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Gestational diabetes mellitus: An educational opportunity

Ameed Siyam
, Nikita Lotwala
, Gloria Bachmann
, Teresa Janevic
, Susan Peck
, Mary Gastrich

Gestational diabetes mellitus (GDM) currently affects 7% of all pregnancies (Setji et al, 2005). In particular, gestational impaired glucose tolerance is associated with increased rates of prematurity, large for gestational age infants, macrosomic infants and admission to the neonatal intensive care unit for 2 days or longer (Ostlund et al, 2003). Using a validated survey tool (Carolan et al, 2010), this American study assessed the knowledge, attitudes and beliefs of pregnant women about this condition. Questions addressed medical risk, prevention and outcomes of GDM as well as nutritional and exercise benefits. This article also discusses the implications of these findings for future educational programmes.

Gestational diabetes mellitus (GDM), which presents during pregnancy, is one of the most common antepartum complications, affecting approximately 7% of all pregnancies, with a range from 1 to 14%, depending on the population sample and diagnostic criteria (Setji et al, 2005). GDM affects around 3.5% of all pregnancies in England and Wales. During the past 20 years in the US, there has been an 10-100% increase in GDM, especially in susceptible ethnicity groups (Dabelea et al, 2005; Ferrara, 2007). Known risk factors for GDM include obesity, family history of diabetes and older maternal age (Ferrara, 2007).

Scope of GDM sequelae
Gestational impaired glucose tolerance is significantly associated with infant prematurity, increased proportion of large for gestational age infants, macrosomic infants and admission of infants to the neonatal intensive care unit for 2 days or longer (Ostlund et al, 2003). Excessive maternal weight gain is often the first sign of GDM (Metzger et al, 2007; American Diabetes Association, 2010). GDM is attributable to adverse perinatal outcomes, including increased risk of cardiovascular outcomes, stillbirth, early childhood obesity and adverse maternal outcomes, such as, increased rates of pre-eclampsia, caesarean and operative births (Kendrick, 2011).

A recent literature review has also suggested that gestational diabetes and fetal macrosomia are independent risk factors for shoulder dystocia (Young and Ecker, 2013). While GDM thresholds need further definition, randomised trials of glycaemic control in pregnancies complicated by GDM show that treatment decreases rates of these conditions (Young and Ecker, 2013). 

Previous studies
There are few validated questionnaire studies on GDM. Three studies have assessed women’s knowledge of GDM, two of which were small-scale studies (n<20). A qualitative study was conducted in Australia (n=17) on South Asian women who were recently diagnosed with GDM in order to assess their experiences and understanding of GDM after diagnosis (Bandyopadhyay et al, 2011). However, the study produced mixed results for various reasons (for example, emotional state of the participants) and participants had difficulty following a prescribed diet, presumably because of poor comprehension and cultural differences (Bandyopadhyay et al, 2011). 

Another interview study (n=12) was conducted in a diabetes clinic in an urban hospital in Western Canada. Results indicated women diagnosed with GDM had difficulty with lifestyle changes, but were aware of their obligation to remain healthy for both themselves and the newborn and expressed a need to communicate with their peers about their experience (Evans and O’Brien, 2004). 

The larger study involved a cross-sectional survey administered at a Pregnancy Diabetes Clinic in Melbourne, Australia to women of various ethnicities (n=200) in order to evaluate the attitudes towards GDM (Carolan et al, 2010). The results of the study indicated the women did not perceive GDM to be serious. Non-Caucasian women were identified as having a higher risk of GDM and associated with significant differences in perinatal outcomes, including higher rates of neonatal morbidity. The reasons were not well-defined but it was suggested that it may be a result of poorer access to services and socioeconomic disparity (Carolan et al, 2010). The authors also suggested that non-Caucasian women may be at risk of poorer self-management due to lower education and a poor understanding of GDM. Results of the study suggested that GDM educational strategies need to be implemented.

Educational efforts
In the US, the national Diabetes Prevention Program has shown the positive impact of educational interventions to prevent progression from GDM to type 2 diabetes (Gabbe et al, 2013). Early counselling of families has been recommended by the Fifth International Workshop Conference on GDM (Metzger et al, 2007) to avoid excessive maternal and fetal weight gain. Educational programmes have been recommended that emphasise reduced fat and energy intake, regular physical activity and regular clinic visits (American Diabetes Association, 2002). The study by Carolan et al (2010) indicates that education of GDM was not adequate. 

Study aims
The objective of this study was to assess GDM knowledge and beliefs of pregnant women on their first antepartum visit by the use of a modified Carolan et al (2010) questionnaire (Box 1). Women participated before they were screened for GDM. 

Method
This cross-sectional survey study was approved by the Robert Wood Johnson Medical School Institutional Review Board Human Subjects Protection Program.

Pregnant, low-risk women attending a prenatal, obstetric practice were asked to participate in this study (n=85). The women completed the survey during their initial prenatal ambulatory visit, at an average of 8–10 weeks’ gestation. None of the women, their clinicians or the study team knew whether the women had GDM. The survey took place from January 2011 to September 2012. 

A validated questionnaire (Box 1) developed by Carolan et al (2010) was used. A modified, shortened version of the survey was used for two reasons: firstly, to exclude questions relating to the treatment of diabetes, since our study group did not have diabetes; and secondly, to reflect American nomenclature. The survey questions covered diagnosis of GDM factors, nutrition, prevention, medical risks of GDM, treatment, causes and potential outcomes.

Statistical analysis
The percentage of women who correctly answered each multiple choice question was calculated and a “GDM knowledge score” was calculated for each participant. Cronbach’s alpha was used to assess internal consistency. After omitting questions 2 and 17, which no one answered correctly, Cronbach’s alpha was 0.77. This result indicates that the questions did an acceptable job of measuring GDM knowledge. Questions 2 and 17 were then dropped and knowledge scores recalculated. Finally, the GDM knowledge scores between age and ethnic groups were compared using ANOVA. Estimates for all tests were considered to be statistically significant with P<0.05.

Results
Eighty-five English-speaking pregnant women (aged 18–45) participated. The ethnicity of the participants is shown in Table 1. Final analysis was performed on 79 surveys (six surveys were missing or had incomplete data). Most of the women were not previously diagnosed with GDM (n=74). Table 2 indicates the percentage of participants who correctly answered the survey questions.

Questions answered correctly
The six questions that were answered correctly by more than 50% of the participants fell into three medical categories including: 

  • Diagnosis of GDM factors: For example, in uncontrolled GDM, blood glucose levels are increased (74.1% answered correctly); importance of blood glucose control (83.5%); complications of poor control of GDM (64.6%); and what to do if you feel low blood glucose levels (72.9%).
  • Nutritional status of common foods: For example, rice is a carbohydrate (88.2% answered correctly) and butter is a fat (82.4%). 
  • Prevention: For example, 52.9% answered correctly that exercise is important in GDM. 

Questions answered incorrectly
The categories that participants knew the least about (less than 50% answered correctly) were:

  • Medical risks of GDM: For example, risk factors for GDM (0% answered correctly). 
  • Treatment of GDM (what to do questions): For example, measurement of GDM (normal range for fasting blood sugar, 14.1%) or general nutrition (foods permitted to eat, 37.7%). 
  • Causes of the condition: Only 10.6% knew the cause of low blood sugar; with regard to prevention and purpose of prevention, only 37.7% knew about the foods they were permitted to eat to prevent GDM.
  • Outcomes of GDM: Only 9.4% understood consequences to baby and 8.2% knew consequences for mother.  

Of interest, while over 50% of participants knew that moderate exercise is important for GDM, none responded correctly to the question concerning how exercise lowers blood glucose, prevents excessive weight gain and allows a woman to consume more calories. They also did not respond correctly to GDM risk factors, such as being overweight or being of Indian, Asian or Middle Eastern descent.

Regarding the mean number of questions answered correctly by age and ethnicity (Table 3), there was a statistically significant difference between age and the mean number of questions answered correctly (P=0.03). Women over 35 years of age answered more questions accurately than women who were below 25 years (9 versus 6.3 questions). In a post-hoc analysis, women were examined in high-risk categories to determine if they knew that being in an older age group is a risk factor for GDM. Of women over 30, only 13.6% were able to correctly identify older age as a risk factor for diabetes. 

As expected, there was a statistically significant difference in the number of correct answers among those previously diagnosed with GDM as compared with those that had not been diagnosed or did not know (P=0.01). There were no significant differences in responses to questions on the survey among the different ethnicities (P=0.99).

Discussion
Similar to the findings of Carolan et al (2010), our data also suggest that educational strategies on GDM need to be encouraged and implemented, especially for young, fertile women of all ethnicities. In a post-hoc analysis, women were examined in high-risk categories to determine if they were able to correctly identify that being in an older age group is a risk factor for gestational diabetes. Our findings show that women aged 35 years old or older answered more questions correctly than the younger age groups, perhaps due to this group having previously received health information on GDM. Regarding ethnicity, among women of Asian descent, only 19.2% (5 of 26) identified ethnicity as a risk factor for GDM. 

Although the sample size of these groups was limited, these findings suggest the need for aggressive educational strategies in high-risk groups of young women. A strength of this study was the use of a validated questionnaire in a population of pregnant women who did not know GDM status at the time of the survey. In addition, this is one of the few studies conducted using a validated survey to assess pregnant women’s awareness of GDM in the US. Our results suggest that women need targeted education to better understand and reduce their risk of GDM.

Conclusions
The rise in diabetes has taken on international significance. GDM is a condition that can have adverse outcomes on women’s health and the health of their offspring. The results of our survey confirm results of previous studies (Metzger et al, 2007; Carolan et al, 2010) and support the recommendation that education on GDM is required for women, both prior to conception and during pregnancy.

One such model of education is the California Diabetes and Pregnancy Program (CDAPP). The benefits of CDAPP are two-fold:

  1. It  provides comprehensive technical support.
  2. It provides education to medical personnel and community workers in order to improve outcomes for high-risk pregnant women.

High-risk pregnant women include those with pre-existing diabetes and those who develop gestational diabetes. Based on the results of this study, we hope to develop an educational programme, which will include early counselling for high-risk pregnant women.

REFERENCES:

American Diabetes Association (2002) Gestational diabetes mellitus (Position Statement). Diabetes Care 27: S88–90
American Diabetes Association (2010) Diagnosis and classification of diabetes. Diabetes Care 33: S62–9
Bandyopadhyay M, Small R, Davey M et al (2011) Lived experience of gestational diabetes mellitus among immigrant South Asian women in Australia. Aust NZ J Obstet Gynoecol 51: 360–4
Carolan M, Steele C, Margetts H (2010) Attitudes towards gestational diabetes among a multiethnic cohort in Australia. J Clinical Nurs 19: 2446–53
Dabelea D, Snell-Bergeon JK, Hartsfield CL et al (2005) Increasing prevalence of gestational diabetes mellitus over time and by birth cohort. Diabetes Care 28: 579–84
Evans MK, O’Brien B (2005) Gestational diabetes: The meaning of an at-risk pregnancy. Qual Health Res 15: 66–81
Ferrara A (2007) Increasing prevalence of gestational diabetes mellitus. Diabetes Care 30: S141–46
Kendrick JM (2011). Screening and diagnosing gestational diabetes mellitus revisited. J Perinat Neonat Nursing 25: 226–32
Gabbe SG, Landon M, Warren-Boulton E, Fradkin J (2012) Promoting health after gestational diabetes. Obstet Gynecol 119: 171–6
Metzger BE, Buchanan TA, Coustan DR et al (2007) Summary and recommendations of the fifth international workshop-conference on gestational diabetes mellitus. Diabetes Care 30: S252–60
Ostlund I, Hanson U, BJ, Orklund A et al (2003) Maternal and fetal outcomes if gestational impaired glucose tolerance is not treated. Diabetes Care 26: 2107–11
Setji TL, Brown AJ, Feinglos MN (2005) Gestational diabetes mellitus. Clinical Diabetes 23: 17–24
Young BC, Ecker JL (2013) Fetal macrosomia and shoulder dystocia in women with gestational diabetes. Curr Diab Rep 13: 12–8

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