The prevalence of depression may be affected by changes in psychiatric practices and the availability of online mental health information in the past two decades. This study aimed to evaluate the ...aggregate prevalence of depression in communities from different countries between 1994 and 2014 and to explore the variations in prevalence stratified by geographical, methodological and socio-economic factors. A total of 90 studies were identified and met the inclusion criteria (n = 1,112,573 adults) with 68 studies on single point prevalence, 9 studies on one-year prevalence, and 13 studies on lifetime prevalence of depression. A random-effects model meta-analysis that was performed to calculate the aggregate point, one-year and lifetime prevalence of depression calculated prevalences of 12.9%, 7.2% and 10.8% respectively. Point prevalence of depression was significantly higher in women (14.4%), countries with a medium human development index (HDI) (29.2%), studies published from 2004 to 2014 (15.4%) and when using self-reporting instruments (17.3%) to assess depression. Heterogeneity was identified by meta-regression and subgroup analysis, and response rate, percentage of women and year of publication, respectively, were determined contribute to depression prevalence. This meta-analysis allows benchmarking of the prevalence of depression during the era when online health information emerged, facilitating future comparisons.
This study models local and cross-city transmissions of the novel coronavirus in China between January 19 and February 29, 2020. We examine the role of various socioeconomic mediating factors, ...including public health measures that encourage social distancing in local communities. Weather characteristics 2 weeks prior are used as instrumental variables for causal inference. Stringent quarantines, city lockdowns, and local public health measures imposed in late January significantly decreased the virus transmission rate. The virus spread was contained by the middle of February. Population outflow from the outbreak source region posed a higher risk to the destination regions than other factors, including geographic proximity and similarity in economic conditions. We quantify the effects of different public health measures in reducing the number of infections through counterfactual analyses. Over 1.4 million infections and 56,000 deaths may have been avoided as a result of the national and provincial public health measures imposed in late January in China.
African swine fever (ASF) is believed to have evolved in eastern and southern Africa in a sylvatic cycle between common warthogs (Phacochoerus africanus) and argasid ticks of the Ornithodoros moubata ...complex that live in their burrows. The involvement of warthogs and possibly other wild suids in the maintenance of ASF virus means that the infection cannot be eradicated from Africa, but only prevented and controlled in domestic pig populations. Historically, outbreaks of ASF in domestic pigs in Africa were almost invariably linked to the presence of warthogs, but subsequent investigations of the disease in pigs revealed the presence of another cycle involving domestic pigs and ticks, with a third cycle becoming apparent when the disease expanded into West Africa where the sylvatic cycle is not present. The increase in ASF outbreaks that has accompanied the exponential growth of the African pig population over the last three decades has heralded a shift in the epidemiology of ASF in Africa, and the growing importance of the pig husbandry and trade in the maintenance and spread of ASF. This review, which focuses on the ASF situation between 1989 and 2017, suggests a minor role for wild suids compared with the domestic cycle, driven by socio‐economic factors that determine the ability of producers to implement the control measures needed for better management of ASF in Africa.
Summary Background In 2011, WHO member states signed up to the 25 × 25 initiative, a plan to cut mortality due to non-communicable diseases by 25% by 2025. However, socioeconomic factors influencing ...non-communicable diseases have not been included in the plan. In this study, we aimed to compare the contribution of socioeconomic status to mortality and years-of-life-lost with that of the 25 × 25 conventional risk factors. Methods We did a multicohort study and meta-analysis with individual-level data from 48 independent prospective cohort studies with information about socioeconomic status, indexed by occupational position, 25 × 25 risk factors (high alcohol intake, physical inactivity, current smoking, hypertension, diabetes, and obesity), and mortality, for a total population of 1 751 479 (54% women) from seven high-income WHO member countries. We estimated the association of socioeconomic status and the 25 × 25 risk factors with all-cause mortality and cause-specific mortality by calculating minimally adjusted and mutually adjusted hazard ratios HR and 95% CIs. We also estimated the population attributable fraction and the years of life lost due to suboptimal risk factors. Findings During 26·6 million person-years at risk (mean follow-up 13·3 years SD 6·4 years), 310 277 participants died. HR for the 25 × 25 risk factors and mortality varied between 1·04 (95% CI 0·98–1·11) for obesity in men and 2 ·17 (2·06–2·29) for current smoking in men. Participants with low socioeconomic status had greater mortality compared with those with high socioeconomic status (HR 1·42, 95% CI 1·38–1·45 for men; 1·34, 1·28–1·39 for women); this association remained significant in mutually adjusted models that included the 25 × 25 factors (HR 1·26, 1·21–1·32, men and women combined). The population attributable fraction was highest for smoking, followed by physical inactivity then s ocioeconomic status. Low socioeconomic status was associated with a 2·1-year reduction in life expectancy between ages 40 and 85 years, the corresponding years-of-life-lost were 0·5 years for high alcohol intake, 0·7 years for obesity, 3·9 years for diabetes, 1·6 years for hypertension, 2·4 years for physical inactivity, and 4·8 years for current smoking. Interpretation Socioeconomic circumstances, in addition to the 25 × 25 factors, should be targeted by local and global health strategies and health risk surveillance to reduce mortality. Funding European Commission, Swiss State Secretariat for Education, Swiss National Science Foundation, the Medical Research Council, NordForsk, Portuguese Foundation for Science and Technology.
Politicizing immigration in Western Europe Grande, Edgar; Schwarzbözl, Tobias; Fatke, Matthias
Journal of European public policy,
10/2019, Volume:
26, Issue:
10
Journal Article
Peer reviewed
Open access
Immigration has become a hot topic in West European politics. The factors responsible for the intensification of political conflict on this issue are a matter of considerable controversy. This holds ...in particular for the role of socio-economic factors and of radical right populist parties. This article explores the politicization of immigration issues and its driving forces in the electoral arena. It is based on a comparative study using both media and manifesto data covering six West European countries (Austria, France, Germany, Netherlands, Switzerland, and the UK) for a period from the early 1990s until 2017. We find no association between socio-economic factors and levels of politicization. Political conflict over immigration follows a political logic and must be attributed to parties and party competition rather than to ‘objective pressures.’ More specifically, we provide evidence that the issue entrepreneurship of radical right populist parties plays a crucial role in explaining variation in the politicization of immigration.
The COVID-19 pandemic has affected cities particularly hard. Here, we provide an in-depth characterization of disease incidence and mortality and their dependence on demographic and socioeconomic ...strata in Santiago, a highly segregated city and the capital of Chile. Our analyses show a strong association between socioeconomic status and both COVID-19 outcomes and public health capacity. People living in municipalities with low socioeconomic status did not reduce their mobility during lockdowns as much as those in more affluent municipalities. Testing volumes may have been insufficient early in the pandemic in those places, and both test positivity rates and testing delays were much higher. We find a strong association between socioeconomic status and mortality, measured by either COVID-19-attributed deaths or excess deaths. Finally, we show that infection fatality rates in young people are higher in low-income municipalities. Together, these results highlight the critical consequences of socioeconomic inequalities on health outcomes.
The United States has the highest number of coronavirus disease 2019 (COVID-19) in the world, with high variability in cases and mortality between communities. We aimed to quantify the associations ...between socio-economic status and COVID-19–related cases and mortality in the U.S.
The study design includes nationwide COVID-19 data at the county level that were paired with the Distressed Communities Index (DCI) and its component metrics of socio-economic status.
Severely distressed communities were classified by DCI>75 for univariate analyses. Adjusted rate ratios were calculated for cases and fatalities per 100,000 persons using hierarchical linear mixed models.
This cohort included 1,089,999 cases and 62,298 deaths in 3127 counties for a case fatality rate of 5.7%. Severely distressed counties had significantly fewer deaths from COVID-19 but higher number of deaths per 100,000 persons. In risk-adjusted analysis, the two socio-economic determinants of health with the strongest association with both higher cases per 100,000 persons and higher fatalities per 100,000 persons were the percentage of adults without a high school degree (cases: RR 1.10; fatalities: RR 1.08) and proportion of black residents (cases and fatalities: Relative risk(RR) 1.03). The percentage of the population aged older than 65 years was also highly predictive for fatalities per 100,000 persons (RR 1.07).
Lower education levels and greater percentages of black residents are strongly associated with higher rates of both COVID-19 cases and fatalities. Socio-economic factors should be considered when implementing public health interventions to ameliorate the disparities in the impact of COVID-19 on distressed communities.
•Socio-economic factors play an important role in coronavirus disease 2019 (COVID-19) prevalence and mortality.•Lower education level was the strongest association with both cases and fatalities.•The higher proportion of Black residents was also associated with cases and fatalities.•The poverty rate and median income were also associated with COVID-19 cases.•Median income and change in employment were also associated with COVID-19 fatalities.
Reliable energy consumption forecasting can provide effective decision-making support for planning development strategies to energy enterprises and for establishing national energy policies. ...Accordingly, the present study aims to apply a hybrid intelligent approach named ADE–BPNN, the back-propagation neural network (BPNN) model supported by an adaptive differential evolution algorithm, to estimate energy consumption. Most often, energy consumption is influenced by socioeconomic factors. The proposed hybrid model incorporates gross domestic product, population, import, and export data as inputs. An improved differential evolution with adaptive mutation and crossover is utilized to find appropriate global initial connection weights and thresholds to enhance the forecasting performance of the BPNN. A comparative example and two extended examples are utilized to validate the applicability and accuracy of the proposed ADE–BPNN model. Errors of the test data sets indicate that the ADE–BPNN model can effectively predict energy consumption compared with the traditional back-propagation neural network model and other popular existing models. Moreover, mean impact value based analysis is conducted for electrical energy consumption in U.S. and total energy consumption forecasting in China to quantitatively explore the relative importance of each input variable for the improvement of effective energy consumption prediction.
•Enhanced back-propagation neural network (ADE-BPNN) for energy consumption forecasting.•ADE-BPNN outperforms the current best models for two comparative cases.•Mean impact value approach explores socio-economic factors' relative importance.•ADE-BPNN's adjusted goodness-of-fit is 99.2% for China's energy consumption forecasting.
Broadband access in the home is a necessity, especially since the COVID-19 pandemic. Increasingly, connectivity is of vital importance for school, work, family, and friends. Existing international ...research on the implementation of broadband has studied its adoption patterns with a focus on the rural/urban digital divide. This paper explores the digital divide in a case study of the seventh largest city, by population, in the United States; San Antonio is a majority-minority city where over half of the people are Hispanic. This paper focuses on the five key affordability factors that drive broadband adoption. Researchers test social exclusion theory, the structural facets of poverty and social marginality to ascertain its potential impact on broadband access. The authors conducted a survey in both English and Spanish to learn more about the affordability factors that influence the broadband digital divide. Through our analysis, we found evidence that four of the factors (geographical disparities, profit-based discrimination, technology deployment cost, and socio-economic factors) played a role in the digital divide in this case study. The results of this study demonstrate that the digital divide is not exclusively a rural/urban digital divide, but can also occur in an intra-city context. This is especially evident in low-income areas within the city because they have substantially lower broadband adoption rates. The results of this study demonstrate the importance of looking closely at issues of social exclusion of marginalized groups and the affordability of broadband access intra-city.
•Paper explored the digital divide in a case study a large U.S. city.•Examined five key affordability factors that drive broadband adoption.•Tested social exclusion theory and its potential impact on broadband access.•Surveyed affordability factors that influence the broadband digital divide.•Evidence for geographical disparities, profit-based discrimination, technology deployment cost, and socio-economic factors.
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