Sociodemographic Predictors and Trends of Cardiovascular Risk Clusters in Turkiye: 2014–2022
Abstract
Background: The aim of this study was to examine temporal changes in cardiovascular disease (CVD) risk factor clusters in Turkiye between 2014 and 2022—a period characterized by large-scale national prevention programmes—and to assess their sociodemographic predictors to inform targeted public health interventions.
Methods: This repeated cross-sectional study analyzed data from 71,903 adults across four waves (2014, 2016, 2019, 2022) of the nationally representative Turkish Health Survey. Two-step cluster analysis—using body mass index, physical activity, smoking, diabetes, and hypertension—was conducted. The cluster structure derived from the 2022 cohort (n = 21,444) was applied to prior waves for temporal comparison. Multinomial logistic regression was used to identify sociodemographic determinants.
Results: In 2022, 89.7% of adults had at least 1 CVD risk factor. Five risk factor clusters were identified: (1) overweight/obese with adequate physical activity (13.4%); (2) chronic disease (23.2%); (3) overweight/obese with insufficient physical activity (18.0%); (4) smokers (23.1%); and (5) low-risk (22.3%). During this period, high-risk clusters showed a slight reduction with only a marginal increase in the low-risk cluster (20.8% to 22.3%). Using the low-risk cluster as reference, higher education was associated with a lower probability of belonging to the chronic disease cluster (OR = 0.38, 95% CI:0.34–0.43, p < 0.001), whereas age ≥65 strongly increased it (OR = 11.80, 95% CI:9.79–14.21, p < 0.001).
Conclusions: Despite the national prevention programmes, CVD risk clusters remained largely unchanged in Turkiye between 2014 and 2022. Risk factors were aggregated into distinct and persistent clusters and were largely influenced by age and education. These findings may imply the need to shift from isolated single-risk interventions towards comprehensive, cluster-based strategies targeting specific sociodemographic profiles.
Key messages: • CVD risk clusters in Turkiye remained largely unchanged between 2014 and 2022 despite national prevention initiatives, forming stable risk profiles.
• No observable downward trend in risk profiles may imply the need to shift from single-risk interventions to integrated, cluster-based strategies targeting high-risk populations.
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BibTeX
@article{torun2026sociodemographic,
title = {{Sociodemographic Predictors and Trends of Cardiovascular Risk Clusters in Turkiye: 2014–2022}},
author = {P Torun and S Duzcan and E Günay and H Okan and E Kızılyel},
journal = {The European Journal of Public Health},
year = {2026},
month = oct,
doi = {10.1093/eurpub/ckag169.1149},
url = {https://doi.org/10.1093/eurpub/ckag169.1149},
note = {CC BY-NC 4.0},
}
RIS
TY - JOUR
TI - Sociodemographic Predictors and Trends of Cardiovascular Risk Clusters in Turkiye: 2014–2022
AU - P Torun
AU - S Duzcan
AU - E Günay
AU - H Okan
AU - E Kızılyel
PY - 2026
DA - 2026/10/01
JO - The European Journal of Public Health
DO - 10.1093/eurpub/ckag169.1149
UR - https://doi.org/10.1093/eurpub/ckag169.1149
AB - Background: The aim of this study was to examine temporal changes in cardiovascular disease (CVD) risk factor clusters in Turkiye between 2014 and 2022—a period characterized by large-scale national prevention programmes—and to assess their sociodemographic predictors to inform targeted public health interventions. Methods: This repeated cross-sectional study analyzed data from 71,903 adults across four waves (2014, 2016, 2019, 2022) of the nationally representative Turkish Health Survey. Two-step cluster analysis—using body mass index, physical activity, smoking, diabetes, and hypertension—was conducted. The cluster structure derived from the 2022 cohort (n = 21,444) was applied to prior waves for temporal comparison. Multinomial logistic regression was used to identify sociodemographic determinants. Results: In 2022, 89.7% of adults had at least 1 CVD risk factor. Five risk factor clusters were identified: (1) overweight/obese with adequate physical activity (13.4%); (2) chronic disease (23.2%); (3) overweight/obese with insufficient physical activity (18.0%); (4) smokers (23.1%); and (5) low-risk (22.3%). During this period, high-risk clusters showed a slight reduction with only a marginal increase in the low-risk cluster (20.8% to 22.3%). Using the low-risk cluster as reference, higher education was associated with a lower probability of belonging to the chronic disease cluster (OR = 0.38, 95% CI:0.34–0.43, p < 0.001), whereas age ≥65 strongly increased it (OR = 11.80, 95% CI:9.79–14.21, p < 0.001). Conclusions: Despite the national prevention programmes, CVD risk clusters remained largely unchanged in Turkiye between 2014 and 2022. Risk factors were aggregated into distinct and persistent clusters and were largely influenced by age and education. These findings may imply the need to shift from isolated single-risk interventions towards comprehensive, cluster-based strategies targeting specific sociodemographic profiles. Key messages: • CVD risk clusters in Turkiye remained largely unchanged between 2014 and 2022 despite national prevention initiatives, forming stable risk profiles. • No observable downward trend in risk profiles may imply the need to shift from single-risk interventions to integrated, cluster-based strategies targeting high-risk populations.
SN - 1101-1262
SN - 1464-360X
ER -