Coffee consumption and all-cause and cardiovascular mortality in older adults: should we consider cognitive function?

Background: The association between coffee and mortality risk has been found in most previous studies, and recent studies have found an association between coffee consumption and cognition. However, there is still a lack of research exploring whether the association between coffee and mortality is influenced by cognitive function. Objective: The purpose of this study was to explore the association of coffee, caffeine intake in coffee and decaffeinated coffee with all-cause mortality and cardiovascular disease (CVD) mortality in older adults with different cognitive performances. Methods: The study was based on data from the National Health and Nutrition Examination Survey (NHANES) 2011-2014. Coffee and caffeine consumption data were obtained from two 24-h dietary recalls. Individual cognitive functions were assessed by CERAD-word learning test (CERAD-WLT), animal fluency test (AFT), and digit symbol substitution test (DSST). In addition, principal component analysis (PCA) was performed with the above test scores to create global cognitive score. The lowest quartile of scores was used to classify cognitive performance. Cox regression and restricted cubic spline (RCS) were applied to assess the relationship between coffee and caffeine consumption and mortality. Results: In the joint effects analysis, we found that those with cognitive impairment and who reported without drinking coffee had the highest risk of all-cause and cardiovascular mortality compared with others. In the analysis of population with cognitive impairment, for all-cause mortality, those who showed cognitive impairment in the AFT displayed a significant negative association between their total coffee consumption and mortality {T3 (HR [95% CI]), 0.495 [0.291-0.840], p = 0.021 (trend analysis)}. For DSST and global cognition, similar results were observed. Whereas for CERAD-WLT, restricted cubic spline (RCS) showed a "U-shaped" association between coffee consumption and mortality. For CVD mortality, a significant negative trend in coffee consumption and death was observed only in people with cognitive impairment in AFT or DSST. In addition, we observed that decaffeinated coffee was associated with reduced mortality in people with cognitive impairment. Conclusion: Our study suggested that the association between coffee consumption and mortality is influenced by cognition and varies with cognitive impairment in different cognitive domains.

Regression models for near-infrared measurement of subcutaneous adipose tissue thickness.

Obesity is often associated with the risks of diabetes and cardiovascular disease, and there is a need to measure subcutaneous adipose tissue (SAT) thickness for acquiring the distribution of body fat. The present study aimed to develop and evaluate different model-based methods for SAT thickness measurement using an SATmeter developed in our laboratory. Near-infrared signals backscattered from the body surfaces from 40 subjects at 20 body sites each were recorded. Linear regression (LR) and support vector regression (SVR) models were established to predict SAT thickness on different body sites. The measurement accuracy was evaluated by ultrasound, and compared with results from a mechanical skinfold caliper (MSC) and a body composition balance monitor (BCBM). The results showed that both LR- and SVR-based measurement produced better accuracy than MSC and BCBM. It was also concluded that by using regression models specifically designed for certain parts of human body, higher measurement accuracy could be achieved than using a general model for the whole body. Our results demonstrated that the SATmeter is a feasible method, which can be applied at home and in the community due to its portability and convenience.

Measurement of subcutaneous adipose tissue thickness by near-infrared.

Obesity is strongly associated with the risks of diabetes and cardiovascular disease, and there is a need to measure the subcutaneous adipose tissue (SAT) layer thickness and to understand the distribution of body fat. A device was designed to illuminate the body parts by near-infrared (NIR), measure the backscattered light, and predict the SAT layer thickness. The device was controlled by a single-chip microcontroller (SCM), and the thickness value was presented on a liquid crystal display (LCD). There were 30 subjects in this study, and the measurements were performed on 14 body parts for each subject. The paper investigated the impacts of pressure and skin colour on the measurement. Combining with principal component analysis (PCA) and support vector regression (SVR), the measurement accuracy of SAT layer thickness was 89.1 % with a mechanical caliper as reference. The measuring range was 5-11 mm. The study provides a non-invasive and low-cost technique to detect subcutaneous fat thickness, which is more accessible and affordable compared to other conventional techniques. The designed device can be used at home and in community.