Israel Journal of Health Policy Research (Jun 2020)

A comprehensive descriptive assessment of obesity related chronic morbidity and estimated annual cost burden from a population-based electronic health record database

  • Orna Reges,
  • Morton Leibowitz,
  • Avital Hirsch,
  • Dror Dicker,
  • Nick Finer,
  • Christiane Lundegaard Haase,
  • Altynai Satylganova,
  • Maya Leventer-Roberts,
  • Becca Feldman

DOI
https://doi.org/10.1186/s13584-020-00378-1
Journal volume & issue
Vol. 9, no. 1
pp. 1 – 10

Abstract

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Abstract Background The growing prevalence of obesity and its complications pose a huge burden on the individual and health care systems worldwide. This study presents the frequency of multiple prevalent co-morbidities and estimated annual cost burden by body mass index (BMI) groups, age, and sex among the Israeli adult population to provide policy makers with further evidence to appropriately target interventions. Methods This cross-sectional study utilized population-based electronic medical records from the largest payer-provider health fund in Israel. The population included individuals ≥25 years as of 01/01/2014. A new approach assessing body system-related morbidity (BSRM) prevalence was assessed along with estimated annual cost burden for the year 2015 and presented across BMI group, age, and sex via heat maps. Results Among 1,756,791 adults, 65% had an elevated BMI (BMI > 25 kg/m2). Heat map analysis demonstrated a higher multi-BSRM prevalence and relative estimated annual cost burden among participants with obesity in all age groups. There was a notably higher multi-BSRM prevalence among men and women aged 25–29 with class III obesity (26 and 30%, respectively) compared to the corresponding BMI groups between 18·5- < 25 kg/m2 (5 and 9%, respectively). Healthcare costs were 1·72 times higher among men aged 25–29 with class III obesity and 2·75 times among women aged 25–29 with class III obesity compared to those of healthy weight. Conclusions The detailed analysis describes the uneven distribution of burdens across BMI groups, age, and sex allowing policy makers to identify sub-populations for targeted interventions.

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