10,137 participants, respectively, followed by welder's pneumoconiosis (n = 163, 1.6%), asbestosis (n = 156, 1.5%), cement pneumoconiosis (n = 52, 0.5%), founder's pneumoconiosis (n = 29, 0.3%), potter's pneumoconiosis (n = 23, 0.2%), mica pneumoconiosis (n = 8, 0.1%), and the others (n = 428, 4.2%). In stratified analysis, the numbers of pneumoconiosis patients were usually too small except for silicosis and CWP, and the differences in the prevalence of PTB combined with these kinds of pneumoconiosis were relatively small. Therefore, they were merged with the other types of pneumoconiosis for analysis in this paper.

Diagnosis of PTB were identified from inpatient or outpatient medical records. In China, the diagnosis of PTB is mainly based on the WS 288-2017 Diagnostic Criteria for Pulmonary Tuberculosis,[15] which are in line with the diagnostic criteria of the WHO.[16] Diagnostic methods included detection of acid-fast-bacilli in smears of specimens, culture, tuberculin purified protein derivative skin test, and serological testing for M. tuberculosis infection.

Investigated social determinants and individual risk factors

Social determinants and individual risk factors for PTB infection were selected for this analysis. Demographic sociology and personal lifestyle factors included sex, age, marital status, smoking history, smoking index, age of starting smoking, alcohol intake, body mass index (BMI), etc. The smoking index is a unit for measuring cigarette consumption during the past year and was calculated using the following formula: smoking index = cigarettes smoked per day (CPD) × years of tobacco use.[17] The smoking index categories were <100, 100 to 199, 200 to 399, and ≥400. Non-smokers affirmed that they had never smoked or had a smoking index of <100 cigarettes. Patients who smoked at the time of investigation and had a smoking index ≥100 cigarettes were considered current smokers. Patients who had smoked ≥100 cigarettes but had not smoked during the past six months were considered former smokers. BMI was calculated as body weight (kg) divided by height (m) squared and was classified into four categories: underweight (<18.5 kg/m2), average weight (18.5–23.9 kg/m2), overweight (24.0–27.9 kg/m2), and obese (≥28.0 kg/m2), according to the Chinese BMI criteria.[18]

Socioeconomic factors included region, education level, annual personal income per capita, and annual family income per capita. Factors related to the working and living environment included birthplace, residence, kinds of the work unit, current employment status, dust exposure history, whether engaged in mining, construction material processing and stone processing, accumulated dust exposure time, and workplace and residence ventilation. Social security included WRII, urban resident basic medical insurance (URBMI), new rural cooperative medical scheme (NCMS), and urban employee basic medical insurance (UEBMI). History of close contact with PTB included in-hospital PTB exposure, household PTB exposure, and workplace or residential district PTB exposure (e.g., whether patients in the same ward, family members, co-workers, and neighbors have PTB). The Bacille Calmette-Guérin (BCG) vaccination status was determined by checking for a BCG vaccine scar on the arm or was reported by the participants.

Disease and treatment conditions included the source of case, type of pneumoconiosis, stage of pneumoconiosis, history of PTB, pulmonary bulla or emphysema, diabetes, acute exacerbation of pneumoconiosis, history of drug use for the treatment of pneumoconiosis and its complications, history of using immune-enhancing drugs, and other drugs. Other investigated factors included survey season and dietary meat, fish, eggs, and fruit [Supplementary Table 1, https://links.lww.com/CM9/B350]. Each patient's self-rated health status was ascertained using the self-reported health status.[19]

Statistical analysis

After the questionnaires were collected, reviewed, and cleaned up, the survey data were double-entered using Epidata 3.1 (The EpiData Association, Odense, Denmark), and SPSS 26.0 software (IBM Corp., Armonk, NY, USA) was used for establishing the database, error detection, and statistical analysis. R V4.1.1 (TUNA Team, Tsinghua University; release date: April 24, 2020) was used to establish figures. Questionnaires with logical errors and missing values were all supplemented through telephone interviews by the investigators responsible for the questionnaires. Measurement data conforming to the normal distribution were expressed as mean ± standard deviation, and count data were expressed as rates or composition ratios. T tests were used for continuous variables with normal or near normal data distribution, and equal variances were assumed. Chi-square analysis and Fisher's exact test were used for categorical data. Multivariate logistic regression was used to perform model fitting incorporating all cases, including cases living in rural areas, or cases residing in urban areas. The models were adjusted for sex, age, and other confounding factors. P < 0.05 was considered to indicate statistical significance. The odds ratio (OR) with a 95% confidence interval (CI) was calculated for categorical variables in the study to assess the strength of association between risk factors and PTB prevalence.

To estimate the risk of PTB combined with pneumoconiosis in patients with multiple risk factors for PTB and to gain a preliminary understanding of the interactions among these risk factors, we selected six kinds of risk factors from the results of a multivariate analysis. The six risk factors were: history of close contact with PTB in hospital, no WRII, smoker (current smokers or former smokers), underweight (BMI <18.5 kg/m2), history of close contact with PTB at home, and former drinker, included as Factors 1 to 6, respectively. Next, we combined every three factors and formed six risk combinations. The pneumoconiosis patients who were all negative for the three factors were referred to as the control group. We compared positive pneumoconiosis patients for only one factor, each combination of two factors, and all three factors with the control group and calculated the OR with 95% CI. Additionally, we calculated the proportion of pneumoconiosis patients with each risk combination in the total number of respondents. We performed stratified analyses to estimate the trend of PTB rate among pneumoconiosis patients with different BMI groups and smoking index groups under the influence of high-risk factors.

The population attributable fractions (PAFs) for the main risk factors were calculated using Levin's formula: PAF = P × (RR − 1)/(1 + P × [RR–1]), where P is the population prevalence of the risk factor.[20] We used ORs from the multiple logistic analysis to substitute for relative risk (RR). Through univariate and multivariate analyses, 11 risk factors were screened out, the commonality of each element was obtained by factor analysis, and the weight, weighted PAF, and adjusted PAF of each aspect were calculated separately. The 95% CIs for the PAF and adjusted PAF were calculated using Walter's[21] formula and the method recommended by Natarajan et al,[22] respectively.

Results

Baseline characteristics

The average age of the 10,137 included patients was 58 ± 12 years, mainly males (97.4%, n = 9875). The average age was 55 ± 10 years among rural patients (n = 5713) and 61 ± 13 years among urban patients (n = 4424). Rural patients were significantly younger than urban patients (t = −29.932, P < 0.001). Among the urban patients, 79.3% (3507/4424) were covered by the UEBMI, 12.8% (565/4424) by the NCMS, and 5.4% (237/4424) by the URBMI. Among the rural patients, 74.1% (4231/5713) were covered by the NCMS, 17.7% (1010/5713) by the UEBMI, and 5.5% (317/5713) by the URBMI. There were 31.9% (1822/5713) of the rural patients and 71.9% (3179/4424) of the urban patients covered by the WRII, which showed a significant difference (χ2 = 1593.256, P < 0.001).

The average dust exposure time was 19 ± 10 years. Silicosis and CWP were major diseases, accounting for 91.5% (n = 9280). Cases at stages I, II, and III accounted for 44.8% (n = 4540), 24.8% (n = 2518), and 21.1% (n = 2134), respectively, and 9.3% (n = 945) had no information on stage. The proportion of rural patients suffering from bullae or emphysema was higher than that of urban patients (12.1% [689/5713] vs. 6.5% [288/4424], χ2 = 88.191, P < 0.001).

The proportion of rural patients with a history of alcohol consumption was higher than that of urban patients (26.8% [1532/5713] vs. 22.8% [1009/4424], χ2 = 28.856, P < 0.001). The average age at starting smoking in patients with pneumoconiosis was 23 ± 8 years. The smoking rate in the rural patients was significantly higher than that in the urban patients (54.3% [3104/5713] vs. 47.4% [2097/4424], χ2 = 47.952, P < 0.001). Among them, 17.0% (969/5713) of the rural patients and 14.4% (638/4424) of the urban patients had a smoking index of 200 to 399, and 27.6% (1577/5713) of the rural patients and 23.7% (1050/4424) of the urban patients had a smoking index >399. The proportion of moderate and heavy smokers in rural patients was higher than that in urban patients (χ2 = 49.868, P < 0.001). The average BMI of all patients was 23.2 ± 3.6 kg/m2, and the BMI of the urban patients, at 24.0 ± 3.5 kg/m2, was significantly higher than that of the rural patients at 22.7 ± 3.6 kg/m2 (t = –18.998, P < 0.001). In addition, 9.6% (549/5713) of the rural patients and 4.7% (208/4424) of the urban patients were underweight, which was significantly different between the two groups (χ2 = 86.917, P < 0.001). Table 1 shows the main demographic and sociological characteristics of the patients with pneumoconiosis from 27 provinces of China, as well as the sociological determinants and risk factors for PTB in patients with various stages of pneumoconiosis. For the others, see Supplementary Table 2, https://links.lww.com/CM9/B350.

Table 1 - Demographics of patients with pneumoconiosis from 27 provinces of China, with risk factors and social determinants for PTB, by pneumoconiosis stage.
Items Total (n = 10,137) No PTB (n = 9375) Case stage I with PTB (n = 175) Case stage II with PTB (n = 193) Case stage III with PTB (n = 269) Clinical case with PTB (n = 125) P for difference
Proportion of participants (%) 100.0 92.5 1.7 1.9 2.7 1.2
Male 9875 (97.4) 9127 (97.4) 166 (94.9) 191 (99.0) 268 (99.6) 123 (98.4) 0.109
Smoking index <0.001
 <100 4936 (48.7) 4633 (49.4) 96 (54.9) 75 (38.9) 99 (36.8) 33 (26.4)
 100–199 967 (9.5) 905 (9.7) 13 (7.4) 18 (9.3) 22 (8.2) 9 (7.2)
 200–399 1607 (15.9) 1474 (15.7) 29 (16.6) 34 (17.6) 48 (17.8) 22 (17.6)
 >399 2627 (25.9) 2363 (25.2) 37 (21.1) 66 (34.2) 100 (37.2) 61 (48.8)
Alcohol intake <0.001
 Current drinkers 2103 (20.7) 2012 (21.5) 27 (15.4) 30 (15.5) 21 (7.8) 13 (10.4)
 Former drinkers 2541 (25.1) 2269 (24.2) 37 (21.1) 67 (34.7) 125 (46.5) 43 (34.4)
BMI 23.25 ± 0.04 23.36 ± 0.04 22.98 ± 0.26 23.04 ± 0.29 21.04 ± 0.27 20.87 ± 0.24 <0.001
 <18.5 kg/m2 757 (7.5) 623 (6.6) 13 (7.4) 19 (9.8) 76 (28.3) 26 (20.8)
 18.5–23.9 kg/m2 5386 (53.1) 4953 (52.8) 100 (57.1) 108 (56.0) 140 (52.0) 85 (68.0)
 24.0–27.9 kg/m2 3225 (31.8) 3070 (32.7) 52 (29.7) 45 (23.3) 46 (17.1) 12 (9.6)
 ≥28.0 kg/m2 769 (7.6) 729 (7.8) 10 (5.7) 21 (10.9) 7 (2.6) 2 (1.6)
Region of China <0.001
 Eastern 3475 (34.3) 3307 (35.3) 48 (27.4) 47 (24.4) 69 (25.7) 4 (3.2)
 Central 2002 (19.7) 1848 (19.7) 21 (12.0) 35 (18.1) 58 (21.6) 40 (32.0)
 Western 3743 (36.9) 3399 (36.3) 66 (37.7) 93 (48.2) 105 (39.0) 80 (64.0)
 Northeastern 917 (9.0) 821 (8.8) 40 (22.9) 18 (9.3) 37 (13.8) 1 (0.8)
Working and living environment
 Born in rural areas 8609 (84.9) 7915 (84.4) 140 (80.0) 175 (90.7) 260 (96.7) 119 (95.2) <0.001
 Living in rural areas 5713 (56.4) 5200 (55.5) 71 (40.6) 125 (64.8) 226 (84.0) 91 (72.8) <0.001
  Employment status <0.001
   Retirement 3996 (39.4) 3762 (40.1) 91 (52.0) 71 (36.8) 56 (20.8) 16 (12.8)
   Unemployment 2802 (27.6) 2458 (26.2) 37 (21.1) 79 (40.9) 161 (59.9) 67 (53.6)
   Temporary employment 1177 (11.6) 1098 (11.7) 13 (7.4) 23 (11.9) 22 (8.2) 21 (16.8)
   Long-term employment 1193 (11.8) 1154 (12.3) 17 (9.7) 7 (3.6) 6 (2.2) 9 (7.2)
   Others 969 (9.6) 903 (9.6) 17 (9.7) 13 (6.7) 24 (8.9) 12 (9.6)
Social security
 WRII <0.001
  Yes 5512 (54.4) 5254 (56.0) 109 (62.3) 80 (41.5) 55 (20.4) 14 (11.2)
  No 4625 (45.6) 4121 (44.0) 66 (37.7) 113 (58.5) 214 (79.6) 111 (88.8)
History of close contact with PTB and vaccination
 In hospital 0.001
  Yes 1411 (13.9) 1096 (11.7) 52 (29.7) 72 (37.3) 119 (44.2) 72 (57.6)
  No 8726 (86.1) 8279 (88.3) 123 (70.3) 121 (62.7) 150 (55.8) 53 (42.4)
 In household 0.001
  Yes 342 (3.4) 274 (2.9) 13 (7.4) 17 (8.8) 25 (9.3) 13 (10.4)
  No 9795 (96.6) 9101 (97.1) 162 (92.6) 176 (91.2) 244 (90.7) 112 (89.6)
 In workplace or residential district 0.001
  Yes 1593 (15.7) 1425 (15.2) 20 (11.4) 45 (23.3) 87 (32.3) 16 (12.8)
  No 8544 (84.3) 7950 (84.8) 155 (88.6) 148 (76.7) 182 (67.7) 109 (87.2)
 BCG history 0.002
  Yes 5199 (51.3) 4813 (51.3) 74 (42.3) 101 (52.3) 152 (56.5) 59 (47.2)
  No 1803 (17.8) 1635 (17.4) 55 (31.4) 46 (23.8) 47 (17.5) 20 (16.0)
  Missing 3135 (30.9) 2927 (31.2) 46 (26.3) 46 (23.8) 70 (26.0) 46 (36.8)
Disease and treatment conditions
 Source of cases <0.001
  Screening cases 980 (9.7) 955 (10.2) 10 (5.7) 6 (3.1) 8 (3.0) 1 (0.8)
  Inpatient cases 4477 (44.2) 4086 (43.6) 94 (53.7) 103 (53.4) 104 (38.7) 90 (72.0)
  Outpatient cases 2275 (22.4) 2155 (23.0) 31 (17.7) 26 (13.5) 39 (14.5) 24 (19.2)
  Household cases 2405 (23.7) 2179 (23.2) 40 (22.9) 58 (30.1) 118 (43.9) 10 (8.0)
 Types of pneumoconiosis <0.001
  Silicosis 4836 (47.7) 4334 (46.2) 104 (59.4) 131 (67.9) 192 (71.4) 75 (60.0)
  CWP 4444 (43.8) 4212 (44.9) 63 (36.0) 58 (30.1) 69 (25.7) 42 (33.6)
  Others 857 (8.5) 829 (8.8) 8 (4.6) 4 (2.1) 6 (3.0) 8 (6.4)
 Pulmonary bullae or pneumothorax <0.001
  Yes 977 (9.6) 822 (8.8) 22 (12.6) 28 (14.5) 96 (35.7) 9 (7.2)
  No 9160 (90.4) 8553 (91.2) 153 (87.4) 165 (85.5) 173 (64.3) 116 (92.8)
 History of hormone therapy for pneumoconiosis <0.001
  Yes 483 (4.8) 413 (4.4) 9 (5.1) 19 (9.8) 41 (15.2) 1 (0.8)
  No 9654 (95.2) 8962 (95.6) 166 (94.9) 174 (90.2) 228 (84.8) 124 (99.2)
Season for survey <0.001
 Spring 1613 (15.9) 1517 (16.2) 16 (9.1) 21 (10.9) 51 (19.0) 8 (6.4)
 Summer 3603 (35.5) 3281 (35.0) 84 (48.0) 86 (44.6) 96 (35.7) 56 (44.8)
 Autumn 2915 (28.8) 2678 (28.6) 54 (30.9) 53 (27.5) 77 (28.6) 53 (42.4)
 Winter 2006 (19.8) 1899 (20.3) 21 (12.0) 33 (17.1) 45 (16.7) 8 (6.4)
Data are expressed as number (%) and mean ± standard deviation. Eastern region includes seven provinces (municipalities): Beijing, Hebei, Jiangsu, Zhejiang, Fujian, Shandong and Guangdong; Tianjin, Shanghai and Hainan were not surveyed; Central region includes six provinces: Shanxi, Anhui, Jiangxi, Henan, Hubei and Hunan. Western region includes 11 provinces (autonomous regions, municipalities): Inner Mongolia, Guangxi, Chongqing, Sichuan, Guizhou, Yunnan, Shaanxi, Gansu, Qinghai, Ningxia and Xinjiang; Tibet was not surveyed; Northeastern region includes three provinces: Liaoning, Jilin, Heilongjiang. Hongkong, Macao and Taiwan were also not surveyed. BCG: Bacille Calmette-Guérin; BMI: Body-mass index; CWP: Coal workers’ pneumoconiosis; PTB: Pulmonary tuberculosis; WRII: Work-Related Injury Insurance.

The self-rated health scores in rural and urban patients were 55.3 ± 18.4 and 61.5 ± 17.2, respectively. The former was significantly lower than the latter (t = –18.872, P < 0.001). The self-rated health scores of the patients with PTB and without PTB were 52.0 ± 18.3 and 58.5 ± 18.1, respectively, and the former was significantly lower than the latter (t = –9.843, P < 0.001). In addition, patients with unemployment, complications of bullae or emphysema, with a history of hormone drug therapy, malnutrition, hospitalization, or exposure to tuberculosis by the hospital or household contact often had lower self-rated health scores (P < 0.01). In contrast, drinkers had a higher self-rated score than former drinker or non-drinker (P < 0.01).

Prevalence and risk factors of PTB in patients with pneumoconiosis

The prevalence of PTB in the investigated patients with pneumoconiosis was 7.5% (95% CI: 7.0%–8.0%). The prevalence was 9.0% (8.2%–9.7%) in rural patients and 5.6% (4.9%–6.3%) in urban patients. Univariate analysis showed that multiple factors were associated with the risk of PTB in these patients, including population sociological factors (region, urban or rural area, work), lifestyle (smoking, drinking, diet, etc), socioeconomic characteristics (personal and family annual income), working and living environment (ventilation conditions, family size), WRII, medical insurance, close contact with PTB patients, BCG-unvaccinated, disease, and treatment (types and stages of pneumoconiosis, complication with pulmonary bullae and emphysema, medicine and hormone therapy, and hospitalization history), survey season, etc, among which higher smoking index, earlier age at starting smoking, lower BMI, lower educational level, shorter dust exposure time, higher pneumoconiosis stage, and more acute exacerbations were associated with a higher risk of PTB, and also showed significant dose-response relationships (P < 0.001; Table 2 and Supplementary Table 3, https://links.lww.com/CM9/B350).

Table 2 - Prevalence and ORs for PTB with risk factors and social determinants in patients with pneumoconiosis from 27 provinces of China, by rural and urban residence.
Prevalence (%) in patients (95% CI)

Items Living in rural Living in urban Total OR 95% CI P
Smoking index
 <100 6.9 (5.9–7.8) 5.3 (4.4–6.2) 6.1 (5.5–6.8) 1.00 ref
 100–199 7.2 (5.0–9.3) 5.4 (3.2–7.6) 6.4 (4.9–8.0) 1.05 0.79–1.39 0.750
 200–399 10.3 (8.4–12.2) 5.2 (3.5–6.9) 8.3 (6.9–9.6) 1.38 1.12–1.71 <0.001
 >399 12.3 (10.7–13.9) 6.7 (5.2–8.2) 10.0 (8.9–11.2) 1.71 1.44–2.03 <0.001
P for trend <0.001 0.184 <0.001
Alcohol intake
 Non-drinkers 8.2 (7.2–9.1) 6.2 (5.3–7.1) 7.3 (6.6–8.0) 1.00 ref
 Current drinkers 5.1 (3.8–6.3) 3.3 (2.2–4.5) 4.3 (3.5–5.2) 0.58 0.46–0.73 <0.001
 Former drinkers 13.6 (11.9–15.4) 6.2 (4.8–7.7) 10.7 (9.5–11.9) 1.53 1.30–1.80 <0.001
P for difference <0.001 0.004 <0.001
BMI
 <18.5 kg/m2 19.7 (16.3–23.0) 12.5 (8.0–17.0) 17.7 (15.0–20.4) 2.46 1.99–3.04 <0.001
 18.5–23.9 kg/m2 8.8 (7.8–9.8) 6.8 (5.7–7.9) 8.0 (7.3–8.8) 1.00 ref
 24.0–27.9 kg/m2 5.7 (4.5–6.8) 4.1 (3.2–5.0) 4.8 (4.1–5.5) 0.58 0.48–0.70 <0.001
 ≥28.0 kg/m2 7.7 (4.8–10.6) 3.4 (1.7–5.1) 5.2 (3.6–6.8) 0.63 0.45–0.88 0.006
P for trend <0.001 <0.001 <0.001
Region of China
 Eastern 6.0 (4.9–7.0) 3.6 (2.7–4.5) 4.8 (4.1–5.5) 1.00 ref
 Central 10.8 (8.9–12.7) 4.3 (3.0–5.6) 7.7 (6.5–8.9) 1.64 1.31–2.06 <0.001
 Western 9.2 (8.1–10.3) 9.2 (7.5–10.9) 9.2 (8.3–10.1) 1.99 1.65–2.41 <0.001
 Northeastern 29.7 (22.4–37.1) 6.8 (5.0–8.5) 10.5 (8.5–12.5) 2.30 1.77–2.99 <0.001
P for difference <0.001 <0.001 <0.001
Birthplace
 Rural areas 9.0 (8.3–9.8) 6.2 (5.3–7.1) 8.1 (7.5–8.6) 1.88 1.46–2.43 <0.001
 Urban areas 2.4 (0–7.2) 4.5 (3.5–5.6) 4.5 (3.4–5.5) 1.00 ref
P for difference 0.106 0.012 <0.001
Employment status
 Retirement 6.2 (4.7–7.6) 5.7 (4.9–6.6) 5.9 (5.1–6.6) 1.00 ref
 Unemployment 12.3 (11.0–13.6) 12.0 (8.5–15.6) 12.3 (11.1–13.5) 2.25 1.89–2.68 <0.001
 Temporary employment 6.8 (5.2–8.3) 6.5 (2.8–10.2) 6.7 (5.3–8.1) 1.16 0.89–1.51 0.280
 Long–term employment 3.8 (2.1–5.5) 2.9 (1.7–4.2) 3.3 (2.3–4.3) 0.54 0.39–0.77 <0.001
 Others 8.2 (6.2–10.3) 3.6 (1.5–5.8) 6.8 (5.2–8.4) 1.18 0.89–1.56 0.260
P for difference <0.001 <0.001 <0.001
WRII
 Yes 4.5 (3.5–5.4) 4.8 (4.1–5.4) 4.7 (4.1–5.2) 1.00 ref
 No 10.9 (9.9–11.8) 11.0 (8.5–13.4) 10.9 (10.0–11.8) 2.49 2.13–2.91 <0.001
P for difference <0.001 <0.001 <0.001
History of close contact with PTB and vaccination
 In hospital
  Yes 26.3 (23.3–29.3) 16.7 (13.6–19.7) 22.3 (20.2–24.5) 5.32 4.55–6.23 <0.001
  No 6.0 (5.4–6.7) 4.0 (3.3–4.6) 5.1 (4.7–5.6) 1.00 ref
   P for difference <0.001 <0.001 <0.001
 In household
  Yes 22.9 (17.4–28.5) 14.5 (8.3–20.7) 19.9 (15.7–24.1) 3.26 2.47–4.29 <0.001
  No 8.4 (7.7–9.2) 5.4 (4.7–6.0) 7.1 (6.6–7.6) 1.00 ref
   P for difference <0.001 <0.001 <0.001
 In workplace or residential district
  Yes 11.7 (9.9–13.5) 6.5 (4.0–9.1) 10.5 (9.0–12.1) 1.58 1.32–1.89 <0.001
  No 8.2 (7.4–9.0) 5.5 (4.8–6.3) 7.0 (6.4–7.5) 1.00 ref
   P for difference <0.001 0.246 <0.001
 BCG history
  Yes 9.8 (8.7–10.9) 4.6 (3.7–5.4) 7.4 (6.7–8.1) 1.00 ref
  No 10.3 (8.3–12.3) 8.3 (6.5–10.2) 9.3 (8.0–10.7) 1.28 1.06–1.55 0.010
  Missing 7.2 (6.1–8.4) 5.7 (4.4–7.0) 6.6 (5.8–7.5) 0.89 0.74–1.06 0.175
   P for difference <0.001 <0.001 <0.001
Disease and treatment conditions
 Source of cases
  Screening cases 2.6 (1.1–4.1) 2.5 (1.2–3.8) 2.6 (1.6–3.5) 1.00 ref
  Inpatient cases 11.1 (9.7–12.5) 6.8 (5.9–7.8) 8.7 (7.9–9.6) 3.66 2.43–5.51 <0.001
  Outpatient cases 6.4 (5.0–7.8) 3.9 (2.8–5.1) 5.3 (4.4–6.2) 2.13 1.37–3.30 <0.001
  Household cases 9.8 (8.5–11.1) 6.9 (4.2–9.5) 9.4 (8.2–10.6) 3.96 2.60–6.03 <0.001
   P for difference <0.001 <0.001 <0.001
 Type of pneumoconiosis
  Others 4.6 (2.4–6.8) 2.3 (1.0–3.7) 3.3 (2.1–4.5) 1.00 ref
  Silicosis 11.4 (10.3–12.5) 8.4 (7.1–9.8) 10.4 (9.5–11.2) 3.43 2.33–5.05 <0.001
  CWP 6.1 (5.1–7.1) 4.4 (3.5–5.2) 5.2 (4.6–5.9) 1.63 1.09–2.43 0.020
   P for difference <0.001 <0.001 <0.001
 Stages of pneumoconiosis
  Stage I 3.9 (3.0–4.8) 3.8 (3.1–4.5) 3.9 (3.3–4.4) 1.00 ref
  Stage II 8.1 (6.8–9.5) 6.9 (5.3–8.5) 7.7 (6.6–8.7) 2.07 1.68–2.56 <0.001
  Stage III 13.5 (11.9–15.2) 9.3 (6.7–12.0) 12.6 (11.2–14.0) 3.60 2.95–4.39 <0.001
  Clinical cases (no classified stage) 13.0 (10.5–15.5) 13.9 (9.5–18.2) 13.2 (11.1–15.4) 3.80 2.99–4.84 <0.001
   P for trend <0.001 <0.001 <0.001
 Pulmonary bullae or pneumothorax
  Yes 16.7 (13.9–19.5) 13.9 (9.9–17.9) 15.9 (13.6–18.2) 2.66 2.20–3.21 <0.001
  No 7.9 (7.2–8.7) 5.1 (4.4–5.7) 6.6 (6.1–7.1) 1.00 ref
   P for difference <0.001 <0.001 <0.001
 History of hormone therapy for pneumoconiosis
 Yes 14.9 (11.2–18.7) 13.3 (7.6–19.1) 14.5 (11.4–17.6) 2.20 1.68–2.86 <0.001
 No 8.6 (7.8–9.3) 5.4 (4.7–6.1) 7.2 (6.7–7.7) 1.00 ref
P for difference <0.001 <0.001 <0.001
 Season for survey
  Spring 7.6 (6.0–9.2) 2.9 (1.5–4.3) 6.0 (4.8–7.1) 1.00 ref
  Summer 10.4 (9.0–11.7) 7.4 (6.2–8.6) 8.9 (8.0–9.9) 1.55 1.23–1.96 <0.001
  Autumn 11.0 (9.4–12.6) 5.3 (4.2–6.5) 8.1 (7.1–9.1) 1.40 1.09–1.79 0.007
  Winter 6.0 (4.7–7.3) 4.0 (2.5–5.5) 5.3 (4.4–6.3) 0.89 0.67–1.18 0.422
   P for difference <0.001 <0.001 <0.001
BCG: Bacille Calmette-Guérin; BMI: Body-mass index; CI: Confidence interval; CWP: Coal workers’ pneumoconiosis; OR: Odds ratio; PTB: Pulmonary tuberculosis; WRII: Work-Related Injury Insurance.

Multivariate analysis of risk factors for PTB in patients with pneumoconiosis

The model incorporating all patients showed that protective factors for PTB included alcohol consumption and BMI higher than usual (24.0 kg/m2 ≤ BMI ≤ 27.9 kg/m2); risk factors included a smoking index of ≥200, being underweight (BMI <18.5 kg/m2), living in western or northeastern regions, being born in a rural area, being unemployed, without WRII, in-hospital or household exposure to PTB patients, BCG-unvaccinated, inpatient, outpatient or household cases, issues of the higher stage of pneumoconiosis or clinically diagnosed cases, silicosis, complication with pulmonary bullae or emphysema, hospitalization history, or receiving a survey in summer or fall. Income and diet did not show a significant association with PTB.

Among all the three models, including all patients, rural patients, and urban patients models, drinking, and overweight (24.0 kg/m2 ≤ BMI ≤ 27.9 kg/m2) were protective factors, and living in the northeastern regions, exposure to PTB patients in hospital or household, stage II pneumoconiosis, clinically diagnosed cases and receiving the survey in summer were risk factors. Being a former drinker was a statistically significant risk factor in the model for rural patients. However, living in western regions, being born in a rural area, BCG-unvaccinated, type of pneumoconiosis, and complications with bullae or emphysema were not statistically significant in the model for rural patients. Regarding the model for urban patients, smoking, being born in a rural area, being unemployed, without WRII, inpatient, outpatient or household cases, hospitalization history, and survey in autumn did not show statistical significance [Table 3].

Table 3 - Multiple-adjusted ORs for PTB associated with risk factors in patients with pneumoconiosis in China from 2017 to 2021.
All pneumoconiosis cases Living in rural areas Living in urban areas



Items OR (95% CI) P OR (95% CI) P OR (95% CI) P
Smoking index
 <100 1.00 (ref) 1.00 (ref) 1.00 (ref)
 100–199 0.93 (0.68–1.27) 0.639 0.89 (0.60–1.33) 0.574 0.96 (0.58–1.60) 0.878
 200–399 1.31 (1.04–1.65) 0.025 1.54 (1.16–2.05) 0.003 0.93 (0.61–1.43) 0.752
 >399 1.37 (1.12–1.67) 0.002 1.60 (1.25–2.06) <0.001 1.02 (0.71–1.45) 0.925
Drinking
 No drinking 1.00 (ref) 1.00 (ref) 1.00 (ref)
 Drinking 0.67 (0.52–0.85) 0.001 0.69 (0.51–0.94) 0.019 0.65 (0.42–0.99) 0.046
 Stop drinking 1.16 (0.96–1.39) 0.128 1.27 (1.01–1.60) 0.039 0.91 (0.65–1.28) 0.591
BMI
 <18.5 kg/m2 1.45 (1.15–1.85) 0.002 1.57 (1.19–2.07) 0.001 1.11 (0.68–1.84) 0.673
 18.5–23.9 kg/m2 1.00 (ref) 1.00 (ref) 1.00 (ref)
 24.0–27.9 kg/m2 0.69 (0.57–0.85) <0.001 0.69 (0.53–0.90) 0.006 0.66 (0.49–0.91) 0.010
 ≥28.0 kg/m2 0.81 (0.57–1.15) 0.234 0.92 (0.58–1.45) 0.704 0.61 (0.34–1.07) 0.086
Region of China
 Eastern 1.00 (ref) 1.00 (ref) 1.00 (ref)
 Central 1.20 (0.93–1.55) 0.163 1.19 (0.85–1.65) 0.309 1.13 (0.71–1.79) 0.611
 Western 1.45 (1.16–1.81) 0.001 1.31 (0.99–1.73) 0.063 2.00 (1.34–2.98) 0.001
 Northeastern 2.41 (1.76–3.31) <0.001 3.60 (2.11–6.14) <0.001 1.70 (1.09–2.64) 0.019
Born in rural areas 1.37 (1.01–1.85) 0.044 2.35 (0.31–17.9) 0.410 1.34 (0.97–1.86) 0.075
Unemployment 1.26 (1.05–1.52) 0.014 1.26 (1.02–1.56) 0.030 1.32 (0.82–2.11) 0.253
Without WRII 1.48 (1.19–1.83) <0.001 1.70 (1.27–2.27) <0.001 1.36 (0.92–2.01) 0.129
History of houshold contacts with PTB patients 1.94 (1.41–2.66) <0.001 1.81 (1.23–2.66) 0.002 2.17 (1.20–3.90) 0.010
History of hospitalization contacts with PTB patients 3.30 (2.77–3.93) <0.001 3.35 (2.69–4.19) <0.001 3.22 (2.38–4.36) <0.001
No BCG vaccination 1.32 (1.07–1.62) 0.010 1.30 (0.99–1.72) 0.061 1.27 (0.89–1.80) 0.187
Source of case
 Medical examination 1.00 (ref) 1.00 (ref) 1.00 (ref)
 Inpatient 2.24 (1.43–3.50) <0.001 3.25 (1.69–6.28) <0.001 1.79 (0.94–3.39) 0.076
 Outpatient 1.66 (1.05–2.63) 0.030 2.42 (1.24–4.70) 0.009 1.30 (0.67–2.54) 0.441
 Households 2.19 (1.39–3.44) 0.001 3.08 (1.61–5.90) 0.001 2.05 (1.00–4.23) 0.051
Stages of pneumoconiosis
 Stage I 1.00 (ref) 1.00 (ref) 1.00 (ref)
 Stage II 1.66 (1.32–2.09) <0.001 1.67 (1.22–2.31) 0.002 1.62 (1.14–2.28) 0.006
 Stage III 1.83 (1.44–2.32) <0.001 1.94 (1.42–2.66) <0.001 1.32 (0.85–2.06) 0.219
 Clinical cases (no classified stage) 3.25 (2.42–4.34) <0.001 3.24 (2.24–4.68) <0.001 3.34 (1.94–5.74) <0.001
Types of pneumoconiosis
 Others 1.00 (ref) 1.00 (ref) 1.00 (ref)
 Silicosis 1.93 (1.27–2.93) 0.002 1.58 (0.90–2.76) 0.110 2.43 (1.29–4.61) 0.006
 CWP 1.28 (0.83–1.95) 0.262 1.05 (0.59–1.86) 0.864 1.50 (0.78–2.87) 0.224
Bulla or emphysema 1.36 (1.09–1.69) 0.007 1.24 (0.95–1.62) 0.118 1.60 (1.07–2.41) 0.024
Former hospitalized 1.57 (1.22–2.02) 0.001 1.66 (1.22–2.25) 0.001 1.40 (0.86–2.28) 0.181
Season of the questionnaire
 Spring 1.00 (ref) 1.00 (ref) 1.00 (ref)
 Summer 1.78 (1.36–2.32) <0.001 1.72 (1.25–2.36) 0.001 1.80 (1.03–3.14) 0.040
 Autumn 1.58 (1.19–2.09) 0.001 1.55 (1.10–2.18) 0.012 1.41 (0.79–2.52) 0.245
 Winter 1.01 (0.74–1.37) 0.969 0.98 (0.68–1.40) 0.891 1.15 (0.59–2.25) 0.683
BCG: Bacille Calmette-Guérin; BMI: Body-mass index; CI: Confidence interval; CWP: Coal workers’ pneumoconiosis; OR: Odds ratio; PTB: pulmonary tuberculosis; WRII: Work-Related Injury Insurance.

In the multivariate model, including 169 patients under medical surveillance, the risk of PTB in patients with pneumoconiosis was >5 times that in subjects under medical surveillance with OR = 5.22 (95% CI: 1.25–21.8; P = 0.024).

Interaction of multiple factors

By combining multiple factors, including the history of exposure to active PTB, without WRII, smoking, being formerly drinking, and being underweight, it was found that the more risk factors a patient had, the higher the risk of PTB [Figure 1]. The risk of PTB was significantly increased, especially in patients with a history of close contact with PTB in hospital, who had no WRII and were underweight (OR = 28.70, 95% CI: 19.21–42.89), which accounted for 1.1% of the study population. Additionally, the odds of pneumoconiosis in patients with a history of close contact with PTB at home, who had no WRII and were underweight was 19.90 times that of controls (OR = 19.90, 95% CI: 9.81–40.38), with a proportion of 0.3% in the study population. Pneumoconiosis patients who were smokers with a history of close contact with PTB in hospital and had no WRII, accounting for 4.1% of the study population, also had a higher risk of PTB compared with controls (OR = 17.53, 95% CI: 13.10–23.46).

F1
Figure 1:
Age- and sex-adjusted ORs according to the multiple risk factors for PTB in patients with pneumoconiosis. (A–F) are models using combinations of three factors (A: Factor 1, Factor 2, Factor 3; B: Factor 1, Factor 2, Factor 4; C: Factor 5, Factor 2, Factor 3; D: Factor 5, Factor 2, Factor 4; E: Factor 1, Factor 2, Factor 6; F: Factor 5, Factor 2, Factor 6) out of a total of six factors. Factor 1 is ever contact with PTB in hospital, Factor 2 is no WRII, Factor 3 is smoker, Factor 4 is underweight, Factor 5 is ever contact with PTB in household, and Factor 6 is former drinker. CI: Confidence interval; OR: Odds ratio; PTB: Pulmonary tuberculosis; WRII: Work-related injury insurance.

The combinations of different factors were associated with various risks. Stratified analysis of smoking index, BMI, exposure to PTB patients in hospital, and complications with pulmonary bulla or emphysema indicated that both smoking index and BMI displayed a dose-response relationship with the prevalence of PTB [Figure 2]. It shows the trends in the rate of PTB in pneumoconiosis patients among different BMI groups along with the increase in the smoking index, comparing pneumoconiosis patients with or without a history of close contact with PTB in hospital, as well as those with or without bullae or emphysema. Moreover, exposure to PTB patients in the hospital or complications with pulmonary bulla or emphysema showed there might be a positive interaction between smoking and being underweight.

F2
Figure 2:
Prevalence of PTB with multiple risk factors in patients with pneumoconiosis. (A–D) are models using stratified analysis on the smoking index, BMI, exposure to PTB patients in hospital, and complications with pulmonary bulla or emphysema, respectively. (A) Prevalence of PTB in patients with pneumoconiosis and no history of close contact with PTB patients in hospital; (B) prevalence of PTB in patients with pneumoconiosis and a history of close contact with PTB patients in hospital; (C) prevalence of PTB in patients with pneumoconiosis and no pulmonary bulla or emphysema; (D) prevalence of PTB in patients with pneumoconiosis and pulmonary bulla or emphysema. With an increase in the smoking index, the comorbidity rate of PTB in low-weight (BMI <18.5 kg/m2) patients with pneumoconiosis increased, showing a dose-response relationship. Among pneumoconiosis patients with bullae or emphysema, the PTB rate of overweight pneumoconiosis patients (BMI >28.0 kg/m2) also increased significantly with an increase in the smoking index if it was <400. Under most stratification conditions, low-weight pneumoconiosis patients had significantly higher PTB rates than those with higher BMIs, except in rare cases, such as those with a smoking index of 200 to 399 among pneumoconiosis patients with bullae or emphysema, and those with a smoking index of 100 to 199 among pneumoconiosis patients with no history of close contact with PTB in hospital. BMI: Body mass index; PTB: Pulmonary tuberculosis.

PAF for risk factors for PTB

Table 4 lists estimates of the crude PAFs, weighted PAFs, adjusted PAFs, and overall PAF of PTB in pneumoconiosis cases for each of the 11 risk factors identified and presents the ORs, risk factor prevalence, and commonality. The proportion of PTB cases that were theoretically preventable through the elimination of the 11 identified risk factors (i.e., overall weighted PAF) was 71.6% (95% CI: 53.7%–89.6%). The adjusted overall PAF obtained by calculating the adjusted OR after controlling for other factors was 82.8% (95% CI: 63.6–101.9). In-hospital or household exposure to PTB patients, being without WRII, being born in a rural area, unemployment, smoking, being a former drinker, malnutrition, and complication of pulmonary bullae or emphysema, all led to higher PAF.

Table 4 - PAF for PTB risk factors in patients with pneumoconiosis from 27 provinces of China (n = 11,037).
Risk factors OR for PTB (95% CI) Risk factor prevalence Communality PAF (95% CI) Weighted PAF (95% CI) ORadj (95% CI) PAFadj (95% CI)
History of household contacts with PTB patients 3.3 (2.5–4.3) 3.4 73.7 7.1 (5.0–9.2) 2.2 (0.7–3.6) 1.9 (1.3–2.7) 2.8 (1.0–5.4)
History of hospitalization contacts with PTB patients 5.3 (4.5–6.2) 13.9 52.2 37.6 (33.6–41.6) 11.6 (8.8–14.3) 3.9 (3.2–4.7) 28.4 (23.0–34.1)
Smoking 1.5 (1.3–1.7) 51.3 45.7 19.8 (12.5–27.0) 6.1 (1.1–11.1) 1.2 (1.0–1.5) 10.2 (0.4–19.8)
Former drinkers 1.7 (1.5–2.0) 25.1 40.6 14.4 (8.8–19.9) 4.4 (0.6–8.2) 1.4 (1.1–1.6) 9.9 (2.4–14.0)
Underweight 3.0 (2.4–3.7) 7.5 28.7 13.0 (10.1–15.9) 4.0 (2.0–6.0) 1.9 (1.4–2.4) 6.0 (3.0–9.6)
No BCG vaccination 1.4 (1.2–1.7) 25.7 40.9 6.8 (1.5–12.1) 2.1 (–1.6–5.7) 1.3 (1.0–1.7) 7.6 (1.0–14.8)
History of using hormone therapy 1.2 (1.0–1.5) 44.9 44.0 9.9 (1.6–18.1) 3.0 (–2.6–8.7) 1.3 (1.0–1.7) 12.7 (2.3–23.1)
Bulla or emphysema 2.7 (2.2–3.2) 9.6 43.3 13.8 (10.6–17.0) 4.3 (2.1–6.4) 1.5 (1.2–2.0) 4.9 (1.9–8.7)
Born in rural areas 1.9 (1.5–2.4) 84.9 44.7 42.8 (29.6–56.1) 13.2 (7.9–18.5) 1.5 (1.1–2.2) 31.4 (7.1–49.9)
Unemployment 2.3 (2.0–2.7) 27.6 52.9 26.7 (21.8–31.5) 8.2 (4.9–11.6) 1.4 (1.2–1.8) 10.5 (4.1–17.4)
Without WRII 2.5 (2.1–2.9) 45.6 63.4 40.5 (34.4–46.6) 12.5 (8.3–16.7) 2.0 (1.6–2.5) 30.9 (20.2–40.9)
Overall PAF 71.6 (53.7-89.6) 82.8 (63.6-101.9)
BCG: Bacille Calmette-Guérin; CI: Confidence interval; OR: Odds ratio; PAF: Population attributable fraction; PTB: Pulmonary tuberculosis; WRII: Work-Related Injury Insurance.

Discussion

As early as the 1920s and 1930s, the close connection between silicosis and PTB had been confirmed by many epidemiological studies, clinical studies, animal experiments, and autopsy data, although the prevalence of PTB in patients with silicosis varied with the country.[23] Until the second half of the 20th century, silicosis and PTB were effectively controlled in high-income countries, and the incidence declined. In recent 10 years, CWP in the United States, Australia, and other countries has been revived, and the number of cases of silicosis caused by artificial stone has also increased.[24] The prevention and control of pneumoconiosis and its complications have gained renewed attention. The International Labour Organization List of Occupational Diseases still includes silicotuberculosis (silicosis complicated by tuberculosis).[25]

The prevalence of PTB in patients with pneumoconiosis in our study was 7.4%, about half of the value reported in 1986 in China. The remarkable decrease in the prevalence of PTB in this population is closely associated with the continuous reduction in the incidence and prevalence of PTB in the general population due to the great effort of China in the prevention and control of PTB for decades, and also a result of continuously expanding the coverage of WRRI and basic medical insurance.[26]

However, as reported in other developing countries, patients with pneumoconiosis remain a high-risk population for PTB in China. A recent meta-analysis of eight studies of silicosis and tuberculosis published from 1986 to 2013 yielded a pooled RR of 4.01 (95% CI: 2.88–5.58).[27] The risk of PTB in patients with pneumoconiosis in our study was 5.22 times that of subjects under medical surveillance, which was higher than the result of the above meta-analysis, indicating that the burden of PTB in Chinese patients with pneumoconiosis is still heavy. China is a country with a high incidence of both pneumoconiosis and PTB, and the prevention and control of PTB in patients with pneumoconiosis still need to be strengthened.

M. tuberculosis is spread from person to person through airborne droplet nuclei. Once infected, approximately 5%–15% of infected people will develop active PTB during their lifetime. Most infections are subclinical and asymptomatic, with PTB replication contained by the host immunity, a condition called latent PTB infection (LTBI).[28] Social determinants and risk factors that affect not only all aspects of the “exposure-infection-disease-adverse outcome” spectrum but also several aspects of the health of populations, in general, are called the critical underlying determinants of PTB.[29] Our study systematically apply the concept and model of CSDH to analyze PTB's social determinants and risk factors in patients with pneumoconiosis. We also calculated the PAFs of significant risk factors for PTB with pneumoconiosis.

Our study suggested that most of the risk factors for PTB in patients with pneumoconiosis were also the risk factors for PTB in the general population. Smoking index, BMI, personal income, and years of exposure to dust had a good dose-response relationship with infection risk even a after adjusting for confounding factors such as age, sex, and pneumoconiosis type. However, there existed variation regarding the risk factors between patients with pneumoconiosis and the general population; for example, sex and age did not show a significant correlation with PTB, probably because patients with pneumoconiosis were mainly middle-aged or elderly males. Our study also found multiple factors, including no WRII, unemployment, in-hospital or household contact with PTB patients, BCG-unvaccinated complications with pulmonary bullae or emphysema, and a history of hospitalization associated with a higher risk of PTB. Patients with the above risk factors had lower self-rated health scores, which was consistent with the lower self-rated health score among patients with PTB.

In our study, the coverage rate of WRII in the patients with pneumoconiosis living in rural areas was 31.9%, which is consistent with the 30% overall coverage rate for all migrant workers in China.[30] These patients have poor economic status, cannot find other jobs after illness, and have relatively low health conditions; therefore, they may be more susceptible to PTB and progress to active PTB more easily. In 2017, the Chinese government issued a policy to strengthen the medical therapy of pneumoconiosis among migrant workers. Those without WRII can access free medical diagnosis and treatment or be compensated through basic medical insurance for urban and rural residents. A future follow-up study will continue to analyze the effects of related policies.

Patients with a history of hospitalization or who once had contact with patients with PTB in the hospital had a higher prevalence of PTB. These patients may have be infected with PTB before being hospitalized or be infected during hospitalization owing to close contact with PTB patients. It is necessary to continue follow-up of uninfected patients in the study. However, this indicates the possibility and high risk of hospital infection, mainly for patients living in rural areas. Most of these patients typically choose medical treatment in county-level hospitals or township hospitals.[31] Whether the rules for PTB prevention were not strictly followed in these institutions requires scrutiny from hospital management departments. In China, occupational disease hospitals mainly rely on chest X-rays and clinical symptoms of patients to screen for PTB. They lack specialized laboratories and molecular biology examination techniques for PTB. It has been reported that the misdiagnosis rate of PTB in patients with pneumoconiosis was as high as 30%, and delayed diagnosis was also common.[32] This may be why patients hospitalized in county-level or township hospitals had a higher risk of PTB infection.

It is reported that, in China, the incidence of tuberculosis in rural residents was higher than that in urban residents. The incidence was also increased relative to other areas in western and northeastern regions.[33] Therefore, patients with pneumoconiosis born in rural, northeastern, and western regions had a higher probability of exposure to PTB. Clinically, doctors sometimes use hormone drugs to treat pneumoconiosis and pulmonary inflammation. Our study found that patients who once used hormonal drugs had a higher risk of PTB. Whether hormonal medications suppress the patient's immunity and lead to latent PTB recurrence requires further research. Previous studies have found that the latent infection rate of PTB in patients with pneumoconiosis is 65%, which was significantly higher than that in the general population (20%).[34] It is recommended that clinicians evaluate for LTBI and the immune status of the patient before using hormone drugs for pneumoconiosis.

Studies have found a summer peak of PTB incidence in the northern hemisphere.[35] Our study showed that PTB infection had a summer and autumn peak, mainly presenting as an increase in outpatient and inpatient cases who actively sought out doctors. The subjects diagnosed through passively receiving physical examination or household survey did not show a seasonal difference, suggesting that patients are more likely to seek medical attention in summer and fall, and have a higher chance of diagnosis. On the other hand, considering that the preclinical period from infection to development of active PTB may last from a few weeks to several months,[36] it is probable that the peak of noted tuberculosis in patients with pneumoconiosis during the summer and autumnal seasons is the consequence of M. tuberculosis transmission during winter and early spring months, which is also consistent with the high risk of PTB in the western and northeastern regions where winter and early spring are relatively cold, and patients stay in overcrowded and poorly ventilated settings for longer time. In addition, patients with pneumoconiosis generally have poor health in winter and early spring, and choose to be treated in hospital during this time, which increases the chance of tuberculosis infection. Despite this, the seasonal difference in PTB diagnosis in patients with pneumoconiosis needs further follow-up study.

The risk of PTB in smokers showed urban/rural variation, which may be related to the different smoking rates in urban and rural patients. In addition, the prevalence of PTB was lower in current drinkers but higher in former drinkers. Patients with PTB generally abstain from drinking to improve their health, which may partially explain the above result. However, the finding also needs further studies for validation.

We also conducted combinational analysis incorporating multiple factors such as close contact with active PTB patients, being without WRII, smoking, formerly drinking, and being underweight. The result showed that the more risk factors a person had, the higher their risk of PTB. Although the estimated PAF for being underweight was smaller than the PAF of former drinkers and smokers, underweight showed an interaction effect with smokers and former drinkers, and the interaction risk of being underweight with the other two fixed factors was higher than that of former drinkers or smokers with the other two fixed factors. The stratified analysis also showed that the prevalence of PTB was higher when multiple factors were superimposed. These analyses provide valuable clues for screening high-risk populations and focusing on interventions. The weighted PAFs of being born in a rural area and being without WRII were relatively high, at 13.2% (95% CI: 7.9%–18.5%) and 12.5% (95% CI: 8.3%–16.7%), respectively, followed by exposure to PTB in hospital, with a weighted PAF of 11.6% (95% CI: 8.8%–14.3%). The PAFs of the above three factors were significantly higher than the PAFs of other risk factors, and these three risk factors are social structural factors that cannot be altered by patients themselves, and need to be addressed by the efforts of society and the government. This is the guiding ideology of WHO's “End tuberculosis strategy for 2015 to 2035”. It is necessary to design and implement comprehensive strategies to eliminate tuberculosis through universal health coverage and interventions to address the underlying social determinants of tuberculosis.

In summary, this study basically conformed to the social determinant and risk factor models of the “exposure-infection-disease-adverse outcome” spectrum of PTB. We adopted this model and modified it slightly [Figure 3]. The fundamental strategy adopted by WHO is to integrate health into all policies, and this has become the central concept of multiple policies issued by the Chinese government, including the “Healthy China 2030” blueprint, “Healthy China Initiative 2019 to 2030,” “End tuberculosis Plan (2019–2022),” and “Pneumoconiosis Prevention and Control Plan (2021–2025).”[37] Only by improving the health status of vulnerable groups can we fundamentally solve their health problems.

F3
Figure 3:
Framework for proximate risk factors, upstream determinants, and PTB mechanics. BCG: Bacille Calmette-Guérin; BMI: Body-mass index; LTBI: Latent tuberculous infection; PPE: Personal protection equipment; PTB: Pulmonary tuberculosis; SES: Socio-economic status; WRII: Work-Related Injury Insurance.

Since 2015, the Chinese government has included the health management of patients with tuberculosis in the national basic public health service project, and the target populations include those with suspected and diagnosed tuberculosis. However, there are still some high-risk populations that are difficult to cover by current policy, including patients with pneumoconiosis and dust-exposed workers. China has reported 915,000 cumulative cases of pneumoconiosis, and about 450,000 of these patients are still alive.[2] According to the prevalence of 7.5% for PTB, there are 33,750 active PTB cases in patients with pneumoconiosis. Additionally, there are a certain number of individuals who do not meet the stage I criteria of pneumoconiosis by imaging assessment, as well as clinical cases which are not diagnosed as occupational pneumoconiosis. Therefore, there may be a large number of hidden PTB patients who are not diagnosed. In conclusion, given the social and individual risk factors, effective measures should be taken in terms of promotion, prevention, diagnosis, control, treatment, and social security to achieve the preset target of PTB control.

Acknowledgments

The most important acknowledgment is of the participants in the study and the members of the survey teams in each of the 27 regional centers, and the project development and management teams.

Funding

This work was supported by the Advisory Research Project of the Chinese Academy of Engineering in 2019 (No. 2019-XZ-70) and the National Key Research & Development Program of China (No. 2021 YFC2500700).

Conflicts of interest

None.

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Keywords:

Pulmonary tuberculosis; Pneumoconiosis; Social determinants; Risk factors

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