Neurocognitive consequences of socioeconomic disparities: the intersection of cognitive neuroscience and public health

2013 ◽  
Vol 16 (5) ◽  
pp. 639-640 ◽  
Author(s):  
Kimberly G. Noble ◽  
Martha J. Farah
Keyword(s):  
Public Health ◽  
Cognitive Neuroscience ◽  
Socioeconomic Disparities

scholarly journals Understanding the complexity of socioeconomic disparities in smoking prevalence in Sweden: a cross-sectional study applying intersectionality theory

BMJ Open ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. e042323
Author(s):  
Sten Axelsson Fisk ◽  
Martin Lindström ◽  
Raquel Perez-Vicente ◽  
Juan Merlo
Keyword(s):  
Public Health ◽  
Smoking Prevalence ◽  
Health Management ◽  
Educational Achievement ◽  
Smoking Habit ◽  
Household Composition ◽  
Socioeconomic Disparities ◽  
Cross Sectional ◽  
Intersectionality Theory ◽  
Discriminatory Accuracy

ObjectivesSocioeconomic disparities in smoking prevalence remain a challenge to public health. The objective of this study was to present a simple methodology that displays intersectional patterns of smoking and quantify heterogeneities within groups to avoid inappropriate and potentially stigmatising conclusions exclusively based on group averages.SettingThis is a cross-sectional observational study based on data from the National Health Surveys for Sweden (2004–2016 and 2018) including 136 301 individuals. We excluded people under 30 years of age, or missing information on education, household composition or smoking habits. The final sample consisted on 110 044 individuals or 80.7% of the original sample.OutcomeApplying intersectional analysis of individual heterogeneity and discriminatory accuracy (AIHDA), we investigated the risk of self-reported smoking across 72 intersectional strata defined by age, gender, educational achievement, migration status and household composition.ResultsThe distribution of smoking habit risk in the population was very heterogeneous. For instance, immigrant men aged 30–44 with low educational achievement that lived alone had a prevalence of smoking of 54% (95% CI 44% to 64%), around nine times higher than native women aged 65–84 with high educational achievement and living with other(s) that had a prevalence of 6% (95% CI 5% to 7%). The discriminatory accuracy of the information was moderate.ConclusionA more detailed, intersectional mapping of the socioeconomic and demographic disparities of smoking can assist in public health management aiming to eliminate this unhealthy habit from the community. Intersectionality theory together with AIHDA provides information that can guide resource allocation according to the concept proportionate universalism.

scholarly journals An online health status report to support public health in Belgium

2019 ◽  
Vol 29 (Supplement_4) ◽  
Author(s):  
A Scohy ◽  
B Devleesschauwer ◽  
F Renard
Keyword(s):  
Public Health ◽  
Health Status ◽  
Assessment Tool ◽  
International Comparisons ◽  
Health Indicators ◽  
Warning Signal ◽  
Good Health ◽  
Socioeconomic Disparities ◽  
Status Report ◽  
Country Level

Abstract Issue Monitoring population health is crucial for policymakers. In Belgium, health monitoring only existed at regional level, with no integrated view at country level. Policy/tool The Health Status Report (HSR) project developed a tool for centralizing key health indicators. The HSR aims to support policymakers in multiple ways: as a ’warning signal’, by contributing to the planning of health policies, and as an assessment tool for those policies. Rather than being exhaustive, the HSR selects key indicators to highlight important needs. These indicators have been identified through literature and consultations with experts and stakeholders. Topics include life and health expectancies, mortality, morbidity, and lifestyles, with an important focus on socioeconomic inequalities. Good results and health gaps are underlined with international comparisons, trend analyses, and comparisons with reference values. By disaggregating the data by sex, age, geographic level or socio-economic level, specific health needs are identified. Results The main outcome of the project is a continuously updated website: www.healthybelgium.be. The report highlighted that, although the Belgian health status is rather good, there is room for improvement: for some indicators Belgium lags behind other European countries; regional disparities remain important, with most indicators revealing a better health status in Flanders than in Brussels and Wallonia. Socioeconomic disparities also remain very important, and for some indicators even tend to worsen. Comparing the Belgian health status to that of the EU-15 results in more severe conclusions than in international reports. Conclusions We developed a new tool to support public health policy in Belgium through benchmarking and trend and disparity analyses of several health indicators. The tool will be expanded in the next years, integrating for instance the results of the Belgian national burden of disease study. Key messages We developed an online health status monitoring tool to inform policymakers. The rather good health status hides important regional and socioeconomic disparities in Belgium.

scholarly journals Understanding the complexity of socioeconomic disparities in type 2 diabetes risk: a study of 4.3 million people in Sweden

2019 ◽  
Vol 7 (1) ◽  
pp. e000749 ◽  
Author(s):  
Maria Wemrell ◽  
Louise Bennet ◽  
Juan Merlo
Keyword(s):  
Public Health ◽  
Type 2 Diabetes ◽  
Low Income ◽  
Educational Achievement ◽  
Absolute Risk ◽  
Diabetes Risk ◽  
Socioeconomic Disparities ◽  
Heterogeneous Distribution ◽  
Discriminatory Accuracy

ObjectiveInvestigating demographic and socioeconomic factors as intersecting rather than as separate dimensions may improve our understanding of the heterogeneous distribution of type 2 diabetes in the population. However, this complexity has scarcely been investigated and we still do not know the accuracy of these factors for predicting type 2 diabetes. Improved understanding of the demographic and socioeconomic disparities predicting type 2 diabetes risk in the population would contribute to more precise and effective public health interventions.Research design and methodsWe analyzed the risk of type 2 diabetes among 4 334 030 individuals aged 40–84 years who by 2010 had resided in Sweden for at least 5 years. We stratified the study population into 120 strata defined by categories of age, gender, income, education, and immigration status. We calculated measures of absolute risk (prevalence) and relative risk (prevalence ratio), and quantified the discriminatory accuracy of the information for predicting type 2 diabetes in the population.ResultsThe distribution of type 2 diabetes risk in the population was highly heterogeneous. For instance, immigrated men aged 70–79 years with low educational achievement and low income had a risk around 32 times higher than native women aged 40–49 years with high income and high educational achievement (ie, 17.6% vs 0.5%). The discriminatory accuracy of the information was acceptable.ConclusionA more detailed, intersectional mapping of socioeconomic and demographic distribution of type 2 diabetes can assist in public health management aiming to reduce the prevalence of the disease.

scholarly journals Socioeconomic disparities and the distribution of HIV in Cameroon: a multilevel logistic regression analysis

2020 ◽  
Author(s):  
Zhongshang Yuan ◽  
Weiqiang Lin ◽  
Marlvin Anemey Tewara ◽  
Liu Yunxia ◽  
Helen Binang Barong ◽  
...  
Keyword(s):  
Public Health ◽  
Logistic Regression ◽  
Regression Model ◽  
Socioeconomic Factors ◽  
Urban Areas ◽  
Regional Distribution ◽  
Socioeconomic Disparities ◽  
Multilevel Logistic Regression ◽  
Multilevel Regression ◽  
The Relationship

Abstract Background: There have been controversial debates on the relationship between socioeconomic status and the distribution of HIV in Cameroon. We aim to illustrate the vulnerability of socioeconomic disparities and the risk of getting HIV for public health interventions. Methods: Descriptive statistics was conducted to quantify the socioeconomic gradients of HIV. A Multilevel logistic regression model was used to study the relationship between socioeconomic factors and HIV. The effect of the factors was presented as odds ratios (OR), with 95% confidence intervals (CIs). P-value less than 0.05 was considered to be statistically significant. We further mapped HIV prevalence in ArcGIS to visualize the regional distribution of HIV.Results: HIV was significantly associated with age (p<0.001), sex (p<0.001) and varies significantly by geographic region (p<0.001), level of education (p=0.001), wealth status (p<0.001), religion (p=0.042), ethnicity (p<0.001) and residence (p=0.001). HIV positive participants were more likely to be women, people with higher educational level, live in urban areas, practice the protestant religious belief, belong to the ethnicity of Kako/Meka/Pygmy and distributed in the East, South, and Yaoundé regions. Age, sex, region, education level, and ethnicity were significantly associated with the odds of having HIV from the multilevel regression model. Conclusion: Our finding recommends for novel intervention programs that will target the various socioeconomic factors associated with the odds of having HIV for proper public health management of the disease in Cameroon.

scholarly journals Impact of COVID-19 Mortality on U.S. Life Expectancy by Socioeconomic Rank of County of Residence

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. 236-236
Author(s):  
Denys Dukhovnov ◽  
Magali Barbieri
Keyword(s):  
Public Health ◽  
Life Expectancy ◽  
Mitigation Strategies ◽  
Socioeconomic Disparities ◽  
National Data ◽  
Disadvantaged Communities ◽  
Life Expectancy At Birth ◽  
The Us ◽  
Spatio Temporal ◽  
The Impact

Abstract Mortality disparities due to COVID-19 pandemic in the US accentuated the gap in the targeted public health and education response among disadvantaged communities. We use county data from John Hopkins University of Medicine in conjunction with county socioeconomic decile rankings, and weekly national data from the Centers for Disease Control to uncover the impact of county-level socioeconomic deprivation on the spatio-temporal dynamic of COVID-19 mortality. We estimate that over the course of 2020, the pandemic reduced the life expectancy at birth by 1.33 years (95% CI 1.0-1.56), and by 0.84 years (95% CI 0.59-1.0) by age 85 across all county SES decile groups, relative to the previous year's projection. The highest losses occurred in counties at the ends of the deprivation spectrum, and least affecting those in its middle. Decomposition of the impact of the COVID-19 mortality by seasonal time periods of 2020 reveals that coastal urban and high-SES counties endured a heavy death toll in the initial stages of the pandemic, though managed to cut it by more than a half by the end of 2020. The least affluent, inland, and rural counties have experienced a dramatic and lasting increase in deaths toward the second half of the year. We find that preexisting socioeconomic disparities before COVID-19 remained in force during the pandemic, leaving populations at all ages residing in underserved communities at a greater risk. This both calls into question and further instructs the ongoing public health interventions enabling more effective and equitable infectious disease mitigation strategies.

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