Multiple logistic regression allows different components of an experiment to be identified in how they affect an overall outcome. Using the behavioral risk factor surveillance system survey data provided by the Rhode Island Department of Health (RIDOH), life satisfaction and preventative health models were constructed through a public health perspective. With these models, it was possible to identify which variables had the largest impact, spanning 2014-2017. Variables of importance in each year included physical and mental health, employment status and more. To determine the importance of these variables, different methods were used including odds ratios. These predictive models can be used in different settings to give the RIDOH and other public health organizations to come up with recommendations for better public health outcomes.

life satisfaction, risk prevention, multiple logistic regression, public health.

Received: January 15, 2021; Accepted: January 28, 2021; Published: February 4, 2021

How to cite this article: Yajni Warnapala and Tyler Simmons, Health by numbers: a public health case study of the state of Rhode Island, United States, JP Journal of Biostatistics 18(1) (2021), 125-133. DOI: 10.17654/BS018010125

This Open Access Article is Licensed under Creative Commons Attribution 4.0 International License

Reference:

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