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The University of Louisville Journal of Respiratory Infections

Abstract

Background: One weakness that applies to all population-based studies performed in the United States (US) is that investigators perform population-based extrapolations without providing objective statistical evidence to show how well a particular city is a suitable surrogate for the US. The objective of this study was to propose and utilize a novel computational metric to compare individual US cities with the US average.

Methods: This was a secondary data analysis of publicly available databases containing US sociodemographic, economic, and health-related data. In total, 58 demographic, housing, economic, health behavior, and health status variables for each US city with a residential population of at least 500,000 were obtained. All variables were recorded as proportions. Euclidean, Manhattan and the average absolute difference metrics were used to compare the 58 variables to the average in the US.

Results: Oklahoma City, Oklahoma had the lowest distance from the United States, with Euclidean and Manhattan distances in proportion of 0.261 and 1.519, respectively. Louisville, Kentucky had the second lowest distance for both Euclidean distance and Manhattan distance, with distances of 0.286 and 1.545, respectively. The average absolute differences in proportion for Oklahoma City and Louisville to the US average were 0.026 and 0.027, respectively.

Conclusions: To our knowledge, this represents the first study evaluating a method for computing statistical comparisons of United States city sociodemographic, economic, and health-related data with the United States average. Our study shows that among cities with at least 500,000 residents, Oklahoma City is the closest to the United States, followed closely by Louisville. On average, these cities deviate from the US average on any variable studied by less than 3 percent.

Funder

The author(s) received no specific funding for this work

DOI

10.18295/jri/vol4/iss2/4

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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