Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 197
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 271
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3165
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 597
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 511
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 317
Function: require_once
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Background: Causes of death statistics provide crucial health intelligence in national and international communities. An efficient death registration system provides reliable information for health policy system. In many developing countries, death registration systems face a degree of misclassification and incompleteness. There are many impediments to putting an estimate of cause-specific death rates. Addressing those challenges could prevent misleading results.
Methods: Our data was collected by Ministry of Health and Medical Education, Tehran and Isfahan cemeteries from 1995 to 2010. After converting ICD codes of Iran's death registration into GBD codes, 170 underlying causes of deaths were recognized in the available data. A wide range of methods were applied for preparing the data. We used several statistical models to estimate mortality rates in age-sex-province groups for all causes of deaths. The considerable number of combinations for age, sex, cause of death, year, and province variables made further complicated model selection and evaluation of the results.
Results: Totally, 58.91% of deaths were related to males. The majority of cases of death were classified as NCDs (77.83%) and injuries (14.80%). We extrapolated 71.76% and 14.71% of causes of death by mixed effect model, spline model with parameter 0.9 and 0.6, respectively.
Conclusion: A comprehensive and unique registration system is able to solve many DRS issues. It is necessary to assess the quality and validity of cause of death data. Scientific methods like analyzing mortality level and cause-of-death data are used to provide an overview for better decisions.
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