820 resultados para Socioeconomic inequalities


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This study assessed oral health outcomes (perceived dental treatment need, untreated dental caries, gingival bleeding, periodontal pockets, and pain in teeth and gums), in relation to color/race inequalities among adolescents in each Brazilian region. The database included dental examination and interview of 16,833 15-19-year-old adolescents, surveyed by the Brazilian health authority, from May 2002 to October 2003, in accordance with international diagnostic criteria standardized by the World Health Organization. Prevalence ratios estimated by Poisson regression, and controlled by socioeconomic status and access to fluoridated piped water, assessed oral health differentials among color/race groups and country's regions. Except for periodontal pockets, prevalence figures were higher in the North and Northeast: perceived dental treatment needs, untreated dental caries, gingival bleeding at probing and pain in teeth and gums varied between 80-83%, 75-76%, 38-43%, and 17-18%, respectively, in these regions. Adolescents living in the Southeast - the richest Brazilian region - presented a better general profile of oral health than their counterparts living in the remaining regions; they had a lower prevalence of untreated dental caries (54%) and unfavorable gingival status (29%). However, the Southeast presented color/race inequalities in all oral health outcomes, with a poorer profile systematically affecting browns or blacks, depending on the oral health condition under consideration. These results reinforce the need for expanding the amplitude of health initiatives aimed at adolescent oral health. Socially appropriate health programs should concurrently aim at the reduction of levels of oral disease and its inequalities.

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Background: Despite the importance of collecting individual data of socioeconomic status (SES) in epidemiological oral health surveys with children, this procedure relies on the parents as respondents. Therefore, type of school (public or private schools) could be used as an alternative indicator of SES, instead of collecting data individually. The aim of this study was to evaluate the use of the variable type of school as an indicator of socioeconomic status as a substitute of individual data in an epidemiological survey about dental caries in Brazilian preschool children. Methods: This study followed a cross-sectional design, with a random sample of 411 preschool children aged 1 to 5 years, representative of Catalao, Brazil. A calibrated examiner evaluated the prevalence of dental caries and parents or guardians provided information about several individual socioeconomic indicators by means of a semi-structured questionnaire. A multilevel approach was used to investigate the association among individual socioeconomic variables, as well as the type of school, and the outcome. Results: When all significant variables in the univariate analysis were used in the multiple model, only mother's schooling and household income (individual socioeconomic variables) presented significant associations with presence of dental caries, and the type of school was not significantly associated. However, when the type of school was used alone, children of public school presented significantly higher prevalence of dental caries than those enrolled in private schools. Conclusions: The type of school used as an alternative indicator for socioeconomic status is a feasible predictor for caries experience in epidemiological dental caries studies involving preschool children in Brazilian context.

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OBJECTIVE: Data from municipal databases can be used to plan interventions aimed at reducing inequities in health care. The objective of the study was to determine the distribution of infant mortality according to an urban geoeconomic classification using routinely collected municipal data. METHODS: All live births (total of 42,381) and infant deaths (total of 731) that occurred between 1994 and 1998 in Ribeirão Preto, Brazil, were considered. Four different geoeconomic areas were defined according to the family head's income in each administrative urban zone. RESULTS: The trends for infant mortality rate and its different components, neonatal mortality rate and post-neonatal mortality rate, decreased in Ribeirão Preto from 1994 to 1998 (chi-square for trend, p<0.05). These rates were inversely correlated with the distribution of lower salaries in the geoeconomic areas (less than 5 minimum wages per family head), in particular the post-neonatal mortality rate (chi-square for trend, p<0.05). Finally, the poor area showed a steady increase in excess infant mortality. CONCLUSIONS: The results indicate that infant mortality rates are associated with social inequality and can be monitored using municipal databases. The findings also suggest an increase in the impact of social inequality on infant health in Ribeirão Preto, especially in the poor area. The monitoring of health inequalities using municipal databases may be an increasingly more useful tool given the continuous decentralization of health management at the municipal level in Brazil.

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OBJECTIVE: To identify clustering areas of infants exposed to HIV during pregnancy and their association with indicators of primary care coverage and socioeconomic condition. METHODS: Ecological study where the unit of analysis was primary care coverage areas in the city of Porto Alegre, Southern Brazil, in 2003. Geographical Information System and spatial analysis tools were used to describe indicators of primary care coverage areas and socioeconomic condition, and estimate the prevalence of liveborn infants exposed to HIV during pregnancy and delivery. Data was obtained from Brazilian national databases. The association between different indicators was assessed using Spearman's nonparametric test. RESULTS: There was found an association between HIV infection and high birth rates (r=0.22, p<0.01) and lack of prenatal care (r=0.15, p<0.05). The highest HIV infection rates were seen in areas with poor socioeconomic conditions and difficult access to health services (r=0.28, p<0.01). The association found between higher rate of prenatal care among HIV-infected women and adequate immunization coverage (r=0.35, p<0.01) indicates that early detection of HIV infection is effective in those areas with better primary care services. CONCLUSIONS: Urban poverty is a strong determinant of mother-to-child HIV transmission but this trend can be fought with health surveillance at the primary care level.

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OBJECTIVE: To describe the effects of social inequities on the health and nutrition of children in low and middle income countries. METHODS: We reviewed existing data on socioeconomic disparities within-countries relative to the use of services, nutritional status, morbidity, and mortality. A conceptual framework including five major hierarchical categories affecting inequities was adopted: socioeconomic context and position, differential exposure, differential vulnerability, differential health outcomes, and differential consequences. The search of the PubMed database since 1990 identified 244 articles related to the theme. Results were also analyzed from almost 100 recent national surveys, including Demographic Health Surveys and the UNICEF Multiple Indicator Cluster Surveys. RESULTS: Children from poor families are more likely, relative to those from better-off families, to be exposed to pathogenic agents; once they are exposed, they are more likely to become ill because of their lower resistance and lower coverage with preventive interventions. Once they become ill, they are less likely to have access to health services and the quality of these services is likely to be lower, with less access to life-saving treatments. As a consequence, children from poor family have higher mortality rates and are more likely to be undernourished. CONCLUSIONS: Except for child obesity and inadequate breastfeeding practices, all the other adverse conditions analyzed were more prevalent in children from less well-off families. Careful documentation of the multiple levels of determination of socioeconomic inequities in child health is essential for understanding the nature of this problem and for establishing interventions that can reduce these differences.

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OBJECTIVE: To assess regional and sociodemographic differences in self-perceived health status among older adults. METHODS: A face-to-face quality of life survey was conducted in a representative sample of the Spanish population comprising 1,106 non-institutionalized elderly aged 60 or more in 2008. Logistic regression models were used to explain self-perceived health status according to the EuroQol Group Visual Analogue Scale (EQ-VAS). Independent variables included sociodemographic and health characteristics as well as the nomenclature of territorial units for statistics level 1 (NUTS1: group of autonomous regions) and level 2 (NUTS 2: autonomous regions). RESULTS: Younger and better off respondents were more likely to have a positive self-perceived health status. Having no chronic conditions, independence in performing daily living activities and lower level of depression were also associated with positive self-perceived health status. People living in the south of Spain showed a more negative self-perceived health status than those living in other regions. CONCLUSION: The study results point to health inequality among Spanish older adults of lower socioeconomic condition and living in the south of Spain. The analysis by geographic units allows for international cross-regional comparisons.

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This paper develops an accounting framework to consider the effect of deaths on the longitudinal analysis of income-related health inequalities. Ignoring deaths or using inverse probability weights (IPWs) to re-weight the sample for mortality-related attrition can produce misleading results, since to do so would be to disregard the most extreme of all health outcomes. Incorporating deaths into the longitudinal analysis of income-related health inequalities provides a more complete picture in terms of the evaluation of health changes in respect to socioeconomic status. We illustrate our work by investigating health mobility in Quality Adjusted Life Years (QALYs) as measured by the SF6D from 1999 till 2004 using the British Household Panel Survey (BHPS). We show that for Scottish males explicitly accounting for the dead, rather than using IPWs to account for mortality-related attrition, changes the direction of the relationship between relative health changes and initial income position, while for other population groups it increases the strength of this relationship by up to 14 times. When deaths are explicitly incorporated into the analysis it is found that over this five year period for both Scotland and England & Wales the relative health changes were significantly regressive such that the poor experienced a larger share of the health losses relative to their initial share of health and a large amount of this was related to mortality.

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BACKGROUND: Socioeconomic adversity in early life has been hypothesized to "program" a vulnerable phenotype with exaggerated inflammatory responses, so increasing the risk of developing type 2 diabetes in adulthood. The aim of this study is to test this hypothesis by assessing the extent to which the association between lifecourse socioeconomic status and type 2 diabetes incidence is explained by chronic inflammation. METHODS AND FINDINGS: We use data from the British Whitehall II study, a prospective occupational cohort of adults established in 1985. The inflammatory markers C-reactive protein and interleukin-6 were measured repeatedly and type 2 diabetes incidence (new cases) was monitored over an 18-year follow-up (from 1991-1993 until 2007-2009). Our analytical sample consisted of 6,387 non-diabetic participants (1,818 women), of whom 731 (207 women) developed type 2 diabetes over the follow-up. Cumulative exposure to low socioeconomic status from childhood to middle age was associated with an increased risk of developing type 2 diabetes in adulthood (hazard ratio [HR] = 1.96, 95% confidence interval: 1.48-2.58 for low cumulative lifecourse socioeconomic score and HR = 1.55, 95% confidence interval: 1.26-1.91 for low-low socioeconomic trajectory). 25% of the excess risk associated with cumulative socioeconomic adversity across the lifecourse and 32% of the excess risk associated with low-low socioeconomic trajectory was attributable to chronically elevated inflammation (95% confidence intervals 16%-58%). CONCLUSIONS: In the present study, chronic inflammation explained a substantial part of the association between lifecourse socioeconomic disadvantage and type 2 diabetes. Further studies should be performed to confirm these findings in population-based samples, as the Whitehall II cohort is not representative of the general population, and to examine the extent to which social inequalities attributable to chronic inflammation are reversible. Please see later in the article for the Editors' Summary.

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The increase in life expectancy that we continue to observe raises a complex set of challenges for policy. Among these challenges is the need to respond to the heterogeneity that remains in life expectancy within the older population. Most important is that life expectancy, even at older ages, differs markedly by socioeconomic position. In addition, despite increases in longevitymany individuals now effectively retire before state pension age and a large proportion of these are dependent on benefit income. In contrast, the contribution by older people to informal careprovision and other services has the potential to provide an important input into society, the economy and their own well-being. A crucial question, therefore, is which sections of the older population will live healthy active lives and which will be dependent on formal and informal sources of support. To answer this, we need to understand how inequalities in health are distributed in the older population and what the underlying causal processes are.

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Analysis of infant mortality and life expectancy across London by various dimensions of inequality- socioeconomic; gender; geographical, and trends

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BACKGROUND: Low socioeconomic status (SES) is consistently associated with higher mortality in high income countries. Only few studies have assessed this association in low and middle income countries, mainly because of sparse reliable mortality data. This study explores SES differences in overall and cause-specific mortality in the Seychelles, a rapidly developing small island state in the African region. METHODS: All deaths have been medically certified over more than two decades. SES and other lifestyle-related risk factors were assessed in a total of 3246 participants from three independent population-based surveys conducted in 1989, 1994 and 2004. Vital status was ascertained using linkage with vital statistics. Occupational position was the indicator of SES used in this study and was assessed with the same questions in the three surveys. RESULTS: During a mean follow-up of 15.0 years (range 0-23 years), 523 participants died (overall mortality rate 10.8 per 1000 person-years). The main causes of death were cardiovascular disease (CVD) (219 deaths) and cancer (142 deaths). Participants in the low SES group had a higher mortality risk for overall (HR = 1.80; 95% CI: 1.24-2.62), CVD (HR = 1.95; 1.04-3.65) and non-cancer/non-CVD (HR = 2.14; 1.10-4.16) mortality compared to participants in the high SES group. Cancer mortality also tended to be patterned by SES (HR = 1.44; 0.76-2.75). Major lifestyle-related risk factors (smoking, heavy drinking, obesity, diabetes, hypertension, hypercholesterolemia) explained a small proportion of the associations between low SES and all-cause, CVD, and non-cancer/non-CVD mortality. CONCLUSIONS: In this population-based study assessing social inequalities in mortality in a country of the African region, low SES (as measured by occupational position) was strongly associated with overall, CVD and non-cancer/non-CVD mortality. Our findings support the view that the burden of non-communicable diseases may disproportionally affect people with low SES in low and middle income countries.

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BACKGROUND: Differences in morbidity and mortality between socioeconomic groups constitute one of the most consistent findings of epidemiologic research. However, research on social inequalities in health has yet to provide a comprehensive understanding of the mechanisms underlying this association. In recent analysis, we showed health behaviours, assessed longitudinally over the follow-up, to explain a major proportion of the association of socioeconomic status (SES) with mortality in the British Whitehall II study. However, whether health behaviours are equally important mediators of the SES-mortality association in different cultural settings remains unknown. In the present paper, we examine this issue in Whitehall II and another prospective European cohort, the French GAZEL study. METHODS AND FINDINGS: We included 9,771 participants from the Whitehall II study and 17,760 from the GAZEL study. Over the follow-up (mean 19.5 y in Whitehall II and 16.5 y in GAZEL), health behaviours (smoking, alcohol consumption, diet, and physical activity), were assessed longitudinally. Occupation (in the main analysis), education, and income (supplementary analysis) were the markers of SES. The socioeconomic gradient in smoking was greater (p<0.001) in Whitehall II (odds ratio [OR] = 3.68, 95% confidence interval [CI] 3.11-4.36) than in GAZEL (OR = 1.33, 95% CI 1.18-1.49); this was also true for unhealthy diet (OR = 7.42, 95% CI 5.19-10.60 in Whitehall II and OR = 1.31, 95% CI 1.15-1.49 in GAZEL, p<0.001). Socioeconomic differences in mortality were similar in the two cohorts, a hazard ratio of 1.62 (95% CI 1.28-2.05) in Whitehall II and 1.94 in GAZEL (95% CI 1.58-2.39) for lowest versus highest occupational position. Health behaviours attenuated the association of SES with mortality by 75% (95% CI 44%-149%) in Whitehall II but only by 19% (95% CI 13%-29%) in GAZEL. Analysis using education and income yielded similar results. CONCLUSIONS: Health behaviours were strong predictors of mortality in both cohorts but their association with SES was remarkably different. Thus, health behaviours are likely to be major contributors of socioeconomic differences in health only in contexts with a marked social characterisation of health behaviours. Please see later in the article for the Editors' Summary.

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Background: This paper analyses gender inequalities in health status and in social determinants of health among the elderly in Western Europe. Methods: Data came from the first wave of the “Survey of Health, Ageing and Retirement in Europe” (SHARE, 2004). For the purposes of this study a subsample of community-residing people aged 65-85 years with no paid work was selected (4218 men and 5007 women). Multiple logistic regression models separated by sex and adjusted for age and country were fitted. Results: Women were more likely to report poor health status, limitations in mobility and poor mental health. Whereas in both sexes educational attainment was associated with the three health indicators, household income was only related to poor self-rated health among women. The relationship between living arrangements and health differed by gender and was primarily associated with poor mental health. In both sexes, not living with the partner but living with other people and being the household head was related to poor mental health status (aOR=2.14; 95% CI=1.11-4.14 for men and aOR=1.75; 95% CI=1.12-2.72 for women). Additionally, women living with their partner and other(s) and those living alone were more likely to report poor mental health status (aOR=1.67; 95% CI=1.17-2.41 and aOR=1.58; 95% CI=1.26-1.97, respectively). Conclusions: Health inequalities persist among the elderly. Women have poorer health status than men and in both sexes the risk of poor health status increases among those with low educational attainment. Living arrangements are primarily associated with poor mental health status with patterns that differ by gender.

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This study analyses gender inequalities in health among elderly people in Catalonia (Spain) by adopting a conceptual framework that globally considers three dimensions of health determinants : socio-economic position, family characteristics and social support. Data came from the 2006 Catalonian Health Survey. For the purposes of this study a sub-sample of people aged 65–85 years with no paid job was selected (1,113 men and 1,484 women). The health outcomes analysed were self-perceived health status, poor mental health status and long-standing limiting illness. Multiple logistic regression models separated by sex were fitted and a hierarchical model was fitted in three steps. Health status among elderly women was poorer than among the men for the three outcomes analysed. Whereas living with disabled people was positively related to the three health outcomes and confidant social support was negatively associated with all of them in both sexes, there were gender differences in other social determinants of health. Our results emphasise the importance of using an integrated approach for the analysis of health inequalities among elderly people, simultaneously considering socio-economic position, family characteristics and social support, as well as different health indicators, in order fully to understand the social determinants of the health status of older men and women.

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This paper presents a method for the measurement of changes in health inequality and income-related health inequality over time in a population.For pure health inequality (as measured by the Gini coefficient) andincome-related health inequality (as measured by the concentration index),we show how measures derived from longitudinal data can be related tocross section Gini and concentration indices that have been typicallyreported in the literature to date, along with measures of health mobilityinspired by the literature on income mobility. We also show how thesemeasures of mobility can be usefully decomposed into the contributions ofdifferent covariates. We apply these methods to investigate the degree ofincome-related mobility in the GHQ measure of psychological well-being inthe first nine waves of the British Household Panel Survey (BHPS). Thisreveals that dynamics increase the absolute value of the concentrationindex of GHQ on income by 10%.