Background: Ultra-processed foods are industrial formulations made from food extracts or constituents with little or no intact food and often containing additives that confer hyper-palatability. The consumption of these products increases the risk of chronic non-communicable diseases. Stressed people may engage in unhealthy eating as a way to cope. This study aimed to verify whether ultra-processed food consumption was associated with perceived stress levels in industrial and retail workers from Vitoria da Conquista, Brazil. Methods: This was a cross-sectional study carried out between July 2017 and August 2018. During the study period, 1270 participants completed a survey administered by an interviewer. Stress levels were assessed using the Perceived Stress Scale. Information regarding weekly ultra-processed food consumption was collected. Ultra-processed foods were classified into four groups: sugary drinks; sugary foods; fast foods; and canned foods, frozen foods, or processed meat. The Student’s t-test or one-way analysis of variance was used to assess the differences in stress levels and ultra-processed food consumption. Ordinal regression was used to determine the association between the degrees of stress and ultra-processed food consumption levels. Results: Factors such as a young age, being unmarried, smoking, high-risk alcohol consumption, negative health perception, and high perceived stress level indicated higher rates of ultra-processed food consumption. Ordinal regression analysis showed that high stress levels were associated with increased odds of higher ultra-processed food consumption (odds ratio: 1.94; 95% CI: 1.54–2.45). Conclusions: These findings could help identify appropriate target areas for interventions aimed at mental health promotion and healthier food consumption.

Background: This study aimed to assess the quality of life associated with gender inequalities in formal workers and to determine the effect of sociodemographic, clinical, and behavioral factors on the quality of life (QOL). Methods: This cross-sectional study involved 1270 workers. Quality of life was measured using the EUROHIS-QOL 8-Item and assessed in terms of psychological, environmental, social, and physical domains, while demographic, socioeconomic, behavioral, and clinical variables served as explanatory variables. Analyses were performed using an ordinal logistic regression model whose significance level was 5%. Results: Of the participants, 80.2% were men, and 19.8% were women; the mean age was 34 (standard deviation: ±10) and 32 (±9) years, respectively. In all prediction scenarios, men were more likely to have a higher quality of life, especially in the physical (odds ratio: 2.16; 95% confidence interval: 1.60–2.93) and psychological (odds ratio: 2.09; 95% confidence interval: 1.51–2.91) domains. Conclusions: Men and women had significantly different levels of quality of life, and sociodemographic, clinical, and behavioral variables partially clarified these differences, which were possibly established by a socio-historical process of construction of the work role determined by gender issues.

Background: This study aimed to identify the factors associated with the quality of life of young workers of a Social Work of Industry Unit. Methods: This was a cross-sectional study conducted on 1270 workers. Data were collected using a digital questionnaire built on the KoBoToolbox platform that included the EUROHIS-QOL eight-item index to assess quality of life. Demographic, socioeconomic, behavioral, and clinical variables were considered explanatory. The associations were analyzed using the ordinal logistic regression model at a 5% significance level. Results: Men and women had a mean quality of life of 31.1 and 29.4, respectively. Workers that rated their health as “very good” had an odds ratio of 7.4 (95% confidence interval (CI) = 5.17–10.81), and those who rated it as “good” had an odds ratio of 2.9 (95% CI = 2.31–3.77). Both these groups of workers were more likely to have higher levels of quality of life as compared to workers with “regular”, “poor”, or “very poor” self-rated health. Physically active individuals were 30% more likely to have higher levels of quality of life (odds ratio = 1.3; 95% CI = 1.08–1.65). After adjusting the model by gender, age group, marital status, socioeconomic class, self-rated health, nutritional status, and risky alcohol consumption, the odds ratio of active individuals remained stable (odds ratio = 1.3; 95% CI = 1.05–1.66). Conclusions: In the present study, self-rated health, physical activity, and gender were associated with young workers’ quality of life.

BACKGROUND: Physician and patient-related characteristics can influence prescription of medications to older patients within primary healthcare. Use of Brazilian criteria may indicate the real prevalence of prescription of potentially inappropriate medications to this population. OBJECTIVES: To evaluate prescription of potentially inappropriate medications to older patients within primary care and identify patient-related and prescribing physician-related factors. DESIGN AND SETTING: This cross-sectional study was conducted in 22 public primary care facilities in Brazil, among older people (>= 60 years) who were waiting for medical consultations. METHODS: Interviews were conducted before and after the medical consultations. If the patient received a medical prescription at the consultation, all the drugs prescribed and the physician's medical council registration number were recorded. Prevalence ratios were estimated to ascertain the magnitude of prescription of potentially inappropriate medications, along with patient and physician-related factors associated with such prescription. RESULTS: In total, 417 older patients were included; 45.3% had received >= 1 potentially inappropriate medication, and 86.8% out of 53 physicians involved had prescribed >= 1 potentially inappropriate medication. The strongest patient-related factor associated with higher prevalence of prescription of potentially inappropriate medications was polypharmacy. Among physician-related factors, the number of patients attended, number of prescriptions and length of medical practice < 10 years were positively associated with prescription of potentially inappropriate medications. CONCLUSIONS: High prevalence of prescription of potentially inappropriate medications was observed. Physician-related characteristics can influence prescription of medications to older people within primary healthcare. This suggests that there is a need for interventions among all physicians, especially younger physicians.

Backgound: Potentially inappropriate prescribing (PIP) has been evaluated in several countries, and several strategies have been devised for deprescribing drugs in older adults. The aim of this study was to evaluate the efficacy of a mobile application in reducing PIP for older adults in primary care facilities in Brazil. Methods: This randomised, triple-blind, parallel-group trial was conducted in 22 public primary care facilities in Brazil. During the intervention phase, the general practitioners (GPs) were randomly allocated to the intervention (MPI Brasil app provides information about PIP, therapeutic alternatives and deprescribing) or control (MedSUS app provides general information about medications) group. All GPs were trained on the Clinical Decision-Making Process and how to access an Evidence-Based Health website. The GPs received an Android tablet with an installed mobile application depending on their allocated group, which they used when caring for older patients over at least 3 months. At the end of this period, a sample of older patients aged ≥ 60 years who had been awaiting medical consultation by the participating GPs were interviewed and their prescriptions analysed. The primary outcome was the frequency of PIP in and between the groups. Results: Among 53 GPs who were administered the baseline survey, 14 were included in the clinical trial. At baseline, 146 prescriptions were analysed: the PIP overall was 37.7% (55/146), in the intervention group was 40.6% (28/69), and in the control group was 35.1% (27/77). After the intervention, 284 prescriptions were analysed: the PIP overall was 31.7% (90/284), in the intervention group was 32.2% (46/143), and in the control group was 31.2% (44/141) (RR: 1.16; 95% CI, 0.76–1.76). In the within-group analysis, the PIP reduced from before to after the intervention in both groups—more significantly in the intervention than in the control group (p < 0.001). In the stratified analysis of PIP frequency by GPs, there was a relative risk reduction in 86% (6/7) of GPs in the intervention group compared to 71% (5/7) in the control group. Conclusion: We found that the MPI Brasil app effectively reduced PIP, suggesting that it may be useful to incorporate this tool into clinical practice. Trial registration: The study was registered at ClinicalTrials.gov (NCT02918643). First registration on 22/09/2016.