Decoding Suicide Decedent Profiles and Signs of Suicidal Intent Using Latent Class Analysis

Author:

Xiao Yunyu1,Bi Kaiwen2,Yip Paul Siu-Fai23,Cerel Julie4,Brown Timothy T.5,Peng Yifan1,Pathak Jyotishman1,Mann J. John678

Affiliation:

1. Department of Population Health Sciences, Weill Cornell Medicine/NewYork-Presbyterian, New York

2. Department of Social Work and Social Administration, The University of Hong Kong, Hong Kong

3. Hong Kong Jockey Club Centre for Suicide Research and Prevention, The University of Hong Kong, Hong Kong

4. College of Social Work, University of Kentucky, Lexington

5. School of Public Health, University of California, Berkeley

6. Department of Psychiatry, Columbia University Irving Medical Center, Columbia University, New York, New York

7. Department of Radiology, Columbia University Irving Medical Center, Columbia University, New York, New York

8. Division of Molecular Imaging and Neuropathology, New York State Psychiatric Institute, New York

Abstract

ImportanceSuicide rates in the US increased by 35.6% from 2001 to 2021. Given that most individuals die on their first attempt, earlier detection and intervention are crucial. Understanding modifiable risk factors is key to effective prevention strategies.ObjectiveTo identify distinct suicide profiles or classes, associated signs of suicidal intent, and patterns of modifiable risks for targeted prevention efforts.Design, Setting, and ParticipantsThis cross-sectional study used data from the 2003-2020 National Violent Death Reporting System Restricted Access Database for 306 800 suicide decedents. Statistical analysis was performed from July 2022 to June 2023.ExposuresSuicide decedent profiles were determined using latent class analyses of available data on suicide circumstances, toxicology, and methods.Main Outcomes and MeasuresDisclosure of recent intent, suicide note presence, and known psychotropic usage.ResultsAmong 306 800 suicide decedents (mean [SD] age, 46.3 [18.4] years; 239 627 males [78.1%] and 67 108 females [21.9%]), 5 profiles or classes were identified. The largest class, class 4 (97 175 [31.7%]), predominantly faced physical health challenges, followed by polysubstance problems in class 5 (58 803 [19.2%]), and crisis, alcohol-related, and intimate partner problems in class 3 (55 367 [18.0%]), mental health problems (class 2, 53 928 [17.6%]), and comorbid mental health and substance use disorders (class 1, 41 527 [13.5%]). Class 4 had the lowest rates of disclosing suicidal intent (13 952 [14.4%]) and leaving a suicide note (24 351 [25.1%]). Adjusting for covariates, compared with class 1, class 4 had the highest odds of not disclosing suicide intent (odds ratio [OR], 2.58; 95% CI, 2.51-2.66) and not leaving a suicide note (OR, 1.45; 95% CI, 1.41-1.49). Class 4 also had the lowest rates of all known psychiatric illnesses and psychotropic medications among all suicide profiles. Class 4 had more older adults (23 794 were aged 55-70 years [24.5%]; 20 100 aged ≥71 years [20.7%]), veterans (22 220 [22.9%]), widows (8633 [8.9%]), individuals with less than high school education (15 690 [16.1%]), and rural residents (23 966 [24.7%]).Conclusions and RelevanceThis study identified 5 distinct suicide profiles, highlighting a need for tailored prevention strategies. Improving the detection and treatment of coexisting mental health conditions, substance and alcohol use disorders, and physical illnesses is paramount. The implementation of means restriction strategies plays a vital role in reducing suicide risks across most of the profiles, reinforcing the need for a multifaceted approach to suicide prevention.

Publisher

American Medical Association (AMA)

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