Secular trends in Dietary Inflammatory Index among adults in the United States, 1999-2014

The Mediating Effect of Central Obesity on the Association between Dietary Quality, Dietary Inflammation Level and Low-Grade Inflammation-Related Serum Inflammatory Markers in Adults

To date, few studies have explored the role of central obesity on the association between diet quality, measured by the health eating index (HEI), inflammatory eating index (DII), and low-grade inflammation-related serum inflammatory markers. In this paper, we use the data from the 2015-2018 National Health and Nutrition Examination Survey (NHANES) to explore this. Dietary intakes were measured during two 24-h dietary recall interviews and using USDA Food Pattern Equivalence Database (FPED) dietary data. Serum inflammatory markers were obtained from NHANES Laboratory Data. Generalized structural equation models (GSEMs) were used to explore the mediating relationship. Central obesity plays a significant mediating role in the association between HEI-2015 and high-sensitivity C-reactive protein (hs-CRP), mediating 26.87% of the associations between the two; it also mediates 15.24% of the associations between DII and hs-CRP. Central obesity plays a mediating role in 13.98% of the associations between HEI-2015 and white blood cells (WBC); it also mediates 10.83% of the associations between DII and WBC. Our study suggests that central obesity plays a mediating role in the association of dietary quality with low-grade inflammation-related serum inflammatory markers (hs-CRP and WBC).

Associations between dietary and blood inflammatory indices and their effects on cognitive function in elderly Americans

Objective

To determine the correlations between dietary and blood inflammation indices in elderly Americans and their effects on cognitive function.

Methods

This research extracted data from the 2011-2014 National Health and Nutrition Examination Survey for 2,479 patients who were ≥60 years old. Cognitive function was assessed as a composite cognitive function score (Z-score) calculated from the results of the Consortium to Establish a Registry for Alzheimer's Disease Word Learning and Delayed Recall tests, the Animal Fluency test, and the Digit Symbol Substitution Test. We used a dietary inflammatory index (DII) calculated from 28 food components to represent the dietary inflammation profile. Blood inflammation indicators included the white blood cell count (WBC), neutrophil count (NE), lymphocyte count (Lym), neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), neutrophil-albumin ratio (NAR), systemic immune-inflammation index [SII, calculated as (peripheral platelet count) × NE/Lym], and systemic inflammatory response index [SIRI, calculated as (monocyte count) × NE/Lym]. WBC, NE, Lym, NLR, PLR, NAR, SII, SIRI, and DII were initially treated as continuous variables. For logistic regression, WBC, NE, Lym, NLR, PLR, NAR, SII, and SIRI were divided into quartile groups, and DII was divided into tertile groups.

Results

After adjusting for covariates, WBC, NE, NLR, NAR, SII, SIRI, and DII scores were markedly higher in the cognitively impaired group than in the normal group (p < 0.05). DII was negatively correlated with the Z-score when combined with WBC, NE, and NAR (p < 0.05). After adjusting for all covariates, DII was positively correlated with SII in people with cognitive impairment (p < 0.05). Higher DII with NLR, NAR, SII, and SIRI all increased the risk of cognitive impairment (p < 0.05).

Conclusion

DII was positively correlated with blood inflammation indicators, and higher DII and blood inflammation indicators increased the risk of developing cognitive impairment.

Machine learning for the prediction of cognitive impairment in older adults

Objective

The purpose of this study was to develop and validate a predictive model of cognitive impairment in older adults based on a novel machine learning (ML) algorithm.

Methods

The complete data of 2,226 participants aged 60-80 years were extracted from the 2011-2014 National Health and Nutrition Examination Survey database. Cognitive abilities were assessed using a composite cognitive functioning score (Z-score) calculated using a correlation test among the Consortium to Establish a Registry for Alzheimer's Disease Word Learning and Delayed Recall tests, Animal Fluency Test, and the Digit Symbol Substitution Test. Thirteen demographic characteristics and risk factors associated with cognitive impairment were considered: age, sex, race, body mass index (BMI), drink, smoke, direct HDL-cholesterol level, stroke history, dietary inflammatory index (DII), glycated hemoglobin (HbA1c), Patient Health Questionnaire-9 (PHQ-9) score, sleep duration, and albumin level. Feature selection is performed using the Boruta algorithm. Model building is performed using ten-fold cross-validation, machine learning (ML) algorithms such as generalized linear model (GLM), random forest (RF), support vector machine (SVM), artificial neural network (ANN), and stochastic gradient boosting (SGB). The performance of these models was evaluated in terms of discriminatory power and clinical application.

Results

The study ultimately included 2,226 older adults for analysis, of whom 384 (17.25%) had cognitive impairment. After random assignment, 1,559 and 667 older adults were included in the training and test sets, respectively. A total of 10 variables such as age, race, BMI, direct HDL-cholesterol level, stroke history, DII, HbA1c, PHQ-9 score, sleep duration, and albumin level were selected to construct the model. GLM, RF, SVM, ANN, and SGB were established to obtain the area under the working characteristic curve of the test set subjects 0.779, 0.754, 0.726, 0.776, and 0.754. Among all models, the GLM model had the best predictive performance in terms of discriminatory power and clinical application.

Conclusions

ML models can be a reliable tool to predict the occurrence of cognitive impairment in older adults. This study used machine learning methods to develop and validate a well performing risk prediction model for the development of cognitive impairment in the elderly.

The Association Between Dietary Inflammatory Index and Cognitive Performance in Older Adults Aged 60 Years and Older

Background

Neuroinflammation has been linked to the development of cognitive performance. Epidemiological evidence on dietary inflammatory potential and cognitive performance is scarce. We evaluated the association between dietary inflammatory index (DII) and cognitive performance in older adults.

Methods

This study included adults aged 60 years or older from the 2011–2014 National Health and Nutrition Examination Survey. The DII scores were calculated based on 27 nutritional parameters. Cognitive performance was assessed with four cognitive tests: the Digit Symbol Substitution Test (DSST, n = 2,780), the Consortium to Establish a Registry for Alzheimer’s Disease Word Learning (CERAD-WL, n = 2,859) and Delayed Recall (CERAD-DR, n = 2,857), and the Animal Fluency (AF, n = 2,844) tests. Restricted cubic splines and logistic regression were adopted to assess the associations.

Results

Comparing the highest to lowest tertile of DII scores, the odds ratio (95% CI) of lower cognitive functioning was 1.97 (1.08–3.58) [P-trend = 0.02, per 1 unit increment: 1.17 (1.01–1.38)] on DSST, 1.24 (0.87–1.76) [P-trend = 0.24, per 1 unit increment: 1.09 (0.96–1.23)] on CERAD-WL, 0.93 (0.57–1.51) [P-trend = 0.74, per 1 unit increment: 1.02 (0.87–1.20)] on CERAD-DR, and 1.76 (1.30–2.37) [P-trend < 0.01, per 1 unit increment: 1.17 (1.05–1.29)] on AF. The above-mentioned associations were observed in both men and women. In non-linear dose–response analysis, the association between DII and lower cognitive functioning was not significant at lower DII scores up to 3.0, after which the association was significant and the curve rose steeply.

Conclusion

Higher DII is associated with lower scores on DSST and AF tests in older adults.

Social Determinants of Placental Health and Future Disease Risks for Babies

Birthweight is a well-known predictor of adult-onset chronic disease. The placenta plays a necessary role in regulating fetal growth and determining birth size. Maternal stressors that affect placental function and prenatal growth include maternal overnutrition and undernutrition, toxic social stress, and exposure to toxic chemicals. These stressors lead to increased vulnerability to disease within any population. This vulnerability arises from placental and fetal exposure to stressors during fetal life. The biological drivers linking various social determinants of health to compromised placental function and fetal development have been little studied.

The association between Dietary Inflammatory Index and disability in older adults

BACKGROUND & AIMS

The impact of the potential inflammatory effect of diet on disability has not been adequately investigated. We examined the association of Dietary Inflammatory Index (DII) on disability in older American adults and detected if these associations differed by stratification across sex and body mass index (BMI) level.

METHODS

Data were from the National Health and Nutrition Examination Survey (2007-2016). DII scores were calculated through two 24-h dietary recall interviews. Disability including functional limitations and activities of daily living (ADL) limitations were self-reported. The associations of DII scores on functional limitations and ADL limitations were evaluated by age-sex and multivariable adjusted logistic regression models and further stratification of these associations by sex and BMI level. Restricted cubic splines analyses were used to assess the shapes of these associations.

RESULTS

A total of 6893 participants aged 60 years and above were eligible for this study. DII was related to higher odds of functional limitations. Compared to the lowest quintile of DII scores, the odds ratio (OR) for participants in the second, third, fourth, and highest quintile were 1.61 (95%CI:1.20-2.15), 1.42(95%CI:1.09-1.85), 1.51 (95%CI:1.09-2.09) and 1.97 (95%CI:1.37-2.82) for functional limitations (P-trend = 0.003). The positive associations between DII scores and functional limitations were observed both in men and women. The corresponding ORs (95%CI) across all quintiles were 1.68(1.07-2.66), 1.54(1.06-2.25), 2.03(1.18-3.47), 2.11(1.19-3.74) in men (P-trend = 0.008) and 1.52(1.03-2.27), 1.32(0.86-2.02), 1.24(0.81-1.90), 1.74(1.11-2.73) in women (P-trend = 0.089). In the stratified analyses by BMI level, comparing the lowest quintiles, the corresponding ORs of functional limitations in second, third, fourth, and fifth quintiles were 2.71 (95% CI: 1.57-4.68), 2.39(95% CI: 1.38-4.11), 2.34(95% CI: 1.31-4.19), 2.54(95% CI: 1.25-5.13) in overweight (P-trend = 0.019) and 1.32(95% CI: 0.81-2.15), 1.17(95% CI: 0.71-1.92), 1.33(95% CI: 0.77-2.30), 2.15(95% CI: 1.19-3.87) in obesity (P-trend = 0.032).

CONCLUSIONS

The results provide evidence of a positive association between DII score and functional limitations in American older adults, especially participants with overweight and obesity.