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)

Suicide

Total Deaths
47,173
Avg Rate /100K
16.5
Highest Rate State
Montana
28.9/100K
Lowest Rate State
District of Columbia
6.6/100K

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 Suicide Heart disease Difference
Total Deaths 47,173 647,457 B +600,284 (93%)
Avg Age-Adjusted Rate 16.5/100K 166.0/100K B +149.5/100K
Highest Rate State Montana
28.9/100K
Oklahoma
237.2/100K
Different states
Lowest Rate State District of Columbia
6.6/100K
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 Suicide Heart disease
1999 11.8 256.1
2000 11.7 249.6
2001 12.1 241.9
2002 12.3 237.0
2003 12.2 230.2
2004 12.4 215.5
2005 12.3 211.5
2006 12.4 201.3
2007 12.7 192.4
2008 13.1 188.5
2009 13.1 180.1
2010 13.8 176.8
2011 14.0 171.6
2012 14.4 169.6
2013 14.4 169.1
2014 14.9 167.8
2015 15.4 168.9
2016 15.6 167.0
2017 16.5 166.0

Top 5 States by Death Rate (2017)

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

Suicide

1. Montana 28.9/100K
2. Alaska 27.0/100K
3. Wyoming 26.9/100K
4. New Mexico 23.3/100K
5. Idaho 23.2/100K

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)

Suicide

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: X60-X84 (Suicide), 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.