MENU PLANNING FOR PREGNANT WOMEN WITH GESTATIONAL DIABETES - THE NECESSITY OF A NUTRITIONIST

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1 Orgnal scentfc paper UDC : :[ :618.3 MENU PLANNING FOR PREGNANT WOMEN WITH GESTATIONAL DIABETES THE NECESSITY OF A NUTRITIONIST Petra Oreškovć 1, Krstna Tušek 2, Jasenka Gajdoš Kljusurć 1*, Želmr Kurtanjek 1 1 Faculty of Food Technology and Botechnology, Unversty of Zagreb, Perottjeva 6, 1, Zagreb, Croata 2 Department of Emergency Medcne KrapnaZagorje County, Dr. Mrka Crkvenca 1, 49 Krapna, Croata * emal: jgajdos@pbf.hr Abstract Gestatonal dabetes or dabetes of pregnancy s the dagnoss whch s affectng an ncreasng number of pregnant women due to the recent ntroducton of new, more strngent crtera. Snce n Croata all pregnant women sufferng from gestatonal dabetes are beng recommended unversal sample menu of 18 kcal, ths study ncluded sx pregnant women dagnosed wth the above, wth the am to evaluate ther nutrtonal status and to determne ther ndvdual energy and nutrtonal needs. Threeday food dary was used to analyse adherence to the recommended number of unts of the Amercan Dabetes Assocaton (ADA) exchange lst for dabetes. The am of ths study was to analyse the daly ntake before and after the stated dagnoss and to examne the applcablty of the method of lnear optmzaton n ndvdual menu plannng for pregnant women wth gestatonal dabetes. The results showed that the unversal sample menu s nadequate for four of the sx pregnant women whose energy demands are greater than 18 kcal, and that none of the pregnant women dd not consume the recommended number of unts from the ADA exchange lst. The menus made usng lnear optmsaton are not n accordance wth the recommended number of unts of the ADA exchange lst and therefore can not be used as a sample menu. Ths conclusons lead to the need for personalzed menu optmzaton wth a more approprate optmzaton accountng for personal dfferences. Key words: Gestatonal dabetes, Menu plannng, Nutrtonst. 1. Introducton Ancent Greek phlosophers, ncludng Socrates were lookng for some general nsght that showed or suggested that all thngs (ncludng the role of the ndvdual n socety) was, s, or can be set to the best possble way expressed n today s vocabulary ths would mply optmzaton. By defnton, optmzaton s the search for the best solutons to a problem, observng approprate restrctons for observed varables. Problems of optmzaton and optmal processes can be found n many areas of natural, socal and engneerng scences [1]. One can say that these problems have always been and are nextrcably lnked to the development of manknd. What would generally mean the optmal soluton? The optmal soluton s the one that satsfes all the condtons set n the restrctons model. Therefore, the optmal soluton s the one that s also the best, n the set of possble solutons [2 4]. The term most optmal does not exst, because f somethng s optmal t s the most acceptable and the gradaton goes from good better the optmal (or the best). In Detetcs optmsaton can be appled as well. What are the constrants n the optmzaton model, such as det? Lmtatons of the model are the questons rased by people who plan such optmal daly offers. For example, when a daly menu s planned (for ndvdual or group) t s mportant to know the followng: habts and needs of an ndvdual or a group whether there are specal features n the det of an ndvdual or group (lke vegetaran, kosher, etc.) nutrents that should be observed (f there are specfc need specfc nutrents should be more mportant than others) specfc preferences, etc. 81

2 Recent studes on menu plannng examne varables such as menu tem selecton process and crtera, menu changes and varety, and menu tem nnovaton. Those studes prmarly assume that menu plannng s a crtcal manageral actvty to the success of restaurant frms [5]. It s wellknown today that a healthy lfestyle and det can be used n preventon of today s deadly chronc degeneratve dseases [6]. Human nutrton should meet some basc settngs: () contan suffcent amounts of energy, and () contanng all necessary nutrtonal and protectve substances n accordance wth the detary needs of ndvduals or populaton groups, n order to ensure a balance between foods that are easly dgestble and provde a feelng of fullness and satsfacton after takng meals. Thngs mentoned above are the frst nformatons needed for the menu plannng. Intakes of nutrents that are much hgher or lower than recommended can ncrease the rsk of development of chronc llnesses such as coronary heart dsease, dabetes, cancer, obesty etc [7]. So, the recommendatons are the nputs that are used n the menu optmsaton as lmtatons that must be met. In ths paper, as a specfc group for menu plannng were chosen, were pregnant women wth gestatonal dabetes aged 28 42, because numerous studes have shown ther nadequate nourshment hgh ntake of refned sugars and fats and nsuffcent ntake of needed protens, ron and fbres [8, and 9]. Gestatonal dabetes (GD) s defned as glucose ntolerance of varable degree wth onset or frst recognton durng pregnancy. GD usually begns md to late pregnancy and contnues to term [1, 11]. The etology of GD s not yet clear. In ths paper, t s suggested that hghnsulnogenc nutrton represents the key factor n the etology of GD. An attempt to understand the dabetogenc effect of pregnancy must take nto account two factors () a transent physologc nsuln resstance and hypernsulnema are characterstc of normal pregnancy and () det composton has a sgnfcant mpact on the nsuln acton of pregnancy [12]. Regstered detcans from the Dabetes Care and Educaton and the Women s Health and Reproductve Nutrton detetc practce groups developed nutrton practce gudelnes for gestatonal dabetes melltus [13, and 14]. The energy needs ncreases durng pregnancy [7] but the share of energy and macronutrents n pregnant women wth GD s crucal and should be n the range as presented n Table 1. Table 1. Share of energy and carbohydrates n the daly food ntake [17, 24] Meal Share of daly energy ntake, E d (%) Share of carbohydrates (E d, %) breakfast» snack» lunch» snack» dnner» snack» The am of ths work was to A) analyse dets of pregnant woman wth dagnose of GD and B) to plan ther det accordng the recommendatons gven by Amercan Dabetes Assocaton (ADA). For problems that have one goal, and nclude a large number of data and nformaton, applcaton of computer plays a crucal role. In ths paper, lnear optmzaton was appled because t allows to search for a solutons that has one goal (e.g., economcally acceptable daly offer), where the result should be a daly offer that must meet a number of constrants for e.g. energy and nutrtonal constrants [15]. 2. Materals and Methods 2.1 Food ntake analyss Pregnant women (all trmesters) have taken a threeday food dary to record the food, mass of t and the way the food was prepared. The descrptve statstcs was used to evaluate the ntake of energy and nutrents. 2.2 Menu plannng The energy plan for pregnant women wth GD s based on a daly ntake of»75 kj (18 kcal). Followng the ADA recommendatons, t s mportant to avod smple carbohydrates. Pregnant women wth GD usually have an addtonal meal at nght (slow absorbng carbohydrates) n order to prevent the occurrence of nocturnal hypoglycaema and ketoss [16, and 17]. The appled lnear programmng s desgned to address the problem by choosng between several possble or avalable meals n order to acheve the most sutable combnaton of the selected (optmal result) daly meal combnaton [18 21]. Applyng these premses (goal and constrans), models were constructed n order to fnd the so called optmal soluton. Usng lnear optmsaton n menu plannng, t s very mportant to ndcate the upper and lower lmts,.e. mnmum and/or maxmum value that s needed to satsfy the daly nutrton needs [22]: Mnmum Acceptable energy or nutrent amounts Maxmum 82

3 Nutrent needs are often defned n ranges between the mnmum and maxmum, and for example; accepted daly energy ntake s 18 kcal, but concernng the acceptable coeffcent of varance form 1%, the mnmum would be defned as 162 kcal and the maxmum as 198 kcal. Ths was also appled on the ntakes of foods from dfferent food groups takng n to account the share of carbohydrate ntake. 3. Results and Dscusson Analyss of the food dary s presented on Fgure 1 whch hghlghts the daly average energy ntake and the share of carbohydrates. Average energy ntake s under the recommended value of 18 kcal (156 kcal), what s nsuffcent regardng the pregnancy [2]. Energy, Ed (kcal) mn Daly energy ntake (E d) Carbohdrate share n E d Fgure 1. Average energy ntake wth the share of carbohydrates The standard devatons for the daly energy ntake ranged from 23 to 22 kcal. Regardng the observed share of carbohydrates, the average value of approxmately 45% s relatvely acceptable. Gven that the daly energy ntake s not n accordance wth the recommendatons [14, 16], t was decded to apply lnear optmsaton to correct ther energy and nutrent ntake what other studes showed as preferable [2, 23]. The basc structure of the lnear model s consstng of a goal functon, and constrans, followng the role that nether varable can be negatve. Goal functon: F = c Breakfast + c Snack + c Lunch + + c Snack (1),1 + c Dnner + c Snack, 2,3 Constrans that wll restrct energy and nutrent content of daly offers: a j Breakfast + aj Snack, 1 + aj Lunch + + aj Snack, 2 + aj Dnner + aj Snack, 3 b, a j Breakfast + aj Snack, 1 + aj Lunch + + aj Snack, 2 + aj Dnner + aj Snack, 3 b, (2) CHO (% Ed) mn max Where: c x j a j b meal prce x meals (Breakfast, Snacks, Lunch and Dnnerr) for 7 days (), = 1,..., 7 a observed parameter (energy and macronutrents) (j), j = 1, 2,..., 4, for observed meals, recommended ntakes of energy, water or nutrents The number of observed varables was lmted to the content of energy, carbohydrates, fats and protens what s presented n Table 2. Table 2. Recommended ntake of energy and macronutrents that dffer as reflecton of the pregnancy trmester [7] Intake Detary reference ntake durng pregnancy 18 Energy (kcal) 18 Protens (% of E d ) > 1 Fats (% of E d ) < 35 Carbohydrates (% of E d ) Each daly offer ncluded one breakfast (B), lunch (L) and dnner (D) and 3 snacks (Sn). So, the data bass of meals was bult up of 42 dshes (7 B + 7 L +7 D + 21 Sn); what would, n an deal case, result wth 117,649 dfferent daly offers (7 B x 7 L x7 D x 7 Sn 1 x 7 Sn 2 x7 Sn 3 ). But the usage of the optmsaton tools wll clarfy whch offers ncluded n the large set of possble meal combnatons (daly offers) are well balanced and n accordance wth the requred energy and nutrent content. Table 3. Proposed optmal daly offer Proposed meal Breakfast Snack 1 Lunch Snack 2 Dnner Snack 3 Foods graham bread: ½ slce, 35 g low fat fresh cheese: 12 g cream (12 % fat): 1 tablespoons sesame seeds: ½ tablespoon fresh paprka: 5 g yogurt: 1 cup, 18 ml mxed bread: 1 slce, 6 g boled egg whtes: one lean ham: 3 g pear: 1 small, 1g cooked brown rce: 12 g mxed bread: ½ slce, 3 g veal: 6 g sesame seeds: ½ tablespoon olve ol: 1 teaspoon mandarns: 2 smaller, 15 g apple: 1 g nuts: 4 halves of a nut bscuts: pett beurre, 4 peces, 5 g cooked potatoes: 1 g spnach: boled, 15 g baked fsh: 6 g (e.g. anchovy) ol: 1 teaspoon sesame seeds: ½ tablespoon tomato salad: 1 g apple: 1 g mxed bread: ½ slce, 3 g skmmed mlk: 1 cup, 18 ml 83

4 One optmal soluton s presented n Table 3. Ths sample can be talored accordng the personal needs of the pregnant woman by changng the amounts of foods n a meal adaptng t to ndvdual needs. Unfortunately, the number of solutons that are n accordance wth the recommendatons s reduced from the large set of possble daly offers to a number of 28, what s enough to complete a monthly offer. Ths shows that even a small number of lmtatons (as mentoned n Table 2) can be a very strct flter for menu offers that should have defned content of energy and macronutrents. The am was also to examne the dstrbuton of carbohydrates throughout the day, accordng to portons. The energy and carbohydrate dstrbuton durng the day should rse tll lunch, and then slowly fall, as presented for optmzed meals (OM) n Fgure 2. Energy (%) OM IM Breakfast Snack 1 Lunch Snack 2 Supper Snack 3 Fgure 3. Average energy share for meals that were consumed by the pregnant women (IM) and optmzed meal offers (OM) 6 5 IM OM 3 25 OM IM Recommended range 4 2 CHO (g) 3 2 Energy (%) Breakfast Snack 1 Lunch Snack 2 Supper Snack 3 Breakfast Lunch Supper Snack 1 Snack 2 Snack 3 Fgure 2. Content of carbohydrates (CHO) ntake wth the share of carbohydrates for meals that were consumed by the pregnant women (IM) and optmzed meal offers (OM) Fgure 4. Average share of carbohydrates n the total energy ntake for meals that were consumed by the pregnant women (IM) and optmzed meal offers (OM) In the case of dabetes the recommendatons for the breakfast are to eat smaller meals because the nsuln resstance s the hghest n the mornng [16, 17, and 24]. Therefore, t s often necessary to avod smple carbohydrates, fruts and frut juces n the mornng meal to prevent the occurrence of hyperglycaema. If energy ntake for breakfast s only 1% of total calores requred, t s desrable to nclude protens and carbohydrates n the mdmornng snack n order to prevent the occurrence of excessve hunger for lunch [24]. Pregnant women usually have a meal durng the nght (the best choces are slow absorbng carbohydrates) n order to prevent the occurrence of nocturnal hypoglycaema and ketoss [16, 17]. Concernng the dstrbuton of energy and carbohydrates n daly meals (accordng the recommendatons gven n Table 1) the changes n meals that present optmzed offers can be seen n Fgures 3 and 4. The recommendatons that should be followed when a daly menu plan s made for dabetcs are gven n Table 1. Those recommendatons are also ndcated n Fgure 4 presentng the acceptance range from mnmal to maxmal values. The second objectve of ths study was to assess whether the method of lnear optmzaton (LO) could be appled n the daly menu plannng for women wth GD because some studes have shown effectve applcaton of LO n quck and easy fndng of solutons that meet a large number of constrants [2, 25, and 26]. To nclude the personal talorng n daly menu plans, where each pregnant woman should be able to choose the number of daly snacks (1 to 3), t s mportant to be aware that the ncrease n body weght by overweghed pregnant women could endanger the lfe of the chld and the mother [16, 24, and 27] ncreasng the rsk of potental developng ketoss, whch can lead to neurodevelopmental problems foetuses [28]. For some pregnant woman the carbohydrate ntake per meal exceeded 73 g (not presented n the results), and completely opposte case s detected for one pregnant woman whch daly ntake of carbohydrates was only 63 grams (not presented n the results). Thus, low carbohydrate ntake s totally unacceptable, snce, the DRI recommendatons defne the daly ntake as at least 175 g, n order to prevent ketoss and to ensure a suffcent amount of glucose for bran functon of 84

5 mother and foetus wthout relyng on the breakdown of fats and protens [16, 29]. The postve change n the optmzed det of pregnant women wth GD s the ncrease of the daly meals number what s n accordance wth the recommendaton [16, 17, 24] where s ponted out that pregnant women wth GD schedules energy ntake, especally carbohydrates n three small to medum large meals, and 2 4 snacks to avod the occurrence of hyperglycaema. Our frst concluson s that the unversal det of 18 kcal dvded nto sx daly meals s not n accordance wth the energy needs because the needs n daly energy ntake vares based on body composton, and t may not be rrelevant f a pregnant woman has an acceptable body mass ndex, or not. We would lke to pont out the necessty of personaltalorng n the menu plannng n general wth specal emphass on specal menu plannng for users as woman wth GD. Method of lnear optmzaton was chosen because t was a helpful tool n many studes [2, 25, 26]. The second, mportant fact that can be concluded from presented results s the possblty of adaptng the optmal solutons to personal needs (as mentoned for results gven n Table 3) where the applcaton of optmzaton s justfed by talorng one soluton to personal needs. Results show no unversal trend of ncreased or decreased number of servngs from specfc food groups for all pregnant women; we found that dfferent food groups were represented n a larger or smaller number of servngs (compared to the recommendatons) n the case of each subject.. A very smlar concluson was reached n the study by Maes and coworkers [26], whch examned the applcablty of optmzaton methods n gvng detary advce to adolescents regardng the necessary changes n ther det to meet the nutrtonal recommendatons. Research shows that the use of optmzaton certanly has ts advantages and represents a step forward n nutrton nterventons, but also stresses the necessty of upgradng the model for optmzaton, n order to get the results that would be more easly applcable for gvng detary advces. 4. Conclusons Change of detary habts n GD s the frst step whch can mprove glycemc control and pernatal outcomes. Use of optmzaton n creatng daly menus for pregnant women wth gestatonal dabetes algned the offers wth recommended shares of energy and carbohydrates n each meal. The optmzed daly offer presents energy and nutrtonally balanced meals. All results and optmzaton program s based on the energy ntake of unversal sample menus of 18 kcal what s not n accordance wth a personal menu plannng. We consder t approprate and necessary because some pregnant women could fal to meet daly recommendatons for mcronutrents that are crtcal for the perod of pregnancy n whch they resde. Research has shown the necessty of a nutrtonst n a team that cares for pregnant women wth GD whose task was to create a personalzed sample menus talored accordng to ther energy and nutrtonal needs helpng them to control the level of glucose n the blood adherng to the recommended number of unts from certan food groups of replacement system and to educate pregnant women about the mportance of proper nutrton and ncluson of all groups of foods n necessary quanttes n ther daly det. 5. References [1] Koroušć Seljak B. (29). Computerbased detary menu plannng. Journal of Food Composton and Analyss, 22, (5), pp [2] Đunđek S., Gajdoš Kljusurć J., Magdć D., Luknac Čačć J., Kurtanjek Ž. (211). Optmsaton of the Daly Nutrent Composton of Daly Intakes Durng Gestaton. Croatan Journal of Food Technology, Botechnology and Nutrton, 6, (12), pp [3] Rumora I., Kobrehel Pntarć I., Gajdoš Kljusurć J., Marć O., Karlovć D. (213). Effcent use of modellng n new foodproduct desgn and development. Acta Almentara, 42, (4), pp [4] Škevn D., Domjan T., Kraljć K., Gajdoš Kljusurć J., Neđeral S., Obranovć M. (212). Optmzaton of Bleachng Parameters for Soybean Ol. Food Technology and Botechnology, 5, (2), pp [5] Ozdemr B., Calskan O. (213). A revew of lterature on restaurant menus: Specfyng the manageral ssues. Internatonal Journal of Gastronomy and Food Scence, ScenceDrect, Elsever. <URL: Accessed 17 January 214. [6] Mahan K. L., EscottStump S. (27). Krause s Food and Nutrton Therapy (12 Ed.). Saundres, Elsever, Phladelpha, USA. [7] Insttute of Medcne. (25). DRI for energy, carbohydrate, fber, fat, fatty acds, cholesterol, proten, and amno acds (macronutrents). Natonal Academy Press, Washngton, D.C., USA. [8] Kaser L. L., Allen L. (22). Poston of the ADA: nutrton and lfestyle for a healthy pregnancy outcome. Journal of Amercan Det. Assocaton, 12, pp [9] Mungen E. (23). Iron supplementaton n pregnancy. Journal of Pernatal Medcne, 31, pp [1] Metzger B. E. (Ed.). (1991). Summary and Recommendatons of the Thrd Internatonal WorkshopConference on Gestatonal Dabetes Melltus. In: Proceedngs of the thrd nternatonal gestatonal dabetes workshop/conference, Dabetes, 4, (Suppl 2), pp

6 [11] JovanovcPetersen L, Mesel B, Bever W, Peterson CM. (1997). The Rubenesque pregnancy: a progresson towards hgher blood pressure correlates wth a measure of endogenous and exogenous nsuln levels. Amercan Journal of Pernatology, 14, pp [12] Kopp W. (25). Role of hghnsulnogenc nutrton n the etology of gestatonal dabetes melltus. Medcal Hypotheses, 64, pp [13] Reader D., Splett P., Gunderson E. P. (26). Impact of Gestatonal Dabetes Melltus Nutrton Practce Gudelnes Implemented by Regstered Dettans on Pregnancy Outcomes. Journal of the Amercan Detetc Assocaton, 16, pp [14] ADA. (21). Poston statement of the Amercan Dabetes Assocaton: The evdence for Medcal Nutrton Therapy for Type 1 and Thype 2 Dabetes n adults. Dabetes Care, 11, pp [15] Gajdoš J., Vdaček S. I., Kurtanjek Ž. (21). Meal plannng n boardng schools n Croata usng optmsaton of food components. Current Studes of Botechnology Envronment, 2, pp [16] ADA. (28). Poston statement of the Amercan Dabetes Assocaton: Nutrton recommendatons and Interventons for Dabetes. Dabetes Care, 31, (suppl 1), pp. S61S78. [17] Juras J. (29). Nutrton n dabetc pregnancy (n Croatan). In: Dabetes n Women (n Croatan), Đelmš J., Ivanševć M., and Metelko Ž. (Eds.), Medcnska naklada, Zagreb, pp [18] Kalpć D., Mornar V. (1996). Operatons Research (n Croatan). DRIP, Zagreb, Croata. [19] Deb K. (21). MultObjectve Optmzaton Usng Evolutonary Algorthms. John Wley & Sons, Ltd., Hoboken, New York, USA. [2] Darmon N., Ferguson E., Brend A. (22). Lnear and nonlnear programmng to optmze the nutrent densty of a populaton s det: an example based on dets of preschool chldren n rural Malaw. Amercan Journal of Clncal Nutrton, 75, pp [21] Brown R. M. (1966). Automated menu plannng. M.S. Thess. Kansas State Unversty, Manhattan, KS, USA. [22] Bhatt M. A. (2). Practcal Optmzaton Methods. SprngerVerlag, New York, USA. [23] Magdć D., Gajdoš Kljusurć J., Matjevć L., Frketć D. (213). Analyss of det optmzaton models for enablng condtons for hypertrophc muscle enlargement n athletes. Croatan Journal of Food Scence and Technology, 5, (1), pp [24] Luke, B. (24). Detary management. In: Dabetes n Women, Reece E. A, Coustan D. R. and Gabbe S. G. (Eds.), Lppncott Wllams & Wlkns, Phladelpha (USA), pp [25] Mallot M., Veux F., Ferguson E. F., Voltaer J. L., Amot M. J., Darmon N. (29). To meet nutrent recommendatons, most French adults need to expand ther habtual food repertore. Journal of Nutrton, 139, pp [26] Maes L., Vereecken C. A., Gedrch K., Reken K., Schert Hellert W., De Bourdeaudhuj I., Kerstng M., Manos Y., Plada M., Hagstromer M., Detrch S., Matthys C. (28). A feasblty study of usng a det optmzaton approach n a webbased computertalorng nterventon for adolescents. Internatonal Journal of Obesty, 32, pp [27] PavlćRenar I. (28). Nutrton for dabetc persons (n Croatan). Medcus, 17, (1), pp [28] Magon N., Seshah V. (211). Gestatonal dabetes melttus: nonnsuln management (revew). Indan Journal of Endocrnology and. Metabolsm, 15, pp [29] EAL. (213). Gestatonal Dabetes Melltus Evdencebased Nutrton Practce gudelne. EAL Academy of Nutrton and Detetcs Evdence Analyss Lbrary. <URL: Accessed 24 October