diff --git a/DESCRIPTION b/DESCRIPTION
index 56b97e04bb..e361c6d128 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,7 +1,7 @@
 Package: tern
 Title: Create Common TLGs Used in Clinical Trials
-Version: 0.8.5.9004
-Date: 2023-08-02
+Version: 0.8.5.9005
+Date: 2023-08-04
 Authors@R: c(
     person("Joe", "Zhu", , "joe.zhu@roche.com", role = c("aut", "cre")),
     person("Daniel", "Sabanés Bové", , "daniel.sabanes_bove@roche.com", role = "aut"),
diff --git a/NEWS.md b/NEWS.md
index 04f9c07aff..e1085f55a4 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,7 +1,8 @@
-# tern 0.8.5.9004
+# tern 0.8.5.9005
 
 ### Miscellaneous
 * Fix swapped descriptions for the `.N_row` and `.N_col` parameters.
+* Fix bug in `analyze_vars_in_cols` when categorical data was used.
 
 # tern 0.8.5
 
diff --git a/R/analyze_vars_in_cols.R b/R/analyze_vars_in_cols.R
index 88eef5523f..91eea31965 100644
--- a/R/analyze_vars_in_cols.R
+++ b/R/analyze_vars_in_cols.R
@@ -256,6 +256,14 @@ analyze_vars_in_cols <- function(lyt,
           # Main statistics
           res <- s_summary(u, ...)[[stat]]
 
+          if (is.list(res)) {
+            if (length(res) > 1) {
+              stop("The analyzed column produced more than one category of results.")
+            } else {
+              res <- unlist(res)
+            }
+          }
+
           # Label from context
           label_from_context <- .spl_context$value[nrow(.spl_context)]
 
diff --git a/tests/testthat/_snaps/analyze_vars_in_cols.md b/tests/testthat/_snaps/analyze_vars_in_cols.md
index d3febcac6c..f6d6bc55ae 100644
--- a/tests/testthat/_snaps/analyze_vars_in_cols.md
+++ b/tests/testthat/_snaps/analyze_vars_in_cols.md
@@ -126,3 +126,41 @@
             B                               9    28.0   0.0    0.0    0.0             0.0        
             C                               9    37.6   0.0    0.0    0.0             0.0        
 
+# analyze_vars_in_cols works well with categorical data
+
+    Code
+      build_table(lyt = lyt, df = adpp %>% mutate(counter = factor("n")))
+    Output
+      STRATA1   A: Drug X   B: Placebo   C: Combination
+        SEX                                            
+      —————————————————————————————————————————————————
+      A                                                
+        F           0           0          81 (100%)   
+        M           0           0          81 (100%)   
+      B                                                
+        F           0           0          90 (100%)   
+        M           0           0          81 (100%)   
+      C                                                
+        F           0           0          117 (100%)  
+        M           0           0          72 (100%)   
+
+---
+
+    Code
+      basic_table(show_colcounts = TRUE) %>% split_rows_by(var = "STRATA1",
+        label_pos = "topleft") %>% split_cols_by("ARM") %>% analyze(vars = "SEX",
+        afun = count_fraction) %>% append_topleft("  SEX") %>% build_table(adpp)
+    Output
+      STRATA1   A: Drug X   B: Placebo   C: Combination
+        SEX       (N=0)       (N=0)         (N=522)    
+      —————————————————————————————————————————————————
+      A                                                
+        F           0           0           81 (16%)   
+        M           0           0           81 (16%)   
+      B                                                
+        F           0           0           90 (17%)   
+        M           0           0           81 (16%)   
+      C                                                
+        F           0           0          117 (22%)   
+        M           0           0           72 (14%)   
+
diff --git a/tests/testthat/test-analyze_vars_in_cols.R b/tests/testthat/test-analyze_vars_in_cols.R
index 9d1c975d29..7985b6fb11 100644
--- a/tests/testthat/test-analyze_vars_in_cols.R
+++ b/tests/testthat/test-analyze_vars_in_cols.R
@@ -208,3 +208,65 @@ testthat::test_that("summarize works with nested analyze", {
 
   testthat::expect_snapshot(tbl_sorted)
 })
+
+testthat::test_that("analyze_vars_in_cols works well with categorical data", {
+  # Regression test after #1013
+  adpp <- tern_ex_adpp %>% h_pkparam_sort()
+
+  lyt <- basic_table() %>%
+    split_rows_by(var = "STRATA1", label_pos = "topleft") %>%
+    split_rows_by(
+      var = "SEX",
+      label_pos = "topleft",
+      child_label = "hidden"
+    ) %>%
+    # split_cols_by("STRATA1") %>%
+    analyze_vars_in_cols(
+      vars = "ARM",
+      .stats = c("n", "count_fraction"),
+      .labels = c("count_fraction" = "argh")
+    )
+  testthat::expect_error(
+    result <- build_table(lyt = lyt, df = adpp),
+    "The analyzed column produced more than one category of results."
+  )
+
+  lyt <- basic_table() %>%
+    split_rows_by(var = "STRATA1", label_pos = "topleft") %>%
+    split_rows_by(
+      var = "SEX",
+      label_pos = "topleft",
+      child_label = "hidden"
+    ) %>%
+    split_cols_by("ARM") %>%
+    analyze_vars_in_cols(
+      vars = "counter",
+      .stats = c("count_fraction"),
+      .labels = c("count_fraction" = " ")
+    )
+  testthat::expect_snapshot(build_table(
+    lyt = lyt,
+    df = adpp %>% mutate(counter = factor("n"))
+  ))
+
+  # Alternative to discuss (xxx)
+  count_fraction <- function(x, .spl_context, .N_col) { # nolint
+    ret_list <- as.list(table(x))
+    if (length(x) == 0) {
+      aform <- "xx"
+    } else {
+      ret_list <- lapply(ret_list, function(i) {
+        c(i, i / .N_col)
+      })
+      aform <- "xx. (xx.%)"
+    }
+    in_rows(.list = ret_list, .formats = aform)
+  }
+
+  testthat::expect_snapshot(basic_table(show_colcounts = TRUE) %>%
+    split_rows_by(var = "STRATA1", label_pos = "topleft") %>%
+    split_cols_by("ARM") %>%
+    analyze(vars = "SEX", afun = count_fraction) %>%
+    append_topleft("  SEX") %>%
+    build_table(adpp))
+})