Association of physical activity and socio-economic status on mortality in older adults: a retrospective cohort study of KNHANES-mortality linked data.

We examined the joint association of physical activity (PA) and socio-economic status (SES) on all-causes and cardiovascular disease (CVD) mortality in 6945 elderly Koreans (mean age: 71.6 years, 41.8% male) using data from the Korean National Health and Nutrition Examination Survey (2007-2013) and death data from Statistics Korea (2019). The SES included household income and education level. PA was assessed using the IPAQ and categorized according to the 2018 PA Guidelines. In stratified analyses using Cox proportional hazards by SES adherence to PA guidelines those who low household income group was associated with a reduced risk of all-cause mortality and CVD mortality, while in the lowest educational level group, it was associated with a reduced risk of all-cause mortality and CVD mortality. In the joint analysis, PA was associated with a significant reduction in all-cause mortality in all groups when compared with those who did not meet PA those who had the lowest SES. However, PA with CVD mortality risk was not significantly associated in the 'upper-middle' income and 'high school' education groups. The study revealed that PA significantly association mortality, particularly among older adults with low SES. This finding suggests the potential for targeted government interventions to promote healthy aging.

The impact of perceived environmental uncertainty on green innovation: evidence from text recognition of Chinese listed companies' annual reports.

China has implemented a series of environmental policies aimed at promoting green and innovative development by enterprises, to mitigate the adverse effects of environmental pollution. However, the frequent revision and introduction of environmental policies have also increased enterprises' perception of environmental uncertainty. This study, based on the upper echelon theory, uses data from listed companies in China from 2011 to 2021 to construct an index of perceived environmental uncertainty of firms through textual analysis and empirically examines its impact on green innovation and its potential mechanisms and boundary effects. The results show that, first, perceived environmental uncertainty of firms has a noteworthy inhibiting impact on green innovation. Second, mechanism analysis reveals that perceived environmental uncertainty of firms inhibits green innovation mainly in two ways: reducing the level of transparency in corporate information and reducing R&D investment. Third, the moderating effect finds that government subsidies can mitigate the inhibitory impact of perceived environmental uncertainty on green innovation among firms. In other words, higher government subsidies correspond to a reduced inhibitory effect of perceived environmental uncertainty on green innovation among firms. In addition, heterogeneity analysis shows that this inhibition is more obvious in non-state-owned enterprises, small enterprises, and enterprises in non-heavy pollution industries. This study holds immense practical significance for enterprises in harnessing the opportunities of green innovation amidst perceived environmental uncertainty, facilitating progressive green development, and ultimately fostering the harmonized growth of economic and environmental benefits for enterprises.

Socioeconomic position is associated with glycemic control in youth and young adults with type 1 diabetes.

OBJECTIVE: Health inequities persist in youth and young adults (YYA) with type 1diabetes in achieving optimal glycemic control. The purpose of this study was to assess the contribution of multiple indicators of social need to these inequities. RESEARCH DESIGN AND METHODS: Two hundred and twenty two YYA withtype 1 diabetes enrolled in the SEARCH Food Insecurity Study in South Carolina and Washington between the years 2013 and 2015 were included. Latent class analysis was used to identify socioeconomic profiles based on household income, parental education, health insurance, household food insecurity, and food assistance. Profiles were evaluated in relation to glycemic control using multivariable linear and logistic regression, with HbA1c > 9%(75 mmol/mol) defined as high-risk glycemic control. RESULTS: Two profiles were identified: a lower socioeconomic profile included YYA whose parents had lower income and/or education, and were more likely to be uninsured, receive food assistance, and be food insecure. A higher socioeconomic profile included YYA whose circumstances were opposite to those in the lower socioeconomic profile. Those with a lower socioeconomic profile were more likely to have high-risk glycemic control relative to those with a higher socioeconomic profile (OR = 2.24, 95%CI = 1.16-4.33). CONCLUSIONS: Lower socioeconomic profiles are associated with high-risk glycemic control among YYA with type 1 diabetes. This supports recommendations that care providers of YYA with type 1 diabetes assess individual social needs in tailoring diabetes management plans to the social context of the patient.

Health care access and glycemic control in youth and young adults with type 1 and type 2 diabetes in South Carolina.

Affordability and geographic accessibility are key health care access characteristics. We used data from 481 youth and young adults (YYA) with diabetes (389 type 1, 92 type 2) to understand the association between health care access and glycemic control as measured by HbA1c values. In multivariate models, YYA with state or federal health insurance had HbA1c percentage values 0.68 higher (P = 0.0025) than the privately insured, and those without insurance 1.34 higher (P < 0.0001). Not having a routine diabetes care provider was associated with a 0.51 higher HbA1c (P = 0.048) compared to having specialist care, but HbA1c did not differ significantly (P = 0.069) between primary vs specialty care. Distance to utilized provider was not associated with HbA1c among YYA with a provider (P = 0.11). These findings underscore the central role of health insurance and indicate a need to better understand the root causes of poorer glycemic control in YYA with state/federal insurance.

Food Acquisition and Shopping Patterns among Residents of Low-Income and Low-Access Communities in South Carolina.

BACKGROUND: Little is known about the food acquisition and shopping habits of residents living in food deserts. OBJECTIVE: To identify distinct food acquisition and shopping patterns among residents, most of whom (81%) live in food desert (low income and low access) census tracts, and characterize these patterns with respect to the residents' socioeconomic status, nutrition knowledge, and perceptions of their food environment. DESIGN: This is a cross-sectional study. PARTICIPANTS/SETTING: Four hundred sixty-six primary food shoppers were included from two counties in South Carolina during 2013-2014. MAIN OUTCOME MEASURES: Participants' self-reported food acquisition and shopping habits, including shopping distance; frequency; store type; transportation mode; use of farmers' markets, food banks/pantries, and church/social service organizations, were used to develop shopping patterns and group residents. Supplemental Nutrition Assistance Program participation, food security, income, and education, nutrition knowledge, and perceptions of the food environment were used to characterize these groups. STATISTICAL ANALYSES PERFORMED: Latent class analysis and multinomial logistic regression were used to identify and characterize patterns, respectively. RESULTS: Three patterns were identified, including those who use community food resources, are infrequent grocery shoppers, and use someone else's car or public transportation when shopping (Class 1) (35%), those who use community food resources and are more frequent and proximal shoppers (Class 2) (41%), and those who do not use community food resources and are distal shoppers (Class 3) (24%). Compared with Class 3, Class 1 had comparatively lower socioeconomic status. Class 2 also had comparatively lower socioeconomic attributes except for income. Class 2 was not significantly different from Class 1 except that a higher proportion in Class 1 saw food access as a problem. No significant differences across classes were found regarding fruit and vegetable recommendation knowledge. CONCLUSIONS: Shopping frequency, use of community food resources, transportation methods, and shopping distance were the key factors that defined distinct patterns among residents living in low-income areas. Future interventions to increase healthy food access in underserved areas should not only consider accessibility but also community food resource use.

What does a person's eating identity add to environmental influences on fruit and vegetable intake?

OBJECTIVE: To evaluate whether knowledge of a person's eating identity (EI) can explain any additional variation in fruit and vegetable intake above and beyond that explained by food environment characteristics, perceptions of the food environment, and shopping behaviors. DESIGN: Cross-sectional study. SETTING: A total of 968 adults were recruited for a telephone survey by the Survey Research Laboratory in an eight-county region in South Carolina. SUBJECTS: The survey queried information on shopping behaviors, perceptions of the food environment, demographic and address information, fruit and vegetable intake, and EI. EI was assessed using the Eating Identity Type Inventory, a 12-item instrument that differentiates four eating identity types: healthy, emotional, meat, and picky. Statistical analyses were restricted to 819 participants with complete data. RESULTS: Healthy EI and picky EI were significantly and directly related to fruit and vegetable intake, with coefficients of 0.31 (p-value<0.001) for healthy EI and -0.16 (p-value<0.001) for picky EI, whereas emotional EI (ß = 0.00, p-value = 0.905) and meat EI (ß = -0.04, p-value = 0.258) showed no association. Shopping frequency also directly and significantly influenced fruit and vegetable intake (ß = 0.13, p-value = 0.033). With the inclusion of EI, 16.3% of the variation in fruit and vegetable intake was explained. CONCLUSIONS: Perceptions and GIS-based measures of environmental factors alone do not explain a substantial amount of variation in fruit and vegetable intake. EI, especially healthy EI and picky EI, is an important, independent predictor of fruit and vegetable intake and contributes significantly to explaining the variation in fruit and vegetable intake.

Atherosclerotic Plaque Tissue: Noninvasive Quantitative Assessment of Characteristics with Software-aided Measurements from Conventional CT Angiography.

Purpose To (a) evaluate whether plaque tissue characteristics determined with conventional computed tomographic (CT) angiography could be quantitated at higher levels of accuracy by using image processing algorithms that take characteristics of the image formation process coupled with biologic insights on tissue distributions into account by comparing in vivo results and ex vivo histologic findings and (b) assess reader variability. Materials and Methods Thirty-one consecutive patients aged 43-85 years (average age, 64 years) known to have or suspected of having atherosclerosis who underwent CT angiography and were referred for endarterectomy were enrolled. Surgical specimens were evaluated with histopathologic examination to serve as standard of reference. Two readers used lumen boundary to determine scanner blur and then optimized component densities and subvoxel boundaries to best fit the observed image by using semiautomatic software. The accuracy of the resulting in vivo quantitation of calcification, lipid-rich necrotic core (LRNC), and matrix was assessed with statistical estimates of bias and linearity relative to ex vivo histologic findings. Reader variability was assessed with statistical estimates of repeatability and reproducibility. Results A total of 239 cross sections obtained with CT angiography and histologic examination were matched. Performance on held-out data showed low levels of bias and high Pearson correlation coefficients for calcification (-0.096 mm2 and 0.973, respectively), LRNC (1.26 mm2 and 0.856), and matrix (-2.44 mm2 and 0.885). Intrareader variability was low (repeatability coefficient ranged from 1.50 mm2 to 1.83 mm2 among tissue characteristics), as was interreader variability (reproducibility coefficient ranged from 2.09 mm2 to 4.43 mm2). Conclusion There was high correlation and low bias between the in vivo software image analysis and ex vivo histopathologic quantitative measures of atherosclerotic plaque tissue characteristics, as well as low reader variability. Software algorithms can mitigate the blurring and partial volume effects of routine CT angiography acquisitions to produce accurate quantification to enhance current clinical practice. Clinical trial registration no. NCT02143102 © RSNA, 2017 Online supplemental material is available for this article. An earlier incorrect version of this article appeared online. This article was corrected on September 15, 2017.

A quantitative risk-assessment system (QR-AS) evaluating operation safety of Organic Rankine Cycle using flammable mixture working fluid.

Mixture of hydrocarbon and carbon dioxide shows excellent cycle performance in Organic Rankine Cycle (ORC) used for engine waste heat recovery, but the unavoidable leakage in practical application is a threat for safety due to its flammability. In this work, a quantitative risk assessment system (QR-AS) is established aiming at providing a general method of risk assessment for flammable working fluid leakage. The QR-AS covers three main aspects: analysis of concentration distribution based on CFD simulations, explosive risk assessment based on the TNT equivalent method and risk mitigation based on evaluation results. A typical case of propane/carbon dioxide mixture leaking from ORC is investigated to illustrate the application of QR-AS. According to the assessment results, proper ventilation speed, safe mixture ratio and location of gas-detecting devices have been proposed to guarantee the security in case of leakage. The results revealed that this presented QR-AS was reliable for the practical application and the evaluation results could provide valuable guidance for the design of mitigation measures to improve the safe performance of ORC system.

Inter-Method Performance Study of Tumor Volumetry Assessment on Computed Tomography Test-Retest Data.

RATIONALE AND OBJECTIVES: Tumor volume change has potential as a biomarker for diagnosis, therapy planning, and treatment response. Precision was evaluated and compared among semiautomated lung tumor volume measurement algorithms from clinical thoracic computed tomography data sets. The results inform approaches and testing requirements for establishing conformance with the Quantitative Imaging Biomarker Alliance (QIBA) Computed Tomography Volumetry Profile. MATERIALS AND METHODS: Industry and academic groups participated in a challenge study. Intra-algorithm repeatability and inter-algorithm reproducibility were estimated. Relative magnitudes of various sources of variability were estimated using a linear mixed effects model. Segmentation boundaries were compared to provide a basis on which to optimize algorithm performance for developers. RESULTS: Intra-algorithm repeatability ranged from 13% (best performing) to 100% (least performing), with most algorithms demonstrating improved repeatability as the tumor size increased. Inter-algorithm reproducibility was determined in three partitions and was found to be 58% for the four best performing groups, 70% for the set of groups meeting repeatability requirements, and 84% when all groups but the least performer were included. The best performing partition performed markedly better on tumors with equivalent diameters greater than 40 mm. Larger tumors benefitted by human editing but smaller tumors did not. One-fifth to one-half of the total variability came from sources independent of the algorithms. Segmentation boundaries differed substantially, not ony in overall volume but also in detail. CONCLUSIONS: Nine of the 12 participating algorithms pass precision requirements similar to what is indicated in the QIBA Profile, with the caveat that the present study was not designed to explicitly evaluate algorithm profile conformance. Change in tumor volume can be measured with confidence to within ±14% using any of these nine algorithms on tumor sizes greater than 10 mm. No partition of the algorithms was able to meet the QIBA requirements for interchangeability down to 10 mm, although the partition comprising best performing algorithms did meet this requirement for a tumor size of greater than approximately 40 mm.