BUG: Large number of PerformanceWarnings when attempting to read .xpt file

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Pandas version checks

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Reproducible Example

import pandas as pd
diet = pd.read_sas('DR1TOT_J.XPT',index='SEQN')

Issue Description

Hi there,

When attempting to read in a .XPT file downloaded from the CDC website using pandas.read_sas, a large number of PerformanceWarnings is printed. The file that causes the warnings to appear is this one: https://wwwn.cdc.gov/Nchs/Nhanes/2017-2018/DR1TOT_J.XPT .

```:1: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling frame.insert many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()````

The above warning is repeated 68 times. A different file that doesn't produce any warnings is: https://wwwn.cdc.gov/Nchs/Nhanes/2017-2018/DEMO_J.XPT

I'm not familiar with the inner workings of read_sas but I can only assume that it's creating the DataFrame in a way that is causing another part of pandas to complain.

Thanks a lot!

Expected Behavior

The expected behavior is for the file to be read in without a large number of warnings being printed. :)

Installed Versions

INSTALLED VERSIONS

commit : ca60aab
python : 3.9.13.final.0
python-bits : 64
OS : Linux
OS-release : 5.10.16.3-microsoft-standard-WSL2
Version : #1 SMP Fri Apr 2 22:23:49 UTC 2021
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : C.UTF-8
LOCALE : en_US.UTF-8

pandas : 1.4.4
numpy : 1.23.3
pytz : 2022.2.1
dateutil : 2.8.2
setuptools : 65.3.0
pip : 22.2.2
Cython : None
pytest : 7.1.3
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.9.1
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.2
IPython : 8.5.0
pandas_datareader: None
bs4 : 4.11.1
bottleneck : None
brotli :
fastparquet : None
fsspec : 2022.8.2
gcsfs : None
markupsafe : 2.1.1
matplotlib : 3.5.3
numba : None
numexpr : 2.7.3
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : 1.9.1
snappy : None
sqlalchemy : 1.4.41
tables : 3.6.1
tabulate : 0.8.10
xarray : 2022.6.0
xlrd : None
xlwt : None
zstandard : None

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Thank you very much for looking at this. :)