Chapter 1 An Example (Characteristics of Women with Depression and Eating Disorders)

The objective of the present study was to assess traits present in women whom have either depression or an eating disorder, along with a control sample, in a sample of women from different demographic and educational backgrounds. Several measures were taken from 516 Women aged 18 or above. Questionnaires for screening eating disorders and Depression, Anxiety and Stress Scale, perfectionism and self esteem scores were performed on participants.

The underlying factors, , which can cause someone to have an eating disorder, depression or both are of interest in how depression and eating disorders are related for better diagnosis if the disorders are co-morbid.

1.1 Data set source and description

This data set was obtained from COGSTATE, Cogstate is an Australian leading cognitive science company.

library(RCurl)
library(formatR)

x = getURL("https://raw.githubusercontent.com/Phayder/Datasets/main/CogData.txt")
CogData = read.delim(text = x,na.strings = '#NULL!')


knitr::kable(
  head(CogData, 20), caption = 'Top 20 Observations',
  booktabs = TRUE
)
Table 1.1: Top 20 Observations
Age Living State Studying EduCurrent EduHighest DiagGroup EDE_Q_1 EDE_Q_2 EDE_Q_3 EDE_Q_4 EDE_Q_5 EDE_Q_6 EDE_Q_7 EDE_Q_8 EDE_Q_9 EDE_Q_10 EDE_Q_11 EDE_Q_12 EDE_Q_13 EDE_Q_14 EDE_Q_15 Binge Num_Binge Num_LostControl LostControl_NoBinge Num_LostCon_NoBinge Purging Laxatives Diuretics Ex_Hard EDE_Q_29 EQE_Q_30 EDE_Q_31 EDE_Q_32 EQE_Q_33 EDE_Q_34 EDE_Q_35 EQE_Q_36 GlobalEDEQ OCD_Symptoms Height HeightMeters Weight BMI Perfectionism_Total Depression_Total Anxiety_Total Stress_Total DASS_Total Self_Esteem_Total
25 2 3 1 3 2 4 6 3 6 6 6 6 6 0 1.0 6 6 6 6 6 6 2 NA NA 1 2 0 1 0 1 6 6 6 6 6 6 6 6 105 45.00 157 1.57 42 17.04 168.00 8 10.00 15 33.00 8
37 3 2 2 NA 4 4 6 0 6 6 6 6 6 6 6.0 6 6 6 6 6 5 1 20 20 2 NA 0 0 0 0 6 6 0 6 6 4 6 6 96 10.00 163 1.63 61 22.96 145.00 11 4.00 10 25.00 7
25 1 2 1 3 2 4 6 3 4 6 6 6 6 1 5.0 6 6 6 6 6 6 1 1 1 1 1 1 1 0 0 6 6 0 6 6 6 6 6 97 23.00 156 1.56 60 24.65 135.00 NA NA NA NA NA
19 1 3 1 3 2 4 4 1 6 5 3 3 2 1 2.0 6 3 2 6 4 3 2 10 10 1 10 0 0 0 1 6 4 0 2 4 0 5 2 66 3.00 164 1.64 49 18.22 116.00 2 2.00 9 13.00 13
22 1 3 1 3 2 4 0 0 0 0 6 6 6 0 0.0 0 6 0 0 0 0 2 NA NA 2 NA 0 0 0 0 6 6 2 6 6 6 2 2 48 2.00 172 1.72 43 14.53 62.00 6 11.05 11 28.05 27
19 2 2 1 3 2 4 5 2 6 6 6 5 6 3 1.0 6 4 6 6 6 5 1 5 1 1 10 0 0 0 1 6 6 6 6 6 4 6 6 99 5.00 157 1.57 54 21.91 145.00 12 2.00 9 23.00 8
49 3 3 1 4 4 4 6 0 3 6 0 1 6 0 1.0 6 1 6 3 3 3 2 NA NA 2 NA 0 0 0 0 5 5 6 5 6 5 6 5 73 28.59 156 1.56 49 20.13 118.61 1 5.00 9 15.00 17
19 1 2 2 NA 3 4 6 6 6 6 6 6 6 1 1.0 6 6 6 6 6 4 2 NA NA 1 10 0 0 0 1 5 6 6 4 5 6 6 6 104 45.00 170 1.70 40 13.84 151.00 18 15.00 21 54.00 9
18 1 3 1 3 2 4 6 4 4 6 6 4 4 1 1.6 4 3 4 5 4 4 2 NA NA 1 7 0 0 0 0 2 5 6 4 4 4 4 4 78 1.00 169 1.69 53 18.56 72.00 NA NA NA NA NA
43 5 6 2 NA 5 4 6 0 5 6 0 1 1 0 0.0 2 2 3 3 6 2 2 NA NA 2 NA 0 0 0 1 6 6 6 6 4 0 5 4 72 8.00 163 1.63 60 22.58 135.61 NA NA NA NA NA
34 3 3 2 NA 4 4 1 0 1 0 1 1 1 0 0.0 6 1 6 5 2 4 2 NA NA 1 3 0 0 0 0 4 4 2 4 4 0 4 4 50 4.00 181 1.81 68 20.76 95.00 NA NA NA NA 16
46 5 2 2 NA 2 4 6 2 5 2 4 2 4 1 1.0 5 2 6 5 5 5 2 NA NA 1 20 0 1 0 0 6 6 5 5 4 1 5 2 77 5.00 170 1.70 64 22.15 86.00 20 1.00 7 28.00 14
20 2 3 1 3 2 4 6 5 6 6 6 4 6 6 0.0 6 3 6 6 6 3 1 28 28 2 NA 1 0 0 0 6 6 5 6 6 4 4 4 96 34.00 167 1.67 70 25.10 NA NA NA NA NA NA
30 4 3 2 NA 2 4 6 0 6 6 2 6 0 0 0.0 6 6 6 6 6 5 2 NA NA 2 NA 0 0 0 1 6 6 0 6 6 6 6 6 92 2.00 171 1.71 76 25.99 56.00 NA NA NA NA NA
19 2 3 1 3 2 4 6 5 6 6 6 5 6 1 1.0 6 6 6 6 6 6 2 NA NA 1 2 1 1 0 1 6 6 2 6 6 6 6 6 103 33.00 178 1.78 55 17.36 140.00 13 14.00 15 42.00 9
28 2 2 2 NA 5 4 6 1 6 6 6 6 6 2 3.0 6 6 4 5 6 3 1 10 10 1 5 0 1 0 1 5 3 6 6 5 5 6 4 93 27.58 168 1.68 58 20.55 83.11 5 7.00 9 21.00 26
23 1 2 2 NA NA 4 6 4 6 6 6 4 6 1 3.0 6 4 6 6 6 6 1 2 0 1 2 0 0 0 1 6 6 3 6 6 5 6 6 99 36.00 168 1.68 68 24.09 167.00 7 7.00 8 22.00 3
22 1 3 2 NA 2 4 6 5 6 5 6 6 6 0 1.0 6 6 6 6 6 6 1 27 3 1 27 0 0 0 1 6 6 6 6 6 6 6 6 106 28.00 165 1.65 52 19.10 131.65 10 15.00 18 43.00 8
39 4 3 2 NA NA 4 6 0 6 6 0 5 6 4 1.0 6 4 5 6 6 4 1 5 4 1 6 1 0 0 0 4 4 3 6 6 3 5 5 82 29.00 162 1.62 64 24.39 142.00 12 5.00 13 30.00 12
24 2 2 2 NA 4 4 6 1 6 6 6 6 6 3 0.0 5 6 6 6 6 5 1 15 15 1 10 1 0 0 0 6 4 6 6 4 4 6 6 98 NA NA NA NA NA NA NA NA NA NA NA

1.2 Data pre-processing and preliminary analysis

library(RCurl)
library(formatR)

x = getURL("https://raw.githubusercontent.com/Phayder/Datasets/main/CogData.txt")
CogData = read.delim(text = x,na.strings = '#NULL!')
CogData$Studying[CogData$Studying==1]="Yes"
CogData$Studying[CogData$Studying==2]="No"
CogData$DiagGroup[CogData$DiagGroup==4]="Eating Disorder"
CogData$DiagGroup[CogData$DiagGroup==7]="Depression"
CogData$DiagGroup[CogData$DiagGroup==10]="Control"
CogData$EduHighest[CogData$EduHighest==1]="Did Not Complete Secondary College"
CogData$EduHighest[CogData$EduHighest==2]="Secondary College"
CogData$EduHighest[CogData$EduHighest==3]="TAFE"
CogData$EduHighest[CogData$EduHighest==4]="Undergraduate University Degree"
CogData$EduHighest[CogData$EduHighest==5]="Postgraduate University Degree"
CogData$EduHighest[CogData$EduHighest==6]="Other"

CogData$EduCurrent[CogData$EduCurrent==1]="Secondary College"
CogData$EduCurrent[CogData$EduCurrent==2]="TAFE"
CogData$EduCurrent[CogData$EduCurrent==3]="Undergraduate University Degree"
CogData$EduCurrent[CogData$EduCurrent==4]="Postgraduate University Degree"
CogData$EduCurrent[CogData$EduCurrent==5]="Other"
CogData$EduCurrent[CogData$EduCurrent==6]="Not Currently Studying"

CogData$Living[CogData$Living==1]="At home with parent(s)"
CogData$Living[CogData$Living==2]="With friends/roommates"
CogData$Living[CogData$Living==3]="Living Alone"
CogData$Living[CogData$Living==4]="With a partner(unmarried)"
CogData$Living[CogData$Living==5]="With a husband(married)"
CogData$DiagGroup = factor(CogData$DiagGroup, levels = c("Depression", "Eating Disorder", 
    "Control"))

CogData$EduHighest = factor(CogData$EduHighest, levels = c("Did Not Complete Secondary College", 
    "Secondary College", "TAFE", "Undergraduate University Degree", "Postgraduate University Degree", 
    "Other"))

CogData$EduCurrent = factor(CogData$EduCurrent, levels = c("Secondary College", "TAFE", 
    "Undergraduate University Degree", "Postgraduate University Degree", "Other", 
    "Not Currently Studying"))

CogData$Living = factor(CogData$Living, levels = c("At home with parent(s)", "
With friends/roommates", 
    "Living Alone", "With a partner(unmarried)", "With a husband(married)"))
##              Age(Years) Height(cm)   BMI
## median            26.00    166.000 21.85
## mean              28.79    166.211 22.85
## SE.mean            0.42      0.341  0.25
## CI.mean.0.95       0.83      0.670  0.48
## var               91.06     58.702 30.27
## std.dev            9.54      7.662  5.50
## coef.var           0.33      0.046  0.24

The majority of the participants were neither in the Depression or Eating disorder group, making up more than 70% of the total participants. The depression and eating disorder group are a lot smaller, however we only need a sample size as big as 30 to guarantee normality.

There seems to be a connection between the highest level of education attained and both disorder groups. There was no information on what the

, in highest level of education attained was, one possibility could be homeschooling, or no education attained if that would fall under is not clear however.

The number of participants with an eating disorder seem to be significantly concentrated in current highschool students.

There seems to be a connection between living with someone in a relationship and the proportion with those of either disorder compared with those either living alone or at home with parents.

It appears that those with either an eating disorder or depression score similarly with each other in almost all the different questionnaires, this is of primary interest in properly diagnosing a disorder, for example one disorder may be mistaken for the other or may be undiagnosed if both are present.

1.3 Discussion

It seems clear that many prevalent traits present in those with major depression are also present in those with an eating disorder. Major depression is the most commonly noted psychiatric disorder in women with anorexia nervosa. Previous studies indicate that anorexia nervosa occurs both before depression and vice versa.

However people with bulimia nervosa-associated major depression have different depressive features than those with depression. Depression can be present before bulimia nervosa and vice versa, and some individuals with bulimia nervosa continue to experience depression after recovering from the eating disorder.

Further statistical analysis can provide insight into which personality traits are present in either depression or eating disorders in order for better diagnosis.