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Difficulty in Equating Mass and Energy in Humans

Equating Net Energy and Fat Balance in

Open Systems of Enzymatic and Reversible Reactions

Benjamin E. Neusse

California University of Pennsylvania

PRF 810 G4

Research in Performance Enhancement

1

Difficulty in Equating Mass and Energy in Humans 2

Introduction

Professionals constantly advise, eat less and exercise more, and burn more calories than

you eat, to lose weight. Most claim that a reduction of net calories by 3,500 results in the loss of

one pound of fat. Scientists, doctors, and fitness professionals recite similar statements, but are

they grounded in science, medicine, and fitness experience? One can demonstrate that a pound

of fat provides 3,500 kcal when combusted in a bomb calorimeter, however this procedure and

results cannot be generalized to the human. The several differences between a human and bomb

calorimeter threaten the external validity of simply relating units of mass to units of energy.

Humans are open systems, which never reach equilibrium, that can harness reversible

reactions, vary reaction rates, and utilize enzymes which lower activation energy (Barr &

Wright, 2010; Koenigstorfer & Schmidt, 2011). Medical science raises confounding concepts

such as variable insulin sensitivity, protein turnover, omega-3 to omega-6 fatty acid balance, and

up-regulation of lipogenic enzymes (Feinman & Fine, 2003; Fine & Feinman, 2004). Despite

these other factors influencing human fat balance, professionals offer the same cliché advice and

cite protocol non-compliance to explain why subjects always lose less fat than predicted. Surely

some participants in some studies do follow the protocols but don’t experience the predicted fat

loss. Are subjects following hypocaloric protocols and experiencing poor results due to other

factors?

Problem statement: The purpose of this study is to determine the expected body fat change in

kilograms resulting from changes in net energy balance in kcal over time in order to refine

weight loss advice and research.


Annotated Bibliography

Barr, S. B., & Wright, J. C. (2010). Postprandial energy expenditure in whole-food and processed-food meals: Implications for daily energy expenditure. Food & Nutrition Research, 54, 1-9. doi:10.3402/fnr.v54i0.5144

The purpose of this study was to examine the difference in human energy expenditure

following a meal of processed foods versus a meal of whole foods. The researchers

followed a cross-over design with 12 women and 5 men measuring each participant’s

postprandial energy expenditure for 5 to 6 hours following a meal. An indirect

calorimeter provided the energy expenditure data. The researchers used a pair-wise t-test

to analyze the difference between the whole food and processed food test groups, while

age and sex groups were analyzed with a two-sample t-test. The researchers concluded

that whole food meals require more digestion energy than processed foods and provide an

advantage toward weight-loss programs given each meal provided the same number of

calories and satiety. This study shows that factors other than caloric intake can directly

alter caloric expenditure which points to an invalidity of the simple net calories equation.

Bouchard, C., Tremblay, A., Despres, J., Nadeau, A., Lupien, P. J., Theriault, G., … Fournier, G. (1990). The response to long-term overfeeding in identical twins. The New England Journal of Medicine, 322, 1477-1482.

The purpose of this study was to determine the presence of individual and genotype

differences in response to long-term over feeding, specifically on body composition and

body fat topography. The researchers overfed 12 pairs of male identical twins by 1000

kcal daily for 84 days. The participants lived in a closed section of the dormitory with

the research staff for 120 days. Researchers used scales, skinfold calipers, and measuring

tape daily while under-water weighing provided body composition data at three points.

The researchers used a two-way ANOVA with the F ratio providing the ratio of variance


between pairs to that within pairs. The average weight gain was 8.1 kg and the

researchers noted a threefold difference in the weight gained from the same caloric intake

excess. The researchers concluded that individual differences exist in the tendency to

gain fat mass through an increase in caloric intake and that unknown genetic factors are

likely responsible. This study demonstrates that changes in net calories can explain the

direction but not the magnitude of change in body weight or body fat mass specifically as

participants averaged only 74% of excess calories stored as body tissue.

Bouchard, C., Treinblay, A., Despres J., Theriauit, G., Nadeau, A., Lupien, P. J., … Fournier, G. (1994). The response to exercise with constant energy intake in identical twins. Obesity Research, 2, 400-410.

The purpose of this study was to determine the individual and genotype differences in

response to exercise induced caloric deficit on body weight. The researchers subjected

seven pairs of male twins to two cycling workouts daily inducing a 1000 kcal deficit

while holding caloric intake and other activity constant over 90 days. The researchers

used scales and skinfold calipers and under water weighing. A two-way ANOVA was

used for statistical analysis while the F ratio provided information regarding variance.

Participants experienced an average weight loss of 5 kg of fat or about 39000 kcal of the

more than 58000 kcal exercise induced deficit. Furthermore participant pairs showed a

14.1 fold variance in changes in body fat. The researchers concluded that genetic

variations must be responsible for the vast variance in body fat loss. This study

demonstrated that even under the most controlled conditions a caloric deficit only

resulted in an average fat loss of 67% of the predictions of the net calorie equation, and

this result varied widely across seven pairs of twins. This study shows similar results


though opposite in magnitude as Bouchard’s previous study on twins as a caloric excess

only produced about a 70% increase in body weight (Bouchard et al., 1990)

Buchholz, A. C., & Schoeller, D. A. (2004). Is a calorie a calorie? American Journal of Clinical Nutrition, 79(Suppl.), 899-906.

The purpose of this review was to determine from the data the role a high protein or low

carbohydrate diet plays in increased weight loss. The authors reviewed nine studies of

free-living adults consuming hypocaloric diets. On average the authors found that such

diets resulted in 2.5 kg greater weight loss at 12 weeks than the control or other diets.

The authors reported a standard deviation of 1.8 kg for 12 week losses and 0.4 kg

standard deviation for an average of 4.0 kg of greater weight loss at 24 weeks. The

authors make several attempts to account for the 20000 kcal difference but none of their

calculations or adjustments can explain more than one third of this difference. Despite

the data, the authors conclude that a calorie is a calorie. The authors attempt to account

for the caloric difference by blaming the participants of the studies for under reporting

their caloric intake. This review demonstrates that most professionals assume the

external validity between a bomb calorimeter and a human body as after all attempts fail

to account for all the calories the authors fault the participants.

Del Corral P., Bryan, D. R., Garvey, W. T., Gower, B. A., & Hunter, G. R. (2011). Dietary adherence during weight loss predicts weight regain. Obesity, 19, 1177-1181. doi: 10.1038/oby.2010.298

The purpose of this study was to examine the relationship between dietary compliance

and weight regain. The researchers studied 160 women who had previously lost an

average 12 kg. The researchers used doubly labeled water to measure body composition

changes. This method seems to assume that weight lost is a dependent variable of dietary


compliance and that no other factors account for the variance in weight lost. This

assumption conflicts with the study on twins that showed a wide variation of weight loss

due to exercise induced caloric deficit (Bouchard, et at. 1994). The researchers used a

repeated ANOVA to examine the relation between compliance and subsequent weight

gain. The study found that participants in the highest quartile of weight loss results

experienced a weight regain of 31% one year after their weight loss diet, while those in

the bottom quartile regained 69% of weight lost. The researchers concluded that dietary

adherence significantly reduces the percentage of weight regained following a

hypocaloric weight loss diet. This study does demonstrate that individuals who have met

with successful weight reduction are more likely to keep the weight off, however this

study attributes that to only one factor, previous weight loss success.

Demling, R. H., & DeSanti, L. (2000). Effect of a hypocaloric diet, increased protein intake, and resistance training on lean mass gains and fat mass. Annals of Nutrition & Metabolism, 44, 21-29.

The purpose of this study was to determine the effect on body weight and composition

between a hypocaloric diet with and without protein supplements on men conducting

resistance training. The participants included 38 overweight police officers placed on a

diet of 80% of calculated energy needs divided into three groups, one control, and two

groups given either whey or a casein protein supplement. Researchers used scales and

skinfold calipers to measure weight and body composition. The researchers used the

paired t-test to determine significance of the changes between the three protocols. The

study found roughly the same weight loss between the three groups of about 2.6 kg;

however fat mass loss was 7 kg for the casein group and 4.2 kg of fat mass loss from the

whey group. The researchers concluded that the inclusion of protein and casein


specifically helped to maintain and even increase lean mass while reducing fat mass

during hypocaloric diets combined with exercise training. This study demonstrated

varied fat mass lost with similar caloric intakes. This conflicts with a strict view of the

generic energy balance equation.

Dennis, E. A., Dengo, A. L., Comber, D. L., Flack, K. D., Savla, J., Davy, K. P., & Davy, B. M. (2010). Water consumption increases weight loss during a hypocaloric diet intervention in middle-aged and older adults. Obesity, 18, 300-307. doi: 10.1038/oby.2009.235

The purpose of this study was to determine the effect on energy intake following water

consumption during a weight loss, hypocaloric diet. The researchers recruited 48

participants who were randomized into groups provided about a liter of water and

instructions to ingest it 30 min prior to meals and those given water with no instructions.

Participants were encouraged to maintain physical activity. Researchers used the

repeated ANOVA to determine significance of variance as well as independent t-test and

Pearson’s χ2 as well as t-tests for post hoc analysis. After 12 weeks both groups

demonstrated weight loss while the water preload group exhibited a 44% greater weight

loss. Furthermore the water preload group lost 5.4% fat mass on average compared to

3.3% fat mass. The researchers concluded that preloading water before each meal

resulted in greater fat loss; though such fat loss was not entirely explained by the

subsequent reduction in energy intake at each meal. This study shows another example

of a change in body fat stores resulting from a factor other than a change in net calories.

This demonstrates that factors other than calorie balance affect fat balance.

Kempen, K. P., Saris, W. H., & Westerterp, K. R. (1995). Energy balance during an 8-wk energy-restricted diet with and without exercise in obese women. The American Journal of Clinical Nutrition, 62, 722-729.


The purpose of this study was to determine the difference between energy restricted diet

and energy restricted diet plus moderate exercise on energy balance. The researchers

studied 20 obese women for eight weeks who were matched by body fat percentage and

Body Mass Index (BMI) into two groups. The researchers measured energy expenditure

through an overnight stay in an indirect calorimeter, while body composition was

determined with a scale, measuring tape, and underwater weighing. The interaction of

diet and exercise was analyzed with a two way repeated ANOVA, while the t-test was

used for post hoc testing. The diet plus exercise group demonstrated a larger percentage

of fat mass loss than the diet only group as well as a shift to an increase in fat metabolism

during exercise compared to the diet only group. The researchers concluded that exercise

enhances fat loss but not weight loss. In this study the researchers blamed participants

compliance when predicted weight loss was not achieved rather than considering other

factors or questioning the external validity of the energy balance equation.

Koenigstorfer, J. & Schmidt, W. F. (2011). Effects of exercise training and a hypocaloric diet on female monozygotic twins in free-living conditions. Physiology & Behavior, 104, 838-844.

The purpose of this study was to examine the results of various exercise bout timings

relative to meals on body weight and composition in six female twins. Six pairs of

untrained twins were split into two groups, one twin exercised before dinner, the other

after dinner. Researchers measured body weight, body composition and resting energy

and metabolic rates using scales, tape measures, bioelectric impedance, and indirect

calorimetry. The researchers used two-way ANOVA to determine statistical significance.

The researchers concluded that the timing of the exercise bout had no effect on the

dependent variables, that twins showed similar changes in dependent variables while


significant variance existed between pairs implicating genetic differences in weight loss.

This study also showed less weight loss than predicted due to change in net calories,

while the researchers cited under reporting of caloric intake. This explanation does not

seem plausible in twin studies as each twin would have to under report by a similar

amount to have similar weight loss results.

Shai, I., Schwarzfuchs, D., Henkin, Y., Shahar, D. R., Witkow, S., Greenberg, I., . . . Fiedler, G. (2008). Weight loss with a low-carbohydrate, Mediterranean, or low-fat diet. New England Journal of Medicine, 359, 229-241. doi: 10.1056/NEJMoa0708681

The purpose of this study was to compare the three nutritional protocols. The authors

presented three different treatment diets to over 272 obese participants measuring caloric

dietary intake as well as weight loss over a period of two years. The authors used a scale

sensitive to 0.1 kg to monthly measure participant’s weight while clothed but without

shoes. Participants answered a validated food-frequency questionnaire from which the

authors could calculate dietary caloric intake. A validated questionnaire also allowed

measurement of physical activity. The authors used ANOVA to analyze the weight,

calorie and physical activity data. The low fat diet had and average daily caloric

reduction of 572 kcal and a weight loss of 3.3 kg; the Med-diet had and average reduction

of 371 kcal and a weight loss of 4.6 kg; while the low-carb diet had and average

reduction of 550 kcal and a weight loss of 5.5 kg. The authors concluded that the

Mediterranean diet and the low-carb diet are safe and effective alternatives to the low-fat

diet. This research shows similar changes in net calories resulting in different changes in

body weight as well as similar changes in body weight with different changes in net

calories.


Conclusions

Each of the studies presented here and those cited in the review by Buchholz and

Schoeller (2004) demonstrated that fat balance does not change in lock step with net energy

balance. Though each study did show a negative caloric balance resulted in fat loss and a

positive caloric balance resulted in fat gain a significant portion of calories went unaccounted

for. Even in the two most controlled studies there was a mismatch of energy and mass by around

30% (Bouchard et al., 1990; Bouchard et al., 1994). In nearly every study the researchers

defaulted to the position of participant non-compliance in order to explain the lack of fat loss.

Not one study examined or questioned the ability to generalize the values from a bomb

calorimeter to a human being.

There must be more factors affecting fat balance than just net calories. The twin studies

clearly demonstrate great variance in weight loss or weight gain resulting from genetic

differences (Bouchard et al., 1990; Bouchard et al., 1994; Koenigstorfer & Schmidt, 2011).

Additional studies indicate macronutrient ratios further alter fat balance and fat loss beyond what

caloric deficits can explain (Demling & DeSanti, 2000; Shai et al., 2008). Furthermore a study

involving increased water consumption showed greater weight loss than expected from its

subsequent reduction in energy intake during meals (Dennis et al., 2010). The researchers did

not consider the energy requirements to heat the ingested water to body temperature though that

is the very definition of a calorie.

The results of each study demonstrate a failure of the energy balance equation. This

should not be surprising because the concept is applied in violation of the assumptions of the

laws of thermodynamics, particularly that of a closed system. Humans are constantly


exchanging heat with their surroundings, and even expend energy to heat and cool themselves.

Additionally not all combustible energy is recoverable metabolically. Finally organisms

manufacture enzymes from proteins in order to lower activation energy of reactions. This one

phenomenon can explain the plateau effect noted in several of these studies. Clearly lack of

participant adherence to dietary reporting or protocols should not be the default position of

researchers as we can predict that weight loss will not match the induced caloric deficit.

Clinical Implications

In recognizing that fat loss does not occur in direct proportion to caloric deficit one

should not emphasize a strategy of calorie counting when counseling or training clients.

Counting calories is sure to lead to disappointment as one could never achieve predicted results.

Positive implications do however exist in that certain macronutrient skews and simple

interventions such as increased water consumption can help clients achieve their body

composition goals. The studies involving exercise do demonstrate greater and faster weight lost

as well as maintenance of lean body mass (Demling & DeSanti, 2000; Kempen et al., 1995).

This underscores the double advantage of resistance training in conjunction with dietary changes

to reach body composition goals.

This research also proves useful when working with a client who has tried diets and

failed in the past. Being able to explain that it was not a client’s fault but any number of other

factors that contributed to less weight loss than expected enables a coach to reach and help more

people. This research should offer hope to those who have tried and failed, prompting them to

exercise, drink more water, and swap processed foods for whole foods. This research can aid


other coaches to understand why their training and guidance works on some individuals but not

others.

Future Research

The information here seems to indicate the lack of validity of the energy balance equation

but it also provides directions for future research in order to create more productive weight loss

strategies. It would prove helpful to measure changes in the level of metabolic enzymes that

occur under hypocaloric conditions and whether they differ with and without the inclusion of

exercise. Such information could improve weight loss advice and perhaps advocate diets of

constantly varying macronutrient ratios or caloric deficits to prevent plateaus. The body adapts

to stimuli presented to it and perhaps it would be possible to prevent the body from improving

efficiency by utilizing a varied diet with mixed modes and durations of exercise.

Additionally it would be interesting to determine the degree to which free living humans

exchange heat energy with their environment. This would include the consumption of foods and

liquids at temperatures different from core body temperature. This may prove useful to

recommend drinking cool fluids and avoiding hot fluids, or it may prove better to drink differing

temperatures throughout the day to again prevent adaptations of efficiency.

Finally there must be other factors other than genetic which influence how the body

partitions energy (Fine & Feinman, 2004; Feinman & Fine, 2003). There could also be factors

that change how nutrients are absorbed in the intestinal track. Understanding these factors could

enable one to influence how the liver and other organs work together to contribute to fat balance

in the body. Such knowledge could prove useful in developing novel strategies to make up the

gap between predicted and actual weight loss due to caloric deficits.


References

Barr, S. B., & Wright, J. C. (2010). Postprandial energy expenditure in whole-food and processed-food meals: Implications for daily energy expenditure. Food & Nutrition Research, 54, 1-9. doi:10.3402/fnr.v54i0.5144

Bouchard, C., Tremblay, A., Despres, J., Nadeau, A., Lupien, P. J., Theriault, G., . . . Fournier, G. (1990). The response to long-term overfeeding in identical twins. The New England Journal of Medicine, 322, 1477-1482.

Bouchard, C., Treinblay, A., Despres J., Theriauit, G., Nadeau, A., Lupien, P. J., . . . Fournier, G. (1994). The response to exercise with constant energy intake in identical twins. Obesity Research, 2, 400-410.

Buchholz, A. C., & Schoeller, D. A. (2004). Is a calorie a calorie? American Journal of Clinical Nutrition, 79(Suppl.), 899-906.

Del Corral P., Bryan, D. R., Garvey, W. T., Gower, B. A., & Hunter, G. R. (2011). Dietary adherence during weight loss predicts weight regain. Obesity, 19, 1177-1181. doi: 10.1038/oby.2010.298

Demling, R. H., & DeSanti, L. (2000). Effect of a hypocaloric diet, increased protein intake, and resistance training on lean mass gains and fat mass. Annals of Nutrition & Metabolism, 44, 21-29.

Dennis, E. A., Dengo, A. L., Comber, D. L., Flack, K. D., Savla, J., Davy, K. P., & Davy, B. M. (2010). Water consumption increases weight loss during a hypocaloric diet intervention in middle-aged and older adults. Obesity, 18, 300-307. doi: 10.1038/oby.2009.235

Fine, E. J., & Feinman, R. D. (2004). Thermodynamics of weight loss diets. Nutrition & Metabolism, 1(15), 1-8. doi:10.1186/1743-7075-1-15

Feinman, R. D. & Fine, E. J. (2003). Thermodynamics and metabolic advantage of weight loss diets. Metabolic Syndrome and Related Disorders, 1(3), 209-219.

Kempen, K. P., Saris, W. H., & Westerterp, K. R. (1995). Energy balance during an 8-wk energy-restricted diet with and without exercise in obese women. The American Journal of Clinical Nutrition, 62, 722-729.

Koenigstorfer, J., & Schmidt, W. F. (2011). Effects of exercise training and a hypocaloric diet on female monozygotic twins in free-living conditions. Physiology & Behavior, 104, 838-844.

Shai, I., Schwarzfuchs, D., Henkin, Y., Shahar, D. R., Witkow, S., Greenberg, I., . . . Fiedler, G. (2008). Weight loss with a low-carbohydrate, Mediterranean, or low-fat diet. New England Journal of Medicine, 359, 229-241. doi: 10.1056/NEJMoa0708681