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BackgroundWith continuous efforts made to promote the strategic goals of carbon neutrality and carbon peak, it is crucial to meet the growing and diversified needs of the public for fitness by practicing the concept of green development and promote the combination of national fitness and ecological civilization.MethodsTo achieve this purpose, an OLS regression model was applied to estimate the role of green space exposure in Chinese residents’ participation in physical activity and its underlying mechanisms, using the microdata from the China General Social Survey (CGSS) data and the Provincial Vegetation Cover Index (NDVI) matched macrostatistical data.ResultsThe empirical results show that green space exposure significantly increases the probability of residents’ physical activity participation, and creating a green environment is conducive to creating a favorable physical activity environment for residents. Also, the core conclusions still hold after the year-by-year regression test is passed and the endogeneity problem is addressed. As revealed by mechanistic studies, green space exposure has indirect effects on the physical activity participation of residents through the independent mediating roles of reducing carbon emissions and promoting social interaction. According to heterogeneity results, males, those in marriage, and urban dweller groups are more inclined to perform physical activity in green spaces.ConclusionThe results show that the exposure of green space can help increase the probability of residents’ participation in physical exercise, and can that it achieved through two channels: reducing carbon emissions and enhancing social interaction. It is necessary to further strengthen the protection of the ecological lifestyle, give full play to the advantages of greenness and low-carbon, and create favorable conditions for the green development of a new model of national fitness.

Abstract Backgrounds Fasting blood glucose (FBG) variability may make an impact on adverse events in patients with diabetes mellitus. However, the association between long‐term changes in FBG and cancer remains unclear. We aimed to investigate this association in a large‐scale longitudinal study. Methods Data were collected from 46 761 patients with type 2 diabetes mellitus aged 20–80 years who participated in the Diabetes Standardized Management Program in Shanghai, China. We adopted four indicators, including standard deviation (SD), coefficient of variation (CV), variation independent of the mean (VIM), and average real variability (ARV) to describe FBG variability. Adjusted multivariable Cox regression analyses and restricted cubic splines were used to investigate the association between long‐term FBG variability and cancer risk. We also determined the interactive effect of FBG variability with hypertension and FBG‐mean with hypertension on cancer risk, respectively. Results In this study, we confirmed 2218 cancer cases (51.1% male) over a median follow‐up of 2.86 years. In the multivariable‐adjusted models, participants in the highest quartile of FBG variability had an increased risk of cancer compared with those in the lowest quartile. The nonlinear association was found when using FBG‐VIM, FBG‐ARV, and FBG‐SD in restricted cubic spline plots. There was a significant interaction effect of FBG variability with hypertension on cancer, whereas the effect of FBG‐mean with hypertension did not attain significance. Conclusions Our retrospective cohort study demonstrated a positive association between the long‐term changes in FBG and cancer risk in patients with type 2 diabetes mellitus. FBG variability may independently predict cancer incidence.

Abstract Background Gait disturbances may appear prior to cognitive dysfunction in the early stage of silent cerebrovascular disease (SCD). Subtle changes in gait characteristics may provide an early warning of later cognitive decline. Our team has proposed a vision-based artificial intelligent gait analyzer for the rapid detection of spatiotemporal parameters and walking pattern based on videos of the Timed Up and Go (TUG) test. The primary objective of this study is to investigate the relationship between gait features assessed by our artificial intelligent gait analyzer and cognitive function changes in patients with SCD. Methods This will be a multicenter prospective cohort study involving a total of 14 hospitals from Shanghai and Guizhou. One thousand and six hundred patients with SCD aged 60–85 years will be consecutively recruited. Eligible patients will undergo the intelligent gait assessment and neuropsychological evaluation at baseline and at 1-year follow-up. The intelligent gait analyzer will divide participant into normal gait group and abnormal gait group according to their walking performance in the TUG videos at baseline. All participants will be naturally observed during 1-year follow-up period. Primary outcome are the changes in Mini-Mental State Examination (MMSE) score. Secondary outcomes include the changes in intelligent gait spatiotemporal parameters (step length, gait speed, step frequency, step width, standing up time, and turning back time), the changes in scores on other neuropsychological tests (Montreal Cognitive Assessment, the Stroop Color Word Test, and Digit Span Test), falls events, and cerebrovascular events. We hypothesize that both groups will show a decline in MMSE score, but the decrease of MMSE score in the abnormal gait group will be more significant. Conclusion This study will be the first to explore the relationship between gait features assessed by an artificial intelligent gait analyzer and cognitive decline in patients with SCD. It will demonstrate whether subtle gait abnormalities detected by the artificial intelligent gait analyzer can act as a cognitive-related marker for patients with SCD. Trial registration This trial was registered at ClinicalTrials.gov ( NCT04456348 ; 2 July 2020).

Abstract. Background. The relationship of uric acid (UA) with the thyroid function among healthy individuals remains unclear. We aimed to examine the relationship between UA contents and thyroid hormone levels in healthy Chinese individuals. Methods. This was a cross-sectional study of 1186 Chinese adults (736 men and 450 women) who underwent a health check-up at the Huadong Hospital Affiliated to Fudan University (Shanghai, China) between January 1, 2010 and July 31, 2018. Clinical and thyroid hormone levels were compared in different UA groups (in male and menopause women groups, MG1: UA < 5 mg/dL; MG2: 5 mg/dL ≤ UA< 7 mg/dL; and MG3: UA ≥ 7 mg/dL; in female groups, FG1 to FG3 represent the UA levels of

Abstract Background Obesity and diabetes are two risk factors for cancer. To evaluate the association of body mass index (BMI) with cancer risk in diabetic patients may improve current understanding of potential mechanisms. Methods A retrospective cohort study was conducted in 51,004 newly diagnosed T2DM patients derived from an electronic health record (EHR) database of Minhang district in Shanghai, China. Incident cancer cases and all-cause deaths occurred before September 30, 2015 were identified by linking with the Shanghai Cancer Registry and the Shanghai Vital Statistics. To examine the potential non-linear and linear relationships of BMI and cancer risk, Cox proportional hazard models with and without restricted cubic spline functions were used, respectively. Results A non-linear association was observed between BMI and overall cancer incidence in men younger than 60 years old (p for non-linearity = 0.009). Compared with those having BMI of 25.0 kg/m2, the cancer risk increased in those with either lower or higher BMI. In women older than 60 years old, linear dose-response relationships were observed between BMI and the risk of both overall cancer and breast cancer. As each unit increase in BMI, the overall cancer risks elevated by 3% (95%CI: 1–5%) and the breast cancer risks increased by 7% (95%CI: 1–13%). No significant association was observed between BMI and other common cancer sites. Conclusions Our results show that the effect of BMI on cancer risk in Chinese patients with T2DM may vary by gender, age and cancer subtypes, suggesting different underlying biological mechanisms.

Background: Type 2 diabetes mellitus (T2DM) has been suggested to increase the risk of cancers. The aim of this study was to investigate the risk of common cancers in Chinese patients with T2DM.Methods: A population-based retrospective cohort study including 36,379 T2DM patients was conducted in Minhang District of Shanghai, China, during 2004 to 2010. All T2DM patients were enrolled from the standardized management system based on local electronic information system. Newly-diagnosed cancer cases were identified by record-linkage with the Shanghai Cancer Registry. Standardized incidence ratios (SIR) and 95% confidence interval (CI) were used to estimate the risk of cancers among T2DM patients.Results: Overall crude incidence rate (CIR) of cancers was 955.21 per 105 person-years in men and 829.57 per 105 person-years in women. Increased risk of cancer was found in both gender, with an SIR being 1.28 (95% CI = 1.17-1.38) in men and 1.44 (95% CI =1.32-1.55) in women. Increased risk of colon (SIR = 1.97; 95% CI = 1.49 to 2.46), rectum (1.72; 1.23 to 2.21), prostate (2.87; 2.19 to 3.56), and bladder cancers (1.98, 1.28 to 2.68) were observed in men and elevated risk of colon (1.67; 1.25 to 2.08), breast (1.66; 1.38 to 1.95), and corpus uteri cancers (2.87; 2.03 to 3.71) were observed in women.Conclusions: Our results indicate that Chinese patients with T2DM may have an increased risk of some cancers, and the increase may vary by sub-sites of cancers. [ABSTRACT FROM AUTHOR]

In this article, we study the robust estimation of both mean and variance components in generalized partial linear mixed models based on the construction of robustified likelihood function. Under some regularity conditions, the asymptotic properties of the proposed robust estimators are shown. Some simulations are carried out to investigate the performance of the proposed robust estimators. Just as expected, the proposed robust estimators perform better than those resulting from robust estimating equations involving conditional expectation like Sinha (2004, Journal of the American Statistical Association 99, 451–460) and Qin and Zhu (2007, Journal of Multivariate Analysis 98, 1658–1683). In the end, the proposed robust method is illustrated by the analysis of a real data set. [ABSTRACT FROM AUTHOR]