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BACKGROUND: Urban-rural disparities in suicide mortality have received considerable attention. Varying conceptualizations of urbanity may contribute to the conflicting findings. This ecological study on Germany assessed how and to what extent urban-rural suicide associations are affected by 14 different urban-rural indicators. METHODS: Indicators were based on continuous or k-means classified population data, land-use data, planning typologies, or represented population-based accessibility indicators. Agreements between indicators were tested with correlation analyses. Spatial Bayesian Poisson regressions were estimated to examine urban-rural suicide associations while adjusting for risk and protective factors. RESULTS: Urban-rural differences in suicide rates per 100,000 persons were found irrespective of the indicator. Strong and significant correlation was observed between different urban-rural indicators. Although the effect sign consistently referred to a reduced risk in urban areas, statistical significance was not universally confirmed by all regressions. Goodness-of-fit statistics suggested that the population potential score performs best, and that population density is the second best indicator of urbanicity. Numerical indicators are favored over classified ones. Regional planning typologies are not supported. CONCLUSIONS: The strength of suicide urban-rural associations varies with respect to the applied indicator of urbanicity. Future studies that put urban-rural inequalities central are recommended to apply either unclassified population potentials or population density indicators, but sensitivity analyses are advised.
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Mortalidade/tendências , População Rural/tendências , Fatores Socioeconômicos , Suicídio/tendências , População Urbana/tendências , Teorema de Bayes , Estudos Transversais , Alemanha/epidemiologia , Humanos , Prevenção do SuicídioRESUMO
The 3-30-300 rule offers benchmarks for cities to promote equitable nature access. It dictates that individuals should see three trees from their dwelling, have 30 % tree canopy in their neighborhood, and live within 300 m of a high-quality green space. Implementing this demands thorough measurement, monitoring, and evaluation methods, yet little guidance is currently available to pursue these actions. To overcome this gap, we employed an expert-based consensus approach to review the available ways to measure 3-30-300 as well as each measure's strengths and weaknesses. We described seven relevant data and processes: vegetation indices, street level analyses, tree inventories, questionnaires, window view analyses, land cover maps, and green space maps. Based on the reviewed strengths and weaknesses of each measure, we presented a suitability matrix to link recommended measures with each component of the rule. These recommendations included surveys and window-view analyses for the '3 component', high-resolution land cover maps for the '30 component', and green space maps with network analyses for the '300 component'. These methods, responsive to local situations and resources, not only implement the 3-30-300 rule but foster broader dialogue on local desires and requirements. Consequently, these techniques can guide strategic investments in urban greening for health, equity, biodiversity, and climate adaptation.
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Características de Residência , Árvores , Humanos , Cidades , BiodiversidadeRESUMO
INTRODUCTION: Diabetic retinopathy (DR) is the second most common microvascular complication and the most common cause of blindness in patients with diabetes mellitus (DM). Despite the ongoing research, the findings of diabetic retinopathy epidemiological and risk factors are, until now, not consistent. More finding may be revealed by epidemiological studies, consistently mapping DR epidemiology under the current possibilities of investigations and treatment of the DM. DIARET SK: DIARET SK Study, with 5 000 enrolled patients with diabetes mellitus in the Slovak Republic, is, until now, the largest epidemiological study to set the prevalence of diabetic retinopathy. The primary aim is to establish the prevalence of diabetic retinopathy in patients with diabetes mellitus type I and II, according to the duration of the disease. The secondary aim is to establish prevalence of the different stages of the DR and diabetic macular edema (DME) and analysis of the risk factors influence. Included are patients with DM type I and II regardless to the ocular complications history and the period of DM duration. Each enrolled patient has both complex diabetic and ophthalmic examinations.Projects to establish DR prevalence: Tens of projects concerned with diabetic retinopathy epidemiology with different approaches to establish the prevalence and with different patients population. Results from different studies vary significantly (from 12.3 % to 66.9 %). The results depend on the design of the study and the patients recruitment, used examination methods, specific patients population with regard to the geography, prevalence of risk factors, period of diabetes duration, glycated hemoglobin (HbA1C) level, blood pressure, and is higher in type I diabetic patients. The most accurate results are from population epidemiological studies with well-controlled patient recruitment and uniform complex examination that are similar to the DIARET SK study. CONCLUSION: The DIARET SK study represents the largest epidemiological study to establish the prevalence of the diabetic retinopathy in patients with DM type I and II. Thanks to the quality design, similar to the already published studies, but with larger number of patients and newest examinations methods, the DIARET SK study has the aspiration to obtain the most accurate up to date data of diabetic retinopathy prevalence and risk factors influence to its outbreak. The patients recruitment started in February 2015. The expected date of patients recruitment termination is in the end of the year 2015, and the data analysis in 2016.
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Diabetes Mellitus Tipo 1/complicações , Diabetes Mellitus Tipo 2/complicações , Retinopatia Diabética/epidemiologia , Predisposição Genética para Doença , Edema Macular/epidemiologia , Adulto , Idoso , Diabetes Mellitus Tipo 1/epidemiologia , Diabetes Mellitus Tipo 2/epidemiologia , Retinopatia Diabética/complicações , Retinopatia Diabética/genética , Feminino , Hemoglobinas Glicadas , Humanos , Edema Macular/etiologia , Edema Macular/genética , Masculino , Pessoa de Meia-Idade , Prevalência , Estudos Retrospectivos , Fatores de Risco , Eslováquia/epidemiologiaRESUMO
AIM: The aim of this study is to validate the Slovak version of the National Eye Institute Visual Function Questionnaire-25 (NEI VQF-25) in patients with chronic ocular diseases. MATERIAL AND METHODS: The questionnaire was tested on 211 responders. The first group consisted of 83 patients with age-related macular degeneration (AMD), the second group represented 68 patients with diabetic macular edema (DME), and the control group had 60 responders. The Questionnaire (NEI VQF-25) consists of the base of 25 vision-targeted questions representing 11 vision-related constructs, plus an additional single-item general health-rating question. The data - demographic data and information from the Visual Function Questionnaire were obtained during one single visit of the patients during the period November 1st, 2010 and February 20th, 2011. The internal consistency and safety of the test were evaluated using Cronbachs alpha reliability coefficient. For separate groups the standard score was evaluated. RESULTS: The coefficient higher than 0.7, evaluated as good reliability, was calculated in all constructs except the sub-scale "ocular pain". The validity, evaluated using multivariable analysis measuring convergence and discrimination analysis, in the end confirmed accomplishment of all circumstances. The composite score of NEI VQF-25 in the DME group was 69.9 ± 4.6, in the AMD group 68.5 ± 4.3, and the highest score had the control group 91 ± 1.8. CONCLUSION: The questionnaire NEI VQF-25 in the Slovak version is useful and safe instrument to measure the quality of life in patients with DME and AMD.