Dataset Information

Estimating my equilibrium energy intake during lockdown: very introspective study.

ABSTRACT:

Objective

To estimate the daily dietary energy intake for me to maintain a constant body weight. How hard can it be?

Design

Very introspective study.

Setting

At home. In lockdown. (Except every Tuesday afternoon and Saturday morning, when I went for a run.) PARTICIPANTS: Me. n=1.

Main outcome measures

My weight, measured each day.

Results

Sleeping, I shed about a kilogram each night (1.07 (SD 0.25) kg). Running 5 km, I shed about half a kilogram (0.57 (SD 0.15) kg). My daily equilibrium energy intake is about 10?000 kJ (10?286 (SD 201) kJ). Every kJ above (or below) 10?000 kJ adds (or subtracts) about 40 mg (35.4 (SD 3.2) mg).

Conclusions

Body weight data show persistent variability, even when the screws of control are tightened and tightened.

SUBMITTER: Lewis RA

PROVIDER: S-EPMC7739109 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Estimating my equilibrium energy intake during lockdown: very introspective study.

Lewis R A RA

BMJ (Clinical research ed.) 20201216

<h4>Objective</h4>To estimate the daily dietary energy intake for me to maintain a constant body weight. How hard can it be?<h4>Design</h4>Very introspective study.<h4>Setting</h4>At home. In lockdown. (Except every Tuesday afternoon and Saturday morning, when I went for a run.) PARTICIPANTS: Me. n=1.<h4>Main outcome measures</h4>My weight, measured each day.<h4>Results</h4>Sleeping, I shed about a kilogram each night (1.07 (SD 0.25) kg). Running 5 km, I shed about half a kilogram (0.57 (SD 0.15 ...[more]

PMID: 33328169

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Project description:Chrononutrition emerges as a novel approach to promote circadian alignment and metabolic health by means of time-of-the-day dietary intake. However, the relationship between maternal circadian rhythm and temporal dietary intake during pregnancy remains understudied. This study aimed to determine the change in melatonin levels in pregnant women across gestation and its association with temporal energy and macronutrient intake. This was a prospective cohort involving 70 healthy primigravidas. During the second and third trimesters, pregnant women provided salivary samples collected at 9:00, 15:00, 21:00, and 3:00 h over a 24 h day for melatonin assay. Data on chrononutrition characteristics were collected using a 3-day food record. Parameters derived from melatonin measurements including mean, amplitude, maximal level, area under the curve with respect to increase (AUCI), and area under the curve with respect to ground (AUCG) were computed. A rhythmic melatonin secretion over the day that remained stable across trimesters was observed among the pregnant women. There was no significant elevation in salivary melatonin levels as pregnancy advanced. In the second trimester, higher energy intake during 12:00-15:59 h and 19:00-06:59 h predicted a steeper melatonin AUCI (β=-0.32, p = 0.034) and higher AUCG (β = 0.26, p = 0.042), respectively. Macronutrient intake within 12:00-15:59 h was negatively associated with mean melatonin (Fat: β=-0.28, p = 0.041) and AUCG (Carbohydrate: β=-0.37, p = 0.003; Protein: β=-0.27, p = 0.036; Fat: β=-0.32, p = 0.014). As pregnant women progressed from the second to the third trimester, a flatter AUCI was associated with a reduced carbohydrate intake during 12:00-15:59 h (β=-0.40, p = 0.026). No significant association was detected during the third trimester. Our findings show that higher energy and macronutrient intakes particularly during 12:00-15:59 h and 19:00-06:59 h are associated with the disparities in maternal melatonin levels. Findings suggest the potential of time-based dietary approaches to entrain circadian rhythm in pregnant women.

Dataset Information

Estimating my equilibrium energy intake during lockdown: very introspective study.

Objective

Design

Setting

Main outcome measures

Results

Conclusions

Publications

Estimating my equilibrium energy intake during lockdown: very introspective study.

Similar Datasets

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