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Socioeconomic data predict adverse cardiovascular outcomes
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Abstract
Background/Introduction
Socioeconomic status (SES) factors predict the occurrence of adverse cardiovascular (CV) outcomes.
Purpose
SES has been studied in many contexts. We present data on SES in a new context using yelp, an American public company that publishes crowd-sourced reviews about businesses. A dataset containing aggregated yelp data for New Jersey zip codes pertaining to the number of fast-food restaurants, grocery stores, gyms and other fitness centers, nursing homes, and pharmacies was created. Cardiovascular outcomes were obtained from the Myocardial Infarction Data Acquisition System (MIDAS).
Methods
Linear regression models of the SES factors were used to predict the occurrence of hospitalized stroke, myocardial infarction (MI), and heart failure (HF).
Results
Overall, the number of fast-food restaurants, grocery stores, nursing homes, and pharmacies were associated with increased rate of adverse CV outcomes, while gyms and other fitness centers were associated with improved outcomes. Also, the SES factors of grocery, nursing home, pharmacy and fast-food restaurants were associated with increased rate of MI (p<0.0001). In addition, the SES factors of grocery, nursing home, pharmacy and fast food were associated with increased rate of HF (p<0.0001). On the contrary, gyms and other fitness centers were associated with lower rate of CV outcomes (p<0.0001). With respect to stroke, the SES factors of grocery, nursing home, pharmacy and fast-food restaurants were associated with increased rate of this condition (p<0.0001, figure). The y axis of the figure is proportional to the square root of the number of strokes in each zip code per 10,000 people.
Conclusions
In conclusion, persons living in zip codes of low socioeconomic status are associated with a high rate of occurrence of MI, HF and stroke. The number of gyms and other fitness centers is associated with a low rate of these outcomes. This information may be important in designing and implementing preventive strategies.
Funding Acknowledgement
Type of funding sources: None.
Oxford University Press (OUP)
Title: Socioeconomic data predict adverse cardiovascular outcomes
Description:
Abstract
Background/Introduction
Socioeconomic status (SES) factors predict the occurrence of adverse cardiovascular (CV) outcomes.
Purpose
SES has been studied in many contexts.
We present data on SES in a new context using yelp, an American public company that publishes crowd-sourced reviews about businesses.
A dataset containing aggregated yelp data for New Jersey zip codes pertaining to the number of fast-food restaurants, grocery stores, gyms and other fitness centers, nursing homes, and pharmacies was created.
Cardiovascular outcomes were obtained from the Myocardial Infarction Data Acquisition System (MIDAS).
Methods
Linear regression models of the SES factors were used to predict the occurrence of hospitalized stroke, myocardial infarction (MI), and heart failure (HF).
Results
Overall, the number of fast-food restaurants, grocery stores, nursing homes, and pharmacies were associated with increased rate of adverse CV outcomes, while gyms and other fitness centers were associated with improved outcomes.
Also, the SES factors of grocery, nursing home, pharmacy and fast-food restaurants were associated with increased rate of MI (p<0.
0001).
In addition, the SES factors of grocery, nursing home, pharmacy and fast food were associated with increased rate of HF (p<0.
0001).
On the contrary, gyms and other fitness centers were associated with lower rate of CV outcomes (p<0.
0001).
With respect to stroke, the SES factors of grocery, nursing home, pharmacy and fast-food restaurants were associated with increased rate of this condition (p<0.
0001, figure).
The y axis of the figure is proportional to the square root of the number of strokes in each zip code per 10,000 people.
Conclusions
In conclusion, persons living in zip codes of low socioeconomic status are associated with a high rate of occurrence of MI, HF and stroke.
The number of gyms and other fitness centers is associated with a low rate of these outcomes.
This information may be important in designing and implementing preventive strategies.
Funding Acknowledgement
Type of funding sources: None.
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