diff --git a/pandas/_libs/parsers.pyx b/pandas/_libs/parsers.pyx
index 5b94f45490da4..d1ea4092efe40 100644
--- a/pandas/_libs/parsers.pyx
+++ b/pandas/_libs/parsers.pyx
@@ -2126,12 +2126,18 @@ def sanitize_objects(ndarray[object] values, set na_values) -> int:
 
     n = len(values)
     onan = np.nan
+    bool_set = {True, False}
 
     for i in range(n):
         val = values[i]
         if val in na_values:
             values[i] = onan
             na_count += 1
+        elif val in bool_set:
+            # GH60088: Skip memoization
+            # since 1 == 1.0 == True == np.True_
+            # and 0 == 0.0 == False == np.False_
+            values[i] = val
         elif val in memo:
             values[i] = memo[val]
         else:
diff --git a/pandas/tests/io/excel/test_readers.py b/pandas/tests/io/excel/test_readers.py
index 71fb8f490e114..024fc71bbf17b 100644
--- a/pandas/tests/io/excel/test_readers.py
+++ b/pandas/tests/io/excel/test_readers.py
@@ -168,6 +168,42 @@ def test_read_excel_type_check(self, col, tmp_excel, read_ext):
         df2 = pd.read_excel(tmp_excel, dtype={"bool_column": "boolean"})
         tm.assert_frame_equal(df, df2)
 
+    def test_read_excel_int_bool_mix_type_check(self, tmp_excel, read_ext):
+        # GH 60088
+        if read_ext in (".xlsb", ".xls"):
+            pytest.skip(f"No engine for filetype: '{read_ext}'")
+
+        df1 = DataFrame(
+            {
+                "a": [True, True],
+                "b": [1, True],
+                "c": [True, 1],
+                "d": [False, 0],
+                "e": [0, False],
+                "f": [False, False],
+            },
+            dtype=object,
+        )
+        df1.to_excel(tmp_excel, index=False)
+
+        df2 = pd.read_excel(tmp_excel, dtype=object)
+
+        tm.assert_frame_equal(df1, df2)
+
+        for idx, row in df2.iterrows():
+            for col in df2.columns:
+                val = row[col]
+                exp_val = df1.iloc[idx][col]
+                # Check if values match
+                assert val == exp_val, (
+                    f"Mismatch at Row {idx} Column {col}: {val} != {exp_val}"
+                )
+                # Check if types match
+                assert type(val) == type(exp_val), (
+                    f"Type mismatch at Row {idx} Column {col}: "
+                    f"{type(val)} != {type(exp_val)}"
+                )
+
     def test_pass_none_type(self, datapath):
         # GH 58159
         f_path = datapath("io", "data", "excel", "test_none_type.xlsx")
diff --git a/pandas/tests/io/parser/common/test_common_basic.py b/pandas/tests/io/parser/common/test_common_basic.py
index 3680273f5e98a..96da78f997962 100644
--- a/pandas/tests/io/parser/common/test_common_basic.py
+++ b/pandas/tests/io/parser/common/test_common_basic.py
@@ -15,6 +15,7 @@
 
 from pandas._config import using_string_dtype
 
+from pandas._libs import parsers as libparsers
 from pandas.compat import HAS_PYARROW
 from pandas.errors import (
     EmptyDataError,
@@ -830,3 +831,15 @@ def test_read_seek(all_parsers):
             actual = parser.read_csv(file)
         expected = parser.read_csv(StringIO(content))
     tm.assert_frame_equal(actual, expected)
+
+
+def test_dtype_conversion_in_sanitization():
+    # GH60088
+    values = np.array([1, True, 0, False, 1.0, 0.0, np.True_, np.False_], dtype=object)
+    expected = np.array(
+        [1, True, 0, False, 1.0, 0.0, np.True_, np.False_], dtype=object
+    )
+    libparsers.sanitize_objects(values, na_values=set())
+    for v, e in zip(values, expected, strict=True):
+        assert v == e
+        assert type(v) == type(e)