Graphic 1: Distribution of CES-D8 Depression Scores

ggplot(df_aus[!is.na(df_aus$CESD_TOTAL), ], aes(x = CESD_TOTAL)) +
  geom_histogram(binwidth = 1, fill = "steelblue", color = "black") +
  labs(
    title = "Distribution of Depression Scores (CES-D8)",
    subtitle = "ESS Round 11, Austria",
    x = "CES-D8 Score",
    y = "Frequency",
    caption = "Source: ESS11, own calculation"
  ) +
  theme_minimal()

Core message: Most individuals report low to moderate levels of depressive symptoms; the distribution is right-skewed.

Visual design: Histogram showing CESD_TOTAL (CES-D8 score), with frequency count.

Graphic 2: Depression Score by Income Satisfaction

ggplot(df_aus[!is.na(df_aus$CESD_TOTAL) & !is.na(df_aus$hincfel_num), ],
       aes(x = factor(hincfel_num), y = CESD_TOTAL)) +
  geom_boxplot(fill = "lightblue") +
  labs(
    title = "Income Satisfaction and Depression Levels",
    subtitle = "ESS Round 11, Austria",
    x = "Income Satisfaction (1 = Very Difficult – 4 = Living Comfortably)",
    y = "Depression Score (CES-D8)",
    caption = "Source: ESS11, own calculation"
  ) +
  theme_minimal()

Core message: Higher income satisfaction is associated with lower depression scores.

Visual design: Boxplot of CESD_TOTAL by income satisfaction (hincfel_num).

Graphic 3: Self-Rated Health by Gender

ggplot(df_aus[!is.na(df_aus$health),], aes(gndr)) +
  geom_bar(aes(fill = health), position = "fill", width = 0.6) +
  scale_y_continuous(labels = scales::percent) +
  scale_fill_manual(values = c("darkgreen", "lightgreen", "grey", "orange", "red")) +
  coord_flip() +
  labs(
    title = "Self-Rated Health by Gender",
    subtitle = "ESS Round 11, Austria",
    x = "Gender",
    y = "Percentage",
    caption = "Source: ESS11, own calculation",
    fill = "Health Status"
  ) +
  theme_minimal()

Core message: Perceived health status differs by gender; visualizing proportions reveals distributional differences.

Visual design: 100% stacked bar chart of health by gender.