DOI: 10.1097/ms9.0000000000004967 ISSN: 2049-0801

Obesity as a risk factor for acute lymphoblastic leukemia in individuals younger than 20 years across 204 countries and territories from 1990 to 2021: a benchmarking global analysis

Aishwar Dixit, Abdul Rafae Faisal, Asad Zaman, Muhammad Faizan, Ahila Ali, Syed Zaeem Ahmad, Henna A. Qadri, Mohammad Maaz Alam, Pramod Singh
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Background:

Childhood obesity has increased substantially over the past three decades and has been implicated in the development and progression of several malignancies, including acute lymphoblastic leukemia (ALL). This study evaluated global trends in the ALL burden attributable to high body mass index (BMI) from 1990 to 2021 using Global Burden of Disease (GBD) 2021 data.

Methods:

We conducted an ecological, population-level, cross-sectional time-trend analysis across 204 countries and territories. Age-standardized incidence rates (ASIR), mortality rates, and disability-adjusted life year rates per 100 000 population were extracted. Joinpoint regression was used to assess temporal trends, and Spearman correlation was employed to evaluate associations between national obesity prevalence and ALL incidence. Estimates were derived from GBD comparative risk assessment modeling and are reported with 95% uncertainty intervals.

Results:

Globally, the ASIR of ALL attributable to high BMI increased from 0.83 to 0.95 per 100 000 between 1990 and 2021 (a 14.2% increase). The highest burden was observed in North America and Western Europe, while middle-income regions demonstrated rising incidence and mortality trends. Country-level obesity prevalence was strongly correlated with ASIR ( ρ  = 0.76, P < 0.01), indicating a population-level association. Lower reported rates in low-income countries likely reflect underdiagnosis and limited cancer registry coverage. GBD modeling attributed approximately 14.2% of the observed global increase in ALL incidence to high BMI exposure.

Conclusion:

This ecological analysis demonstrates a population-level association between rising obesity prevalence and increasing global ALL burden. However, causal inference cannot be established due to the cross-sectional design and reliance on modeled estimates. Findings should be interpreted cautiously, particularly in data-limited settings. Longitudinal and individual-level studies are needed to clarify causality and inform targeted prevention strategies.

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