Social Determinants of Health

**Overview**
This data package contains information on the conditions in the environment in which people are born, live, learn, work, play, worship; it also has age information that affects a wide range of health, functioning, and quality-of-life outcomes and risks. Conditions (e.g., social, economic, and physical) in these various environments and settings (e.g., school, church, workplace, and neighborhood) have been referred to as place.

**Description**
This data package contains information on social determinants of health such as daily smoking, HIV Incidence, population & social demographics. The social determinants of health (SDOH or SDH) are linked to the economic and social conditions and their distribution among the population that influence individual and group differences in health status. They are health-promoting factors found in one's living and working conditions such as the distribution of income, wealth, influence, and power rather than individual risk factors such as behavioral risk factors or genetics that influence the risk for a disease, or vulnerability to disease or injury. According to some viewpoints, the distributions of social determinants are shaped by public policies that reflect the influence of prevailing political ideologies of those governing a jurisdiction. The patterns of social engagement and a sense of security and well-being are also affected by where people live. Resources that enhance the quality of life can have a significant influence on population health outcomes.

**Benefits**
- Useful data package for physicians as it contains information on the conditions like social, economic and physical in these various environments and settings (e.g., school, church, workplace, and neighborhood) have been referred to as place.

**License Information**
The use of John Snow Labs datasets is free for personal and research purposes. For commercial use please subscribe to the [Data Library](https://www.johnsnowlabs.com/marketplace/) on John Snow Labs website. The subscription will allow you to use all John Snow Labs datasets and data packages for commercial purposes.

**Included Datasets**
- [Daily Smoking Prevalence](https://www.johnsnowlabs.com/marketplace/daily-smoking-prevalence)
- The Global Burden of Disease Study 2019 (GBD 2019), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors at the global, regional, national, territorial, and, for a subset of countries, subnational level.
- [Disability Weights](https://www.johnsnowlabs.com/marketplace/disability-weights)
- This dataset contains information of GBD (Global Burden of Disease) 2019 sequelae, health states, health state lay descriptions and disability weights.
- [HIV Incidence Prevalence and Mortality](https://www.johnsnowlabs.com/marketplace/hiv-incidence-prevalence-and-mortality)
- The Global Burden of Disease Study 2015 (GBD 2015), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors globally, for 21 regions, and for 195 countries and territories. This dataset was also published in The Lancet in July 2016 in "Global, regional, and national incidence, prevalence, and mortality for HIV, 1980-2015: estimates from the Global Burden of Disease Study 2015."
- [ICD-9 and ICD-10 Codes Mapped To Fatal Nonfatal Causes](https://www.johnsnowlabs.com/marketplace/icd-9-and-icd-10-codes-mapped-to-fatal-nonfatal-causes)
- This dataset contains the List of International Classification of Diseases (ICD) codes mapped to the Global Burden of Disease cause list for causes of death and ICD-9 and ICD-10 codes used in the extraction of hospital and claims data, mapped to GBD 2015 nonfatal causes, impairments, and nature of injury categories.
- [Opioid Overdose Mortality in the US](https://www.johnsnowlabs.com/marketplace/opioid-overdose-mortality-in-the-us)
- This dataset contains age-adjusted statistical data on deaths caused by opioids overdose by state and the increase of deaths caused by opioids overdose.
- [Population Estimates 1970-2019](https://www.johnsnowlabs.com/marketplace/population-estimates-1970-2019)
- This dataset contains information of GBD (Global Burden of Disease) 2019 population estimates from 1970 to 2019.
- [Socio-Demographic Index Values](https://www.johnsnowlabs.com/marketplace/socio-demographic-index-values)
- This dataset consists of a summary measure that identifies where countries or other geographic areas sit on the spectrum of development. Expressed on a scale of 0 to 1, SDI (Socio-Demographic Index) is a composite average of the rankings of the incomes per capita, average educational attainment, and fertility rates of all areas in the GBD (Global Burden of Disease) study.

**Data Engineering Overview**
**We deliver high-quality data**
- Each dataset goes through 3 levels of quality review
- 2 Manual reviews are done by domain experts
- Then, an automated set of 60+ validations enforces every datum matches metadata & defined constraints
- Data is normalized into one unified type system
- All dates, unites, codes, currencies look the same
- All null values are normalized to the same value
- All dataset and field names are SQL and Hive compliant
- Data and Metadata
- Data is available in both CSV and Apache Parquet format, optimized for high read performance on distributed Hadoop, Spark & MPP clusters
- Metadata is provided in the open Frictionless Data standard, and its every field is normalized & validated
- Data Updates
- Data updates support replace-on-update: outdated foreign keys are deprecated, not deleted

**Our data is curated and enriched by domain experts**

Each dataset is manually curated by our team of doctors, pharmacists, public health & medical billing experts:
- Field names, descriptions, and normalized values are chosen by people who actually understand their meaning
- Healthcare & life science experts add categories, search keywords, descriptions and more to each dataset
- Both manual and automated data enrichment supported for clinical codes, providers, drugs, and geo-locations
- The data is always kept up to date – even when the source requires manual effort to get updates
- Support for data subscribers is provided directly by the domain experts who curated the data sets
- Every data source’s license is manually verified to allow for royalty-free commercial use and redistribution.

**Need Help?**
If you have questions about our products, contact us at [[e-mail]](mailto:[e-mail]).

**概述**
本数据集套件包含与人们出生、生活、学习、工作、娱乐、礼拜所处环境相关的各类信息，同时涵盖影响健康水平、机体功能与生活质量结局及风险的年龄相关信息。上述各类环境与场景（如学校、教堂、工作场所与社区）中的各类条件（社会、经济与物理条件等）被统称为**场所（place）**。

**数据描述**
本数据集套件包含健康社会决定因素（social determinants of health, SDOH/SDH）相关信息，例如每日吸烟率、HIV发病率、人口与社会人口学数据。健康社会决定因素（SDOH/SDH）指与经济社会条件及其在人群中的分布相关的因素，这些因素会造成个体与群体健康状态的差异。它们是存在于人们生活与工作环境中的健康促进因素，例如收入、财富、影响力与权力的分配，而非诸如行为风险因素或遗传因素这类影响疾病患病风险、疾病易感性或损伤易感性的个体风险因素。部分观点认为，社会决定因素的分布格局由公共政策塑造，而这些政策反映了管辖区域执政者所持主流政治意识形态的影响。人们的居住地点同样会影响社会参与模式以及安全感与幸福感。能够提升生活质量的各类资源，对人群健康结局可产生显著影响。

**数据价值**
- 本数据集套件对医师极具实用价值，其涵盖了各类环境与场景（如学校、教堂、工作场所与社区）中的社会、经济与物理相关条件信息，此类条件即前文所述的场所（place）。

**许可信息**
约翰·斯诺实验室（John Snow Labs）的数据集可免费用于个人用途与科研场景。若需商用，请前往约翰·斯诺实验室官网订阅[数据资源库（Data Library）](https://www.johnsnowlabs.com/marketplace/)，订阅后可商用所有约翰·斯诺实验室的数据集与数据集套件。

**包含数据集**
- [每日吸烟率（Daily Smoking Prevalence）](https://www.johnsnowlabs.com/marketplace/daily-smoking-prevalence)
- 由健康指标与评估研究所（Institute for Health Metrics and Evaluation, IHME）牵头的2019年全球疾病负担研究（Global Burden of Disease Study 2019, GBD 2019），对全球、区域、国家、领地以及部分国家的次国家级层面的疾病、损伤与风险因素负担进行了估算。
- [伤残权重（Disability Weights）](https://www.johnsnowlabs.com/marketplace/disability-weights)
- 本数据集包含2019年全球疾病负担研究（GBD 2019）的后遗症、健康状态、健康状态通俗描述以及伤残权重相关信息。
- [HIV发病率、患病率与死亡率（HIV Incidence Prevalence and Mortality）](https://www.johnsnowlabs.com/marketplace/hiv-incidence-prevalence-and-mortality)
- 由健康指标与评估研究所（IHME）牵头的2015年全球疾病负担研究（GBD 2015），对全球21个区域以及195个国家和领地的疾病、损伤与风险因素负担进行了估算。该数据集于2016年7月发表于《柳叶刀》期刊，题为《1980-2015年全球、区域及国家层面HIV的发病率、患病率与死亡率：来自2015年全球疾病负担研究的估算结果》。
- [映射至致命与非致命病因的ICD-9与ICD-10编码（ICD-9 and ICD-10 Codes Mapped To Fatal Nonfatal Causes）](https://www.johnsnowlabs.com/marketplace/icd-9-and-icd-10-codes-mapped-to-fatal-nonfatal-causes)
- 本数据集包含国际疾病分类（ICD）编码列表，该列表已映射至全球疾病负担研究的死因列表；同时包含用于提取医院与理赔数据的ICD-9与ICD-10编码，这些编码已映射至2015年全球疾病负担研究的非致命病因、损伤与损伤性质分类。
- [美国阿片类药物过量死亡率（Opioid Overdose Mortality in the US）](https://www.johnsnowlabs.com/marketplace/opioid-overdose-mortality-in-the-us)
- 本数据集包含按州划分的阿片类药物过量致死年龄标化统计数据，以及阿片类药物过量致死人数的增长情况。
- [1970-2019年人口估算值（Population Estimates 1970-2019）](https://www.johnsnowlabs.com/marketplace/population-estimates-1970-2019)
- 本数据集包含1970年至2019年的2019年全球疾病负担研究（GBD 2019）人口估算相关信息。
- [社会人口学指数值（Socio-Demographic Index Values）](https://www.johnsnowlabs.com/marketplace/socio-demographic-index-values)
- 本数据集包含一项综合衡量指标，用于体现国家或其他地理区域在发展光谱上的所处位置。社会人口学指数（Socio-Demographic Index, SDI）以0至1的区间进行表示，是全球疾病负担研究（GBD）中所有区域的人均收入、平均受教育年限与生育率排名的综合平均值。

**数据工程概览**
**我们提供高质量数据**
- 每份数据集均通过三级质量审核
- 2次人工审核由领域专家完成
- 随后执行60余项自动化验证流程，确保每一条数据都符合元数据与既定约束条件
- 数据将被归一化至统一类型系统
- 所有日期、单位、编码与货币格式保持统一
- 所有空值均被归一化为统一的标准值
- 所有数据集与字段名称均兼容SQL与Hive规范
- 数据与元数据
- 数据以CSV与Apache Parquet两种格式提供，针对分布式Hadoop、Spark与MPP集群的高读取性能进行了优化
- 元数据采用开放的无障碍数据标准（Frictionless Data），且所有字段均经过归一化与验证
- 数据更新
- 数据更新采用更新即替换机制：过时的外键将被弃用，而非直接删除

**我们的数据由领域专家进行精选与富集**
每份数据集均由我们的医生、药剂师、公共卫生与医疗结算专家团队手动精选：
- 字段名称、描述与归一化值均由真正理解其含义的专业人员选定
- 医疗健康与生命科学专家会为每份数据集添加分类、搜索关键词、描述等额外信息
- 针对临床编码、供应商、药品与地理定位，均可支持人工与自动化双重数据富集流程
- 数据将始终保持更新，即便数据源需要手动操作才能获取更新
- 数据订阅者的支持服务将由精选该数据集的领域专家直接提供
- 所有数据源的许可协议均经过人工验证，以确保可免版权商用与再分发

**需要帮助？**
若您对我们的产品有任何疑问，请发送邮件至[[e-mail]](mailto:[e-mail]).

搜集汇总

背景与挑战

背景概述

该数据集是关于健康社会决定因素的综合性数据包，包含吸烟率、HIV流行病学、人口统计等多维度健康相关指标，数据来源于全球疾病负担研究等权威机构，并经过三级质量审核流程。数据集特别关注社会经济环境对群体健康差异的影响，为公共卫生研究提供重要参考。