Research: Depression's Role in Adolescent Obesity Development

This research report investigates the role of depression in the development and persistence of obesity among adolescents, particularly young girls. Utilizing data from the National Longitudinal Study of Adolescent Health, the study examines the mood and body mass index (BMI) of 9374 adolescents to...Read More

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Research
Title: A Prospective Study of the Role of Depression in the Development and Persistence
of Adolescent Obesity
Abstract
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Abstract word count 200
Depression is viewed as a contributor to adolescent obesity especially in young girls. This
paper will examine the influence of depression on the occurrence and severity of obesity
amongst adolescents. The primary objective of this study is to determine whether depressive
mood has a predictive influence on the occurrence and persistence of obesity in adolescents. It
will also examine previous studies that have proposed a direct correlation between adolescent
depression and considerably high body mass index in the same demographic. Data collection
was done through the use of a secondary source in the form of the National Longitudinal
Study of Adolescent Health. The data gathered relates to youths in the grade bracket 7 to 12.
The individuals addressed in the data had to meet several criteria to qualify for the
assessment: less than 20 years of age; have a guardian or parental figure at homes; and lastly
the participants completed the in-home interview. The methodology examines the mood of
9374 adolescent against their body mass index to determine whether or not a relationship
exists between depression and obesity within the cohort. The results will establish what
percentage of the entire focus group was overweight, obese, and exhibited symptoms of
depression.
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Text
Research reports should be written in IMRAD format (Introduction, Methods, Results and
Discussion).
Case reports should comprise a Clinical record followed by a Discussion.
Text word count 1208
Introduction
Obesity has been a critical issue in most developed nations and is regarded a major public
health issue by humanitarian organizations like the United Nations. It is estimated that 300,00
deaths a year are attributed to obesity and obesity-related complications. Even thou the
increment of obesity in the general populace has been viewed as considerably uniform across
all races, age groups, gender facets, and social classes; the prevalence of obesity amongst
individuals aged between 14 and 29 years has blossomed considerably over the past (Corona,
2014). This suggests that there are several factors that are making adolescents more
susceptible to obesity. Research has indicated a strong correlation between adolescent obesity
and early adulthood weight issues. Moreover, psychiatrists believe that there are several
psychosocial issues that significantly attribute to the development of adolescent obesity; such
as, family instability and financial difficulties at home. Economists indicate that obese
adolescent who fail to lose weight become overweight adults who earn considerably less
compared to their healthier counterparts in the workforce. This economic situation is
especially true for women, since, obese females are presented with fewer and less lucrative
job opportunities compared to healthier women with the same work qualifications. As such,
some groups feel that addressing adolescent obesity is a step in the right direction towards
resolving, social and economic inequalities (Goodman & Whitaker, 2002).
Method
The study data was retrieved from the National Longitudinal Study of Adolescent Health with
the baseline year being 1995 and follow-up year 1996 for youths aged less than 20 years
attending any grade between 7 and 12. There were five inclusion criteria that were employed
to the data sample of 9374 individuals. These inclusion criteria were founded on: the age of
the participants; the nature of parental guardianship; BMI; interviewee responses; and race.
Due to the disparities that exist in the definition of obesity and depression across racial/ethnic
groups, the study was limited to white participants (Fuller, et al., 2017). Therefore, the 9374
participant where entirely white adolescents. The data was divided into two groups un-
weighted and weighted sample size that were there represented in percentage form in tables.
To avoid the occurrence of a Type I error the weighted sample was normalized to ensure that
it matched the observed sample size. Regression analysis was done with the aid of SPSS
version 19; while, all tests of statistical significance and descriptive statistics were performed
in Microsoft Excel 2013 to address issues of design effects. Two tests were used to evaluate
the data with regard to bivariate and multivariable analyses. For bivariate a logistic regression
was employed while a linear regression techniques was employed for multivariate analysis.
(Askari, et al., 2013)
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Multivariate analysis was performed to assess the relationship between obesity at baseline,
depressed mood, obesity at follow-up, and BMI Z-scores; as such, the regression analysis
dealt entirely with these four variables. Another multivariate regression examined the
association between depressed mood at follow-up and obesity at baseline. A Pearson
correlation analysis at r=0.05 was performed that focused on the evaluation of socioeconomic
status of the participants' families by comparing parental education and household income.
Another multivariate analysis was conducted with parental education and household income
as the independent variables, and adolescent obesity as the dependent variable. The analysis
variables were not consistent; since, the education and income categories had numerous
missing data due to the reluctance of parents to expose their financial situation and academic
achievements (Goodman & Whitaker, 2002).
Results
The correlation and descriptive analysis performed in Microsoft excel on participants'
baseline data revealed that 12.9% were overweight, 8.8% harbored depressed mood, and 9.7%
were obese. There was no significant association between those obese at baseline and those
with depressed mode at baseline. Only 9.0% of all depressed individuals at baseline were
actually obese, while, 9.8% of non-depressed adolescents were found to be obese; hence,
there is no significant association between depression and obesity. Moreover, only a minute
8.2% of all obese individuals were found to be depressed, while, 8.9% of all non-obese
participants were indeed depressed. In the multivariate analysis having obese parent was
found to be a great influence on the occurrence of adolescent obesity. In second part was the
gender of the participants. Women were found to be more obese and depressed than their
male counterparts. Moreover, correlation was established between all behavioral and
psychological variables, and baseline depression. However, the same could not be established
between the aforementioned covariates and obesity at follow-up. 9.7% were discovered to be
obese at follow-up which is 0.8% more that those who were found to be depressed (Goodman
& Whitaker, 2002).
In addition, obesity was found in 79.7% of all individuals who were obese at baseline, 1.8%
of all recorded to be normal weight at baseline, and 18.5% of all participants registered at
baseline as overweight. In biviariate analyses, weak association between baseline depression
and follow-up obesity was discovered. The analysis revealed that 12.4% of all participants
found to be depressed at baseline were registered as obese at follow-up; and, only 9.4% of
those not depressed at baseline were actually obese at follow up. The p-value for this bivariate
analysis was 0.048 which is lower than 0.05 making the regression statistically significant. In
the multivariate analyses, the relationship between baseline depression (independent variable)
and follow-up obesity (dependent variable) was also statistically significant. The magnitude
of the latter was similar to that of those who were non-depressed at baseline but developed
obesity one year later at follow-up. Logistic regression between behavioral and psychological
covariates supported the information presented above with regard to baseline depression and
follow-up obesity. However, with the introduction of cigarette smoking as a variable the
association between the two primary variables was lost (Pan, et al., 2011).
Discussion of Results
The findings observed in the research report AT1 are consistent with those observed in this
paper. For instance, the manner in which depression is treated as a causative agent instead of
a side attribute of obesity and being over-weight creates a direct correlation between the a
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person's mental state and their eating habit. Moreover, the two studies emphasise the
importance of mental health towards the attainment of commendable dietary habits.
Nevertheless, the two assessment do differ in terms of how best to tackle the issue of
depression amongst adolescent in order to aid in weight -loss and improved self-esteem.
Under ATI the research favours positive re-enforcement in the process by creating a
responsive communication channel that will allow children and adolescents to openly express
their opinion and problems without judgement. While AT2 is founded on the use of
preventive measures that will ensure children and adolescents are sheltered from depression
and coincidently obesity. Nevertheless, both assessment studies borrow heavy from previous
research projects in their respectively areas of interest. In spite of the fact they do expound
significantly on the underlining subject matter.
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References
References should be in Vancouver style and should not appear as endnotes.
References to material on the Internet should include the organisation, the page title, the article title and
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References
1. Corona M. The Association Between Depression and Overweight/Obesity Among Ethnic
Minority Youth. Seattle:; 2014.
2. Goodman E, Whitaker RC. A Prospective Study of the Role of Depression in the
Development and Persistence of Adolescent Obesity. Journal of American Academy of
Pediatrics. 2002;: p. 1-10.
3. Fuller NR, Burns J, Sainsbury A, Horsfield S, Luz Fd, Zhang S, et al. Examining the
association between depression and obesity during a weight management programme.
Wiley & Sons. 2017;: p. 1-24.
4. Askari J, Hassanbeigi A, Khosravi HM, Malek M, Dordanehnbeigi , Pourmovahed Z, et al.
The Relationship Between Obesity and Depression. Elsevier. 2013;: p. 796-801.
5. Pan A, Sun Q, Czernichow S, Kivimaki M, Okereke OI, Lucas M, et al. Bidirectional
Association between Depression and Obesity in Middle-aged and Older Women. HHS
Public Access. 2011;: p. 595-602.
6. Jantaratnotai NJiataNN, Mosikanon K, Lee Y, McIntyre RS. The interface of depression
and obesity. Obesity Research Clinical Practice. 2017;: p. 1-30.
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Comaprison of AT1 And AT2
Criteria Similarities Differences
Sample Size The research has a relatively large
sample size
The research group is made up of
young people
Data collection The use of secondly data sources Use of data from different sources
The se of primary data sources difference in the research publication
used: AT1 (mostly international) and
AT2 (mostly local)
Analysis
Technique
Statistics-based Use of different time-frame
assessment: AT1 (constinous) and
AT2 (discrete i.e. base year and
follow-up year)
quantitative in nature
Results Majority of the particpants were
influenced in one way or the other
by depression to becoming
obesity or overweight
Conclusion A correlation between obesity and
causative factors like depression
and poor self-esteem
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