752 resultados para Self-reported health


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One of the most persistent and lasting debates in economic research refers to whether the answers to subjective questions can be used to explain individuals’ economic behavior. Using panel data for twelve EU countries, in the present study we analyze the causal relationship between self-reported housing satisfaction and residential mobility. Our results indicate that: i) households unsatisfied with their current housing situation are more likely to move; ii) housing satisfaction raises after a move, and; iii) housing satisfaction increases with the transition from being a renter to becoming a homeowner. Some interesting cross-country differences are observed. Our findings provide evidence in favor of use of subjective indicators of satisfaction with certain life domains in the analysis of individuals’ economic conduct.

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This study investigated the direction of effects of temporal and downward social comparisons on self-rated health in very old age. Self-rated health can either reinforce or hinder comparison processes. In the framework of the Swiss Interdisciplinary Longitudinal Study on the Oldest Old, individuals aged 80 to 84 at baseline were interviewed and followed longitudinally for 5 years. Multilevel analyses were used to test the relative importance of temporal and social comparisons on self-rated health evaluations synchronically and diachronically (with a time lag of 12 to 18 months) as well as the direction of these relative influences. Results indicate that (a) at the synchronic level, continuity temporal comparisons have more impact than downward social comparisons on self-rated health; (b) both types of comparison had an independent and positive effect on self-rated health at the diachronic level; (c) self-rated health has an independent synchronic effect on both types of comparison and an independent diachronic effect in temporal comparison.

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PURPOSE: To examine the associations between substance use and other health-risk behaviors and quality of life (QOL) among young men. METHODS: The analytical sample consisted of 5,306 young Swiss men who participated in the Cohort Study on Substance Use Risk Factors. Associations between seven distinct self-reported health-risk behaviors (risky single-occasion drinking; volume drinking; cigarette smoking; cannabis use; use of any other illicit drugs; sexual intercourse without a condom; low physical activity) were assessed via chi-square analysis. Logistic regression analyses were conducted to study the associations between each particular health-risk behavior and either physical or mental QOL (assessed with the SF-12v2) while adjusting for socio-demographic variables and the presence of all other health-risk behaviors. RESULTS: Most health-risk behaviors co-occurred. However, low physical activity was not or negatively related to other health-risk behaviors. Almost all health-risk behaviors were associated with a greater likelihood of compromised QOL. However, sexual intercourse without a condom (not associated with both physical and mental QOL) and frequent risky single-occasion drinking (not related to mental QOL after adjusting for the presence of other health-risk behaviors; positively associated with physical QOL) differed from this pattern. CONCLUSIONS: Health-risk behaviors are mostly associated with compromised QOL. However, sexual intercourse without a condom and frequent risky single-occasion drinking differ from this pattern and are therefore possibly particularly difficult to change relative to other health-risk behaviors.

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BACKGROUND: Outcome after lung transplantation (LTx) is affected by the onset of bronchiolitis obliterans syndrome (BOS) and lung function decline. Reduced health-related quality of life (HRQL) and physical mobility have been shown in patients developing BOS, but the impact on the capacity to walk is unknown. We aimed to compare the long-term HRQL and 6-minute walk test (6MWT) between lung recipients affected or not by BOS Grade > or =2. METHODS: Fifty-eight patients were prospectively followed for 5.6 +/- 2.9 years after LTx. Assessments included the St George's Respiratory Questionnaire (SGRQ) and the 6MWT, which were performed yearly. Moreover, clinical complications were recorded to estimate the proportion of the follow-up time lived without clinical intercurrences after transplant. Analyses were performed using adjusted linear regression and repeated-measures analysis of variance. RESULTS: BOS was a significant predictor of lower SGRQ scores (p < 0.01) and reduced time free of clinical complications (p = 0.001), but not of 6MWT distance (p = 0.12). At 7 years post-transplant, results were: 69.0 +/- 21.8% vs 86.9 +/- 5.6%, p < 0.05 (SGRQ); 58.5 +/- 21.6% vs 88.7 +/- 11.4%, p < 0.01 (proportion of time lived without clinical complications); and 82.2 +/- 10.9% vs 91.9 +/- 14.2%, p = 0.27 (percent of predicted 6MWT), respectively, for patients with BOS and without BOS. CONCLUSIONS: Despite significantly less time lived without clinical complications and progressive decline of self-reported health status, the capacity to walk of patients affected by BOS remained relatively stable over time. These findings may indicate that the development of moderate to severe BOS does not prevent lung recipients from walking independently and pursuing an autonomous life.

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Obese persons (those with a body mass index [BMI] ≥30 kg/m2) tend to underestimate their weight, leading to an underestimation of their true (measured) BMI and obesity prevalence.1,2 In contrast, underweight people (BMI <18.5 kg/m2) tend to report themselves heavier, resulting in a higher BMI compared with measured BMI and an underestimation of underweight prevalence.

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INTRODUCTION: Common variation in the CHRNA5-CHRNA3-CHRNB4 gene region is robustly associated with smoking quantity. Conversely, the association between one of the most significant single nucleotide polymorphisms (SNPs; rs1051730 within the CHRNA3 gene) with perceived difficulty or willingness to quit smoking among current smokers is unknown. METHODS: Cross-sectional study including current smokers, 502 women, and 552 men. Heaviness of smoking index (HSI), difficulty, attempting, and intention to quit smoking were assessed by questionnaire. RESULTS: The rs1051730 SNP was associated with increased HSI (age, gender, and education-adjusted mean ± SE: 2.6 ± 0.1, 2.2 ± 0.1, and 2.0 ± 0.1 for AA, AG, and GG genotypes, respectively, p < .01). Multivariate logistic regression adjusting for gender, age, education, leisure-time physical activity, and personal history of cardiovascular or lung disease showed rs1051730 to be associated with higher smoking dependence (odds ratio [OR] and 95% CI for each additional A-allele: 1.38 [1.11-1.72] for smoking more than 20 cigarette equivalents/day; 1.31 [1.00-1.71] for an HSI ≥5 and 1.32 [1.05-1.65] for smoking 5 min after waking up) and borderline associated with difficulty to quit (OR = 1.29 [0.98-1.70]), but this relationship was no longer significant after adjusting for nicotine dependence. Also, no relationship was found with willingness (OR = 1.03 [0.85-1.26]), attempt (OR = 1.00 [0.83-1.20]), or preparation (OR = 0.95 [0.38-2.38]) to quit. Similar findings were obtained for other SNPs, but their effect on nicotine dependence was no longer significant after adjusting for rs1051730. Conclusions: These data confirm the effect of rs1051730 on nicotine dependence but failed to find any relationship with difficulty, willingness, and motivation to quit.

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This second edition of Health at a Glance: Europe presents a set of key indicators of health and health systems in 35 European countries, including the 27 European Union member states, 5 candidate countries and 3 EFTA countries. The selection of indicators is based largely on the European Community Health Indicators (ECHI) shortlist, a list of indicators that has been developed by the European Commission to guide the development and reporting of health statistics. It is complemented by additional indicators on health expenditure and quality of care, building on the OECD expertise in these areas. Contents: Introduction 12 Chapter 1. Health status 15 1.1. Life expectancy and healthy life expectancy at birth 1.2. Life expectancy and healthy life expectancy at age 65 1.3. Mortality from all causes 1.4. Mortality from heart disease and stroke 1.5. Mortality from cancer 1.6. Mortality from transport accidents 1.7. Suicide 1.8. Infant mortality 1.9. Infant health: Low birth weight 1.10. Self-reported health and disability 1.11. Incidence of selected communicable diseases 1.12. HIV/AIDS 1.13. Cancer incidence 1.14. Diabetes prevalence and incidence 1.15. Dementia prevalence 1.16. Asthma and COPD prevalence Chapter 2. Determinants of health 49 2.1. Smoking and alcohol consumption among children 2.2. Overweight and obesity among children 2.3. Fruit and vegetable consumption among children 2.4. Physical activity among children 2.5. Smoking among adults 2.6. Alcohol consumption among adults 2.7. Overweight and obesity among adults 2.8. Fruit and vegetable consumption among adults Chapter 3. Health care resources and activities 67 3.1. Medical doctors 3.2. Consultations with doctors 3.3. Nurses 3.4. Medical technologies: CT scanners and MRI units 3.5. Hospital beds 3.6. Hospital discharges 3.7. Average length of stay in hospitals 3.8. Cardiac procedures (coronary angioplasty) 3.9. Cataract surgeries 3.10. Hip and knee replacement 3.11. Pharmaceutical consumption 3.12. Unmet health care needs Chapter 4. Quality of care 93 Care for chronic conditions 4.1. Avoidable admissions: Respiratory diseases 4.2. Avoidable admissions: Uncontrolled diabetes Acute care 4.3. In-hospital mortality following acute myocardial infarction 4.4. In-hospital mortality following stroke Patient safety 4.5. Procedural or postoperative complications 4.6. Obstetric trauma Cancer care 4.7. Screening, survival and mortality for cervical cancer 4.8. Screening, survival and mortality for breast cancer 4.9. Screening, survival and mortality for colorectal cancer Care for communicable diseases 4.10. Childhood vaccination programmes 4.11. Influenza vaccination for older people Chapter 5. Health expenditure and financing 117 5.1. Coverage for health care 5.2. Health expenditure per capita 5.3. Health expenditure in relation to GDP 5.4. Health expenditure by function. 5.5. Pharmaceutical expenditure 5.6. Financing of health care 5.7. Trade in health services Bibliography 133 Annex A. Additional information on demographic and economic context 143 Most European countries have reduced tobacco consumption via public awareness campaigns, advertising bans and increased taxation. The percentage of adults who smoke daily is below 15% in Sweden and Iceland, from over 30% in 1980. At the other end of the scale, over 30% of adults in Greece smoke daily. Smoking rates continue to be high in Bulgaria, Ireland and Latvia (Figure 2.5.1). Alcohol consumption has also fallen in many European countries. Curbs on advertising, sales restrictions and taxation have all proven to be effective measures. Traditional wine-producing countries, such as France, Italy and Spain, have seen consumption per capita fall substantially since 1980. Alcohol consumption per adult rose significantly in a number of countries, including Cyprus, Finland and Ireland (Figure 2.6.1).This resource was contributed by The National Documentation Centre on Drug Use.

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The Institute of Public health in Ireland (IPH) produces population prevalence estimates and forecasts for a number of chronic conditions among adults. IPH has now applied the methodology to examine health conditions among young children across the island of Ireland.This report uses information collected from parents in the Millennium Cohort Study (MCS) along with population data collected in the 2011 Northern Ireland Census to estimate the prevalence of any longstanding condition, asthma, eczema, sight problems and hearing problems among seven-year-olds in Northern Ireland in 2011. The analysis identifies risk factors associated with each condition and provides estimates of the prevalence of these conditions for each of the 11 Local Government Districts.A report on health conditions among three-year-olds in the Republic of Ireland has previously been published by the IPH.See the Chronic Conditions Hub for more details.

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BACKGROUND: Adherence to combination antiretroviral therapy (cART) is a dynamic process, however, changes in adherence behavior over time are insufficiently understood. METHODS: Data on self-reported missed doses of cART was collected every 6 months in Swiss HIV Cohort Study participants. We identified behavioral groups associated with specific cART adherence patterns using trajectory analyses. Repeated measures logistic regression identified predictors of changes in adherence between consecutive visits. RESULTS: Six thousand seven hundred nine individuals completed 49,071 adherence questionnaires [median 8 (interquartile range: 5-10)] during a median follow-up time of 4.5 years (interquartile range: 2.4-5.1). Individuals were clustered into 4 adherence groups: good (51.8%), worsening (17.4%), improving (17.6%), and poor adherence (13.2%). Independent predictors of worsening adherence were younger age, basic education, loss of a roommate, starting intravenous drug use, increasing alcohol intake, depression, longer time with HIV, onset of lipodystrophy, and changing care provider. Independent predictors of improvements in adherence were regimen simplification, changing class of cART, less time on cART, and starting comedications. CONCLUSIONS: Treatment, behavioral changes, and life events influence patterns of drug intake in HIV patients. Clinical care providers should routinely monitor factors related to worsening adherence and intervene early to reduce the risk of treatment failure and drug resistance.

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OBJECTIVES: Alcohol use is associated with self-reported health status. However, little is known about the concurrent association between alcohol screening scores and patient perception of health. We evaluated this association in a sample of primarily older male veterans.METHODS: This secondary, cross-sectional analysis included male general medicine outpatients from 7 VA medical centers who returned mailed questionnaires. Screening scores from the Alcohol Use Disorders Identification Test Consumption (AUDIT-C) questionnaire were divided into 6 categories (0, 1­3, 4­5, 6­7, 8­9, and 10­12). Outcomes included scores on the 8 subscales and 2 component scores of the 36-item Short Form Health Survey (SF-36). Unadjusted and adjusted linear regression models were fit to characterize the association between AUDIT-C categories and SF-36 scores. Models were adjusted for demographic characteristics, smoking, and site?both alone and in combination with 14 self-reported comorbid conditions.RESULTS: Male respondents (n = 24,531; mean age = 63.6 years) represented 69% of those surveyed with the SF-36. After adjustment, a quadratic (inverted U-shaped) relationship was demonstrated between AUDIT-C categories and all SF-36 scores such that patients with AUDIT-C scores 4­5 or 6­7 reported the highest health status, and patients with AUDIT-C scores 0, 8­9, and =10 reported the lowest health status.CONCLUSIONS: Across all measures of health status, patients with the most severe alcohol misuse had significantly poorer health status than those who screened positive for alcohol misuse at mild or moderate levels of severity. The relatively good health status reported by patients with mild-moderate alcohol misuse might interfere with clinicians' acceptance and adoption of guidelines recommending that they counsel these patients about their drinking.