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SA JOURNAL OF DIABETES & VASCULAR DISEASE
RESEARCH ARTICLE
VOLUME 18 NUMBER 1 • JULY 2021
5
outcomes, appropriate individuals to screen, optimal screening
time, the appropriate screening tool and appropriate diagnostic
criteria. This has resulted in several revisions of diagnostic criteria
by various groups.
There are two large studies that have influenced the interpretation
of diagnostic criteria. The 2005 Australian Carbohydrate Intolerance
Study in Pregnancy (ACHOIS)
14
demonstrated that mild forms of
hyperglycaemia, below those diagnostic of GDM, were associated
with poor perinatal outcomes. The 2008 Hyperglycaemia and
Pregnancy Outcomes (HAPO) study
15
showed a linear association
between maternal hyperglycaemia and adverse events, including
macrosomia, pre-eclampsia, caesarean section rates and neonatal
hypoglycaemia with no clear cut-off above which these adverse
events occurred.
Following the HAPO study, the IADPSG recommended new
criteria for the diagnosis of GDM with a fasting plasma glucose
cut-off level much lower than the WHO criteria.
16
This has
resulted in up to a three-fold increase in the proportion of women
diagnosed as having GDM using the IADPSG criteria compared
to WHO criteria. There is varied opinion as to whether IADPSG
criteria universally translate into improved outcomes, particularly
when applied to a population that is different from that in the
HAPO study.
16-19
Some guidelines favour selective screening of women with
known risk factors for GDM in order to avoid unnecessary
screening of low-risk women. Whether the traditional risk factors,
as described in studies in high-income countries, are applicable to
and predict GDM in sub-Saharan Africa has not been explored.
Establishing a risk-factor profile for women with GDM to be
prioritised for screening is essential, particularly in a low-resource
setting such as Malawi where routine screening of all pregnant
women is not feasible. Random blood glucose (RBG), fasting blood
glucose and the 50-g oral glucose tolerance (OGTT) tests have all
been used in studies as screening tests.
20
Finger-prick RBG, although
inferior to formal laboratory glucose tests, is a feasible screening
option in Malawi where the majority of the population has limited
access to formal blood glucose tests.
This study aimed to establish the prevalence and risk factors for
GDM among urban women in Blantyre, compare the differences
in prevalence using the different cut-offs defined in the WHO and
IADPSG criteria, and assess if the prevalence would differ in women
seen at government antenatal clinics (ANCs) compared to those
attending private ANCs.
Methods
Blantyre is the main commercial city in southern Malawi, with an
estimated population of 1.1 million.
21
Queen Elizabeth Central
Hospital (QECH) is the main government tertiary referral centre.
Chilomoni and Limbe health centres are government primary-
care facilities in Blantyre with an average ANC attendance of 100
women per day. Mwaiwathu and Blantyre Adventist hospitals are
the two main private hospitals in Blantyre.
In this cross-sectional study, consecutive women presenting
at any gestational age to QECH, Chilomoni and Limbe ANCs
between 1 June and 30 September 2012 and at Mwaiwathu and
Blantyre Adventist hospital private ANCs between February and
April 2013 were asked to participate in the study. Recruitment was
restricted to women of Malawian origin residing in Blantyre during
the study period.
Ethical approval for the study was obtained from the Malawi
College of Medicine Research and Ethics Committee (reference
number P02 12 1170). Each participant provided written consent.
For participants who could not read or write, the consent form
was read out to them by a research assistant and the participant
gave verbal consent and put her fingerprint on the consent form
to acknowledge her voluntary participation in the study. The
consent form was available in English and the vernacular and had
been approved by the College of Medicine Research and Ethics
Committee prior to commencement of the study.
Consenting women had a capillary RBG test done at the clinic site
with a finger-prick test and a SDCheck
®
glucometer (SD Standard
Diagnostics Inc, Hagal-dong, Korea). A sub-sample of 200 women
from the government ANCs and 50 women from the private
ANCs were randomly selected for an OGTT by selecting every fifth
woman who was recruited. Gestational age was calculated from
the last normal menstrual period.
For RBG, a sample size of 614 was initially calculated in order
to detect hyperglycaemia at an estimated prevalence of 2–3%
(suggested by local Blantyre obstetricians from observation) but
the sample size was subsequently increased after detecting a high
proportion of normal RBGs when recruitment began. Furthermore,
the test could easily be administered to large numbers of women
attending the facilities within a short period of time. The sample
size of 250 for OGTTs was limited by available resources to
perform OGTTs.
All OGTTs were done at QECH laboratory and plasma glucose
level was determined using an automatic analyzer (KeyLab BPC
BioSed
®
, Rome, Italy). OGTTs were done following the 1999 WHO
guidelines, with each participant having a fasting plasma glucose
test done and then being given 75 g of anhydrous glucose dissolved
in 200 ml of water to drink. Plasma glucose level was re-checked
two hours after taking the glucose solution.
Using the WHO criteria,
22
GDM was defined as a fasting plasma
glucose of 7.0 mmol/l or a two-hour plasma glucose of 11.1 mmol/l.
Using the modified IADPSG criteria,
15
GDM was defined as a fasting
plasma glucose of ≥ 5.1 mmol/l or two-hour plasma glucose of
8.5 mmol/l.
16
Blood pressure (BP), weight, height and mid upper-arm
circumference (MUAC) were recorded on recruitment. BP was
measured with an Omron
®
digital BP machine (Omron Healthcare
Worldwide, Kyoto, Japan). Weight was measured using a digital
scale. Where previously documented in the woman’s health records,
the pre-pregnancy weight was noted. The majority of the women
did not have a documented pre-pregnancy weight or height and
pre-pregnancy body mass index (BMI) could not be calculated.
MUAC was used to assess nutritional status as a single BMI in
pregnancy is not an accurate measure because of the additional
weight gain from pregnancy.
23,24
Patients diagnosed with GDM or hypertension were referred to
the QECH, Mwaiwathu and Blantyre Adventist specialist diabetes
clinics for follow up and management.
Statistical analysis
Means and percentages were used to explore the distribution
of risk factors between government and private ANCs. The
relationship between GDM prevalence and risk factors was first
explored through univariate analyses. The
t
-test comparing women
with GDM to those without GDM was used to assess if any of
the continuous risk factors were associated with prevalence. To