PlainHealth

Compare Causes of Death

Select two causes of death to compare total deaths, age-adjusted rates, most-affected states, and 19-year national trends. Data from CDC WONDER, 1999–2017.

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Summary (2017)

Stroke

Total Deaths
146,383
Avg Rate /100K
37.4
Highest Rate State
Mississippi
51.1/100K
Lowest Rate State
New York
24.6/100K

Heart disease

Total Deaths
647,457
Avg Rate /100K
166.0
Highest Rate State
Oklahoma
237.2/100K
Lowest Rate State
Minnesota
119.1/100K

Head-to-Head (2017)

Metric Stroke Heart disease Difference
Total Deaths 146,383 647,457 B +501,074 (77%)
Avg Age-Adjusted Rate 37.4/100K 166.0/100K B +128.6/100K
Highest Rate State Mississippi
51.1/100K
Oklahoma
237.2/100K
Different states
Lowest Rate State New York
24.6/100K
Minnesota
119.1/100K
Different states

Age-Adjusted Rate Trend

National average age-adjusted death rate per 100,000 population, 1999–2017.

View trend data as table
Year Stroke Heart disease
1999 62.9 256.1
2000 61.6 249.6
2001 59.2 241.9
2002 58.3 237.0
2003 55.6 230.2
2004 51.6 215.5
2005 48.8 211.5
2006 45.4 201.3
2007 43.9 192.4
2008 42.7 188.5
2009 40.5 180.1
2010 39.9 176.8
2011 38.6 171.6
2012 37.6 169.6
2013 36.6 169.1
2014 36.8 167.8
2015 37.5 168.9
2016 37.2 167.0
2017 37.4 166.0

Top 5 States by Death Rate (2017)

States with the highest age-adjusted death rates for each cause.

Stroke

2. Alabama 50.0/100K
3. Louisiana 47.4/100K
4. Delaware 46.2/100K
5. Tennessee 45.0/100K

Heart disease

1. Oklahoma 237.2/100K
2. Mississippi 231.6/100K
3. Arkansas 223.8/100K
4. Alabama 223.2/100K
5. Louisiana 214.4/100K

Lowest 5 States by Death Rate (2017)

Stroke

Heart disease

1. Minnesota 119.1/100K
2. Colorado 122.7/100K
3. Hawaii 129.8/100K
4. Oregon 134.0/100K

Age-adjusted rates per 100,000 population, using year 2000 US standard population. ICD-10 codes: I60-I69 (Stroke), I00-I09 (Heart disease). Source: CDC WONDER, Underlying Cause of Death.

How PlainHealth Comparison Works

The comparison tool lets you stack two or more records side by side so you can see their key metrics at the same time. Comparisons are produced deterministically from the underlying dataset, the same inputs always produce the same output, so you can cite them, bookmark them, and return later with confidence that the numbers have not been quietly edited by an algorithm tuned for engagement.

Reading a Comparison Page Well

Comparison tables highlight differences first and similarities second. Pay attention to the time frame each column covers, records refreshed at different cadences can appear more different than they really are. Look at the denominator of any rate-based field; a record with a small denominator can show a dramatic rate from a handful of observations. Where a metric is known to be noisy, we flag it on the page. The goal is to help you triage quickly, then click through to the full records for the substantive detail.

When to Use Compare

Comparison is most useful early in research, when you want to shortlist candidates, narrow a geography, or decide which records deserve a deeper read. It is less useful as the final step of a consequential decision. Once you have shortlisted records from the comparison view, click through to the full record page to see every field, the methodology notes, and any warnings we attach to the data quality of that specific record. For legal, medical, financial, safety, or employment decisions, verify the underlying fact with the issuing agency before acting.

Methodology Notes

The comparison page pulls live from the same canonical dataset that powers the rest of the site. We do not re-rank, re-weight, or post-process values for the comparison view, every cell you see is the same value you would see on the individual record page. When a field is missing on one of the compared records, we show an em dash rather than a zero, so that "absent" is never confused with "zero." If a comparison appears to contradict a record page, email us the specific record IDs and we will triage within the next refresh cycle.