diff --git a/README.md b/README.md
index ecd08e13e..45610294b 100644
--- a/README.md
+++ b/README.md
@@ -155,3 +155,6 @@ The detailed description can be found
 
 #### 1.6.8 Scale Means Marginal
 - Add capability to calculate the scale means marginal. This is used when analysing a 2D cube, and obtaining a sort of a "scale mean _total_" for each of the variables constituting a cube.
+
+#### 1.6.9 Bugfix
+- When Categorical Array variable is selected in multitable export, and Scale Means is selected, the cube fails, because it tries to access the non-existing slice (the CA is only _interpreted_ as multiple slices in tabbooks). This fix makes sure that the export cube doesn't fail in such case.
diff --git a/setup.py b/setup.py
index 670a2a36e..0b641b59d 100644
--- a/setup.py
+++ b/setup.py
@@ -3,7 +3,7 @@
 
 from setuptools import setup, find_packages
 
-version = '1.6.8'
+version = '1.6.9'
 
 
 def get_long_desc():
diff --git a/src/cr/cube/cube_slice.py b/src/cr/cube/cube_slice.py
index dc6b48f8e..c06016c06 100644
--- a/src/cr/cube/cube_slice.py
+++ b/src/cr/cube/cube_slice.py
@@ -252,6 +252,8 @@ def is_double_mr(self):
         return self.dim_types == ['multiple_response'] * 2
 
     def scale_means(self, hs_dims=None, prune=False):
+        if self.ca_as_0th:
+            return [None, None]
         return self._cube.scale_means(hs_dims, prune)[self._index]
 
     @lazyproperty
diff --git a/tests/unit/test_cube_slice.py b/tests/unit/test_cube_slice.py
index 5020fb775..f07df6937 100644
--- a/tests/unit/test_cube_slice.py
+++ b/tests/unit/test_cube_slice.py
@@ -385,3 +385,10 @@ def test_scale_means_marginal(self, mock_sm_init, mock_sm_margin):
         fake_axis = Mock()
         cs.scale_means_margin(fake_axis)
         assert mock_sm_margin.called_once_with(fake_axis)
+
+    def test_scale_means_for_ca_as_0th(self):
+        """Test that CA as 0th slice always returns empty scale means."""
+        cube = Mock()
+        cube.dim_types = ['categorical_array']
+        cs = CubeSlice(cube, 0, ca_as_0th=True)
+        assert cs.scale_means() == [None, None]