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Em 3 de março de 2026 11:21:57 UTC, Gravatar IDP Admin:
  • Adicionados os seguintes campos ao recurso Suicides by Causes em Suicides in India

      additional_info com valor lgd_mapping com valor indicators com valor mapping_status com valor similar_resources com valor


  • Os seguintes campos foram removidos do recurso Suicides by Causes em Suicides in India

      similar_datasets village_no tags


  • Valor alterado do campo data_insights do recurso Suicides by Causes para The Suicides by Causes dataset provides deep insights into the complex and multifactorial nature of suicide in India, enabling researchers to identify dominant social, economic, and personal factors contributing to suicidal behavior. By categorizing cases into causes such as family problems, illness, bankruptcy, unemployment, failure in examination, love affairs, drug or alcohol abuse, and other socio-personal stressors, Suicides by Causes dataset allows analysts to trace how different pressures manifest across demographic groups and regions.Cause-wise analysis reveals patterns of vulnerability for example, whether economic distress and unemployment contribute more to suicides among men, or if illness and family-related issues are more prevalent among women. Temporal trends help identify emerging or declining causes, such as the growing burden of mental illness, substance dependency, or financial stress linked to economic shifts. Regional and gender disaggregation further highlights disparities across states and social groups, pointing to localized socio-economic and cultural risk factors. (anteriormente The Suicides by Causes dataset provides deep insights into the complex and multifactorial nature of suicide in India, enabling researchers to identify dominant social, economic, and personal factors contributing to suicidal behavior. By categorizing cases into causes such as family problems, illness, bankruptcy, unemployment, failure in examination, love affairs, drug or alcohol abuse, and other socio-personal stressors, Suicides by Causes dataset allows analysts to trace how different pressures manifest across demographic groups and regions. Cause-wise analysis reveals patterns of vulnerability for example, whether economic distress and unemployment contribute more to suicides among men, or if illness and family-related issues are more prevalent among women. Temporal trends help identify emerging or declining causes, such as the growing burden of mental illness, substance dependency, or financial stress linked to economic shifts. Regional and gender disaggregation further highlights disparities across states and social groups, pointing to localized socio-economic and cultural risk factors.) em Suicides in India


  • Valor do campo idp_ready alterado para True no recursoSuicides by Causes em Suicides in India