Length bias correction in one-day cross-sectional assessments - The nutritionDay study.
OBJECTIVE
A major problem occurring in cross-sectional studies is sampling bias. Length of hospital stay (LOS) differs strongly between patients and causes a length bias as patients with longer LOS are more likely to be included and are therefore overrepresented in this type of study. To adjust for the length bias higher weights are allocated to patients with shorter LOS. We determined the effect of length-bias adjustment in two independent populations.


METHODS
Length-bias correction is applied to the data of the nutritionDay project, a one-day multinational cross-sectional audit capturing data on disease and nutrition of patients admitted to hospital wards with right-censoring after 30 days follow-up. We applied the weighting method for estimating the distribution function of patient baseline variables based on the method of non-parametric maximum likelihood. Results are validated using data from all patients admitted to the General Hospital of Vienna between 2005 and 2009, where the distribution of LOS can be assumed to be known. Additionally, a simplified calculation scheme for estimating the adjusted distribution function of LOS is demonstrated on a small patient example.


CONCLUSIONS
The crude median (lower quartile; upper quartile) LOS in the cross-sectional sample was 14 (8; 24) and decreased to 7 (4; 12) when adjusted. Hence, adjustment for length bias in cross-sectional studies is essential to get appropriate estimates.
Section for Medical Statistics, Center for Medical Statistics, Informatics and Intelligent Systems, Medical University Vienna, A-1090 Vienna, Austria.
Sophie
S
Frantal
Section for Medical Statistics, Center for Medical Statistics, Informatics and Intelligent Systems, Medical University Vienna, A-1090 Vienna, Austria.
Elisabeth
E
Pernicka
Division Cardiac-, Thoracic-, Vascular Anaesthesia and Intensive Care, Medical University Vienna, A-1090 Vienna, Austria.
Michael
M
Hiesmayr
Medical Clinic III, Division Endocrinology, Medical University Vienna, A-1090 Vienna, Austria.
Karin
K
Schindler
Section for Medical Statistics, Center for Medical Statistics, Informatics and Intelligent Systems, Medical University Vienna, A-1090 Vienna, Austria. Electronic address: peter.bauer@meduniwien.ac.at.
Peter
P
Bauer
D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001835:Body Weight; D003430:Cross-Sectional Studies; D005260:Female; D005500:Follow-Up Studies; D006760:Hospitalization; D006801:Humans; D007902:Length of Stay; D044342:Malnutrition / Q000175:diagnosis / Q000517:prevention & control; D008875:Middle Aged; D015596:Nutrition Assessment; D009752:Nutritional Status; D015203:Reproducibility of Results; D015983:Selection Bias; D011795:Surveys and Questionnaires; D055815:Young Adult
Cross-sectional study; Length bias; NutritionDay; Validation; Weighting