The role of genetically-influenced phospholipid transfer protein activity in lipoprotein metabolism and coronary artery disease.

BACKGROUND: Phospholipid transfer protein (PLTP) transfers surface phospholipids between lipoproteins and as such plays a role in lipoprotein metabolism, but with unclear effects on coronary artery disease (CAD) risk. We aimed to investigate the associations of genetically-influenced PLTP activity with 1-H nuclear magnetic resonance (1H-NMR) metabolomic measures and with CAD. Furthermore, using factorial Mendelian randomization (MR), we examined the potential additional effect of genetically-influenced PLTP activity on CAD risk on top of genetically-influenced low-density lipoprotein-cholesterol (LDL-C) lowering. METHODS: Using data from UK Biobank, genetic scores for PLTP activity and LDL-C were calculated and dichotomised based on the median, generating four groups with combinations of high/low PLTP activity and high/low LDL-C levels for the factorial MR. Linear and logistic regressions were performed on 168 metabolomic measures (N = 58,514) and CAD (N = 318,734, N-cases=37,552), respectively, with results expressed as ß coefficients (in standard deviation units) or odds ratios (ORs) and 95% confidence interval (CI). RESULTS: Irrespective of the genetically-influenced LDL-C, genetically-influenced low PLTP activity was associated with a higher high-density lipoprotein (HDL) particle concentration (ß [95% CI]: 0.03 [0.01, 0.05]), smaller HDL size (-0.14 [-0.15, -0.12]) and higher triglyceride (TG) concentration (0.04 [0.02, 0.05]), but not with CAD (OR 0.99 [0.97, 1.02]). In factorial MR analyses, genetically-influenced low PLTP activity and genetically-influenced low LDL-C had independent associations with metabolomic measures, and genetically-influenced low PLTP activity did not show an additional effect on CAD risk. CONCLUSIONS: Low PLTP activity associates with higher HDL particle concentration, smaller HDL particle size and higher TG concentration, but no association with CAD risk was observed.

No evidence linking sleep traits with white blood cell counts: Multivariable-adjusted and Mendelian randomization analyses.

BACKGROUND: Disturbances in habitual sleep have been associated with multiple age-associated diseases. However, the biological mechanisms underpinning these associations remain largely unclear. We assessed the possible involvement of the circulating immune system by determining the associations between sleep traits and white blood cell counts using multivariable-adjusted linear regression and Mendelian randomization. METHODS: Cross-sectional multivariable-adjusted linear regression analyses were done using participants within the normal range of total white blood cell counts (>4.5 × 109 and <11.0 × 109/µL) from UK Biobank. For the sleep traits, we examined (short and long) sleep duration, chronotype, insomnia symptoms and daytime dozing. Two-sample Mendelian randomization analyses were done using instruments for sleep traits derived from European-ancestry participants from UK Biobank (over 410,000 participants) and using SNP-outcome data derived from European-ancestry participants from the Blood Cell Consortium (N = 563,946) to which no data from UK Biobank contributed. RESULTS: Using data from 357,656 participants (mean [standard deviation] age: 56.5 [8.1] years, and 44.4% men), we did not find evidence that disturbances in any of the studied sleep traits were associated with differences in blood cell counts (total, lymphocytes, neutrophiles, eosinophiles and basophiles). Also, we did not find associations between disturbances in any of the studied sleep traits and white blood cell counts using Mendelian Randomization. CONCLUSION: Based on the results from two different methodologies, disturbances in habitual sleep are unlikely to cause changes in blood cell counts and thereby differences in blood cell counts are unlikely to be underlying the observed sleep-disease associations.

Differential and sex- and age-specific risks of cardiometabolic diseases with unrelated metabolic syndrome dimensions.

OBJECTIVE: This study aimed to investigate whether independent dimensions of metabolic syndrome (MetS) components are associated differentially with incident cardiometabolic diseases. METHODS: Principal components analysis was performed using the five MetS components from 153,073 unrelated European-ancestry participants (55% women) from the UK Biobank. The associations of the principal components (PCs) with incident type 2 diabetes mellitus (T2D), coronary artery disease (CAD), and (ischemic) stroke were analyzed using multivariable-adjusted Cox proportional hazards models in groups stratified by sex and baseline age. RESULTS: PC1 (40.5% explained variance; increased waist circumference with dyslipidemia) and PC2 (22.7% explained variance; hyperglycemia) were both associated with incident cardiometabolic disease. Hazard ratios for CAD and T2D were higher for PC1 than for PC2 (1.27 [95% CI: 1.25-1.29] vs. 1.06 [95% CI: 1.03-1.08] and 2.09 [95% CI: 2.03-2.16] vs. 1.39 [95% CI: 1.34-1.44], respectively). Furthermore, the association of PC1 with T2D was slightly higher for women than for men, and especially the HRs of PC1 with CAD and T2D attenuated with increasing age (p values for heterogeneity test among subgroups < 0.05). CONCLUSIONS: MetS can be dissected into two distinct presentations characterized by differential sex- and age-associated cardiometabolic disease risk, confirming the loss of information using the dichotomous MetS.

The joint effects of physical activity and air pollution on type 2 diabetes in older adults.

BACKGROUND: Older adults with type 2 diabetes are at higher risk of developing common geriatric syndromes and have a lower quality of life. To prevent type 2 diabetes in older adults, it's unclear whether the health benefits of physical activity (PA) will be influenced by the harms caused by increased exposure to air pollution during PA, especially in developing countries with severe air pollution problem. We aimed to investigate the joint effects of PA and long-term exposure to air pollution on the type 2 diabetes in older adults from China. METHODS: This cross-sectional study was based on the China Multi-Ethnic cohort (CMEC) study. The metabolic equivalent of PA was calculated according to the PA scale during the CMEC baseline survey. High resolution air pollution datasets (PM10, PM2.5 and PM1) were collected from open products. The joint effects were assessed by the marginal structural mean model with generalized propensity score. RESULTS: A total of 36,562 participants aged 50 to 79 years were included in the study. The prevalence of type 2 diabetes was 10.88%. The mean (SD) level of PA was 24.93 (18.60) MET-h/d, and the mean (SD) level of PM10, PM2.5, and PM1 were 70.00 (23.32) µg/m3, 40.45 (15.66) µg/m3 and 27.62 (6.51) µg/m3, respectively. With PM10 < 92 µg/m3, PM2.5 < 61 µg/m3, and PM1 < 36 µg/m3, the benefit effects of PA on type 2 diabetes was significantly greater than the harms due to PMs when PA levels were roughly below 80 MET-h/d. With PM10 ≥ 92 µg/m3, PM2.5 ≥ 61 µg/m3, and PM1 ≥ 36 µg/m3, the odds ratio (OR) first decreased and then rose rapidly with confidence intervals progressively greater than 1 and break-even points close to or even below 40 MET-h/d. CONCLUSIONS: Our findings implied that for the prevention of type 2 diabetes in older adults, the PA health benefits outweighed the harms of air pollution except in extreme air pollution situations, and suggested that when the air quality of residence is severe, the PA levels should ideally not exceed 40 MET-h/d.

Urban-rural differences in the association between long-term exposure to ambient air pollution and obesity in China.

INTRODUCTION: Ambient air pollution might increase the risk of obesity; however, the evidence regarding the relationship between air pollution and obesity in comparable urban and rural areas is limited. Therefore, our aim was to contrast the effect estimates of varying air pollution particulate matter on obesity between urban and rural areas. METHODS: Four obesity indicators were evaluated in this study, namely, body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR). Exposure to ambient air pollution (e.g., particulate matter with aerodynamic diameters 1.0 µm [PM1], PM2.5, and PM10) was estimated using satellite-based random forest models. Linear regression and logistic regression models were used to assess the associations between air pollution particulate matter and obesity. Furthermore, the effect estimates of different air pollution particulates were contrasted between urban and rural areas. RESULTS: A total of 36,998 participants in urban areas and 31, 256 in rural areas were included. We found positive associations between long-term exposure to PM1, PM2.5, and PM10 and obesity. Of these air pollutants, PM2.5 had the strongest association. The results showed that the odds ratios (ORs) for general obesity were 1.8 (95% CI, 1.64 to 1.98) per interquartile range (IQR) µg/m3 increase in PM1, 1.89 (95% CI, 1.71 to 2.1) per IQR µg/m3 increase in PM2.5, and 1.74 (95% CI, 1.58 to 1.9) per IQR µg/m3 increase in PM10. The concentrations of air pollutants were lower in rural areas, but the effects of air pollution on obesity of rural residents were higher than those of urban residents. CONCLUSION: Long-term (3 years average) exposure to ambient air pollution was associated with an increased risk of obesity. We observed regional disparities in the effects of particulate matter exposure from air pollution on the risk of obesity, with higher effect estimates found in rural areas. Air quality interventions should be prioritized not only in urban areas but also in rural areas to reduce the risk of obesity.

Associations of long-term exposure to ambient air pollution and physical activity with insomnia in Chinese adults.

BACKGROUND: Air pollution is a potential environmental risk for sleep disturbance. However, the evidence is very limited in China. On the other hand, physical activity (PA) is a preventive behavior that can improve insomnia, but whether PA mitigates the negative impact of air pollution on insomnia is unknown. METHODS: We obtained data from the baseline of China Multi-Ethnic Cohort (CMEC) survey, and examined the association between air pollution and insomnia, as well as PA's modification effect of on this association. We included 70,668 respondents and assessed insomnia by self-reported symptoms collected using electronic questionnaires. Using satellite data, we estimated the residence-specified, three-year average PM1, PM2.5, PM10 (particulate matter with aerodynamic diameters of ≤1 µm, ≤2.5 µm and 10 µm, respectively), O3 (ozone), and NO2 (nitrogen dioxide) concentrations. We established the associations between air pollutants and insomnia through logistic regression. We evaluated the modification impact of total and domain-specific PA (leisure, occupation, housework, transportation) by introducing an interaction term. RESULTS: Positive associations were observed between long-term exposure to PM1, PM2.5, PM10, and O3 and insomnia symptoms, with ORs (95% CI) of 1.09 (1.03-1.16), 1.11 (1.07-1.15), 1.07 (1.05-1.10) and 1.15 (1.11-1.20), respectively. As total PA increased, the ORs of air pollution for insomnia tended to decrease and then rise. We observed varying modification effects of domain-specific PA. With an increase in leisure PA, the ORs for PM2.5 and PM10 significantly declined. However, increased ORs of air pollutants were related to insomnia among participants with higher levels of occupational and housework PA. CONCLUSION: Long-term exposure to higher concentrations of PM1, PM2.5, PM10, and O3 increases the risk of insomnia symptoms. Moderate to high levels of leisure PA alleviate the harmful effects of air pollution on insomnia, while high levels of occupation and housework PA intensify such effects.

Obesity and activity patterns before and during COVID-19 lockdown among youths in China.

This study aim to assess changes in obesity and activity patterns among youths in China during the COVID-19 lockdown. We used the COVID-19 Impact on lifestyle change survey (COINLICS), a national retrospective survey distributed via social media platforms in early May 2020 where more than 10 000 youth participants in China have voluntarily reported their basic sociodemographic information, weight status, and routine lifestyles in the months before and during COVID-19 lockdown. The extended IOTF and WHO standards were used to define overweight and obesity of the participants. We used paired t-tests or χ2 tests and non-parametric methods to evaluate the significance of differences in weight-related outcomes and lifestyles across education levels, between sexes, and before and during COVID-19 lockdown. The mean body mass index of all participating youths has significantly increased (21.8-22.6) and in all education subgroups during COVID-19 lockdown. Increases also occurred in the prevalence of overweight/obesity (21.3%-25.1%, P < .001) and obesity (10.5% to 12.9%, P < .001) in overall youths, especially in high school and undergraduate students. Their activity patterns had also significantly changed, including the decreased frequency of engaging in active transport, moderate-/vigorous-intensity housework, leisure-time moderate-/vigorous-intensity physical activity, and leisure-time walking, and the increased sedentary, sleeping, and screen time. Our findings would inform policy-makers and clinical practitioners of these changes in time, for better policy making and clinical practice. School administrators should also be informed of these changes, so in-class and/or extracurricular physical activity programs could be designed to counteract them.

Chinese Nurses' Preferences for and Attitudes About e-Learning in Continuing Education: A Correlational Study.

BACKGROUND: This study aimed to examine nurses' preferences for and attitudes toward e-learning, identify factors that motivated or discouraged their e-learning participation, and also find the relationship between the nurse's attitude and their characteristics. METHOD: A total of 534 RNs from eight hospitals in Shanghai were recruited. Data were collected using a questionnaire that consisted of e-learning experiences, barriers, motivating factors, learning preferences, and attitudes toward e-learning. RESULTS: Flexibility was the most important motivating factor and lack of time was the most common barrier to their participating in e-learning. Participants who had no e-learning experiences reported more barriers about lack of familiarity with e-learning and e-learning platforms. Nearly half of the participants exhibited positive attitudes toward e-learning. Regression analysis identified that nurses who were married, used computers frequently, and worked in rural hospitals were associated with more positive attitudes toward e-learning. CONCLUSION: Nurse educators and managers could provide more opportunities for nurses to increase their familiarity with online education technology and develop more high-quality online courses to meet nurses' learning needs. [J Contin Educ Nurs. 2020;51(2):87-96.].

Nurses' Attitudes toward, and Needs for Online Learning: Differences between Rural and Urban Hospitals in Shanghai, East China.

Health professionals need continuing education to maintain their qualifications and competency. Online learning increases the accessibility and flexibility of continuing education. Assessment of nurses' attitudes toward, and needs for, online learning can provide suggestions regarding learning program design and delivery. This study aimed to evaluate Chinese nurses' attitudes toward, and needs for, online learning, and to explore the differences in attitudes and needs between nurses working in rural and urban hospitals. This work is a secondary analysis of a multicenter cross-sectional study conducted in Shanghai in 2015 (n = 550). Multiple regression techniques were used to determine the factors associated with nurses' attitudes toward, and needs for, online learning. Results showed that nurses in rural hospitals had more positive attitudes toward online learning (102.7 ± 14.2) than those in urban hospitals (98.3 ± 12.9) (p < 0.001). For rural hospitals, nurses who could use computers and access the internet in their workplace reported more positive attitudes than those who could not. For urban hospitals, nurse educators showed significantly more positive attitudes than others. Communication skills (86.5%) and patient education (86.3%) were the most commonly-reported learning needs for nurses regardless of their working settings. Chinese nurses were willing to adopt online learning as a continuing education method. Nurses working in rural hospitals displayed more positive attitudes toward, and needs for, online learning than those working in urban hospitals. Nursing educators and managers should develop online learning programs and provide appropriate support to fulfill nurses' learning needs, especially for those working in rural healthcare settings.