Health characteristics and behaviors associated with self-reported depression among Brazilian reproductive-aged women: Data from a population-based survey (2020-2021)

This cross-sectional study aimed to evaluate the health characteristics and behaviors associated with depression in a large probabilistic sample of Brazilian reproductive-aged women. A total of 11,698 non-pregnant women aged 18-49 years old from the 26 Brazilian capitals and Federal District were interviewed by landline between 2020 and 2021. Logistic regression models were used to estimate the Odds Ratio (OR) of health characteristics and behaviors (smoking, alcohol abuse, physical activity, regular intake of fruits and vegetables, overweight, obesity and poor self-rated health) according to the presence of depression and drug treatment for depression. Medical diagnosis of depression, and other health characteristics and behaviors were self-reported. Analyses were adjusted by age, race/skin color, education, and marital status. Prevalence of self-reported depression was 13.3% and drug treatment for depression was reported by 5.3% of the total studied population. The presence of self-reported depression was associated with smoking (adjusted OR - aOR 2.15; CI95%:1.44-3.20), regular intake of fruits and vegetables (aOR 0.75; CI95%:0.59-0.95), overweight (aOR 1.38; CI95%:1.10-1.71), obesity (aOR 1.34; CI95%:1.04-1.71) and poor self-rated health (aOR 4.34; CI95%:3.04-6.21). Drug treatment for depression was associated with smoking (aOR 2.29; CI95%:1.33-3.95), overweight (aOR 1.65; CI95%:1.18-2.30) and poor self-rated health (aOR 4.20; CI95%:2.59-6.83). Self-reported depression and drug treatment for depression were associated with unfavorable health characteristics and behaviors among reproductive-aged women in Brazil.

Temporal Trend in the Coexistence of Risk Behaviors for Noncommunicable Diseases in Brazil: 2009–2019

INTRODUCTION

Individuals can accumulate multiple risk factors for noncommunicable diseases, increasing the chance of adverse health outcomes. We aimed to analyze the temporal trend in the coexistence of risk behaviors for noncommunicable diseases and their association with sociodemographic characteristics among adults in Brazil from 2009 through 2019.

METHODS

This cross-sectional study and time-series analysis was based on data collected by the Surveillance System for Risk Factors and Protection for Chronic Diseases by Telephone Survey (Vigitel) from 2009 through 2019 (N = 567,336). We used item response theory to identify the coexistence of risk behaviors (infrequent consumption of fruits and vegetables, regular consumption of sugar-sweetened beverages, smoking, abusive alcohol consumption, insufficient leisure-time physical activity). We used Poisson regression models to assess the temporal trend in the prevalence of the coexistence of noncommunicable disease-related risk behaviors and associated sociodemographic characteristics.

RESULTS

Risk behaviors that most contributed to the occurrence of coexistence were smoking, consumption of sugar-sweetened beverages, and alcohol abuse. Coexistence was more frequent among men and was inversely associated with age and education level. During the study period, we found a significant decrease in coexistence (adjusted prevalence ratio decreased from 0.99 in 2012 to 0.94 in 2019; P = .001), especially before 2015 (adjusted prevalence ratio = 0.94; P = .001).

CONCLUSION

We found a reduction in the frequency of the coexistence of noncommunicable disease-related risk behaviors and their association with sociodemographic characteristics. It is necessary to implement effective actions to reduce risk behaviors, especially behaviors that lead to a greater coexistence of those behaviors.

Changes in Screen Time in Brazil: A Time-Series Analysis 2016-2021

PURPOSE

To analyze the temporal trend of leisure screen time among adults in Brazil between 2016 and 2021.

DESIGN

Time-series analysis of six cross-sectional surveys.

SETTING

Data from the Surveillance System for Risk and Protective Factors for Chronic Diseases by Telephone Survey (Vigitel) (2016/21).

SUBJECTS

A probabilistic sample of 265 252 adults (≥18 years).

MEASURES

Time watching television (TV), or using cell phone, computer, or tablet (CCT) during leisure time, and indicators of prolonged exposure for the total population and sociodemographic groups.

ANALYSIS

Prais-Winsten regression models were used to identify trends in the studied period.

RESULTS

Mean time watching TV remained stable (2.3 h to 2.2 h/day) as the frequency of adults watching TV ≥ 3 hours/day (25.7% to 25.1%) for 2016/21. There was an increase in mean time spent on CCT (1.7 h to 2.0 h/day; .08 h/day/year; P < .001) and in the frequency of adults spending ≥ 3 hours/day on CCT (19.9% to 25.5%; 1.33 pp/year; P < .001) for 2016/21. The increase in screen time was relevant in all sociodemographic groups.

CONCLUSION

Leisure screen time has increased in Brazil, with greater intensity over time.

Chronic disease risk and protective behaviors in Brazilian state capitals and the Federal District, according to the National Health Survey and the Chronic Disease Risk and Protective Factors Telephone Survey Surveillance System, 2019

OBJECTIVE

To describe and compare the results of the main risk and protective factors for chronic non-communicable diseases, in the 26 Brazilian capitals and the Federal District, obtained through the National Health Survey (PNS) and the Surveillance System for Risk and Protective Factors for Chronic Diseases by Telephone Survey (VIGITEL) in 2019.

METHODS

Cross-sectional study, in which the difference in prevalence between health behavior indicators investigated by PNS and VIGITEL was calculated.

RESULTS

The largest discrepancy between the surveys, PNS (n = 32,111) and VIGITEL (n = 52,443), were observed in relation to leisure-time physical activity (6.8 in percentage points - p.p.), recommended physical activity in the transport domain (7.4 p.p.), and high screen time (21.8 p.p.). Both surveys presented similar prevalence regarding nutritional status, food consumption, smoking, alcohol abuse and negative self-rated health.

CONCLUSION

Prevalence in both surveys presented small differences, but point to results in the same direction.