Associations of Suicide Rates With Socioeconomic Status and Social Isolation: Findings From Longitudinal Register and Census Data

Suicide represents a major challenge to public mental health. In order to provide empirical evidence for prevention strategies, we hypothesized current levels of low socioeconomic status (SES) and high social isolation (SI) to be linked to increased suicide rates in N = 390 administrative districts since SES and SI are associated with mental illness. Effects of SES on suicide rates were further expected to be especially pronounced in districts with individuals showing high SI levels as SI reduces the reception of social support and moderates the impact of low SES on poor mental health. We linked German Microcensus data to register data on all 149,033 German suicides between 1997 and 2010 and estimated Prentice and Sheppard’s model for aggregate data to test the hypotheses, accounting for spatial effect correlations. The findings reveal increases in district suicide rates by 1.20% (p < 0.035) for 1% increases of district unemployment, suicide rate decreases of -0.39% (p < 0.028) for 1% increases in incomes, increases of 1.65% (p < 0.033) in suicides for 1% increases in one-person-households and increases in suicide rates of 0.54% (p < 0.036) for 1% decreases in single persons' incomes as well as suicide rate increases of 3.52% (p < 0.000) for 1% increases in CASMIN scores of individuals who moved throughout the year preceding suicide. The results represent appropriate starting points for the development of suicide prevention strategies. For the definition of more precise measures, future work should focus on the causal mechanisms resulting in suicidality incorporating individual level data

Associations of Suicide Rates With Socioeconomic Status and Social Isolation: Findings From Longitudinal Register and Census Data

Suicide represents a major challenge to public mental health. In order to provide empirical evidence for prevention strategies, we hypothesized current levels of low socioeconomic status (SES) and high social isolation (SI) to be linked to increased suicide rates in N = 390 administrative districts since SES and SI are associated with mental illness. Effects of SES on suicide rates were further expected to be especially pronounced in districts with individuals showing high SI levels as SI reduces the reception of social support and moderates the impact of low SES on poor mental health. We linked German Microcensus data to register data on all 149,033 German suicides between 1997 and 2010 and estimated Prentice and Sheppard’s model for aggregate data to test the hypotheses, accounting for spatial effect correlations. The findings reveal increases in district suicide rates by 1.20% (p < 0.035) for 1% increases of district unemployment, suicide rate decreases of -0.39% (p < 0.028) for 1% increases in incomes, increases of 1.65% (p < 0.033) in suicides for 1% increases in one-person-households and increases in suicide rates of 0.54% (p < 0.036) for 1% decreases in single persons' incomes as well as suicide rate increases of 3.52% (p < 0.000) for 1% increases in CASMIN scores of individuals who moved throughout the year preceding suicide. The results represent appropriate starting points for the development of suicide prevention strategies. For the definition of more precise measures, future work should focus on the causal mechanisms resulting in suicidality incorporating individual level data

The Effect of Socioeconomic Factors and Indoor Residual Spraying on Malaria in Mangaluru, India: A Case-Control Study

India faces 0.5 million malaria cases annually, including half of all Plasmodium vivax malaria cases worldwide. This case–control study assessed socioeconomic determinants of urban malaria in coastal Mangaluru, Karnataka, southwestern India. Between June and December 2015, we recruited 859 malaria patients presenting at the governmental Wenlock Hospital and 2190 asymptomatic community controls. We assessed clinical, parasitological, and socioeconomic data. Among patients, p. vivax mono-infection (70.1%) predominated. Most patients were male (93%), adult (median, 27 years), had no or low-level education (70.3%), and 57.1% were daily labourers or construction workers. In controls (59.3% male; median age, 32 years; no/low-level education, 54.5%; daily labourers/construction workers, 41.3%), 4.1% showed asymptomatic Plasmodium infection. The odds of malaria was reduced among those who had completed 10th school grade (aOR, 0.3; 95% CI, 0.26–0.42), lived in a building with a tiled roof (aOR, 0.71; 95% CI, 0.53–0.95), and reported recent indoor residual spraying (aOR, 0.02; 95% CI, 0.01–0.04). In contrast, migrant status was a risk factor for malaria (aOR, 2.43; 95% CI, 1.60–3.67). Malaria in Mangaluru is influenced by education, housing condition, and migration. Indoor residual spraying greatly contributes to reducing malaria in this community and should be promoted, especially among its marginalised members.Peer Reviewe

Assessing Associations of Suicide with Socioeconomic Status and Social Isolation

With yearly rates ranking clearly above world average in Europe, suicide constitutes a substantial public health problem. Because of that, prevention has become a major concern for German mental health institutions. A requirement for successful prevention strategies is to address all key factors that contribute to suicidality. It is highly relevant in this respect that suicidal behaviour itself exhibits a social gradient: drawing on the relevant literature, low socioeconomic status (SES) and a high extent of social isolation (SI) are related to increased suicide risks (Lorant et al. 2005; Li et al. 2011; Qin et al. 2003; Agerbo et al. 2007). The purpose of this study was therefore to add to these findings and to further investigate associations of SES and SI with suicide in order to define starting points for public health interventions. It was consequently hypothesized that lower individual levels of SES and higher individual levels of SI are correlated with increased suicide rates. SI potentially compromises the perception of social support in stressful live events associated with low SES (Cohen et al. 2006; Kumari et al. 2010). Since such life events correlate with suicidal behavior (Beautrais et al. 1997; Cohen et al. 2019), the effects of low SES were further hypothesized to be aggravated in individuals with high SI levels (SES x SI interaction). In order to test the hypotheses, all 149.033 suicide deaths between 1997 and 2010 (T = 14 years) were extracted from the official German death record as coded by ICD categories E950 - E959 for 1997 and X60 - X84 for the years from 1998 onwards, respectively. Information on SES and SI was gained by merging the dataset with Germany’s main household survey, i.e. the Microcensus. In accordance with the existing literature, established indexes on occupational status (ISEI, Ganzeboom & Treiman 1996) and educational achievements (CASMIN, König et al. 1988) were applied as well as items on income, minor employment, unemployment, the number of received public transfers and the reception of social bene fits due to unemployment (ALG I/II) in order to capture SES. SI was proxied with variables measuring single marital status, living in a one-person-household and relocations throughout the year before the survey was conducted. Due to German data protection regulations that do not permit the analysis of death record data based on individual level information, suicide deaths were examined as aggregated rates at the level of N = 390 administrative districts. In order to deal with two problems associated with this kind of statistical analysis, Prentice and Sheppard’s model for aggregate data (1995) was applied accounting for potential estimation biases due to differences in baseline suicide rates between districts and between time periods. The model specification further corrected for spatial effect correlations. An important limitation to this procedure is that the estimates represent a blend of effects at the individual and district levels. However, an adequate solution is only available through the application of individual level data. The statistical analysis turned out the following results: The positive effect on suicide rates of unemployment and the negative effect of income as two out of seven SES proxies and the positive effect of living in a one-person-household as one out of three SI proxies validate the proposed hypotheses on the relations of SES and SI with suicide rates. Confirming the hypothesis on SI mediating SES effects, the model revealed positive effects on suicide rates of income decreases in single individuals. Likewise, we observed positive effects on district suicide rates for decreasing levels of CASMIN in district population shares who had relocated throughout the past year. In contradiction to the theoretical claims, however, increases in CASMIN scores were found to result in positive effects on suicide rates just as a history of relocation prior to suicide was related to decreasing suicide rates. Furthermore, decreases in income were found to result in negative effects on suicide rates in the district population of persons living in a one-person-household. The results indicating associations of SES and SI with increases in district suicide rates represent appropriate starting points for the definition of suicide prevention strategies. Thus, particularly the unemployed, individuals with low incomes, persons living in one-person-households and relocated individuals with lower educational levels should be targeted by public health interventions. Moreover, the observations of the present study clearly demonstrate the significance of longitudinal individual level data for public health policies. Respective research incorporating such data would permit a better understanding of the causal mechanisms resulting in suicidality and help to further investigate the robustness of the shown results. By this means, prevention strategies could be better adapted to the specfic needs of the individuals under concern. Regarding the findings contradicting the theoretical claims, it needs to be mentioned that associations of low SES and high SI levels with increases in suicide risks can not be ruled out at the individual level. Rather, the observed inconsistent effects might be attributable to differences in district compositions than to differences in characteristics of the respective subjects. Also a statistical separation of compositional effects from effects of individual traits would be made possible by including individual level data in future work.:Abbrevations II Tables II 1 Introduction 1 1.1 Suicide - A Global Health Burden 1 1.2 Risk Factors and Etiology of Suicide 1 1.3 Suicide Prevention 2 1.4 Social Disparities in Suicide 2 1.4.1 Socioeconomic Status 2 1.4.2 Social Isolation 3 1.4.3 Health Inequalities and Health Inequities 4 1.4.4 Causation and Selection 5 1.4.5 Individual Life Courses 7 1.5 Stress and Diathesis 8 1.5.1 Critical Life Events 9 1.6 Neurobiological Correlates of Suicidality 9 1.6.1 Neurobiological Correlates of SES and SI 10 1.7 SES, SI and Social Support 11 1.8 Aims of the Thesis 11 1.9 Methods 12 2 Original Publication 14 Summary 23 References 26 Supplementary Materials - Further Statistical Tests & Models 41 Structural Breaks in Suicide Numbers 41 Age- and Gender-Adjustment of District Suicide Rates 42 Alternate Model Specifications Anlagen i Erklärung über die eigenständige Abfassung der Arbeit i Spezifizierung des eigenen wissenschaftlichen Beitrags iii Danksagung ii

Effects of Face Mask Mandates on COVID-19 Transmission in 51 Countries: Retrospective Event Study

BackgroundThe question of the utility of face masks in preventing acute respiratory infections has received renewed attention during the COVID-19 pandemic. However, given the inconclusive evidence from existing randomized controlled trials, evidence based on real-world data with high external validity is missing. ObjectiveTo add real-world evidence, this study aims to examine whether mask mandates in 51 countries and mask recommendations in 10 countries increased self-reported face mask use and reduced SARS-CoV-2 reproduction numbers and COVID-19 case growth rates. MethodsWe applied an event study approach to data pooled from four sources: (1) country-level information on self-reported mask use was obtained from the COVID-19 Trends and Impact Survey, (2) data from the Oxford COVID-19 Government Response Tracker provided information on face mask mandates and recommendations and any other nonpharmacological interventions implemented, (3) mobility indicators from Google’s Community Mobility Reports were also included, and (4) SARS-CoV-2 reproduction numbers and COVID-19 case growth rates were retrieved from the Our World in Data—COVID-19 data set. ResultsMandates increased mask use by 8.81 percentage points (P=.006) on average, and SARS-CoV-2 reproduction numbers declined on average by −0.31 units (P=.008). Although no significant average effect of mask mandates was observed for growth rates of COVID-19 cases (−0.98 percentage points; P=.56), the results indicate incremental effects on days 26 (−1.76 percentage points; P=.04), 27 (−1.89 percentage points; P=.05), 29 (−1.78 percentage points; P=.04), and 30 (−2.14 percentage points; P=.02) after mandate implementation. For self-reported face mask use and reproduction numbers, incremental effects are seen 6 and 13 days after mandate implementation. Both incremental effects persist for >30 days. Furthermore, mask recommendations increased self-reported mask use on average (5.84 percentage points; P<.001). However, there were no effects of recommendations on SARS-CoV-2 reproduction numbers or COVID-19 case growth rates (−0.06 units; P=.70 and −2.45 percentage points; P=.59). Single incremental effects on self-reported mask use were observed on days 11 (3.96 percentage points; P=.04), 13 (3.77 percentage points; P=.04) and 25 to 27 (4.20 percentage points; P=.048 and 5.91 percentage points; P=.01) after recommendation. Recommendations also affected reproduction numbers on days 0 (−0.07 units; P=.03) and 1 (−0.07 units; P=.03) and between days 21 (−0.09 units; P=.04) and 28 (−0.11 units; P=.05) and case growth rates between days 1 and 4 (−1.60 percentage points; P=.03 and −2.19 percentage points; P=.03) and on day 23 (−2.83 percentage points; P=.05) after publication. ConclusionsContrary to recommendations, mask mandates can be used as an effective measure to reduce SARS-CoV-2 reproduction numbers. However, mandates alone are not sufficient to reduce growth rates of COVID-19 cases. Our study adds external validity to the existing randomized controlled trials on the effectiveness of face masks to reduce the spread of SARS-CoV-2

Secondary data for global health digitalisation

Substantial opportunities for global health intelligence and research arise from the combined and optimised use of secondary data within data ecosystems. Secondary data are information being used for purposes other than those intended when they were collected. These data can be gathered from sources on the verge of widespread use such as the internet, wearables, mobile phone apps, electronic health records, or genome sequencing. To utilise their full potential, we offer guidance by outlining available sources and approaches for the processing of secondary data. Furthermore, in addition to indicators for the regulatory and ethical evaluation of strategies for the best use of secondary data, we also propose criteria for assessing reusability. This overview supports more precise and effective policy decision making leading to earlier detection and better prevention of emerging health threats than is currently the case

White Paper - Verbesserung des Record Linkage für die Gesundheitsforschung in Deutschland

Die personenbezogene Verknüpfung von unterschiedlichen, gesundheitsbezogenen Daten mit dem Ziel einen Forschungsdatensatz zu erstellen, wird als Record Linkage bezeichnet. Diese Daten zu einer Person können bei voneinander getrennten Datenhaltern vorliegen. Auf diese Weise lassen sich wissenschaftliche Fragestellungen beantworten, die wegen des beschränkten Variablenumfangs mit einer Datenquelle alleine nicht zu beantworten wären. Diese verknüpften Daten entfalten ein riesiges Potential für die Gesundheitsforschung, um Prävention, Therapie und Versorgung der Bevölkerung zu verbessern. Da es sich dabei um sensible Daten handelt, gelten strenge Rechtsvorschriften um vor potenziellen Missbrauch zu schützen. Die derzeitigen rechtlichen Gegebenheiten schränken allerdings die Nutzung der Gesundheitsdaten für die Forschung so stark ein, dass ihr Potenzial für eine Verbesserung von Prävention und Versorgung bisher nicht ausgeschöpft werden kann. Record Linkage wird in Deutschland dadurch erschwert bzw. in vielen Fällen sogar unmöglich gemacht, dass es im Gegensatz zu Ländern keinen eindeutigen personenbezogenen Identifikator gibt, der eine Zusammenführung über verschiedene Datenkörper hinweg ermöglichen würde. Zudem sind in Deutschland interoperable Lösungen nicht vorhanden, um ein umfassendes studien- und datenkörperübergreifendes Record Linkage in einer gesicherten Umgebung durchführen zu können. Dem berechtigten Interesse auf Schutz der personenbezogenen Daten steht z. B. das Interesse entgegen, Risiken und Nutzen von Behandlungen zu erforschen und diese zur Verbesserung der gesundheitlichen Versorgung zu nutzen. Bei der Durchführung von Record Linkage-Projekten steht die Wissenschaft vor großen Herausforderungen. Oftmals wird von Datenhaltern oder Datenschützern für die Verknüpfung personenbezogener Daten die informierte Einwilligung der einzelnen Studienteilnehmenden gefordert, selbst wenn dies nicht erforderlich ist, z. B. weil klare gesetzliche Regelungen fehlen. Hinzu kommt eine unterschiedliche Auslegung der gesetzlichen Rahmenbedingungen durch Datenschutzbehörden. Zweitens erlauben die Informationen der zu verknüpfenden Datenquellen oft keine exakte Verknüpfung. So ist die Datensatzverknüpfung nicht nur ein rechtliches, sondern auch eine methodische Herausforderung. Insgesamt ist festzuhalten, dass das Record Linkage für die Gesundheitsforschung in Deutschland gegenwärtig weit hinter den Standards anderer europäischer Länder hinterherhinkt. So müssen für jeden Anwendungsfall und jedes Record Linkage-Projekt einzelfallspezifische Lösungen entwickelt, geprüft, ggf. modifiziert und – falls positiv beschieden – umgesetzt werden. Die Limitationen und Möglichkeiten dieser unterschiedlichen und spezifisch auf verschiedene Anwendungsfelder zugeschnittenen Ansätze werden diskutiert und es werden die Voraussetzungen beschrieben, die erfüllt sein müssen, um einen forschungsfreundlicheren Ansatz für die personenbezogene Datensatzverknüpfung zwischen verschiedenen Datenquellen in Deutschland zu erreichen. Dabei werden auch entsprechende Empfehlungen an den Gesetzgeber formuliert. Das White Paper soll die Grundlage für eine Verbesserung des Record Linkage für die Gesundheitsforschung in Deutschland schaffen. Es zielt darauf ab, praktikable Lösungen für die personenbezogene Datensatzverknüpfung von unterschiedlichen Datenquellen anzubieten, die im Einklang mit der europäischen Datenschutzgrundverordnung stehen