Specific dietary micronutrients are causally associated with arthritis subtypes: results from the NHANES 2015-2018 and Mendelian randomization study.

Previous studies have shown that serum albumin levels are associated with a greater risk of metabolic syndrome (MetS). However, it is unclear whether this association is causal or only influenced by confounding factors, so further investigation is needed to determine the causal relationships. Researchers selected participants with serum albumin, metabolic syndrome, and related covariates from the National Health and Nutrition Examination Survey (NHANES) database for a total of 14,036 individuals, including 5483 individuals with MetS and 8553 individuals without MetS. The association of serum albumin levels with metabolic syndrome and its components was estimated using weighted multivariable logistic regression, with its nonlinearity being examined by restricted cubic spline (RCS) regression. Bidirectional two-sample Mendelian randomization (MR) analysis was performed using Genome-Wide Association Study (GWAS) data on serum albumin and MetS to assess the causal relationship between serum albumin levels and MetS and its components. The primary MR analyses were performed via an inverse variance weighting (IVW) approach. In addition, several sensitivity analyses were performed to assess the robustness of the results. The STROBE-MR checklist for the reporting of MR studies was used in this study. After confounder adjustment, when the serum albumin levels were analyzed as a continuous variable, the multivariable logistic analysis revealed a significant association between it and metabolic syndrome (OR: 1.032, 95% CI: 1.012–1.052). When the serum albumin levels were used as categorical variables, the adjusted odds ratios (ORs) with 95% confidence intervals (CIs) for metabolic syndrome across higher serum albumin levels quartiles were 0.981 (0.842–1.143), 1.290 (1.115–1.492), and 1.244 (1.064–1.454) compared to the lowest quartile, respectively. In the forward MR study, the IVW method revealed that genetic predicted increased levels of serum albumin were positively correlated with metabolic syndrome (OR: 1.149, 95% CI: 1.016–1.299) and its components, including hypertension (OR: 1.130, 95% CI: 1.013–1.260) and triglycerides (OR: 1.343, 95% CI: 1.209–1.492). In the reverse MR study, the IVW method showed no significant causal relationship between MetS, hypertension, fasting blood glucose and HDL-C with serum albumin levels. The results from the NHANES and MR analysis have revealed a causal relationship between serum albumin levels and both metabolic syndrome and hypertension, indicating that elevated levels of serum albumin are a risk factor for these conditions. Our results provide new biomarkers for preventive and therapeutic strategies for metabolic syndrome.

Low levels of high-density lipoprotein cholesterol (HDL-C) are commonly seen in patients with type 2 diabetes mellitus (T2DM). However, it is unclear whether there is an independent or causal link between HDL-C levels and T2DM. This study aims to address this gap by using the The National Health and Nutrition Examination Survey (NHANES) database and Mendelian randomization (MR) analysis. Data from the NHANES survey (2007-2018) with 9,420 participants were analyzed using specialized software. Logistic regression models and restricted cubic splines (RCS) were used to assess the relationship between HDL-C and T2DM incidence, while considering covariates. Genetic variants associated with HDL-C and T2DM were obtained from genome-wide association studies (GWAS), and Mendelian randomization (MR) was used to evaluate the causal relationship between HDL-C and T2DM. Various tests were conducted to assess pleiotropy and outliers. In the NHANES study, all groups, except the lowest quartile (Q1: 0.28-1.09 mmol/L], showed a significant association between HDL-C levels and reduced T2DM risk (all P < 0.001). After adjusting for covariates, the Q2 [odds ratio (OR) = 0.67, 95% confidence interval (CI): (0.57, 0.79)], Q3 [OR = 0.51, 95% CI: (0.40, 0.65)], and Q4 [OR = 0.29, 95% CI: (0.23, 0.36)] groups exhibited average reductions in T2DM risk of 23%, 49%, and 71%, respectively. In the sensitivity analysis incorporating other lipid levels, the Q4 group still demonstrates a 57% reduction in the risk of T2DM. The impact of HDL-C levels on T2DM varied with age (P for interaction = 0.006). RCS analysis showed a nonlinear decreasing trend in T2DM risk with increasing HDL-C levels (P = 0.003). In the MR analysis, HDL-C levels were also associated with reduced T2DM risk (OR = 0.69, 95% CI = 0.52-0.82; P = 1.41 × 10-13), and there was no evidence of pleiotropy or outliers. This study provides evidence supporting a causal relationship between higher HDL-C levels and reduced T2DM risk. Further research is needed to explore interventions targeting HDL-C levels for reducing T2DM risk.

Hypertension and non-alcoholic fatty liver disease (NAFLD) share several pathophysiologic risk factors, and the exact relationship between the two remains unclear. Our study aims to provide evidence concerning the relationship between hypertension and NAFLD by analyzing data from the National Health and Nutrition Examination Survey (NHANES) 2017-2018 and Mendelian randomization (MR) analyses. Weighted multivariable-adjusted logistic regression was applied to assess the relationship between hypertension and NAFLD risk by using data from the NHANES 2017-2018. Subsequently, a two-sample MR study was performed using the genome-wide association study (GWAS) summary statistics to identify the causal association between hypertension, systolic blood pressure (SBP), diastolic blood pressure (DBP), and NAFLD. The primary inverse variance weighted (IVW) and other supplementary MR approaches were conducted to verify the causal association between hypertension and NAFLD. Sensitivity analyses were adopted to confirm the robustness of the results. A total of 3144 participants were enrolled for our observational study in NHANES. Weighted multivariable-adjusted logistic regression analysis suggested that hypertension was positively related to NAFLD risk (odds ratio [OR] = 1.677; 95% confidence interval [CI], 1.159-2.423). SBP ≥130 mmHg and DBP ≥80 mmHg were also significantly positively correlated with NAFLD. Moreover, hypertension was independently connected with liver steatosis ( β = 7.836 [95% CI, 2.334-13.338]). The results of MR analysis also supported a causal association between hypertension (OR = 7.203 [95% CI, 2.297-22.587]) and NAFLD. Similar results were observed for the causal exploration between SBP (OR = 1.024 [95% CI, 1.003-1.046]), DBP (OR = 1.047 [95% CI, 1.005-1.090]), and NAFLD. The sensitive analysis further confirmed the robustness and reliability of these findings (all P >0.05). Hypertension was associated with an increased risk of NAFLD.

Risk of myocardial infarction and Osteoporosis: Insights from the 2015–2018 NHANES and Mendelian randomization Studies

Autoimmune liver diseases (AILDs), including autoimmune hepatitis (AIH), primary biliary cholangitis (PBC), and primary sclerosing cholangitis (PSC), often have complex interactions with thyroid diseases (TDs), such as hypothyroidism, hyperthyroidism, and Hashimoto thyroiditis (HT). These conditions frequently coexist and may share common autoimmune mechanisms, but their exact relationship remains poorly understood. Chronic hepatitis C (CHC), a viral liver disease, also affects thyroid function, but its interaction with TD is still under investigation. This study explores the causal links between AILD, CHC, and TD using data from the National Health and Nutrition Examination Survey (NHANES) and Mendelian randomization (MR) analysis. Data were sourced from NHANES (2013–2018) and various genome-wide association studies. The NHANES analysis included 8978 participants after applying inclusion and exclusion criteria. Logistic regression models were used to assess associations between CHC and TD. MR analysis employed single-nucleotide polymorphisms as instrumental variables to investigate causal relationships between AILD, CHC, and TD. NHANES analysis revealed no significant association between CHC and TD. Forward MR analysis indicated significant causal relationships between PBC and hypothyroidism (inverse variance weighting [IVW] odds ratio [OR] = 1.004, 95% confidence intervals [CI] 1.002–1.006, P < .001), PSC and hyperthyroidism (IVW OR = 1.002, 95% CI 1.002–1.003, P < .001), and PBC and HT (IVW OR = 1.05, 95% CI 1.012–1.089, P = .010). Reverse MR analysis suggested causal links between hypothyroidism, hyperthyroidism, HT, thyroid cancer, and AIH, as well as hypothyroidism with PBC and PSC. Multivariable MR confirmed significant associations between AIH and hypothyroidism (P < .001), hyperthyroidism (P = .008) across IVW method. The IVW method also revealed another significant causal relationship between PSC and hyperthyroidism (P < .001), HT (P = .013). Multivariable MR also analysis to investigate the association between TD as exposures and AILD as outcomes; the IVW method revealed a noteworthy causal association solely between HT and AIH (P = .035). The study identified significant causal associations between AILD (particularly PBC and PSC) and specific TD, emphasizing the need for regular thyroid monitoring in AILD patients. However, no significant causal link was found between CHC and TD.

BackgroundDiabetes mellitus (DM) and arthritis are prevalent conditions worldwide. The intricate relationship between these two conditions, especially in the context of various subtypes of arthritis, remains a topic of interest.ObjectiveTo investigate the relationship between diabetes and arthritis, with a focus on Rheumatoid Arthritis (RA), using data from the National Health and Nutrition Examination Survey (NHANES) and Mendelian Randomization (MR) analysis.MethodsData from six consecutive NHANES cycles from 2007 to 2018 were analyzed, involving 30,062 participants after applying exclusion criteria. The association between diabetes and arthritis was assessed using logistic regression. MR was employed to determine the causal relationship between the two conditions using Genome-Wide Association Study (GWAS) data.ResultsThe prevalence of arthritis in diabetic patients was almost twice that of non-diabetic patients. Logistic regression showed a significant gross association between arthritis and diabetes with an OR of 2.90 (95% CI: 2.66–3.16). After adjusting for age, gender, race, and other factors, the association yielded an OR of 1.14 (95% CI: 1.00–1.29, p < 0.05). MR analyses indicated a significant association between Type 1 Diabetes and RA (OR = 1.407, p = 0.002), but no significant correlation was observed for Type 2 Diabetes.ConclusionThere is an association between diabetes and arthritis, with potential genetic links between Type 1 Diabetes and RA.

This study examines the causal association between hyperlipidemia and Alzheimer disease (AD) by utilizing a mix of data from the National Health and Nutrition Examination Survey (NHANES) and 2 sample Mendelian randomization (MR) analysis. The NHANES cross-sectional data (2011–2012 and 2013–2014) was used to investigate the correlation between hyperlipidemia and cognitive impairment in individuals with AD, as measured by the consortium to establish a registry for AD word learning (CERAD-WL). This was accomplished by employing multivariable logistic regression models to compute odds ratios (ORs). The MR analysis leveraged summary-level genetic data to assess the causal effects of various cholesterol traits, consisting of total cholesterol, triglycerides, low-density lipoprotein (LDL) cholesterol, and high-density lipoprotein (HDL) cholesterol, medium HDL cholesterol, and cholesteryl ester levels in small very LDL, on AD risk. There were several MR approaches that were utilized, including the inverse-variance weighted, weighted median, MR-Egger, and weighted mode. The NHANES data showed that participants with low cognition (lowest quartile of CERAD-Total score) had significantly greater incidences of hyperlipidemia in comparison to individuals who possessed normal cognitive abilities. The multivariable-adjusted OR was 2.159 (95% CI: 1.161–4.451, P <.001) for the lowest versus highest CERAD-Total score quartile. The MR analysis provided evidence for causal links between cholesterol traits and AD risk. Higher levels of total cholesterol (OR: 0.867, 95% CI: 0.776–0.968, P = .011), triglycerides (OR:0.870, 95% CI: 0.767–0.985, P = .028) were connected to increased AD risk. Higher HDL cholesterol was protective (OR: 1.045, 95% CI: 1.000–1.092, P = .049). Not a very strong causative effect was found for LDL cholesterol, medium HDL cholesterol or cholesteryl ester in small very LDL and AD. This combined NHANES and MR analysis provides robust evidence that hyperlipidemia, specifically elevated total cholesterol, and triglycerides, is causally associated with increased risk of AD, while higher HDL cholesterol is protective. These data indicate that addressing irregularities in cholesterol levels could be a potential strategy for controlling and preventing AD.

It is currently controversial whether smoke exposure is associated with the risk of kidney stones. Herein, publicly available databases were combined to explore relationships with the risk of nephrolithiasis in terms of smoking status and serum cotinine concentrations. First, we conducted an observational study using data from 2007 to 2018, based on the National Health and Nutrition Examination Survey (NHANES) database. Univariate analysis, multivariate logistic regression, trend testing, restricted cubic spline (RCS), and multiple imputation (MI) were the main analytical methods of our study. Then, A Mendelian randomization (MR) analysis was performed to explore the causal relationship between serum cotinine and nephrolithiasis. Genetic instruments for serum cotinine and pooled data for kidney stones were derived from publicly available large-scale genome-wide association studies (GWAS). Inverse-variance weighting (IVW) was the primary method for our MR analysis. A total of 34,657 and 31,352 participants were included in the observational study based on smoking status and serum cotinine concentrations, respectively. Under full adjustment of covariates, current smokers had an increased risk of kidney stones compared to non-smokers [OR = 1.17 (1.04-1.31), P = 0.009, P for trend = 0.010]. Compared with serum cotinine of <0.05 ng/ml, serum cotinine levels of 0.05-2.99 ng/ml [OR = 1.15 (1.03-1.29), P = 0.013] and ≥3.00 ng/ml [OR = 1.22 (1.10-1.37), P < 0.001] were observed to have a higher risk of nephrolithiasis (P for trend < 0.001). In addition, a non-linear relationship between log2-transformed serum cotinine and the risk of nephrolithiasis was found (P for non-linearity = 0.028). Similar results were found when serum cotinine (log2 transformation) was used as a continuous variable [OR = 1.02 (1.01-1.03), P < 0.001] or complete data was used to analyze after MI. In the MR analysis, genetically predicted high serum cotinine was causally related to the high risk of nephrolithiasis [IVW: OR = 1.09 (1.00-1.19), P = 0.044]. Current smoking and high serum cotinine concentrations may be associated with an increased risk of kidney stones. Further research is needed to validate this relationship and explore its underlying mechanisms.

Obstructive Sleep Apnea (OSA) is associated with metabolic disturbances, including hypertension, insulin resistance, and dyslipidemia, collectively known as Metabolic Syndrome (MetS). The relationship between OSA and MetS remains controversial. This study aims to investigate the relationship between OSA and MetS by conducting an observational study using data from NHANES and applying Mendelian Randomization (MR) analysis to examine the bidirectional causal relationship. We utilized data from the National Health and Nutrition Examination Survey (NHANES) collected between 2005 and 2008. Diagnosis of OSA was evaluated using the multivariate apnea predictive index (MAP index), while MetS was identified based on established clinical criteria. Genetic data were sourced from recent genome-wide association studies (GWAS) to perform a two-sample MR analysis. Instrumental variables were selected based on strict significance thresholds and linkage disequilibrium criteria. The primary MR analysis employed the inverse variance weighted (IVW) method, supplemented by weighted median and MR-Egger regression methods. A strong association was identified between OSA and Mets through multivariate logistic regression analysis by using data from the NHANES. The MR analysis revealed a significant bidirectional causal relationship between OSA and MetS. Specifically, OSA was found to increase the risk of MetS (IVW OR = 1.52, 95% CI = 1.08-2.14, P = 0.016), and MetS was similarly found to elevate the risk of OSA (IVW OR = 1.97, 95% CI = 1.76-2.21, P = 7.58E-32). Sensitivity analyses confirmed the robustness of these findings, with no significant evidence of pleiotropy. This study provides genetic evidence supporting a bidirectional causal relationship between OSA and MetS. These findings underscore the interlinked nature of sleep-disordered breathing and metabolic health, suggesting that addressing one condition could benefit the other. Integrated treatment strategies targeting shared risk factors, such as obesity, may enhance overall health outcomes.

The association between dietary zinc intake and epilepsy remains unclear. This study aimed to investigate the relationship between zinc intake from the diet and epilepsy, employing Mendelian randomization (MR) to explore potential causal links between zinc and epilepsy. The cross-sectional study utilized data from the National Health and Nutrition Examination Survey (NHANES) conducted between 2013 and 2018. Among the 4,434 participants included, 1.5% (67/4,434) reported having epilepsy. Restricted cubic spline models and logistic regression models were employed to examine the relationships between dietary zinc intakes and epilepsy. Subsequently, a 2-sample Mendelian randomization (MR) analysis was conducted using the inverse variance weighted (IVW) approach as the primary analysis. In the restricted cubic spline (RCS) analysis, the relationship between dietary zinc consumption and epilepsy displayed an L-shaped curve (nonlinear, p = 0.049). After multivariate adjustments, the adjusted odds ratios for epilepsy in T2 (5.0-11.0 mg/day) and T3 (≥11.0 mg/day) were 0.49 (95% confidence interval [CI]: 0.26-0.92, p = 0.026) and 0.60 (95% CI: 0.31-1.17, p = 0.132), respectively, compared to the lowest dietary zinc consumption tertile (T1, ≤5.0 mg/day). The IVW method indicated that genetically predicted zinc intake per standard-deviation increase was inversely associated with three types of epilepsy, including all types of epilepsy (OR = 1.06, 95% CI: 1.02-1.11, p = 0.008), generalized epilepsy (OR = 1.13, 95% CI: 1.01-1.25, p = 0.030), and focal epilepsy (documented hippocampal sclerosis) (OR = 1.01, 95% CI: 1.00-1.02, p = 0.025). Our findings suggest that a daily zinc intake ranging from 5.0 to 11.0 mg is associated with the lowest risk of epilepsy. Furthermore, Mendelian randomization (MR) studies provide additional support for the existence of a causal relationship between zinc and epilepsy.

Background: The association of vitamin A intake with depression remains unclear. This study combined observational research and Mendelian randomization (MR) analysis to explore the relationship between vitamin A intake and depression. Methods: First, we performed a cross-sectional study utilizing the National Health and Nutrition Examination Survey (NHANES) data from 2005 to 2020. Weighted multivariable logistic regressions and restricted cubic spline (RCS) regression were applied to explore the association between vitamin A intake and depression. We also conducted stratified and sensitivity analyses to assess the robustness of the results. Second, we conducted a MR analysis to assess the causal association between vitamin A and depression risk using the publicly available Genome-Wide Association Studies (GWAS) database. The inverse-variance weighted (IVW) method was our primary method for MR analysis. In addition, we performed multiple sensitivity analyses to evaluate the reliability of the results, including Cochran’s Q test, MR-Egger intercept regression, MR-Pleiotropy Residual Sum and Outlier (MR-PRESSO), and leave-one-out analysis. Results: In the cross-sectional study, a total of 38,157 individuals were enrolled. The vitamin A intake was negatively associated with depression after adjusting for all covariates (OR=0.92, 95%CI: 0.88-0.97, P=0.001). Similar inverse associations were observed when vitamin A intake was converted into categorical variables. The RCS analysis found an L-shaped nonlinear relationship between dietary vitamin A intake and depression (P for non-linearity=0.010) after adjusting for all covariates. Vitamin A consumption was inversely associated with depression (OR=0.999, 95% CI: 0.999-1.000, P=0.002) for intakes below 492.00 μg. In contrast, no association was found between dietary vitamin A intake and depression (P=0.656) for intakes of 492.00 μg or higher. Furthermore, The inverse relationship between vitamin A intake and depression remained robust in both stratified and sensitivity analyses. In the MR analysis, a total of 15 single-nucleotide polymorphisms (SNPs) were identified as instrumental variables (IVs). The IVW method found no significant causal relationship between vitamin A and the risk of depression (OR=0.39, 95%CI: 0.10-1.58, P=0.188). Similar results were found in MR-Egger method, weighted median method, simple mode method, and weighted mode method. Sensitivity analyses confirmed the reliability of these results. Conclusions: The observational study found that vitamin A intake was inversely associated with depression, regardless of whether vitamin A was measured as a continuous or categorical variable. However, findings from the MR analysis did not indicate a causal relationship between vitamin A and depression risk.

Evidence from observational studies on the association between folate and metabolic dysfunction-associated steatotic liver disease (MASLD) is conflicting. This study aimed to investigate the association between serum folate concentration and MASLD and further assess the causal relationship using Mendelian randomization (MR) analysis. To investigate the causal relationship between serum folate and MASLD, we conducted a cross-sectional study that selected 1,117 participants from the 2017-2020 National Health and Nutrition Examination Survey (NHANES). The association between serum folate level and the risk of MASLD was evaluated under a multivariate logistic regression model. In addition, we conducted a two-sample MR study using genetic data from a large genome-wide association study (GWAS) to compare serum folate level (37,465 individuals) and MASLD (primary analysis: 8,434 cases/770,180 controls; Secondary analysis:1,483 cases/17,781 controls) were performed to infer causal relationships between them. Inverse variance weighted (IVW) was used as the primary method of MR Analysis. The results from the NHANES database showed that Tertile 3 group (Tertile 3: ≥ 48.6 nmol/L) had a significantly lower risk (OR = 0.58, 95% CI: 0.38-0.88, p = 0.010) of MASLD than Tertile 1 group (Tertile 1: < 22.3 nmol/L) after complete adjustments. However, in the IVW of MR analysis, there was no causal relationship between serum folate level and MASLD risk in the primary analysis (OR = 0.75, 95% CI: 0.55-1.02, p = 0.065) and secondary analysis (OR = 0.83, 95% CI: 0.39-1.74, p = 0.618). In observational analyses, we observed an inverse association between higher serum folate concentrations and a reduced risk of MASLD. Our MR study generated similar results, but the association failed to reach the significance threshold of p < 0.05, suggesting that our MR study does not support a causal relationship between serum folate levels and MASLD risk. Additional research involving a larger number of cases would contribute to enhancing the confirmation of our preliminary findings.

Airway inflammation is considered one of the pathogenic factors in rheumatoid arthritis (RA), but the role of chronic obstructive pulmonary disease (COPD) in the development of RA remains unclear. We used cross-sectional studies and Mendelian randomization (MR) analysis to explore the link between COPD and RA. In National Health and Nutrition Examination Survey (NHANES) 2013-2018, the association between COPD and RA was investigated using weighted logistic regression models. We also used subgroup analysis and interaction tests to explore the relationship between COPD and RA in populations with different clinical characteristics. The inverse-variance weighted (IVW) method was the primary method of MR analysis for investigating the causal effect of exposure on outcome. After adjusting for smoking history and other variables, weighted logistic regression analysis of 14 768 participants indicated that COPD is associated with an increased odds of developing RA (OR = 1.899, p < 0.001). Interaction tests showed that there is an interaction with this relationship concerning gender, age, body mass index (BMI), and hypercholesterolemia (p < 0.05). MR analysis showed a causal relationship between COPD and increased odds of RA (OR = 1.072, p = 0.008). Multivariable MR analysis, adjusted for smoking, also yielded the same result (OR = 1.071, p = 0.024). Our study suggests that COPD may have a potential causal role in the development of RA. Further research is needed to validate our findings.

BackgroundBeef is common in daily diet, but its association with the risk of rheumatoid arthritis (RA) remains uncertain. The objective of this study is to explore the relationship between beef intake and the risk of RA.Materials and methodsWe investigated the association between beef intake and risk of RA by multivariate logistic regression, based on the National Health and Nutrition Examination Survey (NHANES) 1999–2016 involving 9,618 participants. The dose–response relationship between beef intake and RA was explored as well. Furthermore, we performed Mendelian randomization (MR) analysis to examine the causal effect of beef intake on RA. Genetic instruments for beef intake were selected from a genome-wide association study (GWAS) including 335,576 individuals from the UK Biobank study, and summary statistics relating to RA were obtained from a GWAS meta-analysis of 14,361 RA patients and 43,923 controls. The inverse-variance weighted (IVW) approach was used to estimate the causal association, and MR-Egger regression and Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) test were applied to evaluate the pleiotropy and outliers.ResultsCompared with the lowest quintile (0 to ≤33.50 g/d), beef intake was found to be significantly associated with the risk of RA [odds ratio (OR): 1.94; 95% confidence interval (CI): 1.20–3.12] in the third quintile (50.26 to ≤76.50 g/d). Moreover, a reversed “U” dose–response relationship between beef and RA (Pnon–linearity = 0.023) was found. In the MR analysis, beef intake was associated with an increased risk of RA (OR: 3.05; 95% CI: 1.11–8.35; P = 0.030) by the IVW method. The results from MR-Egger regression and MR-PRESSO test showed that there were no pleiotropic variations and outliers.ConclusionThis study indicated that there is suggestive evidence to support the causal effect of beef intake on the risk of RA, while further studies are warranted to elucidate the exact association.

Cognitive function (CF) deterioration is a pressing concern in geriatric research. This study aimed to explore the relationship between physical activity (PA) and CF in older adults. This study adopted a dual approach, employing both observational and genetic approaches through data from the National Health and Nutrition Examination Survey (NHANES) 2011-2014 and Mendelian Randomization (MR) analysis. For the NHANES component, PA levels were evaluated using the Global Physical Activity Questionnaire, and CF was assessed via standardized tests. Multivariate regression, threshold effect analysis, smoothing curve fitting, and subgroup analyses were conducted to examine the association between PA and CF. In parallel, MR methods, using genetic variants as instrumental variables, assessed the causal impact of PA on CF and related conditions such as Alzheimer's disease and dementia. Observational findings from NHANES demonstrated a positive correlation between PA and CF, notably among female participants. The detailed analysis identified specific thresholds of PA that correlate with cognitive enhancements. However, MR results did not support a significant causal relationship between PA and CF or dementia-related outcomes, indicating an absence of a direct genetic basis for the observational associations. Although observational data from NHANES suggest that PA is positively associated with CF in older adults, particularly among women, MR analysis did not confirm these findings as causally related. The discrepancy highlights the complexity of the PA-CF relationship and underscores the need for further research. These results emphasize the potential of PA as a modifiable risk factor for CF, though causal effects remain to be definitively established.