Overall and Central Obesity and Risk of Lung Cancer: A Pooled Analysis

Yu, Danxia; Wang, Zheng; Johansson, Mattias; Lan, Qing; Park, Yikyung; White, Emily; Matthews, Charles E.; Sawada, Norie; Gao, Yu Tang; Robien, Kim; Sinha, Rashmi; Langhammer, Arnulf; Kaaks, Rudolf; Giovannucci, Edward; Liao, Linda M.; Xiang, Yong Bing; Lazovich, De Ann; Peters, Ulrike; Zhang, Xuehong; Bueno‐de‐Mesquita, Bas; Willett, Walter C.; Tsugane, Shoichiro; Takata, Yumie; Smith‐Warner, Stephanie A.; Blot, William J.; Shu, Xiao Ou

doi:10.1093/jnci/djx286

Cited by 92 publications

(123 citation statements)

References 42 publications

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“…The RR for BMI from observational studies were extracted from the World Cancer Research Fund (WCRF) Third Expert Report, except for lung cancer which used a large pooled analysis. 21,22 MR confirms and refines the causal effect of BMI on six obesity-related cancers For six out of seven evaluated cancer sites that were previously identified as being positively associated with BMI in the WCRF report, we also observed risk increases based on the MR analysis ( Figure 2). However, for each of these six cancer sites, the MR estimate for a 5-unit increment in BMI was notably higher than the WCRF estimate, being approximately 2-fold higher for cancers of the kidney [e.g.…”

Section: Methodssupporting

confidence: 82%

Commentary: What can Mendelian randomization tell us about causes of cancer?

Mariosa

Carreras‐Torres

Martin

et al. 2019

International Journal of Epidemiology

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Section: Methodssupporting

confidence: 82%

Commentary: What can Mendelian randomization tell us about causes of cancer?

Mariosa

Carreras‐Torres

Martin

et al. 2019

International Journal of Epidemiology

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“…BMI is crude measure of obesity, and other more accurate measures (eg, waist circumference, adipokines and so on) are required to fully explore the relationship between obesity, inflammation and the microbiome in development of CRC. An exemplar of this relationship is demonstrated for lung cancer, wherein the use of BMI demonstrates that a lower risk of lung cancer is associated with higher BMI but use of waist circumference or waist to hip ratio demonstrates and increased risk of lung cancer 51. Thus, this study sets the stage for future research to consider adding measures of adiposity beyond BMI when studying the aetiology and risk of CRC as well as other cancers influenced by obesity.…”

Section: Discussionmentioning

confidence: 82%

Gut microbiome meta-analysis reveals dysbiosis is independent of body mass index in predicting risk of obesity-associated CRC

Greathouse

White

Padgett

et al. 2019

BMJ Open Gastroenterol

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ObjectiveObesity is a risk factor for colorectal cancer (CRC), accounting for more than 14% of CRC incidence. Microbial dysbiosis and chronic inflammation are common characteristics in both obesity and CRC. Human and murine studies, together, demonstrate the significant impact of the microbiome in governing energy metabolism and CRC development; yet, little is understood about the contribution of the microbiome to development of obesity-associated CRC as compared to individuals who are not obese.DesignIn this study, we conducted a meta-analysis using five publicly available stool and tissue-based 16S rRNA and whole genome sequencing (WGS) data sets of CRC microbiome studies. High-resolution analysis was employed for 16S rRNA data, which allowed us to achieve species-level information to compare with WGS. ResultsCharacterisation of the confounders between studies, 16S rRNA variable region and sequencing method did not reveal any significant effect on alpha diversity in CRC prediction. Both 16S rRNA and WGS were equally variable in their ability to predict CRC. Results from diversity analysis confirmed lower diversity in obese individuals without CRC; however, no universal differences were found in diversity between obese and non-obese individuals with CRC. When examining taxonomic differences, the probability of being classified as CRC did not change significantly in obese individuals for all taxa tested. However, random forest classification was able to distinguish CRC and non-CRC stool when body mass index was added to the model.ConclusionOverall, microbial dysbiosis was not a significant factor in explaining the higher risk of colon cancer among individuals with obesity.

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“…Several studies have attempted to use NHANES self-reported and measured weight data to generate corrections for BRFSS self-reported weight and height data (11,12,15) or for NHIS data (12,17,18,30), as well as for other data sets (31,32). However, the differences between the self-reported data in NHANES and the self-reported data in NHIS and BRFSS suggest that such corrections may not be completely accurate.…”

Section: Discussionmentioning

confidence: 99%

Comparisons of Self‐Reported and Measured Height and Weight, BMI, and Obesity Prevalence from National Surveys: 1999‐2016

Flegal

Ogden

Fryar

et al. 2019

Obesity

104

116

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Objective The aim of this study was to compare national estimates of self‐reported and measured height and weight, BMI, and obesity prevalence among adults from US surveys. Methods Self‐reported height and weight data came from the National Health and Nutrition Examination Survey (NHANES), the National Health Interview Survey, and the Behavioral Risk Factor Surveillance System for the years 1999 to 2016. Measured height and weight data were available from NHANES. BMI was calculated from height and weight; obesity was defined as BMI ≥ 30. Results In all three surveys, mean self‐reported height was higher than mean measured height in NHANES for both men and women. Mean BMI from self‐reported data was lower than mean BMI from measured data across all surveys. For women, mean self‐reported weight, BMI, and obesity prevalence in the National Health Interview Survey and Behavioral Risk Factor Surveillance System were lower than self‐report in NHANES. The distribution of BMI was narrower for self‐reported than for measured data, leading to lower estimates of obesity prevalence. Conclusions Self‐reported height, weight, BMI, and obesity prevalence were not identical across the three surveys, particularly for women. Patterns of misreporting of height and weight and their effects on BMI and obesity prevalence are complex.

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Overall and Central Obesity and Risk of Lung Cancer: A Pooled Analysis

Abstract: The inverse BMI-lung cancer association is not entirely due to smoking and reverse causation. Central obesity, particularly concurrent with low BMI, may help identify high-risk populations for lung cancer.

Cited by 92 publications

References 42 publications

Commentary: What can Mendelian randomization tell us about causes of cancer?

Commentary: What can Mendelian randomization tell us about causes of cancer?

Gut microbiome meta-analysis reveals dysbiosis is independent of body mass index in predicting risk of obesity-associated CRC

Comparisons of Self‐Reported and Measured Height and Weight, BMI, and Obesity Prevalence from National Surveys: 1999‐2016

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