Family Systems Cultural and Resilience Dimensions to Consider in Nutrition Interventions: Exploring Preschoolers' Eating and Physical Activity Routines During COVID-19.

OBJECTIVE: To describe the weight-related family functioning of racial minority families with low income using family systems theory as an interpretive framework. DESIGN: Primarily a qualitative study with interviews plus; descriptive demographics, anthropometrics, a family functioning measure, and food insecurity screening. SETTING: Telephone interviews with families of preschool-aged children in an urban setting. PARTICIPANTS: Primary caregivers of preschool-aged children. PHENOMENON OF INTEREST: Cultural impacts on family systems. ANALYSIS: Interviews were audio-recorded, transcribed verbatim, and loaded into NVivo 12 for thematic analysis. Descriptive statistics. RESULTS: The 23 participants were mothers and 2 maternal grandmothers. Seventy-four percent were African American, most children were normal weight (n = 15, 65%), mean family function scores were high, and more than half the families were at risk for food insecurity (n = 13, 56%). Acculturation and intergenerational eating-related cultural dimensions were discerned as the overarching themes influencing family cohesion. Family cohesion appeared to have helped the families adapt to the impact of coronavirus disease 2019. CONCLUSIONS AND IMPLICATIONS: Cultural dimensions such as acculturation and intergenerational influences appeared to be associated with social cohesion and family functioning around weight-related behaviors for these families. These findings add cultural and family resilience dimensions to family systems theory in nutrition interventions.

Energy requirements for critically ill patients with COVID-19.

Early reports suggested that predictive equations significantly underestimate the energy requirements of critically ill patients with coronavirus disease 2019 (COVID-19) based on the results of indirect calorimetry (IC) measurements. IC is the gold standard for measuring energy expenditure in critically ill patients. However, IC is not available in many institutions. If predictive equations significantly underestimate energy requirements in severe COVID-19, this increases the risk of underfeeding and malnutrition, which is associated with poorer clinical outcomes. As such, the purpose of this narrative review is to summarize and synthesize evidence comparing measured resting energy expenditure via IC with predicted resting energy expenditure determined via commonly used predictive equations in adult critically ill patients with COVID-19. Five articles met the inclusion criteria for this review. Their results suggest that many critically ill patients with COVID-19 are in a hypermetabolic state, which is underestimated by commonly used predictive equations in the intensive care unit (ICU) setting. In nonobese patients, energy expenditure appears to progressively increase over the course of ICU admission, peaking at week 3. The metabolic response pattern in patients with obesity is unclear because of conflicting findings. Based on limited evidence published thus far, the most accurate predictive equations appear to be the Penn State equations; however, they still had poor individual accuracy overall, which increases the risk of underfeeding or overfeeding and, as such, renders the equations an unsuitable alternative to IC.