Статті в журналах з теми "Dietary changes"

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1

Champagne, Catherine M., Margaret L. Bogle, and William H. Karge. "Using national dietary data to measure dietary changes." Public Health Nutrition 5, no. 6a (December 2002): 985–89. http://dx.doi.org/10.1079/phn2002375.

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AbstractObjective:To demonstrate that dietary datasets from the Continuing Survey of Food Intakes by Individuals, a US population survey, allow comparisons with national data and provide food composition datasets that can be used to generate similar dietary data.Design:Two studies are described: the Lower Mississippi Delta Nutrition Intervention Research Initiative (Delta NIRI), which used a 24-hour recall, and a Department of Defense Military Nutrition Research Task, which used 3-day dietary records. Both studies used the same food composition tables.Setting:Rural Lower Mississippi Delta and an Army post.Subjects:Four hundred and nine residents (adults and children) from the rural Delta region of Arkansas, Louisiana and Mississippi, and 74 career soldiers from the Sergeants Major Academy, Fort Bliss, Texas.Results:The Delta NIRI study found that fruit and vegetable consumption for these rural residents was lower than that found nationally. Additionally, the quality of vegetable servings is of concern since a large percentage came from french fries and potato chips. In the Sergeants Major Academy study, the national survey food composition tables allowed for easy analysis of intake data and comparisons with dietary recommendations.Conclusions:Strategies similar to those used for the Delta NIRI and Military Nutrition Research Task can be used widely, allowing comparisons of ‘defined populations’ with nationally distributed data. Additionally, measurement of dietary change is more efficient when the same protocol is used subsequently to collect more data, a method similar to that used by the US Department of Agriculture to describe food consumption patterns from one survey to another.
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2

Roberson, Kortnee Y., and Emily White VanGompel. "Dietary changes to improve depression." Evidence-Based Practice 21, no. 4 (April 2018): E20. http://dx.doi.org/10.1097/01.ebp.0000542073.78274.57.

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3

Luca, F., G. H. Perry, and A. Di Rienzo. "Evolutionary Adaptations to Dietary Changes." Annual Review of Nutrition 30, no. 1 (July 2010): 291–314. http://dx.doi.org/10.1146/annurev-nutr-080508-141048.

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4

Bergström, E., O. Hernell, and LÅ Persson. "Dietary changes in Swedish adolescents." Acta Paediatrica 82, no. 5 (May 1993): 472–80. http://dx.doi.org/10.1111/j.1651-2227.1993.tb12726.x.

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5

Pereira, John, and Yoram Shir. "Reducing Pain Through Dietary Changes." Clinical Nutrition INSIGHT 34, no. 2 (February 2008): 1–4. http://dx.doi.org/10.1097/01.nmd.0000311962.17065.56.

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6

Jardine, G. "Obesity and dietary behavioural changes." Journal of Endocrinology, Metabolism and Diabetes of South Africa 15, no. 2 (July 2010): 88–90. http://dx.doi.org/10.1080/22201009.2010.10872233.

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7

Maskarinec, G., S. Murphy, D. M. Shumay, and H. Kakai. "Dietary changes among cancer survivors." European Journal of Cancer Care 10, no. 1 (March 2001): 12–20. http://dx.doi.org/10.1046/j.1365-2354.2001.00245.x.

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8

Wennberg, Anna Lena, Anette Lundqvist, Ulf Högberg, Herbert Sandström, and Katarina Hamberg. "Women's experiences of dietary advice and dietary changes during pregnancy." Midwifery 29, no. 9 (September 2013): 1027–34. http://dx.doi.org/10.1016/j.midw.2012.09.005.

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9

Morris, M. A., E. L. Wilkins, M. Galazoula, S. D. Clark, and M. Birkin. "Assessing diet in a university student population: a longitudinal food card transaction data approach." British Journal of Nutrition 123, no. 12 (March 5, 2020): 1406–14. http://dx.doi.org/10.1017/s0007114520000823.

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AbstractStarting university is an important time with respect to dietary changes. This study reports a novel approach to assessing student diet by utilising student-level food transaction data to explore dietary patterns. First-year students living in catered accommodation at the University of Leeds (UK) received pre-credited food cards for use in university catering facilities. Food card transaction data were obtained for semester 1, 2016 and linked with student age and sex. k-Means cluster analysis was applied to the transaction data to identify clusters of food purchasing behaviours. Differences in demographic and behavioural characteristics across clusters were examined using χ2 tests. The semester was divided into three time periods to explore longitudinal changes in purchasing patterns. Seven dietary clusters were identified: ‘Vegetarian’, ‘Omnivores’, ‘Dieters’, ‘Dish of the Day’, ‘Grab-and-Go’, ‘Carb Lovers’ and ‘Snackers’. There were statistically significant differences in sex (P < 0·001), with women dominating the Vegetarian and Dieters, age (P = 0·003), with over 20s representing a high proportion of the Omnivores and time of day of transactions (P < 0·001), with Dieters and Snackers purchasing least at breakfast. Many students (n 474, 60·4 %) changed dietary cluster across the semester. This study demonstrates that transactional data present a feasible method for dietary assessment, collecting detailed dietary information over time and at scale, while eliminating participant burden and possible bias from self-selection, observation and attrition. It revealed that student diets are complex and that simplistic measures of diet, focusing on narrow food groups in isolation, are unlikely to adequately capture dietary behaviours.
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10

Leveille, G. A., and P. F. Cloutier. "Isocaloric diets: effects of dietary changes." American Journal of Clinical Nutrition 45, no. 1 (January 1, 1987): 158–63. http://dx.doi.org/10.1093/ajcn/45.1.158.

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11

Kriwanek, Stephan, Wolfgang Blauensteiner, Elfriede Lebisch, Philipp Beckerhinn, and Rudolf Roka. "Dietary Changes after Vertical Banded Gastroplasty." Obesity Surgery 10, no. 1 (February 1, 2000): 37–40. http://dx.doi.org/10.1381/09608920060674085.

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12

Yang, Wei, and Marsha Read. "Dietary pattern changes of Asian immigrants." Nutrition Research 16, no. 8 (August 1996): 1277–93. http://dx.doi.org/10.1016/0271-5317(96)00137-6.

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13

Wakimoto, P., and G. Block. "Dietary Intake, Dietary Patterns, and Changes With Age: An Epidemiological Perspective." Journals of Gerontology Series A: Biological Sciences and Medical Sciences 56, Supplement 2 (October 1, 2001): 65–80. http://dx.doi.org/10.1093/gerona/56.suppl_2.65.

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14

Huang, Jingbo, Jiri Frohlich, and Andrew P. Ignaszewski. "The Impact of Dietary Changes and Dietary Supplements on Lipid Profile." Canadian Journal of Cardiology 27, no. 4 (July 2011): 488–505. http://dx.doi.org/10.1016/j.cjca.2010.12.077.

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15

Huang, Jincheng, Yueyan Liu, Xiaoying Zhang, Yu Wang, and Yisong Wang. "A Scenario-Based Simulation of Land System Changes on Dietary Changes: A Case Study in China." Sustainability 11, no. 19 (September 23, 2019): 5196. http://dx.doi.org/10.3390/su11195196.

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The dietary change of Chinese residents is driven by increasing incomes and urbanization, which will bring about non-negligible changes in the food production of the land system. To explore how dietary changes might influence future land systems and the environment, this research hypothesizes two potential dietary change scenarios in the period 2010–2030, based on the current trends and Dietary Guidelines for Chinese Residents (DGCR), and applies the CLUMondo model to simulate the spatiotemporal patterns of land systems and estimates a lifecycle’s environmental impacts on dietary change. As shown in the results, dietary changes would obviously alter the land cover, agricultural intensity, and livestock density of land systems, and the changes in land use intensity are noteworthy. If the current trend of dietary change is unchecked, the intensification and expansion of agriculture and animal husbandry would be widely distributed in North China and Northwest China, where the intensity of cropland was low in the past and the ecosystem was relatively fragile. Moreover, the increasing demands for food lead to sharp increases in the carbon footprint, water footprint, and ecological footprint from food production. In contrast, the balanced diet recommended by DGCR could offer considerable environmental benefits. This diet is conducive to cutting down land use intensity, helping natural systems avoid intensification, and the expansion of agriculture and animal husbandry, which lower footprints from food production and have helped to implement the policy of returning croplands to grassland and forests in China. Therefore, popularizing balanced diets could be a win–win for human health and environmental sustainability.
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16

Cosgrove, Kelly, and Christopher Wharton. "Predictors of COVID-19-Related Perceived Improvements in Dietary Health: Results from a US Cross-Sectional Study." Nutrients 13, no. 6 (June 19, 2021): 2097. http://dx.doi.org/10.3390/nu13062097.

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The COVID-19 pandemic resulted in substantial lifestyle changes. No US study has identified predictors of perceived dietary healthfulness changes during the pandemic period. This study included analyses of lifestyle and dietary healthfulness changes using 958 survey responses from US primary household food purchasers. Information was collected related to demographics, COVID-19-related household changes, and health-related habits before and during the pandemic. Binary logistic regression identified predictors of perceived increase in dietary healthfulness during the pandemic period. Overall, 59.8%, 16.4%, and 23.4% of participants reported that their eating habits likely changed, may have changed, and likely did not change, respectively. Of the participants whose dietary habits likely or may have changed, 64.1%, 16.8%, and 19% reported healthier, neither healthier nor less healthy, and less healthy eating habits, respectively. COVID-19-related income loss, more meals consumed with household members in front of the television, an increase in food advertisement exposure, increased perceived stress, and better perceived current health were significant predictors of a perceived increase in dietary healthfulness. Overall, dietary habits were perceived to become healthier during the pandemic. The predictors of perceived improvement in dietary healthfulness were surprising and indicate the need for further study of these factors in crisis and noncrisis situations.
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17

Nutter, June. "Seasonal Changes in Female Athletes' Diets." International Journal of Sport Nutrition 1, no. 4 (December 1991): 395–407. http://dx.doi.org/10.1123/ijsn.1.4.395.

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Dietary intakes of 24 female athletes in various sports were compared inseason and postseason to those reported by 24 nonathletes during the same time period. Diets were analyzed for energy, carbohydrate, fat, protein, vitamins A and C, thiamin, riboflavin, niacin, folacin, calcium, and iron. During the study, the athletes' and nonathletes' diets were similar. Their energy intakes were lower than recommended while their iron and calcium intakes were marginal (less than 70% of the recommended dietary allowance). Although few dietary changes were observed, the nonathletes' diets changed more than those of the athletes during the study. Both groups reduced their energy intakes but only the nonathletes' reduction was significant. Initially many subjects were dieting. More subjects reported dieting during the second recording period. These results suggest that the desire to be thin may influence dietary intakes of female athletes more than changes in exercise training.
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18

White, Emily, Marshall Hurlich, Robert S. Thompson, Margo N. Woods, Maureen M. Henderson, Nicole Urban, and Alan Kristal. "Dietary Changes Among Husbands of Participants in a Low-Fat Dietary Intervention." American Journal of Preventive Medicine 7, no. 5 (September 1991): 319–25. http://dx.doi.org/10.1016/s0749-3797(18)30905-x.

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19

Facchinetti, Fabio, Giulia Dante, Elisabetta Petrella, and Isabella Neri. "Dietary Interventions, Lifestyle Changes, and Dietary Supplements in Preventing Gestational Diabetes Mellitus." Obstetrical & Gynecological Survey 69, no. 11 (November 2014): 669–80. http://dx.doi.org/10.1097/ogx.0000000000000121.

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20

Macdonald, Helen M., Susan A. New, and David M. Reid. "Longitudinal changes in dietary intake in Scottish women around the menopause: changes in dietary pattern result in minor changes in nutrient intake." Public Health Nutrition 8, no. 4 (June 2005): 409–16. http://dx.doi.org/10.1079/phn2005705.

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AbstractObjectiveTo examine dietary change that has occurred over 5 to 6 years.SubjectsA cohort of Scottish women (n=898) with a mean age of 47.5 years (range 45–54 years) at baseline.DesignDietary intake was assessed by validated food-frequency questionnaire (FFQ) and analysed using the UK Composition of Foods database.ResultsSince the first dietary assessment, mean daily energy intake had decreased from 8.2±2.3 to 7.9±2.2 MJ. The degree of low energy reporting (defined as ratio of energy intake to basal metabolic rate >1.1) had increased from 18.7% at baseline to 25.6% at follow-up. Low energy reporters were significantly heavier than ‘normal’ energy reporters (mean weight at follow-up, 68.9±12.6 vs. 66.8±11.3 kg) and could be deliberately restricting intake rather than underreporting. Overall there were decreases in intakes of red meat, processed meat and cheese, but increases in poultry and non-oily fish consumption. Consumption of bread, biscuits and cakes had gone down and there was an increase in cereal and rice/pasta consumption. Intake of potatoes had decreased whereas fruit intake had increased. There were small but statistically significant differences in intakes for most nutrients (>8% change). Nutrient intakes at both visits were similar across menopausal status and usage groups of hormone replacement therapy. Modifications to the computer version of the McCance and Widdowson nutrient database, which differed from the published version, were noted. These changes altered the original baseline values for our study.ConclusionsThe menopause per se is not a period of marked change in nutrient intake. Caution is advised when using computer databases of food compositions for longitudinal studies.
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21

Keyamura, Yuka, Chifumi Nagano, Masayuki Kohashi, Manabu Niimi, Masanori Nozako, Takashi Koyama, Hiroyuki Itabe, and Tomohiro Yoshikawa. "Dietary Cholesterol Atherogenic Changes in Juvenile Rabbits." Biological & Pharmaceutical Bulletin 38, no. 5 (2015): 785–88. http://dx.doi.org/10.1248/bpb.b14-00775.

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22

Popkin, B. M., P. S. Haines, and R. E. Patterson. "Dietary changes in older Americans, 1977–1987." American Journal of Clinical Nutrition 55, no. 4 (April 1, 1992): 823–30. http://dx.doi.org/10.1093/ajcn/55.4.823.

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23

Parmenter, Kate. "Changes in nutrition knowledge and dietary behaviour." Health Education 102, no. 1 (February 2002): 23–29. http://dx.doi.org/10.1108/09654280210412376.

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Knapp, Vincent J. "Major Dietary Changes in Nineteenth-Century Europe." Perspectives in Biology and Medicine 31, no. 2 (1988): 188–93. http://dx.doi.org/10.1353/pbm.1988.0062.

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25

Conlin, Paul R. "Dietary modification and changes in blood pressure." Current Opinion in Nephrology and Hypertension 10, no. 3 (May 2001): 359–63. http://dx.doi.org/10.1097/00041552-200105000-00010.

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26

Nichols, Sarah Frank, Suzanne Galesloot, Dolly Bondarianzadeh, and Susan Buhler. "Dietary Changes Albertan Women Make During Pregnancy: Thematic Analysis of Self-reported Changes and Reasons." Canadian Journal of Dietetic Practice and Research 80, no. 1 (March 1, 2019): 39–43. http://dx.doi.org/10.3148/cjdpr-2018-031.

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Purpose: To explore dietary changes Albertan women make during pregnancy, reasons they make changes, and alignment with prenatal nutrition recommendations. Methods: Women up to 6 months postpartum were recruited in public health centres and Primary Care Networks. Qualitative data were collected through a self-administered survey including 2 open-ended questions that asked about changes made to food/beverage intake during pregnancy and why these changes were made. Results: A majority (n = 577) of the 737 women completing the survey described changes they made to their food/beverage intake during pregnancy and 193 respondents provided reasons for these changes. Increased intake of fruits/vegetables, meat, milk, and their alternatives (n = 600); limiting or avoidance of foods/beverages known to be harmful during pregnancy (n = 445); and increased food/fluid intake or meal/snack frequency (n = 405) were commonly reported dietary changes. Motivations relating to health and to control physiological changes/manage health conditions were the most frequent reasons provided. Conclusions: Women make diverse dietary changes and have various motivations for food choices during pregnancy. A majority make dietary changes to support a healthy pregnancy. However, the motivation to control discomforts and respond to hunger and thirst sensations reflect a stronger influencer on women’s choices than is currently addressed in prenatal nutrition messages.
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27

Shimpo, Misa, Rie Akamatsu, Yui Kojima, Tetsuji Yokoyama, Tsuyoshi Okuhara, and Tsuyoshi Chiba. "Factors Associated with Dietary Change since the Outbreak of COVID-19 in Japan." Nutrients 13, no. 6 (June 14, 2021): 2039. http://dx.doi.org/10.3390/nu13062039.

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In Japan, dietary habits have greatly changed since the coronavirus disease (COVID-19) outbreak; we examined factors related to dietary changes. An online cross-sectional questionnaire survey was conducted in November 2020 among 6,000 Japanese adults (aged 20–64 years) registered with a research company and gathered data on demographics, socioeconomic factors, medical history, COVID-19 status of the respondent’s family and neighbors, fear of COVID-19, and changes in lifestyle and dietary habits since the COVID-19 outbreak. To the question “Have you made healthier changes to your dietary habits compared with the dietary habits before the spread of COVID-19 (1 year ago, November 2019)?”, 1,215 (20.3%), 491 (8.2%), and 4294 (71.6%) participants answered that their dietary habits were healthier, unhealthier, and unchanged, respectively. Healthier and unhealthier dietary habits were associated with greater fear of COVID-19, altered exercise and sleep times, and smoking. Unhealthy habits were positively associated with living alone, decreasing household income, colleagues with COVID-19, stress, and weight loss/gain. Annual household income, changing household income, COVID-19 in friends, health literacy, exercise frequency, weight loss, and starting smoking were positively associated with healthier dietary changes. The generalizability of these results and strategies to inculcate healthy diets in this “new normal” should be investigated.
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28

Luger, Eva, Rosa Aspalter, Maria Luger, Rita Longin, Anita Rieder, and Thomas Ernst Dorner. "Changes of dietary patterns during participation in a web-based weight-reduction programme." Public Health Nutrition 19, no. 7 (September 28, 2015): 1211–21. http://dx.doi.org/10.1017/s1368980015002852.

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AbstractObjectiveTo examine the weight-loss success associated with distinct dietary patterns and to determine changes of these dietary patterns during participation in a web-based weight-reduction programme.DesignFactor analysis was used to identify the dietary patterns of twenty-two food groups that were administered in 14 d dietary protocols at baseline and after 3 months. Successful weight loss (≥5 % of initial weight) and BMI were calculated. Logistic regression analyses were used to assess the rates of weight-loss success from each dietary pattern and changing or remaining in the initial dietary pattern. A generalised linear mixed model was used to estimate the effects of changing or staying in a dietary pattern on change in BMI.SubjectsAdults (n 1635) aged 18–81 years.SettingUsers of a web-based weight-reduction programme (2006–2012).ResultsParticipants who aligned to a healthful dietary pattern at baseline (OR=1·8; 95 % CI 1·5, 2·3) and after 3 months (OR=1·5; 95 % CI 1·2, 1·9) had a greater chance of successfully losing weight. After adjusting for age, sex, initial dietary pattern and BMI, participants who started with or changed to the healthful dietary pattern had a greater chance of being successful (OR=1·4; 95 % CI 1·1, 1·7) and a higher BMI reduction of 0·30 (95 % CI 0·2, 0·5) kg/m2 compared with those who started with or changed to the energy-dense or high-carbohydrate dietary pattern.ConclusionsA favourable healthful dietary pattern at the beginning and after 3 months was positively associated with anthropometry. However, successful weight loss was feasible in each dietary pattern.
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29

Forbes, Laura, Jocelyn Graham, Casey Berglund, and Rhonda Bell. "Dietary Change during Pregnancy and Women’s Reasons for Change." Nutrients 10, no. 8 (August 8, 2018): 1032. http://dx.doi.org/10.3390/nu10081032.

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Women often make dietary changes during pregnancy; however, dietary modifications and reasons for changes are not well studied. We aimed to describe the dietary changes made during pregnancy, describe reasons for dietary changes, and determine what changes aligned with recommendations. Pregnant women (n = 379) recruited to the Alberta Pregnancy Outcomes and Nutrition (APrON) study in 2009/2010 completed a questionnaire in which they described dietary changes made during pregnancy and reasons for those changes. Changes and reasons were coded into categories. Women commonly reported increasing their intake of milk products, fruit, and sweet items and commonly decreased or eliminated intake of caffeine, alcohol, and meats. Women frequently reduced intake of foods for the baby’s health and increased foods to satisfy cravings. Changes made commonly aligned with recommendations for caffeine, alcohol intake, food safety, milk and alternatives, and fruit. Changes contrary to recommendations were common for fish and meats. The dietary changes women make during pregnancy appear to reflect women’s efforts to balance physiological changes accompanying pregnancy with the desire for healthy pregnancy outcomes. Understanding the reasons behind dietary change during pregnancy will help researchers and health professionals design effective strategies and public health messages to promote healthier pregnancies.
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YAMAMOTO, Mari, Nobufumi TAHARA, Yuichi YAMAGUCHI, and Kenkou TSUJI. "Changes in Dietary Fiber Contents in Tea Leaves." NIPPON SHOKUHIN KAGAKU KOGAKU KAISHI 43, no. 12 (1996): 1309–13. http://dx.doi.org/10.3136/nskkk.43.1309.

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Kudlová, Eva, and Dagmar Schneidrová. "Dietary Patterns and Their Changes in Early Childhood." Central European Journal of Public Health 20, no. 2 (June 1, 2012): 126–34. http://dx.doi.org/10.21101/cejph.a3703.

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32

Walker, Alexander R. P., Betty F. Walker, and Sandra Stelma. "Is breast cancer avoidable? Could dietary changes help?" International Journal of Food Sciences and Nutrition 46, no. 4 (January 1995): 373–81. http://dx.doi.org/10.3109/09637489509012569.

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33

Woo, Hee-Soon. "Dysphagia and Dietary Changes Cause of Frontotemporal Dementia." Swallowing Rehabilitation 1, no. 1 (March 31, 2018): 7–14. http://dx.doi.org/10.31115/sr.2018.1.1.7.

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34

Quintero-Lesmes, Doris Cristina, and Oscar F. Herran. "Food Changes and Geography: Dietary Transition in Colombia." Annals of Global Health 85, no. 1 (March 5, 2019): 28. http://dx.doi.org/10.5334/aogh.1643.

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35

Rosenberg, Karen. "Dietary Changes Affect Biomarkers of Colon Cancer Risk." AJN, American Journal of Nursing 115, no. 10 (October 2015): 53. http://dx.doi.org/10.1097/01.naj.0000471945.69664.1d.

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36

Watt, R. G., and A. Sheiham. "Dietary patterns and changes in inner city adolescents." Journal of Human Nutrition and Dietetics 9, no. 6 (December 1996): 451–61. http://dx.doi.org/10.1046/j.1365-277x.1996.00480.x.

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37

Sorensen, Glorian, Anne Stoddard, and Everly Macario. "Social Support and Readiness to Make Dietary Changes." Health Education & Behavior 25, no. 5 (October 1998): 586–98. http://dx.doi.org/10.1177/109019819802500506.

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38

Capewell, S., and M. O'Flaherty. "Can dietary changes rapidly decrease cardiovascular mortality rates?" European Heart Journal 32, no. 10 (March 2, 2011): 1187–89. http://dx.doi.org/10.1093/eurheartj/ehr049.

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39

Bing, R. F., A. M. Heagerty, and J. D. Swales. "Dietary Changes in Membrane Lipids and Leucocyte Calcium." Journal of Cardiovascular Pharmacology 12, no. 3 (1988): S110–113. http://dx.doi.org/10.1097/00005344-198800120-00015.

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