Disease Burden of Non-COVID-19 Lower Respiratory Infections, Risk Factors, and Aetiologies in China 1990-2021: insights from the Global Burden of Disease Study 2021

Disease Burden of Non-COVID-19 Lower Respiratory Infections, Risk Factors, and Aetiologies in China 1990-2021: insights from the Global Burden of Disease Study 2021 | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Disease Burden of Non-COVID-19 Lower Respiratory Infections, Risk Factors, and Aetiologies in China 1990-2021: insights from the Global Burden of Disease Study 2021 Baojun Guo, Guowen Chen, Miaolian Chen, Ruixia Huang, Jinliang Mo, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5311940/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Lower respiratory infections (LRI) are the highest mortality diseases among infectious diseases globally, with China ranking second in the incidence and mortality of lower respiratory infections in 2021. This study, based on GBD 2021, investigates the burden of lower respiratory infections, risk factors, and etiologies in China from 1990 to 2021. Methods This study analyzes the trends in the disease burden of lower respiratory infections in China from 1990 to 2021, categorized by gender, age, and year, and explores the attributable mortality and disability-adjusted life years (DALYs) rates related to the risk factors and aetiologies associated with lower respiratory infections. Results Compared to 1990, the age-standardized incidence rate (ASIR), age-standardized mortality rate (ASMR), and age-standardized DALY rate (ASDAR) of lower respiratory infections in China decreased by 48%, 77%, and 89% in 2021. Ambient particulate matter pollution surpassed household air pollution from solid fuels to become the leading risk factor. Despite the significant decline, Streptococcus pneumoniae remains the primary pathogen associated with lower respiratory infections. Conclusion The disease burden of lower respiratory infections in China has significantly decreased over the past 32 years, but there is still a need to strengthen air pollution control, enhance tobacco regulation, and focus on the health of the elderly population. In response to the changes in the pathogen spectrum, it is necessary to improve detection capabilities and develop new antimicrobial drugs and vaccines. Lower Respiratory Infection Global Burden of Disease risk factors DALYs Etiology Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction In 2021, there were 344 million (95% UI: 325–364) cases of lower respiratory infections globally, with 2.18 million (95% UI: 1.98–2.36) deaths; both incidence and mortality rates remained high[ 1 ]. Before the outbreak of COVID-19, the age-standardized mortality ratio for lower respiratory infections among men and women worldwide was 1.31 (95% UI: 1.23–1.41)[ 2 ]. According to data from the World Health Organization (WHO), lower respiratory infections ranked as the fourth leading cause of death globally and the first among infectious diseases. In low-income countries, lower respiratory infections are the second leading cause of death, while in lower-middle-income and upper-middle-income countries, they rank fifth, and in high-income countries, they are the sixth leading cause of death[ 3 ]. The inability to identify pathogens, leading to imprecise drug treatment, is a significant reason for the high mortality rate of lower respiratory infections. Zhu et al. found that nearly half of patients with community-acquired pneumonia in China could not have their pathogens clearly identified. Among adults, the top three detected pathogens were Mycoplasma (15.01%), Streptococcus pneumoniae (11.68%), and Influenza A virus (12.28%). In children, the top three pathogens were Mycoplasma (19.16%), Respiratory Syncytial Virus (RSV) (16.01%), and Streptococcus pneumoniae (9.44%), with antibiotic resistance issues of Streptococcus pneumoniae being particularly severe[ 4 ]. Research statistics show that between 2000 and 2015, the global daily antibiotic consumption increased from 2.11 billion to 3.48 billion doses, representing a 65% increase. The antibiotic consumption rate rose from 11.3 doses per thousand residents per day to 15.7, marking a 39% increase. This growth is primarily contributed by low- and middle-income countries, while in high-income countries, although the antibiotic consumption has increased, the consumption rate has decreased by 4%[ 5 ]. In 2021, the number of deaths due to lower respiratory infections in China was 206,930.22 (95% UI: 171,260.88–251,990.47), ranking second globally, imposing a heavy economic and financial burden on the government, patients, and society as a whole. The outbreak of the COVID-19 pandemic at the end of 2019 once again highlighted the severity and impact of lower respiratory infections, leading to a deeper public understanding of the prevention and treatment of these infections. Understanding the disease burden and epidemiological trends of lower respiratory infections in China is crucial for developing effective prevention and control policies. This study, based on the GBD 2021 database, investigated the incidence rate, mortality rate, and DALYs rate of lower respiratory infections in China, as well as the associated risk factors and etiologies, with the aim of providing a scientific basis for developing relevant prevention and management strategies. Method Data sources The relevant data on the disease burden of lower respiratory infections in China are sourced from the Institute for Health Metrics and Evaluation (IHME), a subsidiary of the University of Washington, through the Global Health Data Exchange (GHDx) platform ( https://ghdx.healthdata.org/gbd-2021/data-input-sources ). GHDx is committed to assessing the disease burden of 371 diseases, injuries, and risk factors across 204 countries and regions globally. The database encompasses annual incidence, mortality, DALYs, etiology, and risk factor data spanning from 1990 to 2021. GBD 2021 data sources include population censuses, household surveys, healthcare service utilization, air pollution monitoring, satellite imagery, disease notifications, and more. The definition of LRI does not include tuberculosis, whooping cough, or COVID-19. Age-standardized rate Age standardization is a method used to compare data across different age groups, eliminating biases caused by variations in age structures. This involves selecting a standard population, calculating weights for each age group based on the standard population, and applying these weights to standardize the data. This standardization method helps to accurately compare features or indicators among different populations. The specific method for calculating ASR can be referred to in the methodologies reported in previous studies[ 6 ]. Disability-adjusted life-years (DALYs) DALYs is a comprehensive health indicator utilized to assess the burden of diseases, injuries, and health conditions. The calculation of DALYs aims to integrate the impacts of Years of Life Lost (YLLs) resulting from premature mortality and Years Lived with Disability (YLDs) attributed to impaired health. Each year of lost health condition is quantified as one DALY. The formula for calculating DALYs is: DALYs = YLLs + YLDs Where: YLLs = N × L YLDs = I × DW × L N is the number of premature deaths, L is the years of life lost per premature death, I is the number of individuals with disabilities, DW is the disability weight, representing the impact of disability on quality of life, L is the duration of disability in years. Statistical analysis The IHME Bayesian regression tool, DisMod-MR V.2.1, is employed for the analysis, modeling, and estimation of disease burden in the database. This tool helps mitigate uncertainties associated with original data sources, data processing, measurement errors, and model selection. The database covers indicators such as incidence, prevalence, mortality, and DALYs, providing 95% uncertainty intervals (UI) for direct statistical analysis. GraphPad 8.0.2 is used for creating graphical representations. Result Trends in the Disease Burden of Lower Respiratory Infections in China from 1990 to 2021. In the past 32 years, the number of incidence cases, ASIR, number of deaths, ASMR, number of DALYs, ASDAR for lower respiratory infections in males have consistently been higher than in females during the same period. The ASIR, ASMR, ASDAR, and number of DALY for both males and females show a declining trend. The number of incidence cases and deaths exhibits a trend of first decreasing and then increasing. Specifically, the lowest number of male incidence cases was 21,522,553.40 (95% UI: 20,249,110.7–22,971,324.91) in 2003, while the lowest number of female incidence cases was 19,412,410.22 (95% UI: 18,166,663.43-20,786,840.63) in 2008. The lowest number of male deaths was 105,552.84 (95% UI: 95,937.64–118,796.98) in 2012, and the lowest number of female deaths was 74,862.86 (95% UI: 62,238.40–97,107.14) in 2013 (Fig. 1 and Table 1 ). Table 1 In 1990 and 2021, the ASIR, ASMR, Age-Standardized DALYs Rate, and Percentage Change for LRI in China 1990 2021 Change (%) ASMR Both 60.65 (52.96, 66.66) 14.03 (11.68, 17.00) -0.77 (-0.81, -0.71) Male 71.32 (64.39, 78.39) 20.45 (17.14, 24.06) -0.71 (-0.76, -0.65) Female 54.51 (43.40, 61.45) 10.31 (7.90, 14.07) -0.81 (-0.86, -0.73) ASDAR Both 3,128.39 (2,724.11, 3,579.57) 347.67 (301.28, 402.94) -0.89 (-0.91, -0.86) Male 3,340.53 (2,883.47, 3,810.16) 445.70 (379.02, 515.46) -0.87 (-0.89, -0.84) Female 2,946.21 (2,542.50, 3,390.86) 271.00 (223.85, 331.31) -0.91 (-0.93, -0.88) ASIR Both 5,481.13 (5,149.05, 5,836.35) 2,853.81 (2,663.94, 3,067.55) -0.48 (-0.50, -0.45) Male 5,621.89 (5,285.09, 5,997.34) 3,118.18 (2,914.12, 3,353.68) -0.45 (-0.47, -0.42) Female 5,411.27 (5,073.27, 5,786.22) 2,664.57 (2,485.61, 2,870.23) -0.51 (-0.53, -0.48) Abbreviations: ASIR, age-standardized incidence rate; ASMR, age-standardized mortality rate; ASDAR, age-standardized disability-adjusted life years rate. The Disease Burden of Lower Respiratory Infections in China in 2021. In 2021, the highest number of incidence cases of lower respiratory infections in China was in the 80 + age group (11,496,755.71, 95% UI: 10,093,516.62-13,040,461.38), followed by the 5–9 age group (2,757,299.77, 95% UI: 2,074,692.93-3,607,662.369) and the < 5 age group (2,398,985.20, 95% UI: 1,997,575.87-2,834,649.53). Except for the 80 + age group, the number of incidence cases for all other age groups in females was lower than in males. The incidence rate of lower respiratory infections decreases with increasing age, reaching its lowest point in the 35–39 age group (844.21, 95% UI: 668.03-1,033.84), and then increases again. The number of deaths, mortality rate, number of DALYs, and DALY rate all initially decrease and then increase with age, peaking in the 80 + age group (Fig. 2 ). Trends in Risk Factors for Lower Respiratory Infections in China from 1990 to 2021. We selected the nine main risk factors related to lower respiratory infections from the GBD 2021 database, which include ambient particulate matter pollution, non-exclusive breastfeeding, secondhand smoke, child growth failure, low temperature, low birth weight and short gestation, no access to handwashing facilities, smoking, and household air pollution from solid fuels. The study indicates that in 1990, the burden of ASMR for lower respiratory infections was primarily attributed to three risk factors: household air pollution from solid fuels, child growth failure, and secondhand smoke. By 2021, the main risk factors for this burden had shifted to ambient particulate matter pollution, smoking, and low temperature. The top three risk factors contributing to the burden of ASDAR changed from child growth failure, household air pollution from solid fuels, and secondhand smoke to ambient particulate matter pollution, child growth failure, and secondhand smoke. Compared to 1990, the disease burden caused by the nine risk factors decreased in 2021. For females, the burdens of ASMR from secondhand smoke and ASDAR from household air pollution from solid fuels fell below those for males after 1996 and 1993, respectively. For the remaining seven risk factors, the disease burden for females was consistently lower than that for males at any given time (Fig. 3 ). Risk Factors for Lower Respiratory Infections in China in 2021. We compared the differences in risk factors between genders and age groups and found that child growth failure, low birth weight and short gestation, and non-exclusive breastfeeding are specific risk factors for the < 5 age group, while smoking is a specific risk factor for individuals over 30. The disease burden from smoking and secondhand smoke is more strongly correlated with age in males, and the impact of smoking on males is significantly greater than on females (Fig. 4 ). The changing trends in the etiology of lower respiratory infections in China from 1990 to 2021. The GBD 2021 database includes 18 pathogens associated with lower respiratory infections. Compared to 1990, the disease burden from all pathogens decreased in 2021. In the 30 years leading up to 2019, the three pathogens with the highest mortality rates were Streptococcus pneumoniae, Staphylococcus aureus, and Influenza. After 2019, the burden from Influenza significantly decreased, while other viral etiologies of LRI rose to the third position. In 1990, the three pathogens with the highest age-standardized DALY rates were Streptococcus pneumoniae, Influenza, and other viral etiologies of LRI. After 2004, Staphylococcus aureus surpassed Influenza, and other viral etiologies rose to the second position. In 2019, after a significant decrease in Influenza, it was surpassed by other viral etiologies (Fig. 5 ). The etiology of lower respiratory infections in China in 2021. We presented the distribution of mortality rates and DALY rates attributed to 18 pathogens across different genders and age groups. The results show that the distribution of mortality rates and DALY rates associated with pathogens related to lower respiratory infections exhibits similar characteristics and trends across different age groups: they decrease with increasing age, reach a low point in adulthood, and then increase again. The mortality rate for all pathogens is highest in the 80 + age group, followed by the < 5 age group. The DALY rates for RSV and polymicrobial infections are highest in the < 5 age group, followed by the 80 + age group, while the DALY rates for the remaining pathogens are highest in the 80 + age group and then in the < 5 age group. Additionally, for all pathogens, the mortality and DALY rates for females are lower than those for males in the same age group (Fig. 6 ). Discussion The GBD 2021 database provides relevant data on the disease burden of 371 diseases and injuries across 204 countries and regions, as well as 811 subnational areas. This includes data on incidence, prevalence, DALYs, years of life lost (YLLs), years lived with disability (YLDs), healthy life expectancy (HALE), risk factors, and etiologies[ 7 ]. We extracted and analyzed relevant data on lower respiratory infections in China and found that in 2021, the number of incidence cases, the incidence rates, the number of deaths, the mortality rates, the number of DALYs, and the DALY rates for lower respiratory infections have all decreased compared to 32 years ago. However, due to the large population base and the increasing aging population, the reduction in the number of incidence cases is not significant compared to other indicators, and the annual number of new cases remains a substantial burden. Due to various factors such as seasonality, geographical variations, and population demographics, there are significant differences in the prevalence patterns and pathogen spectra of lower respiratory infections among different countries globally and within different regions of a country[ 8 ]. A retrospective study covering 23 provinces in mainland China found that the incidence of community-acquired pneumonia in urban populations decreases in the summer and autumn seasons, rises in the winter, and peaks in the spring. Provinces in the eastern and northeastern regions exhibit higher incidence rates compared to those in the southern regions. The age groups with the highest incidence are individuals under 5 years old and those over 80 years old[ 9 ]. Another multicenter prospective study discovered that between 2001 and 2005, bacterial infections predominantly caused community-acquired pneumonia (CAP) in Chinese adults, whereas from 2009 to 2016, there was a significant increase in the proportion of viral infections[ 10 ]. Therefore, understanding the local epidemiology, pathogen spectrum, and associated risk factors of lower respiratory tract infections is crucial for precisely formulating prevention and control strategies, as well as for the rational allocation of medical resources. We observed that the incidence and mortality of lower respiratory infections in males are higher than in females. This can be attributed to the fact that females exhibit a stronger cellular and humoral immune response[ 11 ]. Studies have found that estrogen can regulate various immune cells, including macrophages, T cells, natural killer cells, and B cells[ 12 ]. Additionally, estrogen promotes the expression of immunoglobulin G (IgG) and immunoglobulin M (IgM), while testosterone inhibits this expression[ 13 ]. There is also research indicating that estrogen can mediate the upregulation of endothelial nitric oxide synthase (eNOS) transcription, enhancing the production of nitric oxide (NO), resulting in higher levels of nitric oxide in females compared to males[ 14 ]. Nitric oxide is a gaseous component in the immune system that contributes to clearing pathogens and foreign substances from the body, inhibiting viral replication[ 15 ]. In addition, the proportion of smoking and alcohol consumption is higher in males than in females, contributing to a higher susceptibility to lower respiratory infections in males. Numerous studies have confirmed the correlation between smoking, alcohol consumption, and respiratory infections[ 16 – 19 ]. Exposure to tobacco smoke and nicotine in utero and postnatally can disrupt lung development, increasing susceptibility to lower respiratory tract infections and the prevalence of wheezing[ 20 ]. In a prospective cohort study conducted by He and colleagues, it was found that Chinese school-age children exposed to secondhand smoke showed an increased incidence of cough and decreased lung function compared to children not exposed[ 21 ]. Another study indicated that exposure to secondhand smoke significantly increased the risk of lower respiratory tract infections and decreased lung function in children. When both parents smoked, the risk of infants developing lower respiratory tract infections increased by 1.82 times. If the fetus was exposed to maternal smoking during pregnancy, the risk of developing lower respiratory tract infections increased by 1.19 times[ 22 ]. McEvoy and colleagues conducted a randomized controlled trial, revealing that offspring of smoking pregnant women who received vitamin C during gestation exhibited better lung function in the first year of life compared to those born to smoking pregnant women without treatment. However, the mechanism of the potential protective effects of vitamin C on prenatal smoking exposure remains unclear[ 23 ]. Excessive alcohol consumption can weaken both the innate and adaptive immune systems, and individuals who are intoxicated often experience aspiration, thereby increasing the likelihood of lower respiratory infections[ 19 ]. A recent network meta-analysis indicates that alcohol exposure may enhance the inflammation induced by COVID-19 by boosting inflammatory effects and suppressing the activity of anti-inflammatory mediators, including glucocorticoid receptors[ 24 ]. Two additional meta-analyses have found a proportional relationship between alcohol consumption and the risk of lower respiratory infections. On average, for each additional daily drink, the risk of lower respiratory tract infections increases by 8% (95% CI 6–9%) and 6% (95% CI 1–11%) [ 25 , 26 ]. To reduce the harmful effects of smoking and alcohol consumption, countries around the world are actively implementing measures such as increasing taxes on tobacco and alcohol, raising the legal purchasing age, banning smoking in public places, restricting tobacco advertising and promotions, and promoting smoking and alcohol cessation education[ 27 – 30 ]. Apart from smoking and alcohol, the GBD database also covers other risk factors related to lower respiratory infections, such as child growth failure, air pollution, non-optimal temperature, and lack of access to handwashing facilities. Hand hygiene and access to handwashing facilities play a crucial role in controlling the spread of various infectious diseases, including lower respiratory infections. Handwashing effectively reduces the transmission of pathogens, thereby lowering the incidence of common infectious diseases such as respiratory infections and diarrhea. In particular, within healthcare settings, hand hygiene controls nosocomial infections, reduces the spread of drug-resistant pathogens, and plays a vital role in public health emergencies. Enhancing hand hygiene education and increasing access to handwashing facilities help improve overall community hygiene and are essential components of global health[ 31 , 32 ]. The incidence of lower respiratory infections is closely related to seasonal changes and temperature. The virulence of pathogens is usually associated with their biological characteristics and the immune capacity of the host. Studies have found that most common respiratory pathogens, such as Streptococcus pneumoniae, influenza virus, and RSV, typically have higher incidence rates in winter. Additionally, the human immune system also exhibits seasonal variations, often becoming more vulnerable in the winter [ 33 , 34 ]. Another time-series study found that a greater diurnal temperature range is associated with increased outpatient visits for acute lower respiratory infections, pneumonia, and bronchiolitis in children, and this phenomenon is more pronounced during the rainy season[ 35 ]. Additionally, research by Sonego et al. suggests that compared to well-nourished children with pneumonia, those with moderate malnutrition have a 2.46-fold higher risk of mortality, while those with severe malnutrition have a 4.27-fold higher risk[ 36 ]. Household air pollution can pose serious hazards to the respiratory system[ 37 ]. A four-year time-series analysis covering over 4.2 million pneumonia hospitalization cases in 184 Chinese cities reveals that, nationwide, a 10 µg/m3 increase in the 3-day moving average concentrations of PM2.5 and PM10 is associated with a 0.31% and 0.19% rise in pneumonia hospitalization numbers, respectively[ 38 ]. Our analysis shows that over the past thirty-two years, the disease burden caused by various risk factors has been declining. This is attributed to several factors, including China’s rapid economic development, accelerated infrastructure construction, significant improvements in population nutrition levels, the promotion of clean energy usage, the widespread adoption of air conditioning and air purification systems, and the continuous strengthening of air pollution control efforts. In 2021, the global number of deaths from lower respiratory infections was 2.18 million (95% UI: 1.98–2.36), with Streptococcus pneumoniae accounting for 505,000 deaths (95% UI: 454,000-555,000). In China, Streptococcus pneumoniae was responsible for 51,179 deaths (95% UI: 42,055–62,158) from lower respiratory infections[ 1 ], making it the pathogen with the highest disease burden from lower respiratory infections in the country. Due to the high incidence and mortality rates caused by pneumococcal-induced lower respiratory tract infections, it is crucial not only to select sensitive antibiotics through susceptibility testing but also to prioritize vaccination with the pneumococcal conjugate vaccine[ 39 ]. Research predicts that administering the pneumococcal vaccine can prevent 34% of global infection-related deaths[ 40 ], the "Global Pneumonia Action Plan" recommends countries to undertake large-scale vaccination efforts targeting pneumococcal infections. As of 2019, the global coverage rate of pneumococcal conjugate vaccines for infants is approximately 47.9%[ 41 ]. In mainland China, the pneumococcal vaccine coverage rate among the population is 21.7%, and there is currently no available data on vaccine coverage specifically for Chinese children. However, due to the current absence of the pneumococcal vaccine in China's national immunization program and variations in awareness, there are significant differences in vaccination coverage among local families, migrant families, and left-behind families[ 42 , 43 ]. Our study found that, compared to 1990, the incidence and mortality rates of pneumococcal lower respiratory infections in China have significantly decreased. However, there has been a rising trend since 2019, making it crucial to enhance diagnostic capabilities and strengthen vaccination efforts. Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter spp. belong to the ESKAPE pathogens, known for their ability to "escape" treatment from various common antibiotics, including broad-spectrum antibiotics. They pose significant risks, especially in hospital-acquired infections, increasing infection-related mortality and length of hospitalization, thus presenting substantial challenges for clinical treatment[ 44 ]. In recent years, the global prevalence of Staphylococcus aureus has been on the rise, particularly methicillin-resistant Staphylococcus aureus (MRSA), with isolation rates exceeding 40% in regions such as Tibet, Shanghai, and Jiangsu. Due to effective antimicrobial stewardship in China, the resistance rate of MRSA to trimethoprim-sulfamethoxazole has decreased from 20.1–6.4% in recent years (now lower than the 15% seen in methicillin-susceptible Staphylococcus aureus), and the resistance rate to rifampicin has dropped from 58% in 2010 to around 3.7% in 2022[ 44 ]. As of 2022, the resistance rates of Klebsiella pneumoniae in China to tigecycline, polymyxin, and ceftazidime-avibactam were 2.6%, 2.8%, and 6.2%, respectively. The resistance rates to imipenem and meropenem have increased from 8.8% and 8.9% in 2010 to 22.6% and 24.2% in 2022, respectively. Meanwhile, the clinical isolation rate of carbapenem-resistant Klebsiella pneumoniae (CRKP) rose from 4.9% in 2013 to 9.0% in 2017, with the isolation rate in Shanghai increasing to 26.9%. High resistance rates are mainly concentrated in eastern China[ 45 – 48 ]. In China, the resistance of Pseudomonas aeruginosa to most antibiotics has shown a generally stable or declining trend. Specifically, the isolation rates of imipenem and meropenem-resistant strains decreased from 30.8% and 25.8% in 2010 to 22.1% and 17.6% in 2022[ 46 ]. An earlier study indicated that the detection rate of carbapenem-resistant Pseudomonas aeruginosa (CRPA) in Canada was the lowest at 3.3%, while resistance rates in countries such as Russia, Brazil, Greece, and Saudi Arabia exceeded 50%, with China's resistance rate around 35%[ 49 ]. Additionally, a meta-analysis involving 7,951 cases across 16 countries showed that the highest prevalence of multidrug-resistant (MDR) Pseudomonas aeruginosa causing ventilator-associated pneumonia (VAP) was found in Iran at 87.5% (95% CI: 69-95.7%), followed by China at 85.3% (95% CI: 79.3–89.8%), while the lowest rate was observed in the United States at 19.7% (95% CI: 18.6–20.7%)[ 50 ]. In 2022, Enterobacter species ranked fifth in isolation rates among Gram-negative bacteria in China, with the lowest resistance rates to amikacin and tigecycline at 1.6% and 1.9%, respectively. The resistance rate to imipenem was 9.7%, while the resistance rate to cefotaxime reached as high as 96%[ 46 ]. Enterobacter species typically include Enterobacter cloacae, Enterobacter aerogenes, Enterobacter asburiae, Enterobacter hormaechei, and Enterobacter kobei, with Enterobacter cloacae being the most commonly encountered in clinical settings. A study by Zhang et al. found that carbapenem-resistant Enterobacter cloacae in China had susceptibility rates to colistin, amikacin, ciprofloxacin, fosfomycin, and tigecycline of 93.8%, 62.5%, 25.0%, 35.3%, and 6.8%, respectively. The resistance rates to amoxicillin-clavulanic acid, cefotaxime, ceftazidime, imipenem, and meropenem were all over 91%[ 51 ]. The infection rate of Acinetobacter baumannii is lower compared to other ESKAPE pathogens; however, approximately 45% of Acinetobacter baumannii strains globally are considered multidrug-resistant, with resistance rates exceeding 60% in the United States. According to WTO statistics, the level of multidrug resistance in Acinetobacter baumannii is over four times that of Klebsiella pneumoniae and Pseudomonas aeruginosa[ 46 , 52 , 53 ]. A study by Chen et al. found that drug-resistant Acinetobacter baumannii in China exhibits broad resistance characteristics, with the highest sensitivity to polymyxins and tigecycline; however, compared to other countries in the Asia-Pacific region, the Acinetobacter baumannii isolates in China have the lowest sensitivity to tigecycline[ 54 ]. Our study found that the trend in the disease burden of the aforementioned five pathogens is similar to that of Streptococcus pneumoniae, showing a gradual decline before 2019, followed by a slight rebound thereafter. The significant decrease in mortality and DALY rates reflects the effectiveness of medical interventions and public health measures, but attention must still be paid to changes in resistance rates. Influenza in most regions of China exhibits a seasonal pattern, with more outbreaks occurring in the fall and winter seasons. The incidence decreases noticeably after March. Since 2007, the incidence of influenza in China has gradually increased, with a particularly significant rise observed between 2013 and 2017[ 55 ]. Research indicates that the influenza vaccination rate among the population aged 40 and above in mainland China is 2.4%[ 56 ]. Another study points out that as of March 2018, influenza vaccine coverage in the population of mainland China peaked between 2009 and 2010[ 57 ]. Fan et al. analyzed the influenza vaccination rates among healthcare personnel globally and found that, in the decades leading up to 2023, the global influenza vaccination rate for healthcare personnel was 41.7%, with the highest rate in the Americas (67.1%), the lowest in Africa (6.5%), and a rate of 28.5% in Asia. The highest vaccination rate occurred from 2020 to 2023, reaching 52.8%. The second-highest rate was observed from 2009 to 2012 at 46.7%, while the lowest rate was recorded between 2017 and 2019 at 31.4%[ 58 ]. This may be attributed to the H1N1 influenza pandemic (2009 to 2010) and the COVID-19 outbreak, which have driven vaccine uptake. Our study found that since the outbreak of COVID-19 in 2019, the DALY rates and mortality rates for influenza have significantly decreased, which aligns with the findings of the aforementioned studies. Currently, antiviral drugs approved by the United States Food and Drug Administration (FDA) and recommended for clinical treatment of influenza include neuraminidase inhibitors (NAIs) such as oseltamivir, zanamivir, and peramivir, as well as viral RNA polymerase inhibitors such as baloxavir, favipiravir, and pimodivir. However, there have been reports of resistance to oseltamivir in certain viruses[ 59 ]. RSV has shown a significant decline in disease burden similar to that of influenza since 2019. A systematic review by Maggi et al. found that the hospitalization and mortality rates for RSV and influenza among older adults are comparable[ 60 ]. A study by Liu et al. suggests that RSV is the most common pathogen in severe community-acquired pneumonia among children in China[ 61 ]. Our study similarly found that RSV is the only pathogen, aside from polymicrobial infections, that has a higher mortality rate in children compared to older adults. The prevalence of RSV infections typically follows a seasonal pattern, with outbreaks commonly occurring in the northern hemisphere between October and May of the following year, and in the southern hemisphere between May and September. In tropical regions, RSV outbreaks often occur during the rainy season, with a weaker correlation to specific seasons[ 62 , 63 ]. Due to the lack of specific antiviral medications, adults can typically receive vaccinations to prevent RSV infection. For infants, there are currently no available vaccines, so maternal vaccination during pregnancy can be employed. This process generates antibodies in the mother, which are then transferred to the fetus through the placenta, providing protective effects. Alternatively, immunoprophylaxis can be achieved in infants using monoclonal antibodies such as Palivizumab and Nirsevimab[ 64 ]. Due to the lack of market approval for the mentioned drugs in mainland China, medical institutions in mainland China typically resort to symptomatic supportive treatment when dealing with lower respiratory tract infections caused by RSV. Additionally, recent clinical trials have demonstrated the efficacy of EDP-938 (a Respiratory Syncytial Virus Inhibitor) in reducing viral load and alleviating clinical symptoms, suggesting significant therapeutic potential[ 65 ]. In addition to the common pathogens mentioned above, we also analyzed the trends in disease burden caused by pathogens such as Haemophilus influenzae, Mycoplasma, Escherichia coli, and fungi. The study found that since 2019, aside from influenza and RSV, the ASMR and ASDAR associated with other pathogens have shown an increase. However, compared to 1990, the overall burden of disease related to all pathogens has declined. Nevertheless, the spread of antibiotic resistance remains a major threat to global health. To address this challenge, it is essential to develop new antimicrobial drugs and vaccines, use existing medications judiciously, strengthen infection prevention and control measures, and establish a global monitoring and data-sharing system to quickly identify and respond to the spread of resistant bacteria. This study has several limitations. The Global Burden of Disease (GBD) relies on health data collected by various countries, but there are significant differences in data collection standards and capabilities, especially in low- and middle-income countries, which often lack comprehensive disease monitoring and reporting systems. This results in insufficient or inaccurate data, affecting the precision of the research findings. Due to the incompleteness of global data, the statistical models used for data prediction in the GBD may produce errors or biases and may not adequately reflect the health status of specific regions. Additionally, the GBD typically assesses the impact of each risk factor independently, failing to fully capture their synergistic or exacerbating effects. The study lacks specific data from different provinces, ethnic groups, and quarters. In summary, due to improvements in healthcare, the number of deaths and the ASMR from lower respiratory infections in China have shown a declining trend from 1990 to 2021. However, the decrease in the number of incidence cases is not as pronounced due to the increasing aging population. Household air pollution from solid fuels is the most effectively controlled risk factor, primarily due to the gradual replacement of wood and charcoal with cleaner energy sources for household fuel. Smoking shows the greatest gender disparity among risk factors, while child growth failure and smoking are the primary risk factors for children under 5 and individuals over 30, respectively. Streptococcus pneumoniae remains the leading pathogen for lower respiratory infections in China, with the most notable decline in disease burden, while RSV has a greater impact on children than on older adults. Therefore, it is essential to strengthen epidemiological research on lower respiratory infections in the Chinese population and implement differentiated management and targeted prevention strategies. Declarations Data Availability The foundation of this research lies in the publicly accessible data provided by the Global Burden of Disease Study 2021. The data is available for free download from the IHME data repository (http://ghdx.healthdata.org/gbd-results-tool) without the need for any download permissions. Acknowledgments The authors convey their thanks to the Global Burden of Disease Study team for furnishing the data, allowing us to carry out our research without hindrance. Conflicts of Interest The authors affirm the absence of any conflicts of interest in this work. Author contributions BJG, GWC, MLC, and JJL were involved in the design of this study. JLM and RXH were responsible for the extraction and analysis of data. BJG, ZML, QLJ, and XQL contributed to the interpretation of analysis results. BJG, GWC, RXH, JJL, and MLC participated in writing the first draft of this article. BJG, JLM, ZML, and QLJ revised the manuscript. All authors approved the submitted manuscript. Funding No funding was received for this study. Consent for publication Not applicable. Informed Consent Statement Not applicable. Institutional Review Board Statement The data utilized in this study underwent anonymization prior to usage. All methodologies were executed in alignment with pertinent guidelines and regulations. References Global, regional, and national incidence and mortality burden of non-COVID-19 lower respiratory infections and aetiologies, 1990-2021: a systematic analysis from the Global Burden of Disease Study 2021 . The Lancet Infectious diseases 2024, 24 (9):974-1002. Age-sex differences in the global burden of lower respiratory infections and risk factors, 1990-2019: results from the Global Burden of Disease Study 2019 . The Lancet Infectious diseases 2022, 22 (11):1626-1647. The top 10 causes of death [https://www.who.int/zh/news-room/fact-sheets/detail/the-top-10-causes-of-death] Zhu YG, Tang XD, Lu YT, Zhang J, Qu JM: Contemporary Situation of Community-acquired Pneumonia in China: A Systematic Review . Journal of translational internal medicine 2018, 6 (1):26-31. Klein EY, Van Boeckel TP, Martinez EM, Pant S, Gandra S, Levin SA, Goossens H, Laxminarayan R: Global increase and geographic convergence in antibiotic consumption between 2000 and 2015 . Proceedings of the National Academy of Sciences of the United States of America 2018, 115 (15):E3463-e3470. Liu Z, Jiang Y, Yuan H, Fang Q, Cai N, Suo C, Jin L, Zhang T, Chen X: The trends in incidence of primary liver cancer caused by specific etiologies: Results from the Global Burden of Disease Study 2016 and implications for liver cancer prevention . Journal of hepatology 2019, 70 (4):674-683. Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021 . Lancet (London, England) 2024, 403 (10440):2133-2161. Feldman C, Shaddock E: Epidemiology of lower respiratory tract infections in adults . Expert review of respiratory medicine 2019, 13 (1):63-77. Sun Y, Li H, Pei Z, Wang S, Feng J, Xu L, Gao P, Cao B, Zhan S: Incidence of community-acquired pneumonia in urban China: A national population-based study . Vaccine 2020, 38 (52):8362-8370. Zhou F, Wang Y, Liu Y, Liu X, Gu L, Zhang X, Pu Z, Yang G, Liu B, Nie Q et al : Disease severity and clinical outcomes of community-acquired pneumonia caused by non-influenza respiratory viruses in adults: a multicentre prospective registry study from the CAP-China Network . The European respiratory journal 2019, 54 (2). Fish EN: The X-files in immunity: sex-based differences predispose immune responses . Nature reviews Immunology 2008, 8 (9):737-744. Klein SL, Marriott I, Fish EN: Sex-based differences in immune function and responses to vaccination . Transactions of the Royal Society of Tropical Medicine and Hygiene 2015, 109 (1):9-15. Ruggieri A, Anticoli S, D'Ambrosio A, Giordani L, Viora M: The influence of sex and gender on immunity, infection and vaccination . Annali dell'Istituto superiore di sanita 2016, 52 (2):198-204. MacRitchie AN, Jun SS, Chen Z, German Z, Yuhanna IS, Sherman TS, Shaul PW: Estrogen upregulates endothelial nitric oxide synthase gene expression in fetal pulmonary artery endothelium . Circulation research 1997, 81 (3):355-362. Saura M, Zaragoza C, McMillan A, Quick RA, Hohenadl C, Lowenstein JM, Lowenstein CJ: An antiviral mechanism of nitric oxide: inhibition of a viral protease . Immunity 1999, 10 (1):21-28. Rosoff DB, Yoo J, Lohoff FW: Smoking is significantly associated with increased risk of COVID-19 and other respiratory infections . Communications biology 2021, 4 (1):1230. Gergen PJ, Fowler JA, Maurer KR, Davis WW, Overpeck MD: The burden of environmental tobacco smoke exposure on the respiratory health of children 2 months through 5 years of age in the United States: Third National Health and Nutrition Examination Survey, 1988 to 1994 . Pediatrics 1998, 101 (2):E8. Oberg M, Jaakkola MS, Woodward A, Peruga A, Prüss-Ustün A: Worldwide burden of disease from exposure to second-hand smoke: a retrospective analysis of data from 192 countries . Lancet (London, England) 2011, 377 (9760):139-146. Morojele NK, Shenoi SV, Shuper PA, Braithwaite RS, Rehm J: Alcohol Use and the Risk of Communicable Diseases . Nutrients 2021, 13 (10). Herring MJ, Putney LF, Wyatt G, Finkbeiner WE, Hyde DM: Growth of alveoli during postnatal development in humans based on stereological estimation . American journal of physiology Lung cellular and molecular physiology 2014, 307 (4):L338-344. He QQ, Wong TW, Du L, Jiang ZQ, Yu TS, Qiu H, Gao Y, Wong AH, Liu WJ, Wu JG: Environmental tobacco smoke exposure and Chinese schoolchildren's respiratory health: a prospective cohort study . American journal of preventive medicine 2011, 41 (5):487-493. Jayes L, Haslam PL, Gratziou CG, Powell P, Britton J, Vardavas C, Jimenez-Ruiz C, Leonardi-Bee J: SmokeHaz: Systematic Reviews and Meta-analyses of the Effects of Smoking on Respiratory Health . Chest 2016, 150 (1):164-179. McEvoy CT, Schilling D, Clay N, Jackson K, Go MD, Spitale P, Bunten C, Leiva M, Gonzales D, Hollister-Smith J et al : Vitamin C supplementation for pregnant smoking women and pulmonary function in their newborn infants: a randomized clinical trial . Jama 2014, 311 (20):2074-2082. Huang W, Zhou H, Hodgkinson C, Montero A, Goldman D, Chang SL: Network Meta-Analysis on the Mechanisms Underlying Alcohol Augmentation of COVID-19 Pathologies . Alcoholism, clinical and experimental research 2021, 45 (4):675-688. Samokhvalov AV, Irving HM, Rehm J: Alcohol consumption as a risk factor for pneumonia: a systematic review and meta-analysis . Epidemiology and infection 2010, 138 (12):1789-1795. Simou E, Britton J, Leonardi-Bee J: Alcohol and the risk of pneumonia: a systematic review and meta-analysis . BMJ open 2018, 8 (8):e022344. Mehrotra R, Yadav A, Sinha DN, Parascandola M, John RM, Ayo-Yusuf O, Nargis N, Hatsukami DK, Warnakulasuriya S, Straif K et al : Smokeless tobacco control in 180 countries across the globe: call to action for full implementation of WHO FCTC measures . The Lancet Oncology 2019, 20 (4):e208-e217. Sornpaisarn B, Shield KD, Cohen JE, Schwartz R, Rehm J: Can pricing deter adolescents and young adults from starting to drink: An analysis of the effect of alcohol taxation on drinking initiation among Thai adolescents and young adults . Journal of epidemiology and global health 2015, 5 (4 Suppl 1):S45-57. Limaye RJ, Srirojn B, Lilleston P, Aramrattana A, Thomson N, Celentano DD, Sherman SG: A qualitative exploration of the effects of increasing the minimum purchase age of alcohol in Thailand . Drug and alcohol review 2013, 32 (1):100-105. Marynak K, Mahoney M, Williams KS, Tynan MA, Reimels E, King BA: State and Territorial Laws Prohibiting Sales of Tobacco Products to Persons Aged <21 Years - United States, December 20, 2019 . MMWR Morbidity and mortality weekly report 2020, 69 (7):189-192. Aiello AE, Coulborn RM, Perez V, Larson EL: Effect of hand hygiene on infectious disease risk in the community setting: a meta-analysis . American journal of public health 2008, 98 (8):1372-1381. Pittet D, Allegranzi B, Sax H, Dharan S, Pessoa-Silva CL, Donaldson L, Boyce JM: Evidence-based model for hand transmission during patient care and the role of improved practices . The Lancet Infectious diseases 2006, 6 (10):641-652. Fares A: Factors influencing the seasonal patterns of infectious diseases . International journal of preventive medicine 2013, 4 (2):128-132. Mirsaeidi M, Motahari H, Taghizadeh Khamesi M, Sharifi A, Campos M, Schraufnagel DE: Climate Change and Respiratory Infections . Annals of the American Thoracic Society 2016, 13 (8):1223-1230. Zhang Z, Xu D, Chen J, Meng Q, Liang Z, Zhang X: Daily diurnal temperature range associated with outpatient visits of acute lower respiratory infection in children: A time-series study in Guangzhou, China . Frontiers in public health 2022, 10 :951590. Sonego M, Pellegrin MC, Becker G, Lazzerini M: Risk factors for mortality from acute lower respiratory infections (ALRI) in children under five years of age in low and middle-income countries: a systematic review and meta-analysis of observational studies . PloS one 2015, 10 (1):e0116380. Gordon SB, Bruce NG, Grigg J, Hibberd PL, Kurmi OP, Lam KB, Mortimer K, Asante KP, Balakrishnan K, Balmes J et al : Respiratory risks from household air pollution in low and middle income countries . The Lancet Respiratory medicine 2014, 2 (10):823-860. Tian Y, Liu H, Wu Y, Si Y, Li M, Wu Y, Wang X, Wang M, Chen L, Wei C et al : Ambient particulate matter pollution and adult hospital admissions for pneumonia in urban China: A national time series analysis for 2014 through 2017 . PLoS medicine 2019, 16 (12):e1003010. Waight PA, Andrews NJ, Ladhani SN, Sheppard CL, Slack MP, Miller E: Effect of the 13-valent pneumococcal conjugate vaccine on invasive pneumococcal disease in England and Wales 4 years after its introduction: an observational cohort study . The Lancet Infectious diseases 2015, 15 (5):535-543. Chen C, Cervero Liceras F, Flasche S, Sidharta S, Yoong J, Sundaram N, Jit M: Effect and cost-effectiveness of pneumococcal conjugate vaccination: a global modelling analysis . The Lancet Global health 2019, 7 (1):e58-e67. Measuring routine childhood vaccination coverage in 204 countries and territories, 1980-2019: a systematic analysis for the Global Burden of Disease Study 2020, Release 1 . Lancet (London, England) 2021, 398 (10299):503-521. Zhou Y, Li D, Cao Y, Lai F, Wang Y, Long Q, Zhang Z, An C, Xu X: Immunization coverage, knowledge, satisfaction, and associated factors of non-National Immunization Program vaccines among migrant and left-behind families in China: evidence from Zhejiang and Henan provinces . Infectious diseases of poverty 2023, 12 (1):93. Shao W, Chen X, Zheng C, Wang G, Zhang B, Zhang W: Pneumococcal vaccination coverage and willingness in mainland China . Tropical medicine & international health : TM & IH 2022, 27 (10):864-872. Miller WR, Arias CA: ESKAPE pathogens: antimicrobial resistance, epidemiology, clinical impact and therapeutics . Nature reviews Microbiology 2024, 22 (10):598-616. Paterson DL, Bonomo RA: Extended-spectrum beta-lactamases: a clinical update . Clinical microbiology reviews 2005, 18 (4):657-686. Luo Q, Lu P, Chen Y, Shen P, Zheng B, Ji J, Ying C, Liu Z, Xiao Y: ESKAPE in China: epidemiology and characteristics of antibiotic resistance . Emerging microbes & infections 2024, 13 (1):2317915. Chen D, Li H, Zhao Y, Qiu Y, Xiao L, He H, Zheng D, Li X, Huang L, Yu X et al : Characterization of carbapenem-resistant Klebsiella pneumoniae in a tertiary hospital in Fuzhou, China . Journal of applied microbiology 2020, 129 (5):1220-1226. Hu Y, Liu C, Shen Z, Zhou H, Cao J, Chen S, Lv H, Zhou M, Wang Q, Sun L et al : Prevalence, risk factors and molecular epidemiology of carbapenem-resistant Klebsiella pneumoniae in patients from Zhejiang, China, 2008-2018 . Emerging microbes & infections 2020, 9 (1):1771-1779. Hong DJ, Bae IK, Jang IH, Jeong SH, Kang HK, Lee K: Epidemiology and Characteristics of Metallo-β-Lactamase-Producing Pseudomonas aeruginosa . Infection & chemotherapy 2015, 47 (2):81-97. Li Y, Roberts JA, Walker MM, Aslan AT, Harris PNA, Sime FB: The global epidemiology of ventilator-associated pneumonia caused by multi-drug resistant Pseudomonas aeruginosa: A systematic review and meta-analysis . International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases 2024, 139 :78-85. Zhang R, Liu L, Zhou H, Chan EW, Li J, Fang Y, Li Y, Liao K, Chen S: Nationwide Surveillance of Clinical Carbapenem-resistant Enterobacteriaceae (CRE) Strains in China . EBioMedicine 2017, 19 :98-106. Magill SS, Edwards JR, Bamberg W, Beldavs ZG, Dumyati G, Kainer MA, Lynfield R, Maloney M, McAllister-Hollod L, Nadle J et al : Multistate point-prevalence survey of health care-associated infections . The New England journal of medicine 2014, 370 (13):1198-1208. Lob SH, Hoban DJ, Sahm DF, Badal RE: Regional differences and trends in antimicrobial susceptibility of Acinetobacter baumannii . International journal of antimicrobial agents 2016, 47 (4):317-323. Chen CH, Wu PH, Lu MC, Ho MW, Hsueh PR: Geographic patterns of carbapenem-resistant, multi-drug-resistant and difficult-to-treat Acinetobacter baumannii in the Asia-Pacific region: results from the Antimicrobial Testing Leadership and Surveillance (ATLAS) program, 2020 . International journal of antimicrobial agents 2023, 61 (2):106707. Li H, Ge M, Wang C: Spatio-temporal evolution patterns of influenza incidence and its nonlinear spatial correlation with environmental pollutants in China . BMC public health 2023, 23 (1):1685. Fan J, Cong S, Wang N, Bao H, Wang B, Feng Y, Lv X, Zhang Y, Zha Z, Yu L et al : Influenza vaccination rate and its association with chronic diseases in China: Results of a national cross-sectional study . Vaccine 2020, 38 (11):2503-2511. Wang Q, Yue N, Zheng M, Wang D, Duan C, Yu X, Zhang X, Bao C, Jin H: Influenza vaccination coverage of population and the factors influencing influenza vaccination in mainland China: A meta-analysis . Vaccine 2018, 36 (48):7262-7269. Fan J, Xu S, Liu Y, Ma X, Cao J, Fan C, Bao S: Influenza vaccination rates among healthcare workers: a systematic review and meta-analysis investigating influencing factors . Frontiers in public health 2023, 11 :1295464. Sarker A, Gu Z, Mao L, Ge Y, Hou D, Fang J, Wei Z, Wang Z: Influenza-existing drugs and treatment prospects . European journal of medicinal chemistry 2022, 232 :114189. Maggi S, Veronese N, Burgio M, Cammarata G, Ciuppa ME, Ciriminna S, Di Gennaro F, Smith L, Trott M, Dominguez LJ et al : Rate of Hospitalizations and Mortality of Respiratory Syncytial Virus Infection Compared to Influenza in Older People: A Systematic Review and Meta-Analysis . Vaccines 2022, 10 (12). Liu YN, Zhang YF, Xu Q, Qiu Y, Lu QB, Wang T, Zhang XA, Lin SH, Lv CL, Jiang BG et al : Infection and co-infection patterns of community-acquired pneumonia in patients of different ages in China from 2009 to 2020: a national surveillance study . The Lancet Microbe 2023, 4 (5):e330-e339. Chadha M, Hirve S, Bancej C, Barr I, Baumeister E, Caetano B, Chittaganpitch M, Darmaa B, Ellis J, Fasce R et al : Human respiratory syncytial virus and influenza seasonality patterns-Early findings from the WHO global respiratory syncytial virus surveillance . Influenza and other respiratory viruses 2020, 14 (6):638-646. Staadegaard L, Caini S, Wangchuk S, Thapa B, de Almeida WAF, de Carvalho FC, Fasce RA, Bustos P, Kyncl J, Novakova L et al : Defining the seasonality of respiratory syncytial virus around the world: National and subnational surveillance data from 12 countries . Influenza and other respiratory viruses 2021, 15 (6):732-741. See KC: Vaccination for Respiratory Syncytial Virus: A Narrative Review and Primer for Clinicians . Vaccines 2023, 11 (12). Ahmad A, Eze K, Noulin N, Horvathova V, Murray B, Baillet M, Grey L, Mori J, Adda N: EDP-938, a Respiratory Syncytial Virus Inhibitor, in a Human Virus Challenge . The New England journal of medicine 2022, 386 (7):655-666. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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2021.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-5311940/v1/17c0b9ae95d3578a9de93bb7.png"},{"id":68237943,"identity":"abad133f-7e16-4b02-8a20-0a21a65f2569","added_by":"auto","created_at":"2024-11-05 07:32:46","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":349732,"visible":true,"origin":"","legend":"\u003cp\u003eIn 2021, the numbers and rates of incidence, mortality, and DALYs of Lower Respiratory Infections by age and sex in China.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-5311940/v1/8c1ce5c0a05ab784523eb372.png"},{"id":68237944,"identity":"c473927a-c5ef-466c-a846-2ffdad4f6d43","added_by":"auto","created_at":"2024-11-05 07:32:46","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":643004,"visible":true,"origin":"","legend":"\u003cp\u003eChange of risk factors of Lower Respiratory Infections attributable to age-standardized mortality rates and age-standardized DALYs rates in China from 1990 to 2021.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-5311940/v1/d1974637c14c52e8286fb9f2.png"},{"id":68237947,"identity":"526a4a56-3e7c-46db-bad1-ec62a09d4f9c","added_by":"auto","created_at":"2024-11-05 07:32:46","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":250271,"visible":true,"origin":"","legend":"\u003cp\u003eProportion of Deaths (A) and DALYs (B) attributabe to risk factors by age and sex in 2021.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-5311940/v1/1014447f73a65bb0613052de.png"},{"id":68238771,"identity":"946b80d1-6639-4024-81b0-ff9842f932aa","added_by":"auto","created_at":"2024-11-05 07:40:46","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":865207,"visible":true,"origin":"","legend":"\u003cp\u003eAge-standardized DALY rates and age-standardized mortality rates attributed to lower respiratory infections from different etiologies in China from 1990 to 2021. (Other viral etiologies of LRI: The total of all viruses except for influenza and respiratory syncytial virus.)\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-5311940/v1/49c8cccdbe2eae216b0a9f1a.png"},{"id":68237948,"identity":"b8146990-9ef3-4785-b31d-d0c88d3fa715","added_by":"auto","created_at":"2024-11-05 07:32:46","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":300366,"visible":true,"origin":"","legend":"\u003cp\u003eThe trends in etiologies by gender and age group in China for 2021.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-5311940/v1/c1c831356d40e371e1bec92d.png"},{"id":70937545,"identity":"97ac2408-0c93-4efd-a753-4d6274c83b9c","added_by":"auto","created_at":"2024-12-09 11:17:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4521063,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5311940/v1/43ed4f26-0fdd-4cf3-8780-00f895e659cf.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Disease Burden of Non-COVID-19 Lower Respiratory Infections, Risk Factors, and Aetiologies in China 1990-2021: insights from the Global Burden of Disease Study 2021","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIn 2021, there were 344\u0026nbsp;million (95% UI: 325\u0026ndash;364) cases of lower respiratory infections globally, with 2.18\u0026nbsp;million (95% UI: 1.98\u0026ndash;2.36) deaths; both incidence and mortality rates remained high[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Before the outbreak of COVID-19, the age-standardized mortality ratio for lower respiratory infections among men and women worldwide was 1.31 (95% UI: 1.23\u0026ndash;1.41)[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. According to data from the World Health Organization (WHO), lower respiratory infections ranked as the fourth leading cause of death globally and the first among infectious diseases. In low-income countries, lower respiratory infections are the second leading cause of death, while in lower-middle-income and upper-middle-income countries, they rank fifth, and in high-income countries, they are the sixth leading cause of death[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe inability to identify pathogens, leading to imprecise drug treatment, is a significant reason for the high mortality rate of lower respiratory infections. Zhu et al. found that nearly half of patients with community-acquired pneumonia in China could not have their pathogens clearly identified. Among adults, the top three detected pathogens were Mycoplasma (15.01%), Streptococcus pneumoniae (11.68%), and Influenza A virus (12.28%). In children, the top three pathogens were Mycoplasma (19.16%), Respiratory Syncytial Virus (RSV) (16.01%), and Streptococcus pneumoniae (9.44%), with antibiotic resistance issues of Streptococcus pneumoniae being particularly severe[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Research statistics show that between 2000 and 2015, the global daily antibiotic consumption increased from 2.11\u0026nbsp;billion to 3.48\u0026nbsp;billion doses, representing a 65% increase. The antibiotic consumption rate rose from 11.3 doses per thousand residents per day to 15.7, marking a 39% increase. This growth is primarily contributed by low- and middle-income countries, while in high-income countries, although the antibiotic consumption has increased, the consumption rate has decreased by 4%[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn 2021, the number of deaths due to lower respiratory infections in China was 206,930.22 (95% UI: 171,260.88\u0026ndash;251,990.47), ranking second globally, imposing a heavy economic and financial burden on the government, patients, and society as a whole. The outbreak of the COVID-19 pandemic at the end of 2019 once again highlighted the severity and impact of lower respiratory infections, leading to a deeper public understanding of the prevention and treatment of these infections. Understanding the disease burden and epidemiological trends of lower respiratory infections in China is crucial for developing effective prevention and control policies. This study, based on the GBD 2021 database, investigated the incidence rate, mortality rate, and DALYs rate of lower respiratory infections in China, as well as the associated risk factors and etiologies, with the aim of providing a scientific basis for developing relevant prevention and management strategies.\u003c/p\u003e"},{"header":"Method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData sources\u003c/h2\u003e \u003cp\u003eThe relevant data on the disease burden of lower respiratory infections in China are sourced from the Institute for Health Metrics and Evaluation (IHME), a subsidiary of the University of Washington, through the Global Health Data Exchange (GHDx) platform (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://ghdx.healthdata.org/gbd-2021/data-input-sources\u003c/span\u003e\u003cspan address=\"https://ghdx.healthdata.org/gbd-2021/data-input-sources\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). GHDx is committed to assessing the disease burden of 371 diseases, injuries, and risk factors across 204 countries and regions globally. The database encompasses annual incidence, mortality, DALYs, etiology, and risk factor data spanning from 1990 to 2021. GBD 2021 data sources include population censuses, household surveys, healthcare service utilization, air pollution monitoring, satellite imagery, disease notifications, and more. The definition of LRI does not include tuberculosis, whooping cough, or COVID-19.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eAge-standardized rate\u003c/h3\u003e\n\u003cp\u003eAge standardization is a method used to compare data across different age groups, eliminating biases caused by variations in age structures. This involves selecting a standard population, calculating weights for each age group based on the standard population, and applying these weights to standardize the data. This standardization method helps to accurately compare features or indicators among different populations. The specific method for calculating ASR can be referred to in the methodologies reported in previous studies[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eDisability-adjusted life-years (DALYs)\u003c/h3\u003e\n\u003cp\u003eDALYs is a comprehensive health indicator utilized to assess the burden of diseases, injuries, and health conditions. The calculation of DALYs aims to integrate the impacts of Years of Life Lost (YLLs) resulting from premature mortality and Years Lived with Disability (YLDs) attributed to impaired health. Each year of lost health condition is quantified as one DALY.\u003c/p\u003e \u003cp\u003eThe formula for calculating DALYs is:\u003c/p\u003e \u003cp\u003eDALYs\u0026thinsp;=\u0026thinsp;YLLs\u0026thinsp;+\u0026thinsp;YLDs\u003c/p\u003e \u003cp\u003eWhere:\u003c/p\u003e \u003cp\u003eYLLs\u0026thinsp;=\u0026thinsp;N \u0026times; L\u003c/p\u003e \u003cp\u003eYLDs\u0026thinsp;=\u0026thinsp;I \u0026times; DW \u0026times; L\u003c/p\u003e \u003cp\u003eN is the number of premature deaths, L is the years of life lost per premature death, I is the number of individuals with disabilities, DW is the disability weight, representing the impact of disability on quality of life, L is the duration of disability in years.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe IHME Bayesian regression tool, DisMod-MR V.2.1, is employed for the analysis, modeling, and estimation of disease burden in the database. This tool helps mitigate uncertainties associated with original data sources, data processing, measurement errors, and model selection. The database covers indicators such as incidence, prevalence, mortality, and DALYs, providing 95% uncertainty intervals (UI) for direct statistical analysis. GraphPad 8.0.2 is used for creating graphical representations.\u003c/p\u003e \u003c/div\u003e"},{"header":"Result","content":"\u003cp\u003e \u003cb\u003eTrends in the Disease Burden of Lower Respiratory Infections in China from 1990 to 2021.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eIn the past 32 years, the number of incidence cases, ASIR, number of deaths, ASMR, number of DALYs, ASDAR for lower respiratory infections in males have consistently been higher than in females during the same period.\u003c/p\u003e \u003cp\u003eThe ASIR, ASMR, ASDAR, and number of DALY for both males and females show a declining trend. The number of incidence cases and deaths exhibits a trend of first decreasing and then increasing. Specifically, the lowest number of male incidence cases was 21,522,553.40 (95% UI: 20,249,110.7–22,971,324.91) in 2003, while the lowest number of female incidence cases was 19,412,410.22 (95% UI: 18,166,663.43-20,786,840.63) in 2008. The lowest number of male deaths was 105,552.84 (95% UI: 95,937.64–118,796.98) in 2012, and the lowest number of female deaths was 74,862.86 (95% UI: 62,238.40–97,107.14) in 2013 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eIn 1990 and 2021, the ASIR, ASMR, Age-Standardized DALYs Rate, and Percentage Change for LRI in China\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1990\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eChange (%)\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eASMR\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60.65\u003c/p\u003e \u003cp\u003e(52.96, 66.66)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.03\u003c/p\u003e \u003cp\u003e(11.68, 17.00)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.77\u003c/p\u003e \u003cp\u003e(-0.81, -0.71)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71.32\u003c/p\u003e \u003cp\u003e(64.39, 78.39)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.45\u003c/p\u003e \u003cp\u003e(17.14, 24.06)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.71\u003c/p\u003e \u003cp\u003e(-0.76, -0.65)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54.51\u003c/p\u003e \u003cp\u003e(43.40, 61.45)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.31\u003c/p\u003e \u003cp\u003e(7.90, 14.07)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.81\u003c/p\u003e \u003cp\u003e(-0.86, -0.73)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eASDAR\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,128.39\u003c/p\u003e \u003cp\u003e(2,724.11, 3,579.57)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e347.67\u003c/p\u003e \u003cp\u003e(301.28, 402.94)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.89\u003c/p\u003e \u003cp\u003e(-0.91, -0.86)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,340.53\u003c/p\u003e \u003cp\u003e(2,883.47, 3,810.16)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e445.70\u003c/p\u003e \u003cp\u003e(379.02, 515.46)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.87\u003c/p\u003e \u003cp\u003e(-0.89, -0.84)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,946.21\u003c/p\u003e \u003cp\u003e(2,542.50, 3,390.86)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e271.00\u003c/p\u003e \u003cp\u003e(223.85, 331.31)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.91\u003c/p\u003e \u003cp\u003e(-0.93, -0.88)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eASIR\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5,481.13\u003c/p\u003e \u003cp\u003e(5,149.05, 5,836.35)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,853.81\u003c/p\u003e \u003cp\u003e(2,663.94, 3,067.55)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.48\u003c/p\u003e \u003cp\u003e(-0.50, -0.45)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5,621.89\u003c/p\u003e \u003cp\u003e(5,285.09, 5,997.34)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3,118.18\u003c/p\u003e \u003cp\u003e(2,914.12, 3,353.68)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.45\u003c/p\u003e \u003cp\u003e(-0.47, -0.42)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5,411.27\u003c/p\u003e \u003cp\u003e(5,073.27, 5,786.22)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,664.57\u003c/p\u003e \u003cp\u003e(2,485.61, 2,870.23)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.51\u003c/p\u003e \u003cp\u003e(-0.53, -0.48)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003eAbbreviations: ASIR, age-standardized incidence rate; ASMR, age-standardized mortality rate; ASDAR, age-standardized disability-adjusted life years rate.\u003c/p\u003e \u003cp\u003e \u003cb\u003eThe Disease Burden of Lower Respiratory Infections in China in 2021.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eIn 2021, the highest number of incidence cases of lower respiratory infections in China was in the 80 + age group (11,496,755.71, 95% UI: 10,093,516.62-13,040,461.38), followed by the 5–9 age group (2,757,299.77, 95% UI: 2,074,692.93-3,607,662.369) and the \u0026lt; 5 age group (2,398,985.20, 95% UI: 1,997,575.87-2,834,649.53). Except for the 80 + age group, the number of incidence cases for all other age groups in females was lower than in males.\u003c/p\u003e \u003cp\u003eThe incidence rate of lower respiratory infections decreases with increasing age, reaching its lowest point in the 35–39 age group (844.21, 95% UI: 668.03-1,033.84), and then increases again. The number of deaths, mortality rate, number of DALYs, and DALY rate all initially decrease and then increase with age, peaking in the 80 + age group (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eTrends in Risk Factors for Lower Respiratory Infections in China from 1990 to 2021.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eWe selected the nine main risk factors related to lower respiratory infections from the GBD 2021 database, which include ambient particulate matter pollution, non-exclusive breastfeeding, secondhand smoke, child growth failure, low temperature, low birth weight and short gestation, no access to handwashing facilities, smoking, and household air pollution from solid fuels.\u003c/p\u003e \u003cp\u003eThe study indicates that in 1990, the burden of ASMR for lower respiratory infections was primarily attributed to three risk factors: household air pollution from solid fuels, child growth failure, and secondhand smoke. By 2021, the main risk factors for this burden had shifted to ambient particulate matter pollution, smoking, and low temperature. The top three risk factors contributing to the burden of ASDAR changed from child growth failure, household air pollution from solid fuels, and secondhand smoke to ambient particulate matter pollution, child growth failure, and secondhand smoke.\u003c/p\u003e \u003cp\u003eCompared to 1990, the disease burden caused by the nine risk factors decreased in 2021. For females, the burdens of ASMR from secondhand smoke and ASDAR from household air pollution from solid fuels fell below those for males after 1996 and 1993, respectively. For the remaining seven risk factors, the disease burden for females was consistently lower than that for males at any given time (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eRisk Factors for Lower Respiratory Infections in China in 2021.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eWe compared the differences in risk factors between genders and age groups and found that child growth failure, low birth weight and short gestation, and non-exclusive breastfeeding are specific risk factors for the \u0026lt; 5 age group, while smoking is a specific risk factor for individuals over 30. The disease burden from smoking and secondhand smoke is more strongly correlated with age in males, and the impact of smoking on males is significantly greater than on females (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eThe changing trends in the etiology of lower respiratory infections in China from 1990 to 2021.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe GBD 2021 database includes 18 pathogens associated with lower respiratory infections. Compared to 1990, the disease burden from all pathogens decreased in 2021. In the 30 years leading up to 2019, the three pathogens with the highest mortality rates were Streptococcus pneumoniae, Staphylococcus aureus, and Influenza. After 2019, the burden from Influenza significantly decreased, while other viral etiologies of LRI rose to the third position.\u003c/p\u003e \u003cp\u003eIn 1990, the three pathogens with the highest age-standardized DALY rates were Streptococcus pneumoniae, Influenza, and other viral etiologies of LRI. After 2004, Staphylococcus aureus surpassed Influenza, and other viral etiologies rose to the second position. In 2019, after a significant decrease in Influenza, it was surpassed by other viral etiologies (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eThe etiology of lower respiratory infections in China in 2021.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eWe presented the distribution of mortality rates and DALY rates attributed to 18 pathogens across different genders and age groups. The results show that the distribution of mortality rates and DALY rates associated with pathogens related to lower respiratory infections exhibits similar characteristics and trends across different age groups: they decrease with increasing age, reach a low point in adulthood, and then increase again.\u003c/p\u003e \u003cp\u003eThe mortality rate for all pathogens is highest in the 80 + age group, followed by the \u0026lt; 5 age group. The DALY rates for RSV and polymicrobial infections are highest in the \u0026lt; 5 age group, followed by the 80 + age group, while the DALY rates for the remaining pathogens are highest in the 80 + age group and then in the \u0026lt; 5 age group. Additionally, for all pathogens, the mortality and DALY rates for females are lower than those for males in the same age group (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e "},{"header":"Discussion","content":"\u003cp\u003eThe GBD 2021 database provides relevant data on the disease burden of 371 diseases and injuries across 204 countries and regions, as well as 811 subnational areas. This includes data on incidence, prevalence, DALYs, years of life lost (YLLs), years lived with disability (YLDs), healthy life expectancy (HALE), risk factors, and etiologies[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. We extracted and analyzed relevant data on lower respiratory infections in China and found that in 2021, the number of incidence cases, the incidence rates, the number of deaths, the mortality rates, the number of DALYs, and the DALY rates for lower respiratory infections have all decreased compared to 32 years ago. However, due to the large population base and the increasing aging population, the reduction in the number of incidence cases is not significant compared to other indicators, and the annual number of new cases remains a substantial burden. Due to various factors such as seasonality, geographical variations, and population demographics, there are significant differences in the prevalence patterns and pathogen spectra of lower respiratory infections among different countries globally and within different regions of a country[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. A retrospective study covering 23 provinces in mainland China found that the incidence of community-acquired pneumonia in urban populations decreases in the summer and autumn seasons, rises in the winter, and peaks in the spring. Provinces in the eastern and northeastern regions exhibit higher incidence rates compared to those in the southern regions. The age groups with the highest incidence are individuals under 5 years old and those over 80 years old[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Another multicenter prospective study discovered that between 2001 and 2005, bacterial infections predominantly caused community-acquired pneumonia (CAP) in Chinese adults, whereas from 2009 to 2016, there was a significant increase in the proportion of viral infections[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Therefore, understanding the local epidemiology, pathogen spectrum, and associated risk factors of lower respiratory tract infections is crucial for precisely formulating prevention and control strategies, as well as for the rational allocation of medical resources.\u003c/p\u003e\u003cp\u003eWe observed that the incidence and mortality of lower respiratory infections in males are higher than in females. This can be attributed to the fact that females exhibit a stronger cellular and humoral immune response[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Studies have found that estrogen can regulate various immune cells, including macrophages, T cells, natural killer cells, and B cells[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Additionally, estrogen promotes the expression of immunoglobulin G (IgG) and immunoglobulin M (IgM), while testosterone inhibits this expression[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. There is also research indicating that estrogen can mediate the upregulation of endothelial nitric oxide synthase (eNOS) transcription, enhancing the production of nitric oxide (NO), resulting in higher levels of nitric oxide in females compared to males[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Nitric oxide is a gaseous component in the immune system that contributes to clearing pathogens and foreign substances from the body, inhibiting viral replication[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. In addition, the proportion of smoking and alcohol consumption is higher in males than in females, contributing to a higher susceptibility to lower respiratory infections in males. Numerous studies have confirmed the correlation between smoking, alcohol consumption, and respiratory infections[\u003cspan additionalcitationids=\"CR17 CR18\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e–\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Exposure to tobacco smoke and nicotine in utero and postnatally can disrupt lung development, increasing susceptibility to lower respiratory tract infections and the prevalence of wheezing[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. In a prospective cohort study conducted by He and colleagues, it was found that Chinese school-age children exposed to secondhand smoke showed an increased incidence of cough and decreased lung function compared to children not exposed[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Another study indicated that exposure to secondhand smoke significantly increased the risk of lower respiratory tract infections and decreased lung function in children. When both parents smoked, the risk of infants developing lower respiratory tract infections increased by 1.82 times. If the fetus was exposed to maternal smoking during pregnancy, the risk of developing lower respiratory tract infections increased by 1.19 times[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. McEvoy and colleagues conducted a randomized controlled trial, revealing that offspring of smoking pregnant women who received vitamin C during gestation exhibited better lung function in the first year of life compared to those born to smoking pregnant women without treatment. However, the mechanism of the potential protective effects of vitamin C on prenatal smoking exposure remains unclear[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Excessive alcohol consumption can weaken both the innate and adaptive immune systems, and individuals who are intoxicated often experience aspiration, thereby increasing the likelihood of lower respiratory infections[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. A recent network meta-analysis indicates that alcohol exposure may enhance the inflammation induced by COVID-19 by boosting inflammatory effects and suppressing the activity of anti-inflammatory mediators, including glucocorticoid receptors[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Two additional meta-analyses have found a proportional relationship between alcohol consumption and the risk of lower respiratory infections. On average, for each additional daily drink, the risk of lower respiratory tract infections increases by 8% (95% CI 6–9%) and 6% (95% CI 1–11%) [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. To reduce the harmful effects of smoking and alcohol consumption, countries around the world are actively implementing measures such as increasing taxes on tobacco and alcohol, raising the legal purchasing age, banning smoking in public places, restricting tobacco advertising and promotions, and promoting smoking and alcohol cessation education[\u003cspan additionalcitationids=\"CR28 CR29\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e–\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eApart from smoking and alcohol, the GBD database also covers other risk factors related to lower respiratory infections, such as child growth failure, air pollution, non-optimal temperature, and lack of access to handwashing facilities. Hand hygiene and access to handwashing facilities play a crucial role in controlling the spread of various infectious diseases, including lower respiratory infections. Handwashing effectively reduces the transmission of pathogens, thereby lowering the incidence of common infectious diseases such as respiratory infections and diarrhea. In particular, within healthcare settings, hand hygiene controls nosocomial infections, reduces the spread of drug-resistant pathogens, and plays a vital role in public health emergencies. Enhancing hand hygiene education and increasing access to handwashing facilities help improve overall community hygiene and are essential components of global health[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. The incidence of lower respiratory infections is closely related to seasonal changes and temperature. The virulence of pathogens is usually associated with their biological characteristics and the immune capacity of the host. Studies have found that most common respiratory pathogens, such as Streptococcus pneumoniae, influenza virus, and RSV, typically have higher incidence rates in winter. Additionally, the human immune system also exhibits seasonal variations, often becoming more vulnerable in the winter [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Another time-series study found that a greater diurnal temperature range is associated with increased outpatient visits for acute lower respiratory infections, pneumonia, and bronchiolitis in children, and this phenomenon is more pronounced during the rainy season[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Additionally, research by Sonego et al. suggests that compared to well-nourished children with pneumonia, those with moderate malnutrition have a 2.46-fold higher risk of mortality, while those with severe malnutrition have a 4.27-fold higher risk[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Household air pollution can pose serious hazards to the respiratory system[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. A four-year time-series analysis covering over 4.2\u0026nbsp;million pneumonia hospitalization cases in 184 Chinese cities reveals that, nationwide, a 10 µg/m3 increase in the 3-day moving average concentrations of PM2.5 and PM10 is associated with a 0.31% and 0.19% rise in pneumonia hospitalization numbers, respectively[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Our analysis shows that over the past thirty-two years, the disease burden caused by various risk factors has been declining. This is attributed to several factors, including China’s rapid economic development, accelerated infrastructure construction, significant improvements in population nutrition levels, the promotion of clean energy usage, the widespread adoption of air conditioning and air purification systems, and the continuous strengthening of air pollution control efforts.\u003c/p\u003e\u003cp\u003eIn 2021, the global number of deaths from lower respiratory infections was 2.18\u0026nbsp;million (95% UI: 1.98–2.36), with Streptococcus pneumoniae accounting for 505,000 deaths (95% UI: 454,000-555,000). In China, Streptococcus pneumoniae was responsible for 51,179 deaths (95% UI: 42,055–62,158) from lower respiratory infections[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], making it the pathogen with the highest disease burden from lower respiratory infections in the country. Due to the high incidence and mortality rates caused by pneumococcal-induced lower respiratory tract infections, it is crucial not only to select sensitive antibiotics through susceptibility testing but also to prioritize vaccination with the pneumococcal conjugate vaccine[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Research predicts that administering the pneumococcal vaccine can prevent 34% of global infection-related deaths[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], the \"Global Pneumonia Action Plan\" recommends countries to undertake large-scale vaccination efforts targeting pneumococcal infections. As of 2019, the global coverage rate of pneumococcal conjugate vaccines for infants is approximately 47.9%[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. In mainland China, the pneumococcal vaccine coverage rate among the population is 21.7%, and there is currently no available data on vaccine coverage specifically for Chinese children. However, due to the current absence of the pneumococcal vaccine in China's national immunization program and variations in awareness, there are significant differences in vaccination coverage among local families, migrant families, and left-behind families[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Our study found that, compared to 1990, the incidence and mortality rates of pneumococcal lower respiratory infections in China have significantly decreased. However, there has been a rising trend since 2019, making it crucial to enhance diagnostic capabilities and strengthen vaccination efforts.\u003c/p\u003e\u003cp\u003eStaphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter spp. belong to the ESKAPE pathogens, known for their ability to \"escape\" treatment from various common antibiotics, including broad-spectrum antibiotics. They pose significant risks, especially in hospital-acquired infections, increasing infection-related mortality and length of hospitalization, thus presenting substantial challenges for clinical treatment[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. In recent years, the global prevalence of Staphylococcus aureus has been on the rise, particularly methicillin-resistant Staphylococcus aureus (MRSA), with isolation rates exceeding 40% in regions such as Tibet, Shanghai, and Jiangsu. Due to effective antimicrobial stewardship in China, the resistance rate of MRSA to trimethoprim-sulfamethoxazole has decreased from 20.1–6.4% in recent years (now lower than the 15% seen in methicillin-susceptible Staphylococcus aureus), and the resistance rate to rifampicin has dropped from 58% in 2010 to around 3.7% in 2022[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. As of 2022, the resistance rates of Klebsiella pneumoniae in China to tigecycline, polymyxin, and ceftazidime-avibactam were 2.6%, 2.8%, and 6.2%, respectively. The resistance rates to imipenem and meropenem have increased from 8.8% and 8.9% in 2010 to 22.6% and 24.2% in 2022, respectively. Meanwhile, the clinical isolation rate of carbapenem-resistant Klebsiella pneumoniae (CRKP) rose from 4.9% in 2013 to 9.0% in 2017, with the isolation rate in Shanghai increasing to 26.9%. High resistance rates are mainly concentrated in eastern China[\u003cspan additionalcitationids=\"CR46 CR47\" citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e–\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. In China, the resistance of Pseudomonas aeruginosa to most antibiotics has shown a generally stable or declining trend. Specifically, the isolation rates of imipenem and meropenem-resistant strains decreased from 30.8% and 25.8% in 2010 to 22.1% and 17.6% in 2022[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. An earlier study indicated that the detection rate of carbapenem-resistant Pseudomonas aeruginosa (CRPA) in Canada was the lowest at 3.3%, while resistance rates in countries such as Russia, Brazil, Greece, and Saudi Arabia exceeded 50%, with China's resistance rate around 35%[\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Additionally, a meta-analysis involving 7,951 cases across 16 countries showed that the highest prevalence of multidrug-resistant (MDR) Pseudomonas aeruginosa causing ventilator-associated pneumonia (VAP) was found in Iran at 87.5% (95% CI: 69-95.7%), followed by China at 85.3% (95% CI: 79.3–89.8%), while the lowest rate was observed in the United States at 19.7% (95% CI: 18.6–20.7%)[\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. In 2022, Enterobacter species ranked fifth in isolation rates among Gram-negative bacteria in China, with the lowest resistance rates to amikacin and tigecycline at 1.6% and 1.9%, respectively. The resistance rate to imipenem was 9.7%, while the resistance rate to cefotaxime reached as high as 96%[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Enterobacter species typically include Enterobacter cloacae, Enterobacter aerogenes, Enterobacter asburiae, Enterobacter hormaechei, and Enterobacter kobei, with Enterobacter cloacae being the most commonly encountered in clinical settings. A study by Zhang et al. found that carbapenem-resistant Enterobacter cloacae in China had susceptibility rates to colistin, amikacin, ciprofloxacin, fosfomycin, and tigecycline of 93.8%, 62.5%, 25.0%, 35.3%, and 6.8%, respectively. The resistance rates to amoxicillin-clavulanic acid, cefotaxime, ceftazidime, imipenem, and meropenem were all over 91%[\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. The infection rate of Acinetobacter baumannii is lower compared to other ESKAPE pathogens; however, approximately 45% of Acinetobacter baumannii strains globally are considered multidrug-resistant, with resistance rates exceeding 60% in the United States. According to WTO statistics, the level of multidrug resistance in Acinetobacter baumannii is over four times that of Klebsiella pneumoniae and Pseudomonas aeruginosa[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. A study by Chen et al. found that drug-resistant Acinetobacter baumannii in China exhibits broad resistance characteristics, with the highest sensitivity to polymyxins and tigecycline; however, compared to other countries in the Asia-Pacific region, the Acinetobacter baumannii isolates in China have the lowest sensitivity to tigecycline[\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Our study found that the trend in the disease burden of the aforementioned five pathogens is similar to that of Streptococcus pneumoniae, showing a gradual decline before 2019, followed by a slight rebound thereafter. The significant decrease in mortality and DALY rates reflects the effectiveness of medical interventions and public health measures, but attention must still be paid to changes in resistance rates.\u003c/p\u003e\u003cp\u003eInfluenza in most regions of China exhibits a seasonal pattern, with more outbreaks occurring in the fall and winter seasons. The incidence decreases noticeably after March. Since 2007, the incidence of influenza in China has gradually increased, with a particularly significant rise observed between 2013 and 2017[\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. Research indicates that the influenza vaccination rate among the population aged 40 and above in mainland China is 2.4%[\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. Another study points out that as of March 2018, influenza vaccine coverage in the population of mainland China peaked between 2009 and 2010[\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. Fan et al. analyzed the influenza vaccination rates among healthcare personnel globally and found that, in the decades leading up to 2023, the global influenza vaccination rate for healthcare personnel was 41.7%, with the highest rate in the Americas (67.1%), the lowest in Africa (6.5%), and a rate of 28.5% in Asia. The highest vaccination rate occurred from 2020 to 2023, reaching 52.8%. The second-highest rate was observed from 2009 to 2012 at 46.7%, while the lowest rate was recorded between 2017 and 2019 at 31.4%[\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. This may be attributed to the H1N1 influenza pandemic (2009 to 2010) and the COVID-19 outbreak, which have driven vaccine uptake. Our study found that since the outbreak of COVID-19 in 2019, the DALY rates and mortality rates for influenza have significantly decreased, which aligns with the findings of the aforementioned studies. Currently, antiviral drugs approved by the United States Food and Drug Administration (FDA) and recommended for clinical treatment of influenza include neuraminidase inhibitors (NAIs) such as oseltamivir, zanamivir, and peramivir, as well as viral RNA polymerase inhibitors such as baloxavir, favipiravir, and pimodivir. However, there have been reports of resistance to oseltamivir in certain viruses[\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eRSV has shown a significant decline in disease burden similar to that of influenza since 2019. A systematic review by Maggi et al. found that the hospitalization and mortality rates for RSV and influenza among older adults are comparable[\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. A study by Liu et al. suggests that RSV is the most common pathogen in severe community-acquired pneumonia among children in China[\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. Our study similarly found that RSV is the only pathogen, aside from polymicrobial infections, that has a higher mortality rate in children compared to older adults. The prevalence of RSV infections typically follows a seasonal pattern, with outbreaks commonly occurring in the northern hemisphere between October and May of the following year, and in the southern hemisphere between May and September. In tropical regions, RSV outbreaks often occur during the rainy season, with a weaker correlation to specific seasons[\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. Due to the lack of specific antiviral medications, adults can typically receive vaccinations to prevent RSV infection. For infants, there are currently no available vaccines, so maternal vaccination during pregnancy can be employed. This process generates antibodies in the mother, which are then transferred to the fetus through the placenta, providing protective effects. Alternatively, immunoprophylaxis can be achieved in infants using monoclonal antibodies such as Palivizumab and Nirsevimab[\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. Due to the lack of market approval for the mentioned drugs in mainland China, medical institutions in mainland China typically resort to symptomatic supportive treatment when dealing with lower respiratory tract infections caused by RSV. Additionally, recent clinical trials have demonstrated the efficacy of EDP-938 (a Respiratory Syncytial Virus Inhibitor) in reducing viral load and alleviating clinical symptoms, suggesting significant therapeutic potential[\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn addition to the common pathogens mentioned above, we also analyzed the trends in disease burden caused by pathogens such as Haemophilus influenzae, Mycoplasma, Escherichia coli, and fungi. The study found that since 2019, aside from influenza and RSV, the ASMR and ASDAR associated with other pathogens have shown an increase. However, compared to 1990, the overall burden of disease related to all pathogens has declined. Nevertheless, the spread of antibiotic resistance remains a major threat to global health. To address this challenge, it is essential to develop new antimicrobial drugs and vaccines, use existing medications judiciously, strengthen infection prevention and control measures, and establish a global monitoring and data-sharing system to quickly identify and respond to the spread of resistant bacteria.\u003c/p\u003e\u003cp\u003eThis study has several limitations. The Global Burden of Disease (GBD) relies on health data collected by various countries, but there are significant differences in data collection standards and capabilities, especially in low- and middle-income countries, which often lack comprehensive disease monitoring and reporting systems. This results in insufficient or inaccurate data, affecting the precision of the research findings. Due to the incompleteness of global data, the statistical models used for data prediction in the GBD may produce errors or biases and may not adequately reflect the health status of specific regions. Additionally, the GBD typically assesses the impact of each risk factor independently, failing to fully capture their synergistic or exacerbating effects. The study lacks specific data from different provinces, ethnic groups, and quarters.\u003c/p\u003e\u003cp\u003eIn summary, due to improvements in healthcare, the number of deaths and the ASMR from lower respiratory infections in China have shown a declining trend from 1990 to 2021. However, the decrease in the number of incidence cases is not as pronounced due to the increasing aging population. Household air pollution from solid fuels is the most effectively controlled risk factor, primarily due to the gradual replacement of wood and charcoal with cleaner energy sources for household fuel. Smoking shows the greatest gender disparity among risk factors, while child growth failure and smoking are the primary risk factors for children under 5 and individuals over 30, respectively. Streptococcus pneumoniae remains the leading pathogen for lower respiratory infections in China, with the most notable decline in disease burden, while RSV has a greater impact on children than on older adults. Therefore, it is essential to strengthen epidemiological research on lower respiratory infections in the Chinese population and implement differentiated management and targeted prevention strategies.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe foundation of this research lies in the publicly accessible data provided by the Global Burden of Disease Study 2021. The data is available for free download from the IHME data repository (http://ghdx.healthdata.org/gbd-results-tool) without the need for any download permissions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors convey their thanks to the Global Burden of Disease Study team for furnishing the data, allowing us to carry out our research without hindrance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors affirm the absence of any conflicts of interest in this work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBJG, GWC, MLC, and JJL were involved in the design of this study. JLM and RXH were responsible for the extraction and analysis of data. BJG, ZML, QLJ, and XQL contributed to the interpretation of analysis results. BJG, GWC, RXH, JJL, and MLC participated in writing the first draft of this article. BJG, JLM, ZML, and QLJ revised the manuscript. All authors approved the submitted manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funding was received for this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed Consent Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInstitutional Review Board Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data utilized in this study underwent anonymization prior to usage. All methodologies were executed in alignment with pertinent guidelines and regulations.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003e\u003cstrong\u003eGlobal, regional, and national incidence and mortality burden of non-COVID-19 lower respiratory infections and aetiologies, 1990-2021: a systematic analysis from the Global Burden of Disease Study 2021\u003c/strong\u003e. \u003cem\u003eThe Lancet Infectious diseases \u003c/em\u003e2024, \u003cstrong\u003e24\u003c/strong\u003e(9):974-1002.\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eAge-sex differences in the global burden of lower respiratory infections and risk factors, 1990-2019: results from the Global Burden of Disease Study 2019\u003c/strong\u003e. \u003cem\u003eThe Lancet Infectious diseases \u003c/em\u003e2022, \u003cstrong\u003e22\u003c/strong\u003e(11):1626-1647.\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eThe top 10 causes of death \u003c/strong\u003e[https://www.who.int/zh/news-room/fact-sheets/detail/the-top-10-causes-of-death]\u003c/li\u003e\n\u003cli\u003eZhu YG, Tang XD, Lu YT, Zhang J, Qu JM: \u003cstrong\u003eContemporary Situation of Community-acquired Pneumonia in China: A Systematic Review\u003c/strong\u003e. \u003cem\u003eJournal of translational internal medicine \u003c/em\u003e2018, \u003cstrong\u003e6\u003c/strong\u003e(1):26-31.\u003c/li\u003e\n\u003cli\u003eKlein EY, Van Boeckel TP, Martinez EM, Pant S, Gandra S, Levin SA, Goossens H, Laxminarayan R: \u003cstrong\u003eGlobal increase and geographic convergence in antibiotic consumption between 2000 and 2015\u003c/strong\u003e. \u003cem\u003eProceedings of the National Academy of Sciences of the United States of America \u003c/em\u003e2018, \u003cstrong\u003e115\u003c/strong\u003e(15):E3463-e3470.\u003c/li\u003e\n\u003cli\u003eLiu Z, Jiang Y, Yuan H, Fang Q, Cai N, Suo C, Jin L, Zhang T, Chen X: \u003cstrong\u003eThe trends in incidence of primary liver cancer caused by specific etiologies: Results from the Global Burden of Disease Study 2016 and implications for liver cancer prevention\u003c/strong\u003e. \u003cem\u003eJournal of hepatology \u003c/em\u003e2019, \u003cstrong\u003e70\u003c/strong\u003e(4):674-683.\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eGlobal incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021\u003c/strong\u003e. \u003cem\u003eLancet (London, England) \u003c/em\u003e2024, \u003cstrong\u003e403\u003c/strong\u003e(10440):2133-2161.\u003c/li\u003e\n\u003cli\u003eFeldman C, Shaddock E: \u003cstrong\u003eEpidemiology of lower respiratory tract infections in adults\u003c/strong\u003e. \u003cem\u003eExpert review of respiratory medicine \u003c/em\u003e2019, \u003cstrong\u003e13\u003c/strong\u003e(1):63-77.\u003c/li\u003e\n\u003cli\u003eSun Y, Li H, Pei Z, Wang S, Feng J, Xu L, Gao P, Cao B, Zhan S: \u003cstrong\u003eIncidence of community-acquired pneumonia in urban China: A national population-based study\u003c/strong\u003e. \u003cem\u003eVaccine \u003c/em\u003e2020, \u003cstrong\u003e38\u003c/strong\u003e(52):8362-8370.\u003c/li\u003e\n\u003cli\u003eZhou F, Wang Y, Liu Y, Liu X, Gu L, Zhang X, Pu Z, Yang G, Liu B, Nie Q\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eDisease severity and clinical outcomes of community-acquired pneumonia caused by non-influenza respiratory viruses in adults: a multicentre prospective registry study from the CAP-China Network\u003c/strong\u003e. \u003cem\u003eThe European respiratory journal \u003c/em\u003e2019, \u003cstrong\u003e54\u003c/strong\u003e(2).\u003c/li\u003e\n\u003cli\u003eFish EN: \u003cstrong\u003eThe X-files in immunity: sex-based differences predispose immune responses\u003c/strong\u003e. \u003cem\u003eNature reviews Immunology \u003c/em\u003e2008, \u003cstrong\u003e8\u003c/strong\u003e(9):737-744.\u003c/li\u003e\n\u003cli\u003eKlein SL, Marriott I, Fish EN: \u003cstrong\u003eSex-based differences in immune function and responses to vaccination\u003c/strong\u003e. \u003cem\u003eTransactions of the Royal Society of Tropical Medicine and Hygiene \u003c/em\u003e2015, \u003cstrong\u003e109\u003c/strong\u003e(1):9-15.\u003c/li\u003e\n\u003cli\u003eRuggieri A, Anticoli S, D\u0026apos;Ambrosio A, Giordani L, Viora M: \u003cstrong\u003eThe influence of sex and gender on immunity, infection and vaccination\u003c/strong\u003e. \u003cem\u003eAnnali dell\u0026apos;Istituto superiore di sanita \u003c/em\u003e2016, \u003cstrong\u003e52\u003c/strong\u003e(2):198-204.\u003c/li\u003e\n\u003cli\u003eMacRitchie AN, Jun SS, Chen Z, German Z, Yuhanna IS, Sherman TS, Shaul PW: \u003cstrong\u003eEstrogen upregulates endothelial nitric oxide synthase gene expression in fetal pulmonary artery endothelium\u003c/strong\u003e. \u003cem\u003eCirculation research \u003c/em\u003e1997, \u003cstrong\u003e81\u003c/strong\u003e(3):355-362.\u003c/li\u003e\n\u003cli\u003eSaura M, Zaragoza C, McMillan A, Quick RA, Hohenadl C, Lowenstein JM, Lowenstein CJ: \u003cstrong\u003eAn antiviral mechanism of nitric oxide: inhibition of a viral protease\u003c/strong\u003e. \u003cem\u003eImmunity \u003c/em\u003e1999, \u003cstrong\u003e10\u003c/strong\u003e(1):21-28.\u003c/li\u003e\n\u003cli\u003eRosoff DB, Yoo J, Lohoff FW: \u003cstrong\u003eSmoking is significantly associated with increased risk of COVID-19 and other respiratory infections\u003c/strong\u003e. \u003cem\u003eCommunications biology \u003c/em\u003e2021, \u003cstrong\u003e4\u003c/strong\u003e(1):1230.\u003c/li\u003e\n\u003cli\u003eGergen PJ, Fowler JA, Maurer KR, Davis WW, Overpeck MD: \u003cstrong\u003eThe burden of environmental tobacco smoke exposure on the respiratory health of children 2 months through 5 years of age in the United States: Third National Health and Nutrition Examination Survey, 1988 to 1994\u003c/strong\u003e. \u003cem\u003ePediatrics \u003c/em\u003e1998, \u003cstrong\u003e101\u003c/strong\u003e(2):E8.\u003c/li\u003e\n\u003cli\u003eOberg M, Jaakkola MS, Woodward A, Peruga A, Pr\u0026uuml;ss-Ust\u0026uuml;n A: \u003cstrong\u003eWorldwide burden of disease from exposure to second-hand smoke: a retrospective analysis of data from 192 countries\u003c/strong\u003e. \u003cem\u003eLancet (London, England) \u003c/em\u003e2011, \u003cstrong\u003e377\u003c/strong\u003e(9760):139-146.\u003c/li\u003e\n\u003cli\u003eMorojele NK, Shenoi SV, Shuper PA, Braithwaite RS, Rehm J: \u003cstrong\u003eAlcohol Use and the Risk of Communicable Diseases\u003c/strong\u003e. \u003cem\u003eNutrients \u003c/em\u003e2021, \u003cstrong\u003e13\u003c/strong\u003e(10).\u003c/li\u003e\n\u003cli\u003eHerring MJ, Putney LF, Wyatt G, Finkbeiner WE, Hyde DM: \u003cstrong\u003eGrowth of alveoli during postnatal development in humans based on stereological estimation\u003c/strong\u003e. \u003cem\u003eAmerican journal of physiology Lung cellular and molecular physiology \u003c/em\u003e2014, \u003cstrong\u003e307\u003c/strong\u003e(4):L338-344.\u003c/li\u003e\n\u003cli\u003eHe QQ, Wong TW, Du L, Jiang ZQ, Yu TS, Qiu H, Gao Y, Wong AH, Liu WJ, Wu JG: \u003cstrong\u003eEnvironmental tobacco smoke exposure and Chinese schoolchildren\u0026apos;s respiratory health: a prospective cohort study\u003c/strong\u003e. \u003cem\u003eAmerican journal of preventive medicine \u003c/em\u003e2011, \u003cstrong\u003e41\u003c/strong\u003e(5):487-493.\u003c/li\u003e\n\u003cli\u003eJayes L, Haslam PL, Gratziou CG, Powell P, Britton J, Vardavas C, Jimenez-Ruiz C, Leonardi-Bee J: \u003cstrong\u003eSmokeHaz: Systematic Reviews and Meta-analyses of the Effects of Smoking on Respiratory Health\u003c/strong\u003e. \u003cem\u003eChest \u003c/em\u003e2016, \u003cstrong\u003e150\u003c/strong\u003e(1):164-179.\u003c/li\u003e\n\u003cli\u003eMcEvoy CT, Schilling D, Clay N, Jackson K, Go MD, Spitale P, Bunten C, Leiva M, Gonzales D, Hollister-Smith J\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eVitamin C supplementation for pregnant smoking women and pulmonary function in their newborn infants: a randomized clinical trial\u003c/strong\u003e. \u003cem\u003eJama \u003c/em\u003e2014, \u003cstrong\u003e311\u003c/strong\u003e(20):2074-2082.\u003c/li\u003e\n\u003cli\u003eHuang W, Zhou H, Hodgkinson C, Montero A, Goldman D, Chang SL: \u003cstrong\u003eNetwork Meta-Analysis on the Mechanisms Underlying Alcohol Augmentation of COVID-19 Pathologies\u003c/strong\u003e. \u003cem\u003eAlcoholism, clinical and experimental research \u003c/em\u003e2021, \u003cstrong\u003e45\u003c/strong\u003e(4):675-688.\u003c/li\u003e\n\u003cli\u003eSamokhvalov AV, Irving HM, Rehm J: \u003cstrong\u003eAlcohol consumption as a risk factor for pneumonia: a systematic review and meta-analysis\u003c/strong\u003e. \u003cem\u003eEpidemiology and infection \u003c/em\u003e2010, \u003cstrong\u003e138\u003c/strong\u003e(12):1789-1795.\u003c/li\u003e\n\u003cli\u003eSimou E, Britton J, Leonardi-Bee J: \u003cstrong\u003eAlcohol and the risk of pneumonia: a systematic review and meta-analysis\u003c/strong\u003e. \u003cem\u003eBMJ open \u003c/em\u003e2018, \u003cstrong\u003e8\u003c/strong\u003e(8):e022344.\u003c/li\u003e\n\u003cli\u003eMehrotra R, Yadav A, Sinha DN, Parascandola M, John RM, Ayo-Yusuf O, Nargis N, Hatsukami DK, Warnakulasuriya S, Straif K\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eSmokeless tobacco control in 180 countries across the globe: call to action for full implementation of WHO FCTC measures\u003c/strong\u003e. \u003cem\u003eThe Lancet Oncology \u003c/em\u003e2019, \u003cstrong\u003e20\u003c/strong\u003e(4):e208-e217.\u003c/li\u003e\n\u003cli\u003eSornpaisarn B, Shield KD, Cohen JE, Schwartz R, Rehm J: \u003cstrong\u003eCan pricing deter adolescents and young adults from starting to drink: An analysis of the effect of alcohol taxation on drinking initiation among Thai adolescents and young adults\u003c/strong\u003e. \u003cem\u003eJournal of epidemiology and global health \u003c/em\u003e2015, \u003cstrong\u003e5\u003c/strong\u003e(4 Suppl 1):S45-57.\u003c/li\u003e\n\u003cli\u003eLimaye RJ, Srirojn B, Lilleston P, Aramrattana A, Thomson N, Celentano DD, Sherman SG: \u003cstrong\u003eA qualitative exploration of the effects of increasing the minimum purchase age of alcohol in Thailand\u003c/strong\u003e. \u003cem\u003eDrug and alcohol review \u003c/em\u003e2013, \u003cstrong\u003e32\u003c/strong\u003e(1):100-105.\u003c/li\u003e\n\u003cli\u003eMarynak K, Mahoney M, Williams KS, Tynan MA, Reimels E, King BA: \u003cstrong\u003eState and Territorial Laws Prohibiting Sales of Tobacco Products to Persons Aged \u0026lt;21 Years - United States, December 20, 2019\u003c/strong\u003e. \u003cem\u003eMMWR Morbidity and mortality weekly report \u003c/em\u003e2020, \u003cstrong\u003e69\u003c/strong\u003e(7):189-192.\u003c/li\u003e\n\u003cli\u003eAiello AE, Coulborn RM, Perez V, Larson EL: \u003cstrong\u003eEffect of hand hygiene on infectious disease risk in the community setting: a meta-analysis\u003c/strong\u003e. \u003cem\u003eAmerican journal of public health \u003c/em\u003e2008, \u003cstrong\u003e98\u003c/strong\u003e(8):1372-1381.\u003c/li\u003e\n\u003cli\u003ePittet D, Allegranzi B, Sax H, Dharan S, Pessoa-Silva CL, Donaldson L, Boyce JM: \u003cstrong\u003eEvidence-based model for hand transmission during patient care and the role of improved practices\u003c/strong\u003e. \u003cem\u003eThe Lancet Infectious diseases \u003c/em\u003e2006, \u003cstrong\u003e6\u003c/strong\u003e(10):641-652.\u003c/li\u003e\n\u003cli\u003eFares A: \u003cstrong\u003eFactors influencing the seasonal patterns of infectious diseases\u003c/strong\u003e. \u003cem\u003eInternational journal of preventive medicine \u003c/em\u003e2013, \u003cstrong\u003e4\u003c/strong\u003e(2):128-132.\u003c/li\u003e\n\u003cli\u003eMirsaeidi M, Motahari H, Taghizadeh Khamesi M, Sharifi A, Campos M, Schraufnagel DE: \u003cstrong\u003eClimate Change and Respiratory Infections\u003c/strong\u003e. \u003cem\u003eAnnals of the American Thoracic Society \u003c/em\u003e2016, \u003cstrong\u003e13\u003c/strong\u003e(8):1223-1230.\u003c/li\u003e\n\u003cli\u003eZhang Z, Xu D, Chen J, Meng Q, Liang Z, Zhang X: \u003cstrong\u003eDaily diurnal temperature range associated with outpatient visits of acute lower respiratory infection in children: A time-series study in Guangzhou, China\u003c/strong\u003e. \u003cem\u003eFrontiers in public health \u003c/em\u003e2022, \u003cstrong\u003e10\u003c/strong\u003e:951590.\u003c/li\u003e\n\u003cli\u003eSonego M, Pellegrin MC, Becker G, Lazzerini M: \u003cstrong\u003eRisk factors for mortality from acute lower respiratory infections (ALRI) in children under five years of age in low and middle-income countries: a systematic review and meta-analysis of observational studies\u003c/strong\u003e. \u003cem\u003ePloS one \u003c/em\u003e2015, \u003cstrong\u003e10\u003c/strong\u003e(1):e0116380.\u003c/li\u003e\n\u003cli\u003eGordon SB, Bruce NG, Grigg J, Hibberd PL, Kurmi OP, Lam KB, Mortimer K, Asante KP, Balakrishnan K, Balmes J\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eRespiratory risks from household air pollution in low and middle income countries\u003c/strong\u003e. \u003cem\u003eThe Lancet Respiratory medicine \u003c/em\u003e2014, \u003cstrong\u003e2\u003c/strong\u003e(10):823-860.\u003c/li\u003e\n\u003cli\u003eTian Y, Liu H, Wu Y, Si Y, Li M, Wu Y, Wang X, Wang M, Chen L, Wei C\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eAmbient particulate matter pollution and adult hospital admissions for pneumonia in urban China: A national time series analysis for 2014 through 2017\u003c/strong\u003e. \u003cem\u003ePLoS medicine \u003c/em\u003e2019, \u003cstrong\u003e16\u003c/strong\u003e(12):e1003010.\u003c/li\u003e\n\u003cli\u003eWaight PA, Andrews NJ, Ladhani SN, Sheppard CL, Slack MP, Miller E: \u003cstrong\u003eEffect of the 13-valent pneumococcal conjugate vaccine on invasive pneumococcal disease in England and Wales 4 years after its introduction: an observational cohort study\u003c/strong\u003e. \u003cem\u003eThe Lancet Infectious diseases \u003c/em\u003e2015, \u003cstrong\u003e15\u003c/strong\u003e(5):535-543.\u003c/li\u003e\n\u003cli\u003eChen C, Cervero Liceras F, Flasche S, Sidharta S, Yoong J, Sundaram N, Jit M: \u003cstrong\u003eEffect and cost-effectiveness of pneumococcal conjugate vaccination: a global modelling analysis\u003c/strong\u003e. \u003cem\u003eThe Lancet Global health \u003c/em\u003e2019, \u003cstrong\u003e7\u003c/strong\u003e(1):e58-e67.\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eMeasuring routine childhood vaccination coverage in 204 countries and territories, 1980-2019: a systematic analysis for the Global Burden of Disease Study 2020, Release 1\u003c/strong\u003e. \u003cem\u003eLancet (London, England) \u003c/em\u003e2021, \u003cstrong\u003e398\u003c/strong\u003e(10299):503-521.\u003c/li\u003e\n\u003cli\u003eZhou Y, Li D, Cao Y, Lai F, Wang Y, Long Q, Zhang Z, An C, Xu X: \u003cstrong\u003eImmunization coverage, knowledge, satisfaction, and associated factors of non-National Immunization Program vaccines among migrant and left-behind families in China: evidence from Zhejiang and Henan provinces\u003c/strong\u003e. \u003cem\u003eInfectious diseases of poverty \u003c/em\u003e2023, \u003cstrong\u003e12\u003c/strong\u003e(1):93.\u003c/li\u003e\n\u003cli\u003eShao W, Chen X, Zheng C, Wang G, Zhang B, Zhang W: \u003cstrong\u003ePneumococcal vaccination coverage and willingness in mainland China\u003c/strong\u003e. \u003cem\u003eTropical medicine \u0026amp; international health : TM \u0026amp; IH \u003c/em\u003e2022, \u003cstrong\u003e27\u003c/strong\u003e(10):864-872.\u003c/li\u003e\n\u003cli\u003eMiller WR, Arias CA: \u003cstrong\u003eESKAPE pathogens: antimicrobial resistance, epidemiology, clinical impact and therapeutics\u003c/strong\u003e. \u003cem\u003eNature reviews Microbiology \u003c/em\u003e2024, \u003cstrong\u003e22\u003c/strong\u003e(10):598-616.\u003c/li\u003e\n\u003cli\u003ePaterson DL, Bonomo RA: \u003cstrong\u003eExtended-spectrum beta-lactamases: a clinical update\u003c/strong\u003e. \u003cem\u003eClinical microbiology reviews \u003c/em\u003e2005, \u003cstrong\u003e18\u003c/strong\u003e(4):657-686.\u003c/li\u003e\n\u003cli\u003eLuo Q, Lu P, Chen Y, Shen P, Zheng B, Ji J, Ying C, Liu Z, Xiao Y: \u003cstrong\u003eESKAPE in China: epidemiology and characteristics of antibiotic resistance\u003c/strong\u003e. \u003cem\u003eEmerging microbes \u0026amp; infections \u003c/em\u003e2024, \u003cstrong\u003e13\u003c/strong\u003e(1):2317915.\u003c/li\u003e\n\u003cli\u003eChen D, Li H, Zhao Y, Qiu Y, Xiao L, He H, Zheng D, Li X, Huang L, Yu X\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eCharacterization of carbapenem-resistant Klebsiella pneumoniae in a tertiary hospital in Fuzhou, China\u003c/strong\u003e. \u003cem\u003eJournal of applied microbiology \u003c/em\u003e2020, \u003cstrong\u003e129\u003c/strong\u003e(5):1220-1226.\u003c/li\u003e\n\u003cli\u003eHu Y, Liu C, Shen Z, Zhou H, Cao J, Chen S, Lv H, Zhou M, Wang Q, Sun L\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003ePrevalence, risk factors and molecular epidemiology of carbapenem-resistant Klebsiella pneumoniae in patients from Zhejiang, China, 2008-2018\u003c/strong\u003e. \u003cem\u003eEmerging microbes \u0026amp; infections \u003c/em\u003e2020, \u003cstrong\u003e9\u003c/strong\u003e(1):1771-1779.\u003c/li\u003e\n\u003cli\u003eHong DJ, Bae IK, Jang IH, Jeong SH, Kang HK, Lee K: \u003cstrong\u003eEpidemiology and Characteristics of Metallo-\u0026beta;-Lactamase-Producing Pseudomonas aeruginosa\u003c/strong\u003e. \u003cem\u003eInfection \u0026amp; chemotherapy \u003c/em\u003e2015, \u003cstrong\u003e47\u003c/strong\u003e(2):81-97.\u003c/li\u003e\n\u003cli\u003eLi Y, Roberts JA, Walker MM, Aslan AT, Harris PNA, Sime FB: \u003cstrong\u003eThe global epidemiology of ventilator-associated pneumonia caused by multi-drug resistant Pseudomonas aeruginosa: A systematic review and meta-analysis\u003c/strong\u003e. \u003cem\u003eInternational journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases \u003c/em\u003e2024, \u003cstrong\u003e139\u003c/strong\u003e:78-85.\u003c/li\u003e\n\u003cli\u003eZhang R, Liu L, Zhou H, Chan EW, Li J, Fang Y, Li Y, Liao K, Chen S: \u003cstrong\u003eNationwide Surveillance of Clinical Carbapenem-resistant Enterobacteriaceae (CRE) Strains in China\u003c/strong\u003e. \u003cem\u003eEBioMedicine \u003c/em\u003e2017, \u003cstrong\u003e19\u003c/strong\u003e:98-106.\u003c/li\u003e\n\u003cli\u003eMagill SS, Edwards JR, Bamberg W, Beldavs ZG, Dumyati G, Kainer MA, Lynfield R, Maloney M, McAllister-Hollod L, Nadle J\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eMultistate point-prevalence survey of health care-associated infections\u003c/strong\u003e. \u003cem\u003eThe New England journal of medicine \u003c/em\u003e2014, \u003cstrong\u003e370\u003c/strong\u003e(13):1198-1208.\u003c/li\u003e\n\u003cli\u003eLob SH, Hoban DJ, Sahm DF, Badal RE: \u003cstrong\u003eRegional differences and trends in antimicrobial susceptibility of Acinetobacter baumannii\u003c/strong\u003e. \u003cem\u003eInternational journal of antimicrobial agents \u003c/em\u003e2016, \u003cstrong\u003e47\u003c/strong\u003e(4):317-323.\u003c/li\u003e\n\u003cli\u003eChen CH, Wu PH, Lu MC, Ho MW, Hsueh PR: \u003cstrong\u003eGeographic patterns of carbapenem-resistant, multi-drug-resistant and difficult-to-treat Acinetobacter baumannii in the Asia-Pacific region: results from the Antimicrobial Testing Leadership and Surveillance (ATLAS) program, 2020\u003c/strong\u003e. \u003cem\u003eInternational journal of antimicrobial agents \u003c/em\u003e2023, \u003cstrong\u003e61\u003c/strong\u003e(2):106707.\u003c/li\u003e\n\u003cli\u003eLi H, Ge M, Wang C: \u003cstrong\u003eSpatio-temporal evolution patterns of influenza incidence and its nonlinear spatial correlation with environmental pollutants in China\u003c/strong\u003e. \u003cem\u003eBMC public health \u003c/em\u003e2023, \u003cstrong\u003e23\u003c/strong\u003e(1):1685.\u003c/li\u003e\n\u003cli\u003eFan J, Cong S, Wang N, Bao H, Wang B, Feng Y, Lv X, Zhang Y, Zha Z, Yu L\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eInfluenza vaccination rate and its association with chronic diseases in China: Results of a national cross-sectional study\u003c/strong\u003e. \u003cem\u003eVaccine \u003c/em\u003e2020, \u003cstrong\u003e38\u003c/strong\u003e(11):2503-2511.\u003c/li\u003e\n\u003cli\u003eWang Q, Yue N, Zheng M, Wang D, Duan C, Yu X, Zhang X, Bao C, Jin H: \u003cstrong\u003eInfluenza vaccination coverage of population and the factors influencing influenza vaccination in mainland China: A meta-analysis\u003c/strong\u003e. \u003cem\u003eVaccine \u003c/em\u003e2018, \u003cstrong\u003e36\u003c/strong\u003e(48):7262-7269.\u003c/li\u003e\n\u003cli\u003eFan J, Xu S, Liu Y, Ma X, Cao J, Fan C, Bao S: \u003cstrong\u003eInfluenza vaccination rates among healthcare workers: a systematic review and meta-analysis investigating influencing factors\u003c/strong\u003e. \u003cem\u003eFrontiers in public health \u003c/em\u003e2023, \u003cstrong\u003e11\u003c/strong\u003e:1295464.\u003c/li\u003e\n\u003cli\u003eSarker A, Gu Z, Mao L, Ge Y, Hou D, Fang J, Wei Z, Wang Z: \u003cstrong\u003eInfluenza-existing drugs and treatment prospects\u003c/strong\u003e. \u003cem\u003eEuropean journal of medicinal chemistry \u003c/em\u003e2022, \u003cstrong\u003e232\u003c/strong\u003e:114189.\u003c/li\u003e\n\u003cli\u003eMaggi S, Veronese N, Burgio M, Cammarata G, Ciuppa ME, Ciriminna S, Di Gennaro F, Smith L, Trott M, Dominguez LJ\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eRate of Hospitalizations and Mortality of Respiratory Syncytial Virus Infection Compared to Influenza in Older People: A Systematic Review and Meta-Analysis\u003c/strong\u003e. \u003cem\u003eVaccines \u003c/em\u003e2022, \u003cstrong\u003e10\u003c/strong\u003e(12).\u003c/li\u003e\n\u003cli\u003eLiu YN, Zhang YF, Xu Q, Qiu Y, Lu QB, Wang T, Zhang XA, Lin SH, Lv CL, Jiang BG\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eInfection and co-infection patterns of community-acquired pneumonia in patients of different ages in China from 2009 to 2020: a national surveillance study\u003c/strong\u003e. \u003cem\u003eThe Lancet Microbe \u003c/em\u003e2023, \u003cstrong\u003e4\u003c/strong\u003e(5):e330-e339.\u003c/li\u003e\n\u003cli\u003eChadha M, Hirve S, Bancej C, Barr I, Baumeister E, Caetano B, Chittaganpitch M, Darmaa B, Ellis J, Fasce R\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eHuman respiratory syncytial virus and influenza seasonality patterns-Early findings from the WHO global respiratory syncytial virus surveillance\u003c/strong\u003e. \u003cem\u003eInfluenza and other respiratory viruses \u003c/em\u003e2020, \u003cstrong\u003e14\u003c/strong\u003e(6):638-646.\u003c/li\u003e\n\u003cli\u003eStaadegaard L, Caini S, Wangchuk S, Thapa B, de Almeida WAF, de Carvalho FC, Fasce RA, Bustos P, Kyncl J, Novakova L\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eDefining the seasonality of respiratory syncytial virus around the world: National and subnational surveillance data from 12 countries\u003c/strong\u003e. \u003cem\u003eInfluenza and other respiratory viruses \u003c/em\u003e2021, \u003cstrong\u003e15\u003c/strong\u003e(6):732-741.\u003c/li\u003e\n\u003cli\u003eSee KC: \u003cstrong\u003eVaccination for Respiratory Syncytial Virus: A Narrative Review and Primer for Clinicians\u003c/strong\u003e. \u003cem\u003eVaccines \u003c/em\u003e2023, \u003cstrong\u003e11\u003c/strong\u003e(12).\u003c/li\u003e\n\u003cli\u003eAhmad A, Eze K, Noulin N, Horvathova V, Murray B, Baillet M, Grey L, Mori J, Adda N: \u003cstrong\u003eEDP-938, a Respiratory Syncytial Virus Inhibitor, in a Human Virus Challenge\u003c/strong\u003e. \u003cem\u003eThe New England journal of medicine \u003c/em\u003e2022, \u003cstrong\u003e386\u003c/strong\u003e(7):655-666.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Lower Respiratory Infection, Global Burden of Disease, risk factors, DALYs, Etiology","lastPublishedDoi":"10.21203/rs.3.rs-5311940/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5311940/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eLower respiratory infections (LRI) are the highest mortality diseases among infectious diseases globally, with China ranking second in the incidence and mortality of lower respiratory infections in 2021. This study, based on GBD 2021, investigates the burden of lower respiratory infections, risk factors, and etiologies in China from 1990 to 2021.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis study analyzes the trends in the disease burden of lower respiratory infections in China from 1990 to 2021, categorized by gender, age, and year, and explores the attributable mortality and disability-adjusted life years (DALYs) rates related to the risk factors and aetiologies associated with lower respiratory infections.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eCompared to 1990, the age-standardized incidence rate (ASIR), age-standardized mortality rate (ASMR), and age-standardized DALY rate (ASDAR) of lower respiratory infections in China decreased by 48%, 77%, and 89% in 2021. Ambient particulate matter pollution surpassed household air pollution from solid fuels to become the leading risk factor. Despite the significant decline, Streptococcus pneumoniae remains the primary pathogen associated with lower respiratory infections.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe disease burden of lower respiratory infections in China has significantly decreased over the past 32 years, but there is still a need to strengthen air pollution control, enhance tobacco regulation, and focus on the health of the elderly population. In response to the changes in the pathogen spectrum, it is necessary to improve detection capabilities and develop new antimicrobial drugs and vaccines.\u003c/p\u003e","manuscriptTitle":"Disease Burden of Non-COVID-19 Lower Respiratory Infections, Risk Factors, and Aetiologies in China 1990-2021: insights from the Global Burden of Disease Study 2021","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-05 07:32:41","doi":"10.21203/rs.3.rs-5311940/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"03d8320c-5f33-470a-9ec8-ca340ce3d380","owner":[],"postedDate":"November 5th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-12-09T11:09:02+00:00","versionOfRecord":[],"versionCreatedAt":"2024-11-05 07:32:41","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5311940","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5311940","identity":"rs-5311940","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}