Serum creatinine/cystatin C ratio as a screening tool for sarcopenia and prognostic indicator for patients with esophageal cancer.

BACKGROUND & AIMS: Sarcopenia is associated with poor clinical outcomes of patients who underwent esophagectomy. The current diagnostic criteria for sarcopenia are complex and laborious. We aimed to employ the simple and economic indicator sarcopenia index (SI = creatinine/cystatin C ×100) to screen for sarcopenia and to evaluate its prognostic value in patients with esophageal cancer (EC). METHODS: Older participants in the National health and nutrition examination survey (NHANES) database (1999-2002) were divided into three groups according to tertiles of the SI value to explore the feasibility of SI in the diagnosis of sarcopenia. Restricted cubic spline (RCS) was utilized to show the non-linear relationship between all-cause mortality and SI. Patients with EC admitted to Jinling Hospital were enrolled to validate the efficacy and prognostic value of SI. Cut-off values of SI were determined using receiver operating characteristic curves. Multivariable logistic analyses and Cox analyses were used to identify the independent factors of postoperative complications and long-term survival, respectively. RESULTS: A total of 989 participants were identified from the NHANES database. SI showed the diagnostic value of sarcopenia (tertile 1 vs. tertile 3: odds ratio [OR]=3.67, 95% confidence interval [CI]: 1.52-8.87, p=0.004; tertile 2 vs. tertile 3: OR=1.79, 95% CI: 0.75-4.28, p=0.191) adjusted for race, gender, and body mass index (BMI). Individuals with SI ≤ 68 had a poorer overall survival (OS) (hazard ratio [HR]=2.14, 95% CI: 1.71-2.68, p<0.001), and the RCS plot showed that the all-cause mortality risk gradually decreased with the increase in SI. Then, 203 patients with EC were enrolled, of which 76 patients were diagnosed with sarcopenia. There was a linear correlation between SI and skeletal muscle index and prealbumin, indicating that SI was reliable for diagnosing sarcopenia. Patients in the high sarcopenia risk group (Male: SI < 62; Female: SI < 55) showed a higher incidence of complications (OR=3.50, 95% CI: 1.85-6.61, p<0.001) and poorer long-term survival (HR=2.62, 95% CI: 1.02-6.77, p=0.046). CONCLUSION: SI could be used to identify sarcopenia in patients with EC, and it is a useful prognostic factor of postoperative complications and long-term survival.

Greenness around schools associated with lower risk of hypertension among children: Findings from the Seven Northeastern Cities Study in China.

Evidence suggests that residential greenness may be protective of high blood pressure, but there is scarcity of evidence on the associations between greenness around schools and blood pressure among children. We aimed to investigate this association in China. Our study included 9354 children from 62 schools in the Seven Northeastern Cities Study. Greenness around each child's school was measured by NDVI (Normalized Difference Vegetation Index) and SAVI (Soil-Adjusted Vegetation Index). Particulate matter ≤ 1 µm (PM1) concentrations were estimated by spatiotemporal models and nitrogen dioxide (NO2) concentrations were collected from air monitoring stations. Associations between greenness and blood pressure were determined by generalized linear and logistic mixed-effect models. Mediation by air pollution was assessed using mediation analysis. Higher greenness was consistently associated with lower blood pressure. An increase of 0.1 in NDVI corresponded to a reduction in SBP of 1.39 mmHg (95% CI: 1.86, -0.93) and lower odds of hypertension (OR = 0.76, 95% CI: 0.69, 0.82). Stronger associations were observed in children with higher BMI. Ambient PM1 and NO2 mediated 33.0% and 10.9% of the association between greenness and SBP, respectively. In summary, greater greenness near schools had a beneficial effect on blood pressure, particularly in overweight or obese children in China. The associations might be partially mediated by air pollution. These results might have implications for policy makers to incorporate more green space for both aesthetic and health benefits.

Association between community greenness and obesity in urban-dwelling Chinese adults.

Living in greener places may protect against obesity, but epidemiological evidence is inconsistent and mainly comes from developed nations. We aimed to investigate the association between greenness and obesity in Chinese adults and to assess air pollution and physical activity as mediators of the association. We recruited 24,845 adults from the 33 Communities Chinese Health Study in 2009. Central and peripheral obesity were defined by waist circumference (WC) and body mass index (BMI), respectively, based on international obesity standards. The Normalized Difference Vegetation Index (NDVI) was used to quantify community greenness. Two-level logistic and generalized linear mixed regression models were used to evaluate the association between NDVI and obesity, and a conditional mediation analysis was used also performed. In the adjusted models, an interquartile range increase in NDVI500-m was significantly associated with lower odds of peripheral 0.80 (95% confidence interval [CI]: 0.74-0.87) and central obesity 0.88 (95% CI: 0.83-0.93). Higher NDVI values were also significantly associated with lower BMI. Age, gender, and household income significantly modified associations between greenness and obesity, with stronger associations among women, older participants, and participants with lower household incomes. Air pollution mediated 2.1-20.8% of the greenness-obesity associations, but no mediating effects were observed for physical activity. In summary, higher community greenness level was associated with lower odds of central and peripheral obesity, especially among women, older participants, and those with lower household incomes. These associations were partially mediated by air pollutants. Future well-designed longitudinal studies are needed to confirm our findings.

Human Exposure Assessment for Air Pollution.

Assessment of human exposure to air pollution is a fundamental part of the more general process of health risk assessment. The measurement methods for exposure assessment now include personal exposure monitoring, indoor-outdoor sampling, mobile monitoring, and exposure assessment modeling (such as proximity models, interpolation model, air dispersion models, and land-use regression (LUR) models). Among these methods, personal exposure measurement is considered to be the most accurate method of pollutant exposure assessment until now, since it can better quantify observed differences and better reflect exposure among smaller groups of people at ground level. And since the great differences of geographical environment, source distribution, pollution characteristics, economic conditions, and living habits, there is a wide range of differences between indoor, outdoor, and individual air pollution exposure in different regions of China. In general, the indoor particles in most Chinese families comprise infiltrated outdoor particles, particles generated indoors, and a few secondary organic aerosol particles, and in most cases, outdoor particle pollution concentrations are a major contributor to indoor concentrations in China. Furthermore, since the time, energy, and expense are limited, it is difficult to measure the concentration of pollutants for each individual. In recent years, obtaining the concentration of air pollutants by using a variety of exposure assessment models is becoming a main method which could solve the problem of the increasing number of individuals in epidemiology studies.