TABLE A-2 Observed and Expected Suicide Rates by Age, Race, and Sex. Data: CMF 1996–1998

Age Group

Race

Sex

Number of Suicides

Population

Observed Rate

Expected Rate (1)

Expected Rate (2)

05–14

Black

Male

79

9,256,227

0.000009

0.000010

0.000009

05–14

Black

Female

28

8,978,221

0.000003

0.000003

0.000002

05–14

Other

Male

620

50,356,003

0.000012

0.000014

0.000012

05–14

Other

Female

206

47,847,778

0.000004

0.000005

0.000004

15–24

Black

Male

1,333

8,389,386

0.000159

0.000177

0.000160

15–24

Black

Female

191

8,352,196

0.000023

0.000024

0.000021

15–24

Other

Male

9,482

47,906,710

0.000198

0.000222

0.000198

15–24

Other

Female

1,673

45,396,608

0.000037

0.000042

0.000037

25–44

Black

Male

2,546

15,274,935

0.000167

0.000184

0.000164

25–44

Black

Female

474

17,191,095

0.000028

0.000033

0.000030

25–44

Other

Male

27,209

109,106,670

0.000249

0.000283

0.000250

25–44

Other

Female

6,977

108,864,081

0.000064

0.000072

0.000064

45–64

Black

Male

861

7,741,680

0.000111

0.000124

0.000111

45–64

Black

Female

224

9,633,227

0.000023

0.000026

0.000023

45–64

Other

Male

17,358

72,740,945

0.000239

0.000267

0.000239

45–64

Other

Female

5,307

76,289,629

0.000070

0.000078

0.000070

65+

Black

Male

415

3,295,133

0.000126

0.000142

0.000131

65+

Black

Female

83

5,140,632

0.000016

0.000014

0.000013

65+

Other

Male

14,074

38,889,596

0.000362

0.000398

0.000361

65+

Other

Female

2,814

55,229,051

0.000051

0.000057

0.000051

Note: (1) Mixed-effect model

(2) GEE model

spection of Table A-3 reveals remarkably close agreement between observed and expected numbers of suicides.

Second, we can use the Bayes estimates directly to obtain county-level suicide rates adjusted for the effects of race, sex, and age. In the case of a Poisson model, the Bayes estimate for a given county is a multiple of the national suicide rate adjusted for the case mix in that county (i.e., race, sex and age). For example, a Bayes estimate of 1.0 represents an adjusted rate that is equal to the national rate. By contrast, a Bayes estimate of 2.0 represents a doubling of the national rate, and a Bayes estimate of 0.5 represents one-half of the national rate. Figure A-2 displays the Bayes estimates by county across the U.S. Inspection of Figure A-2 reveals that even after accounting for these important demographic variables, considerable spatial variability remains. Again, the highest adjusted rates are typically found in the less densely populated areas of the western U.S.

The map in Figure A-2 also provides a useful tool for qualitative research into the etiology of suicide. A natural approach is to examine the



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