Chapter 6.2 · The sliver

Gun homicide and the causes of early death

The tract clusters with the highest firearm homicide rates hold 50% of the deaths implied for 2022 to 2024 and 9.5% of residents outside New York City, and in Cook County the residents of the highest-rate clusters have a life expectancy of 71.7 years (deaths in 2010 to 2015), 9.5 fewer than those in clusters with no recorded deaths.

Author: Vishal Singh
Affiliation: NYU Stern
Published: 9 October 2026

The tract clusters with the highest firearm homicide rates hold 50% of the deaths that CDC's rates imply for 2022 to 2024 outside New York City, and 9.5% (95% CI 8.3% to 10.8%) of residents. At the other end of the ranking, 30.7% (95% CI 29.0% to 32.6%) of residents live in clusters with no recorded firearm homicide in any year from 2022 to 2024. A rate for a state, a county or a city averages over both ends, and the neighborhood is where they separate.

This chapter follows that concentration down to Cook County, the county that holds Chicago and its suburbs, and then widens to the other kinds of early death. It changes grain once. The first four figures describe tract clusters, the unit in which CDC publishes neighborhood death rates. The last four describe counties, the finest grain at which County Health Rankings reports deaths from overdose, suicide, homicide and motor-vehicle crashes. Neither grain describes individuals.

CDC's injury and violence dashboard publishes death rates for census tracts, but not for single tracts. It combines small neighboring tracts into clusters large enough to report a stable rate and repeats the cluster's rate on every member tract. The median tract belongs to a cluster of 5 tracts, and the largest cluster has 20. A cluster-year with a few deaths gets a modeled estimate with an interval, one with none gets a rate of zero, one with many gets a direct rate, and CDC withholds the rate when the model is unstable. The unit in this section is the cluster, and each of the 17,814 clusters in the national curve is counted once.

To draw the curve, rank every cluster from its highest to its lowest mean annual rate for 2022 to 2024, multiply each rate by the cluster's residents to get implied deaths, and accumulate residents and deaths down the ranking. Equal shares would follow the diagonal. The curve in Figure 1 bends far above it. The clusters that hold the highest-rate tenth of residents hold 51.3% (95% CI 48.1% to 54.4%) of implied deaths. Reaching 50% of deaths takes 9.5% (95% CI 8.3% to 10.8%) of residents, and reaching 75% takes 24.1% (95% CI 22.2% to 26.0%).

Figure 1

The tract clusters with the highest firearm homicide rates hold 50% of implied deaths and 9.5% of residents outside New York City

Cumulative share of implied firearm homicide deaths against cumulative share of residents, tract clusters ranked from the highest to the lowest mean annual rate, 2022 to 2024, outside New York City

Cumulative share of firearm homicide deaths (%)

Show data

Data for The tract clusters with the highest firearm homicide rates hold 50% of implied deaths and 9.5% of residents outside New York City
conf_high	conf_low	pct_residents	series	share_deaths
n/a	n/a	0	Firearm homicide deaths	0
15.02	12.36	1	Firearm homicide deaths	13.93
23.60	19.23	2	Firearm homicide deaths	21.70
29.75	24.60	3	Firearm homicide deaths	27.45
34.76	29.14	4	Firearm homicide deaths	32.20
39.03	33.12	5	Firearm homicide deaths	36.28
42.74	36.67	6	Firearm homicide deaths	39.89
46.09	39.89	7	Firearm homicide deaths	43.16
49.12	42.80	8	Firearm homicide deaths	46.10
51.87	45.55	9	Firearm homicide deaths	48.79
54.39	48.10	10	Firearm homicide deaths	51.31
56.71	50.48	11	Firearm homicide deaths	53.66
58.84	52.73	12	Firearm homicide deaths	55.87
60.89	54.85	13	Firearm homicide deaths	57.94
62.78	56.87	14	Firearm homicide deaths	59.89
64.60	58.77	15	Firearm homicide deaths	61.74
66.28	60.63	16	Firearm homicide deaths	63.49
67.85	62.36	17	Firearm homicide deaths	65.15
69.35	64.01	18	Firearm homicide deaths	66.73
70.79	65.59	19	Firearm homicide deaths	68.24
72.19	67.12	20	Firearm homicide deaths	69.68
73.50	68.57	21	Firearm homicide deaths	71.06
74.74	69.96	22	Firearm homicide deaths	72.38
75.92	71.31	23	Firearm homicide deaths	73.65
77.04	72.59	24	Firearm homicide deaths	74.85
78.11	73.83	25	Firearm homicide deaths	76.01
79.15	75.01	26	Firearm homicide deaths	77.12
80.16	76.16	27	Firearm homicide deaths	78.18
81.11	77.24	28	Firearm homicide deaths	79.21
82.04	78.29	29	Firearm homicide deaths	80.20
82.91	79.30	30	Firearm homicide deaths	81.16
83.78	80.28	31	Firearm homicide deaths	82.07
84.59	81.22	32	Firearm homicide deaths	82.96
85.42	82.13	33	Firearm homicide deaths	83.82
86.17	83.01	34	Firearm homicide deaths	84.65
86.92	83.87	35	Firearm homicide deaths	85.45
87.64	84.70	36	Firearm homicide deaths	86.22
88.31	85.50	37	Firearm homicide deaths	86.96
88.97	86.27	38	Firearm homicide deaths	87.68
89.60	87	39	Firearm homicide deaths	88.36
90.22	87.72	40	Firearm homicide deaths	89.02
90.81	88.41	41	Firearm homicide deaths	89.66
91.36	89.07	42	Firearm homicide deaths	90.27
91.90	89.71	43	Firearm homicide deaths	90.85
92.41	90.32	44	Firearm homicide deaths	91.41
92.91	90.90	45	Firearm homicide deaths	91.94
93.38	91.45	46	Firearm homicide deaths	92.45
93.84	91.99	47	Firearm homicide deaths	92.95
94.28	92.50	48	Firearm homicide deaths	93.42
94.71	93	49	Firearm homicide deaths	93.88
95.12	93.47	50	Firearm homicide deaths	94.32
95.52	93.93	51	Firearm homicide deaths	94.74
95.89	94.37	52	Firearm homicide deaths	95.15
96.26	94.79	53	Firearm homicide deaths	95.55
96.61	95.21	54	Firearm homicide deaths	95.93
96.95	95.60	55	Firearm homicide deaths	96.30
97.28	95.98	56	Firearm homicide deaths	96.66
97.59	96.36	57	Firearm homicide deaths	97
97.90	96.72	58	Firearm homicide deaths	97.33
98.19	97.06	59	Firearm homicide deaths	97.65
98.47	97.40	60	Firearm homicide deaths	97.96
98.75	97.71	61	Firearm homicide deaths	98.25
99	98.02	62	Firearm homicide deaths	98.52
99.23	98.32	63	Firearm homicide deaths	98.79
99.44	98.59	64	Firearm homicide deaths	99.04
99.64	98.85	65	Firearm homicide deaths	99.27
99.80	99.10	66	Firearm homicide deaths	99.48
99.95	99.32	67	Firearm homicide deaths	99.67
100	99.53	68	Firearm homicide deaths	99.84
100	99.72	69	Firearm homicide deaths	99.97
100	99.88	70	Firearm homicide deaths	100
n/a	n/a	71	Firearm homicide deaths	100
n/a	n/a	72	Firearm homicide deaths	100
n/a	n/a	73	Firearm homicide deaths	100
n/a	n/a	74	Firearm homicide deaths	100
n/a	n/a	75	Firearm homicide deaths	100
n/a	n/a	76	Firearm homicide deaths	100
n/a	n/a	77	Firearm homicide deaths	100
n/a	n/a	78	Firearm homicide deaths	100
n/a	n/a	79	Firearm homicide deaths	100
n/a	n/a	80	Firearm homicide deaths	100
n/a	n/a	81	Firearm homicide deaths	100
n/a	n/a	82	Firearm homicide deaths	100
n/a	n/a	83	Firearm homicide deaths	100
n/a	n/a	84	Firearm homicide deaths	100
n/a	n/a	85	Firearm homicide deaths	100
n/a	n/a	86	Firearm homicide deaths	100
n/a	n/a	87	Firearm homicide deaths	100
n/a	n/a	88	Firearm homicide deaths	100
n/a	n/a	89	Firearm homicide deaths	100
n/a	n/a	90	Firearm homicide deaths	100
n/a	n/a	91	Firearm homicide deaths	100
n/a	n/a	92	Firearm homicide deaths	100
n/a	n/a	93	Firearm homicide deaths	100
n/a	n/a	94	Firearm homicide deaths	100
n/a	n/a	95	Firearm homicide deaths	100
n/a	n/a	96	Firearm homicide deaths	100
n/a	n/a	97	Firearm homicide deaths	100
n/a	n/a	98	Firearm homicide deaths	100
n/a	n/a	99	Firearm homicide deaths	100
n/a	n/a	100	Firearm homicide deaths	100
n/a	n/a	0	Equal shares	0
n/a	n/a	1	Equal shares	1
n/a	n/a	2	Equal shares	2
n/a	n/a	3	Equal shares	3
n/a	n/a	4	Equal shares	4
n/a	n/a	5	Equal shares	5
n/a	n/a	6	Equal shares	6
n/a	n/a	7	Equal shares	7
n/a	n/a	8	Equal shares	8
n/a	n/a	9	Equal shares	9
n/a	n/a	10	Equal shares	10
n/a	n/a	11	Equal shares	11
n/a	n/a	12	Equal shares	12
n/a	n/a	13	Equal shares	13
n/a	n/a	14	Equal shares	14
n/a	n/a	15	Equal shares	15
n/a	n/a	16	Equal shares	16
n/a	n/a	17	Equal shares	17
n/a	n/a	18	Equal shares	18
n/a	n/a	19	Equal shares	19
n/a	n/a	20	Equal shares	20
n/a	n/a	21	Equal shares	21
n/a	n/a	22	Equal shares	22
n/a	n/a	23	Equal shares	23
n/a	n/a	24	Equal shares	24
n/a	n/a	25	Equal shares	25
n/a	n/a	26	Equal shares	26
n/a	n/a	27	Equal shares	27
n/a	n/a	28	Equal shares	28
n/a	n/a	29	Equal shares	29
n/a	n/a	30	Equal shares	30
n/a	n/a	31	Equal shares	31
n/a	n/a	32	Equal shares	32
n/a	n/a	33	Equal shares	33
n/a	n/a	34	Equal shares	34
n/a	n/a	35	Equal shares	35
n/a	n/a	36	Equal shares	36
n/a	n/a	37	Equal shares	37
n/a	n/a	38	Equal shares	38
n/a	n/a	39	Equal shares	39
n/a	n/a	40	Equal shares	40
n/a	n/a	41	Equal shares	41
n/a	n/a	42	Equal shares	42
n/a	n/a	43	Equal shares	43
n/a	n/a	44	Equal shares	44
n/a	n/a	45	Equal shares	45
n/a	n/a	46	Equal shares	46
n/a	n/a	47	Equal shares	47
n/a	n/a	48	Equal shares	48
n/a	n/a	49	Equal shares	49
n/a	n/a	50	Equal shares	50
n/a	n/a	51	Equal shares	51
n/a	n/a	52	Equal shares	52
n/a	n/a	53	Equal shares	53
n/a	n/a	54	Equal shares	54
n/a	n/a	55	Equal shares	55
n/a	n/a	56	Equal shares	56
n/a	n/a	57	Equal shares	57
n/a	n/a	58	Equal shares	58
n/a	n/a	59	Equal shares	59
n/a	n/a	60	Equal shares	60
n/a	n/a	61	Equal shares	61
n/a	n/a	62	Equal shares	62
n/a	n/a	63	Equal shares	63
n/a	n/a	64	Equal shares	64
n/a	n/a	65	Equal shares	65
n/a	n/a	66	Equal shares	66
n/a	n/a	67	Equal shares	67
n/a	n/a	68	Equal shares	68
n/a	n/a	69	Equal shares	69
n/a	n/a	70	Equal shares	70
n/a	n/a	71	Equal shares	71
n/a	n/a	72	Equal shares	72
n/a	n/a	73	Equal shares	73
n/a	n/a	74	Equal shares	74
n/a	n/a	75	Equal shares	75
n/a	n/a	76	Equal shares	76
n/a	n/a	77	Equal shares	77
n/a	n/a	78	Equal shares	78
n/a	n/a	79	Equal shares	79
n/a	n/a	80	Equal shares	80
n/a	n/a	81	Equal shares	81
n/a	n/a	82	Equal shares	82
n/a	n/a	83	Equal shares	83
n/a	n/a	84	Equal shares	84
n/a	n/a	85	Equal shares	85
n/a	n/a	86	Equal shares	86
n/a	n/a	87	Equal shares	87
n/a	n/a	88	Equal shares	88
n/a	n/a	89	Equal shares	89
n/a	n/a	90	Equal shares	90
n/a	n/a	91	Equal shares	91
n/a	n/a	92	Equal shares	92
n/a	n/a	93	Equal shares	93
n/a	n/a	94	Equal shares	94
n/a	n/a	95	Equal shares	95
n/a	n/a	96	Equal shares	96
n/a	n/a	97	Equal shares	97
n/a	n/a	98	Equal shares	98
n/a	n/a	99	Equal shares	99
n/a	n/a	100	Equal shares	100

The curve rises far above the equal-shares line: the clusters holding the highest-rate tenth of residents hold 51.3% of deaths, and 30.7% of residents live in clusters with a rate of zero. The line plots the cumulative share of deaths against the cumulative share of residents, with a 95% interval from a bootstrap over counties; the dashed line marks equal shares.Note: A cluster is a group of neighboring tracts for which CDC publishes one rate, repeated on each member tract; the median tract belongs to a cluster of 5 tracts and the largest cluster has 20. The curve counts each of the 17,814 clusters once, so its unit is the cluster, not the tract.Note: Left out: New York City, where CDC records almost no deaths in this file, and the clusters where CDC withholds the rate in at least one year from 2022 to 2024 (4.7% of residents outside New York City). The data for 2024 are provisional, and CDC withholds more rates for that year (455 clusters, against 312 in 2022). Filling the withheld years from the published count range gives between 8.9% and 10.2% of residents holding 50% of deaths.Note: Deaths are each cluster's annual rate times its residents, averaged over the three years. With the same residents on both sides they come to 78.6% of the deaths the county file implies for the same counties, so the curve describes shares and not totals. The shortfall is uneven: the clusters imply 7.3% of the county file's deaths in Essex County, New Jersey, 8.7% in Suffolk County, Massachusetts, 27.6% in San Diego County, California, and 28.1% in Santa Clara County, California, the counties where they imply under 30% of a county-file toll of at least 15 deaths a year. Dropping the clusters of those four counties moves the share holding 50% of deaths to 9.6%.Note: Intervals are 95% intervals from a bootstrap that draws whole counties with replacement (replicates and seed are in the methods note). They describe which places are in the file and do not include the modeling error in CDC's rates. Puerto Rico is absent from the tract file.Source: CDC Mapping Injury, Overdose, and Violence, tract file, firearm homicide, 2022-2024; modeled estimates for tract clusters; ACS 2019-2023 population

The interval around each share comes from resampling whole counties, so it describes which places are in the file. It leaves out the modeling error in CDC's rates. Redrawing every modeled rate from CDC's own interval, a separate check, shifts the estimate upward: the share of residents holding 50% of deaths comes out between 9.6% and 9.8%, above the estimate of 9.5% and inside the resampling interval.

Studies of crime incidents on street segments in several U.S. cities find that a small share of segments accounts for a large share of incidents, a regularity Weisburd calls the law of crime concentration.[1] Averaging over a cluster can only lower measured concentration, so the curve in Figure 1 is a lower bound for what block-level rates would show if CDC published them.

Two groups of residents are not on the curve. New York City is left out because CDC's file records almost no deaths there, and the clusters where CDC withholds the rate in at least one year from 2022 to 2024 hold 4.7% of the remaining residents. The data for 2024 are provisional, and CDC withholds more rates for that year (455 clusters, against 312 in 2022). The curve covers 308.7 million residents. Filling the withheld years from the count range CDC publishes for them puts the share of residents who hold 50% of deaths between 8.9% and 10.2%, so the exclusion does not drive the result.

The file also undercounts deaths outside New York City. With the same residents on both sides, the deaths implied by the cluster rates come to 78.6% of what the county file implies for the same counties, so the curve describes how deaths are distributed and not how many there are. The shortfall is uneven. In Essex County, New Jersey, and Suffolk County, Massachusetts, the clusters imply 7.3% and 8.7% of the county file's deaths, and in San Diego and Santa Clara counties, California, 27.6% and 28.1%. These are the counties where the clusters imply under 30% of a county-file toll of at least 15 deaths a year. Dropping their clusters moves the share holding 50% of deaths from 9.5% to 9.6%.

Counties differ in how steeply the curve bends

The same curve can be drawn inside one county. Figure 2 shows it for the 8 counties with the most implied firearm homicide deaths a year. In Cook County, 50% of deaths sit with 10.5% (95% CI 9.1% to 12.2%) of residents. The share is larger in every other county shown, and in Shelby County, Tennessee, around Memphis, it reaches 24.4% (95% CI 20.4% to 29.3%). Harris County, Texas, around Houston, comes close, and its interval overlaps Shelby's.

Figure 2

In Cook County the clusters holding 50% of firearm homicide deaths hold 10.5% of residents, against 24.4% in the county with the largest share

Cumulative share of implied firearm homicide deaths against cumulative share of residents, tract clusters ranked from the highest rate, the counties with the most implied deaths, 2022 to 2024

Cumulative share of firearm homicide deaths (%)

Cumulative share of the county's residents, clusters ranked from the highest rate (%)

Show data

Data for In Cook County the clusters holding 50% of firearm homicide deaths hold 10.5% of residents, against 24.4% in the county with the largest share
conf_high	conf_low	county	pct_residents	share_deaths
n/a	n/a	Cook County, IL	0	0
8.22	5.76	Cook County, IL	1	6.98
15.40	10.93	Cook County, IL	2	13.07
21.47	15.61	Cook County, IL	3	18.45
26.99	19.96	Cook County, IL	4	23.18
32.16	24.05	Cook County, IL	5	27.79
36.99	28.03	Cook County, IL	6	32.23
41.37	31.92	Cook County, IL	7	36.51
45.56	35.67	Cook County, IL	8	40.57
49.53	39.28	Cook County, IL	9	44.45
52.93	42.85	Cook County, IL	10	48.15
56.01	46.28	Cook County, IL	11	51.48
58.85	49.41	Cook County, IL	12	54.47
61.40	52.16	Cook County, IL	13	57.12
63.77	54.80	Cook County, IL	14	59.59
65.94	57.09	Cook County, IL	15	61.75
67.92	59.10	Cook County, IL	16	63.71
69.69	61.04	Cook County, IL	17	65.47
71.37	62.79	Cook County, IL	18	67.16
72.95	64.43	Cook County, IL	19	68.76
74.46	66.01	Cook County, IL	20	70.28
75.92	67.53	Cook County, IL	21	71.76
77.36	69.03	Cook County, IL	22	73.23
78.77	70.47	Cook County, IL	23	74.65
80.10	71.84	Cook County, IL	24	76.04
81.34	73.21	Cook County, IL	25	77.37
82.50	74.57	Cook County, IL	26	78.68
83.61	75.87	Cook County, IL	27	79.91
84.69	77.14	Cook County, IL	28	81.10
85.74	78.35	Cook County, IL	29	82.23
86.75	79.46	Cook County, IL	30	83.32
87.59	80.64	Cook County, IL	31	84.38
88.36	81.69	Cook County, IL	32	85.37
89.13	82.73	Cook County, IL	33	86.28
89.83	83.75	Cook County, IL	34	87.13
90.49	84.75	Cook County, IL	35	87.94
91.06	85.61	Cook County, IL	36	88.70
91.65	86.49	Cook County, IL	37	89.39
92.21	87.28	Cook County, IL	38	90.03
92.76	88.01	Cook County, IL	39	90.64
93.27	88.68	Cook County, IL	40	91.23
93.76	89.36	Cook County, IL	41	91.77
94.21	89.98	Cook County, IL	42	92.27
94.64	90.57	Cook County, IL	43	92.75
95.06	91.16	Cook County, IL	44	93.22
95.41	91.67	Cook County, IL	45	93.68
95.76	92.21	Cook County, IL	46	94.12
96.10	92.69	Cook County, IL	47	94.56
96.40	93.16	Cook County, IL	48	94.97
96.70	93.60	Cook County, IL	49	95.36
96.97	94.03	Cook County, IL	50	95.72
n/a	n/a	Wayne County, MI	0	0
5.45	3.32	Wayne County, MI	1	4.42
10.36	6.53	Wayne County, MI	2	8.33
15.01	9.61	Wayne County, MI	3	12.07
19.25	12.63	Wayne County, MI	4	15.75
23.38	15.57	Wayne County, MI	5	19.30
27.12	18.32	Wayne County, MI	6	22.48
30.77	21.03	Wayne County, MI	7	25.55
34.17	23.57	Wayne County, MI	8	28.45
37.52	26.02	Wayne County, MI	9	31.31
40.80	28.41	Wayne County, MI	10	34.05
43.96	30.78	Wayne County, MI	11	36.77
46.93	33.10	Wayne County, MI	12	39.48
49.86	35.42	Wayne County, MI	13	42.17
52.68	37.70	Wayne County, MI	14	44.76
55.44	39.93	Wayne County, MI	15	47.23
57.91	42.11	Wayne County, MI	16	49.67
60.30	44.21	Wayne County, MI	17	52.05
62.45	46.37	Wayne County, MI	18	54.42
64.54	48.51	Wayne County, MI	19	56.70
66.62	50.64	Wayne County, MI	20	58.95
68.77	52.64	Wayne County, MI	21	61.06
70.64	54.49	Wayne County, MI	22	63.03
72.33	56.47	Wayne County, MI	23	64.82
74.12	58.30	Wayne County, MI	24	66.54
75.73	60.19	Wayne County, MI	25	68.23
77.31	62.04	Wayne County, MI	26	69.91
78.91	63.69	Wayne County, MI	27	71.59
80.38	65.26	Wayne County, MI	28	73.26
81.69	66.93	Wayne County, MI	29	74.80
82.88	68.46	Wayne County, MI	30	76.26
83.98	69.95	Wayne County, MI	31	77.60
84.98	71.43	Wayne County, MI	32	78.85
86	72.78	Wayne County, MI	33	80.05
86.84	74.14	Wayne County, MI	34	81.21
87.63	75.47	Wayne County, MI	35	82.36
88.33	76.66	Wayne County, MI	36	83.39
88.95	77.89	Wayne County, MI	37	84.38
89.65	79.07	Wayne County, MI	38	85.31
90.30	80.17	Wayne County, MI	39	86.18
90.87	81.41	Wayne County, MI	40	87.03
91.43	82.47	Wayne County, MI	41	87.88
91.95	83.43	Wayne County, MI	42	88.60
92.46	84.37	Wayne County, MI	43	89.27
92.93	85.28	Wayne County, MI	44	89.88
93.36	86.07	Wayne County, MI	45	90.45
93.77	86.91	Wayne County, MI	46	90.98
94.19	87.69	Wayne County, MI	47	91.47
94.58	88.41	Wayne County, MI	48	91.94
94.89	89.01	Wayne County, MI	49	92.40
95.19	89.62	Wayne County, MI	50	92.85
n/a	n/a	Los Angeles County, CA	0	0
6.11	4.77	Los Angeles County, CA	1	5.48
11.12	8.79	Los Angeles County, CA	2	10.10
15.42	12.28	Los Angeles County, CA	3	13.96
19.22	15.45	Los Angeles County, CA	4	17.37
22.58	18.34	Los Angeles County, CA	5	20.47
25.66	21.06	Los Angeles County, CA	6	23.36
28.49	23.61	Los Angeles County, CA	7	26.08
31.14	26	Los Angeles County, CA	8	28.59
33.62	28.29	Los Angeles County, CA	9	30.96
35.94	30.54	Los Angeles County, CA	10	33.24
38.15	32.68	Los Angeles County, CA	11	35.44
40.28	34.78	Los Angeles County, CA	12	37.56
42.38	36.79	Los Angeles County, CA	13	39.63
44.42	38.78	Los Angeles County, CA	14	41.65
46.40	40.73	Los Angeles County, CA	15	43.59
48.34	42.57	Los Angeles County, CA	16	45.48
50.18	44.39	Los Angeles County, CA	17	47.34
52.01	46.20	Los Angeles County, CA	18	49.16
53.79	47.98	Los Angeles County, CA	19	50.90
55.54	49.70	Los Angeles County, CA	20	52.62
57.24	51.36	Los Angeles County, CA	21	54.31
58.85	53.02	Los Angeles County, CA	22	55.96
60.48	54.65	Los Angeles County, CA	23	57.59
62.06	56.25	Los Angeles County, CA	24	59.17
63.56	57.77	Los Angeles County, CA	25	60.71
65.03	59.36	Los Angeles County, CA	26	62.21
66.46	60.84	Los Angeles County, CA	27	63.67
67.87	62.26	Los Angeles County, CA	28	65.08
69.21	63.67	Los Angeles County, CA	29	66.47
70.54	65.04	Los Angeles County, CA	30	67.81
71.83	66.37	Los Angeles County, CA	31	69.11
73.12	67.68	Los Angeles County, CA	32	70.38
74.33	68.95	Los Angeles County, CA	33	71.63
75.52	70.17	Los Angeles County, CA	34	72.85
76.69	71.38	Los Angeles County, CA	35	74.04
77.82	72.57	Los Angeles County, CA	36	75.21
78.93	73.73	Los Angeles County, CA	37	76.34
79.96	74.85	Los Angeles County, CA	38	77.44
80.98	75.98	Los Angeles County, CA	39	78.51
81.99	77.09	Los Angeles County, CA	40	79.55
82.96	78.15	Los Angeles County, CA	41	80.56
83.89	79.17	Los Angeles County, CA	42	81.54
84.78	80.14	Los Angeles County, CA	43	82.50
85.65	81.10	Los Angeles County, CA	44	83.43
86.47	82.06	Los Angeles County, CA	45	84.33
87.27	82.96	Los Angeles County, CA	46	85.19
88.01	83.83	Los Angeles County, CA	47	86.02
88.70	84.69	Los Angeles County, CA	48	86.81
89.36	85.52	Los Angeles County, CA	49	87.55
89.99	86.29	Los Angeles County, CA	50	88.24
n/a	n/a	Maricopa County, AZ	0	0
5.14	3.39	Maricopa County, AZ	1	4.36
9.34	6.49	Maricopa County, AZ	2	7.95
12.92	9.36	Maricopa County, AZ	3	11.20
16.15	12.07	Maricopa County, AZ	4	14.14
19.20	14.71	Maricopa County, AZ	5	16.94
22.18	17.25	Maricopa County, AZ	6	19.62
24.99	19.73	Maricopa County, AZ	7	22.27
27.70	22.20	Maricopa County, AZ	8	24.85
30.27	24.55	Maricopa County, AZ	9	27.40
32.76	26.90	Maricopa County, AZ	10	29.87
35.28	29.17	Maricopa County, AZ	11	32.24
37.64	31.32	Maricopa County, AZ	12	34.51
39.95	33.43	Maricopa County, AZ	13	36.70
42.14	35.45	Maricopa County, AZ	14	38.81
44.20	37.44	Maricopa County, AZ	15	40.82
46.26	39.35	Maricopa County, AZ	16	42.80
48.23	41.27	Maricopa County, AZ	17	44.73
50.15	43.05	Maricopa County, AZ	18	46.59
51.93	44.73	Maricopa County, AZ	19	48.43
53.70	46.44	Maricopa County, AZ	20	50.17
55.44	48.13	Maricopa County, AZ	21	51.84
57.05	49.75	Maricopa County, AZ	22	53.42
58.70	51.29	Maricopa County, AZ	23	54.99
60.25	52.79	Maricopa County, AZ	24	56.54
61.81	54.30	Maricopa County, AZ	25	58.06
63.31	55.84	Maricopa County, AZ	26	59.54
64.80	57.25	Maricopa County, AZ	27	61.01
66.25	58.69	Maricopa County, AZ	28	62.46
67.64	60.06	Maricopa County, AZ	29	63.89
69	61.48	Maricopa County, AZ	30	65.28
70.35	62.84	Maricopa County, AZ	31	66.63
71.58	64.22	Maricopa County, AZ	32	67.96
72.79	65.48	Maricopa County, AZ	33	69.24
74.02	66.74	Maricopa County, AZ	34	70.49
75.17	68.01	Maricopa County, AZ	35	71.70
76.36	69.22	Maricopa County, AZ	36	72.87
77.52	70.39	Maricopa County, AZ	37	74.01
78.60	71.55	Maricopa County, AZ	38	75.11
79.66	72.68	Maricopa County, AZ	39	76.21
80.71	73.76	Maricopa County, AZ	40	77.27
81.73	74.88	Maricopa County, AZ	41	78.29
82.68	75.97	Maricopa County, AZ	42	79.30
83.63	76.95	Maricopa County, AZ	43	80.29
84.51	77.99	Maricopa County, AZ	44	81.24
85.36	78.99	Maricopa County, AZ	45	82.17
86.25	79.97	Maricopa County, AZ	46	83.10
87.10	80.89	Maricopa County, AZ	47	84.01
87.94	81.79	Maricopa County, AZ	48	84.89
88.67	82.69	Maricopa County, AZ	49	85.74
89.43	83.59	Maricopa County, AZ	50	86.57
n/a	n/a	Dallas County, TX	0	0
7.67	3.10	Dallas County, TX	1	5.88
13.39	6.14	Dallas County, TX	2	9.17
17.35	9.14	Dallas County, TX	3	12.39
20.46	12.12	Dallas County, TX	4	15.56
23.48	15.05	Dallas County, TX	5	18.72
26.37	17.84	Dallas County, TX	6	21.85
29.17	20.44	Dallas County, TX	7	24.80
31.64	22.77	Dallas County, TX	8	27.44
34.10	24.92	Dallas County, TX	9	29.92
36.48	27.02	Dallas County, TX	10	32.14
38.70	28.82	Dallas County, TX	11	34.22
40.78	30.57	Dallas County, TX	12	36.10
42.76	32.29	Dallas County, TX	13	37.86
44.53	33.98	Dallas County, TX	14	39.50
46.27	35.62	Dallas County, TX	15	41.06
47.84	37.20	Dallas County, TX	16	42.61
49.48	38.79	Dallas County, TX	17	44.15
50.96	40.39	Dallas County, TX	18	45.66
52.44	41.90	Dallas County, TX	19	47.17
53.87	43.41	Dallas County, TX	20	48.67
55.28	44.87	Dallas County, TX	21	50.16
56.65	46.34	Dallas County, TX	22	51.61
58.03	47.80	Dallas County, TX	23	52.99
59.41	49.19	Dallas County, TX	24	54.36
60.83	50.61	Dallas County, TX	25	55.73
62.10	52	Dallas County, TX	26	57.07
63.37	53.36	Dallas County, TX	27	58.37
64.59	54.72	Dallas County, TX	28	59.67
65.81	56.02	Dallas County, TX	29	60.96
66.97	57.32	Dallas County, TX	30	62.23
68.14	58.61	Dallas County, TX	31	63.49
69.27	59.91	Dallas County, TX	32	64.74
70.34	61.10	Dallas County, TX	33	65.98
71.45	62.36	Dallas County, TX	34	67.13
72.47	63.55	Dallas County, TX	35	68.24
73.44	64.70	Dallas County, TX	36	69.30
74.37	65.88	Dallas County, TX	37	70.36
75.32	67.02	Dallas County, TX	38	71.37
76.26	68.09	Dallas County, TX	39	72.36
77.14	69.16	Dallas County, TX	40	73.34
78.09	70.21	Dallas County, TX	41	74.28
78.96	71.17	Dallas County, TX	42	75.22
79.82	72.14	Dallas County, TX	43	76.12
80.66	73.12	Dallas County, TX	44	77.02
81.48	74.03	Dallas County, TX	45	77.90
82.28	74.95	Dallas County, TX	46	78.75
83.07	75.84	Dallas County, TX	47	79.59
83.83	76.71	Dallas County, TX	48	80.40
84.60	77.58	Dallas County, TX	49	81.20
85.35	78.42	Dallas County, TX	50	81.99
n/a	n/a	Philadelphia, PA	0	0
4.86	2.49	Philadelphia, PA	1	4.05
9.03	4.95	Philadelphia, PA	2	6.90
12.33	7.35	Philadelphia, PA	3	9.67
15.30	9.72	Philadelphia, PA	4	12.40
18.15	12.02	Philadelphia, PA	5	14.95
20.94	14.24	Philadelphia, PA	6	17.37
23.56	16.44	Philadelphia, PA	7	19.76
26.22	18.59	Philadelphia, PA	8	22.13
28.74	20.72	Philadelphia, PA	9	24.49
31.05	22.74	Philadelphia, PA	10	26.77
33.41	24.70	Philadelphia, PA	11	28.93
35.79	26.58	Philadelphia, PA	12	31.09
37.81	28.50	Philadelphia, PA	13	33.25
40.03	30.35	Philadelphia, PA	14	35.30
41.97	32.22	Philadelphia, PA	15	37.27
43.97	34	Philadelphia, PA	16	39.20
45.92	35.78	Philadelphia, PA	17	41.12
47.71	37.43	Philadelphia, PA	18	42.87
49.45	39.16	Philadelphia, PA	19	44.55
51.14	40.80	Philadelphia, PA	20	46.16
52.82	42.40	Philadelphia, PA	21	47.74
54.44	43.98	Philadelphia, PA	22	49.31
56.15	45.48	Philadelphia, PA	23	50.87
57.78	46.99	Philadelphia, PA	24	52.43
59.31	48.49	Philadelphia, PA	25	53.97
60.72	49.90	Philadelphia, PA	26	55.45
62.11	51.33	Philadelphia, PA	27	56.88
63.51	52.74	Philadelphia, PA	28	58.20
64.86	54.05	Philadelphia, PA	29	59.49
66.19	55.39	Philadelphia, PA	30	60.76
67.52	56.63	Philadelphia, PA	31	62.03
68.80	57.85	Philadelphia, PA	32	63.28
70.05	59.01	Philadelphia, PA	33	64.51
71.16	60.22	Philadelphia, PA	34	65.74
72.29	61.42	Philadelphia, PA	35	66.96
73.45	62.60	Philadelphia, PA	36	68.15
74.57	63.79	Philadelphia, PA	37	69.34
75.65	64.95	Philadelphia, PA	38	70.51
76.70	66.06	Philadelphia, PA	39	71.62
77.68	67.11	Philadelphia, PA	40	72.68
78.66	68.17	Philadelphia, PA	41	73.74
79.64	69.24	Philadelphia, PA	42	74.74
80.57	70.20	Philadelphia, PA	43	75.71
81.49	71.20	Philadelphia, PA	44	76.66
82.39	72.22	Philadelphia, PA	45	77.57
83.23	73.17	Philadelphia, PA	46	78.49
84.05	74.11	Philadelphia, PA	47	79.39
84.83	75.07	Philadelphia, PA	48	80.28
85.60	76.03	Philadelphia, PA	49	81.17
86.33	76.93	Philadelphia, PA	50	82.01
n/a	n/a	Harris County, TX	0	0
4.53	3.20	Harris County, TX	1	4.19
8.62	6.23	Harris County, TX	2	7.65
12.14	9.08	Harris County, TX	3	10.70
15.32	11.64	Harris County, TX	4	13.57
18.21	13.95	Harris County, TX	5	16.30
20.87	16.11	Harris County, TX	6	18.66
23.36	18.17	Harris County, TX	7	20.89
25.58	20.15	Harris County, TX	8	22.96
27.75	22.10	Harris County, TX	9	24.96
29.84	23.99	Harris County, TX	10	26.88
31.88	25.80	Harris County, TX	11	28.77
33.81	27.59	Harris County, TX	12	30.64
35.60	29.33	Harris County, TX	13	32.40
37.39	31.05	Harris County, TX	14	34.14
39.16	32.72	Harris County, TX	15	35.85
40.84	34.31	Harris County, TX	16	37.54
42.47	35.90	Harris County, TX	17	39.18
44.04	37.48	Harris County, TX	18	40.72
45.57	39.01	Harris County, TX	19	42.25
47.09	40.52	Harris County, TX	20	43.76
48.64	42.03	Harris County, TX	21	45.27
50.12	43.51	Harris County, TX	22	46.76
51.59	44.96	Harris County, TX	23	48.23
53.04	46.39	Harris County, TX	24	49.67
54.44	47.79	Harris County, TX	25	51.08
55.84	49.16	Harris County, TX	26	52.47
57.25	50.51	Harris County, TX	27	53.81
58.54	51.80	Harris County, TX	28	55.14
59.88	53.10	Harris County, TX	29	56.46
61.19	54.39	Harris County, TX	30	57.76
62.48	55.68	Harris County, TX	31	59.01
63.75	56.94	Harris County, TX	32	60.24
64.97	58.15	Harris County, TX	33	61.47
66.17	59.36	Harris County, TX	34	62.67
67.41	60.58	Harris County, TX	35	63.87
68.60	61.78	Harris County, TX	36	65.07
69.79	62.97	Harris County, TX	37	66.24
70.95	64.14	Harris County, TX	38	67.40
72.11	65.27	Harris County, TX	39	68.54
73.17	66.41	Harris County, TX	40	69.67
74.22	67.55	Harris County, TX	41	70.78
75.31	68.68	Harris County, TX	42	71.87
76.39	69.77	Harris County, TX	43	72.95
77.43	70.86	Harris County, TX	44	74
78.41	71.91	Harris County, TX	45	75.03
79.39	72.98	Harris County, TX	46	76.04
80.34	74	Harris County, TX	47	77.02
81.27	74.97	Harris County, TX	48	78
82.18	75.95	Harris County, TX	49	78.96
83.08	76.92	Harris County, TX	50	79.90
n/a	n/a	Shelby County, TN	0	0
3.35	2.13	Shelby County, TN	1	2.76
6.68	4.25	Shelby County, TN	2	5.52
9.65	6.32	Shelby County, TN	3	8.03
12.70	8.34	Shelby County, TN	4	10.54
15.44	10.35	Shelby County, TN	5	13.05
18.15	12.33	Shelby County, TN	6	15.41
20.72	14.28	Shelby County, TN	7	17.65
23.23	16.16	Shelby County, TN	8	19.74
25.83	18.07	Shelby County, TN	9	21.82
28.34	19.94	Shelby County, TN	10	23.88
30.73	21.73	Shelby County, TN	11	25.94
32.99	23.47	Shelby County, TN	12	27.95
35.28	25.18	Shelby County, TN	13	29.93
37.60	26.90	Shelby County, TN	14	31.91
39.58	28.63	Shelby County, TN	15	33.87
41.60	30.26	Shelby County, TN	16	35.82
43.59	31.92	Shelby County, TN	17	37.73
45.55	33.59	Shelby County, TN	18	39.54
47.46	35.22	Shelby County, TN	19	41.31
49.31	36.81	Shelby County, TN	20	43.05
51.04	38.36	Shelby County, TN	21	44.78
52.73	39.81	Shelby County, TN	22	46.34
54.49	41.28	Shelby County, TN	23	47.91
56.08	42.67	Shelby County, TN	24	49.44
57.73	44.14	Shelby County, TN	25	50.96
59.35	45.53	Shelby County, TN	26	52.36
60.91	46.94	Shelby County, TN	27	53.75
62.40	48.26	Shelby County, TN	28	55.14
63.91	49.58	Shelby County, TN	29	56.48
65.29	50.86	Shelby County, TN	30	57.81
66.75	52.10	Shelby County, TN	31	59.13
68.12	53.35	Shelby County, TN	32	60.45
69.48	54.60	Shelby County, TN	33	61.75
70.76	55.83	Shelby County, TN	34	63.03
72.05	57.05	Shelby County, TN	35	64.32
73.29	58.24	Shelby County, TN	36	65.58
74.51	59.41	Shelby County, TN	37	66.83
75.68	60.54	Shelby County, TN	38	67.99
76.80	61.74	Shelby County, TN	39	69.15
78.05	62.78	Shelby County, TN	40	70.29
79.14	63.88	Shelby County, TN	41	71.42
80.16	65.08	Shelby County, TN	42	72.47
81.19	66.11	Shelby County, TN	43	73.53
82.23	67.14	Shelby County, TN	44	74.58
83.24	68.27	Shelby County, TN	45	75.63
84.18	69.31	Shelby County, TN	46	76.67
85.11	70.40	Shelby County, TN	47	77.70
85.94	71.36	Shelby County, TN	48	78.69
86.79	72.37	Shelby County, TN	49	79.66
87.66	73.37	Shelby County, TN	50	80.63

Cook County's curve bends hardest, and the curves for Harris and Shelby counties bend least. Each line plots one county's cumulative share of deaths against its cumulative share of residents, tract clusters ranked by mean annual rate; the horizontal axis stops at 50% of each county's residents, where the curves have reached between 79.9% and 95.7% of deaths.Note: The 8 counties are those with the most implied firearm homicide deaths a year in the cluster file; New York City is left out. A cluster that crosses a county line counts in each county with only the residents who live there.Note: The unit is the tract cluster, a group of neighboring tracts with one CDC rate. In every county shown at least 80.2% of residents live in a cluster with a rate in every year from 2022 to 2024, and 87.7% do in Cook County; the others are left out.Note: Each curve carries a 95% interval from a bootstrap that draws clusters within the county with replacement (replicates and seed are in the methods note); the intervals are in the tooltip and the data table. A county line cuts through metropolitan areas, so a county that includes suburbs holds more low-rate residents than one that does not.Source: CDC Mapping Injury, Overdose, and Violence, tract file, firearm homicide, 2022-2024; modeled estimates for tract clusters; ACS 2019-2023 population

Each curve rests on the clusters with a rate in every year from 2022 to 2024, which is at least 80.2% of residents in every county shown and 87.7% in Cook County. A county line is not a neighborhood boundary. A county that includes a low-rate suburban ring holds more residents at the low end of the curve than a county whose line follows the city limits, so a comparison of the curves compares county definitions as well as places.

Chicago, cluster by cluster

Figure 3 maps the clusters of Cook County, with each tract carrying its cluster's rate. Of the 1,163 tracts with a rate in every year from 2022 to 2024, 24.2% sit in clusters with no recorded firearm homicide, and the highest cluster rate is 89 deaths per hundred thousand residents a year. Of the residents in the highest-rate tenth of clusters, 90.8% live in tracts south of the Loop, judged by tract centroid, and the tracts well north of the Loop sit at the low end of the rate range. The remaining 168 tracts are gray because CDC withholds the rate in at least one year or because no one lives there.

Figure 3

In Cook County, 24.2% of tracts with an estimate sit in clusters with no recorded firearm homicide, while the highest cluster rate reaches 89 per hundred thousand residents

Mean firearm homicide rate per 100,000 residents, 2022 to 2024, of the tract cluster each Cook County tract belongs to

Loading tract outlines

Firearm homicide deaths per 100,000 residents per year, 2022 to 2024

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Select a class to show only those places.

Find a tract

Hover or tap a tract for its value, or search by name. Zoom with the buttons on the map, then drag to move it.

Clusters at the high end of the key lie south of the Loop, where 90.8% of the residents in the highest-rate tenth live by tract centroid, and the tracts well north of the Loop sit at the low end of the key; gray tracts have no stable estimate. Each tract takes the rate of its cluster, so neighbors in one cluster share a shade; the tooltip gives the cluster size, life expectancy and deprivation rank.Note: The unit of this map is the tract cluster. CDC publishes one rate for each group of neighboring tracts (the median tract sits in a cluster of 5) and the file repeats it on every member tract, so a shade covers a cluster and the map does not describe single tracts. 1,163 tracts are shaded and 168 are gray.Note: A cluster-year with 1 to 9 deaths gets a CDC modeled estimate, one with no deaths a rate of zero from a count of zero, and one with 10 or more deaths a direct rate. A mean rate is shown only when CDC publishes a rate in each of 2022, 2023 and 2024, and the data for 2024 are provisional. The highest cluster rate is an average over several tracts, so a single block can run higher.Note: Life expectancy is the USALEEP estimate for deaths in 2010 to 2015, area-weighted onto 2020 tracts, with institutional tracts left blank; the deprivation rank is the 2023 national percentile, 1 least and 100 most deprived.Source: CDC Mapping Injury, Overdose, and Violence, tract file, firearm homicide, 2022-2024; modeled estimates for tract clusters; USALEEP 2010-2015; ADI 2023

A cluster's rate averages over several tracts and over the years 2022 to 2024, so the highest figure on the map is a floor for the rate on the worst blocks and not a ceiling. The map describes clusters, and nothing on it describes a person who lives in one.

The highest-rate tenths of Cook County are also its most deprived and shortest-lived

Rank Cook County residents by the firearm homicide rate of their cluster and cut the ranking into tenths (Figure 4). Clusters with no recorded deaths hold 27.0% (95% CI 22.1% to 32.2%) of the 87.7% of residents who live in clusters with a rate in every year from 2022 to 2024, so the lowest two tenths and part of the third all have a rate of zero and are ordered at random. The highest tenth lives in clusters with a mean rate of 60 (95% CI 56 to 65) deaths per hundred thousand residents a year and a mean Area Deprivation Index national rank of 74 (95% CI 71 to 78), on a scale where the highest rank is the most deprived. Life expectancy at birth for deaths in 2010 to 2015 is 71.7 (95% CI 71.0 to 72.4) years in that tenth and 81.2 (95% CI 80.7 to 81.7) years in the clusters with no recorded deaths, a gap of 9.5 (95% CI 8.6 to 10.4) years within one county. The ninth tenth sits with the tenth: its life expectancy and its deprivation rank both lie beyond the intervals of the other eight tenths.

Figure 4

In Cook County, residents of the highest-rate tenth of clusters have a life expectancy of 71.7 years (deaths in 2010 to 2015), 9.5 fewer than residents of clusters with no recorded deaths

Cook County residents in tenths by the firearm homicide rate of their tract cluster, 2022 to 2024: the rate, life expectancy at birth for deaths in 2010 to 2015, and the Area Deprivation Index

The highest tenth of Cook County residents lives in clusters with a rate of 60 per hundred thousand residents

Mean firearm homicide deaths per 100,000 residents a year, 2022 to 2024, by tenth of residents

Firearm homicide deaths per 100,000 residents per year

Tenth of Cook County residents, clusters ranked by firearm homicide rate (1 lowest, 10 highest)

The bars are zero for the lowest two tenths and climb to the highest tenth, whose interval lies above that of the ninth. Each bar is the population-weighted mean of cluster rates with a 95% interval.

Show data

Data for In Cook County, residents of the highest-rate tenth of clusters have a life expectancy of 71.7 years (deaths in 2010 to 2015), 9.5 fewer than residents of clusters with no recorded deaths, Firearm homicide rate
conf_high	conf_low	estimate	n_units	tenth
n/a	n/a	0	30	1
n/a	n/a	0	30	2
0.490	0.110	0.300	27	3
2.13	1.85	1.99	27	4
3.25	2.87	3.05	27	5
5.83	5.30	5.57	26	6
10.65	9.18	9.91	30	7
17.03	15.55	16.29	25	8
30.45	25.20	27.75	31	9
65.05	55.83	60.03	26	10

As the homicide rate rises across the tenths, life expectancy falls and the deprivation rank rises, and the two highest tenths stand apart from the other eight on both. The tabs plot the population-weighted mean of tract values within each tenth with 95% intervals from a bootstrap over clusters.Note: The unit is the tract cluster. CDC publishes one rate for each group of neighboring tracts, and tracts inherit it. Tenths hold equal numbers of residents among the 87.7% of Cook County residents who live in clusters with a rate in every year from 2022 to 2024. Clusters with zero recorded deaths hold 27.0% of those residents and fill the lowest two tenths and part of the third, ordered among themselves at random with the book's fixed seed, so the first three tenths differ only in who lives there.Note: The tenths are formed on the rate itself, so the first tab shows how far apart the groups were sorted. Life expectancy is the USALEEP estimate for deaths in 2010 to 2015, area-weighted onto 2020 tracts, with institutional tracts left out; the rates are for 2022 to 2024.Note: Intervals are 95% intervals from a bootstrap that draws clusters with replacement (replicates and seed are in the methods note).Source: CDC Mapping Injury, Overdose, and Violence, tract file, firearm homicide, 2022-2024; modeled estimates for tract clusters; USALEEP 2010-2015; ADI 2023; population-weighted

The life expectancy estimates come from USALEEP and cover deaths in 2010 to 2015, a decade before the firearm homicide rates. The comparison shows that the same places have high homicide rates and short lives. It does not say how much of the gap firearm homicide accounts for, and it describes places, not people. The tenths are formed on the rate itself, so the first tab shows how far apart the groups were sorted, and the other two tabs carry the information. The gradient of life expectancy across deprivation deciles for the whole country is in Chapter 6.1, Place and the length of a life, and a national version of this comparison is planned in Chapter 6.5, Violence and the life-expectancy gap.

Premature mortality rises with county deprivation

Firearm homicide is one of several ways to die young, and the others follow deprivation as well. County Health Rankings reports age-adjusted deaths of residents before age 75, pooled over 2019 to 2021 from National Center for Health Statistics records. Ranking counties by their Area Deprivation Index, the least deprived tenth of counties has 307 (95% CI 296 to 318) premature deaths per hundred thousand residents and the most deprived tenth has 701 (95% CI 660 to 740). Across 3,083 counties, the population-weighted correlation between county deprivation and premature mortality is +0.78 (95% CI 0.74 to 0.83).

Figure 5

Premature mortality rises from 307 to 701 per hundred thousand residents across deciles of county deprivation

Population-weighted mean age-adjusted deaths before age 75 per 100,000 residents, by decile of the county Area Deprivation Index, counties, County Health Rankings 2024 release

Premature deaths per 100,000 residents, age-adjusted

Show data

Data for Premature mortality rises from 307 to 701 per hundred thousand residents across deciles of county deprivation
conf_high	conf_low	decile	estimate	n_units
317.6	296.1	1	306.9	308
387.5	356.6	2	372.7	308
438.9	399.7	3	417.1	308
493.3	439.2	4	465.4	309
510.6	465.7	5	490.1	308
536.2	483.2	6	505.8	308
563.4	502	7	531.3	309
588.4	508.8	8	543.4	308
631.6	568.9	9	604	307
739.9	659.7	10	701.1	310

The estimate is higher in each decile than in the one before it, and the intervals separate the first decile from the second and the ninth from the tenth while those in the middle of the range overlap. The line plots the population-weighted mean of county rates in each decile with a 95% interval from a bootstrap over states; the correlation across counties is +0.78.Note: Counties are ranked by the population-weighted mean of their tract Area Deprivation Index ranks and split into ten groups with equal numbers of counties; the means are weighted by county population. 3,083 counties have both a rate and a rank; County Health Rankings leaves out a county with fewer than 20 premature deaths in the window. Puerto Rico is not in County Health Rankings and is not drawn.Note: The band is a 95% interval for the mean, from a bootstrap that draws whole states with replacement (replicates and seed are in the methods note); it is not the spread of counties within a decile. The rate is County Health Rankings premature age-adjusted mortality, deaths of residents under 75 per hundred thousand, pooled over 2019 to 2021.Source: County Health Rankings 2024 release, NCHS death counts 2019-2021, age-adjusted rates from full counts, population-weighted; Area Deprivation Index 2023

County Health Rankings is a different source from the CDC panel, at a coarser grain. Its rates are counts of deaths pooled over several years, and a county with fewer than 10 deaths from a cause in the window gets no rate (20 for premature mortality). A missing rate means too few deaths to report, not a rate of zero. Chapter 10.5, Suppressed counties in death data covers what that does to death data.

The mix of deaths differs between the least and most deprived fifths

Take four kinds of death: drug overdose, suicide, homicide and motor-vehicle crashes. Adding their crude rates, which are deaths per hundred thousand residents with no age adjustment, gives a toll for a group of counties, and each kind's share of that toll is its place in the mix. The four overlap a little, because a suicide by drug poisoning is counted as both an overdose and a suicide, so the toll includes such a death in both of those shares. The 1,248 counties that publish all four rates hold 89.6% of county residents, and Figure 6 sorts them into fifths of residents by county deprivation.

The toll is larger in the most deprived fifth than in the least deprived, 76 (95% CI 69 to 84) deaths per hundred thousand residents against 42 (95% CI 37 to 47), and the mix differs between those end fifths. Overdose is 51.0% (95% CI 46.9% to 57.6%) of the toll in the least deprived fifth and 43.6% (95% CI 38.4% to 48.2%) in the most deprived, a change of −7.4 percentage points (95% CI −15.5 percentage points to −1.3 percentage points). Homicide rises from 8.8% (95% CI 5.9% to 10.2%) to 13.1% (95% CI 11.7% to 14.7%) of the toll (+4.3 percentage points (95% CI 2.2 percentage points to 7.5 percentage points)) and motor-vehicle crashes from 16.0% (95% CI 12.6% to 17.9%) to 21.4% (95% CI 18.4% to 24.6%) (+5.4 percentage points (95% CI 1.8 percentage points to 10.5 percentage points)). Suicide holds a similar share in the end fifths, 24.2% (95% CI 21.6% to 29.5%) and 21.9% (95% CI 20.1% to 23.9%). The figure also shows the fifths in between, and the overdose and motor-vehicle shares do not follow a steady line across all five, so it supports a comparison of the two ends and no more.

Figure 6

Overdose is 51.0% of the four-cause toll in the least deprived fifth of residents and 43.6% in the most, while motor-vehicle crashes go from 16.0% to 21.4%

Each kind of death's share of the sum of four crude death rates (overdose, suicide, homicide, motor-vehicle crash), by fifth of residents ranked by county deprivation, counties with all four rates published

Fifth of residents by county deprivation

Show data

Data for Overdose is 51.0% of the four-cause toll in the least deprived fifth of residents and 43.6% in the most, while motor-vehicle crashes go from 16.0% to 21.4%
cause	conf_high	conf_low	n_units	quintile	rate	share
Drug overdose	57.56	46.95	71	1 (least deprived)	21.58	50.97
Suicide	29.49	21.62	71	1 (least deprived)	10.23	24.16
Homicide	10.21	5.90	71	1 (least deprived)	3.74	8.83
Motor-vehicle crash	17.93	12.58	71	1 (least deprived)	6.79	16.03
Drug overdose	51.82	43.30	117	2	24.84	47.08
Suicide	28.86	22.59	117	2	13.46	25.51
Homicide	10.24	7.57	117	2	4.78	9.06
Motor-vehicle crash	20.68	15.55	117	2	9.68	18.35
Drug overdose	50.35	42.32	189	3	27.79	46.56
Suicide	27.08	21.39	189	3	14.26	23.88
Homicide	13.28	8.39	189	3	6.31	10.58
Motor-vehicle crash	21.38	16.21	189	3	11.32	18.97
Drug overdose	52.09	42.41	253	4	32.31	47.43
Suicide	24.50	20.81	253	4	15.36	22.54
Homicide	13.37	9.49	253	4	7.85	11.53
Motor-vehicle crash	20.92	15.90	253	4	12.60	18.50
Drug overdose	48.22	38.43	618	5 (most deprived)	33.30	43.58
Suicide	23.85	20.06	618	5 (most deprived)	16.71	21.87
Homicide	14.67	11.67	618	5 (most deprived)	10.05	13.15
Motor-vehicle crash	24.65	18.44	618	5 (most deprived)	16.36	21.41

The overdose share is smaller, and the homicide and motor-vehicle shares are larger, in the most deprived fifth than in the least deprived fifth, and the total toll is larger too. Each bar covers one group of residents ranked by county deprivation; segments are population-weighted mean rates as a share of the four-cause total, with 95% intervals in the tooltip.Note: Only counties with all four rates published enter (1,248 counties, 89.6% of county residents): County Health Rankings leaves a county out of a cause when it has fewer than 10 deaths in the window, so small counties are missing and a missing rate means too few deaths, not zero. Fifths hold equal numbers of residents, not counties.Note: The four rates are crude, so they are comparable with one another, and they overlap a little: a suicide by drug poisoning counts as both an overdose and a suicide. Firearm deaths are left out because they sit inside suicide and homicide, and child mortality has a different denominator. The windows differ by cause (overdose 2019 to 2021, suicide 2017 to 2021, homicide and motor-vehicle crashes 2015 to 2021). Overdose appears in this chapter only in this mix, the leading-kind map and a cross-check against the CDC panel; the overdose maps, gradients and trend are in the chapters on overdose, alcohol and suicide and on mortality trends.Note: Shares are the cause's population-weighted mean rate divided by the sum of the four means, with 95% intervals from a bootstrap that draws whole states with replacement (replicates and seed are in the methods note). The total toll is 42 per hundred thousand in the least deprived fifth and 76 in the most.Source: County Health Rankings 2024 release, NCHS death counts 2015-2021 in windows that differ by cause, crude rates from full counts, population-weighted; Area Deprivation Index 2023

The rates cover different windows: 2019 to 2021 for overdose, 2017 to 2021 for suicide, and 2015 to 2021 for homicide and motor-vehicle crashes. The mix therefore compares rates measured over different spans, and counties with few deaths have noisy rates. Overdose enters this chapter only in this mix, in the map of the highest-rate kind of death and in a cross-check against the CDC panel. The overdose maps and gradients are in Chapter 6.3, Overdose, alcohol and suicide, and the overdose trend since 2018 is in Chapter 6.4, Mortality trends, 2018 to 2024.

Figure 7 correlates seven County Health Rankings measures with county deprivation and with the rural share of residents. The first two views weight counties by population and the last two count every county once. Weighted by population, all seven correlations with deprivation are positive. The largest are for premature mortality, child mortality and motor-vehicle crashes, and the interval excludes zero for every measure except the share of crash deaths that involve alcohol. The homicide rate has a correlation of +0.41 (95% CI 0.34 to 0.48) with county deprivation, and +0.49 (95% CI 0.42 to 0.55) when every county counts once.

Figure 7

Homicide and other causes of early death are higher in more deprived counties, with a population-weighted correlation of +0.41 for homicide

Correlation across counties of each death measure with the county Area Deprivation Index and with the rural share of residents, weighted by county population or counting every county once, County Health Rankings 2024 release

Show data

Data for Homicide and other causes of early death are higher in more deprived counties, with a population-weighted correlation of +0.41 for homicide
conf_high	conf_low	estimate	group	measure	n_units	view	weighting
0.584	0.281	0.464	Suicide (age-adjusted rate)	Suicide (age-adjusted rate)	2,427	deprivation	population-weighted
0.317	0.098	0.207	Suicide (age-adjusted rate)	Suicide (age-adjusted rate)	2,427	deprivation	unweighted
0.604	0.446	0.527	Suicide (age-adjusted rate)	Suicide (age-adjusted rate)	2,427	rural	population-weighted
0.438	0.323	0.374	Suicide (age-adjusted rate)	Suicide (age-adjusted rate)	2,427	rural	unweighted
0.225	−0.105	0.083	Alcohol-impaired driving (share of crash deaths)	Alcohol-impaired driving (share of crash deaths)	3,102	deprivation	population-weighted
0.005	−0.131	−0.062	Alcohol-impaired driving (share of crash deaths)	Alcohol-impaired driving (share of crash deaths)	3,102	deprivation	unweighted
0.221	−0.029	0.104	Alcohol-impaired driving (share of crash deaths)	Alcohol-impaired driving (share of crash deaths)	3,116	rural	population-weighted
0.099	−0.029	0.032	Alcohol-impaired driving (share of crash deaths)	Alcohol-impaired driving (share of crash deaths)	3,116	rural	unweighted
0.677	0.478	0.600	Firearm death, any intent (crude rate)	Firearm death, any intent (crude rate)	2,279	deprivation	population-weighted
0.516	0.325	0.423	Firearm death, any intent (crude rate)	Firearm death, any intent (crude rate)	2,279	deprivation	unweighted
0.367	0.129	0.265	Firearm death, any intent (crude rate)	Firearm death, any intent (crude rate)	2,279	rural	population-weighted
0.425	0.294	0.359	Firearm death, any intent (crude rate)	Firearm death, any intent (crude rate)	2,279	rural	unweighted
0.482	0.342	0.413	Homicide (crude rate)	Homicide (crude rate)	1,376	deprivation	population-weighted
0.554	0.415	0.490	Homicide (crude rate)	Homicide (crude rate)	1,376	deprivation	unweighted
0.053	−0.175	−0.055	Homicide (crude rate)	Homicide (crude rate)	1,376	rural	population-weighted
0.345	0.121	0.246	Homicide (crude rate)	Homicide (crude rate)	1,376	rural	unweighted
0.705	0.562	0.624	Motor-vehicle crash (crude rate)	Motor-vehicle crash (crude rate)	2,688	deprivation	population-weighted
0.621	0.494	0.556	Motor-vehicle crash (crude rate)	Motor-vehicle crash (crude rate)	2,688	deprivation	unweighted
0.718	0.585	0.655	Motor-vehicle crash (crude rate)	Motor-vehicle crash (crude rate)	2,688	rural	population-weighted
0.643	0.566	0.602	Motor-vehicle crash (crude rate)	Motor-vehicle crash (crude rate)	2,688	rural	unweighted
0.756	0.602	0.693	Child mortality (crude rate)	Child mortality (crude rate)	2,038	deprivation	population-weighted
0.610	0.499	0.552	Child mortality (crude rate)	Child mortality (crude rate)	2,038	deprivation	unweighted
0.419	0.201	0.324	Child mortality (crude rate)	Child mortality (crude rate)	2,038	rural	population-weighted
0.489	0.352	0.423	Child mortality (crude rate)	Child mortality (crude rate)	2,038	rural	unweighted
0.827	0.737	0.781	Premature mortality (age-adjusted rate)	Premature mortality (age-adjusted rate)	3,083	deprivation	population-weighted
0.722	0.574	0.644	Premature mortality (age-adjusted rate)	Premature mortality (age-adjusted rate)	3,083	deprivation	unweighted
0.495	0.317	0.417	Premature mortality (age-adjusted rate)	Premature mortality (age-adjusted rate)	3,088	rural	population-weighted
0.327	0.183	0.251	Premature mortality (age-adjusted rate)	Premature mortality (age-adjusted rate)	3,088	rural	unweighted

Weighted by population, every estimate against deprivation is positive, and premature mortality, child mortality and motor-vehicle crashes sit farthest right; the interval for the alcohol-impaired driving share spans zero. Each dot is a correlation across counties with a 95% interval from a bootstrap over states. The other views show the rural share and the same correlations counting every county once.Note: Each correlation uses the counties with a published rate for that measure (County Health Rankings leaves out a county with fewer than 10 deaths in the window, 20 for premature mortality), so the counties differ across rows and the number is in the tooltip. The 1,376 counties with a homicide rate are less rural than counties as a whole (43.3% against 64.1% mean rural share), because a county with few homicides gets no rate, so the homicide rows describe the counties that report and not all counties. Alcohol-impaired driving is a share of motor-vehicle crash deaths, not a rate per resident. Correlations across counties describe places, not people.Note: Intervals are 95% intervals from a bootstrap that draws whole states with replacement (replicates and seed are in the methods note). Rural share is the County Health Rankings measure of the share of residents living outside urban areas. County deprivation and rural share correlate at +0.56 across counties, weighted by population.Source: County Health Rankings 2024 release, NCHS death counts 2015-2021 in windows that differ by cause, crude rates for four measures, age-adjusted rates for two and a share of crash deaths for one, from full counts, population-weighted or unweighted as each view states; Area Deprivation Index 2023

On the rural-share views, suicide and motor-vehicle death rates are higher where more residents live outside urban areas. The population-weighted correlations are +0.53 (95% CI 0.45 to 0.60) and +0.66 (95% CI 0.58 to 0.72), and the unweighted ones are +0.37 (95% CI 0.32 to 0.44) and +0.60 (95% CI 0.57 to 0.64). The homicide estimate depends on the weighting: −0.05 (95% CI −0.18 to 0.05) weighted by population and +0.25 (95% CI 0.12 to 0.35) counting every county once.

Which counties enter matters for homicide. Only the 1,376 counties with enough homicides to publish a rate are in, and a county with few homicides gets none, so these counties are less rural than counties as a whole, with a mean rural share of 43.3% against 64.1%. County deprivation and rural share are themselves correlated (+0.56 (95% CI 0.48 to 0.63)), so the deprivation and rural-share views overlap. Among the counties that report, the homicide rate is near zero against rural share when large counties dominate and modestly positive when every county counts equally. Neither estimate describes all counties, because the counties missing from the sample are the ones with the fewest homicides.

Homicide and suicide rates differ by race in opposite directions

County Health Rankings also publishes rates for Black and white residents, neither group including anyone who identifies as Hispanic, in counties where a group has enough deaths to report. These are county rates averaged over the counties that report, and they are not national rates by race. County Health Rankings publishes the homicide rate as a crude rate and the suicide rate as an age-adjusted rate, so the homicide ratio below also carries any difference in age structure between the two groups. In the 486 counties that report both groups, the homicide rate is 27.3 (95% CI 23.8 to 31.8) deaths per hundred thousand Black residents and 2.8 (95% CI 2.5 to 3.2) per hundred thousand white residents, a ratio of 9.6 (95% CI 8.1 to 11.6). The suicide rate runs the other way: 16.4 (95% CI 14.8 to 18.0) for white residents and 7.8 (95% CI 7.1 to 8.5) for Black residents in the 297 counties that report both, a ratio of 2.1 (95% CI 1.9 to 2.3).

A county reports a group's rate only when the group has enough deaths, so the reporting counties are larger and less rural than the rest, and each comparison is between groups in the same counties. The ratio describes those counties. It leaves out Black residents of counties with too few deaths to report, and it says nothing about the risk to any one person.

The kind of death with the highest rate differs by county

Figure 8 labels each county by whichever of the four kinds of death has the highest crude rate there. Among the 1,248 counties that publish all four rates, overdose is highest in 829, suicide in 207, motor-vehicle crashes in 201 and homicide in 11. The gray counties lack at least one rate and are mostly small, so the map speaks for the labeled counties, which hold 89.6% of county residents, and not for the land they sit on.

Figure 8

Overdose has the highest rate of the four causes in 829 of 1,248 counties, and homicide in only 11

Kind of death with the highest crude death rate among overdose, suicide, homicide and motor-vehicle crash, counties with all four rates published, County Health Rankings 2024 release

Loading county values

Cause with the highest rate

No data (3,143 counties)

Select a class to show only those places.

Find a county

Hover or tap a county for its value, or search by name. Zoom with the buttons on the map, then drag to move it.

Overdose leads in most of the mapped counties, suicide in 207 and motor-vehicle crashes in 201, and homicide leads in a short run of Southern counties. Each county takes the color of the cause with the highest rate; gray counties lack at least one of the four rates, and the tooltip gives the four rates.Note: Gray means at least one of the four rates is missing. County Health Rankings leaves out a county's rate when it has fewer than 10 deaths from that cause in the window, so a missing rate means too few deaths, not zero, and the gray counties are mostly small ones. The map answers only for the 1,248 counties with all four rates, which hold 89.6% of county residents.Note: Counties are compared on rates computed over windows of different lengths (overdose 2019 to 2021, suicide 2017 to 2021, homicide and motor-vehicle crashes 2015 to 2021), and small counties have noisy rates, so a label in a county with few deaths can change with one year of data. Puerto Rico is not on the map. Connecticut is drawn as its eight legacy counties.Source: County Health Rankings 2024 release, NCHS death counts 2015-2021 in windows that differ by cause, crude rates from full counts

The counties where homicide is highest are Dallas and Montgomery in Alabama; Crittenden, Jefferson and Mississippi in Arkansas; Bibb and Muscogee in Georgia; Caddo Parish in Louisiana; and Adams, Hinds and Yazoo in Mississippi. Non-Hispanic Black residents are a median 56.1% of residents in these counties and 7.1% across the labeled counties, which fits the racial gap in homicide rates above. The comparison describes county populations and says nothing about any individual.

County Health Rankings and the CDC injury panel both draw on the nation's death certificates, so their agreement checks the processing and not the underlying counts. Population-weighted correlations between the two county rates, with the panel's modeled estimate for 2021, run from +0.87 (95% CI 0.83 to 0.90) for suicide to +0.95 (95% CI 0.94 to 0.96) for drug overdose, which measures agreement between the two sources and not a gradient. Counting every county once, the suicide correlation falls to +0.64 (95% CI 0.58 to 0.71), so the agreement is lower when small counties count equally.

What place-based evidence shows

Concentration makes it possible to aim programs at the places where violence is highest, and evaluations of such programs differ in design. A meta-analysis of quasi-experimental evaluations of focused deterrence, which pairs a warning to the people most involved in violence with offers of services, finds a moderate average reduction in crime in treated areas, with smaller estimates in evaluations that use stronger designs.[2] The evaluation of CeaseFire in Chicago compared most program sites with matched comparison areas and found shooting hot spots shrinking at most sites, with the decrease linked to the program at some of them.[3] Both designs compare treated areas with areas that were not assigned at random. A systematic review of Cure Violence evaluations, written by staff of Cure Violence Global who note that this presents a bias, reports reductions in most findings but statistical significance in a minority, with results that differ by site.[4]

The box below reports a trial in which assignment was random.

Causal evidenceCluster randomized controlled trial

A randomized test of remediating vacant lots

In Philadelphia, Branas and colleagues randomly assigned vacant lots, grouped into clusters of neighboring lots, to remediation (cleaning, grading, planting grass and trees, and low fencing), to trash cleanup only, or to no treatment. Because assignment was random, differences in outcomes between treated and untreated clusters can be attributed to the treatment and not to which neighborhoods were treated. Police-reported gun assaults fell around treated lots compared with untreated lots, with the clearest reductions in neighborhoods below the poverty line, and residents near treated lots reported feeling safer.[5] The reduction across all neighborhoods was smaller.

The trial tested a low-cost change to the built environment and not a violence prevention program, in one city. It does not show that the same change would lower gun violence elsewhere, or that any program aimed at concentrated violence works.

What these data cannot show

The firearm homicide figures describe tract clusters, and CDC's rates for them are modeled estimates, so they say nothing about single tracts, blocks or people. The curves and the Cook County map average over clusters of neighboring tracts, which lowers measured concentration, and the cluster file's implied deaths fall short of the county file's, so the figures describe shares and not totals. New York City is absent, four more counties have clusters that imply a small share of the county file's deaths, and the clusters where CDC withholds a rate are left out, with more withheld for the provisional year 2024. The fill check bounds the last exclusion and cannot remove it.

Every comparison across places is ecological. The life expectancy of Cook County's highest-rate tenth comes from deaths in 2010 to 2015 and the rates from 2022 to 2024, so the data cannot say whether firearm homicide shortened these lives or whether the same conditions underlie both. County gradients and correlations describe counties, and the homicide and rural-share correlation differs with the weighting and depends on which counties report, so a correlation across counties says little about the people in them. The Area Deprivation Index understates deprivation in high-cost cities, and it is built from survey measures that overlap with several outcome measures.

County Health Rankings leaves out counties with few deaths, so the mix of deaths and the map of the highest-rate kind speak for the larger counties. The rates in those two figures are crude, so a county with an older population has a higher rate for the same risk, and the correlation figure mixes crude and age-adjusted measures, which its row labels state. The race-specific rates are a composite of reporting counties and not national rates, and the cross-check against the injury panel compares two compilations of the same death records. Outside the box above, nothing in this chapter supports a claim about what changes violence.

Data sources

CDC injury and violence mappingCDC firearm homicide rates for tract clusters, 2022 to 2024 (modeled estimates for 1 to 9 deaths, zero for none, direct rates for 10 or more), and the county file, 2021 to 2024Years: 2019-2024 for counties, 2022-2024 for tracts (data as of 2026-05-14) · Weights: ACS 2019-2023 residents of each cluster · License: Public domain (CDC, U.S. Department of Health and Human Services)
American Community SurveyTotal population of 2020 tracts, 2019-2023Years: 2019-2023 (5-year) · Weights: none (full count) · License: Public domain (U.S. Census Bureau)
USALEEP life expectancyLife expectancy at birth by tract, deaths in 2010 to 2015, 2020 tractsYears: 2010-2015 · Weights: 2020 tract population · License: Public domain (NCHS, CDC)
Area Deprivation IndexArea Deprivation Index national rank, 2023, tracts rolled up to countiesYears: 2023 release (version 4.0.1; built on ACS 2019-2023) · Weights: 2019-2023 tract population · License: Free for non-commercial use; cite the Neighborhood Atlas and Kind and Buckingham
County Health RankingsCounty death rates for premature mortality (age-adjusted), suicide (crude and age-adjusted), overdose, homicide, motor-vehicle crashes and firearms (crude), 2024 release, with race-specific homicide and suicide rates and rural shareYears: 2024 release · Weights: county population · License: CC BY 4.0 (University of Wisconsin Population Health Institute)

All data sources

Methods

The first four figures describe tract clusters, the unit in which CDC publishes neighborhood firearm homicide rates, using modeled rates averaged over 2022, 2023 and 2024; each cluster's rate is repeated on its member tracts, and New York City is left out. The last four describe counties, using County Health Rankings death rates pooled over windows that end in 2021 and differ by cause, so the mix of deaths compares rates measured over different spans, and a county with too few deaths has no rate. Life expectancy covers deaths in 2010 to 2015, earlier than the rates it is compared with. Every comparison describes places and not people.

Which clusters and years enter the concentration curves

Firearm homicide rates come from the CDC injury and violence tract file, which publishes one rate for each cluster of neighboring tracts (the median tract sits in a cluster of 5) and repeats it on every member tract.

The chapter works on clusters: it keeps one row per cluster, sets a cluster's population to the sum of its tracts' 2019-2023 American Community Survey population, and averages the annual rates for 2022, 2023 and 2024.

A cluster enters only if CDC publishes a rate in all three years; New York City, where the file records almost no deaths, is left out, and a sensitivity check drops the clusters of the counties where the cluster rates imply under 30% of the county file's deaths.

Figures explained here: Figure 1, Figure 2 and Figure 3

How implied deaths and the curves are computed

Implied deaths are the rate times the cluster's residents. Clusters are ranked from the highest rate and the curve accumulates residents and implied deaths.

Figures explained here: Figure 1, Figure 2 and Figure 4

Where the county death rates come from

County Health Rankings rates are deaths per 100,000 from National Center for Health Statistics records, pooled over windows that end in 2021 and differ by cause (2019 to 2021 for overdose and premature mortality, 2017 to 2021 for suicide, 2015 to 2021 for homicide and motor-vehicle crashes); premature mortality and suicide are age-adjusted, and the overdose, homicide, motor-vehicle, firearm and child mortality rates are crude (the cause mix and the leading-kind map use CHR's crude suicide rate so that four rates share one basis).

A county is missing a rate when it has fewer than 10 deaths in the window (20 for premature mortality).

Race-specific rates are county rates for non-Hispanic Black and white residents, averaged over counties that publish both, each group weighted by its residents.

Figures explained here: Figure 5, Figure 6, Figure 7 and Figure 8

How deprivation and life expectancy are measured

County deprivation is the mean of tract Area Deprivation Index national ranks weighted by tract population; Connecticut tracts map to the eight legacy counties.

Life expectancy is the National Center for Health Statistics estimate for deaths in 2010 to 2015, area-weighted onto 2020 tracts, with institutional tracts left out.

Figures explained here: Figure 4 and Figure 5

How uncertainty is measured

Intervals for national concentration statistics come from a bootstrap that draws whole counties with replacement, and those for one county from a bootstrap that draws clusters, 2,000 replicates with seed 12345, as percentile intervals.

Decile means, shares and correlations across counties come from a bootstrap that draws whole states with replacement, 2,000 replicates, seed 12345, weighted by county population.

Figures explained here: Figure 1, Figure 2, Figure 6 and Figure 7

References

Weisburd, David (2015). The law of crime concentration and the criminology of place. Criminology 53(2): 133-157. doi:10.1111/1745-9125.12070
Braga, Anthony A.; Weisburd, David; Turchan, Brandon (2018). Focused deterrence strategies and crime control: an updated systematic review and meta-analysis of the empirical evidence. Criminology & Public Policy 17(1): 205-250. doi:10.1111/1745-9133.12353
Skogan, Wesley G.; Hartnett, Susan M.; Bump, Natalie; Dubois, Jill (2008). Evaluation of CeaseFire-Chicago. National Institute of Justice (NCJ 227181); Northwestern University Institute for Policy Research. www.ojp.gov/ncjrs/virtual-library/abstracts/evaluation-ceasefire-chicago
Ransford, Charles; Williams, Monique; Slutkin, Gary (2025). A systematic review on the effectiveness of the Cure Violence approach. INQUIRY: The Journal of Health Care Organization, Provision, and Financing 62: 00469580251366142. doi:10.1177/00469580251366142
Branas, Charles C.; South, Eugenia; Kondo, Michelle C.; Hohl, Bernadette C.; Bourgois, Philippe; Wiebe, Douglas J.; MacDonald, John M. (2018). Citywide cluster randomized trial to restore blighted vacant land and its effects on violence, crime, and fear. Proceedings of the National Academy of Sciences 115(12): 2946-2951. doi:10.1073/pnas.1718503115

How to cite

@misc{singh2026gunhomicideandcausesofearlydeath,
  author = {Singh, Vishal},
  title = {Gun homicide and the causes of early death},
  year = {2026},
  url = {https://vishalsingh.org/zipcode/gun-homicide-and-causes-of-early-death},
  note = {In ZIP Code Destiny. Published 9 October 2026.}
}

Firearm homicide deaths concentrate in a small share of tract clusters

Counties differ in how steeply the curve bends

Chicago, cluster by cluster

The highest-rate tenths of Cook County are also its most deprived and shortest-lived

Premature mortality rises with county deprivation

The mix of deaths differs between the least and most deprived fifths

Rural share moves with suicide and motor-vehicle deaths, and homicide depends on the weighting

Homicide and suicide rates differ by race in opposite directions

The kind of death with the highest rate differs by county

What place-based evidence shows

What these data cannot show

Data sources

Methods

Which clusters and years enter the concentration curves

How implied deaths and the curves are computed

Where the county death rates come from

How deprivation and life expectancy are measured

How uncertainty is measured

References

How to cite

Reading paths