- Does the title clearly state the problem, variables, and population under study? Yes, it does. The title of the research is “Food Availability as a Determinant of Weight Gain among Renal Transplant Recipients.” Here, weight gain is the problem, food availability the variable and renal transplant recipients are the population under study.
- Does the abstract clearly and concisely summarize the main features of the report? Yes. The abstract presents the problem (weight gain among renal transplant patients), the variables (availability of food) and its effect on patients (body mass index change), as well as the scope in the area of patients under study (Memphis, Tennessee).
- Is the problem statement clear? Yes. Bloodworth et al. (2014) concisely present the problem statement indicating the commonality and dangers of weight gain among renal transplant patients. They additionally state, “In the current study, we explored how food availability affected BMI change during the first year after renal transplant, in a largely low-income cohort at a Memphis, TN transplant center” (Bloodworth et al., 2014, p. 254).
- Does the investigator identify key research questions and variables to be examined? No. The investigators do not provide key research questions but instead present hypotheses, although food availability is presented as a dependent variable.
- Is the significant (importance) of the study discussed? No. The authors do not discuss the significance of the study. However, the identify the gaps in research, particularly the role of food availability in weight gain among the study population. The authors state, “Renal transplant recipients typically experience more weight gain than in the general population, and the role of food availability in weight gain in this clinical population has not been explored” (Bloodworth et al., 2014, p. 254). The statement ideally presents the gap that authors wish to fill, even without discussing the importance of the study.
- Yes. The study identified the availability of food, particularly fast food chains and convenience stores, as the main contributors to weight gain among the population under study. Given the risks of weight gain for both the clinical population and general population, the study significant data to help clinicians advise the study population on healthy eating, which then solves the problem of weight gain in the study population.
- Yes. The authors indicate that they explored food availability and its effects on BMI change on renal transplant patients in their first year after the operation.
- Yes. The authors explored the significance of food availability and its effect on weight gain among renal transplant patients. In doing the investigation, the researchers hoped to identify the contribution of food availability to weight gain, given that most renal transplant patients experience weight gain and the dangers of excessive weight gain to the patients and the larger population.
- No. The authors did not explicitly state the research questions but instead provide hypotheses.
- Yes. According to Farrugia et al. (2010) hypotheses usually come from research questions. Additionally, the authors (Farrugia et al., 2010) posit that hypothesis are research questions written in statement form. The two hypotheses presented by the researchers, therefore, are enough to guide their investigation even without research questions.
- Yes. The authors discuss how weight gain is a common occurrence among renal transplant patients. Using research and literature they identify contributing factors to the weight gain including race, gender, age, and socioeconomic status. The review also identifies pharmacological and behavioral risks of weight gain for the study population, leading to the gap in the study that their research set out to fill.
- Yes. In their literature review, the authors explored research on the relationship between unhealthy food outlets and increased obesity. Additionally, they explored the negative relationship between grocery stores and obesity, in addition to the relationship between neighborhood food availability and body weight. They further delved into body weight gain among renal transplant recipients, eventually identifying the gap of the relationship between food availability and weight gain among the study population.
- Yes. The authors indicate that while previous studies had explored easy access to fast foods and weight gain, behavioral risk factors among the study population and weight gain, none had explored the relationship between food availability and weight gain among the study population (Bloodworth et al., 2014), a gap that their study set out to fill.
- No. From the literature review, the study jumps right to the research design, leaving no theories to explain the phenomenon under study as is the purpose of the theoretical framework.
- No. The absence of the theoretical framework from which assumptions are derived means there is no possibility of assumptions in the study.
- Yes. The authors present two hypotheses. One of the hypotheses is “greater availability of fast food restaurants and convenience stores and larger ratios of fast food restaurants and convenience stores to total food sources would be associated with BMI increase” (Bloodworth et al., 2014, p. 254). The second hypothesis states “lower availability of grocery stores and a lower ratio of grocery stores to total food sources would be associated with BMI
increase” (Bloodworth et al., 2014, p. 254).
- Yes. The two hypotheses are clearly stated and are testable. For instance, it is possible to test the greater availability of fast food restaurants and BMI increase for people around fast food restaurants. Similarly, it is possible to compare BMIs for individuals around a wide availability of grocery with those at lower grocery stores availability.
- No. While the study has two hypotheses, there is no stated theoretical/conceptual framework.
- Yes. Food availability and BMI are the variables. However, they have not been operationally defined as either dependent or independent. It is however likely that food availability is dependent on BMI increase.
- Yes. The authors state that their study is an exploratory study using a retrospective cohort design (Bloodworth et al., 2014).
- Yes. Klebanoff and Snowden (2018) posit that retrospective cohort studies look back into archived reports to determine risk between different people. By using the design, the authors were able to test their hypotheses, making the design appropriate for the study.
- The research was a retrospective cohort design and not experimental. There was, therefore, no control for threats to internal and external validity.
- No experimental design was used, thus there was no need for appropriate assignment of subjects to experimental and control groups.
- To control for extraneous variables the authors limited their scope to transplant recipients between January 2004 and July 2010, with residence in Shelby County. The starting date was significant as it marked the beginning of electronic recording at Methodist University Transplant Institute (MUTI), whose transplant data the study used. The use of electronic records meant that the authors could easily verify any outliers and retrieve any missing data.
- Yes. Bloodworth et al., (2014) state that the participants/subjects were renal transplant recipients, who had received the transplant between January 1, 2004, and July 31, 2010, and who resided in Shelby country. The study used clustered sampling, taking only subjects who resided in Shelby County.
- Yes. The authors did not use a power analysis, however, they targeted 484 individuals, but eliminated 172 who resided outside Shelby County. Further, they eliminated Hispanic, Asians, and Native Hawaii/Pacific Islanders due to their small sample sizes.
- No. There was no recipient contact or exposure to substantial risk. The study only used hospital records. Moreover, the study has not mentioned any of the patient’s names.
- No. According to Hassan, Schattner, and Mazza (2006), a pilot study is a small study whose purpose is to test the research in preparation for the full-scale research. However, the retrospective design of the research, there was no need for a pilot study.
- Yes. According to Bloodworth et al., (2014), the study used clinical and sociodemographic data that included race, gender, date of transplant, and age at the time of transplant among other data from a data specialist at MUTI using the Organ Procurement and Transplantation Network Database.
- No. Data for the study was conducted from a single point using a single individual for data retrieval from the database. Interrater reliability was therefore of no significance.
- The authors presented their data in sectional headings including sample characteristics, food sources, and association of food availability with BMI change. Both narrative and visual representation of data were used. The author largely used tables for the visual representation of the data.
- Yes. For the most part, the authors used standard deviation and standard error in measuring the relationship between distance in miles for patients’ residence and types of food sources and the overall change in their BMI. They also used multiple linear regression analysis in determining fast food restaurant availability and change in BMI.
- Yes. The authors’ interest was on the availability of food sources within the participants’ residence and change in the BMI. Standard deviation and standard error as statistical methods were therefore appropriate in handling the level of measurement, the small sample size, the retrospective cohort design, and the two hypotheses presented.
- Yes. There are three tables presenting results for restaurant availability and change in BMI, convenience store availability as a predictor in the change in BMI, and grocery store availability as a predictor of change in BMI, essentially covering the two hypotheses presented by the authors.
- Yes. The tables provide an in-depth illustration of the results presenting not only the number of convenience fast food restaurants, convenience stores, and grocery stores within a 3-mile radius of the participants but also the level, as predictors, of the three food sources for change in BMI among the participants.
- Yes. The authors present a contrast in the results of the study with those of previous studies focusing on the general population. Additionally, they also find congruence in the result with other studies, particularly those that looked into the relationship between grocery store proximity with BMI change.
- Yes. The authors mentioned the results for the three food sources types as being consistent with results in the general population. Convenience stores, fast food restaurants, and grocery stores are all in the hypotheses, while the mention of result in the general population point to reference of literature used in the literature review for the study.
- No. The study findings focused on renal transplant patients. The fact that the sample size was small makes it imprudent to make any generalizations within the scope of the findings.
- No. The authors do not discuss the implications, mostly decrying the small size of the sample used.
- Yes. Weight gain is one of the major health issues nurses deal with among their patients and in the general population. It is good to know the contributing factors such as proximity to food sources. Knowledge of the contributing factors is important in advising remedial actions on weight gain.
- No. The study found an association between the proximity of grocery stores and BMI increase. The two variables are out of the scope of nursing practice. Nurses, therefore, have nothing to implement based on the findings of the study.
- Yes. The study did not include any risk to the participants or researchers. It has however presented some benefit, especially in finding the relation between grocery story proximity and BMI change. Such a finding is important in explaining different characteristics and phenomena, as well as the relationship between weight gain and food source proximity.
- Yes. The researchers point out the small size of the sample size (299) and state that a larger sample size would be more appropriate in detecting statistically significant effects. The researchers also point out that the participants were only from a single transplant center and lived in the same country essentially reducing sample variability. They also indicate that limited finding made it impossible for them to get data from food sources for more than a year that they used.
Bloodworth, R., F. et al. (2014). Food availability as a determinant of weight gain among renal transplant recipients. Research in Nursing & Health, 37, 253-259.
Farrugia, P. et al. (2010). Research questions, hypotheses and objectives. Canadian Journal of Surgery, 53(4), 278-281. Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2912019/.
Hassan, Z., A., Schattner, P., & Mazza, D. (2006). Doing a pilot study: Why is it essential? Malaysian Family Physician, 1(2-3), 70-73. Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4453116/.
Klebanoff, M., A. & Snowden, J., M. (2018). Historical (retrospective) cohort studies and other epidemiologic study designs in perinatal research. American Journal of Obstetrics & Gynecology, 219(5), 447-450.