Introduction

Type 1 diabetes mellitus (T1DM) is an autoimmune disease inherited in a non-Mendelian way (Pociot & McDermott, 2002). It is thought that environmental factors (both protective and inductive) do determine the penetrance of T1DM susceptibility genes (Akerblom et al, 2002). However, whether viral infections, dietary habits, lifestyle, and socioeconomic status may be important in the development of T1DM is debatable (Lipton et al, 1999; Littorin et al, 2001). Moreover, behavioural science research in diabetes promotes lifestyle changes related to nutrition and physical activity (Wing et al, 2001), because these factors play a major role in the prevention and treatment of diabetes and related complications. However, it is often difficult to discern the efficacy of diabetes education. Thus, there is insufficient awareness on the part of physicians of the effectiveness of their own interventions.

To analyse behaviour patterns in population subgroups of public health importance, we compared lifestyle, dietary intake of energy and selected nutrients, and nutritional biomarkers of type 1 patients and nondiabetic first-degree relatives against control subjects with no family history of T1DM. This study is among the first to use the European Prospective Investigation of Cancer and Nutrition food frequency and lifestyle questionnaires to evaluate Italian type 1 diabetes families.

Materials and methods

Subjects

This cross-sectional study was carried out in the following groups of subjects:

1. A total of 38 T1DM patients with duration of disease ranging from 4 months to 41 y (mean 1811 y). From the roster of all patients with T1DM who visited the Clinic between 31 January 2001 and 19 July 2001, we selected those patients who resided in Pisa, who had at least one living biological relative alive, who fulfilled the inclusion criteria, and who gave informed consent. The group consisted of 19 patients without diabetic complications, 10 patients with retinopathy (background or proliferative, determined by fluorescein angiography following fundus examination), and nine patients with nephropathy. All patients with nephropathy had also diabetic retinopathy. All patients had been treated from time of diagnosis with at least two daily insulin injections and were now receiving at least four daily insulin injections. None received medical treatment except insulin (0.60.2 U/kg) and possibly antihypertensive drugs.
2. In total, 76 first-degree relatives of T1DM patients, 44 parents and 32 siblings (21 relative per proband). None of the relatives had clinical evidence of illness or was taking any drugs. If fasting plasma glucose was 7 mmol/l, a 75-g oral glucose tolerance test (OGTT) was performed.
3. In all, 95 healthy subjects were recruited from the local community to achieve a similar distribution of age and sex to the families. They had no family history of T1DM, were taking no drugs, and had no clinical signs or symptoms of illness.

All subjects gave informed consent and the ethical committee of the hospital approved the study proposal.

Data collection

To assess dietary intake the country-specific questionnaire designed to capture local dietary habits in the prospective collaborative study European Prospective Investigation of Cancer and Nutrition (EPIC) was administered (Riboli & Kaaks, 1997). EPIC study was conducted in 10 European countries and used a self-administered, scanner-readable food-frequency questionnaire (FFQ) whose development, reproducibility, and relative validity were described in detail previously (Franceschi et al, 1993; 1995; Decarli et al, 1996; Pisani et al, 1997; Pasanisi et al, 2002). Energy and nutrient intakes from dietary assessment were calculated by using data from the Italian food code (Salvini et al, 1998). Daily amount (vq, g/day) and daily frequency of consumption (vf) of specific food items consumed were also provided.

Demographic, socioeconomic and lifestyle information was obtained by Lifestyle EPIC questionnaire (including questions on history of previous illness and surgical operations, lifetime history of consumption of tobacco and alcoholic beverages, and physical activity) (Salvini et al, 2002). Current smokers were defined as subjects smoking one or more cigarette, cigar or pipe per day. Ex smokers were subjects who had smoked in the past. Subjects reported the daily number of hours they engaged in housework as well as the weekly number of hours they engaged in physical activities during leisure (walking, cycling, gardening, repairing, exercise; through the year or seasonally) and during work (sedentary; standing; manual work; heavy manual work). Exercise (or sporting activities) included gymnastics, running, playing tennis, swimming, etc.

The body mass index (BMI) was calculated as body weight/height² (in kg/m²). For all subjects basal metabolic rate (BMR) was calculated based on the formulas of Harris–Benedict (Harris & Benedict, 1919). The energy ratio equals daily energy intake divided by BMR. Sitting systolic and diastolic blood pressure (Korotkoff V) were measured twice and averaged after 10 min rest. Mean blood pressure (MBP) was calculated as diastolic BP+1/3 (systolic BP-diastolic BP).

Assuming that urea nitrogen excretion is a constant proportion (85%) of total urinary nitrogen, protein intake was derived from the following formula (Isaksson, 1980):

The protein ratio equals daily protein intake divided by calculated protein intake. Na and K ratios equal the daily intakes of either sodium or potassium divided by respective daily urinary excretions. Recommended Dietary Allowances (RDAs) and Adequate Intakes (AIs) were from Dietary reference intakes for energy, carbohydrate, fibre, fatty, fatty acids, cholesterol, protein and amino acids (Institute of Medicine, 1997; 1998; 2000; Food and Nutrition Board, Institute of Medicine, 2002; 2003).

Collection of samples and laboratory methods

Fasting venous blood samples and 24-h urine collections were obtained on a single occasion during the same period. Measurements were performed in freshly obtained material immediately after withdrawal, except insulin that has been measured on samples frozen at -20°C.

Creatinine, glucose, albumin, cholesterol, and triglycerides were measured by MODULAR ANALYTICS SWA and reagents from Roche Diagnostics (Milano, Italy); circulating iron by ADVIA 1650 (Bayer Divisione Diagnostici, Milano, Italy). HbA1c was evaluated by Bio-Rad DIAMAT™ fully automated glycosylated haemoglobin Analyzer System. Fasting plasma tHcy concentrations were determined by enzyme-linked immunoassay and automated fluorescence polarization analyser (FPIA, IMX System, Abbott Diagnostics, Roma, Italy). Plasma concentrations of folate and vitamin B₁₂ were measured by AxSYM System (Abbott Diagnostics, Roma, Italy).

Immunoreactive insulin (IRI) was measured by commercial radioimmunoassay (Medgenix Diagnostics, Fleurus, Belgium). Insulin resistance was estimated by homeostasis model assessment (HOMA_IR) (Matthews et al, 1985).

Statistical analysis

The results are presented as meanstandard deviation or median and range (food items vq and vf). Data not normally distributed were logarithmically transformed to achieve normal distributions before t-tests and ANOVA. The cutoff level for statistical significance was set at P<0.05. The unpaired Student's t-test (two-tailed) and Mann–Whitney U-test were used to determine significant differences between independent groups. Statistical analyses comparing multiple variables were performed by using ANOVA (followed by Bonferroni correction) and Kruskal–Wallis rank test. Comparison of categories was by ² test. We estimated the associations by linear regression analysis (Spearman's rank correlation analysis) as well as by stepwise regression analysis and multiple linear regression (Statview Package, Abacus Concepts, Berkeley, CA, USA). When regressing the energy ratio on BMI, we adjusted for levels of physical activity. Besides analysing data from the whole study population, we also performed analyses after including separate subsets of individuals (either control subjects or T1DM patients) in the multiple regression analyses relating circulating concentrations of folate or tHcy to explanatory variables. For the purpose of making between-sex comparisons, estimated total energy and nutrient intakes were divided into body surface area (BSA, m²=kg^0.425 cm^0.725 0.007184). In search of systematic measurement error (Heerstrass et al, 1998), mostly in the form of under-reporting, we performed linear regression analysis to analyse the relationship between estimated and calculated (on the basis of laboratory measurements) nutrient intakes as well as between BMI and energy ratio.

Results

Healthy control subjects

Table 1 displays general characteristics of the healthy control population. A total of 43 controls (45%) could be defined overweight (BMI25 kg/m²) and overweight was prevalent in the male gender.

Table 1 - Characteristics of the healthy control participants.

Full table

Among the healthy control subjects, current smokers were 56%. Despite the mainly seated/standing occupation (73%), the energy ratio was 1.60.3. The percentage of energy from protein, carbohydrates, and fat was 162, 516, 335%, respectively, with P:S ratio 0.320.07. The median value of alcohol consumed was 5.3 g/day (range 0–59), that is, less than 1.4% of the total calories.

In comparison with RDAs/AIs, ADA and AHA dietary guidelines, daily intake of total fat (9731 g) and cholesterol (413136 mg) was abundant, whereas intakes of fibre (226 g), folic acid (28273 g), vitamin D (3.21.4 g) and vitamin E (8.32.4 mg) were inadequate.

A marginal plasma folate deficiency (10.44.7 nmol/l) was observed, consistent with the low estimated folate intake. About 82% of our control subjects had serum folate 15 nmol/l. The mean plasma tHcy concentration (11.87.0 mol/l) was in the upper normal range. Among control subjects, serum folate showed a negative association with total energy (r=-0.3, P<0.001), protein energy (r=-0.3, P<0.001), and alcohol (r=-0.2, P<0.01) intakes. Plasma tHcy concentration was associated (multiple r=0.5, P<0.001) positively with plasma creatinine (coefficient=0.005, s.e.=0.001, t-value=4, P<0.001) while negatively with plasma concentrations of vitamins B₉ (-0.02, 0.01, -2, P<0.05; Figure 1) and B₁₂ (-0.0004, 0.0001, -3, P<0.01).

Figure 1.

Relationship between plasma concentrations of homocysteine and folates in healthy control subjects.

Full figure and legend (80K)

Women had lower BMI, MBP, fasting plasma glucose (FPG) and insulin (FPI), HOMA IR (1.91.0 vs 2.41.3, P<0.05), triglicerydes, and homocysteine, while higher HDL cholesterol, and plasma folate than men. The frequency of smoking was similar in both sexes. Women reported lower levels of regular exercise (2.01.5 vs 3.02.1 h/week, P<0.01), but were the only persons who spent time in household activities (2.51.2 vs 0 h/day, P<0.001). Women tended to consume more soluble carbohydrates, fibre, vitamins B₉, C, A, and E (adjusted for BSA) than men. A total of 12 women (23%) were nondrinkers, and the remaining drank 3.5 g alcohol daily. A total of four men (9%) were nondrinkers, and the remaining drank 7.5 g alcohol daily (P<0.01 vs women).

TIDM families vs matched controls

T1DM patients had higher FPG, HbA1c, and plasma folate (Table 2). Their dietary habits appeared healthier than those observed in controls. Diabetes was associated with reduced intake of total calories, soluble carbohydrate, total and saturated fat. Even though daily cholesterol intake did not reach the suggested value (<300 mg/day), their P:S ratio was higher than that of controls. The mean plasma folate concentration was elevated in the T1DM subset in which, however, folate intake was not correspondingly increased. Plasma tHcy concentration showed a stronger association (r=0.8) with the same variables as in control subjects.

Table 2 - Characteristics of T1DM patients and matched controls.

Full table

There was a distinct pattern in the negative association between plasma folate concentration and diastolic blood pressure among healthy controls (y=19.65-0.14x, P<0.05) and among T1DM patients (y=27.92-0.19x, P=0.10). The regression equation significantly differs between groups in the parameter a (Figure 2). Moreover, the levels of plasma folate increased progressively with increasing category of microangiopathic complications (9.13.8 nmol/l in controls, 12.75.4 in T1DM without complications, 15.67.9 in T1DM with retinopathy, 15.47.7 in T1DM with nephropathy, P<0.001) (Figure 3). Depicted groups did not differ as to age, gender, BMI, and MBP (19 controls, 4411 y, 254 kg/m², 889 mmHg; 10 T1DM without complications, 378, 264, 899; 10 T1DM with retinopathy, 459, 253, 859; 9 T1DM with nephropathy, 4211, 253, 9311).

Figure 2.

Relationship between plasma concentrations of folates and diastolic blood pressure in healthy control (upper panel) and T1DM subjects (lower panel).

Full figure and legend (88K)

Figure 3.

Levels of plasma folate in control subjects and T1DM patients gathered by microangiopathic complications.

Full figure and legend (60K)

Relatives had a higher plasma total cholesterol concentration (Table 3). The total amount of niacin they consumed per day was higher than corresponding controls did (higher consumption of chicken—vq 39, 0–128, in relatives vs 30, 0–77, in controls, P<0.01—and crisp bread—vq 4.0, 0–58, vs 1.2, 0–32; vf 0.4, 0–6.8, vs 0.2, 0–4.0, P<0.05). They reported lower physical activity levels, largely determined by their reduced routine use of cycle (0.30.2 vs 0.40.2 h/week, P<0.01). No difference in alcohol consumption emerged among families and controls (T1DM 4.2 g, 0–58, vs controls 4.3, 0–49; relatives 5.9, 0–95, vs controls 6.1, 0–59).

Table 3 - Demographics, biomarkers, the composition of dietary intakes estimated from the food-frequency questionnaire of all relatives and matched controls.

Full table

Whole study population

The principal components analysis identified some food items that were associated with decreased folate, vitamin E, and vitamin D consumption. The intake of vitamin D fell as fish consumption frequency decreased (vq 29, 0–172; vf 0.2, 0–0.8). Low intakes of vitamin E could be related to the preferential use of olive oil (vq 27, 0.9–73; vf 3, 0.1–8) rather than other vegetable oils (vq 0.2, 0–37; vf 0.1, 0–3); low folate intake to decreased consumption of vegetables (leafy vegetables vq 14, 0–86; vf 0.6, 1–1.8; cooked veg. 10, 0–114; 0.2, 0–0.5).

Estimated intakes of protein (10331 g), sodium (2.81.1 g), and potassium (3.40.9 g) were correlated (r=0.4, 0.3, and 0.3, respectively, P<0.001) with calculated protein intake (16555 g), sodium output (3.91.7 g) and potassium (2.50.9 g) output, respectively. In comparison with values derived from urinary measurements, FFQ-derived protein and sodium intakes were significantly (P<0.001) under-reported, whereas FFQ potassium intake was overreported (P<0.001).

When regressing the energy ratio on BMI (r=0.2, P<0.001), a degree of BMI-related under-reporting was apparent, but the significance was abolished after adjustment for exercise, that was decreasing with increasing BMI.

Increasing age was associated with unchanged energy intake (r=0.01, -0.00004, 0.0003, -0.1, P=0.9), reduced exercise (r=-0.4, -3.1, 0.5, -6.7, P<0.001), and increased BMI (r=0.2, 0.7, 0.25, 2.6, P<0.01).

In the whole study population, BMI correlated (multiple r=0.4, P<0.001) negatively with kJ/BMR (-0.52, 0.12, -4.4, P<0.0001) and time spent in housework (-0.32, 0.15, -2.0, P<0.05) and exercise (-0.28, 0.15, -1.9, P=0.05), whereas positively with age (0.06, 0.02, P<0.0130), and K ratio (0.9, 0.38, 2.3, P<0.05).

Discussion

Interesting findings emerged from this study that obtained for the first time in T1DM families a detailed assessment of nutrient intake levels and lifestyle using standardized EPIC questionnaires adapted for use in the Italian population. Indeed, current diet of residents from Pisa province may not provide appropriate amounts of macro- and micronutrients. EPIC data in the Italian EPIC cohorts (Pala et al, 2003), the Data Food Networking Reports (Trichopoulou & Naska, 2003), and evidence from a primary school health program carried out in Pisa (Giampietro et al, 2002) confirmed that Italian eating habits are undergoing marked changes with a tendency to less healthy eating.

The American Diabetes Association (ADA) recommends that dietary intake of fat is reduced to no more than 30% of total calories (saturated <10%, polyunsaturated 10%). Dietary intake of cholesterol should be reduced to below 300 mg/day. A low fat/high carbohydrate (55–60%) diet, rich in fiber (25–30 g/day), is advised. It may be prudent to avoid protein intakes >15–20% of total daily energy (American Diabetes Association, 2003). American Heart Association (AHA) dietary guidelines advice limiting salt intake (<6 g/day) and engaging in a regular physical activity (30–60 min on most if not all days of the week) (Krauss et al, 2000). Energy intake in balance with energy expenditure is essential to prevent weight gain that accompanies aging. Polyunsaturated/saturated (P/S) ratio should be >1.0. Recent evidence supports that type 2 diabetic men in the P/S ratio >0.28 had a significantly lower risk for coronary heart disease death (Soinio et al, 2003).

An emerging health issue in our study is the fact that increasing age was associated with increasing body mass and decreasing activity in sport in front of an unchanged intake of total calories, contrary to recent findings in different populations (Mitchell et al, 2003). The distribution of energy sources was also incorrect. The proportion of caloric intake derived from total fat and cholesterol did not match general guidelines. Most controls (presumed to be consuming a free diet) ate up to 50% more protein (1.50.4 g/kg based on FFQ protein intake, 2.20.6 g/kg based on calculated protein intake) than recommended as RDAs/AIs. Total dietary fibre consumption was assessed to be adequate (25 g/day) in only 27% of all the participants. An even more relevant and unexpected health issue was the evidence of mild to moderate combined-vitamin-deficient intakes in otherwise well-nourished healthy adults. Disorders of vitamins are currently considered to be rarely epidemic especially in developed nations. Nevetheless, estimated daily intakes of water-soluble vitamin B₉ (or total folates) and fat-soluble vitamin D (sum of ergocalcipherol and cholecalcipherol) and vitamin E (sum of all tocopherols and tocotrienols) were deficient in comparison with RDAs and AIs (400 g, 5–10 g, and 15 mg, respectively). Taking into account that RDA values probably rely on outdated concepts of deficiency diseases and the special issue needs a reappraisal of current knowledge as to the optimal dietary intake for minimising degenerative diseases (Challem, 1999), the observed diet patterns may be seriously inadequate for health.

Despite many limitations, questionnaire assessments of dietary behaviours and physical activity levels were useful in numerous diseases, including cancer (Bingham et al, 2003) and coronary heart disease (Soinio et al, 2003). Biomarkers of dietary intake, such as urinary nitrogen and electrolytes, have been applied in nutritional validation studies. Based on our correlation coefficients, present data are within the range observed previously (Kroke et al, 1999), indicating comparable relative validity for the FFQ used in the present study population. Furthermore, the direct measurement of plasma folate confirmed FFQ results. Energy and potassium ratios entered the regression model vs BMI. We did not observe differential underreporting depending on subject characteristics (obesity) when data were adjusted for differential physical activity.

Nutritional status and nutrition can have profound effects on health and immune functions (Harbige, 1996). The deficiency of vitamin D, whose biologically active form is a potent modulator of the immune system, has been suggested among the dietary putative etiological factors in the pathogenesis of T1DM (Akerblom et al, 2002; Zella & DeLuca, 2003). However, vitamin D is rather a hormone. With adequate sunlight (as in Italy) no dietary supplements are usually needed. Since calcium homeostasis was not our target, we evaluated neither plasma concentrations nor urinary wasting of calcium and phosphate ions. Thus, we were unable to confirm a real state of hypovitaminosis D. Vitamin E supplementation, by a direct antioxidant effect or some other unknown mechanisms, could delay the progress of certain autoimmune diseases (Harbige, 1996) and prevent diabetes-induced endothelial dysfunction (Dhein et al, 2003). Unfortunately, we did not measure circulating levels of -tocopherol to confirm antioxidant vitamin E reserve compromised. In contrast, a reduced intake of folic acid was confirmed by the measurement of its plasma concentration as well as by the correspondent increase in plasma homocysteine levels. The usual reference range for fasting total plasma homocysteine is 5–15 mol/l, but some authors believe that the upper limit of the normal range should be 10–12 mol/l. In addition to glomerular filtration rate, circulating level of vitamins B₉ and B₁₂ are among main determinants of plasma tHcy. In subjects with plasma folate concentrations above 15 nmol/l (ie 7 ng/ml) the tHcy concentration is on a low, normal plateau. At lower levels of plasma folate, the plasma tHcy concentration increases steadily (Fonseca et al, 1999; Seshadri & Robinson, 2000). Dietary factors, such as an oral fat load, a single high-fat meal, an oral methionine load, or dietary animal protein, can cause temporary endothelial dysfunction in healthy volunteers. Indeed, among our control subjects, serum folate showed a negative association with total energy and protein energy intakes. The relationship between the median value of alcohol consumption intakes of micronutrients has been extensively investigated (Kesse et al, 2001). That the intake of folic acid decreased with alcohol consumption may partly contribute to lower folic acid intake of men.

In addition to lowering tHcy levels, folates possess antioxidant potential (Verhaar et al, 2002). The main form of folate in the circulation, 5-methyltetrahydrofolate, can reduce superoxide generation by xanthine oxidase/hypoxanthine and endothelial NO synthase (eNOS). Moreover, beneficial effects of folates on haem-containing oxygenase domain of eNOS may be explained by different mechanisms: (1) tetrahydrobiopterin (BH4) rescue, (2) antioxidant effects and (3) direct effects on eNOS. Our results from food frequency EPIC questionnaire exclude an increased folate intake in T1DM. Thus, why plasma folate is high remains unclear. Could higher serum folates be necessary to promote the regeneration of BH4 and, in turn, BH4-dependent restoration of eNOS? Redox status and circulating insulin could play a role (Das, 2003). Increased basal levels of plasma nitric oxide in type 2 diabetic subjects have been interpreted as a compensatory phenomenon for the decreased vascular responsiveness (Maejima et al, 2001). The ability of folate, BH4, insulin, and O₂^- to interact with each other and influence NO generation, stability and action could pertain to our finding of a different association between plasma folate and diastolic blood pressure in T1DM patients and control subjects.

Niacin or vitamin PP (as the sum of nicotinic acid and nicotinamide) was the only micronutrient whose intake was estimated to differ in relatives vs controls, contributed for by different dietary patterns. Interestingly, niacin has been tested for the prevention of T1DM in subjects considered at risk of developing the disease (Beales et al, 1999).

The prevalence of adoption and maintenance of healthful eating and physical activity habits was higher in women (spontaneously?) and T1DM patients (probably as a consequence of the medical educational intervention). Thus, we could also assess achieved compliance with diabetes clinical practice recommendations by a reliable, objective measure of patient outcomes. Since making appropriate food choices is among patient-knowledge measures (Glasgow & Osteen, 1992), our patients did translate knowledge into improved eating patterns. On the contrary, judging by dietary habits of relatives indistinguishable from those of controls, supportiveness of the family in term of changing the undesirable behaviours at home seemed to fail. However, our study included individuals spanning a wide range of ages and many relative pairs currently living apart.

In conclusion, this study of Italian T1DM families provides first evidence indicating unhealthy dietary behaviours, which could even predispose to the development of diabetes and cardiovascular complications, in subjects living in Pisa. The combination of vitamin B₉ and vitamin E deprivation could be deleterious for endothelial function, since these dietary antioxidants have been implicated in the modulation of nitric oxide and eicosanoid signalling. Ignored mild to moderated deficiencies of essential nutrients, possibly involved in the development of cardiovascular disease, could account for the fact that, regardless of current intake level, large observational studies have shown a correlation between dietary or supplemental consumption of antioxidants and cardiovascular benefits (Morris & Carson, 2003).

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Acknowledgements

We gratefully thank Dr S Salvini, Dr D Palli, and Dr G Cordopatri of the Centro per lo Studio e la Prevenzione Oncologica (CSPO), Scientific Institute of Tuscany, Florence, Italy, for their assistance with EPIC questionnaires.