Anwara T. Merchant

Objectives: To investigate the associations between nutritional status and early childhood caries (ECC) in a Thai population, hypothesizing that nutritional extremes, including undernutrition and overnutrition, are associated with increased ECC risk. Methods: Data from a birth cohort study of Thai children in Khon Kaen were analyzed. Nutritional status at 2 y of age was assessed using anthropometric measurements (height-for-age, weight-for-age, weight-for-height, and body mass index–for-age [BMI-for-age]) categorized by Z-scores adjusted for age and sex. Dental caries was assessed at ages 3 to 4 y using World Health Organization criteria, with ECC defined by the presence of cavitated lesions. Modified Poisson and negative binomial regression analyses with robust variance estimated relative risks (RRs) and 95% confidence intervals (CIs) for ECC prevalence and dmft scores, adjusting for maternal education, breastfeeding duration, sweet consumption frequency, and visible plaque. Results: Among 549 children, overweight/obese children (n = 27) exhibited a significantly lower prevalence of ECC compared with those with normal weight (n = 471) or wasting (n = 50; 59.3% versus 89% and 94%, respectively; P < 0.001). The adjusted RR for overweight/obesity was 0.66 (95% CI: 0.48–0.92) compared with normal weight and 0.64 (95% CI: 0.46 –0.90) compared with wasting. Children with normal weight and those with wasting had comparable ECC prevalence rates (P = 0.50). Similar trends were observed for dmft scores, with overweight/obese children having significantly lower scores compared with those with normal weight or wasting (4.3 versus 7.3 and 8.0, respectively; P = 0.004). Height-for-age and weight-for-age were not significantly associated with ECC, while BMI-for-age yielded results consistent with those for weight-for-height. Conclusion: This study reveals an unexpected inverse relationship between overweight status and ECC, suggesting a more complex interplay between nutrition and caries risk. These findings underscore the need for further research into the mechanisms underlying this relationship to inform ECC prevention strategies. Knowledge Transfer Statement: Our findings challenge the hypothesis that all nutritional extremes increase caries risk, revealing an unexpected protective effect of being overweight. This highlights the complex nutrition–caries relationship and the need for context-specific evidence. Further research into the mechanisms behind this surprising link is essential to develop effective and targeted preventive strategies, rather than assuming all nutritional improvements are beneficial for dental health.

Inconsistent findings regarding health outcomes associated with Supplemental Nutrition Assistance Program (SNAP) use may be influenced by common biases in observational studies. We used negative control methods to evaluate the association between SNAP and cognition while adjusting for unmeasured bias. This observational study analysed data from six waves (2008–18) of the Health and Retirement Study—a biennial cohort survey of US adults aged ≥51 years. The analytic sample included 11 942 community-dwelling participants without dementia. SNAP use and household income were self-reported. Global cognitive function (0–27) was assessed via telephone interview. Group differences in cognitive performance were estimated by using three approaches: multiple linear regression, negative control outcome (NCO), and double negative controls (DNCs). Linear regression models indicated that SNAP users had lower cognitive scores post-SNAP use, with the deficit increasing from –1.48 [95% confidence interval (CI): –1.77, –1.18] in 2010 to –1.84 (95% CI: –2.24, –1.44) in 2018. On the contrary, both the NCO and DNC adjustment results indicated minimal associations between SNAP use and subsequent cognitive performance. NCO estimates ranged from 0.16 (95% CI: –0.23, 0.55) in 2010 to –0.04 (95% CI: –0.57, 0.50) in 2018. DNC estimates ranged from 0.22 (95% CI: –0.40, 0.84) in 2010 to –0.17 (95% CI: –1.06, 0.73). Sensitivity analyses produced similar results. After common biases were accounted for by using negative controls, SNAP use had little association with cognitive performance. Valid estimates of potential health benefits or harms associated with SNAP may better inform policies and individual decision-making.

Background: The presence of the apolipoprotein E4 ( APOE4 ) allele and periodontal disease are independently correlated with higher levels of amyloid-β and inflammation in the brain, worse cognition, and Alzheimer's disease. Objective: To assess whether the presence of the APOE4 allele modifies the relationship between IgG antibodies against periodontal microorganisms and cognitive function in older adults participating in the NHANES III study. Methods: This cross-sectional analysis was conducted among participants of the third National Health and Nutrition Examination Survey (NHANES III) (1988 to 1994), aged 60 years and older, with measurements of IgG antibodies against 19 periodontal microorganisms and APOE4 alleles (N = 1644). Results: Approximately 77.5% of participants carried no APOE4 allele, 20.0% had one allele, and 2.6% were homozygous. Mean cognitive scores were 16.1, 16.0, and 15.3 for non-carriers, heterozygous, and homozygous APOE4 allele carriers, respectively (p = 0.01). Antibody groups were not correlated with APOE4 carrier status. The Orange-Blue cluster (antibodies against E. nodatum, A. naeslundii ) was correlated with cognitive score (Spearman r = 0.08, p < 0.001), but not other antibody groups. In the multivariable-adjusted models, APOE4 alleles did not modify the associations between antibody clusters and cognitive score (p-interaction > 0.05). Conclusions: Mean cognitive scores were lower among APOE4 carriers. The APOE4 allele did not modify associations between groups of IgG antibodies against periodontal microorganisms and cognition among older aged adults without cognitive impairment. These findings need to be verified in larger prospective studies.

Introduction: Household food insecurity, defined as inconsistent access to sufficient food in a household, affects 1 in 15 individuals over the age of 60 years in the US. In these individuals it is associated with numerous chronic conditions, medication underuse leading to poorly controlled conditions such as diabetes and hypertension, and poor oral health. However, the relationship between food insecurity and oral health is understudied. We therefore evaluated the associations between food insecurity and aspects of oral health in older US adults.Methods: We prospectively evaluated a subset of participants of the Health and Retirement Study (HRS) who responded to questions evaluating food insecurity in 2013 and a supplemental questionnaire regarding dental health and dental health services in 2018 (N = 472).Results: Approximately 1 in 5 people in our study reported being food insecure in the last year. Food insecurity was correlated with poor oral health-related quality of life scores and more tooth loss. Individuals who were food insecure reported worse self-rated oral health (OR = 2.67), greater odds of losing 8 or more teeth (OR = 2.35), and lower odds of receiving oral care (OR = 0.60) compared to their food secure peers.Conclusions: Though individuals experiencing food insecurity were likely to have more unmet oral health needs than their peers, they were less likely to seek dental care. To improve the oral health status of this group, in addition to making oral health care more accessible, it may also be necessary to address the social and environmental factors preventing these people from seeking oral health care.

Alissa J. Roberts, Joshua Sellner, Erin Sullivan, Kelsey B. Eitel, Angela D. Liese, Elizabeth T. Jensen, Anwar T. Merchant, Lawrence M. Dolan, Santica Marc Alissa J. Roberts, Joshua Sellner, Erin Sullivan, Kelsey B. Eitel, Angela D. Liese, Elizabeth T. Jensen, Anwar T. Merchant, Lawrence M. Dolan, Santica Marc

Background: Cognitive impairment has multiple risk factors spanning several domains, but few studies have evaluated risk factor clusters. We aimed to identify naturally occurring clusters of risk factors of poor cognition among middle-aged and older adults and evaluate associations between measures of cognition and these risk factor clusters. Methods: We used data from the National Health and Nutrition Examination Survey (NHANES) III (training dataset, n = 4074) and the NHANES 2011–2014 (validation dataset, n = 2510). Risk factors were selected based on the literature. We used both traditional logistic models and support vector machine methods to construct a composite score of risk factor clusters. We evaluated associations between the risk score and cognitive performance using the logistic model by estimating odds ratios (OR) and 95% confidence intervals (CI). Results: Using the training dataset, we developed a composite risk score that predicted undiagnosed cognitive decline based on ten selected predictive risk factors including age, waist circumference, healthy eating index, race, education, income, physical activity, diabetes, hypercholesterolemia, and annual visit to dentist. The risk score was significantly associated with poor cognitive performance both in the training dataset (OR _{Tertile 3 verse tertile 1} = 8.15, 95% CI: 5.36–12.4) and validation dataset (OR _{Tertile 3 verse tertile 1} = 4.31, 95% CI: 2.62–7.08). The area under the receiver operating characteristics curve for the predictive model was 0.74 and 0.77 for crude model and model adjusted for age, sex, and race. Conclusion: The model based on selected risk factors may be used to identify high risk individuals with cognitive impairment.

Background: Physical activity (PA) is essential for optimal diabetes management. Household food insecurity (HFI) may negatively affect diabetes management behaviors. The purpose of this study was to cross-sectionally examine the association between HFI and PA in youth and young adults (YYA) with type 1 (N = 1998) and type 2 (N = 391) diabetes from the SEARCH for Diabetes in Youth Study. Methods: HFI was measured with the US Household Food Security Survey Module. PA was measured with the International Physical Activity Questionnaire Short Form. Walking, moderate-intensity PA (excluding walking), vigorous-intensity PA, moderate- to vigorous-intensity PA, and total PA were estimated as minutes per week, while time spent sitting was assessed in minutes per day. All were modeled with median regression. Meeting PA guidelines or not was modeled using logistic regression. Results: YYA with type 1 diabetes who experienced HFI spent more time walking than those who were food secure. YYA with type 2 diabetes who experienced HFI spent more time sitting than those who were food secure. Conclusions: Future research should examine walking for leisure versus other domains of walking in relation to HFI and use objective PA measures to corroborate associations between HFI and PA in YYA with diabetes.