Disability and Health Insurance - Seattle Neighborhoods

Table from the American Community Survey (ACS) 5-year series on disabilities and health insurance related topics for City of Seattle Council Districts, Comprehensive Plan Growth Areas and Community Reporting Areas. Table includes C21007 Age by Veteran Status by Poverty Status in the Past 12 Months by Disability Status, B27010 Types of Health Insurance Coverage by Age, B22010 Receipt of Food Stamps/SNAP by Disability Status for Households. Data is pulled from block group tables for the most recent ACS vintage and summarized to the neighborhoods based on block group assignment. Vintages: 2024 ACS Table(s): C21007, B27010, B22010 Data downloaded from: Census Bureau's Explore Census Data The United States Census Bureau's American Community Survey (ACS): About the Survey Geography & ACS Technical Documentation News & Updates This ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data. Data Note from the Census: Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables. Data Processing Notes: Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2020 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto Rico Census tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99). Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey. Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page. Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations: The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate. Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution. The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate. The estimate is controlled. A statistical test for sampling variability is not appropriate. The data for this geographic area cannot be displayed because the number of sample cases is too small.本数据集为美国社区调查（American Community Survey, ACS）5年系列中，针对西雅图市议会选区、综合规划增长区及社区报告区域的残疾与健康保险相关主题表格。 本数据集包含以下三张统计表格：C21007《按年龄、退伍军人身份、过去12个月贫困状况及残疾状况划分》、B27010《按年龄划分的健康保险覆盖类型》、B22010《家庭按残疾状况划分的食品券/补充营养援助计划（Supplemental Nutrition Assistance Program, SNAP）领取情况》。 数据取自最新ACS年份的街区组（block group）表格，并根据街区组分配规则汇总至各社区。本次使用的ACS数据年份为2024年，涉及表格为C21007、B27010、B22010。数据下载自美国人口普查局的"Explore Census Data"平台。 美国人口普查局美国社区调查（ACS）的相关资源包括：调查介绍、地理与ACS技术文档、新闻与更新。 该预制图层可在ArcGIS Pro、ArcGIS Online及其可配置应用、仪表板、故事地图（Story Maps）、自定义应用及移动应用中使用。 数据亦可导出用于离线工作流程。 使用本数据时，请引用美国人口普查局及ACS作为数据来源。 美国人口普查局的数据说明：本数据基于抽样调查，存在抽样变异性。抽样变异性带来的估计值不确定性通过误差边际（margin of error）体现，本次展示的为90%置信水平的误差边际。误差边际可理解为：由估计值减去误差边际与估计值加上误差边际所构成的区间（即上下置信边界），有90%的概率包含真实数值。除抽样变异性外，ACS估计值还存在非抽样误差（相关讨论详见《数据精度》一文），本统计表格未体现非抽样误差的影响。 数据处理说明：本数据的边界取自美国人口普查局TIGER地理数据库（Topologically Integrated Geographic Encoding and Referencing, TIGER），具体为国家次州地理数据库（命名格式为tlgdb_(年份)_a_us_substategeo.gdb）。边界数据与ACS数据同步更新（每年一次），边界年份与人口普查局指定的数据年份完全匹配。 为满足制图与地图绘制需求，本数据已移除普查边界中的水体及海岸线：对于普查街区（census tract），水体裁剪基于TIGER提供的2020年面积水文边界子集，移除了面积≥5000万平方米的大中型水体及其他重要地物；对于州与县级边界，水体及海岸线取自2020年500k分辨率TIGER制图边界形状文件的海岸线，以更精准地呈现海岸线及五大湖区域。原始的AWATER与ALAND字段仍作为属性保留在数据表中，单位为平方米。 州图层共包含52条记录，涵盖美国所有州、华盛顿哥伦比亚特区及波多黎各。本数据服务已移除水域区域（如海洋）内无人口的普查街区（编码以99开头的普查街区）。 百分比及派生计数与对应的误差边际为计算值（字段名中带有"_calc_"前缀），遵循美国社区调查的规范定义。字段别名基于美国社区调查汇总文件文档页面提供的表壳（Table Shells）文件生成。 部分负值（如-4444…）已被设置为空值，仅-5555…被设置为零。原始API数据中的负值对应以下情形： 1. 误差边际列表明无足够抽样观测值可计算标准误差及误差边际，不适合进行统计检验； 2. 无足够抽样观测值可计算估计值，或无法计算中位数比值，因为其中一个或两个中位数估计值落在开放式分布的最低或最高区间内； 3. 中位数落在开放式分布的最低或最高区间内； 4. 不适合进行统计检验； 5. 估计值已被控制，不适合进行抽样变异性统计检验； 6. 因抽样案例数量过少，无法展示该地理区域的数据。