jbm > Volume 29(1); 2022 > Article
Heu, Lee, Kim, Ha, and Park: Validation of a New Food Frequency Questionnaire for Protein Intake Assessment in Korean

Abstract

Background

Protein intake is a modifiable factor associated with sarcopenia prevention; however, no appropriate methods exist to assess dietary protein intake in Koreans. This study developed and validated a simple and convenient food frequency questionnaire (FFQ) to determine protein intake in Koreans.

Methods

A total of 120 participants aged >19 years were asked to complete both the FFQ used by the Korean National Health and Nutrition Examination Survey (KNHANES) and the newly developed Korean Protein Assessment Tool (KPAT). Protein intakes measured using the FFQ and the KPAT were compared using Pearson correlation coefficients, Bland-Altman plots, and intraclass correlation coefficients.

Results

Protein intakes from the FFQ (62.06±25.56 g/day) and KPAT (61.12±24.26 g/day) did not differ significantly (P=0.144). Pearson’s correlation coefficient values ranging from 0.92 to 0.96 indicated a positive correlation, while the intraclass correlation coefficient of 0.979 indicated excellent reliability in protein intake of the FFQ and the KPAT. The Bland-Altman plot also showed high agreement in the mean differences in protein intakes estimated by the FFQ and the KPAT.

Conclusions

KPAT, a newly developed and simplified method, showed an acceptable correlation compared to previous FFQ tools. Thus, the KPAT may be useful to assess dietary protein intake in the Korean population.

INTRODUCTION

Sarcopenia is a progressive skeletal muscle disease characterized by a gradual loss of muscle mass and function and related to a high risk for falls, frailty, hospitalization, and mortality.[1] Epidemiological studies showed that sufficient protein intake was positively associated with muscle protein synthesis in the elders.[2,3] The European Society for Clinical Nutrition and Metabolism Expert Group suggested protein intakes of 1.0 to 1.2 g/kg/day for healthy adults in the age of more than 65 years old, and 1.2 to 1.5 g/kg/day for older adults with the disease at risk of malnutrition.[4] Our previous double-blind randomized controlled trial reported that protein supplementation of 1.5 g/kg/day improved muscle mass and physical performance compared to protein supplementation of 0.8 g/kg/day or 1.2 g/kg/day in undernourished pre-frail and frail older Koreans.[5] However, the Korean National Health and Nutrition Examination Survey (KNHANES) showed that 48% of elderly men and 60% of elderly women consumed less than the amount of dietary reference intakes for Koreans (KDRI), the recommended amount of nutrients for Korean population, 0.91 g/kg/day.[6]
Identifying appropriate methods is important for evaluating protein intake. Protein intake cannot be measured using serum or urine samples, since serum level of protein is always maintained at a certain level, and protein is not appeared in urine unless patients have kidney disease.[7] Thus, protein intake can be evaluated by various dietary surveys including 24-hr recall, dietary records, and the food frequency questionnaire (FFQ), which measure all nutrients including protein.[8] Dietary records and 24-hr recall are not good for the measurement of habitual intake, while FFQ is reflect habitual intake but takes a long time to complete because of containing 112 food items to measure all nutrient intake.[9] There was a rapid self-management FFQ to evaluate dietary protein intake which included food items frequently consumed by the French population.[10] However, since the major protein foods for the Korean and French population are different according to the KNHANES, the French FFQ could not be used in the Korean population.[11] Thus, a new rapid questionnaire to measure only protein intake is needed to develop based on major protein foods consumed by Korean using the KNHANES data. To validate the newly developed questionnaire called Korean Protein Assessment Tool (KPAT), protein intake was measured by KPAT and FFQ using KNHANES was compared. Therefore, the purpose of the present study was to investigate the hypothesis that protein intakes measured by the newly developed simplified method called KPAT and FFQ using KNHANES were not significantly different.

METHODS

1. Participants

Adults aged 19 or older were recruited from inpatient and outpatient of Chung-Ang University Hospital Orthopedics. Participants who had changed their dietary patterns over the past year, had cognitive impairment, were pregnant, or were lactating women were excluded. This study was conducted in accordance with the Declaration of Helsinki, and all procedures were approved by the Institutional Review Board (IRB) of Chung-Ang University (IRB no. 2107-037-19376). Written informed consent was obtained from all the patients before participation.

2. Assessment of dietary protein intake

Demographic information about age, sex, height, and weight was self-reported from all participants. The dietician conducted face-to-face interviews to complete 2 questionnaires, the FFQ from the KNHANES and the developed separate questionnaire for protein intake called KPAT. The FFQ and the KPAT assessed average intake over the past year. Protein intake in FFQ was analyzed using CAN-Pro 5.0 (Korean Nutrition Society, Seoul, Korea), and protein intake in KPAT was analyzed by a KPAT self-calculated file.
The FFQ used by the KNHANES included 112 food items, and there were 9 intake frequency categories; once a day, twice a day, 3 times a day, once a week, 2 to 4 times a week, 5 to 6 times a week, once a month, 2 to 3 a month and never or seldom.[12] The serving size of food items was categorized by small, medium, large in FFQ. The KPAT was developed by adjusting the food list for estimating protein intake by integrating with the KNHANES 2013 to 2018.[13-17] The KPAT comprised 39 categories with 50 food items with high protein content and frequently consumed by Koreans in the existing FFQ order (Table 1). Food with similar protein content was arranged in one category and calculated on average. The frequency of food intake was written as the number per day, week, or month.

3. Statistical analyses

All data were analyzed using the SPSS statistics version 27.0 (SPSS Inc., Chicago, IL, USA). The significance level was set at a P-value of less than 0.05. Continuous variables were presented as the mean±standard deviation using the independent t-tests, and the proportions of nominal were presented by numbers (percentages) using the χ2 test. The difference in the intake of protein between the FFQ and the KPAT was analyzed by a paired t-test. The correlation between protein intakes of the FFQ and the KPAT was investigated with the Pearson correlation coefficients. The Bland-Altman plot was used to compare the FFQ and the KPAT for quantifying the protein intakes. The distribution of protein intake was categorized into quartiles to test agreement at an individual level, and the Intraclass correlation coefficient was applied to assess reliability based on the 95% confident interval (CI) between the 2 dietary assessment methods, the FFQ and the KPAT.[18]

RESULTS

One hundred twenty participants completed both the FFQ and the KPAT (Table 2). There were 33% males and 67% females in total participants, 31 (54.4%) of participants aged <65 years, and 49 (77.8%) of participants aged ≥65 years were women. Participants were classified based on the age of 65 due to the difference in daily protein intake in accordance with KDRI.[11] Participants aged <65 years were significantly taller and heavier and consumed higher energy, carbohydrate, fat, and protein compared to participants aged ≥65 years. There was no significant difference in body mass index between the participants aged <65 years and aged ≥65 years.
Protein intakes investigated by the FFQ and the KPAT were not significantly different in both participants aged <65 years and aged ≥65 years (Table 3). The intraclass correlation coefficient of 0.979 (95% CI, 0.970-0.986) indicated excellent reliability in protein intakes (g/day) estimated by both the FFQ and the KPAT (Table 4). Regarding protein intake as g/kg/day, the intraclass correlation coefficient of 0.972 (95% CI, 0.960-0.980) also indicated excellent reliability in protein intakes assessed by FFQ and KPAT (Supplementary Appendix 1). Pearson’s correlation coefficient showed a significant positive correlation between the FFQ and the KPAT in total participants and participants aged <65 years and aged ≥65 years (Fig. 1). With the Bland-Altman plot, there were no significant mean differences of estimated protein intake measured by 2 methods within 95% limits of agreement (Fig. 2).

DISCUSSION

The present study showed that protein intake estimated by both the FFQ and the KPAT were not significantly different, and the measurement values of protein intake between the FFQ and the KPAT were positively correlated.
According to 2013 to 2017 the KNHANES, the average protein intake was 83 to 88 g/day for men aged <65 years, 58 to 64 g/day for women aged <65 years.[13-17] In this study, the average protein intake estimated by FFQ and KPAT was 83 and 81 g/day for men aged <65 years, 64 and 63 g/day for women aged <65 years, respectively. Protein intake of participants aged <65 years in this study showed similar results to the KNHANES data. In addition, according to the 2013 to 2017 KNHANES, the average protein intake was 58 to 69 g/day for men aged ≥65 years, 38 to 50 g/day for women aged ≥65 years.[13-17] In this study, the average protein intake estimated by FFQ and KPAT was 62 and 60 g/day for men aged ≥65 years, 50 and 50 g/day for women aged ≥65 years, respectively. Thus, the protein intake of participants aged ≥65 years in this study showed similar results to the KNHANES data. Previous studies reported that Korean elders over 65 years old consumed about 20 g less protein per day than adults aged 30 to 64 years old, which showed similar to the results of the present study.[6,19] The KDRI recommends a daily protein intake of 60 to 65 g/day for men aged <65 years and 50 to 55 g/day for women aged <65 years, and 60 g/day for men aged ≥65 years and 50 g/day for women aged ≥65 years.[11] The study showed that 21% of the Koreans consumed less than the recommended amount of intake based on the KDRI for protein. Our result was similar to 23%, which was reported by the KNHANES.[20]
Morin et al. [10] previously developed a rapid the FFQ for protein intake of the French population and showed that protein intakes were not significantly different using paired t-test between their new FFQ and dietary record (P=0.075), and between the new FFQ and 24-hr recall (P=0.520), which were consistent with our study (P=0.144). The French study showed that protein intakes measured by the new FFQ, dietary record, and 24-hr recall had no difference in variability using the Bland-Altman plot.[10] In the present study, protein intakes measured by the FFQ and KPAT had no difference in variability using the Bland-Altman plot with the narrow range compared to the previous French study.
The French FFQ comprised 20 food items, frequently consumed by the French population, such as meat and dairy products.[10] However, KPAT included not only meat and dairy products but also grains which were major protein foods in Korea. According to the KNHANES, grains were the top protein source, followed by meat, fish and shellfish, vegetables, beans, and legumes.[11] In this study, grains were also the top protein source, followed by meat, egg, vegetables, pizza. The ranking of protein-based foods in our study was similar to that of protein-based foods in the KNHANES. Animal-based proteins with a high protein content of a higher quality contained all the essential amino acids required by the human body and were more digestible.[21] However, the main sources of dietary protein in the Korean population were rice and other grains. The Korean diet is a plant-based protein, contributing to nearly 2-thirds of total protein intake and the amount of protein in these foods could not be ignored.[22]
In the present study, the Pearson correlation coefficient of protein intake estimated by the FFQ and the KPAT was 0.92 to 0.96, suggesting a very high correlation as compared with other nutrient validation. Previous studies showed that Pearson correlation coefficients obtained from calcium intakes to validate questionnaires were in the range of 0.56 to 0.84 in Asian,[23,24] and 0.64 to 0.90 in westerners.[25,26] The correlation coefficients of calcium questionnaires were narrower ranges in studies done in Americans and Europeans than in studies done in Asian. The sources of calcium intake for Americans and Europeans were simple due to their high large dependence on milk and milk products, which were rich in calcium content and had high availability and good absorption in the intestine.[27] The sources of calcium in the Asian diet were more diverse than the American and European diet, and their source of calcium included dark green, beans, seaweed, and seafood.[28]
Gross classification according to the quartiles of intake indicated that 74% of participants were classified into the same or adjacent quartile. Intraclass correlation coefficient showed excellent reliability of 0.979, a 97.9% agreement, between the FFQ and the KPAT. This result was better than 0.79 to 0.86 of the intraclass correlation coefficient obtained from calcium intake in a previous study.[29] In addition, the Bland-Altman plot showed good agreement between the FFQ and the KPAT.
The present study had a few limitations. First, basic dietary survey methods might have some reporting bias using self-reported dietary intake and recall bias using intake memories over the past year. Second, the intake of protein could be affected by seasonal variation, and the developed KPAT was not validated in all 4 seasons. Third, Participants were recruited only in a hospital, not the entire population, and selection bias might have existed.
The KPAT has a few strengths. First, the newly developed KPAT is a simple questionnaire tool to assess protein intake. Second, the KPAT is convenient and simple to estimate protein intake, since KPAT consists of only 39 questions but FFQ has 112 questions. Third, the dietary protein intake can be assessed by good validity and reproducibility. The present study suggests that the developed KPAT can be a useful and simple evaluation tool to assess dietary protein intake for the Korean population. The KPAT can be useful for the rapid evaluation of protein intake at the clinical setting, and for prescribing appropriated amount of protein for patients whose protein intake is low. The KPAT will be released as an online version to use at the clinical setting.

Supplementary Information

Acknowledgments

The authors are grateful to the participants for their involvement in this study.

DECLARATIONS

Funding

This work was supported by Korean Society for Bone and Mineral Research and BK21 FOUR (Fostering Outstanding Universities for Research) project of the National Research Foundation of Korea Grant.

Ethics approval and consent to participate

This study was conducted in accordance with the Declaration of Helsinki, and all procedures were approved by the Institutional Review Board (IRB) of Chung-Ang University (IRB no. 2107-037-19376).

Conflict of interest

No potential conflict of interest relevant to this article was reported.

Fig. 1
Pearson correlation of protein intake assessed the food frequency questionnaires used by the Korean National Health and Nutrition Examination Survey (KNHANES) and the Korean Protein Assessment Tool (KPAT) for all participants, participants aged <65 years, and participants aged ≥65 years.
jbm-2022-29-1-35f1.jpg
Fig. 2
Bland-Altman plot of difference in protein intake assessed the food frequency questionnaires used by the Korean Notional Health and Nutrition Examination Survey (KNHANES) and the Korean Protein Assessment Tool (KPAT) for all participants, participants aged <65 years, and participants aged ≥65 years.
jbm-2022-29-1-35f2.jpg
Table 1
List of the food items included in the Korean Protein Assessment Tool (KPAT)
Food group Categories Food item
Grains Rice Rice
Mixed grains Mixed grains
Rice cakes Rice cakes
Noodles Noodles
Breads, Cakes Breads, Cakes
Root and tuber crops Potato, Sweet potato
Corns Corns

Legumes Nuts Nuts
Soybeans Soybeans
Bean curd Bean curd
Soy bean milk Soy bean milk
Fermented soybean paste Fermented soy bean paste

Meats & Fishes Meats Meats
Meat soups Meat soups
Meat processed products Ham, Sausage, Bacon
Egg Egg
Fishes Chub mackerel, Cutlassfish, Corvina, Pacific saury
Squid, Shrimp Squid, Shrimp
Long arm octopus, Webfoot octopus Long arm octopus, Webfoot octopus
Anchovy Anchovy
Shellfish Shellfish
Fish cake Fish cake
Fish soups Fish soups

Vegetables Vegetables Vegetables
Kimchi Kimchi
Sea weed Sea weed
Mushrooms Mushrooms

Dairy products Milk Milk
Liquid yogurt Liquid yogurt
Yogurt Yogurt
Cheddar cheese Cheddar cheese

Fruits Fruits Fruits (Banana, Apple, Grape, Strawberry)
Melon, Watermelon Melon, Watermelon

Instant foods Ramen Ramen
Hamburger, Sandwich Hamburger, Sandwich
Pizza Pizza
Dumpling Dumpling
Snacks Snacks
Makgeolli (Rice wine) Makgeolli (Rice wine)
Table 2
General characteristics of participants aged <65 years and aged ≥65 years
Total (N=120) Age P-value

<65 years (N=57) ≥65 years (N=63)
Age (yr) 58.85±20.07 40.23±12.00 75.70±5.99 <0.001

Female 80 (66.7) 31 (54.4) 49 (77.8) 0.011

Weight (kg) 59.88±12.96 64.45±15.34 55.74±8.56 <0.001

Height (cm) 160.41±10.17 165.44 ±9.57 155.87±8.45 <0.001

BMI (kg/m2) 23.13±3.63 23.27±3.77 23.00±3.60 0.676

Dietary intake
 Energy intake (kcal/day) 1,808.49±731.41 2,145.17±743.67 1,503.88±573.37 <0.001
 Carbohydrate (g/day) 291.01±115.89 326.15±116.19 259.21±106.87 0.001
 Fat (g/day) 39.57±24.25 52.41±26.27 27.95±14.72 <0.001
 Protein (g/day) 62.06±25.56 72.66±27.19 52.47±19.74 <0.001
 Protein (g/kg/day) 1.04±0.38 1.14±0.40 0.95±0.34 0.006

The data is presented as N (%) of participants for categorical variables or mean±standard deviation for continuous variables.

BMI, body mass index.

Table 3
Comparison of protein intakes assessed by a food frequency questionnaire used by KNHANES and KPAT
Protein intake by KNHANES (g/day) Protein intake by KPAT (g/day) P-valuea) Protein intake by KNHANES (g/kg/day) Protein intake by KPAT (g/kg/day) P-valueb)
Total (N=120) 62.06±25.56 61.12±24.26 0.144 1.04±0.38 1.03±0.37 0.250
Age <65 yr (N=57) 72.66±27.19 71.17±25.97 0.105 1.14±0.40 1.12±0.39 0.189
Age ≥65 yr (N=63) 52.47±19.74 52.02±18.54 0.621 0.95±0.34 0.94±0.32 0.708

The data is presented as mean±standard deviation for continuous variables.

a) Statistical difference on protein intakes between KNHANES and KPAT using the paired t-test.

b) Statistical difference on protein intakes per body weight between KNHANES and KPAT using the paired t-test.

KNHANES, the Korean National Health and Nutrition Examination Survey; KPAT, the Korean Protein Assessment Tool.

Table 4
Intraclass correlation coefficient for protein intake assessed by the food frequency questionnaires used by KNHANES and KPAT
Protein intake by KNHANES (g/day) Protein intake by KPAT (g/day) Intraclass correlation coefficient
≤45.46 45.46 < to ≤ 59.30 59.30 < to ≤ 72.17 >72.17
≤43.47 25a) 4 1 0 0.979
43.47 < to ≤ 59.58 5 20 5 0
59.58 < to ≤ 75.50 0 6 19 5
>75.50 0 0 5 25

a) Each value expressed the number of participants matching each quartile in the food frequency questionnaire and KPAT and each quartile had 30 participants.

KNHANES, the Korean National Health and Nutrition Examination Survey; KPAT, the Korean Protein Assessment Tool.

REFERENCES

1. Cruz-Jentoft AJ, Bahat G, Bauer J, et al. Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing 2019;48:16-31. https://doi.org/10.1093/ageing/afy169.
crossref pmid
2. Liao CD, Chen HC, Huang SW, et al. The role of muscle mass gain following protein supplementation plus exercise therapy in older adults with sarcopenia and frailty risks: A systematic review and meta-regression analysis of randomized trials. Nutrients 2019;11:1713.https://doi.org/10.3390/nu11081713.
crossref pmc
3. Deer RR, Volpi E. Protein intake and muscle function in older adults. Curr Opin Clin Nutr Metab Care 2015;18:248-53. https://doi.org/10.1097/mco.0000000000000162.
crossref pmid pmc
4. Deutz NE, Bauer JM, Barazzoni R, et al. Protein intake and exercise for optimal muscle function with aging: recommendations from the ESPEN Expert Group. Clin Nutr 2014;33:929-36. https://doi.org/10.1016/j.clnu.2014.04.007.
crossref pmid pmc
5. Park Y, Choi JE, Hwang HS. Protein supplementation improves muscle mass and physical performance in undernourished prefrail and frail elderly subjects: a randomized, double-blind, placebo-controlled trial. Am J Clin Nutr 2018;108:1026-33. https://doi.org/10.1093/ajcn/nqy214.
crossref pmid
6. Park HA. Adequacy of protein Intake among Korean elderly: An analysis of the 2013-2014 Korea national health and nutrition examination survey data. Korean J Fam Med 2018;39:130-4. https://doi.org/10.4082/kjfm.2018.39.2.130.
crossref pmid pmc
7. Young VR, Marchini JS, Cortiella J. Assessment of protein nutritional status. J Nutr 1990;120:Suppl 11. 1496-502. https://doi.org/10.1093/jn/120.suppl_11.1496.
crossref pmid
8. McClung HL, Ptomey LT, Shook RP, et al. Dietary intake and physical activity assessment: Current tools, techniques, and technologies for use in adult populations. Am J Prev Med 2018;55:e93-104. https://doi.org/10.1016/j.amepre.2018.06.011.
crossref pmid
9. Dumartheray EW, Krieg MA, Cornuz J, et al. Validation and reproducibility of a semi-quantitative Food Frequency Questionnaire for use in elderly Swiss women. J Hum Nutr Diet 2006;19:321-30. https://doi.org/10.1111/j.1365-277X.2006.00721.x.
crossref pmid
10. Morin P, Herrmann F, Ammann P, et al. A rapid self-administered food frequency questionnaire for the evaluation of dietary protein intake. Clin Nutr 2005;24:768-74. https://doi.org/10.1016/j.clnu.2005.03.002.
crossref pmid
11. Ministry of Health and Welfare, The Korean Nutrition Society. Dietary reference intakes for Koreans 2020. Sejong: Ministry of Health and Welfare; 2020.

12. Korea Disease Control and Prevention Agency. Guideline for raw data use of the seventh Korea national health and nutrition examination survey (KNAHNES VII) 2016-2018 2020 [cited by 2022 Feb 15]. Available from: https://knhanes.cdc.go.kr/knhanes/sub03/sub03_06_02.do.

13. Ministry of Health and Welfare, Korea Centers for Disease Control and Prevention. Korea Health Statistics 2013: Korea national health and nutrition examination survey (KNHANES VI-1). Sejong: Korea Centers for Disease Control and Prevention; 2014.

14. Ministry of Health and Welfare, Korea Centers for Disease Control and Prevention Korea Health Statistics. 2014 Korea national health and nutrition examination survey (KNHANES VI-2). Sejong: Korea Centers for Disease Control and Prevention; 2015.

15. Ministry of Health and Welfare, Korea Centers for Disease Control and Prevention Korea Health Statistics. 2016 Korea national health and nutrition examination survey (KNHANES VII-1). Sejong: Korea Centers for Disease Control and Prevention; 2017.

16. Ministry of Health and Welfare, Korea Centers for Disease Control and Prevention Korea Health Statistics. 2017 Korea national health and nutrition examination survey (KNHANES VII-2). Sejong: Korea Centers for Disease Control and Prevention; 2018.

17. Ministry of Health and Welfare, Korea Centers for Disease Control and Prevention Korea Health Statistics. 2018 Korea national health and nutrition examination survey (KNHANES VII-3). Sejong: Korea Centers for Disease Control and Prevention; 2019.

18. Koo TK, Li MY. A guideline of selecting and reporting intraclass correlation coefficients for reliability research. J Chiropr Med 2016;15:155-63. https://doi.org/10.1016/j.jcm.2016.02.012.
crossref pmid pmc
19. Park KB, Park HA, Kang JH, et al. Animal and plant protein intake and body mass index and waist circumference in a Korean elderly population. Nutrients 2018;10:577.https://doi.org/10.3390/nu10050577.
crossref pmc
20. Statistics Korea. Korean statistical information service: Statistical database 2021 [cited by 2021 Feb 15]. Available from: https://kosis.kr/eng/.

21. Landi F, Calvani R, Tosato M, et al. Protein intake and muscle health in old age: From biological plausibility to clinical evidence. Nutrients 2016;8:295.https://doi.org/10.3390/nu8050295.
crossref pmc
22. So E, Choi SK, Joung H. Impact of dietary protein intake and obesity on lean mass in middle-aged individuals after a 12-year follow-up: the Korean Genome and Epidemiology Study (KoGES). Br J Nutr 2019;122:322-30. https://doi.org/10.1017/s000711451900117x.
crossref pmid
23. Khan NC, Mai le B, Hien VT, et al. Development and validation of food frequency questionnaire to assess calcium intake in postmenopausal Vietnamese women. J Nutr Sci Vitaminol (Tokyo) 2008;54:124-9. https://doi.org/10.3177/jnsv.54.124.
crossref pmid
24. Chee WS, Suriah AR, Zaitun Y, et al. Dietary calcium intake in postmenopausal Malaysian women: comparison between the food frequency questionnaire and three-day food records. Asia Pac J Clin Nutr 2002;11:142-6. https://doi.org/10.1046/j.1440-6047.2002.00276.x.
crossref pmid
25. Magkos F, Manios Y, Babaroutsi E, et al. Development and validation of a food frequency questionnaire for assessing dietary calcium intake in the general population. Osteoporos Int 2006;17:304-12. https://doi.org/10.1007/s00198-004-1679-1.
crossref pmid
26. Montomoli M, Gonnelli S, Giacchi M, et al. Validation of a food frequency questionnaire for nutritional calcium intake assessment in Italian women. Eur J Clin Nutr 2002;56:21-30. https://doi.org/10.1038/sj.ejcn.1601278.
crossref pmid
27. Martini D, Rosi A, Angelino D, et al. Calcium intake from different food sources in Italian women without and with non-previously diagnosed osteoporosis. Int J Food Sci Nutr 2021;72:418-27. https://doi.org/10.1080/09637486.2020.1818698.
crossref pmid
28. Bhavadharini B, Dehghan M, Mente A, et al. Association of dairy consumption with metabolic syndrome, hypertension and diabetes in 147 812 individuals from 21 countries. BMJ Open Diabetes Res Care 2020;8:e000826.https://doi.org/10.1136/bmjdrc-2019-000826.
crossref pmid pmc
29. Xu L, Porteous JE, Phillips MR, et al. Development and validation of a calcium intake questionnaire for postmenopausal women in China. Ann Epidemiol 2000;10:169-75. https://doi.org/10.1016/s1047-2797(99)00055-1.
crossref pmid


ABOUT
ARTICLE CATEGORY

Browse all articles >

BROWSE ARTICLES
EDITORIAL POLICY
FOR CONTRIBUTORS
Editorial Office
#1001, Hyundai Kirim Officetel, 42 Seocho-daero 78-gil, Seocho-gu, Seoul 06626, Korea
Tel: +82-2-3473-2231    Fax: +82-70-4156-2230    E-mail: editors.jbm@gmail.com                

Copyright © 2024 by The Korean Society for Bone and Mineral Research.

Developed in M2PI

Close layer
prev next