Body composition and risk of gastric cancer: A population‐based prospective cohort study

Liu, An-Ran; He, Qiangsheng; Wu, Wenhui; Du, Jianliang; Kuo, Zichong; Xia, Bin; Tang, Yan; Peng, Yun; Cheung, Eddie C.; Tang, Ying‐Mei; Zhang, Changhua; Yuan, Jinqiu

doi:10.1002/cam4.3808

Cited by 12 publications

(10 citation statements)

References 27 publications

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“…Changes in anthropometric parameters, including weight, BMI, waist circumference, waist‐to‐hip ratio, FM, and FFM, reflect an individual's nutritional status to some extent and can, therefore, greatly predict the risk and prognosis of chronic diseases, including cancer 17,18 . Similar to our partial results, some studies based on the UK Biobank have also shown that FFM is strongly associated with the risk of all cancers, including lung and digestive system cancers 7,19,20 . Another study on body composition using dual‐emission X‐ray absorptiometry also demonstrated a significant association between FFM and the malignancy of prostate cancer 21 .…”

Section: Discussionsupporting

confidence: 87%

“…17,18 Similar to our partial results, some studies based on the UK Biobank have also shown that FFM is strongly associated with the risk of all cancers, including lung and digestive system cancers. 7,19,20 Another study on body composition using dual-emission X-ray absorptiometry also demonstrated a significant association between FFM and the malignancy of prostate cancer. 21 At the same time, there are also some heterogeneous conclusions.…”

Section: Discussionmentioning

confidence: 97%

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Predicted lean body mass trajectories, and cancer risk and cancer‐specific and all‐cause mortality: A prospective cohort study

Liu,

Zhang,

Liu

et al. 2023

J cachexia sarcopenia muscle

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BackgroundAlthough many studies have investigated the association between body composition, cancer risk and mortality, predicting these risks through a single body composition measurement undoubtedly increases the limitations of the study. Few studies have explored the association between the trajectory of changes in body composition and the risk of cancer and death. We aimed to explore the association of predicted lean mass trajectories with cancer risk, cancer‐specific mortality and all‐cause mortality.MethodsThe participants in this study were all from the Kailuan cohort, a prospective, periodic, resurvey cohort study initiated in 2006. Latent mixture modelling was used to identify predicted lean mass trajectories for 2006–2010. The hazard ratios (HRs) and 95% confidence intervals (95% CIs) of the Cox proportional hazard models were used to describe the association between predicted lean mass trajectories and cancer risk and cancer‐specific and all‐cause mortality during follow‐up (2010–2021).ResultsA total of 44 374 participants (average age, 53.01 ± 11.41 years, 78.99% men and 21.01% women) were enrolled in this study. Five distinct trajectories were identified: low‐stable (n = 12 060), low‐increasing (n = 8027), moderately stable‐decreasing (n = 4725), moderately stable‐increasing (n = 8053) and high‐stable (n = 11 509). During the 11‐year follow‐up period, 2183 cancer events were recorded. After adjusting for age, predicted fat mass in 2010, sex, BMI, sedentary, physical activity, smoke, alcohol use, salt consumption, high‐fat diet, high‐sensitivity C‐reactive protein, serum creatinine, family history of tumour, hypertension, diabetes mellitus, compared with the low‐stable group, participants in the low‐increasing group (HR = 0.851, 95% CI, 0.748–0.969), moderately stable‐increasing group (HR = 0.803, 95% CI, 0.697–0.925) and high‐stable group (HR = 0.770, 95% CI, 0.659–0.901) had a lower cancer risk, but not in the moderately stable‐decreasing group (HR = 0.864, 95% CI, 0.735–1.015). Compared with the low‐stable group, the risk of cancer‐specific mortality was reduced by 25.4% (8.8–38.9%), 36.5% (20.3–49.4%) and 35.4% (17.9–49.2%), and the risk of all‐cause mortality was reduced by 24.2% (16.9–30.8%), 37.0% (30.0–43.2%) and 47.4% (41.0–53.1%) in the low‐increasing, moderately stable‐increasing group and high‐stable groups, respectively.ConclusionsPredicted lean mass trajectories may be closely associated with cancer risk and cancer‐specific and all‐cause mortality. Regular monitoring of body composition is necessary.

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Section: Discussionsupporting

confidence: 87%

Section: Discussionmentioning

confidence: 97%

Predicted lean body mass trajectories, and cancer risk and cancer‐specific and all‐cause mortality: A prospective cohort study

Liu,

Zhang,

Liu

et al. 2023

J cachexia sarcopenia muscle

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“…Body shape not only reflects the weight information, but also reflects the information of body composition ( 23 ). In order to reduce recall bias and incorporate body composition information into the analysis, our study used Stunkard body shape as a component of lifestyle variables ( 9 , 38 ). Consistent with previous studies, our study also found that a suitable body size is associated with a lower GC risk ( 10 , 39 ).…”

Section: Discussionmentioning

confidence: 99%

“…A number of large-scale cohort studies and meta-analyses have examined the relationship between smoking ( 6 ), alcohol drinking ( 7 ), poor oral hygiene habits ( 8 ), BMI and body composition ( 9 , 10 ), diet ( 11 – 15 ), physical activity ( 16 – 18 ) and the risk of GC. The observed reduced GC risk associated with refrigerator usage also suggests that food storage method may be one of the GC-risk-related lifestyle factors ( 19 ).…”

Section: Introductionmentioning

confidence: 99%

Healthy Lifestyle Factors, Cancer Family History, and Gastric Cancer Risk: A Population-Based Case-Control Study in China

Man

Yang

et al. 2021

Front. Nutr.

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Background: We aimed to explore the relationship between lifestyle factors, cancer family history, and gastric cancer risk.Methods: We examined the association between lifestyle factors, cancer family history, and gastric cancer risk based on a population-based case-control study in Taixing, China, with 870 cases and 1928 controls. A lifestyle score was constructed considering body shape, smoking, alcohol drinking, tooth brushing habit, and food storage method. Unconditional logistic regression models were used to calculate odd ratios (ORs) and 95% confidence intervals (CIs).Results: Compared with participants with a lifestyle score of 0, subjects with a lifestyle score of 1 (OR 0.59, 95%CI 0.43–0.83), 2 (OR 0.42, 95%CI 0.30–0.59), 3 (OR 0.29, 95%CI 0.20–0.41), 4 (OR 0.20, 95%CI 0.13–0.32), or 5 (OR 0.10, 95%CI 0.04–0.22) had a lower risk of gastric cancer (P for trend < 0.001). Overall, 34% of gastric cancer cases (95%CI 27–41%) can be attributed to non-compliance with ≥3 healthy lifestyle. Family history of early-onset cancer is closely related to the occurrence of gastric cancer, with an OR ranging from 1.77 to 3.27. Regardless of family history, a good lifestyle is associated with a reduced risk of gastric cancer, with an OR value between 0.38 and 0.70.Conclusions: The early-onset cancer family history is closely related to the occurrence of gastric cancer and a good lifestyle is associated with a reduced risk of gastric cancer regardless of family history. Our results provide a basis for identifying and providing behavior guidance of high-risk groups of gastric cancer.

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“…www.co-urology.com analyzing weight without taking into consideration the different body compositions can lead to different biases. A recent population-based prospective cohort study by Liu et al [22] reported that both male (HR ¼ 1.70) and female patients (HR ¼ 2.47) with higher levels of body fat-free mass had a higher risk of gastric cancer [22]. In contrast, in female patients fat mass was identified as a protective factor of gastric cancer (HR per 5-unit increase 0.86).…”

Section: Key Pointsmentioning

confidence: 99%

Metabolic syndrome, obesity and cancer risk

Belladelli

Montorsi

Martini

2022

Current Opinion in Urology

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Purpose of reviewThis review aims to report the latest discoveries regarding the relationship between BMI, obesity, and cancer development and treatment. Recent findingsObesity and metabolic syndrome relationships with cancer have been deeply investigated in the literature but their association is still debated. Currently, it has been recorded an association between BMI and endometrial, colorectal, gastric, liver, bladder, and prostate cancer. The mechanisms behind this association have also been investigated. It has been hypothesized that chronic inflammation determined by obesity may concur to the development of tumors and that Insulin Resistance may enhance cell proliferation directly or indirectly. Moreover, different studies suggest that the relationship between higher BMI and cancer may include metabolic disturbances comparable to those linked to metabolic syndrome. However, greater weight has been linked to a better overall prognosis in patients with advanced disease, a concept called the obesity paradox. This paradox has been recently investigated in the context of urological malignancies, such as bladder, prostate, and kidney cancer. SummaryPatients' metabolic and morphological status may impact their risk of developing different types of tumors and the response to systemic therapy. However, further research is necessary to better delineate the mechanisms behind these associations and how they could or should affect medical decision.

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Body composition and risk of gastric cancer: A population‐based prospective cohort study

Cited by 12 publications

References 27 publications

Predicted lean body mass trajectories, and cancer risk and cancer‐specific and all‐cause mortality: A prospective cohort study

Predicted lean body mass trajectories, and cancer risk and cancer‐specific and all‐cause mortality: A prospective cohort study

Healthy Lifestyle Factors, Cancer Family History, and Gastric Cancer Risk: A Population-Based Case-Control Study in China

Metabolic syndrome, obesity and cancer risk

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