92 resultados para Socioeconomic Factors.
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Background¦The outcome after primary percutaneous coronary intervention (pPCI) for STElevation¦Myocardial Infarction (STEMI) is strongly affected by time delays. In thepresent study, we sought to identify the impact of specific socioeconomic factors on time delays, subsequent STEMI management and outcomes in STEMI patients from a well-defined region of the French part of Switzerland.¦Method¦A total of 402 consecutive patients undergoing pPCI for STEMI in a large tertiary hospital were retrospectively studied. Symptom-to-first-medical-contact time was analyzed for the following socioeconomic factors: level of education, gender, origin and marital status. Main exclusion criteria were: time delay beyond 12 hours, previous treatment by fibrinolysis or patients immediately referred for CABG.¦Therefore, 352 patients were finally included.¦Results¦At one year, there was no difference in mortality amongst the different socioeconomic groups. Furthermore, there was no difference in management characteristics between them. Symptom-to-first-medical-contact time was significantly higher for patients with a low level of education, Swiss citizens and non-married patients with median differences of 40 minutes, 48 minutes, and 60 minutes, respectively (p<0.05).¦Nevertheless, no difference was found regarding in-hospital management and clinical outcome.¦Conclusion¦This study demonstrates that symptom-to-first-medical-contact time is higher amongst people with a lower educational level, Swiss-citizens, and non-married people. Because of the low mortality rate in general, these differences in time delays did not affect clinical outcomes. Still, primary prevention measures should particularly focus on these vulnerable populations.
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BACKGROUND: Obesity is a contemporary epidemic that does not affect all age groups and sections of society equally. OBJECTIVE: The objective was to examine socioeconomic differences in trajectories of body mass index (BMI; in kg/m(2)) and obesity between the ages of 45 and 65 y. DESIGN: A total of 13,297 men and 4532 women from the French GAZEL (Gaz de France Electricité de France) cohort study reported their height in 1990 and their weight annually over the subsequent 18 y. Changes in BMI and obesity between ages 45 and 49 y, 50 and 54 y, 55 and 59 y, and 60 and 65 y as a function of education and occupational position (at age 35 y) were modeled by using linear mixed models and generalized estimating equations. RESULTS: BMI and obesity rates increased between the ages of 45 and 65 y. In men, BMI was higher in unskilled workers than in managers at age 45 y; this difference in BMI increased from 0.82 (95% CI: 0.66, 0.99) at 45 y to 1.06 (95% CI: 0.85, 1.27) at 65 y. Men with a primary school education compared with those with a high school degree at age 45 y had a 0.75 (95% CI: 0.51, 1.00) higher BMI, and this difference increased to 1.32 (95% CI: 1.03,1.62) at age 65 y. Obesity rates were 3.35% and 7.68% at age 45 y and 9.52% and 18.10% at age 65 y in managers and unskilled workers, respectively; the difference in obesity increased by 4.25% (95% CI: 1.87, 6.52). A similar trend was observed in women. Conclusions: Weight continues to increase in the transition between midlife and old age; this increase is greater in lower socioeconomic groups.
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The outcome after primary percutaneous coronary intervention (pPCI) for ST-elevation myocardial infarction (STEMI) is strongly affected by time delays. In this study, we sought to identify the impact of specific socioeconomic factors on time delays, subsequent STEMI management and outcomes in STEMI patients undergoing pPCI, who came from a well-defined region of the French part of Switzerland. A total of 402 consecutive patients undergoing pPCI for STEMI in a large tertiary hospital were retrospectively studied. Symptom-to-first-medical-contact time was analysed for the following socioeconomic factors: level of education, origin and marital status. Main exclusion criteria were: time delay beyond 12 hours, previous treatment with fibrinolytic agents or patients immediately referred for coronary artery bypass graft surgery. Therefore, 222 patients were finally included. At 1 year, there was no difference in mortality between the different socioeconomic groups. Furthermore, there was no difference in management characteristics between them. Symptom-to-first-medical-contact time was significantly longer for patients with a low level of education, Swiss citizens and unmarried patients, with median differences of 23 minutes, 18 minutes and 13 minutes, respectively (p <0.05). Nevertheless, no difference was found regarding in-hospital management and clinical outcome. This study demonstrates that symptom-to-first-medical-contact time is longer amongst people with a lower educational level, Swiss citizens and unmarried people. Because of the low mortality rate in general, these differences in delays did not affect clinical outcomes. Still, tertiary prevention measures should particularly focus on these vulnerable populations.
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This review aims at identifying gaps in knowledge on socioeconomic gradients in mortality in the oldest old. The authors review literature on oldest old population with a focus on unanswered questions: do socioeconomic status (SES) gradients in mortality persist after 80; does the magnitude of the gradient change as compared with younger populations; which socioeconomic/socio-demographic determinants should be used in this population with specific characteristics (e.g., with respect to sex ratio and household type)? Results are often inconsistent while conclusions drawn by selected studies are generally limited by the difficulty of disentangling the effects of age and cohort, and of generalizing results observed in preponderantly small, selected samples (which typically exclude institutionalized persons). Future research should explore the effects of socio-demographic indicators other than education and social class (e.g., marital status, loss of the partner) and adequately differentiate the social position of oldest old women. The authors recommend that research applies a life-course perspective combined with an interdisciplinary perspective to improve our understanding of the SES gradients in later life. Research is needed to elucidate which causal pathways depending on SES in younger age impact on mortality in higher ages up to oldest old.
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OBJECTIVES: The objectives were to identify the social and medical factors associated with emergency department (ED) frequent use and to determine if frequent users were more likely to have a combination of these factors in a universal health insurance system. METHODS: This was a retrospective chart review case-control study comparing randomized samples of frequent users and nonfrequent users at the Lausanne University Hospital, Switzerland. The authors defined frequent users as patients with four or more ED visits within the previous 12 months. Adult patients who visited the ED between April 2008 and March 2009 (study period) were included, and patients leaving the ED without medical discharge were excluded. For each patient, the first ED electronic record within the study period was considered for data extraction. Along with basic demographics, variables of interest included social (employment or housing status) and medical (ED primary diagnosis) characteristics. Significant social and medical factors were used to construct a logistic regression model, to determine factors associated with frequent ED use. In addition, comparison of the combination of social and medical factors was examined. RESULTS: A total of 359 of 1,591 frequent and 360 of 34,263 nonfrequent users were selected. Frequent users accounted for less than a 20th of all ED patients (4.4%), but for 12.1% of all visits (5,813 of 48,117), with a maximum of 73 ED visits. No difference in terms of age or sex occurred, but more frequent users had a nationality other than Swiss or European (n = 117 [32.6%] vs. n = 83 [23.1%], p = 0.003). Adjusted multivariate analysis showed that social and specific medical vulnerability factors most increased the risk of frequent ED use: being under guardianship (adjusted odds ratio [OR] = 15.8; 95% confidence interval [CI] = 1.7 to 147.3), living closer to the ED (adjusted OR = 4.6; 95% CI = 2.8 to 7.6), being uninsured (adjusted OR = 2.5; 95% CI = 1.1 to 5.8), being unemployed or dependent on government welfare (adjusted OR = 2.1; 95% CI = 1.3 to 3.4), the number of psychiatric hospitalizations (adjusted OR = 4.6; 95% CI = 1.5 to 14.1), and the use of five or more clinical departments over 12 months (adjusted OR = 4.5; 95% CI = 2.5 to 8.1). Having two of four social factors increased the odds of frequent ED use (adjusted = OR 5.4; 95% CI = 2.9 to 9.9), and similar results were found for medical factors (adjusted OR = 7.9; 95% CI = 4.6 to 13.4). A combination of social and medical factors was markedly associated with ED frequent use, as frequent users were 10 times more likely to have three of them (on a total of eight factors; 95% CI = 5.1 to 19.6). CONCLUSIONS: Frequent users accounted for a moderate proportion of visits at the Lausanne ED. Social and medical vulnerability factors were associated with frequent ED use. In addition, frequent users were more likely to have both social and medical vulnerabilities than were other patients. Case management strategies might address the vulnerability factors of frequent users to prevent inequities in health care and related costs.
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Objective: We assessed the 15-year trends in the distribution of body mass index (BMI) categories in the Seychelles (Indian Ocean, African Region) and the relationship with sex, age and socio-economic status (SES). Methods: We conducted three population-based examination surveys in 1989 (n=1,081; participation rate: 86.4%), in 1994 (n=1,067; 87.0%), and in 2004 (n=1,255; 80.2%). Occupation was categorized as "laborer", "intermediate" or "professional". Results are adjusted to the population of 2002. Results: Between 1989 and 2004, mean BMI increased markedly in all sex and age categories (overall: ∼0.15 kg/m2/calendar year). The prevalence of overweight and obesity combined ("excess weight", BMI ≥25 kg/m2) increased from 29% to 52% in men and from 50% to 67% in women. The prevalence of obesity (BMI ≥30 kg/m2) increased from 4% to 15% in men and from 23% to 34% in women. Mean BMI - respectively the prevalence of excess weight- was lower in laborers than professionals in men but higher in laborers that professionals in women and this pattern was similar in the three surveys. Odds ratios for excess weight in professionals vs. laborers were 2.10 (95% CI: 1.94-2.17) in men and 0.51 (0.48-0.53) in women, adjusting for calendar year and participants' age and smoking habits. Conclusion: The prevalence of overweight/obesity increased markedly during a 15- year period. Similar increase of BMI over time in all age and sex categories suggests common environment obesogenic factors. The association between SES and excess weight was in opposite directions in men and women. The study emphasizes the need for prevention measures in all sex, age and SES groups, and suggests that they should be tailored according to sex and SES categories.
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Average physical stature has increased dramatically during the 20th century in many populations across the world with few exceptions. It remains unclear if social inequalities in height persist despite improvements in living standards in the welfare economies of Western Europe. We examined trends in the association between height and socioeconomic indicators in adults over three decades in France. The data were drawn from the French Decennial Health Surveys: a multistage, stratified, random survey of households, representative of the population, conducted in 1970, 1980, 1991, and 2003. We categorised age into 10-year bands, 25-34, 35-44, 45-54 and 55-64 years. Education and income were the two socioeconomic measures used. The slope index of inequality (SII) was used as a summary index of absolute social inequalities in height. The results show that average height increased over this period; men and women aged 25-34 years were 171.9 and 161.2 cm tall in 1970 and 177.0 and 164.0 cm in 2003, respectively. However, education-related inequalities in height remained unchanged over this period and in men were 4.48 cm (1970), 4.71 cm (1980), 5.58 cm (1991) and 4.69 cm (2003), the corresponding figures in women were 2.41, 2.37, 3.14 and 2.96 cm. Income-related inequalities in height were smaller and much attenuated after adjustment for education. These results suggest that in France, social inequalities in adult height in absolute terms have remained unchanged across the three decades under examination.
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With a life expectancy at the age of 65 of around 20 years, damaging health risk behaviours of young-old adults have become a target for preventive actions. Such risk factors necessitate an accurate understanding of the present and past socioeconomic conditions associated with health risk behaviours. The aim of our study is to assess the impact of certain life events as well as economic and environmental factors on health risk behaviours. We included 1309 participants of the Lausanne Cohort Lc65+ aged 65-70 years and employed logistic regression analyses, with individuals nested within areas. The results illustrate the influences of socioeconomic factors from childhood to young-old age. Life experiences in adulthood and economic resources in young-old age are both associated with unfavourable health behaviours. Neighbourhood is a modest determinant as well, particularly regarding alcohol consumption. Therefore, prevention against health risk behaviours should focus on population subgroups defined on the basis of their socioeconomic and living contexts.
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BACKGROUND: Hepatitis C virus (HCV) infection is associated with decreased health-related quality of life (HRQOL). Although HCV has been suggested to directly impair neuropsychiatric functions, other factors may also play a role. PATIENTS AND METHODS: In this cross-sectional study, we assessed the impact of various host-, disease- and virus-related factors on HRQOL in a large, unselected population of anti-HCV-positive subjects. All individuals (n = 1736) enrolled in the Swiss Hepatitis C Cohort Study (SCCS) were asked to complete the Short Form 36 (SF-36) and the Hospital Anxiety Depression Scale (HADS). RESULTS: 833 patients (48%) returned the questionnaires. Survey participants had significantly worse scores in both assessment instruments when compared to a general population. By multivariable analysis, reduced HRQOL (mental and physical summary scores of SF-36) was independently associated with income. In addition, a low physical summary score was associated with age and diabetes, whereas a low mental summary score was associated with intravenous drug use. HADS anxiety and depression scores were independently associated with income and intravenous drug use. In addition, HADS depression score was associated with diabetes. None of the SF-36 or HADS scores correlated with either the presence or the level of serum HCV RNA. In particular, SF-36 and HADS scores were comparable in 555 HCV RNA-positive and 262 HCV RNA-negative individuals. CONCLUSIONS: Anti-HCV-positive subjects have decreased HRQOL compared to controls. The magnitude of this decrease was clinically important for the SF-36 vitality score. Host and environmental, rather than viral factors, seem to impact on HRQOL level.
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BACKGROUND: Up to 5% of patients presenting to the emergency department (ED) four or more times within a 12 month period represent 21% of total ED visits. In this study we sought to characterize social and medical vulnerability factors of ED frequent users (FUs) and to explore if these factors hold simultaneously. METHODS: We performed a case-control study at Lausanne University Hospital, Switzerland. Patients over 18 years presenting to the ED at least once within the study period (April 2008 toMarch 2009) were included. FUs were defined as patients with four or more ED visits within the previous 12 months. Outcome data were extracted from medical records of the first ED attendance within the study period. Outcomes included basic demographics and social variables, ED admission diagnosis, somatic and psychiatric days hospitalized over 12 months, and having a primary care physician.We calculated the percentage of FUs and non-FUs having at least one social and one medical vulnerability factor. The four chosen social factors included: unemployed and/or dependence on government welfare, institutionalized and/or without fixed residence, either separated, divorced or widowed, and under guardianship. The fourmedical vulnerability factors were: ≥6 somatic days hospitalized, ≥1 psychiatric days hospitalized, ≥5 clinical departments used (all three factors measured over 12 months), and ED admission diagnosis of alcohol and/or drug abuse. Univariate and multivariate logistical regression analyses allowed comparison of two JGIM ABSTRACTS S391 random samples of 354 FUs and 354 non-FUs (statistical power 0.9, alpha 0.05 for all outcomes except gender, country of birth, and insurance type). RESULTS: FUs accounted for 7.7% of ED patients and 24.9% of ED visits. Univariate logistic regression showed that FUs were older (mean age 49.8 vs. 45.2 yrs, p=0.003),more often separated and/or divorced (17.5%vs. 13.9%, p=0.029) or widowed (13.8% vs. 8.8%, p=0.029), and either unemployed or dependent on government welfare (31.3% vs. 13.3%, p<0.001), compared to non-FUs. FUs cumulated more days hospitalized over 12 months (mean number of somatic days per patient 1.0 vs. 0.3, p<0.001; mean number of psychiatric days per patient 0.12 vs. 0.03, p<0.001). The two groups were similar regarding gender distribution (females 51.7% vs. 48.3%). The multivariate linear regression model was based on the six most significant factors identified by univariate analysis The model showed that FUs had more social problems, as they were more likely to be institutionalized or not have a fixed residence (OR 4.62; 95% CI, 1.65 to 12.93), and to be unemployed or dependent on government welfare (OR 2.03; 95% CI, 1.31 to 3.14) compared to non-FUs. FUs were more likely to need medical care, as indicated by involvement of≥5 clinical departments over 12 months (OR 6.2; 95%CI, 3.74 to 10.15), having an ED admission diagnosis of substance abuse (OR 3.23; 95% CI, 1.23 to 8.46) and having a primary care physician (OR 1.70;95%CI, 1.13 to 2.56); however, they were less likely to present with an admission diagnosis of injury (OR 0.64; 95% CI, 0.40 to 1.00) compared to non-FUs. FUs were more likely to combine at least one social with one medical vulnerability factor (38.4% vs. 12.1%, OR 7.74; 95% CI 5.03 to 11.93). CONCLUSIONS: FUs were more likely than non-FUs to have social and medical vulnerability factors and to have multiple factors in combination.
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OBJECTIVE: To examine the association of socioeconomic status (SES) with subjective and objective sleep disturbances and the role of socio-demographic, behavioural and psychological factors in explaining this association. METHODS: Analyses are based on 3391 participants (53% female, aged 40-81 years) of the follow-up of the CoLaus study (2009-2012), a population-based sample of the city of Lausanne, Switzerland. All participants completed a sleep questionnaire and a sub-sample (N = 1569) underwent polysomnography. RESULTS: Compared with men with a high SES, men with a low SES were more likely to suffer from poor sleep quality [prevalence ratio (PR) for occupational position = 1.68, 95% Confidence Interval (CI): 1.30-2.17], and to have long sleep latency (PR = 4.90, 95%CI: 2.14-11.17), insomnia (PR = 1.47, 95% CI: 1.12-1.93) and short sleep duration (PR = 3.03, 95% CI: 1.78-5.18). The same pattern was observed among women (PR = 1.29 for sleep quality, 2.34 for sleep latency, 2.01 for daytime sleepiness, 3.16 for sleep duration, 95%CIs ranging from 1.00 to 7.51). Use of sleep medications was not patterned by SES. SES differences in sleep disturbances were only marginally attenuated by adjustment for other socio-demographic, behavioural and psychological factors. Results from polysomnography confirmed poorer sleep patterns among participants with low SES (p <0.05 for sleep efficiency/stage shifts), but no SES differences were found for sleep duration. CONCLUSIONS: In this population-based sample, low SES was strongly associated with sleep disturbances, independently of socio-demographic, behavioural, and psychological factors. Further research should establish the extent to which social differences in sleep contribute to socioeconomic differences in health outcomes.
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OBJECTIVES: To estimate the prevalence of youth who use cannabis but have never been tobacco smokers and to assess the characteristics that differentiate them from those using both substances or neither substance. DESIGN: School survey. SETTING: Postmandatory schools. PARTICIPANTS: A total of 5263 students (2439 females) aged 16 to 20 years divided into cannabis-only smokers (n = 455), cannabis and tobacco smokers (n = 1703), and abstainers (n = 3105). OUTCOME MEASURES: Regular tobacco and cannabis use; and personal, family, academic, and substance use characteristics. RESULTS: Compared with those using both substances, cannabis-only youth were younger (adjusted odds ratio [AOR], 0.82) and more likely to be male (AOR, 2.19), to play sports (AOR, 1.64), to live with both parents (AOR, 1.33), to be students (AOR, 2.56), and to have good grades (AOR, 1.57) and less likely to have been drunk (AOR, 0.55), to have started using cannabis before the age of 15 years (AOR, 0.71), to have used cannabis more than once or twice in the previous month (AOR, 0.64), and to perceive their pubertal timing as early (AOR, 0.59). Compared with abstainers, they were more likely to be male (AOR, 2.10), to have a good relationship with friends (AOR, 1.62), to be sensation seeking (AOR, 1.32), and to practice sports (AOR, 1.37) and less likely to have a good relationship with their parents (AOR, 0.59). They were more likely to attend high school (AOR, 1.43), to skip class (AOR, 2.28), and to have been drunk (AOR, 2.54) or to have used illicit drugs (AOR, 2.28). CONCLUSIONS: Cannabis-only adolescents show better functioning than those who also use tobacco. Compared with abstainers, they are more socially driven and do not seem to have psychosocial problems at a higher rate.
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The health status and need for care differ depending on the gender. The most notable differences are life expectancy, life expectancy in good health and the prevalence of geriatric syndromes or chronic illnesses. Some social health determinants (social isolation or financial precariousness) seem to act as risk factors for vulnerability, mostly amongst old or very old women. Through some examples of differences between men and women in terms of health and caregiving needs, this article tries to heighten the awareness of health professionals to a gender based approach of the elderly patient in order to promote the best possible equity in healthcare.