Cardiometabolic Risk Patterns Among Adults: A Latent Class Analysis from the Hoveyzeh Cohort Study

Q: What is the clinical evidence from this study?

Study design: Cohort. Population: Cardiometabolic risk / Incident dyslipidemia (n=1660). Intervention: Class 2 (higher-risk cardiometabolic profile with higher probabilities of hypertension, diabetes, metabolic waist, low physical activity, and high saturated-fat intake) vs. Class 1 (lower-risk cardiometabolic profile). Primary outcome: Incident dyslipidemia at reassessment (RR 1.03, 95% CI 0.92-1.14, p=0.626).

Q: What does this research mean for the field?

Membership in a higher-risk latent cardiometabolic profile is not associated with an increased risk of incident dyslipidemia over five years compared to a lower-risk profile. Novelty: ClaimNovelty.INCREMENTAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

Bahman Cheraghian; Nader Saki; Sara Sarvandian; Seyed Ahmad Hosseini; Rozhan Khezri; Zahra Rahimi

doi:10.21203/rs.3.rs-10825177/v1

October 16, 2026Open Access

Cardiometabolic Risk Patterns Among Adults: A Latent Class Analysis from the Hoveyzeh Cohort Study

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Key result

High-risk latent cardiometabolic profile is not associated with increased risk of incident dyslipidemia.

RR 1.03
95% CI 0.92-1.14
P=0.626
n=1,660

Why the study?

Cardiometabolic risk factors may cluster into heterogeneous patterns not fully captured by conventional approaches, and the association of latent cardiometabolic profiles with incident dyslipidemia required evaluation.

Does a high-risk latent cardiometabolic profile (Class 2) increase the risk of incident dyslipidemia compared to a lower-risk profile (Class 1) in adults free of dyslipidemia at baseline?

Key Points

To identify latent cardiometabolic risk profiles and examine their association with incident dyslipidemia among adults free of dyslipidemia at baseline.
Prospective cohort study including 1,660 adults free of dyslipidemia at baseline from the Hoveyzeh Cohort Study, reassessed after approximately five years.
Latent class analysis was conducted using five binary indicators: hypertension, diabetes, low physical activity, high saturated-fat intake, and metabolic waist.
Robust Poisson regression models were used to estimate crude and adjusted risk ratios (RRs) and 95% confidence intervals (CIs) for incident dyslipidemia.
A two-class model identified Class 1 (n=1,197, 72.1%) with lower indicator probabilities and Class 2 (n=463, 27.9%) with higher probabilities of hypertension (50.0%), diabetes (35.5%), and metabolic waist (82.4%).
During follow-up, 876 participants (52.8%) developed incident dyslipidemia.
Latent class membership was not significantly associated with incident dyslipidemia in crude analysis (RR = 0.97, 95% CI: 0.88–1.08; P=0.562) or fully adjusted analysis (adjusted RR = 1.03, 95% CI: 0.92–1.14; P=0.626).

Study Design

Type

Cohort (n=1,660)

Multicenter

No

Structured PICO

Does a high-risk latent cardiometabolic profile (Class 2) increase the risk of incident dyslipidemia compared to a lower-risk profile (Class 1) in adults free of dyslipidemia at baseline?

P

Population

1,660 Iranian adults (mean age 48.4 years, 63.7% female) free of dyslipidemia at baseline from the Hoveyzeh Cohort Study, followed for approximately 5 years.

E

Exposure

Latent Class 2 cardiometabolic profile (n=463, 27.9%), characterized by higher probabilities of hypertension (50.0%), diabetes (35.5%), metabolic waist (82.4%), low physical activity (53.9%), and high saturated-fat intake (30.2%)

C

Comparator

Latent Class 1 cardiometabolic profile (n=1,197, 72.1%), characterized by lower probabilities of hypertension (9.0%), diabetes (6.0%), metabolic waist (56.3%), low physical activity (24.4%), and high saturated-fat intake (19.7%)

O

Outcome

Incident dyslipidemia (newly developed dyslipidemia defined by Adult Treatment Panel III criteria as having at least one abnormal lipid component: elevated triglycerides, elevated LDL-C, low HDL-C, or elevated total cholesterol from fasting blood samples) at approximately 5 years of follow-upsurrogate

Main Result

Relative Risk: 1.03 (95% CI 0.92–1.14)

p-value: p=0.626

Limitations

Self-reported behavioral variables (dietary intake and physical activity) may be subject to recall or measurement error.
Latent classes were derived from five specific binary indicators and may not fully capture the broader spectrum of cardiometabolic risk.
Residual confounding cannot be excluded due to the observational study design.
Findings from a single regional cohort in Iran may have limited generalizability to other ethnic and geographic groups.
Self-reported behavioral variables (dietary intake and physical activity) may be subject to recall or measurement error
Latent classes were derived from a specific set of five indicators and may not fully capture the broader spectrum of cardiometabolic risk
Residual confounding cannot be excluded
Limited generalizability to different ethnic and geographic groups without replication in independent cohorts

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Implication

Although latent class analysis identified two distinct cardiometabolic risk profiles among Iranian adults, membership in the higher-risk cluster (characterized by hypertension, diabetes, and metabolic waist) did not predict 5-year incident dyslipidemia, highlighting the continued necessity of direct lipid screening across all risk strata.

Abstract

Cardiometabolic risk factors may cluster into heterogeneous patterns that are not fully captured by conventional approaches. This study aimed to identify latent cardiometabolic profiles and examine their association with incident dyslipidemia among adults participating in the Hoveyzeh Cohort Study. This prospective cohort study included 1,660 adults free of dyslipidemia at baseline who were reassessed approximately five years later. Latent class analysis was conducted using five binary indicators: hypertension, diabetes, low physical activity, high saturated-fat intake, and metabolic waist. Two-, three-, and four-class models were evaluated based on fit, convergence, interpretability, and classification quality. Incident dyslipidemia was defined as newly developed dyslipidemia at reassessment. Risk ratios (RRs) and 95% confidence intervals (CIs) were estimated using robust Poisson regression. A two-class model was selected. Class 1 included 1,197 participants (72.1%) and had lower probabilities of the indicators, whereas Class 2 included 463 (27.9%) and showed higher probabilities of hypertension, diabetes, and metabolic waist. During follow-up, 876 participants (52.8%) developed dyslipidemia. No association was observed between Class 2 and incident dyslipidemia in crude (RR = 0.97, 95% CI: 0.88–1.08) or adjusted analyses (RR = 1.03, 95% CI: 0.92–1.14). Two distinct cardiometabolic profiles were identified, but latent class membership was not associated with incident dyslipidemia.

Discussion

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Cite This Study

Cheraghian et al. (2026) conducted a cohort in Cardiometabolic risk / Incident dyslipidemia (n=1,660). Class 2 (higher-risk cardiometabolic profile with higher probabilities of hypertension, diabetes, metabolic waist, low physical activity, and high saturated-fat intake) vs. Class 1 (lower-risk cardiometabolic profile) was evaluated on Incident dyslipidemia at reassessment (RR 1.03, 95% CI 0.92-1.14, p=0.626). Membership in a higher-risk latent cardiometabolic profile (Class 2) was not associated with incident dyslipidemia over 5 years compared to a lower-risk profile (adjusted RR 1.03, 95% CI 0.92–1.14).

synapsesocial.com/papers/6ae682a3e432e7a5c4ef35f8 https://doi.org/10.21203/rs.3.rs-10825177/v1

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Cardiometabolic Risk Patterns Among Adults: A Latent Class Analysis from the Hoveyzeh Cohort Study

Key Points

Study Design

Structured PICO

Main Result

Limitations

Ask about this paper

Implication

Abstract

Discussion

Cite This Study

Cardiometabolic Risk Patterns Among Adults: A Latent Class Analysis from the Hoveyzeh Cohort Study

Key Points

Study Design

Structured PICO

Main Result

Limitations

Ask about this paper

Implication

Abstract

Discussion

Cite This Study

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