1
|
Visoki E, Moore TM, Zhang X, Tran KT, Ly C, Gataviņš MM, DiDomenico GE, Brogan L, Fein JA, Warrier V, Guloksuz S, Barzilay R. Classification of Suicide Attempt Risk Using Environmental and Lifestyle Factors in 3 Large Youth Cohorts. JAMA Psychiatry 2024:2821270. [PMID: 39018056 PMCID: PMC11255979 DOI: 10.1001/jamapsychiatry.2024.1887] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2024] [Accepted: 04/30/2024] [Indexed: 07/18/2024]
Abstract
Importance Suicide is the third-leading cause of death among US adolescents. Environmental and lifestyle factors influence suicidal behavior and can inform risk classification, yet quantifying and incorporating them in risk assessment presents a significant challenge for reproducibility and clinical translation. Objective To quantify the aggregate contribution of environmental and lifestyle factors to youth suicide attempt risk classification. Design, Setting, and Participants This was a cohort study in 3 youth samples: 2 national longitudinal cohorts from the US and the UK and 1 clinical cohort from a tertiary pediatric US hospital. An exposome-wide association study (ExWAS) approach was used to identify risk and protective factors and compute aggregate exposomic scores. Logistic regression models were applied to test associations and model fit of exposomic scores with suicide attempts in independent data. Youth from the Adolescent Brain Cognitive Development (ABCD) study, the UK Millennium Cohort Study (MCS), and the Children's Hospital of Philadelphia emergency department (CHOP-ED) were included in the study. Exposures A single-weighted exposomic score that sums significant risk and protective environmental/lifestyle factors. Main Outcome and Measure Self-reported suicide attempt. Results A total of 40 364 youth were included in this analysis: 11 564 from the ABCD study (3 waves of assessment; mean [SD] age, 12.0 [0.7] years; 6034 male [52.2%]; 344 attempted suicide [3.0%]; 1154 environmental/lifestyle factors were included in the ABCD study), 9000 from the MCS cohort (mean [SD] age, 17.2 [0.3] years; 4593 female [51.0%]; 661 attempted suicide [7.3%]; 2864 environmental/lifestyle factors were included in the MCS cohort), and 19 800 from the CHOP-ED cohort (mean [SD] age, 15.3 [1.5] years; 12 937 female [65.3%]; 2051 attempted suicide [10.4%]; 36 environmental/lifestyle factors were included in the CHOP-ED cohort). In the ABCD discovery subsample, ExWAS identified 99 risk and protective exposures significantly associated with suicide attempt. A single weighted exposomic score that sums significant risk and protective exposures was associated with suicide attempt in an independent ABCD testing subsample (odds ratio [OR], 2.2; 95% CI, 2.0-2.6; P < .001) and explained 17.6% of the variance (based on regression pseudo-R2) in suicide attempt over and above that explained by age, sex, race, and ethnicity (2.8%) and by family history of suicide (6.3%). Findings were consistent in the MCS and CHOP-ED cohorts (explaining 22.6% and 19.3% of the variance in suicide attempt, respectively) despite clinical, demographic, and exposure differences. In all cohorts, compared with youth at the median quintile of the exposomic score, youth at the top fifth quintile were substantially more likely to have made a suicide attempt (OR, 4.3; 95% CI, 2.6-7.2 in the ABCD study; OR, 3.8; 95% CI, 2.7-5.3 in the MCS cohort; OR, 5.8; 95% CI, 4.7-7.1 in the CHOP-ED cohort). Conclusions and Relevance Results suggest that exposomic scores of suicide attempt provided a generalizable method for risk classification that can be applied in diverse samples from clinical or population settings.
Collapse
Affiliation(s)
- Elina Visoki
- Department of Child and Adolescent Psychiatry and Behavioral Sciences, Children’s Hospital of Philadelphia (CHOP), Philadelphia, Pennsylvania
- Lifespan Brain Institute of CHOP and Penn Medicine, Philadelphia, Pennsylvania
| | - Tyler M. Moore
- Lifespan Brain Institute of CHOP and Penn Medicine, Philadelphia, Pennsylvania
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Xinhe Zhang
- Cambridge University, Cambridge, United Kingdom
| | - Kate T. Tran
- Department of Child and Adolescent Psychiatry and Behavioral Sciences, Children’s Hospital of Philadelphia (CHOP), Philadelphia, Pennsylvania
- Lifespan Brain Institute of CHOP and Penn Medicine, Philadelphia, Pennsylvania
| | - Christina Ly
- Lifespan Brain Institute of CHOP and Penn Medicine, Philadelphia, Pennsylvania
| | - Mārtiņš M. Gataviņš
- Department of Child and Adolescent Psychiatry and Behavioral Sciences, Children’s Hospital of Philadelphia (CHOP), Philadelphia, Pennsylvania
- Lifespan Brain Institute of CHOP and Penn Medicine, Philadelphia, Pennsylvania
| | - Grace E. DiDomenico
- Department of Child and Adolescent Psychiatry and Behavioral Sciences, Children’s Hospital of Philadelphia (CHOP), Philadelphia, Pennsylvania
- Lifespan Brain Institute of CHOP and Penn Medicine, Philadelphia, Pennsylvania
| | - Leah Brogan
- Center for Violence Prevention, Children’s Hospital of Philadelphia (CHOP), Philadelphia, Pennsylvania
| | - Joel A. Fein
- Center for Violence Prevention, Children’s Hospital of Philadelphia (CHOP), Philadelphia, Pennsylvania
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | | | - Sinan Guloksuz
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, the Netherlands
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut
| | - Ran Barzilay
- Department of Child and Adolescent Psychiatry and Behavioral Sciences, Children’s Hospital of Philadelphia (CHOP), Philadelphia, Pennsylvania
- Lifespan Brain Institute of CHOP and Penn Medicine, Philadelphia, Pennsylvania
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| |
Collapse
|
2
|
Zheng J, Zhang H, Shi J, Li X, Zhang J, Zhang K, Gao Y, He J, Dai J, Wang J. Association of air pollution exposure with overweight or obesity in children and adolescents: A systematic review and meta-analysis. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 910:168589. [PMID: 37984657 DOI: 10.1016/j.scitotenv.2023.168589] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 11/12/2023] [Accepted: 11/13/2023] [Indexed: 11/22/2023]
Abstract
Childhood overweight and obesity is a global problem. 38 million children under five years old were reported as being overweight/obese in 2019. However, current evidence regarding the effects of air pollution on children weight status remains scarce and inconsistent. This study aimed to determine the association between air pollutants and the weight status of children and adolescents. Four databases were searched up to August 9, 2023. Adjusted merged odds ratios (ORs), regression coefficients (β), and their 95 % confidence intervals (95 % CIs) were calculated and pooled. A total of 27 studies were included. The results showed that air pollutants had adverse effects on the body weight of children and adolescents. Exposure to PM1, PM2.5, PMcoarse, and PM10 were associated with increased risk of overweight/obesity, with pooled ORs (95 % CI) of 1.23 (1.09, 1.40), 1.18 (1.10, 1.28), 1.04 (1.03, 1.05) and 1.11 (1.06, 1.17) per 10 μg/m3 increment, respectively. Individuals with higher exposure levels to NOX, O3, SO2 and CO (per 10 μg/m3 increment) were associated with 12 %, 6 %, 28 % and 1 % increased odds of being overweight/obese, respectively. With respect to the level of body mass index, the pooled β (95 % CIs) for each 10 μg/m3 increase in PM1, PM2.5, PM10, and NOX exposure were 0.15 (0.12, 0.18), 0.11 (0.06, 0.16), 0.07 (0.03, 0.10), and 0.03 (0.01, 0.04), respectively. PM1 has relatively strong adverse effects on body weight status. The subgroup analysis revealed a significantly increase in the risk of overweight/obesity when the concentrations of PM2.5, PM10, and NO2 exceeded 35 μg/m3, 50 μg/m3, and 40 μg/m3, respectively. Exposure to PM2.5, PM10 and NOX increased the risk of overweight/obesity, especially in Asia. This study provides evidence of the association between air pollution and being overweight/obese in children and adolescents.
Collapse
Affiliation(s)
- Jingying Zheng
- School of Public Health, Jilin University, Changchun 130021, China
| | - Huiling Zhang
- School of Public Health, Jilin University, Changchun 130021, China
| | - Jianyang Shi
- School of Public Health, Jilin University, Changchun 130021, China
| | - Xin Li
- School of Public Health, Jilin University, Changchun 130021, China
| | - Jing Zhang
- School of Public Health, Jilin University, Changchun 130021, China
| | - Kunlun Zhang
- School of Public Health, Jilin University, Changchun 130021, China
| | - Yameng Gao
- School of Public Health, Jilin University, Changchun 130021, China
| | - Jingtong He
- School of Public Health, Jilin University, Changchun 130021, China
| | - Jianghong Dai
- School of Public Health, Xinjiang Medical University, Xinjiang 834000, China
| | - Juan Wang
- School of Public Health, Jilin University, Changchun 130021, China.
| |
Collapse
|
3
|
The Emerging Prevalence of Obesity within Families in Europe and its Associations with Family Socio-Demographic Characteristics and Lifestyle Factors; A Cross-Sectional Analysis of Baseline Data from the Feel4Diabetes Study. Nutrients 2023; 15:nu15051283. [PMID: 36904286 PMCID: PMC10005317 DOI: 10.3390/nu15051283] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 02/24/2023] [Accepted: 03/02/2023] [Indexed: 03/08/2023] Open
Abstract
The Feel4Diabetes study is a type 2 diabetes prevention program that recruited 12,193 children [age: 8.20 (±1.01) years] and their parents from six European countries. The current work used pre-intervention data collected from 9576 children-parents pairs, to develop a novel family obesity variable and to examine its associations with family sociodemographic and lifestyle characteristics. Family obesity, defined as the presence of obesity in at least two family members, had a prevalence of 6.6%. Countries under austerity measures (Greece and Spain) displayed higher prevalence (7.6%), compared to low-income (Bulgaria and Hungary: 7%) and high-income countries (Belgium and Finland: 4.5%). Family obesity odds were significantly lower when mothers (OR: 0.42 [95% CI: 0.32, 0.55]) or fathers (0.72 [95% CI: 0.57, 0.92]) had higher education, mothers were fully (0.67 [95% CI: 0.56, 0.81]) or partially employed (0.60 [95% CI: 0.45, 0.81]), families consumed breakfast more often (0.94 [95% CI: 0.91 0.96]), more portions of vegetables (0.90 [95% CI: 0.86, 0.95]), fruits (0.96 [95% CI: 0.92, 0.99]) and wholegrain cereals (0.72 [95% CI: 0.62, 0.83]), and for more physically active families (0.96 [95% CI: 0.93, 0.98]). Family obesity odds increased when mothers were older (1.50 [95% CI: 1.18, 1.91]), with the consumption of savoury snacks (1.11 [95% CI: 1.05, 1.17]), and increased screen time (1.05 [95% CI: 1.01, 1.09]). Clinicians should familiarise themselves with the risk factors for family obesity and choose interventions that target the whole family. Future research should explore the causal basis of the reported associations to facilitate devising tailored family-based interventions for obesity prevention.
Collapse
|
4
|
Relationship of 24-Hour Movement Behaviors with Weight Status and Body Composition in Chinese Primary School Children: A Cross-Sectional Study. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19148586. [PMID: 35886438 PMCID: PMC9319103 DOI: 10.3390/ijerph19148586] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 07/10/2022] [Accepted: 07/12/2022] [Indexed: 02/01/2023]
Abstract
24 h movement behaviors, specifically physical activity (PA), sedentary behavior, and sleep, play a crucial role in the prevention and intervention of childhood obesity. This study aimed to examine the association of 24 h movement behaviors with weight status and body composition among Chinese primary school children. Using a random stratified sampling, 978 eligible participants (9.1 ± 1.4 years, 53.2% boys) were recruited from 1 May to 15 July 2021. Demographics included children’s age, gender, grade, parents’ education level, and household income. Movement behaviors were measured by validated self-reported scales. Weight status and body composition (percent of body fat, PBF; fat-free mass, FFM; skeletal muscle mass, SMM) were measured objectively. Results indicated that participants who were younger, boys, and at lower grade showed higher guidelines adherence. PA was inversely associated with PBF, while screen time (ST) was positively associated with overweight/obesity risk and FFM. Sleep showed no association with any health indicators. Meeting the behavioral guidelines was associated with better weight status and lower PBF, yet not with FFM and SMM. Interventions to improve the Children’s weight status and PBF should involve enhancing their overall movement behaviors and considering their demographic differences. More research on examining the association of movement guidelines adherence with body composition indicators is needed.
Collapse
|