Maija Salmenhaara
email: maija.salmenhaara@thl.fi

MSc Liisa Uusitalo

Dr Ulla Uusitalo

Dr Carina Kronberg- Kippilä

MSc Harri Sinkko

MSc Suvi Ahonen

MSc Riitta Veijola

Dr Mikael Knip

Prof Minna Kaila

Dr Suvi M Virtanen

Diet and weight gain characteristics of pregnant women with gestational diabetes

Keywords: gestational diabetes, diet, weight gain

Objectives: To determine if women with gestational diabetes (GD) modify their diet and nutrient intake in late pregnancy and gain more weight during pregnancy compared to women without GD.

Subjects and methods: Food and nutrient intake of 3 613 pregnant women was studied using food frequency questionnaires from the Type 1 Diabetes Prediction and Prevention Nutrition Study.

Results: GD was reported in 4.8% of the participating women (n=174). Women with GD gained less weight during pregnancy than those unaffected by GD (mean 9.4 kg vs. 12.6 kg, p<0.001). Women with GD consumed more milk products (84 vs. 76 g/MJ, p=0.002), cereal products (21 vs. 18 g/MJ, p<0.001), vegetables (32 vs. 22 g/MJ, p<0.001) and meat (16 vs. 14 g/MJ, p<0.001) than unaffected women. The intake of protein (18 vs. 16 E%, p<0.001) and dietary fibre (3.1 vs. 2.4 g/MJ, p<0.001) was higher, while the intake of sugars (13.3 g/MJ vs. 15.0 g/MJ, p<0.001) and saturated fatty acids (3.49 g/MJ vas. 3.98 g/MJ, p<0.001) was lower, among women with GD. The nutrient density of the diet was higher in women with GD with higher intakes of vitamin A and D, folate and iron.

Conclusions:

The late pregnancy diet of women with GD differed considerably from that of unaffected women. Women with GD had a higher body weight at the beginning of the pregnancy, but they gained less weight during pregnancy. These findings indicate that abnormal glucose tolerance during pregnancy encourages women to modify their dietary habits towards healthier food choices.

Introduction

Gestational diabetes (GD) represents the onset or first recognition of glucose intolerance during pregnancy [START_REF] Metzger | Summary and recommendations of the Fourth International Workshop-Conference on Gestational Diabetes Mellitus. The Organizing Committee[END_REF]. It has been associated with adverse foetal outcomes such as macrosomia and birth trauma [START_REF] Blank | Effects of gestational diabetes on perinatal morbidity reassessed. Report of the International Workshop on Adverse Perinatal Outcomes of Gestational Diabetes Mellitus[END_REF][START_REF] Crowther | Effect of treatment of gestational diabetes mellitus on pregnancy outcomes[END_REF].

Women with GD may face other pregnancy complications such as pre-eclampsia and have also increased risk of developing glucose intolerance in subsequent pregnancies [START_REF] Dornhorst | Risk and prevention of type 2 diabetes in women with gestational diabetes[END_REF][START_REF] Metzger | Summary and recommendations of the Fourth International Workshop-Conference on Gestational Diabetes Mellitus. The Organizing Committee[END_REF]. In addition, those with a history of GD are also at increased risk of developing type 2 diabetes. Although glucose tolerance is impaired in all women during pregnancy, only a small percentage go on to develop GD. In 2006, 8.4% of pregnant Finnish women were found to have an abnormal result in an oral glucose tolerance test (National Research and Development Centre for Welfare and Health, 2007). Worldwide, the estimates of GD prevalence vary widely, depending on the diagnostic criteria used.

Age, parity, smoking, increased body weight and body mass index (BMI), along with previous GD are factors known to increase the risk of GD in pregnant women [START_REF] Langer | Gestational diabetes: the consequences of not treating[END_REF][START_REF] Rudra | Weight characteristics and height in relation to risk of gestational diabetes mellitus[END_REF][START_REF] Solomon | A prospective study of pregravid determinants of gestational diabetes mellitus[END_REF][START_REF] Wang | Dietary variables and glucose tolerance in pregnancy[END_REF]. Generally GD is more common among overweight and obese women than among lean women (American [START_REF] College | ACOG Committee Opinion number 315[END_REF][START_REF] Chu | Maternal obesity and risk of gestational diabetes mellitus[END_REF][START_REF] Solomon | A prospective study of pregravid determinants of gestational diabetes mellitus[END_REF]. It has been indicated that women with GD gain less weight during pregnancy than those without GD [START_REF] Catalano | Weight gain in women with gestational diabetes[END_REF][START_REF] Couch | Maternal and cord plasma lipid and lipoprotein concentrations in women with and without gestational diabetes mellitus. Predictors of birth weight?[END_REF][START_REF] Teramo | Fetal macrosomia in women with gestational diabetes and healthy controls[END_REF]. This is a likely reflection of the effectiveness of lifestyle interventions available for women with GD at maternity welfare clinics when the condition is first detected.

The cornerstone of the management of GD is nutrition therapy [START_REF] Gunderson | Gestational diabetes and nutritional recommendations[END_REF][START_REF] Metzger | Summary and recommendations of the Fourth International Workshop-Conference on Gestational Diabetes Mellitus. The Organizing Committee[END_REF]. The goal of dietary intervention is to attain normoglycemia and to maintain a moderate weight gain (around 6-8 kg) through pregnancy [START_REF] Gunderson | Gestational diabetes and nutritional recommendations[END_REF][START_REF] Hasunen | Lapsi, perhe ja ruoka. Imeväis-ja leikki-ikäisten lasten, odottavien ja imettävien äitien ravitsemussuositus. (The Child, Family and Food. Nutrition recommendations for infants and young children as well as pregnant and breastfeeding mothers[END_REF]. However, those who fail to respond to the glycemic targets through diet receive insulin in conjunction with nutrition therapy. At Finnish maternity welfare clinics, women with GD are advised to follow a diet that favours vegetables, fruits, berries and whole grain cereal over high energy content food [START_REF] Hasunen | Lapsi, perhe ja ruoka. Imeväis-ja leikki-ikäisten lasten, odottavien ja imettävien äitien ravitsemussuositus. (The Child, Family and Food. Nutrition recommendations for infants and young children as well as pregnant and breastfeeding mothers[END_REF]. They are also recommended to increase their intake of fibre, and to moderate their consumption of fats, while ensuring an adequate intake of unsaturated fats. The intake of protein is recommended to not exceed 20-25%, total fat 30-40% and carbohydrates 40-50% of the total daily energy intake [START_REF] Virtanen | Diabeetikon ruokavaliosuositus 2008. (Nutritional recommendations for subjects with diabetes[END_REF]. Furthermore, women with GD are advised to increase their level of physical activity (American Diabetes [START_REF] Diabetes | Gestational diabetes mellitus[END_REF][START_REF] Hasunen | Lapsi, perhe ja ruoka. Imeväis-ja leikki-ikäisten lasten, odottavien ja imettävien äitien ravitsemussuositus. (The Child, Family and Food. Nutrition recommendations for infants and young children as well as pregnant and breastfeeding mothers[END_REF].

Pregnancy is an ideal time for behavioral and lifestyle modifications pertaining to diet and physical exercise [START_REF] Artal | A lifestyle intervention of weight-gain restriction: diet and exercise in obese women with gestational diabetes mellitus[END_REF]. Although pregnant women with GD are generally advised to improve the quality of their diet, it is not well known whether women adhere to the given instructions. In the present study, we firstly wanted to determine if women with GD modify their diet and nutrient intake in late pregnancy compared to women without GD.

Secondly, we wanted to determine if women with GD gain more weight during pregnancy compared to women without GD.

Materials and methods

Subjects of the present study are participating in the ongoing Type 1 Diabetes Prediction and Prevention (DIPP) study, a large population-based birth cohort study in Finland which started in 1994 [START_REF] Kupila | Feasibility of genetic and immunological prediction of type I diabetes in a population-based birth cohort[END_REF]. The study was established to predict the development of type 1 diabetes and to search for means to prevent or delay progression of increased genetic susceptibility to clinical type 1 diabetes. Infants who carry increased genetic risk represent about 15% of the total population. Infants for the DIPP study were screened for HLA-DQB1conferred susceptibility to type 1 diabetes using samples of cord blood, and those with a high risk were invited to participate in the DIPP study in the area of their local university hospital 1). Baseline dietary data was available from 3 783 women, of which 51 were rejected because of incomplete dietary data (for example more than 10 missing food items in the food frequency questionnaire, FFQ). A total of 3 732 women with dietary data were available for this study (70% of the women eligible to the DIPP Study). The research questions were studied between women with and without GD. We excluded those with type 1 or type 2 diabetes from the comparison group. The total study population was thereafter 3 613. For our analyses on maternal weight and weight gain, we needed to exclude further subjects based on the following criteria: women with twin and triple pregnancies, those with missing information on the number of foetuses and women with incomplete weight gain information. After this exclusion, data on 3 260 were available for weight gain analysis.

The food frequency questionnaire

Maternal diet during pregnancy was assessed retrospectively by a self-administered, semiquantitative FFQ, which has been validated specifically for the present study population [START_REF] Erkkola | Validity and reproducibility of a food frequency questionnaire for pregnant Finnish women[END_REF]. This 181-item questionnaire assesses the mother's usual dietary intake over the last month before maternity leave, usually the 8 th month of the pregnancy in Finland.

The mothers filled in the questionnaire 1-3 months after the delivery and returned it at their first visit to the study center where a trained study nurse checked the FFQ and if required, completed it in consultation with the mother. All returned FFQs were also double-checked by a trained nutritionist. The FFQ contained questions about the frequency (number of times per day, week or month) and the amount of foods consumed, in units of common serving sizes.

The food consumption data was entered into a dietary database and the Finnish Food Composition Database Fineli ® (National Institute for Health and Welfare Nutrition Unit, 2009) was used to calculate daily food and nutrient intakes. Besides food consumption data, the FFQ also enquired about the use of dietary supplements (i.e. brand name and manufacturer, dosage and gestational weeks when used). Supplement intake was divided by the length of the pregnancy (days) and represents the whole time period of the pregnancy.

Information on GD, pregnancy and background characteristics

In Finland, free-of-charge health care is offered to all pregnant women in maternity welfare clinics and in practice all pregnant women attend the service. During the present study an oral glucose tolerance test was performed usually at 26-28 week of gestation for those women who fulfilled one or more of the following criteria: glucosuria after fasting, overweight (BMI>25 kg/m 2 ), age >40 years, earlier delivery of a baby with birth weight >4 500 g or macrosomic foetus [START_REF] Berger | Screening for gestational diabetes mellitus[END_REF]. GD is diagnosed when at least one of the values is pathological in a 75 g (2 hrs) oral glucose tolerance test (American Diabetes [START_REF] Diabetes | Gestational diabetes mellitus[END_REF]. The FFQ required the women to indicate if they followed any special diets during pregnancy by selecting one of the following alternatives: no special diets, food allergy or hypersensitivity, lactose intolerance, type 1 diabetes, type 2 diabetes, gestational diabetes, coeliac disease, vegetarian diet or other special diets. This reported information of the GD is the main outcome of the study.

The maternal weight and height information at the beginning of the pregnancy, as well as the weight gain during pregnancy, was obtained from the follow-up card kept at the maternity welfare clinic. In Finnish healthcare system, the first antenatal visit is usually between 8 th and 12 th gestational week. The rate of weight gain (kg/week) was calculated as the difference in body weight between the last and the first antenatal visit divided by the number of gestational weeks at the time of the weight measurement. BMI was calculated based on the weight and height information. The women's age and education details were registered by a structured questionnaire completed after the delivery. Professional education was merged into three groups from the seven education groups available in the questionnaire. Information about parity, place of residence and smoking habits during pregnancy was derived from the Medical Birth Registries of the Oulu and Tampere University Hospitals. The same registries contained information on the municipality code, from which the degree of urbanization (urban, population centre, rural) was derived.

Statistical analysis

Stepwise logistic regression using forward elimination was used to analyse the association between background factors and GD. The energy densities (g/MJ) of foods and nutrients were calculated to eliminate the effects of differences in total energy intake. Foods and nutrients that were not normally distributed were transformed into logarithmic scale for statistical analyses. The associations between GD and food and nutrient intake were studied using linear regression analyses and were adjusted for maternal age, place of residence, degree of urbanization, vocational education, BMI and parity. T-test was used to investigate the difference in weight gain through pregnancy and the child's birth weight between women with and without GD. The proportions of vitamin and mineral supplement users between the two groups were tested using χ 2 -test. In addition, the differences of the mean supplement intakes between women with and without GD were tested using non-parametric Mann-Whitney test. A p-value of <0.05 was considered statistically significant. SPSS 15.0 for Windows (SPSS Inc., Chicago, IL, USA) was used to analyse the data.

Results

In the present study GD was reported in 174 (4.8%) of the participating women (total n=3 613). GD was more common among women in the two oldest age categories (30-34 years and ≥35 years). Furthermore, women with GD had higher BMI at the first visit (mean 28.1 kg/m 2 ) than women without GD (mean 24.1 kg/m 2 ). The risk of GD was higher among women living in northern Finland (Oulu University Hospital district) and those who had an upper secondary vocational education. (Table 1) Women affected by GD gained less weight (p<0.001) (mean 9.4 kg, SD 5.1) than the unaffected women (mean 12.6 kg, SD 4.5). The mean rate of weight gain was 0.34 kg/wk in women with GD and 0.43 kg/wk in women without GD (p<0.001) (Figure 2). Infant birth weights differed between the two groups of women (mean 3 650 g in women with GD vs. 3 560 g in unaffected women; p=0.036).

The diet of the women with GD differed from the diet of the women without GD. The former consumed more milk and cereal products than the latter. Those with GD consumed less fruits and berries but more vegetables. Meat was consumed more frequently by the women with GD than by the unaffected women. Women with GD consumed less chocolate and sweets than those unaffected. (Table 2) The dietary intake of most nutrients differed statistically between the women with GD and those without. However, for many nutrients the difference was too small to be of practical importance. If the difference was <10%, we concluded that the difference is not of clinical importance and did not analyse the results further. The intake of sugars was lower while the intake of starch and dietary fibre was higher among women with GD. Their intake of protein was higher than that of the unaffected women. Intake of saturated fatty acids was lower in women with GD. Their intake of vitamins A and D, folate and iron was higher than that of the unaffected women. The intake of iron was also higher in subjects with GD. (Table 3) Most of the women (77.2%) complemented their diet with dietary supplements during pregnancy. No difference was found in nutrition intake from supplements between the two groups of women. Subjects with GD took iron supplements less frequently than other subjects. (Table 4)

Discussion

The present study was undertaken to explore differences in food and nutrient intakes between pregnant women with GD and those unaffected. Our study revealed that the diet in late pregnancy among women with GD differed considerably from the diet of those without GD.

Women with GD consumed more milk and cereal products, vegetables and meat than those unaffected, and consequently their intake of protein, starch and dietary fibre, and that of vitamin A and D, folate and iron, was higher. In addition, women with GD had a lower intake of sugars and saturated fatty acids. Women affected by GD also gained less weight than the unaffected women. Our findings indicate that when abnormal glucose tolerance is first detected, women tend to modify their dietary habits towards healthier food choices. Since the first line of treatment of GD is through nutrition therapy in maternity welfare clinics, our findings indicate that the dietary advice women receive is in fact effective.

The main strength of the current study was the large sample size of a population-based cohort.

In addition, since virtually all deliveries in Finland take place in public hospitals, our study population is likely to be a close representation of the overall population of pregnant women in the areas of the university hospitals of the study. A further strength is our use of an FFQ which was specifically validated for the purpose of this study population [START_REF] Erkkola | Validity and reproducibility of a food frequency questionnaire for pregnant Finnish women[END_REF]. However, the study involves some limitations, of which most are related to the retrospective study design and its potential for recall bias. Firstly, since the participants needed to recall their food use retrospectively, the influence of their current diet is a possible source of error [START_REF] Bunin | Recall of diet during a past pregnancy[END_REF]. On the other hand, it could also be argued that women may recall their dietary habits during pregnancy particularly well because of this unique period in their lives. Secondly, as the women without GD mostly had a relatively uncomplicated pregnancy, while those with GD received dietary guidance, it is possible that the latter may have over-reported their consumption of healthy foods. Thirdly, since we used an FFQ to study the maternal intake during pregnancy, there is a possibility that the food consumption and nutrient intake data are overestimates, especially that of vegetables, and energy and energy-yielding nutrients [START_REF] Erkkola | Validity and reproducibility of a food frequency questionnaire for pregnant Finnish women[END_REF][START_REF] Nelson | Assessment of food consumption and nutrient intake[END_REF]. Then again, some studies have reported that the energy intake among certain groups of women, such as those who are overweight, weight-conscious or pregnant, is often too low to meet the physiological energy requirements [START_REF] Hill | The validity of self-reported energy intake as determined using the doubly labelled water technique[END_REF][START_REF] Trabulsi | Evaluation of dietary assessment instruments against doubly labeled water, a biomarker of habitual energy intake[END_REF].

Hence, the reduced energy intake among the women with GD in our study may in fact to certain extent be down to the tendency of under-reporting by obese women [START_REF] Hill | The validity of self-reported energy intake as determined using the doubly labelled water technique[END_REF]. We therefore took steps to minimize the effects of over and underreporting in the present study, and thus estimated the energy densities of food and nutrient intakes in the analyses. Finally, as the GD status in our study was reported by the responding mothers, we could not confirm the status independently.

Our data showed that women with GD had a lower intake of sugars and saturated fatty acids whilst having a higher intake of protein, starch and dietary fibre, as compared with the unaffected women. A recent study among British women with GD, who also received dietary advice, observed similar differences in the intakes of saturated fats, added sugar, complex carbohydrates and dietary fibre [START_REF] Thomas | Nutrient intake of women with and without gestational diabetes with a specific focus on fatty acids[END_REF]. In our study, the women with GD had a total fat intake of 32% of the total energy intake, while the unaffected women had a slightly higher intake of fat at 34%. The mean intake of protein among women with GD was 18% of the total daily energy intake and hence fell below the recommended level of 20-25% [START_REF] Virtanen | Diabeetikon ruokavaliosuositus 2008. (Nutritional recommendations for subjects with diabetes[END_REF]. In women without GD the intake of protein was even lower at 16% of the total energy intake. However, the proportion of carbohydrates of the total energy intake was similar in both groups at 49% of the total daily energy intake.

In line with many previous studies, we observed that the women with GD were generally older and had a higher BMI at the beginning of the pregnancy than women without GD [START_REF] Hackmon | The impact of maternal age, body mass index and maternal weight gain on the glucose challenge test in pregnancy[END_REF][START_REF] Radesky | Diet during early pregnancy and development of gestational diabetes[END_REF][START_REF] Rudra | Weight characteristics and height in relation to risk of gestational diabetes mellitus[END_REF][START_REF] Solomon | A prospective study of pregravid determinants of gestational diabetes mellitus[END_REF][START_REF] Wang | Dietary variables and glucose tolerance in pregnancy[END_REF]. In our study, those with GD also had a higher body weight at the beginning of the pregnancy than those not affected, but they gained less weight during the course of the pregnancy. Similar observations have been made previously in a case-control study, which evaluated weight gain during pregnancy in women with GD and those without [START_REF] Catalano | Weight gain in women with gestational diabetes[END_REF]. However, although the study indicated that the weight gain in women with GD was less than in controls, the effect was considered to be attributed to their greater pregravid weight. In contrast to previous studies, parity and cigarette smoking were not associated with GD in the present study [START_REF] England | Glucose tolerance and risk of gestational diabetes mellitus in nulliparous women who smoke during pregnancy[END_REF][START_REF] Solomon | A prospective study of pregravid determinants of gestational diabetes mellitus[END_REF].

Overall the use of dietary supplements was quite common in our study population; 77% of all women took at least one dietary supplement. Our results are similar to an earlier study among pregnant Finnish women in which 70% of women were reported to take dietary supplements [START_REF] Erkkola | Folate, vitamin D, and iron intakes are low among pregnant Finnish women[END_REF]. However, in the present study population women with GD took iron supplementation less frequently than the unaffected women. The high consumption of meat and cereal products, both good sources of iron, among women with GD is a likely explanation to this finding.

In conclusion, our findings indicate that women diagnosed with GD are capable of modifying their dietary habits when given nutrition guidance at the maternity welfare clinics. This observation is of great importance from the perspective of type 2 diabetes prevention. Thus by means of dietary advise, regular exercise, stabilizing weight and monitoring blood glucose levels, it is possible to delay or prevent the progression of GD to type 2 diabetes and its further complications in women with a history of GD. Since the maternal nutritional status before pregnancy, as reflected by pre-pregnancy BMI, is known to be more important than the diet during pregnancy in the development of GD, efforts to reduce rates of GD should continue to focus on reducing the prevalence of obesity among women in fertile age. Furthermore, any efforts to promote physical activity and healthy eating habits among women at this age should be strengthened.

Tables

Table 1 Characteristics of women with and without gestational diabetes (GD) in the DIPP nutrition study, with child born in 20.10.1997-31.12.2002

(

  Oulu, Tampere and Turku University Hospitals). The study is approved by the local Ethical Committees. All participating families have given their informed, written consent. The DIPP Nutrition Study falls within the framework of the larger DIPP Study. The DIPP Nutrition Study aims at investigating maternal nutrition during pregnancy and lactation, and child's nutrition, in relation to the natural progression from increased genetic susceptibility to the development of β-cell autoimmunity and clinical manifestation of type 1 diabetes, allergic diseases and asthma. The subjects of the present study are women whose child was born between October 20, 1997 and December 31, 2002 in Oulu and Tampere University Hospitals (n=5 339) (Figure

  in Tampere and Oulu University Hospital districts. Logistic regression stepwise analysis for developing GD. All estimates are simultaneously adjusted for all other characteristics in the table.

		Women with GD	Women without GD
			(n=174)	(n=3 439)
		n	%	n	%	OR a (95% CI)
	Age (years) b
	<25	18	10.3	678	19.7	1
	25-29	48	27.6	1 185	34.5	1.53 (0.83-2.82)
	30-34	56	32.2	1 017	29.6	2.02 (1.11-3.68)
	≥35	52	29.9	559	16.3	3.20 (1.73-5.93)
	Place of residence
	District of Tampere	68	39.1	2 062	60.0	1
	District of Oulu	106	60.9	1 377	40.0	2.33 (1.66-3.26)
	Degree of urbanization
	Urban	117	67.2	2 642	76.8	NS
	Population centre	20	11.5	332	9.7
	Rural	35	20.1	438	12.7
	Missing data	2	1.1	27	0.8
	BMI at the first antenatal
	visit (kg/m 2 )
	1. quarter (<21.4)	12	6.9	847	24.6	1
	2. quarter (21.4-23.4)	22	12.6	839	24.4	1.60 (0.76-3.41)
	3. quarter (23.4-26.1)	35	20.1	826	24.0	2.77 (1.38-5.54)
	4. quarter (>26.1)	100	57.5	760	22.1	8.58 (4.51-16.31)
	Missing data	5	2.9	167	4.9
	Smoking during
	pregnancy
	No	153	87.9	2 962	86.1	NS
	Yes	15	8.6	359	10.4
	Missing data	6	3.4	118	3.4
	Professional education
	Academic	28	16.1	748	21.8	1
	Upper secondary
	vocational education	92	52.9	1 377	40.0	1.65 (1.03-2.65)
	None or vocational
	school or course	49	28.2	1 221	35.5	1.01 (0.60-1.70)
	Missing data	5	2.9	93	2.7
	Parity
	0	55	31.6	1 581	46.0	NS
	1	56	32.2	1 081	31.4
	2	25	14.4	476	13.8
	≥3	36	20.7	277	8.1
	Missing data	2	1.1	24	0.7

Abbreviations: BMI, body mass index; OR, odds ratio; CI, confidence intervals; NS, not significant 18 a b At the time of the delivery.

Table 2

 2 Consumption of foods (g/MJ) in women with gestational diabetes (GD) and unaffected women.

		Women with GD	Women without GD
		(n=174)	(n=3 439)
		mean	SD	mean	SD	p-value a
	Milk products (g/MJ)	84.3	33.5	75.5	31.6	0.002
	Cereal products (g/MJ)	20.7	5.2	17.9	4.4	<0.001
	Fruits and berries (g/MJ)	44.3	24.5	52.8	28.3	0.004
	Vegetables (g/MJ)	32.3	18.8	21.5	11.6	<0.001
	Meat (g/MJ)	16.3	5.1	14.2	5.0	<0.001
	Fish (g/MJ)	2.6	2.0	2.2	1.7	0.062
	Dietary fats (g/MJ)	4.0	1.4	4.0	1.4	0.344
	Chocolate and sweets (g/MJ)	1.1	1.4	2.6	2.2	<0.001
	Abbreviations: SD, standard deviation

a Linear regression analyses adjusted for maternal age, place of residence, degree of urbanization, vocational education, BMI and parity.

Table 3

 3 Intake of energy and nutrients from foods adjusted for energy (per MJ) in women with gestational diabetes (GD) and unaffected women.

		Women with GD	Women without
		(n=174)	GD (n=3 439)
		mean	SD	mean	SD	p-value a
	Energy (MJ)	10.8	2.9	11.5	3.4
	(kcal)	2579	699	2759	814	0.009
	Protein (E%)	18		16		<0.001
	Carbohydrates (E%)	49		49		0.712
	Starch (g/MJ)	15.0	3.0	13.2	2.5	<0.001
	Sugars (g/MJ)	13.3	3.3	15.0	3.4	<0.001
	Dietary fibre (g/MJ)	3.08	0.91	2.40	0.66	<0.001
	Total fat (E%)	32		34		<0.001
	Saturated fatty acids (g/MJ)	3.49	0.77	3.98	0.76	<0.001
	Trans fatty acids (g/MJ)	0.13	0.04	0.14	0.04	0.003
	Monounsaturated fatty acids (g/MJ)	3.06	0.53	3.23	0.54	0.001
	Polyunsaturated fatty acids (g/MJ)	1.31	0.32	1.26	0.29	0.016
	N-3 fatty acids (g/MJ)	0.29	0.08	0.28	0.08	0.408
	N-6 fatty acids (g/MJ)	1.00	0.27	0.95	0.23	0.007
	Vitamin A (μg/MJ)	189	110	141	72	<0.001
	Vitamin D (μg/MJ)	0.50	0.21	0.43	0.19	<0.001
	Vitamin E (mg/MJ)	1.38	0.31	1.25	0.25	<0.001
	Folate (μg/MJ)	37.4	8.37	32.1	6.40	<0.001
	Vitamin C (mg/MJ)	17.5	8.3	17.3	8.7	0.134
	Calcium (mg/MJ)	174	41.7	161	41.9	<0.001
	Iron (mg/MJ)	1.67	0.32	1.44	0.27	<0.001
	Abbreviations: SD, standard deviation

a Linear regression analyses adjusted for maternal age, place of residence, degree of urbanization, vocational education, BMI and parity.

Acknowledgements

This project was supported by the Academy of Finland (grants 63672, 79685, 79686, 80846, 201988, 210632), the Finnish Pediatric Research Foundation, the Juho Vainio Foundation, the Yrjö Jahnsson Foundation, the European Foundation for the Study of Diabetes, Medical Research Funds, Turku, Oulu and Tampere University Hospitals, JDRF (grants 197032, 4-1998-274, 4-1999-731, 4-2001-435), Novo Nordisk Foundation and EU Biomed 2 Program (BMH4-CT98-3314). We express our gratitude to the children and parents who participated and we want to thank the DIPP research nurses, doctors, nutritionists and laboratory staff for excellent collaboration. We are grateful to Marianne Prasad for language editing.

Conflict of interest

There are no conflicts of interest.

Table 4 Proportion of vitamin and mineral supplement users and nutrient intake from supplements in women with gestational diabetes (GD) and unaffected women.


Stefan Storcksdieck
email: stefan.storcksdieck@eufic.org

Genannt Bonsmann

Laura Fernández Celemín

Ainhoa Larrañaga

Salome Egger

Josephine M Wills

Charo Hodgkins

Monique M Raats

Dr Stefan Storcksdieck Genannt Bonsmann

Penetration of nutrition information on food labels across the EU-27 plus Turkey

Keywords: Labelling, Nutrition information, Food products, Consumers Nutrition labelling penetration in Europe

à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

INTRODUCTION

In light of the growing prevalence of diet-related diseases, governments, retailers and food companies promote nutrition labelling to help the consumer make healthy, informed food choices. Additionally, the World Health Organization includes nutrition labelling as part of its Global Strategy on Diet, Physical Activity and Health (World Health Organization 2004).

Nutrition labelling aims at highlighting essential information about the nutritional value and composition of products. Currently, such information is not compulsory in the European Union (EU) unless a nutrition or health claim is made [START_REF] Ec | Council Directive 90/496/EEC of 24 September 1990 on nutrition labelling for foodstuffs[END_REF][START_REF] Ec | Regulation (EC) No 1924/2006 of the European Parliament and of the Council of 20 December 2006 on nutrition and health claims made on foods[END_REF].

According to a recent review [START_REF] Grunert | A review of European research on consumer response to nutrition information on food labels[END_REF], consumers showed widespread interest in nutrition information on food packages, though this interest varied across situations and products. Most consumers reported good subjective understanding of the most common signposting formats, which is supported by findings showing reasonable objective understanding [START_REF] Grunert | Use and understanding of nutrition information on food labels in six European countries[END_REF][START_REF] Malam | Comprehension and use of UK nutrition signpost labelling schemes[END_REF]. On the other hand, virtually no insight exists as to how labelling information is, or will be, used in a real-world shopping situation, and how it affects consumers' dietary patterns (Cowburn andStockley 2005, Grunert and[START_REF] Grunert | A review of European research on consumer response to nutrition information on food labels[END_REF].

Food Labelling to Advance Better Education for Life (FLABEL) is an EU-funded project which has been set up to elucidate whether the use of nutrition labelling on food products impacts on consumers' dietary choices and shopping habits. Fundamental to this objective is the assessment of current exposure of consumers to nutrition information on food labels. At present, data on the penetration of nutrition information on food labels in Europe are scarce, with previous studies reporting an average prevalence of tabular nutrition information of 56% (European Advisory Services 2004). However, that audit involved only a subset of countries, considered only tabular nutrition information, and did not look at all products within a product category. On the other hand, two surveys from the U.S., where nutrition labelling became mandatory in 1994, reported virtually complete labelling of pre-packaged foods from a broad range of product categories [START_REF] Brecher | Status of nutrition labeling, health claims, and nutrient content claims for processed foods: 1997 Food Label and Package Survey[END_REF][START_REF] Legault | 2000-2001 food label and package survey: an update on prevalence of nutrition labeling and claims on processed, packaged foods[END_REF].

To our knowledge, the results presented in this paper constitute the first EU-wide study to give a real-life insight into current exposure of consumers to nutrition information on food labels.

MATERIALS AND METHODS

Auditing period, setting and product categories

The audit period lasted from September 2008 to April 2009 and data collection was carried out in all 27 EU Member States and Turkey. In each country, three types of food retail stores were selected with an emphasis on broad coverage of different product manufacturers: a food retailer from the top five in terms of market share, a consumer cooperative (or national retailer if a consumer cooperative was not available), and a discounter (hard discounter if possible).

All products within the following five categories were examined: sweet biscuits, breakfast cereals, pre-packed chilled ready meals, carbonated soft drinks and yoghurts. The criteria for choosing these product categories were that they were pre-packaged foods, both foods and beverages, both meal and snack items, and foods consumed at different times and in different contexts. The five different food categories were defined as follows:

1) Sweet biscuits -main ingredients flour, sugar, fat; including chocolate-coated, with jam, in bags, packs, etc.

2) Breakfast cereals -cereals to be eaten at breakfast time (with milk), excluding cereal bars.

3) Pre-packed chilled ready meals -fresh ready meals stored at 2-8°C, ideally containing a carbohydrate source (rice, pasta, potatoes), a protein source (meat, poultry, fish) and vegetables. This includes vegetarian varieties, and dishes that constitute a meal (even if not containing the 3 elements above). 4) Carbonated soft drinks -non-alcoholic fizzy drinks that people drink as refreshment, in cans or bottles. 5) Yoghurts -fermented milk products containing the word "yoghurt" on the pack, natural or fruit-flavoured, single pack or multi-pack, also drinkable yoghurt.

Data collection process

Two data collection grids were developed for use in the stores, a product and a nutrition information grid. The product grid was used to record the product name, brand name, manufacturer, pack size, and if applicable, variety. The nutrition information grid was used to record the nutrition information found on each food package, such as the type of labelling scheme (e.g. traffic lights, guideline daily amounts (GDA), health logo, nutrition table), the format of the schemes (i.e. horizontal, vertical, tabular), the presence of nutrition information (e.g. "Big 4" (i.e. energy, carbohydrates, protein, fat) or "Big 8" (i.e. "Big 4" plus sugar, saturated fat, fibre, sodium)), or the presence of nutrition or health claims as defined by current European law [START_REF] Ec | Council Directive 90/496/EEC of 24 September 1990 on nutrition labelling for foodstuffs[END_REF][START_REF] Ec | Regulation (EC) No 1924/2006 of the European Parliament and of the Council of 20 December 2006 on nutrition and health claims made on foods[END_REF].

In this study, logos on food packages were considered as "health logos" if their use was restricted to food products that fulfilled certain nutrient criteria (which may vary from logo to logo and may consider dietary guidelines) and as such represented a healthier option in that category.

Information was considered as front-of-pack (FOP) if it was displayed in the principal field of vision [START_REF] Ec | Proposal for a Regulation of the European Parliament and of the Council of 30 January 2008 on the provision of food information to consumers[END_REF], which in turn was guided by the placement of product name and brand. The remaining area was defined as back-of-pack (BOP).

Data analysis

Descriptive statistics (percentages, minima, maxima, means) and graphs were computed using Microsoft Excel 2003 SP 3.

RESULTS

Penetration of nutrition information by country

In total, 37365 products from five food and beverage product categories were audited (Table 1) in 84 individual retail stores across all 27 EU Member States and Turkey (Table 2). The vast majority of stores was located in capital or big cities, with the exact choice guided by easy access from the nearest airport or major train station. An average of 85% (range 70-97%) of these products displayed on the back of the pack one or more of the items considered, versus 48% (range 24-82%) for FOP penetration (Fig. 1). Countries at the top end of the range for provision of BOP information were Ireland, UK and The Netherlands, whereas Slovenia and Cyprus represented the bottom end. For FOP information, the leading countries were the UK and Ireland, while Turkey showed the lowest penetration.

The most widespread format across all countries was BOP tabular or linear listing of nutrition content (84% average penetration), highlighting either the "Big 4" (34% penetration) or the "Big 8" (49% penetration), the remainder being made up of other combinations or just the energy content (1% penetration) (Fig. 2). The ratio of "Big 8":"Big 4" was 1.4 across all products, ranging from 0.7 for yoghurts to 5.2 for breakfast cereals.

The GDA system was the most prevalent form of FOP nutrition information, ranging from 2% in Turkey to 63% in the UK and averaging 25% across all countries (Fig. 3).

Whereas penetration of FOP nutrition claims ranged from 12% in Estonia to 37% in Ireland and Portugal, with a European average of 25% (Fig. 4), health claims and health logos were used on very few products (data not shown). The average penetration of health claims was 4% BOP (from 0.5% in Spain and Czech Republic to 8% in Ireland) and 2% FOP (from < 0.5% in France, Portugal and Spain to 6% in Finland), while the average penetration of health logos was 1% on the BOP (from 0.1% in Portugal and Latvia to 9% in The Netherlands) versus 2% on the FOP (from 0.1% in Portugal and Latvia to 12% in Sweden and The Netherlands). In the following seven countries, none of the audited products bore any health logos: Cyprus, Czech Republic, France, Germany, Poland, Romania, and Slovakia. In contrast, health logos peaked at 47% on breakfast cereals in Sweden and at 27% on yoghurts in The Netherlands. Depending on the product category, Austria, Denmark, Estonia, Finland, Greece, Ireland, Slovenia, and the UK exceeded a level of 5% penetration for health logos, with varying emphasis on FOP or BOP labelling.

Traffic light labelling was only encountered on products audited in Spain (3% FOP, 3% BOP) and the UK (3% FOP, 2% BOP) (data not shown).

Penetration of nutrition information by category

Among the five categories of products audited, breakfast cereals showed the highest penetration of items considered in this audit, providing BOP information on 94% of products (from 79% in Bulgaria to 100% in France, Ireland and The Netherlands) and FOP information on 70% of products (from 43% in Turkey to 93% in France and Germany) (data not shown).

Typically, the minimum information provided was the BOP nutrition table (94%), mostly containing the "Big 8" (78% vs. 15% "Big 4"). On the other hand, sweet biscuits had the lowest penetration of nutrition-related information (76% BOP, 25% FOP), and the split for the BOP nutrition table (76% penetration) was even between "Big 8" and "Big 4" at 38% each.

Yoghurts were the only product category where the "Big 4" were more prevalent than the "Big 8" (51% vs. 36%, total BOP nutrition table 88%). At the same time, yoghurts showed the highest penetration of health claims, reaching up to around 30% (BOP) in Ireland and Bulgaria, and around 20% in the UK, Romania, Denmark, Belgium, Malta, and The Netherlands. Of note, no ready meals fitting the criteria FLABEL defined for this category were found in the following five countries: Bulgaria, Cyprus, Italy, Malta, and Romania.

However, these countries do have chilled ready meal-type foods that are available unlabelled and unpackaged over the deli counter.

DISCUSSION

This study provides a realistic picture of the penetration of nutrition labelling and related information on food packs in Europe. The main finding is that tabular/linear nutrition information as defined in Nutrition Labelling Directive 90/496/EEC was present on a large majority of products audited despite the fact that the provision of this information is a voluntary practice in Europe in the absence of nutrition or health claims [START_REF] Ec | Council Directive 90/496/EEC of 24 September 1990 on nutrition labelling for foodstuffs[END_REF][START_REF] Ec | Regulation (EC) No 1924/2006 of the European Parliament and of the Council of 20 December 2006 on nutrition and health claims made on foods[END_REF]. To our knowledge, this audit is the first to assess the penetration of nutrition labelling across all 27 EU Member States and Turkey. A previous, smaller-scale study (European Advisory Services 2004) recorded the presence of tabular nutrition labelling ("Big 4" or "Big 8") on 2954 products from 51 product categories in the four EU Member States Germany, Poland, Spain and the UK, and reported an average penetration of 56%. This lower figure is probably explained by two factors: 1) food labelling practices are continuously evolving and the number and penetration of labelling systems has increased since 2004, and 2) product categories such as spices, chewing gum, tea and coffee were included, which rarely carry the tabular nutrition information audited for. Additionally, not all products in each of the 51 categories were audited, so that the real penetration per category may have been different. Survey data from the United States, where mandatory nutrition labelling was implemented in 1994, showed that in 1997 practically all packages from a representative sample of food products falling under the national labelling regulation had nutrition labels [START_REF] Brecher | Status of nutrition labeling, health claims, and nutrient content claims for processed foods: 1997 Food Label and Package Survey[END_REF]. These results were confirmed in a follow-up survey in 2000-2001 [START_REF] Legault | 2000-2001 food label and package survey: an update on prevalence of nutrition labeling and claims on processed, packaged foods[END_REF].

All products belonging to the categories defined for the FLABEL audit fulfilled the nutrition labelling requirements except for pre-packed chilled ready meals, which had 90-99.9% labelling.

With regard to the extent of nutrition information, in most cases at least the calorie, fat, carbohydrate and protein contents (the "Big 4") of a specific product were provided, and this information was usually found on the back of pack (BOP 84% vs. FOP 3%). However, this high penetration is not explained by the presence of nutrition or health claims, which would render the provision of such information mandatory [START_REF] Ec | Council Directive 90/496/EEC of 24 September 1990 on nutrition labelling for foodstuffs[END_REF][START_REF] Ec | Regulation (EC) No 1924/2006 of the European Parliament and of the Council of 20 December 2006 on nutrition and health claims made on foods[END_REF]. Research suggests that consumers value the presence of nutrition information on food packs [START_REF] Gracia | Consumers' valuation of nutritional information: A choice experiment study[END_REF], which in turn might drive manufacturers to provide such information voluntarily in order to create a marketing advantage.

More recently, various front-of-pack nutrition labelling schemes have emerged such as the Traffic Lights scheme, GDA, or health logos, to provide consumers with nutrition information that is easy to access while shopping. It is noteworthy that the 1990 Nutrition Labelling Directive 90/496/EEC [START_REF] Ec | Council Directive 90/496/EEC of 24 September 1990 on nutrition labelling for foodstuffs[END_REF]) is currently being revised and the new proposal includes mandatory FOP labelling of energy, fat, saturated fat, carbohydrates, sugar, and salt per 100 g/ml [START_REF] Ec | Proposal for a Regulation of the European Parliament and of the Council of 30 January 2008 on the provision of food information to consumers[END_REF]. Ireland and the UK have been very active in nutrition labelling and this is supported by the high penetration of FOP GDA (58% and 63%, respectively). [START_REF] Camp | UK food manufacturer responses to voluntary front of package nutrition schemes[END_REF] recently reported comparable figures for FOP GDA in the UK and likewise found higher figures for (breakfast) cereals and ready meals than for sweet biscuits. The UK also plays a prominent role in Traffic Lights labelling (e.g. Sainsbury, ASDA), however, few other countries have retailers employing such colour-coded systems (e.g. Intermarché in France, Eroski in Spain).

Health claims, on the other hand, were much less widely spread in the present study (4% BOP, 2% FOP), and mainly occurred on breakfast cereals and yoghurts. A similar situation has been observed outside Europe. For example, nutrient content and health claims in the U.S. had an average penetration of 34% and 4%, respectively [START_REF] Legault | 2000-2001 food label and package survey: an update on prevalence of nutrition labeling and claims on processed, packaged foods[END_REF], with large differences between product categories. Two Australian studies that focused entirely on the presence of claims on pre-packed foods reported 36% of the audited products to bear a nutrient content claim [START_REF] Williams | Nutrition and related claims used on packaged Australian foods--implications for regulation[END_REF] and 14% to carry a health-related claim [START_REF] Williams | Nutrition function, health and related claims on packaged Australian food products--prevalence and compliance with regulations[END_REF]. Again, large variations were observed depending on the product category, but energy or sports drinks and (breakfast) cereals frequently appeared among the top categories.

The high numbers for health logos in some product categories in Sweden and The Netherlands are largely explained by the use of the Swedish Keyhole ® (Swedish National Food Administration 2007), the Choices logo (Choices International Foundation 2007), and the own-brand logo "Healthy Choice Clover" by the Dutch retailer Albert Heijn included in this audit, respectively. The Swedish Keyhole ® was developed by the Swedish National Food Administration and applies to products that contain less fat, sugar, and salt and more fibre (depending on the category) than a comparable product, and as such represent a healthier option within a product category. The Choices logo is a FOP logo on food products that also fulfil a set of qualifying criteria, based on international dietary guidelines, and is currently used by around 130 companies around the globe. The Albert Heijn logo "Healthy Choice Clover" considers the contents of saturated fat, trans fat, sugar and salt of foods and highlights a "healthy choice" or an "informed choice" depending on the product category. It has been speculated that health logos based on international consensus may be a simple way to brand healthier food options, especially for young children [START_REF] Cinar | A holistic food labelling strategy for preventing obesity and dental caries[END_REF].

Limitations of the study

The physical audit had to be restricted to a select number of stores for reasons of feasibility, and store choice was partly governed by retailer permission to conduct the research in their stores. This means that not all of the existing nutrition labelling schemes in a country (e.g. colour-coded labelling in France) were taken into account. However the major aim of this audit was to map the penetration of nutrition information irrespective of format.

Food products in supermarkets are usually organised and grouped by aisle, and we audited all the food products present in the corresponding product category aisle in the different retail stores. However, products belonging to any of the five product categories audited but placed elsewhere in the store (e.g. in an organic aisle, or a specific discount area) were not included.

The impact of this omission is likely to be small, though, as for example products on promotion are usually also found in the main category aisle, and specialty products (such as "organic" range or "diabetic" products) are not necessarily singled out on separate shelves elsewhere in the store. Additionally, in both cases the number of products tends to constitute a small fraction of the total in that product category.

Finally, Tesco as a partner in the FLABEL consortium, provided store access in 7 of the 28 countries. Tesco uses GDA labelling on its own-brand products, which may have resulted in an overrepresentation of GDA labelling in the study. Nevertheless, Tesco is not the only retailer using the GDA system in Europe and Tesco-brand products represented only a fraction (2.7%) of all the food products audited. On the other hand, many of the branded goods manufacturers use GDA labelling on their brands in categories such as breakfast cereals, carbonated soft drinks and yoghurts, thus leading to the overall high penetration figures for GDA across countries.

In conclusion

Taken together, a large majority of the more than 37000 products audited carried tabular/linear nutrition information, which is at present voluntary in the absence of nutrition or health claims. These findings provide the basis for subsequent studies involving attention, reading, liking, understanding and use by consumers of different nutrition labelling formats, which will be explored in the next phases of the FLABEL project. Major outcomes of FLABEL will be best practice guidelines for research into nutrition labelling as well as a research-based best practice proposal for nutrition labelling, tested in a real-world store environment.

Fig. 1

 1 Fig. 1 Penetration of nutrition labelling and related information across five product categories in EU-27 and Turkey

Fig. 3

 3 Fig. 3 Penetration of Guideline Daily Amount (GDA) information on the front of pack (FOP) and back of pack (BOP) across five product categories

Table 1 .

 1 Number of products audited per category per country

		Sweet	Breakfast	Ready	Carbonated
	Country	biscuits	cereals	meals	soft drinks	Yoghurts TOTAL
	Austria	318	213	86	222	298	1137
	Belgium	562	218	245	348	267	1640
	Bulgaria	567	137	0	196	221	1121
	Cyprus	624	333	0	238	206	1401
	Czech Republic	632	325	26	143	454	1580
	Denmark	249	152	11	173	161	746
	Estonia	282	230	15	138	251	916
	Finland	465	339	230	229	475	1738
	France	742	199	243	252	312	1748
	Germany	459	283	175	124	542	1583
	Greece	350	128	40	190	455	1163
	Hungary	338	178	34	138	274	962
	Ireland	399	280	158	177	249	1263
	Italy	593	117	0	227	359	1296
	Latvia	313	164	10	151	401	1039
	Lithuania	372	196	5	134	326	1033
	Luxemburg	427	157	129	285	384	1382
	Malta	784	416	0	205	379	1784
	The Netherlands	440	134	171	294	273	1312
	Poland	685	249	11	220	566	1731
	Portugal	477	180	1	156	418	1232
	Romania	284	99	0	155	241	779
	Slovakia	788	361	47	243	667	2106
	Slovenia	615	271	40	136	442	1504
	Spain	493	160	86	294	278	1311
	Sweden	316	376	101	342	401	1536
	Turkey	300	97	9	217	282	905
	UK	360	283	293	239	242	1417
	TOTAL	13234	6275	2166	5866	9824	37365

ACKNOWLEDGEMENTS

The authors would like to thank the retailers who granted access to their stores and the local contacts for helping with the data collection in the different countries. The support by the European Community of Consumer Cooperatives (Eurocoop), Tesco Stores Ltd., the European Association of Craft, Small and Medium-sized Enterprises (UEAPME) and the Confederation of Family Organisations in the European Union (COFACE) deserves special mention. The help of Fanny Rollin of EUFIC in drafting the manuscript is gratefully acknowledged. FLABEL receives research funding from the European Community's Seventh Framework Programme (Contract n° 211905).

research, co-designed the audit, and comments on the manuscript.

analysis. JMW collected parts of the data, provided input on the methodology, and critically reviewed the paper. CH and MMR contributed to the audit design and data collection, and provided