scholarly journals The Association of Gut Microbiota with Resting Metabolic Rate in Overweight/Obese Women: A Case-Control Study

2021 ◽  
Author(s):  
Sanaz Mehranfar ◽  
Seyed Davar Siadat ◽  
Sara Ahmadi Badi ◽  
Sara Hajishizari ◽  
Mir Saeed Yekaninejad ◽  
...  
Keyword(s):  
Energy Expenditure ◽  
Metabolic Rate ◽  
Resting Metabolic Rate ◽  
Positive Association ◽  
Gut Microflora ◽  
Obese Women ◽  
Significant Positive Association ◽  
Genetic And Environmental Factors ◽  
Future Work ◽  
The Impact

Abstract Purpose Low Resting Metabolic Rate (RMR), as a risk factor for obesity, can be affected by many factors. Indeed, genetic and environmental factors are variables taken into account when predicting RMR, and may contribute to a high inter-individual variance. Besides the well-known causes of obesity, researchers have demonstrated the contribution of gut microflora in obesity and energy expenditure. Therefore, the goal of the current study was to compare the Firmicutes/Bacteroidetes ratio and the relative abundance of, Prevotellaceae, Faecalibacterium prausnitzii, bifidobactrium spp, lactobacillus spp, Akkermansia muciniphila, Bacteroides fragilis, and Escherichia coli in two groups of people with normal and low RMR in overweigh/obese women in Iran. Results The abundance of F. prausnitzii (p>0.001), B. fragilis (P= 0.02), and Firmicutes phylum (P= 0.02) were significantly higher in the controls compared to the cases, and showed significant positive association with RMR, (β = 1.29 ×10−5, P=0.01), (β = 4.13 ×10−6, p= 0.04), and (β = 7.76 ×10−1, p= 0.01), respectively. Regarding Lactobacilus, the results showed a significant positive association with RMR (β = 1.73 ×10−4, p= 0.01). Conclusion Intestinal microbiota may be associated with host metabolism. Therefore, future work should investigate, using clinical trials, the impact of manipulating gut microflora to positively influence energy expenditure.

scholarly journals Alcohol and its acute effects on resting metabolic rate and diet-induced thermogenesis

1990 ◽  
Vol 64 (2) ◽  
pp. 413-425 ◽  
Author(s):  
Jan A. Weststrate ◽  
Ingrid Wunnink ◽  
Paul Deurenberg ◽  
Joseph G. A. J. Hautvast
Keyword(s):  
Energy Expenditure ◽  
Metabolic Rate ◽  
Resting Metabolic Rate ◽  
Resting Energy Expenditure ◽  
Random Order ◽  
Systematic Difference ◽  
Control Treatment ◽  
Diet Induced Thermogenesis ◽  
The Impact ◽  
Thermic Effect

The impact of alcohol (ethanol) on resting energy expenditure of male non-obese volunteers was determined in two studies. In the first study the thermic effect of alcohol on resting metabolic rate (RMR) was assessed in ten male non-obese volunteers. In the second study the impact of alcohol on diet-induced thermogenesis (DIT) was determined in twelve male non-obese volunteers. Energy expenditure was measured with a ventilated-hood system. RMR was measured for 60 min with the subjects in a fasting state. In the first study subjects received in random order 20 g alcohol in concentrations of 75, 180 and 300 ml/I water respectively. After measurement of the RMR the thermic effect of alcohol was measured for 90 min. In the second study volunteers received in random order and in duplicate either a meal of food (2 MJ) plus an alcoholic aperitif (20 g alcohol in a 180 ml/1 solution) or an isoenergetic meal of food alone (2.55 MJ) plus a placebo aperitif containing no alcohol. DIT was measured for 240 min. Alcohol induced a significant thermic effect, which varied between 0.22 and 0.30 kJ/min. No systematic difference in DIT was observed among the different concentrations. DIT was not significantly affected by the ingestion of alcohol. Total DIT was 219 (SE 14) kJ for the alcohol treatment and 185 (SE 20) kJ for the control treatment. The results do not support the suggestion that alcohol is less efficiently used as an energy source in comparison with, for example, fats and carbohydrates.

Nutrient pattern of unsaturated fatty acids and vitamin E increase resting metabolic rate of overweight and obese women

2020 ◽  
pp. 1-9
Author(s):  
Habib Yarizadeh ◽  
Leila Setayesh ◽  
Caroline Roberts ◽  
Mir Saeed Yekaninejad ◽  
Khadijeh Mirzaei
Keyword(s):  
Vitamin E ◽  
Metabolic Rate ◽  
Unsaturated Fatty Acids ◽  
Resting Metabolic Rate ◽  
Blood Parameters ◽  
Cross Sectional Study ◽  
Obese Women ◽  
Cross Sectional ◽  
Dietary Nutrients ◽  
Nutrient Patterns

Abstract. Objectives: Obesity plays an important role in the development of chronic diseases including cardiovascular disease and diabetes. A low resting metabolic rate (RMR) for a given body size and composition is a risk factor for obesity, however, there is limited evidence available regarding the association of nutrient patterns and RMR. The aim of this study was to determine the association of nutrient patterns and RMR in overweight and obese women. Study design: This cross-sectional study was conducted on 360 women who were overweight or obese. Method: Dietary intake was assessed using a semi-quantitative standard food frequency questionnaire (FFQ). Nutrient patterns were also extracted by principal components analysis (PCA). All participants were evaluated for their body composition, RMR, and blood parameters. Result: Three nutrient patterns explaining 64% of the variance in dietary nutrients consumption were identified as B-complex-mineral, antioxidant, and unsaturated fatty acid and vitamin E (USFA-vit E) respectively. Participants were categorized into two groups based on the nutrient patterns. High scores of USFA-vit E pattern was significantly associated with the increase of RMR (β = 0.13, 95% CI = 0.79 to 68.16, p = 0.04). No significant associations were found among B-complex-mineral pattern (β = −0.00, 95% CI = −49.67 to 46.03, p = 0.94) and antioxidant pattern (β = 0.03, 95% CI −41.42 to 22.59, p = 0.56) with RMR. Conclusion: Our results suggested that the “USFA-vit E” pattern (such as PUFA, oleic, linoleic, vit.E, α-tocopherol and EPA) was associated with increased RMR.

Determination of total energy expenditure, resting metabolic rate and physical activity in lean and overweight people

1997 ◽  
Vol 36 (4) ◽  
pp. 310-312 ◽  
Author(s):  
F. Thielecke ◽  
J. Möseneder ◽  
A. Kroke ◽  
K. Klipstein-Grobusch ◽  
H. Boeing ◽  
...  
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Metabolic Rate ◽  
Total Energy ◽  
Resting Metabolic Rate ◽  
Total Energy Expenditure ◽  
Overweight People

Energy Expenditure of Level Overground Walking in Young Adults: Comparison With Prediction Equations

2021 ◽  
pp. 1-8
Author(s):  
Jingjing Xue ◽  
Shuo Li ◽  
Rou Wen ◽  
Ping Hong
Keyword(s):  
Young Adults ◽  
Energy Expenditure ◽  
Metabolic Rate ◽  
Energy Cost ◽  
Sports Medicine ◽  
Resting Metabolic Rate ◽  
Prediction Equations ◽  
Overground Walking ◽  
All Speeds ◽  
Walking Energy Cost

Background: The purpose of this study was to investigate the accuracy of the published prediction equations for determining level overground walking energy cost in young adults. Methods: In total, 148 healthy young adults volunteered to participate in this study. Resting metabolic rate and energy expenditure variables at speeds of 4, 5, and 6 km/h were measured by indirect calorimetry, walking energy expenditure was estimated by 3 published equations. Results: The gross and net metabolic rate per mile of level overground walking increased with increased speed (all P < .01). Females were less economical than males. The present findings revealed that the American College of Sports Medicine and Pandolf et al equations significantly underestimated the energy cost of overground walking at all speeds (all P < .01) in young adults. The percentage mean bias for American College of Sports Medicine, Pandolf et al, and Weyand et al was 12.4%, 16.8%, 1.4% (4 km/h); 21.6%, 15.8%, 7.1% (5 km/h); and 27.6%, 12%, 6.6% (6 km/h). Bland–Altman plots and prediction error analysis showed that the Weyand et al was the most accurate in 3 existing equations. Conclusions: The Weyand et al equation appears to be the most suitable for the prediction of overground walking energy expenditure in young adults.

scholarly journals Motivating Information Technology Professionals: The case of New Zealand

2017 ◽  
Vol 21 ◽  
Author(s):  
Shoaib Ahmed ◽  
Nazim Taskin ◽  
David J. Pauleen ◽  
Jane Parker
Keyword(s):  
Job Satisfaction ◽  
New Zealand ◽  
Turnover Intention ◽  
Professional Growth ◽  
Critical Role ◽  
Positive Association ◽  
It Professionals ◽  
Online Questionnaire ◽  
Significant Positive Association ◽  
The Impact

IT professionals play a critical role in organizations. Research indicates that they may be unique in their attitudes toward motivation and job satisfaction. In New Zealand, a shortage of skilled professionals may contribute to or impact on motivation. Using a modified model of Herzberg’s two-factor theory by Smerek and Peterson (2007), this research seeks to answer the question: what motivates New Zealand IT professionals? In response, an online questionnaire was distributed to a population of New Zealand IT professionals and the data analysed using Partial Least Squares to understand the relationship between the various dimensions of job satisfaction, the impact of personal and job characteristics, and turnover intention. The findings show that the New Zealand IT professional is primarily motivated by the nature of his or her work, followed by perceptions of responsibility, and how supervisors encourage an environment for such. Satisfaction with salary is a predictor to a lesser degree. Perhaps somewhat surprisingly, professional growth opportunities, career advancement, and recognition do not have a statistically-significant positive association with motivation. We conclude that, to motivate their IT workforce, organizations should: 1) focus on the nature of the jobs that IT professionals undertake; 2) train supervisors to provide an empowering environment; 3) offer competitive salaries to retain top talent; 4) not hesitate to employ IT professionals born outside New Zealand; and 5) take account of the singularities of the New Zealand labour market in seeking to attract, recruit and retain IT professionals. Implications for policy, practice and theory are discussed.

The impact of short-term depot-medroxyprogesterone acetate treatment on resting metabolic rate

Contraception ◽  
2016 ◽  
Vol 93 (4) ◽  
pp. 317-322 ◽  
Author(s):  
Ryan G. Steward ◽  
Lori A. Bateman ◽  
Cris Slentz ◽  
Frank Z. Stanczyk ◽  
Thomas M. Price
Keyword(s):  
Metabolic Rate ◽  
Medroxyprogesterone Acetate ◽  
Resting Metabolic Rate ◽  
Short Term ◽  
Depot Medroxyprogesterone Acetate ◽  
The Impact

Ethnic differences in sympathetic nervous system-mediated energy expenditure

1991 ◽  
Vol 261 (6) ◽  
pp. E789-E794 ◽  
Author(s):  
M. F. Saad ◽  
S. A. Alger ◽  
F. Zurlo ◽  
J. B. Young ◽  
C. Bogardus ◽  
...  
Keyword(s):  
Nervous System ◽  
Energy Expenditure ◽  
Sympathetic Nervous System ◽  
Fat Mass ◽  
Weight Maintenance ◽  
Resting Metabolic Rate ◽  
Fat Free Mass ◽  
Beta Adrenoceptor ◽  
Sympathetic Nervous ◽  
The Impact

The impact of sympathetic nervous system (SNS) activity on energy expenditure (EE) was evaluated in nondiabetic Caucasian and Pima Indian men while on a weight-maintenance diet using two approaches as follows. 1) The relationship between 24-h EE, measured in a respiratory chamber, and 24-h urinary norepinephrine was studied in 36 Caucasians [32 +/- 8 (SD) yr, 95 +/- 41 kg, 22 +/- 13% fat] and 33 Pimas (29 +/- 6 yr, 103 +/- 28 kg, 30 +/- 9% fat). There was no difference between the two groups in 24-h EE (2,422 vs. 2,523 kcal/24 h) and in urinary norepinephrine (28 vs. 31 micrograms/24 h), even after adjusting for body size and composition. Twenty-four-hour EE correlated significantly with 24-h urinary norepinephrine in Caucasians (r = 0.78, P less than 0.001) but not in Pimas (r = 0.03), independent of fat-free mass (FFM), fat mass, and age. 2) The effect of beta-adrenoceptor blockade with propranolol (120 micrograms/kg FFM bolus and 1.2 micrograms.kg FFM-1.min-1 for 45 min) on the resting metabolic rate (RMR) was evaluated in 36 Caucasians (30 +/- 6 yr, 103 +/- 36 kg, 25 +/- 11% fat) and 32 Pimas (28 +/- 6 yr, 100 +/- 34 kg, 27 +/- 10% fat). The RMR was similar in the two groups (2,052 vs. 1,973 kcal/24 h) even after adjustment for FFM, fat mass, and age and dropped significantly after propranolol infusion in Caucasians (-3.9%, P less than 0.001) but not in Pimas (-0.8%, P = 0.07).(ABSTRACT TRUNCATED AT 250 WORDS)

scholarly journals Adherence to a Low Carbohydrate Diet may Modify Resting Metabolic Rate among Overweight and Obese Women

2020 ◽  
Author(s):  
Seyedeh Forough Sajjadi ◽  
Atieh Mirzababaei ◽  
nasim Ghodoosi ◽  
Sara Pooyan ◽  
Hana Arghavani ◽  
...  
Keyword(s):  
Metabolic Rate ◽  
Resting Metabolic Rate ◽  
Fat Free Mass ◽  
Obese Women ◽  
Carbohydrate Diet ◽  
Cross Sectional ◽  
Low Carbohydrate Diet ◽  
Low Carbohydrate ◽  
Carb Diet ◽  
Adjusted Model

Abstract Objective Resting metabolic rate (RMR) accounts for most of the daily energy expenditure. The low-carb diet attenuates decreases in RMR. This study aims to investigate the relationship between a low-carb diet and resting metabolic rate status. Methods We enrolled 304 overweight and obese women in this cross-sectional study. BMI, fat mass, fat-free mass, visceral fat, insulin level were assessed. RMR was measured using indirect calorimetry. A low carbohydrate diet score was measured using a validated semi-quantitative food frequency questionnaire (FFQ). Results Our results showed no relationship between LCDS and DNR even after adjust for confounders (Inc. RMR: OR: 0.97; 95% CI: 0.92–1.01, P = 0.20; Dec. RMR: OR: 0.97; 95% CI: 0.94-1.00, P = 0.14). Some components of LCDS had significant differences with DNR, such as carbohydrate and Dec. RMR in adjusted model (OR: 1.62; 95% CI: 0.98–1.37, P = 0.08), MUFA and Dec. RMR in adjusted model (OR: 0.48; 95% CI: 0.21–1.10, P = 0.08) and refined grain and Inc. RMR in crude model (OR: 0.87; 95% CI: 0.77–0.99, P = 0.04). Conclusion Our study showed that there is no association between a low-carb diet and RMR status but carbohydrate, MUFA, and refined grain had a significant relationship.

scholarly journals Dietary Intake and Energy Expenditure in Breast Cancer Survivors: A Review

Nutrients ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 3394
Author(s):  
Sarah A. Purcell ◽  
Ryan J. Marker ◽  
Marc-Andre Cornier ◽  
Edward L. Melanson
Keyword(s):  
Breast Cancer ◽  
Physical Activity ◽  
Energy Balance ◽  
Energy Expenditure ◽  
Dietary Intake ◽  
Metabolic Rate ◽  
Cancer Survivors ◽  
Breast Cancer Survivors ◽  
Resting Metabolic Rate ◽  
Fat Free Mass

Many breast cancer survivors (BCS) gain fat mass and lose fat-free mass during treatment (chemotherapy, radiation, surgery) and estrogen suppression therapy, which increases the risk of developing comorbidities. Whether these body composition alterations are a result of changes in dietary intake, energy expenditure, or both is unclear. Thus, we reviewed studies that have measured components of energy balance in BCS who have completed treatment. Longitudinal studies suggest that BCS reduce self-reported energy intake and increase fruit and vegetable consumption. Although some evidence suggests that resting metabolic rate is higher in BCS than in age-matched controls, no study has measured total daily energy expenditure (TDEE) in this population. Whether physical activity levels are altered in BCS is unclear, but evidence suggests that light-intensity physical activity is lower in BCS compared to age-matched controls. We also discuss the mechanisms through which estrogen suppression may impact energy balance and develop a theoretical framework of dietary intake and TDEE interactions in BCS. Preclinical and human experimental studies indicate that estrogen suppression likely elicits increased energy intake and decreased TDEE, although this has not been systematically investigated in BCS specifically. Estrogen suppression may modulate energy balance via alterations in appetite, fat-free mass, resting metabolic rate, and physical activity. There are several potential areas for future mechanistic energetic research in BCS (e.g., characterizing predictors of intervention response, appetite, dynamic changes in energy balance, and differences in cancer sub-types) that would ultimately support the development of more targeted and personalized behavioral interventions.

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