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Effect of a low-glycemic-index diet during pregnancy on obstetric outcomes^1,2,3

¹ From the Illawarra Area Health Service and Wollongong Hospital, Wollongong, NSW, Australia (RGM, ML, WSD, and KJC); Smart Food Center, University of Wollongong, Wollongong, NSW, Australia (LCT); the Department of Statistics, Macquarie University, Sydney, NSW, Australia (PP); and the Human Nutrition Unit, University of Sydney, NSW, Australia (JCB-M)

² Supported by internal revenue from the Illawarra Diabetes Service and the University of Sydney. Several items in the food hamper were provided by Sanitarium Health Foods, Cooranbong, NSW, Australia.

³ Reprints not available. Address correspondence to RG Moses, PO Box 1958, Wollongong West, NSW Australia 2500. E-mail: robert.moses{at}sesiahs.nsw.gov.au.

	ABSTRACT

TOP ABSTRACT INTRODUCTION SUBJECTS AND METHODS RESULTS DISCUSSION REFERENCES

 
Background: Pregnancy is a condition in which the glycemic index (GI) may be of particular relevance because maternal glucose is the main energy substrate for intrauterine growth.

Objective: The aim was to compare the effects of low-GI and conventional dietary strategies on pregnancy outcomes in healthy women. Compliance and acceptability were also investigated.

Design: The subjects were assigned alternately to receive dietary counseling that encouraged either low-GI (LGI) carbohydrate foods or high-fiber, moderate-to-high GI (HGI) foods and were studied 5 times between <16 wk gestation and delivery. Of the 70 women who met the inclusion criteria, 62 completed the study (32 in the LGI and 30 in the HGI groups). Primary outcomes were measures of fetal size.

Results: The mean diet GI fell significantly in the LGI group but not in the HGI group. Compared with the LGI group, women in the HGI group gave birth to infants who were heavier (3408 ± 78 compared with 3644 ± 90 g; P = 0.051) and had a higher birth centile (48 ± 5 compared with 69 ± 5; P = 0.005), a higher ponderal index (2.62 ± 0.04 compared with 2.74 ± 0.04; P = 0.03), and a higher prevalence of large-for-gestational age (3.1% compared with 33.3%; P = 0.01). Women in the LGI group found the diet easier to follow.

Conclusion: Because birth weight and ponderal index may predict chronic disease in later life, a low-GI diet may favorably influence long-term outcomes.

Key Words: Glycemic index • pregnancy • birth weight • ponderal index • insulin sensitivity

	INTRODUCTION

TOP ABSTRACT INTRODUCTION SUBJECTS AND METHODS RESULTS DISCUSSION REFERENCES

 
The clinical significance of the glycemic index (GI) of dietary carbohydrates has been a subject of debate since the concept was raised 25 y ago (1). The relation of the GI and, more recently, dietary glycemic load (GL) to the development and progression of chronic diseases, particularly those associated with insulin resistance, remains controversial (2, 3). Although there is no doubt that a low-GI food choice will ameliorate the postprandial glucose rise (4), the relevance of the postprandial glucose even in disorders such as diabetes is still debated (5). This is not unexpected given the number of confounding variables in both assessing dietary intake and relating this to the progression of chronic diseases and specific complications. In addition, the reliability of GI values extrapolated from foods tested in healthy volunteers in one country may be questionable in other countries and for persons with chronic diseases.

Pregnancy is a physiologic condition in which the GI concept may be of particular relevance because maternal glucose is the main energy substrate for intrauterine growth (6). For example, in pregnancies complicated by diabetes, high concentrations of glucose, particularly after a meal, give rise to an increased nutrient transfer to the fetus and adversely influence birth weight and pregnancy complications (6, 7).

To date, the validity of the GI concept in pregnancy has been assessed for only a small number of foods (8), and there is little knowledge about the effect of a low-GI diet on pregnancy outcomes. Two published studies in glucose-tolerant women have yielded conflicting results (9, 10). Moreover, to our knowledge, no studies have examined the tolerability and sustainability of a low-GI diet in pregnancy.

The primary aim of this study therefore was to compare the effects of 2 diets, one designated as low sugar and high fiber with a moderate-to-high GI (HGI) and one with a low GI (LGI), on pregnancy outcomes in healthy women. The secondary aims were to examine the compliance with and the acceptability of a low-GI diet in pregnancy.

	SUBJECTS AND METHODS

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The study was conducted in the city of Wollongong, NSW, Australia, a coastal city with a population of 280 000 people situated 50 miles south of Sydney. Healthy pregnant women were recruited from the antenatal clinic at Wollongong Hospital and from 2 obstetricians in private practice. They were considered for this parallel controlled study if they were aged 21–40 y, had a singleton pregnancy, were between 12 and 16 wk gestation, were nonsmokers, and had no more than 1 alcoholic drink each day. Exclusion criteria were individually assessed by one of us (RGM) and included any problem that may have been associated with glucose metabolism or insulin resistance or interfered with the ability of the study participant to follow dietary instructions.

Women who were not excluded were assigned alternately to 1 of the 2 diets. A research dietitian saw each woman individually 5 times during the pregnancy. At visit 1 (baseline), a 3-d food record and diet history were obtained, and height and weight were obtained. Weight was measured to the nearest 0.1 kg on floor scales (HD-316, Wedderburn Scales; Tanita Corporation, Tokyo, Japan) with subjects dressed in light clothes and without shoes. Height was measured to the nearest 0.1 cm against a wall with the use of a nonstretchable fiberglass measuring tape (Gulick II; Country Technology, Inc, Gays Mills, WI). At visit 2, 1 wk later, participants received detailed dietary education tailored for the assigned diet and their individual requirements for pregnancy. At visits 3 and 4 at 22 and 30 wk gestation, respectively, a 24-h diet recall was taken. At visit 5 at 36 wk gestation, a second 3-d food record and diet history were obtained.

A fasting venous sample was taken within 2 d of visit 1 for measurement of glucose and insulin, and this was repeated at 28 wk gestation in conjunction with routine glucose tolerance testing (GTT). Homeostasis modeling assessment (HOMA) was used to estimate insulin resistance by using original linear model (HOMA1-IR; fasting glucose x fasting insulin/22.5) (11) and the nonlinear computer model (HOMA2-IR) (12). The computer model also generated HOMA2-insulin sensitivity (HOMA2-%S) and HOMA2-ß cell function (HOMA2-%ß).

Diets
Both diets were compatible with the recommended nutritional intake in pregnancy (13), aiming for energy intake of 30% fat and 55% carbohydrate, with only the recommended choice of carbohydrate foods varying. No specific or individual recommendations were made about the intake of total energy, fiber, and fat. The HGI diet included advice to follow a diet with a high fiber and low sugar content. Potatoes, wheat-meal bread, and specific high-fiber breakfast cereals with moderate-to-high GI were recommended. The LGI diet was based on previously verified low-GI foods, including pasta and brand-name breads and breakfast cereals with a high fiber content. During visits, the dietitian referred to the diets as the "high-fiber, low-sugar" diet or the "low-GI" diet. Participants were provided with a booklet that outlined the carbohydrate choices and the food amounts that constituted one serving. To encourage compliance with both diets, key foods were provided in a monthly hamper. The dietitian also provided information on the whole diet to ensure energy and overall nutrient balance and was available for telephone queries outside of scheduled visits. Study personnel were not blinded to dietary assignment but were aware of the need for impartiality and equivalent treatment.

Food intake data for each participant was entered into a customized database that incorporated the Australian food-composition tables and published GI values by using the scale in which glucose equaled 100 (FOODWORKS PROFESSIONAL, version 4 2005; Xyris Software, Brisbane, Australia). When necessary, additional GI data were obtained from an online database (14). Overall dietary GI was calculated as the sum of the weighted GI of all carbohydrate foods in the diet, with the weighting proportional to the contribution of each food to total carbohydrate intake. Because the target diets aimed for similar carbohydrate content, GL (the product of the GI and the amount of carbohydrate) was influenced only by differences in GI. Any differences in obstetric outcomes could therefore be attributed to the nature of carbohydrate per se (ie, GI) rather than to simultaneous changes in both quantity and quality.

To evaluate the acceptability of the recommended diet changes in pregnancy, at their final visit subjects were asked to score 6 statements on a 5-point Likert scale (1 being "strongly agree" and 5 being "strongly disagree"). The statements were as follows: "It was easy to follow the diet recommended during this study," "I enjoyed the dietary changes that I made," "The changes recommended were affordable," "My family was accepting of the changes made to my eating habits," "The study diet helped me meet the physical challenges of pregnancy," "I enjoyed a wide variety of foods in my eating plan." In addition, women were also asked to indicate on a Likert scale how closely they followed the assigned diet (1 being "all of the time" and 5 being "none of the time").

Pregnancy care was the responsibility of the obstetric health care providers and was conducted in accord with standard practice. Because both diets were within the nutritional guidelines for pregnancy, the obstetric health care providers were not specifically informed of the diet assignments. Obstetric outcomes, including birth weight, length, head circumference, Apgar score, and method of delivery, were obtained from the medical record. For comparison between the 2 groups, the fetal centile was obtained from the Centile Calculator (15) with the use of data from a white British population. In this way the birth weight was adjusted for sex, gestational week of delivery, maternal age, parity, height, and prepregnancy weight by recall. The ponderal index (in g/cm³x 100) of the infant was calculated. The body mass index (BMI; in kg/m²) of the mother was calculated with the prepregnancy weight by recall. The Illawarra Area Health Service and University of Wollongong Human Research Committee approved the research, and participants gave written informed consent.

Statistical analysis
Independent samples t tests were used to compare groups at baseline and at the final time points. In addition, analysis of variance was used to compare groups at final visit with baseline values as covariates. Paired t tests were used to assess changes during the study period for the subjects as a whole and also within groups. Pearson's chi-square test of independence was used to compare method of delivery and prevalence of infants large for gestational age (LGA) and small for gestational age (SGA). Multivariate analysis of variance was used to compare selected maternal and fetal outcomes between groups. SPSS version 12.0 (SPSS Inc, Chicago, IL) was used for all statistical analyses. Unless otherwise stated results are expressed as means ± SEMs. Results were considered significant when P < 0.05.

	RESULTS

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Seventy-seven women were considered for the study, but 7 were not included because they had one of the following conditions: polycystic ovarian disease, Crohn disease, hyperthyroidism, celiac disease, lupus, previous gestational diabetes mellitus (GDM), and history of food allergy. A total of 70 women were enrolled with 35 assigned to each group. In the LGI diet group, 2 women withdrew because they were unwilling to follow the diet and 1 delivered before the final visit at 36 wk gestation. In the HGI diet group, 1 woman was unwilling to follow the diet, 1 was lost to follow-up, and 3 had miscarriages. Data analysis was based on the 32 women in the LGI diet group and 30 women in the HGI group who finished the study.

Women who were assigned to the HGI diet group had a slightly higher BMI (P = 0.04) and higher HOMA2-ß cell function (P = 0.07) than did women in the LGI diet group (Table 1). No other significant differences were observed in the baseline characteristics of the women. All women were white.

Table 2

The reported dietary intake assessed by a 3-d food record is shown in Table 3. At the baseline visit, no significant differences were observed between the 2 groups in energy, macronutrient intakes, or diet GI. At the final visit, both groups had increased their fiber intake (by 5 g/d), but only the LGI diet group had reduced diet GI (by 7 units; P < 0.001) and intake of saturated fat (P = 0.006). Women in the HGI diet group had significantly reduced their intake of polyunsaturated fat (by 17%; P = 0.008). No difference was observed in the contribution of carbohydrate to total energy in both groups (46%). The analysis of the diet histories produced similar findings (data not shown).

Responses in relation to diet acceptability are summarized in Table 4. No differences were observed in the ratings for both diets apart from the response to question 2. Women in the LGI diet group were more likely to agree that their recommended diet was easy to follow (P < 0.048).

	DISCUSSION

TOP ABSTRACT INTRODUCTION SUBJECTS AND METHODS RESULTS DISCUSSION REFERENCES

In nonpregnant, healthy subjects, mixed meals based on low-GI foods lead to a reduction in the postprandial glycemia (16, 17), and this is likely to be relevant in pregnancy. For pregnant women there is a continuum of risk of adverse pregnancy outcomes related to increasing maternal glucose concentrations after GTT (18). In the clinical context, women with GDM who have their management based on the 1-h rather than the 2-h postprandial glucose concentration have better obstetric outcomes (19). For pregnant women an association is recognized between the 1-h postprandial glucose concentration and fetal adiposity as estimated by the fetal abdominal circumference (20). The higher ponderal index found in the infants of women who consumed HGI carbohydrates may suggest an adverse influence of this kind of diet on fetal outcomes.

No significant differences were observed in obstetric outcomes between the 2 groups with respect to the method of delivery or the rate of GDM (only 1 case). GDM is the most common medical problem during pregnancy, and in the Wollongong area it has an incidence of 7.2% (21). Women who develop GDM were found to consume fewer low-GI carbohydrate foods than women who remain glucose tolerant (22). The current study was not powered to look at the effect of a LGI diet on the incidence of GDM. However, the favorable effects of a LGI diet on fetal outcomes could lead to speculation about reducing the incidence of GDM.

In 1998 Clapp (23) reported on a longitudinal study of 12 women who were recruited before pregnancy and followed through to delivery. The women agreed to follow a diet that provided 55–60% carbohydrate. Initially, this diet was composed of foods with a low GI but at 8 wk of gestation they were randomly assigned to either continue with the low-GI diet or to follow a high-GI diet for the duration of pregnancy. For women on a high-GI diet, the glucose responses to a standard meal progressively increased during pregnancy, whereas for women who consumed the low-GI diet the glucose responses did not change. Remarkably, the women who consumed the high-GI diet all had a infant that was LGA and with a mean weight of 1000 g more than the mean weight for women who consumed the low-GI diet. The number of women in this study was relatively small, and an exercise program was a confounding variable.

Scholl et al (10) took a different perspective. They proposed that eating foods with a low GI may lead to lower maternal glucose concentrations and less fuel for the fetus to develop a normal pattern of growth. Women who consumed a low-GI diet had a birth weight that was >100 g lower and also had twice the incidence of SGA infants. However, when dietary GL was considered, no association was observed with birth weight or the risk of a SGA infant. The strength of this study was that it involved >1000 women, but they were all from a particularly underprivileged area. Approximately 50% of the carbohydrate eaten came from refined sugars, and, because sweet drinks and confectionery often have a relatively low GI, it is possible that the lower birth weights for women with the lowest GI diet may have also been influenced by a poor-quality diet overall. In our study, the overall quality of both diets was good, with food and nutritional intakes in accordance with recommendations.

Secondary aims of the present study were to assess the tolerability and sustainability of a LGI diet. The 2 groups of women were well matched for initial macronutrient intake. The GI was similar at baseline and comparable to the median GI of American diets (57 on the glucose scale) (24). Mean dietary GI fell significantly in women in LGI diet group at visits 3, 4, and 5 (the final visit) compared with their baseline result and with the results of women in the HGI diet group. This finding indicated that the LGI diet was sustainable at least for the duration of the pregnancy. Because both diets were similar in carbohydrate content (46% energy or 250 g), only differences in the GI influenced dietary GL (the product of GI x amount of carbohydrate). Finally, although the diets were virtually equal in terms of subjective adherence, enjoyment, affordability, and family acceptability, women who consumed the LGI diet were more likely to report that their diet was easy to follow. This finding should be interpreted cautiously.

The strengths of this study include the study design, large sample size, high continuation rate, high compliance, and the detailed and repeated ascertainment of dietary measurements. Together these factors increase the reliability and sensitivity of the data. A particular strength was extensive knowledge of the GI of the individual Australian foods (25). Importantly, in previous studies we confirmed that sample menus representative of the 2 diets produced differential day-long glucose and insulin postprandial responses as predicted by their calculated GI (17). A further strength was that the subjects were free-living women who represent an important target for early intervention. A potential weakness of the study may have been the alternate assignment of women to one of the study groups.

The study had limitations. Although a similar macronutrient intake was targeted in both groups, subjects in the LGI group reduced their intake of saturated fat and the diet GI, whereas subjects in the HGI group reduced their intake of polyunsaturated fat. These differences may reflect inherent characteristics of the diets that might also operate outside the research setting. Lack of blinding of subjects and investigators to diet assignment can introduce a source of bias. Maternal weight gain and most measures of diet acceptance, however, were similar with both diets, which suggested no overt bias toward any one diet.

In summary, infants of women instructed to consume low-GI carbohydrate foods during pregnancy were of normal size but were smaller and had less body fat than did the women whose dietary GI did not change during pregnancy. Because birth weight and ponderal index predict long-term risk of obesity and chronic disease (26), a low-GI diet in pregnancy may favorably influence long-term outcomes. Adequately powered studies of healthy pregnant women are required to address the possibility that consumption of low-GI carbohydrates during pregnancy could reduce the risk of GDM.

	ACKNOWLEDGMENTS

 
RGM and JCB-M conceived and designed the study, analyzed and interpreted the findings, and contributed to the writing of the manuscript. LCT contributed to the design and conduct of the study, the interpretation of the findings, and the writing of the final manuscript. PP analyzed the findings and contributed to their interpretation. ML, WSD, and KJC conducted the study and contributed to the interpretation of the findings and the writing of the final manuscript.

JCB-M is a coauthor of The Low GI Diet (New York, NY: Marlowe and Co, 2005) and a coauthor of The New Glucose Revolution book series (New York, NY: Marlowe and Co; Sydney, Australia). None of the other authors had any potential conflict of interests relevant to the conduct of this research.

	REFERENCES

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This Article Abstract Full Text (PDF) Purchase Article View Shopping Cart Alert me when this article is cited Alert me if a correction is posted Citation Map Services Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Moses, R. G Articles by Brand-Miller, J. C Search for Related Content PubMed PubMed Citation Articles by Moses, R. G Articles by Brand-Miller, J. C Agricola Articles by Moses, R. G Articles by Brand-Miller, J. C