| Literature DB >> 28182763 |
Ingrid W Leal Bezerra1, António Gouveia Oliveira2, Liana G B Pinheiro1, Célia M M Morais1, Luciano M B Sampaio3.
Abstract
The objective of this study was to assess whether the Brazilian Workers' Food Program (WFP) is associated with changes in the nutritional status of workers in the transformation industry. We conducted a cross-sectional, observational, comparative study, based on prospectively collected data from a combined stratified and two-stage probability sample of workers from 26 small and medium size companies, 13 adherent and 13 non-adherent to the WFP, in the food, mining and textile sectors. Study variables were body mass index (BMI), waist circumference (WC), and dietary intake at lunch obtained by 24-hour dietary recall. Data were analyzed with nested mixed effects linear regression with adjustment by subject variables. Sampling weights were applied in computing population parameters. The final sample consisted of 1069 workers, 541 from WFP-adherent and 528 from WFP non-adherent companies. The groups were different only in education level, income and in-house training. Workers in WFP-adherent companies have greater BMI (27.0 kg/m2 vs. 26.0 kg/m2, p = 0.002) and WC (87.9 cm vs. 86.5, p = 0.04), higher prevalence of excessive weight (62.6% vs. 55.5%, p<0.001) and of increased WC (49.1% vs. 39.9%). Workers of WFP companies have lower intake of saturated fat (-1.34 g, p<0.01) and sodium (-0.3 g, p<0.01) at lunch. In conclusion, this study showed that workers of companies adherent to the Brazilian WFP have greater rates of excessive weight and increased cardiovascular risk-a negative finding-as well as lower intake of sodium and saturated fat-a positive finding. Therefore, the WFP needs to be revisited and its aims redefined according to the current epidemiological status of the target population of the program.Entities:
Mesh:
Year: 2017 PMID: 28182763 PMCID: PMC5300183 DOI: 10.1371/journal.pone.0171821
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Characteristics of the surveyed companies in the two study groups according to the sector of economic activity and the company size.
| Characteristics of surveyed companies | non-WFP | WFP | ||
|---|---|---|---|---|
| nb. of companies | nb. of participants | nb. of companies | nb. of participants | |
| Sector | ||||
| Alimentary | 5 | 181 | 5 | 218 |
| Mining | 3 | 123 | 2 | 77 |
| Textile | 5 | 224 | 6 | 246 |
| Size | ||||
| Small | 7 | 260 | 6 | 240 |
| Medium | 6 | 268 | 7 | 301 |
Workers’ bio-demographic and socioeconomic characteristics in companies non-adherent and adherent to the WFP in the State of Rio Grande do Norte, Brazil, 2014.
| Characteristic | non-WFP | WFP | p | ||||
|---|---|---|---|---|---|---|---|
| (n = 528) | (n = 541) | ||||||
| mean/% | 95% CI | mean/% | 95% CI | ||||
| Age (mean) | 34.5 | 32.4 | 36.7 | 34.5 | 33.2 | 35.8 | 0.77 |
| Male sex % | 64.70 | 48.5 | 80.9 | 54.5 | 43.9 | 65.1 | 0.41 |
| Living alone % | 44.1 | 37.6 | 50.5 | 46.1 | 39.5 | 52.6 | 0.75 |
| Children (mean) | 1.5 | 1.2 | 1.9 | 1.3 | 1.2 | 1.5 | 0.30 |
| Education>middle school % | 36.9 | 27.1 | 46.6 | 68.7 | 60.7 | 76.8 | <0.001 |
| Income > minimum wage % | 29.6 | 20.1 | 39.1 | 45.2 | 36.0 | 54.4 | 0.04 |
| In-house training % | 16.4 | 8.7 | 24.1 | 27.6 | 21.8 | 33.3 | <0.001 |
* Nested mixed effects logistic regression;
** Nested mixed effects linear regression. Fixed factors: WFP and company size; random factors: sector of economic activity and company nested within sector.
Frequency distribution of workers by nutritional diagnosis in companies of the transformation industry non-adherent and adherent to the WFP in the State of Rio Grande do Norte, Brazil.
| Variables | non-WFP | WFP | p | ||||
|---|---|---|---|---|---|---|---|
| (n = 528) | (n = 541) | ||||||
| point estimate | 95% CI | point estimate | 95% CI | ||||
| BMI kg/m2 (m, sd) | 26.0 | 25.5 | 26.6 | 27.0 | 26.5 | 27.4 | 0.002 |
| Adult BMI classification. [ | <0.001 | ||||||
| underweight (<18.5) | 1.9 | 0.7 | 3.1 | 0.6 | 0.0 | 1.4 | |
| normal weight (18.5–24.9) | 42.6 | 36.2 | 49.0 | 36.6 | 32.7 | 41.0 | |
| excessive weight (≥25.0) | 55.5 | 49.1 | 61.9 | 62.6 | 58.4 | 66.7 | |
| overweight (25.0–29.9) | 40.3 | 35.3 | 45.2 | 41.0 | 36.5 | 45.5 | |
| obesity I (30.0–34.9) | 12.3 | 8.8 | 15.8 | 15.7 | 11.8 | 19.6 | |
| obesity II-III (≥35.0) | 3.0 | 0.8 | 5.2 | 5.9 | 3.0 | 8.8 | |
| Waist circumference cm (m,sd) | 86.5 | 85.3 | 87.7 | 87.9 | 86.9 | 88.9 | 0.04 |
| Waist circ. classification 15 (n,%) | 0.02 | ||||||
| normal | 60.1 | 50.3 | 70.0 | 50.9 | 44.6 | 57.2 | |
| increased | 20.6 | 15.9 | 25.3 | 23.3 | 18.0 | 28.5 | |
| substantially increased | 19.3 | 12.6 | 25.9 | 25.9 | 21.8 | 29.9 | |
* Nested mixed effects linear regression; Fixed factors: WFP and company size; random factors: sector of economic activity and company nested within sector.
** Ordered logistic regression. All analyses adjusted by age, sex, education, income and in-house training.
Calories and nutrients consumed at lunch by workers of companies the transformation industry adherent to the WFP compared to workers in non-adherent companies in the State of Rio Grande do Norte, Brazil.
| Variables | non-WFP | WFP | Difference | p | ||||||
|---|---|---|---|---|---|---|---|---|---|---|
| (n = 528) | (n = 541) | |||||||||
| mean | 95% CI | mean | 95% CI | mean | 95% CI | |||||
| Energy (Kcal) | 750 | 667 | 832 | 743 | 675 | 811 | -33.8 | -117.8 | 50.2 | 0.43 |
| Protein (Kcal) | 192 | 174 | 210 | 186 | 170 | 203 | -13.6 | -34.5 | 7.3 | 0.20 |
| Lipids (Kcal) | 214 | 181 | 246 | 211 | 180 | 242 | -18.5 | -57.6 | 20.7 | 0.36 |
| Carbohydrates (Kcal) | 346 | 308 | 385 | 351 | 318 | 383 | 0.4 | -37.0 | 37.9 | 0.98 |
| Fiber (g) | 15.7 | 13.9 | 17.5 | 15.0 | 12.8 | 17.2 | -0.55 | -2.70 | 1.59 | 0.61 |
| Sodium (g) | 1.99 | 1.77 | 2.22 | 1.81 | 1.50 | 2.11 | -0.30 | -0.53 | -0.07 | 0.01 |
| Saturated fat (g) | 9.8 | 4.4 | 15.2 | 6.7 | 6.0 | 7.3 | -1.34 | -2.38 | -0.30 | 0.01 |
* Nested mixed effects linear regression; Fixed factors: WFP and company size; random factors: sector of economic activity and company nested within sector; adjustment by age, sex, education, income and in-house training.