| Literature DB >> 33919560 |
Peggy Ober1,2,3, Carolin Sobek1,2, Nancy Stein3, Ulrike Spielau2,3, Sarah Abel1,2,3, Wieland Kiess1,2, Christof Meigen1,2, Tanja Poulain1,2, Ulrike Igel1,2,4, Tobias Lipek1,2,3, Mandy Vogel1,2.
Abstract
Given the high prevalence of childhood overweight, school-based programs aiming at nutritional behavior may be a good starting point for community-based interventions. Therefore, we investigated associations between school-related meal patterns and weight status in 1215 schoolchildren. Anthropometry was performed on-site in schools. Children reported their meal habits, and parents provided family-related information via questionnaires. Associations between nutritional behavior and weight status were estimated using hierarchical linear and logistic regression. Analyses were adjusted for age, socio-economic status, school type, migration background, and parental weight status. Having breakfast was associated with a lower BMI-SDS (βadj = -0.51, p = 0.004) and a lower risk of being overweight (ORadj = 0.30, p = 0.009), while having two breakfasts resulting in stronger associations (BMI-SDS: βadj = -0.66, p < 0.001; risk of overweight: ORadj = 0.22, p = 0.001). Likewise, children who regularly skipped breakfast on school days showed stronger associations (BMI-SDS: β = 0.49, p < 0.001; risk of overweight: OR = 3.29, p < 0.001) than children who skipped breakfast only occasionally (BMI-SDS: β = 0.43, p < 0.001; risk of overweight: OR = 2.72, p = 0.032). The associations persisted after controlling for parental SES and weight status. Therefore, our data confirm the school setting as a suitable starting point for community-based interventions and may underline the necessity of national programs providing free breakfast and lunch to children.Entities:
Keywords: breakfast; breakfast skipping; children; lunch; meal frequency; obesity; overweight; school
Year: 2021 PMID: 33919560 PMCID: PMC8072724 DOI: 10.3390/nu13041351
Source DB: PubMed Journal: Nutrients ISSN: 2072-6643 Impact factor: 5.717
Figure 1Flow diagram of inclusion and exclusion of study participants. Private schools combine different types of schools.
Description of the study sample.
| Study Population ( | |||
|---|---|---|---|
| Range | |||
| Age (years) | 11.32 (1.35) | 8.94–15.42 | |
| Sex | |||
| Male | 598 (49.2) | ||
| Female | 617 (50.8) | ||
| School type | |||
| Elementary school | 690 (56.8) | ||
| Lower secondary school | 178 (14.7) | ||
| Upper secondary school | 347 (28.6) | ||
| SES group | |||
| Low | 90 (10.7) | ||
| Medium | 467 (55.3) | ||
| High | 287 (34.0) | ||
| Missing | 371 | ||
| Migration background | |||
| Yes | 196 (19.6) | ||
| No | 804 (80.4) | ||
| Missing | 215 | ||
| BMI-SDS | −0.04 (1.08) | −3.58–2.99 | |
| BMI categorization | |||
| BMI-SDS < 1.28 | 1063 (87.8) | ||
| BMI-SDS ≥ 1.28 | 148 (12.2) | ||
| Missing | 4 | ||
| Parental overweight/obesity | |||
| Non | 276 (30.9) | ||
| Both | 180 (20.1) | ||
| Mother | 155 (31.7) | ||
| Father | 283 (17.3) | ||
| Missing | 321 | ||
µ: mean; SD: standard deviation; n: count; BMI: body mass index; SES: socio–economic status.
Associations between regular breakfast skipping (n = 72) and different dependent variables. Effects are given as odds ratios (incl. 95% CI) for the unadjusted and the adjusted analyses.
| Parameter | Breakfast Skipper (Ref: Breakfast Consumer) | ||||||
|---|---|---|---|---|---|---|---|
| Unadjusted OR | Adjusted OR | ||||||
| OR | 95%-CI | ORadj | 95%-CI | ||||
| Age (per year) | 1.54 | (1.27–1.87) | <0.001 | ||||
| Sex | Male | Ref. | |||||
| Female | 1.23 | (1.23–1.24) | <0.001 | ||||
| School type | Elementary school | Ref. | |||||
| Secondary school | 1.80 | (1.11–2.91) | 0.017 | 1.80 † | (1.11–2.92) | 0.016 | |
| SES group | Low | 3.42 | (1.56–7.46) | 0.002 | 3.33 | (1.55–7.14) | 0.002 |
| Medium | Ref. | ||||||
| High | 0.70 | (0.31–1.60) | 0.392 | 0.68 | (0.30–1.54) | 0.350 | |
| SES score | 0.84 | (0.77–0.93) | <0.001 | 0.85 | (0.77–0.93) | <0.001 | |
| Migration background | No | Ref. | |||||
| Yes | 1.69 | (0.87–3.26) | 0.113 | 1.70 | (1.69–1.71) | <0.001 | |
| Parental overweight (biological parents) | Not overweight/obese | Ref. | |||||
| Both overweight/obese | 0.95 | (0.34–2.69) | 0.928 | 0.99 | (0.35–2.82) | 0.986 | |
| Mother overweight/obese | 1.82 | (0.71–4.67) | 0.202 | 2.05 | (0.80–5.29) | 0.130 | |
| Father overweight/obese | 1.08 | (0.44–2.66) | 0.856 | 1.04 | (0.43–2.56) | 0.926 | |
OR: odds ratio; ORadj: adjusted for age and sex; Ref: reference; †: adjusted only for sex.
Figure 2Association of different eating habits with mean BMI-SDS/the likelihood of being overweight. (A). Mean BMI-SDS (incl. 95% CI) for children with different breakfast/lunch behavior: Based on the simple hierarchical regression analysis, children with different eating habits also differed in their mean BMI-SDS (black). Most of the associations persisted after adjustment (red). (B). The likelihood of being overweight (incl. 95% CI) for children with different breakfast/lunch behavior: based on the simple hierarchical logistic regression analysis, children with different eating habits also differed in their likelihood of being overweight (black). The difference in the likelihood between children having and not having breakfast remained statistically significant after adjustment (red).