20250727
18551400
1.0
TRUE
EnrichLayer
None
Created with Business Analyst Pro - EnrichLayer
publication date
Business Analyst Pro
Unknown
<div><span style='color:rgb(0, 0, 0);'><font size='5'><span style='font-weight:bold;'>Age</span></font></span></div><div><br /></div><p><img alt='age' src='https://doc.arcgis.com/en/esri-demographics/latest/data-browser/GUID-EA0757B7-0EBD-44B0-B034-20E58821913D-web.png' /> The <span>Age</span>
data category provides information about population by age groups, including age-specific summaries by gender and total population. <a href='https://doc.arcgis.com/en/esri-demographics/latest/data-browser/advanced-demographics.htm'>Advanced Demographics</a>
Age data provides detailed information about groups of people by their ages, such as age distributions; population grouped into age, race, and gender categories; households by the age of the householder or other household members; and income by the age or race of the householder. See
the <a href='https://doc.arcgis.com/en/esri-demographics/latest/regional-data/regional-data.htm'>regional data category tables</a> for variable distribution.</p><p>Example Age variables include the following:</p><p></p><ul><li>Female Population Age 0–14</li><li>Total Population Age 60+</li><li>Male Population Age 72</li></ul><div><div>Check other Data Category View Layers for variables not included in this set.<br /></div>Explore the <a href='https://doc.arcgis.com/en/esri-demographics/latest/data-browser/data-browser.htm' target='_blank'>Data Browser</a> for variables not included in any of the aforementioned layers.</div>
Demographics
Zip Code
Age
Ages
Current Year Age Variables by Zip Code
Age Variables by Zip Code - Current Year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