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Background Poland's National Health Fund (NFZ) publishes four national series indexed by ICD-10 code E66. Although their labels suggest related measures of obesity, differences in analytical unit, entry rule, look-back period, and temporal structure may alter both the reported level and the apparent response to healthcare-system disruption. We examined whether selecting an official NFZ E66 series materially changes the level, trend, and permissible public-health interpretation of recorded obesity-related activity. Methods This retrospective, descriptive ecological time-series study audited 44 annual resources covering registered morbidity, first-recorded patients, annual E66 patients, and E66-coded services in 2015–2025. We analyzed counts and population-scaled administrative rates, summarized long-term change using log-linear annual percentage change (APC), and used a one-year 2020 indicator as a descriptive pandemic-era stress test. An endpoint sensitivity analysis excluded 2025. Independent BMI sources provided cross-sectional contextual triangulation for 2025. Results In 2025, two official person-based series yielded 1,534,022 persons with a current or earlier principal E66 record and 325,769 persons with qualifying current-year E66 activity, a 4.7-fold difference arising from construction rather than alternative estimates of a single quantity. From 2015 to 2025, endpoint increases ranged from 178.1 to 332.5%, and population-scaled APCs from 10.5 to 14.5%. During 2020, the first year of the COVID-19 pandemic, deviations from the fitted trend were modest for registered morbidity (−3.5%) but substantially larger for the three series requiring current-year activity (−39.4 to −44.3%). Conclusions The same E66 code supports four distinct administrative trajectories. Their growth may reflect a genuine rise in clinical obesity together with changes in recognition, access, recording, and service delivery; the aggregates cannot separate these contributions. Explicit estimand definitions are therefore essential when NFZ indicators are used for surveillance or policy.
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Poboży et al. (2026) studied this question.
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