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A latent class analysis of cardiometabolic risk factors and the predicted prevalence of subclinical atherosclerosis in middle-aged Swedish adults

Anindya, Kanya ; Bendtsen, Marcus ; Jernberg, Tomas ; Calling, Susanna LU ; Lind, Lars ; Weinehall, Lars ; Ng, Nawi and Rosvall, Maria LU (2026) In Scientific Reports 16(1).
Abstract

Previous research on cardiometabolic risk has mostly used a variable-centred approach, assessing risk factors separately or in predefined combinations. This study used a probabilistic modelling approach to identify distinct cardiometabolic risk classes and estimate the predicted prevalence of subclinical atherosclerosis. The analysis included 28,307 middle-aged adults from the Swedish CArdioPulmonary bioImage Study (2013–2018), linked to national registers. Eleven risk factors were assessed: smoking, alcohol consumption, sodium and fibre intake, physical activity, stress, waist circumference, triglycerides, HDL-cholesterol, blood pressure, and fasting glucose. Subclinical atherosclerosis was defined using coronary artery calcium (CAC)... (More)

Previous research on cardiometabolic risk has mostly used a variable-centred approach, assessing risk factors separately or in predefined combinations. This study used a probabilistic modelling approach to identify distinct cardiometabolic risk classes and estimate the predicted prevalence of subclinical atherosclerosis. The analysis included 28,307 middle-aged adults from the Swedish CArdioPulmonary bioImage Study (2013–2018), linked to national registers. Eleven risk factors were assessed: smoking, alcohol consumption, sodium and fibre intake, physical activity, stress, waist circumference, triglycerides, HDL-cholesterol, blood pressure, and fasting glucose. Subclinical atherosclerosis was defined using coronary artery calcium (CAC) scores and the presence of carotid plaque. A three-step latent class analysis identified four cardiometabolic risk classes: “low fibre intake and normolipidemia” (55.2%, Class 1), “high sodium intake and normolipidemia” (12.8%, Class 2), “unhealthy lifestyle and heightened metabolic risk” (10.1%, Class 3), and “unhealthy lifestyle and high metabolic risk” (21.9%, Class 4). Predicted mean CAC scores ranged from 42.6 (Class 2, 95% CI 39.0–46.3) to 92.1 (Class 4, 95% CI 86.2–98.0). Predicted carotid plaque prevalence ranged from 51.6% (Class 2, 95% CI 50.6–52.6) to 60.8% (Class 4, 95% CI 59.8–61.9). Latent classes offered a complementary descriptive framework beyond single risk factors, supporting more tailored prevention according to risk profiles.

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author
; ; ; ; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Atherosclerosis, Bias-adjusted three-step estimation, Cardiometabolic risk factors, Cardiovascular disease, Latent class analysis
in
Scientific Reports
volume
16
issue
1
article number
8255
publisher
Nature Publishing Group
external identifiers
  • scopus:105032417222
  • pmid:41781514
ISSN
2045-2322
DOI
10.1038/s41598-026-42858-5
language
English
LU publication?
yes
additional info
Publisher Copyright: © The Author(s) 2026.
id
87404aff-c1c0-4380-935b-1139a54e910a
date added to LUP
2026-05-18 15:44:49
date last changed
2026-05-19 03:00:02
@article{87404aff-c1c0-4380-935b-1139a54e910a,
  abstract     = {{<p>Previous research on cardiometabolic risk has mostly used a variable-centred approach, assessing risk factors separately or in predefined combinations. This study used a probabilistic modelling approach to identify distinct cardiometabolic risk classes and estimate the predicted prevalence of subclinical atherosclerosis. The analysis included 28,307 middle-aged adults from the Swedish CArdioPulmonary bioImage Study (2013–2018), linked to national registers. Eleven risk factors were assessed: smoking, alcohol consumption, sodium and fibre intake, physical activity, stress, waist circumference, triglycerides, HDL-cholesterol, blood pressure, and fasting glucose. Subclinical atherosclerosis was defined using coronary artery calcium (CAC) scores and the presence of carotid plaque. A three-step latent class analysis identified four cardiometabolic risk classes: “low fibre intake and normolipidemia” (55.2%, Class 1), “high sodium intake and normolipidemia” (12.8%, Class 2), “unhealthy lifestyle and heightened metabolic risk” (10.1%, Class 3), and “unhealthy lifestyle and high metabolic risk” (21.9%, Class 4). Predicted mean CAC scores ranged from 42.6 (Class 2, 95% CI 39.0–46.3) to 92.1 (Class 4, 95% CI 86.2–98.0). Predicted carotid plaque prevalence ranged from 51.6% (Class 2, 95% CI 50.6–52.6) to 60.8% (Class 4, 95% CI 59.8–61.9). Latent classes offered a complementary descriptive framework beyond single risk factors, supporting more tailored prevention according to risk profiles.</p>}},
  author       = {{Anindya, Kanya and Bendtsen, Marcus and Jernberg, Tomas and Calling, Susanna and Lind, Lars and Weinehall, Lars and Ng, Nawi and Rosvall, Maria}},
  issn         = {{2045-2322}},
  keywords     = {{Atherosclerosis; Bias-adjusted three-step estimation; Cardiometabolic risk factors; Cardiovascular disease; Latent class analysis}},
  language     = {{eng}},
  number       = {{1}},
  publisher    = {{Nature Publishing Group}},
  series       = {{Scientific Reports}},
  title        = {{A latent class analysis of cardiometabolic risk factors and the predicted prevalence of subclinical atherosclerosis in middle-aged Swedish adults}},
  url          = {{http://dx.doi.org/10.1038/s41598-026-42858-5}},
  doi          = {{10.1038/s41598-026-42858-5}},
  volume       = {{16}},
  year         = {{2026}},
}