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Background Considering the high morbidity and mortality of lung cancer and the high incidence of pulmonary nodules, clearly distinguishing benign from malignant lung nodules at an early stage is of great significance. However, determining the kind of lung nodule which is more prone to lung cancer remains a problem worldwide. Methods A total of 480 patients with pulmonary nodule data were collected from Shandong, China. We assessed the clinical characteristics and computed tomography (CT) imaging features among pulmonary nodules in patients who had undergone video‐assisted thoracoscopic surgery (VATS) lobectomy from 2013 to 2018. Preliminary selection of features was based on a statistical analysis using SPSS. We used WEKA to assess the machine learning models using its multiple algorithms and selected the best decision tree model using its optimization algorithm. Results The combination of decision tree and logistics regression optimized the decision tree without affecting its AUC. The decision tree structure showed that lobulation was the most important feature, followed by spiculation, vessel convergence sign, nodule type, satellite nodule, nodule size and age of patient. Conclusions Our study shows that decision tree analyses can be applied to screen individuals for early lung cancer with CT. Our decision tree provides a new way to help clinicians establish a logical diagnosis by a stepwise progression method, but still needs to be validated for prospective trials in a larger patient population., Considering the high morbidity and mortality of lung cancer and the high incidence of pulmonary nodules, it is of great significance to clearly distinguish between benign and malignant lung nodules at early stages. However, what kind of lung nodules are more prone to lung cancer is still a worldwide problem. In this study, 458 cases with pulmonary nodules data were collected from Shandong, China. We assessed the clinical characteristics and low‐dose computed tomography (LDCT) imaging features among pulmonary nodules in patients who had undergone video‐assisted thoracoscopic surgery (VATS) lobectomy from 2013 to 2018 to determine the machine learning models using multiple algorithms and select the best decision tree model. Our study shows that decision tree analyses can be applied to screen individuals for early lung cancer with CT. Our decision tree provides a new way to help clinicians establish a logical diagnosis by a stepwise progression method, but still needs to be validated for prospective trials in a larger patient population.

Background With an aging population, China is facing a huge burden of elderly patients with drug resistant tuberculosis (DR-TB), which has become a significant obstacle for the global TB control. There is still little study on DR-TB in the elderly in China so far. Thus, more research on the epidemiological characteristics and trend of primary DR-TB among the elderly will be necessary. Methods A retrospective study was conducted in Shandong, China from 2004 to 2019. We collected 12,661 primary TB cases, of which 4368 elderly (≥60 years) primary TB cases were involved. Clinical characteristics including age, sex, cavity, smoking, drinking, comorbidity and drug susceptibility data were collected from 36 TB prevention and control institutions of Shandong Province. Sputum samples were collected by each surveillance site, and examined in the TB Reference Laboratory of SPCH. Descriptive statistical analysis, chi-square and linear regression were used for analyzing. Results Among 4368 elderly patients with primary TB, the DR-TB and multi-resistant tuberculosis (MDR-TB) accounted for 17.19% and 2.29%, respectively. During 2004-2019, the proportions of MDR-TB, polydrug resistant tuberculosis (PDR-TB), rifampin (RFP)-resistance increased by 160.00%, 18.18%, 231.82%, respectively and the rate of DR-TB among elderly patients with primary cavitary TB increased by 255%. Among the elderly with primary DR-TB during 2004-2019, the proportion of male (from 85.19 to 89.06), cavity (from 7.41 to 46.88), RFP-resistance (from 3.70 to 21.88), and streptomycin (SM)-resistance (from 37.04 to 62.5) increased significantly (P

Background Tuberculosis (TB) is one of the major infectious diseases that seriously endanger people’s health. In Shandong province, the relationship between the level of economic development and TB incidence has not been studied. This study aims to provide more research basis for the government to prevent and control TB by exploring the impact of different economic factors on TB incidence. Methods By constructing threshold regression model (TRM), we described the extent to which different economic factors contribute to TB registered incidence and differences in TB registered incidence among seventeen cities with different levels of economic development in Shandong province, China, during 2006–2017. Data were retrieved from the China Information System for Disease Control and Prevention. Results Per capita medical expenditure (regression coefficient, -0.0314462; SD, 0.0079305; P > |t|, 0.000) and per capita savings (regression coefficient, 0.0001924; SD, 0.0000566; P > |t|, 0.001) passed the significance test at the level of 1%.They are the two economic indicators that have the greatest impact on TB registered incidence. Through the threshold test, we selected the per capita savings as the threshold variable. In the three stages of per capita savings (33,835.5391 CNY), rural per capita income always has a significant negative impact on the TB registered incidence (The regression coefficients are − 0.0015682, − 0.0028132 and − 0.0022253 respectively. P is 0.007,0.000 and 0.000 respectively.).In cities with good economies, TB registered incidence was 38.30% in 2006 and dropped to 25.10% by 2017. In cities with moderate economies, TB registered incidence peaked in 2008 at 43.10% and dropped to 27.1% by 2017.In poorer cities, TB registered incidence peaked in 2008 at 56.30% and dropped to 28.9% in 2017. Conclusion We found that per capita savings and per capita medical expenditure are most closely related to the TB incidence. Therefore, relevant departments should formulate a more complete medical system and medical insurance policy to effectively solve the problem of “difficult and expensive medical treatment”. In order to further reduce the TB incidence, in addition to timely and accurate diagnosis and treatment, it is more important for governments to increase investment in medicine and health care.

Background Given the high burden of tuberculosis (TB) and diabetes mellitus (DM) in China and the worse outcome of TB-DM cases (refers to TB patients with diabetes), and drug-resistant tuberculosis cases (DR-TB), it is of great significance to explore the association between diabetes and primary DR-TB for TB elimination target in China. We assessed the clinical characteristics, drug-resistance profile, and increased risk of resistance among TB-DM patients across China from 2004 to 2017. Method 7223 cases with drug-susceptibility data were collected from Shandong, China. Categorical baseline characteristics of new TB cases were compared by DM status using Fisher's exact or Pearson Chi-square test. Univariable analysis and multivariable logistic models were used to estimate the association between diabetes and different drug-resistance profiles and the risk factors of primary drug resistance among TB-DM cases. Result Of 7223 newly diagnosed TB patients, 426 (5.90%) were TB-DM cases. TB-DM csaes were more likely to be older，accompanied by higher body mass index (BMI) and hypertension than TB-no DM cases (refers to TB patients without diabetes). The rates of DR-TB (21.83% vs 16.96%), polydrug resistant TB (PDR-TB, 6.10% vs 3.80%), isoniazid (INH)+streptomycin (SM)-resistant TB (4.93% vs 3.13%), and SM-resistant TB (16.20% vs 11.7%) among TB-DM group were higher than TB-no DM group, P

To determine the association between daily air pollution and the hospital admissions for respiratory diseases in children aged from 0 to 17 years in Jinan, China. Generalized linear models were used to explore the acute effects of ambient fine particulate matter (PM2.5) on the children's hospital admissions for respiratory diseases. We evaluated the lag associations (including lag 0 to lag 3, lag 01, and lag 03) between daily PM2.5 and the number of children's hospital admissions for respiratory diseases, and stratified by gender, age group (baby group: age 0-1 years; child group: age 1-5 years; student group: age 6-17 years), and cause-specific disease (including upper infection, pneumonia, and acute bronchitis) during 2011-2015. PM2.5 had significant positive impacts on the number of children's hospital admissions for respiratory disease. The results showed that per 10 μg/m3 increase of PM2.5 at lag 1 was associated with an increase in total and male hospital admissions of 0.23% (95% CI, 0.02%-0.45%) and 0.32% (95% CI, 0.04%-0.06%). The corresponding risk of the student group (age 6-17 years) hospital admissions was increased 0.90% (95% CI, 0.39%-1.42%) at lag 1 day. The corresponding risk of the upper infection was increased 0.96% (95% CI, 0.37-1.55%) at lag 1 day. Males and student groups (age 6-17 years) were more vulnerable to PM2.5 exposure. Upper infection admission was identified as the sensitive disease for children. It is a better way to reduce children's outdoor activities to avoid health effects when the air pollution increases.

ObjectivesTo investigate the independent and collective impact of alcohol drinking and tobacco smoking on the drug-resistance of newly diagnosed tuberculosis (TB).DesignThis was a retrospective cohort study.SettingShandong, China.ParticipantsPatients with newly diagnosed TB from 1 January 2004 to 31 December 2020 were collected. Exclusive criteria: retreated cases; extrapulmonary tuberculosis; without information on drug susceptibility testing results, smoking or drinking habits; bacteriological identification as non-tuberculous mycobacteria.Primary and secondary outcome measuresPatients were classified into four groups including smokers only (G1), drinker only (G2), smoker +drinker (G3), non-smoker +non-drinker group (G0). We described the drug-resistant profiles, clinical factors and calculated the ORs of different drug-resistance among G1, G2, G3, compared with G0 through univariate and multivariate logistics regression models.ResultsOf the 7996 TB cases enrolled, the proportions of G1, G2, G3 and G0 were 8.25%, 3.89%, 16.46% and 71.40%, respectively. The rates of drug-resistant (DR)-TB, mono-resistant TB, multidrug resistant (MDR)-TB, polydrug resistant TB in G1, G2, G3 and G0 were 19.24%/16.4%/17.33%/19.08%, 11.52%/8.68%/10.94%/11.63%, 3.03%/2.57%/2.96%/3.66% and 4.70%/4.82%/3.34%/ 4.08%, respectively. G3 had a higher risk of MDR1: isoniazid +rifampin (adjusted OR (aOR)=1.91, 95% CI: 1.036 to 3.532), but had a lower risk of DR-TB (aOR=0.84, 95% CI: 0.71 to 0.99), rifampin-related resistance (aOR=0.68, 95% CI: 0.49 to 0.93), streptomycin-related resistance (aOR=0.82, 95% CI: 0.68 to 0.99), ethambutol-related resistance (aOR=0.57, 95% CI: 0.34 to 0.95), MDR3: isoniazid +rifampin+streptomycin (aOR=0.41, 95% CI: 0.19 to 0.85), any isoniazid +streptomycin resistance (aOR=0.85, 95% CI: 0.71 to 1.00). However, there were no significant differences between G1 and G0, G2 and G0 in all drug-resistant subtypes. Those patients with cavity had a higher risk of DR-TB among G3 (OR=1.35, 95% CI: 1.01 to 1.81).ConclusionAlthough we did not found an independent impact of alcohol drinking or tobacco smoking on TB drug-resistance, respectively, these two habits had a combined effect on TB drug-resistance.

Background: Finding out more predictors of drug-resistant tuberculosis (DR-TB) helps to facilitate TB prevention and control. Previous study had revealed that tobacco smoking and alcohol drinking might be a risk factor for developing drug-resistant tuberculosis. However, few discussed their joint impact on resistance among newly diagnosed TB cases. This study aimed to assess and compare the joint and independent effect of smoking and drinking on TB resistance.Methods: This was a retrospective study of 7996 newly diagnosed TB patients who were collected from Shandong, China from Jan 1, 2004, to Dec 31, 2020, and all had drug susceptibility results, information about smoking and alcohol consumption. Patients were classified into four groups including smoker only(G1), drinker only(G2), smoker+drinker(G3), non-smoker+non-drinker group(G0). We described the drug-resistant profiles, clinical factors and also calculated the ORs of different drug-resistance among G1, G2, G3, compared to G0.Results:Of 7996 TB cases enrolled, the proportions of G1, G2, G3, and G0 were 8.25%, 3.89%, 16.46%, 71.40%, respectively. The rates of DR-TB, mono-resistant (MR)-TB, multidrug resistant (MDR)-TB, polydrug resistant (PDR)-TB in G1, G2, G3 and G0 were 19.24%/16.4%/17.33%/19.08%, 11.52%/8.68%/10.94%/11.63%, 3.03%/2.57%/2.96%/3.66%, 4.7%/4.82%/3.34%/4.08%, respectively. G3 had a higher risk of MDR1: isoniazid+rifampin (adjusted odds ratio (aOR)=1.913, 95% confidence interval(CI): 1.036-3.532), but had a lower risk of DR-TB (aOR=0.839, 95%CI: 0.712-0.988), rifampin-related resistance (aOR=0.675, 95%CI: 0.492-0.925), streptomycin-related resistance (aOR=0.819, 95%CI: 0.675-0.993), EMB-related resistance (aOR=0.571, 95%CI: 0.342-0.954), MDR3: isoniazid+rifampin+streptomycin (aOR=0.406, 95%CI: 0.194-0.851, any isoniazid+streptomycin resistance (aOR=0.845, 95%CI: 0.714-1). However, there were no significant differences between G1 and G0, G2 and G0 in all drug-resistant sub-types. Those who with cavity had a higher risk of DR-TB among G3 (OR=1.354, 95%CI:1.011-1.814).Conclusions: Although we did not found a independent impact of alcohol drinking or tobacco smoking on TB drug-resistance respectively, these two habits had a joint effect on TB drug-resistance. We should be alert for the emergence of isoniazid+rifampin resistance among populations with both smoking and drinking habits.

Background To explore population aging and the epidemic trend of pulmonary tuberculosis (PTB) in the elderly, and provide a basis for the prevention and control of pulmonary tuberculosis among the elderly. Methods We collected clinical information of 239,707 newly active PTB patients in Shandong Province from 2005 to 2017. We analyzed and compared the clinical characteristics, reported incidence and temporal trend of PTB among the elderly group (≥60 years) and the non-elderly group ( Results Among the total PTB cases, 77,192(32.2%) were elderly. Compared with non-elderly patients, newly active elderly PTB patients account for a greater proportion of male cases (OR 1.688, 95% CI 1.656–1.722), rural population cases (OR 3.411, 95% CI 3.320–3.505) and bacteriologically confirmed PTB cases (OR 1.213, 95%CI 1.193–1.234). The annual reported incidence of total, elderly, pulmonary bacteriologically confirmed cases were 35.21, 68.84, 35.63 (per 100,000), respectively. The annual reported incidence of PTB in the whole population, the elderly group and the non-elderly group has shown a slow downward trend since 2008. The joinpoint regression model showed that the overall reported incidence of PTB in the elderly significantly decreased from 2007 to 2017 (APC = -5.3, P P P P = 0.1). The reported incidence of clinically diagnosed PTB among elderly patients from 2005 to 2017 (11.48–38.42/100,000) increased by about 235%. It rose significantly from 2007 to 2014 (APC = 9.4, P Conclusions Compared with the non-elderly population, the reported incidence of PTB in the elderly population is higher. The main burden of PTB will shift to the elderly, men, rural population, and clinically diagnosed patients. With the intensification of aging, more researches on elderly PTB prevention and treatment will facilitate the realization of the global tuberculosis (TB) control targets.

Background Drug-resistant tuberculosis (DR-TB), diabetes and exposure to air pollution are thought to be important threat to human health, but no studies have explored the effects of ambient air pollutants on DR-TB when adjusting diabetes status so far. Methods We performed a study among 3759 newly diagnosed TB cases with drug-susceptibility testing results, diabetes status, and individual air pollution data in Shandong from 2015 to 2019. Generalized linear mixed models (GLMM) including three models (Model 1: without covariates, Model 2: adjusted by diabetes status only, Model 3: with all covariates) were applied. Results Of 3759 TB patients enrolled, 716 (19.05%) were DR-TB, and 333 (8.86%) had diabetes. High exposure to O3 was associated with an increased risk of RFP-resistance (Model 2 or 3: odds ratio (OR) = 1.008, 95% confidence intervals (CI): 1.002–1.014), ethambutol-resistance (Model 3: OR = 1.015, 95%CI: 1.004–1.027) and any rifampicin+streptomycin resistance (Model 1,2,3: OR = 1.01, 95%CI: 1.002–1.018) at 90 days. In contrast, NO2 was associated with a reduced risk of DR-TB (Model 3: OR = 0.99, 95%CI: 0.981–0.999) and multidrug-resistant TB (MDR-TB) (Model 3: OR = 0.977, 95%CI: 0.96–0.994) at 360 days. Additionally, SO2 (Model 1, 2, 3: OR = 0.987, 95%CI: 0.977–0.998) showed a protective effect on MDR-TB at 90 days. PM2.5 (90 days, Model 2: OR = 0.991, 95%CI: 0.983–0.999), PM10 (360 days, Model 2: OR = 0.992, 95%CI: 0.985–0.999) had protective effects on any RFP+SM resistance. Conclusions O3 contributed to an elevated risk of TB resistance but PM2.5, PM10, SO2, NO2 showed an inverse effect. Air pollutants may affect the development of drug resistance among TB cases by adjusting the status of diabetes.

Background: With an aging population, China is facing a huge buedern of elderly patients with drug resistant tuberculosisi (DR-TB), which has become an significant obscale for the global TB control targets. There is still few study on DR-TB among China so far.Thus, more researches on the epidemiological characteristics and trend of primary DR-TB among the elderly will be necessary. Methods: A retrospective study was conducted in Shandong, China from 2004-2019, 12661 primary TB and 4368 elderly (≥60 years of age) primary TB cases were involved. Clinical characteristics including age, sex, Cavity, Smoking, drinking, comorbidity and drug susceptibility data were included. Descriptive statistical analysis, Chi-square and linear regression were used for analyzing.Results: Among 4368 elderly patients with primary TB, the DR-TB and MDR-TB accounted for 17.19% and 2.29% respectively. During 2004 to 2019, the proportions of MDR-TB, PDR-TB, RFP-resistance increased by160.00%, 18.18%, 231.82%, and the rate of DR-TB among elderly patients with primary cavitary TB increased by 255%.Among the elderly with primary DR-TB, the proportion of male (from 85.19 to 89.06), cavity (from 7.41 to 46.88), RFP (from 3.70 to 21.88), SM (from 37.04 to 62.5) increased significantly(PConclusion: Among the elderly, the proportions of MDR-TB, PDR-TB,RFP-resistance and cavitary DR-TB increased significantly. The pattern of DR-TB changed from female, non-cavity and INH-resistant groups to male, cavity and RFP, SM-resistant groups. In order to a better control on the elderly DR-TB in the future, we should pay more attention to, male, smoking, drinking, COPD and diabetes subgroups.

ObjectiveThis study was designed to identify the risk factors for drug-resistant tuberculosis (DR-TB) and the association between comorbidity and drug resistance among retreated pulmonary tuberculosis (PTB).DesignA retrospective study was conducted among all the 36 monitoring sites in Shandong, China, over a 16-year period. Baseline characteristics were collected from the TB Surveillance System. Categorical variables were compared by Fisher’s exact or Pearson’s χ2 test. The risk factors for drug resistance were identified using univariable analysis and multivariable logistic models. The influence of comorbidity on different types of drug resistance was evaluated by performing multivariable logistic models with the covariates adjusted by age, sex, body mass index, drinking/smoking history and cavity.ResultsA total of 10 975 patients with PTB were recorded during 2004–2019, and of these 1924 retreated PTB were finally included. Among retreated PTB, 26.2% were DR-TB and 12.5% had comorbidity. Smoking (adjusted OR (aOR): 1.69, 95% CI 1.19 to 2.39), cavity (aOR: 1.55, 95% CI 1.22 to 1.97) and comorbidity (aOR: 1.44, 95% CI 1.02 to 2.02) were risk factors for DR-TB. Of 504 DR-TB, 9.5% had diabetes mellitus, followed by hypertension (2.0%) and chronic obstructive pulmonary disease (1.8%). Patients with retreated PTB with comorbidity were more likely to be older, have more bad habits (smoking, alcohol abuse) and have clinical symptoms (expectoration, haemoptysis, weight loss). Comorbidity was significantly associated with DR-TB (aOR: 1.44, 95% CI 1.02 to 2.02), overall rifampin resistance (aOR: 2.17, 95% CI 1.41 to 3.36), overall streptomycin resistance (aOR: 1.51, 95% CI 1.00 to 2.27) and multidrug resistance (aOR: 1.96, 95% CI 1.17 to 3.27) compared with pan-susceptible patients (pConclusionSmoking, cavity and comorbidity lead to an increased risk of drug resistance among retreated PTB. Strategies to improve the host’s health, including smoking cessation, screening and treatment of comorbidity, might contribute to the control of tuberculosis, especially DR-TB, in China.

Background Primary drug-resistant tuberculosis (DR-TB) has contributed to a significant health and economic burden on a global scale, especially in China. we sought to estimate epidemiological characteristics of primary DR-TB in China from 2004 to 2018. Methods Eleven thousand four hundred sixty-seven newly diagnosed and 1981 retreated TB cases with drug susceptibility data were included. Chi-Square test for trends, linear regression, a joinpoint regression model and temporal trend in proportions of the different resistance patterns were carried out. Results The proportion of primary DR-TB and mono-resistant TB (MR-TB) in China had reduced by more than 12% since 2004, and were 21.38%, 13.35% in 2018 respectively. Among primary DR-TB cases (2173,18.95%), the percentage of multiresistant TB (MDR-TB, from 5.41 to 17.46%), male (from 77.03 to 84.13%), cavity (from 13.51 to 43.92%), rifampicin(RFP)-resistant TB (from 8.11 to 26.98%), streptomycin(SM)-resistant TB (from 50.00 to 71.43%) increased significantly (P P Conclusion The total rate of drug resistance among new TB cases showed a downward trend in Shandong, China, from 2004 to 2018. Primary drug resistance patterns were shifting from female, non-cavity, INH-resistant TB, and MR-TB groups to male, cavity, RFP/SM-resistant TB, and MDR-TB groups. Considering the rising drug resistance rate among some special population, future control of primary DR-TB in China may require an increased focus on female, cavity, smoking, drinking, or 15 to 44 year-old TB subgroups.

Although the association between diabetes mellitus (DM) and tuberculosis (TB) has been well-documented for centuries, evidence of the link between diabetes and drug resistance among previously treated TB patients remains limited and inconsistent.An observational study was performed that involved 1791 retreated TB-no DM patients (refers to TB cases without diabetes) and 93 retreated TB-DM patients (refers to TB cases with diabetes) in Shandong, China from 2004 to 2017. Baseline data including demographic and clinical characteristics, drug susceptibility test (DST) results, and diabetes status were collected. Categorical baseline characteristics were compared by Fisher's exact or Pearson Chi-square test. Univariable analysis and multivariable logistic models were used to estimate the association between diabetes and different drug resistance profiles.Retreated TB-DM patients have a higher rate of drug resistance than TB-no DM patients (34.41% vs 25.00%, P 0.01). Diabetes co-morbidity was significantly associated with any drug-resistant tuberculosis (DR-TB, odds ratio (OR):1.56, 95% confidence interval (CI): 1.01-2.43), multidrug resistant tuberculosis (MDR-TB, OR: 2.48, 95%CI:1.39-4.41; adjusted OR (aOR):2.94, 95%CI:1.57-5.48), isoniazid-related resistance (OR:1.71, 95%CI:1.04-2.81), rifampin-related resistance (OR:2.56, 0.54, 95%CI: 1.54-4.26; aOR:2.69, 95%CI:1.524-4.74), isoniazid + rifampin resistance (OR: 3.55, 95%CI:1.33-9.44; aOR:4.13, 95%CI:1.46-11.66), any resistance to isoniazid + streptomycin (OR:2.34, 95%CI:1.41-3.89; aOR:2.22, 95%CI:1.26-3.94), and any resistance to rifampin + isoniazid (OR:2.48, 95%CI:1.39-4.41; aOR:2.94, 95%CI: 1.57-5.48), compared with pan susceptible TB cases, P 0.05.The risk of acquired drug resistance increased significantly among retreated TB-DM patients compared with retreated TB-no DM patients, underlining the necessity of more interventions during the clinical management of TB-DM cases.

Background Diagnosis of tuberculosis (TB) in children is challenging. Epidemiological data of childhood pulmonary tuberculosis (PTB) are urgently needed. Methods We described trends in epidemiology, clinical characteristics, and treatment outcomes in seven cities of Shandong province, China, during 2005–2017. Data were collected from the China Information System for Disease Control and Prevention. Results Among 6283 (2.4% of all PTB) PTB cases aged

This study aimed to analyze the epidemiology of pulmonary tuberculosis (PTB) and gained insight into the future TB control plan in China. We extracted epidemiological, clinical, and geographic data from TB prevention and control institutions in 6 cities of Shandong province, China, during 2005 to 2017. Among 224,480 diagnosed PTB, rural residents accounted for 93%, smear-positive PTB 52%, and new cases 92%. The incidence rate of overall PTB declined from 40.8 to 26.25 per 100,000 during 2005 to 2017. Except smear-negative PTB (7.57–19.87 per 100,000), the incidence of smear-positive PTB and all that stratified by age, sex, and treatment history decreased. With 80% reduction, the incidence of smear-positive PTB (6.38 per 100,000) and relapse cases (1.01 per 100,000) were already very low in 2017. With persistent efforts to combat TB, the disease burden had shifted from smear-positive PTB to smear-negative PTB. While new cases need continuous attention, further reducing the incidence of smear-negative PTB and elderly patients may have a greater impact on future TB control.

The health effects of short-term exposure to air pollutants on respiratory deaths and its modifiers such as meteorological indexes have been widely investigated. However, most of the previous studies are limited to single pollutants or total respiratory deaths, and their findings are inconsistent. To comprehensively examine the short-term effects of air pollutants on daily respiratory mortality. Our analysis included 16,931 nonaccidental respiratory deaths (except lung cancer and tuberculosis) among older adults (>65 years) from 2011 to 2017 in Jinan, China. We used a generalized additive Poisson models adjusted for meteorology and population dynamics to examine the associations between air pollutants (particulate matter with an aerodynamic diameter of b2.5μm [PM2.5], particulate matter with an aerodynamic diameter of b10μm [PM10], SO2, NO2, O3) and daily mortality for the total patients, males, females, chronic airway diseases, pneumonia patients, and rest patients in Jinan. Outdoor air pollution was significantly related to mortality from all respiratory diseases especially from chronic airway disease in Jinan, China. The effects of air pollutants had lag effects and harvesting effects, and the effects estimates usually reached a peak at lag 1 or 2 day. An increase of 10 μg/m3 or 10 ppb of PM2.5, PM10, SO2, NO2, and O3 corresponds to increments in mortality caused by chronic airway disease of 0.243% (95% confidence interval [CI]: −0.172–0.659) at lag 1 day, 0.127% (95% CI: −0.161–0.415) at lag 1 day, 0.603% (95% CI: 0.069–1.139) at lag 3 day, 0.649% (95% CI: −0.808–2.128) at lag 0 day and 0.944% (95% CI: 0.156–0.1598) at lag 1 day, respectively. The effects of air pollutants were usually greater in females and varied by respiratory subgroups. Spearman correlation analysis suggested that there was a significant association between meteorological indexes and air pollutants. Sex, age, temperature, humidity, pressure, and wind speed may modify the short-term effects of outdoor air pollution on mortality in Jinan. Compared with the other pollutants, O3 had a stronger effect on respiratory deaths among the elderly. Moreover, chronic airway diseases were more susceptible to air pollution. Our findings provided new evidence for new local environmental and health policies making.

Background Few studies have investigated the associations between outdoor air pollution and outpatient visits for respiratory diseases (RDs) in general population. Methods We collected daily outpatient data of primary RDs from five hospitals in Jinan during January 2012 and December 2016, as well as daily measurements of air pollutants from the Jinan Environmental Monitoring Center and daily meteorological variables from the China Meteorological Data Sharing Service System. A generalized additive model (GAM) with quasi-Poisson regression was constructed to estimate the associations between daily average concentrations of outdoor air pollutants (PM2.5,PM10, SO2, NO2, CO and O3) and daily outpatient visits of RDs after adjusting for long-time trends, seasonality, the “day of the week” effect, and weather conditions. Subgroup analysis stratified by gender, age group and the type of RDs was conducted. Results A total of 1,373,658 outpatient visits for RDs were identified. Increases of 10 μg/m3 in PM2.5, PM10, NO2, CO and O3 were associated with0.168% (95% CI, 0.072–0.265%), 0.149% (95% CI, 0.082–0.215%), 0.527% (95% CI, 0.211–0.843%), 0.013% (95% CI, 0.003–0.023%), and 0.189% (95% CI, 0.032–0.347%) increases in daily outpatient visits for RDs, respectively. PM2.5 and PM10 showed instant and continuous effects, while NO2, CO and O3 showed delayed effects on outpatient visits for RDs. In stratification analysis, PM2.5 and PM10 were associated with acute RDs only. Conclusions Exposure to outdoor air pollutants including PM2.5, PM10, NO2, CO and O3 associated with increased risk of outpatient visits for RDs. Electronic supplementary material The online version of this article (10.1186/s12931-018-0958-x) contains supplementary material, which is available to authorized users.