Cause-of-Death Chains and Years of Life Lost Among Children and Adolescents in Chengdu, China: A Hospital-Based Case Series

Technical Summary: Cause-of-Death Chains and Years of Life Lost Among Children and Adolescents in Chengdu, China

Problem Statement
Current research on child and adolescent mortality in China often suffers from three critical limitations: (1) a narrow age focus, predominantly restricted to children under five, leaving the 5–19 year developmental stage under-analyzed; (2) fragmented cause-of-death (COD) analysis that isolates specific diseases or injuries rather than examining the holistic mortality spectrum; and (3) a reliance on static, single-level statistical descriptions that fail to capture the dynamic pathophysiological sequences leading to death. While global Sustainable Development Goals (SDG 3.2) target the end of preventable deaths, understanding the evolving mortality patterns across the entire 0–19 year continuum is essential for tailoring life-course-specific interventions. Existing Chinese mortality monitoring systems primarily record the underlying cause of death but lack detailed documentation of the dynamic death process (the sequence from root cause to direct cause).

Methodology
This hospital-based case series study analyzed 666 pediatric and adolescent deaths (aged 0–19 years) recorded between 2018 and 2024 across eight major tertiary hospitals in Chengdu, China. The participating institutions included comprehensive general hospitals, specialized women's and children's hospitals, and public health clinical centers, ensuring geographic representation across urban and suburban areas.

• Data Collection: Researchers extracted demographic data, admission/death dates, and the complete sequence of causes of death from electronic medical records and death certificates.
• Classification: Causes of death were coded using ICD-10 and aggregated to chapter levels. Age was stratified into three critical periods: Infancy (0–1 year, subdivided into neonatal and post-neonatal), Early Childhood (1–4 years), and School-age/Adolescence (5–19 years).
• Cause-of-Death (COD) Chain Analysis: The core analytical innovation involved constructing COD chains to delineate pathways from underlying to immediate causes. Chains were classified as "complete" (underlying → intermediate → immediate) or "incomplete" (proximal underlying → immediate). Sankey diagrams were utilized to visualize these flow sequences.
• Statistical Analysis: Descriptive statistics summarized demographics. Associations between categorical variables (age, sex, year) and COD categories were tested using Pearson's chi-square or Fisher's exact tests, with Holm-Bonferroni corrections for multiple comparisons. Standardized residuals identified specific cells driving associations.
• Burden Quantification: Years of Life Lost (YLL) were calculated for each death using a reference life expectancy of 78.6 years, quantifying the premature mortality burden.

Key Results
The study identified a clear, age-dependent epidemiological transition in mortality patterns:

1. Age-Stratified Mortality Spectrum:

   • Infancy (0–1 year): Dominated by Perinatal conditions (66.1% of infant deaths), particularly in the neonatal period (0–27 days), which accounted for 40.2% of all deaths. This group exhibited the highest YLL per death (mean 78.6 years).
   • Early Childhood (1–4 years) & Adolescence (5–19 years): A sharp shift occurred where Injury and poisoning became the leading cause of death (33.0% and 32.7%, respectively). While YLL per death decreased slightly in these groups (75.5 and 65.4 years), the aggregate burden remained substantial due to high case volumes.

2. COD Chain Pathways:

   • Infancy: The dominant fatal pathway flowed from perinatal conditions (e.g., disorders related to prematurity) through intermediate complications to respiratory failure.
   • Early Childhood: Pathways were typically short and direct, moving from external causes (e.g., transport accidents, falls) directly to fatal injuries.
   • Adolescence: While external causes remained prominent, chronic conditions (e.g., nervous system diseases, congenital anomalies) emerged as significant underlying causes, often culminating in respiratory diseases. Notably, intentional self-harm was identified as a specific risk mechanism in this group.

3. Gender and Temporal Trends:

   • Males accounted for 56.8% of deaths, with a statistically significant higher proportion of injury-related deaths (19.0%) compared to females (13.5%).
   • Temporal analysis revealed a transient peak in injury-related deaths in 2021 (43.5% of deaths that year), coinciding with the relaxation of COVID-19 restrictions, while perinatal deaths peaked in 2020.

4. Data Quality Indicators:

   • "Symptoms and signs" (ill-defined causes) accounted for 13.2% of total deaths, serving as a sentinel indicator for potential diagnostic limitations or deficiencies in death certification practices.

Key Contributions

• Dynamic Pathway Visualization: The study moves beyond static frequency distributions by applying COD chain analysis to reveal the specific sequences of morbid events leading to death across different developmental stages.
• Comprehensive Age Coverage: It provides a systematic analysis of the 5–19 year age group, a demographic often excluded from standard pediatric mortality studies in China.
• Quantification of Premature Mortality: By integrating YLL metrics, the study quantifies the life potential lost, highlighting the catastrophic burden of perinatal conditions in infancy versus the persistent threat of injuries in older children.
• Identification of Intervention Nodes: The analysis distinguishes between endogenous biological vulnerabilities (infancy) and exogenous environmental/behavioral risks (childhood/adolescence), pinpointing specific stages for targeted intervention.

Significance and Claims
The authors claim that this study delineates a fundamental epidemiological transition in child mortality in an urban Chinese setting: from endogenous biological vulnerabilities in infancy to exogenous environmental and behavioral risks in later childhood and adolescence.

The significance of these findings lies in their utility for life-course-specific prevention strategies:

• For Infants: Strengthening perinatal care, including maternal health, intrapartum management, and neonatal respiratory support.
• For Young Children: Implementing stringent, passive environmental injury prevention measures (e.g., traffic safety, fall prevention).
• For Adolescents: Adopting an integrated approach that combines environmental safety with mental health support and chronic disease management.

The paper concludes that while the study is limited by its hospital-based design (excluding out-of-hospital deaths) and reliance on clinical records rather than autopsies, the application of COD chain analysis offers a more actionable foundation for public health policy than traditional static statistics. It underscores the need for adaptive surveillance systems capable of detecting shifting risk patterns, as evidenced by the temporal fluctuations observed during the pandemic era.