Prev Med. 2015 Sep;78:72-7.

Dipstick proteinuria as a predictor of all-cause and cardiovascular disease mortality in Bangladesh: A prospective cohort study.


Pesola GR1, Argos M2, Chen Y3, Parvez F4, Ahmed A5, Hasan R5, Rakibuz-Zaman M5, Islam T5, Eunus M5, Sarwar G5, Chinchilli VM6, Neugut AI7, Ahsan H8.
  • 1Dept. of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, United States; Dept. of Medicine (Section of Pulmonary/Critical Care), Harlem Hospital affiliated with Columbia University, New York, NY, United States. Electronic address:
  • 2Dept. of Health Sciences, University of Chicago, IL, United States.
  • 3Dept. of Environmental Medicine, New York University School of Medicine, New York, NY, United States.
  • 4Dept. of Environmental Health Sciences, Mailman School of Public Health, Columbia Univ., New York, NY, United States.
  • 5University of Chicago Research (URB), Ltd., Dhaka, Bangladesh.
  • 6Dept. of Public Health Studies, Penn State College of Medicine, Hershey, PA, United States.
  • 7Dept. of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, United States; Dept. of Medicine, Columbia University, New York, NY, United States.
  • 8Dept. of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, United States; Dept. of Health Sciences, University of Chicago, IL, United States; Dept. of Environmental Health Sciences, Mailman School of Public Health, Columbia Univ., New York, NY, United States; University of Chicago Research (URB), Ltd., Dhaka, Bangladesh.



OBJECTIVE: Baseline, persistent, incident, and remittent dipstick proteinuria have never been tested as predictors of mortality in an undeveloped country. The goal of this study was to determine which of these four types of proteinuria (if any) predict mortality.

METHODS: Baseline data was collected from 2000 to 2002 in Bangladesh from 11,121 adults. Vital status was ascertained over 11-12years. Cox models were used to evaluate proteinuria in relation to all-cause and cardiovascular disease (CVD) mortality. CVD mortality was evaluated only in those with baseline proteinuria. Persistent, remittent, and incident proteinuria were determined at the 2-year exam.

RESULTS: Baseline proteinuria of 1+ or greater was significantly associated with all-cause (hazard ratio (HR) 2.87; 95% C.I., 1.71-4.80) and CVD mortality (HR: 3.55; 95% C.I., 1.81-6.95) compared to no proteinuria, adjusted for age, gender, arsenic well water concentration, education, hypertension, BMI, smoking, and diabetes mellitus. Persistent 1+ proteinuria had a stronger risk of death, 3.49 (1.64-7.41)-fold greater, than no proteinuria. Incident 1+ proteinuria had a 1.87 (0.92-3.78)-fold greater mortality over 9-10years. Remittent proteinuria revealed no increased mortality.

CONCLUSIONS: Baseline, persistent, and incident dipstick proteinuria were predictors of all-cause mortality with persistent proteinuria having the greatest risk. In developing countries, those with 1+ dipstick proteinuria, particularly if persistent, should be targeted for definitive diagnosis and treatment. The two most common causes of proteinuria to search for are diabetes mellitus and hypertension.

KEYWORDS: Bangladesh mortality; Dipstick proteinuria and mortality; Epidemiology; Proteinuria and all-cause mortality; Proteinuria and cardiovascular disease mortality

PMID: 26190365



Normal protein levels in urine and Rationale for urine protein detection by Dipstick

The normal level of total protein in the urine has been defined as 150 mg or less in a 24-hour (24-hr) period. Any level above this suggests some type of disease, usually diabetes or hypertension. During normal proteinuria screening with an office visit or screening world-wide, obtaining a 24-hr urine sample (the gold standard) is not possible or practical, is time consuming, becomes expensive and is often inaccurate due to collection difficulties related to the individual. Therefore, a method to detect increased protein in the urine that can be done in minutes is needed to help screen for disease. The urine dipstick method is used for this purpose.

The urine dipstick takes a fresh urine sample and a dipstick is dipped in the urine, taken out and read in 60 seconds (see figure). A rough estimate of protein in the urine is then obtained and can be used for screening anywhere. Any level at 1+ or more with the dipstick that is consistent on repeat over 3 months or more suggests some type of disease, assuming one does not have an infection in the urine.



Figure. Urine dipstick colors after 60 seconds. Negative is the normal color after 60 seconds.

Neg: < 10 mg/dL

Trace: 10 – 20 mg/dL – microalbuminuria

1+ :   30 mg/dL – macroalbuminuria

2+ :  100 mg/dL

3+ :  300 mg/dL – nephrotic range

4+ : 1000 mg/dL


Excess protein in the urine predicts mortality as has been shown in developed countries for many years using dipstick proteinuria for detection (1, 2). The protein seen as 1+ is approximately 30 mg/dL or 300 mg per liter and since average urine volume varies but is estimated at 1.5 liters per day this would translate into 450 mg of protein excreted per day, clearly above the 150 mg of protein per day that is considered as normal. The dipstick for protein at trace with an average of 15 mg/dL would approximate 150 mg per liter or 225 mg per 1.5 liters and may also be abnormal. However, trace dipstick testing can be very subjective and there may be many false positives (dipstick trace that may really be negative but read as (trace) positive) and some false negatives (dipstick negative should have been read as trace). Therefore, 1+ dipstick proteinuria is more likely to signify disease and if persistent is often used in studies to predict mortality. As can be seen by the above discussion, dipstick proteinuria gives a type of qualitative estimate of a 24-hr urine sample protein content, albeit it is just an estimate.


Brief Current Study Findings with Additional Analysis for Persistent Baseline Trace Proteinuria 

A problem with prospective studies using dipstick proteinuria is which type of dipstick proteinuria are we dealing with: baseline, incident, persistent, or remittent? This study recognizes four types, defines them, and evaluates them prospectively. Additionally, no study has ever evaluated dipstick proteinuria in a developing country to see if it was possible to predict mortality in, theoretically, a less controlled setting.

This study clearly demonstrates an increase in mortality with 1+ dipstick proteinuria over 11-12 years, with an adjusted 3.49 (95% C.I.; 1.64 to 7.41)-fold greater risk of dying (compared to no proteinuria) if the proteinuria is persistent (3). This is similar to the 3.55 (95% C.I.; 1.81 to 6.95)-fold greater risk of dying from cardiovascular disease (heart disease or stroke) as seen with baseline proteinuria (3). More importantly, if persistent proteinuria (not baseline proteinuria) had been evaluated for cardiovascular disease the risk of dying might have been much higher than reported. However, the number of deaths from cardiovascular disease for persistent proteinuria was not high enough to calculate a reliable estimate. A larger study or longer follow-up would have been needed.

Trace baseline proteinuria revealed no difference in all-cause mortality when followed over 11-12 years (3). This may be partly due to difficulties in determining accurately what is trace baseline proteinuria (vide supra). To further evaluate this issue, only trace proteinuria that was present at baseline and at 2 years was evaluated (table) ie persistent baseline trace proteinuria. Crude and age adjusted persistent baseline trace proteinuria were significant, albeit the significance was lost in the fully adjusted model (table). Biologically, it would make sense for any protein in the urine above normal values (normal protein in the urine about 80 mg to 150 mg) to result in increased mortality i.e. glomerular leak of protein reflects generalized vascular damage throughout the body, the Steno hypothesis (4). Therefore, one could at least argue that there is a 1.37 (0.82-2.29)-fold greater increase in all-cause mortality in those with persistent baseline trace dipstick proteinuria in Bangladesh, i.e. if the trends remained the same and the sample size had been larger (5,6).

The persistent baseline trace proteinuria data is consistent with our data on incident persistent trace proteinuria (3, online appendix table 1C). Table 1C revealed an adjusted 1.42 (95% C.I.; 0.59-3.44)-fold greater risk of mortality with hardly any data since it is difficult to obtain data on incident proteinuria and subsequent mortality. Theoretically, incident proteinuria followed over time should give the highest predicted mortality (given that proteinuria is a predictor of mortality). This is because, unlike proteinuria found at baseline which would bias toward those with longer survival, incident proteinuria detects all those with any new-onset proteinuria including those with a short survival. Therefore, incident proteinuria should result in the highest mortality of all when followed over time.


Table: Cox Regression model with the primary exposure variable persistent baseline trace proteinuria and the primary outcome variable all-cause mortality. Crude, age adjusted, and fully adjusted models are presented. Bangladesh data 2000 to 2013.

tab1HR = hazard ratio; hypertension = blood pressure systolic of at least 140 and/or diastolic of at least 90, dichotomous variable; BMI = body mass index; female is referent for sex;, smoking was ever/never; Diabetes means diabetes mellitus. Control/referent group was dipstick negative proteinuria as baseline and at 2 years.


Importance of this study – at least three-fold. 

  1. Demonstration that dipstick proteinuria can be used to predict all-cause as well as cardiovascular disease mortality in any population, including developing countries. Theoretically, at least, competing risks for death might have resulted in no detection of increased mortality with dipstick proteinuria in a developing country. This was not the case and indicates that dipstick proteinuria gives a strong signal predicting mortality in all populations.
  2. This study is the first to define epidemiologically as well as evaluate four different types of proteinuria that can theoretically be seen in prospective studies. Of these 4 types; baseline, persistent, and incident proteinuria were predictors of all-cause mortality in Bangladesh. In addition, baseline proteinuria was a predictor of cardiovascular disease mortality as well.
  3. First study to recognize and suggest that incident proteinuria, relative to any other type of proteinuria, should give the strongest signal predicting mortality for the same sample size and follow-up time. It is difficult to do such an incident proteinuria and mortality study since the investigators have to start with subjects with no proteinuria at baseline, wait for new-onset proteinuria to develop, and then follow these subjects to determine whether or not there is an increase in mortality relative to individuals who do not have proteinuria. The extra time involved makes the study that much more difficult, assuming such a study is conceptually recognized.

Practical Application

Many drug stores sell dipsticks for proteinuria detection in the urine. Anyone can buy the dipsticks and check for protein in their urine. If protein is present, one should see a health care professional to re-check again to make sure they are correct in their interpretation of the dipstick for protein and to get advice, if need be.

Bottom Line

Protein in the urine is a marker for diseases that shorten life expectancy (7) and should be screened for in at-risk populations and in routine health check-up visits. Treatments are available to reduce proteinuria in the urine and hopefully prolong life.



  1. Grimm RH, Svedsen KH, Kasiske B, Keane WF, Wahi MM. 1997. Proteinuria is a risk factor for mortality over 10 years follow-up. Kidney  Int. 52 (Suppl 63):S10-14.
  2. Ha K, Kim HC, Kang DR, Nam CM, Vogue S, Suh AH. 2006. Dipstick urine protein as a predictor of cardiovascular mortality in Korean men. J. Prev. Med. Public Health 39:427-432.
  3. Pesola GR, Argos M, Chen Yu, Parvez F, Ahmed A, Hasan R, Rakibuz-Zaman M, Islam T, Eunus M, Sarwar G, Chinchilli VM, Neugut AI, Ahsan H. 2015. Dipstick proteinuria as a predictor of all-cause and cardiovascular disease mortality in Bangladesh: A prospective cohort study. Prev. Med. 78:72-77.
  4. Deckert T, Feldt-Rasmussen B, Borch-Johnsen K, Jensen T, Kofoed-Enevoldsen A. 1989. Albuminuria reflects widespread vascular damage. The Steno hypothesis. Diabetologia 32:219-226.
  5. Vaughan RD. 2007. The importance of meaning. Am. J. Public Health 97:592-593.
  6. Rothman KJ. 2012. Random error and the role of statistics. 2nd Ed, Chapter 8. Oxford University Press, New York, N.Y.
  7. Turin TC, Tonelli M, Manns BJ, Ahmed SB, Ravani P, James M, Hemmelgarn BR. 2013. Proteinuria and life expectancy. Am. J. Kidney Dis. 61:644-648.



This work was supported by the National Institutes of Health grants P42ES010349, R01CA107431, and R01CA102484.



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