diff --git a/R/geom-histogram.R b/R/geom-histogram.R
index dafc181f15..7bd832b611 100644
--- a/R/geom-histogram.R
+++ b/R/geom-histogram.R
@@ -17,6 +17,12 @@
 #' one change at a time. You may need to look at a few options to uncover
 #' the full story behind your data.
 #'
+#' By default, the _height_ of the bars represent the counts within each bin.
+#' However, there are situations where this behavior might produce misleading
+#' plots (e.g., when non-equal-width bins are used), in which case it might be
+#' preferable to have the _area_ of the bars represent the counts (by setting
+#' `aes(y = after_stat(count / width))`). See example below.
+#'
 #' In addition to `geom_histogram()`, you can create a histogram plot by using
 #' `scale_x_binned()` with [geom_bar()]. This method by default plots tick marks
 #' in between each bar.
@@ -63,6 +69,18 @@
 #' ggplot(diamonds, aes(price, after_stat(density), colour = cut)) +
 #'   geom_freqpoly(binwidth = 500)
 #'
+#'
+#' # When using the non-equal-width bins, we should set the area of the bars to
+#' # represent the counts (not the height).
+#' # Here we're using 10 equi-probable bins:
+#' price_bins <- quantile(diamonds$price, probs = seq(0, 1, length = 11))
+#'
+#' ggplot(diamonds, aes(price)) +
+#'   geom_histogram(breaks = price_bins, color = "black") # misleading (height = count)
+#'
+#' ggplot(diamonds, aes(price, after_stat(count / width))) +
+#'   geom_histogram(breaks = price_bins, color = "black") # area = count
+#'
 #' if (require("ggplot2movies")) {
 #' # Often we don't want the height of the bar to represent the
 #' # count of observations, but the sum of some other variable.
diff --git a/man/geom_histogram.Rd b/man/geom_histogram.Rd
index 1f290dbcdc..a241aa2ba4 100644
--- a/man/geom_histogram.Rd
+++ b/man/geom_histogram.Rd
@@ -192,6 +192,12 @@ different number of bins. You can also experiment modifying the \code{binwidth}
 one change at a time. You may need to look at a few options to uncover
 the full story behind your data.
 
+By default, the \emph{height} of the bars represent the counts within each bin.
+However, there are situations where this behavior might produce misleading
+plots (e.g., when non-equal-width bins are used), in which case it might be
+preferable to have the \emph{area} of the bars represent the counts (by setting
+\code{aes(y = after_stat(count / width))}). See example below.
+
 In addition to \code{geom_histogram()}, you can create a histogram plot by using
 \code{scale_x_binned()} with \code{\link[=geom_bar]{geom_bar()}}. This method by default plots tick marks
 in between each bar.
@@ -255,6 +261,18 @@ ggplot(diamonds, aes(price, colour = cut)) +
 ggplot(diamonds, aes(price, after_stat(density), colour = cut)) +
   geom_freqpoly(binwidth = 500)
 
+
+# When using the non-equal-width bins, we should set the area of the bars to
+# represent the counts (not the height).
+# Here we're using 10 equi-probable bins:
+price_bins <- quantile(diamonds$price, probs = seq(0, 1, length = 11))
+
+ggplot(diamonds, aes(price)) +
+  geom_histogram(breaks = price_bins, color = "black") # misleading (height = count)
+
+ggplot(diamonds, aes(price, after_stat(count / width))) +
+  geom_histogram(breaks = price_bins, color = "black") # area = count
+
 if (require("ggplot2movies")) {
 # Often we don't want the height of the bar to represent the
 # count of observations, but the sum of some other variable.