A cross-sectional analysis of dietary protein intake and body composition among Chinese Americans

Macronutrient Intake, Sleep Quality, Anxiety, Adherence to a Mediterranean Diet and Emotional Eating among Female Health Science Undergraduate Students

INTRODUCTION

COVID-19 provoked a myriad of challenges for people's health, poor life satisfaction and an unhealthy diet that could be associated with serious negative health outcomes and behaviours. University is a stressful environment that is associated with unhealthy changes in the eating behaviours of students. The association between diet and mental health is complex and bidirectional, depending on the motivation to eat; emotional eaters regulate their emotions through the increased consumption of comfort foods.

OBJECTIVE

The aim of this study was to compare the nutritional habits, alcohol consumption, anxiety and sleep quality of female health science college students.

MATERIAL AND METHODS

A cross-sectional study of 191 female undergraduate students in Madrid was used. Their body mass index and waist hip ratio were measured. The questionnaires used included the Mediterranean Diet Adherence test, AUDIT, Emotional Eater Questionnaire, Pittsburgh Sleep Quality Index, and Food Addiction, Perceived Stress Scale and STAI questionnaires.

RESULTS

We observed a high intake of protein, fat, saturated fatty acids and cholesterol. Overall, 9.5% never had breakfast, and 66.5% consciously reduced their food intake. According to Pittsburgh Sleep Quality Index, they mainly slept 6-7 h, and 82% presented with a poor sleep quality; 13.5% presented moderate-high food addiction, and 35% had moderate Mediterranean Diet Adherence score.

CONCLUSION

Female students' macronutrient imbalances were noted, with a high-level protein and fat intake diet and a low proportion of carbohydrates and fibre. A high proportion of them need alcohol education and, depending on the social context, they mainly drank beer and spirits.

Dietary amino acids and anthropometric indices: Tehran Lipid and Glucose Study

Objective

Recent studies investigated the role of amino acids (AAs) in weight management. We aimed to determine the association between AAs and three-year change of anthropometric indices and incident obesity.

Materials and methods

Height, weight, hip, and waist circumference (WC) were collected at baseline and follow up. Three-year changes in anthropometric indices and obesity incident according to body mass index (BMI) (overweight & obesity) and WC cutoffs (obesity-WC) were ascertained. Dietary intakes of AAs were collected at baseline, using a food frequency questionnaire. Data analyses were conducted on 4976 adult participants and two subsamples, including 1,570 and 2,918 subjects, for assessing the AAs relationship with 3-year changes on anthropometric indices and obesity incident.

Results

Lysine and aspartic acid were positively associated with higher weight change, whereas acidic AAs, cysteine, and glutamic acid showed a negative correlation with weight change. Furthermore, a weak positive correlation was shown for alkaline AAs, lysine, and valine with WC; however, acidic AAs, tryptophan, cysteine, and glutamic acid were negatively associated with WC. Aromatic and acidic AAs also demonstrated a weak negative relation with changes in BAI. Phenylalanine and Aromatic AAs showed a negative association with overweight &obesity incidence adjusting for potential confounders. Each quartile increases the dietary lysine, arginine, alanine, methionine, aspartic acid, and alkaline AAs related to a greater risk of obesity-WC, while tryptophan, glutamic acid, proline, and acidic AAs associated with lower obesity-WC risk.

Conclusion

Our results suggested that certain dietary AAs may potentially change anthropometric indices and risk of obesity incident.

Effects of a low-carbohydrate/high-protein diet on metabolic health in individuals with chronic spinal cord injury: An exploratory analysis of results from a randomized controlled trial

We explored the impact of a low-carbohydrate/high-protein diet (LC/HP, ~30% energy from protein, 40% energy from carbohydrate) on indices of metabolic function and body composition in individuals with chronic spinal cord injury (SCI). Adults with SCI (≥3 years post-injury, C4-L2, AIS A-D) and insulin resistance or pre-diabetes were randomly assigned to an 8-week iso-caloric LC/HP diet group (n = 11) or control group (n = 14). All LC/HP meals were delivered weekly to participants' homes, and participants in the control group consumed their habitual diet. Each participant underwent an oral glucose tolerance test (OGTT) to assess glucose tolerance, insulin, area under the curve (AUC) for glucose and insulin, Matsuda Index, glucose-stimulated insulin secretion (GSIS), disposition index, and hepatic insulin extraction (HIE). Fasting blood lipid and inflammation were assessed, and body composition was estimated using dual-energy x-ray absorptiometry. A linear mixed model was used to evaluate the main effect of diet, time, and their interaction. Compared to the control group, participants in the LC/HP group had reduced total body fat mass (LC/HP: -5.9%, Control: 0.7%), visceral fat mass (LC/HP: -16.2%, Control: 5.2%), total- (LC/HP: -20.1, Control: 3.7 mg/dl), and LDL-cholesterol (LC/HP: -13.9, Control: 3.1 mg/dl) (pdiet*time  < 0.05 for all). Regardless of group, AUCinsulin and peak insulin during the OGTT decreased, and HIE increased over time (ptime  < 0.05). A trend for diet*time interaction was observed for glucoseOGTT120min (LC/HP: -20.7, Control: 3.0 mg/dl, pdiet*time  = 0.09) and peak C-peptide (LC/HP: -2.1, Control: 0.0 ng/ml, pdiet*time  = 0.07). HDL-cholesterol, lean body mass, Matsuda Index, fasting glucose, insulin, insulinOGTT120min , AUCglucose , pancreatic beta cell function (GSIS, disposition index), and inflammation (C-reactive protein, IL-6, IL-8, IL-10, TNF-α) did not change over time. In conclusion, our results suggest that individuals with SCI and insulin resistance may adopt an LC/HP diet to improve body composition and lipid profiles. Its impact on glucose metabolism and inflammation remains inconclusive and warrants future investigations.

Nutrient Intake and Muscle Measures in Geriatric Outpatients

OBJECTIVE

Low muscle mass and muscle function are associated with adverse health outcomes in older adults. This study examined nutrient intake as a potential contributing factor for low muscle mass, muscle strength, and muscle power in geriatric outpatients.

METHOD

This cross-sectional study included geriatric outpatients (n = 58, 38 female) with a mean age of 77.2 ± 9.0 years referred to the Falls and Balance outpatient clinic between December 2017 and January 2019. Nutrient intake (macro- and micronutrients) was examined using a 3-day food diary. Energy-adjusted nutrient intake was calculated using the residual method. Sex-standardized muscle measures included muscle mass assessed using bioelectrical impedance analysis (skeletal muscle mass [SMM in kilograms], SMM index [SMM/height² in kg/m²], and SMM/body mass index), handgrip strength (muscle strength) assessed using a dynamometer, and chair-stand test (muscle power). Univariate linear regression analyses were used to examine the associations of nutrient intake with muscle measures adjusted for age and body weight. A Bonferroni correction was applied to account for multiple testing (p < 0.001).

RESULTS

Higher energy, iodine, and folate intake were associated with higher muscle mass, and higher folate intake was associated with higher muscle strength (p < 0.05). After Bonferroni correction, none of the nutrient intakes remained statistically significant. None of the other nutrients was associated with muscle measures.

CONCLUSIONS

Only a few nutrients were associated with muscle measures. Nutrient intake appears to be more related to muscle mass than muscle strength and muscle power in geriatric outpatients.

Protein Intake and Human Health: Implications of Units of Protein Intake

Understanding the health effects of protein intake is bedeviled by a number of factors, including protein quality and source. In addition, different units, including grams, grams per kilogram body weight (g/kg BW), and percent energy, may contribute to confusion about protein's effects on health, especially BW-based units in increasingly obese populations. We aimed to review the literature and to conduct a modeling demonstration of various units of protein intake in relation to markers of cardiometabolic health. Data from the Framingham Heart Study Offspring (n = 1847; 60.3 y; 62.5% women) and Third Generation (n = 2548; 46.2 y; 55.3% women) cohorts and the NHANES 2003-04 (n = 1625; 46.2 y; 49.7% women) and 2005-06 (n = 1347; 43.7 y; 49.5% women) cycles were used to model cross-sectional associations between 7 protein units (grams, percent energy, g/kg ideal BW, g/kg actual BW, BW-adjusted g/kg actual BW, g/kg lean BW, and g/kg fat-free BW) and 9 cardiometabolic outcomes (fasting glucose, systolic and diastolic blood pressure, total and HDL cholesterol, triglycerides, BMI, waist circumference, and estimated glomerular filtration rate). The literature review indicated the use of myriad units of protein intake, with differential results on cardiometabolic outcomes. The modeling demonstration showed units expressed in BW were confounded by BW, irrespective of outcome. Units expressed in grams, percent energy, and ideal BW showed similar results, with or without adjustment for body size. After adjusting for BW, results of units expressed in BW aligned with results of grams, percent energy, and ideal BW. In conclusion, protein intake in cardiometabolic health appears to depend on protein's unit of expression. Authors should be specific about the use of WHO (g/kg ideal BW) compared with US (g/kg actual BW) units, and ideally use gram or percent energy in observational studies. In populations where overweight/obesity are prevalent, intake based on actual BW should be reevaluated.

The Relationships between Total Protein Intake, Protein Sources, Physical Activity, and Lean Mass in a Representative Sample of the US Adults

Background: Although dietary protein and physical activity play essential roles in developing and preserving lean mass, studies exploring these relationships are inconsistent, and large-scale studies on sources of protein and lean mass are lacking. Accordingly, the present study examined the relationship between total protein intake, protein sources, physical activity, and lean mass in a representative sample of US adults. Methods: This cross-sectional study analyzed data from 2011–2016 US National Health and Nutrition Examination Survey and corresponding Food Patterns Equivalents Database (n = 7547). Multiple linear regression models were performed to examine the sex-specific associations between total protein intake, protein sources (Dairy, Total Protein Foods, Seafood, and Plant Proteins), physical activity, and lean mass adjusting for demographics, weight status, and total daily energy intake. Results: Total protein intake was inversely related to lean mass in females only (Lean mass index: β= −0.84, 95%CI: −1.06–−0.62; Appendicular lean mass index: β= −0.35, 95%CI: −0.48–−0.22). However, protein sources and physical activity was positively associated with lean mass in males and/or females (p < 0.05). Conclusion. Study results suggest that consuming more protein daily had a detrimental influence on lean mass in females whereas eating high-quality sources of proteins and being physically active are important for lean mass for men and women. However, the importance of specific protein sources appears to differ by sex and warrants further investigation.

Age and Racial/Ethnic Differences in Dietary Sources of Protein, NHANES, 2011-2016

Background: Dietary protein serves a pivotal role in providing the body with essential amino acids, which are required for the maintenance of body proteins, and the assimilation of structural and functional components required for basic survival. Understanding how dietary protein sources potentially vary for different population subgroups will allow for future nutrition interventions to be more targeted for specific needs.

Objective: The purpose of this analysis was to identify the top ten food category sources of dietary protein by age and race and ethnicity in a nationally representative sample.

Methods: Cross-sectional data on adults (18+ years) from the National Health and Nutrition Examination Survey (NHANES) 2011–2016 with one 24-h dietary recall were analyzed (n = 15,697). Population proportions were calculated based on protein intake (g/day) for What We Eat In America food categories.

Results: The analytic sample (n = 15,697) was 15.0% Hispanic (95% CI [12.1, 17.9], 65.0% non-Hispanic White (95% CI [60.8, 69.3]), 11.5% non-Hispanic Black (95% CI [9.1, 13.9]), 5.4% non-Hispanic Asian (95% CI [4.3, 6.6]), and 3.1% other (95% CI [2.5, 3.6]). In all racial and ethnic groups, as well as age categories, chicken (whole pieces) was the top-ranked source of dietary protein. In addition to chicken (whole pieces), beef (excludes ground), eggs and omelets, and meat mixed dishes food categories ranked in the top ten sources of protein for every race/ethnicity. Only two solely plant-based proteins appeared in the top ten sources: beans, peas and legumes for Hispanics, and nuts and seeds for Other. For all age categories, beef (excludes ground) was among the top five sources and egg/omelets appear in the top ten sources.

Conclusion: The top ten sources of protein accounted for over 40% of dietary protein irrespective of race/ethnicity or age category, having major implications for the sustainability of our nation's food supply. Public health strategies that encourage diversity in protein sources in food preparation and incorporate legumes and nuts along with poultry have the potential to shift the overall population protein intake distribution toward improving overall diet quality.