HBS108: Health Information and Data Assignment 2 Analysis and Solution

This assignment solution for HBS108, titled "Health Information and Data: Assignment 2," provides a comprehensive analysis of various aspects of health and data, including cross-sectional survey design, scales of measurement, and potential biases in data collection, such as underreporting of calo...Read More

Assignment 2 1
HBS108 HEALTH INFORMATION AND DATA: ASSIGNMENT 2
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Assignment 2 2
HBS108 Health Information and Data: Assignment 2
Task A
Q1(a) Cross-sectional survey design
Q1(b) Ordinal scale
Q1(c) i) Ratio scale
ii) Ratio scale
iii) Interval scale
Q1(d) Caloric intake may be under-reported since most individuals tend to
underestimate the sizes of their food portions, they overlook the consumption of foods
which are perceived as unhealthy. According to Basiotis, et al., (2000), people also
have the tendency of exaggerating foods they perceive to be good for their health.
Most individuals especially obese individuals tend to overestimate the energy they
expend in physical activities. Persons who present with the inability to shed weight
regardless of a history of caloric restriction are among a group of individuals who are
prone to misreport their caloric intake and level of physical activity (Lichtman, et al.,
1992).
This is a measurement bias because they are resulting from the poor measurement of
the outcome being measured.
Q1(e) The figure 24.9 means that obese women made up 24.9% of the total
population. This is within the range of 23.1% to 26.8%. The 95% confidence limit
(23.1-26.8) means that there is a 95% chance that the interval 23.1-26.8 contains the
true population mean.
Q1(f) In the period between 1988 and 1994, 24.9% of women were obese compared
to 35.4% in the period between 2009 and 2010. With a 95% confidence interval, in

Assignment 2 3
1988-1995, there is a 95% chance that between 23.1% and 26.8% of the total
population were obese females, whereas with the same interval, between 33.6% and
37.3% of the total population were obese females in 2009-2010.
Q1(g) Yes, there was a statistically significant change in the likelihood of having
obesity over the years. An odds ratio of 1.026 means that an individual had an
increased chance (by 1.026) of being obese in the following year. The 95%
confidence interval for 1.026 ranged from 1.019 to 1.033.
Q1 (h)
(i) This observation can be supported by a statistically insignificant change in
the amount of calories taken between the two periods. In 1988-1994,
women aged eighteen years and older only consumed a mean of 1761 Kcal
whereas, in 2009-2010, they consumed a mean of 1781 Kcal. The
difference between the mean is insignificant. The kcal/day (95% CI) data
was used instead of the APC because the latter does not take into account
the changing rates.
(ii) The authors cite the lack of evidence in the increase in the average daily
caloric intake over the previous two decades. The support their observation
using a 2011 study by Austin and colleagues who made a conclusion of a
decrease in caloric intake in the recent years (Austin, et al., 2011).
(iii) Yes, I would recommend programs to focus on just increasing physical
activity. This is supported by both the conclusion of the authors who stated
that their results laid more emphasis on physical activity as proposed in the
IOM report on obesity. The authors associate BMI and waist
circumference trends with physical activity and not daily caloric intake
(Ladabaum, et al., 2014).

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Task B
Q2(a) The aim of the study was to find out what facilitated or hindered weight loss
and weight loss maintenance among women who participated in a comparative trial
that ran for 18 weeks whose aim was to promote weight loss using and energy-
restricted diet.
Q2(b)
i. After successive weight loss, maintenance of the new weight status often
remains a challenge.
ii. Dietary programs and interventions that often target weight loss in the short
term often fail to support maintenance of the loss over a longer period of time.
iii. About fifty percent of weight lost is often regain within a year, and often,
individuals return to their baseline weight within three to five years.
Q2(c) The authors used questionnaires as the data collection tool. Questionnaires were
ideal for the study aim as they facilitated probing and collection of data on bath
facilitators, barriers and limitations to weight loss maintenance, and also facilitated
investigation of weight regulation, eating patterns and perceptions of snacking among
the participants. Questionnaires were the most ideal as they facilitated the above and
also addresses constructs of theories including health belief model, social cognitive
theory and theory of planned behaviour (Metzgar, et al., 2015).
Q2(d)
A - Planning ahead, mindfulness and awareness
B – Accountability and support
C - Portion control
D – Nutrition education
E – Motivation

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F - Weight loss journey
Q2(e)
i. Tailor programmes to an individual’s needs, biology, physiology, and
stage in life.
ii. Programmes to reinforce the women’s planning skills
iii. Portion control strategies and education are fundamental components of
weight loss.
iv. The inclusion of the elements of social support networks into weight loss
and weight loss maintenance strategies.
Task C
Q3(a) Is a randomized trial design. The findings have good internal validity because
the study design avoids confounds. The authors have also demonstrated the internal
validity using the statement ‘support the internal validity of our data’ (Foster-
Schubert, et al., 2011).
In addition, the design and its conduct have striven to eliminate all possibilities of
bias.
The study randomised a total of 439 women out of the 126, 802 eligible women. This
represented only 0.3% of the total population. This may affect the external validity of
the study owing to the fact that such a small sample is bound to have extreme scores
which are mot balanced by more moderate scores. Therefore, such a small sample
magnifies the probability of sampling error, and as a result, the conclusions arrived at
ought to be tentatively generalised to the entire target population (Wright & Lake,
2016). Drawing conclusions from a small sample may not reflect the total target
population.

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Q3(b) The element of randomisation could have contributed to the finding.
Randomisation is a strength because it helps avoid selection bias.
Q3(c)
Independent variable is weight and body composition
Dependent variables are diet and exercise.
Q3(d) The group that was on both diet and exercise with a -7.5% change.
The p-value for the change in this group when compared to the control group is
<.0001. It is thus statistically significant. The p-value indicates strong evidence that
diet and exercise can help in the regulation of body weight and composition. A p-
value of =0.05 will have indicated no statistical significance in the interventions
applied or not applied in either group whereas a p-value of >5 indicates no positive
intervention in the diet and exercise group.
Q3(e) The diet and exercise group evidenced the greatest changes.
Task D – Conclusion
Q4
On healthy eating and physical activity’s contribution to weight control, Ladabaum et
al. (2014) claim that there is no evidence supporting increased caloric intake and
obesity among adults. As such, they recommend that obesity can be reduced through
increased physical activity only. A randomised trial by Foster-Schubert et al. (2012)
offers a better insight into the same by demonstrating a strong contributor of diet and
exercise combined to weight management.
Pertaining to the barriers and facilitators of attaining healthy weight and maintenance,
Metzgar et al. (2015) identifies the following factors. Lifestyle change whereby one
is expected to incorporate strategies for sustainable dietary and modification of
physical activity, second is nutrition and education in which there is the need for

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dietitians to disseminate accurate nutrition information, and lastly is exercise, which
ought to be incorporated into weight loss and weight loss maintenance interventions.
Recommendation: There is the need for more comprehensive review of the
contradicting claims by the two groups of authors (Ladabaum et al. (2014) vs Foster-
Schubert et al (2012)) in order to establish the ideal solution.

Assignment 2 8
References
Austin, G., Ogden, L. & Hill, J., 2011. Trends in carbohydrate, fat, and protein intakes
and association with energy intake in normal-weight, overweight, and obese
individuals: 1971-2006.. Am J Clin Nutr, 93(4), pp. 836-43.
Basiotis, P., Lino, M. & Dinkins, J., 2000. Consumption of Food Group Servings:
People’s Perceptions vs. Reality. Washington, D.C: USDA Center for Nutrition
Policy and Promotion.
Foster-Schubert, K. et al., 2011. Effect of diet and exercise, alone or combined, on
weight and body composition in overweight-to-obese post-menopausal. Obesity
(Silver Spring), 20(8), pp. 1628-1638.
Ladabaum, U., Mannalithara, A., Myer, P. & Singh, G., 2014. Obesity, abdominal
obesity, physical activity, and caloric intake in US adults: 1988 to 2010. American
Journal of Medicine, 127(8), pp. 717-727.
Lichtman, S. W. et al., 1992. Discrepancy between Self-Reported and Actual Caloric
Intake and Exercise in Obese Subjects. The New England Journal of Medicine,
Volume 327, pp. 1893-1898.
Metzgar, C. J., Preston, A. G., Miller, D. L. & Nickols-Richardson, S. M., 2015.
Facilitators and barriers to weight loss and weight loss maintenance: a qualitative
exploration. Journnal of Human Nutrition and Dietetics, 28(6), pp. 593-603.
Motulsky, H., 2010. Intuitive Biostatistics: A Nonmathematical Guide to Statistical
Thinking. 1st ed. Oxford: Oxford University Press.
Wright, L. L. & Lake, D. A., 2016. Basics of Research for the Health Professions.
[Online]
Available at: http://www.pt.armstrong.edu/wright/hlpr/toc.htm
[Accessed 8 September 2017].