Suicide is a leading cause of death among youth in the United States. The coronavirus disease 2019 (COVID-19) pandemic raised concerns that suicide rates will increase. The National Fatality Review-Case Reporting System documents circumstances of child deaths reviewed by multidisciplinary teams. In April 2021, a question asking whether COVID-19 directly or indirectly impacted the child’s death was added to the National Fatality Review-Case Reporting System. The objective of this study was to identify factors related to suicide deaths among youth during the COVID-19 pandemic.
This exploratory study of youth aged 10 to 17 years occurring during 2020 to 2021 compared demographic and incident characteristics, life stressors, social/mental health histories, and pandemic-related disruptions to school, health, and mental health for COVID-19–impacted suicides and non-COVID-19–impacted suicides using descriptive statistics. χ2 statistics assessed statistical significance in differences across the 2 groups.
A total of 552 suicides were included for study. Higher proportions of COVID-19–impacted suicides (n = 144) were by hanging (51% vs 40%) and occurred in suburban areas (57% vs 45%) compared with non–COVID-19–impacted suicides (n = 408). COVID-19–impacted youth also experienced significantly more isolation (60% vs 14%), school problems (42% vs 19%), depression (43% vs 24%), and/or anxiety disorder (23% vs 12%) diagnoses.
A subset of youth experienced significant effects of the pandemic and associated measures implemented to mitigate the spread of COVID-19. They were proportionally more likely to experience isolation, school and mental health care disruptions, behavior changes, and severe emotional distress; all signs of increased risk for suicide.
The coronavirus disease 2019 pandemic and its associated stay-at-home orders and school closures exacerbated mental health conditions among youth.
A subset of youth at risk for suicide experienced significant effects of the pandemic and measures implemented to mitigate the spread of coronavirus disease 2019. They were more likely to experience isolation and disruptions in school and mental health care.
Suicide is a leading cause of death among youth in the United States, increasing from the third leading cause of death among 10- to 17-year-olds in 1999 to the second leading cause of death in 2020.1 Suicide rates among 10- to 14-year-olds and 15- to 24-year-olds also increased.2
The coronavirus disease 2019 (COVID-19) pandemic raised concerns that suicide rates among youth would increase with a concomitant increase in suicide risk factors, such as isolation, substance use, and mental health problems.3–5 Recent studies documented adverse mental health symptoms among children coinciding with school closures and social lockdown measures instituted early in the pandemic,4 and estimates of the prevalence of elevated depression and anxiety symptoms among youth globally were 25% and 20%, respectively, during the first year of the pandemic relative to prepandemic estimates.5 In the United States, an analysis of data from the National Survey of Children’s Health documented a 25% increase (from 9.4% to 11.8%) in the proportion of children who had anxiety or depression in 2020 compared with 2016.6
Multidisciplinary child death review (CDR) programs exist in every US state.7 Although membership varies by state, CDR teams typically include representatives from medicine, public health, child welfare, law enforcement, and coroner/medical examiner’s office. Team members bring information about the child and family’s history, circumstances, cause, and manner of death to the meeting for the purpose of identifying risk and protective factors and recommending prevention strategies.7,8 The purpose of this study was to identify factors related to suicide deaths among youth during the COVID-19 pandemic using data collected by CDR programs.
Methods
The National Fatality Review-Case Reporting System (NFR-CRS) is a Web-based platform currently used by CDR programs in 47 states to record information obtained during their reviews. The origins of NFR-CRS, its strengths, and limitations have been documented elsewhere.9 In short, NFR-CRS provides CDR teams with a mechanism to systematically record, analyze, and report information on every child death reviewed. After review and discussion of all information brought to the review, details are entered into NFR-CRS. Variables include demographic and social characteristics of the child, family, and supervisor; circumstances of the death, including incident and death investigation details; and risk and protective factors.10 The National Center for Fatality Review and Prevention, a program of the Michigan Public Health Institute, maintains and updates NFR-CRS, provides training and technical assistance to states, and monitors data quality.
In April 2021, questions about the relationship between the COVID-19 pandemic and the death were added to NFR-CRS.10 Written guidance on these new questions was provided to all CDR teams and they were asked to complete these questions for all deaths occurring on or after March 1, 2020. One of these questions asks whether COVID-19 directly or indirectly impacted the child’s death. Response options are: (1) COVID-19 was the immediate or underlying cause of death, (2) COVID-19 was diagnosed at autopsy or child was suspected to have COVID-19, (3) COVID-19 indirectly contributed to the death but was not the immediate or underlying cause of death, (4) the childbearing parent contracted COVID-19, (5) other (specify), (6) COVID-19 had no impact on this child’s death, or (7) unknown.
Our study population included all youth aged 10 to 17 years who died by suicide in 2020 or 2021. Because completion of the review and data entry by CDR teams often lags the child’s death by 7 to 10 months on average, we included only deaths where the data entry complete tick box was checked. We further excluded deaths where the COVID-19 impact question was not answered. These suicide deaths were then stratified by response to the COVID-19 impact question, where deaths indicated as directly or indirectly impacted by COVID-19 as denoted by a response option of 1 to 5 (described above) were classified as impacted and responses 6 or 7 (no, unknown) were classified as no COVID-19 impact.
Covariates of interest included child characteristics, mechanism of injury, current or past child maltreatment, current or past mental health treatment, history of problems in school, substance use, previous suicide attempts, evidence of suicide warning signs within 30 days of death, documented life stressors, and documented disruptions or changes to the child’s school, living, or health care environment in the 12 months before death.
COVID-19–related questions assessing social, family, and community disruptions the child might have experienced in the 12 months before the child’s death were also added in April 2021. We examined the items most relevant to youth suicide: disruptions to school, living environment, medical care, and mental health/substance use care. For this question, there is an option to select “none,” indicating that none of the disruptions listed were documented for the child. If the child experienced the disruption listed, the response was recorded as yes; otherwise, it was recorded as disruption not specified. Another question assessed whether the child lived in an area with a stay-at-home order in the 12 months before their death. If yes, a follow-up question to determine if there was a stay-at-home order in place at the time of the child’s death was asked.
The life stressor variables are grouped into 6 categories: socioeconomic, relationship, school, technology, transition, and trauma. Coding for life stressors is the same as for the COVID-19 disruptions question. Aside from mechanism of injury, geographic area, child age and sex, suicide warning signs, life stressors, and disruptions, the other variables all have yes or no response options.
Data Analysis
Descriptive analyses were conducted, including calculating frequencies and proportions. COVID-19–impacted suicides were compared with suicides with no COVID-19 impact across all covariates. Statistical significance was assessed using the χ2 statistic for all categorical variables, and the t test for difference in mean child age. Additionally, we calculated and compared the number of life stressors for each of the 6 life stressor categories and the mean number for each category, comparing the categorical data by calculating the χ2 statistic and comparing the mean number for each category with a t test statistic. Analyses were conducted using SPSS statistics version 27. This research was ruled exempt by the Michigan Public Health Institute’s institutional review board.
Results
There were 990 deaths by suicide during 2020 and 2021 among 10–17-year-olds in the NFR-CRS on March 1, 2022, when the deidentified data file was prepared. After excluding records where the data entry complete was not checked (n = 220) and records missing a response to the COVID-19 impact question (n = 218), 552 suicide deaths occurring in 28 states remained for analysis.
The average age of decedents was 14.9 years (median = 15); 24% were aged 10 to 13 years and 70% were male. The majority were non-Hispanic white (72%), 13% were non-Hispanic Black, and 20% were Hispanic ethnicity. The most common mechanisms of injury were firearms (43%), hanging (41%), and poisoning (7%).
The deaths of 144 (26%) youth who died by suicide were documented to be impacted by COVID-19; of these, the majority (89%) were noted to be indirectly impacted. No COVID-19 impact was noted for the remaining 408 (74%) suicide deaths. For most of the covariates of interest, including child demographic characteristics, current or past child maltreatment, and history of drug use or suicide attempts, there were no statistically significant differences when comparing the COVID-19–impacted suicides to those with no impact (Table 1). However, differences were noted in the mechanism of injury, geographic area where the suicide occurred, several mental health variables, year of death, pandemic-related disruptions, and the number and type of life stressors experienced.
Demographic, Social, and Incident Characteristics of Suicide Deaths Among Youth Ages 10–17 in the United States, 2020–2021, by COVID-19 Impact
Characteristic . | COVID-19–Impacted, N = 144 . | No Documented COVID-19 Impact, N = 408 . | P . |
---|---|---|---|
Child demographics | |||
Age, y, n (%) | .90 | ||
10–12a | 16 (11) | 48 (12) | |
13 | 19 (13) | 49 (12) | |
14 | 15 (10) | 48 (12) | |
15 | 28 (19) | 71 (17) | |
16 | 33 (23) | 92 (23) | |
17 | 33 (23) | 100 (24) | |
Mean (SD) | 14.9 (1.86) | 14.9 (1.82) | .79 |
Sex, n (%) | .90 | ||
Male | 99 (69) | 285 (70) | |
Female | 44 (31) | 123 (30) | |
Missing (n = 1) | |||
Race, n (%) | .59 | ||
American Indian/Alaska Native | — | 12 (3) | |
Asian American | 8 (6) | 19 (5) | |
Black | 20 (14) | 49 (13) | |
Native Hawaiian/Pacific Islander | — | — | |
White | 104 (74) | 292 (77) | |
Multiracial | — | 6 (2) | |
Missing (n = 31) | |||
Hispanic ethnicity, n (%) | .48 | ||
Yes | 34 (24) | 78 (21) | |
No | 109 (76) | 295 (79) | |
Missing (n = 36) | |||
Incident, n (%) | |||
Year of death | <.01 | ||
2020 | 107 (74) | 251 (62) | |
2021 | 37 (26) | 157 (38) | |
Incident area, n (%) | .04 | ||
Urban | 32 (23) | 95 (26) | |
Suburban | 80 (57) | 165 (45) | |
Rural | 29 (21) | 108 (29) | |
Missing (n = 43) | |||
Mechanism of injury, n (%) | <.00 | ||
Asphyxia/hanging | 71 (51) | 158 (40) | |
GSW/firearm | 46 (33) | 192 (49) | |
Poisoning/overdose | 18 (13) | 21 (5) | |
Other | — | 22 (6) | |
Missing (n = 19) | |||
Child maltreatment, school problems, mental health history | |||
History of child maltreatment, n (%) | .49 | ||
Yes | 34 (26) | 92 (29) | |
No | 99 (74) | 228 (71) | |
Missing (n = 99) | |||
Open CPS record at death, n (%) | .55 | ||
Yes | — | 14 (4) | |
No | 136 (97) | 338 (96) | |
Missing (n = 60) | |||
Child abuse or neglect cause or contribute to death, n (%) | .22 | ||
Yes | 37 (26) | 115 (32) | |
No | 103 (74) | 244 (68) | |
Missing (n = 53) | |||
Had problems in school, n (%) | .02 | ||
Yes | 64 (56) | 113 (43) | |
No | 51 (44) | 153 (56) | |
Missing (n = 171) | |||
History of drug abuse, n (%) | .63 | ||
Yes | 38 (31) | 88 (28) | |
No | 86 (69) | 223 (72) | |
Missing (n = 117) | |||
Received previous mental health services, n (%) | .03 | ||
Yes | 83 (63) | 160 (52) | |
No | 49 (37) | 150 (48) | |
Missing (n = 110) | |||
Currently receiving mental health services, n (%) | .54 | ||
Yes | 54 (40) | 115 (37) | |
No | 82 (60) | 199 (63) | |
Missing (n = 102) | |||
Taking mental health medications, n (%) | .03 | ||
Yes | 50 (38) | 83 (27) | |
No | 83 (62) | 222 (73) | |
Missing (n = 114) | |||
ED visit for mental health in previous year, n (%) | .40 | ||
Yes | 19 (15) | 35 (12) | |
No | 104 (85) | 248 (88) | |
Missing (n = 146) | |||
Hospitalized for mental health in previous year, n (%) | .30 | ||
Yes | 20 (16) | 37 (12) | |
No | 106 (84) | 267 (88) | |
Missing (n = 122) | |||
Diagnosis anxiety, n (%) | <.00 | ||
Yes | 33 (23) | 47 (12) | |
Not specified | 111 (77) | 361 (88) | |
Diagnosis depression, n (%) | <.00 | ||
Yes | 62 (43) | 98 (24) | |
Not specified | 82 (57) | 310 (76) | |
History of suicide attempt, n (%) | .72 | ||
Yes | 33 (32) | 80 (30) | |
No | 71 (68) | 188 (70) | |
Missing (n = 180) | |||
Suicide warning signs, n (%) | |||
Talked about suicide | 42 (29) | 95 (23) | .16 |
Talked about suicide not specified | 102 (71) | 313 (77) | |
Expressed hopelessness | 23 (15) | 57 (14) | .56 |
Expressed hopelessness not specified | 121 (84) | 351 (86) | |
Displayed severe emotional pain/distress | 43 (30) | 78 (19) | .01 |
Severe emotional pain/distress not specified | 101 (70) | 330 (81) | |
Expressed perceived burden on others | 15 (10) | 30 (7) | .25 |
Expressed perceived burden not specified | 129 (90) | 378 (93) | |
Showed marked behavior changes | 45 (31) | 88 (22) | .02 |
Marked behavior changes not specified | 99 (69) | 320 (78) | |
Disruptions/changes in the 12 mo before death, n (%) | |||
School disruption/change | 113 (78) | 101 (25) | <.00 |
School disruption/change not specified | 31 (22) | 307 (75) | |
Living environment disruption/change | 20 (14) | 18 (4) | <.00 |
Living environment disruption not specified | 124 (86) | 390 (96) | |
Medical care disruption/change | 9 (6) | — | <.00 |
Medical care disruption not specified | 135 (94) | 407 (100) | |
Mental health care disruption/change | 35 (24) | 18 (4) | <.00 |
Mental health care disruption not specified | 109 (76) | 390 (96) | |
Stay-at-home order in place, n (%) | |||
In the 12 mo before death | <.00 | ||
Yes | 117 (89) | 176 (57) | |
No | 15 (11) | 135 (43) | |
Missing (n = 109) | |||
At the time of death | <.00 | ||
Yes | 51 (46) | 39 (24) | |
No | 59 (54) | 123 (76) | |
Missing (n = 21) |
Characteristic . | COVID-19–Impacted, N = 144 . | No Documented COVID-19 Impact, N = 408 . | P . |
---|---|---|---|
Child demographics | |||
Age, y, n (%) | .90 | ||
10–12a | 16 (11) | 48 (12) | |
13 | 19 (13) | 49 (12) | |
14 | 15 (10) | 48 (12) | |
15 | 28 (19) | 71 (17) | |
16 | 33 (23) | 92 (23) | |
17 | 33 (23) | 100 (24) | |
Mean (SD) | 14.9 (1.86) | 14.9 (1.82) | .79 |
Sex, n (%) | .90 | ||
Male | 99 (69) | 285 (70) | |
Female | 44 (31) | 123 (30) | |
Missing (n = 1) | |||
Race, n (%) | .59 | ||
American Indian/Alaska Native | — | 12 (3) | |
Asian American | 8 (6) | 19 (5) | |
Black | 20 (14) | 49 (13) | |
Native Hawaiian/Pacific Islander | — | — | |
White | 104 (74) | 292 (77) | |
Multiracial | — | 6 (2) | |
Missing (n = 31) | |||
Hispanic ethnicity, n (%) | .48 | ||
Yes | 34 (24) | 78 (21) | |
No | 109 (76) | 295 (79) | |
Missing (n = 36) | |||
Incident, n (%) | |||
Year of death | <.01 | ||
2020 | 107 (74) | 251 (62) | |
2021 | 37 (26) | 157 (38) | |
Incident area, n (%) | .04 | ||
Urban | 32 (23) | 95 (26) | |
Suburban | 80 (57) | 165 (45) | |
Rural | 29 (21) | 108 (29) | |
Missing (n = 43) | |||
Mechanism of injury, n (%) | <.00 | ||
Asphyxia/hanging | 71 (51) | 158 (40) | |
GSW/firearm | 46 (33) | 192 (49) | |
Poisoning/overdose | 18 (13) | 21 (5) | |
Other | — | 22 (6) | |
Missing (n = 19) | |||
Child maltreatment, school problems, mental health history | |||
History of child maltreatment, n (%) | .49 | ||
Yes | 34 (26) | 92 (29) | |
No | 99 (74) | 228 (71) | |
Missing (n = 99) | |||
Open CPS record at death, n (%) | .55 | ||
Yes | — | 14 (4) | |
No | 136 (97) | 338 (96) | |
Missing (n = 60) | |||
Child abuse or neglect cause or contribute to death, n (%) | .22 | ||
Yes | 37 (26) | 115 (32) | |
No | 103 (74) | 244 (68) | |
Missing (n = 53) | |||
Had problems in school, n (%) | .02 | ||
Yes | 64 (56) | 113 (43) | |
No | 51 (44) | 153 (56) | |
Missing (n = 171) | |||
History of drug abuse, n (%) | .63 | ||
Yes | 38 (31) | 88 (28) | |
No | 86 (69) | 223 (72) | |
Missing (n = 117) | |||
Received previous mental health services, n (%) | .03 | ||
Yes | 83 (63) | 160 (52) | |
No | 49 (37) | 150 (48) | |
Missing (n = 110) | |||
Currently receiving mental health services, n (%) | .54 | ||
Yes | 54 (40) | 115 (37) | |
No | 82 (60) | 199 (63) | |
Missing (n = 102) | |||
Taking mental health medications, n (%) | .03 | ||
Yes | 50 (38) | 83 (27) | |
No | 83 (62) | 222 (73) | |
Missing (n = 114) | |||
ED visit for mental health in previous year, n (%) | .40 | ||
Yes | 19 (15) | 35 (12) | |
No | 104 (85) | 248 (88) | |
Missing (n = 146) | |||
Hospitalized for mental health in previous year, n (%) | .30 | ||
Yes | 20 (16) | 37 (12) | |
No | 106 (84) | 267 (88) | |
Missing (n = 122) | |||
Diagnosis anxiety, n (%) | <.00 | ||
Yes | 33 (23) | 47 (12) | |
Not specified | 111 (77) | 361 (88) | |
Diagnosis depression, n (%) | <.00 | ||
Yes | 62 (43) | 98 (24) | |
Not specified | 82 (57) | 310 (76) | |
History of suicide attempt, n (%) | .72 | ||
Yes | 33 (32) | 80 (30) | |
No | 71 (68) | 188 (70) | |
Missing (n = 180) | |||
Suicide warning signs, n (%) | |||
Talked about suicide | 42 (29) | 95 (23) | .16 |
Talked about suicide not specified | 102 (71) | 313 (77) | |
Expressed hopelessness | 23 (15) | 57 (14) | .56 |
Expressed hopelessness not specified | 121 (84) | 351 (86) | |
Displayed severe emotional pain/distress | 43 (30) | 78 (19) | .01 |
Severe emotional pain/distress not specified | 101 (70) | 330 (81) | |
Expressed perceived burden on others | 15 (10) | 30 (7) | .25 |
Expressed perceived burden not specified | 129 (90) | 378 (93) | |
Showed marked behavior changes | 45 (31) | 88 (22) | .02 |
Marked behavior changes not specified | 99 (69) | 320 (78) | |
Disruptions/changes in the 12 mo before death, n (%) | |||
School disruption/change | 113 (78) | 101 (25) | <.00 |
School disruption/change not specified | 31 (22) | 307 (75) | |
Living environment disruption/change | 20 (14) | 18 (4) | <.00 |
Living environment disruption not specified | 124 (86) | 390 (96) | |
Medical care disruption/change | 9 (6) | — | <.00 |
Medical care disruption not specified | 135 (94) | 407 (100) | |
Mental health care disruption/change | 35 (24) | 18 (4) | <.00 |
Mental health care disruption not specified | 109 (76) | 390 (96) | |
Stay-at-home order in place, n (%) | |||
In the 12 mo before death | <.00 | ||
Yes | 117 (89) | 176 (57) | |
No | 15 (11) | 135 (43) | |
Missing (n = 109) | |||
At the time of death | <.00 | ||
Yes | 51 (46) | 39 (24) | |
No | 59 (54) | 123 (76) | |
Missing (n = 21) |
CPS, Child Protective Services; GSW, gun shot wound;. —, indicates frequency suppressed due to small cell size.
Ages 10 to 12 years grouped because small cell sizes would require suppression if individual ages reported.
The mechanism of injury was significantly different across the 2 suicide groups. Higher proportions of COVID-19–impacted suicides were by hanging (51% vs 40%) or poisoning (13% vs 5%), whereas higher proportions of non–COVID-19– impacted suicides used a firearm (49% vs 33%). Although similar proportions of youth suicide occurred in urban areas (23% impacted, 26% not impacted), higher proportions of COVID-19–impacted suicides occurred in suburban areas (57% vs 45%), whereas suicides in rural areas were proportionally greater among youth with no COVID-19 impact.
In addition, several mental health variables were significantly different, with higher proportions of COVID-19–impacted youth having received mental health services in the past (63% vs 52%), currently taking mental health medications (38% vs 27%), having a diagnosis of anxiety (23% vs 12%) or depression (43% vs 24%), and having problems in school (56% vs 43%). Similarly, 2 of the 5 suicide warning signs were significantly different, with higher proportions of COVID-19– impacted youth having displayed severe emotional pain/distress (35% vs 19%) and showing marked behavior changes (31% vs 22%) in the 30 days before death.
A higher proportion of COVID-19– impacted suicides occurred in 2020 (74% vs 62%). Higher proportions of pandemic-related disruptions to school, living environments, medical, and mental health care were noted for COVID-19–impacted suicides, the largest of these being school disruptions at (76% vs 35%). Similarly, higher proportions of youth whose death was impacted by COVID-19 experienced a stay-at-home order in the 12 months before death (89% vs 57%) and had a stay-at-home order in place at the time of death (46% vs 24%).
Compared with suicides with no COVID-19 impact, the COVID-19– impacted youth had significantly more life stressors documented (Table 2). Individual stressors affecting the highest proportions of youth with COVID-19–impacted suicides were isolation (60% vs 14%), school failure (23% vs 12%), and other school problems (42% vs 19%). When examined by the number and average number of life stressors, youth whose suicide was impacted by COVID-19 had significantly higher number and average number of stressors in each category (Table 2). School stressors stand out again, with 75% of youth whose suicide was impacted by COVID-19 experiencing 1 or more school stressors, compared with 42% of suicides with no COVID-19 impact.
Documented Life Stressors Among Youth Ages 10 to 17 Who Died by Suicide in the United States, 2020–2021, by COVID-19 Impact
Life Stressor . | COVID-19–Impacted, N = 144, N (%) . | No Documented COVID-19 Impact, N = 408, N (%) . | P . |
---|---|---|---|
Socioeconomic stressors | |||
Poverty | 14 (10) | 12 (3) | <.00 |
Poverty not specified | 130 (90) | 396 (97) | |
Housing instability | 9 (6) | 17 (4) | .31 |
Housing instability not specified | 135 (94) | 391 (96) | |
Witnessed violence | 20 (13) | 14 (3) | <.00 |
Witnessed violence not specified | 124 (86) | 394 (97) | |
Relationship stressors | |||
Family discord | 45 (31) | 97 (24) | .08 |
Family discord not specified | 99 (69) | 311 (76) | |
Argument with parents | 47 (33) | 106 (26) | .13 |
Argument with parents not specified | 97 (67) | 302 (74) | |
Parent’s divorce | 28 (19) | 53 (13) | .06 |
Parent’s divorce not specified | 116 (81) | 355 (87) | |
Parent incarcerated | 7 (5) | 12 (3) | .28 |
Parent incarcerated not specified | 137 (95) | 396 (97) | |
Argument with significant other | 10 (7) | 23 (6) | .57 |
Argument with significant other not specified | 134 (93) | 385 (94) | |
Breakup with significant other | 22 (15) | 51 (13) | .40 |
Breakup with significant other not specified | 122 (85) | 357 (87) | |
Social discord | 20 (14) | 29 (7) | .01 |
Social discord not specified | 124 (86) | 379 (93) | |
Bullying victim | 14 (10) | 53 (13) | .30 |
Bullying victim not specified | 130 (90) | 355 (87) | |
Cyberbullying victim | 6 (4) | 12 (3) | .48 |
Cyberbullying victim not specified | 138 (96) | 396 (97) | |
Isolation | 86 (60) | 58 (14) | <.00 |
Isolation not specified | 58 (40) | 350 (86) | |
Gender identity | 6 (4) | 10 (3) | .29 |
Gender identity not specified | 138 (96) | 398 (97) | |
School stressors | |||
School failure | 33 (23) | 48 (12) | <.00 |
School failure not specified | 111 (77) | 360 (88) | |
Pressure to succeed | 23 (16) | 24 (6) | <.00 |
Pressure to succeed not specified | 121 (84) | 384 (94) | |
Extracurricular activities | 7 (5) | 7 (2) | .04 |
Extracurricular activities not specified | 137 (95) | 401 (98) | |
New school | 13 (9) | 21 (5) | .10 |
New school not specified | 131 (91) | 387 (95) | |
Other school problems | 60 (42) | 76 (19) | <.00 |
Other school problems not specified | 84 (58) | 332 (81) | |
Technology stressors | |||
Electronic gaming | 8 (6) | 14 (3) | .26 |
Electronic gaming not specified | 136 (94) | 394 (97) | |
Restriction of technology | 19 (13) | 21 (5) | <.00 |
Restriction of technology not specified | 125 (87) | 387 (95) | |
Social media | 16 (11) | 28 (7) | .11 |
Social media not specified | 128 (89) | 380 (93) | |
Transition stressors | |||
Release from hospital | 6 (4) | 10 (3) | .30 |
Release from hospital not specified | 138 (96) | 398 (97) | |
Mental health level of care | 10 (7) | 21 (5) | .42 |
Mental health level of care not specified | 134 (93) | 387 (95) | |
End-of-school y/break | 22 (15) | 18 (4) | ≤.00 |
End-of-school y not specified | 122 (85) | 390 (96) | |
Trauma stressors | |||
Rape/sexual assault | 9 (6) | 21 (5) | .62 |
Rape/sexual assault not specified | 135 (94) | 387 (95) | |
Previous abuse | 18 (13) | 36 (9) | .20 |
Previous abuse not specified | 126 (87) | 372 (91) | |
Family/domestic violence | 19 (13) | 24 (6) | <.01 |
Family/domestic violence not specified | 125 (87) | 384 (94) | |
Number of trauma stressor per child | |||
Socioeconomic stressors | <.00 | ||
0 | 75 (66) | 277 (86) | |
1 | 25 (22) | 33 (10) | |
2 | 6 (5) | 9 (3) | |
3 | — | — | |
4 | — | — | |
Mean (SD) | 0.56 (0.97) | 0.21 (0.58) | |
Relationship stressors | <.00 | ||
0 | 12 (9) | 89 (25) | |
1 | 41 (30) | 113 (32) | |
2 | 32 (24) | 72 (21) | |
3 | 23 (17) | 32 (9) | |
4 | 14 (10) | 28 (8) | |
5+ | 14 (10) | 16 (5) | |
Mean (SD) | 2.28 (1.64) | 1.59 (1.51) | |
School stressors | <.00 | ||
0 | 33 (25) | 187 (57) | |
1 | 67 (52) | 109 (33) | |
2 | 22 (17) | 29 (9) | |
3+ | 8 (6) | — | |
Mean (SD) | 1.05 (0.84) | 0.54 (0.69) | |
Technology stressors | <.00 | ||
0 | 69 (65) | 265 (83) | |
1 | 28 (26) | 39 (12) | |
2+ | 9 (9) | 15 (5) | |
Mean (SD) | 0.43 (0.64) | 0.23 (0.4) | |
Transition stressors | <.00 | ||
0 | 77 (69) | 273 (86) | |
1 | 30 (27) | 36 (11) | |
2+ | — | 10 (3) | |
Mean (SD) | 0.38 (0.6) | 0.18 (0.49) | |
Trauma stressors | .04 | ||
0 | 75 (71) | 251 (80) | |
1 | 15 (14) | 43 (14) | |
2+ | 15 (14) | 18 (6) | |
Mean (SD) | 0.44 (0.76) | 0.26 (0.59) |
Life Stressor . | COVID-19–Impacted, N = 144, N (%) . | No Documented COVID-19 Impact, N = 408, N (%) . | P . |
---|---|---|---|
Socioeconomic stressors | |||
Poverty | 14 (10) | 12 (3) | <.00 |
Poverty not specified | 130 (90) | 396 (97) | |
Housing instability | 9 (6) | 17 (4) | .31 |
Housing instability not specified | 135 (94) | 391 (96) | |
Witnessed violence | 20 (13) | 14 (3) | <.00 |
Witnessed violence not specified | 124 (86) | 394 (97) | |
Relationship stressors | |||
Family discord | 45 (31) | 97 (24) | .08 |
Family discord not specified | 99 (69) | 311 (76) | |
Argument with parents | 47 (33) | 106 (26) | .13 |
Argument with parents not specified | 97 (67) | 302 (74) | |
Parent’s divorce | 28 (19) | 53 (13) | .06 |
Parent’s divorce not specified | 116 (81) | 355 (87) | |
Parent incarcerated | 7 (5) | 12 (3) | .28 |
Parent incarcerated not specified | 137 (95) | 396 (97) | |
Argument with significant other | 10 (7) | 23 (6) | .57 |
Argument with significant other not specified | 134 (93) | 385 (94) | |
Breakup with significant other | 22 (15) | 51 (13) | .40 |
Breakup with significant other not specified | 122 (85) | 357 (87) | |
Social discord | 20 (14) | 29 (7) | .01 |
Social discord not specified | 124 (86) | 379 (93) | |
Bullying victim | 14 (10) | 53 (13) | .30 |
Bullying victim not specified | 130 (90) | 355 (87) | |
Cyberbullying victim | 6 (4) | 12 (3) | .48 |
Cyberbullying victim not specified | 138 (96) | 396 (97) | |
Isolation | 86 (60) | 58 (14) | <.00 |
Isolation not specified | 58 (40) | 350 (86) | |
Gender identity | 6 (4) | 10 (3) | .29 |
Gender identity not specified | 138 (96) | 398 (97) | |
School stressors | |||
School failure | 33 (23) | 48 (12) | <.00 |
School failure not specified | 111 (77) | 360 (88) | |
Pressure to succeed | 23 (16) | 24 (6) | <.00 |
Pressure to succeed not specified | 121 (84) | 384 (94) | |
Extracurricular activities | 7 (5) | 7 (2) | .04 |
Extracurricular activities not specified | 137 (95) | 401 (98) | |
New school | 13 (9) | 21 (5) | .10 |
New school not specified | 131 (91) | 387 (95) | |
Other school problems | 60 (42) | 76 (19) | <.00 |
Other school problems not specified | 84 (58) | 332 (81) | |
Technology stressors | |||
Electronic gaming | 8 (6) | 14 (3) | .26 |
Electronic gaming not specified | 136 (94) | 394 (97) | |
Restriction of technology | 19 (13) | 21 (5) | <.00 |
Restriction of technology not specified | 125 (87) | 387 (95) | |
Social media | 16 (11) | 28 (7) | .11 |
Social media not specified | 128 (89) | 380 (93) | |
Transition stressors | |||
Release from hospital | 6 (4) | 10 (3) | .30 |
Release from hospital not specified | 138 (96) | 398 (97) | |
Mental health level of care | 10 (7) | 21 (5) | .42 |
Mental health level of care not specified | 134 (93) | 387 (95) | |
End-of-school y/break | 22 (15) | 18 (4) | ≤.00 |
End-of-school y not specified | 122 (85) | 390 (96) | |
Trauma stressors | |||
Rape/sexual assault | 9 (6) | 21 (5) | .62 |
Rape/sexual assault not specified | 135 (94) | 387 (95) | |
Previous abuse | 18 (13) | 36 (9) | .20 |
Previous abuse not specified | 126 (87) | 372 (91) | |
Family/domestic violence | 19 (13) | 24 (6) | <.01 |
Family/domestic violence not specified | 125 (87) | 384 (94) | |
Number of trauma stressor per child | |||
Socioeconomic stressors | <.00 | ||
0 | 75 (66) | 277 (86) | |
1 | 25 (22) | 33 (10) | |
2 | 6 (5) | 9 (3) | |
3 | — | — | |
4 | — | — | |
Mean (SD) | 0.56 (0.97) | 0.21 (0.58) | |
Relationship stressors | <.00 | ||
0 | 12 (9) | 89 (25) | |
1 | 41 (30) | 113 (32) | |
2 | 32 (24) | 72 (21) | |
3 | 23 (17) | 32 (9) | |
4 | 14 (10) | 28 (8) | |
5+ | 14 (10) | 16 (5) | |
Mean (SD) | 2.28 (1.64) | 1.59 (1.51) | |
School stressors | <.00 | ||
0 | 33 (25) | 187 (57) | |
1 | 67 (52) | 109 (33) | |
2 | 22 (17) | 29 (9) | |
3+ | 8 (6) | — | |
Mean (SD) | 1.05 (0.84) | 0.54 (0.69) | |
Technology stressors | <.00 | ||
0 | 69 (65) | 265 (83) | |
1 | 28 (26) | 39 (12) | |
2+ | 9 (9) | 15 (5) | |
Mean (SD) | 0.43 (0.64) | 0.23 (0.4) | |
Transition stressors | <.00 | ||
0 | 77 (69) | 273 (86) | |
1 | 30 (27) | 36 (11) | |
2+ | — | 10 (3) | |
Mean (SD) | 0.38 (0.6) | 0.18 (0.49) | |
Trauma stressors | .04 | ||
0 | 75 (71) | 251 (80) | |
1 | 15 (14) | 43 (14) | |
2+ | 15 (14) | 18 (6) | |
Mean (SD) | 0.44 (0.76) | 0.26 (0.59) |
—, frequency suppressed due to small cell size.
Discussion
This study describes characteristics, including details on pandemic disruptions, mental health issues, and life stressors of youth who died by suicide during the first 2 years of the COVID-19 pandemic, and compares COVID-19–impacted suicides with those where no COVID-19 impact was documented. Although the 2 groups were remarkably similar on several risk factors for suicide, several important differences were noted that may provide clues to identification of a subgroup of vulnerable youth for whom the pandemic and its associated disruptions proved particularly challenging.
The primary differences between COVID-19–impacted suicides and those with no impact were in the mechanism of injury, geographic area where the suicide occurred, mental health, pandemic-related disruptions, and life stressors, particularly related to isolation and school stressors. There was considerable difference in mechanism of injury between the 2 groups, with the majority of COVID-19– impacted suicides occurring by hanging (51%), whereas most suicides with no COVID-19 impact involved a firearm (49%). An effective suicide prevention strategy is the restriction of means used for suicide, such as storing firearms and potential lethal medications in locked locations, and reducing access to tall buildings or bridges.11–13 The large proportion of suicide by hanging in this study is particularly troubling because, not only is hanging highly lethal,14 means for hanging are also ubiquitous everyday items (eg, shoelaces, electrical cords, belts, ropes) that would be impossible to restrict.
An explanation for the high proportion of COVID-19–impacted suicides by hanging is not known but may be related to the high proportion occurring in suburban rather than rural areas where there are more households with guns.15 Concomitant with higher gun ownership, suicide rates in the United States are consistently highest in rural areas, but in this study, the highest proportion of suicides occurred in suburban areas. Perhaps the lower proportion of COVID-19–impacted suicides in rural areas is related to relatively fewer pandemic restrictions in rural areas, and therefore less isolation and social disruption for youth in these areas.16,17
Depression and anxiety are documented risk factors for suicide among youth,18–20 and there is evidence that the prevalence of anxiety and depression symptoms increased among youth during the pandemic.5,6 In this study, higher proportions of youth whose deaths were impacted by COVID-19 had diagnoses of depression and/or anxiety, were taking medications for a mental health condition, and had received mental health services in the past; however, there were no significant differences between the 2 suicide groups on receipt of current services, recent hospitalizations, or emergency department (ED) visits. It is possible that pandemic restrictions made it more difficult to access mental health services while these restrictions exacerbated symptoms in this disproportionally affected population.
In this study, 24% of COVID-19– impacted suicides indicated a disruption in mental health care in the 12 months before death, compared with just 4% of the deaths with no COVID-19 impact. Early research documented a 43% decline in the number of ED visits by youth early in the pandemic when stay-at-home orders were in place throughout much of the United States, compared with the same period in 2019. However, the proportion of ED visits by youth for mental health issues increased beginning in mid-March and persisted through October 2020.21 This proportional increase may have resulted from reductions in clinical or other community mental health services during the pandemic, as well as larger reductions of ED visits for nonmental health problems, or some combination of factors.
Although the COVID-19 pandemic continued through 2021, higher proportions of COVID-19–impacted youth suicides occurred in 2020, the first year of the pandemic, when pandemic-related restrictions were widespread. Documented disruptions to school, living environments, medical, and mental health care, as well as stay-at-home orders at the time of death, were proportionally higher for COVID-19–impacted suicides. In addition to the higher proportions of youth experiencing disruptions, the primary differences between the COVID-19–impacted suicides and those without impact were isolation and school-related problems, known risk factors for suicide and conditions likely exacerbated by pandemic-related school closures.22 These data suggest that the COVID-19 pandemic and its associated mitigation strategies created unique challenges for a subset of youth at risk for suicide.
Although risk factors for suicide are relatively common, most at-risk youth do not die by suicide. The ongoing challenge in suicide prevention is how to identify and intervene for those at highest risk. Screening for depression and other suicide risk factors can be effective in identifying at-risk youth23,24 ; however, many screening programs are based in health care or school settings. Even if health care or school-based screening is typically available, at the beginning of the pandemic, these community resources were not available to youth; schools were closed, and health care facilities limited admittance.
Limitations
There are several potential limitations inherent in NFR-CRS data. CDR is not standardized across the United States, not all states review all child deaths, nor do all states participate in NFR-CRS. Consequently, rates cannot be calculated, and temporal trends cannot be assessed.9 Because all decedents in this study died by suicide, risk factors for or increased risk of youth suicide during the pandemic cannot be assessed, restricting this to a descriptive analysis with results useful for describing factors associated with youth suicide during the pandemic, generating hypotheses, and informing future research. Furthermore, timely analyses of NFR-CRS data can be challenging because of lag between death, review, and data entry.
The COVID-19 questions were not added until April 2021. Although CDR programs were encouraged to return to completed records and complete the COVID-19 questions, this may not have been done by March 1, 2022, when the data for this analysis were compiled. Training was provided on how to complete the COVID-19 questions; however, it was noted during training sessions that if CDR team members had differing interpretations of the COVID-19 impact response option indicating indirect impact, they were often more comfortable recording unknown than indirect impact. This potential for variability in interpretation of response options may result in misclassification. Misclassification of impact would likely result in more conservative estimates of significance because the unknown and no impact responses were combined for comparison with COVID-19–impacted suicides. Finally, because the deidentified NFR-CRS data file includes only the year of death, deaths in January and February 2020 were included in this analysis. The effect of including these suicides would be small and likely result in more conservative estimates of significance because they would be documented as no COVID-19 impact.
Despite these limitations, this study has several strengths. Flexibility in NFR-CRS permitted addition of relevant COVID-19–related questions, including disruptions or significant changes experienced in the period before death, as well as how documenting direct or indirect impact of the pandemic on the death, during the ongoing pandemic. In addition to these questions, NFR-CRS includes many details relevant to suicide risk factors and the decedent’s mental health that are not available in other mortality data systems. Taken together, these system characteristics provide a unique opportunity to examine factors related to youth suicide during the COVID-19 pandemic that may provide important insights for future research.
Conclusions
Suicide is often an impulsive act, facilitated by accessible, lethal means. These characteristics, accompanied by multifactorial risk and protective factors, combine to make suicide prevention particularly challenging. The COVID-19 pandemic and its associated stay-at-home orders and school closures exacerbated mental health conditions among youth.5,22 NFR-CRS data suggest that a subset of youth already at risk for suicide experienced significant effects of the pandemic and the measures implemented to mitigate the spread of COVID-19. They were more likely to experience isolation and school and mental health care disruptions, as well as to express marked behavior changes and severe emotional distress, all troubling signs of increased risk for suicide. Unfortunately, this occurred during a time when systems for screening and referral for care were less available to decrease the risk of transmitting the virus. In December 2021, the US Surgeon General issued an advisory on the youth mental health crisis exacerbated by the COVID-19 pandemic.25 The advisory includes specific recommendations and resources for addressing this national emergency across all sectors of society. As pandemic restrictions ease and the threat of severe illness and death because of COVID-19 fades, it is important not to lose sight of the potential for ongoing increased risk of mental health crises and suicide among youth. The Surgeon General’s recommendations provide important strategies for improving youth mental health and reducing the risk for suicide.25
Dr Schnitzer conceptualized and designed the study, conducted data analyses, and drafted the initial manuscript; Ms Dykstra conceptualized and designed the study, and conducted initial analyses; Ms Collier conceptualized and designed the study; and all authors reviewed and revised the manuscript, approved the final manuscript as submitted, and agree to be accountable for all aspects of the work.
COMPANION PAPER: A companion to this article can be found online at www.pediatrics.org/cgi/doi/10.1542/peds.2022-058375.
This study’s contents are solely the responsibility of the authors and should not be construed as the official position or policy of, nor should any endorsements be inferred by, the Health Resources and Services Administration, the US Department of Health and Human Services, or the US government.
FUNDING: The authors received no financial support for the research, authorship, and/or publication of this article. The National Center for Fatality Review and Prevention developed the National Fatality Review-Case Reporting System with funding support from the US Maternal and Child Health Bureau. The National Center is funded in part by Cooperative Agreement UG728482 from the US Department of Health and Human Services, the Health Resources and Services Administration, and the Maternal and Child Health Bureau as part of an award totaling $2 420 000 annually, with 0% financed with nongovernmental sources. The Health Resources and Services Administration had no role in the design and conduct of the study.
CONFLICT OF INTEREST DISCLAIMER: The authors have indicated they have no conflicts of interest relevant to this article to disclose.
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