# Utility of the US Metabolic Syndrome Severity Calculator for Group-Level Comparison in Estonia

**Authors:** Ülle Parm, Anna-Liisa Tamm, Heete Kuuskla

PMC · DOI: 10.3390/medicina62020363 · Medicina · 2026-02-12

## TL;DR

This study evaluated a US-based metabolic syndrome severity calculator in Estonian women, finding it useful for group comparisons but needing local adaptation for individual risk assessment.

## Contribution

The study demonstrates the applicability of a US-derived MetS calculator for group-level comparisons in a non-US population.

## Key findings

- Physically active women had lower BMI and higher HDL cholesterol compared to other groups.
- The commercial diet plan group showed higher MetS percentiles and severity levels despite lower Z-scores.
- The US MetS calculator can be used for group comparisons in Estonia but requires adaptation for individual risk assessment.

## Abstract

Background and Objectives: Metabolic syndrome (MetS) is globally prevalent, highlighting the need for easy risk identification. This study determined the MetS severity score in different groups of women in Estonia using a calculator developed based on the US population. Materials and Methods: The sample included 153 women (20–50 years): commercial diet plan (CDP) users, physically active women (physical activity, PA, >5 h/week), and a control group (CG). The factors assessed included age, gender, body mass index (BMI), systolic blood pressure, high-density lipoprotein (HDL) cholesterol, triglycerides, and fasting glucose, yielding a MetS percentile and Z-score. Statistical analyses comprised descriptive statistics, t-tests, and χ2 tests. Differences were considered statistically significant at p ≤ 0.05 and at <0.017 when comparing the three study groups. Results: The PA group was younger and had a lower BMI (p < 0.05), while the CDP group had lower HDL cholesterol levels (p < 0.017). MetS percentiles were higher in the CDP group (vs. PA p = 0.002; vs. CG p = 0.016). Despite having a lower Z-score than US women, the CDP group showed higher MetS severity levels (>1). Conclusions: The US calculator is also suitable for comparing different MetS risk study groups located outside the US, but for assessing individual MetS risk, it must be adapted and validated for the relevant population.

## Linked entities

- **Diseases:** metabolic syndrome (MONDO:0000816)

## Full-text entities

- **Genes:** APOB (apolipoprotein B) [NCBI Gene 338] {aka FCHL2, FLDB, LDLCQ4, apoB-100, apoB-48}, APOA1 (apolipoprotein A1) [NCBI Gene 335] {aka AMYLD3, HPALP2, apo(a)}, CRP (C-reactive protein) [NCBI Gene 1401] {aka PTX1}
- **Diseases:** stroke (MESH:D020521), overweight (MESH:D050177), Obesity (MESH:D009765), fatty liver disease (MESH:D005234), weight gain (MESH:D015430), visceral adiposity (MESH:D007418), neuroendocrine dysregulation (MESH:D018358), metabolic abnormalities (MESH:D008659), pancreatic cancer (MESH:D010190), dyslipidemia (MESH:D050171), hyperlipidemia (MESH:D006949), congenital defects (MESH:D000013), peripheral vascular diseases (MESH:D016491), MetS (MESH:D024821), injury to (MESH:D014947), inflammation (MESH:D007249), prediabetes (MESH:D011236), Diabetes (MESH:D003920), heart disease (MESH:D006331), infarction (MESH:D007238), type 2 diabetes (MESH:D003924), Abdominal obesity (MESH:D056128), impaired glucose tolerance (MESH:D018149), hepatocellular carcinoma (MESH:D006528), atherosclerotic cardiovascular diseases (MESH:D050197), hypertension (MESH:D006973), insulin resistance (MESH:D007333), weight loss (MESH:D015431), ischemic disease (MESH:D017202), cardiovascular disease (MESH:D002318)
- **Chemicals:** blood glucose (MESH:D001786), Cholesterol (MESH:D002784), sugars (MESH:D000073893), PA (MESH:D011478), fats (MESH:D005223), TGs (MESH:C026285), TG (MESH:D014280), uric acid (MESH:D014527), EDTA (MESH:D004492), lipid (MESH:D008055), calcium (MESH:D002118), GL (MESH:D005947), magnesium (MESH:D008274), sodium (MESH:D012964), CDP (-), carbohydrate (MESH:D002241)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

_Full body text omitted from this summary view._ Fetch the complete paper as Markdown: https://tomesphere.com/paper/PMC12943269/full.md

## Figures

3 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12943269/full.md

## References

41 references — full list in the complete paper: https://tomesphere.com/paper/PMC12943269/full.md

---
Source: https://tomesphere.com/paper/PMC12943269