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Background: Sustainable development goals (SDGs) 3.9.1 and 11.6.2 call for a reduction in deaths and illnesses from air pollution, improving the air quality of cities. The above goals motivate us to organize workshops to improve the health of traffic police, who bear the brunt of air pollution. The paper examines the effect of workshops on the health-seeking behavior of the traffic police in Bhubaneswar city. Methods: The study conducted two workshops as a quasi-experimental, single-group study at an academic institution in Bhubaneswar. It included 20 traffic police officers (11 male and 9 female). The Kirkpatrick 4-level model was used to assess the effectiveness of the workshops. A paired t-test was used to compare pre- and postworkshop scores. Results: Thirteen traffic police officers rated the workshop sessions as excellent. The score before the workshop ranged from zero to three, with a mean (standard deviation [SD]) of 2.81 (1.0). The postworkshop score had a minimum to maximum score of three to five with a mean (SD) of 4.41 (0.7) (P < 0.005). The effect size dcohen (confidence interval [CI]) was 1.87 (3.27-4.71). The mean (SD) of absolute and relative gain was 1.6 (1.0) and 0.93 (1.02), respectively. All 20 traffic police officers showed improvement in health-seeking behavior. The significant lifestyle changes after the workshops ranged between 5% and 75%. Conclusion: The test scores indicated statistically significant improvement as the P value recorded was smaller than 0.05. This concludes that the improvement in understanding of the session was statistically significant because of the training imparted. [ABSTRACT FROM AUTHOR]

Background: Depression is a major public health concern among Indian adolescents. Pre- and post-natal depression can often alter fetal development and have negative consequences on the physical and mental health of the mother. This paper aims to draw attention to the prevalence of depression and its correlates among currently married, ever-pregnant adolescents from two Indian States, i.e. Uttar Pradesh and Bihar. Methods: This study utilizes data from a subsample (n = 3116) of the prospective cohort study Understanding the Lives of Adolescents and Young Adults (UDAYA) among 10 to 19 year-old adolescents. Bivariate analysis was performed to assess the prevalence of depression by sociodemographic and behavioral characteristics. To further access the predictors associated with depression a logistic regression model was applied. Results: Around one-tenth (9%) of pregnant adolescents had depression. Regression analysis indicated that substance use, religion, autonomy, considering attempting suicide, premarital relationship, violence, dowry, adverse pregnancy outcome, menstrual problem, and parental pressure for the child immediately after marriage were significantly associated with depression. Conclusions: This study confirms the pre-existing annotation that teen pregnancy is linked with depression. Findings indicate that Adolescent mothers experiencing violence, and a history of adverse pregnancy outcomes are at increased risk of developing depression. These study findings call for an urgent need to address depression among adolescent mothers. [ABSTRACT FROM AUTHOR]

Background: Interactive teaching methods aid post graduate students in learning qualitative research. Four academic researchers from the United Kingdom had an opportunity to teach qualitative research methods, specifically consensus methods, to the Master of Public Health students (MPH) during a visit to India. This teaching formed part of a work package with All India Institute of Medical Sciences Rishikesh, India exploring the concept of family resilience among families with children under 6 years. Aims: To use the experiences of the MPH students to gain knowledge and create meaning about using the consensus methods. Participants: The participants were the MPH students. Methods: We used the workshop method to introduce the concept of family resilience by using the question, ‘What will be the three top public health priorities in India to support family resilience in the 21st century?’ as a central theme for all the workshops. Furthermore, we introduced qualitative research methods and hands on experience of consensus methods to the students. The students were introduced to Delphi and Group Concept Mapping (GCM) methods during workshop 1. Workshop 2 introduced Nominal Group Technique (NGT) through a short presentation followed by a practical hands on session using GCM data from workshop 1. The last workshop (3) focused on the World Café method. Results: The students evaluated the workshops highly and asked for online sessions on GCM, NGT, and World Café which will be planned in the future. Conclusion: We concluded that the post graduate curriculum for master’s in public health studies would benefit from teaching using interactive research methods which will enhance their critical thinking and autonomy. Second, although the MPH curriculum had quantitative methods in place, introducing qualitative consensus methods will open new avenues into future research. Finally, teaching using practical demonstration gives students a voice and makes learning effective and enjoyable. [ABSTRACT FROM AUTHOR]

Background: COVID-19 has become a global pandemic, prompting lockdowns in practically every country. To prevent the spread of the disease, India has enforced a rigorous nationwide lockdown that commenced in March 2020. The lockdown imposed amid the pandemic ensured that most commercial activities and vehicle transportation ceased, resulting in a significant reduction in air pollution levels. Material and Methods: The value of air pollutants PM10, PM2.5, NO2, and SO2 from January to May 2020 was obtained from the Indian Central Pollution Control Board. Before lockdown and during lockdown, relative fluctuations in ambient concentrations of four air contaminants were investigated. The Box-Jenkins approach was used to estimate future air pollution data points using time series data analysis. Results: The PM10 level reduced by 61%, 30%, 68%, 37%, and 43% in the selected cities, respectively. Comparison of other pollutant concentrations before and after the lockdown also found a reduction in ambient pollutant concentrations, resulting in improved air quality. Inference of predicted model values to observed values revealed a significant increase in the concentrations of all pollutants. The percentage increases in AQImean from predicted to observed values were 206% in Ghaziabad, 148% in Delhi, 59% in Hyderabad, and 160% in Cochin. Conclusion: The strict lockdown has resulted in a significant drop in air pollutant levels. Upgrading present technologies could help keep pollution to a minimum of 37% under control. The findings would prompt the government to consider how to strictly reduce vehicle and industrial pollution to improve air quality and maintain improved public health. [ABSTRACT FROM AUTHOR]