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CAN811S- COMPUTER APPLICATIONS IN NUTRITION - 1st Opp - JUNE 2022 |
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n Am IBIA u n IVERs ITY
OFSCIEnCEAno TECHno LOGY
FACULTY OF HEALTH, APPLIED SCIENCES AND NATURAL RESOURCES
DEPARTMENT OF HEALTH SCIENCES
QUALIFICATION: BACHELOR OF HUMAN NUTRITION
QUALIFICATION CODE: 08BOHN
COURSE CODE: CAN 811S
LEVEL: 8
COURSE NAME: COMPUTER APPLICATIONS IN
NUTRITION
SESSION: JUNE 2022
PAPER: THEORY
DURATION: 3 HOURS
MARKS: 100
EXAMINER(S)
FIRST OPPORTUNITY EXAMINATION QUESTION PAPER
MRS MARI-LOUISE JEFFERY
DR DIBABA GEMECHU
MODERATOR: MR ERICKUUKULE
INSTRUCTIONS
1. Answer ALL the questions.
2. Write clearly and neatly.
3. Number the answers clearly.
PERMISSIBLE MATERIALS
Nonprogrammable scientific calculator
THIS QUESTION PAPER CONSISTS OF 9 PAGES (Including this front page)
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SECTION A
QUESTION 1
(10 MARKS)
Select the most appropriate answer from the options provided. (Each correct answer earns 1
mark)
1.1 Communication Technology has shortened distances and eroded borders in tapping a global
store of knowledge.
a. True
b. False
1.2 Self-monitoring of diet and physical activity are commonly integrated features of
smartwatches and individuals may record their dietary intake and physical activity, while
establishing goals to meet in these areas, thereby receiving continuous data feedback on their
behaviour.
a. True
b. False
1.3 Information stored in paper files are safe and have no risk of being damaged or lost.
a. True
b. False
1.4 A Health care professional's duties and responsibilities related to telemedicine include:
a. Obtaining informed consent from the patient for the treatment to be given and the use of
telemedicine technology.
b. Providing a good quality service.
c. Ensuring confidentiality, security and safety of patients' personal information.
d. A, Band C.
1.5 In a food and beverage establishment only the departmental managers of the hotel need to
be well conversant with the operating system.
a. True
b. False
1.6 Profit not only is earned by sales, but also can be achieved by cost control.
a. True
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b. False
1.7 A point of sale (POS)system is able to generate:
a. A list of outstanding bills
b. Cashier reports
c. Sales analysis summary
d. Labor costs
e. All of the above
1.8 Nutritional values and allergens provided by the restaurant operator can be entered for raw
ingredients to automatically generate nutritional and allergen information for recipes and
menus which can be printed as a fact sheet or label or viewed on a point of sale terminal or
the establishment's website.
a. True
b. False
1.9 To achieve excellent performance levels at a food and beverage establishment it is necessary
to prevent wastage of materials caused by:
a. Poor preparation
b. Over-production
c. Failure to use standard recipes
d. All of the above
1.10 The main purpose of any business is to ensure staff satisfaction and engagement.
a. True
b. False
QUESTION 2
2.1 Define the following terms:
a. Nutrigenomics
b. Wearable and mobile phone technologies
C. A' la Carte menu
d. Food and beverage control
(10 MARKS}
(2)
(3)
(2)
(3)
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SECTION B
QUESTION 3
(10 MARKS)
3.1 Name the factors to be taken into consideration when selecting a computerized
dietary analysis programme.
(3)
3.2 Discussthe requirements for telemedicine consultations by health professionals.
(4)
3.3 List the information that is typically inserted into a recipe file in the menu
management system.
(3)
QUESTION 4
(20 MARKS)
4.1 Name and explain how information communication technology (ICT) can assist
in improving food security globally.
(12)
4.2 Name and discuss four (4) advantages of using a point of sale (POS)system.
(8)
SECTION C
QUESTION 5
(13 MARKS)
5.1. Describe the uses of the following commands in SPSS:
5.1.1. The compute command and the advantages of IF statement within this command. (3)
5.1.2. The aggregate files procedure.
(3)
5.2. Define the following terms:
5.2.1. Descriptive statistics
(1)
5.2.2. Inferential statistics
(1)
5.2.3. Variable
(1)
5.3. Classify each of the following first as qualitative or quantitative and second
as nominal, ordinal, interval or ratio scale measurements. One mark
for each correct classification.
(4)
5.3.1. Socioeconomic status of a family when classified as low, middle and upper classes.
5.3.2. Blood type of patients: A, B, AB and 0.
5.3.3. The number of malnourished infants in Kavango region.
5.3.4. The body lengths (in inches) of 10 full-term infants at birth.
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QUESTION 6
(17 MARKS)
6.1 The following summary table represents a descriptive summary of wasting among children <5
years by characteristics such as sex of a child, had diary product, fresh foods, and region
(sample result from 2013 NDHS).Answer the following question based on this table.
Male
;g
'ti
Female
0
X
,.CnJ
Total
Yes
c·.; -0
e 0 a.
No
Yes
-"0 '
.... .00...
No
Caprivi
Erongo
Hardap
Karas
Kavango
Khomas
Wasting Categories
Wasted
Cou Row Column
nt
(%) (%)
104 (a) 66.2
Table
(%)
5.9
53 6.0 (b)
(c)
157 8.9 100.0 8.9
56 9.9 35.7
3.2
101 8.4 64.3
5.7
60
12.5 38.2 (i} 3.4
97 7.5 61.8
5.5
14 8.0 8.9
0.8
4
3.6 2.5
0.2
14 9.8 8.9
0.8
7
5.8 4.5
0.4
23 12.7 14.6
1.3
11
9_5(ii) 7.0
0.6
Kunene
9
6.2 5.7
0.5
Ohangwen 12 7.4 7.6
0.7
a
Omaheke
17 13.3 10.8
1.0
Omusati
12 9.0 7.6
0.7
Oshana
12 12.9 7.6
0.7
Oshikoto
13 9.9 8.3
0.7
·.-. C
0
Otjozondju 9
7.0 5.7
0.5
aC:J
pa
Not wasted
Row
Count (%}
772
88.1
Column
{%}
48.0
837
1609
511
1098
419
(d) 52.0
91.1 100.0
90.1 31.8
91.6 68.2
87.5 26.0
1190
92.5 74.0
161
92.0 10.0
107
96.4 6.7
129
90.2 8.0
114
94.2 7.1
158
87.3 9.8
103
90.4 6.4
136
93.8 8.5
150
92.6 9.3
111
86.7 6.9
121
91.0 7.5
81
87.1 5.0
118
90.1 7.3
120
93.0 7.5
Table
(%}
43.7
47.4
91.1
28.9
62.2
23.7
67.4
9.1
6.1
7.3
6.5
8.9
5.8
7.7
8.5
6.3
6.9
4.6
6.7
6.8
Total
Count
876
890
1766
567
1199
479
Column
(%}
49.6
(e)
100.0
32.1
67.9
27.1
1287
72.9
175
9.9
111
6.3
143
8.1
121
6.9
181
10.2
~I 114
145
8.2
162
9.2
128
7.2
133
7.5
93
5.3
131
7.4
129
7.3
6.1.1 Fill in all the missing values (a)-(e)
(5)
6.1.2 Interpret the values in cells (i), (ii) and (iii).
(6)
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6.2 The following graph represents a histogram for age of household head.
Comment on the age of household head based on
this histogram.
(2)
100 t------------------------
Mean=44.54
Std. Dev.= 15.957
l•J=1,517
80 -----
c;' 60
C:
Cl)
::l
C'
:!!
11.
40
20
20
40
60
80
100
Age of household head
6.3 Consider the dataset below and aggregate the variable Weight in kg using
Nutritional status as the break variable. Use the minimum as aggregate
function.
Gender Height Weight Nutritional status
in CM in kg
Male
174
96
Obesity
Male
185
110
Obesity
Female 185
110
Obesity
Female 195
104
Pre-obesity
Male
149
61
Pre-obesity
Male
189
104
Pre-obesity
Male
155
51
Normal weight
Male
191
79
Normal weight
Male
174
90
Pre-obesity
Female 169
103
Obesity
(4)
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QUESTION 7
{20 MARKS)
7.1 The following SPSSoutput is regarding the association between wealth index of the
household and nutritional status of under 5 children based on
stunting.
(8)
Crosstab
Count
Wealth index Poorest
Poorer
Middle
Richer
Richest
Total
Stunting categories
Stunted Not Stunted Total
108
256
364
92
245
337
82
238
320
55
266
321
17
158
175
354
1163
1517
Chi-Square Tests
Asymptotic
Significance (2-
Value
df
sided)
Pearson Chi-Square
37.113a 4
<0.001
Likelihood Ratio
40.775 4
<0.001
Linear-by-Linear
33.256 1
<0.001
Association
N of Valid Cases
1517
Do these results reveal any association between wealth index of the household and
nutritional status of under 5 children? Use a = 0.05. Your answer should include the
following:
7.1.1 State the null and alternative hypothesis
(2)
7.1.2 The degree of freedom
(1)
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7.1.3 The test statics: Pearson-chi-square test statistics
(1)
7.1.4 The rejection region based on the p-value.
(1)
7.1.5 Decision and conclusion
(3)
7.2 Using the table below and at 5% level of significance, test whether the population
mean birth weight in grams is different from 2500g. You should state the null and
alternative hypothesis and report the observed p-value (round to four decimal places)
in your interpretation.
[5]
One-Sample Statistics
Std.
N Mean Deviation
Birth weight in grams 151 4003.5 2396.781
70
Std.
Mean
61.537
Error
One-Sample Test
Test Value = 2500
Mean
95% Confidence Interval of
Sig. (2- Differenc the Difference
t
df tailed)
e
Lower
Upper
Birth weight in 24.433 1516 <0.001 1503.505 1382.80
1624.21
grams
7.3 In a study to determine the relationship between Iron (µmol/L) versus Transferrin saturation
(%} for pregnant women attending ANC in four regions of Namibia, Transferrin saturation y is
thought to be a linear function of Iron x. Answer the following questions based on the SPSS
results given below.
7.3.1 What do you conclude about the relationship between the two variables
based on a scatter plot produced?
(2)
7.3.2 Test for the significance of the correlation between the two variables.
You should state the null and alternative hypothesis and report the
observed p-value (round to four decimal places) in your interpretation.
(5)
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100.00 -·-
R2 Linear= 0.661
80.00
e.::.
C
0
60.00
i
"'.CE 40.00
C
20.00
0
0
0
0 Do
0 00
00
0
i9
o e Qi
0
0
0
0
0
0
0
o
-1.8+1.42"X
,~,,ogi..;'/O'cr;o,.-.::o;:;:&',--o"·
OO 0
00
.00 ·-
.00
10.00
20.00
30.00
40.00
Iron (µmol/L)
50.00
Correlations
Transferrin
saturation
(%)
Transferrin saturation Pearson Correlation 1
(%)
Sig. (2-tailed)
N
336
Iron (µmol/L)
Pearson Correlation .813**
Sig. (2-tailed)
.000
N
336
**. Correlation is significant at the 0.01 level (2-tailed).
60.00
Iron (µmol/L)
.813**
<0.001
336
1
336
GOOD LUCK!
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