| Literature DB >> 35270594 |
Jozaa Z AlTamimi1, Naseem M Alshwaiyat2, Hana Alkhalidy3, Nora A AlFaris1, Nora M AlKehayez1, Reham I Alagal1.
Abstract
Breakfast skipping is linked with obesity incidence. This study was conducted to assess the prevalence of breakfast skipping among a multi-ethnic population of young men residing in Saudi Arabia and its relationship with sociodemographic determinants and weight status. A total of 3600 young men aged 20 to 35 years and living in Riyadh, Saudi Arabia, were involved in this cross-sectional study. Sociodemographic determinants and breakfast-consumption frequency were collected from subjects by personal interviews. This study defines breakfast skipping as skipping breakfast at least one day per week. Weight and height were measured following standardized methods. The prevalence of breakfast skipping was observed among 52.8% of the study subjects. Nationality was a predictor of breakfast skipping, with the lowest and highest rates of breakfast skipping reported among young men from Bangladesh (14.0%) and Saudi Arabia (86.5%), respectively. Weight status was another predictor of breakfast skipping, as the mean body mass index for breakfast skippers (25.4 kg/m2) was significantly (p-value < 0.001) higher than that for breakfast consumers (24.8 kg/m2). Overweight/obese subjects have a significantly higher rate of breakfast skipping (56.9%) than underweight/normal weight subjects (48.9%). In conclusion, breakfast skipping prevalence is relatively high among young men residing in Saudi Arabia. The findings confirm a relationship between breakfast skipping and sociodemographic determinants and weight status.Entities:
Keywords: body mass index; breakfast skipping; multi-ethnic; weight status; young men
Mesh:
Year: 2022 PMID: 35270594 PMCID: PMC8910178 DOI: 10.3390/ijerph19052903
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
Sociodemographic determinants and body weight status of study participants stratified according to breakfast-consumption patterns.
| Variables | Breakfast Consumption | Breakfast Skipping | |
|---|---|---|---|
| All Participants | 1700 (47.2%) | 1900 (52.8%) | |
| Nationality | ˂0.001 | ||
| Saudi | 39 (13.5%) | 250 (86.5%) | |
| Egyptian | 107 (37.0%) | 182 (63.0%) | |
| Yemeni | 127 (37.9%) | 208 (62.1%) | |
| Syrian | 105 (35.8%) | 188 (64.2%) | |
| Jordanian | 46 (16.4%) | 234 (83.6%) | |
| Sudanese | 200 (72.5%) | 76 (27.5%) | |
| Turkish | 124 (61.1%) | 79 (38.9%) | |
| Pakistani | 153 (50.0%) | 153 (50.0%) | |
| Afghan | 190 (62.7%) | 113 (37.3%) | |
| Indian | 174 (58.6%) | 123 (41.4%) | |
| Bangladeshi | 301 (86.0%) | 49 (14.0%) | |
| Filipino | 134 (35.4%) | 245 (64.6%) | |
| Age (years) | 29.9 (3.2) | 29.3 (3.2) | ˂0.001 |
| Residency Period in Saudi Arabia | 0.064 | ||
| 1–5 years | 1065 (48.5%) | 1133 (51.5%) | |
| 6 years or more | 635 (45.3%) | 767 (54.7%) | |
| Household Type | ˂0.001 | ||
| Non-family household | 1490 (51.0%) | 1430 (49.0%) | |
| Family household | 210 (30.9%) | 470 (69.1%) | |
| Marital Status | ˂0.001 | ||
| Single | 789 (41.1%) | 1130 (58.9%) | |
| Married | 911 (54.2%) | 770 (45.8%) | |
| Education Level | ˂0.001 | ||
| High school or less | 1298 (56.8%) | 986 (43.2%) | |
| College degree or more | 402 (30.5%) | 914 (69.5%) | |
| Monthly Income | ˂0.001 | ||
| Low (˂USD 1000) | 1408 (53.5%) | 1222 (46.5%) | |
| High (≥USD 1000) | 292 (30.1%) | 678 (69.9%) | |
| Body Mass Index (kg/m2) | 24.8 (3.0) | 25.4 (3.4) | ˂0.001 |
| Body Weight Status | ˂0.001 | ||
| Underweight/Normal weight | 950 (51.1%) | 910 (48.9%) | |
| Overweight/Obesity | 750 (43.1%) | 990 (56.9%) |
* Categorical variables were analyzed using chi-square test and expressed as numbers and percentages. Continuous variables were analyzed using independent samples t-test and expressed as means and standard deviations.
Figure 1Bar chart illustrating breakfast-skipping prevalence among study participants stratified based on their nationality.
Odds ratios of breakfast skipping among study participants for sociodemographic determinants and body mass index.
| Variables | Unadjusted Odds Ratio | 95% CI | Adjusted | 95% CI | ||
|---|---|---|---|---|---|---|
| Nationality | ||||||
| Bangladeshi | 1.00 | 1.00 | ||||
| Saudi | 39.38 | 25.04–61.93 |
| 27.19 | 15.95–46.35 |
|
| Egyptian | 10.45 | 7.11–15.35 |
| 8.80 | 5.76–13.44 |
|
| Yemeni | 10.06 | 6.92–14.62 |
| 7.97 | 5.39–11.78 |
|
| Syrian | 11.00 | 7.48–16.16 |
| 9.22 | 5.97–14.25 |
|
| Jordanian | 31.25 | 20.18–48.38 |
| 29.10 | 17.97–47.11 |
|
| Sudanese | 2.33 | 1.56–3.49 |
| 2.23 | 1.48–3.37 |
|
| Turkish | 3.91 | 2.59–5.92 |
| 3.58 | 2.33–5.50 |
|
| Pakistani | 6.14 | 4.22–8.95 |
| 4.92 | 3.34–7.24 |
|
| Afghan | 3.65 | 2.50–5.35 |
| 3.02 | 2.04–4.47 |
|
| Indian | 4.34 | 2.97–6.35 |
| 4.10 | 2.79–6.03 |
|
| Filipino | 11.23 | 7.77–16.23 |
| 10.12 | 6.72–15.26 |
|
| Age (years) | 0.95 | 0.93–0.97 |
| 0.97 | 0.95–1.00 |
|
| Residency Period in Saudi Arabia | ||||||
| 1–5 years | 1.00 | 1.00 | ||||
| 6 years or more | 1.14 | 0.99–1.30 | 0.064 | 1.10 | 0.92–1.31 | 0.292 |
| Household Type | ||||||
| Non-family household | 1.00 | 1.00 | ||||
| Family household | 2.33 | 1.95–2.79 |
| 0.89 | 0.69–1.16 | 0.400 |
| Marital Status | ||||||
| Single | 1.00 | 1.00 | ||||
| Married | 0.59 | 0.52–0.67 |
| 0.63 | 0.53–0.76 |
|
| Education Level | ||||||
| High school or less | 1.00 | 1.00 | ||||
| College degree or more | 2.99 | 2.59–3.46 |
| 0.98 | 0.78–1.23 | 0.874 |
| Monthly Income | ||||||
| Low (˂USD 1000) | 1.00 | 1.00 | ||||
| High (≥USD 1000) | 2.68 | 2.29–3.13 |
| 1.37 | 1.10–1.71 |
|
| Body Mass Index (kg/m2) | 1.06 | 1.03–1.08 |
| 1.03 | 1.01–1.06 |
|
* Univariate logistic regression analysis was used to test differences between breakfast skippers versus breakfast consumers (reference group). Differences were considered statistically significant at p value < 0.05, and significant values are presented in bold type. ** Multivariate logistic regression analysis was used to test differences between breakfast skippers versus breakfast consumers (reference group) after adjusting for subjects’ sociodemographic determinants and body mass index. Differences were considered statistically significant at p-value < 0.05, and significant values are presented in bold type.