scholarly journals Radiation and Smoking Effects on Lung Cancer Incidence among Atomic Bomb Survivors

2010 ◽  
Vol 174 (1) ◽  
pp. 72 ◽  
Author(s):  
Kyoji Furukawa ◽  
Dale L. Preston ◽  
Stefan Lönn ◽  
Sachiyo Funamoto ◽  
Shuji Yonehara ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cancer Incidence ◽  
Atomic Bomb ◽  
Lung Cancer Incidence ◽  
Atomic Bomb Survivors

scholarly journals Radiation and Smoking Effects on Lung Cancer Incidence by Histological Types Among Atomic Bomb Survivors

2012 ◽  
Vol 178 (3) ◽  
pp. 191 ◽  
Author(s):  
Hiromi Egawa ◽  
Kyoji Furukawa ◽  
Dale Preston ◽  
Sachiyo Funamoto ◽  
Shuji Yonehara ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cancer Incidence ◽  
Atomic Bomb ◽  
Lung Cancer Incidence ◽  
Histological Types ◽  
Atomic Bomb Survivors

scholarly journals Lifetime Risk Assessment of Lung Cancer Incidence for Nonsmokers in Japan Considering the Joint Effect of Radiation and Smoking Based on the Life Span Study of Atomic Bomb Survivors

2021 ◽  
Vol 46 (3) ◽  
pp. 83-97
Author(s):  
Kazumasa Shimada ◽  
Michiaki Kai
Keyword(s):  
Lung Cancer ◽  
Risk Assessment ◽  
Sensitivity Analysis ◽  
Atomic Bomb ◽  
Joint Effect ◽  
Mixed Population ◽  
Baseline Risk ◽  
Lung Cancer Incidence ◽  
Life Span Study ◽  
Atomic Bomb Survivors

Background: The lifetime risk of lung cancer incidence due to radiation for nonsmokers is overestimated because of the use of the average cancer baseline risk among a mixed population, including smokers. In recent years, the generalized multiplicative (GM)-excess relative risk (ERR) model has been developed in the life span study of atomic bomb survivors to consider the joint effect of radiation and smoking. Based on this background, this paper discusses the issues of radiation risk assessment considering smoking in two parts.Materials and Methods: In Part 1, we proposed a simple method of estimating the baseline risk for nonsmokers using current smoking data. We performed sensitivity analysis on baseline risk estimation to discuss the birth cohort effects. In Part 2, we applied the GM-ERR model for Japanese smokers to calculate lifetime attributable risk (LAR). We also performed a sensitivity analysis using other ERR models (e.g., simple additive (SA)-ERR model).Results and Discussion: In Part 1, the lifetime baseline risk from mixed population including smokers to nonsmokers decreased by 54% (44%–60%) for males and 24% (18%–29%) for females. In Part 2, comparison of LAR between SA- and GM-ERR models showed that if the radiation dose was ≤200 mGy or less, the difference between these ERR models was within the standard deviation of LAR due to the uncertainty of smoking information.Conclusion: The use of mixed population for baseline risk assessment overestimates the risk for lung cancer due to low-dose radiation exposure in Japanese males.

scholarly journals Multiple air pollutant exposure and lung cancer in Tehran, Iran

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Zahra Khorrami ◽  
Mohsen Pourkhosravani ◽  
Maysam Rezapour ◽  
Koorosh Etemad ◽  
Seyed Mahmood Taghavi-Shahri ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Air Pollution ◽  
Cancer Incidence ◽  
Latent Profile Analysis ◽  
Negative Binomial ◽  
Profile Analysis ◽  
Positive Association ◽  
Air Pollutant ◽  
World Health ◽  
Lung Cancer Incidence

AbstractLung cancer is the most rapidly increasing malignancy worldwide with an estimated 2.1 million cancer cases in the latest, 2018 World Health Organization (WHO) report. The objective of this study was to investigate the association of air pollution and lung cancer, in Tehran, Iran. Residential area information of the latest registered lung cancer cases that were diagnosed between 2014 and 2016 (N = 1,850) were inquired from the population-based cancer registry of Tehran. Long-term average exposure to PM10, SO2, NO, NO2, NOX, benzene, toluene, ethylbenzene, m-xylene, p-xylene, o-xylene (BTEX), and BTEX in 22 districts of Tehran were estimated using land use regression models. Latent profile analysis (LPA) was used to generate multi-pollutant exposure profiles. Negative binomial regression analysis was used to examine the association between air pollutants and lung cancer incidence. The districts with higher concentrations for all pollutants were mostly in downtown and around the railway station. Districts with a higher concentration for NOx (IRR = 1.05, for each 10 unit increase in air pollutant), benzene (IRR = 3.86), toluene (IRR = 1.50), ethylbenzene (IRR = 5.16), p-xylene (IRR = 9.41), o-xylene (IRR = 7.93), m-xylene (IRR = 2.63) and TBTEX (IRR = 1.21) were significantly associated with higher lung cancer incidence. Districts with a higher multiple air-pollution profile were also associated with more lung cancer incidence (IRR = 1.01). Our study shows a positive association between air pollution and lung cancer incidence. This association was stronger for, respectively, p-xylene, o-xylene, ethylbenzene, benzene, m-xylene and toluene.

Do socioeconomic factors modify the effects of PM1 and SO2 on lung cancer incidence in China?

2021 ◽  
Vol 756 ◽  
pp. 143998
Author(s):  
Huagui Guo ◽  
Jing Wei ◽  
Xin Li ◽  
Hung Chak Ho ◽  
Yimeng Song ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Socioeconomic Factors ◽  
Cancer Incidence ◽  
Lung Cancer Incidence

scholarly journals Spatial and Temporal Analysis of Lung Cancer in Shenzhen, 2008–2018

2020 ◽  
Vol 18 (1) ◽  
pp. 26
Author(s):  
Lin Lei ◽  
Anyan Huang ◽  
Weicong Cai ◽  
Ling Liang ◽  
Yirong Wang ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Spatial Autocorrelation ◽  
Incidence Rate ◽  
Cancer Incidence ◽  
Southern China ◽  
Percentage Change ◽  
Spatial Autocorrelation Analysis ◽  
Lung Cancer Incidence ◽  
Annual Percentage Change ◽  
Autocorrelation Analysis

Lung cancer is the most commonly diagnosed cancer in China. The incidence trend and geographical distribution of lung cancer in southern China have not been reported. The present study explored the temporal trend and spatial distribution of lung cancer incidence in Shenzhen from 2008 to 2018. The lung cancer incidence data were obtained from the registered population in the Shenzhen Cancer Registry System between 2008 and 2018. The standardized incidence rates of lung cancer were analyzed by using the joinpoint regression model. The Moran’s I method was used for spatial autocorrelation analysis and to further draw a spatial cluster map in Shenzhen. From 2008 to 2018, the average crude incidence rate of lung cancer was 27.1 (1/100,000), with an annual percentage change of 2.7% (p < 0.05). The largest average proportion of histological type of lung cancer was determined as adenocarcinoma (69.1%), and an increasing trend was observed in females, with an average annual percentage change of 14.7%. The spatial autocorrelation analysis indicated some sites in Shenzhen as a high incidence rate spatial clustering area. Understanding the incidence patterns of lung cancer is useful for monitoring and prevention.

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