MAPPING THE ATTRIBUTABLE ECONOMIC BURDEN OF OBESITY: A $210 BILLION DISEASE-SPECTRUM ANALYSIS ACROSS CLINICAL CONDITIONS IN CHINA
Author(s)
Shengwei Luo, PhD1, Wai-kit Ming, MBA, MPH, PhD, MD2, Chen Zhang, Master3, Joanne Su Yin Yoong, PhD4, Yanhong Catherine Dong, PhD4, Guochun Xiang, PhD5.
1¹ City University of Hong Kong ² National University of Singapore³ Peking University, Hongkong & Singapore & Beijing, Singapore, 2City University of Hong Kong, Hong Kong, China, 3¹ Cornell University ² University of Nottingham Ningbo, Ithaca & Ningbo（China）, NY, USA, 4National University of Singapore, Singapore, Singapore, 5Southern Medical University, Guangzhou, China.
1¹ City University of Hong Kong ² National University of Singapore³ Peking University, Hongkong & Singapore & Beijing, Singapore, 2City University of Hong Kong, Hong Kong, China, 3¹ Cornell University ² University of Nottingham Ningbo, Ithaca & Ningbo（China）, NY, USA, 4National University of Singapore, Singapore, Singapore, 5Southern Medical University, Guangzhou, China.
OBJECTIVES: Asked to identify obesity’s costliest complication, most economists cite type 2 diabetes—a framing that influences resource allocation. We examined whether this assumption holds in China by quantifying the disease-specific economic burden of elevated body mass index across 44 conditions and ten organ systems, and assessing implications of spending misalignment.
METHODS: Using data from the 2023 GBD study, we estimated condition-level population attributable fractions for 44 diseases associated with elevated body mass index. Attributable DALYs were monetized using a human capital approach based on China-specific per-capita GDP. We stratified $210.17 billion in attributable costs across organ systems, ranked diseases by attributable costs, identified high-PAF conditions, and modeled gains under five body mass index reduction scenarios using generalized impact fraction analysis.
RESULTS: Elevated body mass index accounted for 50,228,562 attributable DALYs and $210.17 billion in annual costs across 44 diseases. Contrary to the diabetes-centric assumption, non-endocrine conditions accounted for $144.56 billion (68.8%) of total costs. At the system level, burden was highest in endocrine and metabolic disorders ($66.61 billion), followed by cardiovascular diseases ($37.97 billion), musculoskeletal conditions ($27.09 billion), and neoplasms ($23.24 billion). Disease-level analysis showed type 2 diabetes had the highest attributable fraction (PAF 48.3%), while substantial burdens were also observed for chronic kidney disease (37.9%), hypertensive heart disease (35.4%), gallbladder disease (29.9%), gout (29.0%), ischemic heart disease (25.8%), atrial fibrillation (15.9%), and asthma (16.5%). A 25% reduction in body mass index exposure aligned with national noncommunicable disease targets would generate $52.54 billion in annual savings, concentrated in cardiovascular and musculoskeletal conditions.
CONCLUSIONS: The assumption that obesity’s economic burden is primarily driven by metabolic disease is not supported in China. Approximately two-thirds of obesity-attributable spending is concentrated in cardiovascular, musculoskeletal, and neoplastic conditions. These findings suggest current resource allocation patterns may underestimate the broader economic burden of elevated body mass index across health systems.
METHODS: Using data from the 2023 GBD study, we estimated condition-level population attributable fractions for 44 diseases associated with elevated body mass index. Attributable DALYs were monetized using a human capital approach based on China-specific per-capita GDP. We stratified $210.17 billion in attributable costs across organ systems, ranked diseases by attributable costs, identified high-PAF conditions, and modeled gains under five body mass index reduction scenarios using generalized impact fraction analysis.
RESULTS: Elevated body mass index accounted for 50,228,562 attributable DALYs and $210.17 billion in annual costs across 44 diseases. Contrary to the diabetes-centric assumption, non-endocrine conditions accounted for $144.56 billion (68.8%) of total costs. At the system level, burden was highest in endocrine and metabolic disorders ($66.61 billion), followed by cardiovascular diseases ($37.97 billion), musculoskeletal conditions ($27.09 billion), and neoplasms ($23.24 billion). Disease-level analysis showed type 2 diabetes had the highest attributable fraction (PAF 48.3%), while substantial burdens were also observed for chronic kidney disease (37.9%), hypertensive heart disease (35.4%), gallbladder disease (29.9%), gout (29.0%), ischemic heart disease (25.8%), atrial fibrillation (15.9%), and asthma (16.5%). A 25% reduction in body mass index exposure aligned with national noncommunicable disease targets would generate $52.54 billion in annual savings, concentrated in cardiovascular and musculoskeletal conditions.
CONCLUSIONS: The assumption that obesity’s economic burden is primarily driven by metabolic disease is not supported in China. Approximately two-thirds of obesity-attributable spending is concentrated in cardiovascular, musculoskeletal, and neoplastic conditions. These findings suggest current resource allocation patterns may underestimate the broader economic burden of elevated body mass index across health systems.
Conference/Value in Health Info
2026-11, ISPOR Europe 2026, Vienna, Austria
Value in Health, Volume 29, Issue 12S
Code
CO53
Topic
Clinical Outcomes, Economic Evaluation, Epidemiology & Public Health
Disease
Cardiovascular Disorders (including MI, Stroke, Circulatory), Diabetes/Endocrine/Metabolic Disorders (including obesity), Musculoskeletal Disorders (Arthritis, Bone Disorders, Osteoporosis, Other Musculoskeletal), Oncology, Urinary/Kidney Disorders