Eco Moment on our Carbon Footprints

Use the class data posted in the “Shared Data” Discussion containing the Week 3
Carbon Footprint Data Tables.
This data project will address Course Outcomes 1 and 3:
interpret quantitative information to determine effects of human activity on the environment and to evaluate
environmentally sustainable decisions
effectively communicate and use scientific evidence regarding human impact on the environment with
emphasize on sustainability and global citizenship
Description
This data project will be composed of two parts. In Part I of your report, you will compile class data from the
Week 3 Eco Moment on our Carbon Footprints (found in the “Shared Data” Discussion, under Carbon Footprint
Data) and summarize/analyze it with Excel (or similar spreadsheet program). Discuss what trend(s) you see in
the class data that relate to course concepts. Think about the best way to present your findings–tabular or
graphical form? There is no “right answer” here, as long as you pick a format that highlights your main findings
and support your table(s) and/or graph(s) with clear text that interpret the results. Do any of the findings
surprise you? Why or why not?
In Part II, you will research and discuss possible solutions to the environmental problems reflected in the class
data. Here, you will want to support your argument with reliable, scientific resources (e.g., peer-reviewed
scientific papers, white papers, and government websites). Be sure to end with a strong concluding paragraph
that summarizes the main data trend(s), along with the merits and relevance of your chosen solution(s).
Format
The page limit for your written report for both Part I and Part II is 2 pages, plus 1 page for the data
table/graph(s) you use to present your findings in Part I. The page limit does not include an optional title page,
the reference list, and the appendix with the raw class data. The report should be double-spaced with one-inch
margins all around and use a 12-pt font.
Here is the order in which to present the various project components:
Part I = describe the class data we collected, include the methodology, relevant web tool (if applicable), the
mean and sample size for each result, table/graph(s) that depict the main findings and/or trends; interpret the
table/graph(s) for the reader
Part II = summarize research on possible solutions; be sure to incorporate reliable in-text citations and focus
on relevant, attainable solutions
Reference List
Appendix of Raw Data = screenshot or copy in the Excel table showing all the class data (no analysis or mean)
More info Submission Feedback
Overall Feedback
Nice job. Please remember to incorporate graphs or tables in Part I. All direct quotes need the page number
and references need dates -see paragraph one (Kinsella) did not have a date. On your reference page,
references need to be in alpahbetical order.

Sample Solution

-BP ≥90th percentile according to age and sex
Waist circumference percentiles for the Indian Population were published recently by Khadilkar et al (18). They have suggested a cut-off of 70th percentile for WC, to screen for Metabolic Syndrome in Indian children.

5. Nonalcoholic Fatty Liver Disease (NAFLD):
Nonalcoholic fatty liver disease (NAFLD) constitutes a spectrum of conditions, ranging from steatosis to nonalcoholic steatohepatitis (NASH) and cirrhosis, in the absence of excessive alcohol consumption. The prevalence of NAFLD is 34.2% in obese children & adolescents and the reported prevalence is highest in Asia (19).
Most children are asymptomatic, while some may complain of right upper quadrant pain or abdominal discomfort. NAFLD aggravates hepatic insulin resistance, thereby increasing the risk of developing T2DM.
The liver SAFETY (Screening ALT for Elevation in Today’s Youth) study was conducted to develop ALT thresholds and the cut-off of ALT >25 for boys and >22 for girls were suggested for screening NAFLD in children (20).

6. Polycystic Ovary Syndrome (PCOS):
Increased adiposity, especially abdominal, is associated with hyperandrogenemia and increased metabolic risk. The diagnosis of PCOS in an adolescent girl should be made based on the presence of clinical and/or biochemical evidence of hyperandrogenism (after exclusion of other pathologies) in the presence of persistent oligomenorrhea (21). Polycystic ovary morphology on ultrasound is not reliable to make a diagnosis in adolescents because multi-follicular ovaries are a feature of normal puberty that subsides with onset of regular menstrual cycles (22).

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