Bronchus and lung cancer-related mortality trends in the United States from 1999 to 2023

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This study analyzed the mortality trends related to bronchus and lung cancer among U.S. adults ≥ 25 years old from 1999 to 2023 from demographic and geographic perspectives. Methods We utilized the CDC WONDER database to investigate the trends in Bronchus and lung cancer-related mortality in the United States. Age-adjusted mortality rates per 100,000 people (AAMR), annual percentage change (APC), and average annual percentage change (AAPC) with 95% confidence intervals (CIs) were calculated and the data were stratified by year, age groups, sex, race/ethnicity, census region, urban-rural and states classification. The Joinpoint Regression Program was utilized to estimate mortality trends between 1999 and 2023. Results From 1999 to 2023, there was a significant decline in AAMRs for bronchus and lung cancer across the United States. The crude mortality rate (CMR) for bronchus and lung cancer demonstrates a significant decline across most age groups males had higher AAMRs than females, with persistent disparities highlighting the need for targeted interventions. Non-Hispanic Black individuals had the highest AAMRs, while Hispanic or Latino individuals had the lowest. Geographic disparities were evident, with the West region having the lowest mortality rates compared to the South and Midwest regions; nonmetropolitan had higher mortality rates than metropolitan. Compared to 1999, AAMRs decreased in all U.S. states in 2023, with the most significant declines observed in the District of Columbia, Nevada, and California. The slight increase in AAMRs from 2020 to 2023 may be linked to the COVID-19 pandemic, further emphasizing the importance of ongoing surveillance and adaptive public health measures. Conclusion It is crucial to assess potential health disparities among different regions and population groups. There is an urgent need for further research and the implementation of targeted public health interventions, as well as improvements in resource allocation and health outcomes among populations. CDC WONDER Bronchus and lung cancer Mortality trends Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 1. Introduction Bronchus and lung cancer is one of the most common and deadly types of cancer in United States. It is a malignant disease characterized by the uncontrolled growth of abnormal cells in the lungs, which can invade surrounding tissues and spread to other parts of the body through the bloodstream or lymphatic system. 1 , 2 The two main types of lung cancer are non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC), with NSCLC being the most prevalent form. 3 , 4 It has been well-documented that bronchus and lung cancer is frequently the result of chronic exposure to carcinogens, most notably cigarette smoke, which remains the leading cause of bronchus and lung cancer globally. 5 In addition to smoking, exposure to other harmful substances has also been shown to play a significant role in the development of the disease, including radon gas, asbestos, workplace exposure to chemical fumes (such as arsenic, chromium, and nickel compounds), and air pollution. In response to persistent exposure to these carcinogens, genetic mutations and epigenetic changes occur in the lung cells, leading to the transformation of normal cells into cancerous ones. 5 , 6 Bronchus and lung cancer is characterized by a range of nonspecific symptoms in its early stages, including persistent cough, chest pain, shortness of breath, and hemoptysis. As the disease progresses, patients may experience more severe symptoms such as weight loss, fatigue, and bone pain. These symptoms often indicate advanced stages of the disease, which significantly complicates treatment and worsens prognosis. 6 , 7 In terms of treatment, bronchus and lung cancer management is highly dependent on the stage of the disease and the patient's overall health. For early-stage non-small cell lung cancer (NSCLC), surgical resection remains the primary treatment option, offering the potential for cure. However, for patients who are not surgical candidates, stereotactic body radiation therapy (SBRT) provides an effective alternative. 8 In advanced stages, targeted therapies and immunotherapies have emerged as promising options, especially for those with specific genetic mutations or without actionable targets. Chemotherapy continues to play a crucial role when other treatments are not applicable. 2 , 7 Despite therapeutic progress, bronchus and lung cancer continues to pose a substantial health challenge in the United States. It remains the primary cause of cancer-related mortality, with around 235,000 new cases diagnosed and over 125,000 deaths each year. 9 While recent initiatives have contributed to a reduction in mortality rates, the high incidence rate underscores the persistent difficulty in managing this disease. 9 In this study, the Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research (CDC WONDER) database was examined from 1999 to 2023 to assess concurrent mortality trends of lung cancer in the United States, stratified by age groups, sex, race/ethnicity, census region and urban-rural, state. 10 This analysis is crucial for developing targeted interventions to mitigate the disease burden. 2. Methods 2.1 Research Context and population To investigate mortality trends related to bronchus and lung cancer, we utilized death certificate data from the CDC WONDER database, covering the period from 1999 to 2023. Diagnostic coding was based on the International Classification of Diseases, 10th Revision (ICD-10) 11 , using codes C34.0, C34.1, C34.2, C34.3, C34.8, and C34.9 to identify cases of lung and bronchus cancer. The study focused on Bronchus and Lung Cancer-related deaths among individuals aged more than 25 years in the United States. This age range was selected because lung cancer is uncommon in individuals under 25 years of age, and we aimed to focus on the older population, where the prevalence of this disease is higher 12–14 . The study adhered to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines 15 . Since the data were de-identified and publicly available, no institutional review board approval was required. 2.2 Data extraction Population size, year, demographics, geographic division, state-specific data were included. Demographics referring to age, sex(classified as male or female), and race/ethnicity. As seen in similar studies, age groups were defined as 25–34, 35–44, 45–54, 55–64, 65–74, 75–84, and 85+ years of age 16 , and race/ethnicity was categorized into Hispanic, Non-Hispanic (NH) Black, NH White, and NH Other groups (including NH Asian or Pacific Islander, NH Hawaiians, NH American Indian or Alaska Native, among others) 17 . For geographic variables: The urban-rural classification was based on the National Center for Health Statistics (NCHS) scheme, which categorizes areas into Metropolitan and nonmetropolitan regions. The former regions include Large Central Metro, Large Fringe Metro, Medium Metro, and Small Metro, while the latter include Micropolitan (Nonmetro) and Noncore (Nonmetro) in the database 18 . Due to missing urban-rural data for 2021–2023, the corresponding stratified analyses for these years were not conducted in this study. States include the District of Columbia, all 50 states, and other states being included. Categorization of geographical areas into the Northeast, Midwest, South, and West regions was done via the United States Census Bureau’s criteria 18 . The data utilized in the analysis was death certificate reported information and has also been a source for earlier research using the aforementioned database. 2.3 Statistical analysis To examine national trends in bronchus and lung cancer mortality from 1999 to 2023, we computed both crude and age-adjusted mortality rates (AAMRs) per 100,000 population. These rates were analyzed by age group, sex, race/ethnicity, census region, urban-rural classification and states, with 95% confidence intervals (CIs) provided. Crude rates were derived by dividing Bronchus and Lung Cancer deaths by the U.S. population for each year. AAMRs were standardized to the 2000 U.S. population 19 . We used the Joinpoint Regression Program (Version 5.0) to calculate annual percentage changes (APCs) and 95% CIs for AAMRs to evaluate annual trends 20 . The weighted average of APCs, reported as average annual percentage changes (AAPCs) with 95% CIs, summarized the overall mortality trend. APCs and AAPCs were considered significant if the slope of mortality change over time was significantly different from zero (p ≤ 0.05) by a two-tailed t-test. All data processing and graphical analyses were conducted using RStudio (version 4.4.3). 3. Results Between 1999 and 2023, there were 3778807 Bronchus and Lung Cancer-related deaths in the United States (Table 1). The overall Bronchus and Lung Cancer-related AAMR was 55.41 in 1999, decreasing to 29.49 in 2023 per 1,000,000 individuals, with an average annual percentage change (AAPC) of -2.6268 (Table 3). Initially, there was a non-significant decrease from 1999 to 2002 (APC: -0.26; 95% CI: -1.41 to 0.90). However, this trend changed significantly from 2002 to 2010, with a substantial decline observed during this period (APC: -1.84; 95% CI: -2.15 to -1.54). After 2010, the decline continued, with a significant decrease through 2014 (APC: -3.00; 95% CI: -4.12 to -1.86). This downward trend persisted from 2014 to 2019, with a notable acceleration in the rate of decrease (APC: -4.65; 95% CI: -5.37 to -3.92). Finally, after 2019, there was a significant decrease through 2023 (APC: -3.02; 95% CI: -3.79 to -2.24)(Figure 1). 3.1 Stratification by Age Group Throughout the study period, the crude mortality rates (CMRs) were highest among adults aged ≥85 years, falling from 296.85 in 1999 to 275.79 in 2023 (AAPC: -0.55, 95% CI: -0.86 to -0.24) (Table 2). Marked reductions were also observed in adults aged 75–84 years (361.89 to 225.96, AAPC: -2.02, 95% CI: -2.24 to -1.79), with the steepest decline occurring between 2012 and 2023 (APC: -3.78; 95% CI: -4.01 to -3.55). A sustained downward trajectory was documented for the 65–74 age group (281.29 to 128.58, AAPC: -3.238, 95% CI: -3.51 to -2.96). Successively younger cohorts exhibited progressively sharper decreases, 55–64, 45–54 and 35–44 years—each with AAPC values of -3.277, -4.50 and -5.16, respectively (all P < 0.05). The 25–34 age group maintained the lowest CMRs throughout, remaining below 0.5 per 100 000 and decreasing modestly (AAPC: -2.515, 95% CI: -3.07 to -1.96) (Figure 2, Figure 3). 3.2 Stratification by Sex In the sex-stratified analysis, age-adjusted mortality rates (AAMR) remained consistently higher among males than females from 1999 to 2023(Table 4); however, the decline was markedly steeper in males (AAPC: males -3.35; 95% CI -3.68 to -3.01; females -1.85; 95% CI: -2.09 to -1.61). The sharpest decrease for males occurred between 2015 and 2018 (APC -5.62; 95% CI: -7.72 to -3.47). While female AAMR also exhibited a sustained and significant downward trend, albeit with a gentler slope (Table 3, Table 4 and Figure 1). 3.3 Stratification by Race/Ethnicity When stratified by race/ethnicity, AAMRs in 1999 showed a clear gradient: non-Hispanic Black (NH Black) had the highest burden at 101.50 (95%CI: 99.91 to 103.10), followed by non-Hispanic White（NH White）at 88.43 (95%CI: 87.95 to 88.92), non-Hispanic Other (NH Other) at 45.79 (95%CI: 43.87 to 7.70), and Hispanic or Latino at the lowest level, 38.68(95%CI: 37.35 to 40.01)(Table 5). Notably, NH Black experienced the sharpest decline in AAMR over the study period, with an AAPC of -3.05 (95% CI: -3.26 to -2.83). The steepest reduction occurred between 2013 and 2020, reaching an APC of -4.95 (95% CI: -5.33 to -4.57). Consequently, the NH Black AAMR first fell below that of NH White in 2015 and has remained lower ever since, while the NH White rate has stayed above all other racial/ethnic groups. In contrast, Hispanic or Latino and NH Other groups experienced more gradual declines, yet their AAMRs have consistently remained below those of the other two groups (Table 5, Figure 4). 3.4 Stratification by Census Region Across all census regions, AAMRs declined steadily and significantly throughout the study period. (Table 6) The South and Midwest maintained comparatively high levels, with nearly identical rates and trajectories (AAPC: -2.66%; 95% CI: -2.92 to -2.40 versus -2.80%; 95% CI: -3.12 to -2.48, respectively) (Table 3). By contrast, the West consistently recorded the lowest AAMR and exhibited the steepest decline nationwide (AAPC -3.21%; 95% CI: -3.57 to -2.84) (Table 3, Figure 5). 3.5 Stratification by Urban-Rural Overall, AAMRs declined in both metropolitan and non-metropolitan areas throughout the study period, with metropolitan areas experienced the sharper decrease (Table 3, Table 7). From 1999 to 2020, AAMRs in metropolitan fell steadily, registering an overall AAPC of -2.83 (95% CI: -2.99 to -2.66); the most pronounced drop occurred between 2014 and 2020 (APC: -4.79%; 95% CI: -4.97 to -4.61) (Table 3, Table 7, Figure 6). In non-metropolitan, AAMRs likewise trended downward, interrupted only by modest upticks in 2000 and 2007, and the overall decline was more gradual compared with metropolitan (AAPC: -1.73; 95% CI: -1.97 to -1.48) (Table 3, Table 7, Figure 6). 3.6 Stratification by State Across all states, the AAMRs for bronchus and lung cancer showed a consistent decline from 1999 to 2023(Table 8, Figure 7). The percent change of AAMR values were all negative, ranged from -32% to -59% (Table 8), indicating a reduction in mortality rates over the 25-year period. The District of Columbia exhibited the largest reduction in mortality rates, with a percent change of -59%. Nevada and California followed closely, with percent changes of -57% and -56%, respectively. In 1999, the highest AAMR was observed in Mississippi (108.93 per 100,000), while the lowest was in Utah (40.87 per 100,000). By 2023, the highest AAMR was in Kentucky (75.62 per 100,000), and the lowest remained in Utah (23.76 per 100,000) (Table 8, Figure 7). The overall reduction in AAMRs was substantial, with many states experiencing a more than 50% decrease in mortality rates. Despite the general downward trend, there was significant variability in the magnitude of the decline among different states. States such as Kentucky, West Virginia, and Louisiana still had relatively high AAMRs in 2023, although they also showed notable reductions compared to 1999. In contrast, states like Utah, Colorado, and Washington exhibited lower initial AAMRs in 1999 and maintained lower levels in 2023 (Table 8, Figure 7). 4. Discussion The overall decline in bronchus and lung cancer-related mortality from 1999 to 2023 in the United States is a promising trend, likely attributable to a combination of factors including heightened awareness of the dangers of smoking, reduced accessibility and affordability of cigarettes, and improved treatment options 21 , 22 . However, several notable disparities and trends found in this study warrant further investigation and targeted interventions. The analysis of Bronchus and Lung Cancer mortality rates across different age groups from 1999 to 2023 reveals significant trends and patterns that provide valuable insights into the disease dynamics over time. The data show a consistent decline in crude mortality rates across most age groups, indicating improvements in healthcare, early detection, and treatment options for Bronchus and Lung Cancer 23 , 24 . Consistent with previous research, males exhibited higher AAMRs than females throughout the study period 9 . This difference may be partly explained by historical smoking patterns, as men have traditionally had higher smoking rates than women 21 , 22 . Additionally, biological and physiological differences between sexes could also contribute to the observed disparities. For instance, men may have a higher susceptibility to the carcinogenic effects of tobacco smoke or other risk factors. While both sexes experienced significant declines in AAMRs over the years, the steeper decline in males compared to females suggests that targeted smoking cessation programs and other preventive measures for men may have been particularly effective 24 , 25 . However, continued efforts are needed to address the remaining gap and ensure that both sexes benefit equally from public health initiatives. The observed disparities in AAMRs among different racial and ethnic groups highlight the complex interplay of genetic, socioeconomic, and environmental factors in lung cancer mortality. Non-Hispanic (NH) Black individuals had the highest AAMRs, which is concerning given their relatively lower smoking prevalence compared to NH White individuals 23 , 26 . This suggests that other factors such as genetic predisposition, environmental exposures, and healthcare access may play a significant role in the higher mortality rates among this group. On the other hand, Hispanic or Latino populations had the lowest AAMRs, potentially due to protective factors such as lower smoking rates and possibly genetic or lifestyle factors that reduce their susceptibility to lung cancer 27 . The significant declines in AAMRs observed among all racial/ ethnic groups indicate the positive impact of broad public health measures 28 . The differences in AAMRs across census regions and urban-rural classifications highlight the importance of regional and local factors in lung cancer mortality. The Northeast region, which had the higher initial AAMRs, experienced a significant decline over the study period, possibly due to early adoption of smoking cessation programs and better access to healthcare. In contrast, the Midwest and South regions, which had highest AAMRs in the later years, may require more focused efforts to address the underlying causes of lung cancer mortality. The higher AAMRs in non-metropolitan areas compared to metropolitan areas could be attributed to several factors, including limited access to specialized healthcare, fewer smoking cessation resources, and potentially higher exposure to environmental carcinogens such as radon 29 – 31 . The significant declines in AAMRs in both metropolitan and non-metropolitan areas indicate that efforts to reduce lung cancer mortality have been effective across different settings. However, the continued higher rates in non-metropolitan areas suggest that targeted interventions are needed to address the unique challenges faced by these communities. For example, increasing the availability of smoking cessation programs and improving access to lung cancer screening in rural areas could help reduce the mortality gap 29 , 32 . The substantial variability in AAMRs among different states highlights the importance of state-specific factors in lung cancer mortality. States such as Kentucky, West Virginia, and Arkansas, which had relatively high AAMRs in 2023, may benefit from targeted public health initiatives and policy changes to reduce smoking rates and improve access to healthcare. In contrast, states like Utah, Colorado, and New Mexico, which had lower initial AAMRs and maintained lower levels in 2023, may serve as models for other states to emulate. The large reductions in AAMRs observed in many states indicate the potential for further improvements through sustained efforts to address the risk factors and underlying causes of lung cancer 33 . State-level policies such as tobacco control measures, funding for cancer screening programs, and support for research into novel treatments could play a crucial role in reducing lung cancer mortality. The slight increase in AAMRs from 2020 to 2023 may be partly attributed to the COVID-19 pandemic. The pandemic led to disruptions in healthcare services, delays in cancer screening and treatment, and increased exposure to respiratory infections, all of which could have contributed to higher lung cancer mortality rates. Additionally, the stress and lifestyle changes associated with the pandemic may have led to increased smoking rates or other unhealthy behaviors that could have exacerbated the risk of lung cancer. Further research is needed to fully understand the impact of the COVID-19 pandemic on lung cancer mortality and to develop strategies to mitigate any long-term effects 34 . 5. Conclusion This study on bronchus and lung cancer-related mortality in the United States from 1999 to 2023 revealed several key findings: There was a significant decrease in age-adjusted mortality rates (AAMRs) for bronchus and lung cancer across the United States, indicating progress in reducing the burden of this disease. The crude mortality rate for Bronchus and Lung Cancer demonstrates a significant decline across most age groups, highlighting the positive impact of advancements in medical technology, public health interventions, and improved treatment protocols. Males consistently had higher AAMRs than females, highlighting the need for targeted interventions to address smoking and other risk factors among men. Non-Hispanic Black individuals had the highest AAMRs, while Hispanic or Latino individuals had the lowest. This underscores the importance of tailored public health strategies to address disparities in these populations. Significant differences were observed across census regions and urban-rural classifications, with the West region having the lowest mortality rates compared to the Northeast and Midwest regions; nonmetropolitan had higher mortality rates than metropolitan. Compared to 1999, AAMRs decreased in all U.S. states in 2023, with the most significant declines observed in the District of Columbia, Nevada, and California. A slight increase in AAMRs from 2020 to 2023 may be attributed to the COVID-19 pandemic, emphasizing the need for ongoing surveillance and adaptive public health measures. 6. Limitations and Future Research This study has several limitations. The reliance on death certificate data and ICD-10 codes may introduce misclassification bias, potentially underestimating or overestimating lung cancer mortality rates. Additionally, the lack of individual-level data on smoking status, comorbidities, and other risk factors limits the ability to draw definitive conclusions about the underlying causes of the observed trends. Future research should aim to incorporate more detailed individual-level data to provide a more comprehensive understanding of the factors contributing to lung cancer mortality. Furthermore, studies should focus on identifying the specific mechanisms underlying the observed disparities and developing targeted interventions to address these disparities. 7. Countributions Conception and design: Mingfeng Wei, Huibiao Zhang, Xiaoyong Shen; administrative support: Mingfeng Wei, Xiaoyu Chen, Wei Cheng, Xuelin Zhang; database acquisition and cleaning: Mingfeng Wei, Xiaoyu Chen, Wei Cheng, Lefei Hu, Shixiang Guo; data analysis and interpretation: Mingfeng Wei, Xiaoyu Chen, Wei Cheng, Zheng Li, Huibiao Zhang, Xiaoyong Shen; manuscript writing: all authors; final approval of manuscript: all authors Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Competing interests The authors declare no competing interests. Author Contribution Conception and design: Mingfeng Wei, Huibiao Zhang, Xiaoyong Shen; administrative support: Mingfeng Wei, Xiaoyu Chen, Wei Cheng, Xuelin Zhang; database acquisition and cleaning: Mingfeng Wei, Xiaoyu Chen, Wei Cheng, Lefei Hu, Shixiang Guo; data analysis and interpretation: Mingfeng Wei, Xiaoyu Chen, Wei Cheng, Zheng Li, Huibiao Zhang, Xiaoyong Shen; manuscript writing: all authors; final approval of manuscript: all authors. References Siegel RL, Miller KD, Fuchs HE, Jemal A. Cancer statistics, 2022. CA Cancer J Clin . 2022;72(1):7-33. doi:10.3322/caac.21708 Hj X, J Z, D ZM, N ZD, A EB, T T. Inhibiting tumour metastasis by DQA modified paclitaxel plus ligustrazine micelles in treatment of non-small-cell lung cancer. Artif Cells Nanomed Biotechnol . 2019;47(1). doi:10.1080/21691401.2019.1653900 Hendriks LEL, Remon J, Faivre-Finn C, et al. Non-small-cell lung cancer. 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Demographic disparities in lung cancer mortality and trends in the United States from 1999 through 2020: a population-based CDC database analysis. J Natl Compr Cancer Netw: JNCCN . 2024;22(6):e247004. doi:10.6004/jnccn.2024.7004 Telehealth in response to the COVID-19 pandemic: implications for rural health disparities - PubMed. Accessed June 6, 2025. https://pubmed.ncbi.nlm.nih.gov/32589735/ Tables Table 1. Overall Bronchus and Lung Cancer-related Mortality per 1,000,000 Adults in the United States, 1999 to 2023 Year Deaths Population Age-Adjusted Mortality Rate (95% CI) 1999 152063 279040168 55.41 (55.14 – 55.69) 2000 155431 281421906 56.07 (55.79 – 56.35) 2001 155973 284968955 55.31 (55.04 – 55.59) 2002 157630 287625193 54.93 (54.65 – 55.20) 2003 157992 290107933 54.10 (53.83 – 54.37) 2004 158009 292805298 53.22 (52.96 – 53.49) 2005 159220 295516599 52.65 (52.39 – 52.91) 2006 158600 298379912 51.51 (51.26 – 51.77) 2007 158686 301231207 50.59 (50.34 – 50.84) 2008 158592 304093966 49.50 (49.25 – 49.74) 2009 158086 306771529 48.33 (48.09 – 48.57) 2010 158249 308745538 47.61 (47.37 – 47.84) 2011 156957 311591917 45.98 (45.75 – 46.21) 2012 157426 313914040 44.87 (44.65 – 45.10) 2013 156178 316128839 43.35 (43.13 – 43.57) 2014 155529 318857056 42.08 (41.87 – 42.29) 2015 153722 321418820 40.48 (40.28 – 40.69) 2016 148870 323127513 38.35 (38.15 – 38.54) 2017 145849 325719178 36.60 (36.41 – 36.79) 2018 142081 327167434 34.75 (34.57 – 34.94) 2019 139603 328239523 33.41 (33.23 – 33.58) 2020 136084 329484123 31.84 (31.67 – 32.01) 2021 134504 331893745 31.73 (31.56 – 31.91) 2022 131889 333287557 30.05 (29.88 – 30.21) 2023 131584 334914895 29.49 (29.33 – 29.65) Table 2 Crude Mortality Rate per 100,100 adults of Bronchus and Lung Cancer in the United States stratified by age groups, 1999 to 2023 Year Crude Mortality Rate per 100,100 adults 25-34 35-44 45-54 55-64 65-74 75-84 85+ 1999 0.44 (0.38 – 0.51) 6.04 (5.81 – 6.27) 31.24 (30.67 – 31.82) 123.33 (121.92 – 124.74) 281.29 (278.87 – 283.71) 361.89 (358.52 – 365.26) 296.85 (291.61 – 302.08) 2000 0.49 (0.42 – 0.56) 6.10 (5.87 – 6.32) 31.59 (31.03 – 32.16) 122.39 (121.00 – 123.78) 283.98 (281.55 – 286.42) 370.59 (367.19 – 373.98) 301.94 (296.71 – 307.17) 2001 0.40 (0.34 – 0.46) 6.20 (5.97 – 6.43) 30.55 (30.00 – 31.09) 118.54 (117.19 – 119.88) 278.50 (276.09 – 280.91) 370.64 (367.28 – 374.00) 308.96 (303.72 – 314.21) 2002 0.42 (0.36 – 0.48) 6.03 (5.81 – 6.26) 30.35 (29.81 – 30.89) 114.84 (113.55 – 116.12) 273.20 (270.81 – 275.59) 376.53 (373.16 – 379.89) 312.26 (307.02 – 317.50) 2003 0.39 (0.33 – 0.45) 5.61 (5.38 – 5.83) 30.29 (29.76 – 30.82) 110.44 (109.21 – 111.67) 266.81 (264.46 – 269.17) 376.78 (373.43 – 380.13) 315.26 (310.05 – 320.47) 2004 0.37 (0.31 – 0.43) 5.53 (5.31 – 5.75) 29.88 (29.36 – 30.41) 106.03 (104.85 – 107.20) 262.54 (260.21 – 264.86) 372.91 (369.59 – 376.23) 317.67 (312.49 – 322.85) 2005 0.34 (0.28 – 0.39) 5.33 (5.12 – 5.55) 29.67 (29.15 – 30.19) 102.31 (101.18 – 103.44) 256.17 (253.89 – 258.46) 374.87 (371.55 – 378.18) 328.17 (322.99 – 333.35) 2006 0.39 (0.33 – 0.46) 4.68 (4.47 – 4.88) 29.11 (28.60 – 29.62) 98.04 (96.95 – 99.12) 249.23 (247.00 – 251.46) 372.03 (368.73 – 375.33) 326.93 (321.85 – 332.01) 2007 0.34 (0.28 – 0.40) 4.32 (4.12 – 4.52) 28.37 (27.87 – 28.86) 94.18 (93.14 – 95.23) 244.36 (242.17 – 246.54) 369.39 (366.10 – 372.69) 327.89 (322.89 – 332.89) 2008 0.36 (0.30 – 0.42) 3.80 (3.61 – 3.99) 28.16 (27.67 – 28.66) 90.12 (89.11 – 91.12) 235.46 (233.36 – 237.56) 366.52 (363.24 – 369.81) 332.82 (327.86 – 337.78) 2009 0.36 (0.30 – 0.41) 3.65 (3.47 – 3.83) 27.82 (27.33 – 28.31) 87.42 (86.44 – 88.39) 228.50 (226.47 – 230.54) 359.66 (356.40 – 362.92) 327.84 (322.99 – 332.68) 2010 0.39 (0.33 – 0.45) 3.29 (3.11 – 3.46) 26.84 (26.37 – 27.32) 85.34 (84.39 – 86.29) 223.75 (221.76 – 225.74) 357.14 (353.90 – 360.38) 332.25 (327.43 – 337.07) 2011 0.29 (0.24 – 0.34) 3.10 (2.93 – 3.27) 25.68 (25.21 – 26.15) 83.44 (82.52 – 84.35) 214.21 (212.30 – 216.12) 345.88 (342.71 – 349.06) 323.61 (318.95 – 328.26) 2012 0.41 (0.35 – 0.47) 2.89 (2.73 – 3.06) 25.08 (24.61 – 25.55) 81.49 (80.59 – 82.39) 205.97 (204.15 – 207.78) 339.44 (336.31 – 342.58) 323.47 (318.88 – 328.07) 2013 0.29 (0.24 – 0.34) 2.83 (2.67 – 2.99) 23.84 (23.38 – 24.29) 79.91 (79.02 – 80.79) 196.54 (194.81 – 198.27) 328.36 (325.30 – 331.42) 319.78 (315.27 – 324.29) 2014 0.30 (0.25 – 0.35) 2.73 (2.57 – 2.89) 22.38 (21.94 – 22.83) 78.41 (77.54 – 79.28) 189.31 (187.65 – 190.97) 321.04 (318.04 – 324.04) 311.61 (307.20 – 316.02) 2015 0.30 (0.25 – 0.35) 2.50 (2.34 – 2.65) 20.44 (20.02 – 20.87) 76.79 (75.95 – 77.64) 180.85 (179.26 – 182.43) 306.16 (303.25 – 309.07) 315.99 (311.60 – 320.39) 2016 0.28 (0.23 – 0.33) 2.18 (2.04 – 2.33) 18.53 (18.12 – 18.94) 73.19 (72.37 – 74.01) 167.85 (166.35 – 169.35) 295.30 (292.48 – 298.13) 305.03 (300.75 – 309.32) 2017 0.24 (0.20 – 0.29) 2.06 (1.92 – 2.20) 16.48 (16.09 – 16.86 70.21 (69.41 – 71.02) 160.45 (159.01 – 161.89) 283.41 (280.69 – 286.13) 295.11 (290.93 – 299.30) 2018 0.26 (0.21 – 0.31) 1.89 (1.76 – 2.03) 15.04 (14.67 – 15.42) 68.48 (67.70 – 69.27) 150.84 (149.47 – 152.22) 267.79 (265.21 – 270.38) 286.06 (281.96 – 290.15) 2019 0.23 (0.18 – 0.27) 1.85 (1.72 – 1.98) 13.63 (13.28 – 13.99) 64.76 (64.00 – 65.53) 144.26 (142.94 – 145.59) 260.78 (258.28 – 263.29) 281.11 (277.06 – 285.15) 2020 0.27 (0.22 – 0.32) 1.79 (1.66 – 1.92) 12.51 (12.17 – 12.86) 62.83 (62.08 – 63.59) 139.94 (138.66 – 141.23) 246.10 (243.71 – 248.50) 262.10 (258.22 – 265.99) 2021 0.26 (0.21 – 0.30) 1.78 (1.66 – 1.91) 11.91 (11.58 – 12.25) 60.47 (59.74 – 61.21) 134.45 (133.21 – 135.69) 248.76 (246.33 – 251.19) 289.25 (284.94 – 293.56) 2022 0.25 (0.21 – 0.30) 1.76 (1.64 – 1.88) 11.08 (10.76 – 11.41) 57.92 (57.19 – 58.65) 131.86 (130.63 – 133.08) 232.48 (230.22 – 234.73) 259.81 (255.89 – 263.73) 2023 0.27 (0.23 – 0.32) 1.66 (1.54 – 1.78) 10.55 (10.24 – 10.87) 55.52 (54.81 – 56.24) 128.58 (127.38 – 129.77) 225.96 (223.78 – 228.13) 275.79 (271.65 – 279.92) Table 3 Annual Percentage Changes (APCs) and Average Annual Percentage Changes (AAPCs) in Bronchus and Lung Cancer-related mortality in the United States from 1999 to 2023. Variable Lower Endpoint – Upper Endpoint APC (95% CI) P-value AAPC (95% CI) P-value Overall 1999 – 2002 -0.26 ( -1.41 – 0.90) 0.629609 -2.63 (-2.92 to -2.34) <0.000001 2002 – 2010 -1.84 ( -2.15 – -1.54) <0.000001 2010 – 2014 -3.00 ( -4.12 – -1.86) 0.000127 2014 – 2019 -4.65 ( -5.37 – -3.92) <0.000001 2019 – 2023 -3.02 ( -3.79 – -2.24) 0.000004 Sex Male 1999 – 2001 -0.93 ( -2.99 – 1.17) 0.347079 -3.35 (-3.68 to -3.01) <0.000001 2001 – 2010 -2.48 ( -2.71 – -2.26) <0.000001 2010 – 2015 -3.83 ( -4.48 – -3.16) <0.000001 2015 – 2018 -5.62 ( -7.72 – -3.47) 0.000148 2018 – 2023 -3.99 ( -4.50 – -3.48) <0.000001 Female 1999 – 2002 0.98 ( -0.08 – 2.06) 0.066034 -1.85 (-2.09 to -1.61) <0.000001 2002 – 2008 -0.90 ( -1.35 – -0.45) 0.001087 2008 – 2014 -2.09 ( -2.54 – -1.65) 0.000001 2014 – 2020 -4.08 ( -4.52 – -3.63) <0.000001 2020 – 2023 -1.52 ( -2.57 – -0.46) 0.009454 Race/Ethnicity Hispanic or Latino 1999 – 2014 -2.12 ( -2.34 – -1.90) <0.000001 -2.73 (-3.30 to -2.16) <0.000001 2014 – 2017 -5.59 ( -9.92 – -1.05) 0.019404 2017 – 2023 -2.81 ( -3.57 – -2.04) 0.000001 NH Black 1999 – 2004 -1.60 ( -2.10 – -1.09) 0.00001 -3.05 (-3.26 to -2.83) <0.000001 2004 – 2013 -2.57 ( -2.82 – -2.33) <0.000001 2013 – 2020 -4.95 ( -5.33 – -4.57) <0.000001 2020 – 2023 -2.38 ( -3.59 – -1.15) 0.001022 NH White 1999 – 2001 0.61 ( -1.62 – 2.90) 0.562185 -2.32 (-2.60 to -2.04) <0.000001 2001 – 2008 -1.31 ( -1.68 – -0.94) 0.000009 2008 – 2014 -2.48 ( -2.97 – -1.98) <0.000001 2014 – 2019 -4.41 ( -5.13 – -3.69) <0.000001 2019 – 2023 -2.66 ( -3.43 – -1.88) 0.000013 NH Other 1999 – 2011 -0.83 ( -1.15 – -0.51) 0.000029 -2.16 (-2.35 to -1.97) <0.000001 2011 – 2023 -3.46 ( -3.71 – -3.22) <0.000001 Census Region Midwest 1999 – 2002 0.18 ( -1.12 – 1.49) 0.772914 -2.09 (-2.40 to -1.79) <0.000001 2002 – 2008 -1.10 ( -1.66 – -0.53) 0.00143 2008 – 2014 -2.06 ( -2.63 – -1.49) 0.000007 2014 – 2019 -4.34 ( -5.15 – -3.53) <0.000001 2019 – 2023 -2.46 ( -3.32 – -1.58) 0.000073 Northeast 1999 – 2002 -0.56 ( -1.81 – 0.69) 0.3434 -2.80 (-3.12 to -2.48) <0.000001 2002 – 2010 -1.69 ( -2.02 – -1.35) <0.000001 2010 – 2015 -3.11 ( -3.91 – -2.30) 0.000004 2015 – 2020 -5.20 ( -6.03 – -4.36) <0.000001 2020 – 2023 -3.41 ( -4.83 – -1.96) 0.000325 South 1999 – 2005 -0.93 ( -1.41 – -0.45) 0.001001 -2.66 (-2.92 to -2.40) <0.000001 2005 – 2013 -2.45 ( -2.82 – -2.08) <0.000001 2013 – 2019 -4.39 ( -5.01 – -3.77) <0.000001 2019 – 2023 -3.03 ( -3.95 – -2.10) 0.000007 West 1999 – 2009 -2.14 ( -2.40 – -1.88) <0.000001 -3.21 (-3.57 to -2.84) <0.000001 2009 – 2015 -3.76 ( -4.49 – -3.02) <0.000001 2015 – 2019 -5.44 ( -7.11 – -3.75) 0.000009 2019 – 2023 -2.76 ( -3.89 – -1.62) 0.000145 Urban-Rural Metropolitan 1999 – 2001 -0.36 ( -1.40 – 0.70) 0.456499 -2.83 (-2.99 to -2.66) <0.000001 2001 – 2005 -1.53 ( -2.04 – -1.02) 0.000131 2005 – 2010 -2.24 ( -2.56 – -1.91) <0.000001 2010 – 2014 -3.08 ( -3.59 – -2.57) 0.000001 2014 – 2020 -4.79 ( -4.97 – -4.61) <0.000001 Nonmetropolitan 1999 – 2001 1.40 ( -0.68 – 3.52) 0.167806 -1.73 (-1.97 to -1.48) <0.000001 2001 – 2008 -0.78 ( -1.12 – -0.44) 0.000362 2008 – 2014 -1.86 ( -2.31 – -1.42) 0.000002 2014 – 2020 -3.70 ( -4.04 – -3.35) <0.000001 Table 4 . Bronchus and Lung Cancer-related Mortality per 1,000,000 Adults in the United States stratified by sex, 1999 to 2023 Year Age-Adjusted Mortality Rate (95% CI) Female Male 1999 62.18 (61.70 – 62.67) 118.78 (117.99 – 119.57) 2000 63.86 (63.37 – 64.35) 118.59 (117.81 – 119.38) 2001 63.51 (63.02 – 64.00) 116.27 (115.50 – 117.04) 2002 64.30 (63.81 – 64.78) 113.52 (112.77 – 114.27) 2003 63.83 (63.34 – 64.31) 110.99 (110.25 – 111.73) 2004 63.27 (62.79 – 63.75) 108.42 (107.70 – 109.14) 2005 62.79 (62.32 – 63.26) 106.86 (106.15 – 107.56) 2006 62.05 (61.58 – 62.51) 103.61 (102.92 – 104.30) 2007 61.92 (61.46 – 62.38) 100.38 (99.71 – 101.05) 2008 60.42 (59.97 – 60.87) 98.17 (97.51 – 98.83) 2009 59.66 (59.21 – 60.10) 94.88 (94.24 – 95.52) 2010 58.91 (58.47 – 59.34) 93.17 (92.54 – 93.80) 2011 57.27 (56.84 – 57.70) 89.23 (88.63 – 89.84) 2012 56.25 (55.84 – 56.67) 86.67 (86.08 – 87.26) 2013 54.83 (54.42 – 55.24) 83.07 (82.50 – 83.63) 2014 53.65 (53.25 – 54.05) 79.86 (79.32 – 80.41) 2015 51.75 (51.36 – 52.14) 76.54 (76.01 – 77.07) 2016 49.23 (48.85 – 49.60) 72.19 (71.68 – 72.70) 2017 47.33 (46.97 – 47.70) 68.55 (68.06 – 69.04) 2018 45.31 (44.95 – 45.66) 64.54 (64.08 – 65.01) 2019 43.55 (43.21 – 43.89) 61.94 (61.49 – 62.39) 2020 41.64 (41.31 – 41.97) 58.84 (58.41 – 59.28) 2021 42.14 (41.81 – 42.48) 57.83 (57.40 – 58.27) 2022 40.25 (39.93 – 40.57) 54.46 (54.04 – 54.87) 2023 39.92 (39.60 – 40.23) 52.68 (52.28 – 53.08) Table 5 . Bronchus and Lung Cancer-related Mortality per 1,000,000 Adults in the United States stratified by race, 1999 to 2023 Year Age-Adjusted Mortality Rate (95% CI) Hispanic or Latino NH Black NH White NH Other 1999 38.68 (37.35 – 40.01) 101.50 (99.91 – 103.10) 88.43 (87.95 – 88.92) 45.79 (43.87 – 47.70) 2000 38.23 (36.94 – 39.53) 100.30 (98.72 – 101.87) 89.99 (89.50 – 90.47) 45.13 (43.28 – 46.98) 2001 36.98 (35.75 – 38.20) 97.94 (96.39 – 99.48) 89.21 (88.73 – 89.69) 46.68 (44.86 – 48.51) 2002 37.45 (36.24 – 38.65) 97.12 (95.60 – 98.64) 88.72 (88.25 – 89.20) 43.09 (41.39 – 44.79) 2003 36.68 (35.52 – 37.85) 95.55 (94.06 – 97.04) 87.55 (87.08 – 88.02) 44.83 (43.14 – 46.52) 2004 35.80 (34.67 – 36.93) 93.70 (92.23 – 95.17) 86.36 (85.90 – 86.82) 44.96 (43.32 – 46.59) 2005 36.05 (34.96 – 37.15) 91.76 (90.32 – 93.19) 85.78 (85.32 – 86.24) 43.92 (42.34 – 45.49) 2006 33.41 (32.38 – 34.44) 88.86 (87.47 – 90.26) 84.27 (83.82 – 84.72) 42.71 (41.20 – 44.23) 2007 33.82 (32.80 – 34.83) 86.96 (85.59 – 88.32) 82.93 (82.48 – 83.38) 43.48 (41.98 – 44.97) 2008 33.46 (32.48 – 34.44) 83.57 (82.24 – 84.89) 81.31 (80.87 – 81.75) 43.02 (41.57 – 44.47) 2009 31.59 (30.66 – 32.52) 81.22 (79.93 – 82.51) 79.79 (79.36 – 80.22) 41.63 (40.23 – 43.02) 2010 31.55 (30.63 – 32.46) 81.35 (80.07 – 82.63) 78.45 (78.02 – 78.87) 41.82 (40.45 – 43.18) 2011 30.52 (29.65 – 31.39) 78.00 (76.77 – 79.23) 76.09 (75.68 – 76.51) 41.13 (39.82 – 42.45) 2012 29.66 (28.83 – 30.50) 76.61 (75.41 – 77.82) 74.22 (73.81 – 74.62) 40.25 (39.00 – 41.51) 2013 28.92 (28.12 – 29.72) 74.45 (73.28 – 75.61) 71.94 (71.54 – 72.33) 38.70 (37.50 – 39.90) 2014 28.23 (27.46 – 29.00) 70.67 (69.55 – 71.79) 70.23 (69.84 – 70.62) 37.79 (36.65 – 38.93) 2015 27.40 (26.67 – 28.14) 66.61 (65.54 – 67.67) 67.74 (67.36 – 68.12) 36.91 (35.83 – 38.00) 2016 25.73 (25.03 – 26.43) 63.64 (62.62 – 64.67) 64.23 (63.87 – 64.60) 35.50 (34.46 – 36.55) 2017 24.05 (23.39 – 24.71) 60.02 (59.04 – 61.00) 61.74 (61.38 – 62.09) 33.55 (32.56 – 34.53) 2018 23.32 (22.68 – 23.95) 57.06 (56.12 – 58.00) 58.75 (58.41 – 59.10) 31.57 (30.63 – 32.50) 2019 22.93 (22.31 – 23.54) 55.13 (54.22 – 56.04) 56.43 (56.10 – 56.76) 31.19 (30.28 – 32.09) 2020 21.74 (21.16 – 22.33) 51.61 (50.74 – 52.48) 54.04 (53.71 – 54.36) 30.13 (29.26 – 31.00) 2021 21.90 (21.32 – 22.49) 51.64 (50.77 – 52.52) 54.20 (53.88 – 54.53) 29.14 (28.34 – 29.95) 2022 21.04 (20.49 – 21.60) 49.86 (49.01 – 50.71) 51.30 (50.99 – 51.61) 28.08 (27.32 – 28.84) 2023 20.21 (19.67 – 20.75) 47.87 (47.05 – 48.69) 50.66 (50.35 – 50.97) 27.68 (26.94 – 28.43) Table 6 . Bronchus and Lung Cancer-related Mortality per 1,000,000 Adults in the United States stratified by Census Region, 1999 to 2023 Year Age-Adjusted Mortality Rate (95% CI) Midwest Northeast South West 1999 87.36 (86.46 – 88.26) 81.35 (80.42 – 82.27) 93.51 (92.75 – 94.26) 74.81 (73.91 – 75.71) 2000 87.96 (87.06 – 88.85) 82.04 (81.12 – 82.96) 95.48 (94.72 – 96.24) 74.64 (73.75 – 75.53) 2001 87.94 (87.04 – 88.83) 80.66 (79.75 – 81.57) 93.92 (93.18 – 94.67) 73.32 (72.45 – 74.20) 2002 87.85 (86.97 – 88.74) 80.29 (79.39 – 81.19) 93.33 (92.60 – 94.07) 71.89 (71.04 – 72.75) 2003 86.64 (85.76 – 87.51) 78.83 (77.94 – 79.72) 91.71 (90.99 – 92.43) 71.35 (70.51 – 72.19) 2004 86.68 (85.81 – 87.55) 77.43 (76.55 – 78.30) 90.44 (89.73 – 91.15) 68.23 (67.41 – 69.04) 2005 85.10 (84.24 – 85.96) 76.68 (75.81 – 77.55) 89.98 (89.28 – 90.68) 67.41 (66.61 – 68.21) 2006 84.01 (83.16 – 84.85) 75.23 (74.37 – 76.09) 87.60 (86.92 – 88.29) 65.58 (64.80 – 66.37) 2007 83.72 (82.88 – 84.56) 74.62 (73.77 – 75.48) 84.99 (84.32 – 85.65) 64.13 (63.37 – 64.90) 2008 82.24 (81.42 – 83.07) 72.52 (71.69 – 73.36) 83.40 (82.74 – 84.05) 62.38 (61.63 – 63.13) 2009 80.42 (79.61 – 81.23) 70.42 (69.61 – 71.24) 81.55 (80.91 – 82.19) 61.11 (60.38 – 61.84) 2010 79.21 (78.41 – 80.01) 70.13 (69.32 – 70.95) 80.37 (79.74 – 81.00) 59.41 (58.70 – 60.12) 2011 77.19 (76.40 – 77.97) 67.80 (67.00 – 68.59) 77.52 (76.92 – 78.13) 56.74 (56.05 – 57.43) 2012 76.07 (75.30 – 76.84) 66.49 (65.71 – 67.27) 75.57 (74.97 – 76.16) 54.61 (53.95 – 55.27) 2013 73.71 (72.95 – 74.46) 64.32 (63.56 – 65.08) 73.11 (72.53 – 73.68) 52.51 (51.87 – 53.15) 2014 72.82 (72.08 – 73.56) 61.57 (60.83 – 62.30) 70.92 (70.36 – 71.48) 50.55 (49.93 – 51.17) 2015 69.73 (69.01 – 70.45) 59.73 (59.01 – 60.45) 67.68 (67.14 – 68.22) 49.46 (48.85 – 50.06) 2016 66.55 (65.86 – 67.25) 56.91 (56.21 – 57.61) 64.43 (63.92 – 64.95) 45.64 (45.07 – 46.21) 2017 63.92 (63.24 – 64.59) 53.20 (52.54 – 53.87) 61.54 (61.04 – 62.04) 44.06 (43.51 – 44.62) 2018 60.40 (59.75 – 61.05) 51.44 (50.79 – 52.09) 58.73 (58.25 – 59.21) 40.95 (40.42 – 41.47) 2019 58.59 (57.96 – 59.23) 48.70 (48.07 – 49.32) 56.53 (56.07 – 57.00) 39.22 (38.71 – 39.73) 2020 56.08 (55.47 – 56.70) 45.68 (45.08 – 46.29) 54.15 (53.70 – 54.60) 37.43 (36.94 – 37.92) 2021 56.38 (55.76 – 57.00) 44.33 (43.74 – 44.92) 54.01 (53.56 – 54.47) 37.71 (37.22 – 38.21) 2022 53.31 (52.72 – 53.90) 42.63 (42.06 – 43.20) 50.80 (50.37 – 51.22) 35.77 (35.30 – 36.25) 2023 52.94 (52.35 – 53.53) 41.46 (40.91 – 42.02) 49.92 (49.50 – 50.34) 34.72 (34.26 – 35.18) Table 7 . Bronchus and Lung Cancer-related Mortality in the United States stratified by urban-rural, 1999 to 2020 Year * Age-Adjusted Mortality Rate (95% CI) Metropolitan Nonmetropolitan 1999 84.95 (84.47 – 85.42) 89.16 (88.13 – 90.18) 2000 85.40 (84.93 – 85.88) 92.54 (91.50 – 93.58) 2001 84.22 (83.76 – 84.69) 91.73 (90.70 – 92.75) 2002 83.43 (82.97 – 83.89) 91.92 (90.90 – 92.94) 2003 82.14 (81.69 – 82.60) 90.68 (89.67 – 91.68) 2004 80.64 (80.19 – 81.09) 90.07 (89.07 – 91.06) 2005 79.63 (79.19 – 80.07) 89.89 (88.90 – 90.88) 2006 77.76 (77.33 – 78.19) 88.33 (87.36 – 89.31) 2007 75.93 (75.51 – 76.36) 88.80 (87.83 – 89.77) 2008 74.28 (73.87 – 74.70) 87.00 (86.05 – 87.95) 2009 72.45 (72.05 – 72.85) 85.53 (84.59 – 86.47) 2010 71.34 (70.94 – 71.74) 84.47 (83.54 – 85.40) 2011 68.57 (68.18 – 68.95) 83.31 (82.39 – 84.22) 2012 66.91 (66.54 – 67.29) 81.31 (80.42 – 82.21) 2013 64.60 (64.24 – 64.96) 79.10 (78.23 – 79.98) 2014 62.53 (62.18 – 62.89) 77.83 (76.97 – 78.70) 2015 60.04 (59.70 – 60.38) 75.60 (74.75 – 76.45) 2016 56.61 (56.28 – 56.94) 72.90 (72.07 – 73.72) 2017 54.08 (53.77 – 54.40) 69.65 (68.84 – 70.45) 2018 51.31 (51.00 – 51.61) 66.37 (65.60 – 67.15) 2019 49.15 (48.86 – 49.44) 64.70 (63.94 – 65.46) 2020 46.68 (46.40 – 46.97) 62.74 (62.00 – 63.49) * Due to missing urban-rural data for 2021–2023, the corresponding stratified analyses for these years were not conducted in this study. Table 8 AAMRs per 100 000 adults and Percent Change of Bronchus and Lung Cancer of District of Columbia, all 50 states in the United States in 1999 and 2023. State AAMR 2023 AAMR 1999 Percent Change (%) * District of Columbia 33.88 83.45 -59.40 Nevada 42.76 98.99 -56.80 California 32.70 74.32 -56.00 New Jersey 37.20 81.82 -54.53 Arizona 35.06 76.58 -54.23 Montana 37.88 82.43 -54.05 Washington 41.20 88.51 -53.45 Maryland 42.48 90.54 -53.08 New York 36.42 77.24 -52.85 Texas 40.66 85.24 -52.30 Rhode Island 45.56 92.77 -50.88 Georgia 45.54 92.61 -50.82 Colorado 30.94 62.38 -50.40 Oregon 42.03 84.24 -50.11 Massachusetts 42.01 83.51 -49.70 Delaware 53.32 105.52 -49.47 Florida 44.25 87.37 -49.35 Virginia 47.10 90.68 -48.05 New Hampshire 45.55 86.83 -47.54 Wyoming 42.19 80.16 -47.37 New Mexico 31.05 58.52 -46.94 Alaska 44.23 82.85 -46.62 Connecticut 40.98 75.47 -45.70 South Carolina 51.40 92.92 -44.68 Illinois 48.81 87.56 -44.26 Pennsylvania 48.57 84.52 -42.53 Louisiana 58.23 101.22 -42.47 North Carolina 54.19 93.79 -42.22 Utah 23.76 40.87 -41.86 Mississippi 63.55 108.93 -41.66 Alabama 56.83 96.65 -41.19 Idaho 39.12 66.51 -41.17 Vermont 50.02 84.83 -41.04 Minnesota 43.46 73.11 -40.55 Ohio 56.73 94.21 -39.79 South Dakota 46.60 76.90 -39.41 Maine 54.43 89.72 -39.33 Nebraska 48.37 79.37 -39.06 Indiana 61.88 101.34 -38.95 Hawaii 34.64 56.72 -38.92 Wisconsin 46.06 75.23 -38.77 Tennessee 63.74 103.84 -38.61 Arkansas 64.41 104.84 -38.57 West Virginia 70.08 113.35 -38.18 Kansas 51.85 83.33 -37.78 Oklahoma 60.96 96.76 -37.00 Michigan 54.82 87.00 -36.99 Missouri 61.57 95.78 -35.72 Iowa 51.21 78.47 -34.74 Kentucky 75.62 114.36 -33.88 North Dakota 43.53 64.29 -32.29 * Percent Change = (AAMR 2023 - AAMR 1999)/AAMR 1999)*100% Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 16 Apr, 2026 Read the published version in Journal of Cardiothoracic Surgery → Version 1 posted Editorial decision: Revision requested 25 Jan, 2026 Reviews received at journal 18 Jan, 2026 Reviews received at journal 12 Jan, 2026 Reviewers agreed at journal 10 Jan, 2026 Reviewers agreed at journal 08 Jan, 2026 Reviewers agreed at journal 01 Jan, 2026 Reviews received at journal 08 Oct, 2025 Reviewers agreed at journal 04 Sep, 2025 Reviewers agreed at journal 29 Aug, 2025 Reviewers invited by journal 28 Aug, 2025 Editor assigned by journal 13 Aug, 2025 Submission checks completed at journal 13 Aug, 2025 First submitted to journal 06 Aug, 2025 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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12:23:47","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7309766/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7309766/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s13019-026-04075-z","type":"published","date":"2026-04-16T15:56:55+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":90601871,"identity":"b1645a06-1385-4da3-85ea-50a6fd1dbd8a","added_by":"auto","created_at":"2025-09-04 14:42:54","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":72420,"visible":true,"origin":"","legend":"\u003cp\u003eAAMRs per 100 000 adults of Bronchus and Lung Cancer, stratified by sex in in the United States between 1999 and 2023. The * denotes the APC that was found to be statistically significant at α \u0026lt; 0.05\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7309766/v1/b8536e78003edfd4a4284f6d.png"},{"id":90602256,"identity":"e89cdff3-73be-4d72-b72c-14340a792b25","added_by":"auto","created_at":"2025-09-04 14:50:54","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":794239,"visible":true,"origin":"","legend":"\u003cp\u003eTen year age group joinpoint analysis of bronchus and lung cancer crude rate mortality per 100,000 adults, 1999–2023\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7309766/v1/5bc4809a5afa06ef3a486834.png"},{"id":90601872,"identity":"4746e65c-b63e-41f2-aea0-58d7a065719e","added_by":"auto","created_at":"2025-09-04 14:42:54","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":139075,"visible":true,"origin":"","legend":"\u003cp\u003eAAMRs per 100 000 adults of Bronchus and Lung Cancer, stratified by age groups in in the United States between 1999 and 2023. The * denotes the APC that was found to be statistically significant at α \u0026lt; 0.05\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7309766/v1/0e04efab0e299eb0ac3369da.png"},{"id":90600778,"identity":"7cf57eef-14d8-4056-93a3-ccc59cd9473f","added_by":"auto","created_at":"2025-09-04 14:34:54","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":113778,"visible":true,"origin":"","legend":"\u003cp\u003eAAMRs per 100 000 adults of Bronchus and Lung Cancer, stratified by race in the United States between 1999 and 2023. The * denotes the APC that was found to be statistically significant at α \u0026lt; 0.05\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7309766/v1/fae7bd5ac3da2420ec0113f7.png"},{"id":90602263,"identity":"2195d606-0428-4127-ad6c-624b161f4994","added_by":"auto","created_at":"2025-09-04 14:50:55","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":126760,"visible":true,"origin":"","legend":"\u003cp\u003eThe AAMRs per 100 000 adults of Bronchus and Lung Cancer, stratified by census region in the United States between 1999 and 2023. The * denotes the APC that was found to be statistically significant at α \u0026lt; 0.05\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7309766/v1/c4818f5ae4298c29af4b0c5f.png"},{"id":90600780,"identity":"a4faeec9-d6f6-4d68-851e-d6035a70aa5d","added_by":"auto","created_at":"2025-09-04 14:34:54","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":86031,"visible":true,"origin":"","legend":"\u003cp\u003eAAMRs per 100 000 adults of Bronchus and Lung Cancer, stratified by census region in the United States between 1999 and 2023. The * denotes the APC that was found to be statistically significant at α \u0026lt; 0.05\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-7309766/v1/24c5e896993c41ed5ddc7738.png"},{"id":90602257,"identity":"a2206a70-6ffb-4d06-a5aa-15c6451258e3","added_by":"auto","created_at":"2025-09-04 14:50:54","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":129108,"visible":true,"origin":"","legend":"\u003cp\u003eFigure A , AAMRs per 100 000 of Bronchus and Lung Cancer of District of Columbia, all 50 states in the United States in 1999. Figure B , AAMRs per 100 000 adults of Bronchus and Lung Cancer of District of Columbia, all 50 states in the United States in 2023.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-7309766/v1/536c10d93ff086f29e82b1e8.png"},{"id":107350735,"identity":"2fea4b70-ca5a-43c7-a8ab-a449e36ad09c","added_by":"auto","created_at":"2026-04-20 16:02:01","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2718693,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7309766/v1/f4f17309-4db5-4fe0-8eda-4691f9cd4f73.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Bronchus and lung cancer-related mortality trends in the United States from 1999 to 2023","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eBronchus and lung cancer is one of the most common and deadly types of cancer in United States. It is a malignant disease characterized by the uncontrolled growth of abnormal cells in the lungs, which can invade surrounding tissues and spread to other parts of the body through the bloodstream or lymphatic system.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e The two main types of lung cancer are non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC), with NSCLC being the most prevalent form.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eIt has been well-documented that bronchus and lung cancer is frequently the result of chronic exposure to carcinogens, most notably cigarette smoke, which remains the leading cause of bronchus and lung cancer globally.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e In addition to smoking, exposure to other harmful substances has also been shown to play a significant role in the development of the disease, including radon gas, asbestos, workplace exposure to chemical fumes (such as arsenic, chromium, and nickel compounds), and air pollution. In response to persistent exposure to these carcinogens, genetic mutations and epigenetic changes occur in the lung cells, leading to the transformation of normal cells into cancerous ones.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eBronchus and lung cancer is characterized by a range of nonspecific symptoms in its early stages, including persistent cough, chest pain, shortness of breath, and hemoptysis. As the disease progresses, patients may experience more severe symptoms such as weight loss, fatigue, and bone pain. These symptoms often indicate advanced stages of the disease, which significantly complicates treatment and worsens prognosis.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eIn terms of treatment, bronchus and lung cancer management is highly dependent on the stage of the disease and the patient's overall health. For early-stage non-small cell lung cancer (NSCLC), surgical resection remains the primary treatment option, offering the potential for cure. However, for patients who are not surgical candidates, stereotactic body radiation therapy (SBRT) provides an effective alternative.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e In advanced stages, targeted therapies and immunotherapies have emerged as promising options, especially for those with specific genetic mutations or without actionable targets. Chemotherapy continues to play a crucial role when other treatments are not applicable.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eDespite therapeutic progress, bronchus and lung cancer continues to pose a substantial health challenge in the United States. It remains the primary cause of cancer-related mortality, with around 235,000 new cases diagnosed and over 125,000 deaths each year.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e While recent initiatives have contributed to a reduction in mortality rates, the high incidence rate underscores the persistent difficulty in managing this disease.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e In this study, the Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research (CDC WONDER) database was examined from 1999 to 2023 to assess concurrent mortality trends of lung cancer in the United States, stratified by age groups, sex, race/ethnicity, census region and urban-rural, state.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e This analysis is crucial for developing targeted interventions to mitigate the disease burden.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cp\u003e\u003cstrong\u003e2.1 Research Context and population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo investigate mortality trends related to bronchus and lung cancer, we utilized death certificate data from the CDC WONDER database, covering the period from 1999 to 2023. Diagnostic coding was based on the International Classification of Diseases, 10th Revision (ICD-10)\u003csup\u003e11\u003c/sup\u003e, using codes C34.0, C34.1, C34.2, C34.3, C34.8, and C34.9 to identify cases of lung and bronchus cancer. The study focused on Bronchus and Lung Cancer-related deaths among individuals aged more than 25 years in the United States. This age range was selected because lung cancer is uncommon in individuals under 25 years of age, and we aimed to focus on the older population, where the prevalence of this disease is higher\u003csup\u003e12\u0026ndash;14\u003c/sup\u003e. The study adhered to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines\u003csup\u003e15\u003c/sup\u003e. Since the data were de-identified and publicly available, no institutional review board approval was required.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2 Data extraction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePopulation size, year, demographics, geographic division, state-specific data were included. Demographics referring to age, sex(classified as male or female), and race/ethnicity. As seen in similar studies, age groups were defined as 25\u0026ndash;34, 35\u0026ndash;44, 45\u0026ndash;54, 55\u0026ndash;64, 65\u0026ndash;74, 75\u0026ndash;84, and 85+ years of age\u003csup\u003e16\u003c/sup\u003e, and race/ethnicity was categorized into Hispanic, Non-Hispanic (NH) Black, NH White, and NH Other groups (including NH Asian or Pacific Islander, NH Hawaiians, NH American Indian or Alaska Native, among others)\u003csup\u003e17\u003c/sup\u003e. For geographic variables: The urban-rural classification was based on the National Center for Health Statistics (NCHS) scheme, which categorizes areas into Metropolitan and nonmetropolitan regions. The former regions include Large Central Metro, Large Fringe Metro, Medium Metro, and Small Metro, while the latter include Micropolitan (Nonmetro) and Noncore (Nonmetro) in the database\u003csup\u003e18\u003c/sup\u003e.\u0026nbsp;Due to missing urban-rural data for 2021\u0026ndash;2023, the corresponding stratified analyses for these years were not conducted in this study. States include the District of Columbia, all 50 states, and other states being included. Categorization of geographical areas into the Northeast, Midwest, South, and West regions was done via the United States Census Bureau\u0026rsquo;s criteria\u003csup\u003e18\u003c/sup\u003e. The data utilized in the analysis was death certificate reported information and has also been a source for earlier research using the aforementioned database.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3 Statistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo examine national trends in bronchus and lung cancer mortality from 1999 to 2023, we computed both crude and age-adjusted mortality rates (AAMRs) per 100,000 population. These rates were analyzed by age group, sex, race/ethnicity, census region, urban-rural classification and states, with 95% confidence intervals (CIs) provided. Crude rates were derived by dividing Bronchus and Lung Cancer deaths by the U.S. population for each year. AAMRs were standardized to the 2000 U.S. population\u003csup\u003e19\u003c/sup\u003e. We used the Joinpoint Regression Program (Version 5.0) to calculate annual percentage changes (APCs) and 95% CIs for AAMRs to evaluate annual trends\u003csup\u003e20\u003c/sup\u003e. The weighted average of APCs, reported as average annual percentage changes (AAPCs) with 95% CIs, summarized the overall mortality trend. APCs and AAPCs were considered significant if the slope of mortality change over time was significantly different from zero (p \u0026le; 0.05) by a two-tailed t-test. All data processing and graphical analyses were conducted using RStudio (version 4.4.3).\u003c/p\u003e"},{"header":"3. Results","content":"\u003cp\u003eBetween 1999 and 2023, there were 3778807 Bronchus and Lung Cancer-related deaths in the United States (Table 1). The overall Bronchus and Lung Cancer-related AAMR was 55.41 in 1999, decreasing to 29.49 in 2023 per 1,000,000 individuals, with an average annual percentage change (AAPC) of -2.6268 (Table 3). Initially, there was a non-significant decrease from 1999 to 2002 (APC: -0.26; 95% CI: -1.41 to 0.90). However, this trend changed significantly from 2002 to 2010, with a substantial decline observed during this period (APC: -1.84; 95% CI: -2.15 to -1.54). After 2010, the decline continued, with a significant decrease through 2014 (APC: -3.00; 95% CI: -4.12 to -1.86). This downward trend persisted from 2014 to 2019, with a notable acceleration in the rate of decrease (APC: -4.65; 95% CI: -5.37 to -3.92). Finally, after 2019, there was a significant decrease through 2023 (APC: -3.02; 95% CI: -3.79 to -2.24)(Figure 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.1 Stratification by Age Group\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThroughout the study period, the crude mortality rates (CMRs) were highest among adults aged \u0026ge;85 years, falling from 296.85 in 1999 to 275.79 in 2023 (AAPC: -0.55, 95% CI: -0.86 to -0.24) (Table 2). Marked reductions were also observed in adults aged 75\u0026ndash;84 years (361.89 to 225.96, AAPC: -2.02, 95% CI: -2.24 to -1.79), with the steepest decline occurring between 2012 and 2023 (APC: -3.78; 95% CI: -4.01 to -3.55). A sustained downward trajectory was documented for the 65\u0026ndash;74 age group (281.29 to 128.58, AAPC: -3.238, 95% CI: -3.51 to -2.96). Successively younger cohorts exhibited progressively sharper decreases, 55\u0026ndash;64, 45\u0026ndash;54 and 35\u0026ndash;44 years\u0026mdash;each with AAPC values of -3.277, -4.50 and -5.16, respectively (all P \u0026lt; 0.05). The 25\u0026ndash;34 age group maintained the lowest CMRs throughout, remaining below 0.5 per 100 000 and decreasing modestly (AAPC: -2.515, 95% CI: -3.07 to -1.96) (Figure 2, Figure 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 Stratification by Sex\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the sex-stratified analysis, age-adjusted mortality rates (AAMR) remained consistently higher among males than females from 1999 to 2023(Table 4); however, the decline was markedly steeper in males (AAPC: males -3.35; 95% CI -3.68 to -3.01; females -1.85; 95% CI: -2.09 to -1.61). The sharpest decrease for males occurred between 2015 and 2018 (APC -5.62; 95% CI: -7.72 to -3.47). While female AAMR also exhibited a sustained and significant downward trend, albeit with a gentler slope (Table 3, Table 4 and Figure 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3 Stratification by Race/Ethnicity\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWhen stratified by race/ethnicity, AAMRs in 1999 showed a clear gradient: non-Hispanic Black (NH Black) had the highest burden at 101.50 (95%CI: 99.91 to 103.10), followed by non-Hispanic White（NH White）at 88.43 (95%CI: 87.95 to 88.92), non-Hispanic Other (NH Other) at 45.79 (95%CI: 43.87 to 7.70), and Hispanic or Latino at the lowest level, 38.68(95%CI: 37.35 to 40.01)(Table 5).\u003c/p\u003e\n\u003cp\u003eNotably, NH Black experienced the sharpest decline in AAMR over the study period, with an AAPC of -3.05 (95% CI: -3.26 to -2.83). The steepest reduction occurred between 2013 and 2020, reaching an APC of -4.95 (95% CI: -5.33 to -4.57). Consequently, the NH Black AAMR first fell below that of NH White in 2015 and has remained lower ever since, while the NH White rate has stayed above all other racial/ethnic groups. In contrast, Hispanic or Latino and NH Other groups experienced more gradual declines, yet their AAMRs have consistently remained below those of the other two groups (Table 5, Figure 4).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4 Stratification by Census Region\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAcross all census regions, AAMRs declined steadily and significantly throughout the study period. (Table 6) The South and Midwest maintained comparatively high levels, with nearly identical rates and trajectories (AAPC: -2.66%; 95% CI: -2.92 to -2.40 versus -2.80%; 95% CI: -3.12 to -2.48, respectively) (Table 3). By contrast, the West consistently recorded the lowest AAMR and exhibited the steepest decline nationwide (AAPC -3.21%; 95% CI: -3.57 to -2.84) (Table 3, Figure 5).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.5 Stratification by Urban-Rural\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOverall, AAMRs declined in both metropolitan and non-metropolitan areas throughout the study period, with metropolitan areas experienced the sharper decrease (Table 3, Table 7). From 1999 to 2020, AAMRs in metropolitan fell steadily, registering an overall AAPC of -2.83 (95% CI: -2.99 to -2.66); the most pronounced drop occurred between 2014 and 2020 (APC: -4.79%; 95% CI: -4.97 to -4.61) (Table 3, Table 7, Figure 6). In non-metropolitan, AAMRs likewise trended downward, interrupted only by modest upticks in 2000 and 2007, and the overall decline was more gradual compared with metropolitan (AAPC: -1.73; 95% CI: -1.97 to -1.48) (Table 3, Table 7, Figure 6).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.6 Stratification by State\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAcross all states, the AAMRs for bronchus and lung cancer showed a consistent decline from 1999 to 2023(Table 8, Figure 7). The percent change of AAMR values were all negative, ranged from -32% to -59% (Table 8), indicating a reduction in mortality rates over the 25-year period. The District of Columbia exhibited the largest reduction in mortality rates, with a percent change of -59%. Nevada and California followed closely, with percent changes of -57% and -56%, respectively. In 1999, the highest AAMR was observed in Mississippi (108.93 per 100,000), while the lowest was in Utah (40.87 per 100,000). By 2023, the highest AAMR was in Kentucky (75.62 per 100,000), and the lowest remained in Utah (23.76 per 100,000) (Table 8, Figure 7). The overall reduction in AAMRs was substantial, with many states experiencing a more than 50% decrease in mortality rates. Despite the general downward trend, there was significant variability in the magnitude of the decline among different states. States such as Kentucky, West Virginia, and Louisiana still had relatively high AAMRs in 2023, although they also showed notable reductions compared to 1999. In contrast, states like Utah, Colorado, and Washington exhibited lower initial AAMRs in 1999 and maintained lower levels in 2023 (Table 8, Figure 7).\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe overall decline in bronchus and lung cancer-related mortality from 1999 to 2023 in the United States is a promising trend, likely attributable to a combination of factors including heightened awareness of the dangers of smoking, reduced accessibility and affordability of cigarettes, and improved treatment options\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. However, several notable disparities and trends found in this study warrant further investigation and targeted interventions.\u003c/p\u003e\u003cp\u003eThe analysis of Bronchus and Lung Cancer mortality rates across different age groups from 1999 to 2023 reveals significant trends and patterns that provide valuable insights into the disease dynamics over time. The data show a consistent decline in crude mortality rates across most age groups, indicating improvements in healthcare, early detection, and treatment options for Bronchus and Lung Cancer\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eConsistent with previous research, males exhibited higher AAMRs than females throughout the study period\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. This difference may be partly explained by historical smoking patterns, as men have traditionally had higher smoking rates than women\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Additionally, biological and physiological differences between sexes could also contribute to the observed disparities. For instance, men may have a higher susceptibility to the carcinogenic effects of tobacco smoke or other risk factors. While both sexes experienced significant declines in AAMRs over the years, the steeper decline in males compared to females suggests that targeted smoking cessation programs and other preventive measures for men may have been particularly effective\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. However, continued efforts are needed to address the remaining gap and ensure that both sexes benefit equally from public health initiatives.\u003c/p\u003e\u003cp\u003eThe observed disparities in AAMRs among different racial and ethnic groups highlight the complex interplay of genetic, socioeconomic, and environmental factors in lung cancer mortality. Non-Hispanic (NH) Black individuals had the highest AAMRs, which is concerning given their relatively lower smoking prevalence compared to NH White individuals\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. This suggests that other factors such as genetic predisposition, environmental exposures, and healthcare access may play a significant role in the higher mortality rates among this group. On the other hand, Hispanic or Latino populations had the lowest AAMRs, potentially due to protective factors such as lower smoking rates and possibly genetic or lifestyle factors that reduce their susceptibility to lung cancer\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. The significant declines in AAMRs observed among all racial/ ethnic groups indicate the positive impact of broad public health measures\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe differences in AAMRs across census regions and urban-rural classifications highlight the importance of regional and local factors in lung cancer mortality. The Northeast region, which had the higher initial AAMRs, experienced a significant decline over the study period, possibly due to early adoption of smoking cessation programs and better access to healthcare. In contrast, the Midwest and South regions, which had highest AAMRs in the later years, may require more focused efforts to address the underlying causes of lung cancer mortality. The higher AAMRs in non-metropolitan areas compared to metropolitan areas could be attributed to several factors, including limited access to specialized healthcare, fewer smoking cessation resources, and potentially higher exposure to environmental carcinogens such as radon\u003csup\u003e\u003cspan additionalcitationids=\"CR30\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. The significant declines in AAMRs in both metropolitan and non-metropolitan areas indicate that efforts to reduce lung cancer mortality have been effective across different settings. However, the continued higher rates in non-metropolitan areas suggest that targeted interventions are needed to address the unique challenges faced by these communities. For example, increasing the availability of smoking cessation programs and improving access to lung cancer screening in rural areas could help reduce the mortality gap\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe substantial variability in AAMRs among different states highlights the importance of state-specific factors in lung cancer mortality. States such as Kentucky, West Virginia, and Arkansas, which had relatively high AAMRs in 2023, may benefit from targeted public health initiatives and policy changes to reduce smoking rates and improve access to healthcare. In contrast, states like Utah, Colorado, and New Mexico, which had lower initial AAMRs and maintained lower levels in 2023, may serve as models for other states to emulate. The large reductions in AAMRs observed in many states indicate the potential for further improvements through sustained efforts to address the risk factors and underlying causes of lung cancer\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. State-level policies such as tobacco control measures, funding for cancer screening programs, and support for research into novel treatments could play a crucial role in reducing lung cancer mortality.\u003c/p\u003e\u003cp\u003eThe slight increase in AAMRs from 2020 to 2023 may be partly attributed to the COVID-19 pandemic. The pandemic led to disruptions in healthcare services, delays in cancer screening and treatment, and increased exposure to respiratory infections, all of which could have contributed to higher lung cancer mortality rates. Additionally, the stress and lifestyle changes associated with the pandemic may have led to increased smoking rates or other unhealthy behaviors that could have exacerbated the risk of lung cancer. Further research is needed to fully understand the impact of the COVID-19 pandemic on lung cancer mortality and to develop strategies to mitigate any long-term effects\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis study on bronchus and lung cancer-related mortality in the United States from 1999 to 2023 revealed several key findings: There was a significant decrease in age-adjusted mortality rates (AAMRs) for bronchus and lung cancer across the United States, indicating progress in reducing the burden of this disease. The crude mortality rate for Bronchus and Lung Cancer demonstrates a significant decline across most age groups, highlighting the positive impact of advancements in medical technology, public health interventions, and improved treatment protocols. Males consistently had higher AAMRs than females, highlighting the need for targeted interventions to address smoking and other risk factors among men. Non-Hispanic Black individuals had the highest AAMRs, while Hispanic or Latino individuals had the lowest. This underscores the importance of tailored public health strategies to address disparities in these populations. Significant differences were observed across census regions and urban-rural classifications, with the West region having the lowest mortality rates compared to the Northeast and Midwest regions; nonmetropolitan had higher mortality rates than metropolitan. Compared to 1999, AAMRs decreased in all U.S. states in 2023, with the most significant declines observed in the District of Columbia, Nevada, and California. A slight increase in AAMRs from 2020 to 2023 may be attributed to the COVID-19 pandemic, emphasizing the need for ongoing surveillance and adaptive public health measures.\u003c/p\u003e"},{"header":"6. Limitations and Future Research","content":"\u003cp\u003eThis study has several limitations. The reliance on death certificate data and ICD-10 codes may introduce misclassification bias, potentially underestimating or overestimating lung cancer mortality rates. Additionally, the lack of individual-level data on smoking status, comorbidities, and other risk factors limits the ability to draw definitive conclusions about the underlying causes of the observed trends. Future research should aim to incorporate more detailed individual-level data to provide a more comprehensive understanding of the factors contributing to lung cancer mortality. Furthermore, studies should focus on identifying the specific mechanisms underlying the observed disparities and developing targeted interventions to address these disparities.\u003c/p\u003e"},{"header":"7. Countributions","content":"\u003cp\u003eConception and design: Mingfeng Wei, Huibiao Zhang, Xiaoyong Shen; administrative support: Mingfeng Wei, Xiaoyu Chen, Wei Cheng, Xuelin Zhang; database acquisition and cleaning: Mingfeng Wei, Xiaoyu Chen, Wei Cheng, Lefei Hu, Shixiang Guo; data analysis and interpretation: Mingfeng Wei, Xiaoyu Chen, Wei Cheng, Zheng Li, Huibiao Zhang, Xiaoyong Shen; manuscript writing: all authors; final approval of manuscript: all authors\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConception and design: Mingfeng Wei, Huibiao Zhang, Xiaoyong Shen; administrative support: Mingfeng Wei, Xiaoyu Chen, Wei Cheng, Xuelin Zhang; database acquisition and cleaning: Mingfeng Wei, Xiaoyu Chen, Wei Cheng, Lefei Hu, Shixiang Guo; data analysis and interpretation: Mingfeng Wei, Xiaoyu Chen, Wei Cheng, Zheng Li, Huibiao Zhang, Xiaoyong Shen; manuscript writing: all authors; final approval of manuscript: all authors.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSiegel RL, Miller KD, Fuchs HE, Jemal A. Cancer statistics, 2022. \u003cem\u003eCA Cancer J Clin\u003c/em\u003e. 2022;72(1):7-33. doi:10.3322/caac.21708\u003c/li\u003e\n\u003cli\u003eHj X, J Z, D ZM, N ZD, A EB, T T. Inhibiting tumour metastasis by DQA modified paclitaxel plus ligustrazine micelles in treatment of non-small-cell lung cancer. \u003cem\u003eArtif Cells Nanomed Biotechnol\u003c/em\u003e. 2019;47(1). doi:10.1080/21691401.2019.1653900\u003c/li\u003e\n\u003cli\u003eHendriks LEL, Remon J, Faivre-Finn C, et al. Non-small-cell lung cancer. \u003cem\u003eNat Rev, Dis Primers\u003c/em\u003e. 2024;10(1):71. doi:10.1038/s41572-024-00551-9\u003c/li\u003e\n\u003cli\u003eKoyi H, Brand\u0026eacute;n E, Kasim I, Wilander E. Co-localisation of glandular and squamous cell markers in non-small cell lung cancer. \u003cem\u003eAnticancer Res\u003c/em\u003e. 2018;38(6):3341-3346. doi:10.21873/anticanres.12600\u003c/li\u003e\n\u003cli\u003eF I, Ec M, B T, et al. 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Distribution, risk factors, and temporal trends for lung cancer incidence and mortality: a global analysis. \u003cem\u003eChest\u003c/em\u003e. 2022;161(4):1101-1111. doi:10.1016/j.chest.2021.12.655\u003c/li\u003e\n\u003cli\u003eGeographic patterns in U.S. lung cancer mortality and cigarette smoking - PubMed. Accessed June 5, 2025. https://pubmed.ncbi.nlm.nih.gov/36413442/\u003c/li\u003e\n\u003cli\u003eJohn U, Hanke M. Lung cancer mortality and years of potential life lost among males and females over six decades in a country with high smoking prevalence: an observational study. \u003cem\u003eBMC Cancer\u003c/em\u003e. 2015;15:876. doi:10.1186/s12885-015-1807-7\u003c/li\u003e\n\u003cli\u003evon Elm E, Altman DG, Egger M, et al. The strengthening the reporting of observational studies in epidemiology (STROBE) statement: guidelines for reporting observational studies. \u003cem\u003eAnn Intern Med\u003c/em\u003e. 2007;147(8):573-577. doi:10.7326/0003-4819-147-8-200710160-00010\u003c/li\u003e\n\u003cli\u003eBrown A, Karl A, Murugan V, Billion T, Jabbar ABA, Mirza M. Emphysema-related mortality rates in the U.S. from 1999 to 2022. \u003cem\u003eFront Med\u003c/em\u003e. 2025;12. doi:10.3389/fmed.2025.1579177\u003c/li\u003e\n\u003cli\u003eGoyal A, Saeed H, Sulaiman SA, et al. Emerging trends and disparities in cardiovascular, kidney, and diabetes-related mortality: a retrospective analysis of the wide-ranging online data for epidemiologic research database. \u003cem\u003ePLOS One\u003c/em\u003e. 2025;20(5):e0320670. doi:10.1371/journal.pone.0320670\u003c/li\u003e\n\u003cli\u003eIngram DD, Franco SJ. 2013 NCHS urban-rural classification scheme for counties. \u003cem\u003eVital Health Stat 2\u003c/em\u003e. 2014;(166):1-73.\u003c/li\u003e\n\u003cli\u003eAge standardization of death rates: implementation of the year 2000 standard - PubMed. Accessed June 5, 2025. https://pubmed.ncbi.nlm.nih.gov/9796247/\u003c/li\u003e\n\u003cli\u003eJoinpoint regression program. Accessed June 5, 2025. https://surveillance.cancer.gov/joinpoint/\u003c/li\u003e\n\u003cli\u003eBurden of cigarette use in the U.S. | data and statistics | campaign resources | tips from former smokers | CDC. Accessed June 6, 2025. https://www.cdc.gov/tobacco/campaign/tips/resources/data/cigarette-smoking-in-united-states.html\u003c/li\u003e\n\u003cli\u003eAm A, Ts S, N N, D H, Js A. Gender differences in smoking behavior and dependence motives among daily and nondaily smokers. \u003cem\u003eNicotine Tob Res : Off J Soc Res Nicotine Tob\u003c/em\u003e. 2016;18(6). doi:10.1093/ntr/ntv138\u003c/li\u003e\n\u003cli\u003eD D. [lung cancer epidemiology: evolution over the last twenty years]. \u003cem\u003eBulletin du Cancer\u003c/em\u003e. 2025;112(3S1). doi:10.1016/S0007-4551(25)00152-3\u003c/li\u003e\n\u003cli\u003eKruk ME, Gage AD, Arsenault C, et al. High-quality health systems in the sustainable development goals era: time for a revolution. \u003cem\u003eLancet, Glob Health\u003c/em\u003e. 2018;6(11):e1196-e1252. doi:10.1016/S2214-109X(18)30386-3\u003c/li\u003e\n\u003cli\u003eN M, A F, S P, A A. Gender-specific aspects of epidemiology, molecular genetics and outcome: lung cancer. \u003cem\u003eESMO Open\u003c/em\u003e. 2020;5(Suppl 4). doi:10.1136/esmoopen-2020-000796\u003c/li\u003e\n\u003cli\u003eMollica MA, Weaver KE, McNeel TS, Kent EE. Examining urban and rural differences in perceived timeliness of care among cancer patients: a SEER-CAHPS study. \u003cem\u003eCancer\u003c/em\u003e. 2018;124(15):3257-3265. doi:10.1002/cncr.31541\u003c/li\u003e\n\u003cli\u003eCigarette smoking behaviors and the importance of ethnicity and genetic ancestry - PubMed. Accessed June 6, 2025. https://pubmed.ncbi.nlm.nih.gov/33633108/\u003c/li\u003e\n\u003cli\u003eSr G, Ta L, Ab M, et al. Racial and ethnic disparities among participants in US-based phase 3 randomized cancer clinical trials. \u003cem\u003eJNCI Cancer Spectr\u003c/em\u003e. 2020;4(5). doi:10.1093/jncics/pkaa060\u003c/li\u003e\n\u003cli\u003eHenley SJ, Anderson RN, Thomas CC, Massetti GM, Peaker B, Richardson LC. Invasive cancer incidence, 2004-2013, and deaths, 2006-2015, in nonmetropolitan and metropolitan counties - united states. \u003cem\u003eMorb Mortal Wkly Rep, Surveill Summ (wash DC: 2002)\u003c/em\u003e. 2017;66(14):1-13. doi:10.15585/mmwr.ss6614a1\u003c/li\u003e\n\u003cli\u003eFairfield KM, Black AW, Ziller EC, et al. Area deprivation index and rurality in relation to lung cancer prevalence and mortality in a rural state. \u003cem\u003eJNCI Cancer Spectr\u003c/em\u003e. 2020;4(4):pkaa011. doi:10.1093/jncics/pkaa011\u003c/li\u003e\n\u003cli\u003eA statewide investigation of geographic lung cancer incidence patterns and radon exposure in a low-smoking population - PubMed. Accessed June 6, 2025. https://pubmed.ncbi.nlm.nih.gov/29385999/\u003c/li\u003e\n\u003cli\u003ePatterns and factors associated with adherence to lung cancer screening in diverse practice settings - PubMed. Accessed June 6, 2025. https://pubmed.ncbi.nlm.nih.gov/33929519/\u003c/li\u003e\n\u003cli\u003eDidier AJ, Roof L, Stevenson J. Demographic disparities in lung cancer mortality and trends in the United States from 1999 through 2020: a population-based CDC database analysis. \u003cem\u003eJ Natl Compr Cancer Netw: JNCCN\u003c/em\u003e. 2024;22(6):e247004. doi:10.6004/jnccn.2024.7004\u003c/li\u003e\n\u003cli\u003eTelehealth in response to the COVID-19 pandemic: implications for rural health disparities - PubMed. Accessed June 6, 2025. https://pubmed.ncbi.nlm.nih.gov/32589735/\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1.\u0026nbsp;\u003c/strong\u003eOverall Bronchus and Lung Cancer-related Mortality per 1,000,000 Adults in the United States, 1999 to 2023\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eYear\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDeaths\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePopulation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge-Adjusted Mortality Rate (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1999\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e152063\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e279040168\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e55.41 (55.14 \u0026ndash; 55.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e155431\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e281421906\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e56.07 (55.79 \u0026ndash; 56.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e155973\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e284968955\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e55.31 (55.04 \u0026ndash; 55.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e157630\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e287625193\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e54.93 (54.65 \u0026ndash; 55.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e157992\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e290107933\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e54.10 (53.83 \u0026ndash; 54.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2004\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e158009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e292805298\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e53.22 (52.96 \u0026ndash; 53.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2005\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e159220\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e295516599\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e52.65 (52.39 \u0026ndash; 52.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2006\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e158600\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e298379912\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e51.51 (51.26 \u0026ndash; 51.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2007\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e158686\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e301231207\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e50.59 (50.34 \u0026ndash; 50.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2008\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e158592\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e304093966\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e49.50 (49.25 \u0026ndash; 49.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2009\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e158086\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e306771529\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e48.33 (48.09 \u0026ndash; 48.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2010\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e158249\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e308745538\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e47.61 (47.37 \u0026ndash; 47.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2011\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e156957\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e311591917\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e45.98 (45.75 \u0026ndash; 46.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2012\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e157426\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e313914040\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e44.87 (44.65 \u0026ndash; 45.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2013\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e156178\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e316128839\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e43.35 (43.13 \u0026ndash; 43.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2014\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e155529\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e318857056\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e42.08 (41.87 \u0026ndash; 42.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2015\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e153722\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e321418820\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e40.48 (40.28 \u0026ndash; 40.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2016\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e148870\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e323127513\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e38.35 (38.15 \u0026ndash; 38.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2017\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e145849\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e325719178\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e36.60 (36.41 \u0026ndash; 36.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2018\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e142081\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e327167434\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e34.75 (34.57 \u0026ndash; 34.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2019\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e139603\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e328239523\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e33.41 (33.23 \u0026ndash; 33.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2020\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e136084\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e329484123\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e31.84 (31.67 \u0026ndash; 32.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2021\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e134504\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e331893745\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e31.73 (31.56 \u0026ndash; 31.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2022\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e131889\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e333287557\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e30.05 (29.88 \u0026ndash; 30.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2023\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e131584\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e334914895\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e29.49 (29.33 \u0026ndash; 29.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e2\u003c/strong\u003e Crude Mortality Rate per 100,100 adults of Bronchus and Lung Cancer in the United States stratified by age groups, 1999 to 2023\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eYear\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"7\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCrude Mortality Rate per 100,100 adults\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e25-34\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e35-44\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e45-54\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e55-64\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e65-74\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e75-84\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e85+\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1999\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.44 (0.38 \u0026ndash; 0.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e6.04 (5.81 \u0026ndash; 6.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e31.24 (30.67 \u0026ndash; 31.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e123.33 (121.92 \u0026ndash; 124.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e281.29 (278.87 \u0026ndash; 283.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e361.89 (358.52 \u0026ndash; 365.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e296.85 (291.61 \u0026ndash; 302.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.49 (0.42 \u0026ndash; 0.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e6.10 (5.87 \u0026ndash; 6.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e31.59 (31.03 \u0026ndash; 32.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e122.39 (121.00 \u0026ndash; 123.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e283.98 (281.55 \u0026ndash; 286.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e370.59 (367.19 \u0026ndash; 373.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e301.94 (296.71 \u0026ndash; 307.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.40 (0.34 \u0026ndash; 0.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e6.20 (5.97 \u0026ndash; 6.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e30.55 (30.00 \u0026ndash; 31.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e118.54 (117.19 \u0026ndash; 119.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e278.50 (276.09 \u0026ndash; 280.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e370.64 (367.28 \u0026ndash; 374.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e308.96 (303.72 \u0026ndash; 314.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.42 (0.36 \u0026ndash; 0.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e6.03 (5.81 \u0026ndash; 6.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e30.35 (29.81 \u0026ndash; 30.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e114.84 (113.55 \u0026ndash; 116.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e273.20 (270.81 \u0026ndash; 275.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e376.53 (373.16 \u0026ndash; 379.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e312.26 (307.02 \u0026ndash; 317.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.39 (0.33 \u0026ndash; 0.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e5.61 (5.38 \u0026ndash; 5.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e30.29 (29.76 \u0026ndash; 30.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e110.44 (109.21 \u0026ndash; 111.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e266.81 (264.46 \u0026ndash; 269.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e376.78 (373.43 \u0026ndash; 380.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e315.26 (310.05 \u0026ndash; 320.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2004\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.37 (0.31 \u0026ndash; 0.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e5.53 (5.31 \u0026ndash; 5.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e29.88 (29.36 \u0026ndash; 30.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e106.03 (104.85 \u0026ndash; 107.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e262.54 (260.21 \u0026ndash; 264.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e372.91 (369.59 \u0026ndash; 376.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e317.67 (312.49 \u0026ndash; 322.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2005\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.34 (0.28 \u0026ndash; 0.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e5.33 (5.12 \u0026ndash; 5.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e29.67 (29.15 \u0026ndash; 30.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e102.31 (101.18 \u0026ndash; 103.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e256.17 (253.89 \u0026ndash; 258.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e374.87 (371.55 \u0026ndash; 378.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e328.17 (322.99 \u0026ndash; 333.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2006\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.39 (0.33 \u0026ndash; 0.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e4.68 (4.47 \u0026ndash; 4.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e29.11 (28.60 \u0026ndash; 29.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e98.04 (96.95 \u0026ndash; 99.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e249.23 (247.00 \u0026ndash; 251.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e372.03 (368.73 \u0026ndash; 375.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e326.93 (321.85 \u0026ndash; 332.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2007\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.34 (0.28 \u0026ndash; 0.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e4.32 (4.12 \u0026ndash; 4.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e28.37 (27.87 \u0026ndash; 28.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e94.18 (93.14 \u0026ndash; 95.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e244.36 (242.17 \u0026ndash; 246.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e369.39 (366.10 \u0026ndash; 372.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e327.89 (322.89 \u0026ndash; 332.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2008\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.36 (0.30 \u0026ndash; 0.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e3.80 (3.61 \u0026ndash; 3.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e28.16 (27.67 \u0026ndash; 28.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e90.12 (89.11 \u0026ndash; 91.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e235.46 (233.36 \u0026ndash; 237.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e366.52 (363.24 \u0026ndash; 369.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e332.82 (327.86 \u0026ndash; 337.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2009\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.36 (0.30 \u0026ndash; 0.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e3.65 (3.47 \u0026ndash; 3.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e27.82 (27.33 \u0026ndash; 28.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e87.42 (86.44 \u0026ndash; 88.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e228.50 (226.47 \u0026ndash; 230.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e359.66 (356.40 \u0026ndash; 362.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e327.84 (322.99 \u0026ndash; 332.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2010\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.39 (0.33 \u0026ndash; 0.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e3.29 (3.11 \u0026ndash; 3.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e26.84 (26.37 \u0026ndash; 27.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e85.34 (84.39 \u0026ndash; 86.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e223.75 (221.76 \u0026ndash; 225.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e357.14 (353.90 \u0026ndash; 360.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e332.25 (327.43 \u0026ndash; 337.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2011\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.29 (0.24 \u0026ndash; 0.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e3.10 (2.93 \u0026ndash; 3.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e25.68 (25.21 \u0026ndash; 26.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e83.44 (82.52 \u0026ndash; 84.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e214.21 (212.30 \u0026ndash; 216.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e345.88 (342.71 \u0026ndash; 349.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e323.61 (318.95 \u0026ndash; 328.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2012\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.41 (0.35 \u0026ndash; 0.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e2.89 (2.73 \u0026ndash; 3.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e25.08 (24.61 \u0026ndash; 25.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e81.49 (80.59 \u0026ndash; 82.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e205.97 (204.15 \u0026ndash; 207.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e339.44 (336.31 \u0026ndash; 342.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e323.47 (318.88 \u0026ndash; 328.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2013\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.29 (0.24 \u0026ndash; 0.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e2.83 (2.67 \u0026ndash; 2.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e23.84 (23.38 \u0026ndash; 24.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e79.91 (79.02 \u0026ndash; 80.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e196.54 (194.81 \u0026ndash; 198.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e328.36 (325.30 \u0026ndash; 331.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e319.78 (315.27 \u0026ndash; 324.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2014\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.30 (0.25 \u0026ndash; 0.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e2.73 (2.57 \u0026ndash; 2.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e22.38 (21.94 \u0026ndash; 22.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e78.41 (77.54 \u0026ndash; 79.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e189.31 (187.65 \u0026ndash; 190.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e321.04 (318.04 \u0026ndash; 324.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e311.61 (307.20 \u0026ndash; 316.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2015\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.30 (0.25 \u0026ndash; 0.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e2.50 (2.34 \u0026ndash; 2.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e20.44 (20.02 \u0026ndash; 20.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e76.79 (75.95 \u0026ndash; 77.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e180.85 (179.26 \u0026ndash; 182.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e306.16 (303.25 \u0026ndash; 309.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e315.99 (311.60 \u0026ndash; 320.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2016\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.28 (0.23 \u0026ndash; 0.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e2.18 (2.04 \u0026ndash; 2.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e18.53 (18.12 \u0026ndash; 18.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e73.19 (72.37 \u0026ndash; 74.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e167.85 (166.35 \u0026ndash; 169.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e295.30 (292.48 \u0026ndash; 298.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e305.03 (300.75 \u0026ndash; 309.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2017\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.24 (0.20 \u0026ndash; 0.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e2.06 (1.92 \u0026ndash; 2.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e16.48 (16.09 \u0026ndash; 16.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e70.21 (69.41 \u0026ndash; 71.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e160.45 (159.01 \u0026ndash; 161.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e283.41 (280.69 \u0026ndash; 286.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e295.11 (290.93 \u0026ndash; 299.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2018\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.26 (0.21 \u0026ndash; 0.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e1.89 (1.76 \u0026ndash; 2.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e15.04 (14.67 \u0026ndash; 15.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e68.48 (67.70 \u0026ndash; 69.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e150.84 (149.47 \u0026ndash; 152.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e267.79 (265.21 \u0026ndash; 270.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e286.06 (281.96 \u0026ndash; 290.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2019\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.23 (0.18 \u0026ndash; 0.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e1.85 (1.72 \u0026ndash; 1.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e13.63 (13.28 \u0026ndash; 13.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e64.76 (64.00 \u0026ndash; 65.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e144.26 (142.94 \u0026ndash; 145.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e260.78 (258.28 \u0026ndash; 263.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e281.11 (277.06 \u0026ndash; 285.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2020\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.27 (0.22 \u0026ndash; 0.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e1.79 (1.66 \u0026ndash; 1.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e12.51 (12.17 \u0026ndash; 12.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e62.83 (62.08 \u0026ndash; 63.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e139.94 (138.66 \u0026ndash; 141.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e246.10 (243.71 \u0026ndash; 248.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e262.10 (258.22 \u0026ndash; 265.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2021\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.26 (0.21 \u0026ndash; 0.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e1.78 (1.66 \u0026ndash; 1.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e11.91 (11.58 \u0026ndash; 12.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e60.47 (59.74 \u0026ndash; 61.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e134.45 (133.21 \u0026ndash; 135.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e248.76 (246.33 \u0026ndash; 251.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e289.25 (284.94 \u0026ndash; 293.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2022\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.25 (0.21 \u0026ndash; 0.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e1.76 (1.64 \u0026ndash; 1.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e11.08 (10.76 \u0026ndash; 11.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e57.92 (57.19 \u0026ndash; 58.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e131.86 (130.63 \u0026ndash; 133.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e232.48 (230.22 \u0026ndash; 234.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e259.81 (255.89 \u0026ndash; 263.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2023\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.27 (0.23 \u0026ndash; 0.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e1.66 (1.54 \u0026ndash; 1.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e10.55 (10.24 \u0026ndash; 10.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e55.52 (54.81 \u0026ndash; 56.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e128.58 (127.38 \u0026ndash; 129.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e225.96 (223.78 \u0026ndash; 228.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e275.79 (271.65 \u0026ndash; 279.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u003c/strong\u003e Annual Percentage Changes (APCs) and Average Annual Percentage Changes (AAPCs) in Bronchus and Lung Cancer-related mortality in the United States from 1999 to 2023.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLower Endpoint \u0026ndash; Upper Endpoint\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAPC (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAAPC (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverall\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e1999 \u0026ndash; 2002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-0.26 ( -1.41 \u0026ndash; 0.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.629609\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-2.63 (-2.92 to -2.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026lt;0.000001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e2002 \u0026ndash; 2010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-1.84 ( -2.15 \u0026ndash; -1.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026lt;0.000001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e2010 \u0026ndash; 2014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-3.00 ( -4.12 \u0026ndash; -1.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.000127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e2014 \u0026ndash; 2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-4.65 ( -5.37 \u0026ndash; -3.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026lt;0.000001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e2019 \u0026ndash; 2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-3.02 ( -3.79 \u0026ndash; -2.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.000004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e1999 \u0026ndash; 2001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-0.93 ( -2.99 \u0026ndash; 1.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.347079\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-3.35 (-3.68 to -3.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026lt;0.000001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e2001 \u0026ndash; 2010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-2.48 ( -2.71 \u0026ndash; -2.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026lt;0.000001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e2010 \u0026ndash; 2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-3.83 ( -4.48 \u0026ndash; -3.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026lt;0.000001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e2015 \u0026ndash; 2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-5.62 ( -7.72 \u0026ndash; -3.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.000148\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e2018 \u0026ndash; 2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-3.99 ( -4.50 \u0026ndash; -3.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026lt;0.000001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e1999 \u0026ndash; 2002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e0.98 ( -0.08 \u0026ndash; 2.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.066034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-1.85 (-2.09 to -1.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026lt;0.000001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e2002 \u0026ndash; 2008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-0.90 ( -1.35 \u0026ndash; -0.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.001087\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e2008 \u0026ndash; 2014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-2.09 ( -2.54 \u0026ndash; -1.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.000001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e2014 \u0026ndash; 2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-4.08 ( -4.52 \u0026ndash; -3.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026lt;0.000001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e2020 \u0026ndash; 2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-1.52 ( -2.57 \u0026ndash; -0.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.009454\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRace/Ethnicity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003eHispanic or Latino\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e1999 \u0026ndash; 2014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-2.12 ( -2.34 \u0026ndash; -1.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026lt;0.000001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-2.73 (-3.30 to -2.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026lt;0.000001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e2014 \u0026ndash; 2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-5.59 ( -9.92 \u0026ndash; -1.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.019404\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e2017 \u0026ndash; 2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-2.81 ( -3.57 \u0026ndash; -2.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.000001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003eNH Black\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e1999 \u0026ndash; 2004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-1.60 ( -2.10 \u0026ndash; -1.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-3.05 (-3.26 to -2.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026lt;0.000001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e2004 \u0026ndash; 2013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-2.57 ( -2.82 \u0026ndash; -2.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026lt;0.000001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e2013 \u0026ndash; 2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-4.95 ( -5.33 \u0026ndash; -4.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026lt;0.000001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e2020 \u0026ndash; 2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-2.38 ( -3.59 \u0026ndash; -1.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.001022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003eNH White\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e1999 \u0026ndash; 2001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e0.61 ( -1.62 \u0026ndash; 2.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.562185\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-2.32 (-2.60 to -2.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026lt;0.000001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e2001 \u0026ndash; 2008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-1.31 ( -1.68 \u0026ndash; -0.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.000009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e2008 \u0026ndash; 2014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-2.48 ( -2.97 \u0026ndash; -1.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026lt;0.000001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e2014 \u0026ndash; 2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-4.41 ( -5.13 \u0026ndash; -3.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026lt;0.000001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e2019 \u0026ndash; 2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-2.66 ( -3.43 \u0026ndash; -1.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.000013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003eNH Other\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e1999 \u0026ndash; 2011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-0.83 ( -1.15 \u0026ndash; -0.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.000029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-2.16 (-2.35 to -1.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026lt;0.000001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e2011 \u0026ndash; 2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-3.46 ( -3.71 \u0026ndash; -3.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026lt;0.000001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCensus Region\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003eMidwest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e1999 \u0026ndash; 2002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e0.18 ( -1.12 \u0026ndash; 1.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.772914\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-2.09 (-2.40 to -1.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026lt;0.000001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e2002 \u0026ndash; 2008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-1.10 ( -1.66 \u0026ndash; -0.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.00143\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e2008 \u0026ndash; 2014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-2.06 ( -2.63 \u0026ndash; -1.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.000007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e2014 \u0026ndash; 2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-4.34 ( -5.15 \u0026ndash; -3.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026lt;0.000001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e2019 \u0026ndash; 2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-2.46 ( -3.32 \u0026ndash; -1.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.000073\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003eNortheast\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e1999 \u0026ndash; 2002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-0.56 ( -1.81 \u0026ndash; 0.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.3434\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-2.80 (-3.12 to -2.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026lt;0.000001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e2002 \u0026ndash; 2010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-1.69 ( -2.02 \u0026ndash; -1.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026lt;0.000001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e2010 \u0026ndash; 2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-3.11 ( -3.91 \u0026ndash; -2.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.000004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e2015 \u0026ndash; 2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-5.20 ( -6.03 \u0026ndash; -4.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026lt;0.000001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e2020 \u0026ndash; 2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-3.41 ( -4.83 \u0026ndash; -1.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.000325\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003eSouth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e1999 \u0026ndash; 2005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-0.93 ( -1.41 \u0026ndash; -0.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.001001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-2.66 (-2.92 to -2.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026lt;0.000001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e2005 \u0026ndash; 2013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-2.45 ( -2.82 \u0026ndash; -2.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026lt;0.000001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e2013 \u0026ndash; 2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-4.39 ( -5.01 \u0026ndash; -3.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026lt;0.000001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e2019 \u0026ndash; 2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-3.03 ( -3.95 \u0026ndash; -2.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.000007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003eWest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e1999 \u0026ndash; 2009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-2.14 ( -2.40 \u0026ndash; -1.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026lt;0.000001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-3.21 (-3.57 to -2.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026lt;0.000001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e2009 \u0026ndash; 2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-3.76 ( -4.49 \u0026ndash; -3.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026lt;0.000001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e2015 \u0026ndash; 2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-5.44 ( -7.11 \u0026ndash; -3.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.000009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e2019 \u0026ndash; 2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-2.76 ( -3.89 \u0026ndash; -1.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.000145\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUrban-Rural\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003eMetropolitan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e1999 \u0026ndash; 2001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-0.36 ( -1.40 \u0026ndash; 0.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.456499\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-2.83 (-2.99 to -2.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026lt;0.000001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e2001 \u0026ndash; 2005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-1.53 ( -2.04 \u0026ndash; -1.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.000131\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e2005 \u0026ndash; 2010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-2.24 ( -2.56 \u0026ndash; -1.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026lt;0.000001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e2010 \u0026ndash; 2014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-3.08 ( -3.59 \u0026ndash; -2.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.000001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e2014 \u0026ndash; 2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-4.79 ( -4.97 \u0026ndash; -4.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026lt;0.000001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003eNonmetropolitan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e1999 \u0026ndash; 2001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e1.40 ( -0.68 \u0026ndash; 3.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.167806\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-1.73 (-1.97 to -1.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026lt;0.000001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e2001 \u0026ndash; 2008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-0.78 ( -1.12 \u0026ndash; -0.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.000362\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e2008 \u0026ndash; 2014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-1.86 ( -2.31 \u0026ndash; -1.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.000002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e2014 \u0026ndash; 2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-3.70 ( -4.04 \u0026ndash; -3.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026lt;0.000001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4\u003c/strong\u003e. Bronchus and Lung Cancer-related Mortality per 1,000,000 Adults in the United States stratified by sex, 1999 to 2023\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eYear\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge-Adjusted Mortality Rate (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1999\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e62.18 (61.70\u0026nbsp;\u0026ndash;\u0026nbsp;62.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e118.78 (117.99\u0026nbsp;\u0026ndash;\u0026nbsp;119.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e63.86 (63.37\u0026nbsp;\u0026ndash;\u0026nbsp;64.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e118.59 (117.81\u0026nbsp;\u0026ndash;\u0026nbsp;119.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e63.51 (63.02\u0026nbsp;\u0026ndash;\u0026nbsp;64.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e116.27 (115.50\u0026nbsp;\u0026ndash;\u0026nbsp;117.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e64.30 (63.81\u0026nbsp;\u0026ndash;\u0026nbsp;64.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e113.52 (112.77\u0026nbsp;\u0026ndash;\u0026nbsp;114.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e63.83 (63.34\u0026nbsp;\u0026ndash;\u0026nbsp;64.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e110.99 (110.25\u0026nbsp;\u0026ndash;\u0026nbsp;111.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2004\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e63.27 (62.79\u0026nbsp;\u0026ndash;\u0026nbsp;63.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e108.42 (107.70\u0026nbsp;\u0026ndash;\u0026nbsp;109.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2005\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e62.79 (62.32\u0026nbsp;\u0026ndash;\u0026nbsp;63.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e106.86 (106.15\u0026nbsp;\u0026ndash;\u0026nbsp;107.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2006\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e62.05 (61.58\u0026nbsp;\u0026ndash;\u0026nbsp;62.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e103.61 (102.92\u0026nbsp;\u0026ndash;\u0026nbsp;104.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2007\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e61.92 (61.46\u0026nbsp;\u0026ndash;\u0026nbsp;62.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e100.38 (99.71\u0026nbsp;\u0026ndash;\u0026nbsp;101.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2008\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e60.42 (59.97\u0026nbsp;\u0026ndash;\u0026nbsp;60.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e98.17 (97.51\u0026nbsp;\u0026ndash;\u0026nbsp;98.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2009\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e59.66 (59.21\u0026nbsp;\u0026ndash;\u0026nbsp;60.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e94.88 (94.24\u0026nbsp;\u0026ndash;\u0026nbsp;95.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2010\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e58.91 (58.47\u0026nbsp;\u0026ndash;\u0026nbsp;59.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e93.17 (92.54\u0026nbsp;\u0026ndash;\u0026nbsp;93.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2011\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e57.27 (56.84\u0026nbsp;\u0026ndash;\u0026nbsp;57.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e89.23 (88.63\u0026nbsp;\u0026ndash;\u0026nbsp;89.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2012\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e56.25 (55.84\u0026nbsp;\u0026ndash;\u0026nbsp;56.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e86.67 (86.08\u0026nbsp;\u0026ndash;\u0026nbsp;87.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2013\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e54.83 (54.42\u0026nbsp;\u0026ndash;\u0026nbsp;55.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e83.07 (82.50\u0026nbsp;\u0026ndash;\u0026nbsp;83.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2014\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e53.65 (53.25\u0026nbsp;\u0026ndash;\u0026nbsp;54.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e79.86 (79.32\u0026nbsp;\u0026ndash;\u0026nbsp;80.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2015\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e51.75 (51.36\u0026nbsp;\u0026ndash;\u0026nbsp;52.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e76.54 (76.01\u0026nbsp;\u0026ndash;\u0026nbsp;77.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2016\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e49.23 (48.85\u0026nbsp;\u0026ndash;\u0026nbsp;49.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e72.19 (71.68\u0026nbsp;\u0026ndash;\u0026nbsp;72.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2017\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e47.33 (46.97\u0026nbsp;\u0026ndash;\u0026nbsp;47.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e68.55 (68.06\u0026nbsp;\u0026ndash;\u0026nbsp;69.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2018\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e45.31 (44.95\u0026nbsp;\u0026ndash;\u0026nbsp;45.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e64.54 (64.08\u0026nbsp;\u0026ndash;\u0026nbsp;65.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2019\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e43.55 (43.21\u0026nbsp;\u0026ndash;\u0026nbsp;43.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e61.94 (61.49\u0026nbsp;\u0026ndash;\u0026nbsp;62.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2020\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e41.64 (41.31\u0026nbsp;\u0026ndash;\u0026nbsp;41.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e58.84 (58.41\u0026nbsp;\u0026ndash;\u0026nbsp;59.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2021\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e42.14 (41.81\u0026nbsp;\u0026ndash;\u0026nbsp;42.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e57.83 (57.40\u0026nbsp;\u0026ndash;\u0026nbsp;58.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2022\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e40.25 (39.93\u0026nbsp;\u0026ndash;\u0026nbsp;40.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e54.46 (54.04\u0026nbsp;\u0026ndash;\u0026nbsp;54.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2023\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e39.92 (39.60\u0026nbsp;\u0026ndash;\u0026nbsp;40.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e52.68 (52.28\u0026nbsp;\u0026ndash;\u0026nbsp;53.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5\u003c/strong\u003e. Bronchus and Lung Cancer-related Mortality per 1,000,000 Adults in the United States stratified by race, 1999 to 2023\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eYear\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge-Adjusted Mortality Rate (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHispanic or Latino\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNH Black\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNH White\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNH Other\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1999\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e38.68 (37.35\u0026nbsp;\u0026ndash;\u0026nbsp;40.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e101.50 (99.91\u0026nbsp;\u0026ndash;\u0026nbsp;103.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e88.43 (87.95\u0026nbsp;\u0026ndash;\u0026nbsp;88.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e45.79 (43.87\u0026nbsp;\u0026ndash;\u0026nbsp;47.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e38.23 (36.94\u0026nbsp;\u0026ndash;\u0026nbsp;39.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e100.30 (98.72\u0026nbsp;\u0026ndash;\u0026nbsp;101.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e89.99 (89.50\u0026nbsp;\u0026ndash;\u0026nbsp;90.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e45.13 (43.28\u0026nbsp;\u0026ndash;\u0026nbsp;46.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e36.98 (35.75\u0026nbsp;\u0026ndash;\u0026nbsp;38.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e97.94 (96.39\u0026nbsp;\u0026ndash;\u0026nbsp;99.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e89.21 (88.73\u0026nbsp;\u0026ndash;\u0026nbsp;89.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e46.68 (44.86\u0026nbsp;\u0026ndash;\u0026nbsp;48.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e37.45 (36.24\u0026nbsp;\u0026ndash;\u0026nbsp;38.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e97.12 (95.60\u0026nbsp;\u0026ndash;\u0026nbsp;98.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e88.72 (88.25\u0026nbsp;\u0026ndash;\u0026nbsp;89.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e43.09 (41.39\u0026nbsp;\u0026ndash;\u0026nbsp;44.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e36.68 (35.52\u0026nbsp;\u0026ndash;\u0026nbsp;37.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e95.55 (94.06\u0026nbsp;\u0026ndash;\u0026nbsp;97.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e87.55 (87.08\u0026nbsp;\u0026ndash;\u0026nbsp;88.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e44.83 (43.14\u0026nbsp;\u0026ndash;\u0026nbsp;46.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2004\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e35.80 (34.67\u0026nbsp;\u0026ndash;\u0026nbsp;36.93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e93.70 (92.23\u0026nbsp;\u0026ndash;\u0026nbsp;95.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e86.36 (85.90\u0026nbsp;\u0026ndash;\u0026nbsp;86.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e44.96 (43.32\u0026nbsp;\u0026ndash;\u0026nbsp;46.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2005\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e36.05 (34.96\u0026nbsp;\u0026ndash;\u0026nbsp;37.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e91.76 (90.32\u0026nbsp;\u0026ndash;\u0026nbsp;93.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e85.78 (85.32\u0026nbsp;\u0026ndash;\u0026nbsp;86.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e43.92 (42.34\u0026nbsp;\u0026ndash;\u0026nbsp;45.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2006\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e33.41 (32.38\u0026nbsp;\u0026ndash;\u0026nbsp;34.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e88.86 (87.47\u0026nbsp;\u0026ndash;\u0026nbsp;90.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e84.27 (83.82\u0026nbsp;\u0026ndash;\u0026nbsp;84.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e42.71 (41.20\u0026nbsp;\u0026ndash;\u0026nbsp;44.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2007\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e33.82 (32.80\u0026nbsp;\u0026ndash;\u0026nbsp;34.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e86.96 (85.59\u0026nbsp;\u0026ndash;\u0026nbsp;88.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e82.93 (82.48\u0026nbsp;\u0026ndash;\u0026nbsp;83.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e43.48 (41.98\u0026nbsp;\u0026ndash;\u0026nbsp;44.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2008\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e33.46 (32.48\u0026nbsp;\u0026ndash;\u0026nbsp;34.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e83.57 (82.24\u0026nbsp;\u0026ndash;\u0026nbsp;84.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e81.31 (80.87\u0026nbsp;\u0026ndash;\u0026nbsp;81.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e43.02 (41.57\u0026nbsp;\u0026ndash;\u0026nbsp;44.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2009\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e31.59 (30.66\u0026nbsp;\u0026ndash;\u0026nbsp;32.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e81.22 (79.93\u0026nbsp;\u0026ndash;\u0026nbsp;82.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e79.79 (79.36\u0026nbsp;\u0026ndash;\u0026nbsp;80.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e41.63 (40.23\u0026nbsp;\u0026ndash;\u0026nbsp;43.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2010\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e31.55 (30.63\u0026nbsp;\u0026ndash;\u0026nbsp;32.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e81.35 (80.07\u0026nbsp;\u0026ndash;\u0026nbsp;82.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e78.45 (78.02\u0026nbsp;\u0026ndash;\u0026nbsp;78.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e41.82 (40.45\u0026nbsp;\u0026ndash;\u0026nbsp;43.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2011\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e30.52 (29.65\u0026nbsp;\u0026ndash;\u0026nbsp;31.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e78.00 (76.77\u0026nbsp;\u0026ndash;\u0026nbsp;79.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e76.09 (75.68\u0026nbsp;\u0026ndash;\u0026nbsp;76.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e41.13 (39.82\u0026nbsp;\u0026ndash;\u0026nbsp;42.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2012\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e29.66 (28.83\u0026nbsp;\u0026ndash;\u0026nbsp;30.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e76.61 (75.41\u0026nbsp;\u0026ndash;\u0026nbsp;77.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e74.22 (73.81\u0026nbsp;\u0026ndash;\u0026nbsp;74.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e40.25 (39.00\u0026nbsp;\u0026ndash;\u0026nbsp;41.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2013\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e28.92 (28.12\u0026nbsp;\u0026ndash;\u0026nbsp;29.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e74.45 (73.28\u0026nbsp;\u0026ndash;\u0026nbsp;75.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e71.94 (71.54\u0026nbsp;\u0026ndash;\u0026nbsp;72.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e38.70 (37.50\u0026nbsp;\u0026ndash;\u0026nbsp;39.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2014\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e28.23 (27.46\u0026nbsp;\u0026ndash;\u0026nbsp;29.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e70.67 (69.55\u0026nbsp;\u0026ndash;\u0026nbsp;71.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e70.23 (69.84\u0026nbsp;\u0026ndash;\u0026nbsp;70.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e37.79 (36.65\u0026nbsp;\u0026ndash;\u0026nbsp;38.93)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2015\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e27.40 (26.67\u0026nbsp;\u0026ndash;\u0026nbsp;28.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e66.61 (65.54\u0026nbsp;\u0026ndash;\u0026nbsp;67.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e67.74 (67.36\u0026nbsp;\u0026ndash;\u0026nbsp;68.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e36.91 (35.83\u0026nbsp;\u0026ndash;\u0026nbsp;38.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2016\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e25.73 (25.03\u0026nbsp;\u0026ndash;\u0026nbsp;26.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e63.64 (62.62\u0026nbsp;\u0026ndash;\u0026nbsp;64.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e64.23 (63.87\u0026nbsp;\u0026ndash;\u0026nbsp;64.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e35.50 (34.46\u0026nbsp;\u0026ndash;\u0026nbsp;36.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2017\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e24.05 (23.39\u0026nbsp;\u0026ndash;\u0026nbsp;24.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e60.02 (59.04\u0026nbsp;\u0026ndash;\u0026nbsp;61.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e61.74 (61.38\u0026nbsp;\u0026ndash;\u0026nbsp;62.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e33.55 (32.56\u0026nbsp;\u0026ndash;\u0026nbsp;34.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2018\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e23.32 (22.68\u0026nbsp;\u0026ndash;\u0026nbsp;23.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e57.06 (56.12\u0026nbsp;\u0026ndash;\u0026nbsp;58.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e58.75 (58.41\u0026nbsp;\u0026ndash;\u0026nbsp;59.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e31.57 (30.63\u0026nbsp;\u0026ndash;\u0026nbsp;32.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2019\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e22.93 (22.31\u0026nbsp;\u0026ndash;\u0026nbsp;23.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e55.13 (54.22\u0026nbsp;\u0026ndash;\u0026nbsp;56.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e56.43 (56.10\u0026nbsp;\u0026ndash;\u0026nbsp;56.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e31.19 (30.28\u0026nbsp;\u0026ndash;\u0026nbsp;32.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2020\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e21.74 (21.16\u0026nbsp;\u0026ndash;\u0026nbsp;22.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e51.61 (50.74\u0026nbsp;\u0026ndash;\u0026nbsp;52.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e54.04 (53.71\u0026nbsp;\u0026ndash;\u0026nbsp;54.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e30.13 (29.26\u0026nbsp;\u0026ndash;\u0026nbsp;31.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2021\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e21.90 (21.32\u0026nbsp;\u0026ndash;\u0026nbsp;22.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e51.64 (50.77\u0026nbsp;\u0026ndash;\u0026nbsp;52.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e54.20 (53.88\u0026nbsp;\u0026ndash;\u0026nbsp;54.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e29.14 (28.34\u0026nbsp;\u0026ndash;\u0026nbsp;29.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2022\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e21.04 (20.49\u0026nbsp;\u0026ndash;\u0026nbsp;21.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e49.86 (49.01\u0026nbsp;\u0026ndash;\u0026nbsp;50.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e51.30 (50.99\u0026nbsp;\u0026ndash;\u0026nbsp;51.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e28.08 (27.32\u0026nbsp;\u0026ndash;\u0026nbsp;28.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2023\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e20.21 (19.67\u0026nbsp;\u0026ndash;\u0026nbsp;20.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e47.87 (47.05\u0026nbsp;\u0026ndash;\u0026nbsp;48.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e50.66 (50.35\u0026nbsp;\u0026ndash;\u0026nbsp;50.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e27.68 (26.94\u0026nbsp;\u0026ndash;\u0026nbsp;28.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6\u003c/strong\u003e. Bronchus and Lung Cancer-related Mortality per 1,000,000 Adults in the United States stratified by Census Region, 1999 to 2023\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"98%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eYear\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge-Adjusted Mortality Rate (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMidwest\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNortheast\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSouth\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWest\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1999\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e87.36 (86.46\u0026nbsp;\u0026ndash;\u0026nbsp;88.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e81.35 (80.42\u0026nbsp;\u0026ndash;\u0026nbsp;82.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e93.51 (92.75\u0026nbsp;\u0026ndash;\u0026nbsp;94.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e74.81 (73.91\u0026nbsp;\u0026ndash;\u0026nbsp;75.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e87.96 (87.06\u0026nbsp;\u0026ndash;\u0026nbsp;88.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e82.04 (81.12\u0026nbsp;\u0026ndash;\u0026nbsp;82.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e95.48 (94.72\u0026nbsp;\u0026ndash;\u0026nbsp;96.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e74.64 (73.75\u0026nbsp;\u0026ndash;\u0026nbsp;75.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e87.94 (87.04\u0026nbsp;\u0026ndash;\u0026nbsp;88.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e80.66 (79.75\u0026nbsp;\u0026ndash;\u0026nbsp;81.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e93.92 (93.18\u0026nbsp;\u0026ndash;\u0026nbsp;94.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e73.32 (72.45\u0026nbsp;\u0026ndash;\u0026nbsp;74.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e87.85 (86.97\u0026nbsp;\u0026ndash;\u0026nbsp;88.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e80.29 (79.39\u0026nbsp;\u0026ndash;\u0026nbsp;81.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e93.33 (92.60\u0026nbsp;\u0026ndash;\u0026nbsp;94.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e71.89 (71.04\u0026nbsp;\u0026ndash;\u0026nbsp;72.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e86.64 (85.76\u0026nbsp;\u0026ndash;\u0026nbsp;87.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e78.83 (77.94\u0026nbsp;\u0026ndash;\u0026nbsp;79.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e91.71 (90.99\u0026nbsp;\u0026ndash;\u0026nbsp;92.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e71.35 (70.51\u0026nbsp;\u0026ndash;\u0026nbsp;72.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2004\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e86.68 (85.81\u0026nbsp;\u0026ndash;\u0026nbsp;87.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e77.43 (76.55\u0026nbsp;\u0026ndash;\u0026nbsp;78.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e90.44 (89.73\u0026nbsp;\u0026ndash;\u0026nbsp;91.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e68.23 (67.41\u0026nbsp;\u0026ndash;\u0026nbsp;69.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2005\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e85.10 (84.24\u0026nbsp;\u0026ndash;\u0026nbsp;85.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e76.68 (75.81\u0026nbsp;\u0026ndash;\u0026nbsp;77.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e89.98 (89.28\u0026nbsp;\u0026ndash;\u0026nbsp;90.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e67.41 (66.61\u0026nbsp;\u0026ndash;\u0026nbsp;68.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2006\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e84.01 (83.16\u0026nbsp;\u0026ndash;\u0026nbsp;84.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e75.23 (74.37\u0026nbsp;\u0026ndash;\u0026nbsp;76.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e87.60 (86.92\u0026nbsp;\u0026ndash;\u0026nbsp;88.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e65.58 (64.80\u0026nbsp;\u0026ndash;\u0026nbsp;66.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2007\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e83.72 (82.88\u0026nbsp;\u0026ndash;\u0026nbsp;84.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e74.62 (73.77\u0026nbsp;\u0026ndash;\u0026nbsp;75.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e84.99 (84.32\u0026nbsp;\u0026ndash;\u0026nbsp;85.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e64.13 (63.37\u0026nbsp;\u0026ndash;\u0026nbsp;64.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2008\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e82.24 (81.42\u0026nbsp;\u0026ndash;\u0026nbsp;83.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e72.52 (71.69\u0026nbsp;\u0026ndash;\u0026nbsp;73.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e83.40 (82.74\u0026nbsp;\u0026ndash;\u0026nbsp;84.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e62.38 (61.63\u0026nbsp;\u0026ndash;\u0026nbsp;63.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2009\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e80.42 (79.61\u0026nbsp;\u0026ndash;\u0026nbsp;81.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e70.42 (69.61\u0026nbsp;\u0026ndash;\u0026nbsp;71.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e81.55 (80.91\u0026nbsp;\u0026ndash;\u0026nbsp;82.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e61.11 (60.38\u0026nbsp;\u0026ndash;\u0026nbsp;61.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2010\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e79.21 (78.41\u0026nbsp;\u0026ndash;\u0026nbsp;80.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e70.13 (69.32\u0026nbsp;\u0026ndash;\u0026nbsp;70.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e80.37 (79.74\u0026nbsp;\u0026ndash;\u0026nbsp;81.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e59.41 (58.70\u0026nbsp;\u0026ndash;\u0026nbsp;60.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2011\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e77.19 (76.40\u0026nbsp;\u0026ndash;\u0026nbsp;77.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e67.80 (67.00\u0026nbsp;\u0026ndash;\u0026nbsp;68.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e77.52 (76.92\u0026nbsp;\u0026ndash;\u0026nbsp;78.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e56.74 (56.05\u0026nbsp;\u0026ndash;\u0026nbsp;57.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2012\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e76.07 (75.30\u0026nbsp;\u0026ndash;\u0026nbsp;76.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e66.49 (65.71\u0026nbsp;\u0026ndash;\u0026nbsp;67.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e75.57 (74.97\u0026nbsp;\u0026ndash;\u0026nbsp;76.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e54.61 (53.95\u0026nbsp;\u0026ndash;\u0026nbsp;55.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2013\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e73.71 (72.95\u0026nbsp;\u0026ndash;\u0026nbsp;74.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e64.32 (63.56\u0026nbsp;\u0026ndash;\u0026nbsp;65.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e73.11 (72.53\u0026nbsp;\u0026ndash;\u0026nbsp;73.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e52.51 (51.87\u0026nbsp;\u0026ndash;\u0026nbsp;53.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2014\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e72.82 (72.08\u0026nbsp;\u0026ndash;\u0026nbsp;73.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e61.57 (60.83\u0026nbsp;\u0026ndash;\u0026nbsp;62.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e70.92 (70.36\u0026nbsp;\u0026ndash;\u0026nbsp;71.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e50.55 (49.93\u0026nbsp;\u0026ndash;\u0026nbsp;51.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2015\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e69.73 (69.01\u0026nbsp;\u0026ndash;\u0026nbsp;70.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e59.73 (59.01\u0026nbsp;\u0026ndash;\u0026nbsp;60.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e67.68 (67.14\u0026nbsp;\u0026ndash;\u0026nbsp;68.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e49.46 (48.85\u0026nbsp;\u0026ndash;\u0026nbsp;50.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2016\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e66.55 (65.86\u0026nbsp;\u0026ndash;\u0026nbsp;67.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e56.91 (56.21\u0026nbsp;\u0026ndash;\u0026nbsp;57.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e64.43 (63.92\u0026nbsp;\u0026ndash;\u0026nbsp;64.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e45.64 (45.07\u0026nbsp;\u0026ndash;\u0026nbsp;46.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2017\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e63.92 (63.24\u0026nbsp;\u0026ndash;\u0026nbsp;64.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e53.20 (52.54\u0026nbsp;\u0026ndash;\u0026nbsp;53.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e61.54 (61.04\u0026nbsp;\u0026ndash;\u0026nbsp;62.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e44.06 (43.51\u0026nbsp;\u0026ndash;\u0026nbsp;44.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2018\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e60.40 (59.75\u0026nbsp;\u0026ndash;\u0026nbsp;61.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e51.44 (50.79\u0026nbsp;\u0026ndash;\u0026nbsp;52.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e58.73 (58.25\u0026nbsp;\u0026ndash;\u0026nbsp;59.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e40.95 (40.42\u0026nbsp;\u0026ndash;\u0026nbsp;41.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2019\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e58.59 (57.96\u0026nbsp;\u0026ndash;\u0026nbsp;59.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e48.70 (48.07\u0026nbsp;\u0026ndash;\u0026nbsp;49.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e56.53 (56.07\u0026nbsp;\u0026ndash;\u0026nbsp;57.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e39.22 (38.71\u0026nbsp;\u0026ndash;\u0026nbsp;39.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2020\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e56.08 (55.47\u0026nbsp;\u0026ndash;\u0026nbsp;56.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e45.68 (45.08\u0026nbsp;\u0026ndash;\u0026nbsp;46.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e54.15 (53.70\u0026nbsp;\u0026ndash;\u0026nbsp;54.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e37.43 (36.94\u0026nbsp;\u0026ndash;\u0026nbsp;37.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2021\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e56.38 (55.76\u0026nbsp;\u0026ndash;\u0026nbsp;57.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e44.33 (43.74\u0026nbsp;\u0026ndash;\u0026nbsp;44.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e54.01 (53.56\u0026nbsp;\u0026ndash;\u0026nbsp;54.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e37.71 (37.22\u0026nbsp;\u0026ndash;\u0026nbsp;38.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2022\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e53.31 (52.72\u0026nbsp;\u0026ndash;\u0026nbsp;53.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e42.63 (42.06\u0026nbsp;\u0026ndash;\u0026nbsp;43.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e50.80 (50.37\u0026nbsp;\u0026ndash;\u0026nbsp;51.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e35.77 (35.30\u0026nbsp;\u0026ndash;\u0026nbsp;36.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2023\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22px;\"\u003e\n \u003cp\u003e52.94 (52.35\u0026nbsp;\u0026ndash;\u0026nbsp;53.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e41.46 (40.91\u0026nbsp;\u0026ndash;\u0026nbsp;42.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e49.92 (49.50\u0026nbsp;\u0026ndash;\u0026nbsp;50.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e34.72 (34.26 \u0026ndash; 35.18)\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\u003e\u003cstrong\u003eTable 7\u003c/strong\u003e. Bronchus and Lung Cancer-related Mortality in the United States stratified by urban-rural, 1999 to 2020\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eYear\u003csup\u003e*\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge-Adjusted Mortality Rate (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMetropolitan\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNonmetropolitan\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1999\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e84.95 (84.47 \u0026ndash; 85.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e89.16 (88.13 \u0026ndash; 90.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e85.40 (84.93 \u0026ndash; 85.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e92.54 (91.50 \u0026ndash; 93.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e84.22 (83.76 \u0026ndash; 84.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e91.73 (90.70 \u0026ndash; 92.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e83.43 (82.97 \u0026ndash; 83.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e91.92 (90.90 \u0026ndash; 92.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e82.14 (81.69 \u0026ndash; 82.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e90.68 (89.67 \u0026ndash; 91.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2004\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e80.64 (80.19 \u0026ndash; 81.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e90.07 (89.07 \u0026ndash; 91.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2005\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e79.63 (79.19 \u0026ndash; 80.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e89.89 (88.90 \u0026ndash; 90.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2006\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e77.76 (77.33 \u0026ndash; 78.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e88.33 (87.36 \u0026ndash; 89.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2007\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e75.93 (75.51 \u0026ndash; 76.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e88.80 (87.83 \u0026ndash; 89.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2008\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e74.28 (73.87 \u0026ndash; 74.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e87.00 (86.05 \u0026ndash; 87.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2009\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e72.45 (72.05 \u0026ndash; 72.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e85.53 (84.59 \u0026ndash; 86.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2010\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e71.34 (70.94 \u0026ndash; 71.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e84.47 (83.54 \u0026ndash; 85.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2011\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e68.57 (68.18 \u0026ndash; 68.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e83.31 (82.39 \u0026ndash; 84.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2012\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e66.91 (66.54 \u0026ndash; 67.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e81.31 (80.42 \u0026ndash; 82.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2013\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e64.60 (64.24 \u0026ndash; 64.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e79.10 (78.23 \u0026ndash; 79.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2014\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e62.53 (62.18 \u0026ndash; 62.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e77.83 (76.97 \u0026ndash; 78.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2015\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e60.04 (59.70 \u0026ndash; 60.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e75.60 (74.75 \u0026ndash; 76.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2016\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e56.61 (56.28 \u0026ndash; 56.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e72.90 (72.07 \u0026ndash; 73.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2017\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e54.08 (53.77 \u0026ndash; 54.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e69.65 (68.84 \u0026ndash; 70.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2018\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e51.31 (51.00 \u0026ndash; 51.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e66.37 (65.60 \u0026ndash; 67.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2019\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e49.15 (48.86 \u0026ndash; 49.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e64.70 (63.94 \u0026ndash; 65.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2020\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e46.68 (46.40 \u0026ndash; 46.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e62.74 (62.00 \u0026ndash; 63.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003e*\u003c/sup\u003eDue to missing urban-rural data for 2021\u0026ndash;2023, the corresponding stratified analyses for these years were not conducted in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 8\u003c/strong\u003e AAMRs per 100 000 adults and Percent Change of Bronchus and Lung Cancer of District of Columbia, all 50 states in the United States in 1999 and 2023.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eState\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAAMR 2023\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAAMR 1999\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePercent Change (%)\u003csup\u003e*\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDistrict of Columbia\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e33.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e83.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e-59.40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNevada\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e42.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e98.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e-56.80\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCalifornia\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e32.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e74.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e-56.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNew Jersey\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e37.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e81.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e-54.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eArizona\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e35.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e76.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e-54.23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMontana\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e37.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e82.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e-54.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n 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York\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e36.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e77.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e-52.85\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTexas\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e40.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e85.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e-52.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRhode Island\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n 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style=\"width: 32px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVirginia\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e47.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e90.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e-48.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNew Hampshire\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e45.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e86.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e-47.54\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n 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style=\"width: 20px;\"\u003e\n \u003cp\u003e44.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e82.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e-46.62\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eConnecticut\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e40.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e75.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e-45.70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSouth Carolina\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e51.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e92.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e-44.68\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIllinois\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e48.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e87.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e-44.26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePennsylvania\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e48.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e84.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e-42.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLouisiana\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e58.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e101.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e-42.47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNorth Carolina\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e54.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e93.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e-42.22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUtah\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e23.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e40.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e-41.86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMississippi\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e63.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e108.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e-41.66\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n 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style=\"width: 20px;\"\u003e\n \u003cp\u003e50.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e84.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e-41.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMinnesota\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e43.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e73.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e-40.55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOhio\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e56.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e94.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e-39.79\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSouth Dakota\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e46.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e76.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e-39.41\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMaine\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e54.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e89.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e-39.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNebraska\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e48.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e79.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e-39.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIndiana\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e61.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e101.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e-38.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHawaii\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e34.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e56.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e-38.92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWisconsin\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e46.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e75.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e-38.77\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTennessee\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e63.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e103.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e-38.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eArkansas\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e64.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e104.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e-38.57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWest Virginia\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e70.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e113.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e-38.18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eKansas\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e51.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e83.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e-37.78\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOklahoma\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e60.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e96.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e-37.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMichigan\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e54.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e87.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e-36.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMissouri\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e61.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e95.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e-35.72\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIowa\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e51.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e78.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e-34.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eKentucky\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e75.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e114.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e-33.88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNorth Dakota\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e43.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e64.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e-32.29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u003csup\u003e*\u003c/sup\u003e\u003c/strong\u003ePercent Change = (AAMR 2023 - AAMR 1999)/AAMR 1999)*100%\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":"journal-of-cardiothoracic-surgery","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jcts","sideBox":"Learn more about [Journal of Cardiothoracic Surgery](http://cardiothoracicsurgery.biomedcentral.com)","snPcode":"13019","submissionUrl":"https://submission.nature.com/new-submission/13019/3","title":"Journal of Cardiothoracic Surgery","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"CDC WONDER, Bronchus and lung cancer, Mortality trends","lastPublishedDoi":"10.21203/rs.3.rs-7309766/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7309766/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eBronchus and lung cancer is one of the most common and deadly types of cancer in United States. This study analyzed the mortality trends related to bronchus and lung cancer among U.S. adults\u0026thinsp;\u0026ge;\u0026thinsp;25 years old from 1999 to 2023 from demographic and geographic perspectives.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eWe utilized the CDC WONDER database to investigate the trends in Bronchus and lung cancer-related mortality in the United States. Age-adjusted mortality rates per 100,000 people (AAMR), annual percentage change (APC), and average annual percentage change (AAPC) with 95% confidence intervals (CIs) were calculated and the data were stratified by year, age groups, sex, race/ethnicity, census region, urban-rural and states classification. The Joinpoint Regression Program was utilized to estimate mortality trends between 1999 and 2023.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eFrom 1999 to 2023, there was a significant decline in AAMRs for bronchus and lung cancer across the United States. The crude mortality rate (CMR) for bronchus and lung cancer demonstrates a significant decline across most age groups males had higher AAMRs than females, with persistent disparities highlighting the need for targeted interventions. Non-Hispanic Black individuals had the highest AAMRs, while Hispanic or Latino individuals had the lowest. Geographic disparities were evident, with the West region having the lowest mortality rates compared to the South and Midwest regions; nonmetropolitan had higher mortality rates than metropolitan. Compared to 1999, AAMRs decreased in all U.S. states in 2023, with the most significant declines observed in the District of Columbia, Nevada, and California. The slight increase in AAMRs from 2020 to 2023 may be linked to the COVID-19 pandemic, further emphasizing the importance of ongoing surveillance and adaptive public health measures.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eIt is crucial to assess potential health disparities among different regions and population groups. There is an urgent need for further research and the implementation of targeted public health interventions, as well as improvements in resource allocation and health outcomes among populations.\u003c/p\u003e","manuscriptTitle":"Bronchus and lung cancer-related mortality trends in the United States from 1999 to 2023","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-04 14:34:50","doi":"10.21203/rs.3.rs-7309766/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-25T07:27:23+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-18T20:20:49+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-13T00:00:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"157741789928245373966788474452786582138","date":"2026-01-10T12:23:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"90101877560996671495982300913512838236","date":"2026-01-08T15:11:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"132536087405890751377299443683659166350","date":"2026-01-01T06:48:16+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-08T11:50:31+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"58149275820633025598251331581744583030","date":"2025-09-04T11:40:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"91766750863582145719310812611167506955","date":"2025-08-29T14:08:59+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-28T13:24:50+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-13T06:23:40+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-13T06:22:30+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Cardiothoracic Surgery","date":"2025-08-06T12:20:36+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-cardiothoracic-surgery","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jcts","sideBox":"Learn more about [Journal of Cardiothoracic Surgery](http://cardiothoracicsurgery.biomedcentral.com)","snPcode":"13019","submissionUrl":"https://submission.nature.com/new-submission/13019/3","title":"Journal of Cardiothoracic Surgery","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7e897112-35ec-448d-8700-095055ae043c","owner":[],"postedDate":"September 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-04-20T16:00:50+00:00","versionOfRecord":{"articleIdentity":"rs-7309766","link":"https://doi.org/10.1186/s13019-026-04075-z","journal":{"identity":"journal-of-cardiothoracic-surgery","isVorOnly":false,"title":"Journal of Cardiothoracic Surgery"},"publishedOn":"2026-04-16 15:56:55","publishedOnDateReadable":"April 16th, 2026"},"versionCreatedAt":"2025-09-04 14:34:50","video":"","vorDoi":"10.1186/s13019-026-04075-z","vorDoiUrl":"https://doi.org/10.1186/s13019-026-04075-z","workflowStages":[]},"version":"v1","identity":"rs-7309766","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7309766","identity":"rs-7309766","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}