Malnutrition and Neurodegenerative Diseases

A critical view of the use of predictive energy equations for the identification of hypermetabolism in motor neuron disease: A pilot study

BACKGROUND AND AIMS

People living with motor neuron disease (MND) frequently struggle to consume an optimal caloric intake. Often compounded by hypermetabolism, this can lead to dysregulated energy homeostasis, prompting the onset of malnutrition and associated weight loss. This is associated with a poorer prognosis and reduced survival. It is therefore important to establish appropriate nutritional goals to ensure adequate energy intake. This is best done by measuring resting energy expenditure (mREE) using indirect calorimetry. However, indirect calorimetry is not widely available in clinical practice, thus dietitians caring for people living with MND frequently use energy equations to predict resting energy expenditure (pREE) and estimate caloric requirements. Energy prediction equations have previously been shown to underestimate resting energy expenditure in over two-thirds of people living with MND. Hypermetabolism has previously been identified using the metabolic index. The metabolic index is a ratio of mREE to pREE, whereby an increase of mREE by ≥110% indicates hypermetabolism. We aim to critically reflect on the use of the Harris-Benedict (1919) and Henry (2005) energy prediction equations to inform a metabolic index to indicate hypermetabolism in people living with MND.

METHODS

mREE was derived using VO₂ and VCO₂ measurements from a GEMNutrition indirect calorimeter. pREE was estimated by Harris-Benedict (HB) (1919), Henry (2005) and kcal/kg/day predictive energy equations. The REE variation, described as the percentage difference between mREE and pREE, determined the accuracy of pREE ([pREE-mREE]/mREE) x 100), with accuracy defined as ≤ ± 10%. A metabolic index threshold of ≥110% was used to classify hypermetabolism. All resting energy expenditure data are presented as kcal/24hr.

RESULTS

Sixteen people living with MND were included in the analysis. The mean mREE was 1642 kcal/24hr ranging between 1110 and 2015 kcal/24hr. When REE variation was analysed for the entire cohort, the HB, Henry and kcal/kg/day equations all overestimated REE, but remained within the accuracy threshold (mean values were 2.81% for HB, 4.51% for Henry and 8.00% for kcal/kg/day). Conversely, inter-individual REE variation within the cohort revealed HB and Henry equations both inaccurately reflected mREE for 68.7% of participants, with kcal/kg/day inaccurately reflecting 41.7% of participants. Whilst the overall cohort was not classified as hypermetabolic (mean values were 101.04% for HB, 98.62% for Henry and 95.64% for kcal/kg/day), the metabolic index ranges within the cohort were 70.75%-141.58% for HB, 72.82%-127.69% for Henry and 66.09%-131.58% for kcal/kg/day, indicating both over- and under-estimation of REE by these equations. We have shown that pREE correlates with body weight (kg), whereby the lighter the individual, the greater the underprediction of REE. When applied to the metabolic index, this underprediction biases towards the classification of hypermetabolism in lighter individuals.

CONCLUSION

Whilst predicting resting energy expenditure using the HB, Henry or kcal/kg/day equations accurately reflects derived mREE at group level, these equations are not suitable for informing resting energy expenditure and classification of hypermetabolism when applied to individuals in clinical practice.

Calorie restriction or dietary restriction: how far they can protect the brain against neurodegenerative diseases?

Finding the correct nutritional intervention is one of the biggest challenges in treating patients with neurodegenerative diseases. In general, these patients develop strong metabolic alterations, resulting in lower treatment efficacy and higher mortality rates. However, there are still many open questions regarding the effectiveness of dietary interventions in neurodiseases. Some studies have shown that a reduction in calorie intake activates key pathways that might be important for preventing or slowing down the progression of such diseases. However, it is still unclear whether these neuroprotective effects are associated with an overall reduction in calories (hypocaloric diet) or a specific nutrient restriction (diet restriction). Therefore, here we discuss how commonly or differently hypocaloric and restricted diets modulate signaling pathways and how these changes can protect the brain against neurodegenerative diseases.

Racial Disparities in Nutritional Risk among Community-Dwelling Older Adults in Adult Day Health Care

Information regarding nutritional risk among users of American adult day health centers (ADHCs), 60% of whom are racial minorities, is scant. This study examined nutritional risk and associated factors in a diverse sample ADHC users aged 50+ using secondary cross-sectional analysis of data collected between 2013 and 2017. Risk was assessed using the DETERMINE checklist, and results were stratified by race. The majority of the sample (N = 188) was at moderate (45.2%) or high (38.5%) nutritional risk, with statistically significant racial differences. Blacks were at greater risk than any other group: 65% had high nutritional risk; 76.5% ate <5 servings of fruits, vegetables, or milk daily; 21% ate <2 meals daily, 48.5% reported involuntary weight loss/gain, and 41.2% had tooth loss/mouth pain. Older adults in ADHCs are at elevated risk of malnutrition, disproportionately so amongst blacks. Both routine nutrition screening and population-specific approaches are needed to attenuate risk.