Universal school lunch programme closes a socioeconomic gap in fruit and vegetable intakes among school children in Japan

Universal school lunch programme closes a socioeconomic gap in fruit and vegetable intakes among... Abstract Background Universal school lunch programmes are expected to cover all children equally, compared with selective programmes that may stigmatize socially vulnerable children. However, the effectiveness of universal programmes in closing dietary disparity has not been empirically proven. We evaluated whether Japan’s universal school lunch programmes contribute to a reduction in the socioeconomic status (SES)-related gradient in fruit and vegetable intakes. Methods We analyzed data for 719 school children aged 6–12 years in a population-based survey conducted in the greater Tokyo metropolitan area. We measured dietary intakes using a validated self-administered brief diet history questionnaire for young children (BDHQ-10 y). We assessed parental education, annual household income and maternal employment status as SES indicators of children. We used multiple regression to estimate mean fruit and vegetable intakes by parental education and household income, and the contribution of school lunch to reducing the SES-related gradient in fruit and vegetable intakes. Results Compared with children with high maternal education (>15 years), those with low maternal education (<13 years) had less vegetable intake by 22.3 g/1000 kcal (95% confidence interval = 12.5, 32.2) and less fruit intake by 7.5 g/1000 kcal (95% confidence interval = −2.4, 17.3). However, fruit and vegetable intakes from school lunch did not vary by SES, indicating that school lunch intake alleviated the SES-related gradient of total vegetable intake by 9.9% and that of fruit intake by 3.4%. Conclusions Universal school lunch programmes can partially contribute to a reduction in the SES-related gradient in dietary intakes. Introduction Accumulated evidence shows that poor diet and unfavourable weight statuses are more prevalent among socioeconomically disadvantaged children.1,2 More specifically, fruit and vegetable intakes were found to be lower among impoverished children than among their richer counterparts.3–6 Because childhood diets affect health throughout life, measures to improve childhood diets are regarded as an important agenda in public health policies. One strategy to improve the diet of children is to provide better access to nutritious food at schools. Evidence supports the notion that school lunch programmes improve diet quality and food security among children,7–9 especially those of low socioeconomic status (SES).9,10 School lunch programmes are often selectively provided to children with socioeconomic difficulties. This selective approach can efficiently reach populations in need but it may also run the risk of stigmatizing children of low SES among their peers.11,12 Universal school lunch programmes may close the socioeconomic disparity in nutrition among children in a more inclusive manner. In Japan, universal school lunch programmes have been implemented in the local municipalities in 194713 and expanded to cover 98.4% of all elementary school children under a strict standardized nationwide protocol for dietary contents.14 In general, all children in the same school are served with the same menu, except for children with specific needs. All children have the lunch in a classroom with their teachers and peers, as Basic Law on Shokuiku has mentioned that the lunch is recognized as an opportunity for education on diet, social manners and socialization in Japanese primary education. The other features of school lunch in Japan were described elsewhere.15 Although previous studies have shown that school lunch in Japan contributes to healthier nutrition intake among Japanese school children,15,16 evidence is scarce on the effects of universal lunch programmes on reducing nutritional disparity among school children. The National Health Nutrition Surveys in 2010 and 2014 revealed socioeconomic disparities in dietary intake, especially fruit and vegetable intakes, among Japanese adults,17,18 and similar disparities are highly likely to exist among children. In this study, we aimed to (i) examine the levels of socioeconomic disparity in fruit and vegetable intakes among Japanese school children in metropolitan setting and (ii) evaluate whether universal school lunch programmes can close the gap if it exists. Methods Data sources We used data from the Japanese Study on Stratification, Health, Income and Neighbourhood (J-SHINE). Details of J-SHINE were described elsewhere.19 The participants were randomly selected from community-dwelling residential records of people aged 25–50 years in four municipalities in the greater Tokyo area. The original first-wave survey was conducted in 2010, followed by supplemental surveys for children aged under 18 years in 2011 and 2013. Among the 2428 participating children, we used the data for 868 school children who went to public elementary schools (aged 6–12 years in Japan). We asked the participating children to answer a dietary habit questionnaire in 2013, the details of which are described briefly. We excluded dietary report data that included energy intake estimates in an outlier range (n = 39), following the criteria proposed in a previous study.20 We also excluded data for children who lacked information on annual household income, parental education or maternal employment (n = 110). Consequently, we analyzed the data for 719 school children. Measurements Fruit and vegetable intakes The J-SHINE survey assessed vegetable and fruit intakes and total energy intakes using the self-administered brief diet history questionnaire-10y (BDHQ-10y),21 modified from a validated original BDHQ for adults.22,23 The children themselves filled in the questionnaire, with help from their primary caretakers if necessary. The questionnaire initially examined the frequency of 54 food items from sources other than school lunch, assuming average portion sizes. The questionnaire then assessed food intakes from school lunch for six items (rice/bread, meat, fish, vegetables, fruit and milk) with a response set comprising ‘rarely eat’, ‘leave half of dish’, ‘leave some of dish’, ‘eat all’, ‘sometimes have second helpings’ and ‘often have second helpings’, by assuming a nationwide standardized protocol for food components of school lunch.24,25 The total intake was estimated by adding the intake estimated from school lunch and that from other sources. The validity of the total fruit and vegetable intakes was confirmed by significant correlations with serum carotenoid concentrations in a previous study but not by the duplicate method.21 Finally, we evaluated the contributions of school lunch to fruit and vegetable intakes per total daily intakes. Socioeconomic status Following the guidelines of a recent study on social determinants of health,26 we used annual household income, maternal and paternal educational attainments and maternal employment status as indicators of children’s SES. Although these indicators are likely to correlate with each other, we specifically used income as an indicator of household purchasing capacity while parental educational attainments reflected knowledge and attitude towards healthier eating habits. Maternal employment status may reflect availability for meal preparation, which can have a high impact on children’s diet. Annual household income was assessed by 15 categories. We used the median value of each category and obtained an equivalent household income based on a previous study.27 It was examined using six responses and re-categorized into three groups: low (≤12 years), medium (13–15 years) and high (≥16 years). It was examined by nine categories and re-categorized into four groups: full-time worker (manager/executive and regular employee), part-time worker (contract/temporary/fixed-term employee), homemaker (unemployment) and other job (self-employed, family worker). Statistical analysis After examining descriptive statistics, we performed multiple regression analyses for the outcomes of total daily intakes and share of school lunch-derived intakes per total intakes. We regarded SES indicators (household income, maternal and paternal educational attainments and maternal employment status) as main explanatory variables, adjusting for children’s sex, age and municipality of residence as covariates because school lunch provision is under municipality management. We used robust standard errors to consider intraclass correlations among children in the same household. We conducted analyses with and without log-transformed values of outcomes and found similar results. Consequently, we report the results without log-transformation for ease of interpretation. Finally, we estimated least-square means of intakes by the levels of SES indicators. Throughout the analyses, we combined the data for girls and boys because our preliminary analyses showed similar values for the associations between SES and fruit and vegetable intakes in both sexes. All analyses were conducted using STATA statistical software, version 13.1 SE (Stata Corporation, Collage Station, TX). Results The mean age of the participants was 9.3 years, and 51.2% of the participants were boys. The mean vegetable intake was 209.4 g/day and the mean fruit intake was 123.4 g/day. Overall, 26% of mothers and 55% of fathers graduated from college or higher education (table 1). Table 1 Participant characteristics Variables n (%) or mean (SD) Children’s characteristics Boys 368 (51.2) Age 9.3 (1.7) 1st grade 126 (17.5) 2nd grade 106 (14.7) 3rd grade 122 (17.0) 4th grade 127 (17.5) 5th grade 111 (15.4) 6th grade 124 (17.2) Dietary intake Vegetable intake (g) 209.4 (88.3) Fruit intake (g) 123.4 (91.0) Vegetable intake (g/1000 kcal) 115.4 (47.0) Fruit intake (g/1000 kcal) 66.6 (45.4) Total energy intake (kcal) 1852 (431.3) Share of vegetable intake from school lunch (%) 39.1 (14.9) Share of fruit intake from school lunch (%) 20.6 (17.1) Maternal education Low (<13 years) 210 (29.6) Medium (13–15 years) 319 (44.4) High (>15 years) 190 (26.4) Paternal education Low (<13 years) 184 (25.6) Medium (13–15 years) 140 (19.5) High (>15 years) 395 (54.9) Household income (million yen) 3.48 (1.6) Maternal employment status Full-time 78 (10.8) Part-time 228 (31.7) Homemaker 370 (51.5) Other job 43 (6.0) Variables n (%) or mean (SD) Children’s characteristics Boys 368 (51.2) Age 9.3 (1.7) 1st grade 126 (17.5) 2nd grade 106 (14.7) 3rd grade 122 (17.0) 4th grade 127 (17.5) 5th grade 111 (15.4) 6th grade 124 (17.2) Dietary intake Vegetable intake (g) 209.4 (88.3) Fruit intake (g) 123.4 (91.0) Vegetable intake (g/1000 kcal) 115.4 (47.0) Fruit intake (g/1000 kcal) 66.6 (45.4) Total energy intake (kcal) 1852 (431.3) Share of vegetable intake from school lunch (%) 39.1 (14.9) Share of fruit intake from school lunch (%) 20.6 (17.1) Maternal education Low (<13 years) 210 (29.6) Medium (13–15 years) 319 (44.4) High (>15 years) 190 (26.4) Paternal education Low (<13 years) 184 (25.6) Medium (13–15 years) 140 (19.5) High (>15 years) 395 (54.9) Household income (million yen) 3.48 (1.6) Maternal employment status Full-time 78 (10.8) Part-time 228 (31.7) Homemaker 370 (51.5) Other job 43 (6.0) Notes. SD, standard deviation. Share of vegetable intake from school lunch (%) = (vegetable intake from school lunch/total vegetable intake) × 100. Share of fruit intake from school lunch (%) = (fruit intake from school lunch/total fruit intake) × 100. Maternal employment status: ‘homemaker’ includes unemployment and ‘other job’ refers to self-employment or family worker. Table 1 Participant characteristics Variables n (%) or mean (SD) Children’s characteristics Boys 368 (51.2) Age 9.3 (1.7) 1st grade 126 (17.5) 2nd grade 106 (14.7) 3rd grade 122 (17.0) 4th grade 127 (17.5) 5th grade 111 (15.4) 6th grade 124 (17.2) Dietary intake Vegetable intake (g) 209.4 (88.3) Fruit intake (g) 123.4 (91.0) Vegetable intake (g/1000 kcal) 115.4 (47.0) Fruit intake (g/1000 kcal) 66.6 (45.4) Total energy intake (kcal) 1852 (431.3) Share of vegetable intake from school lunch (%) 39.1 (14.9) Share of fruit intake from school lunch (%) 20.6 (17.1) Maternal education Low (<13 years) 210 (29.6) Medium (13–15 years) 319 (44.4) High (>15 years) 190 (26.4) Paternal education Low (<13 years) 184 (25.6) Medium (13–15 years) 140 (19.5) High (>15 years) 395 (54.9) Household income (million yen) 3.48 (1.6) Maternal employment status Full-time 78 (10.8) Part-time 228 (31.7) Homemaker 370 (51.5) Other job 43 (6.0) Variables n (%) or mean (SD) Children’s characteristics Boys 368 (51.2) Age 9.3 (1.7) 1st grade 126 (17.5) 2nd grade 106 (14.7) 3rd grade 122 (17.0) 4th grade 127 (17.5) 5th grade 111 (15.4) 6th grade 124 (17.2) Dietary intake Vegetable intake (g) 209.4 (88.3) Fruit intake (g) 123.4 (91.0) Vegetable intake (g/1000 kcal) 115.4 (47.0) Fruit intake (g/1000 kcal) 66.6 (45.4) Total energy intake (kcal) 1852 (431.3) Share of vegetable intake from school lunch (%) 39.1 (14.9) Share of fruit intake from school lunch (%) 20.6 (17.1) Maternal education Low (<13 years) 210 (29.6) Medium (13–15 years) 319 (44.4) High (>15 years) 190 (26.4) Paternal education Low (<13 years) 184 (25.6) Medium (13–15 years) 140 (19.5) High (>15 years) 395 (54.9) Household income (million yen) 3.48 (1.6) Maternal employment status Full-time 78 (10.8) Part-time 228 (31.7) Homemaker 370 (51.5) Other job 43 (6.0) Notes. SD, standard deviation. Share of vegetable intake from school lunch (%) = (vegetable intake from school lunch/total vegetable intake) × 100. Share of fruit intake from school lunch (%) = (fruit intake from school lunch/total fruit intake) × 100. Maternal employment status: ‘homemaker’ includes unemployment and ‘other job’ refers to self-employment or family worker. Maternal education was significantly related to vegetable intake. By reference to children with high maternal education (>15 years), those with low maternal education (<13 years) were estimated to have 22.3 g [95% confidence interval (CI) = 12.5, 32.2] less vegetable intake per 1000 kcal intake. The corresponding value for fruit intake was −7.5 g (95% CI = −2.4, 17.3). Meanwhile, paternal education was not associated with both fruit and vegetable intakes (data not shown). Every 1 million yen unit increase in annual household income was associated with 2.4 g/1000 kcal (95% CI = 0.2, 4.6) more fruit intake (table 2). Among children with low maternal education, the share of school lunch in vegetable intake was 7.4% (95% CI = 4.2, 10.6) higher than that for children with high maternal education. The share of school lunch in fruit intake for children with higher household income was 0.8% (95% CI = −1.6, 0.0) lower than that for children with lower household income (table 2). Table 2 Associations of vegetable or fruit intake and share of vegetable or fruit intake from school lunch with SES by multiple regression analysis among school children in Japan (n = 719) Vegetable intake (g/1000 kcal) Share of vegetable intake from school lunch (%) Fruit intake (g/1000 kcal) Share of fruit intake from school lunch (%) Coeff. 95% CI Coeff. 95% CI Coeff. 95% CI Coeff. 95% CI Maternal education     High (>15 years) 0.0 Ref. 0.0 Ref. 0.0 Ref. 0.0 Ref.     Medium (13–15 years) −17.5 −26.1, −8.9 2.7 0.0, 5.3 −5.1 −13.7, 3.5 −0.6 −3.6, 2.5     Low (<13 years) −22.3 −32.2, −12.5 7.4 4.2, 10.6 −7.5 −17.3, 2.4 4.2 −0.5, 8.8 Household income (per 1 million yen) −1.1 −3.5, 1.3 0.0 −0.7, 0.8 2.4 0.2, 4.6 −0.8 −1.6, 0.0 Maternal employment status     Full-time 0.0 Ref. 0.0 Ref. 0.0 Ref. 0.0 Ref.     Part-time 5.5 −7.3, 18.2 −2.2 −6.5, 2.2 −1.4 −11.9, 9.1 0.5 −3.3, 4.4     Homemaker 3.1 −8.2, 14.4 −1.6 −5.8, 2.5 4.8 −6.1, 15.6 1.0 −2.7, 4.8     Other job −10.0 −2.4, 1.5 0.3 −5.9, 6.5 2.0 18.7, 22.7 5.7 2.0, 13.4 Vegetable intake (g/1000 kcal) Share of vegetable intake from school lunch (%) Fruit intake (g/1000 kcal) Share of fruit intake from school lunch (%) Coeff. 95% CI Coeff. 95% CI Coeff. 95% CI Coeff. 95% CI Maternal education     High (>15 years) 0.0 Ref. 0.0 Ref. 0.0 Ref. 0.0 Ref.     Medium (13–15 years) −17.5 −26.1, −8.9 2.7 0.0, 5.3 −5.1 −13.7, 3.5 −0.6 −3.6, 2.5     Low (<13 years) −22.3 −32.2, −12.5 7.4 4.2, 10.6 −7.5 −17.3, 2.4 4.2 −0.5, 8.8 Household income (per 1 million yen) −1.1 −3.5, 1.3 0.0 −0.7, 0.8 2.4 0.2, 4.6 −0.8 −1.6, 0.0 Maternal employment status     Full-time 0.0 Ref. 0.0 Ref. 0.0 Ref. 0.0 Ref.     Part-time 5.5 −7.3, 18.2 −2.2 −6.5, 2.2 −1.4 −11.9, 9.1 0.5 −3.3, 4.4     Homemaker 3.1 −8.2, 14.4 −1.6 −5.8, 2.5 4.8 −6.1, 15.6 1.0 −2.7, 4.8     Other job −10.0 −2.4, 1.5 0.3 −5.9, 6.5 2.0 18.7, 22.7 5.7 2.0, 13.4 Notes. CI, confidence interval; Coeff., coefficient. Share of vegetable intake from school lunch (%) = (vegetable intake from school lunch/total vegetable intake) × 100. Share of fruit intake from school lunch (%) = (fruit intake from school lunch/total fruit intake) × 100. Adjustment for: age, sex and municipality of residence. Table 2 Associations of vegetable or fruit intake and share of vegetable or fruit intake from school lunch with SES by multiple regression analysis among school children in Japan (n = 719) Vegetable intake (g/1000 kcal) Share of vegetable intake from school lunch (%) Fruit intake (g/1000 kcal) Share of fruit intake from school lunch (%) Coeff. 95% CI Coeff. 95% CI Coeff. 95% CI Coeff. 95% CI Maternal education     High (>15 years) 0.0 Ref. 0.0 Ref. 0.0 Ref. 0.0 Ref.     Medium (13–15 years) −17.5 −26.1, −8.9 2.7 0.0, 5.3 −5.1 −13.7, 3.5 −0.6 −3.6, 2.5     Low (<13 years) −22.3 −32.2, −12.5 7.4 4.2, 10.6 −7.5 −17.3, 2.4 4.2 −0.5, 8.8 Household income (per 1 million yen) −1.1 −3.5, 1.3 0.0 −0.7, 0.8 2.4 0.2, 4.6 −0.8 −1.6, 0.0 Maternal employment status     Full-time 0.0 Ref. 0.0 Ref. 0.0 Ref. 0.0 Ref.     Part-time 5.5 −7.3, 18.2 −2.2 −6.5, 2.2 −1.4 −11.9, 9.1 0.5 −3.3, 4.4     Homemaker 3.1 −8.2, 14.4 −1.6 −5.8, 2.5 4.8 −6.1, 15.6 1.0 −2.7, 4.8     Other job −10.0 −2.4, 1.5 0.3 −5.9, 6.5 2.0 18.7, 22.7 5.7 2.0, 13.4 Vegetable intake (g/1000 kcal) Share of vegetable intake from school lunch (%) Fruit intake (g/1000 kcal) Share of fruit intake from school lunch (%) Coeff. 95% CI Coeff. 95% CI Coeff. 95% CI Coeff. 95% CI Maternal education     High (>15 years) 0.0 Ref. 0.0 Ref. 0.0 Ref. 0.0 Ref.     Medium (13–15 years) −17.5 −26.1, −8.9 2.7 0.0, 5.3 −5.1 −13.7, 3.5 −0.6 −3.6, 2.5     Low (<13 years) −22.3 −32.2, −12.5 7.4 4.2, 10.6 −7.5 −17.3, 2.4 4.2 −0.5, 8.8 Household income (per 1 million yen) −1.1 −3.5, 1.3 0.0 −0.7, 0.8 2.4 0.2, 4.6 −0.8 −1.6, 0.0 Maternal employment status     Full-time 0.0 Ref. 0.0 Ref. 0.0 Ref. 0.0 Ref.     Part-time 5.5 −7.3, 18.2 −2.2 −6.5, 2.2 −1.4 −11.9, 9.1 0.5 −3.3, 4.4     Homemaker 3.1 −8.2, 14.4 −1.6 −5.8, 2.5 4.8 −6.1, 15.6 1.0 −2.7, 4.8     Other job −10.0 −2.4, 1.5 0.3 −5.9, 6.5 2.0 18.7, 22.7 5.7 2.0, 13.4 Notes. CI, confidence interval; Coeff., coefficient. Share of vegetable intake from school lunch (%) = (vegetable intake from school lunch/total vegetable intake) × 100. Share of fruit intake from school lunch (%) = (fruit intake from school lunch/total fruit intake) × 100. Adjustment for: age, sex and municipality of residence. The fruit and vegetable intakes from school lunch did not vary large by SES, despite the existence of SES-based differences in the total amounts of fruit and vegetable intakes (figure 1). Thus, school lunch contributed to a reduction in the inequality of vegetable intake by 9.9% and fruit intake by 3.4% (table 3). Table 3 Average total vegetable intake, vegetable intake from home by maternal education and average total fruit intake, fruit intake from home by household income, adjusting for all SES indicators, children’s sex and age and municipality of residence Maternal education Household income Ratio of high/low Change of ratio (%) High (>15 years) Low (<13 years) High (>3.61 million yen) Low (<2.79 million yen) Total vegetable intake (g/1000 kcal) 129.7 107.5 1.21 9.89 Vegetable intake from home (g/1000 kcal) 88.1 65.8 1.34 Total fruit intake (g/1000 kcal) 69.7 60.5 1.15 3.36 Fruit intake from home (g/1000 kcal) 61.3 51.5 1.19 Maternal education Household income Ratio of high/low Change of ratio (%) High (>15 years) Low (<13 years) High (>3.61 million yen) Low (<2.79 million yen) Total vegetable intake (g/1000 kcal) 129.7 107.5 1.21 9.89 Vegetable intake from home (g/1000 kcal) 88.1 65.8 1.34 Total fruit intake (g/1000 kcal) 69.7 60.5 1.15 3.36 Fruit intake from home (g/1000 kcal) 61.3 51.5 1.19 Table 3 Average total vegetable intake, vegetable intake from home by maternal education and average total fruit intake, fruit intake from home by household income, adjusting for all SES indicators, children’s sex and age and municipality of residence Maternal education Household income Ratio of high/low Change of ratio (%) High (>15 years) Low (<13 years) High (>3.61 million yen) Low (<2.79 million yen) Total vegetable intake (g/1000 kcal) 129.7 107.5 1.21 9.89 Vegetable intake from home (g/1000 kcal) 88.1 65.8 1.34 Total fruit intake (g/1000 kcal) 69.7 60.5 1.15 3.36 Fruit intake from home (g/1000 kcal) 61.3 51.5 1.19 Maternal education Household income Ratio of high/low Change of ratio (%) High (>15 years) Low (<13 years) High (>3.61 million yen) Low (<2.79 million yen) Total vegetable intake (g/1000 kcal) 129.7 107.5 1.21 9.89 Vegetable intake from home (g/1000 kcal) 88.1 65.8 1.34 Total fruit intake (g/1000 kcal) 69.7 60.5 1.15 3.36 Fruit intake from home (g/1000 kcal) 61.3 51.5 1.19 Figure 1 View largeDownload slide Average vegetable and fruit intake by household SESs, adjusting for all other socioeconomic indicators, children’s sex and age and municipality of residence Figure 1 View largeDownload slide Average vegetable and fruit intake by household SESs, adjusting for all other socioeconomic indicators, children’s sex and age and municipality of residence Discussion The key findings of this study are as follows. First, maternal education was associated with overall fruit and vegetable intakes independently of other individual and household sociodemographic characteristics, while paternal education was not. Household income was only associated with fruit intake. These results are consistent with those of previous studies conducted in Western countries, showing that maternal education is positively associated with fruit and vegetable intakes among school children.3–6,28 Second, we demonstrated that children whose mothers were less educated had greater reliance on school lunch for their vegetable intake, and children with lower household income had more contribution from school lunch to their fruit intake. However, because the serving of fruit in school lunches as well as overall fruit intake is low in Japan compared with Western countries,29 the attributable effects of school lunch in reducing the socioeconomic disparity in regard to fruit intake may be limited. Our study adds new evidence that universal school lunch programmes are effective in at least partially reducing the gap in diet across parental SES. Lower socioeconomic children had less access to high quality and balanced meals at home, and universal school lunch programmes may provide greater contributions to children in lower socioeconomic conditions. In our study, maternal education had stronger associations with fruit and vegetable intakes than paternal education. This may reflect the notion that the person who usually cooks at home affects the nutritional intake of their children. In the majority of Japanese households, mothers are more likely to prepare most meals for their children. According to a government nationwide survey comprising a general survey of social life, women spend 2.5 h/day on housekeeping including meal preparation, while men spend only 0.3 h/day.30 Household income was also associated with fruit intake. Fruits might be considered ‘luxury items’. This was reflected by the governmental survey of price elasticity that categorized fruit and snacks as amenity foods.31 Additionally, maternal skills and knowledge on diet may have less effect on their children’s fruit intake than on their vegetable intake. The correlation between vegetable intake and income was not statistically significant. This was not consistent with the National Health and Nutrition Survey.17,18 A potential explanation of the inconsistency may be the difference in age distribution between the groups. This study focuses on children, who are more influenced by parental food choices and household characteristics. Alternatively, the measurement of income is significantly different between the studies. The National Surveys used only three categories (≤2 million yen, 2–6 million yen, ≤6 million yen) when determining household income, potentially more vulnerable to error. Further studies are needed to conclude the correlation between vegetable intake and household income in Japanese children. Given that maternal education may reflect their skills and knowledge on diet to serve healthy meals, it is plausible that mothers with lower educational attainment may have difficulties in regularly providing balanced meals at home. Maternal food preferences may also affect children’s diet. Evidence suggests strong correlations between mothers and children in their vegetable and fruit consumptions.5,32–34 Thus, the socioeconomic gap in dietary intakes among children is likely to be mainly derived from their home intakes. However, we found that SES did not impact fruit and vegetable intake from school lunch. These findings are particularly noteworthy because they strongly suggest that universal school lunch programmes could equally provide the opportunities for fruit and vegetable intake to all children regardless of their SES. Nonetheless, SES-based disparity remained at 22.3 g/1000 kcal for vegetable intake and 7.5 g/1000 kcal for fruit intake between low and high maternal educational attainments. To further reduce these gaps, additional measures to secure more availability and accessibility of fruit and vegetables through school meal programmes35 and other sources including home intakes are warranted. For example, providing opportunities for children, in community settings, to eat balanced meals for breakfast and dinner that are free or available at affordable prices may help to further reduce the health disparity in diets.36 Nutrition and cooking education during early childhood may also contribute to children acquiring cooking skills and nutritional knowledge regardless of their SES.37 We used adjusted values for total and school lunch-derived fruit and vegetable intake per 1000 kcal to account for age-related variation in caloric intake. In studies in the USA, children of lower SES have been found to have higher energy intake due to excess portions and snacking. In this case, it may be more important to reduce caloric intake rather than enhance vegetable intake. However, studies in Japan38 have not shown a clear correlation between children’s SES and energy intake. In our sample, energy intake was slightly higher among children of higher household income. There are limitations to this study. First, the generalizability of the study may be limited because all participants were selected from four municipalities in the greater Tokyo metropolitan area.39 Further studies should evaluate the effectiveness of universal school lunch programmes in other settings in terms of place, culture and quality of lunch. Second, the validity of fruit and vegetable intakes specifically from school lunch estimated by the BDHQ-10y has not yet been examined. Compared with a school nutrition report in 2015,40 the total vegetable intake from school lunch was 17.5 g less in this study, while the total fruit intake from school lunch did not differ much. These data partly support the validity of the BDHQ-10y as a tool for nutritional analysis of Japanese school lunch. Third, some younger children were helped to answer dietary habit questionnaire, which may be susceptible to reporting bias by their mothers, especially with higher education and consciousness about healthy diet. However, sub-analysis limited to those that children answered by themselves did not make change in the results. Household income and parental education were self-reported; therefore, the possibility of misclassification exists. Furthermore, we did not have information about the curricula of the schools, which may have an effect on student eating habits. School lunch programmes were highly standardized by each municipality’s education authority under the School Lunch Program Act. Hence, we included municipality dummy codes in our regression analysis to incorporate any fixed effects related to differences between municipalities. Achievement of standardized universal school lunch programmes is a challenge. Sustainability in food logistics systems and financing for nationwide universal school lunch programmes are other topics to be investigated. Other challenges in universal school lunch programmes are the costs required to meet various needs for food preferences based on religious and cultural diversity in schools. Studies investigating the cost-effectiveness of universal lunch programmes are warranted. Although there are some challenges, notwithstanding this successful case in Japan—where the school lunch program was started in 1947 under the support of United Nations Children's Fund (UNICEF) and the School Lunch Law was established in 1954—we believe that the promotion of universal school lunch programmes can be an effective vehicle for closing the nutrition-associated gap in schoolchildren overcoming socioeconomic challenges. Conclusion In this study, we demonstrated the effectiveness of standardized universal school lunch programmes in partially reducing the maternal–education-related gradient in vegetable intake and household income-related fruit intakes in the Japanese elementary school setting. Additional community interventions may be needed to further close the gap in children’s dietary intake. Acknowledgements The authors thank Satoshi Sasaki and Satomi Kobayashi for advice on the statistical analyses. Funding The Japanese Study on Stratification, Health, Income and Neighbourhood (J-SHINE) was supported by a Grant-in-Aid for Scientific Research on Innovative Areas (No. 21119002) from the Ministry of Education, Culture, Sports, Science and Technology, Japan and the Ministry of Health, Labour and Welfare, Japan (H27–junkankitou-ippan-002, H28-junkankitou-ippan-008). Conflicts of interest: None declared. Key points Parental SES was associated with overall fruit and vegetable intakes. Children whose mothers were less educated had greater reliance on school lunch for their vegetable intake. Children with lower household income had more contribution from school lunch to their fruit intake. Universal school lunch programmes can in part contribute to a reduction in the SES-related gradient in diets. References 1 Wang Y , Beydoun MA . 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Google Scholar CrossRef Search ADS PubMed 13 Marmot M , Allen J , Goldblatt P , et al. Fair Society, Healthy Lives (The Marmot Review), Strategic Review of Health Inequalities in England post- 2010 . 14 Ministry of Education , Culture, Sports, Science, and Technology. Study for the school lunch program, 2014 . Available at: http://www.mext.go.jp/b_menu/toukei/chousa05/kyuushoku/1267027.htm (1 August 2016, date last accessed). 15 Asakura K , Sasaki S . School lunches in Japan: their contribution to healthier nutrient intake among elementary-school and junior high-school children . Public Health Nutr 2017 ; 20 : 1523 – 33 . Google Scholar CrossRef Search ADS PubMed 16 Toshiyuki K , Naoko K , Tatsuki I , Satoshi S . Effects of the National School Lunch Program on bone growth in Japanese Elementary School Children . J Nutr Sci Vitaminol 2016 ; 62 : 303 – 9 . Google Scholar CrossRef Search ADS PubMed 17 Nishi N , Horikawa C , Murayama N . 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Carotenoid, tocopherol, and fatty acid biomarkers and dietary intake estimated by using a brief self-administered diet history questionnaire for older Japanese children and adolescents . J Nutr Sci Vitaminol 2009 ; 55 : 231 – 41 . Google Scholar CrossRef Search ADS PubMed 22 Kobayashi S , Honda S , Murakami K , et al. Both comprehensive and brief self-administered diet history questionnaires satisfactorily rank nutrient intakes in Japanese adults . J Epidemiol 2012 ; 22 : 151 – 9 . Google Scholar CrossRef Search ADS PubMed 23 Kobayashi S , Murakami K , Sasaki S , et al. 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 . Public Health Nutr 2011 ; 14 : 1200 – 11 . Google Scholar CrossRef Search ADS PubMed 24 Ministry of Education , Culture, Sports, Science, and Technology. Nutritional standards for school lunch, 2013 . Available at: http://www.mext.go.jp/b_menu/hakusho/nc/1332086.htm (4 February 2017, date last accessed). 25 Ministry of Education , Culture, Sports, Science, and Technology. The food construction table for school lunch, 2011 . Available at: http://www.city.settsu.osaka.jp/cmsfiles/contents/0000007/7121/25.3siryou6-2.pdf (4 February 2017, date last accessed). 26 Galobardes B , Shaw M , Lawlor DA , et al. Indicators of socioeconomic position (part 1) . J Epidemiol Community Health 2006 ; 60 : 7 – 12 . Google Scholar CrossRef Search ADS PubMed 27 Higashi K , Itoh M , Toyokawa S , Kobayashi Y . Subsidy and parental attitudes toward pediatric health care in the Tokyo metropolitan area . Pediatr Int 2016 ; 58 : 132 – 8 . Google Scholar CrossRef Search ADS PubMed 28 van Ansem WJ , Schrijvers CT , Rodenburg G , van de Mheen D . Maternal educational level and children’s healthy eating behaviour: role of the home food environment (cross-sectional results from the INPACT study) . Int J Behav Nutr Phys Act 2014 ; 11 : 113 . Google Scholar CrossRef Search ADS PubMed 29 European Food Safety Authority . The EFSA comprehensive European food consumption database, 2008 . Available at: http://www.efsa.europa.eu/en/food-consumption/comprehensive-database (29 October 2017, date last accessed). 30 Ministry of Internal Affairs and Communications . General survey of social life, 2011 . Available at: http://www.stat.go.jp/data/shakai/2011/gaiyou.htm#a02 (23 September 2017, date last accessed). 31 Saito M , Matsuo Y . Estimation of price elasticity . Econ Anal 1979 ; 74 : 94 . 32 Campbell KJ , Abbott G , Spence AC , et al. Home food availability mediates associations between mothers’ nutrition knowledge and child diet . Appetite 2013 ; 71 : 1 – 6 . Google Scholar CrossRef Search ADS PubMed 33 Ball K , Crawford D . Socio-economic factors in obesity: a case of slim chance in a fat world? Asia Pac J Clin Nutr 2006 ; 15 Suppl : 15 – 20 . 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Google Scholar CrossRef Search ADS PubMed 39 Kepper M , Tseng T-S , Volaufova J , et al. Pre-school obesity is inversely associated with vegetable intake, grocery stores and outdoor play . Pediatr Obes 2016 ; 11 :e6–8. 40 Ministry of Education, Culture, Sports, Science, and Technology . School nutrition report, 2015 . Available at: http://www.mext.go.jp/b_menu/toukei/chousa05/eiyou/gaiyou/1376285.htm (19 September 2016, date last accessed). © The Author(s) 2018. Published by Oxford University Press on behalf of the European Public Health Association. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The European Journal of Public Health Oxford University Press

Universal school lunch programme closes a socioeconomic gap in fruit and vegetable intakes among school children in Japan

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Oxford University Press
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© The Author(s) 2018. Published by Oxford University Press on behalf of the European Public Health Association.
ISSN
1101-1262
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1464-360X
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10.1093/eurpub/cky041
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Abstract

Abstract Background Universal school lunch programmes are expected to cover all children equally, compared with selective programmes that may stigmatize socially vulnerable children. However, the effectiveness of universal programmes in closing dietary disparity has not been empirically proven. We evaluated whether Japan’s universal school lunch programmes contribute to a reduction in the socioeconomic status (SES)-related gradient in fruit and vegetable intakes. Methods We analyzed data for 719 school children aged 6–12 years in a population-based survey conducted in the greater Tokyo metropolitan area. We measured dietary intakes using a validated self-administered brief diet history questionnaire for young children (BDHQ-10 y). We assessed parental education, annual household income and maternal employment status as SES indicators of children. We used multiple regression to estimate mean fruit and vegetable intakes by parental education and household income, and the contribution of school lunch to reducing the SES-related gradient in fruit and vegetable intakes. Results Compared with children with high maternal education (>15 years), those with low maternal education (<13 years) had less vegetable intake by 22.3 g/1000 kcal (95% confidence interval = 12.5, 32.2) and less fruit intake by 7.5 g/1000 kcal (95% confidence interval = −2.4, 17.3). However, fruit and vegetable intakes from school lunch did not vary by SES, indicating that school lunch intake alleviated the SES-related gradient of total vegetable intake by 9.9% and that of fruit intake by 3.4%. Conclusions Universal school lunch programmes can partially contribute to a reduction in the SES-related gradient in dietary intakes. Introduction Accumulated evidence shows that poor diet and unfavourable weight statuses are more prevalent among socioeconomically disadvantaged children.1,2 More specifically, fruit and vegetable intakes were found to be lower among impoverished children than among their richer counterparts.3–6 Because childhood diets affect health throughout life, measures to improve childhood diets are regarded as an important agenda in public health policies. One strategy to improve the diet of children is to provide better access to nutritious food at schools. Evidence supports the notion that school lunch programmes improve diet quality and food security among children,7–9 especially those of low socioeconomic status (SES).9,10 School lunch programmes are often selectively provided to children with socioeconomic difficulties. This selective approach can efficiently reach populations in need but it may also run the risk of stigmatizing children of low SES among their peers.11,12 Universal school lunch programmes may close the socioeconomic disparity in nutrition among children in a more inclusive manner. In Japan, universal school lunch programmes have been implemented in the local municipalities in 194713 and expanded to cover 98.4% of all elementary school children under a strict standardized nationwide protocol for dietary contents.14 In general, all children in the same school are served with the same menu, except for children with specific needs. All children have the lunch in a classroom with their teachers and peers, as Basic Law on Shokuiku has mentioned that the lunch is recognized as an opportunity for education on diet, social manners and socialization in Japanese primary education. The other features of school lunch in Japan were described elsewhere.15 Although previous studies have shown that school lunch in Japan contributes to healthier nutrition intake among Japanese school children,15,16 evidence is scarce on the effects of universal lunch programmes on reducing nutritional disparity among school children. The National Health Nutrition Surveys in 2010 and 2014 revealed socioeconomic disparities in dietary intake, especially fruit and vegetable intakes, among Japanese adults,17,18 and similar disparities are highly likely to exist among children. In this study, we aimed to (i) examine the levels of socioeconomic disparity in fruit and vegetable intakes among Japanese school children in metropolitan setting and (ii) evaluate whether universal school lunch programmes can close the gap if it exists. Methods Data sources We used data from the Japanese Study on Stratification, Health, Income and Neighbourhood (J-SHINE). Details of J-SHINE were described elsewhere.19 The participants were randomly selected from community-dwelling residential records of people aged 25–50 years in four municipalities in the greater Tokyo area. The original first-wave survey was conducted in 2010, followed by supplemental surveys for children aged under 18 years in 2011 and 2013. Among the 2428 participating children, we used the data for 868 school children who went to public elementary schools (aged 6–12 years in Japan). We asked the participating children to answer a dietary habit questionnaire in 2013, the details of which are described briefly. We excluded dietary report data that included energy intake estimates in an outlier range (n = 39), following the criteria proposed in a previous study.20 We also excluded data for children who lacked information on annual household income, parental education or maternal employment (n = 110). Consequently, we analyzed the data for 719 school children. Measurements Fruit and vegetable intakes The J-SHINE survey assessed vegetable and fruit intakes and total energy intakes using the self-administered brief diet history questionnaire-10y (BDHQ-10y),21 modified from a validated original BDHQ for adults.22,23 The children themselves filled in the questionnaire, with help from their primary caretakers if necessary. The questionnaire initially examined the frequency of 54 food items from sources other than school lunch, assuming average portion sizes. The questionnaire then assessed food intakes from school lunch for six items (rice/bread, meat, fish, vegetables, fruit and milk) with a response set comprising ‘rarely eat’, ‘leave half of dish’, ‘leave some of dish’, ‘eat all’, ‘sometimes have second helpings’ and ‘often have second helpings’, by assuming a nationwide standardized protocol for food components of school lunch.24,25 The total intake was estimated by adding the intake estimated from school lunch and that from other sources. The validity of the total fruit and vegetable intakes was confirmed by significant correlations with serum carotenoid concentrations in a previous study but not by the duplicate method.21 Finally, we evaluated the contributions of school lunch to fruit and vegetable intakes per total daily intakes. Socioeconomic status Following the guidelines of a recent study on social determinants of health,26 we used annual household income, maternal and paternal educational attainments and maternal employment status as indicators of children’s SES. Although these indicators are likely to correlate with each other, we specifically used income as an indicator of household purchasing capacity while parental educational attainments reflected knowledge and attitude towards healthier eating habits. Maternal employment status may reflect availability for meal preparation, which can have a high impact on children’s diet. Annual household income was assessed by 15 categories. We used the median value of each category and obtained an equivalent household income based on a previous study.27 It was examined using six responses and re-categorized into three groups: low (≤12 years), medium (13–15 years) and high (≥16 years). It was examined by nine categories and re-categorized into four groups: full-time worker (manager/executive and regular employee), part-time worker (contract/temporary/fixed-term employee), homemaker (unemployment) and other job (self-employed, family worker). Statistical analysis After examining descriptive statistics, we performed multiple regression analyses for the outcomes of total daily intakes and share of school lunch-derived intakes per total intakes. We regarded SES indicators (household income, maternal and paternal educational attainments and maternal employment status) as main explanatory variables, adjusting for children’s sex, age and municipality of residence as covariates because school lunch provision is under municipality management. We used robust standard errors to consider intraclass correlations among children in the same household. We conducted analyses with and without log-transformed values of outcomes and found similar results. Consequently, we report the results without log-transformation for ease of interpretation. Finally, we estimated least-square means of intakes by the levels of SES indicators. Throughout the analyses, we combined the data for girls and boys because our preliminary analyses showed similar values for the associations between SES and fruit and vegetable intakes in both sexes. All analyses were conducted using STATA statistical software, version 13.1 SE (Stata Corporation, Collage Station, TX). Results The mean age of the participants was 9.3 years, and 51.2% of the participants were boys. The mean vegetable intake was 209.4 g/day and the mean fruit intake was 123.4 g/day. Overall, 26% of mothers and 55% of fathers graduated from college or higher education (table 1). Table 1 Participant characteristics Variables n (%) or mean (SD) Children’s characteristics Boys 368 (51.2) Age 9.3 (1.7) 1st grade 126 (17.5) 2nd grade 106 (14.7) 3rd grade 122 (17.0) 4th grade 127 (17.5) 5th grade 111 (15.4) 6th grade 124 (17.2) Dietary intake Vegetable intake (g) 209.4 (88.3) Fruit intake (g) 123.4 (91.0) Vegetable intake (g/1000 kcal) 115.4 (47.0) Fruit intake (g/1000 kcal) 66.6 (45.4) Total energy intake (kcal) 1852 (431.3) Share of vegetable intake from school lunch (%) 39.1 (14.9) Share of fruit intake from school lunch (%) 20.6 (17.1) Maternal education Low (<13 years) 210 (29.6) Medium (13–15 years) 319 (44.4) High (>15 years) 190 (26.4) Paternal education Low (<13 years) 184 (25.6) Medium (13–15 years) 140 (19.5) High (>15 years) 395 (54.9) Household income (million yen) 3.48 (1.6) Maternal employment status Full-time 78 (10.8) Part-time 228 (31.7) Homemaker 370 (51.5) Other job 43 (6.0) Variables n (%) or mean (SD) Children’s characteristics Boys 368 (51.2) Age 9.3 (1.7) 1st grade 126 (17.5) 2nd grade 106 (14.7) 3rd grade 122 (17.0) 4th grade 127 (17.5) 5th grade 111 (15.4) 6th grade 124 (17.2) Dietary intake Vegetable intake (g) 209.4 (88.3) Fruit intake (g) 123.4 (91.0) Vegetable intake (g/1000 kcal) 115.4 (47.0) Fruit intake (g/1000 kcal) 66.6 (45.4) Total energy intake (kcal) 1852 (431.3) Share of vegetable intake from school lunch (%) 39.1 (14.9) Share of fruit intake from school lunch (%) 20.6 (17.1) Maternal education Low (<13 years) 210 (29.6) Medium (13–15 years) 319 (44.4) High (>15 years) 190 (26.4) Paternal education Low (<13 years) 184 (25.6) Medium (13–15 years) 140 (19.5) High (>15 years) 395 (54.9) Household income (million yen) 3.48 (1.6) Maternal employment status Full-time 78 (10.8) Part-time 228 (31.7) Homemaker 370 (51.5) Other job 43 (6.0) Notes. SD, standard deviation. Share of vegetable intake from school lunch (%) = (vegetable intake from school lunch/total vegetable intake) × 100. Share of fruit intake from school lunch (%) = (fruit intake from school lunch/total fruit intake) × 100. Maternal employment status: ‘homemaker’ includes unemployment and ‘other job’ refers to self-employment or family worker. Table 1 Participant characteristics Variables n (%) or mean (SD) Children’s characteristics Boys 368 (51.2) Age 9.3 (1.7) 1st grade 126 (17.5) 2nd grade 106 (14.7) 3rd grade 122 (17.0) 4th grade 127 (17.5) 5th grade 111 (15.4) 6th grade 124 (17.2) Dietary intake Vegetable intake (g) 209.4 (88.3) Fruit intake (g) 123.4 (91.0) Vegetable intake (g/1000 kcal) 115.4 (47.0) Fruit intake (g/1000 kcal) 66.6 (45.4) Total energy intake (kcal) 1852 (431.3) Share of vegetable intake from school lunch (%) 39.1 (14.9) Share of fruit intake from school lunch (%) 20.6 (17.1) Maternal education Low (<13 years) 210 (29.6) Medium (13–15 years) 319 (44.4) High (>15 years) 190 (26.4) Paternal education Low (<13 years) 184 (25.6) Medium (13–15 years) 140 (19.5) High (>15 years) 395 (54.9) Household income (million yen) 3.48 (1.6) Maternal employment status Full-time 78 (10.8) Part-time 228 (31.7) Homemaker 370 (51.5) Other job 43 (6.0) Variables n (%) or mean (SD) Children’s characteristics Boys 368 (51.2) Age 9.3 (1.7) 1st grade 126 (17.5) 2nd grade 106 (14.7) 3rd grade 122 (17.0) 4th grade 127 (17.5) 5th grade 111 (15.4) 6th grade 124 (17.2) Dietary intake Vegetable intake (g) 209.4 (88.3) Fruit intake (g) 123.4 (91.0) Vegetable intake (g/1000 kcal) 115.4 (47.0) Fruit intake (g/1000 kcal) 66.6 (45.4) Total energy intake (kcal) 1852 (431.3) Share of vegetable intake from school lunch (%) 39.1 (14.9) Share of fruit intake from school lunch (%) 20.6 (17.1) Maternal education Low (<13 years) 210 (29.6) Medium (13–15 years) 319 (44.4) High (>15 years) 190 (26.4) Paternal education Low (<13 years) 184 (25.6) Medium (13–15 years) 140 (19.5) High (>15 years) 395 (54.9) Household income (million yen) 3.48 (1.6) Maternal employment status Full-time 78 (10.8) Part-time 228 (31.7) Homemaker 370 (51.5) Other job 43 (6.0) Notes. SD, standard deviation. Share of vegetable intake from school lunch (%) = (vegetable intake from school lunch/total vegetable intake) × 100. Share of fruit intake from school lunch (%) = (fruit intake from school lunch/total fruit intake) × 100. Maternal employment status: ‘homemaker’ includes unemployment and ‘other job’ refers to self-employment or family worker. Maternal education was significantly related to vegetable intake. By reference to children with high maternal education (>15 years), those with low maternal education (<13 years) were estimated to have 22.3 g [95% confidence interval (CI) = 12.5, 32.2] less vegetable intake per 1000 kcal intake. The corresponding value for fruit intake was −7.5 g (95% CI = −2.4, 17.3). Meanwhile, paternal education was not associated with both fruit and vegetable intakes (data not shown). Every 1 million yen unit increase in annual household income was associated with 2.4 g/1000 kcal (95% CI = 0.2, 4.6) more fruit intake (table 2). Among children with low maternal education, the share of school lunch in vegetable intake was 7.4% (95% CI = 4.2, 10.6) higher than that for children with high maternal education. The share of school lunch in fruit intake for children with higher household income was 0.8% (95% CI = −1.6, 0.0) lower than that for children with lower household income (table 2). Table 2 Associations of vegetable or fruit intake and share of vegetable or fruit intake from school lunch with SES by multiple regression analysis among school children in Japan (n = 719) Vegetable intake (g/1000 kcal) Share of vegetable intake from school lunch (%) Fruit intake (g/1000 kcal) Share of fruit intake from school lunch (%) Coeff. 95% CI Coeff. 95% CI Coeff. 95% CI Coeff. 95% CI Maternal education     High (>15 years) 0.0 Ref. 0.0 Ref. 0.0 Ref. 0.0 Ref.     Medium (13–15 years) −17.5 −26.1, −8.9 2.7 0.0, 5.3 −5.1 −13.7, 3.5 −0.6 −3.6, 2.5     Low (<13 years) −22.3 −32.2, −12.5 7.4 4.2, 10.6 −7.5 −17.3, 2.4 4.2 −0.5, 8.8 Household income (per 1 million yen) −1.1 −3.5, 1.3 0.0 −0.7, 0.8 2.4 0.2, 4.6 −0.8 −1.6, 0.0 Maternal employment status     Full-time 0.0 Ref. 0.0 Ref. 0.0 Ref. 0.0 Ref.     Part-time 5.5 −7.3, 18.2 −2.2 −6.5, 2.2 −1.4 −11.9, 9.1 0.5 −3.3, 4.4     Homemaker 3.1 −8.2, 14.4 −1.6 −5.8, 2.5 4.8 −6.1, 15.6 1.0 −2.7, 4.8     Other job −10.0 −2.4, 1.5 0.3 −5.9, 6.5 2.0 18.7, 22.7 5.7 2.0, 13.4 Vegetable intake (g/1000 kcal) Share of vegetable intake from school lunch (%) Fruit intake (g/1000 kcal) Share of fruit intake from school lunch (%) Coeff. 95% CI Coeff. 95% CI Coeff. 95% CI Coeff. 95% CI Maternal education     High (>15 years) 0.0 Ref. 0.0 Ref. 0.0 Ref. 0.0 Ref.     Medium (13–15 years) −17.5 −26.1, −8.9 2.7 0.0, 5.3 −5.1 −13.7, 3.5 −0.6 −3.6, 2.5     Low (<13 years) −22.3 −32.2, −12.5 7.4 4.2, 10.6 −7.5 −17.3, 2.4 4.2 −0.5, 8.8 Household income (per 1 million yen) −1.1 −3.5, 1.3 0.0 −0.7, 0.8 2.4 0.2, 4.6 −0.8 −1.6, 0.0 Maternal employment status     Full-time 0.0 Ref. 0.0 Ref. 0.0 Ref. 0.0 Ref.     Part-time 5.5 −7.3, 18.2 −2.2 −6.5, 2.2 −1.4 −11.9, 9.1 0.5 −3.3, 4.4     Homemaker 3.1 −8.2, 14.4 −1.6 −5.8, 2.5 4.8 −6.1, 15.6 1.0 −2.7, 4.8     Other job −10.0 −2.4, 1.5 0.3 −5.9, 6.5 2.0 18.7, 22.7 5.7 2.0, 13.4 Notes. CI, confidence interval; Coeff., coefficient. Share of vegetable intake from school lunch (%) = (vegetable intake from school lunch/total vegetable intake) × 100. Share of fruit intake from school lunch (%) = (fruit intake from school lunch/total fruit intake) × 100. Adjustment for: age, sex and municipality of residence. Table 2 Associations of vegetable or fruit intake and share of vegetable or fruit intake from school lunch with SES by multiple regression analysis among school children in Japan (n = 719) Vegetable intake (g/1000 kcal) Share of vegetable intake from school lunch (%) Fruit intake (g/1000 kcal) Share of fruit intake from school lunch (%) Coeff. 95% CI Coeff. 95% CI Coeff. 95% CI Coeff. 95% CI Maternal education     High (>15 years) 0.0 Ref. 0.0 Ref. 0.0 Ref. 0.0 Ref.     Medium (13–15 years) −17.5 −26.1, −8.9 2.7 0.0, 5.3 −5.1 −13.7, 3.5 −0.6 −3.6, 2.5     Low (<13 years) −22.3 −32.2, −12.5 7.4 4.2, 10.6 −7.5 −17.3, 2.4 4.2 −0.5, 8.8 Household income (per 1 million yen) −1.1 −3.5, 1.3 0.0 −0.7, 0.8 2.4 0.2, 4.6 −0.8 −1.6, 0.0 Maternal employment status     Full-time 0.0 Ref. 0.0 Ref. 0.0 Ref. 0.0 Ref.     Part-time 5.5 −7.3, 18.2 −2.2 −6.5, 2.2 −1.4 −11.9, 9.1 0.5 −3.3, 4.4     Homemaker 3.1 −8.2, 14.4 −1.6 −5.8, 2.5 4.8 −6.1, 15.6 1.0 −2.7, 4.8     Other job −10.0 −2.4, 1.5 0.3 −5.9, 6.5 2.0 18.7, 22.7 5.7 2.0, 13.4 Vegetable intake (g/1000 kcal) Share of vegetable intake from school lunch (%) Fruit intake (g/1000 kcal) Share of fruit intake from school lunch (%) Coeff. 95% CI Coeff. 95% CI Coeff. 95% CI Coeff. 95% CI Maternal education     High (>15 years) 0.0 Ref. 0.0 Ref. 0.0 Ref. 0.0 Ref.     Medium (13–15 years) −17.5 −26.1, −8.9 2.7 0.0, 5.3 −5.1 −13.7, 3.5 −0.6 −3.6, 2.5     Low (<13 years) −22.3 −32.2, −12.5 7.4 4.2, 10.6 −7.5 −17.3, 2.4 4.2 −0.5, 8.8 Household income (per 1 million yen) −1.1 −3.5, 1.3 0.0 −0.7, 0.8 2.4 0.2, 4.6 −0.8 −1.6, 0.0 Maternal employment status     Full-time 0.0 Ref. 0.0 Ref. 0.0 Ref. 0.0 Ref.     Part-time 5.5 −7.3, 18.2 −2.2 −6.5, 2.2 −1.4 −11.9, 9.1 0.5 −3.3, 4.4     Homemaker 3.1 −8.2, 14.4 −1.6 −5.8, 2.5 4.8 −6.1, 15.6 1.0 −2.7, 4.8     Other job −10.0 −2.4, 1.5 0.3 −5.9, 6.5 2.0 18.7, 22.7 5.7 2.0, 13.4 Notes. CI, confidence interval; Coeff., coefficient. Share of vegetable intake from school lunch (%) = (vegetable intake from school lunch/total vegetable intake) × 100. Share of fruit intake from school lunch (%) = (fruit intake from school lunch/total fruit intake) × 100. Adjustment for: age, sex and municipality of residence. The fruit and vegetable intakes from school lunch did not vary large by SES, despite the existence of SES-based differences in the total amounts of fruit and vegetable intakes (figure 1). Thus, school lunch contributed to a reduction in the inequality of vegetable intake by 9.9% and fruit intake by 3.4% (table 3). Table 3 Average total vegetable intake, vegetable intake from home by maternal education and average total fruit intake, fruit intake from home by household income, adjusting for all SES indicators, children’s sex and age and municipality of residence Maternal education Household income Ratio of high/low Change of ratio (%) High (>15 years) Low (<13 years) High (>3.61 million yen) Low (<2.79 million yen) Total vegetable intake (g/1000 kcal) 129.7 107.5 1.21 9.89 Vegetable intake from home (g/1000 kcal) 88.1 65.8 1.34 Total fruit intake (g/1000 kcal) 69.7 60.5 1.15 3.36 Fruit intake from home (g/1000 kcal) 61.3 51.5 1.19 Maternal education Household income Ratio of high/low Change of ratio (%) High (>15 years) Low (<13 years) High (>3.61 million yen) Low (<2.79 million yen) Total vegetable intake (g/1000 kcal) 129.7 107.5 1.21 9.89 Vegetable intake from home (g/1000 kcal) 88.1 65.8 1.34 Total fruit intake (g/1000 kcal) 69.7 60.5 1.15 3.36 Fruit intake from home (g/1000 kcal) 61.3 51.5 1.19 Table 3 Average total vegetable intake, vegetable intake from home by maternal education and average total fruit intake, fruit intake from home by household income, adjusting for all SES indicators, children’s sex and age and municipality of residence Maternal education Household income Ratio of high/low Change of ratio (%) High (>15 years) Low (<13 years) High (>3.61 million yen) Low (<2.79 million yen) Total vegetable intake (g/1000 kcal) 129.7 107.5 1.21 9.89 Vegetable intake from home (g/1000 kcal) 88.1 65.8 1.34 Total fruit intake (g/1000 kcal) 69.7 60.5 1.15 3.36 Fruit intake from home (g/1000 kcal) 61.3 51.5 1.19 Maternal education Household income Ratio of high/low Change of ratio (%) High (>15 years) Low (<13 years) High (>3.61 million yen) Low (<2.79 million yen) Total vegetable intake (g/1000 kcal) 129.7 107.5 1.21 9.89 Vegetable intake from home (g/1000 kcal) 88.1 65.8 1.34 Total fruit intake (g/1000 kcal) 69.7 60.5 1.15 3.36 Fruit intake from home (g/1000 kcal) 61.3 51.5 1.19 Figure 1 View largeDownload slide Average vegetable and fruit intake by household SESs, adjusting for all other socioeconomic indicators, children’s sex and age and municipality of residence Figure 1 View largeDownload slide Average vegetable and fruit intake by household SESs, adjusting for all other socioeconomic indicators, children’s sex and age and municipality of residence Discussion The key findings of this study are as follows. First, maternal education was associated with overall fruit and vegetable intakes independently of other individual and household sociodemographic characteristics, while paternal education was not. Household income was only associated with fruit intake. These results are consistent with those of previous studies conducted in Western countries, showing that maternal education is positively associated with fruit and vegetable intakes among school children.3–6,28 Second, we demonstrated that children whose mothers were less educated had greater reliance on school lunch for their vegetable intake, and children with lower household income had more contribution from school lunch to their fruit intake. However, because the serving of fruit in school lunches as well as overall fruit intake is low in Japan compared with Western countries,29 the attributable effects of school lunch in reducing the socioeconomic disparity in regard to fruit intake may be limited. Our study adds new evidence that universal school lunch programmes are effective in at least partially reducing the gap in diet across parental SES. Lower socioeconomic children had less access to high quality and balanced meals at home, and universal school lunch programmes may provide greater contributions to children in lower socioeconomic conditions. In our study, maternal education had stronger associations with fruit and vegetable intakes than paternal education. This may reflect the notion that the person who usually cooks at home affects the nutritional intake of their children. In the majority of Japanese households, mothers are more likely to prepare most meals for their children. According to a government nationwide survey comprising a general survey of social life, women spend 2.5 h/day on housekeeping including meal preparation, while men spend only 0.3 h/day.30 Household income was also associated with fruit intake. Fruits might be considered ‘luxury items’. This was reflected by the governmental survey of price elasticity that categorized fruit and snacks as amenity foods.31 Additionally, maternal skills and knowledge on diet may have less effect on their children’s fruit intake than on their vegetable intake. The correlation between vegetable intake and income was not statistically significant. This was not consistent with the National Health and Nutrition Survey.17,18 A potential explanation of the inconsistency may be the difference in age distribution between the groups. This study focuses on children, who are more influenced by parental food choices and household characteristics. Alternatively, the measurement of income is significantly different between the studies. The National Surveys used only three categories (≤2 million yen, 2–6 million yen, ≤6 million yen) when determining household income, potentially more vulnerable to error. Further studies are needed to conclude the correlation between vegetable intake and household income in Japanese children. Given that maternal education may reflect their skills and knowledge on diet to serve healthy meals, it is plausible that mothers with lower educational attainment may have difficulties in regularly providing balanced meals at home. Maternal food preferences may also affect children’s diet. Evidence suggests strong correlations between mothers and children in their vegetable and fruit consumptions.5,32–34 Thus, the socioeconomic gap in dietary intakes among children is likely to be mainly derived from their home intakes. However, we found that SES did not impact fruit and vegetable intake from school lunch. These findings are particularly noteworthy because they strongly suggest that universal school lunch programmes could equally provide the opportunities for fruit and vegetable intake to all children regardless of their SES. Nonetheless, SES-based disparity remained at 22.3 g/1000 kcal for vegetable intake and 7.5 g/1000 kcal for fruit intake between low and high maternal educational attainments. To further reduce these gaps, additional measures to secure more availability and accessibility of fruit and vegetables through school meal programmes35 and other sources including home intakes are warranted. For example, providing opportunities for children, in community settings, to eat balanced meals for breakfast and dinner that are free or available at affordable prices may help to further reduce the health disparity in diets.36 Nutrition and cooking education during early childhood may also contribute to children acquiring cooking skills and nutritional knowledge regardless of their SES.37 We used adjusted values for total and school lunch-derived fruit and vegetable intake per 1000 kcal to account for age-related variation in caloric intake. In studies in the USA, children of lower SES have been found to have higher energy intake due to excess portions and snacking. In this case, it may be more important to reduce caloric intake rather than enhance vegetable intake. However, studies in Japan38 have not shown a clear correlation between children’s SES and energy intake. In our sample, energy intake was slightly higher among children of higher household income. There are limitations to this study. First, the generalizability of the study may be limited because all participants were selected from four municipalities in the greater Tokyo metropolitan area.39 Further studies should evaluate the effectiveness of universal school lunch programmes in other settings in terms of place, culture and quality of lunch. Second, the validity of fruit and vegetable intakes specifically from school lunch estimated by the BDHQ-10y has not yet been examined. Compared with a school nutrition report in 2015,40 the total vegetable intake from school lunch was 17.5 g less in this study, while the total fruit intake from school lunch did not differ much. These data partly support the validity of the BDHQ-10y as a tool for nutritional analysis of Japanese school lunch. Third, some younger children were helped to answer dietary habit questionnaire, which may be susceptible to reporting bias by their mothers, especially with higher education and consciousness about healthy diet. However, sub-analysis limited to those that children answered by themselves did not make change in the results. Household income and parental education were self-reported; therefore, the possibility of misclassification exists. Furthermore, we did not have information about the curricula of the schools, which may have an effect on student eating habits. School lunch programmes were highly standardized by each municipality’s education authority under the School Lunch Program Act. Hence, we included municipality dummy codes in our regression analysis to incorporate any fixed effects related to differences between municipalities. Achievement of standardized universal school lunch programmes is a challenge. Sustainability in food logistics systems and financing for nationwide universal school lunch programmes are other topics to be investigated. Other challenges in universal school lunch programmes are the costs required to meet various needs for food preferences based on religious and cultural diversity in schools. Studies investigating the cost-effectiveness of universal lunch programmes are warranted. Although there are some challenges, notwithstanding this successful case in Japan—where the school lunch program was started in 1947 under the support of United Nations Children's Fund (UNICEF) and the School Lunch Law was established in 1954—we believe that the promotion of universal school lunch programmes can be an effective vehicle for closing the nutrition-associated gap in schoolchildren overcoming socioeconomic challenges. Conclusion In this study, we demonstrated the effectiveness of standardized universal school lunch programmes in partially reducing the maternal–education-related gradient in vegetable intake and household income-related fruit intakes in the Japanese elementary school setting. Additional community interventions may be needed to further close the gap in children’s dietary intake. Acknowledgements The authors thank Satoshi Sasaki and Satomi Kobayashi for advice on the statistical analyses. Funding The Japanese Study on Stratification, Health, Income and Neighbourhood (J-SHINE) was supported by a Grant-in-Aid for Scientific Research on Innovative Areas (No. 21119002) from the Ministry of Education, Culture, Sports, Science and Technology, Japan and the Ministry of Health, Labour and Welfare, Japan (H27–junkankitou-ippan-002, H28-junkankitou-ippan-008). Conflicts of interest: None declared. Key points Parental SES was associated with overall fruit and vegetable intakes. Children whose mothers were less educated had greater reliance on school lunch for their vegetable intake. Children with lower household income had more contribution from school lunch to their fruit intake. Universal school lunch programmes can in part contribute to a reduction in the SES-related gradient in diets. References 1 Wang Y , Beydoun MA . 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The European Journal of Public HealthOxford University Press

Published: Mar 26, 2018

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