Comparison of Urinalysis and Fasting Plasma Sugar
By
1. Adamu AN*. MWACP, FMCP
2. Ohwovoriole AE†. FWACP, FMCP
3. Fasanmade OA†. FWACP
4. Olarinoye JK*. FWACP
5. Ekpebegh CO† MWACP, FMCP
Name of the Institutions- *Department of Medicine, University of Ilorin, Nigeria.
†Department of Medicine, University of Lagos, Nigeria.
Name of Department and Institution to which the work should be attributed- Department of
Medicine, University of Ilorin, Nigeria.
Disclaimer- None
Contact information for corresponding authorsName- Abdullahi Ndaman Adamu
Department of Medicine, University of Ilorin. PMB 1515, Ilorin 24001. Nigeria
Phone- +2347058024401, +2348023435240
E-mail- abdullahiadamu2003@yahoo.com
Name and address of author to who request for reprint should be made- same as above.
Source of support – None
Word count- 1,962
Number of Tables= 2 Figures=5
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Conflict of Interest Notification
There is no conflict of interest of whatever form in conception to final execution of this article.
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Abstract
Objective- To evaluate random urine samples a screening test for type 2 diabetes mellitus among people
with systemic hypertension.
METHODOLOGY- Between January and May 2004, screening for Type 2 diabetes was conducted
among people known to have systemic hypertension and who were regular attendees of medical outpatient clinic of the Lagos University Teaching Hospital. Screening was done using random urine sample.
Fasting plasma glucose estimation was carried out on all the subjects as the standard for the diagnosis of
diabetes. Subjects were classified as screen positive if the urinalysis result is positive. The American
diabetes association criterion of FPG ≥7mmol/l (≥126mg/dl) was used as a gold standard to interpret the
result.
Results- We recruited 206 persons to give room for attrition, out of which 131 (participation rate of
63.41%) of them had FPG estimation and urinalysis done; 87 were females constituting 65.64% while
males were 44 in number constituting 34.35%. A sensitivity of 28%, specificity of 98%, positive
predictive value of 77.77%, negative predictive value of 85.24% was reported. The correlation of random
urinalysis to FPG was 0.52 and the r2 was 0.27. P value 0.00.
Conclusion- Urinalysis is a poor screening tool for type 2 diabetes mellitus among people with systemic
hypertension however, showed a statistically significant correlation with fasting plasma glucose.
Key words- screening- type 2 diabetes mellitus- urinalysis- Fasting plasma glucose..
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Introduction
Screening for Type 2 diabetes is a hot topic for public health. The prevalence of diabetes is increasing
rapidly all over the world, with diabetes becoming known as an epidemic disease (1). It may remain
undetected for a number of years; a significant number of newly diagnosed type 2 diabetes has established
complications (2). There is indirect evidence that early detection and treatment of diabetes and
cardiovascular risk factors reduces severe retinal, renal and cardiovascular complications (3, 4). Thus,
preventing or delaying diabetic complications may improve patients’ quality of life and reduce healthcare expense (5).
Screening for diabetes using biochemical tests (random blood sugar, fasting blood) is the common
practice in many industrialized worlds. This may be a difficult task in poor resource nations because of its
technicality and invasive methods. Safety issues in dealing with blood specimens also need to be
considered. Moreover, fasting plasma glucose (FPG) is also a component of diagnostic testing which is
preferred in clinical settings because it is easier and faster to perform. It is also more convenient and
acceptable to patients and less expensive (6).
The available studies using urinalysis as screening tests were done at community level and included those
with known diabetes and not known to have diabetes (7, 8). Some did not include those known to have
diabetes (9-11). All of them were prospective diagnostic studies, some used clinistest® for urinalysis and
fasting blood sugar and OGTT as diagnostic test.
No study to our understanding used combined clinistix® which is specific for glucose, fasting plasma
sugar as a diagnostic test in a high risk group subjects. Our objective in this study was to assess the
correlation between urinalysis (clinistix®) as a screening method for diabetes and fasting plasma sugar,
American diabetes association criteria for diagnosing diabetes in high risk people with systemic
hypertension.
Methodology
Study Design: Cross sectional study
Study Location: This study was carried out at the Department of Medicine of the Lagos University
Teaching Hospital (LUTH) and the Endocrine Unit Laboratory of the Department of Medicine of the
College of Medicine, University of Lagos over a period of three months, spanning from January to March
2004. The Lagos University Teaching Hospital is located in Idi-Araba on the mainland and functions as a
tertiary health care centre.
Subjects: The subjects were people was People with known history of systemic hypertension on life-style
modification and/ or drug (s) for the control of the hypertension, attending the Medical out Patients’
Department of the hospital were consecutively recruited for the screening exercise for type 2 diabetes.
Those patients with established secondary form of hypertension, chronic renal failure and chronic liver
disease were excluded from the study to avoid situations that will interfere with glucose metabolism.
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Sample Size:
We recruited 206 persons to give room for attrition, out of which 131 (participation rate of 63.41%) of
them had FPS (Fasting Plasma Sugar) and urinalysis done; 87 were females constituting 65.64% while
males were 44 in number constituting 34.35%.
Approval was obtained from the Ethical Committee of the Lagos University Teaching Hospital. An
informed consent was obtained from the patients/ subjects before commencing the studies.
The patients on usual medical follow up were approached and given a brief health talk on the importance
of screening for diabetes among people with systemic hypertension. A questionnaire containing biodata
and anthropometry of the subjects were taken. The information taken included: name, age, gender,
hospital number, height (m) with measurement taken to the closest centimeter, weight (kg) to the closest
mg, and BMI calculated as the ratio of weight to the square of height in metres. Waist circumference was
taken at umbilical level, to the closest centimeter, Hip circumference measured at the maximal dimension
of the buttocks, to closest centimeters. Waist to hip ratio was calculated by finding the ratio of the waist to
that of hip.
Fasting Plasma Sugar Sampling and Preservation of plasma Sample
On the appointed day which is about fortnightly from the day the questionnaire was administered, they
presented by 7.30am. They were advised not to eat anything after the previous day dinner. Fasting Blood
samples were taken after the subjects had rested for about 30mins.
The venous blood samples were taken and centrifuged. The aliquots were prepared within 30min of
collection and were frozen at -80oC until conduction of the analyses in the same laboratory. Plasma
glucose was analyzed according to the method of Trinder (12) using glucose oxidase enzyme buffered in
phenoxylate and dissolved in colour reagent. The coefficient of variation for intra-assay was 3.5% and
inter-assay was 9%. Diabetes was diagnosed based on FPG of ≥126mg/dl (7.0mmol/l).
Performance of urinalysis
The Urinalysis was carried out in the clinic after the administration of the questionnaire. Plain bottles
were given to the patients to pass 3-5ml of non-fasting urine. The urine was mixed thoroughly and tested
by dipping the reagent area of the Clinistix® strip directly into the urine and removed immediately. The
edge of the strip was run against the rim of the container to remove excess urine during removal. The
colour change was read within 5- 10seconds by matching and comparing it with the colours on the strip
container. Presence of glucose in urine reading depicts a positive test and absence of glucose depicts a
negative test.
Statistics
The data were entered into a Microsoft Excel database. Analysis of data was with SPSS version 11. The
Means±SDs were assessed for continuous variables, and frequencies and proportions were assessed for
categorical variables. Differences among groups were assessed using t- test and p ≤ 0.05 is considered
significant. Sensitivity, specificity, predictive values and efficiency were assessed from 2x2 table 2 made
between FPG and urinalysis. The following performance of the test was carried out (13); Sensitivity is the
proportion of a diseased population that is identified by the screening test as positive-the true positive,
specificity is the proportion of the healthy population that is identified as healthy by the screening testthe true negatives, positive predictive result is the proportion of positive results in a mixed population of
sick and healthy people, negative predictive value is the proportion of negative results in a mixed
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population of sick and healthy people while efficiency is the percentage that the sum of the true positives
and the true negatives is of the grand total population.
A plot of correlation was made using a linear regression model where r and y were estimated.
Results
The mean age of the subjects was 53.11±8.69years and ranged from 31 to 78yrs and median of 52. The
mean parameters of the subjects studied were height of 1.63±0.68m, weight of 81.31±17.78kg, BMI of
30.43±6.66kg/m2, waist measurement of 98.21±11.65cm, hip measurement of 107.92±11.50cm, waist to
hip ratio of 0.91±0.08 and duration of hypertension was 8.56±8.80years. Nine (6.87%) of the subjects
tested positive for the screening test, constituting six females (4.58) and three males (2.26%) while one
hundred and twenty-two tested negative (93.13%); 81(61.83%) females and 41(31.30%) males. The
comparative parameters of those that tested positive and negative are as shown in table 1. The
anthropometric parameters were not significantly different except the biochemical profile, FPS.
The BMI of the subjects with positive screening tests increases with age while those with negative
screening results decrease as shown in fig 1. The waist to hip ratio of the subjects increases with age but
more remarkable among those with negative results as shown in fig. 2. The duration of hypertension
increases with age among people with negative result, while it is bimodal in people with positive result; it
is higher in those ≤ 40years compare to those who were 60-69years in the ratio of 1.1:1 as shown in fig. 3.
The mean FPS is 116.43±79.4mmol/dl; median is 96.30; 95.40 for females and 100.80 for males. The
range of the FPS is 56.70 – 583.20; 56.70-583.20 for females and 60.30-512.10 for males. The mean FPS
increases with age until age 60years when it began to decrease but more marked in those with positive
result as shown in fig. 4. Twenty five of the subjects tested positive for diagnostic test; 16 females and 9
males. While 106 tested negative; making 71 females and 35 males.
Using various modalities of assessing the performance of a screening test to the diagnostic test (13) shows
a sensitivity of 28%, specificity of 98%, positive predictive value of 77.77%, negative predictive value of
85.24% and efficiency of 84.73%. The correlation coefficient was 0.52; r2 is 0.27 which was statistically
significant (P v 0.00).
Discussion
Several health organizations have recommended screening for several reasons (6, 14, 15). First, one-third
to one-half of type 2 diabetes is undiagnosed and, hence, untreated (16, 17). Second, diabetic
complications are frequently present at clinical diagnosis (2, 18). Finally, earlier diagnosis and treatment
is believed to prevent or delay such complications and improve health outcomes (19).
Measurement of glycosuria using a cutoff point greater than or equal to a trace value has a low sensitivity
and a high specificity (7). Performance is usually better with random, postprandial, or glucose-loaded
measurements than with fasting measurements, perhaps in part because the renal threshold for glucose is
reached more often in the non fasting state (9). These statements were not coherent with our result. We
used random urine sample but still recorded low sensitivity value though a good specificity. Comparison
of the result of our study showed almost similar level of sensitivity reported by west et al (7) using
clinistix® for screening and FPG as gold standard. They reported a sensitivity of 35% while we got 28%
6
which is a bit higher than our sensitivity result. The reported specificity of 99.7% by west et al (7) is
comparable to our specificity of 98%. The marginal difference in the result of west et al (7) compare to
ours may be due to the fact that they recruited 4262 subjects including 50 known diabetes diabetics.
Another reason stated as part of the study weakness was that false negative rate was not extrapolated to
whole population in sensitivity calculation. The reported sensitivity of friderichsen et al (11) was lower
compare to our result. They reported sensitivity of 20%, though a comparable specificity of 99.14% in an
epidemiologic survey of 3041 out of which 1530 responded. They also used similar study apparatus;
glukotest® which is specific for glucose and FPG as gold standard. The reported low sensitivity in the
study of friderichsen et al (11) may be due to community sample of the study while ours was among the
high risk subjects. There is also reported good correlation between urine glucose and plasma glucose (20)
as reported in our study. Lawrence et al (20) reported a good correlation of 0.77 amongst people with
diabetes. Though the two correlations were statistically significant, the better correlation in the study of
Lawrence et al (20) compare to ours may be due to the fact that the sample population were diabetes
subjects.
Performance of a screening test using sensitivity, specificity and predictive scores have an interpretation
not shared by other measures of effect like odd ratio. They give a direct estimate of the proportion of the
population that can be correctly identified to develop or not to develop the outcome on the basis of a
criterion measure (21). These also have the advantage of not been a relative measure that requires a
comparison to a reference value (21).
This study is significant because no study to our understanding had carried similar study among people
with systemic hypertension. Our attempt to compare the screening yield among people with risk factor for
type 2 diabetes was cardinal. Similarly no available study has made attempt to calculate predictive factors
and to correlate the relationship between urinalysis as a screening tool with FPG. We have put all these
into analysis in our study.
Conclusion
This study supports the previous studies showing that urinalysis is a poor screening tool for type 2
diabetes. The yield is not increased by the presence of systemic hypertension as a risk factor for type 2
diabetes mellitus.
Limitations
Limited numbers of subjects were used and it was a hospital based study, we advise that a larger sample
of people with systemic hypertension should be used in further studies to substantiate the result we got in
this study.
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19. Pauker SG: Deciding about screening. Ann Intern Med 1993; 118:901–902,
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9
Table 1. Characteristic features of those screened for diabetes using urinalysis.
Features
Urinalysis
P value
Positive
Negative
Age(years)
54.44±9
53.02±8.66
0.63
Height(m)
1.66±0.07
1.63±0.08
0.025
Weight(Kg)
85.39±11.70
81±18.15
0.48
Body Mass Index(Kg/m2)
31.06±6.60
30.39±6.69
0.77
Waist (cm)
101.89±7.80 97.94±11.86
0.33
Hip (cm)
110.56±8.56 107.73±11.69
0.48
Waist to Hip ratio
0.92±0.05
0.91±0.08
0.69
Duration of Hypertension
8.56±8.80
9.31±8.07
0.79
Means Fasting Plasma Glucose (mg/dl) 267.91±184 105.25±52.07
0.00
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Table 2. Cross tabulation of Mean Fasting Plasma Sugar with Urinalysis values.
MeanFbsCat * Uri neCat Crosstabulation
Count
MeanFbsCat
Total
-VE
+VE
Uri neCat
Negative
Pos itive
104
2
18
7
122
9
Total
106
25
131
11
34
33
32
31
30
Mean BMI
29
Uri neCat
28
Negative
27
Positive
Less than 40yrs
40 - 49yrs
50 - 59yrs
70yrs and above
60 - 69yrs
Age in category
Fig 1. Relationship betw een BMI and Age category
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1.1
Mean WHRATIO
1.0
.9
Uri neCat
Negative
.8
Positive
Less than 40yrs
40 - 49yrs
50 - 59yrs
70yrs and above
60 - 69yrs
Age in category
Fig 2. Relationship betw een Waist to Hip ratio and Age category
13
20
10
Uri neCat
Negative
0
Positive
Less than 40yrs
40 - 49yrs
50 - 59yrs
70yrs and above
60 - 69yrs
Age in category
Fig 3. Relationship betw een Duration of hypertension and Age category
14
500
400
Mean MEANFBS
300
200
Uri neCat
100
Negative
0
Positive
Less than 40yrs
40 - 49yrs
50 - 59yrs
70yrs and above
60 - 69yrs
Age in category
Fig 4. Relationship betw een mean FPS and age category
15
600
500
400
300
MEANFBS
200
100
0
Rsq = 0.2701
-.2
0.0
.2
.4
.6
.8
1.0
Uri neCat
Fig 5. Correlation betw een FBS and Urinalysis
y=105.25 + 162.65, r =520
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1.2