Contrasting Tracheal, Bronchus, and Lung Cancer Burdens and Care Quality: A Comparative Analysis of China and Global Trends 

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Additionally, changes in attributable risk factors and the quality of care were evaluated. Methods Based on data from the Fujian Provincial Center for Disease Control and Prevention and the Global Burden of Disease (GBD), the age-standardized rates (ASRs) of incidence, death, and disability-adjusted life years (DALY) were collected and analyzed. Joinpoint regression analysis and age-period-cohort models were used to estimate temporal trends, and principal component analysis is used to estimate the quality-of-care index (QCI). Results In 2019, the ASRs of incidence, death, and DALYs in 2019 were 39.08, 35.29, and 778.39 per 100,000 in Fujian Province, respectively. From 1990 to 2019, ASRs increased, with average annual percent changes (AAPCs) of 1.08 (95% confidence interval [CI]: 0.77 to 1.38), 0.65 (95% CI: 0.35 to 0.95), and 0.18 (95% CI: -0.07 to 0.42), respectively. When analyzed age, the burden sharply increased after age 50. By gender, the ASRs of male incidence, death, and DALY in Fujian Province were all over 3-folds higher than in females. However, females burden showed increasing trend from 2015 to 2019. While DALY ASRs attributed to ambient particulate matter pollution increased significantly, solid fuels in households decreased compared to 1990. Moreover, we founded that QCI increased with age. The temporal trends indicated decrease in QCI from 1990 to 2019. Conclusion The burden of tracheal, bronchus, and lung cancer in Fujian Province remained significant. Smoking, secondhand smoke, and ambient particulate matter pollution were the main risk factors. The quality of care for patients needed improvement. Lung cancer disease burden temporal trend prediction risk factor quality of care Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Research in context Evidence before this study We searched using the keywords “lung cancer”, “disease burden” and “epidemiology” in the PubMed and China National Knowledge Infrastructure (CNKI) databases, with the search timeframe spanning from 1997 to 2023. Previous studies had been conducted at global and national levels. In China, it was the cancer with the highest incidence and mortality rate. However, some studies indicated that there were regional disparities in lung cancer burden, with relatively higher mortality rates in the eastern regions of China. Nevertheless, to our knowledge, there had been no epidemiological studies analyzing the lung cancer burden in Fujian Province using such comprehensive indicators. Therefore, it was necessary to conduct a thorough analysis of the disease burden and its temporal trends across different age and gender groups. Additionally, we searched the PubMed and CNKI databases using the keywords "lung cancer" and "quality of care", with the search period ranging from 1983 to 2023. The majority of studies focused on the quality of surgical care for lung cancer patients or analyzed quality of life surveys on a small number of lung cancer patients. The estimation of the quality of care outcomes for the entire lung cancer population remained unknown. Added value of this study This study utilized the surveillance data from Fujian Province and GBD 2019 to analyze the temporal trends in the incidence, death and DALY of tracheal, bronchus and lung cancer. Furthermore, projections of disease burden from 2020 to 2050 were analyzed. Compared with 2019, the ASR of incidence, death, and DALY may decrease by 19.47%, 46.33%, and 4.77% in Fujian Province, respectively. Additionally, we identified changes in the burden of attributable risk factors for tracheal, bronchus and lung cancer. In particular, the ASR of DALY attributable to household air pollution from solid fuels decreased substantially. The ASR of DALY attributable to ambient particulate matter pollution increased substantially in Fujian Province and China. Lastly, the QCI was used to assess the quality of care. Fujian Province experienced the largest decrease, dropping from 49.27 in 1990 to 40.00 in 2019. Implications of all the available evidence In conclusion, this study identified the epidemiological trends of tracheal, bronchus and lung cancer in the Fujian province, with the disease burden remaining severe. Predictions for future trends and assessments of the quality of care may facilitate the development of future medical strategies and more effective allocation of healthcare resources. It was deemed necessary to focus on the disease burden attributable to smoking, secondhand smoke, and environmental pollution, in order to formulate targeted public health policies and intervention measures. Introduction The five-year survival rate for lung cancer has ranged from 4–17%, depending on stage and regional differences [ 1 ]. The International Agency for Research on Cancer reported in 2020 that lung cancer ranks second in the global cancer incidence spectrum and first in the cancer mortality spectrum [ 2 ], and tracheal, bronchus, and lung cancer disability-adjusted life-years (DALY) rank second globally early-onset cancer [ 3 ]. In China, lung cancer remains the leading cancer in terms of both incidence and mortality rates [ 4 ], imposing a major public health issue. However, the disease burden varies significantly across different regions and periods, which is associated with many factors. Fujian Province is located in the southeastern coastal province of China. Other scholars have indicated that the incidence of lung cancer in Fujian Province was increasing, and it belonged to the province with higher lung cancer incidence in China [ 5 ]. Therefore, it is necessary to understand the epidemiological trends of lung cancer in Fujian Province and analyze the disease burden among different populations at different times. Additionally, the etiology of lung cancer is complex, with modifiable independent risk factors including smoking, occupational history, exposure to air particulate matter and so on [ 6 ]. Comprehensive the contribution of attributable risk factors to the burden of lung cancer can assist policymakers in formulating accurate policies and measures. The quality of healthcare services also influenced the disease burden. A review study had indicated that healthcare disparities were associated with race, socioeconomic status, and overall level of risk [ 7 ]. Previously, lung cancer was observed to have a higher risk level among males, but now there is an increasing number of cases among non-smoking females each year [ 8 ]. Whether healthcare disparities exist between different genders remains unknown. One study designed a method to examine the care outcomes for tumors in various countries, the Quality-of-Care Index (QCI) [ 9 ]. This index had been validated in multiple cancers and serves as an indicator of effective healthcare access [ 10 , 11 ]. Currently, there is few research systematically quantifying and comparing the disparities in quality of care among different patients for lung cancer. Therefore, this study analyzed the temporal trends in the incidence, death and DALY of tracheal, bronchus and lung cancer in Fujian Province, China and globally. Furthermore, we identified changes in the attributable risk factors for tracheal, bronchus and lung cancer, which could aid in updating comprehensive prevention policies. Lastly, the QCI was used to assess the quality of care among lung cancer populations to assessment of healthcare equity. Materials and Methods Study data This study assessed the burden of tracheal, bronchus and lung cancer in Fujian Province, China, and globally using age-standardized rates (ASRs) for incidence, death, and DALY. Data for Fujian Province were sourced from our institution and submitted to the Global Burden of Disease Study 2019 (GBD 2019) Collaboration Group. The same standardized methodology as GBD 2019 was used. China and global data were obtained from GBD 2019. The GBD 2019 database is publicly available, and data on incidence, death, DALY, years of life lost (YLL), years lived with disability (YLD), and risk factors were downloaded via the Global Health Data Exchange query tool ( http://ghdx.healthdata.org/gbd-results-tool ). Sources included epidemiological research, cause of death reporting systems, disease surveillance sites, and maternal and child surveillance systems [ 12 , 13 ]. DisMod-MR 2.1, a Bayesian meta-regression tool, was used for systematic assessment [ 13 ]. Detailed data processing methods are available on the GBD website and previous reports [ 13 – 16 ]. Joinpoint regression model We used the average annual percent change (AAPC) to estimate temporal trends in the burden of tracheal, bronchus and lung cancer from 1990 to 2019 by joinpoint regression model. AAPC, defined as the geometrically weighted average of annual percent changes (APCs), described the trends in ASRs [ 17 , 18 ]. AAPC use the segmented APCs to summarise and compare the ASRs of change over time and identify long-term trends in the ASRs, even if they are unstable [ 19 ]. Positive AAPC values with lower 95% confidence intervals (CI) indicate increasing trends, while negative values with upper 95% CIs indicate descending trends. The calculation involved establishing a linear relationship between the natural logarithm of ASRs and periods, identifying significant joinpoints, calculating APC for each segment, and then computing the geometrically weighted average of APCs to obtain AAPCs [ 20 ]. The National Cancer Institute’s Joinpoint Regression Analysis software (version 5.0.2) was used, applying the Monte Carlo method for significance testing and Bonferroni correction [ 17 ]. Age-period-cohort analysis Age-period-cohort model was used in this study to show the temporal trends in rates for tracheal, bronchus and lung cancer by age, period and cohort. By adjusting for age, period, and cohort, the independent effects were analyzed [ 21 , 22 ]. This study utilized the age-period-cohort model to decompose the variations in incidence, death, and DALY rates into age, period (year), and cohort (birth year) effects. Age and period were analyzed in 5-year intervals ranging from 10 to 95 years, periods from 1990 to 2019, and successive cohorts (period-age) from 1900 to 2009. Furthermore, rate ratios (RRs) were calculated for each period and cohort to summarize the relative risks of tracheal, bronchus and lung cancer incidence, death, and DALY rates compared to the overall average rates. The estimable functions in the age-period-cohort model were validated through the Wald chi-square test [ 21 ]. This analysis was performed using the RStudio software (version 4.2.2). Predicting the burden through 2050 Population projections for 2050 were sourced from the United Nations Department of Economic and Social Affairs Population Division for global and China’s data [ 23 ]. For Fujian Province, projections by Chen et al were used [ 24 ], focusing on the Shared Socioeconomic Pathways (SSPs) scenarios 2, which closely align with current trends in Fujian. Bayesian age-period-cohort (BAPC) forecasting method, proposed by Andrea Riebler et al. [ 25 ], was utilized to predict future ASRs from 2020 to 2050 under a fully Bayesian inference setting. The BAPC package in the RStudio (version 4.2.2) facilitated these forecasts. QCI and GDR This study was described the quality of care by age and gender differences from 1990 to 2019. Four secondary indicators were computed and combined to estimate the QCI, which was explained in detail in previous studies [ 9 , 11 ]. Firstly, the four secondary indicators were calculated: Mortality-to-Incidence Ratio (MIR), Prevalence-to-Incidence Ratio, DALYs-to- Prevalence Ratio, and Years of Life Lost (YLL)-to-Years Lived with Disability (YLD) Ratio. Secondly, the first and second principal components were extracted from these four indicators using Principal Component Analysis (PCA) to compute the QCI. The PCA was conducted using RStudio software (version 4.2.2). Finally, it was adjusted to a scale of 0 to 100, where higher scores indicate better quality of care. More detailed statistical analysis processes can be found in the Table S2. Furthermore, the Gender Disparity Ratio (GDR) was calculated using the formula: \(\:GDR\:=\:\frac{QCI\left(females\right)}{QCI\left(males\right)}\) . The GDR was used to describe gender inequality in quality of care. Results Disease burden of tracheal, bronchus and lung cancer in 2019 In 2019, the numbers of total incident cases, death cases, and DALYs of tracheal, bronchus and lung cancer in Fujian Province were 20.07 (95% uncertainty interval [UI]: 15.73 to 25.13) thousand, 17.71 (95% UI: 13.87 to 21.99) thousand, and 414.36 (95% UI: 324.41 to 523.88) thousand, respectively (Table 1 ). From 1990 to 2019, the number of cases continuously increasing (Fig. 1 ). The ASRs of incidence, death, and DALY in 2019 were 39.08 (95% UI: 30.91 to 49.05), 35.29 (95% UI: 27.69 to 43.63), and 778.39 (95% UI: 610.86 to 978.74) per 100,000 in Fujian Province, respectively (Table 1 ). From 1990 to 2019, the ASRs of incidence, death and DALY were fluctuated, with AAPCs of 1.08 (95% CI: 0.77 to 1.38), 0.65 (95% CI: 0.35 to 0.95) and 0.18 (95% CI: -0.07 to 0.42), respectively. In general, the ASRs were increasing trends. The most dramatic increased occurred between 1998–2002 (incidence APC: 4.41, 95% CI: 2.43 to 6.42; death APC: 4.25, 95% CI: 2.30 to 6.23; DALY APC: 3.27, 95% CI: 2.39 to 4.15) (Table S1 and Figure S2). During 2010–2014, ASRs showed decreased trends, notably in death (APC: -1.11, 95% CI: -2.03 to -0.17) and DALY (APC: -1.69, 95% CI: -2.53 to -0.85). However, ASRs of incidence increased again during 2014–2019 (APC: 0.82, 95% CI: 0.39 to 1.25). Table 1 Number of incidences, deaths and DALYs, ASRs (per 100,000 population) and AAPCs (Both) in Fujian Province, China and Global, 1990 and 2019 Variable Incidence Deaths DALYs Numbers (95% UI) ASR (95% UI) AAPC (95% CI) Numbers (95% UI) ASR (95% UI) AAPC (95% CI) Numbers (95% UI) ASR (95% UI) AAPC (95% CI) Global 1990 1124006.07 (1077618.40, 1176491.42) 28.39 (27.18, 29.67) -0.08 (-0.24, 0.08) 1065138.99 (1019216.81, 1117181.48) 27.30 (26.03, 28.59) -0.27 (-0.39, -0.14) 27122576.95 (25859878.00, 28498448.16) 657.98 (628.28, 690.83) -0.60 (-0.72, -0.48) 2019 2259998.15 (2067316.08, 2451832.04) 27.66 (25.28, 29.99) 2042639.74 (1879241.24, 2193268.97) 25.18 (23.16, 27.01) 45857963.48 (42297425.07, 49339875.98) 551.58 (508.97, 593.12) China 1990 257044.68 (221285.90, 293647.85) 30.20 (26.20, 34.26) 1.15 (0.92, 1.38) 256325.53 (221055.12, 294555.60) 31.18 (27.14, 35.52) 0.77 (0.54, 1.00) 6960865.13 (5966957.99, 8039127.12) 760.68 (654.28, 875.37) 0.31 (0.11, 0.51) 2019 832922.16 (700293.15, 981631.63) 41.71 (35.22, 48.80) 757171.25 (638741.18, 887751.81) 38.70 (32.80, 45.03) 17128584.02 (14340490.76, 20231342.32) 831.27 (699.11, 979.99) Fujian 1990 5905.75 (4800.08, 7166.54) 28.67 (23.64, 34.49) 1.08 (0.77, 1.38) 5835.69 (4747.01, 7081.30) 29.30 (24.27, 34.91) 0.65 (0.35, 0.95) 162681.24 (129561.46, 199195.10) 742.13 (596.69, 901.47) 0.18 (-0.07, 0.42) 2019 20067.21 (15726.70, 25132.89) 39.08 (30.91, 49.05) 17712.88 (13872.85, 21992.47) 35.29 (27.69, 43.63) 414363.88 (324406.68, 523878.63) 778.39 (610.86, 978.74) Nationally, China's 2019 burden was higher than Fujian's, with ASRs per 100,000 of 41.71 (95% UI: 32.22 to 48.80) for incidence, 38.70 (95% UI: 32.80 to 45.03) for death, and 831.27 (95% UI: 699.11 to 979.99) for DALY (Table 1 ). From 1990 to 2019, the ASRs of incidence, death and DALY showed an increased trend in China (Figure S1 ). The corresponding AAPCs were 1.15 (95% CI: 0.92 to 1.38), 0.77 (95% CI: 0.54 to 1.00), and 0.31 (95% CI: 0.11 to 0.51) (Table 1 ). In terms of segmented joinpoint periods, the trends in China were similar to Fujian Province (Figure S3). Globally, the 2019 ASRs per 100,000 were 27.66 (95%UI: 25.28 to 29.99) for incidence, 25.18 (95% UI: 23.16 to 27.01) for death, and 551.58 (95% UI: 508.97 to 593.12) for DALY (Table 1 ). From 1990 to 2019, global ASRs declined with AAPCs of -0.08 (95% CI: -0.24 to -0.08), -0.27 (95% CI: -0.39 to -0.14) and − 0.60 (95% CI: -0.72 to -0.48) for incidence, death, and DALY, respectively. Incidence and death ASRs showed a linear decline, while DALY ASR increased before 2003 and declined after 2009 (Figure S4). Age-period-cohort analyses Figure 2 A illustrated the trends of incidence, death and DALY rates across different age groups in Fujian Province from 1990 to 2019. Incidence rates notably increased among those aged over 70, with the highest rates (over 300 per 100,000) observed in the 85–89, 80–84, and 75–79 age groups during 2015–2019. Death rates for these age groups exceeded 200 per 100,000 in the same period. The highest DALY rates shifted from the 70–74 age group (1990–2014) to the 75–79 age group (2015–2019). Post-2005, DALY rates consistently rose for the over-75 age groups, while declining for the younger. Figure 2 B highlights that incidence, death, and DALY rates began increasing significantly after age 50 in all periods, remaining higher in recent years for older age groups. Figure 2 C shows cohort-based variations, with continuous increases in incidence, death, and DALY rates among those over 75 in later-born cohorts. For the 50–74 age groups, DALY rates initially rose before declining in later-born cohorts. Differences between males and females Both at the global level, national level and Fujian Province, the burden of tracheal, bronchus and lung cancer were much higher for males than females. In Fujian Province, ASR of incidence for males was 3.03-fold higher than females, ASR of death was 3.18-fold higher, and ASR of DALY was 3.03-fold higher in 2019 (Table 2 ). From 1990 to 2019, most ASRs increased, exception of the ASR for female DALY. The AAPCs of ASRs for both genders in China from 1990 to 2019 were similar to those of Fujian province, with slightly higher AAPCs compared to Fujian province. Similarly, the ASRs of incidence, death and DALY in males showed decreased trends between 1990 and 2019 in global. Instead, females showed increased trends, with AAPCs of 0.69 (95% CI: 0.63 to 0.76), 0.47 (95% CI: 0.41 to 0.52) and 0.17 (95% CI: 0.12 to 0.22). The results for gender-specific effects owing to period and cohort using the Poisson log-linear model were shown in Fig. 3 . For males, the period effects on incidence, death and DALY rates were peaked in 2005–2009, with RRs of 1.03 (95% CI: 1.01 to 1.05), 1.04 (95% CI: 1.02 to 1.06) and 1.05 (95% CI: 1.045 to 1.052) in Fujian, respectively (Fig. 3 A, C and E). Post-2009, these period effects showed declining trends. By 2015–2019, RRs of males incidence, death, and DALY rates were below 0, indicating reduced risks. In contrast, females risk of incidence, death, and DALY peaked in 2015–2019, with RRs of 1.04 (95% CI: 1.02 to 1.06), 1.03 (95% CI: 1.01 to 1.05), and 1.02 (95% CI: 1.02 to 1.03), respectively. After controlling for age and period effects, cohort effects revealed relatively consistent trends for both genders (Fig. 3 B, D, F). Early birth cohorts exhibited increasing risks for incidence, death, and DALY. The 1950–1959 birth cohort had higher risks of incidence both genders (Fig. 3 B), while the 1930–1954 cohort had elevated death risks (Fig. 3 D). Higher DALY risks were noted in the 1940–1959 male and 1930–1959 female cohorts (Fig. 3 F). Predicting the future burden under 5 SSPs scenarios Future predictions of tracheal, bronchus and lung cancer burden in Fujian Province by the 5 SSPs scenarios were illustrated in Fig. 4 and Figures S5-8. The ASRs for incidence and death are expected to decline, while the ASR for DALY shows a minimal decrease. Under the SSP2 scenario, projected 2050 ASRs for incidence, death, and DALY are 28.37, 18.94, and 741.29 per 100,000, respectively (Fig. 4 A, D, G). Compared to 2019, these represent reductions of 19.47%, 46.33%, and 4.77%. Males may have significant decreases in incidence, death and DALY ASRs (ASRs of incidence: -40.41%; ASRs of death: -55.62%; ASRs of DALY: -32.69%), whereas females might see modest declines in incidence and death (ASRs of incidence: -7.11%; ASRs of death: -15.20%), but a substantial increase in DALY (ASRs of DALY: 88.64%). At China's national level, total population and males show decreasing trends in incidence, death and DALY ASRs from 2019 to 2050 (Fig. 4 B, E, and H). However, females’ incidence and death ASR remain modest, with a potential rise in DALY ASR. Globally, female ASRs for death and DALY do not exhibit similar increases (Fig. 4 F, and I). Attributable risk factor analysis Compared to 1990, the risk factors influencing the ASR of DALY of tracheal, bronchus, and lung cancer in 2019 had undergone changes (Fig. 5 ). In particular, the ASR of DALY attributable to household air pollution from solid fuels decreased substantially. The ASR of DALY attributable to ambient particulate matter pollution increased substantially in Fujian Province and China. However, this alert was not observed at the global level. In 2019, the top risk factor for males was smoking in Fujian Province (ASR of DALY: 964.21, 95% UI: 696.49 to 1273.24) (Fig. 5 A). The second risk factor for males was ambient particulate matter pollution (ASR of DALY: 202.83, 95% UI: 128.92 to 293.11). The ASR of DALY attributed to smoking was much lower in females than in males. In 2019, ambient particulate matter pollution and second-hand smoking were the main contributors to females ASR of DALY, accounting for 63.45 (95% UI: 42.91 to 93.91), and 52.34 (95% UI: 30.41 to 81.66), respectively. In China, the ASR of DALY associated with smoking for males was 961.58 (95% UI: 754.84 to 1198.42) in 2019 (Fig. 5 B). However, the ASR of DALY for males attributed to smoking globally (598.26, 95% UI: 538.87 to 661.34) was much lower than in China (Fig. 5 C). Moreover, the ASR of DALY in males and females attributed to ambient particulate matter pollution, household air pollution from solid fuels, and secondhand smoke in China were about 2.0-fold higher than the global (Fig. 5 B and C). At the global level, it was noteworthy that the occupational exposure to asbestos for males was the third major risk factor, with an associated age-standardized DALY rate of 81.25 (95% UI: 53.66 to 109.40) (Fig. 5 C). Quality-of-care index and gender disparity ratio In 2019, the QCI for tracheal, bronchus, and lung cancer in Fujian, China, and globally were similar, with trends consistent between males and females. However, there were significant age differences in QCI (Fig. 6 ). With increasing age, the QCI also increased. Despite this, the average QCI from 1990 to 2019 showed a decline, with Fujian experiencing the largest drop from 49.27 in 1990 to 40.00 in 2019. Fujian's QCI was lower than both global (41.81) and national (41.83) in 2019. From 1990 to 2019, the GDR decreased slightly but remained near 1, indicating relative stability (Figure S9). Fujian's GDR consistently stayed slightly higher, dropping from 1.06 in 1990 to 1.02 in 2019. By specific age groups, in 1990, the quality of care for females was slightly higher than for males in the 10–24 age groups, but the advantage disappeared with age. By 2019, there were no significant gender differences across most age groups. Discussion Lung cancer remains a significant public health challenge globally, constituting a primary cause of both cancer incidence and mortality [ 2 , 26 ]. However, the disease burden varies greatly across countries and within each country. In this study, we presented epidemiological trends and quality of care for tracheal, bronchus and lung cancer in Fujian Province, China, and globally from 1990 to 2019. Overall, the burden of tracheal, bronchus and lung cancer in China was higher than the global level. In China, the burden of tracheal, bronchus and lung cancer in Fujian Province was slightly lower than the national average but still higher than the global level. According to this study findings, the ASRs of death and DALY were higher in earlier years and began to decline after 2010. Similarly, a study conducted in Fujian Province showed that the five-year survival rate for lung cancer in Fujian Province increased from 13.8–23.7% between 2011 and 2020 [ 5 ]. This may be largely attributed to advancements in healthcare and primary prevention. In recent years, targeted therapies and immunotherapies for lung cancer have continually progressed, leading to significant advancements. From the predictive results of this study, it was observed that by the 2050, the ASR in Fujian Province were projected to decrease. Currently, next-generation sequencing technologies have enabled comprehensive identification of the genetic features of lung cancer, allowing for personalized treatment targeting mutation hotspots. As early as two decades ago, inhibitors targeting EGFR , KRAS , ROS1 , among others, have been employed in clinical therapy [ 27 ]. However, the persistent challenge of acquired resistance during treatment remains unresolved, with only approximately 25% of patients benefiting from targeted therapies [ 28 ]. This contributes to lung cancer’s continued high mortality rates. Consequently, the development of combined precision immunotherapy and targeted treatment research has begun, aiming to improve long-term clinical outcomes and increase overall survival [ 28 – 30 ]. However, despite these improvements, we found that the ASR of incidence had continued to increase after 2014 in Fujian Province. In China, a large-scale lung cancer screening project was initiated in 2010 [ 31 , 32 ]. This trend may be attributed to screening efforts. Some scholars have contended that lung cancer screening might result in overdiagnosis, given that a considerable number of patients identified through low-dose computed tomography (LDCT) scans do not exhibit malignant progression during subsequent follow-ups, yet still opt for surgery, especially among low-risk populations [ 33 ]. Nonetheless, screening for high-risk populations remains crucial, with LDCT proven effective in reducing lung cancer burden by aiding in early detection, improving prognosis, and reduced lung cancer mortality by 31% [ 34 ]. Therefore, to reduce over-screening and enhance cost-effectiveness, the China National Lung Cancer Screening Guideline with LDCT (2023 Version) specify defining high-risk populations for lung cancer as adults aged 50 and above with any of the following risk factors: smoking history, exposure to environmental or occupational carcinogens, presence of chronic obstructive pulmonary disease or diffuse pulmonary fibrosis or a history of tuberculosis, a history of malignant tumors, or a family history of lung cancer [ 32 ]. Additionally, other factors such as passive smoking and air pollution should also be considered in the assessment [ 32 , 35 ]. This study also supports the observable increase in the burden of lung cancer among individuals aged 50 and older, emphasizing the significance of risk factors such as smoking, ambient particulate matter pollution, and secondhand smoke. This study analyzed the burden of tracheal, bronchus and lung cancer across different age groups and found that the burden increased with age, especially among individuals aged 70 and above. Elderly individuals are susceptible to many diseases, particularly cancer. The aging process induces alterations in the microenvironment within the body, including epigenetic changes, alterations in cellular communication, protein homeostasis changes, mitochondrial dysfunction, and cellular senescence [ 36 ]. These processes manifest as the production of inflammatory mediators and weakening of the immune system, thereby driving the occurrence and progression of tumors in elderly individuals [ 37 ]. Meanwhile, the problem of aging in China is becoming increasingly serious [ 38 , 39 ], which may concentrate the incidence and mortality rates among the elderly. A study on age-related lung cancer burden in China also suggested that population aging is a primary driving factor for increases in disease burden [ 40 ]. When analyzed by gender, it was observed that the burden of lung cancer in males higher than that in females. On the one hand, genetic factors contributed to this gender disparity. Research had identified gender-specific susceptibility genes on the X chromosome, with 24 SNPs found to be associated with male lung cancer cases but not with females [ 41 ]. On the other hand, from a risk factor perspective, the burden of lung cancer attributable to smoking was notably high among males. In China, the burden of lung cancer due to smoking was 1.26 times the global average level. Chinese males account for approximately 40% of global cigarette consumption [ 42 ]. Although the smoking rate in Fujian was slightly lower than the national level, the male smoking rate reached 48.9% [ 5 ]. However, between 2015 and 2019, there had been a declining trend in the burden of lung cancer in males. This could be attributed to tobacco control measures implemented by the Chinese government [ 43 ], but further strengthening of anti-smoking policies remained necessary in the future [ 42 , 44 ]. Additionally, it is worth noting that the burden of lung cancer in females had been increased in recent years, with projections suggesting a continued upward trend until 2050. Females had needed to be vigilant about the effects of secondhand smoke and household air pollution. A prospective study had found a significant association between secondhand smoke exposure and the occurrence of EGFR mutations [ 45 ]. What’s more, young and middle-aged females are more likely to be frequently exposed to high-temperature cooking fumes in the kitchen. Cooking fumes contain harmful particulate matters and volatile organic compounds, including fine (ultrafine) particles, aldehydes, and polycyclic aromatic hydrocarbons [ 46 ]. Results from a Chinese cohort study showed that long-term exposure to cooking fumes increased the risk of lung cancer in non-smoking females by 1.4 to 3.8-folds [ 47 ]. Moreover, due to genetic factors and estrogen, females had been more susceptible to developing lung adenocarcinoma [ 48 , 49 ]. In addition to the aforementioned risk factors, Fujian Province also need to address the burden of lung cancer caused by ambient particulate matter pollution. In 2019, ambient particulate matter pollution ranked as the second-largest factor contributing to lung cancer ASR of DALY in China, following only smoking. This held true for Fujian Province as well. Many strong evidence indicated that air pollution played a driving role in the occurrence and development of lung cancer [ 50 – 52 ]. With the rapid development of the economy and the acceleration of urbanization, considerable environmental challenges have also been brought to China. China was one of the countries with the worst air quality in the world. In 2017, with 81.1% of the population still lived in areas exceeding the least stringent WHO air quality interim target of 35 µg/m 3 [ 53 ]. Fujian has better air quality than other high-pollution areas in China and is recognized as relatively good air quality in the country. In 2021, the PM2.5 level in Fujian Province was 18µg/m 3 [ 54 ], while the national average PM2.5 concentration was 30µg/m 3 [ 55 ]. This may also be one of the reasons why the burden of lung cancer in Fujian Province was slightly lower than the national average. Because of the development of the Chinese economy, the proportion of lung cancer ASR of DALY caused by household air pollution from solid fuels had been decreasing year by year. The number of households using solid fuels had decreased significantly [ 53 ]. In recent years, the government has taken a series of measures to improve air quality, and further efforts will be needed to advance environmental protection policies in the future. Moreover, in 2019, occupational exposure to asbestos was identified as the third risk factor for global burden of tracheal, bronchus, and lung cancers, especially among males. Asbestos was commonly used in the processing of building materials. However, asbestos produces large clouds of dust during mining, processing and application. Asbestos was classified as a Class I carcinogen by the International Agency for Research on Cancer. Previous studies had indicated that the burden of non-communicable diseases caused by asbestos was higher in high sociodemographic index (SDI) regions, while the burden in medium and low SDI regions was continued to increase [ 56 ]. In addition, the asbestos-induced lung cancer accounted for 55%-85% of occupational cancers [ 56 ]. Based on the survey finding [ 57 ], it was revealed that due to the development strategy of the Western Development and strengthened environmental controls in eastern cities in China, asbestos production enterprises were mainly located in western and central regions. The cases of asbestosis were predominantly reported in Tianjin, Beijing, Shandong, and Xinjiang, with fewer cases in Fujian Province, where the number of asbestosis cases was less than 30. It is imperative to continuously improve measures for the prevention and control of occupational asbestos exposure and related diseases. Governments worldwide are strongly encouraged to decrease the use of asbestos. Age and gender equality in the quality of care are key elements of the health system standards [ 9 ]. In this study, we did not observe significant gender differences in the quality of care, but differences based on age were evident. The QCI improved with increasing age, possibly due to several reasons. On the one hand, Elderly patients often received more attention and specialized care due to their complex healthcare needs [ 58 , 59 ]. On the other hand, healthcare providers might prioritize elderly patients or allocate more resources to them. A cohort study indicated higher satisfaction with care among elderly cancer patients, who also spent more time with physicians [ 60 ]. Conversely, the quality of care for younger individuals might be lower due to limited access to healthcare services, lack of awareness about preventive measures, and delays in diagnosis or treatment. Younger individuals might also have different healthcare priorities or face higher financial burden in care [ 60 ], resulting in lower quality care compared to the elderly. Furthermore, this study also observed decreased trends in QCI over the past 30 years. Considering the advancements in medical technology and improvements in healthcare policies, the decline in the quality of lung cancer care seems contrary to expectations. However, several reasons could contribute to this decrease. For instance, societal factors such as changes in environmental pollution, race, and disparities in access to healthcare could impact the incidence and management of lung cancer [ 61 – 64 ], thus affecting its overall quality of care. Additionally, precision oncology treatments are costly and do not benefit all cancer patients [ 65 ]. Healthcare policies or resource allocation strategies need to be weighed against cost-effectiveness, leading to potential gaps or inefficiencies in service delivery [ 66 ]. In Fujian Province, a more pronounced decline in QCI was observed. It could be attributed to disparities in the allocation and efficiency of utilization of resources. High-level public hospitals exhibited relatively higher bed occupancy rates, while other hospitals showed lower rates [ 67 ]. The workload of hospital physicians may be substantial, potentially impacting the efficiency and quality of medical services. Additionally, investments in health care in Fujian Province might be lower compared to other more economically developed regions in China, indicating a need to further strengthen the construction of the health service system [ 68 ]. Other specific reasons would require higher-level evidence from research to explore and substantiate. This study has several strengths. Firstly, it comprehensively analyzed tracheal, bronchial, and lung cancer epidemiological trends in Fujian, informing future healthcare strategies. Secondly, changes in risk factors were identified, guiding updates to comprehensive prevention policies. Lastly, this study used QCI to evaluate healthcare equity for lung cancer populations. However, there are limitations. Firstly, it relied on GBD 2019 data, which has inherent limitations in accuracy. However, GBD collaborators continuously update and improve statistical methods to minimize errors [ 13 , 69 ]. Secondly, GBD 2019 lacks data on lung cancer’s pathological subtypes, limiting detailed insights into subtype-specific burdens. Conclusions The tracheal, bronchial, and lung cancer burden in Fujian Province and China exceeded the global level. The elderly faced disproportionate burdens, with males bearing more than females. However, female burden has increased and is predicted to continue increasing. Key risk factors include smoking, ambient particulate matter pollution, and secondhand smoke. Notably, elderly care quality was high, with no gender disparities observed. Abbreviations QCI, Quality-of-Care Index; DALY, disability-adjusted life years; GBD 2019, Global Burden of Disease Study 2019; ASRs, age-standardized rates; AAPCs, average annual percent changes; APCs, annual percent changes; CI, confidence interval; RRs, rate ratios; SSPs, shared socioeconomic pathways; BAPC, Bayesian age-period-cohort; MIR, Mortality-to-Incidence Ratio; YLL, years of life lost; YLD, years lived with disability; PCA, principal component analysis; GDR, gender disparity ratio; UI: uncertainty interval; LDCT, low-dose computed tomography; SDI, sociodemographic index. Declarations Ethics approval and consent to participate The patients and the public were not involved in the design, conduct, reporting or dissemination of our studies. The data used in this study were obtained from publicly available sources. The institutional review board approval was not required. Consent for publication Not applicable. Availability of data and materials Data is available in a public, open access repository by the IHME, which is available called the GHDx (Global Health Data Exchange) query tool (http://ghdx.healthdata.org/gbd-results-tool). Competing interests The authors declare that they have no conflict of interest. Funding This work was supported by Fujian Province Pilot Project (grant number: 2020Y0060), Fujian Provincial Health Technology Project (grant number: 2020GGA026), and Fujian Provincial Natural Science Foundation Project (grant number: 2023J01093). Authors' contributions XQL and WLZ had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. SWL and FH conceived and designed the study. SWL drafted of the manuscript. YTD and XQL acquired, analyzed or interpreted data. YTD performed the statistical analysis. XQL, JHZ, FH and WLZ provided technical and material support. 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Table 2 Table 2 is available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Table2.docx GraphicalAbstract.tif SupplementalMaterials.docx Cite Share Download PDF Status: Published Journal Publication published 11 Aug, 2025 Read the published version in BMC Cancer → Version 1 posted Editorial decision: Revision requested 17 Mar, 2025 Reviews received at journal 17 Mar, 2025 Reviews received at journal 17 Mar, 2025 Reviews received at journal 15 Mar, 2025 Reviewers agreed at journal 08 Mar, 2025 Reviewers agreed at journal 07 Mar, 2025 Reviewers agreed at journal 07 Mar, 2025 Reviewers agreed at journal 06 Mar, 2025 Reviewers agreed at journal 06 Mar, 2025 Reviewers agreed at journal 05 Mar, 2025 Reviewers agreed at journal 26 Aug, 2024 Reviewers invited by journal 12 Aug, 2024 Editor invited by journal 09 Jul, 2024 Editor assigned by journal 05 Jul, 2024 Submission checks completed at journal 05 Jul, 2024 First submitted to journal 04 Jul, 2024 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. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4688998","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":332476958,"identity":"89d5e45d-0e61-4e12-b267-829f660bf4e2","order_by":0,"name":"Xiuquan Lin","email":"","orcid":"","institution":"Fujian Provincial Center for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Xiuquan","middleName":"","lastName":"Lin","suffix":""},{"id":332476960,"identity":"e14847d3-a414-4d7d-ba07-e41a203b04ad","order_by":1,"name":"Shiwen Liu","email":"","orcid":"","institution":"Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Shiwen","middleName":"","lastName":"Liu","suffix":""},{"id":332476962,"identity":"4cc8c3e5-3d0a-4c7a-b4d3-5537b2c3ea5c","order_by":2,"name":"Yating Ding","email":"","orcid":"","institution":"Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yating","middleName":"","lastName":"Ding","suffix":""},{"id":332476964,"identity":"8379f0bd-4811-484f-bf56-94b422bc2627","order_by":3,"name":"Jianhui Zhao","email":"","orcid":"","institution":"Zhejiang University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Jianhui","middleName":"","lastName":"Zhao","suffix":""},{"id":332476967,"identity":"a6735162-1096-479f-bfd4-2684e8082810","order_by":4,"name":"Fei He","email":"","orcid":"","institution":"Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Fei","middleName":"","lastName":"He","suffix":""},{"id":332476969,"identity":"78324c1a-1ada-4f9d-8ccb-582ce01a2e31","order_by":5,"name":"Wenling Zhong","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAnElEQVRIiWNgGAWjYDACCSB+UCEhJ0+aloQzFsaGDSRpSWyrSGQ4QKwO3dntzyQS50kkMDYwP3x0gxgtZncOpEkkbpPIY2dgMzbOIUrLjYRjN4BaihkbeNikidSS2HYjcY5EYsMB4rUks91IbCBJy51j7D8SjkkYGzYT7Zfb7Y8NPtTUycmzNz98TJQWBGAmTfkoGAWjYBSMAnwAADGNMTa8bTzwAAAAAElFTkSuQmCC","orcid":"","institution":"Fujian Provincial Center for Disease Control and Prevention","correspondingAuthor":true,"prefix":"","firstName":"Wenling","middleName":"","lastName":"Zhong","suffix":""}],"badges":[],"createdAt":"2024-07-05 01:55:50","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4688998/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4688998/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12885-025-14645-4","type":"published","date":"2025-08-11T15:58:04+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":62126483,"identity":"1212bdda-ff6d-4804-8550-187db7936dc6","added_by":"auto","created_at":"2024-08-09 14:48:00","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":6374939,"visible":true,"origin":"","legend":"\u003cp\u003eNumber of (A) Incidence, (B) Deaths, and (C) DALYs and ASRs double-Y-bar graph (Both, Male, Female) in Fujian Province, 1990-2019.\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4688998/v1/a94e7825d3c71e64f7cec923.jpg"},{"id":62124858,"identity":"1baf7e4e-955a-4538-a44c-1dd8345bdfff","added_by":"auto","created_at":"2024-08-09 14:32:00","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":7680877,"visible":true,"origin":"","legend":"\u003cp\u003eAge, period, and birth cohort effects of (A) Incidence, (B) Deaths, and (C) DALYs rates in Fujian Province, 1990-2019 (Both).\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4688998/v1/220ebc2877853114b854bb8f.jpg"},{"id":62124854,"identity":"1375a332-20b6-4039-9dbb-24fbd4ef4136","added_by":"auto","created_at":"2024-08-09 14:32:00","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":5823699,"visible":true,"origin":"","legend":"\u003cp\u003ePeriod and cohort effects of trachea, bronchus and lung cancer stratified by sex in Fujian Province. (A) Period effect of morbidity. (B) Cohort effect of morbidity. (C) Period effect of mortality. (D) Cohort effect of mortality. (E) Period effect of DALY rate. (F) Cohort effect of DALY rate.\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4688998/v1/36f622884ebb5875a06de10d.jpg"},{"id":62125524,"identity":"40f641f4-4cf2-4a17-a322-349eb4af5369","added_by":"auto","created_at":"2024-08-09 14:40:00","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":2860107,"visible":true,"origin":"","legend":"\u003cp\u003eGlobal, China and Fujian predictions of tracheal, bronchial, and lung cancer (both, male, female). (A) Age-standardized rate incidence prediction map in Global. (B) Age-standardized rate incidence prediction map in China. (C) Age-standardized rate incidence prediction map in Fujian Province. (D) Age-standardized rate deaths prediction map in Global. (E) Age-standardized rate deaths prediction map in China. (F) Age-standardized rate deaths prediction map in Fujian Province. (G) Age-standardized rate DALYs prediction map in Global. (H) Age-standardized DALYs rate prediction map in China. (I) Age-standardized rate DALYs prediction map in Fujian Province.\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4688998/v1/fe69887f3c9765cccf51794f.jpg"},{"id":62125521,"identity":"5f8522bf-6d6f-4e17-a5a2-436be267f5c0","added_by":"auto","created_at":"2024-08-09 14:40:00","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":12136656,"visible":true,"origin":"","legend":"\u003cp\u003eTracheal, Bronchus, and Lung Cancer DALY Rates Attributable to Risk Factors in Fujian Province, China, and Global in 1990 and 2019 (Male, Female).\u003c/p\u003e","description":"","filename":"Figure5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4688998/v1/56faca251657e0667a2c05a3.jpg"},{"id":62124860,"identity":"9e288bc6-3f5f-4267-bc85-46b15f5fb08b","added_by":"auto","created_at":"2024-08-09 14:32:00","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":3924861,"visible":true,"origin":"","legend":"\u003cp\u003eQuality care of index (QCI) for tracheal, bronchial and lung cancer in Fujian Province. (A)Temporal QCI from 1990 to 2019. (B)Age trend of QCI in 1990. (C) Age trend of QCI in 2019.\u003c/p\u003e","description":"","filename":"Figure6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4688998/v1/2261804898b1c0ad3edbfeb6.jpg"},{"id":89310967,"identity":"8fdcf4d2-9a70-48b0-8cd6-71a0122862df","added_by":"auto","created_at":"2025-08-18 16:10:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":41458729,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4688998/v1/317154a5-e5ae-4187-a615-96ee52efccb0.pdf"},{"id":62124853,"identity":"b9734cf7-6de8-489e-b975-103d2ff39863","added_by":"auto","created_at":"2024-08-09 14:32:00","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":22404,"visible":true,"origin":"","legend":"","description":"","filename":"Table2.docx","url":"https://assets-eu.researchsquare.com/files/rs-4688998/v1/7d103f206c2d4a55cbb36b50.docx"},{"id":62127097,"identity":"b3129938-3749-491f-8eae-159f9dac396b","added_by":"auto","created_at":"2024-08-09 14:56:00","extension":"tif","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":332560,"visible":true,"origin":"","legend":"","description":"","filename":"GraphicalAbstract.tif","url":"https://assets-eu.researchsquare.com/files/rs-4688998/v1/c709e31174c7d287dd82d47b.tif"},{"id":62124861,"identity":"16b23b4a-4389-4ba2-ab81-f7b141fe9b03","added_by":"auto","created_at":"2024-08-09 14:32:00","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":3036836,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementalMaterials.docx","url":"https://assets-eu.researchsquare.com/files/rs-4688998/v1/efecac7e1aa217ac3b06d67c.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Contrasting Tracheal, Bronchus, and Lung Cancer Burdens and Care Quality: A Comparative Analysis of China and Global Trends ","fulltext":[{"header":"Research in context","content":"\u003cp\u003e\u003cstrong\u003eEvidence before this study\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe searched using the keywords \u0026ldquo;lung cancer\u0026rdquo;, \u0026ldquo;disease burden\u0026rdquo; and \u0026ldquo;epidemiology\u0026rdquo; in the PubMed and China National Knowledge Infrastructure (CNKI) databases, with the search timeframe spanning from 1997 to 2023. Previous studies had been conducted at global and national levels. In China, it was the cancer with the highest incidence and mortality rate. However, some studies indicated that there were regional disparities in lung cancer burden, with relatively higher mortality rates in the eastern regions of China. Nevertheless, to our knowledge, there had been no epidemiological studies analyzing the lung cancer burden in Fujian Province using such comprehensive indicators. Therefore, it was necessary to conduct a thorough analysis of the disease burden and its temporal trends across different age and gender groups. Additionally, we searched the PubMed and CNKI databases using the keywords \u0026quot;lung cancer\u0026quot; and \u0026quot;quality of care\u0026quot;, with the search period ranging from 1983 to 2023. The majority of studies focused on the quality of surgical care for lung cancer patients or analyzed quality of life surveys on a small number of lung cancer patients. The estimation of the quality of care outcomes for the entire lung cancer population remained unknown.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAdded value of this study\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study utilized the surveillance data from Fujian Province and GBD 2019 to analyze the temporal trends in the incidence, death and\u0026nbsp;DALY\u0026nbsp;of tracheal, bronchus and\u0026nbsp;lung cancer. Furthermore, projections of disease burden from 2020 to 2050 were analyzed.\u0026nbsp;Compared with 2019, the ASR of incidence, death, and DALY may decrease by 19.47%, 46.33%, and 4.77% in Fujian Province, respectively. Additionally, we identified changes in the burden of attributable risk factors for tracheal, bronchus and lung cancer.\u0026nbsp;In particular, the ASR of DALY\u0026nbsp;attributable to household air pollution from solid fuels decreased substantially. The ASR of DALY attributable to ambient particulate matter pollution increased substantially in Fujian Province and China. Lastly, the QCI was used to assess the quality of care. Fujian Province experienced the largest decrease, dropping from 49.27 in 1990 to 40.00 in 2019.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImplications of all the available evidence\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn conclusion, this study identified the epidemiological trends of tracheal, bronchus and lung cancer in the Fujian province, with the disease burden remaining severe. Predictions for future trends and assessments of the quality of care may facilitate the development of future medical strategies and more effective allocation of healthcare resources. It was deemed necessary to focus on the disease burden attributable to smoking, secondhand smoke, and environmental pollution, in order to formulate targeted public health policies and intervention measures.\u003cbr\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"Introduction","content":"\u003cp\u003eThe five-year survival rate for lung cancer has ranged from 4\u0026ndash;17%, depending on stage and regional differences [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The International Agency for Research on Cancer reported in 2020 that lung cancer ranks second in the global cancer incidence spectrum and first in the cancer mortality spectrum [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], and tracheal, bronchus, and lung cancer disability-adjusted life-years (DALY) rank second globally early-onset cancer [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. In China, lung cancer remains the leading cancer in terms of both incidence and mortality rates [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], imposing a major public health issue. However, the disease burden varies significantly across different regions and periods, which is associated with many factors. Fujian Province is located in the southeastern coastal province of China. Other scholars have indicated that the incidence of lung cancer in Fujian Province was increasing, and it belonged to the province with higher lung cancer incidence in China [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Therefore, it is necessary to understand the epidemiological trends of lung cancer in Fujian Province and analyze the disease burden among different populations at different times. Additionally, the etiology of lung cancer is complex, with modifiable independent risk factors including smoking, occupational history, exposure to air particulate matter and so on [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Comprehensive the contribution of attributable risk factors to the burden of lung cancer can assist policymakers in formulating accurate policies and measures.\u003c/p\u003e \u003cp\u003eThe quality of healthcare services also influenced the disease burden. A review study had indicated that healthcare disparities were associated with race, socioeconomic status, and overall level of risk [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Previously, lung cancer was observed to have a higher risk level among males, but now there is an increasing number of cases among non-smoking females each year [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Whether healthcare disparities exist between different genders remains unknown. One study designed a method to examine the care outcomes for tumors in various countries, the Quality-of-Care Index (QCI) [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. This index had been validated in multiple cancers and serves as an indicator of effective healthcare access [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Currently, there is few research systematically quantifying and comparing the disparities in quality of care among different patients for lung cancer.\u003c/p\u003e \u003cp\u003eTherefore, this study analyzed the temporal trends in the incidence, death and DALY of tracheal, bronchus and lung cancer in Fujian Province, China and globally. Furthermore, we identified changes in the attributable risk factors for tracheal, bronchus and lung cancer, which could aid in updating comprehensive prevention policies. Lastly, the QCI was used to assess the quality of care among lung cancer populations to assessment of healthcare equity.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy data\u003c/h2\u003e \u003cp\u003eThis study assessed the burden of tracheal, bronchus and lung cancer in Fujian Province, China, and globally using age-standardized rates (ASRs) for incidence, death, and DALY. Data for Fujian Province were sourced from our institution and submitted to the Global Burden of Disease Study 2019 (GBD 2019) Collaboration Group. The same standardized methodology as GBD 2019 was used. China and global data were obtained from GBD 2019.\u003c/p\u003e \u003cp\u003eThe GBD 2019 database is publicly available, and data on incidence, death, DALY, years of life lost (YLL), years lived with disability (YLD), and risk factors were downloaded via the Global Health Data Exchange query tool (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://ghdx.healthdata.org/gbd-results-tool\u003c/span\u003e\u003cspan address=\"http://ghdx.healthdata.org/gbd-results-tool\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Sources included epidemiological research, cause of death reporting systems, disease surveillance sites, and maternal and child surveillance systems [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. DisMod-MR 2.1, a Bayesian meta-regression tool, was used for systematic assessment [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Detailed data processing methods are available on the GBD website and previous reports [\u003cspan additionalcitationids=\"CR14 CR15\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eJoinpoint regression model\u003c/h2\u003e \u003cp\u003eWe used the average annual percent change (AAPC) to estimate temporal trends in the burden of tracheal, bronchus and lung cancer from 1990 to 2019 by joinpoint regression model. AAPC, defined as the geometrically weighted average of annual percent changes (APCs), described the trends in ASRs [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. AAPC use the segmented APCs to summarise and compare the ASRs of change over time and identify long-term trends in the ASRs, even if they are unstable [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Positive AAPC values with lower 95% confidence intervals (CI) indicate increasing trends, while negative values with upper 95% CIs indicate descending trends.\u003c/p\u003e \u003cp\u003eThe calculation involved establishing a linear relationship between the natural logarithm of ASRs and periods, identifying significant joinpoints, calculating APC for each segment, and then computing the geometrically weighted average of APCs to obtain AAPCs [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The National Cancer Institute\u0026rsquo;s Joinpoint Regression Analysis software (version 5.0.2) was used, applying the Monte Carlo method for significance testing and Bonferroni correction [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eAge-period-cohort analysis\u003c/h2\u003e \u003cp\u003eAge-period-cohort model was used in this study to show the temporal trends in rates for tracheal, bronchus and lung cancer by age, period and cohort. By adjusting for age, period, and cohort, the independent effects were analyzed [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. This study utilized the age-period-cohort model to decompose the variations in incidence, death, and DALY rates into age, period (year), and cohort (birth year) effects. Age and period were analyzed in 5-year intervals ranging from 10 to 95 years, periods from 1990 to 2019, and successive cohorts (period-age) from 1900 to 2009. Furthermore, rate ratios (RRs) were calculated for each period and cohort to summarize the relative risks of tracheal, bronchus and lung cancer incidence, death, and DALY rates compared to the overall average rates. The estimable functions in the age-period-cohort model were validated through the Wald chi-square test [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. This analysis was performed using the RStudio software (version 4.2.2).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003ePredicting the burden through 2050\u003c/h2\u003e \u003cp\u003ePopulation projections for 2050 were sourced from the United Nations Department of Economic and Social Affairs Population Division for global and China\u0026rsquo;s data [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. For Fujian Province, projections by Chen et al were used [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], focusing on the Shared Socioeconomic Pathways (SSPs) scenarios 2, which closely align with current trends in Fujian.\u003c/p\u003e \u003cp\u003eBayesian age-period-cohort (BAPC) forecasting method, proposed by Andrea Riebler et al. [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], was utilized to predict future ASRs from 2020 to 2050 under a fully Bayesian inference setting. The BAPC package in the RStudio (version 4.2.2) facilitated these forecasts.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eQCI and GDR\u003c/h2\u003e \u003cp\u003eThis study was described the quality of care by age and gender differences from 1990 to 2019. Four secondary indicators were computed and combined to estimate the QCI, which was explained in detail in previous studies [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Firstly, the four secondary indicators were calculated: Mortality-to-Incidence Ratio (MIR), Prevalence-to-Incidence Ratio, DALYs-to- Prevalence Ratio, and Years of Life Lost (YLL)-to-Years Lived with Disability (YLD) Ratio. Secondly, the first and second principal components were extracted from these four indicators using Principal Component Analysis (PCA) to compute the QCI. The PCA was conducted using RStudio software (version 4.2.2). Finally, it was adjusted to a scale of 0 to 100, where higher scores indicate better quality of care. More detailed statistical analysis processes can be found in the Table S2. Furthermore, the Gender Disparity Ratio (GDR) was calculated using the formula: \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:GDR\\:=\\:\\frac{QCI\\left(females\\right)}{QCI\\left(males\\right)}\\)\u003c/span\u003e\u003c/span\u003e. The GDR was used to describe gender inequality in quality of care.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\"\u003e\n \u003ch2\u003eDisease burden of tracheal, bronchus and lung cancer in 2019\u003c/h2\u003e\n \u003cp\u003eIn 2019, the numbers of total incident cases, death cases, and DALYs of tracheal, bronchus and lung cancer in Fujian Province were 20.07 (95% uncertainty interval [UI]: 15.73 to 25.13) thousand, 17.71 (95% UI: 13.87 to 21.99) thousand, and 414.36 (95% UI: 324.41 to 523.88) thousand, respectively (Table\u0026nbsp;\u003cspan\u003e1\u003c/span\u003e). From 1990 to 2019, the number of cases continuously increasing (Fig.\u0026nbsp;\u003cspan\u003e1\u003c/span\u003e). The ASRs of incidence, death, and DALY in 2019 were 39.08 (95% UI: 30.91 to 49.05), 35.29 (95% UI: 27.69 to 43.63), and 778.39 (95% UI: 610.86 to 978.74) per 100,000 in Fujian Province, respectively (Table\u0026nbsp;\u003cspan\u003e1\u003c/span\u003e). From 1990 to 2019, the ASRs of incidence, death and DALY were fluctuated, with AAPCs of 1.08 (95% CI: 0.77 to 1.38), 0.65 (95% CI: 0.35 to 0.95) and 0.18 (95% CI: -0.07 to 0.42), respectively. In general, the ASRs were increasing trends. The most dramatic increased occurred between 1998\u0026ndash;2002 (incidence APC: 4.41, 95% CI: 2.43 to 6.42; death APC: 4.25, 95% CI: 2.30 to 6.23; DALY APC: 3.27, 95% CI: 2.39 to 4.15) (Table \u003cspan\u003eS1\u003c/span\u003e and Figure S2). During 2010\u0026ndash;2014, ASRs showed decreased trends, notably in death (APC: -1.11, 95% CI: -2.03 to -0.17) and DALY (APC: -1.69, 95% CI: -2.53 to -0.85). However, ASRs of incidence increased again during 2014\u0026ndash;2019 (APC: 0.82, 95% CI: 0.39 to 1.25).\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 1\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eNumber of incidences, deaths and DALYs, ASRs (per 100,000 population) and AAPCs (Both) in Fujian Province, China and Global, 1990 and 2019\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003eIncidence\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003eDeaths\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003eDALYs\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eNumbers\u003c/p\u003e\n \u003cp\u003e(95% UI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eASR\u003c/p\u003e\n \u003cp\u003e(95% UI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAAPC\u003c/p\u003e\n \u003cp\u003e(95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eNumbers\u003c/p\u003e\n \u003cp\u003e(95% UI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eASR\u003c/p\u003e\n \u003cp\u003e(95% UI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAAPC\u003c/p\u003e\n \u003cp\u003e(95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNumbers\u003c/p\u003e\n \u003cp\u003e(95% UI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eASR\u003c/p\u003e\n \u003cp\u003e(95% UI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAAPC\u003c/p\u003e\n \u003cp\u003e(95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGlobal\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"12\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1990\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1124006.07\u003c/p\u003e\n \u003cp\u003e(1077618.40, 1176491.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28.39\u003c/p\u003e\n \u003cp\u003e(27.18, 29.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e-0.08\u003c/p\u003e\n \u003cp\u003e(-0.24, 0.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1065138.99\u003c/p\u003e\n \u003cp\u003e(1019216.81, 1117181.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e27.30\u003c/p\u003e\n \u003cp\u003e(26.03, 28.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e-0.27\u003c/p\u003e\n \u003cp\u003e(-0.39, -0.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e27122576.95\u003c/p\u003e\n \u003cp\u003e(25859878.00, 28498448.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e657.98\u003c/p\u003e\n \u003cp\u003e(628.28, 690.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" rowspan=\"2\"\u003e\n \u003cp\u003e-0.60\u003c/p\u003e\n \u003cp\u003e(-0.72, -0.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e2019\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e2259998.15\u003c/p\u003e\n \u003cp\u003e(2067316.08, 2451832.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27.66\u003c/p\u003e\n \u003cp\u003e(25.28, 29.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2042639.74\u003c/p\u003e\n \u003cp\u003e(1879241.24, 2193268.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e25.18\u003c/p\u003e\n \u003cp\u003e(23.16, 27.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e45857963.48\u003c/p\u003e\n \u003cp\u003e(42297425.07, 49339875.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e551.58\u003c/p\u003e\n \u003cp\u003e(508.97, 593.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eChina\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"12\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1990\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e257044.68\u003c/p\u003e\n \u003cp\u003e(221285.90, 293647.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30.20\u003c/p\u003e\n \u003cp\u003e(26.20, 34.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e1.15\u003c/p\u003e\n \u003cp\u003e(0.92, 1.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e256325.53\u003c/p\u003e\n \u003cp\u003e(221055.12, 294555.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e31.18\u003c/p\u003e\n \u003cp\u003e(27.14, 35.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003cp\u003e(0.54, 1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e6960865.13\u003c/p\u003e\n \u003cp\u003e(5966957.99, 8039127.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e760.68\u003c/p\u003e\n \u003cp\u003e(654.28, 875.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" rowspan=\"2\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003cp\u003e(0.11, 0.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e2019\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e832922.16\u003c/p\u003e\n \u003cp\u003e(700293.15, 981631.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41.71\u003c/p\u003e\n \u003cp\u003e(35.22, 48.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e757171.25\u003c/p\u003e\n \u003cp\u003e(638741.18, 887751.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e38.70\u003c/p\u003e\n \u003cp\u003e(32.80, 45.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e17128584.02\u003c/p\u003e\n \u003cp\u003e(14340490.76, 20231342.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e831.27\u003c/p\u003e\n \u003cp\u003e(699.11, 979.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFujian\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"12\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1990\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5905.75\u003c/p\u003e\n \u003cp\u003e(4800.08, 7166.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e28.67\u003c/p\u003e\n \u003cp\u003e(23.64, 34.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e1.08\u003c/p\u003e\n \u003cp\u003e(0.77, 1.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5835.69\u003c/p\u003e\n \u003cp\u003e(4747.01, 7081.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e29.30\u003c/p\u003e\n \u003cp\u003e(24.27, 34.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003cp\u003e(0.35, 0.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e162681.24\u003c/p\u003e\n \u003cp\u003e(129561.46, 199195.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e742.13\u003c/p\u003e\n \u003cp\u003e(596.69, 901.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" rowspan=\"2\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003cp\u003e(-0.07, 0.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e2019\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20067.21\u003c/p\u003e\n \u003cp\u003e(15726.70, 25132.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e39.08\u003c/p\u003e\n \u003cp\u003e(30.91, 49.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17712.88\u003c/p\u003e\n \u003cp\u003e(13872.85, 21992.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e35.29\u003c/p\u003e\n \u003cp\u003e(27.69, 43.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e414363.88\u003c/p\u003e\n \u003cp\u003e(324406.68, 523878.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e778.39\u003c/p\u003e\n \u003cp\u003e(610.86, 978.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eNationally, China\u0026apos;s 2019 burden was higher than Fujian\u0026apos;s, with ASRs per 100,000 of 41.71 (95% UI: 32.22 to 48.80) for incidence, 38.70 (95% UI: 32.80 to 45.03) for death, and 831.27 (95% UI: 699.11 to 979.99) for DALY (Table\u0026nbsp;\u003cspan\u003e1\u003c/span\u003e). From 1990 to 2019, the ASRs of incidence, death and DALY showed an increased trend in China (Figure \u003cspan\u003eS1\u003c/span\u003e). The corresponding AAPCs were 1.15 (95% CI: 0.92 to 1.38), 0.77 (95% CI: 0.54 to 1.00), and 0.31 (95% CI: 0.11 to 0.51) (Table\u0026nbsp;\u003cspan\u003e1\u003c/span\u003e). In terms of segmented joinpoint periods, the trends in China were similar to Fujian Province (Figure S3).\u003c/p\u003e\n \u003cp\u003eGlobally, the 2019 ASRs per 100,000 were 27.66 (95%UI: 25.28 to 29.99) for incidence, 25.18 (95% UI: 23.16 to 27.01) for death, and 551.58 (95% UI: 508.97 to 593.12) for DALY (Table\u0026nbsp;\u003cspan\u003e1\u003c/span\u003e). From 1990 to 2019, global ASRs declined with AAPCs of -0.08 (95% CI: -0.24 to -0.08), -0.27 (95% CI: -0.39 to -0.14) and \u0026minus;\u0026thinsp;0.60 (95% CI: -0.72 to -0.48) for incidence, death, and DALY, respectively. Incidence and death ASRs showed a linear decline, while DALY ASR increased before 2003 and declined after 2009 (Figure S4).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\"\u003e\n \u003ch2\u003eAge-period-cohort analyses\u003c/h2\u003e\n \u003cp\u003eFigure \u003cspan\u003e2\u003c/span\u003eA illustrated the trends of incidence, death and DALY rates across different age groups in Fujian Province from 1990 to 2019. Incidence rates notably increased among those aged over 70, with the highest rates (over 300 per 100,000) observed in the 85\u0026ndash;89, 80\u0026ndash;84, and 75\u0026ndash;79 age groups during 2015\u0026ndash;2019. Death rates for these age groups exceeded 200 per 100,000 in the same period. The highest DALY rates shifted from the 70\u0026ndash;74 age group (1990\u0026ndash;2014) to the 75\u0026ndash;79 age group (2015\u0026ndash;2019). Post-2005, DALY rates consistently rose for the over-75 age groups, while declining for the younger.\u003c/p\u003e\n \u003cp\u003eFigure \u003cspan\u003e2\u003c/span\u003eB highlights that incidence, death, and DALY rates began increasing significantly after age 50 in all periods, remaining higher in recent years for older age groups.\u003c/p\u003e\n \u003cp\u003eFigure \u003cspan\u003e2\u003c/span\u003eC shows cohort-based variations, with continuous increases in incidence, death, and DALY rates among those over 75 in later-born cohorts. For the 50\u0026ndash;74 age groups, DALY rates initially rose before declining in later-born cohorts.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\"\u003e\n \u003ch2\u003eDifferences between males and females\u003c/h2\u003e\n \u003cp\u003eBoth at the global level, national level and Fujian Province, the burden of tracheal, bronchus and lung cancer were much higher for males than females. In Fujian Province, ASR of incidence for males was 3.03-fold higher than females, ASR of death was 3.18-fold higher, and ASR of DALY was 3.03-fold higher in 2019 (Table \u003cspan\u003e2\u003c/span\u003e). From 1990 to 2019, most ASRs increased, exception of the ASR for female DALY. The AAPCs of ASRs for both genders in China from 1990 to 2019 were similar to those of Fujian province, with slightly higher AAPCs compared to Fujian province. Similarly, the ASRs of incidence, death and DALY in males showed decreased trends between 1990 and 2019 in global. Instead, females showed increased trends, with AAPCs of 0.69 (95% CI: 0.63 to 0.76), 0.47 (95% CI: 0.41 to 0.52) and 0.17 (95% CI: 0.12 to 0.22).\u003c/p\u003e\n \u003cdiv\u003eThe results for gender-specific effects owing to period and cohort using the Poisson log-linear model were shown in Fig. \u003cspan\u003e3\u003c/span\u003e. For males, the period effects on incidence, death and DALY rates were peaked in 2005\u0026ndash;2009, with RRs of 1.03 (95% CI: 1.01 to 1.05), 1.04 (95% CI: 1.02 to 1.06) and 1.05 (95% CI: 1.045 to 1.052) in Fujian, respectively (Fig. \u003cspan\u003e3\u003c/span\u003eA, C and E). Post-2009, these period effects showed declining trends. By 2015\u0026ndash;2019, RRs of males incidence, death, and DALY rates were below 0, indicating reduced risks. In contrast, females risk of incidence, death, and DALY peaked in 2015\u0026ndash;2019, with RRs of 1.04 (95% CI: 1.02 to 1.06), 1.03 (95% CI: 1.01 to 1.05), and 1.02 (95% CI: 1.02 to 1.03), respectively. After controlling for age and period effects, cohort effects revealed relatively consistent trends for both genders (Fig. \u003cspan\u003e3\u003c/span\u003eB, D, F). Early birth cohorts exhibited increasing risks for incidence, death, and DALY. The 1950\u0026ndash;1959 birth cohort had higher risks of incidence both genders (Fig. \u003cspan\u003e3\u003c/span\u003eB), while the 1930\u0026ndash;1954 cohort had elevated death risks (Fig. \u003cspan\u003e3\u003c/span\u003eD). Higher DALY risks were noted in the 1940\u0026ndash;1959 male and 1930\u0026ndash;1959 female cohorts (Fig. \u003cspan\u003e3\u003c/span\u003eF).\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\"\u003e\n \u003ch2\u003ePredicting the future burden under 5 SSPs scenarios\u003c/h2\u003e\n \u003cp\u003eFuture predictions of tracheal, bronchus and lung cancer burden in Fujian Province by the 5 SSPs scenarios were illustrated in Fig.\u0026nbsp;\u003cspan\u003e4\u003c/span\u003e and Figures S5-8. The ASRs for incidence and death are expected to decline, while the ASR for DALY shows a minimal decrease.\u003c/p\u003e\n \u003cp\u003eUnder the SSP2 scenario, projected 2050 ASRs for incidence, death, and DALY are 28.37, 18.94, and 741.29 per 100,000, respectively (Fig.\u0026nbsp;\u003cspan\u003e4\u003c/span\u003eA, D, G). Compared to 2019, these represent reductions of 19.47%, 46.33%, and 4.77%. Males may have significant decreases in incidence, death and DALY ASRs (ASRs of incidence: -40.41%; ASRs of death: -55.62%; ASRs of DALY: -32.69%), whereas females might see modest declines in incidence and death (ASRs of incidence: -7.11%; ASRs of death: -15.20%), but a substantial increase in DALY (ASRs of DALY: 88.64%).\u003c/p\u003e\n \u003cp\u003eAt China\u0026apos;s national level, total population and males show decreasing trends in incidence, death and DALY ASRs from 2019 to 2050 (Fig.\u0026nbsp;\u003cspan\u003e4\u003c/span\u003eB, E, and H). However, females\u0026rsquo; incidence and death ASR remain modest, with a potential rise in DALY ASR. Globally, female ASRs for death and DALY do not exhibit similar increases (Fig.\u0026nbsp;\u003cspan\u003e4\u003c/span\u003eF, and I).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\"\u003e\n \u003ch2\u003eAttributable risk factor analysis\u003c/h2\u003e\n \u003cp\u003eCompared to 1990, the risk factors influencing the ASR of DALY of tracheal, bronchus, and lung cancer in 2019 had undergone changes (Fig.\u0026nbsp;\u003cspan\u003e5\u003c/span\u003e). In particular, the ASR of DALY attributable to household air pollution from solid fuels decreased substantially. The ASR of DALY attributable to ambient particulate matter pollution increased substantially in Fujian Province and China. However, this alert was not observed at the global level.\u003c/p\u003e\n \u003cp\u003eIn 2019, the top risk factor for males was smoking in Fujian Province (ASR of DALY: 964.21, 95% UI: 696.49 to 1273.24) (Fig.\u0026nbsp;\u003cspan\u003e5\u003c/span\u003eA). The second risk factor for males was ambient particulate matter pollution (ASR of DALY: 202.83, 95% UI: 128.92 to 293.11). The ASR of DALY attributed to smoking was much lower in females than in males. In 2019, ambient particulate matter pollution and second-hand smoking were the main contributors to females ASR of DALY, accounting for 63.45 (95% UI: 42.91 to 93.91), and 52.34 (95% UI: 30.41 to 81.66), respectively.\u003c/p\u003e\n \u003cp\u003eIn China, the ASR of DALY associated with smoking for males was 961.58 (95% UI: 754.84 to 1198.42) in 2019 (Fig.\u0026nbsp;\u003cspan\u003e5\u003c/span\u003eB). However, the ASR of DALY for males attributed to smoking globally (598.26, 95% UI: 538.87 to 661.34) was much lower than in China (Fig.\u0026nbsp;\u003cspan\u003e5\u003c/span\u003eC). Moreover, the ASR of DALY in males and females attributed to ambient particulate matter pollution, household air pollution from solid fuels, and secondhand smoke in China were about 2.0-fold higher than the global (Fig.\u0026nbsp;\u003cspan\u003e5\u003c/span\u003eB and C). At the global level, it was noteworthy that the occupational exposure to asbestos for males was the third major risk factor, with an associated age-standardized DALY rate of 81.25 (95% UI: 53.66 to 109.40) (Fig.\u0026nbsp;\u003cspan\u003e5\u003c/span\u003eC).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\"\u003e\n \u003ch2\u003eQuality-of-care index and gender disparity ratio\u003c/h2\u003e\n \u003cp\u003eIn 2019, the QCI for tracheal, bronchus, and lung cancer in Fujian, China, and globally were similar, with trends consistent between males and females. However, there were significant age differences in QCI (Fig.\u0026nbsp;\u003cspan\u003e6\u003c/span\u003e). With increasing age, the QCI also increased. Despite this, the average QCI from 1990 to 2019 showed a decline, with Fujian experiencing the largest drop from 49.27 in 1990 to 40.00 in 2019. Fujian\u0026apos;s QCI was lower than both global (41.81) and national (41.83) in 2019.\u003c/p\u003e\n \u003cp\u003eFrom 1990 to 2019, the GDR decreased slightly but remained near 1, indicating relative stability (Figure S9). Fujian\u0026apos;s GDR consistently stayed slightly higher, dropping from 1.06 in 1990 to 1.02 in 2019. By specific age groups, in 1990, the quality of care for females was slightly higher than for males in the 10\u0026ndash;24 age groups, but the advantage disappeared with age. By 2019, there were no significant gender differences across most age groups.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eLung cancer remains a significant public health challenge globally, constituting a primary cause of both cancer incidence and mortality [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. However, the disease burden varies greatly across countries and within each country. In this study, we presented epidemiological trends and quality of care for tracheal, bronchus and lung cancer in Fujian Province, China, and globally from 1990 to 2019. Overall, the burden of tracheal, bronchus and lung cancer in China was higher than the global level. In China, the burden of tracheal, bronchus and lung cancer in Fujian Province was slightly lower than the national average but still higher than the global level.\u003c/p\u003e \u003cp\u003eAccording to this study findings, the ASRs of death and DALY were higher in earlier years and began to decline after 2010. Similarly, a study conducted in Fujian Province showed that the five-year survival rate for lung cancer in Fujian Province increased from 13.8\u0026ndash;23.7% between 2011 and 2020 [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. This may be largely attributed to advancements in healthcare and primary prevention. In recent years, targeted therapies and immunotherapies for lung cancer have continually progressed, leading to significant advancements. From the predictive results of this study, it was observed that by the 2050, the ASR in Fujian Province were projected to decrease. Currently, next-generation sequencing technologies have enabled comprehensive identification of the genetic features of lung cancer, allowing for personalized treatment targeting mutation hotspots. As early as two decades ago, inhibitors targeting \u003cem\u003eEGFR\u003c/em\u003e, \u003cem\u003eKRAS\u003c/em\u003e, \u003cem\u003eROS1\u003c/em\u003e, among others, have been employed in clinical therapy [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. However, the persistent challenge of acquired resistance during treatment remains unresolved, with only approximately 25% of patients benefiting from targeted therapies [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. This contributes to lung cancer\u0026rsquo;s continued high mortality rates. Consequently, the development of combined precision immunotherapy and targeted treatment research has begun, aiming to improve long-term clinical outcomes and increase overall survival [\u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHowever, despite these improvements, we found that the ASR of incidence had continued to increase after 2014 in Fujian Province. In China, a large-scale lung cancer screening project was initiated in 2010 [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. This trend may be attributed to screening efforts. Some scholars have contended that lung cancer screening might result in overdiagnosis, given that a considerable number of patients identified through low-dose computed tomography (LDCT) scans do not exhibit malignant progression during subsequent follow-ups, yet still opt for surgery, especially among low-risk populations [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Nonetheless, screening for high-risk populations remains crucial, with LDCT proven effective in reducing lung cancer burden by aiding in early detection, improving prognosis, and reduced lung cancer mortality by 31% [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Therefore, to reduce over-screening and enhance cost-effectiveness, the China National Lung Cancer Screening Guideline with LDCT (2023 Version) specify defining high-risk populations for lung cancer as adults aged 50 and above with any of the following risk factors: smoking history, exposure to environmental or occupational carcinogens, presence of chronic obstructive pulmonary disease or diffuse pulmonary fibrosis or a history of tuberculosis, a history of malignant tumors, or a family history of lung cancer [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Additionally, other factors such as passive smoking and air pollution should also be considered in the assessment [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. This study also supports the observable increase in the burden of lung cancer among individuals aged 50 and older, emphasizing the significance of risk factors such as smoking, ambient particulate matter pollution, and secondhand smoke.\u003c/p\u003e \u003cp\u003eThis study analyzed the burden of tracheal, bronchus and lung cancer across different age groups and found that the burden increased with age, especially among individuals aged 70 and above. Elderly individuals are susceptible to many diseases, particularly cancer. The aging process induces alterations in the microenvironment within the body, including epigenetic changes, alterations in cellular communication, protein homeostasis changes, mitochondrial dysfunction, and cellular senescence [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. These processes manifest as the production of inflammatory mediators and weakening of the immune system, thereby driving the occurrence and progression of tumors in elderly individuals [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Meanwhile, the problem of aging in China is becoming increasingly serious [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], which may concentrate the incidence and mortality rates among the elderly. A study on age-related lung cancer burden in China also suggested that population aging is a primary driving factor for increases in disease burden [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWhen analyzed by gender, it was observed that the burden of lung cancer in males higher than that in females. On the one hand, genetic factors contributed to this gender disparity. Research had identified gender-specific susceptibility genes on the X chromosome, with 24 SNPs found to be associated with male lung cancer cases but not with females [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. On the other hand, from a risk factor perspective, the burden of lung cancer attributable to smoking was notably high among males. In China, the burden of lung cancer due to smoking was 1.26 times the global average level. Chinese males account for approximately 40% of global cigarette consumption [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Although the smoking rate in Fujian was slightly lower than the national level, the male smoking rate reached 48.9% [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. However, between 2015 and 2019, there had been a declining trend in the burden of lung cancer in males. This could be attributed to tobacco control measures implemented by the Chinese government [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e], but further strengthening of anti-smoking policies remained necessary in the future [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Additionally, it is worth noting that the burden of lung cancer in females had been increased in recent years, with projections suggesting a continued upward trend until 2050. Females had needed to be vigilant about the effects of secondhand smoke and household air pollution. A prospective study had found a significant association between secondhand smoke exposure and the occurrence of EGFR mutations [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. What\u0026rsquo;s more, young and middle-aged females are more likely to be frequently exposed to high-temperature cooking fumes in the kitchen. Cooking fumes contain harmful particulate matters and volatile organic compounds, including fine (ultrafine) particles, aldehydes, and polycyclic aromatic hydrocarbons [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Results from a Chinese cohort study showed that long-term exposure to cooking fumes increased the risk of lung cancer in non-smoking females by 1.4 to 3.8-folds [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Moreover, due to genetic factors and estrogen, females had been more susceptible to developing lung adenocarcinoma [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn addition to the aforementioned risk factors, Fujian Province also need to address the burden of lung cancer caused by ambient particulate matter pollution. In 2019, ambient particulate matter pollution ranked as the second-largest factor contributing to lung cancer ASR of DALY in China, following only smoking. This held true for Fujian Province as well. Many strong evidence indicated that air pollution played a driving role in the occurrence and development of lung cancer [\u003cspan additionalcitationids=\"CR51\" citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. With the rapid development of the economy and the acceleration of urbanization, considerable environmental challenges have also been brought to China. China was one of the countries with the worst air quality in the world. In 2017, with 81.1% of the population still lived in areas exceeding the least stringent WHO air quality interim target of 35 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. Fujian has better air quality than other high-pollution areas in China and is recognized as relatively good air quality in the country. In 2021, the PM2.5 level in Fujian Province was 18\u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e], while the national average PM2.5 concentration was 30\u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. This may also be one of the reasons why the burden of lung cancer in Fujian Province was slightly lower than the national average.\u003c/p\u003e \u003cp\u003eBecause of the development of the Chinese economy, the proportion of lung cancer ASR of DALY caused by household air pollution from solid fuels had been decreasing year by year. The number of households using solid fuels had decreased significantly [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. In recent years, the government has taken a series of measures to improve air quality, and further efforts will be needed to advance environmental protection policies in the future. Moreover, in 2019, occupational exposure to asbestos was identified as the third risk factor for global burden of tracheal, bronchus, and lung cancers, especially among males. Asbestos was commonly used in the processing of building materials. However, asbestos produces large clouds of dust during mining, processing and application. Asbestos was classified as a Class I carcinogen by the International Agency for Research on Cancer. Previous studies had indicated that the burden of non-communicable diseases caused by asbestos was higher in high sociodemographic index (SDI) regions, while the burden in medium and low SDI regions was continued to increase [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. In addition, the asbestos-induced lung cancer accounted for 55%-85% of occupational cancers [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. Based on the survey finding [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e], it was revealed that due to the development strategy of the Western Development and strengthened environmental controls in eastern cities in China, asbestos production enterprises were mainly located in western and central regions. The cases of asbestosis were predominantly reported in Tianjin, Beijing, Shandong, and Xinjiang, with fewer cases in Fujian Province, where the number of asbestosis cases was less than 30. It is imperative to continuously improve measures for the prevention and control of occupational asbestos exposure and related diseases. Governments worldwide are strongly encouraged to decrease the use of asbestos.\u003c/p\u003e \u003cp\u003eAge and gender equality in the quality of care are key elements of the health system standards [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. In this study, we did not observe significant gender differences in the quality of care, but differences based on age were evident. The QCI improved with increasing age, possibly due to several reasons. On the one hand, Elderly patients often received more attention and specialized care due to their complex healthcare needs [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. On the other hand, healthcare providers might prioritize elderly patients or allocate more resources to them. A cohort study indicated higher satisfaction with care among elderly cancer patients, who also spent more time with physicians [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. Conversely, the quality of care for younger individuals might be lower due to limited access to healthcare services, lack of awareness about preventive measures, and delays in diagnosis or treatment. Younger individuals might also have different healthcare priorities or face higher financial burden in care [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e], resulting in lower quality care compared to the elderly. Furthermore, this study also observed decreased trends in QCI over the past 30 years. Considering the advancements in medical technology and improvements in healthcare policies, the decline in the quality of lung cancer care seems contrary to expectations. However, several reasons could contribute to this decrease. For instance, societal factors such as changes in environmental pollution, race, and disparities in access to healthcare could impact the incidence and management of lung cancer [\u003cspan additionalcitationids=\"CR62 CR63\" citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e], thus affecting its overall quality of care. Additionally, precision oncology treatments are costly and do not benefit all cancer patients [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. Healthcare policies or resource allocation strategies need to be weighed against cost-effectiveness, leading to potential gaps or inefficiencies in service delivery [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e]. In Fujian Province, a more pronounced decline in QCI was observed. It could be attributed to disparities in the allocation and efficiency of utilization of resources. High-level public hospitals exhibited relatively higher bed occupancy rates, while other hospitals showed lower rates [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]. The workload of hospital physicians may be substantial, potentially impacting the efficiency and quality of medical services. Additionally, investments in health care in Fujian Province might be lower compared to other more economically developed regions in China, indicating a need to further strengthen the construction of the health service system [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e]. Other specific reasons would require higher-level evidence from research to explore and substantiate.\u003c/p\u003e \u003cp\u003eThis study has several strengths. Firstly, it comprehensively analyzed tracheal, bronchial, and lung cancer epidemiological trends in Fujian, informing future healthcare strategies. Secondly, changes in risk factors were identified, guiding updates to comprehensive prevention policies. Lastly, this study used QCI to evaluate healthcare equity for lung cancer populations. However, there are limitations. Firstly, it relied on GBD 2019 data, which has inherent limitations in accuracy. However, GBD collaborators continuously update and improve statistical methods to minimize errors [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e]. Secondly, GBD 2019 lacks data on lung cancer\u0026rsquo;s pathological subtypes, limiting detailed insights into subtype-specific burdens.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe tracheal, bronchial, and lung cancer burden in Fujian Province and China exceeded the global level. The elderly faced disproportionate burdens, with males bearing more than females. However, female burden has increased and is predicted to continue increasing. Key risk factors include smoking, ambient particulate matter pollution, and secondhand smoke. Notably, elderly care quality was high, with no gender disparities observed.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eQCI, Quality-of-Care Index; DALY, disability-adjusted life years; GBD 2019, Global Burden of Disease Study 2019; ASRs, age-standardized rates; AAPCs, average annual percent changes; APCs, annual percent changes; CI, confidence interval; RRs, rate ratios; SSPs, shared socioeconomic pathways; BAPC, Bayesian age-period-cohort; MIR, Mortality-to-Incidence Ratio; YLL, years of life lost; YLD, years lived with disability; PCA, principal component analysis; GDR, gender disparity ratio; UI: uncertainty interval; LDCT, low-dose computed tomography; SDI, sociodemographic index.\u0026nbsp;\u003c/p\u003e\n"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe patients and the public were not involved in the design, conduct, reporting or dissemination of our studies. The data used in this study were obtained from publicly available sources. The institutional review board approval was not required.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData is available in a public, open access repository\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eby the IHME, which is available called the GHDx (Global Health Data Exchange) query tool (http://ghdx.healthdata.org/gbd-results-tool).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by Fujian Province Pilot Project (grant number: 2020Y0060), Fujian Provincial Health Technology Project (grant number: 2020GGA026), and Fujian Provincial Natural Science Foundation Project (grant number: 2023J01093).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eXQL and WLZ had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. SWL and FH conceived and designed the study. SWL drafted of the manuscript. YTD and XQL acquired, analyzed or interpreted data. YTD performed the statistical analysis. XQL, JHZ, FH and WLZ provided technical and material support. All authors made critical revisions to important intellectual content in the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank Tingyang Huang for helping with data analysis, and thank all collaborators for their contribution and the Global Burden of Disease Study collaborators for their work.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eHirsch FR, Scagliotti GV, Mulshine JL, Kwon R, Curran WJ, Wu YL, Paz-Ares L: \u003cstrong\u003eLung cancer: current therapies and new targeted treatments\u003c/strong\u003e. \u003cem\u003eLANCET\u003c/em\u003e 2017, \u003cstrong\u003e389\u003c/strong\u003e(10066):299-311.\u003c/li\u003e\n\u003cli\u003eBray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A: \u003cstrong\u003eGlobal cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries\u003c/strong\u003e. \u003cem\u003eCA Cancer J Clin\u003c/em\u003e 2018, \u003cstrong\u003e68\u003c/strong\u003e(6):394-424.\u003c/li\u003e\n\u003cli\u003eZhao J, Xu L, Sun J, Song M, Wang L, Yuan S, Zhu Y, Wan Z, Larsson S, Tsilidis K\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eGlobal trends in incidence, death, burden and risk factors of early-onset cancer from 1990 to 2019\u003c/strong\u003e. \u003cem\u003eBMJ Oncology\u003c/em\u003e 2023, \u003cstrong\u003e2\u003c/strong\u003e(1):e000049.\u003c/li\u003e\n\u003cli\u003eCao W, Chen HD, Yu YW, Li N, Chen WQ: \u003cstrong\u003eChanging profiles of cancer burden worldwide and in China: a secondary analysis of the global cancer statistics 2020\u003c/strong\u003e. \u003cem\u003eChin Med J (Engl)\u003c/em\u003e 2021, \u003cstrong\u003e134\u003c/strong\u003e(7):783-791.\u003c/li\u003e\n\u003cli\u003eZhou Y, Xiang Z, Lin W, Lin J, Wen Y, Wu L, Ma J, Chen C: \u003cstrong\u003eLong-term trends of lung cancer incidence and survival in southeastern China, 2011-2020: a population-based study\u003c/strong\u003e. \u003cem\u003eBMC PULM MED\u003c/em\u003e 2024, \u003cstrong\u003e24\u003c/strong\u003e(1):25.\u003c/li\u003e\n\u003cli\u003eSamet JM, Avila-Tang E, Boffetta P, Hannan LM, Olivo-Marston S, Thun MJ, Rudin CM: \u003cstrong\u003eLung cancer in never smokers: clinical epidemiology and environmental risk factors\u003c/strong\u003e. \u003cem\u003eCLIN CANCER RES\u003c/em\u003e 2009, \u003cstrong\u003e15\u003c/strong\u003e(18):5626-5645.\u003c/li\u003e\n\u003cli\u003eHaddad DN, Sandler KL, Henderson LM, Rivera MP, Aldrich MC: \u003cstrong\u003eDisparities in Lung Cancer Screening: A Review\u003c/strong\u003e. \u003cem\u003eAnn Am Thorac Soc\u003c/em\u003e 2020, \u003cstrong\u003e17\u003c/strong\u003e(4):399-405.\u003c/li\u003e\n\u003cli\u003eMederos N, Friedlaender A, Peters S, Addeo A: \u003cstrong\u003eGender-specific aspects of epidemiology, molecular genetics and outcome: lung cancer\u003c/strong\u003e. \u003cem\u003eESMO Open\u003c/em\u003e 2020, \u003cstrong\u003e5\u003c/strong\u003e(Suppl 4):e000796.\u003c/li\u003e\n\u003cli\u003eMohammadi E, Ghasemi E, Azadnajafabad S, Rezaei N, Saeedi MS, Ebrahimi MS, Fattahi N, Habibi Z, Karimi YK, Amirjamshidi A\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eA global, regional, and national survey on burden and Quality of Care Index (QCI) of brain and other central nervous system cancers; global burden of disease systematic analysis 1990-2017\u003c/strong\u003e. \u003cem\u003ePLOS ONE\u003c/em\u003e 2021, \u003cstrong\u003e16\u003c/strong\u003e(2):e0247120.\u003c/li\u003e\n\u003cli\u003eKeykhaei M, Masinaei M, Mohammadi E, Azadnajafabad S, Rezaei N, Saeedi MS, Rezaei N, Nasserinejad M, Abbasi-Kangevari M, Malekpour MR\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eA global, regional, and national survey on burden and Quality of Care Index (QCI) of hematologic malignancies; global burden of disease systematic analysis 1990-2017\u003c/strong\u003e. \u003cem\u003eExp Hematol Oncol\u003c/em\u003e 2021, \u003cstrong\u003e10\u003c/strong\u003e(1):11.\u003c/li\u003e\n\u003cli\u003eGeng J, Zhao J, Fan R, Zhu Z, Zhang Y, Zhu Y, Yang Y, Xu L, Lin X, Hu K\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eGlobal, regional, and national burden and quality of care of multiple myeloma, 1990-2019\u003c/strong\u003e. \u003cem\u003eJ GLOB HEALTH\u003c/em\u003e 2024, \u003cstrong\u003e14\u003c/strong\u003e:4033.\u003c/li\u003e\n\u003cli\u003eIHME|GHDx. 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China, 1997-2019\u003c/strong\u003e. \u003cem\u003eChina CDC Wkly\u003c/em\u003e 2020, \u003cstrong\u003e2\u003c/strong\u003e(18):305-309.\u003c/li\u003e\n\u003cli\u003eKing B, Pecanac K, Krupp A, Liebzeit D, Mahoney J: \u003cstrong\u003eImpact of Fall Prevention on Nurses and Care of Fall Risk Patients\u003c/strong\u003e. \u003cem\u003eGERONTOLOGIST\u003c/em\u003e 2018, \u003cstrong\u003e58\u003c/strong\u003e(2):331-340.\u003c/li\u003e\n\u003cli\u003eGrealish L, Ranse K, Todd JA, Armit L, Billett S, Collier L, Bail K, Moyle W: \u003cstrong\u003eBarriers and enablers to embedding fundamental nursing care for older patients-Implications of a mixed methods study for nursing leadership\u003c/strong\u003e. \u003cem\u003eJ ADV NURS\u003c/em\u003e 2023, \u003cstrong\u003e79\u003c/strong\u003e(3):1162-1173.\u003c/li\u003e\n\u003cli\u003eMariano C, Hanson LC, Deal AM, Yang H, Bensen J, Hendrix L, Muss HB: \u003cstrong\u003eHealthcare satisfaction in older and younger patients with cancer\u003c/strong\u003e. \u003cem\u003eJ GERIATR ONCOL\u003c/em\u003e 2016, \u003cstrong\u003e7\u003c/strong\u003e(1):32-38.\u003c/li\u003e\n\u003cli\u003eLee NW, Wang HY, Du CL, Yuan TH, Chen CY, Yu CJ, Chan CC: \u003cstrong\u003eAir-polluted environmental heavy metal exposure increase lung cancer incidence and mortality: A population-based longitudinal cohort study\u003c/strong\u003e. \u003cem\u003eSCI TOTAL ENVIRON\u003c/em\u003e 2022, \u003cstrong\u003e810\u003c/strong\u003e:152186.\u003c/li\u003e\n\u003cli\u003eJiwnani S, Penumadu P, Ashok A, Pramesh CS: \u003cstrong\u003eLung Cancer Management in Low and Middle-Income Countries\u003c/strong\u003e. \u003cem\u003eTHORAC SURG CLIN\u003c/em\u003e 2022, \u003cstrong\u003e32\u003c/strong\u003e(3):383-395.\u003c/li\u003e\n\u003cli\u003eFilchner K, Zoucha R, Lockhart JS, Denlinger CS: \u003cstrong\u003eLung Cancer Survivor Experiences With Post-Treatment Care: An Integrative Review\u003c/strong\u003e. \u003cem\u003eONCOL NURS FORUM\u003c/em\u003e 2022, \u003cstrong\u003e49\u003c/strong\u003e(2):167-184.\u003c/li\u003e\n\u003cli\u003eMapanga W, Norris SA, Chen WC, Blanchard C, Graham A, Baldwin-Ragaven L, Boyles T, Donde B, Greef L, Huddle K\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eConsensus study on the health system and patient-related barriers for lung cancer management in South Africa\u003c/strong\u003e. \u003cem\u003ePLOS ONE\u003c/em\u003e 2021, \u003cstrong\u003e16\u003c/strong\u003e(2):e0246716.\u003c/li\u003e\n\u003cli\u003eShih YT, Pan IW, Teich N: \u003cstrong\u003eGlobal Challenges in Access to and Implementation of Precision Oncology: The Health Care Manager and Health Economist Perspective\u003c/strong\u003e. \u003cem\u003eAm Soc Clin Oncol Educ Book\u003c/em\u003e 2022, \u003cstrong\u003e42\u003c/strong\u003e:429-437.\u003c/li\u003e\n\u003cli\u003eLuengo-Fernandez R, Leal J, Gray A, Sullivan R: \u003cstrong\u003eEconomic burden of cancer across the European Union: a population-based cost analysis\u003c/strong\u003e. \u003cem\u003eLANCET ONCOL\u003c/em\u003e 2013, \u003cstrong\u003e14\u003c/strong\u003e(12):1165-1174.\u003c/li\u003e\n\u003cli\u003eFujian Provincial Health Commission. Available: \u003cstrong\u003ehttps://wjw.fujian.gov.cn/jggk/csxx/ghyxxc/xxtj_41288/202310/t20231023_6280147.htm.\u003c/strong\u003e [Accessed 05.06, 2024].\u003c/li\u003e\n\u003cli\u003eFujian Provincial Health Commission. Available: \u003cstrong\u003ehttps://wjw.fj.gov.cn/xxgk/gzdt/mtbd/202202/t20220216_5837079.htm.\u003c/strong\u003e [Accessed 05.06, 2024].\u003c/li\u003e\n\u003cli\u003eGBD 2017 DALYs and HALE Collaborators. \u003cstrong\u003eGlobal, regional, and national disability-adjusted life-years (DALYs) for 359 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017\u003c/strong\u003e. \u003cem\u003eLANCET\u003c/em\u003e 2018, \u003cstrong\u003e392\u003c/strong\u003e(10159):1859-1922.\u003cbr\u003e \u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table 2","content":"\u003cp\u003eTable 2 is available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Lung cancer, disease burden, temporal trend, prediction, risk factor, quality of care","lastPublishedDoi":"10.21203/rs.3.rs-4688998/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4688998/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThis study aims to explore the temporal trends of tracheal, bronchus, and lung cancer burden in Fujian Province, China, and globally. Additionally, changes in attributable risk factors and the quality of care were evaluated.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eBased on data from the Fujian Provincial Center for Disease Control and Prevention and the Global Burden of Disease (GBD), the age-standardized rates (ASRs) of incidence, death, and disability-adjusted life years (DALY) were collected and analyzed. Joinpoint regression analysis and age-period-cohort models were used to estimate temporal trends, and principal component analysis is used to estimate the quality-of-care index (QCI).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eIn 2019, the ASRs of incidence, death, and DALYs in 2019 were 39.08, 35.29, and 778.39 per 100,000 in Fujian Province, respectively. From 1990 to 2019, ASRs increased, with average annual percent changes (AAPCs) of 1.08 (95% confidence interval [CI]: 0.77 to 1.38), 0.65 (95% CI: 0.35 to 0.95), and 0.18 (95% CI: -0.07 to 0.42), respectively. When analyzed age, the burden sharply increased after age 50. By gender, the ASRs of male incidence, death, and DALY in Fujian Province were all over 3-folds higher than in females. However, females burden showed increasing trend from 2015 to 2019. While DALY ASRs attributed to ambient particulate matter pollution increased significantly, solid fuels in households decreased compared to 1990. Moreover, we founded that QCI increased with age. The temporal trends indicated decrease in QCI from 1990 to 2019.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe burden of tracheal, bronchus, and lung cancer in Fujian Province remained significant. Smoking, secondhand smoke, and ambient particulate matter pollution were the main risk factors. The quality of care for patients needed improvement.\u003c/p\u003e","manuscriptTitle":"Contrasting Tracheal, Bronchus, and Lung Cancer Burdens and Care Quality: A Comparative Analysis of China and Global Trends ","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-09 14:31:55","doi":"10.21203/rs.3.rs-4688998/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-03-17T15:08:07+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-03-17T05:39:40+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-03-17T05:04:37+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-03-16T00:41:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"205876711220812476894587744239263631727","date":"2025-03-08T06:14:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"125369064599765777152587986052921247819","date":"2025-03-07T22:34:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"284030965975069436339286867635661381237","date":"2025-03-07T14:40:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"178051690596167667304385634987583727033","date":"2025-03-06T21:28:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"275102675848243855079992454724488661710","date":"2025-03-06T19:29:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"188801752408713055977466879369896486476","date":"2025-03-05T18:28:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"126095775353103840468626193967351179135","date":"2024-08-27T00:21:48+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-08-12T10:08:44+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-07-09T17:53:12+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-07-05T11:00:47+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-07-05T11:00:37+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cancer","date":"2024-07-05T01:54:36+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a0636bf8-1f3b-4bd5-9a84-f04cb639086f","owner":[],"postedDate":"August 9th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-08-18T16:06:39+00:00","versionOfRecord":{"articleIdentity":"rs-4688998","link":"https://doi.org/10.1186/s12885-025-14645-4","journal":{"identity":"bmc-cancer","isVorOnly":false,"title":"BMC Cancer"},"publishedOn":"2025-08-11 15:58:04","publishedOnDateReadable":"August 11th, 2025"},"versionCreatedAt":"2024-08-09 14:31:55","video":"","vorDoi":"10.1186/s12885-025-14645-4","vorDoiUrl":"https://doi.org/10.1186/s12885-025-14645-4","workflowStages":[]},"version":"v1","identity":"rs-4688998","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4688998","identity":"rs-4688998","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}