Milestone One Worksheet - Do you have this paper available ? my teacher did not like me using case studies from his paper.

Please table to add context to your responses in the Research Methods table below. Your instructor will provide feedback.

List the title and author of the article you chose.

Food Environments and Obesity: Household Diet Expenditure Versus Food Dessert

Chen, D., Jaenicke, E. C., & Volpe, R. J. (2016).

Describe the purpose of the study.

The purpose of the Study was to examine the relationship between food and obesity in their home and their surrounding community.

What is the research question in the study?

Is there a link between food desert communities and rapid rising rates of obesity?

What is the hypothesis of the study?

If there are food deserts in the community then there will be a high level of obesity.

Research Methods: In this section of your analysis, you will take a deep dive into the research methods used by the authors of the study you chose to analyze. It is important that you are able to identify, describe, and discuss the data collection and data analysis methodology used by the researchers.

Important: Once you receive instructor feedback on this table, you will use it to inform the writing of the Research Methods section in paragraph form for the submission of your final project in Module Seven.

Research Methods Table

Critical Element

Response to the Critical Element

One Example

Identify whether the study design is experimental or observational. Support your identification with examples from the study.

This is an observational study since they read different studies and comparing results.

The study (Comancing C.)

Finding a link between supersized Walmart and high obesity rates in the surrounding community.

Identify the methods used to collect the data and explain why the methods are appropriate based on the research question.

Methods used was reviewing previous documented studies looking at the data set up and comparing each outcome and looking for inconsistencies, and

consistencies on the outcome.

Used studies (Steven & Pinardi) had families write down items in their kitchen by using sampling surveys

Identify the data collected as quantitative or categorical. Support your identification with examples from the study.

I think this study may be using both the categorical and quantitative and will explain in the examples.

I believe it uses food categories to study what families are spending their money are, and table where the individuals BMI are measures. Also uses a formula that measures distances between homes and grocery stores and restaurants

Discuss the potential weaknesses of the data collection methods used. Support your discussion with examples from the study

The weakness of the data collection methods used is that the authors were not involved in any of the studies and would not be able to validate the accuracy of each case study.

When questions are asked, and families are asked to recall information about their spending habits and memory recall may not always be accurate for food consumption frequencies. (Steven, B)

Identify the data analysis methods used and explain why the methods are appropriate based on the research question.

The data analysis methods used was effective because it showed a static relationship between the two variables of food deserts and rapid rising obesity levels,

The method of data collection in the multiply studies had to meet USDA poverty levels and more than a mile from a local grocery stores (USDA food deserts 2014)

Discuss the potential weaknesses of the data analysis methods used. Support your discussion with examples from the study.

The potential weakness of the analysis method was weight and height were asked by a questionnaire.

Individuals are not completely honest about their statical stats of height and weight.

Describe the key demographics of the population sampled and identify the inclusion and exclusion criteria for participants.

The key demographics overall was low income, overweight, and obesity according to USDA standards, contained adults over 18, and children 2 to 17 years old who lived over 1 mile from a grocery store.  The inclusion would be limited families whose distance was less than one mile

In the study by Volpe and Okrent food used the CNNP to evaluate the families food categories, and Iri Consumer Panel.

 

List the title and author of the article you chose.

Food Environments and Obesity: Household Diet Expenditure Versus Food Deserts

Danhong Chen, Ph.D., Edward C. Jaenicke, Ph.D., and Richard J. Volpe, PhD

Describe the purpose of the study.

To see if there is an association between obesity and the environment they live in. They want to know if the area they live in influences the food they eat. If it does, they then want to look at if that causes people to be obese.

What is the research question in the study?

How obesity and overweight are influenced by individual factors, household-factors, and neighborhood-factors. 

What is the hypothesis of the study?

They believe that obesity is influenced by relationships, the environment they live in and trends in society. They also note that an individual's health is also influenced by biological and genetic functions.

Research Methods: In this section of your analysis, you will take a deep dive into the research methods used by the authors of the study you chose to analyze. It is important that you are able to identify, describe, and discuss the data collection and data analysis methodology used by the researchers.

Important: Once you receive instructor feedback on this table, revise it and include it in your final project submission in Module Seven.

Research Methods Table

Critical Element

Response to the Critical Element

One Example

Identify whether the study design is experimental or observational. Support your identification with examples from the study.

This is an observational study. They used data sets collected by the IRi Consumer Panel, the IRi MedProfiler data, Census Bureau's American Community Survey, US Census Bureau's Business Patterns, and USDA.

One of the main household level measures in our analysis, USDA Score, re?ected the home food environment and was constructed from the detailed food purchase information in the IRi Consumer Panel.

We collected data on the average number of food stores or restaurants per 10000 county residents.

Our research, therefore, investigated how obesity and overweight status was in?uenced by (1) individual-level factors, including age, gender, and several self-reported behavior responses; (2) household-level factors, including race, ethnicity, education, income, and a home food environment measure that indicated the overall healthulness of a household's aggregate food-at-home purchases; and (3) neighborhood-level factors, including county-level densities of various food store types, poverty rates, metro status, and a census tract-level indicator of food desert status as de?ned by the USDA.

Identify the methods used to collect the data and explain why the methods are appropriate based on the research question.

They used the IRi Consumer Panel and the IRi MedPro?ler data. They also used the US Census Bureau's County Business Patterns. Finally, they used the Census Bureau's American Community Survey from 2010-2012 and USDA. They compiled a multilevel dataset from several sources.

Neighborhood-level data came from various public sources. From the US Census Bureau's County Business Patterns, we collected food store and restaurant establishment numbers at the county level.

From the Census Bureau's American Community Survey (2010-2012), we extracted population and poverty rate data. From the USDA, we collected county-level 2013 Rural-Urban Continuum Codes and census tract-level food desert information.

Identify the data collected as quantitative or categorical. Support your identification with examples from the study.

The data collected is categorical and quantitative. A quantitative variable is a measurement or recording. In this study the quantitative variables are BMI, overweight, obese, age, household size, and income. Categorical variables are variables that can fit into one of two categories or more. Examples of categorical variables in this study are, gender, diet feature, fast food, exercise, race, education, and marital status.

"Diet feature" was a factor analysis score constructed from 7 MedPro?ler questions

related to special diets, including high-?ber, high-protein, low-calorie, low-carbohydrate, low-fat, low-salt, and low-sugar diets. All responses to these dietary features were either yes (coded as 1) or no (0).

Discuss the potential weaknesses of the data collection methods used. Support your discussion with examples from the study

The potential weakness associated with the collection of data are: they used a self-reported survey, the used a scanner data method that did not include the food away from the house, and they did not take into consideration the geographic distance and mobility obstacles to access the food outlets.

Second, our study relied on self-reported information found in IRi's MedPro?ler data and might be subject to various measurement errors.

Identify the data analysis methods used and explain why the methods are appropriate based on the research question.

They calculated descriptive statistics for the different variables. They used a multilevel intercept logistic models. The checked for robustness by estimating models applied to metro and nonmetro subsamples. They used Stats version 13. Using descriptive statistics allows them to have a summary of the samples and measurements. Using multilevel intercept logistic models allowed them to compare the data at three different levels, individual, household, and neighborhood.

To account for the multilevel data structure, we based our major analyses on random-intercept logistic models (or multilevel models) with random components at the individual, household, and neighborhood levels.

We performed all statistical analyses using Stata version 13 (StataCorp LP, College Station, TX).

We calculated the conditional interclass correlation coef?cient for each model.

Discuss the potential weaknesses of the data analysis methods used. Support your discussion with examples from the study.

The potential weakness of the analysis methods is that they supplemented data. They should have used a sensitivity analysis to help with the issues where they had to supplement data.

Third, the number of food stores or restaurants per capita basically identi?ed a " supply ratio," but it did not take into consideration geographic distance and mobility obstacles to access the food outlets that might be measured if data were geocoded.18However, the density measures were supplemented by the food desert indicator variable, which measured access to a supermarket or large grocery store within a predetermined distance, and which was signi?cantly associated with obesity and overweight status in this study.

Describe the key demographics of the population sampled and identify the inclusion and exclusion criteria for participants.

The study included 38,650 individuals the lived in 18,381 households that were in 2,104 counties in the United States. Because there were some missing observations of some of the variables the sample size was slightly less. More than 85% of the participants were non-Hispanic white and half of them had the college-educated head of households. The average household size was 2 and the average income was about $69,000. The average BMI was 28.50.

In adults ages 18 and older they considered obesity to have a BMI great than or equal to 30. Overweight is BMI equal to or more than 25 but less than 30. The BMI for normal weight is less than 24. In Children aged 2 to17years BMIs lower than the 85th percentile for their age and gender as being underweight or normal weight. Those with BMIs greater than or equal to the 85th percentile but lower than the 95th percentile as overweight, and those with BMIs greater than or equal to the 95th percentile as obese

Compliance with the US Department of Agriculture. They need to be a part of the IRi Consumer Panel and the IRi MedPro?ler data.

Low-income communities are tracts that have "either a poverty rate of 20 percent or greater or a median family income at or below 80 percent of the area median family income." Low-access communities, which differed between metro and nonmetro areas, were de?ned as tracts with "at least 500 persons and/or at least 33% of the census tract's population live more than one mile (10miles for non-metro tracts) from a supermarket or large grocery store."