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Background: Life's Essential 8 (LE8) is a cardiovascular health (CVH) model but does not take into account mental health, an important cardiovascular risk factor, so we constructed Life's Crucial 12 (LC12), a comprehensive cardiovascular care model that takes CVH into account, based on LE8, and hypothesized that it would be a more reliable index of CVH, despite the additional information needed to calculate LC12. Objective: To construct an integrated cardiovascular care model LC12 based on LE8 that can take Psychological Health into account, and to report the association between LC12 and stroke. Design: Population-based, cross-sectional study. Setting: Various locations in the United States. Participants: This study was a cross-sectional study based on data from the 2005-2008 National Health and Nutrition Examination Survey (NHANES), which included 4,478 U.S. adults (≥ 20 years old). Method: The composite cardiovascular care model LC12 with scores (range 0-100) defining low (0-49), medium (50-79) and high (80-100) CVH. Determination of stroke status was obtained by questionnaire. Associations were assessed using multivariate logistic regression models and restricted cubic spline models. Result: Among 4,478 participants, there were 2252 female and 2226 male participants (53.136% and 46.864%, respectively), and 250 participants (5.583%) were diagnosed with stroke. The mean values of LC12, Psychological Health, Health behaviors, and Health factors scores for participants with stroke were 68.953, 52.775, and 55.451, respectively, which were lower than those of Non-Stroke participants. After fully adjusting for confounders, the ORs for the LC 12, Psychological Health, Health Behaviors, and Health Factors moderate and high groups were 0.431 (0.226,0.822), 0.212 (0.060,0.755), 0.536 (0.297, 0.967), 0.357 (0.178,0.713), 0.759 (0.552, 1.043), 0.334 (0.179, 0.623), 0.565 (0.406, 0.786), 0.533 (0.286, 0.994), which were significantly associated with the risk of stroke (P-trend < 0.05) and there was a linear trend between subgroups with different scores (P-value < 0.001). However, no nonlinear dose relationship was observed (P-Nonlinearity > 0.05). Limitation: Because estimates are based on single measures, fluctuations over time could not be determined. Conclusion: These findings suggest that Psychological Health is important in CVH. CVH status assessed by LC12 (Psychological Health, Health behaviors, Health factors) was significantly associated with the risk of developing stroke. When LC12 scores are maintained at high levels, it is beneficial to decrease the risk of stroke.
Background: Life's Essential 8 (LE8) is a cardiovascular health (CVH) model but does not take into account mental health, an important cardiovascular risk factor, so we constructed Life's Crucial 12 (LC12), a comprehensive cardiovascular care model that takes CVH into account, based on LE8, and hypothesized that it would be a more reliable index of CVH, despite the additional information needed to calculate LC12. Objective: To construct an integrated cardiovascular care model LC12 based on LE8 that can take Psychological Health into account, and to report the association between LC12 and stroke. Design: Population-based, cross-sectional study. Setting: Various locations in the United States. Participants: This study was a cross-sectional study based on data from the 2005-2008 National Health and Nutrition Examination Survey (NHANES), which included 4,478 U.S. adults (≥ 20 years old). Method: The composite cardiovascular care model LC12 with scores (range 0-100) defining low (0-49), medium (50-79) and high (80-100) CVH. Determination of stroke status was obtained by questionnaire. Associations were assessed using multivariate logistic regression models and restricted cubic spline models. Result: Among 4,478 participants, there were 2252 female and 2226 male participants (53.136% and 46.864%, respectively), and 250 participants (5.583%) were diagnosed with stroke. The mean values of LC12, Psychological Health, Health behaviors, and Health factors scores for participants with stroke were 68.953, 52.775, and 55.451, respectively, which were lower than those of Non-Stroke participants. After fully adjusting for confounders, the ORs for the LC 12, Psychological Health, Health Behaviors, and Health Factors moderate and high groups were 0.431 (0.226,0.822), 0.212 (0.060,0.755), 0.536 (0.297, 0.967), 0.357 (0.178,0.713), 0.759 (0.552, 1.043), 0.334 (0.179, 0.623), 0.565 (0.406, 0.786), 0.533 (0.286, 0.994), which were significantly associated with the risk of stroke (P-trend < 0.05) and there was a linear trend between subgroups with different scores (P-value < 0.001). However, no nonlinear dose relationship was observed (P-Nonlinearity > 0.05). Limitation: Because estimates are based on single measures, fluctuations over time could not be determined. Conclusion: These findings suggest that Psychological Health is important in CVH. CVH status assessed by LC12 (Psychological Health, Health behaviors, Health factors) was significantly associated with the risk of developing stroke. When LC12 scores are maintained at high levels, it is beneficial to decrease the risk of stroke.
Background and Purpose Diet may influence systemic inflammatory status, vascular calcification, and, therefore, the development of atherosclerosis. The Dietary Inflammatory Index (DII) is a measure of the inflammatory potential of diet. Although previous studies have examined the relationship between DII and cardiovascular diseases, its specific association with carotid artery calcification in ischemic stroke patients remains insufficiently explored. This study aimed to evaluate the relationship between Dietary Inflammatory Index (DII) and carotid artery calcification in patients with ischemic stroke. Methods This is a retrospective cross-sectional analysis based on a prospective registry database. Patients with ischemic stroke were enrolled via Nanjing Stroke Registry Program. DII was calculated based on 39 food components with the help of a food frequency questionnaire. Carotid artery calcification was quantified as calcification score using the Agatston method based on computed tomography angiography. The data were compared among patients stratified by tertiles of DII. Multiple logistic regression models were used to evaluate the influence of DII on carotid artery calcification. Spearman analysis was used to evaluate the relationship between DII and ln-transformed carotid artery calcification score. Results Of the 601 enrolled, carotid artery calcification was detected in 368 (61.23%) patients. Compared with patients with the lowest DII, those with higher DII had a higher ratio of stroke subtypes of large artery atherosclerosis ( p =0.050), a higher calcification score ( p <0.001), and a higher ratio of calcification ( p <0.001). Other baseline characteristics, including sex and age, showed no significant differences across the DII tertiles. Patients with carotid artery calcification had significantly higher DII scores compared to those without calcification ( p = 0.018). Logistic regression analysis showed that patients with the highest DII tertile had a higher risk of carotid artery calcification after adjusting for significant cofounders (OR =1.880, 95% CI, 1.205−2.932; p =0.005). Spearman correlation analysis indicated that DII was associated with ln-transformed carotid artery calcification score in patients with carotid artery calcification (R =0.110, p =0.035). Conclusion DII was associated with carotid artery calcification in patients with ischemic stroke. Considering a possible causal relationship, the mechanism of this relationship warrants further investigation.
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