NUTRITION ESSSAY

 

ASSIGNMENT INSTRUCTIONS:

Write a short (500 words) essay that answers the following question:

Based the studies described in Appendix 1, how convincing is the scientific evidence that nuts decrease the risk of cardiovascular disease or the risk of death from cardiovascular disease? IMPORTANT: There is no “right” answer to this question.  Interpretations, of how convincing the evidence is, can vary e.g. very convincing, somewhat convincing, not very convincing.  What is important is to demonstrate, in making your assessment of the evidence, that you understand the strengths and limitations of the scientific studies presented, can appropriately interpret the studies’ results, and provide a reasonable defense of your position.

 

To complete the assignment

  • You need only use the information found in the abstracts in Appendix 1 (the abstracts-an abstract is a short summary of a scientific study), Appendix 2 and the lecture material on nutritional research. You are NOT required or expected to use any additional sources.
  • You must, however, include a discussion of ALL abstracts, found in Appendix 1, in your essay.
  • Your essay should include a brief introductory paragraph (about 2 sentences), a body (typically consisting of several short paragraphs) and a conclusion (about 2 sentences).
  • You are expected to paraphrase your sources (i.e. the abstracts) properly, and include in-text citations and a bibliography, as described in the document: SCIENCE_WRITING_ Notes2018Update that is posted with the Science Writing Quiz and the How to cite references document, posted with this assignment.
  • Information that you might use to support your argument that comes from the Appendix 2 or the lecture material on nutritional research can be considered common knowledge and does not require citation.
  • For writing tips and information on how the assignment will be graded read Appendix 3 – 5.
  • For info on bibliographic referencing see Appendix 4. Be sure to follow the format correctly. It is slightly different from the format used in the abstracts in Appendix 1.

 

Word limit: 500 (INCLUDING in-text citations, but excluding the bibliography).

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Getting Organized:

 

There is a lot of information in this handout. As shown in the graphic below, it is divided into several appendices, to help you successfully organize and complete your assignment.  Other sources of useful

 

Questions about the assignment:

If you have questions about the assignment you can post them on the course discussion board (a special forum has been set up for assignment questions). Also Dr. Gurfinkel will be available for virtual office offices.  Check Quercus for information on how to request an appointment.

                

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Appendix 1:

Use the abstracts provided below to write your essay.  All of these abstracts are obtained from the PubMed database and should be cited as PubMed abstracts. See Appendix 3 on how to format in-text citations and a bibliography, which is different from the formatting used in the abstracts below.  Please note that, for the purposes of this assignment and for clarity, modifications and additions have been made to the original content of these abstracts. For example, abstracts do not typically contain tables, but they are included here to help you learn how to interpret data. This assignment deals with cardiovascular disease (CVD).  The description below will assist you with the terminology that you will encounter in the abstracts and help you to understand some of the risk factors for cardiovascular disease that are described in the abstracts.

 

Definition of cardiovascular disease, coronary heart disease, and stroke.

The slide below illustrates the definition of CVD, which effects various parts of the body, by blocking blood vessels due to the development of atherosclerosis (described below).  When these blockages take

place in the heart, the terms coronary heart disease (CHD), ischemic heart disease (IHD) and/or coronary artery disease (CAD) are used to describe a variety of conditions of the heart, that develop as a result of these blockages.  The most common of these conditions is heart attack, which is also referred to as myocardial infarction.  When the blockage of the blood vessel occurs in the brain, stroke or ischemic stroke occurs.

Cardiovascular disease refers to disease affecting

both the heart and the brain.

 

Risk factors of CVD.

Atherosclerosis: Most CVD has its origin in the development of atherosclerosis, shown left. A low-density

lipoprotein (LDL)(red arrow), a particle high in cholesterol and also containing triglycerides and protein, that normally circulates in the blood, moves from the blood into the walls of the blood vessels and sets off a series of reactions that include the formation of fatty streaks (shown left).  These fatty streaks eventually form plaques that can block the blood vessel or promote the formation of blood clots that can also block blood vessels. These blockages, if they occur in the arteries of the heart or brain can result in heart attack or stroke.

 

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Lipoproteins and blood lipids: As noted above, a lipoprotein called the low-density lipoprotein, rich in cholesterol, plays a role in the development of CVD.  The amount of cholesterol found in these particles (shown left) is measured and LDL-cholesterol is often referred to as “bad” cholesterol, because of its link to atherosclerosis.  A second important particle is the high-density lipoprotein (HDL).  HDLs function to remove cholesterol from the blood, and so HDLcholesterol, i.e. cholesterol in the HDL particle, is often referred to as “good” cholesterol, because it does not contribute to disease.  In addition to LDL and HDL, there are other lipoproteins that circulate in the blood.  These lipoproteins contain both cholesterol and triglycerides and so total cholesterol and total triglycerides are often measured in the blood, as these blood lipids are associated with

cardiovascular disease risk.  Studies have also shown that the ratio of total cholesterol to HDL-C (i.e. TC/HDL-C) is also a good predictor of CVD risk.  The relationship between blood lipids, that are described in the abstracts, and disease risk is shown in the table below:

 

CVD risk increases with increases in:
•       LDL-cholesterol

•       Total cholesterol

•       TC/HDL-C

CVD risk decreases with increases in:
        •    HDL cholesterol

 

Other risk factors for CVD:  In addition to blood lipids, other risk factors for CVD exist:  

Blood pressure: Blood pressure is measured as two numbers: systolic pressure (pressure when the heart contracts) and diastolic pressure (pressure when the heart relaxes), using the units mmHg. Increases in blood pressure at associated with increases in CVD.

 

Tree Nuts vs Peanuts

In this assignment you will be reading about the relationship between cardiovascular disease and nut consumption.  Nut consumption is usually divided into two categories: tree nuts which include almonds, Brazil nuts, cashews, hazelnuts, macadamia nuts, pecans, pine nuts, pistachio nuts and walnuts. Peanuts are not tree nuts, but legumes that grow in the ground. The nutrient composition of peanuts is similar to that of tree nuts and are therefore often included in studies that look at the health benefits of nut intake. The effects of peanut butter are also considered in some studies.

 

 

 

 

 

 

 

 

 

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Below are the abstracts that are required for this essay:

 

Ghadimi-Nouran M, Kimiagar M, Abadi A, Mirzazadeh M, Harrison G. Peanut consumption and cardiovascular risk. Public Health Nutr. 2010:13(10):1581-6. doi: 10.1017/S1368980009992837. Epub  2009 Dec 22.

 

OBJECTIVE: We evaluated the effects of peanut consumption on lipid profiles and other risk factors for cardiovascular disease.

 

DESIGN: Randomized crossover clinical trial conducted in Tehran, Iran.

 

SETTING: Participants were randomly assigned to two groups. One group was asked to consume peanuts, roasted and lightly-salted, (about 77 g) with their habitual diet for 4 weeks (treatment), while the second group consumed their habitual diet (control).  After a wash-out period, groups were crossed over, so that those that started with the control diet switched to the treatment, and those that started with the treatment, next consumed their habitual diet.

 

SUBJECTS: Fifty-four hypercholesterolemic, but otherwise healthy, men age 25 to 65, (mean age: 43 years).

 

RESULTS: The results below show the effect of the peanut supplementation as indicated by the formula (EP – BP) – (EH – BH), where EP is the value at the end of the peanut-supplemented diet period and BP is the value at the beginning of the peanut-supplemented diet period. EH is the value at the end of the habitual diet period and BH is the value at the beginning of the habitual diet period. The P values shown indicate whether there is a statistically significant difference between the peanut treatment and the habitual diet.

 

  Peanut Effect

(EP – BP) – (EH – BH) +/- std error

P value of peanut effect
Body weight (kg) 0.2 +/- 0.2 0.37
Blood pressure:    
        •    Systolic (mmHg) 1.9 +/- 2.7 0.5
        •    Diastolic (mmHg) -2.5 +/- 1.9 0.19
Blood cholesterol    
        •    Total Cholesterol (TC) 10.1 +/-6.7 0.14
        •       LDL-cholesterol (LDL-C) 7.0 +/- 4.9 0.16
        •     HDL-cholesterol (HDL-C) 6.1 +/- 1.5 0.001
        •    TC/HDL-C -1.0 +/- 0.3 0.001

 

 

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Guasch-Ferré M, Liu X, Malik VS, Sun Q, Willett WC, Manson JE, Rexrode KM, Li Y, Hu FB, Bhupathiraju SN. Nut Consumption and Risk of Cardiovascular Disease. J Am Coll Cardiol. 2017 Nov 14;70(20):25192532. doi: 10.1016/j.jacc.2017.09.035.

 

BACKGROUND: The associations between specific types of nuts, specifically peanuts and walnuts, and cardiovascular disease remain unclear.

OBJECTIVES: The authors sought to analyze the associations between the intake of total and specific types of nuts and the incidence of cardiovascular disease, coronary heart disease, and stroke risk.

 

METHODS: The authors pooled the data from three cohorts from the United States:

  • 76,364 women, age 30 to 55 years at baseline, from the Nurses’ Health Study (duration: 1980 to 2012)
  • 92,946 women, age 25 to 42 at baseline, from the Nurses’ Health Study II (duration:1991 to 2013) and
  • 41,526 men from the Health Professionals Follow-Up Study (duration: 1986 to 2012), age 40 to 75 years at baseline).

All subjects were free of cancer, heart disease, and stroke at baseline. Nut consumption was assessed using food frequency questionnaires at baseline and was updated every 4 years, during the 22 to 32 years of follow-up for each respective cohort.

 

RESULTS:

The associations between total nut consumption and the risk of developing various diseases are shown below. Relative risks have been adjusted for the following confounders: age, body-mass index, physical activity, smoking status, multivitamin use, history of diabetes, hypertension, hypercholesterolemia, total energy intake, alcohol, red or processed meat intake, vegetable and fruit intake, menopausal status (women).

 

  Relative risk (95% Confidence interval)
Frequency of Nut Consumption: Cardiovascular Disease Coronary Heart Disease Stroke
Never or almost never 1 1 1
Less than once per week 0.91 (0.86 – 0.95) 0.88 (0.83 – 0.94) 0.95 (0.88 -1.03)
Once per week 0.90 (0.85 – 0.95) 0.83 (0.78 – 0.90) 1.01 (0.92 – 1.10)
Two to four times per week 0.86 (0.81 – 0.91) 0.82 (0.76 – 0.88) 0.95 (0.87 – 1.04)
Five or more times per week 0.86 (0.79 – 0.93) 0.80 (0.72 – 0.89) 0.98 (0.86 – 1.13)
P for trend 0.0002 0.0001 0.88

 

The associations between specific nuts and cardiovascular disease is shown below:

 

Frequency of Nut Consumption: Relative Risk for Cardiovascular Disease (95% Confidence Interval)
  Peanuts Tree nuts Walnuts Peanut Butter
Never or almost never 1 1 1 1
Less than once per week 0.92 (0.88 – 0.95) 0.95 (0.91 – 0.98) 0.95 (0.89 – 1.02) 0.98 (0.93 – 1.02)
Once per week 0.94 (0.88 – 1.00) 0.96 (0.90 – 1.03)  

0.81 (0.71-0.92)

1.01 (0.96 – 1.07)
Two to four times per week 0.87 (0.82 – 0.93) 0.85 (0.79 – 0.91) 0.99 (0.94 – 1.04)
P for trend 0.0002 0.002 0.001 0.74

 

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Luu HN, Blot WJ, Xiang YB, Cai H, Hargreaves MK, Li H, Yang G, Signorello L, Gao YT, Zheng W, Shu XO. Prospective evaluation of the association of nut/peanut consumption with total and cause-specific mortality. JAMA Intern Med. 2015;175(5):755-66. doi: 10.1001/jamainternmed.2014.8347.

 

IMPORTANCE: High intake of nuts has been linked to a reduced risk of mortality, especially of cardiovascular disease (CVD). Previous studies, however, were primarily conducted among people of European descent, particularly those of high socioeconomic status.

OBJECTIVE: To examine the association of nut consumption with CVD mortality in Americans of African and European descent who were predominantly of low socioeconomic status (SES) and in Chinese individuals in Shanghai, China.

DESIGN, SETTING, AND PARTICIPANTS: Three large cohorts were evaluated:

  • 71,764 US residents of African (67%) and European (33%) descent, age 40 to 79 years at baseline and 39% male, primarily of low SES, who were participants in the Southern Community Cohort Study (SCCS) in the southeastern United States (duration: March 2002 to September 2009),
  • 73,142 participants in the Shanghai Women’s Health Study (SWHS) (duration: December 1996 to May 2000) and
  • 61,123 participants in the Shanghai Men’s Health Study (SMHS) (duration: January 2002 to September 2006) in Shanghai, China

 

Nut consumption in the SCCS and the SMHS/SWHS was assessed using validated food frequency questionnaires. The FFQ was not repeated for any of the cohorts after baseline. For the SCCS, participants were asked to assess their “peanuts and other nuts” consumption.  Participants were also asked to separately assess their peanut butter intake. Analysis was conducted on the effect of total nut consumption (i.e. peanuts and others) and peanut butter consumption separately and combined. No difference was observed so the data presented here are the combined peanut butter and “peanuts and others” data. About 50% of nut intake came from peanuts or peanut butter. For the SMHS and SWHS tree nut consumption was very low, so the data shown here, for these two cohorts, represent peanut consumption only.

The participants were cancer-free at baseline.  Analysis of data either including or excluding participants with metabolic conditions such as hypertension, diabetes or a history of heart disease, yielded similar conclusions, so the data shown here includes participants with metabolic conditions.

 

RESULTS: Hazard Ratios shown below were adjusted for the following confounders: age, sex, education, occupation, income, martial status, smoking status, alcohol consumption, body mass index, physical activity, vitamin supplement use, metabolic conditions, total energy intake, red meat intake, chicken intake, seafood intake, vegetable intake, fruit intake.

 

  Mortality from Cardiovascular Disease: Hazard ratio (95% confidence interval)
Quintiles of Nut Intake: SCCS-African SCCS-European SMHS & SWHS-Asian
1-lowest intake 1 1 1
2 0.85 (0.72 – 1.00) 0.80 (0.61 – 1.06) 0.82 (0.72 – 0.93)
3 0.82 (0.68 – 0.99) 0.74 (0.56 – 0.97) 0.75 (0.67 – 0.84)
4 0.81 (0.68 – 0.97) 0.66 (0.49 – 0.87) 0.69 (0.62 – 0.77)
5-highest intake 0.77 (0.63 – 0.92) 0.62 (0.46 – 0.84) 0.76 (0.67 – 0.85)
P for trend 0.03 0.02 <0.001

 

Tables continue next  page …

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  Mortality from Ischemic Heart Disease: Hazard ratio (95% confidence interval)
Quintiles of Nut Intake: SCCS-African SCCS-European SMHS & SWHS-Asian
1-lowest intake 1 1 1
2 0.67 (0.51 – 0.88) 0.85 (0.59 – 1.24) 0.93 (0.72 – 1.20)
3 0.95 (0.72 – 1.25) 0.73 (0.50 – 1.06) 0.76 (0.60 – 0.97)
4 0.74 (0.55 – 0.98) 0.65 (0.44 – 0.97) 0.75 (0.60 – 0.94)
5-highest intake 0.62 (0.45 – 0.85) 0.60 (0.39 – 0.92) 0.70 (0.54 – 0.89)
P for trend 0.01 0.007 0.001

 

  Mortality from Ischemic Stroke: Hazard ratio (95% confidence interval)
Quintiles of Nut Intake: SCCS-African SCCS-European SMHS & SWHS-Asian
1-lowest intake 1 1 1
2 0.89 (0.49 – 1.62) 0.39 (0.10 – 1.55) 0.89 (0.68 – 1.15)
3 0.72 (0.35 – 1.46) 0.38 (0.10 – 1.46) 0.79 (0.62 – 1.01)
4 0.85 (0.44 – 1.64) 0.43 (0.12 – 1.54) 0.67 (0.52 – 0.85)
5-highest intake 0.89 (0.45 – 1.74) 0.47 (0.12 – 1.76) 0.77 (0.60 – 1.00)
P for trend 0.35 0.38 0.003

 

                

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Torabian S, Haddad E, Cordero-MacIntyre Z, Tanzman J, Fernandez ML, Sabate J.

Long-term walnut supplementation without dietary advice induces favorable serum lipid changes in free-living individuals. Eur J Clin Nutr. 2010;64(3):274-9. doi: 10.1038/ejcn.2009.152.

 

BACKGROUND/OBJECTIVES: Walnuts have been shown to reduce serum lipids in short-term wellcontrolled feeding trials. Little information exists on the effect and sustainability of walnut consumption for longer duration in a free-living situation.

 

SUBJECTS/METHODS: A randomized crossover design in which 87 healthy subjects, 49 females and 38 males, from Southern California, with normal to moderate high plasma total cholesterol were initially assigned to eat walnuts along with their habitual diet or their habitual (control) diet for a 6-month period, then switched to the alternate dietary intervention for a second 6-month period.

 

RESULTS: The results of blood lipid measurements are shown below:

 

Blood Lipids

 

(Walnut effect) – (Control effect)

(mmol/L) +/- std deviation

P-value

Walnut diet compared to control diet

Total cholesterol -0.18 +/- 0.07 0.01
LDL cholesterol -0.16 +/- 0.09 0.06
HDL cholesterol -0.02 +/- 0.05 0.72

 

Researchers also examined whether walnuts had a greater cholesterol-lowering effects for those subjects with the highest cholesterol levels at the start of the study (the 80th percentile).

 

 

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Appendix 2: Research Study Design and the Interpretation of Results

This appendix provides background material required to complete your essay assignment.  It will describe the purpose of the assignment, important concepts in nutritional research study design, and the interpretation of study results and statistical analysis that you will need to know, to complete the assignment. There is a high degree of overlap between this Appendix and the recorded lecture material on nutrition research (week 3).

Purpose of the Assignment

The purpose of this essay is to simulate, in a much shorter and more simplified manner, the process of reviewing the scientific literature on an important topic in nutrition and making an assessment of the scientific literature. This assessment is the content of your essay.

The four steps in a literature review are listed below:

❶Formulate a research question.

❷Search the literature for relevant studies that address this question.

❸Critically evaluate each of the studies.

❹After looking at the individual studies, consider the totality of the scientific evidence and formulate an answer to the research question.

As part of the “simulation” of a literature review, some of the steps in the process have been done for you. For example, a research question been formulated for you to work on:

Based the studies described in Appendix 1, how convincing is the scientific evidence that nuts decrease the risk of cardiovascular disease or the risk of death from cardiovascular disease?

The next step in the process has also been done for you.  The literature has been searched and abstracts from four articles have been made available in appendix 1 of this assignment handout. For the purposes of this assignment the information in these abstracts represents all the scientific evidence needed to assess the relationship between nuts and cardiovascular disease (CVD).

Note that you are not required or expected to use any additional sources. This is intentional so that you can focus your time on the analysis and interpretation of the information that you have been given.  For a real literature search, rather than this simulation, you would need to review many more than just four studies and you would, of course, read each study in its entirety rather than reading the abstract. But for this assignment you only need to concern yourself with the abstracts provided. They have been selected as they are representative of the actual scientific evidence on nuts and CVD.

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Your job in this assignment is steps 3 & 4:  ❸Critically evaluate each of the studies.

❹After looking at the individual studies, consider the totality of the scientific evidence and formulate an answer to the research question.

So what does it mean to critically evaluate a study.  For this assignment it means looking at the strengths and limitations of each study, in terms of the way it was designed and conducted, and also looking at the results of the study: what did the study conclude about the relationship between nuts and CVD.

Nutrition Research: Strengths and Limitations of Common Study Designs

In order to critically evaluate the studies described in the abstracts you need to know about the most common types of study designs in nutritional research. In nutritional research there are main two types of studies:

❶Observational studies

  • Determines an association between diet and health
  • Types of study:
  • Prospective cohort study
  • Case-control study (not discussed in this course)
  • Cross-sectional survey (not discussed in this course)

 

❷Randomized Controlled Trials (RCTs)

  • Determines causation (or establishes a causal link) between diet and health

 

Observational studies are called such because, over the course of the study, researchers simply observe populations and collect information from them about their diet and health status.  Researchers do not ask the population to change their lifestyle in any way.  Observational studies determine whether an association exists between an exposure and an outcome e.g. intake of nutrient X (the exposure) is associated with a reduced risk of disease Y (the outcome).  This is not the same as saying that nutrient X causes a decline in disease Y and why this is so will be explained shortly.

The types of observational studies most commonly used in nutritional research are the prospective cohort study, (a cohort is a group), the case-control study, and the cross-sectional survey.  Only the prospective cohort study or cohort study will be discussed here.

While observational studies can determine an association between diet and health, only a randomized controlled trial can determine causation or establish as a causal link between diet and health.  In other words, the results of an RCT allow you to say that a particular diet or food or nutrient causes an improvement or a decline in health.

The discussion below explains why observational studies determine only associations between exposures and outcomes, while randomized control trials can establish causal links.

 

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Consider the following hypothesis:

HYPOTHESIS:  Nutrient X reduces the risk of disease Y.

Prospective Cohort Study:

The figure opposite describes how, if you were a researcher, you would conduct a prospective cohort study to test the hypothesis of that nutrient X reduces the risk of disease Y.

❶In a prospective cohort study you would select an appropriate sample or cohort (or population), which means that you would recruit a large group of individuals who meet certain characteristics, to be participants in your study. For this study it would be a healthy population that is free of disease Y and you might limit your cohort to middle-aged and older adults, because this is when disease Y develops. ❷In this cohort, you would then determine the dietary intake of nutrient X using food intake assessment methods that we will be discussing later. You would also collect other relevant personal health information. ❸Over the course of the study, and you might follow the participants for five years or 10 years or longer, you track what happens to the health of your cohort particularly the occurrence of disease Y. This is why the study is called a

prospective cohort study because you follow the population or cohort forward in time, or you follow them prospectively.

❹At the end of the study you subdivide the participants into those that have a low intake of nutrient X and those that has a high intake of nutrient X and in each of those groups you determine the proportion of the group that developed disease Y over the course of the study.  This will allow you to determine whether there is an association between nutrient X and disease Y and whether it is consistent with the stated hypothesis.

Important Note: In a prospective cohort study the dietary intake is measured at the beginning of the study on disease-free participants and then the participants are followed over time to see if they develop the disease. In better quality studies the dietary intake is often measured multiple times over the course of the study, and a cumulative average intake is calculated, to account for any dietary changes over time.  This intake measurement would continue until the end of the study or until a participant develops disease Y. The measurement of dietary intake, while the participant is healthy, is a very important design element of the prospective cohort study because it ensures that the exposure, i.e. nutrient X intake, occurs before the development of disease Y. This ensures what is called a proper

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temporal relationship, i.e. the exposure occurs before the disease and therefore it is possible for nutrient X to have influenced disease Y.

At the end of the study, as noted, the study participants are divided into those that have a low intake of nutrient X and those that have a high intake of nutrient X (in most studies populations are divided in to 3-5 groups of increasing intakes; for simplicity only two groups- low & high intake are shown here) and in each of those groups you determine the proportion of the group that developed disease Y over the course of the study.  This will allow you to determine whether there is an association between nutrient X and disease Y and whether it is consistent with the stated hypothesis. The most common results are shown above:

❶You may find that there is no association between nutrient X and disease y i.e. the nutrient, across a range of doses, has no impact on the development of disease Y.

❷Or you may find that there is an inverse association – increases in the intake of nutrient X are associated with a decrease of disease Y- this result would be consistent with the hypothesis of the study.

❸Alternatively you may find that increasing intake of nutrient X is associated with increases in disease Y, which is opposite to the stated hypothesis and is a direct association.

Limitation of Prospective Cohort Study

So let us return to the major limitation of observational studies – that one can only determine associations rather than causal links. Why is this so? Consider our example of nutrient X and disease Y and let us assume that you found an inverse association as shown in the table:

Nutrient X Intake Proportion of Disease Y Cases
Low High
High Low

 

The major limitation of observational studies is that you cannot be certain that the only difference in the population that has a low nutrient X intake compared to the population that has a high nutrient X intake, is nutrient intake alone. There could be other differences between the two groups that may be influencing their risk of disease; in fact there always are.  These differences are often referred to as

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confounding factors. A confounding factor is associated with both the outcome being investigated (Cases of Disease Y) and the exposure (Nutrient X).  For example, what if nutrient X intake in a population happens to be lower in older individuals and we know that older people also get more disease Y? So perhaps the association between nutrient X and disease Y is not really a dietary effect, but is, instead, simply being influenced by age.

Fortunately, by doing statistical adjustment, you can eliminate the effect of age. The details of the specific types of statistical approaches that do this, are beyond the scope of this course and I’ll leave it for your statistics professors to teach you about the methodology. But in our example the effect of age can be eliminated; age is a very common confounder and data are routinely age-adjusted. If there is a real association between nutrient X and disease Y, the inverse relationship between nutrient X and disease Y will still be observed, even after age-adjustment. If the effect was just due to age, there will no longer be an association between nutrient X and disease Y after adjustment.  Good quality studies will typically include adjustment for many potential confounders, such as age, sex, smoking status, socioeconomic status, physical activity, other dietary components besides the exposure of interest and more.  In your essay, when evaluating observational studies, determine whether adjustments for confounders have been made.

One of the problems with confounding factors, however, is that you can only adjust for confounders that you have identified and are able to measure accurately. Age can be measured very accurately; other confounders may be more difficult to measure. Any confounding factors that are either unknown or are subject to errors in measurement can result in the data being vulnerable what’s called residual confounding, confounding for which adjustment is incomplete. It is because there is always a risk, in any observational study, of residual confounding, that they are limited to demonstrating only associations between exposure and outcome; they can never definitively establish a causal link.

For example, sleep pattern, a previously unknown confounding factor, has recently been shown to influence body weight. Individuals who do not get enough sleep are at increased risk for obesity.  As a result, researchers studying obesity, are now asking study participants about their sleep habits and are

including sleep patterns in the statistical adjustments for confounding factors.  But this adjustment is relatively new and there are many studies published on obesity that are unadjusted for sleep patterns. This residual confounding may have influenced the conclusions of some of these studies.

So, returning to the prospective cohort study.  The figure below shows the final step in the study which is the correction, or adjustment, for confounding factors ❶.  This correction helps to strengthen the conclusion of any observational study, but it can never completely eliminate the possibility of residual confounding.  The conclusion of the study can only be that there is an inverse association between the intake of nutrient X and the risk of developing disease Y.

In your essay, when critically evaluating the studies, determine whether the study determined an association or established a causal link.

 

 

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In prospective cohort studies it is also important to consider how the exposure was measured.  In the example discussed here the exposure is nutrient X intake and for the assignment you have to do, it is the nut consumption that is reported.

 

Food intake is commonly measured using a food frequency questionnaire (FFQ); participants are asked to complete a survey about how often they consumed different foods.  In the abstracts that you will be reading for this assignment, the participants intake of nuts and other foods are derived from the food frequency questionnaire.

Another method of measuring food intake, is the 24-hour recall, in which the participant is asked to remember all the food they consumed the previous day. A 24-hour recall includes an interview (face-toface or by phone or via the Internet) between the participant and an interviewer trained to obtain as much detail as possible about the participant’s food intake.

Regardless of the method used, good quality studies always validate their methodology. So, what does it mean to validate a method, for example to validate a food frequency questionnaire?

Validation means the method is compared to a more detailed measure of food intake and there is good agreement between the results. For example, a food frequency questionnaire might ask a participant how often he consumes carrots. For validation the participant might also be asked to record his daily food intake, over multiple days.  If the consumption of carrots as estimated from the food frequency questionnaire is similar to the estimate based on the daily records, and this agreement is seen for other foods and nutrients, then the food frequency questionnaire is considered to be valid and can subsequently be used on its own to estimate food intake. In your essay, when evaluating prospective cohort studies, consider whether the methodologies used to determine food intake are described as validated.

Another important consideration is whether dietary intake was measured repeatedly over the course of the study or only once. As noted above, in a prospective cohort study the dietary intake is measured at the beginning of the study on disease-free participants and then the participants are followed over time to see if they develop the disease. In better quality studies the dietary intake is often measured multiple times over the course of the study, and a cumulative average intake is calculated, to account for any dietary changes over time.  This is especially important for studies that are of very long duration. This intake measurement would continue until the end of the study or until a participant develops disease Y, at which point data collection of food intake would stop.  In your essay, when evaluating studies, consider whether repeated measures of food intake were collected.

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Another important factor to consider is outcome measurement.  Outcomes typically are divided into two categories shown below: disease outcomes or measures of risk factors of disease.  Disease outcomes (often called “hard” outcomes) are commonly measured in prospective cohort studies because they last long enough for disease to develop or for death from disease to occur.

Risk factors of disease, rather than cases of the disease itself, are typically measured in RCTs, as will be discussed below.  Observing a reduction in risk factors does not absolutely guarantee that the occurrence of the disease will be reduced.  So, if your hypothesis is that there will be less disease, ideally disease occurrence should be measured. In your essay, when evaluating studies, consider whether the outcome measured was a disease or a risk factor for that disease.

For this assignment the outcomes that you will be looking at include the risk of developing CVD, the risk of death from CVD, and the risk factors related to the development of CVD, such as blood cholesterol levels or blood pressure.  Background information on CVD and the types of risk factors measured are described in Appendix 1 to assist you in understanding the terminology in the abstracts.

 

 

 

                

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How does this design allow causation to be determined? (See figure above)  ❶When individuals are randomized, confounding factors are equally distributed between the control and intervention group; for example, age is a common confounder, but because of randomization the average age of both the control group and the intervention group will be the same; the same will be true for socioeconomic status and for all potential confounders, including those that are unknown. ❷So the only difference between the two groups is the intervention. If the outcome differs in the treatment group compared to the control group, a causal link is established. The intervention caused the difference.

While the RCT is a better design for establishing causation, it is also more demanding of its participants. Unlike an observational study in which participants are asked only to report information, in an RCT, the participants must change their activities; in nutrition studies participants are asked to change what they eat.  There are several ways that

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dietary interventions are designed, as shown in the figure above.

❶One is the use of metabolic diets, in which all meals are prepared and provided to the participants.  While this is the most effective way to ensure that participants follow the treatment, it is very costly, especially for a long study.  ❷Instead of metabolic diets, participants are often given nutrition education classes on how to select foods that conform to the control or the treatment diet. This approach, while not as good as the metabolic diets, at ensuring that the treatment diet is consumed, is more realistic – as in the real world, people would be given education and advice on what to eat, rather than the food itself. In some studies, participants may be provided with some food products e.g.

participants might be provided with the nuts the researchers would like them to consume, a less costly alternative to metabolic diets.  In your essay, when evaluating studies, consider how the intervention was delivered.

Two types of RCT designs: Parallel and Crossover design

The RCT described above, about nutrient X and disease Y, follows what is called a parallel design in which the participants of the control group and the participants in the treatment group are different

individuals. It is also possible to have an RCT in which the same individual participates in the control group and also in the treatment group. This is called a crossover design and you will encounter it in one of your abstracts, so it is briefly described here. Half the group is randomized to receive the treatment first and half is assigned to the control (1).  After the experimental period ends, there is a washout period, a time for any effects of the previous treatment effect to wear off; then the two groups “crossover” so those who received the control diet now

receives the treatment and vice versa (2). Because this design compares the response that one person has to two diets, a crossover design can be conducted with a smaller sample size.

Limitations of RCTs & Cohort Studies Cohort studies, are just that, observational, and do not ask participants to make changes to their lifestyle, they can continue for many years and measure actual disease outcomes. The major limitation of an observational study, of course, is that casual links between exposure and outcome cannot be established, because residual confounding is always possible. The figure, above, summarizes both the

strengths and limitations of the two most common types of nutritional research studies.  In nutrition

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research, because of these limitations, as you are doing in this essay, results from both types of studies are considered in making overall assessments of the scientific evidence.  

Additional Comment on Study Participants

For different studies different populations are recruited; sometimes healthy subjects are studied, sometimes participants have some medical conditions; sometimes a study looks at only men or only women; ethnicities may vary. When a hypothesis is tested it is desirable to see whether results support the hypothesis across a variety of different populations.

For cohort studies, when large numbers of participants are recruited, comprehensive food intake data, health information data, and demographic data are collected.  This creates a detailed database for a cohort, that can be accessed by researchers to test a variety of hypotheses.  In the abstracts in this assignment, you will read about a number of cohorts were studied and data from these groups were combined or compared to assess the impact of nut consumption.  In your essay, when evaluating multiple studies consider the variation in populations studied.

 

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Interpreting experimental results

 

In the previous section we looked at the strengths and limitations of different research design and some of the study characteristics that you should consider when evaluating studies.  In order to answer the assignment question, in addition to assessing the quality of the studies, you have to also correctly interpret the results of the experiments.  In the reporting of results, one frequently encounters measures of relative risk.  To explain what is meant by relative risk see the figure above.

❶ Let’s assume that you are conducting a prospective cohort study which is made up of a group of 10 people with a low intake of a nutrient (in a real study you would have thousands of subjects, but here n= 10 is being used for simplicity).

❷ After many years of follow-up i.e. following the participants over a period of time, 4 out of 10 develop disease A.

❸So the frequency of the disease is 0.4

❹This information can be expressed as a ratio between two groups called a relative risk.  Here we are showing Relative Risk (RR) = 1 because the low intake group has been selected as the reference group. The purpose of a reference group will become clearer when we look at a second group.

❺Now let’s consider the high nutrient intake group. Here only 2 out 10 people get sick.

❻The frequency of the disease is 0.2.

❼Compared to the low intake group, the RR for the high group is 0.5, i.e. high intake reduces the risk of disease by 50%.

❽When reading studies, results are often presented in tables like the one shown here.

❾Compared to the reference group, which always has RR=1, the disease risk is increased in groups with RR > 1 and decreased in groups with RR < 1.  Which group is selected as the reference group is arbitrary and decided by researchers based on how they want to present the results.

❿ For example, the table shown here communicates exactly the same information as ❽, except the reference group has been changed to the high intake group.

⓫ Finally, the calculation shown here is a RR. You will encounter similar ratios, such as a Hazard Ratio (HR) or an Odds Ratio. There are differences in the way these ratios are calculated but they are interpreted the same way as a RR and are all estimates of the same effect.

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❶Here is table showing some relative risks. The population here was divided into 5 groups or quintiles from lowest diet quality score to highest dietary quality score in a prospective cohort study that lasted over 10 years. In the abstracts you will be reading you will be looking at comparison between low and high intakes of nuts.

 

❷After several years the relationship between the risk of CVD and diet quality was evaluated. Here we see that as diet quality increases, CVD risk decreases i.e. RR is less than 1.

❸ Specifically, comparing lowest to highest quality diet scores, the RR dropped from 1 to 0.61, a drop of 0.39 or 39%.

❹ When researchers see results like this, the next question they ask is whether the difference in disease risk that is observed between high and low quality diet, is due to chance, or indicates a meaningful effect of diet quality on disease risk. In order to do this researchers conduct statistical analysis.

In order to correctly interpret the results of statistical analysis, which you will encounter in this assignment, a few statistically concepts have to be considered.

  • Null hypothesis o This is a somewhat counterintuitive concept. Scientists tend present their hypotheses in a positive light, e.g. increased diet quality results in decreased disease risk. But the null hypothesis describes a situation of no effect e.g. diet quality will have no effect on disease risk; there will be no difference in disease risk between groups, whether consuming high or low quality diets.
  • Alternative hypothesis o This is a hypothesis that is an alternative to the null hypothesis e.g. There will be a difference in disease risk between groups consuming high quality diets compared to low quality diets

        •    Model

o Mathematical equations, used in statistical analysis, that best fit the data

  • Probability or P-value o Expressed as a decimal between 0 and 1, where P = 0 means there is no probability of an event occurring and P = 1, which means there is a certainty that an event will occur. P-values can also be expressed as % e.g. P= 0.50 or 50% probability of an event occurring

o Determines the probability that the observed difference (or greater difference) between groups being compared would occur with repeating experiments assuming:

  • The null hypothesis is true
  • All assumptions used in the mathematical model are correct

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  • Chance alone is operating

Here a P-value has been calculated for the RR data we discussed earlier, P-value = 0.002.  What does this mean?

A P-value indicates that a comparison is being made between at least two groups, so the first step is to know what is being compared. Here the comparison is between the relative risk of

1 and the relative risk of 0.61; a comparison of the lowest vs highest diet quality groups.

P=0.002 means, assuming the null hypothesis is true, the model assumptions are correct, and chance alone is operating, that a difference as large as (or larger than) the one observed, would occur in 1 out of 500 experiments.

One way of looking at the data is that the null hypothesis is true and that the data observed here is essentially an extremely rare (1/500) result.  It is important to recognize that this a legitimate way of interpreting the data. Another way, however, and this is what most scientists would conclude, is that the small P-value of 0.002 is strong evidence against the null hypothesis. Researchers would say that there is a statistically significant difference in disease risk in the low diet quality group compared to the high diet quality group. The data suggests that, indeed, as diet quality increases, the CVD risk may decrease.

Level of significance

There are some conventions that biomedical researchers typically use for interpreting P-values. Researchers say that there is a statistically significant difference between groups when the calculated Pvalue is less than 0.05 and there is no statistically significant difference when P > 0.05. Alternatively when P <0.05 there is evidence to reject the null hypothesis, while P > 0.05 evidence favours not rejecting the null hypothesis.

The 0.05 (or 5%) cut-off, which is called the level of significance, is arbitrary and other levels of significance e.g. P <0.01 or P <0.1 can be used, if appropriate for the research question being addressed. All statistical results have to be interpreted with common sense e.g. there is really no meaningful difference between study results with a P = 0.049 and P= 0.051 even if technically one is significantly different and for the other there is no statistically significant difference. It is important to recognize the word significant is used here in a very strictly defined way, not just as a common word to mean important or substantial. It refers to a statistical assessment and will be used this way in the abstracts. Also a “statistically significant difference” does not PROVE that the null hypothesis is false, although results of studies are often misinterpreted to mean this, especially in the popular media.  Similarly results that are not statistically significant do not PROVE that the null hypothesis is true.  These concepts are summarized in the table below.  There is always uncertainty associated with any conclusions drawn from an analysis of statistical significance, especially from a single scientific study.

That is why it is important to look at multiple studies, as you will do in this assignment, to see how consistent the results are. When multiple studies look at the same problem,  and draw similar conclusions this increases confidence that the conclusions are meaningful. In your essay, when evaluating the results, consider the overall consistency of the results across multiple studies. 

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Statistically significant:  P < 0.05 Not statistically significant:  P > 0.05
Evidence favours rejecting the null hypothesis.  But does not prove that the null hypothesis is false, only that the evidence supporting it is weak; the null hypothesis, however, may still be correct. Evidence favours not rejecting the null hypothesis, but does not prove that the null hypothesis is true; only that the evidence supporting it is strong; but the null hypothesis may still be incorrect.

 

95% confidence intervals

There are other ways to present the results of a statistical comparison of relative risks.  For relative risks a range of values called a 95% confidence interval (95% CI) is usually reported, instead of a P-value.  For the relative risk shown opposite it is (0.49 – 0.75).

What does this interval measure? It indicates that there is a 95% probability that the true relative risk lies within the interval. While 0.61 is the best estimate of the relative risk, the value can be as low as 0.49 or as

high as 0.75. Imbedded in the 95% CI is information about the statistical significance of the relative risk. When comparing an interval to the reference group (which has RR=1) if the interval includes 1 than the results are not statistically significant. If 1 is not included in the interval, such as the example here (0.490.75) there is a statistically significant difference. The 95% confidence interval does not tell you the exact P-value, only that it is greater or less than 0.05. A separate calculation needs to be done to calculate a P-value, as was done here (P = 0.002).  The interpretation of CIs is summarized below:

Confidence intervals are very useful for making comparisons between pairs of groups, such as the comparisons described above between the lowest and highest diet quality categories. But in most observational studies there are multiple categories. Pairwise comparisons are not that useful. In many studies what you want to know is whether there is a trend of increasing or decreasing disease risk across all intake categories i.e. is there an association between exposure and outcome?  This is generally of greater interest than whether there is a statistically significant difference between the reference group and one other category. To determine whether an association exists another type of statistic is calculated: P for trend.  To illustrate this the chart below shows the data on diet quality and CVD risk previously discussed along with the additional data on the relationship between diet and cancer.

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Also shown is the calculation for P for trend which is statistically significant for CVD, P trend <0.001, well below the conventional P <0.05 threshold for significance and is not significant for cancer (P for trend = 0.68). As was noted earlier when you see any P-value you need to know what is being compared.

The flat line indicated by the red arrow is the theoretical representation of no effect or the null hypothesis. The curve indicated by the purple arrow has a P for trend greater than 0.05 suggesting that it is not significantly different from the flat line. There is no apparent association between diet quality and cancer. The curve indicated by the yellow arrow has a P for trend of less than 0.05 indicating that there is significant difference in trend compared to a flat line. The results indicate an inverse association between diet quality and CVD risk.

In this assignment you will see results reported with P-values, confidence intervals, and P for trends and you will have to interpret their meaning as it relates to the relationship between nut intake and CVDProspective cohort studies typically report confidence intervals and, more importantly, P for trend, which indicates whether there is an association between exposure and outcome. In your essay, when assessing the results of the prospective cohort studies, the focus should be on P for trends as they are indicators of an association between exposure and outcome. 

RCTs report between-group differences, e.g. the effect of the treatment group and whether it differs from the control group.  A P-value comparing treatment vs control group indicates whether there is a significant difference between the two groups. More specifically, the change in a variable, such as blood pressure, in the control group, at the end of study, compared to the beginning of the study is compared to this same change in the treatment group.  If the null hypothesis were true (treatment has no effect) you would expect that the change in treatment group would be no different than the control group.  If the treatment had an effect, however, the change in the treatment group would be greater than the change in the control group and a statistically significant difference between treatment and control is present. In your essay, when assessing the results of the RCTs, the focus should be on these P-values and whether they are statistically significant or not. 

 

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Appendix 3: Tips for writing your essay

 

Getting started with your essay:

  • Read the question carefully Read each abstract carefully.
  • To help you understand the study, identify the following characteristics, for each of the abstracts as shown during the lecture recording on nutrition research (week 3):

        •    Observational studies:

  1. Study design
  2. Population; age, gender, healthy, etc.
  3. Study location
  4. Exposure
  5. If dietary intake was assessed, how was it measured? e.g. FFQ, validated? Repeated?
  6. Outcome(s): disease or risk factors
  7. Duration of study; in observational studies the term “follow-up” is used
  8. Result: Was an association between exposure and outcome observed? Statistical significance?
  9. Adjustment for confounders (Y/N)
  10. Strengths of study
  11. Limitations of study
  12. Additional comments: g. Information from Appendix 2 related to sentences, in bold, that begin: “In your essay…”

 

  • Randomized controlled trials (RCTs)- the items that differ from observational studies are shown in bold:
  1. Study design
  2. Population; age, healthy, etc.
  3. Study location

4.Intervention (s): Metabolic diet or education

5.Comparison/Control Group

6. Randomization Y/N

  1. Outcome(s)
  2. Duration of study
  3. Result: Did the intervention impact the outcome? Statistically Significance?
  4. Strengths of study
  5. Limitations of study
  6. Additional comments: g. Information from Appendix 2 related to sentences, in bold, that begin: “In your essay…”

 

  • Place each one of these points on an index card:
  • Limit each card to one concept or point. The less written on each card the easier it will be to order and integrate the ideas into a final essay.
  • Putting information into your own words at this stage is an effective way to avoid plagiarism. If you must copy verbatim, be sure to use quotation marks, so you’ll know that this is information you have to paraphrase later when composing your essay.
  • Examples:

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Black and White 2000 Study Design:

Prospective cohort study

  Black and White 2000  Strength and Limitation:

Limitation: Adjustment for confounders made but residual confounding still possible

 

  • Sort through the cards looking for the best way to support the answer to the assignment question:
  • Look for similarities and differences between studies; for example group all the “study design” cards together, all the “population” cards with results together to more easily make comparisons
  • Put the cards in an order that allows you to address the essay question in a logical and sophisticated manner.
  • At this point it is a good idea to re-read the assignment question and the abstracts again to see if there are any additional ideas that you missed on the first reading.
  • Creating a detailed outline, at this point, might also be helpful.

 

  • Electronic alternatives to using index cards:
  • PowerPoint: Write one idea/slide and use the slide sorter function to order the cards.
  • Word: Create a list of ideas and cut and paste to alter the order of ideas.

 

  • Think about your introductory and concluding paragraphs- for a 500 word essay these need not be more than 2 sentences.

•     Your introduction should summarize how you are answering the question. The reader should know by the end of the first paragraph how you are answering the question.

  • Your conclusion should be strong and should sum up your position in a way that is not an exact repetition of the introduction.

 

  • Use multiple short paragraphs. They are easier to read than longer paragraphs, and are effective signals to the reader when you are changing topics.
  • Be sure to create paragraphs that transition logically from one to the next- this produces a good “flow”
  • Make sure that your essay is written in a persuasive style – you are trying to convince the reader that your assessment of the studies is reasonable.
  • Not sure where to begin. JUST START WRITING. The act of putting ideas in your own words will help you to see how to organize your essay.
  • Revision and Proofreading: After you have completed your first draft, if time permits, don’t read the essay for at least 24 hours.  Returning to the essay after a break allows you to look at it with fresh eyes and spot areas that need improvement more readily.  Rather than editing solely from a screen, it is also recommended that you look at a hard copy of your essay at least once during your revision process.  It is usually easier to spot errors and get a sense of the total essay when looking at a hard copy.

 

Be sure to avoid these common essay flaws:

  • Flaw 1: Not making your position clear.
  • Be sure that you clearly state your evaluation of scientific evidence – do you conclude that the evidence is very convincing, not convincing, or moderately convincing, etc.

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  • Flaw 2: Discussing each study in isolation without making connections between studies or without noting similarities and differences between the study characteristics.
  • Avoid an essay that contains four disconnected paragraphs describing each study in isolation. You have to make connections and transitions between your paragraphs in a logical fashion.
  • For example the bolded phrases help to connect the two paragraphs shown below:

“Brown and White (2014) conducted a high quality prospective cohort study to determine a link between nutrient X and disease Y ….ADDITIONAL DISCUSSION EXPLAINING WHY IT IS A HIGH QUALITY STUDY…..They concluded that there was a statistically significant inverse association between nutrient X and disease Y.

 

Similarly, the study by Black and Grey (2014), is also well-designed cohort study but it did not find a similar association…..CONTINUED DISCUSSION…”

 

  • Also don’t feel your entire essay has to be study-by-study. Consider discussion of multiple studies in a single paragraph, grouped by relevant characteristic such as results, study design, population, etc. For some of the points you want to make, this might be a better approach.

 

  • Flaw 3: Summarizing the study results, without making an evaluation of strengths and limitations of study design e.g. prospective cohort study or RCT. Often students make the evaluation of how convincing the scientific evidence is by looking only at the results, e.g. were statistically significant results found, without saying much about the study design e.g. observational studies compared to intervention trials and how that impacts the reliability of the results. You have to discuss both in the essay.
  • Flaw 4: Ignoring an abstract either through carelessness or because its content was difficult to integrate into the discussion. You must discuss all abstracts in your essay.

Appendix 4: How to format references

This assignment assumes you have completed the Science Writing Quiz and understand the concepts of paraphrasing, in-text citations and bibliographies.

Sources used for the essay should be cited within your text, using the NAME-YEAR format of the Council of Science Editors, and listed in a bibliography, alphabetically by first author, at the end of the essay. (See important note below about multi-author papers).  See the document: How to cite and format references for more details.

 

How to cite an abstract from a database:

In this assignment your sources are abstracts from databases such as PubMed.  It is essential in your bibliography that you indicate that you used abstracts, as you have NOT read the full-text article. This is done by preparing the bibliographic reference as described in the document noted above for a journal article but including the phrase [(Name of database) Abstract] after the title:  e.g. Authors .Year. Title.

[PubMed abstract]  Journal title Volume (issue): inclusive pages.

 

 

 

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Important note about multi-author papers:

  • Never change the order of the authors of a study. The first author of a study is the person that spent the most time preparing the paper and has earned the right to be listed first. The first author is often referred to as the lead author.
  • Your bibliography should be alphabetical by first author. This means that if the first author of a paper is Brown and a second paper has the first author Green, then the Brown paper is listed before the Green paper. If two papers have the same first author than the order of the papers is decided based on the second author’s name.

 

Appendix 5: How the essay is graded:

The essay will be graded based on two major criteria:

Fluency (10%): Overall: Was the writing clear and easy to follow?

Scientific content (90%): Overall: Was the scientific evidence effectively used to answer the question?

 

Use the checklist below to help you evaluate your essay:

 

Fluency:

  • Does your writing flow readily from introduction, to body, to conclusion with good transitions from idea to idea?
  • Have you presented your ideas in an order that is logical and easy for the reader to follow?
  • Is the language of your essay clear and concise?
  • Does your introduction clearly state the answer to the question and did the writing conclude with appropriate emphasis?
  • Are your sources properly paraphrased?
  • Are your in-text citations and bibliography properly formatted? (Errors or omissions in-text citations: deducted: 1 to 4%/100%; Errors or omissions in bibliography: deducted: 1 to 4%/100%)
  • Is your essay within the stated 500 word limit? Note a 15 word overage will be forgiven after which deductions will be made. Excessive length: deducted: 2% to 6%/100%

 

Scientific content:

  • Did you use relevant information from all the abstracts to answer the question?
  • Is the answer to your question well-supported by the evidence presented?
  • Does your essay include a comprehensive analysis of the studies’ strengths and limitations?
    • Did you include the information indicated in Appendix 2 that should be in the essay?

(see bolded sentences that begin “In your essay…”)

  • Did you include a discussion of the results of the studies including their consistency and statistical significance?
    • Did you include the information indicated in Appendix 2 that should be in the essay?

(see bolded sentences that begin “In your essay…”) • Did you include an overall assessment of the scientific evidence?

 

Policy regarding re-reading of assignment:

If you have substantive concerns about the grading of your essay, after it is returned, you may request a re-read.

More information on how to request a re-read will be provided later in the term. If no comments are included, Dr G will not re-read your essay. Your mark can go up, down, or stay the same.  Please note that the higher your original grade, especially >80%, the less likely an upward adjustment in your mark will occur. The deadline for

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submitting requests will be posted on Quercus. This deadline will not be extended. Dr G will advise students when re-reads have been completed. Her decision on grades is final.

 

Appendix 6:  Submitting your essay online 

A link is available on Quercus for you to submit your essay. Your essay must be a Word document: doc or docx to facilitate the determination of word count. Quercus will block your submission if the file format is incorrect. On Quercus, online submissions will automatically be submitted to Turnitin, but you will have to agree to the Turnitin license agreement. See the course syllabus for more information on Turnitin as a plagiarism prevention tool and alternatives.

Formatting:  Please use  Calibri font size 12 for your essay and DOUBLE-space. Be sure to include your name and student number at the top of the page.  DO NOT include a title page, a title, or re-write the essay question. This information is not necessary for this assignment and increases the amount of time TAs spend scrolling online.

 

Appendix 7: Policy regarding the late submission of essay:Please see the course syllabus for the late submissions policy.

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