scholarly journals Dose–response effect of a whey protein preload on within-day energy intake in lean subjects

2010 ◽  
Vol 104 (12) ◽  
pp. 1858-1867 ◽  
Author(s):  
Nerys M. Astbury ◽  
Emma J. Stevenson ◽  
Penelope Morris ◽  
Moira A. Taylor ◽  
Ian A. Macdonald

The effect of consuming different amounts of whey protein on appetite and energy intake was investigated in two separate studies using randomised, crossover designs. Healthy-weight men and women (range: BMI 19·0–25·0 kg/m2, age 19·4–40·4 years) consumed one of four 400 ml liquid preloads, followed by an ad libitum test meal 90 min later. In study 1, preloads were 1675 kJ with 12·5, 25 or 50 % of energy from protein, and in study 2, preloads were 1047 kJ with 10, 20 or 40 % energy from protein. Flavoured water was used as the control in both the studies. Appetite ratings were collected immediately before 30, 60 and 90 min after consuming the preloads; and immediately, 30 and 60 min after consuming the test meal. In study 1, energy intake following the control preload (4136 (sem 337) kJ) was significantly higher than each of the 12·5 % (3520 (sem 296) kJ), 25 % (3384 (sem 265) kJ) and 50 % (2853 (sem 244) kJ) protein preloads (P < 0·05). Intake after the 12·5 % preload was significantly higher than following 25 and 50 % preloads (P < 0·05). In study 2, energy intake following the control preload (4801 (sem 325) kJ) was higher than following the 10 % (4205 (sem 310) kJ), 20 % (3988 (sem 250) kJ) and 40 % (3801 (sem 245) kJ) protein preloads (P < 0·05). There were no differences in subjective appetite ratings between preloads in either study. These findings indicate a dose–response effect of protein content of the preload on energy intake at a subsequent meal.

2013 ◽  
Vol 53 (1) ◽  
pp. 543-550 ◽  
Author(s):  
P.C.B. Lollo ◽  
T.M. Batista ◽  
C.S. Moura ◽  
P.N. Morato ◽  
A.G. Cruz ◽  
...  

2009 ◽  
Vol 24 (S1) ◽  
pp. 1-1
Author(s):  
B. Herman ◽  
F. Mandel

Objective:There appears to be no dose-response effect for pregabalin at doses of 300-600 mg, and a modest dose-response effect in the range of 150-300 mg. The goal of the current investigation was to determine the effect of the starting dose on the speed of onset of anxiolytic efficacy.Methods:Data were analyzed from 7 trials of outpatients with DSM-IV GAD and a HAM-A total score ≥18. Starting doses of pregabalin ranged from 100 mg (N=301) or 150 mg (N=104), to 200 mg (N=167) and 300 mg (N=388). Assessment of early improvement included the HAM-A total score and CGI-Severity and Improvement scores.Results:The mean Week 1 HAM-A change score was similar for a starting dose of 200 mg/d with no titration (-8.24) when compared to patients who started on 200 mg/d and then titrated up to 400 mg/d on Day 4 (-8.64). The mean Week 1 HAM-A change score was somewhat higher for patients started on 300 mg/d, and then titrated to 450 mg/d on Day 4/5 (-8.84) when compared to patients started on a lower (100/150 mg/d) dose and titrated on Day 5 to 400/450 mg/d (-7.32). Starting on a dose of 300 mg/d with no titration resulted in an intermediate Week 1 change score (-7.87). The interaction of starting dose and titration schedule with baseline anxiety severity will be summarized in detail.Conclusion:The initial dose of pregabalin appears to have only a weak effect on the speed of onset of anxiolytic improvement.


1990 ◽  
Vol 46 (4) ◽  
pp. 664-668 ◽  
Author(s):  
Subhkij Angsubhakorn ◽  
Panisa Get-Ngern ◽  
Makoto Miyamoto ◽  
Natth Bhamarapravati

2018 ◽  
Vol 66 (50) ◽  
pp. 13173-13182 ◽  
Author(s):  
Wei Wang ◽  
Weichun Yang ◽  
Ziyi Shen ◽  
Sixian Wen ◽  
Minyu Hu

Thorax ◽  
2018 ◽  
Vol 74 (6) ◽  
pp. 607-610 ◽  
Author(s):  
Anthony A Laverty ◽  
Filippos T Filippidis ◽  
David Taylor-Robinson ◽  
Christopher Millett ◽  
Andrew Bush ◽  
...  

We used data from 11 577 children in the UK Millennium Cohort Study, collected at approximately 14 years of age (early teens), to assess characteristics associated with smoking, and generated regional estimates of numbers of smokers. 13.8% of UK early teens studied had ever smoked; 1.9% were current smokers. This corresponds to 2 28 136 and 39 653 (13–14 year olds) in the UK, respectively. Ever smoking risk increased if caregivers (26.0% vs 10.9%) or friends smoked (35.1% vs 4.0%), with a dose–response effect for friends’ smoking. Caregiver and peer-group smoking remain important drivers of child smoking uptake and thus important targets for intervention.


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