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Importance: Chinese women have the highest rate of lung cancer among female never-smokers in the world, and the etiology is poorly understood., Objective: To assess the association between metabolomics and lung cancer risk among never-smoking women., Design, Setting, and Participants: This nested case-control study included 275 never-smoking female patients with lung cancer and 289 never-smoking cancer-free control participants from the prospective Shanghai Women's Health Study recruited from December 28, 1996, to May 23, 2000. Validated food frequency questionnaires were used for the collection of dietary information. Metabolomic analysis was conducted from November 13, 2015, to January 6, 2016. Data analysis was conducted from January 6, 2016, to November 29, 2018., Exposures: Untargeted ultra-high-performance liquid chromatography-tandem mass spectrometry and nuclear magnetic resonance metabolomic profiles were characterized using prediagnosis urine samples. A total of 39 416 metabolites were measured., Main Outcomes and Measures: Incident lung cancer., Results: Among the 564 women, those who developed lung cancer (275 participants; median [interquartile range] age, 61.0 [52-65] years) and those who did not develop lung cancer (289 participants; median [interquartile range] age, 62.0 [53-66] years) at follow-up (median [interquartile range] follow-up, 10.9 [9.0-11.7] years) were similar in terms of their secondhand smoke exposure, history of respiratory diseases, and body mass index. A peak metabolite, identified as 5-methyl-2-furoic acid, was significantly associated with lower lung cancer risk (odds ratio, 0.57 [95% CI, 0.46-0.72]; P < .001; false discovery rate = 0.039). Furthermore, this peak was weakly correlated with self-reported dietary soy intake (ρ = 0.21; P < .001). Increasing tertiles of this metabolite were associated with lower lung cancer risk (in comparison with first tertile, odds ratio for second tertile, 0.52 [95% CI, 0.34-0.80]; and odds ratio for third tertile, 0.46 [95% CI, 0.30-0.70]), and the association was consistent across different histological subtypes and follow-up times. Additionally, metabolic pathway analysis found several systemic biological alterations that were associated with lung cancer risk, including 1-carbon metabolism, nucleotide metabolism, oxidative stress, and inflammation., Conclusions and Relevance: This prospective study of the untargeted urinary metabolome and lung cancer among never-smoking women in China provides support for the hypothesis that soy-based metabolites are associated with lower lung cancer risk in never-smoking women and suggests that biological processes linked to air pollution may be associated with higher lung cancer risk in this population.

Background: Physical activity is associated with a variety of health benefits, but the biological mechanisms that explain these associations remain unclear. Metabolomics is a powerful tool to comprehensively evaluate global metabolic signature associated with physical activity and helps to pinpoint the pathways that mediate the health effects of physical activity. There has been limited research on metabolomics and habitual physical activity, and no metabolomics study has examined sedentary behaviour and physical activity of different intensities., Methods: In a group of Chinese adults (N = 277), we used an untargeted approach to examine 328 plasma metabolites in relation to accelerometer-measured physical activity, including overall volume of physical activity (physical activity energy expenditure (PAEE) and duration of physically active time) and sedentary time, and measures related to different intensities of physical activity (moderate-to-vigorous activity (MVPA), light activity, average physical activity intensity)., Results: We identified 11 metabolites that were associated with total activity, with a false discovery rate of 0.2 or lower. Notably, we observed generally lower levels of amino acids in the valine, leucine and isoleucine metabolism pathway and of carbohydrates in sugar metabolism among participants with higher activity levels. Moreover, we found that PAEE, time spent in light activity and duration of physically active time were associated with a similar metabolic pattern, whereas the metabolic signature associated with sedentary time mirrored this pattern. In contrast, average activity intensity and time spent in MVPA appeared to be associated with somewhat different metabolic patterns., Conclusions: Overall, the metabolomics patterns support a beneficial role of higher volume of physical activity in cardiometabolic health. Our findings identified candidate pathways and provide insight into the mechanisms underlying the health effects of physical activity., (Published by Oxford University Press on behalf of the International Epidemiological Association 2016. This work is written by US Government employees and is in the public domain in the United States.)

Purpose: In large epidemiologic studies, physical activity (PA) is often assessed using PA questionnaires (PAQ). Because available PAQ may not capture the full range of PA in which urban Chinese adults engage, a PAQ was developed for this purpose. We examined the validity of this PAQ and the 1-yr stability of PA in 545 urban Shanghai adults., Methods: The PAQ was interview-administered twice, approximately 1 yr apart, and participants also wore an accelerometer and completed a PA-log for seven consecutive days every 3 months during the same year. The intraclass correlation coefficient (ICC) was used to evaluate the stability of PA across questionnaire administrations, and Spearman correlation coefficients (ρ) and mean differences and 95% limits of agreement were used to examine the validity of the questionnaire compared against accelerometry and the PA-log., Results: When measured by accelerometry, estimates of time spent in moderate-to-vigorous PA were lower and estimates of time spent sedentary were higher than when self-reported on the PAQ (P < 0.001). Total PA (ICC = 0.65) and PA domains (ICC = 0.45-0.85) showed moderate to high stability across PAQ administrations. Total PA (ρ = 0.30), moderate-to-vigorous activity (ρ = 0.17), light activity (ρ = 0.36), and sedentary behavior (ρ = 0.16) assessed by PAQ and by accelerometry were significantly and positively correlated, and correlations of the PAQ with the PA-log (ρ = 0.36-0.85) were stronger than those observed with accelerometry., Conclusions: The PAQ significantly overestimated time spent in moderate-to-vigorous activity and underestimated time spent in light activity and sedentary behavior compared with accelerometry, but it performed well at ranking participants according to PA level.

Background: Following adoption of a Western lifestyle, China is experiencing a decline in physical activity levels, which is projected to contribute to future increases in the burden of chronic diseases., Purpose: This study aims to target public health interventions and identify personal characteristics associated with physical activity and sedentary behavior in urban Chinese adults., Methods: In a sample of 576 men and women aged 40-74 years from Shanghai, multiple logistic regression was used to examine demographic, anthropometric, and lifestyle factors in relation to levels of physical activity and sedentary behavior assessed by Actigraph accelerometers., Results: Participants spent 317 minutes/day in physical activity and 509 minutes/day sedentary. In multivariate models, people aged > or =60 years were significantly less likely than those aged <50 years to engage in physical activity (OR=0.29, 95% CI=0.17, 0.49) and more likely to spend time sedentary (OR=2.77, 95% CI=1.53, 5.05). Similarly, obese individuals were less likely to be physically active (OR=0.34, 95% CI=0.17, 0.66) and they were suggestively more likely to be sedentary (OR=1.87, 95% CI=0.94, 3.71) than normal-weight individuals. Furthermore, current cigarette smokers were less physically active than those who formerly or never smoked (OR=0.47, 95% CI=0.28, 0.78)., Conclusions: Physical activity promotion programs in urban China should target older people, obese individuals, and cigarette smokers, as these population subgroups exhibited low levels of physical activity., (Published by Elsevier Inc.)