This study employs a cross-sectional observational study design to investigate the social determinants of depression using data from the European Social Survey (ESS) Wave 11. The analysis focuses on the relationship between depressive symptoms, measured through the CES- D8 scale, and two key independent variables: the frequency of social meetings and alcohol consumption. This design allows for an exploration of the associations between the variables at a single point in time, providing valuable insights into their potential relationships within a defined population.

Hypothesis 1: Higher frequency of social meetings is associated with lower levels of depressive symptoms.

Hypothesis 2: Higher alcohol consumption is associated with increased levels of depressive symptoms.

Data sample from Germany

## [1] 2420

Distribution of gender and histogram of age distribution

## 
##   Male Female 
##   1214   1206

#### CES-D8 (depresion scale) summary

## 
## Cronbach's alpha for the 'df_de[, c("d20", "d21", "d22", "d23", "d24", "d25", "d26", "d27")]' data-set
## 
## Items: 8
## Sample units: 2420
## alpha: 0.794
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
##   0.000   3.000   5.000   5.578   7.000  24.000      21

## 
##   0   1   2   3   4   5   6   7   8   9  10  11  12  13  14  15  16  17  18  19 
##  66 148 225 339 339 274 226 216 142 118  77  42  51  31  33  20  13  10   5   6 
##  20  21  22  23  24 
##   7   5   2   2   2

Depression Scale

likert_df = df[,CES_D8]
likert(likert_df)
##      Item None or almost none of the time Some of the time Most of the time
## 1  fltdpr                       64.915835         29.06631         4.557165
## 2 flteeff                       48.395568         38.42383         9.814171
## 3   slprl                       43.873854         39.87056        11.625059
## 4   wrhpp                        4.003510         23.53973        48.886939
## 5  fltlnl                       68.136458         24.27532         5.302253
## 6   enjlf                        5.338783         24.82572        44.804153
## 7   fltsd                       52.489933         41.07451         4.859808
## 8  cldgng                       55.673484         36.10353         6.217928
##   All or almost all of the time
## 1                      1.460694
## 2                      3.366431
## 3                      4.630532
## 4                     23.569817
## 5                      2.285972
## 6                     25.031346
## 7                      1.575748
## 8                      2.005056
plot(likert(likert_df))

Including Plots

##      Item None or almost none of the time Some of the time Most of the time
## 1  fltdpr                       64.915835         29.06631         4.557165
## 2 flteeff                       48.395568         38.42383         9.814171
## 3   slprl                       43.873854         39.87056        11.625059
## 4   wrhpp                        4.003510         23.53973        48.886939
## 5  fltlnl                       68.136458         24.27532         5.302253
## 6   enjlf                        5.338783         24.82572        44.804153
## 7   fltsd                       52.489933         41.07451         4.859808
## 8  cldgng                       55.673484         36.10353         6.217928
##   All or almost all of the time     Mean Count
## 1                      1.460694 1.425627 39981
## 2                      3.366431 1.681515 39983
## 3                      4.630532 1.770123 40017
## 4                     23.569817 2.920231 39890
## 5                      2.285972 1.417377 39983
## 6                     25.031346 2.895281 39878
## 7                      1.575748 1.555214 39981
## 8                      2.005056 1.545546 39949

Kruscal test of depression and alcohol frequency

## 
##  Kruskal-Wallis rank sum test
## 
## data:  df_de$depression and df_de$alcfreq
## Kruskal-Wallis chi-squared = 53.529, df = 6, p-value = 9.182e-10

Kruscal test of depression and alcohol frequency

## 
##  Kruskal-Wallis rank sum test
## 
## data:  df_de$depression and df_de$sclmeet
## Kruskal-Wallis chi-squared = 96.496, df = 6, p-value < 2.2e-16

Post-stratification weight (pspwght) model was used to weight the linear regression.

Linear regression models for Models with Weights

## 
## Call:
## lm(formula = depression ~ sclmeet + alcfreq, data = df_de, weights = pspwght)
## 
## Coefficients:
##                   (Intercept)  sclmeetLess than once a month  
##                        8.3701                         0.5960  
##           sclmeetOnce a month   sclmeetSeveral times a month  
##                       -1.8784                        -2.1628  
##            sclmeetOnce a week    sclmeetSeveral times a week  
##                       -2.5941                        -2.7147  
##              sclmeetEvery day    alcfreqSeveral times a week  
##                       -2.9354                        -0.9539  
##            alcfreqOnce a week       alcfreq2-3 times a month  
##                       -0.3524                        -0.5506  
##           alcfreqOnce a month  alcfreqLess than once a month  
##                       -0.3755                         0.1154  
##                  alcfreqNever  
##                        0.6195
## 
## Call:
## lm(formula = depression ~ sclmeet + alcfreq + gndr, data = df_de, 
##     weights = pspwght)
## 
## Coefficients:
##                   (Intercept)  sclmeetLess than once a month  
##                        8.4017                         0.4728  
##           sclmeetOnce a month   sclmeetSeveral times a month  
##                       -1.9976                        -2.3090  
##            sclmeetOnce a week    sclmeetSeveral times a week  
##                       -2.7293                        -2.8487  
##              sclmeetEvery day    alcfreqSeveral times a week  
##                       -3.0703                        -1.0460  
##            alcfreqOnce a week       alcfreq2-3 times a month  
##                       -0.5901                        -0.8099  
##           alcfreqOnce a month  alcfreqLess than once a month  
##                       -0.6030                        -0.1929  
##                  alcfreqNever                     gndrFemale  
##                        0.3264                         0.6394

Linear regression models for Models WITHOUT Weights

## 
## Call:
## lm(formula = depression ~ sclmeet + alcfreq, data = df_de)
## 
## Coefficients:
##                   (Intercept)  sclmeetLess than once a month  
##                        8.6917                        -1.3012  
##           sclmeetOnce a month   sclmeetSeveral times a month  
##                       -2.8431                        -3.3279  
##            sclmeetOnce a week    sclmeetSeveral times a week  
##                       -3.2670                        -3.8773  
##              sclmeetEvery day    alcfreqSeveral times a week  
##                       -4.3205                        -0.2978  
##            alcfreqOnce a week       alcfreq2-3 times a month  
##                       -0.1703                         0.1837  
##           alcfreqOnce a month  alcfreqLess than once a month  
##                        0.1689                         0.8344  
##                  alcfreqNever  
##                        1.2288
## 
## Call:
## lm(formula = depression ~ sclmeet + alcfreq + gndr, data = df_de)
## 
## Coefficients:
##                   (Intercept)  sclmeetLess than once a month  
##                       8.71499                       -1.42540  
##           sclmeetOnce a month   sclmeetSeveral times a month  
##                      -2.95021                       -3.47151  
##            sclmeetOnce a week    sclmeetSeveral times a week  
##                      -3.39492                       -4.01660  
##              sclmeetEvery day    alcfreqSeveral times a week  
##                      -4.43249                       -0.39334  
##            alcfreqOnce a week       alcfreq2-3 times a month  
##                      -0.35225                       -0.05480  
##           alcfreqOnce a month  alcfreqLess than once a month  
##                      -0.06769                        0.57234  
##                  alcfreqNever                     gndrFemale  
##                       0.95934                        0.60181

The comparison of both models with the weight and without the data from the table. In the case of gender we see that it goes from a coefficient of 0.079 for females to 0.075 when applying the weight formula to the model. In this case generating that being of the female gender tends to have even greater values of depression when applying the weight in the model.

PREDICTOR OF CLINICALLY SIGNIFICANT DEPRESSION

1 is clinically significant depressive symptoms and 0 is not
## 
##    0    1 
## 1975  424

Logistic Regression Model

## 
## Call:
## glm(formula = depressed ~ sclmeet + alcfreq + gndr, family = binomial, 
##     data = df_de)
## 
## Coefficients:
##                               Estimate Std. Error z value Pr(>|z|)    
## (Intercept)                     0.2615     0.4277   0.611 0.540880    
## sclmeetLess than once a month  -0.6743     0.4157  -1.622 0.104768    
## sclmeetOnce a month            -1.5502     0.4142  -3.743 0.000182 ***
## sclmeetSeveral times a month   -1.8232     0.3950  -4.616 3.91e-06 ***
## sclmeetOnce a week             -1.9462     0.4021  -4.840 1.30e-06 ***
## sclmeetSeveral times a week    -2.2184     0.3958  -5.605 2.09e-08 ***
## sclmeetEvery day               -2.1696     0.4344  -4.995 5.88e-07 ***
## alcfreqSeveral times a week    -0.5522     0.2619  -2.109 0.034960 *  
## alcfreqOnce a week             -0.5558     0.2628  -2.115 0.034438 *  
## alcfreq2-3 times a month       -0.4777     0.2778  -1.719 0.085549 .  
## alcfreqOnce a month            -0.1768     0.2887  -0.612 0.540273    
## alcfreqLess than once a month   0.2513     0.2558   0.983 0.325771    
## alcfreqNever                    0.3204     0.2526   1.268 0.204726    
## gndrFemale                      0.3673     0.1174   3.129 0.001756 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## (Dispersion parameter for binomial family taken to be 1)
## 
##     Null deviance: 2232.1  on 2391  degrees of freedom
## Residual deviance: 2065.9  on 2378  degrees of freedom
##   (28 observations deleted due to missingness)
## AIC: 2093.9
## 
## Number of Fisher Scoring iterations: 4
##                   (Intercept) sclmeetLess than once a month 
##                     0.2615484                    -0.6743487 
##           sclmeetOnce a month  sclmeetSeveral times a month 
##                    -1.5501548                    -1.8231595 
##            sclmeetOnce a week   sclmeetSeveral times a week 
##                    -1.9461797                    -2.2184420 
##              sclmeetEvery day   alcfreqSeveral times a week 
##                    -2.1696397                    -0.5521973 
##            alcfreqOnce a week      alcfreq2-3 times a month 
##                    -0.5557599                    -0.4776823 
##           alcfreqOnce a month alcfreqLess than once a month 
##                    -0.1767962                     0.2513248 
##                  alcfreqNever                    gndrFemale 
##                     0.3204029                     0.3672742
##                   (Intercept) sclmeetLess than once a month 
##                     1.2989398                     0.5094882 
##           sclmeetOnce a month  sclmeetSeveral times a month 
##                     0.2122151                     0.1615146 
##            sclmeetOnce a week   sclmeetSeveral times a week 
##                     0.1428186                     0.1087785 
##              sclmeetEvery day   alcfreqSeveral times a week 
##                     0.1142188                     0.5756835 
##            alcfreqOnce a week      alcfreq2-3 times a month 
##                     0.5736362                     0.6202192 
##           alcfreqOnce a month alcfreqLess than once a month 
##                     0.8379506                     1.2857276 
##                  alcfreqNever                    gndrFemale 
##                     1.3776827                     1.4437937
## Waiting for profiling to be done...
##                                    2.5 %    97.5 %
## (Intercept)                   0.56471700 3.0581029
## sclmeetLess than once a month 0.22058549 1.1386125
## sclmeetOnce a month           0.09204662 0.4722883
## sclmeetSeveral times a month  0.07265726 0.3462953
## sclmeetOnce a week            0.06338926 0.3105368
## sclmeetSeveral times a week   0.04885606 0.2336281
## sclmeetEvery day              0.04756556 0.2638045
## alcfreqSeveral times a week   0.34710946 0.9719397
## alcfreqOnce a week            0.34528378 0.9702897
## alcfreq2-3 times a month      0.36139860 1.0775219
## alcfreqOnce a month           0.47702324 1.4843752
## alcfreqLess than once a month 0.78641727 2.1492030
## alcfreqNever                  0.84819797 2.2898717
## gndrFemale                    1.14800149 1.8193069
## [1] 0.2064042

Social meeting

####Compared to those who never meet others, individuals who meet socially more often have significantly lower odds of reporting depression

Alcohol frequency

####Compared to the reference category (likely “Daily” or an omitted baseline group), individuals who consume alcohol once or several times a week have significantly lower odds of being depressed

Gender

Female respondents have significantly higher odds of being depressed compared to male respondents

McFadden’s R^2 ranges from 0 to 1, where 0 indicates that the model doesn’t provide any improvement Its interpretation is often subjective, around 0.2 considered as a decent fit.