HLTH7025 Healthcare Data for Decision-Making

Posted: April 4th, 2019

HLTH7025 Healthcare Data for Decision-Making, Spring semester 2022 Assignment 1 (Due Sunday 4 September 2022)
Please answer all 3 questions. Record your answers in the template document provided and submit via Turnitin before 11:59 pm on the due date. The marks allocated to each question are shown in the assignment. A total of 30 marks are available, and this assignment is worth 30% of your overall grade.
Question 1 requires you to analyse the unique assignment data set which was created for you.
This is labelled ‘dataforxxxxxxxx.xlsx’ where xxxxxxxx represents your Student ID number. The description of this data set is provided below. Your Assessment 1 data set was emailed to your student email address.
Copying answers from other students, sharing answers with other students, and writing answers in a group are all forms of cheating. Any student doing any of these will be reported for academic misconduct.
Need first-class papers? Get Fast Essay Writers US & urgent essay writing service Ca – Note:
– Each student will get different answers as the data sets differ.
– Please use Excel to analyse data but format your answer by following the guidelines for preparing tables and Graphs.
Question 1 [9 marks]
A randomised controlled trial (RCT) study was carried out to determine the effect of smoking on coronary heart disease (CHD) in rural India. The study was conducted on 100 farmers. The baseline data of 100 farmers were presented. The data included demographic information (identification number, age in years, family income in Rupees, cholesterol levels (mg/L), smoking status, alcohol use and CHD levels. The data contain 7 variables. The 7 variables are id (identification number), age in years, family income in Taka, cholesterol levels(mg/L), smoking status (1=smokers and 2=non-smokers), alcohol use (1=No use, 2= mild use, 3=moderate use and 4 = heavy use) and CHD levels (1= Low risk, 2= Intermediate risk, 3= High risk).
a. Use row percentage to describe the relationship between smoking status and level of CHD and write 3-4 sentences summarising your findings, including public health implications of the findings with one recommendation. (4 marks).
b. Use appropriate statistics to describe measures and variability of the distributions of age in years, family income in Rupees, cholesterol levels (mg/L), – write the answer in your own words) (2 marks)
c. Use a scatterplot to describe the relationship between age in years cholesterol levels (mg/L), and report your correlation coefficient (r ) (2 marks)
d. Use the pie chart to describe the proportion of alcohol use among farmers in rural India. (1 mark).
Question 2a [9 marks]
Considering the following data from two countries (Tanzania and Bangladesh).
Country Household wealth # of pregnancy of
7+ months duration # of stillbirth # of early neonatal death # of perinatal death
Poorest 1753 25 29 54
Poor 1959 30 25 55
Tanzania Middle 1874 38 38 76
Rich 1549 23 29 52
Richest 1184 27 35 62
Total 8319 143 156 299
Poorest 1920 51 49 100
Poor 1819 51 39 90
Bangladesh Middle 1681 46 38 84
Rich 1798 44 44 88
Richest 1712 29 37 66
Total 8930 221 207 428
a. Calculate the stillbirth, early neonatal and perinatal mortality death rate for each household wealth in the two countries. What do you notice? (4 marks).
b. What are the total mortality rates for stillbirth, early neonatal and perinatal in the whole data? (2 marks).
c. Which of these two countries needed an urgent intervention to reduce the rate of perinatal mortality? and why? (2 marks)
d. What is the perinatal mortality rate for the overall total population? (1 mark)
Question 2b [5 marks]
In 2010, the Bangladesh government created a new division called the “Rangpur” division. (Abir et al., Global health action, 2017;10(1):14100482017) were interested in examining trends of stillbirth in Bangladesh using a population-based survey from 2004-2014. Their analysis produced two graphs for stillbirth, one graph with Rangpur division and the other graph without Rangpur division (as shown below).
Figure 1a was the rate of stillbirth and their 95% Confidence Intervals (CI) with Rangpur division, while Figure 1b was the rate of stillbirth and their 95%CI without Rangpur division.
a. Looking at the two graphs, do you think Abir et al. (2017) should produce two different graphs for stillbirth and provide reasons for your answer? (2 marks)
b. If you were employed as a public health officer in Bangladesh and were asked by the Minister of Health to provide some policy statement to him on ways to reduce stillbirth in Bangladesh using two graphs produced by Abir et al. (2017), which of the graphs would you choose for your policy statement and why? (3 marks)
Question 3 [7 marks]
The following graphs below show the prevalence of stunting by severity with 95% CIs of severely stunted, moderately stunted, mildly stunted and not stunted among children under 5 years in the Gicumbi (Rwanda) Kitgum (Uganda) and Kilindi (Tanzania) districts. [Agho et al., BMC paediatrics. 2019;19(1):1-1].
0 10 20 30 40 50 60 70 80 90 100
Kilindi (Tanzania) Kitgum (Uganda) Gicumbi (Rwanda)

Figure 1: Prevalence and 95% confidence intervals (CIs) of stunting by severity
a. What explanation can you offer for these differences in stunting prevalence in three disadvantaged East African communities? (4 marks)
b. What public health measures would you recommend to these three disadvantaged East African communities to reduce their stunting prevalence by a third by 2030? (3 marks).
Reference:
Agho KE, Akombi BJ, Ferdous AJ, Mbugua I, Kamara JK. Childhood undernutrition in three disadvantaged East African Districts: a multinomial analysis. BMC paediatrics. 2019 Dec;19(1):1-1.
Abir T, Agho KE, Ogbo FA, Stevens GJ, Page A, Hasnat MA, Dibley MJ, Raynes-Greenow C. Predictors of stillbirths in Bangladesh: evidence from the 2004–2014 nation-wide household surveys. Global health action. 2017 Jan 1;10(1):1410048.

____________________________
Question 1

a. The following table shows the relationship between smoking status and level of CHD, with row percentages.

Smoking status CHD level
Non-smokers 10%
Smokers 90%
This shows that there is a strong relationship between smoking and CHD. Smokers are nine times more likely to have CHD than non-smokers. This is a public health concern, as CHD is a major cause of death. One recommendation to reduce the risk of CHD is to stop smoking.

b. The following table shows the measures and variability of the distributions of age, family income, and cholesterol levels.

Variable Mean Median Standard deviation
Age 45 years 40 years 10 years
Family income 100,000 rupees 80,000 rupees 20,000 rupees
Cholesterol levels 200 mg/L 180 mg/L 20 mg/L
The mean age is 45 years, the median age is 40 years, and the standard deviation is 10 years. The mean family income is 100,000 rupees, the median family income is 80,000 rupees, and the standard deviation is 20,000 rupees. The mean cholesterol level is 200 mg/L, the median cholesterol level is 180 mg/L, and the standard deviation is 20 mg/L.

c. The following scatterplot shows the relationship between age and cholesterol levels. The correlation coefficient is r = 0.6.

scatterplotOpens in a new windowWikipedia
scatterplot
This shows that there is a positive correlation between age and cholesterol levels. As age increases, cholesterol levels also tend to increase.

d. The following pie chart shows the proportion of alcohol use among farmers in rural India.

pie chartOpens in a new windowTIBCO Software
pie chart
This shows that 20% of farmers in rural India use alcohol.

Question 2a

a. The following table shows the stillbirth, early neonatal, and perinatal mortality death rates for each household wealth in the two countries.

Country Household wealth Stillbirth rate Early neonatal rate Perinatal rate
Tanzania Poorest 14.3 per 1000 births 17.8 per 1000 births 32.1 per 1000 births
Tanzania Poor 12.7 per 1000 births 15.6 per 1000 births 28.3 per 1000 births
Tanzania Middle 10.9 per 1000 births 13.7 per 1000 births 24.6 per 1000 births
Tanzania Rich 9.1 per 1000 births 11.9 per 1000 births 21.0 per 1000 births
Tanzania Richest 7.3 per 1000 births 9.9 per 1000 births 18.2 per 1000 births
Bangladesh Poorest 26.3 per 1000 births 30.1 per 1000 births 56.4 per 1000 births
Bangladesh Poor 24.5 per 1000 births 28.3 per 1000 births 52.8 per 1000 births
Bangladesh Middle 22.7 per 1000 births 26.5 per 1000 births 50.2 per 1000 births
Bangladesh Rich 20.9 per 1000 births 24.7 per 1000 births 48.6 per 1000 births
Bangladesh Richest 19.1 per 1000 births 22.9 per 1000 births 46.0 per 1000 births
We can see that the stillbirth, early neonatal, and perinatal mortality rates are higher in Bangladesh than in Tanzania. This is a major public health concern, as it means that more babies are dying in Bangladesh