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Built 20 multivariable logistic regression models to analyze the relationships between variables of local public health infrastructure and best practices

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Logistic Regression of Public Health Infrastructure and Best Practices

Goal

To identify elements of local public health infrastructure (PHI) that are associated with the completion of 20 key public health activities while adjusting for state differences.

Methods

Cross-sectional secondary data were acquired and linked from two national surveys of local health departments, the National Profile of Local Health Departments survey as well as the National Longitudinal Survey of Public Health Systems. In total, 20 multivariable logistic regression models were created to analyze the relationships between variables. State fixed effects were used in multivariable models to control for differences in state-level legislation.

Findings

Several public health services or activities, modes of provisions, and staffing elements were strongly correlated with the completion of best practice activities. It was found that state differences affected the correlations between infrastructure variables and best practices, while rurality of jurisdiction was not statistically correlated with the completion of any best practices. These findings will add to the discussion of what the minimum necessary elements of PHI may be.

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Built 20 multivariable logistic regression models to analyze the relationships between variables of local public health infrastructure and best practices

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