Association of Hours of Paid Work with Dietary Intake and Quality in Japanese Married Women: A Cross-Sectional Study
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Population
2.2. Dietary Intake
2.3. Dietary Quality
2.4. Hours of Paid Work
2.5. Other Variables
2.6. Statistical Analysis
3. Results
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Bianchi, S.M.; Milkie, M.A.; Sayer, L.C.; Robinson, J.P. Is anyone doing the housework? Trends in the gender division of household labor. Soc. Forces 2000, 79, 191–228. [Google Scholar] [CrossRef]
- Statistics Bureau, Ministry of Internal Affairs and Communications. Labor Force Survey Basic Tabulation Whole Japan Yearly, Table 1-4-1, Population of 15 Years Old and over by Labor Force Status, Marital Status and Age Groups. Available online: https://www.e-stat.go.jp/en/dbview?sid=0003008335 (accessed on 15 August 2021).
- Knudsen, K.; Wærness, K. National context and spouses’ housework in 34 countries. Eur. Sociol. Rev. 2007, 24, 97–113. [Google Scholar] [CrossRef]
- OECD. Employment: Time Spent in Paid and Unpaid Work, by Sex. Available online: https://stats.oecd.org/index.aspx?queryid=54757 (accessed on 15 August 2021).
- Bauer, K.W.; Hearst, M.O.; Escoto, K.; Berge, J.M.; Neumark-Sztainer, D. Parental employment and work-family stress: Associations with family food environments. Soc. Sci. Med. 2012, 75, 496–504. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Cawley, J.; Liu, F. Maternal employment and childhood obesity: A search for mechanisms in time use data. Econ. Hum. Biol. 2012, 10, 352–364. [Google Scholar] [CrossRef] [PubMed]
- Monsivais, P.; Aggarwal, A.; Drewnowski, A. Time spent on home food preparation and indicators of healthy eating. Am. J. Prev. Med. 2014, 47, 796–802. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Darmon, N.; Drewnowski, A. Does social class predict diet quality? Am. J. Clin. Nutr. 2008, 87, 1107–1117. [Google Scholar] [CrossRef] [Green Version]
- Nishikitani, M.; Nakao, M.; Tsurugano, S.; Yano, E. The possible absence of a healthy-worker effect: A cross-sectional survey among educated Japanese women. BMJ Open 2012, 2, e000958. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Fan, W.; Lam, J.; Moen, P.; Kelly, E.; King, R.; McHale, S. Constrained choices? Linking employees’ and spouses’ work time to health behaviors. Soc. Sci. Med. 2015, 126, 99–109. [Google Scholar] [CrossRef] [Green Version]
- Murakami, K.; Miyake, Y.; Sasaki, S.; Tanaka, K.; Ohya, Y.; Hirota, Y. Education, but not occupation or household income, is positively related to favorable dietary intake patterns in pregnant Japanese women: The Osaka Maternal and Child Health Study. Nutr. Res. 2009, 29, 164–172. [Google Scholar] [CrossRef]
- Miller, J.; Chan, L.; Mehta, K.; Roberts, R.; Dickinson, K.M.; Yaxley, A.; Matwiejczyk, L.; Thomas, J.; Wray, A.; Jackson, K.; et al. Dietary intake of working women with children does not appear to be influenced by hours of employment: A secondary analysis of the Australian Health Survey (2011–2013). Appetite 2016, 105, 106–113. [Google Scholar] [CrossRef]
- Raza, L.; Ali, M.T.; Hasnain, A. Comparison of dietary practices and body mass index among educated housewives and working women in Karachi. J. Ayub. Med. Coll. Abbottabad 2017, 29, 293–297. [Google Scholar]
- World Economic Forum. The Global Gender Gap Report. 2018. Available online: http://www3.weforum.org/docs/WEF_GGGR_2018.pdf (accessed on 15 August 2021).
- Statistics Bureau, Ministry of Internal Affairs and Communications. Survey on Time Use and Leisure Activities. 2016 Survey on Time Use and Leisure Activities Questionnaire B Results on Time Use by Detailed Activity Coding Time Use, Table 16-1. Average Time Spent in Activities for All Persons (Main Activities) by Kind of Activities, Day of the Week, Sex, Family Type of Household, Usual Economic Activities of a Married Couple (Husbands and Wives)-Japan. Available online: https://www.e-stat.go.jp/en/dbview?sid=0003213070 (accessed on 15 August 2021).
- Djupegot, I.L.; Nenseth, C.B.; Bere, E.; Bjornara, H.B.T.; Helland, S.H.; Overby, N.C.; Torstveit, M.K.; Stea, T.H. The association between time scarcity, sociodemographic correlates and consumption of ultra-processed foods among parents in Norway: A cross-sectional study. BMC Publ. Health 2017, 17, 447. [Google Scholar] [CrossRef] [PubMed]
- Horning, M.L.; Fulkerson, J.A.; Friend, S.E.; Story, M. Reasons parents buy prepackaged, processed meals: It is more complicated than “I Don’t Have Time”. J. Nutr. Educ. Behav. 2017, 49, 60–66. [Google Scholar] [CrossRef] [Green Version]
- Jabs, J.; Devine, C.M. Time scarcity and food choices: An overview. Appetite 2006, 47, 196–204. [Google Scholar] [CrossRef] [PubMed]
- Mc Morrow, L.; Ludbrook, A.; Macdiarmid, J.I.; Olajide, D. Perceived barriers towards healthy eating and their association with fruit and vegetable consumption. J. Publ. Health 2017, 39, 330–338. [Google Scholar] [CrossRef] [Green Version]
- Pinho, M.G.M.; Mackenbach, J.D.; Charreire, H.; Oppert, J.-M.; Bardos, H.; Glonti, K.; Rutter, H.; Compernolle, S.; De Bourdeaudhuij, I.; Beulens, J.W.J.; et al. Exploring the relationship between perceived barriers to healthy eating and dietary behaviours in European adults. Eur. J. Nutr. 2018, 57, 1761–1770. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Fukui, T.; Rhaman, M.; Takahashi, O.; Saito, M.; Shimbo, T.; Endo, H.; Misao, H.; Fukuhara, S.; Hinohara, S. The ecology of medical care in Japan. Jpn. Med. Assoc. J. 2005, 48, 163–167. [Google Scholar]
- Enomoto, A.; Saito, A.; Takahashi, O.; Kimura, T.; Tajima, R.; Rahman, M.; Iida, K. Associations between health literacy and underweight and overweight among japanese adults aged 20 to 39 years: A cross-sectional study. Health Educ. Behav. 2020, 47, 631–639. [Google Scholar] [CrossRef]
- Fukui, T.; Rahman, M.; Ohde, S.; Hoshino, E.; Kimura, T.; Urayama, K.Y.; Omata, F.; Deshpande, G.A.; Takahashi, O. Reassessing the ecology of medical care in Japan. J. Commun. Health 2017, 42, 935–941. [Google Scholar] [CrossRef]
- Matsuura, N.; Saito, A.; Takahashi, O.; Rahman, M.; Tajima, R.; Mabashi-Asazuma, H.; Iida, K. Associations between nutritional adequacy and insomnia symptoms in Japanese men and women aged 18–69 years: A cross-sectional study. Sleep Heal. 2020, 6, 197–204. [Google Scholar] [CrossRef]
- Statistics Bureau, Ministry of Internal Affairs and Communications. Population Census/2010 Population Census/Basic Complete Tabulation on Population and Households Japan. Available online: http://www.stat.go.jp/english/data/kokusei/index.html (accessed on 15 August 2021).
- Shimizutani, S. A new anatomy of the retirement process in Japan. Jpn. World Econ. 2011, 23, 141–152. [Google Scholar] [CrossRef] [Green Version]
- Ministry of Health, Labour and Welfare, Japan. Dietary Reference Intakes for Japanese. 2015. Available online: http://www.mhlw.go.jp/stf/seisakunitsuite/bunya/0000208970.html (accessed on 15 August 2021).
- Kobayashi, S.; Murakami, K.; Sasaki, S.; Okubo, H.; Hirota, N.; Notsu, A.; Fukui, M.; Date, C. Comparison of relative validity of food group intakes estimated by comprehensive and brief-type self-administered diet history questionnaires against 16 d dietary records in Japanese adults. Publ. Health Nutr. 2011, 14, 1200–1211. [Google Scholar] [CrossRef] [PubMed]
- Kobayashi, S.; Honda, S.; Murakami, K.; Sasaki, S.; Okubo, H.; Hirota, N.; Notsu, A.; Fukui, M.; Date, C. Both comprehensive and brief self-administered diet history questionnaires satisfactorily rank nutrient intakes in Japanese adults. J. Epidemiol. 2012, 22, 151–159. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Council for Science and Technology; Ministry of Education, Culture, Sports, Science and Technology, Japan. Standard Tables of Food Composition in Japan, Fifth Revised and Enlarged Edition; National Printing Bureau: Tokyo, Japan, 2005. (In Japanese)
- Fujiwara, A.; Murakami, K.; Asakura, K.; Uechi, K.; Sugimoto, M.; Wang, H.-C.; Masayasu, S.; Sasaki, S. Estimation of starch and sugar intake in a Japanese population based on a newly developed food composition database. Nutrients 2018, 10, 1474. [Google Scholar] [CrossRef] [Green Version]
- Fujiwara, A.; Murakami, K.; Sasaki, S. Relative validity of starch and sugar intake in japanese adults as estimated with comprehensive and brief self-administered diet history questionnaires. J. Epidemiol. 2020, 30, 315–325. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Murakami, K.; Sasaki, S.; Takahashi, Y.; Uenishi, K.; Yamasaki, M.; Hayabuchi, H.; Goda, T.; Oka, J.; Baba, K.; Ohki, K. Misreporting of dietary energy, protein, potassium and sodium in relation to body mass index in young Japanese women. Eur. J. Clin. Nutr. 2008, 62, 111–118. [Google Scholar] [CrossRef] [Green Version]
- Fulgoni, V.L., 3rd; Keast, D.R.; Drewnowski, A. Development and validation of the nutrient-rich foods index: A tool to measure nutritional quality of foods. J. Nutr. 2009, 139, 1549–1554. [Google Scholar] [CrossRef] [Green Version]
- Murakami, K.; Livingstone, M.B.E.; Fujiwara, A.; Sasaki, S. Reproducibility and relative validity of the healthy eating index-2015 and nutrient-rich food index 9.3 estimated by comprehensive and brief diet history questionnaires in japanese adults. Nutrients 2019, 11, 2540. [Google Scholar] [CrossRef] [Green Version]
- World Health Organization. Guideline: Sugars Intake for Adults and Children; World Health Organization: Geneva, Switzerland, 2015. Available online: http://apps.who.int/iris/bitstream/10665/149782/1/9789241549028_eng.pdf?ua=1 (accessed on 15 August 2021).
- Statistics Bureau, Ministry of Internal Affairs and Communications. Survey on Time Use and Leisure Activities, Questionnaire, B. Available online: http://www.stat.go.jp/data/shakai/2001/pdf/chob.pdf (accessed on 15 August 2021). (In Japanese).
- Ogawa, W.; Miyazaki, S. Diagnosis criteria for obesity and obesity disease. Health Eval. Promot. 2015, 42, 301–306. [Google Scholar] [CrossRef] [Green Version]
- Larson, N.I.; Perry, C.L.; Story, M.; Neumark-Sztainer, D. Food preparation by young adults is associated with better diet quality. J. Am. Diet. Assoc. 2006, 106, 2001–2007. [Google Scholar] [CrossRef]
- Welch, N.; McNaughton, S.A.; Hunter, W.; Hume, C.; Crawford, D. Is the perception of time pressure a barrier to healthy eating and physical activity among women? Publ. Health Nutr. 2009, 12, 888–895. [Google Scholar] [CrossRef] [Green Version]
- Williams, L.K.; Thornton, L.; Crawford, D. Optimising women’s diets. An examination of factors that promote healthy eating and reduce the likelihood of unhealthy eating. Appetite 2012, 59, 41–46. [Google Scholar] [CrossRef] [Green Version]
- Devine, C.M.; Jastran, M.; Jabs, J.; Wethington, E.; Farell, T.J.; Bisogni, C.A. “A lot of sacrifices:” work-family spillover and the food choice coping strategies of low-wage employed parents. Soc. Sci. Med. 2006, 63, 2591–2603. [Google Scholar] [CrossRef] [Green Version]
- Eshak, E.S.; Iso, H.; Date, C.; Yamagishi, K.; Kikuchi, S.; Watanabe, Y.; Wada, Y.; Tamakoshi, A. Rice intake is associated with reduced risk of mortality from cardiovascular disease in Japanese men but not women. J. Nutr. 2011, 141, 595–602. [Google Scholar]
- Tajima, R.; Kimura, T.; Enomoto, A.; Yanoshita, K.; Saito, A.; Kobayashi, S.; Masuda, K.; Iida, K. Association between rice, bread, and noodle intake and the prevalence of non-alcoholic fatty liver disease in Japanese middle-aged men and women. Clin. Nutr. 2017, 36, 1601–1608. [Google Scholar] [CrossRef]
- Devine, C.M.; Farrell, T.J.; Blake, C.E.; Jastran, M.; Wethington, E.; Bisogni, C.A. Work conditions and the food choice coping strategies of employed parents. J. Nutr. Educ. Behav. 2009, 41, 365–370. [Google Scholar] [CrossRef] [Green Version]
- Statistics Bureau, Ministry of Internal Affairs and Communications. Survey on Time Use and Leisure Activities.2011 Survey on Time Use and Leisure Activities Questionnaire B Results on Time Use Time Use, 0180202. Average Time Spent for All Persons, for Participants and Participation Rate in Main Activities and Simultaneous Activities (Minor Groups) by Day of the Week, Family Type of Household and Usual Economic Activities of a Married Couple (Husbands and Wives). Available online: https://www.e-stat.go.jp/en/dbview?sid=0003070457 (accessed on 15 August 2021).
- Horikawa, C.; Murayama, N.; Ishida, H.; Yamamoto, T.; Hazano, S.; Nakanishi, A.; Arai, Y.; Nozue, M.; Yoshioka, Y.; Saito, S.; et al. Association between parents’ work hours and nutrient inadequacy in Japanese schoolchildren on weekdays and weekends. Nutrition 2020, 70, 110598. [Google Scholar] [CrossRef]
- Statistics Bureau, Ministry of Internal Affairs and Communications. General Survey on Working Conditions2020, Table 3, Percentage of Companies by Company Size, Industry, and Main Class Of Weekly Scheduled Work Hours, and Average Weekly Scheduled Work Hours. Available online: https://www.e-stat.go.jp/dbview?sid=0003243485 (accessed on 15 August 2021). (In Japanese).
All | Hours of Paid Work Per Week | pc | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0 (Housewives) | 1–14 | 15–34 | 35–42 | ≥43 | |||||||||
n | 644 | (100) | 240 | (37.3) | 82 | (12.7) | 198 | (30.7) | 88 | (13.7) | 36 | (5.6) | |
Age category | 0.59 | ||||||||||||
20–29 years | 10 | (1.6) | 4 | (1.7) | 0 | (0.0) | 2 | (1.0) | 3 | (3.4) | 1 | (2.8) | |
30–39 years | 177 | (27.5) | 73 | (30.4) | 20 | (24.4) | 53 | (26.8) | 25 | (28.4) | 6 | (16.7) | |
40–49 years | 221 | (34.3) | 72 | (30.0) | 32 | (39.0) | 69 | (34.8) | 33 | (37.5) | 15 | (41.7) | |
50–59 years | 236 | (36.6) | 91 | (37.9) | 30 | (36.6) | 74 | (37.4) | 27 | (30.7) | 14 | (38.9) | |
BMI category | 0.29 | ||||||||||||
Underweight: <18.5 kg/m2 | 92 | (14.3) | 40 | (16.7) | 13 | (15.9) | 25 | (12.6) | 10 | (11.4) | 4 | (11.1) | |
Normal weight: 18.5–24.9 kg/m2 | 469 | (72.8) | 173 | (72.1) | 58 | (70.7) | 152 | (76.8) | 59 | (67.0) | 27 | (75.0) | |
Overweight: ≥25 kg/m2 | 83 | (12.9) | 27 | (11.3) | 11 | (13.4) | 21 | (10.6) | 19 | (21.6) | 5 | (13.9) | |
Education level | 0.59 | ||||||||||||
High school or less | 228 | (35.4) | 82 | (34.2) | 26 | (31.7) | 74 | (37.4) | 32 | (36.4) | 14 | (38.9) | |
Vocational school or junior college | 284 | (44.1) | 103 | (42.9) | 45 | (54.9) | 84 | (42.4) | 36 | (40.9) | 16 | (44.4) | |
University or higher | 132 | (20.5) | 55 | (22.9) | 11 | (13.4) | 40 | (20.2) | 20 | (22.7) | 6 | (16.7) | |
Household income (Japanese yen) | 0.44 | ||||||||||||
<4,000,000 | 117 | (18.2) | 53 | (22.1) | 15 | (18.3) | 29 | (14.6) | 13 | (14.8) | 7 | (19.4) | |
≥4,000,000 & <6,000,000 | 190 | (29.5) | 72 | (30.0) | 23 | (28.0) | 66 | (33.3) | 20 | (22.7) | 9 | (25.0) | |
≥6,000,000 & <8,000,000 | 161 | (25.0) | 52 | (21.7) | 24 | (29.3) | 53 | (26.8) | 23 | (26.1) | 9 | (25.0) | |
≥8,000,000 | 176 | (27.3) | 63 | (26.3) | 20 | (24.4) | 50 | (25.3) | 32 | (36.4) | 11 | (30.6) | |
Living with children | 424 | (65.8) | 161 | (67.1) | 58 | (70.7) | 133 | (67.2) | 55 | (62.5) | 17 | (47.2) | 0.13 |
Living with parents | 71 | (11.0) | 22 | (9.2) | 8 | (9.8) | 18 | (9.1) | 17 | (19.3) | 6 | (16.7) | 0.059 |
Size of residential area | 0.16 | ||||||||||||
Ward | 192 | (29.8) | 82 | (34.2) | 22 | (26.8) | 50 | (25.3) | 24 | (27.3) | 14 | (38.9) | |
City | 413 | (64.1) | 149 | (62.1) | 52 | (63.4) | 135 | (68.2) | 59 | (67.0) | 18 | (50.0) | |
Town & village | 39 | (6.1) | 9 | (3.8) | 8 | (9.8) | 13 | (6.6) | 5 | (5.7) | 4 | (11.1) | |
Current smokers | 36 | (5.6) | 8 | (3.3) | 3 | (3.7) | 14 | (7.1) | 7 | (8.0) | 4 | (11.1) | 0.50 |
Alcohol consumers a | 335 | (52.0) | 106 e | (44.2) | 46 | (56.1) | 110 | (55.6) | 53 | (60.2) | 20 | (55.6) | 0.040 |
Energy intake (kcal/day) b | 1658 ± 430 | 1623 ± 410 | 1649 ± 466 | 1657 ± 396 | 1666 ± 454 | 1900 d ± 541 | 0.011 |
Hours of Paid Work Per Week | pa | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
0 (Housewives) | 1–14 | 15–34 | 35–42 | ≥43 | |||||||
(n = 240) | (n = 83) | (n = 198) | (n = 88) | (n = 36) | |||||||
(g/1000 kcal) | Mean | SE | Mean | SE | Mean | SE | Mean | SE | Mean | SE | |
Rice | 134 | 4.1 | 131 | 7.1 | 146 | 4.5 | 156 | 6.8 | 132 | 10.7 | 0.014 |
Bread | 28.3 | 1.1 | 30.6 | 1.9 | 27.3 | 1.2 | 25.4 | 1.8 | 27.0 | 2.9 | 0.14 |
Noodles | 37.0 | 1.5 | 33.9 | 2.6 | 35.2 | 1.7 | 39.9 | 2.5 | 35.9 | 3.9 | 0.68 |
Potatoes | 27.3 | 1.2 | 26.0 | 2.0 | 25.3 | 1.3 | 24.0 | 2.0 | 18.7 | 3.0 | 0.015 |
Soy products | 42.9 | 1.6 | 40.0 | 2.7 | 39.9 | 1.7 | 35.7 | 2.6 | 33.7 | 4.1 | 0.007 |
Vegetables | 135 | 4.0 | 125 | 6.9 | 120 | 4.4 | 115 | 6.7 | 114 | 10.4 | 0.002 |
Mushrooms | 7.7 | 0.4 | 6.7 | 0.6 | 6.9 | 0.4 | 7.1 | 0.6 | 6.5 | 0.9 | 0.14 |
Seaweeds | 7.0 | 0.4 | 7.8 | 0.7 | 6.7 | 0.4 | 5.7 | 0.6 | 5.7 | 1.0 | 0.031 |
Fruit | 42.6 | 2.2 | 35.8 | 3.7 | 40.1 | 2.4 | 39.6 | 3.6 | 43.2 | 5.6 | 0.74 |
Fish | 41.2 | 1.3 | 38.9 | 2.3 | 36.5 | 1.4 | 39.6 | 2.2 | 37.8 | 3.4 | 0.11 |
Meat | 39.4 | 1.0 | 41.0 | 1.8 | 39.3 | 1.1 | 41.4 | 1.7 | 43.3 | 2.7 | 0.30 |
Eggs | 21.0 | 0.9 | 22.1 | 1.5 | 22.6 | 0.9 | 20.3 | 1.4 | 20.6 | 2.2 | 0.98 |
Dairy products | 78.4 | 3.8 | 76.0 | 6.4 | 78.1 | 4.1 | 76.8 | 6.2 | 60.6 | 9.7 | 0.38 |
Confectioneries | 42.9 | 1.6 | 42.5 | 2.8 | 43.7 | 1.8 | 38.1 | 2.7 | 47.1 | 4.3 | 0.73 |
Soft drinks | 27.5 | 3.2 | 35.4 | 5.4 | 32.5 | 3.5 | 30.1 | 5.2 | 27.2 | 8.1 | 0.71 |
Hours of Paid Work Per Week | pa | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
0 (Housewives) | 1–14 | 15–34 | 35–42 | ≥43 | |||||||
(n = 240) | (n = 83) | (n = 198) | (n = 88) | (n = 36) | |||||||
Mean | SE | Mean | SE | Mean | SE | Mean | SE | Mean | SE | ||
Nutrients | |||||||||||
Protein (% energy) | 15.5 | 0.2 | 15.2 | 0.3 | 15.0 | 0.2 | 15.1 | 0.3 | 14.7 | 0.4 | 0.027 |
Total fat (% energy) | 28.5 | 0.3 | 28.6 | 0.5 | 28.1 | 0.3 | 27.3 | 0.5 | 28.2 | 0.8 | 0.10 |
SFA (% energy) | 7.9 | 0.1 | 8.1 | 0.2 | 7.9 | 0.1 | 7.5 | 0.2 | 7.8 | 0.3 | 0.27 |
Carbohydrate (% energy) | 52.8 | 0.4 | 51.5 | 0.8 | 53.9 | 0.5 | 54.0 | 0.7 | 51.9 | 1.1 | 0.14 |
Added sugar (% energy) | 5.8 | 0.2 | 6.3 | 0.3 | 6.1 | 0.2 | 5.8 | 0.3 | 5.9 | 0.5 | 0.87 |
Alcohol (g/1000 kcal) | 3.2 | 0.4 | 5.2 | 0.8 | 2.6 | 0.5 | 3.3 | 0.7 | 5.7 | 1.1 | 0.89 |
Total dietary fiber (g/1000 kcal) | 6.9 | 0.1 | 6.5 | 0.2 | 6.5 | 0.1 | 6.3 | 0.2 | 6.0 | 0.3 | <0.001 |
Vitamin A (µg RAE/1000 kcal) | 400 | 11.3 | 414 | 19.2 | 377 | 12.3 | 378 | 18.6 | 334 | 29.0 | 0.021 |
Vitamin B1 (mg/1000 kcal) | 0.44 | 0.01 | 0.43 | 0.01 | 0.43 | 0.01 | 0.42 | 0.01 | 0.42 | 0.01 | 0.002 |
Vitamin B2 (mg/1000 kcal) | 0.75 | 0.01 | 0.74 | 0.02 | 0.73 | 0.01 | 0.72 | 0.02 | 0.69 | 0.03 | 0.026 |
Niacin (mg NE/1000 kcal) b | 16.1 | 0.2 | 16.0 | 0.3 | 15.5 | 0.2 | 15.8 | 0.3 | 15.7 | 0.5 | 0.14 |
Vitamin B6 (mg/1000 kcal) | 0.70 | 0.01 | 0.69 | 0.02 | 0.66 | 0.01 | 0.67 | 0.02 | 0.67 | 0.03 | 0.006 |
Vitamin B12 (µg/1000 kcal) | 5.2 | 0.1 | 5.2 | 0.2 | 4.8 | 0.2 | 5.0 | 0.2 | 4.9 | 0.4 | 0.12 |
Folate (µg/1000 kcal) | 189 | 3.6 | 180 | 6.1 | 176 | 3.9 | 170 | 5.9 | 164 | 9.3 | <0.001 |
Vitamin C (mg/1000 kcal) | 64.8 | 1.6 | 57.6 | 2.7 | 58.2 | 1.7 | 56.9 | 2.6 | 56.8 | 4.1 | 0.003 |
Vitamin D (mg/1000 kcal) | 7.3 | 0.2 | 7.0 | 0.4 | 6.6 | 0.3 | 6.9 | 0.4 | 6.7 | 0.6 | 0.09 |
Sodium (mg/1000 kcal) | 2344 | 27 | 2232 | 46 | 2288 | 29 | 2281 | 44 | 2244 | 69 | 0.15 |
Potassium (mg/1000 kcal) | 1472 | 22 | 1407 | 37 | 1387 | 24 | 1356 | 36 | 1313 | 56 | <0.001 |
Calcium (mg/1000 kcal) | 318 | 5.8 | 307 | 10.0 | 302 | 6.4 | 293 | 9.6 | 273 | 15.1 | 0.001 |
Magnesium (mg/1000 kcal) | 143 | 1.8 | 138 | 3.0 | 136 | 1.9 | 134 | 2.9 | 131 | 4.6 | <0.001 |
Iron (mg/1000 kcal) | 4.4 | 0.1 | 4.3 | 0.1 | 4.2 | 0.1 | 4.1 | 0.1 | 4.0 | 0.2 | <0.001 |
Zinc (mg/1000 kcal) | 4.5 | 0.03 | 4.4 | 0.1 | 4.4 | 0.04 | 4.4 | 0.1 | 4.3 | 0.1 | 0.11 |
Copper (mg/1000 kcal) | 0.63 | 0.01 | 0.60 | 0.01 | 0.62 | 0.01 | 0.60 | 0.01 | 0.58 | 0.02 | 0.009 |
Diet quality score | |||||||||||
NRF9.3 | 695 | 6.5 | 688 | 11.0 | 674 | 7.1 | 672 | 10.7 | 662 | 16.7 | 0.006 |
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Oono, F.; Matsuura, N.; Saito, A.; Fujiwara, A.; Takahashi, O.; Sasaki, S.; Iida, K. Association of Hours of Paid Work with Dietary Intake and Quality in Japanese Married Women: A Cross-Sectional Study. Nutrients 2021, 13, 3005. https://doi.org/10.3390/nu13093005
Oono F, Matsuura N, Saito A, Fujiwara A, Takahashi O, Sasaki S, Iida K. Association of Hours of Paid Work with Dietary Intake and Quality in Japanese Married Women: A Cross-Sectional Study. Nutrients. 2021; 13(9):3005. https://doi.org/10.3390/nu13093005
Chicago/Turabian StyleOono, Fumi, Nozomi Matsuura, Aki Saito, Aya Fujiwara, Osamu Takahashi, Satoshi Sasaki, and Kaoruko Iida. 2021. "Association of Hours of Paid Work with Dietary Intake and Quality in Japanese Married Women: A Cross-Sectional Study" Nutrients 13, no. 9: 3005. https://doi.org/10.3390/nu13093005
APA StyleOono, F., Matsuura, N., Saito, A., Fujiwara, A., Takahashi, O., Sasaki, S., & Iida, K. (2021). Association of Hours of Paid Work with Dietary Intake and Quality in Japanese Married Women: A Cross-Sectional Study. Nutrients, 13(9), 3005. https://doi.org/10.3390/nu13093005