A decade of socioeconomic inequality in type 2 diabetes area-level prevalence: an unshakeable status quo?

Aims: It is well known that there is a socioeconomic gradient in the prevalence of many chronic diseases, including type 2 diabetes (T2DM). We present a simple assessment of the macro-level association between area socioeconomic disadvantage and the area-level prevalence of T2DM in Danish municipalities and the development in this relationship over the last decade. Methods: We used readily available public data on the socioeconomic composition of municipalities and T2DM prevalence to illustrate this association and report the absolute and relative summary measures of socioeconomic inequality over the time period 2008–2018. Results: The results show a persistent relationship between municipality socioeconomic disadvantage and T2DM prevalence across all analyses, with a modelled gap in T2DM prevalence between the most and least disadvantaged municipalities, the slope index of inequality, of 1.23 [0.97;1.49] in 2018. Conclusions: These results may be used to indicate areas with specific needs, to encourage systematic monitoring of socioeconomic gradients in health, and to provide a descriptive backdrop for a discussion of how to tackle these socioeconomic and geographic inequalities, which seem to persist even in the context of the comprehensive welfare systems in Scandinavia.

Paths to Distance Learning at A University and its Application

The results of a 2019 sociological survey conducted on a nationwide structured Abstract sample of extramural students (2019) and graduates (2000–2018) of Higher Edu cational Institutions (HEIs) are used to reveal cultural, socio-economic, territorial origin of extramural students and graduates and identify the types of their educational strategies as well work experience and status at the enrollment stage. We analyze their movements within the socio-occupational hierarchy as a result of obtaining that education. Extramural students differ from full-timers in that they feature a more de mocratic socioeconomic composition and possess a different amount of educational resources at the enrollment stage. These differences are presented in the form of four educational trajectories, which correlate with indicators of origin on a scale from “weaker” to “stronger”. “Advantages / disadvantages” of the educational trajectories and status at the enrollment stage, affect the degree of success in the application of distance education in the labor market in accordance with the level of qualifications and specialties of the diploma. Extramural students / graduates are formed from two streams: those who enter the HEIs immediately after secondary education and those who come with work experience. The latter get a higher return on the labor market from distance education.

Between-school inequalities in access to STEM curricula in a marketized education system: The case of Australia

We used descriptive statistics and a logistic regression to examine between-school inequalities in science and math curricular offerings in Year 12 (final year) in all schools in one Australian state (Victoria). Dataset contains variables about school contexts: school enrolment size, school socioeconomic composition, school sector, and school location.

Between-school inequalities in access to STEM curricula in a marketized education system: The case of Australia

We used descriptive statistics and a logistic regression to examine between-school inequalities in science and math curricular offerings in Year 12 (final year) in all schools in one Australian state (Victoria). Dataset contains variables about school contexts: school enrolment size, school socioeconomic composition, school sector, and school location.

Changes Over Time in COVID-19 Vaccination Inequalities in Eight Large U.S. Cities

We estimate the associations between community socioeconomic composition and changes in COVID-19 vaccination levels in eight large cities at three time points. Between March and April, low SES communities had significantly lower change in percent vaccinated than high SES communities. Between April and May, this difference was not significant. Thus, the large vaccination gap between communities during restricted vaccine eligibility did not narrow when eligibility opened up. The link between COVID-19 vaccination and community disadvantage may lead to a bifurcated recovery where advantaged communities move on from the pandemic more quickly while disadvantaged communities continue to suffer.

COVID-19 Vaccine Rollouts and the Reproduction of Urban Spatial Inequality: Disparities Within Large U.S. Cities in March and April 2021 by Racial/Ethnic and Socioeconomic Composition

Rollouts of COVID-19 vaccines in the U.S. were opportunities to redress disparities that surfaced during the pandemic. Initial eligibility criteria, however, neglected geographic, racial/ethnic, and socioeconomic considerations. Marginalized populations may have faced barriers to then-scarce vaccines, reinforcing disparities. Inequalities may have subsided as eligibility expanded. Using spatial modeling, we investigate how strongly local vaccination levels were associated with socioeconomic and racial/ethnic composition as authorities first extended vaccine eligibility to all adults. We harmonize administrative, demographic, and geospatial data across postal codes in eight large U.S. cities over three weeks in Spring 2021. We find that, although vaccines were free regardless of health insurance coverage, local vaccination levels in March and April were negatively associated with poverty, enrollment in means-tested public health insurance (e.g., Medicaid), and the uninsured population. By April, vaccination levels in Black and Hispanic communities were only beginning to reach those of Asian and White communities in March. Increases in vaccination were smaller in socioeconomically disadvantaged Black and Hispanic communities than in more affluent, Asian, and White communities. Our findings suggest vaccine rollouts contributed to cumulative disadvantage. Populations that were left most vulnerable to COVID-19 benefited least from early expansions in vaccine availability in large U.S. cities.

Spatiotemporal prediction of COVID-19 cases using inter- and intra-county proxies of human interactions

Measurements of human interaction through proxies such as social connectedness or movement patterns have proved useful for predictive modeling of COVID-19, which is a challenging task, especially at high spatial resolutions. In this study, we develop a Spatiotemporal autoregressive model to predict county-level new cases of COVID-19 in the coterminous US using spatiotemporal lags of infection rates, human interactions, human mobility, and socioeconomic composition of counties as predictive features. We capture human interactions through 1) Facebook- and 2) cell phone-derived measures of connectivity and human mobility, and use them in two separate models for predicting county-level new cases of COVID-19. We evaluate the model on 14 forecast dates between 2020/10/25 and 2021/01/24 over one- to four-week prediction horizons. Comparing our predictions with a Baseline model developed by the COVID-19 Forecast Hub indicates an average 6.46% improvement in prediction Mean Absolute Errors (MAE) over the two-week prediction horizon up to 20.22% improvement in the four-week prediction horizon, pointing to the strong predictive power of our model in the longer prediction horizons.

Overweight and obesity by school socioeconomic composition and adolescent socioeconomic status: a school-based study

Background The main objective of this study was to investigate the interaction effect of school socioeconomic composition (SEC) and adolescent socioeconomic status (SES) in the prevalence of overweight and obesity among a representative sample of French adolescents of the third most populous département of France. Methods 1038 adolescents agreed to participate (response rate: 91.4%). They self-reported anthropomorphic variables, SES, school lunch and physical activity. The body mass index was divided into six categories according to the Center for Disease Control. Multivariable binary logistic regressions analysis without and with interaction term were performed on overweight or obesity. Models fit was compared using the Aikaike Information Criterion. Odds-ratios (OR) and their 95% accelerated-bootstrap confidence interval (95%BCa CI) were computed to estimate overweight or obesity risk. Results 8.9% of the adolescents were overweight. 3.4% were obese. No school-SEC effect was observed among low-SES adolescents. Medium-SES adolescents were at greater risk in low-SEC (OR = 10.75, 95%BCa CI = 2.67–64.57) and medium-SEC (OR = 5.08, 95%BCa CI = 1.55–24.84) compared with high-SEC schools. High-SES adolescents in low-SEC schools were at greater risk compared with those in medium-SEC (OR = 5.94, 95%BCa CI = 1.94–17.29) and high-SEC schools (OR = 4.99, 95%BCa CI = 1.71–13.14). A social gradient was observed in medium-SEC (ORlow/high = 2.79, 95%BCa CI = 1.22–7.41) and high-SEC (ORlow/medium = 6.86, 95%BCa CI = 1.06–5.22*106) schools. Conclusions Physical activity and lunch at and outside school help to understand these differences. Implications for obesity prevention initiatives are discussed.

Investigating the Structure of Son Bias in Armenia With Novel Measures of Individual Preferences

Sex ratios at birth favoring boys are being documented in a growing number of countries, a pattern indicating that families selectively abort females. Son bias also explains why, in many countries, girls have more siblings and are born at relatively earlier parities compared with their brothers. In this study, we develop novel methods for measuring son bias using both questionnaire items and implicit association tests, and we collect data on fertility preferences and outcomes from 2,700 participants in Armenia. We document highly skewed sex ratios, suggesting that selective abortions of females are widespread among parents in our sample. We also provide evidence that sex-selective abortions are underreported, which highlights the problem of social desirability bias. We validate our methods and demonstrate that conducting implicit association tests can be a successful strategy for measuring the relative preference for sons and daughters when social desirability is a concern. We investigate the structure of son-biased fertility preferences within households, across families, and between regions in Armenia, using measures of son bias at the level of the individual decision-maker. We find that men are, on average, considerably more son-biased than women. We also show that regional differences in son bias exist and that they appear unrelated to the socioeconomic composition of the population. Finally, we estimate the degree of spousal correlation in son bias and discuss whether husbands are reliably more son-biased than their wives.