A comparison of principal component analysis, reduced-rank regression, and partial least-squares in the identification of dietary patterns associated with cardiometabolic risk factors in Iranian overweight and obese women.

BACKGROUND: According to epidemiological studies, unhealthy dietary patterns and lifestyle lead to rising obesity and cardiometabolic diseases in Iran. Hybrid techniques were used to identify a dietary pattern characterized by fiber, folic acid, and carotenoid intake due to their association with cardiometabolic risk factors such as anthropometric measurements, blood pressure, lipid profile, C-Reactive Protein (CRP), Plasminogen Activator Inhibitor (PAI), Homeostatic Model Assessment Index (HOMA Index), cardiometabolic index (CMI), and monocyte chemoattractant protein (MCP-1). So, the objective of the recent study is to compare the reduced-rank regression (RRR) and partial least-squares (PLS) approaches to principal component analysis (PCA) for estimating diet-cardiometabolic risk factor correlations in Iranian obese women. METHODS: Data on dietary intake was gathered from 376 healthy overweight and obese females aged 18 to 65 years using a 147-item food frequency questionnaire (FFQ). In this cross-sectional study, participants were referred to health centers of Tehran. Dietary patterns were developed using PCA, PLS, and RRR, and their outputs were assessed to identify reasonable patterns connected to cardiometabolic risk factors. The response variables for PLS and RRR were fiber, folic acid, and carotenoid intake. RESULTS: In this study, 3 dietary patterns were identified by the PCA method, 2 dietary patterns by the PLS method, and one dietary pattern by the RRR method. High adherence to the plant-based dietary pattern identified by all methods were associated with higher fat free mass index (FFMI) (P < 0.05). Women in the highest tertile of the plant-based dietary pattern identified by PLS had 0.06 mmol/L (95% CI: 0.007,0.66, P = 0.02), 0.36 mmHg (95% CI: 0.14,0.88, P = 0.02), and 0.46 mg/l (95% CI: 0.25,0.82, P < 0.001), lower FBS, DBP, and CRP respectively than women in the first tertile. Also, PLS and RRR-derived patterns explained greater variance in the outcome (PCA: 1.05%; PLS: 11.62%; RRR: 25.28%), while the PCA dietary patterns explained greater variance in the food groups (PCA: 22.81%; PLS: 14.54%; RRR: 1.59%). CONCLUSION: PLS was found to be more appropriate in determining dietary patterns associated with cardiometabolic-related risk factors. Nevertheless, the advantage of PLS over PCA and RRR must be confirmed in future longitudinal studies with extended follow-up in different settings, population groups, and response variables.

Large-scale genome-wide interaction analyses on multiple cardiometabolic risk factors to identify age-specific genetic risk factors.

The genetic landscape of cardiometabolic risk factors has been explored extensively. However, insight in the effects of genetic variation on these risk factors over the life course is sparse. Here, we performed genome-wide interaction studies (GWIS) on different cardiometabolic risk factors to identify age-specific genetic risks. This study included 270,276 unrelated European-ancestry participants from the UK Biobank (54.2% women, a median age of 58 [interquartile range (IQR): 50, 63] years). GWIS models with interaction terms between genetic variants and age were performed on apolipoprotein B (ApoB), low-density lipoprotein-cholesterol (LDL-C), log-transformed triglycerides (TG), body mass index (BMI) and systolic blood pressure (SBP). Replication was subsequently performed in the Copenhagen General Population Study (CGPS) and the Estonian Biobank (EstBB). Multiple lead variants were identified to have genome-wide significant interactions with age (Pinteraction < 1e - 08). In detail, rs429358 (tagging APOE4) was identified for ApoB (Pinteraction = 9.0e - 14) and TG (Pinteraction = 5.4e - 16). Three additional lead variants were identified for ApoB: rs11591147 (R46L in PCSK9, Pinteraction = 3.9e - 09), rs34601365 (near APOB, Pinteraction = 8.4e - 09) and rs17248720 (near LDLR, Pinteraction = 2.0e - 09). Effect sizes of the identified lead variants were generally closer to the null with increasing age. No variant-age interactions were identified for LDL-C, SBP and BMI. The significant interactions of rs429358 with age on ApoB and TG were replicated in both CGPS and EstBB. The majority of genetic effects on cardiometabolic risk factors remain relatively constant over age, with the noted exceptions of specific genetic effects on ApoB and TG.

A Higher-Protein, Energy Restriction Diet Containing 4 Servings of Fresh, Lean Beef per Day Does Not Negatively Influence Circulating miRNAs Associated with Cardiometabolic Disease Risk in Women with Overweight.

This study examined the acute effects of 7-d energy restriction normal-protein (NP; ∼15% of daily intake as protein) compared with higher-protein (HP; ∼38% of daily intake as protein) diets varying in quantities of fresh, lean beef on circulating miRNA expression associated with cardiometabolic disease in 16 women with overweight (mean ± SD; age: 35 ± 8.7 y; body mass index: 28.5 ± 1.9 kg/m2). Fasting blood samples were collected at the end of each diet for miRNA expression, glucose, insulin, adiponectin, C-reactive protein (CRP), and IL-6. Of the 12 surveyed, 10 miRNAs (miR-320a-3p, miR-146a-5p, miR-150-5p, miR-423-5p, miR-122-5p, miR-223-3p, miR-199a-5p, miR-214-3p, miR-24-3p, and miR-126-3p) were detected. Several miRNAs were associated with fasting CRP (i.e., miR-150-5p, miR-24-3p, miR-423-5p; all P < 0.05). miR-423-5p was also associated with fasting glucose, IL-6, and homeostasis model assessment 2 %ß cell function (all, P < 0.05). No differences in miRNA expression were identified between diets. These data suggest that fresh, lean beef in a short-term HP, energy restriction diet does not negatively influence circulating miRNAs associated with cardiometabolic disease in women. This trial was registered at clinicaltrials.gov as NCT02614729.

Association between cardiometabolic index and gestational diabetes mellitus: a cross-sectional study.

BACKGROUND: Cardiometabolic index (CMI) is a novel marker of diabetes mellitus. However, few studies have examined its association with gestational diabetes mellitus (GDM) risk. This study aimed to explore the association between CMI and GDM risk among pregnant women in the United States. METHODS: We performed a cross-sectional study utilizing data recorded in the National Health and Nutrition Examination Survey database from 1999 to 2018. Univariate and multivariate logistic regression, restricted cubic splines (RCS), sensitivity, and subgroup analyses were performed to clarify the relationship between CMI and GDM risk. RESULTS: A total of 710 pregnant women were recruited, among whom 113 were diagnosed with GDM based on established criteria. This population showed a significant association between a higher CMI value and GDM (odds ratio: 1.75, 95% confidence interval: 1.03-2.99, P = 0.038). RCS regression analysis identified a linear relationship between CMI and GDM (P-value < 0.001, P-nonlinear = 0.702). Sensitivity analysis further confirmed the validity of this relationship. Subgroup analysis indicated a positive association between CMI and GDM among women who drink or smoke and Mexican Americans. CONCLUSION: This study demonstrates a significant positive association between CMI and GDM risk, suggesting that a higher CMI predicts GDM incidence during pregnancy. Further research is required to investigate the CMI index as an early predictor of GDM.

Inequity in cardiometabolic hospital admissions and blood screening in New Zealand Indigenous Maori with psychosis.

BACKGROUND: People with psychosis experience worse cardiometabolic health than the same-aged general population. In New Zealand, Indigenous Maori experiencing psychosis have greater risk of cardiometabolic and other physical health problems. AIMS: To identify a cohort of adults accessing secondary mental health and addiction services in New Zealand, with a previous psychosis diagnosis as of 1 January 2018, and compare odds of hospital admission outcomes, mortality and receipt of cardiometabolic blood screening between Maori and non-Maori in the following 2 years. METHOD: Crude and adjusted logistic regression models compared odds of hospital admission outcomes, mortality and receipt of cardiometabolic blood screening (lipids and haemoglobin A1c) between Maori and non-Maori, occurring between 1 January 2018 and 31 December 2019. RESULTS: A cohort (N = 21 214) of Maori (n = 7274) and non-Maori (n = 13 940) was identified. Maori had higher adjusted risk of mortality (odds ratio 1.26, 95% CI 1.03-1.54), and hospital admission with diabetes (odds ratio 1.64, 95% CI 1.43-1.87), cardiovascular disease (odds ratio 1.54, 95% CI 1.25-1.88) and any physical health condition (odds ratio 1.07, 95% CI 1.00-1.15) than non-Maori. Around a third of people did not receive recommended cardiometabolic blood screening, with no difference between Maori and non-Maori after covariate adjustment. CONCLUSIONS: Maori experiencing psychosis are more likely to die and be admitted to hospital with cardiovascular disease or diabetes than non-Maori. Because of the higher cardiometabolic risk borne by Maori, it is suggested that cardiometabolic screening shortfalls will lead to worsening physical health inequities for Maori experiencing psychosis.

Association between hypercholesterolemia and isolated and simultaneous consumption of ultra-processed foods in older adults.

Background: Consumption of ultra-processed foods (UPFs) is a risk factor for several cardiovascular diseases and mortality, with potential physiological mechanisms including elevated serum cholesterol levels. Objectives: To analyze the association between hypercholesterolemia and the isolated and simultaneous consumption of UPFs in older adults. Methods: This is a cross-sectional epidemiological study conducted with 1322 Brazilian older adults (mean age of 70.4 years; 55.0% females) from the state of Roraima. The data was obtained from the Department of Epidemiological Surveillance of the State of Roraima. Hypercholesterolemia was diagnosed based on nosology criteria. Food consumption patterns were assessed using a nationally standardized instrument comprising four categories of UPFs. Binary logistic regression models were employed to explore potential associations. Results: The prevalence of hypercholesterolemia was high (54.4%, 95% CI 51.7-56.6). While the simultaneous consumption of all UPFs types was lower (15.2%), over half of the older adults reported consuming at least one type of UPFs (71.8%). Isolated consumption of UPFs was associated with approximately twice the odds of hypercholesterolemia. Older adults who consumed two (OR 1.75, 95% CI 1.26-2.43), three (OR 2.28, 95% CI 1.58-3.29), or all four types of UPF (OR 6.65, 95% CI 4.35-9.44) had a higher likelihood of having hypercholesterolemia. Conclusions: Isolated consumption of UPFs is a risk factor for hypercholesterolemia, which can increase up to sixfold when older adults consume multiple UPFs simultaneously. Prioritizing nutritional education and raising awareness regarding the reduction of UPFs consumption is crucial.

Association of cardiometabolic multimorbidity with risk of late-life depression: a nationwide twin study.

BACKGROUND: Cardiometabolic diseases (CMDs) including heart disease, stroke, and type 2 diabetes have been individually linked to depression. However, their combined impact on depression risk is unclear. We aimed to examine the association between cardiometabolic multimorbidity and depression and explore the role of genetic background in this association. METHODS: Within the Swedish Twin Registry, 40,080 depression-free individuals (mean age 60 years) were followed for 18 years. Cardiometabolic multimorbidity was defined as having ≥2 CMDs. CMDs and depression were ascertained based on the National Patient Register. Cox regression was used to estimate the CMD-depression association in a classical cohort study design and a matched co-twin design involving 176 twin pairs. By comparing the associations between monozygotic and dizygotic co-twins, the contribution of genetic background was estimated. RESULTS: At baseline, 4809 (12.0%) participants had one CMD and 969 (2.4%) had ≥2 CMDs. Over the follow-up period, 1361 participants developed depression. In the classical cohort design, the multi-adjusted hazard ratios (95% confidence interval [CIs]) of depression were 1.52 (1.31-1.76) for those with one CMD and 1.83 (1.29-2.58) for those with ≥2 CMDs. CMDs had a greater risk effect on depression if they developed in mid-life (<60 years) as opposed to late life (≥60 years). In matched co-twin analysis, the CMD-depression association was significant among dizygotic twins (HR = 1.63, 95% CI, 1.02-2.59) but not monozygotic twins (HR = 0.90, 95% CI, 0.32-2.51). CONCLUSIONS: Cardiometabolic multimorbidity is associated with an elevated risk of depression. Genetic factors may contribute to the association between CMDs and depression.

Effect of Nuts Combined with Energy Restriction on the Obesity Treatment: A Systematic Review and Meta-Analysis of Randomized Controlled Trials.

Obesity is a multifactorial disease that is difficult to control worldwide. Although nuts are recognized health foods, the application of food in obesity management is unclear. We systematically reviewed the literature and performed a meta-analysis to evaluate if nut consumption favors people on energy restriction (ER) dietary interventions. Four databases were used to search for eligible articles in May 2024. This review was conducted according to the PRISMA guide, and the bias risk of papers was evaluated. For the meta-analysis, we extracted the endpoint values of the group's variables and estimated the effect sizes by the random-effects model. Sixteen and ten articles were included in the systematic review and meta-analysis, respectively. Almonds were evaluated in the majority of studies (n = 6). The consumption of nuts (28 to 84 g/d, 4 to 72 months) included in ER (-250 to 1000 kcal/d) did not differently affect anthropometry (weight loss, BMI, waist and hip circumferences), body composition (fat mass, fat-free mass, or lean mass), markers of glucose (glycemia and insulinemia), lipid metabolism (total cholesterol, HDL-c, LDL-c, LDL-c/HDL-c, or triglycerides), and systolic and diastolic blood pressure. In most analyses, stratifying studies by type of nut or intervention time did not present different results in the meta-analysis. As there are few studies, in addition to great methodological variability, more high-quality trials are needed to confirm these results. The PROSPERO registration number is CRD42023444878.

Nonlinear relationship between cardiometabolic index and bone mineral density in U.S. adults: the mediating role of percent body fat.

BACKGROUND: Both lipid metabolism and obesity are crucial factors in osteoporosis, influencing the relevance of the cardiometabolic index (CMI), a new body fat index incorporating obesity and lipid metrics. Our study aims to explore the relationship between CMI and lumbar spine bone mineral density (BMD) and the mediating role of body fat percentage. METHODS: Utilizing the National Health and Nutrition Examination Survey (NHANES) data from 2011 to 2018, we conducted a cross-sectional analysis. We employed multiple linear regression models, subgroup analyses, generalized additive models (GAM), smooth curve fitting, and mediation analysis to evaluate the linear and nonlinear relationships between CMI and lumbar spine BMD. RESULTS: The study involved 5,124 participants with an average lumbar spine BMD of 1.03 ± 0.15 g/cm2. We identified a negative correlation between CMI and lumbar spine BMD (ß = -0.015; 95% CI: -0.023, -0.008). Nonlinear associations were evident, with inflection points at CMI values of 1.12 and 2.86. Subgroup analyses showed consistent negative correlations across all categories without significant differences (p for interaction > 0.05). Moreover, body fat percentage negatively correlated with BMD (ß = -0.005; 95% CI: -0.006, -0.004) and mediated 9.41% of the relationship between CMI and BMD. CONCLUSION: Increased CMI levels are associated with lower lumbar spine BMD, with body fat percentage significantly mediating this relationship. This underscores the importance of managing body composition in the context of bone health, highlighting CMI's potential utility in osteoporosis risk assessment.

Are the EAT-Lancet dietary recommendations associated with cardiometabolic health? - insights from the Generation XXI cohort from childhood into early adolescence.

BACKGROUND: The prospective effect of healthy and planetary diets on cardiometabolic health at young ages remains unclear. OBJECTIVE: This study aims to investigate the prospective associations between adherence to the EAT-Lancet dietary recommendations at age 7 and the prevalence of obesity and Metabolic Syndrome (MetS) at 7, 10, and 13 years old (y). METHODS: Participants are children from the Generation XXI birth cohort, who completed 3-day food diaries at age 7, with complete data in variables of interest (n 3564). Adherence to the EAT-Lancet dietary recommendations was evaluated using the World Index for Sustainability and Health (WISH); a higher score indicating a healthier and environmentally sustainable diet. At 7, 10 and 13y, anthropometrics (weight, height and waist circumference-WC), blood pressure (BP) and serum-fasting triglycerides, HDL-cholesterol and glucose were measured. Obesity and MetS prevalence were determined by the World Health Organization and the International Diabetes Federation criteria, respectively. Adjusted custom binomial log-linear models were used to calculate prevalence ratios (PR) and the respective 95% confidence intervals (95%CI) (covariates: mother's age, education, pre-pregnancy BMI, gestational diabetes, child's sex, age, tanner stage, sports practice and total grams of the remaining food). RESULTS: From 7 to 13y, obesity decreased from 14.1% to 9.3% and MetS increased from 1.0% to 5.1%. Higher WISH scores at 7y were associated with a lower prevalence of obesity, measured by both BMI (≥97th percentile: PR=0.912, 95%CI: 0.839,0.991; PR=0.882, 95%CI: 0.79,0.938, respectively at 10 and 13y) and WC (≥90th percentile: PR=0.899, 95%CI: 0.830,0.974; PR=0.858, 95%CI:0.782,0.942, respectively at 10 and 13y). For each 10-point increase in the WISH, a reduction of 16% in MetS prevalence at 13y was observed (PR=0.837, 95%CI: 0.732,0.957). No significant effects were found at younger ages. CONCLUSIONS: The adherence to the EAT-Lancet diet from an early age may help reduce cardiometabolic risk in early adolescence.

Predicting Biochemical and Physiological Parameters: Deep Learning from IgG Glycome Composition.

In immunoglobulin G (IgG), N-glycosylation plays a pivotal role in structure and function. It is often altered in different diseases, suggesting that it could be a promising health biomarker. Studies indicate that IgG glycosylation not only associates with various diseases but also has predictive capabilities. Additionally, changes in IgG glycosylation correlate with physiological and biochemical traits known to reflect overall health state. This study aimed to investigate the power of IgG glycans to predict physiological and biochemical parameters. We developed two models using IgG N-glycan data as an input: a regression model using elastic net and a machine learning model using deep learning. Data were obtained from the Korcula and Vis cohorts. The Korcula cohort data were used to train both models, while the Vis cohort was used exclusively for validation. Our results demonstrated that IgG glycome composition effectively predicts several biochemical and physiological parameters, especially those related to lipid and glucose metabolism and cardiovascular events. Both models performed similarly on the Korcula cohort; however, the deep learning model showed a higher potential for generalization when validated on the Vis cohort. This study reinforces the idea that IgG glycosylation reflects individuals' health state and brings us one step closer to implementing glycan-based diagnostics in personalized medicine. Additionally, it shows that the predictive power of IgG glycans can be used for imputing missing covariate data in deep learning frameworks.

Increased Cardiometabolic Risk in Dynapenic Obesity: Results from the Study of Workers' Health (ESAT).

Background: The coexistence of obesity and low muscle strength-denoted dynapenic obesity (DO)-has been associated with an unhealthy metabolic profile and increased risk for metabolic syndrome. However, there is a lack on studies investigating if DO exhibits higher cardiometabolic risk than non-dynapenic obesity. Objectives: To assess if individuals with DO exhibit elevated cardiometabolic risk compared to non-dynapenic obesity. Methods: a cross-sectional study that analyzed the data of workers from a quaternary care hospital collected between November 2018 and March 2020. Participants were stratified into the following anthropometrical and peripheral muscle strength profiles: non-obese/non-dynapenic (NOND), non-obese/dynapenic (NOD), obese/non-dynapenic (OND), and obese dynapenic (OD). Cardiovascular risk was evaluated by Atherogenic Index (AI), Plasma Atherogenic Index (PAI), Hypertriglyceridemic Waist (HW), A Body Shape Index (ABSI), Atherogenic Dyslipidemia (AD), Castelli Indices I and II, and Framingham Score (FS). Results: the OD group had significantly lower HDL compared to all others (p = 0.009), and despite exhibited lower prevalence of HW compared to OND (p < 0.01), a higher cardiometabolic risk compared to OND profile was observed assessing AI (p = 0.05), Castelli I (p < 0.05) and Castelli II (p < 0.05) scores. Conclusions: in the studied population, individuals with DO exhibit elevated cardiometabolic risk compared to other anthropometrical and peripheral muscle strength profiles.

Lifestyle and Cardiometabolic Risk Factors Associated with Impoverishment Due to Out-of-Pocket Health Expenditure in São Paulo City, Brazil.

The rise in obesity and related chronic noncommunicable diseases (NCDs) during recent decades in Brazil has been associated with increases in the financial burden and risk of impoverishment due to out-of-pocket (OOP) health expenditure. Thus, this study investigated trends and predictors associated with impoverishment due to health expenditure, in the population of São Paulo city, Brazil, between 2003 and 2015. Household data from the São Paulo Health Survey (n = 5475) were used to estimate impoverishment linked to OOP health expenses, using the three thresholds of International Poverty Lines (IPLs) defined by the World Bank at 1.90, 3.20, and 5.50 dollars per capita per day purchasing power parity (PPP) in 2011. The results indicated a high incidence of impoverishment due to OOP disbursements for health care throughout the period, predominantly concentrated among low-income individuals. Lifestyle choices referring to leisure-time physical activity (OR = 0.766 at $3.20 IPL, and OR = 0.789 at $5.50 IPL) were linked to reduction in the risk for impoverishment due to OOP health expenditures whilst there were increases in the probability of impoverishment due to cardiometabolic risk factors referring to obesity (OR = 1.588 at $3.20 IPL, and OR = 1.633 at $5.50 IPL), and diagnosis of cardiovascular diseases (OR = 2.268 at $1.90 IPL, OR = 1.967 at $3.20 IPL, and OR = 1.936 at $5.50 IPL). Diagnosis of type 2 diabetes mellitus was associated with an increase in the probability of impoverishment at only the $1.90 IPL (OR = 2.506), whilst coefficients for high blood pressure presented lack of significance in the models. Health policies should focus on interventions for prevention of obesity to ensure the financial protection of the population in São Paulo city, Brazil, especially targeting modifiable lifestyle choices like promotion of physical activity and reduction of tobacco use.

Sex Differences in Biochemical Analyses, Cardiometabolic Risk Factors and Their Correlation with CRP in Healthy Mexican Individuals.

BACKGROUND: Few studies have been undertaken to detect the presence of cardiovascular risk factors (CRFs) in healthy populations (individuals auto-reported as healthy). These risk factors include high body mass index (BMI), high waist-to-hip ratio (WHR), high systolic and diastolic blood pressure (SBP, DBP), high uric acid and high Castelli's risk index (CRI); this last is the ratio of total cholesterol to HDL cholesterol (TC/HDL-c). In addition, the correlations between CRFs and the biomarker C-reactive protein (CRP) has not been explored in each sex. AIM: Therefore, this study aimed to determine sex differences in the abnormalities in blood and urine analyses, including CRFs and their correlation with CPR in a non-representative sample of healthy Mexican individuals. RESULTS: A total of 238 subjects were included, 123 (51.7%) of whom were women. The main blood alterations detected were high serum lipids, including high total cholesterol, LDL-cholesterol, triglycerides, and the CRI, which were higher in men than in women. The men's samples had a higher frequency of hypertensives and pre-hypertensives than the women's sample. The CRP showed positive significant correlations with the CRFs: BMI, WHR, SBP, DBP, uric acid, and the CRI, with a higher correlation for BMI and WHR, and most of these correlations were higher in women than in men. Additionally, all these factors showed a positive correlation among them. CONCLUSION: In conclusion, the main alterations observed in blood are related to cardiovascular risk and were reported with a higher frequency in men when compared with women. This finding can be related to the higher values of WHR in this sex; additionally, the inflammatory marker CRP was more correlated with the cardiometabolic risk factors in women than in men, which suggests a different relationship between inflammation and cardiometabolic risk factors in each sex.

Disparities in the Cardiometabolic Impact of Adiposity among African American and Hispanic Adolescents.

As adiposity increases in youth, so does the prevalence of cardiometabolic risk factors (CMRFs). The etiology of adiposity-based chronic disease and CMRFs includes ethnoracial disparities that are rarely considered in current treatment approaches. Precision interventions require further characterization of these disparities among high-risk youth. The objective of this study was to characterize differences in CMRF among African American (AA) and Hispanic (H) adolescents with varying levels of adiposity. A cross-sectional analysis of 2284 adolescents aged 12-17 was conducted using 3-year clinical data from Lifedoc Health. CMRF prevalence were compared using χ2, with logistic regression models (LRM) applied to explore the relationships between exposures (age, sex, ethnoracial group, adiposity) and CMRF outcomes. Prevalence of CMRF rose with increasing adiposity, which was the strongest determinant of risk overall. However, individual risk profiles differed between the two groups, with H having higher prevalence of metabolic syndrome (MetS), higher triglycerides and liver enzymes, and low high-density lipoprotein cholesterol (HDL-c). Meanwhile, AA had higher prevalence of elevated blood pressure (BP) in the overweight category, prediabetes in overweight to severe obesity, and type 2 diabetes in obesity. LRM showed 3.0-fold greater chance of impaired glucose metabolism in AA than H, who were 1.7, 5.9, and 8.3 times more likely to have low HDL-c, high liver enzymes, and high triglycerides, respectively. Overweight/obesity prevalence was very high among AA and H adolescents. Excess adiposity was associated with an increased prevalence of CMRF, with individual risk factors differing between groups as adiposity increased. Research within routine clinical settings is required to better characterize these discrepancies and ameliorate their adverse impact on health in the transition to adulthood.

The metabolic signature of blood lipids: a causal inference study using twins.

Dyslipidemia is one of the cardiometabolic risk factors that influences mortality globally. Unraveling the causality between blood lipids and metabolites and the complex networks connecting lipids, metabolites, and other cardiometabolic traits can help to more accurately reflect the body's metabolic disorders and even cardiometabolic diseases. We conducted targeted metabolomics of 248 metabolites in 437 twins from the Chinese National Twin Registry. Inference about Causation through Examination of FAmiliaL CONfounding (ICE FALCON) analysis was used for causal inference between metabolites and lipid parameters. Bidirectional mediation analysis was performed to explore the linkages between blood lipids, metabolites, and other seven cardiometabolic traits. We identified 44, 1, and 31 metabolites associated with triglyceride (TG), total cholesterol (TC), and high-density lipoprotein-cholesterol (HDL-C), most of which were gut microbiota-derived metabolites. There were 9, 1, and 14 metabolites that showed novel associations with TG, TC, and HDL-C, respectively. ICE FALCON analysis found that TG and HDL-C may have a predicted causal effect on 23 and six metabolites, respectively, and one metabolite may have a predicted causal effect on TG. Mediation analysis discovered 14 linkages connecting blood lipids, metabolites, and other cardiometabolic traits. Our study highlights the significance of gut microbiota-derived metabolites in lipid metabolism. Most of the identified cross-sectional associations may be due to the lipids having a predicted causal effect on metabolites, but not vice versa, nor are they due to family confounding. These findings shed new light on lipid metabolism and personalized management of cardiometabolic diseases.

Associations between live birth and cardiometabolic disease in Southwest Chinese women.

BACKGROUND: China has undergone a significant socioeconomic transformation over the past few decades due to the implementation of family planning policies. These societal changes have resulted in an increased susceptibility among females to developing cardiometabolic diseases (CMD). Unfortunately, studies investigating the correlation between family planning policies in China and the incidence of CMD remain scarce. METHODS: Data from 1,226 females, aged 30 years or older with ≥ 1 live birth, undergoing routine physical examinations between January 2018 and December 2021 were collected, and they were grouped by number of live births 1, 2, and ≥ 3. A binary logistic regression model was employed to examine the association between the number of live births with CMD. Furthermore, the subgroup analysis was performed to elucidate the impact of the implementation of family planning policies with CMD. RESULTS: Women with live births ≥ 3 tended to be older, had higher gravidities, a greater proportion of central obesity, general obesity, hypertension, and dyslipidemia (all P < 0.05). Across the three groups (live birth = 1, =2 and ≥ 3), the odds ratio (OR) with 95% CI for obesity were: 1.00, 3.32 (2.36-4.69), and 5.73 (3.79-8.68); for dyslipidemia were: 1.00, 1.75 (1.29-2.39), and 2.02 (1.38-2.94); and for CMD were: 1.00, 1.91 (1.44-2.54), and 2.15 (1.46-3.15), respectively (all P < 0.05). In addition, based on the different periods of the childbearing policy in China, a subgroup analysis (where age was divided into ≤ 45, 45-65, and ≥ 65 years old) found that each additional live birth increased the prevalence risk of obesity and CMD in the younger generations, while hypertension and dyslipidemia in the elder generation. CONCLUSIONS: Higher live births are positively associated with the prevalence of CMD among women in Southwest China. Moreover, giving birth after the implementation of the one-child policy tends to have a higher risk of developing CMD.

Implementing a Diet Risk Score (DRS) for Spanish-Speaking Adults in a Clinical Setting: A Feasibility Study.

Tools to briefly assess diet among US Spanish-speaking adults are needed to identify individuals at risk for cardiometabolic disease (CMD) related to diet. Two registered dietitian nutritionists (RDNs) recruited bilingual medical students to translate the validated Diet Risk Score (DRS) into Spanish (DRS-S). Participants were recruited from a federally qualified health center. Students administered the DRS-S and one 24-h recall (Automated Self-Administered 24-Hour (ASA24®) Dietary Assessment Tool) on one day; a second recall was administered within 1 week. Recalls were scored using the Healthy Eating Index (HEI)-2015, a measure of adherence to the Dietary Guidelines for Americans. Spearman correlations, weighted kappa, and ANOVA were conducted using SAS 9.4 to assess the relative validity of the DRS-S. Thirty-one Spanish-speaking adults (female: n = 17, 53%; mean age: 58 (42-69)) completed assessments. The mean DRS-S was 9 (SD = 4.2) (max: 27; higher score = higher risk) and the mean HEI-2015 score was 65.7 (SD = 9.7) (max: 100; higher score = lower risk), with significant agreement between measures (r: -0.45 (p = 0.01)), weighted kappa: -0.3 (p = 0.03). The DRS-S can be used in resource-constrained settings to assess diet for intervention and referral to RDNs. The DRS-S should be tested in clinical care to assess the impact of dietary changes to reduce CMD risk.

Development and validation of cardiometabolic risk predictive models based on LDL oxidation and candidate geromarkers from the MARK-AGE data.

The predictive value of the susceptibility to oxidation of LDL particles (LDLox) in cardiometabolic risk assessment is incompletely understood. The main objective of the current study was to assess its relationship with other relevant biomarkers and cardiometabolic risk factors from MARK-AGE data. A cross-sectional observational study was carried out on 1089 subjects (528 men and 561 women), aged 40-75 years old, randomly recruited age- and sex-stratified individuals from the general population. A correlation analysis exploring the relationships between LDLox and relevant biomarkers was undertaken, as well as the development and validation of several machine learning algorithms, for estimating the risk of the combined status of high blood pressure and obesity for the MARK-AGE subjects. The machine learning models yielded Area Under the Receiver Operating Characteristic Curve Score ranging 0.783-0.839 for the internal validation, while the external validation resulted in an Under the Receiver Operating Characteristic Curve Score between 0.648 and 0.787, with the variables based on LDLox reaching significant importance within the obtained predictions. The current study offers novel insights regarding the combined effects of LDL oxidation and other ageing markers on cardiometabolic risk. Future studies might be extended on larger patient cohorts, in order to obtain reproducible clinical assessment models.

3-generation family histories of mental, neurologic, cardiometabolic, birth defect, asthma, allergy, and autoimmune conditions associated with autism: An open-source catalog of findings.

The relatively few conditions and family member types (e.g., sibling, parent) considered in investigations of family health history in autism spectrum disorder (ASD, or autism) limits understanding of the role of family history in autism etiology. For more comprehensive understanding and hypothesis-generation, we produced an open-source catalog of autism associations with family histories of mental, neurologic, cardiometabolic, birth defect, asthma, allergy, and autoimmune conditions. All live births in Denmark, 1980-2012, of Denmark-born parents (1,697,231 births), and their 3-generation family members were followed through April 10, 2017 for each of 90 diagnoses (including autism), emigration or death. Adjusted hazard ratios (aHR) were estimated via Cox regression for each diagnosis-family member type combination, adjusting for birth year, sex, birth weight, gestational age, parental ages at birth, and number of family member types of index person; aHRs also calculated for sex-specific co-occurrence of each disorder. We obtained 6462 individual family history aHRS across autism overall (26,840 autistic persons; 1.6% of births), by sex, and considering intellectual disability (ID); and 350 individual co-occurrence aHRS. Results are cataloged in interactive heat maps and down-loadable data files: https://ncrr-au.shinyapps.io/asd-riskatlas/ and interactive graphic summaries: https://public.tableau.com/app/profile/diana.schendel/viz/ASDPlots_16918786403110/e-Figure5. While primarily for reference material or use in other studies (e.g., meta-analyses), results revealed considerable breadth and variation in magnitude of familial health history associations with autism by type of condition, family member type, sex of the family member, side of the family, sex of the index person, and ID status, indicative of diverse genetic, familial, and nongenetic autism etiologic pathways. Careful attention to sources of autism likelihood in family health history, aided by our open data resource, may accelerate understanding of factors underlying neurodiversity.