National Health Research Articles

Background: Palliative care in Iraq remains severely underdeveloped, despite growing recognition of its critical role in alleviating the suffering of patients with terminal illnesses. Structural limitations, socio-cultural barriers, and political instability continue to undermine its accessibility and integration into the national health system. Objectives: This paper explores the evolution, current gaps, and future opportunities for palliative care in Iraq, with a focus on institutional readiness, geographic equity, and cultural dimensions. It aims to offer a comprehensive overview of the systemic challenges and to outline a strategic path forward. Methods: This is a narrative review and policy analysis based on published literature, institutional observations, and recent regional developments in palliative care infrastructure, training, and cultural attitudes. Special emphasis is placed on the interaction between family roles, healthcare delivery, and end-of-life decision-making in the Iraqi context. Results: Findings reveal a profound misalignment between the need for palliative care and its current availability. Terminal patients often receive aggressive, non-beneficial treatments in intensive care settings, while community-based services are scarce or absent. Cultural stigma, lack of trained personnel, insufficient funding, and the legacy of conflict further complicate access. Family caregivers carry a disproportionate burden, often without professional or psychosocial support. Conclusion: Integrating palliative care into Iraq’s health system requires both structural reform and cultural transformation. A national policy that prioritizes palliative education, decentralizes services, and respects local values could significantly improve end-of-life care for Iraqi patients and their families. Keywords: Palliative care, end-of-life care, health system challenges, Iraq, cultural barriers

Although obesity is recognized as a risk factor of migraine chronification, its longitudinal impact on migraine onset remains unclear. The aim of this study was to investigate the association between obesity and the risk of developing migraine in a longitudinal setting. We conducted a population-based prospective cohort study using data from the Korean National Health Insurance Service. Individuals aged 20-39 years who underwent health examinations between 2009 and 2012 were enrolled, excluding those with a history of migraine, missing data, or a migraine diagnosis within the first year. Participants were followed to the end of 2018. Body mass index (BMI) was categorized into 5 groups and waist circumference (WC) into 6 levels. Outcome was the first migraine claim (International Classification of Diseases, Tenth Revision code G43). We evaluated the associations of BMI and WC with the risk of migraine using multivariable Cox proportional hazard regression models. Interaction analyses were conducted based on demographic and lifestyle factors. Among 6,106,560 individuals included (mean age: 30.6 ± 4.98 years; 39% female), the risk of migraine increased with increasing BMI (adjusted hazard ratio [aHR] 1.001 [95% CI 0.991-1.010], 1.047 [95% CI 1.040-1.055], 1.087 [95% CI 1.079-1.094], and 1.121 [95% CI 1.106-1.136] for underweight, overweight, stage 1 obesity, and stage 2 obesity, respectively, compared with normal BMI) and WC (aHR 0.913 [95% CI 0.906-0.921], 0.969 [95% CI 0.960-0.978], 1.022 [95% CI 1.010-1.034], 1.048 [95% CI 1.032-1.065], and 1.048 [95% CI 1.030-1.067] for levels 1, 2, 4, 5, and 6, respectively, compared with level 3). This dose-dependent relationship remained significant for WC after adjusting for BMI, but not vice versa. A stronger association between abdominal obesity and migraine risk was observed in younger individuals (<30 years) (p for interaction = 0.0181), nonsmokers (p for interaction = 0.0341), and heavy drinkers (p for interaction = 0.0143). Obesity was associated with an increased risk of migraine in young adults in a dose-dependent manner, with WC demonstrating a more robust independent association than BMI. Owing to the limitations of claims data, our study needs cautious interpretation and further validation in studies with detailed clinical information.

Chronic kidney disease (CKD) is common and often coexists with cardiometabolic risk factors and cardiovascular disease (CVD). To evaluate CKD prevalence and awareness among US adults overall and in those with cardiometabolic risk factors or CVD. This serial cross-sectional study was conducted among US adults aged 20 years or older participating in the National Health and Nutrition Examination Survey between 2011 and March 2020. The primary outcomes were prevalence of CKD, defined as estimated glomerular filtration rate less than 60 mL/min/1.73 m2 or urine albumin to creatinine ratio of 30 mg/g or greater, and awareness, based on self-report of a "yes" response to the question "Ever told you had weak/failing kidneys?" among all US adults and those with cardiometabolic conditions (hypertension, diabetes, hyperlipidemia, obesity) or CVD. Survey-weighted logistic regression models were also fit to determine temporal changes in prevalence over the study period. This cross-sectional study included 24 646 adults (weighted mean age, 49 years; 48.4% female), including 20 224 adults with cardiometabolic risk factors or CVD. The overall prevalence of CKD among US adults was 14.6% (95% CI, 14.0%-15.3%), and only 12.3% (95% CI, 11.1%-13.5%) were aware of "weak/failing" kidneys. Among adults with cardiometabolic risk factors or CVD, CKD prevalence was 16.7% (95% CI, 16.0%-17.4%). Awareness of "weak/failing" kidneys was low in this population-only 13.2% (95% CI, 11.9%-14.4%) were aware of their diagnosis over the study period, and the largest awareness gaps occurred among those aged 20 to 64 years, women, and Hispanic adults. Although awareness among adults with CKD and cardiometabolic conditions increased modestly, from 11.5% (95% CI, 8.5%-14.5%) in 2011-2012 to 15.1% (95% CI, 13.1%-17.2%) in 2017 through March 2020 (P = .02), these gains were concentrated among older adults aged 65 years or older (10.8%; 95% CI, 6.9%-14.6% to 17.7%; 95% CI, 14.2%-21.3%), men (9.7%; 95% CI, 5.6%-13.8% to 18.4%; 95% CI, 15.5%-21.4%), and non-Hispanic White adults (10.8%; 95% CI, 6.1%-15.5% to 16.3%; 95% CI, 13.4%-19.2%). No significant improvements in awareness were observed among younger adults aged 20 to 64 years, women, or Black and Hispanic adults. In this nationally representative study, CKD affected 1 in 6 US adults with cardiometabolic conditions, and only a minority of respondents were aware of "weak/failing" kidneys. These findings underscore a significant opportunity to promote awareness and optimal management of CKD.

The impact of marital disruption (divorce or widowed) on the mental health of Cambodian persons has not been studied with a comprehensive and representative national sample. In this study, anxiety, depression, and somatic symptoms were compared among divorced, widowed, and married Cambodian individuals using data from a national mental health survey. Data was collected from 2,690 adults residing in nine randomly selected provinces and Phnom Penh from July to August 2011. Socio-demographic characteristics, depression, anxiety symptoms, somatic symptoms, and marital status were collected during in-person interviews. One-way MANOVAs compared anxiety, depression, and somatic symptoms among married, divorced, and widowed participants. Significant differences were observed on anxiety, depression, and somatic symptoms. When demographic covariates were added to the MANOVA, significant differences in depression were observed, with married participants reporting lower levels of depression relative to divorced and widowed participants. An analysis of depression items indicated that the participants in the divorced group reported higher levels of feeling blue, feeling lonely, and experiencing thoughts of ending their own life. Moderator analyses indicated that marital disruption significantly indirectly influenced depression via demographic characteristics (age, sex, and income) and significantly directly influenced depression. These findings suggest that marital disruption is associated with depression in complex ways. Psychosocial interventions may mitigate some of the effects of marital disruption among Cambodian people.

The atherogenic index of plasma (AIP) is an innovative and comprehensive lipid metric. We intend to examine the possible correlation between the AIP index and stroke in American adults. We analyzed data from the 2017-2018 National Health and Nutrition Examination Survey (NHANES). AIP, calculated as log10(triglycerides/HDL-C), was treated as the exposure variable, and self-reported stroke history served as the outcome. Multivariable logistic regression and smooth curve fitting were used to assess the association, and subgroup analyses with interaction tests were performed. A total of 2,604 participants were included, of whom 1,010 (38.79%) reported a history of stroke. After comprehensive adjustment, AIP showed a positive association with stroke prevalence (odds ratio [OR] = 1.55; 95% confidence interval [CI] = 1.07-2.25). Compared with Quartile 1, participants in Quartile 4 had a 52% higher likelihood of stroke (OR = 1.52; 95% CI = 1.09-2.11). Subgroup analyses indicated that race, hypertension, and diabetes significantly modified the association (p < 0.05). Elevated AIP levels may be associated with an increased prevalence of stroke. Future longitudinal studies were need to explore whether AIP could serve as a useful tool for risk stratification or a potential target for therapeutic interventions.

This study aims to analyze the implementation of health policies in the modern era by highlighting the sustainability dynamics of traditional health services amidst the dominance of modern healthcare systems. Using a bibliometric approach, this study explores scientific publications indexed in the Scopus database over the period 2019–2024. The analysis focuses on publication trends, dominant keywords, institutional collaborations, and country contributions related to the integration of traditional health services into national health policies. The findings reveal a significant increase in publications discussing integrative approaches, particularly concerning the formal recognition and potential of traditional services in supporting sustainable healthcare systems. Nevertheless, challenges such as regulatory inconsistencies, limited funding, and scientific validation continue to pose major barriers. This study recommends the formulation of more inclusive and adaptive health policies that accommodate diverse medical systems while prioritizing the effectiveness, safety, and accountability of healthcare delivery.

Bone mineral density (BMD) is a key indicator of bone health, particularly in older populations, where lower BMD is linked to increased risk of osteoporosis and fractures. Metabolic factors like serum uric acid (UA) and high-density lipoprotein cholesterol (HDL-C) have emerged as possible determinants of bone health. The uric acid to HDL cholesterol ratio (UHR) may offer a new perspective on these metabolic influences. This study explores the association between UHR and femoral neck BMD, with a focus on non-linear relationships and subgroup variations by body mass index (BMI), age, and sex. The study used data from 2178 participants from the 2017-2018 National Health and Nutrition Examination Survey (NHANES). UHR was calculated as the ratio of serum UA to HDL-C. BMD measurements were obtained using dual-energy X-ray absorptiometry (DXA) at the femoral neck. A two-piecewise linear regression model was applied to examine the non-linear relationship between UHR and BMD. Stratified analyses were conducted by BMI, gender, and age groups. A significant inflection point was found at UHR 19. Below this threshold, UHR was positively associated with femoral neck BMD (β = 0.0054, p = 0.013), while above the threshold, the association was negative but not statistically significant (β = -0.0016, p = 0.478). Stratified analysis revealed that the relationship between UHR and BMD remained significant among Mexican Americans even after adjusting for covariates (β = 0.0145, p = 0.012). This study identifies a non-linear association between UHR and femoral neck BMD, with a key inflection point at UHR 19. These findings suggest that UHR could be a useful biomarker for bone health, especially in populations with higher metabolic risks. Further longitudinal studies are necessary to establish causality and explore potential interventions targeting UHR to improve bone health.

Stroke is a serious condition associated with high rates of incidence and mortality. Timely and accurate risk assessment is critical for improving prevention and clinical intervention. This study investigates the application of machine learning models in evaluating the risk of stroke. The data for this study were drawn from the National Health and Nutrition Examination Survey, covering the years 1999 to 2002. To construct predictive models and select relevant variables, 3 approaches were applied: LASSO regression combined with stepwise selection, random forest, and the boruta algorithm in conjunction with LASSO regression. Model performance was evaluated through multiple metrics, including receiver operating characteristic and precision-recall curves, as well as calibration and decision curve analyses. The study analyzed data from 9922 participants, among whom 358 had a history of stroke. Key predictors were identified through a combination of LASSO and stepwise regression, producing a model with strong discriminative performance (area under the curve [AUC] = 0.843). In comparison, the random forest approach selected fewer predictors and showed lower predictive accuracy (AUC = 0.612). A model developed using the boruta algorithm followed by LASSO regression achieved a similarly high level of performance (AUC = 0.828). These findings illustrate how different variable selection methods can influence the predictive accuracy of the resulting models. The machine learning model, which is created using the National Health and Nutrition Examination Survey database, and serves as a reliable means of predicting stroke risk. There is every possibility to set up accurate predictive models with the help of different variable selection techniques and modeling methods that have high accuracy and clinical value.

A novel integrative biomarker, the systemic immune-inflammatory index (SII), has been understudied in cancer research. This study aimed to examine potential associations between body mass index (BMI) and SII in cancer patients. It included cancer patients aged 20 to 79 from the National Health and Nutrition Examination Survey (NHANES) conducted between 2013 and 2018. A cross-sectional analysis comparing SII and BMI was performed using EmpowerStats software (version 3.4.3) and R packages. We utilized multivariate regression analysis to examine the association between SII and BMI in cancer patients. To further explore the relationship between the 2, we employed threshold effect analysis, stratified analysis, and smoothed curve fitting. The study included 1067 cancer patients, with a mean SII value of 553.32 ± 390.44. Our multivariate regression analysis revealed a positive association exists between BMI and SII in the fully adjusted model, with this relationship observed across all 3 groups. The threshold value between log-transformed SII (lgSII) and BMI, as identified by the segmented linear regression model, was 3.04 (×103 cells/μL). However, no inflection point was observed in female patients following stratification by gender. Our findings suggest that SII may reflect the systemic inflammatory status associated with obesity. However, its predictive value requires further validation in prospective studies.

Hypertension (HTN) is a major global health burden influenced by multiple factors. Dietary flavonoids have shown health benefits, yet limited epidemiological studies focus on individual flavonoid intake and HTN risk. The baseline characteristics and disease data of the population in this study are derived from National Health and Nutrition Examination Survey, and the flavonoid intake data come from food and nutrient database for dietary studies. After feature selection, we employed multivariable logistic regression to calculate odds ratio and quantify the protective effect of flavonoids. We then conducted sensitivity analyses using a generalized additive model to assess the nonlinear relationship between flavonoid intake and HTN, and finally performed Shapley additive explanations analysis with 3 machine learning models to explore the ranking of variable importance. This study found that higher intakes of individual flavonoids, particularly quercetin, epicatechin, and naringenin, and of flavonoid subclasses, such as flavanones and flavonols, were associated with a lower risk of HTN. Among these, quercetin and naringenin emerged as the most important individual flavonoids in the machine learning models. Furthermore, the associations between flavanones and naringenin with HTN were linear and negative, whereas quercetin, epicatechin, and flavones exhibited nonlinear relationships with HTN. This study suggests that consuming foods rich in individual flavonoids, such as quercetin, epicatechin, and naringenin, may aid in the control and prevention of HTN, thereby reducing the overall cardiovascular disease burden in the population.

The aim of our research was to explore the relationship between healthy lifestyles and rheumatoid arthritis (RA). Data were collected from the National Health and Nutrition Examination Survey database from 1999 to 2018. The healthy lifestyle score (ranging from 0 to 5) was assessed based on current nonsmoking, low to moderate alcohol drinking, adequate physical activity, optimal waist circumference, and healthy diet. RA patients were identified from the questionnaire data. Weighted multiple regression analysis and subgroup analysis were employed to investigate the association between healthy lifestyles and RA. On this basis, a restricted cubic spline plot was used to examine the nonlinear relationship. A total of 25,325 patients were included in our study, among whom 1236 had RA. After adjusting for all covariates, the multivariable logistic regression analysis indicated that participants adhering to 4 to 5 healthy lifestyle behaviors had a lower probability of having RA compared to those adhering to 0 to 1 healthy lifestyle behaviors (odds ratio = 0.417, 95% confidence interval = 0.304-0.573, P < .001). The interaction test revealed an interaction effect of age. The weighted healthy lifestyle score was more effective in assessing the association between lifestyle and the presence of RA, and the restricted cubic spline plot demonstrated a linear relationship. Overall, adherence to a greater variety of healthy lifestyle behaviors shows a negative association with the occurrence of RA.

Age-Specific Associations Between Adiposity and Mortality in U.S. Adults, 1999-2018.

Endometriosis is a prevalent gynecological disorder, with its pathogenesis potentially linked to oxidative stress. Carotenoids, as natural antioxidants, may play a role in its prevention. This study aimed to investigate the association between serum carotenoid levels and the prevalence of endometriosis. This cross-sectional analysis utilized data from the National Health and Nutrition Examination Survey 2001 to 2006, including 1825 female participants. Survey-weighted logistic regression models were used to assess the associations between serum levels of α-carotene, β-carotene, lycopene, β-cryptoxanthin, lutein/zeaxanthin, and total carotenoids with endometriosis prevalence, adjusting for age, body mass index, poverty income ratio, education level, race/ethnicity, smoking status, age at menarche, and number of pregnancies. Higher serum levels of α-carotene (odds ratio [OR] = 0.94, 95% confidence interval [CI]: 0.89-0.99, P = .048), β-carotene (OR = 0.98, 95% CI: 0.96-1.00, P = .038), lycopene (OR = 0.95, 95% CI: 0.91-0.99, P = .021), and total carotenoids (OR = 0.99, 95% CI: 0.98-1.00, P = .044) were significantly associated with a lower prevalence of endometriosis. However, β-cryptoxanthin (OR = 0.94, 95% CI: 0.88-1.01, P = .12) and lutein/zeaxanthin (OR = 1.00, 95% CI: 0.97-1.03, P = .92) were not significantly associated with endometriosis. Subgroup analysis revealed a significant interaction between β-carotene levels and age at menarche (P for interaction < .05). These findings suggest that higher serum levels of α-carotene, β-carotene, lycopene, and total carotenoids may be associated with a lower prevalence of endometriosis. This study highlights the potential role of carotenoid-rich diets in mitigating endometriosis risk; however, further prospective studies are warranted to confirm these associations and explore underlying biological mechanisms.

Cardiovascular-kidney-metabolic (CKM) syndrome is a systemic condition driven by inflammation. The red blood cell distribution width-to-albumin ratio (RAR) has emerged as a novel marker of systemic inflammation, but its prognostic value in CKM remains unclear. We analyzed 9135 participants from National Health and Nutrition Examination Survey 2007 to 2016 with mortality data obtained from the National Death Index. Weighted Cox proportional hazards models assessed the association between RAR and mortality. Generalized additive models, time-dependent receiver operating characteristic curves, and Fine-Gray competing risk models were used for further evaluation. Over a median follow-up of 91.95 months, 987 deaths occurred, including 241 cardiovascular deaths. Based on an optimal cutoff (RAR = 3.33), participants were stratified into higher and lower RAR groups. The weighted Cox proportional hazards model revealed that individuals with higher RAR had significantly increased risks of all-cause mortality (hazard ratio 2.30, 95% confidence interval [CI] 1.95-2.70) and cardiovascular mortality (hazard ratio 3.26, 95% CI 2.40-4.42). Generalized additive models demonstrated a positive association between RAR and mortality. The main findings remained consistent in the sensitivity analyses. The area under the curve values for predicting all-cause mortality at 1, 3, 5, and 10 years were 0.756, 0.717, 0.708, and 0.695, respectively; the corresponding area under the curves for cardiovascular mortality were 0.708, 0.729, 0.737, and 0.714, respectively. Furthermore, even after accounting for noncardiovascular deaths as competing risk factors, The Fine-Gray model revealed that RAR was an independent predictor of cardiovascular mortality (subdistribution hazard ratio 1.68, 95% CI 1.38-2.04). Elevated RAR independently increases the risk of all-cause and cardiovascular mortality in patients with CKM stages 1 to 4.

Osteoarthritis (OA) is a major global public health issue that significantly impairs patients' quality of life. The neutrophil percentage to albumin ratio (NPAR) has emerged as a promising inflammatory marker for the diagnosis and prognosis of various inflammatory conditions, yet its relationship with OA remains unexplored. This study aimed to examine the association between NPAR and OA and evaluate its diagnostic potential. Using cross-sectional data from the National Health and Nutrition Examination Survey (NHANES, 1999-2020), we analyzed 38,302 participants, including 2890 with OA. Weighted multivariate logistic regression, subgroup analyses, curve fitting, and inflection point analyses were employed, with C-reactive protein as a positive control. Diagnostic performance was assessed via receiver operating characteristic curve analysis. After adjusting for covariates, elevated NPAR was significantly associated with increased OA risk (odds ratio [OR] = 1.045; 95% confidence interval [CI]: 1.016-1.075; P = .0029). Subgroup analyses indicated significant associations in males (OR = 1.071; 95% CI: 1.024-1.121; P = .003), individuals aged 20 to 49 (OR = 1.057; 95% CI: 1.001-1.115; P = .045) and 60 to 69 (OR = 1.064; 95% CI: 1.003-1.130; P = .041), Mexican Americans (OR = 1.115; 95% CI: 1.016-1.223; P = .022), non-Hispanic whites (OR = 1.043; 95% CI: 1.009-1.079; P = .014), and moderate drinkers (OR = 1.117; 95% CI: 1.050-1.189; P < .001). Diagnostic evaluation revealed that NPAR had lower overall accuracy than C-reactive protein; however, among males, its diagnostic performance was comparable. In conclusion, NPAR is positively associated with OA risk and may offer supplementary diagnostic value, particularly in populations where C-reactive protein is less sensitive.

Elevated maternal pre-pregnancy body mass index (BMI) has been suggested to increase risk of offspring autism spectrum disorder (ASD) but evidence is mixed across heterogeneous studies and robust estimates spanning the full BMI range are lacking. This study examined the association between maternal BMI and offspring ASD in a harmonized, two-nation study and across the full BMI range. We included all singleton children born in Denmark 2004-2018 and Sweden 1998-2019 to parents of Nordic origin (n = 2,072,445), with follow-up from age 2 until 31 December 2021, or 2022, respectively. Maternal BMI recorded at the first antenatal visit was obtained from the Swedish and Danish Medical Birth Registers and was analyzed as a continuous variable and in World Health Organization-defined categories of underweight (BMI < 18.5), normal weight (18.5-24.9), overweight (25-29.9), obese class I (30-34.9), and obese class II-III (≥ 35). The relative risk of ASD was estimated as hazard ratios (HR) from Cox regression models, adjusted for birth year and parental age, educational level, income, and psychiatric history at time of childbirth, using data from national health and population registers. Both country-specific and pooled analyses were conducted. Subgroup and sensitivity analyses, including a sibling comparison, were performed to address the specificity and robustness of findings. A total of 58,416 (2.8%) children were diagnosed with ASD during follow-up. The risk of ASD exhibited a J-shaped association with BMI, which gradually increased for mothers with both lower and higher BMI compared to BMI 22 (mid-normal range) (HR = 1.16 [95% CI 1.06-1.27] for BMI 15, and HR = 1.50 [95% CI 1.46-1.53] for BMI 30 in the fully adjusted model). Adjustment for familial factors in a sibling comparison attenuated associations. Both high and low maternal BMI are associated with an increased risk of ASD in the offspring. Familial factors, including genetic and environmental components consistent between siblings, may explain part of the association.

Chronic pain, particularly low back pain (LBP), is common among older adults and may be influenced by cellular aging. Telomere length (TL) has been suggested as a marker for age-related susceptibility to musculoskeletal pain, but evidence in elderly populations is limited. This study examined the association between TL and chronic pain, including LBP, and explored the potential mediating role of smoking. We conducted a cross-sectional analysis of 2070 participants aged ≥ 60 years from National Health and Nutrition Examination Survey 1999 to 2002. TL was measured using quantitative polymerase chain reaction, and pain outcomes were self-reported via questionnaires. Weighted multivariable logistic regression models assessed associations between TL and chronic pain. Mediation analysis was performed to evaluate the potential role of smoking in the TL-LBP relationship. Shorter TL was significantly associated with higher odds of LBP (odds ratios = 0.77, 95% confidence interval: 0.63-0.95), while no significant associations were observed for neck or joint pain. TL was inversely associated with smoking, which in turn was related to higher odds of LBP. Mediation analysis suggested that smoking may partially mediate the association between TL and LBP, explaining approximately 60.9% of the total effect. Shorter TL is associated with LBP in older adults, with smoking potentially acting as a partial mediator. These findings highlight TL as a potential biomarker for lumbar spine-related pain and support smoking cessation as a possible intervention target. Longitudinal studies are needed to further clarify causal pathways and site-specific mechanisms.

Rotator cuff injury (RCI) and myocardial infarction (MI) are prevalent conditions in clinical practice. Nevertheless, the causal relationship between the 2 remains poorly understood. This study aimed to explore the complex association between RCI and MI by integrating cross-sectional analysis with Mendelian randomization (MR) approaches. The cross-sectional study utilized data from the National Health and Nutrition Examination Survey spanning 2011 to 2018, which involved in 567,36 participants. It assessed the correlation between RCI and MI using Chi-square tests, T tests, and a multiple logistic regression model. Additionally, we conducted MR analysis to investigate the causal effects of RCI on MI. We employed inverse variance weighted (IVW), sensitivity analysis, heterogeneity testing, and other methods for MR. The RCI data was sourced from the FinnGen (n = 390,666), while the aggregated data on MI was obtained from genome-wide association studies statistics (n = 638,000). In this cross-sectional analysis, after adjusting for age, gender, race, smoking status, marital status, education level, and poverty income ratio, RCI remained an independent risk factor for MI [odds ratio (OR) 95% confidence interval (CI) = 1.68 (1.43-1.96), P < .001]. The subgroup analysis indicated that females aged over 60 exhibited a higher risk of MI associated with RCI compared to the overall population. The forward MR analysis included 79 single nucleotide polymorphisms (SNPs) linked to RCI. The results revealed a statistically significant causal relationship: individuals with genetic predisposition to RCI were at a higher risk of developing MI [IVW: OR = 1.09, 95% CI: 1.03-1.14, P < .001]. No heterogeneity (P > .05) or horizontal pleiotropy (P > .05) was detected, and the leave-one-out test did not identify any single SNP that unduly influenced the outcome. Conversely, the reverse MR analysis (which incorporated 78 MI-associated SNPs) did not provide strong evidence for a causal link in the opposite direction [IVW: OR = 0.98, 95% CI: 0.94-1.02, P = .39]. These findings suggest a directional causal relationship: RCI may increase the risk of MI, and vice versa, an association that is particularly pronounced in women over 60.

Chronic kidney disease (CKD) is a public health and economic burden with serious adverse health outcomes and extremely low awareness. Current evidence on independent correlates of CKD awareness is inconsistent and recent data examining time trends of CKD awareness in the U.S. are dated. The aims of our study are to examine time trends in CKD awareness from 1999 to 2020 and examine independent correlates of CKD awareness in U.S. adults with CKD. We analyzed data from the National Health and Nutrition Examination Survey (1999-2020). The study sample consisted of 9,825 U.S. adults with CKD. The primary outcome was CKD awareness. Independent correlates included sociodemographic, comorbidity and clinical variables. Unadjusted and adjusted logistic regression models were used to examine the association of CKD awareness and covariates. CKD awareness did not change significantly from 1999 (9.4%) to 2020 (10.8%). Fully adjusted model showed male sex (OR 1.41, 95% CI [1.09, 1.84]), non-Hispanic black race/ethnicity (OR 1.73, 95% CI [1.36, 2.20]), multimorbidity (OR 2.92, 95% CI [2.01, 4.25]), having high risk CKD (OR 2.06, 95% CI [1.57, 2.70]), and very high-risk CKD (OR 5.38, 95% CI [3.99, 7.25]) were associated with higher likelihood of CKD awareness. However, age, education, and insurance were not significantly associated with CKD awareness. During the two decades examined in this study CKD awareness remains extremely low. More prospective studies are needed to understand patient-level barriers to CKD awareness and provider-level barriers to CKD screening, CKD education, and knowledge transfer.

The C-reactive protein-albumin-lymphocyte (CALLY) index is a novel composite biomarker integrating nutritional, immune, and inflammatory statuses, which may offer significant prognostic value for chronic diseases. Given the multifactorial nature of diabetes mellitus, involving nutrition imbalance, immune suppression, and chronic inflammation, this study aimed to evaluate the prognostic significance of the CALLY index for all-cause mortality in diabetic patients. We analyzed data from 3988 diabetic patients aged ≥ 40 years from the National Health and Nutrition Examination Survey from 1999 to 2010. Weighted Cox proportional hazards models, Kaplan-Meier survival analyses, and smoothed curve fitting were conducted to examine associations between the CALLY index and mortality risk. The predictive performance was evaluated by the area under curve the receiver operating characteristic curve. During a median follow-up of 131 months, 1821 deaths occurred (weighted mortality: 41.7%). After full adjustments, each 1-unit increase in ln-transformed CALLY was associated with a 15% reduction in all-cause mortality risk (HR = 0.85, 95% CI: 0.81-0.90, P < .0001). Kaplan-Meier analysis demonstrated significantly greater survival with higher CALLY indices (P < .0001). Smooth curve fitting showed a nonlinear negative correlation between CALLY index and mortality. CALLY exhibited superior predictive accuracy (area under curve = 0.821) compared to traditional inflammatory indices (systemic immune-inflammatory index, platelet-to-lymphocyte ratio, neutrophil-to-lymphocyte ratio). Higher CALLY index is significantly associated with lower all-cause mortality among diabetic patients aged ≥ 40 years. As a simple, cost-effective biomarker, the CALLY index may enhance clinical prognostic assessment and facilitate individualized patient management in diabetes care.