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Selective versus universal screening for gestational diabetes mellitus: an evaluation of predictive risk factors

Richard X Davey
Med J Aust 2001; 174 (3): 118-121.
Published online: 5 February 2001

Research

Selective versus universal screening for gestational diabetes mellitus: an evaluation of predictive risk factors

Richard X Davey and P Shane Hamblin

MJA 2001; 174: 118-121
For editorial comment, see Wilson

Abstract - Methods - Results - Discussion - Acknowledgements - References - Authors' details

- - More articles on Obstetrics & gynaecology and women's health


Abstract

Objective: To assess whether selective screening for gestational diabetes mellitus (GDM) on the basis of risk-factor assessment is a practicable alternative to universal screening.
Design: Case-control study.
Setting: A 212-bed regional specialist hospital in Melbourne, providing services in obstetrics and gynaecology, paediatrics, geriatrics and rehabilitation.
Subjects: 6032 women who gave birth at the hospital, May 1996 to August 1997 and November 1997 to August 1998; all were screened for GDM, and 313 were diagnosed with the condition.
Main outcome measures: Odds ratios (ORs) for risk factors (age, obesity, family history of diabetes mellitus and high-risk racial heritage) in women with GDM compared to those without GDM; proportion of women with GDM whose diagnosis would have been missed by selective screening.
Results: ORs were 1.9 for age ≥25 years (95% CI, 1.3-2.7), 2.3 for body mass index ≥27 kg/m2 (95% CI, 1.6-3.3), 2.5 for high-risk racial heritage (95% CI, 2.0-3.2), and 7.1 for family history of diabetes mellitus (95% CI, 5.6-8.9). Other proposed criteria (previous GDM and glycosuria) added no further diagnostic power. Selective screening using the above four criteria would have missed two of 313 cases (0.6%) and could have saved screening up to 1025 women without GDM (17% of all women).
Conclusions: Selective screening for GDM based on prior risk assessment can reduce the need for testing, with negligible loss of diagnostic efficiency.

Gestational diabetes mellitus (GDM) is officially described as carbohydrate intolerance with onset or first recognition during pregnancy.1 It is associated with increased incidence of maternal hypertension, pre-eclampsia and obstetric intervention; a third of women with GDM develop diabetes mellitus in later life. Babies of mothers with GDM may be either macrosomic or small-for-gestational-age, and may suffer birth trauma, hypoglycaemia and other metabolic disturbances. Potential effects later in the child's life are still debated. In Australia, at least 5% of pregnancies are affected by GDM. However, there is no sharply defined maternal blood glucose level beyond which morbidity invariably ensues in either mother or baby,2 and there is disagreement about how to diagnose GDM and how aggressively to treat it.3

In 1998, both the American Diabetes Association (ADA) and the WHO Consultation on diabetes published recommendations on diagnosis and classification of diabetes mellitus that included comments on GDM.4,5 The Australasian Diabetes in Pregnancy Society (ADIPS) has also published GDM guidelines.6

Both the ADA and ADIPS recommendations acknowledge that there are variable levels of risk for GDM and, consequently, that selective rather than universal screening can be considered. Selective screening both reduces costs and, for women deemed not to need screening, eliminates the minor physical inconvenience of the procedure and any anxiety raised by the possibility of suffering diabetes. Both ADA and ADIPS list risk factors for GDM (Box 1). The WHO Consultation's delineation of risk factors for GDM was less clear.5

We tested the hypothesis that selective screening for GDM is a practicable alternative to universal screening. We also investigated the effect of using the different age criteria of ADIPS and ADA as a basis for selective screening.


Methods

We undertook a case-control study to compare the likelihood of particular risk factors (defined in Box 2) among women with and without GDM. We also determined the proportion of women with GDM whose diagnosis would have been missed by selective screening, based on different sets of risk factors.

Study population

Sunshine Hospital is a 212-bed regional specialist hospital in Melbourne, Victoria, which provides service in obstetrics and gynaecology, paediatrics, geriatrics and rehabilitation. The study population comprised all 6032 women who gave birth at the hospital over the 26 months May 1996 to August 1997 and November 1997 to August 1998. Women who gave birth in September and October 1997 were excluded, as their laboratory data were incomplete.

All women were screened with a 50 g glucose challenge test, according to the ADIPS protocol.6 Those with an abnormal result (defined as plasma glucose level after one hour of ≥7.8 mmol/L) proceeded to a 2 h 75 g oral glucose tolerance test (OGTT); GDM was diagnosed if the fasting plasma glucose level was ≥5.5 mmol/L, or the 2 h level was ≥8.0 mmol/L.

Nearly all patients diagnosed with GDM were managed by an endocrinologist (P S H) in conjunction with one of the clinic obstetricians and were offered review and ongoing care from a dietitian and a diabetes nurse educator.

Data retrieval

Case group: We identified all post-delivery patient separations coded for GDM by computer search of the hospital medical information system, with cross-referencing to laboratory, dietitian and diabetes nurse educator records. Women who gave birth twice in the study period were included only once, using details from their first GDM-affected pregnancy. There were 313 women diagnosed with GDM.

Information on risk factors for these women was obtained from medical records containing details of pregnancy management and delivery, endocrinologist's and dietitian's notes and laboratory records (by R X D). If racial heritage was unclear, patients were telephoned at home to obtain more details. Body mass index (BMI) was available for only 290 of the 313 women (93%), but other data were available for over 99%.

Control group: For the 5719 women without GDM, information on age was also obtained from the hospital medical records. However, it was impracticable to investigate racial heritage as closely for this group as for the case group. Therefore, if country of birth was recorded as being in Europe, Asia or Central and South America, it was used for risk categorisation (45.5% of women). All other women were allocated to risk groups in the same proportions as found in the case group. While this biases the outcome in favour of the null hypothesis, it is more accurate than making no such allocation at all.

BMI and family history were not available for the 5719 women without GDM. Therefore, the BMI comparison used BMI data obtained from 303 consecutive non-diabetic women presenting for a glucose challenge test at about 28 weeks' gestation as part of a 1995 study at Sunshine Hospital.8 As the patient catchment area was unchanged between 1995 and 1998, this group should represent an unbiased sample of women who presented between 1995 and 1998.

For the family history comparison, a recent estimate of prevalence of diabetes mellitus in Australia9 was used for the non-GDM patients. Background risk was corrected for the bias caused by the tendency of patients with diabetes to visit their doctors twice as often as non-diabetic patients.10 It was also doubled to give a worst-case estimate, as each parent might pass on heritable risk independently.

Statistical analyses and ethics approval

Data were analysed using Stata statistical software.11 Odds ratios were calculated from the comparative prevalence in affected and control populations by Cornfield's method.

Ethics approval for this study was not required by the Victorian Health Services Act 1988 and was not sought. Data were permanently de-identified after analysis.


Results

Risk-factor comparison

Prevalence of risk factors among women with and without GDM is shown in Box 3, along with odds ratios. Women with GDM were almost twice as likely to be aged 25 years or over compared with those without GDM, more than twice as likely to have a BMI ≥27 kg/m2 or to have a high-risk racial heritage, and more than seven times as likely to have a family history of diabetes mellitus.

To determine the value of racial heritage as a predictor of GDM in isolation from family risk, we determined the OR for high-risk racial heritage among women with no family history of diabetes mellitus. This OR was not statistically different from the earlier OR for high-risk racial heritage that included women with a family history.

Furthermore, birth in Australia, New Zealand or North America (of non-Indigenous background) does not necessarily equate with low heritable GDM risk. Of the 313 women with GDM, 94 were born in these countries, but 19 of these had high-risk racial heritage.

Finally, we also assessed whether glycosuria in pregnancy or previous GDM had any extra value as predictors of GDM. All women with these risk factors qualified for screening on other grounds.

Effect of selective screening

The numbers of women with GDM who would be screened on the basis of risk factors, using different age thresholds, are shown in Box 4. Only the 290 women with complete data for all risk factors are included. However, all 23 women with incomplete risk-factor data would have undergone screening under these selective screening policies, as all had at least one risk factor (10 had two factors and five had three).

Selective screening on the basis of at least one risk factor, using the ADIPS age criterion (≥30 years), would have missed 12 women with GDM (95% CI, 6-19; 4%). Using the ADA age criterion (≥25 years), selective screening would have missed only two women with GDM (95% CI, 0-5; 0.6%). Furthermore, χ2 tests showed that the proportions of women with GDM who had risk factors other than age did not differ significantly between age groups (≥30 years, ≥25 years and all ages); all P values exceeded 0.67.

Among the women without GDM, 83% were aged 25 years or over and 48% were aged 30 years or over. A selective screening policy could therefore have saved testing up to 17%-52% of women without GDM, depending on the age threshold used and the presence of risk factors other than age.


Discussion

We found that selective screening for GDM using the four criteria common to the ADA and ADIPS lists of risk factors -- older age, obesity, family history of diabetes and high-risk racial heritage -- would have missed few women with GDM in our study population. It is clear that the age threshold for screening proposed by ADA (25 years) is diagnostically safer than the ADIPS threshold of 30 years, missing only 0.6% versus 4% of women with GDM.

However, our data also show that it is important to examine risk factors other than age even when the lower age threshold is used, as the other factors underlying susceptibility to GDM operate irrespective of age. Family history and heredity are immutable, and obesity may also be partly under genetic control. These observations are also consonant with the theory that pregnancy unmasks diabetes mellitus prematurely.12

We also found that previous GDM and glycosuria in pregnancy added nothing to the above four criteria for screening. However, this does not mean that GDM in a previous pregnancy should be ignored. It is often regarded as a criterion for a full OGTT, without a prior glucose challenge test, earlier than 28 weeks' gestation; the wisdom of this practice is not doubted.

Not only are the ADA criteria for screening diagnostically safer than the ADIPS criteria, they are also more precise in their definitions. Australian women would benefit if ADIPS recommendations were brought into line with ADA recommendations.

Our conclusions differ from those of Moses and colleagues, who found no benefit from selective screening in their study in the Illawarra region of New South Wales.13,14 Indeed, Moses has championed universal screening.15 However, the Illawarra protocol for GDM screening varied from contemporary practice, as it did not measure fasting glucose level or stringently control the time between the glucose load and blood sampling, making comparison difficult. Its outcomes have been questioned.16,17

In North America, a recent, albeit small, retrospective study of GDM screening in Michigan specifically assessed the ADA selective screening recommendations and concluded that they can be used as they miss "few" (4%) women with GDM.18

A larger study was reported by the Toronto Trihospital Investigators.19 They proposed a scheme that used among its criteria those later published by ADA to differentiate risk levels for GDM, sparing 35% of pregnant women the need for a glucose challenge test. This is at least twice as efficient as using the ADA criteria in our population, which potentially spared up to 17% of women a glucose challenge test (depending on the presence of risk factors other than age). However, an accompanying editorial concluded that the Trihospital criteria were "so hard to discern" that universal screening would continue as the only practicable alternative.20 For busy clinicians, simple systems are essential.

Our study differed from the Toronto study in that only women with positive results on a glucose challenge test proceeded to an OGTT, while, in Toronto, all women had a full OGTT. We will have missed the small number of women who would have had positive results on an OGTT despite their negative results on a challenge test -- perhaps 3%, based on the Toronto data. Short of performing a full OGTT on all pregnant women, which is impracticable, this group will always escape detection.

The Toronto ORs for risk factors among those with GDM generally accord with ours (1.6 for age ≥35 years [95% CI, 1.1-2.5], 3.2 for BMI ≥25.1 kg/m2 [95% CI, 2.1-4.8], 4.8 for Asian race [95% CI, 3.0-7.6]), but our results differ in two ways. Toronto race groupings, apart from "Asian", are difficult to interpret and, by using "white" and "black", ignore the extreme variation among "white" Europeans. Secondly, family history of diabetes mellitus in Toronto did not correlate significantly with higher risk of GDM, whereas our findings strongly support the inclusion of family history among criteria for a glucose challenge test.

Our study, along with the Michigan and Toronto studies, indicates that a selective approach to GDM screening in pregnancy is justifiable. Our simplified algorithm for selective screening is shown in Box 5. In practice, the proportion of women spared a glucose challenge test by selective screening will vary between populations. Consequently, whether selective screening is locally practicable will be a decision for individual groups of obstetricians, endocrinologists and pathologists with local knowledge. It is clear that consideration of a patient's age, rigorous questioning about racial and family history and accurate measurement of height and weight can reduce the need for screening among suitable populations. Selective screening can reduce costs and maternal anxiety, with negligible loss in diagnostic power.

Nevertheless, GDM poses still further challenges. Australia needs a better-directed, more organised, totally inclusive approach to follow-up of women who have had GDM. The third who will go on to develop diabetes mellitus need to be tracked, monitored, and managed prospectively into a healthier future.



Acknowledgements

We thank dietitians Candy d'Menzie-Bunshaw and Ruth Cuttler, specialist diabetes nurse consultant Elizabeth Borg, and health information manager Sianne Banks and her staff at Sunshine Hospital for their invaluable assistance with the study, and Lucy Inocencio for her excellent technical assistance.


References

  1. Metzger BE, editor. Summary and recommendations of the Third International Workshop-Conference on Gestational Diabetes Mellitus. Diabetes 1991; 40 Suppl 2: 197-201.
  2. Sacks DA, Greenspoon JS, Abu-Fadil S, et al. Towards universal criteria for gestational diabetes: The 75-gram glucose tolerance test in pregnancy. Am J Obstet Gynecol 1995; 172: 607-614.
  3. Jovanovic L. A tincture of time does not turn the tide [editorial]. Diabetes Care 2000; 23: 1219-1220.
  4. The Expert Committee on the Diagnosis and Classification of Diabetes Mellitus. Report of the expert committee on the diagnosis and classification of diabetes mellitus. Diabetes Care 1998; 21 (Suppl 1): S5-S19.
  5. Alberti KGMM, Zimmet PZ for the WHO Consultation. Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1. Diagnosis and classification of diabetes mellitus. Provisional report of a WHO consultation. Diabet Med 1998; 15: 539-553.
  6. Hoffman L, Nolan C, Wilson JD, et al, for the Australasian Diabetes in Pregnancy Society. Gestational diabetes mellitus -- management guidelines. Med J Aust 1998; 169: 93-97.
  7. Beischer NA, Oats JN, Henry OA, et al. Incidence and severity of gestational diabetes mellitus according to country of birth in women living in Australia. Diabetes 1991; 40: 35-38.
  8. Davey R. The glucose challenge test: different drink dilutions. Diabet Med 1996; 13: 917-918.
  9. Welborn TA, Reid CM, Marriott G. Australian Diabetes Screening Study: impaired glucose tolerance and non-insulin-dependent diabetes mellitus. Metabolism 1997; 46 (12 Suppl 1): 35-39.
  10. Australian Bureau of Statistics. National health survey: diabetes, Australia, 1995. Canberra: AGPS, 1997. (Catalogue No. 4371.0.)
  11. StataCorp. 1999. Stata Statistical Software: Release 6. College Station. TX: Stata Corporation.
  12. Yue DK, Molyneaux LM, Ross GP, et al. Why does ethnicity affect prevalence of gestational diabetes? The underwater volcano theory. Diabet Med 1996; 13: 748-752.
  13. Moses R, Griffiths R, Davis W. Gestational diabetes: do all women need to be tested? Aust N Z J Obstet Gynaecol 1995; 35: 387-389.
  14. Moses RG, Moses J, Davis WS. Gestational diabetes: do lean young Caucasian women need to be tested? Diabetes Care 1998; 21: 1803-1806.
  15. Moses RG. Diabetes in pregnancy [editorial]. Med J Aust 1998; 169: 68-69.
  16. Davey R. Of gestational diabetes, finesse, and an antipodean snark [letter]. Diabetes Care 1999; 22: 873-874.
  17. Moses RG, Moses J, Davis WS. Response to Davey [letter]. Diabetes Care 1999; 22: 874.
  18. Williams CB, Iqbal S, Zawacki CM, et al. Effect of selective screening for gestational diabetes. Diabetes Care 1999; 22: 418-421.
  19. Naylor CD, Sermer M, Chen E, Farine D. Selective screening for gestational diabetes mellitus. N Engl J Med 1997; 337: 1591-1596.
  20. Greene MF. Screening for gestational diabetes mellitus [editorial]. N Engl J Med 1997; 337: 1625-1626.

(Received 15 May, accepted 21 Sep, 2000)



Authors' details

Western Hospital, Melbourne, VIC.
Richard X Davey, FRCPA, FACB, Clinical Pathologist;
P Shane Hamblin, FRACP, Senior Endocrinologist.

Reprints will not be available from the authors.
Correspondence: Dr R X Davey, Western Hospital, Gordon Street, Footscray, VIC 3011.
richard.daveyATwh.org.au


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1: Risk factors for gestational diabetes mellitus, listed by different sources
Risk factor Australasian Diabetes
in Pregnancy Society6
American Diabetes
Association4

Age
Obesity
Family history of diabetes mellitus
Previous GDM
High risk "ethnic" group
Glycosuria
Previous adverse pregnancy outcome
Yes (>30 years)
Yes (not defined)
Yes
Yes
Yes (examples given)†
Yes
Yes
Yes (>25 years)
Yes (BMI >27kg/m2)
Yes (first-degree relative)
Not mentioned*
Yes (examples given)‡
Not mentioned
Not mentioned*

GDM=Gestational diabetes mellitus. BMI=Body mass index. *While the ADA did not consider previous GDM or adverse pregnancy outcome as sufficiently significant for women to be included in the high-risk GDM group, it did report them as criteria for diabetes testing in asymptomatic, undiagnosed individuals,4 thereby acknowledging them as markers of early, silent diabetes mellitus. †Including Australian Indigenous, Polynesian, Asian and Middle Eastern women. ‡Including Hispanic-American, Native American, Asian-American, African-American and Pacific Islander women.
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2: Definitions of risk factors used in this study

Age: Age was not further defined by ADA or ADIPS; we used age at estimated time of conception — the most conservative calculation.

Obesity: As defined by the ADA — body mass index ≥27kg/m2, determined from pre-pregnancy mass and height.

Family history of diabetes mellitus: As defined by the ADA — diabetes mellitus affecting a first-degree relative.

Racial susceptibility: Termed "ethnic" risk by ADA and ADIPS. We classified a woman as having high-risk racial heritage if she or her parents were born in one of the countries around the Mediterranean (including the Levant, but not the rest of Europe), the Indian subcontinent or Asia, or belonged to the Indigenous populations of Australia, the Pacific or the Americas.7


ADA = American Diabetes Association. ADIPS=Australasian Diabetes in Pregnancy Society.
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3: Prevalence and odds ratios of risk factors for gestational diabetes mellitus (GDM)
Prevalence
 
 
Risk factor Women with GDM
(n=313)
Women without GDM (variable n*) Odds ratio
(95% CI)

Age (years) >25 90.1% 82.9% 1.9 (1.3-2.7)
>30 58.5% 47.8% 1.5 (1.2-1.9)
Body mass index >27 kg/m2 36.2%† 19.8% 2.3 (1.6-3.3)
Family history of diabetes mellitus 39.9% 8.6% 7.1 (5.6-8.9)
High-risk racial heritage 68.7%‡ 46.4% 2.5 (2.0-3.2)
Among women with no family history 71.7%§ 42.8% 2.9 (2.1-4.0)

*Sample size varied between risk factors: 5719 (age), 303 (body mass index), 50371 (family history) and 5719 (racial heritage). †Data were available for 290 of the 313 women. ‡High-risk racial heritage: peri-Mediterranean (56 women), Indian subcontinent (20), Asia (124), South America (12), Indigenous populations (3); low risk racial heritage: United Kingdom (61), other European countries (35) and other (2). §n=187. ¶n=5324.
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4: Effect if selective screening were used among 290* women with gestational diabetes mellitus
  Number of women who would be screened (% of women with GDM)
 
Risk factors† ADIPS age threshold
(≥30 years)
ADA age threshold
(≥25 years)

Age ≥ threshold
  Only risk factor
  Plus any one other factor
  Plus any two other factors
  Plus any three other factors
  Total
13 (4%)
78 (27%)
54 (19%)
20 (7%)
165 (57%)
23 (8%)
120 (41%)
90 (31%)
27 (9%)
260 (90%)
Age ≤ threshold
  One risk factor
  Two risk factors
  Three risk factors
  Total
60 (21%)
42 (14%)
11 (4%)
113 (39%)
18 (6%)
6 (2%)
4 (1%)
28 (10%)
Any risk factor 278 (96%) 288 (99%)

*23 women with gestational diabetes mellitus but incomplete data on risk factors are not included. †Risk factors other than age were body mass index ≥27kg/m2, family history of diabetes mellitus and high-risk racial heritage.
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Box 5
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Received 17 November 2018, accepted 17 November 2018

  • Richard X Davey


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