The objective of our study was to evaluate vitamin D status and its predictors in Slovenian premenopausal and postmenopausal women. A cross-sectional study was carried out between 1 March 2021 and 31 May 2021. A total of 319 healthy women from the Central Slovenian region aged between 44 and 65 were recruited; 176 were included in the final analysis. The vitamin D status was determined by measuring the total 25-Hydroxycholecalciferol (25(OH)D) concentration, vitamin D binding protein (DBP), and albumin and calculating the bioavailable 25(OH)D and free 25(OH)D. For the calculation of bioavailable and free 25(OH)D, we developed a new online calculator. The Endocrine Society’s thresholds for vitamin D deficiency and insufficiency were used; 29.0% of premenopausal and 24.4% of postmenopausal subjects were found to be vitamin D deficient (total 25(OH)D < 50 nmol/L); 76.8% of the premenopausal and 61.7% of postmenopausal subjects were found to have insufficient levels (total 25(OH)D < 75 nmol/L). Premenopausal women had 11.8% lower total 25(OH)D, 32.2% lower bioavailable 25(OH)D, and 25.2% higher DBP than postmenopausal women. The most important predictors of vitamin D status were vitamin D supplementation and time spent in the sun. Contrary to similar studies, the vitamin D status in Slovenian postmenopausal women was significantly better than in premenopausal women. In postmenopausal women, the measurement of free or bioavailable 25(OH)D instead of the total 25(OH)D could be advantageous.

Introduction For almost nine decades, the fortification of foods with vitamin D has been proven effective in preventing rickets. This study aims to build and economically evaluate a fortification model based on egg biofortification and milk (including yoghurt) fortification. Methods A cross-sectional study was carried out between 1. March and 31. May 2021. Three hundred and nineteen healthy women from the Central Slovenian region aged between 44 and 65 were recruited for the study, with 176 participants included in the final analysis. For the fortification model calculations, the vitamin D contents of unenriched milk (including yoghurt) and eggs were replaced by enriched foods containing vitamin D. The economic evaluation was done using available drug and food supplement prices. Fortification costs were calculated using vitamin D prices provided by suppliers. Results Mean vitamin D intake from food was 2.19±1.34 µg/d. With fortification Model 1 (enriched eggs), it would be: 6.49±4.45 µg/d, and with Model 2 (enriched eggs and milk): 10.53±6.49 µg/d. Without fortification, none of the participants would reach a daily vitamin D intake >10 µg. With fortification Model 1 (egg fortification), 15.3% would reach >10 µg and with Model 2 (egg and milk fortification) 46.2% would reach >10 µg. The economic comparison of the annual cost of 10 µg vitamin D/d/person was EUR 6.17 for prescription drugs, EUR 6.37 for food supplements, EUR 0.09 for direct milk fortification and EUR 0.12 for egg biofortification with vitamin D. Conclusions Egg and milk (including yoghurt) fortification could cost-effectively increase vitamin D intake in the Slovenian population of women between 44 and 65 by almost five-fold, and could significantly lower the prevalence of vitamin D deficiency. Additional research and changes to legislation are needed before this can be introduced.

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AimAiming at assessing sufficiency of energy/protein intake in hospitalized patients, the objective was to monitor and analyze actual food intake of patients hospitalized in three clinical wards of one of major Slovenian hospitals.Methods53 patients were included in the study. Food intake was assessed 3 times daily from leftovers. Nutritional status was assessed with Nutritional Risk Screening tool 2002. The observed outcomes were percentage of energy coverage (PEC) and percentage of protein coverage (PPC). In PEC energy nutritional value of the menu (ENVM), and in PPC protein nutritional value of the menu (PNVM) were considered as the main modifiable risk factors. Data were analyzed univariately and multivariately by using logistic regression method.ResultsThe patients did not cover energy needs (67.4±24.5%). Multivariate model for PEC was highly significant (R2=0.347; pmodel<0.001) with ENVM showing high strength of association (b=0.040; p=0.004). Patients also did not cover protein needs (84.0±40.2%). Multivariate model for PEC was highly significant (R2=0.477; pmodel<0.001) and PNVM showing high strength of association (b=0.937; p=0.002).ConclusionFor successful prevention and early detection of malnutrition, food intake in hospitals is vital and should be constantly monitored. A simple method for monitoring is proposed. The menus provided to patients should also be adequate in terms of energy and protein content.