Drinking behaviors by stress level in Korean university students

The purposes of this study are to estimate the stress level of university students, and to verify the relationships between stress level and drinking behavior. A questionnaire survey was administered to 430 university students in the Gangwon area in Korea from November 5 to November 28, 2008, and data from 391 students were used for the final statistical analysis. The most stressful factor was "Worry about academic achievements" (2.86 by Likert-type 4 point scale). The subjects were divided into two groups, a low stress group (≤ 65.0) and a high stress group (≥ 66.0), by the mean value (65.1) and median value (66.0) of the stress levels. The drinking frequency was not different between the two stress groups, but the amount of alcohol consumption was significantly different (P < 0.05). The portion of students reporting drinking "7 glasses or over" was higher in the lower stress group than in the higher stress group. In addition, factor 6, "Lack of learning ability", was negatively correlated with drinking frequency and the amount of alcohol consumption (P < 0.05), and factor 3, "Worry about academic achievements", was negatively correlated with the amount of drinking (P < 0.05). The major motive for drinking was "When overjoyed or there is something to celebrate" (2.62), and the main expected effect of drinking was "Drinking enables me to get together with people and shape my sociability" (2.73). The higher stress group showed significantly higher scores on several items in the categories of motives (P < 0.01), negative experience (P < 0.05), and expected effects (P < 0.05) of drinking than the lower stress group. Our results imply that university students at the lower stress level may drink more from social motives in positive drinking environments, while those at the higher stress level may have more problematic-drinking despite their smaller amount of alcohol consumption

Perseverative Cognition and Health Behaviors: A Systematic Review and Meta-Analysis

Recent developments in stress theory have emphasized the significance of perseverative cognition (worry and rumination) in furthering our understanding of stress-disease relationships. Substantial evidence has shown that perseverative cognition (PC) is associated with somatic outcomes and numerous physiological concomitants have been identified (i.e., cardiovascular, autonomic, and endocrine nervous system activity parameters). However, there has been no synthesis of the evidence regarding the association between PC and health behaviors. This is important given such behaviors may also directly and/or indirectly influence health and disease outcomes (triggered by PC). Therefore, the aim of the current review was to synthesize available studies that have explored the relationship between worry and rumination and health behaviors (health risk: behaviors which, if performed, would be detrimental to health; health promoting: behaviors which, if performed, would be beneficial for health). A systematic review and meta-analyses of the literature were conducted. Studies were included in the review if they reported the association between PC and health behavior. Studies identified in MEDLINE or PsycINFO (k = 7504) were screened, of which 19 studies met the eligibility criteria. Random-effects meta-analyses suggested increased PC was generally associated with increased health risk behaviors but not health promoting behaviors. Further analyses indicated that increases in rumination (r = 0.122), but not reflection (r = -0.080), or worry (r = 0.048) were associated with health risk behaviors. In conclusion, these results showed that increases in PC are associated with increases in health risk behaviors (substance use, alcohol consumption, unhealthy eating, and smoking) that are driven primarily through rumination. These findings provide partial support for our hypothesis that in Brosschot et al.'s (2006) original perseverative cognition hypothesis, there may be scope for additional routes to pathogenic disease via poorer health behaviors

Do Worry and Brooding Predict Health Behaviors? A Daily Diary Investigation

Background Meta-analyses have reported associations between perseverative cognition (both worry and brooding) and increased engagement in health-risk behaviors, poorer sleep, and poorer physiological health outcomes. Method Using a daily diary design, this study investigated the within- and between-person relationships between state and trait perseverative cognition and health behaviors (eating behavior, physical activity, alcohol consumption, and sleep) both crosssectionally and prospectively. Participants (n = 273, 93% students, Mage = 20.2, SD = 4.11, 93% female) completed morning and evening diaries across 7 consecutive days. Results Multilevel modeling analyses revealed that, cross-sectionally, higher levels of state worry were associated with more time spent sitting and higher levels of state brooding predicted less daily walking. Conclusion Worry and brooding may represent useful intervention targets for improving inactivity and walking levels, respectively

Patient-Reported Outcomes and Socioeconomic Status as Predictors of Clinical Outcomes after Hematopoietic Stem Cell Transplantation: A Study from the Blood and Marrow Transplant Clinical Trials Network 0902 Trial

This secondary analysis of a large, multi-center Blood and Marrow Transplant Clinical Trials Network (BMT CTN) randomized trial assessed whether patient-reported outcomes (PROs) and socioeconomic status (SES) before hematopoietic stem cell transplantation (HCT) are associated with each other and predictive of clinical outcomes including time to hematopoietic recovery, acute graft-versus-host disease, hospitalization days, and overall survival (OS) among 646 allogeneic and autologous HCT recipients. Pre-transplant Cancer and Treatment Distress (CTXD), Pittsburgh Sleep Quality Index (PSQI), and mental and physical component scores (MCS and PCS) of the SF-36 were correlated with each other and with SES variables. PROs and SES variables were further evaluated as predictors of clinical outcomes, with the PSQI and CTXD evaluated as OS predictors (p<.01 considered significant given multiple testing). Lower attained education was associated with increased distress (p=.002); lower income was related to worse physical functioning (p=.005) and increased distress (p=.008); lack of employment pre-transplant was associated with worse physical functioning (p<.01); unmarried status was associated with worse sleep (p=.003). In this large heterogeneous cohort of HCT recipients, while PROs and SES variables were correlated at baseline, they were not associated with any clinical outcomes. Future research should focus on HCT recipients at greater psychosocial disadvantage

The development and validation of a scoring tool to predict the operative duration of elective laparoscopic cholecystectomy

Background: The ability to accurately predict operative duration has the potential to optimise theatre efficiency and utilisation, thus reducing costs and increasing staff and patient satisfaction. With laparoscopic cholecystectomy being one of the most commonly performed procedures worldwide, a tool to predict operative duration could be extremely beneficial to healthcare organisations. Methods: Data collected from the CholeS study on patients undergoing cholecystectomy in UK and Irish hospitals between 04/2014 and 05/2014 were used to study operative duration. A multivariable binary logistic regression model was produced in order to identify significant independent predictors of long (> 90 min) operations. The resulting model was converted to a risk score, which was subsequently validated on second cohort of patients using ROC curves. Results: After exclusions, data were available for 7227 patients in the derivation (CholeS) cohort. The median operative duration was 60 min (interquartile range 45–85), with 17.7% of operations lasting longer than 90 min. Ten factors were found to be significant independent predictors of operative durations > 90 min, including ASA, age, previous surgical admissions, BMI, gallbladder wall thickness and CBD diameter. A risk score was then produced from these factors, and applied to a cohort of 2405 patients from a tertiary centre for external validation. This returned an area under the ROC curve of 0.708 (SE = 0.013, p  90 min increasing more than eightfold from 5.1 to 41.8% in the extremes of the score. Conclusion: The scoring tool produced in this study was found to be significantly predictive of long operative durations on validation in an external cohort. As such, the tool may have the potential to enable organisations to better organise theatre lists and deliver greater efficiencies in care

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015

Forouzanfar MH, Afshin A, Alexander LT, et al. Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015. LANCET. 2016;388(10053):1659-1724.Background The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors-the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57.8% (95% CI 56.6-58.8) of global deaths and 41.2% (39.8-42.8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211.8 million [192.7 million to 231.1 million] global DALYs), smoking (148.6 million [134.2 million to 163.1 million]), high fasting plasma glucose (143.1 million [125.1 million to 163.5 million]), high BMI (120.1 million [83.8 million to 158.4 million]), childhood undernutrition (113.3 million [103.9 million to 123.4 million]), ambient particulate matter (103.1 million [90.8 million to 115.1 million]), high total cholesterol (88.7 million [74.6 million to 105.7 million]), household air pollution (85.6 million [66.7 million to 106.1 million]), alcohol use (85.0 million [77.2 million to 93.0 million]), and diets high in sodium (83.0 million [49.3 million to 127.5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Copyright (C) The Author(s). Published by Elsevier Ltd

Measuring the health-related Sustainable Development Goals in 188 countries : a baseline analysis from the Global Burden of Disease Study 2015

Background In September, 2015, the UN General Assembly established the Sustainable Development Goals (SDGs). The SDGs specify 17 universal goals, 169 targets, and 230 indicators leading up to 2030. We provide an analysis of 33 health-related SDG indicators based on the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015). Methods We applied statistical methods to systematically compiled data to estimate the performance of 33 health-related SDG indicators for 188 countries from 1990 to 2015. We rescaled each indicator on a scale from 0 (worst observed value between 1990 and 2015) to 100 (best observed). Indices representing all 33 health-related SDG indicators (health-related SDG index), health-related SDG indicators included in the Millennium Development Goals (MDG index), and health-related indicators not included in the MDGs (non-MDG index) were computed as the geometric mean of the rescaled indicators by SDG target. We used spline regressions to examine the relations between the Socio-demographic Index (SDI, a summary measure based on average income per person, educational attainment, and total fertility rate) and each of the health-related SDG indicators and indices. Findings In 2015, the median health-related SDG index was 59.3 (95% uncertainty interval 56.8-61.8) and varied widely by country, ranging from 85.5 (84.2-86.5) in Iceland to 20.4 (15.4-24.9) in Central African Republic. SDI was a good predictor of the health-related SDG index (r(2) = 0.88) and the MDG index (r(2) = 0.2), whereas the non-MDG index had a weaker relation with SDI (r(2) = 0.79). Between 2000 and 2015, the health-related SDG index improved by a median of 7.9 (IQR 5.0-10.4), and gains on the MDG index (a median change of 10.0 [6.7-13.1]) exceeded that of the non-MDG index (a median change of 5.5 [2.1-8.9]). Since 2000, pronounced progress occurred for indicators such as met need with modern contraception, under-5 mortality, and neonatal mortality, as well as the indicator for universal health coverage tracer interventions. Moderate improvements were found for indicators such as HIV and tuberculosis incidence, minimal changes for hepatitis B incidence took place, and childhood overweight considerably worsened. Interpretation GBD provides an independent, comparable avenue for monitoring progress towards the health-related SDGs. Our analysis not only highlights the importance of income, education, and fertility as drivers of health improvement but also emphasises that investments in these areas alone will not be sufficient. Although considerable progress on the health-related MDG indicators has been made, these gains will need to be sustained and, in many cases, accelerated to achieve the ambitious SDG targets. The minimal improvement in or worsening of health-related indicators beyond the MDGs highlight the need for additional resources to effectively address the expanded scope of the health-related SDGs.Peer reviewe

Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980-2015 : a systematic analysis for the Global Burden of Disease Study 2015

Background Improving survival and extending the longevity of life for all populations requires timely, robust evidence on local mortality levels and trends. The Global Burden of Disease 2015 Study (GBD 2015) provides a comprehensive assessment of all-cause and cause-specific mortality for 249 causes in 195 countries and territories from 1980 to 2015. These results informed an in-depth investigation of observed and expected mortality patterns based on sociodemographic measures. Methods We estimated all-cause mortality by age, sex, geography, and year using an improved analytical approach originally developed for GBD 2013 and GBD 2010. Improvements included refinements to the estimation of child and adult mortality and corresponding uncertainty, parameter selection for under-5 mortality synthesis by spatiotemporal Gaussian process regression, and sibling history data processing. We also expanded the database of vital registration, survey, and census data to 14 294 geography-year datapoints. For GBD 2015, eight causes, including Ebola virus disease, were added to the previous GBD cause list for mortality. We used six modelling approaches to assess cause-specific mortality, with the Cause of Death Ensemble Model (CODEm) generating estimates for most causes. We used a series of novel analyses to systematically quantify the drivers of trends in mortality across geographies. First, we assessed observed and expected levels and trends of cause-specific mortality as they relate to the Socio-demographic Index (SDI), a summary indicator derived from measures of income per capita, educational attainment, and fertility. Second, we examined factors affecting total mortality patterns through a series of counterfactual scenarios, testing the magnitude by which population growth, population age structures, and epidemiological changes contributed to shifts in mortality. Finally, we attributed changes in life expectancy to changes in cause of death. We documented each step of the GBD 2015 estimation processes, as well as data sources, in accordance with Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER). Findings Globally, life expectancy from birth increased from 61.7 years (95% uncertainty interval 61.4-61.9) in 1980 to 71.8 years (71.5-72.2) in 2015. Several countries in sub-Saharan Africa had very large gains in life expectancy from 2005 to 2015, rebounding from an era of exceedingly high loss of life due to HIV/AIDS. At the same time, many geographies saw life expectancy stagnate or decline, particularly for men and in countries with rising mortality from war or interpersonal violence. From 2005 to 2015, male life expectancy in Syria dropped by 11.3 years (3.7-17.4), to 62.6 years (56.5-70.2). Total deaths increased by 4.1% (2.6-5.6) from 2005 to 2015, rising to 55.8 million (54.9 million to 56.6 million) in 2015, but age-standardised death rates fell by 17.0% (15.8-18.1) during this time, underscoring changes in population growth and shifts in global age structures. The result was similar for non-communicable diseases (NCDs), with total deaths from these causes increasing by 14.1% (12.6-16.0) to 39.8 million (39.2 million to 40.5 million) in 2015, whereas age-standardised rates decreased by 13.1% (11.9-14.3). Globally, this mortality pattern emerged for several NCDs, including several types of cancer, ischaemic heart disease, cirrhosis, and Alzheimer's disease and other dementias. By contrast, both total deaths and age-standardised death rates due to communicable, maternal, neonatal, and nutritional conditions significantly declined from 2005 to 2015, gains largely attributable to decreases in mortality rates due to HIV/AIDS (42.1%, 39.1-44.6), malaria (43.1%, 34.7-51.8), neonatal preterm birth complications (29.8%, 24.8-34.9), and maternal disorders (29.1%, 19.3-37.1). Progress was slower for several causes, such as lower respiratory infections and nutritional deficiencies, whereas deaths increased for others, including dengue and drug use disorders. Age-standardised death rates due to injuries significantly declined from 2005 to 2015, yet interpersonal violence and war claimed increasingly more lives in some regions, particularly in the Middle East. In 2015, rotaviral enteritis (rotavirus) was the leading cause of under-5 deaths due to diarrhoea (146 000 deaths, 118 000-183 000) and pneumococcal pneumonia was the leading cause of under-5 deaths due to lower respiratory infections (393 000 deaths, 228 000-532 000), although pathogen-specific mortality varied by region. Globally, the effects of population growth, ageing, and changes in age-standardised death rates substantially differed by cause. Our analyses on the expected associations between cause-specific mortality and SDI show the regular shifts in cause of death composition and population age structure with rising SDI. Country patterns of premature mortality (measured as years of life lost [YLLs]) and how they differ from the level expected on the basis of SDI alone revealed distinct but highly heterogeneous patterns by region and country or territory. Ischaemic heart disease, stroke, and diabetes were among the leading causes of YLLs in most regions, but in many cases, intraregional results sharply diverged for ratios of observed and expected YLLs based on SDI. Communicable, maternal, neonatal, and nutritional diseases caused the most YLLs throughout sub-Saharan Africa, with observed YLLs far exceeding expected YLLs for countries in which malaria or HIV/AIDS remained the leading causes of early death. Interpretation At the global scale, age-specific mortality has steadily improved over the past 35 years; this pattern of general progress continued in the past decade. Progress has been faster in most countries than expected on the basis of development measured by the SDI. Against this background of progress, some countries have seen falls in life expectancy, and age-standardised death rates for some causes are increasing. Despite progress in reducing age-standardised death rates, population growth and ageing mean that the number of deaths from most non-communicable causes are increasing in most countries, putting increased demands on health systems. Copyright (C) The Author(s). Published by Elsevier Ltd.Peer reviewe

Breast cancer screening disparities among ethnically diverse women in California : a latent profile analysis

Breast cancer is one of the most common cancers among women in the United States (U.S. CSWG, 2009). Health care, screening behaviors (e.g., mammography) and late-stage disease detection account for significant differences in breast cancer morbidity and mortality among ethnically diverse women (ACS, 2007). The current study sought to identify variables that best predict women's breast cancer screening behaviors and to develop screening typologies for women in a large multiethnic sample (N = 15,130) from the California Health Interview Survey 2005 (CHIS, 2006). The study examined whether ethnicity (Hispanic, African American, Asian, and non-Hispanic white) moderated the relationship between emergent typologies and screening outcomes. Variables of interest addressed the following themes: health behaviors, women's health, cancer history, health insurance, health care utilization, mental health, as well as acculturation, racial discrimination, education, and socioeconomic status. Latent profile analysis (LPA : Lanza, Flaherty, &amp; Collins, 2003) was employed to empirically derive and subsequently predict screening using each variable simultaneously to develop typologies of women. Post-hoc analyses using logistic regression were utilized to explain significant ethnicity by class interactions. Results revealed three substantive risk domains, Health, Stress, and Demographic, were significantly related to breast cancer screening. LPA revealed two classes, deemed Healthy and Health Risk, emerged significant for the Health domain. Health Risk class women engaged in more mammography screening, relative to Healthy class counterparts across all ethnic groups (ps &lt; .001). In the Stress domain Minimal, Mild, Moderate, and Severe Stress classes emerged. Women reported more breast cancer screening in the Minimal and Mild Stress classes, comparatively to their Moderate and Severe Stress class counterparts (ps &lt; .001). This relationship was significant in follow-up analyses for non -Hispanic white women. Among the Demographic domain Minimal, Limited, Moderate, and Substantial Resource classes emerged. Women in the Minimal and Substantial Resource classes engaged in greater breast cancer screening (ps &lt; .001) than Limited and Moderate Resource class women and this was replicated across ethnic groups. The current study portrays a rich constellation of variables that influence women's screening behaviors and underpins future targets of breast cancer prevention in typologies of ethnically diverse women within Californi

Breast cancer screening disparities among ethnically diverse women in California : a latent profile analysis

Breast cancer is one of the most common cancers among women in the United States (U.S. CSWG, 2009). Health care, screening behaviors (e.g., mammography) and late-stage disease detection account for significant differences in breast cancer morbidity and mortality among ethnically diverse women (ACS, 2007). The current study sought to identify variables that best predict women's breast cancer screening behaviors and to develop screening typologies for women in a large multiethnic sample (N = 15,130) from the California Health Interview Survey 2005 (CHIS, 2006). The study examined whether ethnicity (Hispanic, African American, Asian, and non-Hispanic white) moderated the relationship between emergent typologies and screening outcomes. Variables of interest addressed the following themes: health behaviors, women's health, cancer history, health insurance, health care utilization, mental health, as well as acculturation, racial discrimination, education, and socioeconomic status. Latent profile analysis (LPA : Lanza, Flaherty, &amp; Collins, 2003) was employed to empirically derive and subsequently predict screening using each variable simultaneously to develop typologies of women. Post-hoc analyses using logistic regression were utilized to explain significant ethnicity by class interactions. Results revealed three substantive risk domains, Health, Stress, and Demographic, were significantly related to breast cancer screening. LPA revealed two classes, deemed Healthy and Health Risk, emerged significant for the Health domain. Health Risk class women engaged in more mammography screening, relative to Healthy class counterparts across all ethnic groups (ps &lt; .001). In the Stress domain Minimal, Mild, Moderate, and Severe Stress classes emerged. Women reported more breast cancer screening in the Minimal and Mild Stress classes, comparatively to their Moderate and Severe Stress class counterparts (ps &lt; .001). This relationship was significant in follow-up analyses for non -Hispanic white women. Among the Demographic domain Minimal, Limited, Moderate, and Substantial Resource classes emerged. Women in the Minimal and Substantial Resource classes engaged in greater breast cancer screening (ps &lt; .001) than Limited and Moderate Resource class women and this was replicated across ethnic groups. The current study portrays a rich constellation of variables that influence women's screening behaviors and underpins future targets of breast cancer prevention in typologies of ethnically diverse women within Californi