Obesity has become a major global health concern, nearly tripling in prevalence over the past four decades. In the US, over 40% of adults are obese, with projections exceeding 50% by 2030. Obesity imposes a significant economic burden, accounting for a substantial portion of national medical expenditures. Individuals with obesity face increased risks of various complications (ORCs), including cardiovascular diseases, metabolic disorders, and others, substantially contributing to the economic burden. While previous studies have estimated costs associated with ORCs, many used regional databases or had short follow-up periods, limiting generalizability. This study aimed to examine the association between the number and type of ORCs and total healthcare costs over an eight-year period using a large, nationally representative US dataset to better understand the long-term financial implications of obesity and its associated complications. The study sought to address the existing gap in understanding the longitudinal cost progression of ORCs by using comprehensive, nationwide longitudinal data to determine the relationship between the burden of comorbidity (both the number and type of ORCs) and total healthcare costs over time.

Prior research highlighted the substantial economic burden of obesity and its associated complications in the USA. A 2015 study by Li et al. identified hypertension, dyslipidemia, and osteoarthritis as the costliest ORCs. However, this study's limitations included a predominantly White population, limiting generalizability. Divino et al. (2021) identified osteoarthritis of the knee and heart failure with preserved ejection fraction as the highest-cost ORCs over one year. However, their study's relatively short follow-up period (maximum 3 years) limited insights into cost progression. The heterogeneity in the burden of ORCs across individuals necessitates identifying those with the greatest burden to effectively target preventive services and weight management strategies. This study addresses the limitations of previous research by using a large national dataset with a long follow-up period to assess the longitudinal association between ORCs and healthcare costs.

This retrospective cohort study utilized linked data from the IQVIA Ambulatory Electronic Medical Records (AEMR) database and the IQVIA PharMetrics® Plus database. The study population included adults (≥18 years) with a BMI of 30–<70 kg/m² between January 1, 2007, and March 31, 2012 (index date). Inclusion criteria required continuous enrollment for at least one year pre-index and 2–8 years post-index. Individuals were grouped by the number and type of 14 pre-defined ORCs during the baseline year. The primary outcome was annual total adjusted direct per-person healthcare costs, calculated and converted to 2019 USD. Generalized estimating equations were used to analyze the data, adjusting for age, sex, region, year of cost, and cost department code. The study excluded individuals with certain conditions like cancer (except non-melanoma skin cancer), those enrolled in Medicare or State Children's Health Insurance Program, and those with significant BMI fluctuations. The study identified 14 ORCs using ICD-9 CM and ICD-10-CM codes. Costs were evaluated for inpatient hospitalization, outpatient care, emergency department visits, and medications. Data analysis involved generalizing estimating equations to predict total costs for each cohort, adjusting for several factors. The analysis specifically focused on costs related to several key ORCs, such as type 2 diabetes, heart failure, chronic kidney disease, and osteoarthritis, along with the impact of multiple ORCs and high cardiovascular risk factors.

The study included 28,583 individuals. At baseline, 44.4% had no ORCs, 25.3% had one, 14.6% had two, and 15.7% had three or more. Annual adjusted direct healthcare costs increased significantly with the number of ORCs and over the eight-year follow-up. Outpatient costs were the largest contributor to total costs. Specific ORCs showed substantial cost increases over time, with chronic kidney disease (+78.8%) and type 2 diabetes (+47.8%) showing the largest percentage increases from year 1 to year 8. The presence of three or more ORCs was identified as a key cost driver. Individuals with two or more cardiovascular risk factors (hypertension, dyslipidemia, and type 2 diabetes) incurred higher costs compared to those with fewer risk factors. Costs for individuals with high cardiovascular risk were similar to those with type 2 diabetes. Figure 1 presents the adjusted mean annual total all-cause healthcare costs averaged across eight years for individuals with varying numbers of ORCs. Figure 2 details the adjusted mean annual costs stratified by the presence or absence of specific ORCs. Figure 3 shows the adjusted mean total all-cause per-person healthcare costs at year 1 and year 8, stratified by specific ORCs. Figure 4 displays observed mean inpatient, outpatient, ED, and drug costs per person in the baseline year and years 1 and 8.

This study's findings highlight the substantial and progressive cost burden associated with ORCs in individuals with obesity. The majority of participants had at least one ORC, indicating a high prevalence of comorbidities. The significant increase in costs over time underscores the long-term implications of these complications. The results consistently show that more ORCs lead to higher costs, regardless of specific obesity class. The dominance of outpatient costs suggests intensive medical management, potentially leading to fewer hospitalizations. The association between multiple cardiovascular risk factors and high costs emphasizes the importance of early intervention and risk factor management. The study's large sample size and long follow-up period offer considerable strength. However, the findings might not be fully generalizable to all US populations due to the focus on commercially insured individuals.

This large-scale, longitudinal study demonstrates a strong association between the number of obesity-related complications and escalating healthcare costs over eight years. The findings highlight the importance of early intervention and comprehensive management of ORCs to mitigate the long-term financial burden. Further research should examine the impact of ORCs in uninsured and publicly insured populations, explore the role of severity of complications and lifestyle factors, and investigate cost-effective intervention strategies.

The study's focus on commercially insured individuals limits generalizability to uninsured or publicly insured populations. The inclusion criterion of continuous database information may have introduced selection bias, favoring healthier individuals who remained employed and insured throughout the study. The study's inability to account for ORC severity, lifestyle factors, socioeconomic status, and education level represents further limitations. The high cost observed in the first year might be due to the study design and interaction with the insurance system. Further research is needed to address these limitations and investigate the impact of ORCs in under-represented populations.