Non-communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran, Endocrinology and Metabolism Research center, Endocrinology and Metabolism Research Institute, Tehran, Iran.
Digestive Oncology Research Center, Digestive Disease Research Institute, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran.
Arch Iran Med. 2014 Jan;17(1):7-15.
Iran has witnessed a substantial demographic and health transition, especially during the past 2 decades, which necessitates updated evidence-based policies at national and indeed at subnational scale. The National and Subnational Burden of Diseases, Injuries, and Risk Factors (NASBOD) Study aims to provide the required evidence based on updated data sources available in Iran and novel methods partly adopted from Global Burden of Disease 2010.
This paper aims at explaining the motives behind the study, the design, the definitions, the metrics, and the challenges due to limitations in data availability.
All available published and unpublished data sources will be used for estimating the burden of 291 diseases and 67 risk factors from 1990 to 2013 at national and subnational scale. Published data will be extracted through systematic review. Existing population-based data sources include: registries (death and cancer), Demographic and Health Surveys, National Health Surveys, and other population-based surveys such as Non_Communicable Diseases Surveillance Surveys. Covariates will be extracted from censuses and household expenditure surveys. Hospital records and outpatient data will be actively collected as two distinct projects. Due to lack of data points by year and province, statistical methods will be used to impute the lacking data points based on determined covariates. Two main models will be used for data imputation: Bayesian Autoregressive Multi-level models and Spatio-Temporal regression models. The results from all available models will be used in an Ensemble Model to obtain the final estimates. Five metrics will be used for estimating the burden: prevalence, death, Years of Life Lost due to premature death (YLL), Years of Life Lost due to Disability (YLD), and Disability-Adjusted Life Years Lost (DALY). Burden attributable to risk factors will be estimated through comparative risk assessment based on Population Attributable Fraction (PAF). Uncertainty Intervals (UIs) will be calculated and reported for all aforementioned metrics.
We will estimate trends in terms of prevalence, deaths, YLLs, YLDs, and DALYs for Diseases, Injuries, and Risk Factors province from 1990 to 2013.
Results of the present study will have implications for policy making as they address health gaps in Iranian population and their inequality between provinces.
伊朗经历了重大的人口和健康转变，特别是在过去的 20 年里，这需要在国家乃至地方层面制定基于最新证据的政策。国家和地方疾病、伤害和危险因素负担（NASBOD）研究旨在根据伊朗现有的最新数据来源和部分采用自 2010 年全球疾病负担的新方法提供所需的证据。
本文旨在解释研究的动机、设计、定义、指标以及由于数据可用性的限制而带来的挑战。
将使用所有现有的已发表和未发表的数据来源，从 1990 年到 2013 年，在国家和地方层面估算 291 种疾病和 67 种危险因素的负担。通过系统综述提取已发表的数据。现有的基于人群的数据来源包括：登记处（死亡和癌症）、人口与健康调查、国家健康调查以及其他基于人群的调查，如非传染性疾病监测调查。协变量将从人口普查和家庭支出调查中提取。医院记录和门诊数据将作为两个独立的项目积极收集。由于缺乏按年份和省份划分的数据点，将使用统计方法根据确定的协变量来推断缺失的数据点。将使用两种主要模型进行数据推断：贝叶斯自回归多层模型和时空回归模型。将使用所有可用模型的结果在综合模型中获得最终估计。将使用 5 个指标来估算负担：患病率、死亡、因过早死亡导致的生命年损失（YLL）、因残疾导致的生命年损失（YLD）以及残疾调整生命年损失（DALY）。将通过基于人群归因分数（PAF）的比较风险评估来估算风险因素所致负担。将计算并报告所有上述指标的不确定性区间（UI）。
我们将估算疾病、伤害和危险因素在各省从 1990 年到 2013 年的患病率、死亡、YLLs、YLDs 和 DALYs 的趋势。
本研究的结果将对政策制定产生影响，因为它们解决了伊朗人口的健康差距及其各省之间的不平等问题。
