New York City Health Atlas

Injury ER Visits

Compare This Metric

Description

Number of emergency room visits for injuries, poisonings, or accidents.


Calculation

Number of ER visits for injuries per 1,000 population.


Source

Statewide Planning and Research Cooperative System (SPARCS) Outpatient Data, 2011-2013.


Years of Data

2011-2013


Additional Resources

City Wide Average

76.0

Census Tract 3000900 Average

35.5

Averages

Hide Show

76.0 City-Wide
82.9 Brooklyn
35.5 Tract

Census Tract 3000900

Hide Show

Injury ER Visit Rate Population (2011-2013)
All 35.5 13,447

Sex

Female 39.9 6,571
Male 42.3 6,874

Race/Ethnicity

Asian/Pacific Islander 12.7 1,255
Black 361.0 626
Hispanic 116.5 910
White 13.8 10,055

Age

0-14 years 68.8 1,467
15-24 years 30.7 2,049
25-34 years 19.7 4,421
35-44 years 28.0 2,461
45-54 years 70.2 840
55-64 years 36.3 1,432
65-74 years 38.3 548
75+ years 120.2 208
Download Table (.CSV)

Correlation Is Not Causation

In statistics, correlation is a measure of association between two numeric variables. The strength of correlation between two variables is represented by the correlation coefficient, represented by the abbreviation r. Correlation coefficients range between -1 to 1.

Though the correlation coefficient indicates the strength of an association, it does not provide information about whether the change in one variable is caused by the other.

For example, if the correlation between adult smoking prevalence and child poverty is 0.7—a strong correlation—we cannot say either that adult smoking causes child poverty or, inversely, that child poverty causes smoking. We only know that as one of these variables increases, the other tends to increases.