Related Experiment Video
Updated: Feb 8, 2026

Low-Cost, Volume-Controlled Dipstick Urinalysis for Home-Testing
Published on: May 8, 2021
Dipstick proteinuria predicts all-cause mortality in general population: A study of 17 million Korean adults
Yeongkeun Kwon1,2, Kyungdo Han3, Yang Hyun Kim1,2
1Department of Family Medicine, Korea University College of Medicine, Seoul, Republic of Korea.
Objective:
A quantitative basis for the use of dipstick urinalysis for risk assessment of all-cause mortality is scarce. Therefore, we investigated the association between dipstick proteinuria and all-cause mortality in a general population and evaluated the effect of confounders on this association.
Methods:
The study population included 17,342,956 adults who underwent health examinations between 2005 and 2008 under the National Health Insurance System. Proteinuria was determined using a single dipstick urinalysis, and the primary outcome of this study was all-cause mortality. The prognostic impact of proteinuria was assessed by constructing a multivariable Cox model.
Results:
The mean age of the study population (53.24% male) was 46.06 years; 724,681 deaths from all causes occurred over a median follow-up period of 9.34 years (interquartile range 8.17-10.16), and the maximum follow-up was 12.12 years. After full adjustment for covariates, a higher level of dipstick proteinuria indicated a higher risk of all-cause death [Hazard ratios (95% confidence intervals); 1.22 (1.20-1.24), 1.47 (1.45-1.49), 1.81 (1.77-1.84), 2.32 (2.24-2.41), 2.74 (2.54-2.96); trace to 4+, respectively], and various subgroup analyses did not affect the main outcome for the total population. ≥1+ proteinuria in the group without metabolic diseases (hypertension, diabetes, dyslipidemia, or obesity) resulted in higher hazard ratios than those in the group with metabolic diseases and negative or trace proteinuria.
Conclusions:
Our study showed a strong association between dipstick proteinuria and all-cause mortality in this nationwide population-based cohort in South Korea.
Related Concept Videos
What is Population Genetics?
What are Populations and Communities?
Conservation of Small Populations
Population Growth
Predicting Molecular Geometry
Prediction Intervals
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.

