Association Between the Prognostic Nutritional Index and Cognitive Function Among Older Adults in the United States: A Population-Based Study

One-Year Mortality After Percutaneous Endoscopic Gastrostomy: The Prognostic Role of Nutritional Biomarkers and Care Settings

Background/Objectives: This study aimed to evaluate the clinical outcomes, complications, and one-year mortality of patients undergoing percutaneous endoscopic gastrostomy (PEG) in different care settings (hospital, nursing home, and home). Additionally, we investigated the comparative prognostic role of the prognostic nutritional index (PNI) and the CRP-to-albumin ratio (CAR) in predicting mortality among these patients. Methods: A retrospective analysis of 236 adult patients who underwent PEG placement between January 2022 and December 2023 was performed. Demographic, clinical, and laboratory data were collected. The PNI was calculated according to the following formula: PNI = 10 × (albumin) + 0.005 × (lymphocyte count). The CAR was obtained by the ratio of the CRP level to the albumin level. Patients were categorized based on their post-PEG care settings. Results: Neurologic disorders were the most common indication for PEG (69.9%). The one-year mortality was 32.2%, with a median survival of 38 weeks (95% CI: 35-41). In the multivariable model, a lower PNI (HR = 0.93, 95% CI: 0.89-0.97, p < 0.001), as well as being followed in a hospital setting, emerged as independent predictors of mortality. Patients with timely PEG tube replacement showed a reduced mortality risk. The ROC analysis showed that the PNI had a higher AUROC (0.78 ± 0.04) compared to the CAR (0.69 ± 0.04), indicating superior prognostic accuracy for predicting one-year mortality. Conclusions: Care settings significantly influence survival outcomes, with better mortality rates observed in nursing homes and home environments. The PNI was superior to the CAR in predicting one-year mortality, emphasizing its clinical utility in risk stratification for PEG patients. Proactive tube management and individualized care strategies are critical for improving the prognosis in this population.

Relationship between prognostic nutritional index and asthma: a cross-sectional analysis

Background and objective

Asthma is a chronic disease characterized by inflammation of the airways. The association between nutritional status, inflammation, and asthma has been well-documented, yet the relationship between the Prognostic Nutritional Index (PNI) and asthma remains unclear. This is a study to see whether there is a relationship between PNI and asthma prevalence.

Methods

The present study employed data from the National Health and Nutrition Examination Survey (NHANES) between 2017 and 2020, including a total of 7,869 adult participants were included in the analysis. Participants were categorized into four quartiles based on PNI levels. A multivariable regression model was employed for the purpose of evaluating the correlation between PNI and asthma. In order to ascertain the stability of the association across different populations, subgroup analyses were performed.

Results

Higher PNI levels were significantly associated with lower asthma prevalence. In the complete adjusted model, each additional unit of PNI was associated with a 3% reduction in the prevalence of asthma [0.97 (0.95, 0.99)]. Trend analysis indicated a significant negative correlation between PNI and asthma (p for trend = 0.0041). Subgroup analyses showed a consistent negative association across different populations.

Conclusion

The findings of our study indicated that lower PNI values were linked to an elevated odds prevalence of asthma. Early nutritional intervention and inflammation management in high-risk populations with low PNI may reduce the incidence and severity of asthma. Future prospective studies are needed to confirm this relationship.

Association between prognostic nutritional index and stroke: A nationally representative cross-sectional study from NHANES

BACKGROUND

The correlation between the prognostic nutritional index (PNI) and the risk of stroke has become a hot spot within the medical research community. The available evidence from a large sample regarding the correlation between PNI and stroke is inadequate. There is also a need for more research analysis from national surveys.

OBJECTIVE

The principal goal of this research is to improve our understanding of the relationship between PNI and the risk of stroke. This study also intends to investigate the potential synergistic influence of PNI on stroke in combination with other interacting variables.

METHODS

A cross-sectional study was conducted with 35,549 participants selected from the National Health and Nutrition Examination Survey (NHANES) 2005-2018 cycle. Information was gathered from all participants regarding the following: lymphocyte count, albumin levels, stroke occurrence, age, sex, race/ethnicity, education level, poverty income ratio (PIR), marital status, body mass index (BMI), smoking habits, drinking status, physical activity measured in total metabolic equivalents (PA_total_MET), diabetes status, glycohemoglobin levels, total cholesterol, direct high-density lipoprotein cholesterol(direct HDL-cholesterol), hypertension, and coronary heart disease. Curve fitting, subgroup analysis, and multifactor weighted logistic regression analysis were used to examine the relationship between PNI and stroke.

RESULTS

The overall prevalence of stroke was found to be 3.9%, PNI quartile 4(Q4) had an increased prevalence of stroke than quartile 1, 2, and 3(Q1,2,3). Our research suggested a negative association between PNI and the risk of stroke, as indicated by the odds ratio (OR=0.98) with a 95% confidence interval (CI=0.97∼0.99) and a p-value <0.05 (P=0.005), even after adjusting for all confounders. Subsequent subgroup analysis indicated a significant difference in the impact of PNI on stroke between individuals with different body mass index(BMI) levels (p for interaction = 0.02).

CONCLUSION

Our findings underscore that lower PNI in US adults is associated with an increased stroke risk, shedding light on a potential interrelationship between nutrition, inflammatory parameters, and stroke.

Prognostic nutritional index and albuminuria in adults aged 20 years and above: a cross-sectional analysis in the United States

Background and objective

Albuminuria is an important early marker of kidney damage and progression of chronic kidney disease and is also linked to several chronic systemic diseases. The Prognostic Nutritional Index (PNI) is widely used in the assessment of multiple diseases. However, research dealing with the relationship between PNI and albuminuria remains scarce. This research project aims to examine this association.

Methods and materials

The present study employed data from the National Health and Nutrition Examination Survey (NHANES) between 2017 and 2020, including 7,737 adult participants who met the study criteria. PNI was analyzed as a quartile-categorized variable. Multivariable regression models and smoothing curve fitting were adopted to examine the relationship between PNI and albuminuria. In order to ascertain the stability of the association across different populations, subgroup analyses were performed.

Results

The study found a statistically significant inverse relationship between higher PNI levels and the prevalence of albuminuria. The fully adjusted model indicates that a one-unit increase in PNI is associated with a 4% reduced odds of albuminuria prevalence [0.96 (0.93, 0.98)]. Quartile analysis showed a stable inverse relationship, with the highest PNI quartile having the significantly lower odds of albuminuria prevalence [0.76 (0.62, 0.94), p for trend = 0.0004]. Smooth curve fitting and two-piecewise linear regression models indicated a nonlinear relationship between PNI and albuminuria, with a turning point at 42. Subgroup analysis confirmed the reliability of the inverse relationship between PNI and albuminuria across all groups.

Conclusion

The findings of this study indicated that higher PNI levels are significantly inversely related to the odds prevalence of albuminuria. PNI could serve as an important predictor for the occurrence of albuminuria. Further prospective studies are needed to validate this association.

Correlations between nutritional indicators and cognitive function in patients with stable schizophrenia in a hospital setting

BACKGROUND AND OBJECTIVES

Cognitive impairment is a core feature of schizophrenia, and it is now clear that there is a link between nutritional indicators and cognitive functioning. This study aimed to investigate correlations between three nutritional indicators (prognostic nutritional index [PNI], geriatric nutritional risk index [GNRI], and controlling nutritional status score [CONUT]) and cognitive function in hospitalized patients with stable schizophrenia.

METHODS

A total of 235 patients who were hospitalized with stable schizophrenia were included. Patient demographic information was collected through self-reports or electronic medical records, and cognitive function was assessed using the Montreal Cognitive Assessment in China (MoCA-C). Information on serum albumin and total cholesterol levels, lymphocyte counts, and body mass index during the stable stage of schizophrenia was collected to calculate the PNI, GNRI, and CONUT scores, according to their respective calculation criteria. Covariate-adjusted linear regression model and ordered logistic regression model were constructed to determine the relationship between nutritional indicators and cognitive function.

RESULTS

Overall, 90.2% of the patients were under the age of 60 years, and males comprised 60% of all patients. The median scores for MoCA-C, PNI, GNRI, and CONUT in hospitalized patients with stable schizophrenia were 18 (12,23), 52.85 (50.25,55.90), 110.85 (105.80,116.21), and 3 (3,3), respectively. The results of the correlation analysis showed that only PNI was associated with MoCA-C scores (r = 0.15, P = 0.021). This relationship was further confirmed by covariate-adjusted linear regression modeling (β = 0.147, 95%CI:0.049-0.351, p = 0.01) and ordered logistic regression modeling (OR = 0.054, 95%CI:0.001-0.106, p = 0.046).

CONCLUSIONS

The findings revealed a significant correlation between PNI scores and MoCA-C scores in hospitalized patients with stable schizophrenia.

Association between the prognostic nutritional index and severe headache or migraine: a population-based study

PURPOSE

Migraine is a highly prevalent headache disorder, and intake of various nutrients and special diets may improve migraine symptoms. We aimed to clarify the association between nutritional status and migraine.

PATIENTS AND METHODS

We collected the data of 1838/8953 (migraineurs/all participants) from the National Health and Nutrition Examination Survey (NHANES) 1999-2004 cycle. We used weighted multivariable linear or logistic regression analyses to study the association between the prognostic nutritional index (PNI) and the occurrence of severe headache or migraine.

RESULTS

After adjusting for confounding variables, we found that mild (PNI 45-50) or moderate to severe (PNI <45) malnutrition were associated with higher prevalence of severe headache or migraine (odds ratio [OR] 1.06, 95% confidence interval [CI] 1.00-1.12, P = 0.004; OR 1.07, 95% CI 1.03-1.12, P < 0.001). In addition, we found that those with severe headache or migraine consumed less alcohol, dietary fiber, cholesterol, total folate, vitamin A, riboflavin, vitamin B6, vitamin B12, vitamin C, vitamin K, selenium, potassium, magnesium, and copper, and consumed more caffeine and theobromine than did those without severe headache or migraine.

CONCLUSION

The PNI is associated with migraine prevalence, and may thus serve as a predictor of migraine risk and highlights the potential of nutrition-based strategies for migraine prevention and treatment.

Association between Malnutrition and Migraine Risk Assessed Using Objective Nutritional Indices

Dietary triggers are frequently linked to migraines. Although some evidence suggests that dietary interventions might offer a new avenue for migraine treatment, the connection between migraine and nutrition remains unclear. In this study, we explored the association between nutritional status and migraines. Clinical data spanning 11 years were sourced from the Smart Clinical Data Warehouse. The nutritional statuses of 6603 migraine patients and 90,509 controls were evaluated using the Controlling Nutrition Status (CONUT) score and the Prognostic Nutrition Index (PNI). The results showed that individuals with mild, moderate, and severe malnutrition were at a substantially higher risk of migraines than those with optimal nutrition, as determined by the CONUT score (adjusted odds ratio [aOR]: 1.72, 95% confidence interval [CI]: 1.63-1.82; aOR: 5.09, 95% CI: 4.44-5.84; aOR: 3.24, 95% CI: 2.29-4.59, p < 0.001). Similarly, moderate (PNI: 35-38) and severe (PNI < 35) malnutrition were associated with heightened migraine prevalence (aOR: 4.80, 95% CI: 3.85-5.99; aOR: 3.92, 95% CI: 3.14-4.89, p < 0.001) compared to those with a healthy nutritional status. These findings indicate that both the CONUT and PNI may be used as predictors of migraine risk and underscore the potential of nutrition-oriented approaches in migraine treatment.

Association of Dietary α-Carotene and β-Carotene Intake with Low Cognitive Performance in Older Adults: A Cross-Sectional Study from the National Health and Nutrition Examination Survey

This study aims to examine the relationships of dietary α-carotene and β-carotene intake with cognitive function. The data were selected from the National Health and Nutrition Examination Survey (NHANES) 2011-2014. A total of 2009 participants were included in this analysis. Dietary α-carotene and β-carotene intake were averaged by two 24-h dietary recalls. The Consortium to Establish a Registry for Alzheimer's Disease Word Learning subset (CERAD W-L), Animal Fluency Test (AFT), and Digit Symbol Substitution Test (DSST) were used to evaluate cognitive function. Logistic regression and restricted cubic spline models were applied to explore the associations of dietary α-carotene and β-carotene intake with cognitive performance. After adjusting for all confounding factors, compared with individuals in the lowest quartile of β-carotene dietary intake, those in the highest quartile had lower risks of both CERAD W-L decline [odds ratio (OR) = 0.63, 95% confidence interval (CI): 0.44-0.90] and AFT decline (OR = 0.66, 95% CI: 0.47-0.94). In addition, the third quartile of β-carotene dietary intake had a significantly decreased risk of lower DSST (OR = 0.67, 95% CI: 0.48-0.83). Compared with the lowest quartile of α-carotene intake, the OR of AFT decline in the highest intake quartile was 0.66 (95% CI: 0.46, 0.94). For males, both dietary α-carotene and β-carotene intake were associated with a decreased risk of AFT decline (OR = 0.42, 95% CI: 0.25-0.71; OR = 0.51, 95% CI: 0.30-0.85, respectively). For females, dietary α-carotene intake was associated with a decreased risk of CERAD W-L decline (OR = 0.55, 95% CI: 0.33-0.91) and dietary β-carotene intake was associated with decreased risks of both CERAD W-L and AFT decline (OR = 0.37, 95% CI: 0.21-0.64; OR = 0.58, 95% CI: 0.37-0.91, respectively). Our results suggested that higher dietary α-carotene and β-carotene intake had inverse effects on cognitive function decline among older adults.

Associations between urinary caffeine and caffeine metabolites and cognitive function in older adults

BACKGROUND

The effects of caffeine on cognitive impairment have not been conclusively determined. This study aimed to objectively assess the correlation between the urinary caffeine and caffeine metabolites and cognitive decline in older adults.

METHODS

Data on urinary caffeine and caffeine metabolites and the cognitive performance of participants aged 60 years and older were extracted from the National Health and Nutrition Examination Surveys 2011-2014. Binary logistic regression and restricted cubic splines (RCS) analyses were used to evaluate the association between urinary caffeine and caffeine metabolites and cognitive performance.

RESULTS

Eight hundred twenty-seven individuals were enrolled in this cross-sectional study. We observed that 1-methylxanthine, 3-methylxanthine, 7-methylxanthine, 1,3-dimethylxanthine, 1,7-dimethylxanthine, and 3,7-dimethylxanthine levels were significantly and inversely associated with cognitive decline. The RCS results suggested an approximately linear dose-response relationship between the aforementioned metabolites and cognitive performance. Moreover, the effects of urinary caffeine and caffeine metabolites on cognitive function assessed using the AFT were more evident in men.

CONCLUSIONS

Our study suggested that urinary caffeine and caffeine metabolite levels were associated with a reduced risk of cognitive impairment in a linear manner, especially in men.