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Zhang M, Wang X, Xiao Y, Wang Q, Huang F, Ren X, Guo X, Sun W, Deng J, Jiang Q, Liu J, Zheng W, Yao H. Trends in tuberculosis mortality among older adults in China, 2004-2021: a Joinpoint regression and age-period-cohort analysis. Front Public Health 2025; 12:1500539. [PMID: 39835304 PMCID: PMC11743160 DOI: 10.3389/fpubh.2024.1500539] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2024] [Accepted: 12/09/2024] [Indexed: 01/22/2025] Open
Abstract
Background Tuberculosis (TB) remains a major public health problem in China and globally, particularly among older adults. This study aimed to examine secular trends in TB mortality among older adults in China and the net effects of age, period, and cohort. Methods Data from the National Disease Surveillance Points (DSPs) system were analyzed using Joinpoint regression to determine annual changes in TB mortality among individuals aged 60 years and older from 2004 to 2021. An age-period-cohort (APC) analysis using the intrinsic estimator (IE) method was conducted to estimate the independent effects of age, period, and cohort. Results The age-standardized TB mortality rate was 5.68 per 100,000, with higher rates observed in men, rural areas, and western regions. TB mortality among older adults declined overall from 2004 to 2021, although the rate of decline has slowed in recent years. The APC analysis revealed increased TB mortality with age, with the relative risk (RR) rising from 0.57 in the 60-64 age group to 1.53 in the 80-84 age group. The period effect decreased from 2007 to 2021, showing a higher risk effect in rural areas (RR = 1.51) than in urban areas (RR = 1.16) during 2007-2011, but this trend reversed in the period 2017-2021. The cohort effect generally declined, with the exception of certain demographic groups that showed an increase in the 1952-1956 and 1957-1961 birth cohorts. Conclusion TB mortality among older adults in China decreased from 2004 to 2021, although the decline has slowed in recent years. Variations in age, period, and cohort effects highlight differences by gender, urban and rural areas, and regions, providing insights for targeted intervention strategies.
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Affiliation(s)
- Mengdi Zhang
- Office of Education and Training (Graduate School), Chinese Center for Disease Control and Prevention, Beijing, China
| | - Xin Wang
- Office of Education and Training (Graduate School), Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yiran Xiao
- Office of Epidemiology (Technical Guidance Office for Patriotic Health Work), Chinese Center for Disease Control and Prevention, Beijing, China
| | - Qiqi Wang
- Office of Epidemiology (Technical Guidance Office for Patriotic Health Work), Chinese Center for Disease Control and Prevention, Beijing, China
| | - Fei Huang
- Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Xiang Ren
- Division of Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Xiaomin Guo
- Center for Logistics Management and Operations, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Wenshan Sun
- Office of Education and Training (Graduate School), Chinese Center for Disease Control and Prevention, Beijing, China
| | - Jinqi Deng
- Office of Education and Training (Graduate School), Chinese Center for Disease Control and Prevention, Beijing, China
| | - Qi Jiang
- Office of Finance, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Jianjun Liu
- Chinese Antituberculosis Association, Beijing, China
| | - Wenjing Zheng
- Office of Epidemiology (Technical Guidance Office for Patriotic Health Work), Chinese Center for Disease Control and Prevention, Beijing, China
| | - Hongyan Yao
- Office of Education and Training (Graduate School), Chinese Center for Disease Control and Prevention, Beijing, China
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Rupani MP, Soundararajan S. Survival analysis shows tuberculosis patients with silicosis experience earlier mortality and need employer-led care models in occupational settings in India. Sci Rep 2024; 14:28891. [PMID: 39572724 PMCID: PMC11582735 DOI: 10.1038/s41598-024-80367-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2024] [Accepted: 11/18/2024] [Indexed: 11/24/2024] Open
Abstract
India's high tuberculosis (TB) burden is exacerbated by concurrent silicosis, which increases TB susceptibility and worsens treatment outcomes. Limited studies on TB patients with silicosis highlight the need to address this vulnerable group's specific challenges, particularly to improve diagnosis and management. This retrospective cohort study analyzed survival data from 137 silico-tuberculosis and 2,605 TB-only patients in Khambhat, India, using Kaplan-Meier curves, log-rank tests, and comparisons between Cox proportional hazards and accelerated failure time (AFT) models. The lognormal AFT model, selected for its lowest Akaike Information Criterion (AIC), estimated survival times based on age, gender, HIV status, and prior TB treatment. Among the 2,742 patients, 309 (11%) died within 27 months. Median time from diagnosis to outcome was shorter for deceased patients (1.7 months) than for censored patients (5.6 months, p < 0.001, median test). Kaplan-Meier analysis showed a significantly steeper survival decline for silico-tuberculosis patients (p < 0.001, log-rank test). Silico-tuberculosis was associated with a two-fold increased mortality risk (HR = 2.0, 95% CI: 1.4-3.0, p < 0.001, Cox-proportional hazards regression). The lognormal AFT model indicated silico-tuberculosis patients had 36% of the median survival time compared to TB-only patients (16 vs. 44 months). These findings highlight significantly earlier mortality in silico-tuberculosis patients, underscoring the need for targeted, employer-led care models and TB-silicosis collaborative screening within India's TB program for high-risk occupational groups.
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Affiliation(s)
- Mihir P Rupani
- Clinical Epidemiology (Division of Health Sciences), ICMR - National Institute of Occupational Health (NIOH), Indian Council of Medical Research (ICMR), Meghaninagar, Ahmedabad, 380016, Gujarat, India.
| | - Soundarya Soundararajan
- Clinical Epidemiology (Division of Health Sciences), ICMR - National Institute of Occupational Health (NIOH), Indian Council of Medical Research (ICMR), Meghaninagar, Ahmedabad, 380016, Gujarat, India.
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Ge R, Zhu G, Tian M, Hou Z, Pan W, Feng H, Liu K, Xiao Q, Chen Z. Analysis on time delay of tuberculosis among adolescents and young adults in Eastern China. Front Public Health 2024; 12:1376404. [PMID: 38651131 PMCID: PMC11033351 DOI: 10.3389/fpubh.2024.1376404] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Accepted: 03/26/2024] [Indexed: 04/25/2024] Open
Abstract
Background Tuberculosis (TB) is recognized as a significant global public health concern. Still, there remains a dearth of comprehensive evaluation regarding the specific indicators and their influencing factors of delay for adolescents and young adults. Methods All notified pulmonary TB (PTB) patients in Jiaxing City were collected between 2005 and 2022 from China's TB Information Management System. Logistic regression models were conducted to ascertain the factors that influenced patient and health system delays for PTB cases, respectively. Furthermore, the impact of the COVID-19 pandemic on local delays has been explored. Results From January 1, 2005 to December 31, 2022, a total of 5,282 PTB cases were notified in Jiaxing City, including 1,678 adolescents and 3,604 young adults. For patient delay, female (AOR: 1.18, 95%CI: 1.05-1.32), PTB complicated with extra-pulmonary TB (AOR: 1.70, 95% CI: 1.28-2.26), passive case finding (AOR: 1.46, 95% CI: 1.07-1.98) and retreatment (AOR: 1.52, 95% CI: 1.11-2.09) showed a higher risk of delay. For health system delay, minorities (AOR: 0.69, 95% CI: 0.53-0.90) and non-students (AOR: 0.83, 95% CI: 0.71-0.98) experienced a lower delay. Referral (AOR: 1.46, 95% CI: 1.29-1.65) had a higher health system delay compared with clinical consultation. Furthermore, county hospitals (AOR: 1.47, 95% CI: 1.32-1.65) and etiological positive results (AOR: 1.46, 95% CI: 1.30-1.63) were associated with comparatively high odds of patient delay. Contrarily, county hospitals (AOR: 0.88, 95% CI: 0.78-1.00) and etiological positive results (AOR: 0.67, 95% CI: 0.59-0.74) experienced a lower health system delay. Besides, the median of patient delay, health system delay, and total delay during the COVID-19 pandemic were significantly lower than that before. Conclusion In general, there has been a noteworthy decline in the notification rate of PTB among adolescents and young adults in Jiaxing City while the declining trend was not obvious in patient delay, health system delay, and total delay, respectively. It also found factors such as gender, case-finding method, and the hospital level might influence the times of seeking health care and diagnosis in health agencies. These findings will provide valuable insights for refining preventive and treatment strategies for TB among adolescents and young adults.
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Affiliation(s)
- Rui Ge
- Jiaxing Center for Disease Control and Prevention, Jiaxing, Zhejiang, China
| | - Guoying Zhu
- Jiaxing Center for Disease Control and Prevention, Jiaxing, Zhejiang, China
| | - Min Tian
- Nanhu Center for Disease Control and Prevention, Jiaxing, Zhejiang, China
| | - Zhigang Hou
- Jiaxing Center for Disease Control and Prevention, Jiaxing, Zhejiang, China
| | - Weizhe Pan
- Jiaxing Center for Disease Control and Prevention, Jiaxing, Zhejiang, China
| | - Hao Feng
- Jiaxing Center for Disease Control and Prevention, Jiaxing, Zhejiang, China
| | - Kui Liu
- Department of Tuberculosis Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, China
| | - Qinfeng Xiao
- The First Hospital of Jiaxing, Jiaxing, Zhejiang, China
| | - Zhongwen Chen
- Jiaxing Center for Disease Control and Prevention, Jiaxing, Zhejiang, China
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Suhairi MH, Mohamad M, Isa MR, Mohd Yusoff MAS, Ismail N. Risk factors for tuberculosis-related death among adults with drug-sensitive pulmonary tuberculosis in Selangor, Malaysia from 2013 to 2019: a retrospective cohort study using surveillance data. BMJ Open 2024; 14:e080144. [PMID: 38413152 PMCID: PMC10900436 DOI: 10.1136/bmjopen-2023-080144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Accepted: 01/04/2024] [Indexed: 02/29/2024] Open
Abstract
OBJECTIVES Due to the paucity of literature on risk factors for tuberculosis (TB)-related death, we determine the sociodemographic and clinical risk factors associated with TB-related deaths among adult pulmonary TB (PTB) patients on treatment in Selangor, Malaysia. DESIGN Retrospective cohort study. SETTING Routinely collected primary care data from all government TB clinics in Selangor. PARTICIPANTS Data of 24 570 eligible adult PTB patients from 2013 to 2019 were obtained from Selangor's State Health Department surveillance records. We included PTB patients aged at least 15 years old at the time of diagnosis with complete documentation of the dates of diagnosis, treatment initiation, end of treatment/follow-up and treatment outcomes. We excluded patients whose diagnoses were changed to non-TB, post-mortem TB diagnosis and multidrug-resistant TB (MDR-TB) patients. PRIMARY AND SECONDARY OUTCOME MEASURES TB-related death, determined from the recorded physicians' consensus during the TB mortality meeting. RESULTS TB-related death was significantly associated with far (adjusted HR (aHR) 9.98, 95% CI 4.28 to 23.28) and moderately advanced (aHR 3.23, 95% CI 1.43 to 7.31) radiological findings at diagnosis; concurrent TB meningitis (aHR 7.67, 95% CI 4.53 to 12.98) and miliary TB (aHR 6.32, 95% CI 4.10 to 9.74) involvement; HIV positive at diagnosis (aHR 2.81, 95% CI 2.21 to 3.57); Hulu Selangor (aHR 1.95, 95% CI 1.29 to 2.93), Klang (aHR 1.53, 95% CI 1.18 to 1.98) and Hulu Langat (aHR 1.31, 95% CI 1.03 to 1.68) residing districts; no formal education (aHR 1.70, 95% CI 1.23 to 2.35); unemployment (aHR 1.54, 95% CI 1.29 to 1.84), positive sputum smear acid-fast bacilli (AFB) at diagnosis (aHR 1.51, 95% CI 1.22 to 1.85); rural residency (aHR 1.39, 95% CI 1.13 to 1.72) and advancing age (aHR 1.03, 95% CI 1.02 to 1.03). CONCLUSIONS Far and moderately advanced radiological findings, concurrent TB meningitis and miliary TB involvement, HIV positive, Hulu Selangor, Klang and Hulu Langat residing districts, no formal education, unemployment, positive sputum smear AFB, rural residency and advancing age are risk factors of TB-related death. Our findings should assist in identifying high-risk patients requiring interventions against TB-related death.
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Affiliation(s)
- Mohammad Haikal Suhairi
- Department of Public Health Medicine, Universiti Teknologi MARA, Sungai Buloh, Malaysia
- Bahagian Pengurusan Latihan Kementerian Kesihatan Malaysia, Putrajaya, Malaysia
| | - Mariam Mohamad
- Department of Public Health Medicine, Universiti Teknologi MARA, Sungai Buloh, Malaysia
| | - Mohamad Rodi Isa
- Department of Public Health Medicine, Universiti Teknologi MARA, Sungai Buloh, Malaysia
| | | | - Nurhuda Ismail
- Department of Public Health Medicine, Universiti Teknologi MARA, Sungai Buloh, Malaysia
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Liu K, Ge R, Luo D, Zheng Y, Shen Z, Chen B, Feng W, Wu Q. Delay analysis of pulmonary tuberculosis in the eastern coastal county of China from 2010 to 2021: evidence from two surveillance systems. Front Public Health 2023; 11:1233637. [PMID: 37637823 PMCID: PMC10450766 DOI: 10.3389/fpubh.2023.1233637] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Accepted: 07/31/2023] [Indexed: 08/29/2023] Open
Abstract
Background Tuberculosis (TB) remains a major public health challenge. However, indicators of delays in assessing effective TB prevention and control and its influencing factors have not been investigated in the eastern coastal county of China. Methods All notified pulmonary tuberculosis (PTB) cases in the Fenghua District, China were collected between 2010 and 2021 from the available TB information management system. Comparison of delays involving patient, health system, and total delays among local and migrant cases. Additionally, in correlation with available Basic Public Health Service Project system, we performed univariate and multivariate logistic regression analyses identified the influencing factors associated with patient and total delays in patients aged >60 years. Results In total, 3,442 PTB cases were notified, including 1,725 local and 1,717 migrant patients, with a male-to-female ratio of 2.13:1. Median patient and total delays of local TB patients were longer than those for migrant patients; the median health system delay did not show any significant difference. For patient delay among the older adult, female (cOR: 1.93, 95% CI: 1.07-3.48), educational level of elementary school and middle school (cOR: 0.23, 95% CI: 0.06-0.84) had a statistical difference from univariable analysis; however, patients without diabetes showed a higher delay for multiple-factor analysis (aOR: 2.12, 95% CI: 1.02-4.41). Furthermore, only the education level of elementary school and middle school presented a low total delay for both univariate (cOR: 0.22, 95% CI: 0.06-0.82) and multivariate analysis (aOR: 0.21, 95% CI: 0.05-0.83) in the older patients. Conclusion The delay of TB cases among migrants was lower than the local population in the Fenghua District, which may be related to the "healthy migrant effect". It highlights that women, illiterate people, and people without diabetes are key groups for reducing delays among older adults. Health awareness should focus on these target populations, providing accessible health services, and reducing the time from symptom onset to diagnosis.
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Affiliation(s)
- Kui Liu
- Department of Tuberculosis Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, China
| | - Rui Ge
- Department of Tuberculosis Control and Prevention, Jiaxing Center for Disease Control and Prevention, Jiaxing, Zhejiang, China
| | - Dan Luo
- Department of Public Health, Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Yan Zheng
- Fenghua Center for Disease Control and Prevention, Ningbo, Zhejiang, China
| | - Zhenye Shen
- Fenghua Center for Disease Control and Prevention, Ningbo, Zhejiang, China
| | - Bin Chen
- Department of Tuberculosis Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, China
| | - Wei Feng
- Fenghua Center for Disease Control and Prevention, Ningbo, Zhejiang, China
| | - Qionghai Wu
- Taizhou Central Hospital (Taizhou University Hospital), Taizhou, Zhejiang, China
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Liu K, Zhang M, Luo D, Zheng Y, Shen Z, Chen B, Jiang J. Influencing Factors of Treatment Outcomes Among Patients with Pulmonary Tuberculosis: A Structural Equation Model Approach. Psychol Res Behav Manag 2023; 16:2989-2999. [PMID: 37559781 PMCID: PMC10408682 DOI: 10.2147/prbm.s419906] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Accepted: 07/09/2023] [Indexed: 08/11/2023] Open
Abstract
BACKGROUND Pulmonary tuberculosis (PTB) is a serious infectious disease, and the factors and pathways that influence final treatment outcomes are unclear. Here, we aimed to assess the factors that influence treatment outcomes in patients with PTB using a structural equation model. METHODS Participants completed a questionnaire covering demographics, understanding of PTB, psychological status, and history of medical treatment. Exploratory factor analysis and reliability testing were performed, and a structural equation model was constructed using the SPSS and Amos software. RESULTS A total of 251 participants were enrolled. Symptoms of depression were observed in 94.4% of participants, whereas 6% showed mild or greater anxiety. Through factor rotation, four common factors were extracted with a total variation of 66.15%. The structural equation model indicated that regular tuberculosis-related follow-up behaviour had a direct and positive effect on the final treatment outcome, with a path coefficient value of 0.20; the level of PTB understanding had a direct positive effect on the testing behaviour for PTB, with a path coefficient of 0.26; patients' psychological characteristics had a direct negative impact on regular testing behaviour, with a path coefficient of -0.13. The psychological characteristics and level of disease understanding of patients exerted indirect effects on the treatment outcome by affecting the way patients approached tuberculosis detection behaviour. CONCLUSION Interventions aimed at improving the treatment outcomes of patients with PTB should mainly focus on financial support and improvements in psychological status in addition to a greater understanding and knowledge of PTB. Furthermore, patients should be encouraged to undergo regular PTB testing during the follow up period, as this mediates the effect of other factors on treatment outcomes and also helps in achieving favourable treatment outcomes.
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Affiliation(s)
- Kui Liu
- Department of Tuberculosis Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang Province, People’s Republic of China
| | - Mengdie Zhang
- Department of Social Medicine of School of Public Health, Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, People’s Republic of China
| | - Dan Luo
- Department of Public Health, Hangzhou Medical College, Hangzhou, Zhejiang Province, People’s Republic of China
| | - Yan Zheng
- Department of Tuberculosis Control and Prevention, Fenghua Center for Disease Control and Prevention, Ningbo, Zhejiang Province, People’s Republic of China
| | - Zhenye Shen
- Department of Tuberculosis Control and Prevention, Fenghua Center for Disease Control and Prevention, Ningbo, Zhejiang Province, People’s Republic of China
| | - Bin Chen
- Department of Tuberculosis Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang Province, People’s Republic of China
| | - Jianmin Jiang
- Department of Tuberculosis Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang Province, People’s Republic of China
- Key Laboratory of Vaccine, Prevention and Control of Infectious Disease of Zhejiang Province, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang Province, People’s Republic of China
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Li D, Tang SY, Lei S, Xie HB, Li LQ. A nomogram for predicting mortality of patients initially diagnosed with primary pulmonary tuberculosis in Hunan province, China: a retrospective study. Front Cell Infect Microbiol 2023; 13:1179369. [PMID: 37333854 PMCID: PMC10272565 DOI: 10.3389/fcimb.2023.1179369] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Accepted: 05/05/2023] [Indexed: 06/20/2023] Open
Abstract
Objective According to the Global Tuberculosis Report for three consecutive years, tuberculosis (TB) is the second leading infectious killer. Primary pulmonary tuberculosis (PTB) leads to the highest mortality among TB diseases. Regretfully, no previous studies targeted the PTB of a specific type or in a specific course, so models established in previous studies cannot be accurately feasible for clinical treatments. This study aimed to construct a nomogram prognostic model to quickly recognize death-related risk factors in patients initially diagnosed with PTB to intervene and treat high-risk patients as early as possible in the clinic to reduce mortality. Methods We retrospectively analyzed the clinical data of 1,809 in-hospital patients initially diagnosed with primary PTB at Hunan Chest Hospital from January 1, 2019, to December 31, 2019. Binary logistic regression analysis was used to identify the risk factors. A nomogram prognostic model for mortality prediction was constructed using R software and was validated using a validation set. Results Univariate and multivariate logistic regression analyses revealed that drinking, hepatitis B virus (HBV), body mass index (BMI), age, albumin (ALB), and hemoglobin (Hb) were six independent predictors of death in in-hospital patients initially diagnosed with primary PTB. Based on these predictors, a nomogram prognostic model was established with high prediction accuracy, of which the area under the curve (AUC) was 0.881 (95% confidence interval [Cl]: 0.777-0.847), the sensitivity was 84.7%, and the specificity was 77.7%.Internal and external validations confirmed that the constructed model fit the real situation well. Conclusion The constructed nomogram prognostic model can recognize risk factors and accurately predict the mortality of patients initially diagnosed with primary PTB. This is expected to guide early clinical intervention and treatment for high-risk patients.
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Affiliation(s)
- Dan Li
- Xiangya School of Nursing, Central South University, Changsha, Hunan, China
- College of Applied Technology, Hunan Open University, Changsha, Hunan, China
| | - Si-Yuan Tang
- Xiangya School of Nursing, Central South University, Changsha, Hunan, China
| | - Sheng Lei
- Interventional Radiology Center, Hunan Chest Hospital, Changsha, Hunan, China
| | - He-Bin Xie
- Department of Drug Clinical Trial Institutions, The Affiliated Changsha Central Hospital, Hengyang Medical School, University of South China, Changsha, Hunan, China
| | - Lin-Qi Li
- School of Public Health, University of South China, Hengyang, China
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