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Demographic Evolution of ZIP Code 81121: A Case Study of Racial Composition Changes in a Micro-Community
CATEGORY
Demographics
DATA
Population
Median Income
Racial Distributions
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Demographics
Population
Median Income
Racial Distributions
ZIP code 81121, located in Arboles, Colorado, has a population of 3 residents as of 2022. This extremely small population makes it challenging to apply standard demographic categorizations. However, observable trends and changes over the past decade can be noted.
From 2013 to 2022, the racial composition of this area has undergone changes. Between 2013 and 2016, the area had a white majority (67-100% white). From 2017 to 2019, the white population decreased to 50%. The most recent data from 2020 to 2022 shows an equal split between white and Hispanic residents (33% each), with the remaining third unaccounted for in the available data.
The median income in this ZIP code has shown fluctuation over the past decade. From 2013 to 2017, median income increased from $50,408 to $60,612, a 20% rise. In 2018-2019, there was a slight decrease to around $60,000. From 2020 to 2022, there was a substantial jump to $73,952, representing a 46% increase from 2013.
These income changes coincide with the demographic shifts, potentially indicating a correlation between increasing diversity and rising income levels. However, with such a small population, individual household changes can dramatically affect these statistics.
The trend towards increasing diversity in this ZIP code aligns with broader national trends. The substantial increase in median income also reflects a general trend of rising incomes in many parts of the United States over the past decade.
The extreme small-scale nature of this community makes it an outlier in many ways. The population fluctuations between 1-3 residents over the years suggest that this area might be more accurately described as a "Micro Community" rather than fitting into standard demographic categories.
ZIP code 81121 shows trends towards increased diversity and rising incomes. However, its extremely small population makes it difficult to apply standard demographic analyses or draw broader conclusions. This case study highlights the importance of considering scale when analyzing demographic data and the limitations of applying general categorizations to micro-communities.
