Freijer K

Nuijten Mjc

Karen Freyer Bsc
email: karen.freyer@nutricia.com

ANALYSIS OF THE HEALTH ECONOMIC IMPACT OF MEDICAL NUTRITION IN THE NETHERLANDS

Keywords: medical nutrition, cost-effectiveness, health economic model, oral nutritional supplements

Objective: A health economic analysis was performed to assess the cost-effectiveness of Oral Nutritional Supplements (ONS), being a medical nutrition product, in The Netherlands.

Methods: This analysis is based on a comparison of the use of ONS versus "no use" of ONS in patients undergoing abdominal surgery. The costs and benefits of the two treatment strategies were assessed using a linear decision analytic model reflecting treatment patterns and outcomes in abdominal surgery. The incremental cost difference was based on costs associated with ONS and hospitalization. Clinical probabilities and resource utilization were based on clinical trials and published literature; cost data were derived from official price tariffs.

Results:

The use of ONS reduces the costs with a € 252 (7.6%) cost saving per patient. The hospitalization costs reduce from € 3,318 to € 3,044 per patient, which is a 8.3% cost saving and corresponds with 0.72 days reduction in length of stay. The use of ONS would lead to an annual cost saving of a minimum of € 40.4 million per year. Sensitivity analyses showed that the use of ONS remains cost saving compared to "no use" of ONS. A threshold analysis on the length of stay shows that at 0.64 days, the use of ONS is still cost-effective, which is an unrealistic value.

Conclusions:

This analysis shows that the use of medical nutrition, ONS in this case, is a cost-effective treatment in The Netherlands and is dominant over standard care without medical nutrition: it leads to cost savings and a higher effectiveness.

INTRODUCTION

Nutritional depletion in Western countries is usually caused by the joint action of an underlying disease, e.g., cancer and dietary deficiency [START_REF] Naber | Prevalence of malnutrition in nonsurgical hospitalized patients and its association with disease complications[END_REF], also known as Disease Related Malnutrition (DRM). As a consequence, treatment should be focused not only on the disease but also on nutritional intervention. A Dutch study found that 40% of the patients in a ward for nonsurgical patients were malnourished at admission, and that the risk of subsequent complications was higher in malnourished patients [START_REF] Naber | Prevalence of malnutrition in nonsurgical hospitalized patients and its association with disease complications[END_REF]. This frequency of DRM was as high as or higher than that reported in surgical patients (30%) [START_REF] Naber | Prevalence of malnutrition in nonsurgical hospitalized patients and its association with disease complications[END_REF]. This 40% percentage of DRM may be an underestimate because patients were excluded if nutritional status could not be assessed within 24 hours after admission. The consequences of malnutrition, if left untreated, are serious, causing a marked decline in physical and psychological health and function [START_REF] Stratton | Who benefits from nutritional support: what is the evidence?[END_REF].

Malnutrition impairs recovery from disease and injury (including surgery), increasing mortality and complications (infections, pressure ulcers, etcetera) and healthcare use (general practitioners visits, length of stay) [START_REF] Martyn | Effect of nutritional status on use of health care resources by patients with chronic disease living in the community[END_REF]. Recently, also a burden of illness study was performed in The Netherlands [START_REF] Siok | The cost of disease related malnutrition and the cost-effectiveness of nutrition interventions: a feasibility study for the Netherlands[END_REF]. This study reports that the additional costs of disease related malnutrition in The Netherlands is € 1,683 billion in 2006, which equals 2.8% of the total Dutch national health expenditures. The majority (49%) of the total costs on disease related costs were attributable to the hospital setting (€ 830 million).

Meta-analyses on treatment of DRM with medical nutrition show a reduction in mortality and complications, for example sepsis, decubitus and pneumonia, improvement of wound healing, and an increase of Quality of Life (www.snellerbeter.nl 2008;Elia et al., 2005;[START_REF] Stratton | Elucidating effective ways to identify and treat malnutrition[END_REF]. Stratton and Elia concluded that nutritional support can be an important part of the management of any patient [START_REF] Stratton | Who benefits from nutritional support: what is the evidence?[END_REF].

The published literature (meta-analyses and systematic reviews) provide evidence that oral nutritional supplements (ONS) are an effective treatment for patients with malnutrition:

• Mortality rates are significantly lower (odds ratio of 0.61; 95% CI 0.48-0.78) [START_REF] Stratton | Who benefits from nutritional support: what is the evidence?[END_REF]. Similar findings were reported in other reviews (e.g. [START_REF] Potter | Oral supplements in the elderly[END_REF]).

• Complication rates, including infections, are significantly reduced (odds ratio of 0.31; 95% CI 0.17-0.56) [START_REF] Stratton | Disease-related malnutrition: an evidenced based approach to treatment[END_REF][START_REF] Stratton | Who benefits from nutritional support: what is the evidence?[END_REF]. Another systematic PROPRIETARY AND CONFIDENTIAL review showed that medical nutrition can significantly reduce the risk (25% risk reduction) of developing pressure ulcers [START_REF] Stratton | Enteral nutritional support in prevention and treatment of pressure ulcers: a systematic review and meta-analysis[END_REF].

In summary, DRM has a high prevalence and its clinical consequences may be severe and costly. Consequently inappropriate management of DRM may have a high economic impact.

STUDY OBJECTIVES

The primary objective of this study was to assess the cost-effectiveness of ONS, being a medical nutrition product, in patients undergoing abdominal surgery in The Netherlands.

METHODS

A model was constructed using decision analytical techniques [START_REF] Weinstein | Clinical decision Analysis[END_REF]. This decision analytic model was developed to estimate the health economic impact of oral ONS in abdominal surgery from the perspective of the society in 2008 in the Netherlands.

Data sources used included published literature, clinical trials and, official Dutch price/tariff lists and national population statistics.

Univariate sensitivity analyses are based on the modification of the basic clinical and economic assumptions in the model in order to test the stability of the conclusions of the analysis over a range of assumptions, probability estimates and value judgments.

• Proportion of malnutrition: The base case analysis (30%) is based on data for abdominal surgery; the range for the sensitivity analysis also includes data for non-surgical patients.

The sensitivity analysis is based on a range varying from 25% to 40%.

• Proportion eligible patients: The base case analysis is based on the assumption that all malnourished patients are treated; a sensitivity analysis is based on a proportion of 50% of malnourished patients being treated with ONS.

• Cost of ONS: The cost of ONS is varied between 10% discount of the market price for inpatients (€ 2.19 per bottle) and an outpatient price including VAT (€ 2.37 per bottle).

• Cost of hospitalisation: The base case analysis is based on a weighted per diem cost for academic and general hospitals. A sensitivity analysis is performed varying the per diem between the per diem of a general hospital (€ 357) and the per diem of an academic hospital (€ 504).

PROPRIETARY AND CONFIDENTIAL

• Duration of treatment with ONS: The base case analysis is based on a mean value of 8.5 days. A sensitivity analysis is performed varying the initiation from 7 to 16 days.

• Length of stay (LOS): A sensitivity analysis is based on a 25% decrease and increase of LOS for all patients (no risk and risk patients). This range was a subjective choice because of lack of data for the construction of a confidence interval. However, a 25% decrease and increase reduction of LOS can be considered a very extreme range and therefore captures the uncertainty in this input variable. A second sensitivity analysis was performed on a 25% decrease and increase of LOS for risk patients.

Model Design

The model calculates and compares the medical costs for a virtual population of abdominal surgery patients with ONS and for a virtual population of abdominal surgery patients without ONS. The health economic impact of ONS is calculated using a decision tree model built in TreeAge Pro 2005/2006 reflecting treatment patterns and outcomes in abdominal surgery.

Figure 1 shows the structure of the model for treatment with ONS. The first branch point in a tree is called a decision node because it corresponds to a choice of treatment -ONS or "no ONS". A decision node is represented as a small square ( ). Subsequent to the decision node, the structure of the decision tree is shown, which is identical for both treatment options.

The other branch points indicate probabilities. The patient may be at medium to high risk for DRM or at low risk for DRM.

Study Population and Comparison

The base case analysis is based on a comparison of the use of ONS versus "no use" of ONS in patients undergoing abdominal surgery.

Cost Assessment

An incremental costing approach was used, and therefore all drug utilisation (and other health care utilisation) being similar between the two treatment arms was not included in the model.

The incremental cost difference was based on the costs associated with the cost of ONS and hospitalisation. The model is based on the assumption that the use of ONS only has an impact on the LOS. The potential favorable impact on adverse events by ONS and therefore the lower costs caused by adverse events were not included in this analysis, because of lack of appropriate data to feed the model. Thus the costing methodology is based on a conservative PROPRIETARY AND CONFIDENTIAL approach towards the use of ONS. The real economic benefits will therefore be higher than could be calculated with the current data set (see Discussion). The perspective of the study was a limited societal perspective, because indirect costs were not included. Indirect costs due to productivity loss were not included in this health economic analysis. This is a conservative assumption towards the use of ONS, because the lower LOS would lead to lower productivity loss and therefore lower indirect costs. On the other hand, a substantial proportion of patients undergoing abdominal surgery may be retired, as the average age is 63.2 according to a Dutch study [START_REF] Kruizenga | Screening of nutritional status in The Netherlands[END_REF]. Discounting of costs and effectiveness measures was not performed, because time horizon of the model did not exceed one year.

DATA SOURCES

The Number of Abdominal Surgery Procedures

A CBO publication reports the annual number of surgery procedures (1.3 million) in The Netherlands (www.cbo.nl, 2007). This is an overall number without defining the type of surgical procedure. The annual number of abdominal surgery procedures is 160,283. [START_REF] Prismant | Data on number of hospitalisations and length of stay[END_REF].

Prevalence of Disease Related Malnutrition (DRM)

Several data on prevalence of DRM in the Netherlands have been published: from an overall prevalence of DRM of 25% [START_REF] Kruizenga | Screening of nutritional status in The Netherlands[END_REF] to a more group specific amount of 30% in surgical patients and 40% in non-surgical patients [START_REF] Naber | Prevalence of malnutrition in nonsurgical hospitalized patients and its association with disease complications[END_REF].: A recent Dutch study reports a range on prevalence of DRM varying from 25% to 40% in hospitalised patients, including surgical and non-surgical patients (www.snellerbeter.nl, 2008). This report also states that only 50% of malnutrition is being diagnosed and treated. The most recent Dutch documentation is based on an annual returning independent measurement of the prevalence of DRM within the Dutch Health Care [START_REF] Halfens | Ondervoeding. In Rapportage resultaten[END_REF][START_REF] Halfens | Ondervoeding. In Rapportage resultaten[END_REF].

The base case analysis is based on data from this Dutch documentation; the range for the sensitivity analysis also includes data for non-surgical patients. Therefore the base case analysis is based on a prevalence of DRM of 30% with a range varying from 25% to 40%.

The base case analysis is based on the assumption that all malnourished patients are treated (eligible patients); a sensitivity analysis is based on the data from "Sneller Beter", which reports that a proportion of 50% of malnourished patients is not treated with a ONS.

Recommended amount of intake of ONS

Typical prescription for ONS is 2 bottles (2 x 200 ml) per day per patient. The literature describes that 7 to 10 days before surgery the intake of ONS ought to be started, which may be continued until 7 to 10 days after surgery [START_REF] Mcclave | Preoperative Issues in Clinical Nutrition[END_REF][START_REF]French Speaking Society for Parenteral and Enteral Nutrition[END_REF][START_REF] Freyer Bsc | Guidelines for the Use of Parenteral and Enteral Nutrition in Adult and Pediatric Patients[END_REF]. Therefore the base case analysis is based on a mean value of 8.5 days before and after surgery.

Costs of Treatment

Costs of ONS

The price of a standard bottle is € 2.19, which corresponds with the list price as registered in the Dutch market. The costs for a hospital are lower due to discounts. The costs for a patient at the pharmacy are higher due to VAT . Therefore the most realistic price for a bottle would be € 2.19.

Costs of hospitalisation

The cost of hospitalisation was derived from the Dutch Costing Manual [START_REF] Oostenbrink | Handleiding voor kostenonderzoek[END_REF].

• Per diem academic hospital: € 476

• Per diem general hospital: € 337

• Distribution: academic hospital 16% and general hospital 84%

The costs were inflated from 2003 to 2008 (www.cbs.nl, 2008).

• Per diem academic hospital: € 504

• Per diem general hospital: € 357

RESULTS

Base case analysis

The results of the base case analysis are shown in Table 2. This analysis shows that the use of ONS does not lead to additional costs. In fact, the use of ONS reduces the costs from € 3,318 to € 3,066, which corresponds with a € 252 (7.6%) cost saving per patient. The additional costs of ONS are more than balanced by a reduction on hospitalisation costs. The hospitalisation costs reduce from € 3,318 to € 3,044 per patient, which is a 8.3% cost saving and corresponds with 0.72 days reduction in LOS.

Table 1 :

 1 Results: base case results and sensitivity analyses.

		range	ONS	no ONS	savings
	base case		€ 3,066	€ 3,318	€ 252
	proportion	25%	€ 3,063	€ 3,318	€ 255
	malnutrition	40%	€ 3,074	€ 3,318	€ 244
	eligible	50%	€ 3,192	€ 3,318	€ 126
	price ONS	1.97	€ 3,064	€ 3,318	€ 254
		2.37	€ 3,068	€ 3,318	€ 250
	cost hospitalisation	357	€ 2,878	€ 3,113	€ 235
		504	€ 4,054	€ 4,395	€ 341
	use of ONS	7	€ 3,063	€ 3,318	€ 255
	before and after
	operation	10	€ 3,070	€ 3,318	€ 248
	length of stay	-25%	€ 2,305	€ 2,489	€ 184
	all patients	25%	€ 3,828	€ 4,148	€ 320
	length of stay	-25%	€ 2,838	€ 3,021	€ 183
	only risk	25%	€ 3,295	€ 3,615	€ 320
			€ 3,066	€ 3,318	€ 252

PROPRIETARY AND CONFIDENTIAL

Table 2 :

 2 Results of two-way sensitivity analyses.

	sens
	=>	0,7500	0,8750	10,000	11,250	12,500
	Risk_LOS_nosupply_larger
	15,000	€ 2,305	€ 2,610	€ 1,914	€ 3,218	€ 3,523 FSMP
		€ 2,626	€ 2,976	€ 3,326	€ 3,676	€ 4,026 No FSMP
		€ 321	€ 366	€ 1,412	€ 458	€ 503 Savings
	13,875	€ 2,305	€ 2,610	€ 2,914	€ 3,219	€ 3,523 FSMP
		€ 2,549	€ 2,888	€ 3,228	€ 3,568	€ 3,908 No FSMP
		€ 243	€ 278	€ 314	€ 349	€ 385 Savings
	12,750	€ 2,305	€ 2,610	€ 2,914	€ 3,219	€ 3,523 FSMP
		€ 2,471	€ 2,801	€ 3,131	€ 3,460	€ 3,790 No FSMP
		€ 166	€ 191	€ 217	€ 241	€ 266 Savings
	11,625	€ 2,305	€ 2,610	€ 2,914	€ 3,219	€ 3,523 FSMP
		€ 2,394	€ 2,714	€ 3,033	€ 3,352	€ 3,671 No FSMP
		€ 89	€ 104	€ 119	€ 133	€ 148 Savings
	10,500	€ 2,305	€ 2,610	€ 2,914	€ 3,219	€ 3,523 FSMP
		€ 2,317	€ 2,626	€ 2,935	€ 3,244	€ 3,553 No FSMP
		€ 12	€ 16	€ 21	€ 26	€ 30 Savings

We performed a health economic analysis in order to assess the health economic impact of ONS in The Netherlands. This analysis was performed for the use of ONS, being a medical nutrition product, in abdominal surgery and showed that the use of ONS is cost-effective in the Dutch health care setting.

PROPRIETARY AND CONFIDENTIAL

This input data for the Dutch model corresponds with the BAPEN study from the UK, although the prevalence of DRM is somewhat lower: 29.3% for patients older than 65 and 20.4% younger than 65 (Elia et al., 2005). The UK data show that the difference in proportion of DRM is higher in the older patients (29.3% versus 20.4%). This difference is however less than 10%, which is much smaller than the range we use for the sensitivity analysis.

Length of Stay

An international observational study, including Dutch centers, evaluated the implementation of an enhanced recovery programme in five European centres and examined the determinants affecting recovery and LOS [START_REF] Maessen | A protocol is not enough to implement an enhanced recovery programme for colorectal resection[END_REF]. This study showed that the median length of stay was 8 days for standard treatment. A multivariate analysis revealed no country specific effect on length of stay. Prismant data from 2003 reports an average length of stay of 12.9 days in abdominal surgery in The Netherlands [START_REF] Prismant | Data on number of hospitalisations and length of stay[END_REF]. For clinical outcomes, the general rule may be to assume that data are not country-specific [START_REF] Nuijten | The selection of data sources for use in modelling studies[END_REF]. LOS in a hospital was considered a clinical outcome, which is not country-specific, which was also an essential assumption in the BAPEN report (Elia et al., 2005).

Therefore international data on LOS were used in this analysis for a Dutch health economic evaluation of ONS.

The following data on LOS were reported in the BAPEN report, which is based on a 30% increase of LOS resulting from malnutrition: Age of population The base case analysis was based on a LOS of 8 days, based on the above mentioned international study, which included Dutch patients, whereas the 30% increase of LOS resulting from malnutrition was derived from the BAPEN report.

PROPRIETARY AND CONFIDENTIAL

The use of ONS would lead to an annual cost saving of € 40.4 million based on 160,283 abdominal procedures per year.

A scenario analysis was based on LOS of 12.9 days according to Prismant data [START_REF] Prismant | Data on number of hospitalisations and length of stay[END_REF]. In this analysis the use of ONS reduces the costs from € 5,350 to € 4,931, which corresponds with a € 419 (7.8%) cost saving per patient.

Sensitivity analysis

The results of the sensitivity analyses are presented in Table 2. These results show that the use of ONS in all sensitivity analyses remains cost saving compared with "no use" of ONS.

Threshold analysis

Threshold analyses were performed in order to calculate the break even point for LOS and risk reduction at which the total costs for both treatment strategies are equal.

The first threshold analysis was performed on LOS. This analysis shows that the threshold for LOSis only 0.64 days. This value can be considered an unrealisticac value compared with the actual length of stay in the UK. This would mean that even at a LOS of 1 day, the use of ONS is still cost-effective. As abdominal surgery requires at least two days of hospitalisation, this threshold analysis shows that the cost-effectiveness of ONS does not depend on local Dutch data on LOS. The second threshold analysis was performed on the increase of LOS for patients with malnutrition. This analysis shows that the threshold for the increase of LOS in risk patients is only 2.7%. This value also can be considered unrealistically low compared with the increase of 30% LOS in the UK. Therefore this threshold analysis shows that the cost-effectiveness of ONS does not depend on local Dutch data on reduction of LOS.

DISCUSSION

An analysis was performed for the use of ONS, being a medical nutrition product, in abdominal surgery in order to assess the health economic impact in The Netherlands. The rational for performing this health economic analysis in abdominal surgery is that this is the most studied indication. The assumption of this study was that there were no clinical differences between the treatment arms, except for LOS. We have shown that the use of ONS is cost-effective, because:

PROPRIETARY AND CONFIDENTIAL 1) Total costs for treatment with ONS are not higher than a treatment strategy without ONS:

the additional costs for ONS are more than balanced by a reduction in hospitalisation costs due to a reduction in length of stay.

2) The analysis is based on similar clinical properties for both treatment strategies. However, the use of ONS is associated with a higher effectiveness, as this treatment leads to a reduction of the LOS.

Consequently, the use of ONS yields at least a similar effectiveness without extra costs and therefore can be considered cost-effective (position 1 in Figure 2). Even if we assume that there is no gain in effectiveness, the use of ONS remains cost-effective, as similar effectiveness is provided at lower costs. The results of this health economic analysis show that the use of ONS leads to lower treatment costs per patient and therefore can be considered cost-effective. The assumption for this health economic analysis is that there is no difference in mortality, complications and Quality of Life between the use of ONS, in this case ONS, versus "no use" of ONS in patients undergoing abdominal surgery. This is a conservative assumption towards the use of ONS, because meta-analyses show a reduction in mortality, complications and an improvement in Quality of Life (www.snellerbeter.nl, 2008;Elia et al., 2005;[START_REF] Stratton | Elucidating effective ways to identify and treat malnutrition[END_REF]. The real economic benefits for the use of ONS are therefore in fact higher than could be calculated with the current data set. A reduction of complications contributes considerably to a reduction in LOS and therefore would lower the costs. However we could not use these data in our model due to the fact that these outcomes for the studied patient group were not the primary ones. Indirect costs due to productivity loss were not included in this analysis. This is a conservative assumption towards the use of ONS, because the lower length of stay would lead to lower indirect costs. On the other hand, a substantial proportion of patients undergoing abdominal surgery may be retired. We may also expect that the use of ONS in fact leads to cost savings in other health care budgets: fewer complications during hospitalisations will also lead to fewer follow-up costs (readmissions, consultations, medication) [START_REF] Gariballa | A randomized double-blind placebo-controlled trial of nutritional supplementation during acute illness[END_REF]. Therefore we may conclude that this health economic is based on conservative assumptions for the use of ONS.

Sensitivity analyses were performed on all parameters, including length of stay and per diem costs. The results showed hat the use of ONS in all sensitivity analyses remains cost saving compared to "no use" of ONS.

PROPRIETARY AND CONFIDENTIAL


Otto Mayer
email: mayero@fnplzen.cz

Jan Filipovský

Markéta Galovcová

Jan Bruthans

Jana Hrbková

Jindra Vrzalová

Renata Cífková

Jaroslav Šimon

PhD Assoc Md

Professor

AN INVERSE ASSOCIATION BETWEEN SERUM LEPTIN CONCENTRATION AND REPORTED ALCOHOL INTAKE IN PATIENTS WITH MANIFEST VASCULAR DISEASE

Keywords: leptin, alcohol intake, coronary heart disease, stroke, secondary prevention, EUROASPIRE

Background/Objectives: It has been reported that alcohol stimulates appetite. We aimed to establish the association between leptin, as a major food intake regulating factor, and alcohol intake in patients with chronic manifest coronary artery or cerebrovascular disease.

Subjects/Methods:

A cross-sectional study of 820 subjects after acute coronary syndrome, coronary revascularisation or after first ischemic stroke. (Czech part of EUROASPIRE III surveys). Leptin concentrations were evaluated among predefined categories of reported weekly alcohol intake: abstainers, light drinkers (up to 2 drinks weekly, 1-44 g of pure alcohol), mild regular drinkers (3-14 drinks weekly, 45-308 g) and moderate or heavy drinkers (more than 15 drinks, ≥ 309 g of alcohol).

Results:

The leptin showed a clear negative trend among alcohol intake categories. Mild regular drinkers showed significantly lower leptin [9.3(8.2)ng/mL], than abstainers [18.7(18.7) ng/mL, p<0.0001] and than light occasional drinkers [14.2(17.8) ng/mL, p=0.00064]. The negative association between leptin and alcohol intake as dependent variable remained significant even after adjustment for potential confounders in multiple linear regression [p=0.00032].

Conclusions: Drinking of small amounts of alcohol was in our setting associated with decreased serum leptin concentration, with possible benefit in terms of cardiovascular risk.

Introduction

Leptin is a polypeptide hormone, secreted mainly from adipocytes (and from gastric mucosa and placenta as well) as a product of the "obese" (ob) gene and is primarily biologically active in hypothalamus [START_REF] Zhang | Positional cloning of the mouse obese gene and its human homologue[END_REF][START_REF] Schwartz | Identification of targets of leptin action in rat hypothalamus[END_REF]. The endogenous leptin is known as major regulatory factor of appetite and food intake. Administration of leptin reduces feeding and body weight and increases energy expediture [START_REF] Schwartz | Identification of targets of leptin action in rat hypothalamus[END_REF][START_REF] Pelleymounter | Effects of the obese gene product on body weight regulation in ob/ob mice[END_REF] while paradoxically, obese subject showed high expession of leptin mRNA in adipose tissue and increased concentrations of leptin in systemic circulation [START_REF] Considine | Serum immunoreactive-leptin concentrations in normal-weight and obese humans[END_REF], probably because of phenomena known as "leptin resistance". The possibility that increased leptin levels might be relevant to many aspects of cardiac and vascular regulation has been raised, suggesting, that leptin promotes athero-trombotic processes involved in the pathophysiology of vascular diseases [START_REF] Bodary | Effect of leptin on arterial thrombosis following vascular injury in mice[END_REF][START_REF] Bouloumie | Leptin induces oxidative stress in human endothelial cells[END_REF][START_REF] Donahue | Is fasting leptin associated with insulin resistance among nondiabetic individuals?: The Miami Community Health Study[END_REF][START_REF] Soderberg | Plasma leptin levels are associated with abnormal fibrinolysis in men and postmenopausal women[END_REF][START_REF] Singhal | Influence of leptin on arterial distensibility: a novel link between obesity and cardiovascular disease?[END_REF][START_REF] Bullo | Systemic inflammation, adipose tissue tumor necrosis factor, and leptin expression[END_REF].

Alcohol has been recognized for centuries as an appetizer, but the interaction between alcohol and leptin has not been well understood and infrequent studies showed equivocal results. In this study we aimed to establish the relation between alcohol intake and serum leptin concentration in the pattern of chronic non-excessive mild drinking.

Methods

The present study represents a cross-sectional analysis. The study population consisted from pooled samples of two surveys of patients with stabilized manifest coronary heart disease (CHD) or after first ischemic stroke. CHD patients were examined in 2006-7 as Czech part of EUROASPIRE III survey. The sample selection and standard protocol of examination were in details described elsewhere [START_REF] Mayer O Jr | The quality of secondary prevention of coronary heart disease in Czech patients in the EUROASPIRE III survey[END_REF]. Briefly, patients aged ≤80 years hospitalized for any of following discharge diagnosis were retrospectively identified from hospital records: first coronary bypass graft (CABG), first percutaneous transluminal coronary angioplasty (PTCA) and acute myocardial infarction or ischemia. Recruitment of patients started with most recent hospital record and proceeded backwards until the required sample of 600 subjects was achieved. The interview of patients was done 6-24 months after the index event (coronary event or revascularisation) The stroke patients were examined in 2007 as Czech part of EUROASPIRE III-stroke survey and again, the sample selection and standard protocol of examination were in details described elsewhere [START_REF] Bruthans | The standards of secondary of stroke in Czech patients in the EUROASPIRE III study-stroke specific module[END_REF]. A total of 507 consecutive patients aged≤80 years hospitalized for first ischemic stroke were selected and the responders were interviewed 6-36 months after the event. Both surveys were conducted in same two centers in Czech Republic: University Hospital Pilsen and Cardio-Centre of Institute of Clinical and Experimental Medicine in Prague.

The standard protocol of EUROASPIRE survey was followed, as described elsewhere [START_REF] Kotseva | EUROASPIRE Study EUROASPIRE III: a survey on the lifestyle, risk factors and use of cardioprotective drug therapies in coronary patients from 22 European countries. Group[END_REF]. Briefly, patients were interviewed at least 6 months after their index event. Information on personal and demographic characteristics, personal and family history of coronary heart disease, life-style and pharmacotherapy were obtained. Following standardized examinations were performed: Height and weight were measured in light indoor clothes without shoes using SECA 220 scales and measuring sticks. Waist circumference was measured using tape measure. Blood pressure (BP) was measured twice in the sitting position on the right arm using standard mercury sphygmomanometer. Breath carbon monoxide was measured by Smokerlyser (model EC 50, Bedfont Scientific, U.K). Venous blood samples were drawn after at least 12 hours of overnight fast. All laboratory examinations were done in series from aliquots stored at -80 degrees by use of commercial kits and included: estimation of total (TCHOL) and HDL cholesterol (HDL), using ARCHITECT c800 analyser (Abbott Laboratoires, Germany) and DOT Diagnostics kits (Czech Republic), while triglycerides (TG) and glucose (GLU) using the same analyser and Abbott Laboratoires standard kits. HbA1c (glycohaemoglobin) was estimated using by ionex liquid chromatography using G7 analyser (TOSOH, Japan), while serum leptin and insulin using commercial radioimmunoassay kits (Millipore-Linco Reseach, USA). Weekly alcohol intake was assessed by one week follow-back (a questionnaire used for INTERSALT study (Elliot &Stamler, 1988)) and the subjects were asked, whether it is their typical alcohol intake (if not, the correction was done using typical week). The total weekly alcohol intake was calculated as follows: one beer 12 o (half liter) 22 g, one beer 10 o 20.5 g, one glass of wine (two deciliters) 22 g, one large glass of spirit (half of deciliter) 20g and one small glass of spirit (0.2 of deciliter) 8g of pure alcohol. The whole sample was categorized by reported weekly alcohol intake into abstainers, light irregular drinkers (1-44 g of pure alcohol weekly), mild regular drinkers (45-308 g) and moderate or heavy drinkers (≥ 309 g).

Statistical analysis was done using software STATISTICA 8. All data were stored under the provisions of the Czech data protection act. The whole study was carried under Good Clinical Practice regulations, the study protocol was approved by local Ethical Committee and all study participants signed the Informed consent form.

Results

A total of 820 vascular patients, 479 with manifest coronary heart disease and 341 after first ischemic stroke were analyzed in the present study. The baseline characteristics of pooled data and separately for CHD and stroke patients are given on table 1. Patients after stroke were significantly older and were more often female than CHD patients. Stroke patients showed in average higher heart rate, total, LDL, HDL cholesterol and serum leptin, while lower waist to hip ratio and reported weekly alcohol intake. Stroke patients were also less often treated with betablockers and statins, while more often with thiazide diuretics.

The association between alcohol intake categories and large set of risk factors or characteristics are given on table 2; the statistical differences were tested between mild regular drinkers (category III) against all three other categories. Comparing mild regular drinkers with abstainers, the latter were older, more often females, showed higher total cholesterol, HDL, LDL and HbA1c, whereas they were less often treated with betablockers and statins.

Serum leptin concentrations significantly decreased with increasing alcohol intake among defined categories (table 2 andfigure 1). The Spearman´ s coefficient for correlation between leptin and weekly alcohol intake was -0.32 (p<0.0001). The independency of association between leptin and alcohol intake was tested by multiple linear regression (table 3). Using weekly alcohol intake as dependent continuous variable, leptin concentration entered significantly negatively the regression as independent variable, also after adjustment for conventional risk factors as potential confounders. Moreover, age, gender, body mass index and waist circumference were identified as significant predictors in this setting. The second regression model (not shown in the table section) consisted from alcohol intake as dependent variable, and age, gender, leptin and concomitant treatments (i.e. betablockers, angiotensinconverting enzyme inhibitors or angiotensin II blockers, thiazide diuretics, statins and antidiabetics). Any concomitant treatment did not enter this regression as significant confounding factor. Table 4 expressed the leptin concentration by alcohol intake categories among pre-specified subgroups of risk factors and characteristics. The majority of these factors themselves influenced leptin significantly (first column), however the overall negative trend in leptin concentration among alcohol intake categories remained statistically significant in all subgroups. The effect of alcohol intake on leptin levels were significantly more pronounced in obese subjects than in non-obese and more in females than in males (last column, table 4).

Discussion

In our study we found a clear, highly statistically significant and independent negative association between serum leptin concentrations and reported weekly alcohol intake. The association remained statistically significant even after adjustment for potential confounders, namely body constitution, glucose metabolism and current smoking. Our study sample consisted of middle aged and elderly patients, with stable manifest vascular disease and rather non-excessive drinking habits. The whole intake of alcohol (if any) resulted generally from regular drinking of small amounts of alcohol, nobody tended to binge drinking habit. The maximal individual reported alcohol intake was 792 g of alcohol weekly, i.e. 36 alcoholic drinks (beers) weekly (or ca. 5 daily). The stroke patient showed significantly lower alcohol consumption than cardiac patients, probably because of higher age and seriousness of comorbidities.

The effect of alcohol on leptin as major appetite regulating factor is not well understood and remains to be elucidated in detail. Alcohol is often taken before meal as an aperitif. It has been reported [START_REF] Hetherington | Stimulation of appetite by alcohol[END_REF]) that an alcoholic beverage taken before the meal had a stimulatory effect on food intake and increased the energy intake by 30%. Chronic alcoholics showed low leptin concentrations [START_REF] Santolaria | Low serum leptin levels and malnutrition in chronic alcohol misusers hospitalized by somatic complications[END_REF], probably because of frequent chronic malnutrition leading to reduced fat tissue mass (as primary organ of leptin synthesis). Leptin also positively correlate with alcohol-craving in patients admitted for detoxification treatment [START_REF] Hillemacher | Evidence of an association of leptin serum levels and craving in alcohol dependence[END_REF]. The interaction between alcohol and leptin on background of only non-excessive chronic alcohol drinking is probably more complex and relative sparse studies of this association showed equivocal results. One interventional study [START_REF] Djurovic | The effect of red wine on plasma leptin levels and vasoactive factors from adipose tissue: a randomized crossover trial[END_REF] reported that a three-week regular intake of one glass of red wine per day increased leptin levels by about 17%, but only in females. Recent general populationbased cross sectional study [START_REF] Marques-Vidal | Distribution of plasma levels of adiponectin and leptin in an adult Caucasian population[END_REF] did not find any significant association between alcohol intake and leptin levels, confirming similar conclusion of two other reports [START_REF] Lagiou | Hormonal, lifestyle, and dietary factors in relation to leptin among elderly men[END_REF], Pischon et al., 2009). On the contrary, an interventional study [START_REF] Röjdmark | Alcohol ingestion decreases both diurnal and nocturnal secretion of leptin in healthy individuals[END_REF] observed in healthy subjects that acute intake of ethanol (0.45 g/ kg, 3 doses, 2 hours apart) inhibited the leptin secretion. Similar study (Otaka et al., 2008) reported that serum leptin significantly decreased in rats 3-6 hours after alcohol ingestion, while gastric levels remained unaffected and leptin concentration in fat tissue significantly increased. This study suggested that decreased serum leptin after alcohol administration might be due to suppression of leptin secretion from adipose tissue into systemic circulation. Our study is in line with these two reports, confirming its conclusions in the subjects with chronic, non-excessive drinking on mild alcohol amounts. The proportion of "more-than-mild" drinkers was in our sample rather low (only 5.1% of sample) and this is probably the reason why the difference in leptin concentration between mild and heavy drinkers did no reach statistical significance (in spite of the clear negative trend).

We may only speculate about pathophysiological mechanism of observed alcohol-leptin interaction. Leptin expression is modulated by several factors, including glucocorticoids, insulin, serotonin which stimulate leptin release, and catecholamines, which inhibit it [START_REF] Fruhbeck | Leptin: physiology and pathophysiology[END_REF][START_REF] Donahoo | Eckel RH Isoproterenol and somatostatin decrease plasma leptin in humans: a novel mechanism regulating leptin secretion[END_REF]. A plausible hypothesis is that alcohol suppressed leptin release from adipose tissue into systemic circulation via increased release of catecholamines. Several indirect mechanisms are also feasible. It is evident that insulin stimulates leptin secretion [START_REF] Malmström | Insulin increases plasma leptin concentrations in normal subjects and patients with NIDDM[END_REF] and that alcohol-drinkers show lower insulinaemia and glucose concentrations [START_REF] Röjdmark | Alcohol ingestion decreases both diurnal and nocturnal secretion of leptin in healthy individuals[END_REF](Röjdmark et al., , Šimon et al., 1997)).

However, in our study abstainers did not show any differences in insulin, glucose or HOMA index, despite their leptin concentration was almost doubled than in mild regular drinkers. This is in accordance with the above mentioned study, showing no changes in insulin in connection with acute alcohol intake (and leptin decrease as well) [START_REF] Röjdmark | Effect of verapamil on insulin response to alcohol hypoglycemia in patients with primary hyperparathyroidism[END_REF].

Because beer was the most common alcoholic beverage, we may also speculate, that observed negative trend in leptin among increased alcohol intake also depends on type of alcoholic beverage. Xantohumol, a compound from beer hops (Humulus lupulus) lowered in mice (beside plasma glucose and triglycerides) the mass of adipose tissue and increased levels of plasma adiponectin (Nozawa et al., 2008), both with very close metabolic relation to leptin concentration. The prevailed type of alcoholic beverage could also be the source of equivocal results of existing alcohol-leptin association studies. Unfortunately, we cannot test this hypothesis since the sample of patients drinking other beverages than beer is very limited.

The crucial question remains whether markedly lower leptin concentration, observed in mild regular drinkers, represents any benefit in terms of individual cardiovascular risk. It is well evident that drinking of mild amounts of alcohol was associated with lower cardiovascular mortality (Keil et al., 2008) in general population, but whether the same holds true for cardiovascular patients and whether leptin plays any role in this causality is not clear. In our setting, subjects with regular drinking habit showed slightly lower body mass index than abstainers. This is a paradox because the majority of alcohol intake was covered by beer (a rather high-caloric beverage). On the other hand, we found a significant positive association of alcohol intake with waist circumference (table 3). This pattern, i.e. (sub)standard BMI, while increased waist circumference ("beer belly" with slim leg) was typically associated with alcohol consumption in several epidemiological studies [START_REF] Filipovský | Abdominal body mass distribution and elevated blood pressure are associated with increased risk of death from cardiovascular diseases and cancer in middle-aged men. The results of a 15-20-year follow-up in the Paris prospective study I[END_REF]. Mild regular alcohol drinkers showed also significantly lower HbA1C levels than abstainers, which could also be hypothetically accounted for by low leptin concentrations. In contrast, in our setting we did not observe usual positive association between alcohol and HDL cholesterol. The possible explanation is very frequent statin treatment (about 70%) "masking" this probably only very slight HDL increase. The more favorable lipid profile of mild drinkers could also be probably explained better by more frequent lipid-lowering treatment than by effect of alcohol itself. Several clinical and experimental studies suggested that leptin promotes atherosclerosis and thrombosis and reported positive associations with established vascular risk factors, such as lipids, blood pressure [START_REF] Donahue | Is fasting leptin associated with insulin resistance among nondiabetic individuals?: The Miami Community Health Study[END_REF], impaired fibrinolysis or prothrombotic status [START_REF] Soderberg | Plasma leptin levels are associated with abnormal fibrinolysis in men and postmenopausal women[END_REF], endothelial dysfunction or increased vessel wall stiffness [START_REF] Bouloumie | Leptin induces oxidative stress in human endothelial cells[END_REF][START_REF] Singhal | Influence of leptin on arterial distensibility: a novel link between obesity and cardiovascular disease?[END_REF], and inflammation [START_REF] Bullo | Systemic inflammation, adipose tissue tumor necrosis factor, and leptin expression[END_REF]. Particular attention is given to possible role of leptin in pathophysiology of type II diabetes and pre-diabetic disorders [START_REF] Leyva | Hyperleptinemia as a component of a metabolic syndrome of cardiovascular risk[END_REF][START_REF] Zimmet | Is there a relationship between leptin and insulin sensitivity independent of obesity? A population-based study in the Indian Ocean nation of Mauritius. Mauritius NCD Study Group[END_REF]. Studies dealing with leptin and incident vascular disease are relatively sparse and heterogenous. Systematic review of 7 prospective studies [START_REF] Sattar | Leptin and coronary heart disease: prospective study and systematic review[END_REF] reported that adjusted risk ratio of CHD among subject with leptin in the top tertile was 1.44, however, it did not reach statistical significance. The authors suggest that the association between leptin and CHD risk is largely dependent on BMI. Thus, the causality of leptin in vascular diseases etiology remains to be elucidated in detail.

Our study has several limitations. Namely, the estimated ethanol intake is based on reported amounts of alcohol drinks and only during one week time-frame (moreover, we asked, whether the reported alcohol intake is the typical one), however similar limitation had probably the majority of epidemiological studies. Nobody showed an excessive increase in gama-glutaryl transferase. Thus, we can presume that reported alcohol intake is generally correct. Our study sample consisted from very specific population of middle-aged or elderly patients with stable manifest vascular diseases and the whole distribution of alcohol intake markedly differed from general population. The usual recommendations for secondary prevention of vascular diseases is to tolerate (but not to encourage) the voluntary intake of mild amounts of alcohol (up to 2 drinks daily) and ca 95% of our subjects was compliant with this rule. Therefore, in contrast to usual standards, the category of light occasional drinkers was taken into account separately. These subjects reported alcohol intake up to 2 drinks weekly (usually during weekend) and we wanted to test whether such a low intake may also play a role in their risk profile. Indeed, their average leptin concentration was between abstainers and mild drinkers.

In conclusion, in our study we found that leptin concentration showed a clear negative trend among alcohol intake categories in vascular disease patients. Whether rather low levels of leptin in subjects with regular mild intake of alcohol represents any benefit in terms of their cardiovascular risk remains to be solved.

Acknowledgement

The present study was founded by Internal Grant Agency of Czech Ministry of Health (grant no. 9333-3) and by Ministry of Education (grant no. 0021620819). We also used several data from EUROASPIRE III and EUROASPIRE III-stroke surveys; we would like to acknowledge the cooperation of all investigators who participated on the EUROASPIRE surveys in the Czech Republic. 8.5 (4.2) 13.9 (13.5) 8.8 (8.0) 9.4 (8.2) 14.5 (9.9) 6.8 (5.8) 14.5 (9.9) 6.8 (5.8) 10.4 (8.3) 8.7 (8.1) 8.5 (7.3) 11.0 (9.7) 8.1 (7.3) 6.6 (4.4) 7.8 (6.9) 5.7 (1.5) 5.6 (0.9) 8.4 (7.5) 9.9 (4.4) 6.6 (7.4) 9.9 (4.4) 6.6 (7.4) 6.9 (4.8) 8.1 (7.9) 7.2 (6.8) 9.5 (6.

Figure legend Figure 1 :

 legend1 Figure legend

Table 1 .

 1 Baseline characteristics of study sample [mean (standard deviation) or factor proportion]

	pooled data	CHD patients stroke patients	p

Table 2 .

 2 The association between categorized weekly alcohol intake and conventional risk factors, glucose metabolism parameters and treatment used.

	alcohol intake	I.	II.	III.	IV.	p 1	p 2	p 3
	categories:	abstainers	light occasional	mild regular	moderate or
			drinkers	drinkers	heavy drinkers	III.vs.I	III. vs. II.	III. vs. IV.
	[weekly alcohol intake]	[0 g]	[1-44 g]	[45-308 g]	[≥ 309 g]
	n	360	138	280	42	-	-	-
	age	67.2 (9.27)	64.9 (8.72)	64.1 (9.27)	59.0 (8.05)	<0.0002	0.54	<0.001
	gender [% of males]	55.3	73.2	84.9	92.9	<0.0001	<0.005	0.17
	current smoking [%]	16.9	15.9	21.1	26.2	0.18	0.21	0.45
	body mass index	29.7 (5.18)	29.5 (4.64)	28.7 (4.42)	29.0 (3.68)	<0.03	0.08	0.51
	waist circumference	100.5 (12.2)	102.5 (13.0)	101.7 (12.4)	103.2 (9.29)	0.23	0.61	0.29
	systolic BP	136.2 (18.9)	138.3 (18.5)	136.1 (16.7)	135.0 (17.1)	0.76	0.25	0.78
	diastolic BP	79.4 (10.0)	81.5 (10.6)	80.7 (10.0)	82.1 (9.4)	<0.04	0.73	0.42
	heart rate	69.6 (11.8)	66.3 (12.9)	66.5 (11.5)	68.0 (8.3)	<0.002	0.97	0.18
	total cholesterol	4.95 (1.41)	4.76 (1.15)	4.68 (1.1)	4.91 (1.19)	<0.02	0.60	0.17
	HDL-cholesterol	1.26 (0.38)	1.22 (0.37)	1.20 (0.36)	1.26 (0.29)	<0.03	0.59	0.13
	LDL-cholesterol	2.97 (1.02)	2.79 (0.91)	2.78 (0.94)	2.91 (0.92)	<0.03	0.66	0.27
	triglycerides	1.72 (2.20)	1.72 (1.08)	1.67 (0.88)	1.77 (1.16)	0.50	0.85	0.78
	fasting glycaemia	7.02 (2.90)	7.13 (2.88)	6.58 (2.88)	6.58 (1.86)	0.97	0.59	0.63
	fasting insulinemia	13.8 (10.7)	17.0 (32.3)	12.9 (9.5)	11.7 (7.5)	0.30	0.11	0.49
	HBA1 C	4.75 (1.49)	4.80 (1.67)	4.38 (0.84)	3.98 (1.25)	<0.03	0.34	0.17
	HOMA index	4.53 (4.68)	5.34 (7.12)	3.92 (3.40)	3.58 (2.65)	0.17	0.09	0.58
	γ-GT	0.73 (1.56)	0.85 (1.35)	0.94 (0.59)	1.84 (2.36)	0.13	0.28	0.08
	serum leptin	18.7 (18.7)	14.2 (17.8)	9.3 (8.2)	7.7 (6.7)	<0.0001	<0.0006	0.19
	Betablockers	63.9	76.1	74.6	73.8	<0.004	0.75	0.91
	ACEi or ARBs	71.4	76.1	71.4	76.2	0.99	0.32	0.52
	Thiazide diuretics	19.4	18.8	16.4	16.7	0.33	0.54	0.97
	Statins	64.4	72.5	76.8	69.0	<0.0008	0.34	0.28
	Antidiabetics	22.2	21.7	20.4	16.7	0.57	0.74	0.58
	Mean (standard deviation) or factor proportion are given; p values calculated by Mann-Whitney U test or Χ 2* test (for categorical variables)

Table 3 .

 3 Multivariate association between weekly alcohol intake as dependent variable, leptin and conventional risk factor as potential confounders in multiple linear regression.

		β coefficient (SE of β) odds ratio (95% CI)	p
	age	-0.127 (0.036)	0.88 (0.82-0.95)	<0.0004
	gender	0.136 (0.038)	1.15 (1.06-1.23)	<0.0005
	current smoking	0.038 (0.034)	1.04 (0.97-1.11)	0.26
	body mass index	-0.154 (0.059)	0.86 (0.76-0.96)	<0.01
	waist circumference	0.209 (0.057)	1.23 (1.10-1.38)	<0.0003
	systolic blood pressure	0.032 (0.034)	1.03 (0.97-1.10)	0.35
	LDL-cholesterol	0.025 (0.035)	1.03 (0.96-1.10)	0.47
	fasting glycaemia	-0.046 (0.038)	0.96 (0.89-1.03)	0.23
	HOMA index	-0.050 (0.041)	0.95 (0.88-1.03)	0.22
	serum leptin	-0.145 (0.040)	0.87 (0.80-0.94)	<0.0004
	SE, standard error; CI, confidence intervals

Table 4 .

 4 Leptin concentrations by alcohol intake categories among subgroups by potential confouders

	alcohol intake	full sample	abstainers	light occasional	mild regular	moderate or	p for	p for
	categories:			drinkers	drinkers	heavy drinkers	trend 1	interaction 2
	[weekly alcohol intake]		[0 g]	[1-44 g]	[45-308 g]	[≥ 309 g]
	age
	> 50 years	14.4 (16.2)	19.0 (19.2)	13.7 (17.8)	9.6 (8.6)
	≤ 50 years	11.8 (11.7)	16.6 (16.2)	16.0 (17.9)	7.8 (5.3)
	gender
	males	10.8 (12.4)	13.2 (14.0)	12.8 (19.0)
	females	22.1 (19.6) ***	25.5 (21.3)	17.7 (13.6)
	current smoking
	smokers	14.7 (16.4)	14.8 (15.7)	10.5 (7.3)
	non-smokers	11.1 (11.8) **	19.5 (11.1)	14.9 (19.1)
	body mass index
	≥ 30 kg/m 2	21.8 (19.4)	27.9 (22.8)	19.6 (17.4)
	< 30 kg/m 2	9.4 (10.6) ***	11.6 (10.5)	10.6 (17.1)
	waist circumference
	≥ 102 m or 88 f cm	18.4 (17.3)	23.4 (20.8)	16.5 (15.6)
	< 102 m or 88 f cm	8.3 (11.1) ***	10.9 (11.0)	10.6 (20.2)
	diabetes mellitus
	present	15.2 (17.4)	19.5 (18.9)	14.9 (23.4)
	absent	13.4 (14.6)	18.2 (18.6)	13.5 (12.0)
	inclusion diagnosis
	coronary heart disease	12.2 (12.8)	17.2 (16.0)	13.6 (14.8)
	stroke	16.7 (18.8)	19.9 (20.6)	15.3 (23.1)


Simone A Johner
email: johner@fke-do.de

Master Lars Libuda

Dr. Lijie Shi

Master Anne Retzlaff

Master Gesa Joslowski

Master Thomas Remer

Urinary fructose: a potential biomarker for dietary fructose intake in children

Keywords: urine, fructose, biomarker, sugar intake, children

Background/Objectives: Recently, urinary fructose and sucrose excretion in 24-h urine have been established experimentally as new biomarkers for dietary sugar intake in adults. Our objective was to investigate 1) whether the fructose biomarker is also applicable in free-living children and 2) for what kind of sugar it is standing for.

Subjects/Methods: Intakes of added and total sugar (including additional sugar from fruit and fruit juices) were assessed by 3-day weighed dietary records in 114 healthy prepubertal children, corresponding 24-h urinary fructose excretion was measured photometrically. The associations between dietary sugar intakes and 10 urinary fructose excretion were examined by using linear regression models. To determine whether one of the two sugar variables may be better associated with the urinary biomarker, the statistical Pitman's test was used.

Results: Added and total sugar correlated significantly with urinary fructose, but the linear regression indicated a weak association between intake of added sugar and urinary log-fructose excretion (β=0.0026, R 2 =0.055, P=0.01). The association between total sugar intake and log-urinary fructose (β=0.0040, R 2 =0.181, P<0.001) showed a significantly better fit (P<0.05).

Conclusions: Urinary fructose excretion seems rather applicable for the estimation of total than of added dietary sugar intake in children. However, since excreted 20 fructose stems almost exclusively from the diet (both from food-intrinsic and added intakes), it can be assumed that urinary fructose represents a potential biomarker for total dietary fructose intake, irrespective of its source.

Introduction

Even though extensively researched since several years, the discussion persists, whether a high dietary sugar intake is (amongst other factors) responsible for the ongoing epidemy of obesity and related cardiovascular diseases [START_REF] Johnson | 10 Potential role of sugar (fructose) in the epidemic of hypertension, obesity and the metabolic syndrome, diabetes, kidney disease, and cardiovascular disease[END_REF]. The term sugar comprises various mono-and disaccharides, that are considered to have different metabolic effects (Sigman-Grant et al., 2003;[START_REF] Englyst | Nutritional characterization and measurement of dietary carbohydrates[END_REF]. Currently, the focus lies on the monosaccharide fructose as a potential risk factor, due to its proposed dysregulating effects on glucose and lipid metabolism [START_REF] Angelopoulos | The effect of high-fructose corn syrup consumption on triglycerides and uric acid[END_REF][START_REF] Jones | Dietary sweeteners containing fructose: overview of a workshop on the state of the science[END_REF][START_REF] Libuda | Soft drinks and body weight development in childhood: is there a relationship?[END_REF]Stanhope et al., 2009). 10

Especially in the United States, this topic attracts rising attention, because of the constantly increasing fructose consumption (Vos et al., 2008).

The major difficulty in estimating dietary sugar intake for the analysis of metabolic effects of sugar, is the lack of a precise assessment method. So far, typically epidemiologic assessments (interviews, questionnaires or dietary records) were used, which are known to be prone to measurement errors, like intentional underreporting, subjective estimations instead of objective measurements or simple disremembering of foods [START_REF] Biro | Selection of methodology to assess food intake[END_REF]. To avoid these limitations the use of a biomarker for the estimation of dietary sugar intake would be generally preferred [START_REF] Jenab | Biomarkers in nutritional epidemiology: applications, needs and new horizons[END_REF], especially one that can differentiate between the various types 20 of sugar.

Recently, two new dietary biomarkers regarded as objective markers of sugar consumption in adults, have been introduced: urinary fructose and sucrose excretion (Tasevska et al., 2005). As neither fructose nor sucrose are synthesized endogenously, their urinary excretion has to be of dietary origin. The mechanism by which they end up in urine is not exactely known. It is proposed that a small amount of sucrose escapes from enzymatic hydrolysis in the small intestine, reaches general circulation and afterwards is excreted in the urine. Similarly, a small proportion of ingested fructose (derived from free fructose as well as from hydrolysis of sucrose) may escape from hepatic fructose metabolism and is excreted in the urine (Tasevska et al., 2009). The excreted amount is very small and mostly proportional to dietary sugar consumption.

These newly developed biomarkers have been supposed to better reflect extrinsic (i.e. added sugar) than intrinsic sugar (naturally contained in food) (Tasevska et al., 2009). This would allow to examine potential disease risks related to a high sugar consumption independently from the naturally occuring sugar in fruits. 10To verify whether the potential biomarker fructose excretion also provides an adequate estimate of dietary sugar intake in free-living children, we studied recorded dietary sugar intake and its association with the 24-h excretion of fructose in a sample of healthy prepubertal German children. A preliminary diet experiment in our institute (results are shown in the method section) yielded less reasonable excretion rates for sucrose compared to fructose, which was the reason to focus on the latter biomarker. Further, in order to characterize the fructose biomarker, we examined in our study in children whether various sugar sources -added and total sugar -are associated with urinary fructose excretion differently.

20

Methods and Materials

Preliminary diet experiment

To adapt the method of measuring urinary fructose and sucrose in our lab and to reproduce the applicability of these biomarkers for assessment of sugar intake we analysed fructose and sucrose excretion in 24-h urine samples collected in a 5-d diet experiment with acute dietary sucrose loads (for fructose and sucrose analytics see section urinary measurements). Nine healthy female adults (24 -59 y, BMI: 18.9 -28.4 kg/m 2 ) participated and ingested a constant diet with all foods weighed and prepared in the institute's own kitchen. Energy and protein intake were 1962 kcal in average and 66.5 g respectively and held constant throughout the whole 5-d period.

There was a 3-d run-in period to metabollically adapt to the lacto-vegetarian whole food basal study diet. The first intervention, consisting of 40 g sucrose, was administered with dinner on day 4, the second (80 g sucrose) with dinner on day 5.

To maintain a constant energy intake, olive oil included in the basal dinner was 10 isocalorically replaced with 40 g or 80 g sucrose. 24-h urine collections (each started immediately after lunch) were performed on day 3 (basal diet), day 4 (40 g sucrose) and day 5 (80 g sucrose). All micturitions of the 24-h collection periods were immediately stored in preservative-free, Extran-cleaned (Extran, MA03; Merck, Darmstadt, Germany) 1-L plastic containers at <-20 °C before the samples were thawed for 24-h urine volume determination and further measurements. No specific precautions were taken to avoid possible sucrose hydrolysis. Compliance with 24-h urine collection was ensured by a mean intra-individual variation of body weightrelated 24-h creatinine excretion rates <10%.

Figure 1 shows the results of the interventions for both urinary fructose and sucrose 20 excretions. There was a significant increase in log-sucrose excretion from basal diet to 40 g sucrose intervention, however no additional clear increase after 80 g sucrose intake. The urinary fructose excretion, in contrast, increased significantly and almost gradually with increasing sucrose intake. Due to the obvious lack of a consistent dose-response relationship between sucrose intake and sucrose excretion, which is similarly observable in other diet studies [START_REF] Luceri | Urinary excretion of sucrose and fructose as a predictor of sucrose[END_REF]Tasevska et al., 2005), we decided to specifically focus on 24-h fructose excretion as a potential biomarker in our examinations in children.

Subjects and study design

The study population for the examinations in children was selected from the Dortmund Nutritional and Anthropometric Longitudinally Designed (DONALD) Study.

The DONALD Study that started in 1985, is an ongoing longitudinal (open cohort) study gathering information about diet, development and metabolism between infancy and adulthood in healthy subjects [START_REF] Kroke | The DONALD Study. History, current status and future perspectives[END_REF]. The regular visits 10 begin at 3 months of age and take place annually from the age of 2 years until the age of 18 years. The regular assessments include three day weighed dietary records, 24-h urine collections and measurements of anthropometric data as well as interviews on lifestyle and medical assessments. The DONALD Study is exclusively observational, non-invasive (until the age of 18) and approved by the Ethics Committee of the University of Bonn (Germany). All examinations are performed with parental, and later on with the children's written consent.

In the present evaluation only children were enrolled who had a completely collected 24-h urine and parallel three day weighed dietary record (including the day of urine collection) one year before puberty initiation. Children and/or their parents were 20 interviewed regarding completeness of urine collection. Subjects with reported unknown losses and/or with body weight-related 24-h creatinine excretion rates <0.1 mmol⋅kg -1 ⋅d -1 were excluded. Plausibility of dietary records was estimated by calculating the ratio of reported total energy intake (EI) to predicted individual basal metabolic rate (BMR,estimated by the method of Schofield (Schofield, 1985)).

Dietary records with a ratio below the age-and sex-specific cut-off values (indicating underreporting) (Sichert-Hellert et al., 1998) were excluded. All EI:BMR ratios were below 2.0, indicating that no relevant overreporting existed [START_REF] Johansson | Under-and overreporting of energy intake related to weight status and lifestyle in a nationwide sample[END_REF].

The timing of the onset of the pubertal growth spurt (age at takeoff, ATO) was used as a marker for the initiation of puberty. ATO was estimated based on subjects' individual growth curves by using the parametric Preece and Baines model (Preece et al., 1978). This ensures that all investigated children were at same biological age and possible effects of beginning puberty could be excluded. ATO could be calculated for 376 children. After excluding those, who had incompletely collected 24-h urines and/or no parallel plausible dietary records before puberty onset, 114 children remained for the present analysis. 10

Dietary records

Three day weighed dietary records were used to estimate the individual food and nutrient intake. On three consecutive days the weight of all consumed food and beverages was recorded using a digital food scale to the nearest 1g. Out-of-home consumed food was estimated by semi-quantitative recording (e.g. numbers of glasses, cups). Energy and nutrient intakes, including food fortification and nutrition supplements, were calculated as individual means of the three recorded days by using our nutrient database LEBTAB (Sichert-Hellert et al., 2007). 20

In the present analysis we calculated the intake of added sugar and total sugar. Added sugar was defined as all refined sugar (e.g. sucrose, maltose, lactose, glucose, dextrin), including honey, eaten separately at the table or used as ingredients in processed or prepared foods. Total sugar was defined as the sum of added sugar and sugar derived from fruits and fruit juices. In the following we referred to sugar derived from fruit and fruit juices as intrinsic sugar.

Urinary measurements

The urine collection of the DONALD participants was generally carried out on the third day of the three day weighed dietary records. Procedures for the 24-h urine collection have been described previously (Remer et al., 2006) The micturitions were immediately frozen at <-20 °C (without preservative, in Extran-cleaned 1-L plastic containers) until transfer to the research institute by a dietitian (further storage at <-20 °C until analysis). Creatinine was measured by the Jaffé method with the use of a creatinine analyzer (Beckman-2; Beckman Instruments Inc, Fullerton, CA). Daily sucrose (diet experiment) and fructose (diet experiment and DONALD population) 10 excretions were measured in 24-h urines with a kit for the enzymatic analysis of sucrose, glucose, and fructose (Saccharose/D-Glucose/D-Fructose; Boehringer MANNHEIM, R-BIOPHARM, Darmstadt) using a spectrophotometer (PM2 DL, Zeiss) according to the assay instructions. During all measurement runs, the analyses were checked for potential side ("creep") reactions which -if occurred in the form of continuous unspecific absorbance increases -were considered as advised in the assay procedures. In case, the reactions did not stop in time, absorbances were continued to read until constant absorbance increases occurred and the corresponding readings were extrapolated to the time of addition of the respective enzyme suspensions. Limit of detection (LOD) was 0.4 mg/L and 2 mg/L for fructose 20 and sucrose, respectively. Intra-and interassay precision were below 4% (8%) and 10% (13%), for fructose (sucrose), respectively. All runs were performed as duplicates with a maximum deviation of duplicates of 15%.

Statistical anlysis

As urinary fructose excretion was skewed it was log 10 transformed and given as geometric mean with 95 % confidence interval. All other investigated variables were normally distributed and presented as means ± S.D.. Sex differences were tested with an unpaired t test.

Analysis of the association between dietary sugar intake and urinary fructose excretion was performed by linear regression models. Log values of urinary fructose were included as dependet variable, and concomitant data of either added or total sugar, were investigated as independent variables. In a further regression model, 10 added sugar and intrinsic sugar together were included as predictor variables for urinary fructose excretion. None of the potential confounding factors age, sex, BMI, urine volume and energy intake showed a significant association with the urinary fructose excretion. Thus, aside from the dietary sugar intake no other independent variables were included into the regression model.

Pitman's test (Snedecor et al., 1987) was used to determine which of the two dietary sugar variables (i.e. added sugar or total sugar) provided a better estimation of urinary fructose excretion. Residuals of the regressions of the criterion variable (urinary fructose) with both estimation models (added and total sugar) were calculated (residuals A and B). Then the correlation of the sum (A + B) and the 20 difference (A -B) was examined. If this correlation differed significantly from zero, the residual with the smaller S.D. was the model with better fit.

Significance was defined as P<0.05. All calculations were performed with SAS procedures (version 9.1.3, SAS Institute, Cary, NC, USA). 1. The average age of the girls was about 1.5 years lower than of the boys due to the physiologic earlier onset of puberty in females. Anthropometric values (except BMI) and energy intake differed significantly by sex, however no differences were observed in dietary sugar intake and urinary fructose excretion between boys and girls.

Results

Characteristics of the study population are presented in Table

Dietary added sugar intake showed a significant association with urinary fructose excretion (Table 2), both R 2 and the correlation plot (Figure 2) indicated that the relationship was weak. When including total sugar intake as independent variable 10 instead of added sugar, R 2 and β value increased. The Pitman test yielded significantly smaller S.D. of the residuals for the regression of total sugar intake on urinary fructose excretion when compared with added sugar intake. Therefore the association between total sugar intake and urinary fructose excretion has been proven as the one with a significantly better fit .

According to the regression equation, an 1-g increase of total sugar intake predicted an increase in log-fructose excretion by 0.004, which is equivalent to a 0.9 % increase of absolut fructose excretion.

In a separate regression model, the predictor variable total sugar intake for fructose excretion was divided into its two components added sugar and intrinsic sugar 20 (Table 2). Both variables showed a significant association with urinary fructose excretion, whereby the intrinsic sugar intake explained a higher proportion of the variability of fructose excretion (part. R 2 = 15.3%) than did added sugar intake (part. R 2 = 5.5%).

Discussion

The results of our study in healthy children, extend the findings of Tasevska et al.

and [START_REF] Luceri | Urinary excretion of sucrose and fructose as a predictor of sucrose[END_REF]Tasevska et al., 2005;Tasevska et al., 2009) in adults, indicating that urinary fructose excretion may be used as a biomarker for sugar intake also during the growing years (at least until the begin of puberty).

Furthermore, the data in children (who almost all consumed mixed, fruit-containing diets) show that urinary fructose can be significantly stronger associated with total sugar than with added sugar consumption. This and the facts that (1st) both components of total dietary sugar intake, i.e., added sugar and natural sugar contain 10 considerable amounts of fructose and (2nd) almost all of the urinary excreted fructose originates from diet, led us to the suggestion that 24-h urinary fructose excretion rather reflects total fructose consumption and may thus be an appropriate biomarker for it. This is also indirectly confirmed by our preliminary diet experiment in adults, which shows a consistent dose response to the ingested amount of fructose administered in the form of sucrose. In this diet experiment the urinary sucrose excretion failed to turn out as a clear biomarker for sugar consumption which is somewhat in contrast to the suggestions of other authors who concluded that both sucrose and fructose are excreted in the urine proportionally to dietary intake [START_REF] Luceri | Urinary excretion of sucrose and fructose as a predictor of sucrose[END_REF]Tasevska et 20 al., 2005;[START_REF] Joosen | Urinary sucrose and fructose as biomarkers of sugar consumption: comparison of normal weight and obese volunteers[END_REF]Tasevska et al., 2009). However, also in some of these studies either a higher intra-individual variation (Tasevska et al., 2005) or a less consistent association [START_REF] Luceri | Urinary excretion of sucrose and fructose as a predictor of sucrose[END_REF] was seen for urinary sucrose compared with fructose. One limitation of our diet experiment, that could possibly explain the missing dose response, was the preservative-free refrigeration of the 24h urines, hence hydrolysis of sucrose could not be fully excluded. Such a possible hydrolysis of sucrose would, however, query the successful application of urinary sucrose as a biomarker in large epidemiological studies in which urine samples are mostly stored without preservatives.

Regarding the eligibility of 24-h urinary fructose as a biomarker for total sugar intake, it should be kept in mind that the corresponding R 2 that we found in children was rather small. The experimental data of Tasevska et al. (Tasevska et al., 2005) and our corresponding data in adults indicate considerable inter-individual differences along with a relatively stable intra-individual excretion level for fructose, i.e. a relevant individual (at least partly genetic) component of urinary fructose excretion.

Therefore, the most feasible application of the biomarker fructose excretion might be 10 in longitudinal surveys with repeated measurements for each subject, as the interindividual variability can be mathematically accounted for using adequate statistical mixed effect models like proc mixed. Despite this, plausible results have been yielded in a cross-sectional study using urinary fructose as biomarker for sugar intake [START_REF] Bingham | Epidemiologic assessment of sugars consumption using biomarkers: comparisons of obese and nonobese individuals in the European prospective investigation of cancer Norfolk[END_REF].

Our observation that intrinsic sugar explained almost the 3-fold of the variability of urinary fructose excretion compared to added sugar (Table 2), shows that sugar derived from fruits and fruit juices (intrinsic sugar) represents an important and not to be disregarded predictor of the urinary fructose excretion. In a recent paper Tasevska et al. (Tasevska et al., 2009) reported significant correlations for urinary 20 sugar excretion with extrinsic sugar intake, but not with intrinsic sugar intake. Two reasons may account for the seemingly difference between the latter authors´ and our findings. Firstly, as pointed out by Tasevska et al. their subjects consumed higher amounts of extrinsic than intrinsic sugar, and secondly the applied definition of extrinsic and intrinsic sugar differed from our definition, in that we differentiated between added and intrinsic sugar. Tasevska et al. classified sugar from fruit juices (which in our definition is intrinsic) as extrinsic sugar. Actually, if we apply the definition of Tasevska et al. to our DONALD data (i.e., if we define extrinsic sugar as sum of added sugar and sugar from fruit juices), the association between this extrinsic sugar and fructose excretion turns more significant (showing a higher explained variability; R 2 =0.14, P<0.0001) and the association between the remaining intrinsic sugar and fructose excretion loses significance (R 2 =0.06, P<0.01).

A limitation of the present analysis is that the calculation of dietary sugar intake by a weighed dietary record could only provide estimates of the true sugar intake (e.g. due to recording errors or underreporting) [START_REF] Biro | Selection of methodology to assess food intake[END_REF]. However, this method has been deemed to be the most exact dietary assessment tool for a study 10 population of this size [START_REF] Bingham | Validation of weighed records and other methods of dietary assessment using 20 the 24 h urine nitrogen technique and other biological markers[END_REF][START_REF] Gibson | Validity in dietary assessment methods[END_REF]. Additionally, the quality of the investigated dietary records was improved by excluding potential underreporting: only such dietary records were considered that had plausible energy intake values. As the dietary sugar consumption is a major determinant of individual's energy intake, it can be assumed, that misreporting of dietary sugar could be limited by our plausibility checks.

Overall, our results suggest that urinary fructose excretion is clearly determined by the consumed amounts of intrinsic sugar sources, like fruits or fruit juices which are typical fructose providers (results in children). At the same time, renal fructose output has also been shown to vary clearly (and obviously dose-dependent) with added 20 fructose (adminstered as sucrose; experimental diet results in adults, and reported data [START_REF] Luceri | Urinary excretion of sucrose and fructose as a predictor of sucrose[END_REF]Tasevska et al., 2005)). Therefore, we suppose that urinary fructose excretion is rather applicable for the direct estimation of total dietary fructose intake (regardless of its origin) than for the estimation of total or added sugar intake. This possible field of application is of particular interest in light of the current discussion about dietary fructose intake and its impact on human health. intake in dietary intervention studies. Cancer Epidemiol Biomarkers Prev 5, 167-171. Preece MA, Baines MJ (1978). A new family of mathematical models describing the human growth curve. Ann Hum Biol 5, 1-24.

Remer T, Fonteyn N, Alexy U, Berkemeyer S (2006). Longitudinal examination of 24h urinary iodine excretion in schoolchildren as a sensitive, hydration statusindependent research tool for studying iodine status. Am J Clin Nutr 83, 639-646.

Schofield WN (1985). Predicting basal metabolic rate, new standards and review of previous work. Hum Nutr Clin Nutr 39 (Suppl 1), 5-41. 10

  Sichert-Hellert W, Kersting M, Chahda C, Schaefer R,Kroke A (2007).German food composition database for dietary evaluations in children and adolescents. J Food Comp Anal 20, 63-70. Sichert-Hellert W, Kersting M, Schoch G (1998). Underreporting of energy intake in 1 to 18 year old German children and adolescents. Z Ernahrungswiss 37, 242-251. Sigman-Grant M, Morita J (2003). Defining and interpreting intakes of sugars. Am J Clin Nutr 78, S815-S826. Snedecor GW, Cochran WG (1987). Statistical methods. Ames, IA: Iowa State University Press. 20 Stanhope KL, Schwarz JM, Keim NL, Griffen SC, Bremer AA, Graham JL et al. (2009). Consuming fructose-sweetened, not glucose-sweetened, beverages increases visceral adiposity and lipids and decreases insulin sensitivity in overweight/obese humans. J Clin Invest 119, 1322-1334. Tasevska N, Runswick SA, McTaggart A, Bingham SA (2005). Urinary sucrose and fructose as biomarkers for sugar consumption. Cancer Epidemiol Biomarkers Prev 14, 1287-1294. Tasevska N, Runswick SA, Welch AA, McTaggart A, Bingham SA (2009). Urinary sugars biomarker relates better to extrinsic than to intrinsic sugars intake in a metabolic study with volunteers consuming their normal diet. Eur J Clin Nutr 63, 653-659. Vos MB, Kimmons JE, Gillespie C, Welsh J, Blanck HM (2008). Dietary fructose consumption among US children and adults: the Third National Health and Nutrition Examination Survey. Medscape J Med 10, 160.

Fig. 1 .

 1 Figure Legends

Fig. 2 .

 2 Fig. 2. Association of dietary added sugar intake (g/d) and dietary total sugar intake

  Figure 1

  Figure 2

Table 1

 1 Study sample characteristics of 114 prepubertal healthy participants of the DONALD Study.

		Boys (n=58)	Girls (n=56)	P	b
	Anthropometrics
	Age (y)	9,3 ± 0,8 a	7,9 ± 0,7	<0,0001
	Weight (kg)	33,0 ± 6,1	27,2 ± 5,7	<0,0001
	Height (cm)	140,3 ± 7,0	129,6 ± 5,9	<0,0001
	BMI (kg/m 2 )	16,7 ± 2,1	16,0 ± 2,2	n.s.
	Dietary parameters
	Total energy intake (MJ/d)	7,5 ± 1,0	6,4 ± 1,0	<0,0001
	Added sugar intake (g/d)	66,4 ± 33,1	56,9 ± 26,5	n.s.
	Sugar from fruits (g/d)	16,3 ± 11,8	16,4 ± 11,0	n.s.
	Sugar from fruit juices (g/d)	19,4 ± 19,1	16,1 ± 21,0	n.s.
	Total sugar intake (g/d)	102,2 ± 39,2	89,4 ± 31,4	n.s.
	Urinary parameters
	24-h urinary volume (ml)	848,3 ± 361,7	681,3 ± 251,6	0,005
	24-h fructose excretion (mg/d)	19,8 (15,9; 24,5) c	20,7 (17,1; 25,0)	n.s.

a All such values are arithmetic means ± S.D. b Sex differences were analyzed by using unpaired t test. c All such values are geometric means (95% confidence interval)

Table 2

 2 Association between dietary sugar intake and urinary fructose excretion in 114 prepubertal children participating in the DONALD Study.Results of the linear regression models. Potential covariates (age, sex, BMI, urine volume and energy intake) were considered but no further adjustment was required.

	Predictor	Log values of fructose in urine ß P	R 2
	Regression 1
	Added sugar	0,0026	0,011	0,055
	Regression 2
	Total sugar	0,0040	<0,001	0,181
	Regression 3
	Added sugar	0,003	<0,005	0,055
	Intrinsic sugar	0,006	<0,0001	0,153

Acknowlegements

The present examination was supported in part by the Long-range Research Initiative (LRI) of the European Chemical Industry Council (Cefic). The DONALD Study is funded by the Ministry of Science and Research of North Rhine Westphalia, Germany.

The present examination was supported in part by the Long-range Research Initiative (LRI) of the European Chemical Industry Council (Cefic). The DONALD Study is funded by the Ministry of Science and Research of North Rhine Westphalia, Germany.

Conflict of interest:

The authors declare no conflict of interest.

Conflict of interest

The authors declare no conflict of interest.