Vol.3, No.1, 58-63 (2013) Open Journal of Preventive Medicine
http://dx.doi.org/10.4236/ojpm.2013.31008
Spouses of patients with diabetes mellitus type 2 at
increased risk of high blood glucose levels*
Ganiyu Lanre Yahaya1, Alero Ann Robert s2*, Victor Akpan Inem2
1Department of Family Medicine, Lagos State University Teaching Hospital, Lagos, Nigeria
2Department of Community Health & Primary Care, College of Medicine, University of Lagos, Lagos, Nigeria
*Corresponding Author: aaroberts@cmul.edu.ng
Received 29 December 2012; revised 29 January 2013; accepted 5 February 2013
ABSTRACT
Introduction: Diabetes mellitus type 2 is a grow-
ing threat in developing countries already bur-
dened with high levels of infectious disease.
Screening the general population has debatable
advant a ges. This s tudy aims to de termine whether
spouses of patients with diabetes mellitus have
higher random blood glucose (RBG) levels as
well as the benefit of RBG testing as a targetted
screening tool. Methodology: The survey em-
ployed a cross-sectional comparative study of
spouses’ of diabetics and non-diabetics attend-
ing the general out-patient department of the La-
gos State University Teaching Hospital (LASUTH),
Ikeja. A modified WHO STEPS Surveillance In-
strument and a one-touch Glucometer were
used to collect data. Blood pressures and BMI
were measured and correlated to blood glucose
levels. Results: Prevalence of high RBG was
found to be 7% among spouses of diabetics and
3.3% among spouses of non-diabetic patients.
Mean RBG was 5.57 mmol/L and 7.7 mmol/L
within the age group 40 - 49 years and 50 - 59
years respectively among spouses of diabetic
patients compared to 5.4 mmol/L and 5.5 mmol/L
within the same age group among the spouses
non-diabetics. S pouses of patients with diabetes
mellitus had higher systolic and diastolic blood
pressures and BMI comp ared to spo uses of non-
diabetics. Conclusion: Being male, married to a
diabetic patient, lower educational levels and
higher body mass index are significantly asso-
ciated with higher random blood glucose in the
spouses of diabetic patients. Random blood
glucose measurements are an effective screen-
ing tool and spouses of diabetic patients can
benefit from targeted screening in controlled
clinical settings.
Keywords: Diabetes Mellitus Type 2;
Non-Communicab le Disease; Rando m Blood
Glucose Levels; Glucose Intolerance; Body Mass
Index; Blood Pressure
1. INTRODUCTION
Diabetes mellitus type 2 is a growing threat in devel-
oping countries already burdened with high morbidity
and mortality rates from infectious diseases, maternal
and infant health concerns and weak ineffective health
systems [1,2]. Analysis of the g lobal and region al burden
of non-communicable diseases shows that almost half the
disease burden in developing countries is from non-
communicable diseases, with 15 to 59 year olds facing a
30% greater risk of death from an NCD than their coun-
terparts in the developed world [3]. In Nigeria there has
been an increase in the prevalence of diabetes mellitus
from 0.39% reported in a hospital population in 1963, to
6.8% in 2003 which is comparable to global estimated
prevalence of 6.4%, with the largest proportion of in-
crease occurring in developing countries [4-6]. Overall
about 1.05 million people are diabetic in Nigeria and
most of these are type II. Urban communities had a
higher over all prevalence of diabetes mellitus (3.3%)
when compared with rural communities (2.6%). The
burden of diabetes in Nigeria is expected to increase
even further [5].
The rising prevalence of diabetes mellitus cannot be
linked only to the genetic factors of ageing populations.
Environmental factors of obesity, diet and physical activ-
ity have a major influence. Various studies have exam-
ined the effect of environmental influences versus ge-
netic factors in twins and cohabiting couples in morbid-
ities such as coronary disease, cancer, hypertension and
depression [7-13].
*Key findings: a statistically significant 7% of spouses of diabetic
p
atients had random blood glucose levels ove
r
11 mmol/L, compared
to 3.3% of spouses in the comparative group. It was also observed that
spouses of non-diabetic patients had statistically significantly lower
systolic and diastolic blood pres s ures.
Copyright © 2013 SciRes. OPEN ACCE SS
G. L. Yahaya et al. / Open Journal of Preventive Medicine 3 (2013) 58-63 59
Screening for disease in the general population is ap-
propriate when certain condition s are met with regards to
representing a public health burden with known patho-
physiology and a defined, asymptomatic preclinical stage
when the disease can be diagnosed by reliable acceptable
tests.
Diabetes meets many of the conditions for screening,
which is cost-effective if done as a systematic process.
Community screening is usually poorly targeted , tends to
test those at low risk (the worried well) and those already
diagnosed. However, in developing countries, there is
benefit to be obtained from case detection using oppor-
tunistic events where there is clinical evidence of risk
fa ctors [14 ,15]. The cost-effectiveness of targeted scr een-
ing of people attending clinics has been shown to have
benefits of being able to institute preventive and thera-
peutic measures to reduce the impact of more serious
complications [16,17]. The use of fasting blood glucose
(FBG) and 2-hour blood glucose (2-hBG) have com-
monly been used as screening for type 2 diabetes melli-
tus especially for making the definitive diagnosis of dia-
betes in patients that h ave pr esen ted with th e typical triad
of polyuria, polyphagia and polydipsia. However, the use
of random blood glucose levels has the advantage of not
requiring a special time of day or trained personnel and
can therefore be quickly used to screen [18]. This study
set out to determine whether spouses of patients with
type 2 diabetes mellitus are at risk of developing higher
levels of random blood glucose and the value of random
blood glucose testing as a screening tool for spouses of
identified diabetic patien ts.
2. METHODOLOGY
This was a cross-sectional comparative study carried
out in the general out-patients department (GOPD) of the
Lagos State University Teaching Hospital. One thousand
four hundred and sixty two patients attending the outpa-
tients’ clinic were divided into 2 groups based on the
sampling formula using a prevalence rate of 2.2% [4].
Respondents of the first group was made up of spouses
of known diabetics aged 30 years and over who had been
diagnosed previously and were attending the GOPD for
regular follow-up. The second group was made up of the
spouses of other patients attending GOPD who neither
had diabetes mellitus nor had been diagnosed with same
at the time of recruitment. For this study, spouses re-
ferred to a married couple aged 30 years and above, of
opposite genders living at the same address, with the
same surname [11].
The WHO STEPS questionnaire was administered to
each respondent after verbal and written consent had
been obtained. The questionnaire examined socio-demo-
graphic and socio-economic data, knowledge of diabetes
mellitus; its risk factors and management, lifestyle risk
perception and behaviour of the respondents of both
groups.
Diabetic patients were those who had previously been
diagnosed by having had two fasting blood glucose lev-
els of >7.0 mmol/L, but who did not require insulin for
management and had not had ketonuria in the previous
six months. All respondents were measured for weight,
height and truncal circumferences. The body mass index
(BMI) and waist-hip (W-H) ratios were calculated and
random blood glucose levels were clinically determined.
Blood pressure was measured as three supine readings
taken at 5 minute intervals. Diastolic pressure was meas-
ured as Korotkoff phase 5.
Data was collated and analyzed using SPSS version 14
and presented as means (±SD) and/or medians (range)
where relevant. Differences in variables between the two
groups was examined using Student’s t test, and χ2
(Chi-Square) was used to examine the discrete variables.
Statistical significance was determined at P < 0.05.
3. RESULTS
Of the 1462 patients recruited into the study, 62 eith er
did no t consent to contin ue in the study, wer e lost to fol-
low-up, or could not be reached at the addresses pro-
vided. Their data were used to establish the contiguity of
the groups but were not included in the final statistical
analysis. There was some statistical difference in the
socio demographic characteristics between the two
groups. More spouses were females and more spouses of
diabetics were aged 60 and over. Significantly more
spouses of non-diabetics earned over N30,000 ($200) a
month. Over a third of the respondents of both groups
lived within walking distance (Table 1).
Seventy two respondents had random blood glucose
levels over 11 mmol/L, of which significantly more than
hal f ( 4 9 /7 2) were spouses of diabetic patients (P > 0. 00 1 ) .
It was also observed that spouses of non-diabetic patients
had statistically significantly lower systolic and diastolic
blood pressures (P > 0.001). Waist-hip ratios measured
were high in both groups, but significantly lower in the
group of spouses of non-diabetics (P = 0.027) (Table 2).
Random blood glucose levels in spouses of diabetic
patients showed statistically significant association with
increasing age, being male and higher income brackets
(P > 0.001). Two-thirds of respondents in both groups
had body mass indices (BMI) over 30, and this was sig-
nificantly more prevalent among spouses of diabetic pa-
tients (Table 3).
4. DISCUSSION
This study shows that spouses of diabetic patients are
twice as likely to have higher than normal random blood
glucose levels compared to spouses of patients that did
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G. L. Yahaya et al. / Open Journal of Preventive Medicine 3 (2013) 58-63
Copyright © 2013 SciRes. OPEN ACCE SS
60
Table 1. Socio-demographic characteristics of respondents.
Variables Spouses of the diabetics N (%) Spouses of Non-diabetics N (%) X
2 P
Age (years)
30 - 39 169 (24.1) 110 (15.7)
40 - 49 24 (3.4) 134 (19.1)
50-59 151 (21.6) 160 (22.9)
60 and above 356 (50.9) 296 ( 42.2) 94.84 0.00**
Sex
Males 332 (47.4) 335 (47.6)
Females 368 (52.6) 365 ( 52.4) 0.872 0.03**
Religion
Christianity 489 (69.9) 484 (69. 1)
Islam 172 (24.6) 167 (23.9)
Traditional Religion 39 (5.6) 49 (7.0) 1.24 0.54
Education
No formal education 190 (27.1) 194 (27.7)
Primary School 260 (37.1) 250 (35.7) 4.9 0.17
Secondary 212 (30.3) 233 (33.3)
University 38 (5.4) 23 (3.3)
Family income per month
Less than N10,0001 267 (38.1) 140 (20.0)
N10,001 to N20,000 191 (27.3) 135 (19.3)
N20,001 to N30,000 124 (17.7) 210 (30.0)
Above N30,000 118 (16.9) 215 (30.7) 102.5 0.00**
Nearness to health care faci li t y
Walking distance 256 (36.6) 275 (39.3)
5 km 140 (20.0) 140 (20.0)
10 km 159 (22.7) 145 (20.7)
15 km 145 (20.7) 140 (20.0) 1.41 0.70
*Computed on the basis of daily incomes of $2 at rate of $1 to N150.
Table 2. Random blood glucose levels in spouses of diabetic and non-diabetic patients.
RBG (mmol/L) Spouse s of diabetics Spouses of non-diabetics P
N (%) N (%)
<11.1 651 (93.0) 677 (96.7)
>11.1 49 (7.0) 23 (3.3) 0.0016**
Blood pressure measurements & W-H ratio
Systolic BP (mmHg) 129.8 ± 13.1 112 ± 10.1 0.000***
Diastolic BP (mmHg) 81.2 ± 8.3 76.1 ± 6.1 0.000***
Waist-Hip Ratio 0.99 ± 0.13 0.97 ± 0.11 0.027***
*Computed on the basis of daily incomes of $2 at rate of $1 to N150.
G. L. Yahaya et al. / Open Journal of Preventive Medicine 3 (2013) 58-63 61
Table 3. Correlates of random blood glucose levels of spouses of diabetic and non-diabetic patients.
Spouses of diabetics RBG (mmol/L) Spouses of non-diabetics RB G (mmol/L)
N (%) N (%) P N (%) N (%) X 2 P
<11.1 >11.1 <11.1 >11.1
Age
30 - 39 159 (22.7) 10 (1.4) 105 (15) 5 (0.7) 0.25 0.62
40 - 49 15 (2.1) 9 (1.3) 129 (18.4) 5 (0.7) 28.74 0.0000**
50 - 59 138 (19.7) 13 (1.9) 155 (22.1) 5 (0.7) 4.29 0.04*
>60 339 (48.4) 17 (2.4) 288 (41.1) 8 (1.1) 1.88
Sex
Males 324 (46.3) 23 (3.3) 542 (77.4) 15(2.14) 8.22 0.004**
Females 327 (46.7) 26 (3.7) 135 (19.3) 8 (1.14) 0.55 0.48
Education
No Formal Education 165 (23.5) 25 (3.5) 187 (26.7) 7 (1.0) 11.46 0.0007**
Primary 244 (34.6) 16 (2.3) 241 (33.4) 9 (1.3) 4.12 0.004**
Secondary 207 (29.6) 5 (0.7) 229 (32.7) 4 (0.6) 9.20 0.002**
University 35 (5.0) 3 (0.4) 0.000** 20 (2.9) 3 (0.4) 0.43
Family Income Per month
Less than 10,000 237 (33.6) 30 (4.3) 134 (19.1) 1(1.9) 0.58
10,001 - 20,000 183 (26.1) 8 (1.1) 121 (17.3) 5 (0.7) 0.32
20,001 - 30,000 119 (17.0) 5 (0.7) 0.007** 207 (29.3) 3 (0.4) 2.26
Above 30,000 112 (16.0) 6 (0.9) 215 (30.7) 2 (0.3) 5.68 0.02**
Body Mass Index
18 - 24.9 167 (23.9) 5 (0.7) 163 (23.3) 4 (0.6) 0.00 0.96
25 - 29.9 30 (4.3) 11 (1.6) 44 (6.3) 5 (0.7) 3.66 0.06
>30 454 (64.6) 35 (5.0) 0.0000** 470 (67.1) 14 (2.0) 9.25 0.0023**
*Computed on the basis of daily incomes of $2 at rate of $1 to N150.
not have diabetes. The findings were very similar to others
who also noted that age, sex, BMI and waist circum-
ference did not have any significant influence on the
findings [19]. The phenomenon of spousal concordance
has been demonstrated in spouses of patients of hyper-
tension who were found to have higher tendencies to
themselves develop hypertension [7] and diabetes [10]
for reasons attributed to both spouses living in environ-
mentally similar situations. The finding of higher blood
pressure and BMI mirrored other studies [11] and this
was significant. In view of the finding that a significant
proportion of spouses of diabetic patients lived on less
than $2 a day (less than N10,000 per month), setting the
random blood glucose cut-off point at 11 mmol/L, pre-
sented the financial advantage to patients of immediately
instituting preventive and therapeutic measures in those
patients are definite risk of microvascular complications.
[20] Lower departures from normal have the opportunity
to be evaluated using FBG and OGTT. Research evi-
dence has consistently shown that early targetted treat-
ment of diabetes mellitus and conditions known to be
risk factors can significantly decrease the development
and/or progression of chronic complications [21-25].
In consonance with studies done to screen for gesta-
tional diabetes mellitus, the use of random blood glucose
testing was shown to have the same sensitivity and
specificity as traditional risk factors and offer a measure
of cost-effectiveness in reducing the tendency to develop
cardiovascular complications [26-28]. Spouses of dia-
betic patients have a greater tendency to higher random
Copyright © 2013 SciRes. OPEN ACCE SS
G. L. Yahaya et al. / Open Journal of Preventive Medicine 3 (2013) 58-63
62
blood glucose levels and can benefit from targeted ran-
dom blood glucose testing as part of a 2-stage screening
process that affords them the opportunity to discuss the
results and management options with a primary care pro-
vider in a clinical setting. Research is needed to deter-
mine whether the extra years of treatment that individu-
als will receive if screening determines their pre-diabetic
state will result in significantly improved diabetes related
cardiovascula r out comes in a cost-effe ct i ve manner.
5. KEY MESSAGES
Spouses of diabetic patients with a greater tendency
to higher random blood glucose levels can benefit from
targetted screening in a clin ical setting.
• Random blood glucose measurements are an effec-
tive screening tool in controlled clinical setting s.
REFERENCES
[1] Miranda, J.J., Kinra, S., Casas, JP.., Smith, G.D. and
Ebrahim, S. (2008) Non-communicable diseases in low-
and middle-income countries: Context, determinants and
health policy. Tropical Medicine & International Health,
13, 1225-1234.
d oi: 10. 1111/j .1 3 65 -3156.2008.02116.x
[2] WHO (2005) Preventing chronic disease: A vital invest-
ment. WHO, Geneva.
[3] Lopez, A.D., Mathers, C.D., Ezzati, M., Jamison, D.T.
and Murray, C.J. (2006) Global and regional burden of
disease and risk factors: Systematic analysis of popula-
tion health data. Lancet, 367, 1747-1757.
doi:10.1016/S0140-6736(06)68770-9
[4] Kinnear, T.W. (1963) The pattern of diabetes mellitus in a
nigeria teaching hospital. East African Medical Journal,
40, 288-294.
[5] Nyenwe, E.A., Odia, O.J., Ihekwaba, A.E., Ojule, A. and
Babatunde, S. (2003) Type 2 diabetes in adult Nigerians:
A study of its prevalence and risk factors in Port Harcourt,
Nigeria. Diabetes Research and Clinical Practice, 62,
177-185. doi:10.1016/j.diabres.2003.07.002
[6] Shaw, J.E., Sicree, R.A. and Zimmet, P.Z. (2009) Global
estimates of the prevalence of diabetes for 2010 and 2030.
Diabetes Research and Clinical Practice, 87, 4-14.
doi:10.1016/j.diabres.2009.10.007
[7] Gwatkin, D., Guillot, M. and Heuveline, P. (1999) The
burden of disease among the global poor. Lancet, 354,
586-589. doi:10.1016/S0140-6736(99)02108-X
[8] Di Castelnuovo, A., Quacquaruccio, G., Donati, M.B., de
Gaetano, G. and Iacoviello, L. (2009) Spousal concor-
dance for major coronary risk factors: A systematic re-
view and meta-analysis. American Journal of Epidemi-
ology, 169, 1-8. doi:10.1093/aje/kwn234
[9] Brenn, T. (1993) Adult family members and their resem-
blance of coronary heart disease risk factors: The cardio-
vascular disease study in Finnmark. European Journal of
Epidemiology, 13, 623-630.
doi:10.1023/A:1007333919898
[10] Freidman, G.D. and Quesenberry, C.P. (1999) Spousal
concordance for cancer incidence: A cohort study. Cancer,
86, 2413-2419.
doi:10.1002/(SICI)1097-0142(19991201)86:11<2413::AI
D-CNCR32>3.0.CO;2-J
[11] Kolonel, L.N. and Lee, J. (1981) Husband-wife corre-
spondence in smoking, drinking and dietary habit. The
American Journal of Clinical Nutrition, 1, 99-104.
[12] Hippisley-Cox, J., Coupland, C., Pringle, M., Crown, N.
and Hammersley, V. (2002) Married couples’ risk of the
same disease: Cross sectional study. British Medical
Journal, 325, 636-638.
doi:10.1136/bmj.325.7365.636
[13] Khan, A., Lasker, S.S. and Chowdhury, T.A. (2003) Are
spouses of patients with type-2 diabetes at increased risk
of developing diabetes? Diabetes Care, 26, 710-712.
doi:10.2337/diacare.26.3.710
[14] American Diabetes Association (Position Statement)
(2003) Screening for type 2 diabetes. Diabetes Care, 26,
S21-S24. doi:10.2337/diacare.26.2007.S21
[15] Beaglehole, R., Epping-Jordan, J., Patel, V., Chopra, M.,
Ebrahim, S., Kidd, M. and Haines, A. (2008) Improving
the prevention and management of chronic disease in
low-income and middle-income countries: A priority for
primary health care. Lancet, 372, 940-949.
doi:10.1016/S0140-6736(08)61404-X
[16] Waugh, N., Scotland, G., McNamee, P., Gillett, M., Bren-
nan, A., Goyder, E., Williams, R. and John, A. (2007)
Screening for type 2 diabetes: Literature review and eco-
nomic modelling. Health Technology Assessment, 11, 1-
125.
[17] Backholer, K., Chen, L. and Shaw, J. (2012) Screening
for diabetes. Pathology, 44, 110-114.
doi:10.1097/PAT.0b013e32834e8e12
[18] Somannavar, S., Ganesan, A., Deepa, M., DAtta, M. and
Mohan, V. (2009) Random capillary blood glucose cut
points for diabetes and prediabetes derived from commu-
nity-based opportunistic screening in India. Diabetes
Care, 32, 641-643. doi:10.2337/dc08-0403
[19] Trejo-Arteaga, J.M., López-Carmona, J.M., Rodríguez-
Moctezuma, J.R., Peralta-Pedrero, M.L., Escudero-Mon-
tero, R., Gutiérrez Escolano, M.F. (2008) Risk of glucose
metabolism changes in spouses of Mexican patients with
type 2 diabetes. Medicina Clínica, 131, 605-608 (Article
in Spanish). doi:10.1157/13127917
[20] McCance, D.R., Hanson, R.L., Charles, M.-A., Jacobsson,
L.T.H., Pettitt, D.J., Bennett, P.H., et al. (1994) Compari-
son of tests for glycated haemoglobin and fasting and two
hour plasma glucose concentrations as diagnostic meth-
ods for diabetes. British Medical Journal, 308, 1323-
1328. doi:10.1136/bmj.308.6940.1323
[21] Diabetes Control and Complications Trial Research
Group (1993) The effect of intensive treatment of diabe-
tes on the development and progression of long term
complications in insulin-dependent diabetes mellitus. The
New England Journal of Medicine, 329, 977-986.
doi:10.1056/NEJM199309303291401
Copyright © 2013 SciRes. OPEN ACCE SS
G. L. Yahaya et al. / Open Journal of Preventive Medicine 3 (2013) 58-63
Copyright © 2013 SciRes. OPEN ACCE SS
63
[22] Okhubo, Y., Kishikawa, H., Araki, E., et al. (1995) Inten-
sive insulin therapy prevents the progression of diabetic
micro-vascular complications in Japanese patients with
non insulin dependent diabetes mellitus: A randomized
prospective 6-year study. Diabetes Research and Clinical
Practice, 28, 103-117.
doi:10.1016/0168-8227(95)01064-K
[23] UK Prospective Diabetes Study (UKPDS) Group (1998)
Intensive blood glucose control with sulphonylurea or
insulin compared with conventional treatment and risk of
complications in patients with type 2 diabetes (UKPDS33).
Lancet, 352, 837-853.
[24] Stratton, I.M., Adler, A.I., Neil, H.A., et al. (2000) Asso-
ciation of glycaemia with macrovascular and microvas-
cular complications of type 2 diabetes (UKPDS 35): Pro-
spective observational study. British Medical Journal, 321,
405-412. doi:10.1136/bmj.321.7258.405
[25] Simmons, R.K., Harding, A.H., Jakes, R.W., Welch, A.,
Wareham, N.J. and Griffin, SJ. (2006) How much might
achievement of diabetes prevention behaviour goals re-
duce the incidence of diabetes if implemented at the
population level? Diabetologia, 49, 905-911.
doi:10.1007/s00125-006-0163-1
[26] Ostlund, I. and Hanson, U. (2004) Repeated random
blood glucose measurements as universal screening test
for gestational diabetes mellitus. Acta Obstetricia et Gy-
necologica Scandinavica, 83, 46-51.
[27] Adegbola, O. and Ajayi, G.O. (2008) Screening for gesta-
tional diabetes mellitus in Nigerian pregnant women us-
ing fifty-gram oral glucose challenge test. West African
Journal of Medicine, 27, 139-143.
[28] Chatterjee, R., Narayan, K.M., Lipscomb, J. and Phillips,
L.S. (2010) Screening adults for pre-diabetes and diabetes
may be cost-saving. Diabetes Care, 33, 1484-1490.
doi:10.2337/dc10-0054