Jennifer A. Nasser

Background: Calcium (Ca) and magnesium (Mg) are essential micronutrients integral to metabolic processes and cardiovascular health. Emerging evidence suggests that the dietary Ca:Mg ratio may influence chronic disease risk, yet variability in this ratio across diverse demographic groups and its relationship to body composition and vitamin D status remain unclear. Methods: Dietary intakes of Ca and Mg were assessed using validated Food Frequency Questionnaires (FFQs) and body composition was quantified via Dual-energy X-ray Absorptiometry (DXA) scans. Relationships between dietary Ca:Mg ratios and demographics, body composition parameters (lean and fat mass), and vitamin D and parathyroid hormone (PTH) levels were examined statistically using SPSS ver. 29.0 and R ver. 4.5.1 (2025) employing Kruskal–Wallis, regression, and moderated mediation analyses. Results: We examined 155 healthy adults with a mean age of 36.6 ± 12.5 years. Only 16.8% had adequate intakes of Mg compared with 45.8% who had adequate dietary Ca intakes. Significant differences in the Ca:Mg ratio were observed across racial groups (p = 0.023) and age groups (p = 0.017). South Asian Indians exhibited the highest median Ca:Mg ratio (4.83), whereas African Americans exhibited the lowest (2.67). Interestingly, our moderated mediation analysis indicated that African Americans were the most sensitive to the impact of PTH changes on the balance of Ca:Mg (indirect effect = −0.762, 95% CI [−1.298, −0.234]), indicating that even slight shifts in their Ca:Mg balances cause significant elevation in the PTH, which, in turn, leads to lowering of their vitamin D levels. Young adults (ages 18–29) had the highest median Ca:Mg ratio (4.73). No statistically significant differences were detected based on Gender (p = 0.425 and BMI (p = 0.744) on Ca:Mg ratios. Additionally, dietary Ca:Mg ratios were positively associated with sPTH in males (r = 0.203, p < 0.05), but not with body composition. Conclusion: Important variations in dietary Ca:Mg ratios exist across racial and age demographics, notably among young adults, and specific ethnic groups exhibited elevated ratios. Tailored nutritional interventions may be necessary for these populations to optimize Ca:Mg balance and support metabolic and cardiovascular health outcomes in these populations.

Interacting with nature may promote mental and physical health. There are multiple ways to interact with nature: indirectly, incidentally, and intentionally. How these types of interactions with nature may be associated with mental and physical health status and health behaviors is unclear. The purpose of this narrative review is to (1) describe the relationship between interactions with nature (indirect, incidental, and intentional) and mental and physical health outcomes and behaviors, (2) identify gaps in the literature, and (3) provide recommendations for future research. Considerable evidence suggests that interacting with nature, indirectly and intentionally, is associated with improvements in mental health and physical exhibitions of mental status. Furthermore, intentionally interacting with nature is associated with engagement in physical activity and gardening is associated with fruit and vegetable consumption. Research suggests that incidentally interacting with nature may be associated with positive mental health status. More research is needed to understand the relationships between incidental interactions with nature and physical health status and behaviors; as well as among all types of interactions with nature and physical health disorders, sleep, and dietary behaviors.

“Loss of control, LOC” eating is a major contributor to the development of obesity. Dietary protein is known to promote satiety, but little attention has been paid to the ability of protein, consumed in close proximity to snacking (20 min), to reduce the intake of ultra-processed, low-protein snack foods. We hypothesized that a high-protein preload (HP, 8 g of protein) consumed in close proximity to eating an ultra-processed snack food would reduce intake of the snack food as compared to a low-protein preload (LP, 1.2 g of protein). Two laboratory test meals were conducted, and the intake of ice cream (1.99 kcal/gram) after consuming dairy-based liquid preloads was measured. Habitual physical activity, a potential modulator of satiety, was assessed by a self-reporting questionnaire. Thirty (responders) out of 50 participants reduced their intake of ice cream after the HP preload, with a significant difference in intake observed between the responders and non-responders (−30 ± 25 and 18 ± 18 g, F (1, 49) = 54.36, p < 0.001 for responders and non-responders, respectively). Our data demonstrate that protein consumed in close proximity to ultra-processed snack food can reduce caloric intake by ~60 kcal, which could potentially reduce body weight by at least 5 pounds per year.

Optimal cognitive functions are necessary for activities of daily living and self-independence. Cognitive abilities are acquired during early childhood as part of progressive neurodevelopmental milestones; unfortunately, regressive changes can occur as part of physiological aging, or more ominously, pathological diseases, such as Alzheimer’s disease (AD). Cases of AD and its milder subset, mild cognitive impairment (MCI), are rising and would impose a burdensome impact beyond the individual level. Various dietary and nutritional approaches have potential for promising results in managing cognitive deterioration. Glucose is the core source of bioenergy in the body; however, glucose brain metabolism could be affected in aging cells or due to disease development. Ketone bodies are an efficient alternate fuel source that could compensate for the deficient glycolytic metabolism upon their supra-physiologic availability in the blood (ketosis), which, in turn, could promote cognitive benefits and tackle disease progression. In this review, we describe the potential of ketogenic approaches to produce cognitive benefits in healthy individuals, as well as those with MCI and AD. Neurophysiological changes of the cognitive brain in response to ketosis through neuroimaging modalities are also described in this review to provide insight into the ketogenic effect on the brain outside the framework of purely molecular explanations.

Chocolate elicits unique brain activity compared to other foods, activating similar brain regions and neurobiological substrates with potentially similar psychoactive effects as substances of abuse. We sought to determine the relationship between chocolate with varying combinations of its main constituents (sugar, cocoa, and fat) and its psychoactive effects. Participants consumed 5 g of a commercially available chocolate with increasing amounts of sugar (90% cocoa, 85% cocoa, 70% cocoa, and milk chocolates). After each chocolate sample, participants completed the Psychoactive Effects Questionnaire (PEQ). The PEQ consists of questions taken from the Morphine-Benzedrine Group (MBG), Morphine (M,) and Excitement (E) subscales of the Addiction Research Center Inventory. After all testing procedures, participants completed the Binge Eating Scale (BES) while left alone and allowed to eat as much as they wanted of each of the different chocolates. We found a measurable psychoactive dose–effect relationship with each incremental increase in the chocolate’s sugar content. The total number of positive responses and the number of positive responses on the E subscale began increasing after tasting the 90% cocoa chocolate, whereas the number of positive responses on the MBG and M subscales began increasing after tasting the 85% cocoa chocolate sample. We did not find a correlation between BES scores and the total amount of chocolate consumed or self-reported scores on the PEQ. These results suggest that each incremental increase in chocolate’s sugar content enhances its psychoactive effects. These results extend our understanding of chocolate’s appeal and unique ability to prompt an addictive-like eating response.

Introduction: Given the current obesity epidemic, the question of why some individuals are able to control their food intake and others are not is very timely. fMRI imaging studies suggest that individuals who are obese have less post-ingestive activity in the lateral prefrontal cortex (lPFC) compared to individuals who are lean. This promotes greater eating frequency with no reduction in amount eaten per episode. Of all the macronutrients, protein is known to have a stronger effect on satiation (ending of the eating episode) and satiety (period between eating episodes). Using fNIRS we ask the question “what is the relationship of PFC activation during eating to amount of food eaten after consuming low (2 gram) or high (28 gram) protein reloads?” Background: In a study of eating preferred versus non-preferred food, we assessed PFC activation (by fNIRS) during eating after a 2-3 hour fast, and found that the relative magnitude of medial prefrontal cortex activity (mPFC) versus lPFC activity during eating (mPFC > lPFC) is associated with greater food intake. This raises the second question of whether the PFC activity is in response to food eaten, or amount of food eaten is in response to differences in regional PFC activation. We hypothesize the later. Approach/Methods: We examined the data obtained from a fNIRS study of the effect of protein preload on PFC activation during consumption of ice cream to see whether PFC activation influences food intake, or food intake influences brain activation. Briefly, the protein preload study involved twenty-nine healthy individuals (15 men, 14 women) participating in two sessions separated by at least two days. Women were only tested in the luteal phase of the menstrual cycle as this is a time of greater food craving and we anticipated having greater sensitivity to detect an effect during this cycle phase. During the test session, participants consumed a 120kcal liquid dairy based preload of bovine milk protein with chocolate flavoring, delivered as 8 ounces of liquid within five minutes. (Order of preload consumption was randomized.) After consuming the preload, participants rested for fifteen minutes and then were fitted with the fNIRS sensory band and a two minute baseline was recorded. Participants were then allowed to consume ice cream ad libitum for ten minutes with continuous fNIRS recording. Participants completed the Three Factor Eating Questionnaire to determine cognitive restraint tendency at the end of the second test session. Data Analysis: We separately compared the time to peak activity for both mPFC and lPFC versus the total eating time in individuals for both the LP and HP preload conditions using Repeated Measures ANOVA. Additionally, we examined the effects of cognitive restraint (CR), BMI and sex on time to peak m and lPFC activation, and total eating time using regression analysis. Food was weighed before and after the test session to determine amount consumed. Results Tables attached as supplemental material Discussion/Future work The demographic data reveals 1) that food intake correlated with BMI under both preload conditions (LP preload: r = 0.609, p <.01; HP preload: r = 0.521, p = 0.004), 2) that the difference in food intake between men and women after LP preload approached significance and was significant after the HP preload, and 3) that the difference in food intake between preloads approached significance when controlled for cognitive restraint). Additionally, our data demonstrates that under both preload conditions, time to peak activity for both mPFC and lPFC were significantly less than total eating time suggesting that amount of food eaten is in response to prior PFC activation. This result agrees with our hypothesis. There was no effect of sex or CR seen on time for peak activity for mPFC or lPFC under either preload. Interestingly, BMI was shown to modulate the time to peak activity for mPFC versus total eating time under both preloads, with the ratio of mPFC/total eating time decreasing as BMI increased. Future work will examine the effect of different types of protein and other macronutrients to affect PFC activation, and subsequent food intake.

Objective: The activity of dopamine‐dependent retinal signaling can be assessed using electroretinography. Response of this system to oral food stimulation might provide accessible insight into the brain dopamine response to oral stimuli as retinal dopamine concentration is dependent upon mid brain dopamine concentration was postulated.Design and Methods: Nine individuals had cone ERG (b wave) response to oral food stimulation and oral methylphenidate (MPH) administration measured on separate days, and completed self reported eating behavior questionnaires.Results: Significant and similar increases in b wave response to both stimuli (P = 0.012 and P = 0.042, MPH and food, respectively) and significant correlations of the food stimulated b wave amplitude with binge eating related behavior as measured by the Gormally Binge Eating Scale (r = 0.68, P = 0.044) and self‐reported trait hunger as measured by the Stunkard and Messick Three Factor Eating Questionnaire (r = 0.67, P = 0.048) were found.Conclusion: The significant increase in food stimulated dopamine dependent b wave amplitude and correlation with methylphenidate stimulated b wave amplitude suggest that ERG may offer a relatively inexpensive and accessible methodology for potentially assess dopaminergic responses to food and other externally applied stimuli that have been implicated in the pathogenesis of a number of human diseases.