Protein Intake Recommendation for Patients with Stage 3 Kidney Disease

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Part I: Address all Aspects of the Prompt & Address Gaps in Literature 

Prompt topic: What is the protein intake recommendation for patients with stage 3 kidney disease and what is the rationale behind this recommendation?  If a patient has COPD and stage 3 kidney disease, what should their protein requirements be and why would you recommend this amount?

The current recommendation for protein in stage 3 chronic kidney disease (CKD)  is anywhere from 0.6-0.8 g/kg per day. Recommendations of 0.6-0.8 g/kg are low compared to the recommendation for promoting weight maintenance in adults, which is 0.8-1.0 g/kg per day. CKD is characterized by failure of the kidneys to function efficiently and successfully remove waste from the blood to be excreted in the urine (Noroqvist, 2017). Nitrogenous waste is formed by the inability of the kidneys to filter protein efficiently and therefore waste builds up in the blood. A diet consisting of high protein consequently causes a rise in glomerular filtration rate and ultimately causes damage to the glomerular structure leading to kidney irritation and progression of CKD (Ko, 2018). High protein diets may instigate kidney impairment and lead to a buildup of unhealthy concentrations of protein metabolites causing a toxic effect on the individual suffering from CKD (Ko, 2018). A low protein diet offers an assortment of benefits to the individual with CKD. Low-protein diets have been promoted for many years as the foundation in the management and treatment of CKD. The specific amount of protein for  CKD patients is still a controversial topic even though many guidelines have been set at 0.6-0.8 g/kg. However, this range may not meet the needs of every single stage 3 CKD individual. In the early 1960’s low protein intake was prescribed to CKD patients with the overall goal to reduce uremic symptoms (Roccio, 2014). In later decades, several studies theorized that a high protein intake could cause an increase in glomerular filtration and lead to quicker progression of CKD in individuals, therefore,  increasing morbidity and mortality. In recent decades the low protein diet has gained support for its role is reducing CKD progression into the further, end stages (Roccio, 2014). In earlier decades it can be predicted that little was known regarding the pathogenesis of CKD in the 1960’s. Uremia is the inability of the kidneys to filter blood and remove waste efficiently, and it can be assumed that a connection between uremic symptoms and CKD was not established at this time. When the connection between uremic symptoms and CKD was established it made sense to lower protein intake because the kidneys, the major organ that filters and excretes waste, is no longer able to efficiently excrete excess nitrogen in the urine leading to an accumulation of toxic metabolites in the blood. Recommendations to lower protein intake in CKD patients has been shown to improve several metabolic effects such as “lowering serum urea nitrogen levels, improving phosphocalcic metabolism and insulin resistance and more recently, ameliorating proteinuria (independent of antiproteinuric medications)” (Denis, 2007). The compromised kidney function reduces the body’s ability to efficiently excrete the metabolite toxins that accumulate when protein-rich foods are consumed, digested and metabolized. Due to this accumulation of toxic metabolites, uremic symptoms become apparent, and the kidneys are no longer able to efficiently filter waste and the CKD patient experiences symptoms of nausea, vomiting and possibly weight loss (Bellizzi, 2016). A reduction in protein can benefit the CKD individual by reducing the accumulation of uremic toxins in the blood and or by delaying the progression of CKD into the further stages.

Chronic pulmonary obstructive disease (COPD) is a public health problem worldwide that is characterized by a cluster of lung diseases that consequently block airflow and make it very difficult for the individual to breath especially as the disease progresses or if it is accompanied by other co-morbid conditions. Reduced body weight as a result of metabolic stress and decreased actual energy intake often serves as an issue for the COPD patient (Hallin, 2006). Decreased energy and protein intake is related to difficulty or pain when eating, higher metabolic rate due to the critical state of COPD and ventilated breathing devices being induced, inflammation due to constant oxidative stress and pharmaceutical treatment with glucocorticoid because of their muscle-wasting side effect. (Hallin, 2006) (Rawal, 2015). Since maintaining a healthy weight is critical to reducing mortality and morbidity energy and protein needs are often set at higher recommendations.  The Nutrition Care Manual recommends choosing foods that are high in protein and calories. In the case that the patient has COPD and does not have stage 3 CKD the main focus of treatment would be to ensure that the patient maintains weight and protein is properly metabolized for muscle and tissue repair. Protein needs should be assessed to the individual’s specific needs, their current weight, and disease progression while being high enough to stimulate protein synthesis (St. Floridian, 2009). Approximately 1.2-1.7 g/kg body weight of protein is recommended in the individual with COPD (St. Floridian, 2009). Compared to the recommended amount for healthy adults promoting weight maintenance of .8-1.0 g/kg, 1.2-1.7 g/kg is significantly higher.

COPD is often linked to comorbidity because of the extreme degradation that the disease takes on the body as it progresses. CKD as a comorbid condition is often misjudged because it goes unseen when looking at serum creatinine since glomerular filtration rate is already suppressed in the COPD patient (Abdelhalim, 2016). If an individual has both COPD and stage 3 CKD how to administer medical nutrition therapy becomes a major consideration due to the two conditions requiring very different macronutrient requirements especially in the case of protein requirement. It is critical to use clinical judgment and take into account several factors before recommending a specific protein intake to the patient with COPD as well as stage 3 CKD. Weight, age, disease status, medical treatment and additional complications of the patient need to be considered prior to recommending any nutritional advice. Since 0.6 g/kg per day is the lowest protein amount prescribed and 1.7 g/kg per day is the highest the registered dietitian and physician should consider all other factors affecting the patient and prescribe a daily protein intake of approximately 1.0-1.3 g/kg body weight. This recommendation provides adequate protein to the COPD individual and is used to promote adult maintenance. Additionally, this range does is not excessively high and should not significantly increase the progression of CKD. However, since the patient is in stage 3 CKD and will eventually progress to stage 4 and 5 (end-stage renal disease), dialysis should be considered as a form of treatment in the near future. If the patient were to choose hemodialysis as a form of treatment protein restriction is no longer necessary because a device is now acting out the function of the kidneys and properly filtering and excreting nitrogenous waste. CKD patients on hemodialysis have increased protein needs similarly to COPD patients, with a protein range of 1.2-1.8 g/kg body weight. If a patient has COPD and stage 3 CKD appropriate and is not on hemodialysis appropriate recommendations would be to use a range of 1.0-1.2 g/kg body weight. If and when the patient starts hemodialysis  appropriate adjustments can be made by increasing protein intake to 1.2-1.7.

References

  1. Abdelhalim, H. A., & Aboelnaga, H. H. (2016). Is Renal Impairment an

Anticipated COPD Comorbidity? Respiratory Care,61(9), 1201-1206. doi:10.4187/respcare.04516

  1. Bellizzi, V., Cupisti, A., & Locatelli, F. (2016). Low-protein diets for chronic

kidney disease patients: The Italian experience. BMC Nephrology. Retrieved October 24, 2018, from https://bmcnephrol.biomedcentral.com/articles/10.1186/s12882-016-0280-0.

  1. Fouque, D., & Aparicio, M. (2007). Eleven reasons to control the protein intake

of patients with chronic kidney disease. Nature Clinical Practice Nephrology,3(7), 383-392. doi:10.1038/ncpneph0524

  1. Hallin, R., Koivisto-Hursti, U., Lindberg, E., & Janson, C. (2006). Nutritional

status, dietary energy intake and the risk of exacerbations in patients with chronic obstructive pulmonary disease (COPD). Respiratory Medicine,100(3), 561-567. doi:10.1016/j.rmed.2005.05.020

  1. Ko, G. J., MD, PhD, Obi, Y., MD, PhD, & Tortoricci, A. R., RD. (2018). Dietary

Protein Intake and Chronic Kidney Disease. US National Library of Medicine. doi:10.1097/MCO.0000000000000342

  1. Noroqvist, C. (2017). Symptoms, causes, and treatment of chronic kidney

disease. MedicalNewsToday. Retrieved October 23, 2018, from https://www.medicalnewstoday.com/articles/172179.php.

  1. Rawal, G., & Yadav, S. (2015). Nutrition in chronic obstructive pulmonary

disease: A review. Journal of Translational Internal Medicine. Retrieved October 24, 2018.

  1. Riccio, E., Nuzzi, A. D., & Pisani, A. (2014). Nutritional treatment in chronic

kidney disease: The concept of nephroprotection. Clinical and Experimental Nephrology,19(2), 161-167. doi:10.1007/s10157-014-1041-7

  1. St. Florian, I., RD, MS. (2009). Nutrition and COPD – Dietary Considerations for

Better Breathing. Today’sDietitian,11, 2nd ser. Retrieved October 24, 2018.

 

 

 

Prompt topic: Discuss the mechanisms of action of ketogenic diets and weight-loss in adults.  Do ketogenic diets yield more desirable weight-loss compared to other diets?  Propose evidence-based strategies to overcome any pitfalls associated with ketogenic diets.

Characteristics of the ketogenic diet include decreased amounts of carbohydrates in addition to increased fat and protein consumption in the diet (Wheless, 2004). The ketogenic diet was originally developed and used for the treatment of epilepsy, especially in the case of children. However, since the early 1960’s the ketogenic diet has been used as one of the most popular weight loss diets and treatment methods for overcoming overweight or obesity (Wheless, 2004). When eaten in adequate amounts carbohydrates are typically used as the body’s major source of fuel, however, when carbohydrate intake is significantly reduced in the diet the body’s metabolism triggers what is known as ketosis. When adequate amounts of carbohydrates are consumed insulin is released allowing glucose into the cells and carbohydrate storage in the form of glycogen in the muscle and liver cells. Insulin secretion stimulates lipogenesis or the storage of fat in the body. When there is an absence or insufficient amount of carbohydrates consumed in the diet insulin secretion is reduced, ultimately leading to the reduction in the formation and storage of fat and an increase in lipolysis or the break down of fat stores (Paoli, 2013). The first few days of following the low carbohydrate, high-fat, ketogenic diet the body is breaking down glycogen stores to use for energy, although after 2-3 days of reduced carbohydrate consumption glycogen stores will become depleted and the body needs to find an alternate source of fuel to keep the body in a functional state (Paoli, 2013). The central nervous system, under normal conditions, uses glucose as its only source of fuel and when carbohydrates are insufficient it is critical that the CNS adapts to finding another source of energy. The CNS is unable to use lipids as a source of fuel and after the first 3-4 days, the body is able to adapt to the ketogenic diet with the formation of ketone bodies that ultimately take the place of glucose acting as fuel to the CNS and other tissues in the body. As fatty acids are broken down in beta-oxidation and acetyl-coA is produced in excess forming ketone bodies (Paoli, 2013). The entire process of ketogenesis occurs in the mitochondrial matrix in the liver, with the main ketone body, acetoacetate, being produced here. Ketone bodies are used in the tissues as well as the central nervous system as a major source of energy but cannot be used by the liver. The ketone bodies take the place of glucose since the insufficient carbohydrate consumption does not yield adequate energy to support the individual’s metabolic needs (Paoli, 2013). The fact that the ketogenic diet induces weight loss is a relatively well-known fact, although the exact method of how the process takes place is not completely known and is a topic of debate (Paoli, 2014). Some claims suggest that weight loss is an effect of consuming a diet that is high in fat and this promotes satiety leading to a reduced energy intake overall and throughout the day (Paoli, 2013). Additionally, the decrease in lipogenesis and increase in lipolysis aids in weight loss as fat stores are minimized decreasing total body weight (Paoli, 2014). Since insulin secretion is inhibited, and glucagon is excreted during carbohydrate depletion it is thought that gluconeogenesis potentially uses more energy increasing metabolism yielding weight loss (Paoli, 2014). Several studies have been conducted that compare weight loss results with the ketogenic diet. A study conducted by Johnston in 2006, compared the ketogenic diets low-carbohydrate, high-fat mechanism against a non-ketogenic diet consisting of low-carbohydrate intake and low-fat intake. The study results showed that both high fat and low-fat were equally effective in weight loss and improving insulin resistance (Johnston, 2006). This particular article concludes that the ketogenic diet should not be practiced long-term due to the harsh metabolic adjustments that take place when the body uses begins to use ketone bodies as its main fuel source (Johnston, 2006). However, it does offer good evidence that the weight loss seen in the ketogenic diet may be primarily due to the low carbohydrate characteristic and independent of the high-fat content. A study assessing the effect of low-fat and/or low-energy diet on weight status in adults showed that a low-fat, low-energy diet resulted in a significant decrease in weight as well as waist circumference in a 12-week intervention (Djuric, 2002). After reading several studies that have assessed the efficiency of weight loss a reduced energy, reduced-fat (specifically saturated and trans fat) diet without emphasis or depletion of any specific nutrient offers the best weight loss results and reduces the risk of adverse effects. Low-carbohydrate diets may initially offer significant weight loss results but can be very hard to maintain and are not achievable for every individual. For example, individuals with diabetes may have significant trouble attaining a ketogenic diet because of their fragile state of glucose instability. Those who are hypoglycemic would also suffer trying to follow a ketogenic diet due to their blood glucose already being considerably low. Additionally, those who have any heart condition where their serum lipid profile is already elevated would not be able to accommodate the excess fat that is prescribed in the ketogenic diet. However for the average overweight adult who does not have any underlying conditions the ketogenic diet may be exactly what is needed to initiate weight loss. The ketogenic diet may be more preferred when compared to the other diets because of its ability to reduce hunger and induce satiety. A study published in The American Journal of Clinical Nutrition stated that the ketogenic diet proves to be beneficial in weight loss and weight control as well as stabilizing blood glucose concentrations in diabetic patients. In general ketogenic diets may not be for everyone, although they have shown to have a significant outcome on weight loss in overweight and obese individuals (Krilanovich, 2007).

 

References

  1. Djuric, Z., Lababidi, S., Heilbrun, L. K., Depper, J. B., Poore, K. M., & Uhley, V.

E. (2002). Effect of Low-Fat and/or Low-Energy Diets on Anthropometric Measures in Participants of the Women’s Diet Study. Journal of the American College of Nutrition,21(1), 38-46. doi:10.1080/07315724.2002.10719192

  1. Johnston, C. S., Tjonn, S. L., Swan, P. D., White, A., Hutchins, H., & Sears, B.

(2006). Ketogenic low-carbohydrate diets have no metabolic advantage over nonketogenic low-carbohydrate diets. The American Journal of Clinical Nutrition,83(5), 1055-1061. doi:10.1093/ajcn/83.5.1055

  1. Krilanovich, N. J. (2007). Benefits of ketogenic diets. The American Journal of

Clinical Nutrition,85(1), 238-239. Retrieved October 24, 2018.

  1. Paoli, A., Rubini, A., Volek, J. S., & Grimaldi, K. A. (2014). Erratum: Beyond

weight loss: A review of the therapeutic uses of very-low-carbohydrate (ketogenic) diets. European Journal of Clinical Nutrition,68(5), 641-641. doi:10.1038/ejcn.2014.47

  1. Paoli, A. (2014). Ketogenic Diet for Obesity: Friend or Foe? International

Journal of Environmental Research and Public Health,11(2), 2092-2107. doi:10.3390/ijerph110202092

  1. Wheless, J. W. (2004). History and Origin of the Ketogenic Diet. Epilepsy and the

Ketogenic Diet,31-50. doi:10.1007/978-1-59259-808-3_2

 

 

 

 

 

 

Part II: Critically Evaluate the Research Article

Article: Caffeine Transiently Affects Food Intake at Breakfast

Title

  • The article title, Caffeine Transiently Affects Food Intake at Breakfast, reflects what was actually done in the study. Participants were randomly given various amounts of caffeine (0 mg/kg, 1 mg/kg, 3 mg/kg) thirty minutes prior to breakfast and their amount of dietary intake, as well as appetite,  was assessed (Panek-Shirley 2018). The results propose that caffeine intake has a minimal or short-lived effect on dietary intake as well as appetite, supporting the word usage of  “transiently” in the title of this article (Panek-Shirley 2018).

Abstract

  • The abstract clearly outlines the background, objective, participants, design, outcomes, statistical analysis, results and conclusion of the article in a concise and easy to follow format. The background information is slightly bleak and could possibly contain more details as to what the driving force was to conduct a study such as this one. The participants were clearly defined although how they were recruited was not mentioned in the abstract (Panek-Shirley, 2018). The study design and intervention are detailed including the time, amount and randomness of administering caffeine to the participants. The purpose of the study was to test the formulated hypothesis that caffeine intake reduces individual’s appetite sensations that ultimately leads to an overall decrease in body mass index (Panek-Shirley, 2018). Results do not directly support the hypothesis and it can be concluded that appetite was not significantly reduced due to caffeine administration and therefore nor was body weight (Panek-Shirley 2018). The abstract provided enough information for the reader understand the goals and outcomes of this study as well as entice the reader to continue reading the article (Panek-Shirley, 2018).

Introduction

  • The authors provided adequate background information on the study and how it relates to the current obesity prevalence and current need to find ways to decrease energy intake and increase physical activity leading to healthier body mass indexes’ in American’s (Panek-Shirley, 2018). The author states that there is a possible gap in the literature regarding the accuracy of if caffeine truly does reduce appetite by mentioning, “acute caffeine administration has been shown to reduce hunger in some studies, but not in others” (Panek-Shirley, 2018). Additionally,  the author mentions previous studies that have tested consuming caffeine prior to eating a meal have had varying results, some showing benefits on reduction in food intake and some showing negative results such as an increase in food intake. The author summarizes that more evidence is needed to support or decline acute effects of caffeine intake in relation to decreasing energy intake and that is one of the main goals of this article (Panek-Shirley, 2018). Caffeine intake in relation to suppressing appetite and reducing energy intake depends on multiple factors such as amount consumed, concentration, the timing of peak, and the weight of the individual. Studies were not included that offered participants a set amount of calories. Instead, individuals were offered a full breakfast buffet allowing an unlimited caloric intake, and participants were likely to eat more as compared to a single meal that contained a set calorie amount (Panek-Shirley, 2018). This might suggest why energy intake did not significantly decrease after caffeine intake, as participants are likely to eat more when offered an unlimited amount of food. The study design, a complete double-blind placebo-controlled, randomized, crossover study was used and is appropriate for testing the hypothesis. Three hypotheses were tested including “1. Caffeine intake directly decreases energy intake in free-living and laboratory settings, 2. Caffeine affects food consumption by decreasing appetite and, 3. The outcomes of caffeine intake on appetite differ related to body mass index” (Panek-Shirley, 2018).

Materials and Methods

  • The article was formulated using a randomized, double-blind, placebo-controlled, crossover study design (Panek-Shirley, 2018). Repeated measures of caffeine intake ranging from 0, 1, 3 mg/kg were deployed at random to patients and each individual ate breakfast in the laboratory at the same time to minimize variability. Crossover studies have several strengths. An important strength to this study is that the hypothesis can be tested rather than generateded. They also enforce equality; meaning at all subjects will receive the same treatment. In this study, a particular strength is that the interventions are the exact same for each patient, limiting variability (Panek-Shirley, 2018). The study design is further strengthened because it is randomized and double-blind giving it the strongest possible basis for reducing any interference regarding treatment effects. Randomized, controlled, double-blind studies are considered the “gold standard” for conducting an experiment. A disadvantage of the crossover design, that is apparent in this particular study, is the fact that the participants must be enrolled in the study for a longer period of time compared to other studies such as cross-sectional. This study took place over 3 consecutive weeks and required patients to follow-up 2-7 days after their final breakfast (Panket-Shirley, 2018). This prolonged time period can be draining to the participant and may result in an increased amount of dropouts, which will consequently skew the results. A control group was present and all participants at some point received a placebo in the form of a bitter tastant that was used to stimulate the awareness of taste (Panek-Shirley, 2018). This strengthened the study as it ensured that each participant received equal treatment and results could be based on the evidence present and not any conflicting factors. The use of the placebo on each patient was appropriate and ensured that each participate got equal treatment. The study included adults who were eighteen to fifty years in age, of which 42% were males (Panek-Shirley, 2018). There were a higher percentage of women than men in this study and because women have a higher amount of body fat using BMI as an outcome variable may not be accurate. The broad age range of ages from 18-50 years old strengthens the study because it can offer more generalized findings as compared to if the study only focused on 18-year-olds for example. Since the study focused only on overweight and obese individuals, the results cannot be generalized to the general public, compared to if they also included individuals with a normal BMI as well. Fifty adults who were between the ages of eighteen to fifty years of age were included in this study. This is a substantial amount of participants that allows for appropriate statistical power. The study consisted of both males (42%) and females (58%) who identified as either Asian American or Caucasian (Panket-Shirley, 2018). The majority of participants reported to earning an income of 0-49,999 dollars per year (Panket-Shirley, 2018). Exclusion criteria included participants who had previously experienced opposite effects of caffeine, had no previous experience with caffeine at all, and those who had engaged in smoking tobacco products in the last six months (Panket-Shirley, 2018). Smoking is also thought to reduce energy intake and could be a confounding variable so smokers were excluded from the study for this reason. The treatment was randomized although, the participants were not completely randomized because they were recruited from flyers as well as Nutrition and Health Research Laboratory database and recruitment emails. The State University of New York University at Buffalo Institutional Review Board permitted the study procedures and all individuals included in the study were provided with written knowledgeable consent to participate in the study. The study did not seem to have any ethical concerns and seemed to be morally well conducted. There was a clear statement stating that the International Review Board (IRB) approved this study. This is significant because this current study used human participants and the IRB ensures that participants will be treated ethically appropriate and their rights will be fully protected. The IRB acts in accordance with the Food and Drug Association, and have the complete and total right to approve or disapprove the research if it doesn’t meet ethical expectations. The methods section of the article was very well organized and contained all the essential data that would be needed for another team of researchers to repeat this study. The methods section was broken up into sections that included the study design, baseline characteristics, caffeine and physical activity abstinence, caffeine preparation and administration, laboratory-buffet breakfast, appetite and mood, free-living intake, appetite and satiety, ecological momentary assessment, dietary analysis, and lastly power and statistical analysis (Panket-Shirley, 2018). Each subsection of the methods section elaborated on how numerical values were measured and summarized to reach the end conclusion of the article. The randomized, double-blind, placebo-controlled, crossover study design was reliable and valid and superior to several other study designs that could have been used. Under baseline characteristics, the author mentions that BMI was used to formulate dose of caffeine. This may not be considered accurate or valid because it is known that there is a positive association between increased adiposity and caffeine concentration, and this may have altered eating patterns and the desired effects may have occurred after leaving the facility (Panket-Shirley, 2018). Also, caffeine is known to have a long half-life and the peak of caffeine concentration may have occurred long after the participants left the facility. Additionally, the study relied on subjective, self-reporting measurements to verify that participants were not consuming caffeine the day before they came to the lab. Though laboratory intake was controlled and measured objectively, free-living intake relied on truthfulness and accuracy of self-report (Panket-Shirley, 2018). The results of caffeine on energy consumption were examined using statistical analysis covariance (ANCOVA). ANCOVA was appropriate because it was able to examine the influence of the independent variable (BMI, caffeine treatment and normal caffeine consumption) on the dependent variable (caffeine dose). The outcome variables were clearly defined to be total and macronutrient intake. Repeated measurements of appetite levels, ecological momentary assessment, and behavioral checklist data were used to ensure accuracy to the study results. A confounding variable becomes apparent when an outside influence affects the independent and dependent variables and therefore altering the results. The study was strengthened with the use of the control group that was given the placebo. In the case that the caffeine intake did have a significant effect on energy intake, the control group should show no obvious decrease in energy intake since they did not receive any caffeine reinforcing the results of the study. The p-value or the statistical probability level is descriptive of the probability of the occurrence that something will take place. Participant characteristic data were considered significant if P<0.05. Panket-Shirley mentions that  “data were considered to be significant if P<0.017. To estimate clinical significance, the effect size was calculated using mean and SDs with alpha=.05 and beta=.80. Effect sizes 0.1 to .29 were considered small, 0.3-0.5 moderate, and >0.5 large” (Panket-Shirley, 2018). All terms and acronyms that were used in the article were clearly defined.

Results

  • The results are organized in a logical sequence that follows the same order as the methods. The results are listed starting with participant characteristics, then the effects of caffeine on laboratory energy consumption and free-living energy consumption, followed by appetite sensations in laboratory participants as well as free-living participants, ending with the effects of caffeine on the behavioral checklist (Panket-Shirley, 2018). Demographics were presented in table one of the research article. They were adequately listed in a table format that allowed the authors to include a sufficient amount of important information on the participants in an easy to read, longitudinal format. Participant demographics included gender, age, BMI, weight (Kg), waist (cm), waist-to-hip ratio, daily caffeine intake (mg/day), a three-factor questionnaire, binge eating scale, menstrual cycle phase, education, annual income, and ethnicity (Panket-Shirley, 2018). The demographics that were collected were necessary to provide additional information on the participants. A total of 5 tables were included in the article, although there were graphics present. However, each table is needed and provides additional information of the patients in an easy to read format and helps to clarify the overall findings (Panket-Shirley, 2018). Table two shows the breakfast items that were offered to the participants at the breakfast buffet 30 minutes after caffeine treatment. Table three shows the mean and total energy intake at the breakfast buffet 30 minutes after the caffeine administration. Table four shows appetite perceptions listed in approximate ranges pre, mid and post caffeine treatment (Panket-Shirley, 2018). Lastly, table five shows the behavioral checklist ratings which included feelings of impatience, mood swings and sadness pre, mid and post caffeine intake. These five tables are clearly presented and help to confirm the results of the study and show the data in a linear format that may be of more use to many readers as compared to reading statistics in a paragraph format. The tables could stand alone if all five were included because each one of the five depicts a different aspect of the research design (Panket-Shirley, 2018).

Discussion

  • The study objective, to test whether caffeine intake reduces energy intake by reducing hunger sensations, was met by conducting a 3- week trial with over-weight and obese participants who were administered various concentrations prior to meals. Data were collected pre, mid, post eating breakfast to assess hunger level, and emotions that the participants were feeling. The authors stated that insufficient studies have examined the influence of acute caffeine consumption on laboratory intake and the ones that have reported ambiguous findings (Panket-Shirley, 2018). Previous studies are equivocal, while some show there are benefits of caffeine on energy intake and some show there are not. Factors such as the timing of caffeine administration, amount of caffeine intake, type of caffeine, type and amount of food offered to the participants all come into play when comparing different studies. The discussion was overly speculative as the authors discussed their current findings, compared them to previous research findings, and explained several limitations and strengths to the study. The limitations of the study were clearly stated (Panket-Shirley, 2018). One major limitation of the study was the fact that the study did not have an objective way to measure abstinence from caffeine prior to treatment and the authors relied on the validity of the participant’s self-reports. Additionally, the fact that the participants knew that caffeine doses were adjusted per body weight and there is a positive association between increased adiposity and caffeine perceptions and eating behavior could have been adjusted and may not reflect their true eating habits (Panket-Shirley, 2018). It is important and ethically correct that the authors clearly state limitations of the study to inform any readers or researchers of the potential flaws in the current research. Conclusions were drawn that support the results of the study appropriately. Results showed that no significant caffeine treatment outcomes or relations with BMI on total energy consumption or macronutrient consumption exist. The authors concluded that the study provides no indication to promote the use of caffeine as a hunger suppressant (Panket-Shirley, 2018).

References/ Acknowledgments

  • The references are cited appropriately in JAND format. A total of 53 references were used in this article. Source of founding were clearly stated for L.M. Panek-Shirley and J.L.Temple was provided by RO1 DA030386 and from the State of New York (Panket-Shirley, 2018). It is important to include the foundations of funding because grants often include precise language requiring the author to mention the grant in any articles that are published that directly uses the grant itself. Additionally, the law often obliges listing bases of founding at the end of the article, and without it, the article may not be considered ethically appropriate (Panket-Shirley, 2018). The article states that there were no potential conflicts of interest reported by the authors. If a conflict of interest is present it could suggest a potential bias of the author and this could skew the overall results of the experiment. L.M. Panek-Shirley is an assistant professor and C. DeNysschen is a professor in the Department of Health, Nutrition and Dietetics, SUNY Buffalo State, Buffalo, NY.E (Panket-Shirley, 2018).

Reference

Panek-Shirley LM, DeNysschen C, O’Brien E, Temple JL. Caffeine Transiently Affects Food Intake at Breakfast. J Acad Nutr Diet. 2018. 118(10): 1832-1843.  doi:  https://doi.org/10.1016/j.jand.2018.05.015

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