Energy intake, dietary pattern and physical activity during the holy month of Ramadan and their impact on body weight.

2019 ◽  
Vol 6 (3-4) ◽  
pp. 291-309
Author(s):  
Sally Ezzat ◽  
◽  
Mohamed Amin ◽  
Keyword(s):  
Physical Activity ◽  
Body Weight ◽  
Energy Intake ◽  
Dietary Pattern

scholarly journals The Trp64Arg Polymorphism of the β3-Adrenergic Receptor Gene Is Not Associated with Body Weight or Body Mass Index in Japanese: A Longitudinal Analysis

2003 ◽  
Vol 88 (12) ◽  
pp. 5914-5920 ◽  
Author(s):  
Yumi Matsushita ◽  
Tetsuji Yokoyama ◽  
Nobuo Yoshiike ◽  
Yasuhiro Matsumura ◽  
Chigusa Date ◽  
...  
Keyword(s):  
Physical Activity ◽  
Body Mass Index ◽  
Body Weight ◽  
Energy Intake ◽  
Body Mass ◽  
Longitudinal Analysis ◽  
Adrenergic Receptor ◽  
Cross Sectional ◽  
Genotype Frequencies ◽  
The Cross

Abstract The β3-adrenergic receptor (ADRB3) is expressed mainly in visceral adipose tissue and is thought to contribute to lipolysis and the delivery of free fatty acids to the portal vein. Although many studies have examined the relationship between the Trp64Arg mutation of ADRB3 and obesity, the results have been inconsistent. We examined the cross-sectional relationship of ADRB3 variants with indexes of obesity, and their longitudinal changes over 10 yr, in men and women, aged 40–69 yr, who were randomly selected from the Japanese rural population. The study considered both dietary energy intake and physical activity levels. Among the 746 participants, the genotype frequencies of the Trp64Trp, Trp64Arg, and Arg64Arg variants were 483, 224, and 39, respectively. The cross-sectional analysis showed no significant differences in height, weight, body mass index, blood pressure, serum total and high density lipoprotein cholesterols, and hemoglobin A1c among the genotype groups even after adjustments for gender, age, smoking, alcohol drinking, physical activity, and energy intake. No significant differences in the weight changes between the genotype groups were evident in the longitudinal analysis. We conclude that the Trp64Arg mutation of ADRB3 has little or no influence on either body weight or body mass index in the general Japanese population.

scholarly journals Trends in energy and macronutrient intakes, body weight and physical activity in female university students (1988–2003), and effects of excluding under-reporters

2004 ◽  
Vol 92 (4) ◽  
pp. 679-688 ◽  
Author(s):  
Penelope M. Warwick ◽  
Jacqueline Reid
Keyword(s):  
Physical Activity ◽  
Body Weight ◽  
University Students ◽  
Energy Intake ◽  
Activity Level ◽  
Carbohydrate Intake ◽  
Macronutrient Intake ◽  
Simple Linear Regression ◽  
Entire Cohort ◽  
Factorial Method

The present study investigated trends in reported energy intake, macronutrient intake, physical activity level (PAL) and body weight and effects of excluding under-reporters (UR). Dietary intake and time spent in sixteen activity categories were recorded by 887 female university students (median age 29 years) from 1988 to 2003. Energy expenditure (EE) and PAL were measured using a factorial method. All data collected were self-reported. Individuals with reported EI:EE<0·76 were classified as UR. The remainder were classified as non-under-reporters (NUR). Trends were determined from simple linear regression of median data for each year for the entire cohort (ALL) and for NUR and UR separately, and from multiple regression analysis with the subgroups (NUR and UR) as an additional predictor (BOTH). Prevalence of under-reporting and overweight increased between 1988 and 2003. In ALL and BOTH there were trends to increased body mass, protein intake (g/d and % energy) and carbohydrate intake (% energy only) and decreased fat and alcohol intakes (g/d and % energy). In BOTH there were also increases in reported EI and carbohydrate intake (g/d). None of the trends in NUR was significantly different from those in UR, but some trends in ALL and/or BOTH were not significant when UR were excluded. Trends remaining significant in NUR were increased reported energy intake, protein (g/d) and carbohydrate (g/d) intakes, and decreased fat (% energy only) intake. There were no significant trends in PAL. We conclude that some, but not all, dietary trends were affected by exclusion of UR.

scholarly journals Energy Expenditure and Physical Activity in Recovering Malnourished Infants

2010 ◽  
Vol 2010 ◽  
pp. 1-7 ◽  
Author(s):  
Russell Rising ◽  
Gul Tiryaki Sonmez
Keyword(s):  
Physical Activity ◽  
Body Weight ◽  
Energy Metabolism ◽  
Energy Expenditure ◽  
Energy Intake ◽  
Body Fat ◽  
Respiratory Quotient ◽  
Lower Amount ◽  
Healthy Controls ◽  
Metabolic Data

Background. Malnourished infants are small for age and weight.Objectives. Determine profiles in 24-hour energy metabolism in recovering malnourished infants and compare to similarly aged healthy controls.Methods. 10 malnourished infants (58.1±5.9 cm,7.7±5.6months) were healthy prior to spending 22 hours in the Enhanced Metabolic Testing Activity Chamber for measurement of EE (kcal/min), sleeping metabolic rate (SMR; kcal/min), respiratory quotient (RQ;VCO2/VO2), and physical activity (PA; oscillations in wt/min/kg body weight). Metabolic data were extrapolated to 24 hours (kcal/kg/d). Energy intake (kcal/kg/d) and the proportions (%) of carbohydrate, protein, and fat were calculated. Anthropometrics for malnourished infants were obtained. Statistical differences (P<.05) between groups were determined (SPSS, version 13).Results. In comparison to controls, malnourished infants were lighter (4.1±1.2versus7.3±0.8 kg;P<.05), had less body fat % (10.3±7.6versus25.7±2.5), and lower BMI (12.0±1.7versus15.5±1.5;P<.05). In contrast, they had greater energy intake (142.7±14.6versus85.1±25.8;P<.05) with a greater percentage of carbohydrates (55.1±3.9versus47.2±5.2;P<.05). However, malnourished infants had greater 24-hour EE (101.3±20.1versus78.6±8.4;P<.05), SMR (92.6±17.1versus65.0±3.9;P<.05), and RQ (1.00±0.13versus0.86±0.08;P<.05) along with a lower amount of PA (2.3±0.94versus4.0±1.5;P<.05).Conclusions. Malnourished infants require more energy, possibly for growth.

scholarly journals Self-reported changes in energy balance behaviors during COVID-19 related home confinement: A Cross-Sectional Study

2020 ◽  
Author(s):  
Surabhi Bhutani ◽  
Jamie A Cooper ◽  
Michelle R Vandellen
Keyword(s):  
Physical Activity ◽  
Body Weight ◽  
Energy Expenditure ◽  
Health Behavior ◽  
Energy Intake ◽  
Overweight And Obesity ◽  
Multiple Time ◽  
Sudden Increase ◽  
Cross Sectional ◽  
At Home

ABSTRACTBackgroundThe COVID-19 pandemic has caused people to shelter-at-home for an extended period, resulting in a sudden rise in unstructured time. This unexpected disruption in everyday life has raised concerns about weight management, especially in high-risk populations of women and individuals with overweight and obesity. This study aimed to investigate the changes in behaviors that may impact energy intake and/or energy expenditure in U.S. adults during the home confinement.MethodsCross-sectional data from 1,779 adults were collected using an online Qualtrics survey between April 24th and May 4th, 2020. Self-reported data on demographics, eating behaviors, physical activity, sleep, screen time, takeout food intake, and food purchasing behaviors were collected. Chi-Square analyses were conducted to evaluate differences in the percent of participants reporting increasing, decreasing, or staying the same in each health behavior since the COVID-19 outbreak in their area. Each analysis was followed by comparing whether increases or decreases were more likely for each health behavior. Similar comparisons were made between male and female participants and between body mass index (BMI) categories.ResultsWe observed an increase in the intake of both healthy and energy-dense unhealthy foods and snacks during the home confinement. Participants also reported increases in sedentary activities and decrease in physical activity, alcohol intake, and consumption of takeout meals during this time. In women, several behavioral changes support greater energy intake and less energy expenditure than men. No clear difference in patterns was observed across BMI status.ConclusionAcute changes in behaviors underscore the significance of a sudden increase in unstructured time at home on potential weight gain. Our findings support the need to implement and support measures that promote strategies to maintain body weight and establish a methodology to collect body weight data at multiple time points to longitudinally assess the dynamic relationship between behaviors and body weight change.

scholarly journals Energy intake, physical activity and body weight: a simulation model

1995 ◽  
Vol 73 (3) ◽  
pp. 337-347 ◽  
Author(s):  
Klaas R. Westerterp ◽  
Jeroen H. H. L. M. Donkers ◽  
Elisabeth W. H. M. Fredrix ◽  
Piet oekhoudt
Keyword(s):  
Physical Activity ◽  
Body Composition ◽  
Body Weight ◽  
Energy Balance ◽  
Energy Expenditure ◽  
Dietary Intake ◽  
Energy Intake ◽  
Relative Size ◽  
The Body ◽  
Fat Free Mass

In adults, body mass (BM) and its components fat-free mass (FFM) and fat mass (FM) are normally regulated at a constant level. Changes in FM and FFM are dependent on energy intake (EI) and energy expenditure (EE). The body defends itself against an imbalance between EI and EE by adjusting, within limits, the one to the other. When, at a given EI or EE, energy balance cannot be reached, FM and FFM will change, eventually resulting in an energy balance at a new value. A model is described which simulates changes in FM and FFM using EI and physical activity (PA) as input variables. EI can be set at a chosen value or calculated from dietary intake with a database on the net energy of foods. PA can be set at a chosen multiple of basal metabolic rate (BMR) or calculated from the activity budget with a database on the energy cost of activities in multiples of BMR. BMR is calculated from FFM and FM and, if necessary, FFM is calculated from BM, height, sex and age, using empirical equations. The model uses existing knowledge on the adaptation of energy expenditure (EE) to an imbalance between EI and EE, and to resulting changes in FM and FFM. Mobilization and storage of energy as FM and FFM are functions of the relative size of the deficit (EI/EE) and of the body composition. The model was validated with three recent studies measuring EE at a fixed EI during an interval with energy restriction, overfeeding and exercise training respectively. Discrepancies between observed and simulated changes in energy stores were within the measurement precision of EI, EE and body composition. Thus the consequences of a change in dietary intake or a change in physical activity on body weight and body composition can be simulated.

scholarly journals Increased energy intake entirely accounts for increase in body weight in women but not in men in the UK between 1986 and 2000

2010 ◽  
Vol 105 (9) ◽  
pp. 1399-1404 ◽  
Author(s):  
Peter Scarborough ◽  
Melanie R. Burg ◽  
Charlie Foster ◽  
Boyd Swinburn ◽  
Gary Sacks ◽  
...  
Keyword(s):  
Physical Activity ◽  
Body Weight ◽  
Total Energy ◽  
Energy Intake ◽  
Credible Interval ◽  
Total Energy Intake ◽  
Activity Levels ◽  
Time Points ◽  
Physical Activity Levels ◽  
The Uk

There is debate over the casual factors for the rise in body weight in the UK. The present study investigates whether increases between 1986 and 2000 for men and women were a result of increases in mean total energy intake, decreases in mean physical activity levels or both. Estimates of mean total energy intake in 1986 and 2000 were derived from food availability data adjusted for wastage. Estimates of mean body weight for adults aged 19–64 years were derived from nationally representative dietary surveys conducted in 1986–7 and 2000–1. Predicted body weight in 1986 and 2000 was calculated using an equation relating body weight to total energy intake and sex. Differences in predicted mean body weight and actual mean body weight between the two time points were compared. Monte Carlo simulation methods were used to assess the stability of the estimates. The predicted increase in mean body weight due to changes in total energy intake between 1986 and 2000 was 4·7 (95 % credible interval 4·2, 5·3) kg for men and 6·4 (95 % credible interval 5·9, 7·1) kg for women. Actual mean body weight increased by 7·7 kg for men and 5·4 kg for women between the two time points. We conclude that increases in mean total energy intake are sufficient to explain the increase in mean body weight for women between 1986 and 2000, but for men, the increase in mean body weight is likely to be due to a combination of increased total energy intake and reduced physical activity levels.

scholarly journals Alcohol energy intake and habitual physical activity in older adults

2004 ◽  
Vol 91 (1) ◽  
pp. 149-152 ◽  
Author(s):  
Klaas R. Westerterp ◽  
Erwin P. Meijer ◽  
Annelies H. C. Goris ◽  
Arnold D. M. Kester
Keyword(s):  
Physical Activity ◽  
Body Weight ◽  
Alcohol Consumption ◽  
Energy Intake ◽  
Alcohol Intake ◽  
Activity Level ◽  
Habitual Physical Activity ◽  
Additional Energy ◽  
Higher Alcohol ◽  
Dietary Record

Alcohol forms a significant component of many diets and it supplements rather than displaces daily energy intake. Surprisingly, alcohol intake does not systematically increase body weight. The present study assessed whether a higher level of habitual physical activity in the daily environment is associated with a higher alcohol intake. Alcohol intake as part of total food intake was measured with a 7 d dietary record while at the same time physical activity was monitored with a tri-axial accelerometer for movement registration. Subjects were twenty women and twenty-four men, aged 61±5 years, of BMI 27·1±4·6 kg/m2. Between subjects, there was a positive association between the level of habitual physical activity and alcohol intake (r 0·41; P<0·01). The subjects with higher alcohol intake had a higher activity level. On days with and days without alcohol consumption there was no difference in physical activity within subjects. In conclusion, it was shown that subjects with higher alcohol consumption are habitually more active. This may explain the lack of increasing body weight through additional energy intake from alcohol.

scholarly journals Effect of Attendance of the Child on Body Weight, Energy Intake, and Physical Activity in Childhood Obesity Treatment

2017 ◽  
Vol 171 (7) ◽  
pp. 622 ◽  
Author(s):  
Kerri N. Boutelle ◽  
Kyung E. Rhee ◽  
June Liang ◽  
Abby Braden ◽  
Jennifer Douglas ◽  
...  
Keyword(s):  
Physical Activity ◽  
Body Weight ◽  
Childhood Obesity ◽  
Energy Intake ◽  
Obesity Treatment

scholarly journals 0032 Timing of Daily Rhythm of Cardiac Autonomic Control Contributes to Weight Loss Resistance, Independent of Daily Energy Intake and Physical Activity Level

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A13-A13
Author(s):  
H Yang ◽  
M Garaulet ◽  
P Li ◽  
C Bandin ◽  
C Lin ◽  
...  
Keyword(s):  
Physical Activity ◽  
Weight Loss ◽  
Body Weight ◽  
Energy Intake ◽  
Physical Activity Level ◽  
Autonomic Control ◽  
Activity Level ◽  
Daily Rhythm ◽  
Cardiac Autonomic Control ◽  
Loss Resistance

Abstract Introduction Obesity is a major health problem. Many treatments have been designed to help overweight/obese people to lose weight, but their effectiveness is highly variable. The same treatments may work for some persons while others have no responses — weight loss resistance. We tested whether the daily rhythm of cardiac autonomic control contributes to weight loss resistance. Methods We studied 39 overweight/obese Caucasian women (BMI&gt;25; age: 21–62 years old) who completed (1) an obesity dietary treatment of up to 30 weeks with weekly assessments of body weight, and (2) ambulatory monitoring of electrocardiogram (ECG) for up to 3.5 days. Heartbeat intervals were derived from ECG. Cardiac autonomic control was assessed in each 1-h bin by examining the temporal correlation in heartbeat fluctuations — a nonlinear measure that quantifies the delicate dynamic interplay between sympathetic and vagal outflows. Daily rhythm was estimated using the cosinor analysis. Results Weight loss was highly variable (range: 0.68%-21.78 % of initial body weight). The correlation in heartbeat fluctuations displayed a 24-h rhythm (p&lt;0.0001) with fewer correlations (more random) during the nighttime. The phase (peak timing) of the rhythm was highly variable, i.e., 10AM to 8PM for most participants, and after midnight in four participants. Weight loss evolution depended on the phase (p=0.006) in a nonlinear manner. Specifically, participants with the phase between 2PM-8PM lost weight faster than those with phases before 2PM and those after 8PM. The effect was independent of total energy intake, physical activity level, and sleep/wake schedules. Conclusion Cardiac autonomic control in overweight/obese women displayed a daily rhythm. The timing of the rhythm had previously un-identified contributions to weight loss. The inter-individual differences in the timing may reflect different circadian regulation of autonomic function and its interaction with the daily behavioral cycle. Support This work was supported by NIH grants R01AG048108, RF1AG059867, RF1AG064312, R01AG017917, and R01NS078009.

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