Compound Disasters and Adolescent Mental Health: Increased Primary Health Care Demand After the Overlap of the Covid-19 Pandemic and A Rainfall Disaster in Brazil

Compound Disasters and Adolescent Mental Health: Increased Primary Health Care Demand After the Overlap of the Covid-19 Pandemic and A Rainfall Disaster in Brazil | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Compound Disasters and Adolescent Mental Health: Increased Primary Health Care Demand After the Overlap of the Covid-19 Pandemic and A Rainfall Disaster in Brazil Júlia Aparecida Procópio, Marco Aurélio de Sousa, Janaina Soares, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9124398/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Background Biological and meteorological disasters can have negative impacts on the mental health of adolescents. However, little is known about the impact of overlapping disasters. The objective of this study was to estimate the impact of the overlap of biological and meteorological disasters on adolescent mental health. Methods The overlap studied occurred in February 2022, when Petrópolis, Brazil, suffered a meteorological disaster related to rainfall during the biological disaster of the COVID-19 pandemic. The data consisted of the number of visits by adolescents aged 10 to 17 years in which the problem or condition evaluated involved mental health diagnoses in the municipality's Primary Health Care (PHC) services. The monthly rates of health care usage were measured by municipality over the six months following the overlap period, which spanned from February to July 2022. These rates were then compared with those from the first six months of the biological disaster (March–August 2020) and with the same period prior to the disaster (February–July 2018–2019). The Mann–Whitney U test and percentage differences were used to analyze these comparisons. Results A total of 2,591 visits were analyzed, with 36.4% occurring after the overlap. Just over half of the consultations were for male adolescents (54.1%), and most were for adolescents aged 10 to 13 years (64.1%). Consultation rates, by sex and age, were higher after the overlap when compared with the periods before and during the pandemic (p < 0.05). The relative increase in rates was 166.2% higher than in the pre-disaster period and 318.4% higher than during the first six months of the pandemic among older male adolescents aged 14 to 17 years (p < 0.05). Conclusion The overlap of biological and meteorological disasters impacts adolescents' demand for mental health care in PHC. Preparing for and coping with the impacts of disasters must consider the additional pressure on the health system imposed by the mental health needs of affected adolescents. Impact of disasters Effects of disasters on health Natural disasters Climate change Adolescents Mental health Figures Figure 1 INTRODUCTION Since the declaration of the COVID-19 pandemic, which represented a biological disaster, in March 2020, until the declaration of the end of the public health emergency of international concern in March 2023 by the World Health Organization, it received the predominant attention globally. During the pandemic, in general, other public health risks did not receive the attention they deserved due to the focus on controlling the transmission of the disease (Leppold et al., 2022 ) Health hazards arising from extreme weather events became more pronounced during this time. These events have become more frequent and more severe as climate change intensifies. In 2020, for example, the number of climate-related disasters worldwide exceeded the annual average of the previous 20 years, reaching 389 disasters, which resulted in more than 15,000 deaths and nearly 100 million people affected, in addition to economic losses of over US $ 171 billion and hundreds of thousands of forced population displacements (Pei et al., 2020 ; United Nations Office for Disaster Risk Reduction, 2020 ). Among the extreme events related to rainfall in 2020, there were more storms, more floods, and more deaths (United Nations Office for Disaster Risk Reduction, 2020 ). More than ever before, during the COVID-19 pandemic, it became clear that two or more disasters can occur simultaneously, interact, and complicate responses, particularly those related to meteorological and biological threats (Fakhruddin, Blanchard e Ragupathy, 2020). For instance, in 2020, amid the COVID-19 pandemic, seventy countries also experienced extreme weather events (Simonovic, Kundzewicz, and Wright, 2021 ). Among these, some of the rain-related events were Storm Dennis in the United Kingdom, flooding in western Canada and southern Poland, and hurricanes Sally and Laura in the United States (Simonovic, Kundzewicz and Wright, 2021 ). Brazil was no exception to this context of compound disasters. In the first half of 2022, still in the midst of the pandemic, Brazil was among the top ten countries in the world in terms of deaths from disasters and among the top five in terms of deaths from COVID-19 (Centre for Research on the Epidemiology of Disasters, 2022 ; World Health Organization, 2021). According to Civil Defense reports, 2,576 incidents – including storms, flash floods, floods, and mass movements – affected 900,000 people in 2022, representing a 402% increase compared to a decade earlier. In the first five months of that year alone, 457 people died in disasters caused by rain. In addition to the loss of lives, 7.8 million individuals had to leave their homes, whether for a short period or permanently. Among the disasters during this period, the largest in terms of number of deaths occurred in Petrópolis, Rio de Janeiro, where 249 people died. Even though they occur simultaneously, there are considerable differences in the health impacts caused by biological and meteorological disasters, requiring different responses (Kamalrathne et al., 2024 ). For this reason, some studies that investigated the potential for meteorological disasters to overlap with the COVID-19 pandemic have focused particularly on the difficulties in managing the pandemic, with an emphasis on the impacts on the spread of the virus (Ishiwatari et al., 2020 ; Paiva et al., 2021 ). Another study focused on analyzing the impact of the necessary responses to a meteorological disaster on the increase in COVID-19 cases (Pei et al., 2020 ). However, few studies have focused on estimating the impacts of this overlap on other aspects of the health of exposed individuals. In general, research suggests that exposure to multiple disasters can have negative effects on health and well-being, and that this exposure has a greater impact than exposure to a single disaster (Leppold et al., 2022 ). Among adolescents, a particularly vulnerable group, studies have indicated that exposure to multiple disasters was negatively associated with well-being, as well as with increased behavioral problems, including conflicts with peers (Campbell, Edwards and Gray, 2024 ). On the other hand, a single exposure to natural disasters was not associated with adverse outcomes (Campbell, Edwards and Gray, 2024 ). These findings suggest that, rather than adapting to disasters, young people exposed to multiple disasters may suffer more than their peers exposed to a single disaster. Furthermore, research indicates that disasters can have cumulative impacts on health, which may result in increasingly severe mental health issues among children and adolescents (Leppold et al., 2022 ). In this context, given that even a single exposure to meteorological or biological disasters has an impact on adolescent mental health, the question arises as to what the estimated impact on mental health care demands would be when meteorological and biological disasters overlap. As meteorological disasters have become more frequent and the risks of a new pandemic are not far off, exposure to this co-occurrence of disasters will also become more common, and the need to estimate the impacts of this overlap becomes important. The hypothesis of this study is that exposure to overlapping meteorological and biological disasters leads to an increase in mental health care utilization among adolescents. The objective was to estimate the impact of overlapping biological and meteorological disasters on the number of mental health care visits by adolescents in the municipality of Petrópolis, Rio de Janeiro. METHODS This article was prepared following the Equator Network's STROBE guidelines for reporting observational studies in epidemiology (Elm, von et al., 2007 ). Study design This research employed an analytical approach and followed an ecological, cross-sectional study design with comparative time-series analysis. Study location The research took place in Petrópolis, a city situated in the mountain area of Rio de Janeiro state, Brazil. In 2022, the municipality experienced several disasters when severe rainfall, a meteorological event, happened simultaneously with the COVID-19 pandemic, which is classified as a biological disaster. Compound disasters refer to the co-occurrence or sequential occurrence of two or more extreme events that interact and produce substantial impacts (Zscheischler et al., 2018 ). Heavy rainfall led to flash floods, landslides, and flooding throughout various parts of the municipality, causing a meteorological disaster. The initial event took place on 15 February 2022, when 259 mm of rain fell in just three hours—an amount equal to the average monthly rainfall—which led to 242 fatalities. A second event occurred on 20 March 2022, causing seven additional deaths. The Civil Defense reported 6,293 incidents across both events, noting that more than 5,000 of these cases involved properties affected by or at risk from landslides. Approximately 3,500 individuals either lost their homes or had to move elsewhere. Structural damage affected 22.7% of local health facilities, including 13 Primary Health Care services and one Emergency Department. The disaster also caused an estimated loss of R $ 700 million to the municipal Gross Domestic Product. During the same period, the municipality was experiencing a wave of COVID-19 cases and deaths associated with the Omicron variant of SARS-CoV-2. Public health measures included restrictions on in-person activities and population mobility, with a reported transmission rate (Rt) ranging from 0.29 to 0.44, indicating that every one hundred infected individuals transmitted the virus to 29 to 44 others. Data studied The study analyzed the monthly number of individual visits by adolescents aged 10 to 17 years who received mental health–related diagnoses during consultations in Primary Health Care (PHC) services. The data came from the Primary Care Information System (Sistema de Informação em Saúde para a Atenção Básica – SISAB), overseen by Brazil's Ministry of Health. SISAB is the official information system used for financing and monitoring adherence to programs and strategies under the National Primary Care Policy ( Política Nacional de Atenção Básica – PNAB). It receives mandatory monthly production records (number of consultations) from all PHC teams nationwide, which municipalities must submit by the tenth business day of the month following service delivery. The data covered the period from January 2018 to July 2022, which is six months after the overlap. The initial data selection considered periods with greater regularity in monthly reporting by municipalities, in accordance with previous methodological recommendations (Cavalcante et al., 2018 ). The analysis included adolescents in early and middle adolescence, defined as ages 10–13 years and 14–17 years, respectively. During this stage of development, individuals experience major changes physically, emotionally, and socially, which may heighten their risk of mental health challenges. Data collection In April 2023, data was systematically gathered from the SISAB platform ( https://sisab.saude.gov.br/ ) following a standardized protocol. SISAB collected monthly data using Brazil as the geographic unit. The extracted reports organized municipalities in rows, with columns indicating production types as defined by the Ministry of Health's twenty-two established "Problems or conditions assessed," which also included mental health. The "Problem or condition assessed – mental health" variable is based on consultations that included any diagnosis listed in Supplementary Material 1. Additional filters included sex (female and male) and age group (10–13 years and 14–17 years). The data collection process generated 268 consolidated monthly production reports in .xlsx format for all Brazilian municipalities. This study included only data from the municipality of Petrópolis. A thorough examination of all extracted files confirmed their consistency, with no discrepancies detected. The analysis kept header details such as year, month, sex, and age group, but left out footer data like source, extraction date, and extraction time. After extraction and verification, the data underwent these processing steps: coding of year, month, sex, and age group variables into columns; and removal of unnecessary header and footer information. Following processing, the datasets underwent a second review, and no errors were found. All spreadsheets were subsequently merged into a single database using the Power Query function in Microsoft Excel. Variables studied The outcome variable was the monthly rate of mental health–related visits per 10,000 adolescent inhabitants, stratified by sex and age group. Estimates of the population from the Brazilian Ministry of Health served as the denominators. Since there were inconsistencies between the 2022 national census and earlier projections, population estimates for 2022 relied on data from 2021. The exposure variable was the overlap of rainfall-related meteorological disasters and the biological disaster associated with the COVID-19 pandemic, categorized into three periods: Pre-disaster period: February–July 2018 and 2019. First six months of the biological disaster: March–August 2020; and First six months following the overlap of meteorological and biological disasters: February–July 2022. The covariates was sex (male, female) and age group (10–13 years and 14–17 years). Data analysis We conducted statistical analyses with IBM SPSS (version 27). The Kolmogorov–Smirnov test (p < 0.05) confirmed that the data were not normally distributed when analyzed by sex and age group. Descriptive analyses included absolute and relative frequencies, as well as medians and interquartile ranges for the number and rates of visits. Nonparametric Mann–Whitney U test to compare median monthly visit rates from the first six months after the overlap with those from both the pre-disaster period and the initial six months of the pandemic. The percentage differences in median rates were determined for the following: 1) the period after the overlap compared with the pre-disaster period; and 2) the period after the overlap compared with the first six months of the biological disaster. All analyses used a two-sided significance threshold of p < 0.05. Ethical aspects As this study used publicly available, anonymized data with unrestricted access, it was exempt from review by a Research Ethics Committee, in accordance with Brazilian regulations. The Research Ethics Committee at Universidade Federal de Minas Gerais (CAAE: 46914221.5.0000.5149) approved the exemption. RESULTS The analysis included 2,591 visits related to adolescent mental health. Of these adolescents, just over half were male (54.1%), and the majority (64.1%) were between 10 and 13 years old. When comparing the study periods separately, the highest proportion of visits (36.4%) occurred during the period of overlapping meteorological and biological disasters (Table 1 ). Table 1 Distribution of cases studied in which the problem or condition assessed was adolescent mental health, according to sex and age. Petrópolis, Brazil. Before the disasters Six first months of the biological disaster First six months after the overlap 2018 2019 2020 2022 Feb-Jul Mar-Aug Feb-Jul Total Gender Female 187 (15.7%) 361 (30.3%) 232 (19.5%) 411 (34.5%) 1,191 Male 239 (17.1%) 395 (28.2%) 233 (16.6%) 533 (38.1%) 1,400 Age 10 to 13 years 275 (16.6%) 485 (29.2%) 309 (18.6%) 592 (35.6%) 1,661 14 to 17 years 151 (16.2%) 271 (29.1%) 156 (16.8%) 352 (37.8%) 930 Total 426 (16.4%) 756 (29.2%) 465 (17.9%) 944 (36.4%) 2,591 During the first six months following the overlap, there was a statistically significant increase in the median monthly rates of mental health–related visits across sex and age groups, compared with both the pre-disaster period and the first six months of the biological disaster. Boys aged 14–17 years experienced the highest relative increase, with rates rising by 166.2% compared to the period before the disaster and by 318.4% compared to the first six months following the biological disaster (p < 0.05). There was also a notable rise of 114.9% (p < 0.05) among girls aged 10–13 years when comparing the period after the overlap to the time before the biological disaster. In addition, when comparing the period after the overlap with the first six months of the biological disaster, the increase reached 116.1% among boys aged 10–13 years (p < 0.05). When differences between groups were examined according to sex and age, it was observed that, despite the greater relative increase among older male adolescents, the absolute median rate of visits in the six months following the overlap was significantly lower among boys aged 14–17 years than among younger adolescents (Table 2 and Fig. 1 ). Table 2 – Differences between monthly rates of medical visits (per 10,000) in the first six months after the overlapping disasters compared to before the meteorological and biological disasters and during the first six months of the biological disaster. Petrópolis, Brazil, n = 2,591. Before the disasters First six months of the biological disaster First six months after the overlap After the overlap vs. Before the disaster biological After the overlap vs. During the disaster biological Median (P25 – P75) Dif. p Dif. p Gender Female 28.2 (22.6–52.4) 31.7 (13.3–55.3) 60.6 (42.1–75.4) 114.9% 0.019 91.2% 0.054 Male 25.5 (16.7–39.2) 22.1 (6.6–32.5) 42.6 (18.8–56.1) 67.1% 0.160 92.8% 0.150 Age 10 to 13 years 44 (38.6–61.0) 36 (20.1–56.0) 77.8 (59.7-101.4) * 76.8% 0.019 116.1% 0.016 14 to 17 years 15.4 (10.6–20.0) 9.8 (6.2–26.6) 41.0 (24.9–55.1) * 166.2% 0.005 318.4% 0.016 Notes: Diff = Difference; p = Mann-Whitney U test; P25–P75 = interquartile ranges; *significant differences between groups. DISCUSSION Our results showed substantial and statistically significant increases in monthly rates of visits in which the problem or condition assessed was adolescent mental health during the first six months following the overlap of meteorological and biological disasters, compared with both the pre-disaster period and the first six months of the biological disaster (COVID-19 pandemic). In most studies examining the mental health impacts of compound disasters, methodological approaches typically compare the risks associated with exposure to compound disaster with those associated with exposure to a single disaster (Leppold et al., 2022 ). In the present study, we extended this approach by comparing exposure not only to the compound (overlapping) disaster but also to the absence of disaster, represented by the pre-disaster period. Mental health care usage rose most sharply among older male adolescents aged 14 to 17, indicating an increased demand in this group. But there were also notable increases among younger adolescents between the ages of 10 and 13. Overall, consistent with findings from other studies on compound disasters, our results evidence of increased demand for mental health care (Campbell, Edwards and Gray, 2024 ; Edwards, Taylor and Gray, 2024 ; Gargano et al., 2019 ; Leppold et al., 2022 ; Rafaloski et al., 2020 ). The higher mental health care utilization rates observed following the overlap underscore the multi-risk context generated by the co-occurrence of extreme events (Simonovic, Kundzewicz and Wright, 2021 ). However, it is important to note that the overlap of the meteorological disaster with the COVID-19 pandemic occurred at a time when demand for adolescent mental health care in the municipality was already increasing. Evidence suggests that adolescents’ mental health showed relative improvement during the first year of the pandemic but deteriorated during the second and third years (Kim et al., 2024 ). Consequently, the overlapping meteorological disaster affected a population that was already psychologically vulnerable due to prolonged pandemic-related stressors. In this context, the risks associated with exposure to compound disasters exceed those linked to exposure to a single disaster, potentially resulting in both short- and long-term psychological distress (Leppold et al., 2022 ). Disasters disrupt daily routines, which can result in heightened psychological vulnerabilities, including negative thoughts and emotions, fear, anxiety, hopelessness, and uncertainty (Cianconi, Betrò and Janiri, 2020 ). Among adolescents exposed to multiple disasters within a short time frame, studies have reported higher levels of psychological distress, including acute stress reactions, post‑traumatic stress disorder, depression, panic disorders, and an increased risk of suicidal behavior (Leppold et al., 2022 ). Another key finding of the results is that the observed increases in mental health care utilization rates reflect only adolescents who were able to access care, and not all those who required it. Despite considerable barriers to access typically seen during disaster recovery periods, service usage increased substantially. Barriers to health care access to care following disasters are often widespread and include damage to or destruction of health care infrastructure, as well as reductions in the health workforce available to provide care (Hertelendy et al., 2025 ). Such barriers may persist for more than one year (Leppold et al., 2022 ). The fact that many adolescents unable to access needed care underscores the considerable challenges faced by Primary Health Care (PHC) services in the context of intersecting and threat-multiplying events. In such scenarios, two potentially severe public health emergencies may unfold simultaneously, placing additional strain on already overstretched health systems. Regarding the differences in the magnitude of impacts on mental health care utilization according to demographic characteristics (sex and age), comparisons with the existing literature reveal a mixed finding (Leppold et al., 2022 ). Nevertheless, the more pronounced increase in service utilization among male adolescents warrants attention, particularly given that female adolescents exhibit higher overall health care-seeking behavior (Oliveira et al., 2018 ). This pattern may be partly explained by prevailing social norms related to masculinity, which often discourage emotional expression and delay help‑seeking, thereby worsening mental health outcomes after disaster exposure (Rahman et al., 2025 ). During the period of overlap, the lower number of observed visits among older male adolescents and girls may be related to socially constructed roles and responsibilities. Older girls often remain in shelters, where they take care of younger children and assist with domestic tasks, whereas boys, in addition to providing support at home or in shelters, frequently accompany family members in cleaning activities and in the recovery of debris. Older adolescents of both sexes also tend to enter the labor market or seek informal work to support household income, particularly in the context of material losses and the loss of family providers, thereby assuming adult responsibilities prematurely (Corrochano and Tarábola, 2023). Studies have suggested that mental health outcomes may vary according to the severity of exposure to multiple disasters, which can be characterized by one or more of the following factors: extent of loss, level of damage, barriers to accessing essential resources, perceived threat, and physical injuries sustained (Leppold et al., 2022 ). In the context of the present study, the severity of both disasters was substantial. At the national level, the country experienced fragile political leadership and weaknesses in social protection and pandemic management, resulting in one of the highest COVID-19 mortality rates worldwide, while at the local level, the municipality endured one of the deadliest rainfall-related disasters in Brazil’s history. It is important to acknowledge that this study has limitations. Because the study was based on municipal data, it was not possible to evaluate differences between the neighborhoods that were most impacted. Nevertheless, this approach enabled the inclusion of a larger volume of data over a shorter time, without requiring financial resources for primary data collection. Another limitation relates to the use of population estimates from the Ministry of Health for 2021 as proxies for 2022, due to the unavailability of official population estimates for 2022 at the time of analysis. On the other hand, this study draws on the only nationwide Brazilian database that is sensitive to short- and medium-term changes in health service utilization following disasters, which made it possible to quantify the impacts of overlapping disasters on mental health care utilization. Our findings underscore the need to rethink and strengthen disaster preparedness and response models. Preparedness strategies should directly address the complex and interacting risks from both rainfall-related disasters and pandemics, focusing on comprehensive approaches to effectively manage these compound threats (Ishiwatari et al., 2020 ; Izumi et al. 2022 ). Communities and health systems should enhance resilience to respond not only to isolated disasters but also to the increasing likelihood of compound disaster scenarios. Strategies aimed at reorganizing PHC services in the post-disaster period, with a focus on adolescent mental health, alongside policies to reduce the risks of global health emergencies and climate change–related meteorological disasters, may help mitigate the impacts of disaster overlap. In this context, the present study aligns with and supports the United Nations Sustainable Development Goals, particularly Goal 3 (Good Health and Well-Being), which seeks to ensure access to quality health care and promotes well-being for all, at all ages. CONCLUSION During the time when both meteorological and biological disasters occurred together, monthly mental health–related visits among adolescents rose notably across all sexes and age groups compared to each disaster period on its own. Older male adolescents experienced the highest rise, but every other group showed increases as well—though these were less pronounced—when compared to both reference periods. Abbreviations PHC: Primary Health Care SISAB: Primary Care Information System ( Sistema de Informação em Saúde para a Atenção Básica ) PNAB: National Primary Care Policy ( Política Nacional de Atenção Básica ) IBM SPSS: IBM Statistical Package for the Social Sciences Declarations Ethical approval and consent to participate The Research Ethics Committee at the Federal University of Minas Gerais (CAAE: 46914221.5.0000.5149) decided that a review was unnecessary. Consent for publication Not applicable. Data availability The datasets used during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare no competing interests. Funding This work was supported by the Brazilian National Council for Scientific and Technological Development ( Conselho Nacional de Desenvolvimento Científico e Tecnológico – CNPq), grant number 408968/2025-7 and the Minas Gerais Research Foundation ( Fundação de Amparo à Pesquisa do Estado de Minas Gerais – FAPEMIG), grant number APQ-00209-24. Authors’ contributions J.A.P. Contributed to data collection, analysis, and interpretation; manuscript writing; and approval of the definitive version. M.A.S., J.S., and M.C.C.R. contributed to writing the manuscript and approving the definitive version. E.W.R.V. contributed to the design, planning, and coordination of the study; data collection, analysis, and interpretation; writing of the manuscript; and approval of the definitive version. Acknowledgments Not applicable References Campbell, P., B. Edwards and M. Gray (2024) Exposure to multiple natural disasters and externalizing and internalizing behavior: A longitudinal study of adolescents. Journal of Adolescent Health . October. Cavalcante, R.B. et al. (2018) Computerization of primary health care information systems: Advances and challenges. Cogitare Enfermagem . 23(3). 8 August. Centre for Research on the Epidemiology of Disasters (2022) Natural hazards & disasters: An overview of the first half of 2022 . https://bit.ly/3OmBQyl (last accessed on 22 November 2024). Cianconi, P., S. Betrò and L. Janiri (2020) ‘The impact of climate change on mental health: A systematic descriptive review’. Frontiers in Psychiatry . 11. 6 March. Corrochano, M.C. and F. de S. Tarabola (2023) Neoliberalism, work and pandemic: Experiences and coping strategies of youth from urban peripheries. Educação & Sociedade . 44. Edwards, B., M. Taylor and M. Gray (2024) ‘The influence of natural disasters and multiple natural disasters on self-harm and suicidal behavior: Findings from a nationally representative cohort study of Australian adolescents. SSM – Population Health . 25. p. 101576. March. Elm, E. von et al. (2007) The strengthening the reporting of observational studies in epidemiology (STROBE) statement: Guidelines for reporting observational studies. PLoS Medicine . 4(10). p. e296. 16 October. Fakhruddin, B., K. Blanchard and D. Ragupathy (2020) Are we there yet? The transition from response to recovery for the COVID-19 pandemic’. Progress in Disaster Science . 7. p. 100102. October. Gargano, L.M. et al. (2019) Comorbid posttraumatic stress disorder and lower respiratory symptoms in disaster survivors: Qualitative results of a 17-year follow-up of World Trade Center disaster survivors. Progress in Disaster Science . 4. p. 100050. 1 December. Hertelendy, A.J. et al. (2025) Strengthening healthcare system resilience: A comprehensive framework for tropical cyclone preparedness and response’. The Lancet Regional Health – Americas . 48. p. 101205. August. Ishiwatari, M. et al. (2020) Managing disasters amid COVID-19 pandemic: Approaches of response to flood disasters. Progress in Disaster Science . 6. p. 100096. April. Izumi, T. et al. (2022) ‘Managing compound hazards: Impact of COVID-19 and cases of adaptive governance during the 2020 Kumamoto flood in Japan’. International Journal of Environmental Research and Public Health . 19(3). p. 1188. 21 January. Kamalrathne, T. et al. (2024) Managing compound events in the COVID-19 era: A critical analysis of gaps, measures taken, and challenges. International Journal of Disaster Risk Reduction . 112. p. 104765. October. Kim, Y. et al. (2024) ‘Changes in mental health among adolescents in South Korea before and after COVID-19: An interrupted time series analysis from 2015 to 2022’. Journal of Adolescent Health . October. Leppold, C. et al. (2022) Public health implications of multiple disaster exposures. The Lancet Public Health . 7(3). p. e274–e286. March. Oliveira, M.M. de et al. (2018) ‘Seeking health services or professionals among Brazilian adolescents, according to the 2015 National School Health Survey’. Revista Brasileira de Epidemiologia . 21(suppl 1). Paiva, V. et al. (2021) ‘Youth and the COVID-19 crisis: Lessons learned from a human rights-based prevention program for youths in São Paulo, Brazil’. Global Public Health . Pei, S. et al. (2020) ‘Compound risks of hurricane evacuation amid the COVID-19 pandemic in the United States’. GeoHealth . 4(12). 30 December. Rafaloski, A.R. et al. (2020) Mental health of people affected by natural disasters from the perspective of involved workers. Saúde em Debate . 44(spe2). p. 230–241. July. Rahman, M.M. et al. (2025) ‘Flood impact on men’s mental health: Evidence from flood-prone areas of Bangladesh’. Frontiers in Public Health . 13. 3 April. Simonovic, S.P., Z.W. Kundzewicz and N. Wright (2021) Floods and the COVID-19 pandemic: A new double hazard problem’. WIREs Water . 8(2). 10 March. United Nations Office for Disaster Risk Reduction (2020) 2020: The non-COVID year in disasters . World Health Organization (2024) WHO Coronavirus (COVID-19) Dashboard . https://covid19.who.int/ (last accessed on 22 February 2026). Zscheischler, J. et al. (2018) Future climate risk from compound events. Nature Climate Change . 8(6). p. 469–477. 14 June. Additional Declarations No competing interests reported. Supplementary Files Supplementarymaterial.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 29 Apr, 2026 Reviews received at journal 22 Apr, 2026 Reviews received at journal 09 Apr, 2026 Reviewers agreed at journal 09 Apr, 2026 Reviewers agreed at journal 06 Apr, 2026 Reviewers invited by journal 02 Apr, 2026 Editor invited by journal 24 Mar, 2026 Editor assigned by journal 19 Mar, 2026 Submission checks completed at journal 19 Mar, 2026 First submitted to journal 14 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9124398","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":618374828,"identity":"7da4a8b5-474a-4905-b911-982f4d13c8de","order_by":0,"name":"Júlia Aparecida Procópio","email":"","orcid":"","institution":"Universidade Federal de Minas Gerais","correspondingAuthor":false,"prefix":"","firstName":"Júlia","middleName":"Aparecida","lastName":"Procópio","suffix":""},{"id":618374829,"identity":"f916b2bd-788b-4322-a32a-2092bed7762e","order_by":1,"name":"Marco Aurélio de Sousa","email":"","orcid":"","institution":"Universidade Federal de Minas Gerais","correspondingAuthor":false,"prefix":"","firstName":"Marco","middleName":"Aurélio","lastName":"de Sousa","suffix":""},{"id":618374832,"identity":"dd4fd28d-5636-49c2-ae78-e4674599f3cf","order_by":2,"name":"Janaina Soares","email":"","orcid":"","institution":"Universidade Federal de Minas Gerais","correspondingAuthor":false,"prefix":"","firstName":"Janaina","middleName":"","lastName":"Soares","suffix":""},{"id":618374834,"identity":"b2ecd11c-b078-423f-805e-33ebcbb9ea9f","order_by":3,"name":"Márcia Christina Caetano Romano","email":"","orcid":"","institution":"Federal University of São João del-Rei","correspondingAuthor":false,"prefix":"","firstName":"Márcia","middleName":"Christina Caetano","lastName":"Romano","suffix":""},{"id":618374836,"identity":"e931210c-0123-4de6-86c5-152ad89d3934","order_by":4,"name":"Ed Wilson Rodrigues Vieira","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+ElEQVRIiWNgGAWjYFCCBIYDD0A0MwPDAQYGGwb2BjCbgJYEhJY0Bp4DRGhhSEDwDhPWws+eY3gg4Y9NnsFx5oOHK2rOJ/aIHb/AXLgHtxbJnjcGBxLb0ooNDrMlHDxz7HZij3ROAfOMZ7i1GNzI3XAgseFw4sxmHoODDWy3E/dL5yQwg1yHC9iDtCT8AWnh/3Cw4d85kC34tRhIgLSwHU7sZ+ZhONjYdgCoJf0AXi0SZ95/APkFqIXN4GBjX7Ix0BaGwzPwaOFvT0v+8OGPTWIb/+HHHxu+2ckCbXn4uACPFmyAx4BEDQwM7A9I1TEKRsEoGAXDGwAALudemIyboj0AAAAASUVORK5CYII=","orcid":"","institution":"Universidade Federal de Minas Gerais","correspondingAuthor":true,"prefix":"","firstName":"Ed","middleName":"Wilson Rodrigues","lastName":"Vieira","suffix":""}],"badges":[],"createdAt":"2026-03-14 18:08:48","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9124398/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9124398/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106434881,"identity":"5f7c1997-c5c5-45c4-836e-e3d8c48546ca","added_by":"auto","created_at":"2026-04-08 13:42:58","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":151566,"visible":true,"origin":"","legend":"\u003cp\u003eDifferences in monthly rates of medical visits (/10,000 [medians and P25 - P75]) in the first six months after the overlapping disasters compared to before the meteorological and biological disasters and during the first six months of the biological disaster. Petrópolis, Brazil, n=2,591.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-9124398/v1/62b3e90a8b16d01d3e908811.png"},{"id":106959536,"identity":"5bab34eb-650d-452c-be75-79b5953e0b0e","added_by":"auto","created_at":"2026-04-15 09:11:12","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":881632,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9124398/v1/62f6dc4b-f723-4c01-8bb6-95f8b90d79c7.pdf"},{"id":106434800,"identity":"718216d4-af43-4897-9bca-279ce77af07d","added_by":"auto","created_at":"2026-04-08 13:42:41","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":25959,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-9124398/v1/81db6022fe2cd8119eeabfba.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eCompound Disasters and Adolescent Mental Health: Increased Primary Health Care Demand After the Overlap of the Covid-19 Pandemic and A Rainfall Disaster in Brazil\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eSince the declaration of the COVID-19 pandemic, which represented a biological disaster, in March 2020, until the declaration of the end of the public health emergency of international concern in March 2023 by the World Health Organization, it received the predominant attention globally. During the pandemic, in general, other public health risks did not receive the attention they deserved due to the focus on controlling the transmission of the disease (Leppold et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eHealth hazards arising from extreme weather events became more pronounced during this time. These events have become more frequent and more severe as climate change intensifies. In 2020, for example, the number of climate-related disasters worldwide exceeded the annual average of the previous 20 years, reaching 389 disasters, which resulted in more than 15,000 deaths and nearly 100\u0026nbsp;million people affected, in addition to economic losses of over US\u003cspan\u003e$\u003c/span\u003e171\u0026nbsp;billion and hundreds of thousands of forced population displacements (Pei et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; United Nations Office for Disaster Risk Reduction, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Among the extreme events related to rainfall in 2020, there were more storms, more floods, and more deaths (United Nations Office for Disaster Risk Reduction, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMore than ever before, during the COVID-19 pandemic, it became clear that two or more disasters can occur simultaneously, interact, and complicate responses, particularly those related to meteorological and biological threats (Fakhruddin, Blanchard e Ragupathy, 2020). For instance, in 2020, amid the COVID-19 pandemic, seventy countries also experienced extreme weather events (Simonovic, Kundzewicz, and Wright, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Among these, some of the rain-related events were Storm Dennis in the United Kingdom, flooding in western Canada and southern Poland, and hurricanes Sally and Laura in the United States (Simonovic, Kundzewicz and Wright, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBrazil was no exception to this context of compound disasters. In the first half of 2022, still in the midst of the pandemic, Brazil was among the top ten countries in the world in terms of deaths from disasters and among the top five in terms of deaths from COVID-19 (Centre for Research on the Epidemiology of Disasters, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; World Health Organization, 2021). According to Civil Defense reports, 2,576 incidents \u0026ndash; including storms, flash floods, floods, and mass movements \u0026ndash; affected 900,000 people in 2022, representing a 402% increase compared to a decade earlier. In the first five months of that year alone, 457 people died in disasters caused by rain. In addition to the loss of lives, 7.8\u0026nbsp;million individuals had to leave their homes, whether for a short period or permanently. Among the disasters during this period, the largest in terms of number of deaths occurred in Petr\u0026oacute;polis, Rio de Janeiro, where 249 people died.\u003c/p\u003e \u003cp\u003eEven though they occur simultaneously, there are considerable differences in the health impacts caused by biological and meteorological disasters, requiring different responses (Kamalrathne et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). For this reason, some studies that investigated the potential for meteorological disasters to overlap with the COVID-19 pandemic have focused particularly on the difficulties in managing the pandemic, with an emphasis on the impacts on the spread of the virus (Ishiwatari et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Paiva et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Another study focused on analyzing the impact of the necessary responses to a meteorological disaster on the increase in COVID-19 cases (Pei et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, few studies have focused on estimating the impacts of this overlap on other aspects of the health of exposed individuals.\u003c/p\u003e \u003cp\u003eIn general, research suggests that exposure to multiple disasters can have negative effects on health and well-being, and that this exposure has a greater impact than exposure to a single disaster (Leppold et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Among adolescents, a particularly vulnerable group, studies have indicated that exposure to multiple disasters was negatively associated with well-being, as well as with increased behavioral problems, including conflicts with peers (Campbell, Edwards and Gray, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). On the other hand, a single exposure to natural disasters was not associated with adverse outcomes (Campbell, Edwards and Gray, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). These findings suggest that, rather than adapting to disasters, young people exposed to multiple disasters may suffer more than their peers exposed to a single disaster. Furthermore, research indicates that disasters can have cumulative impacts on health, which may result in increasingly severe mental health issues among children and adolescents (Leppold et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn this context, given that even a single exposure to meteorological or biological disasters has an impact on adolescent mental health, the question arises as to what the estimated impact on mental health care demands would be when meteorological and biological disasters overlap. As meteorological disasters have become more frequent and the risks of a new pandemic are not far off, exposure to this co-occurrence of disasters will also become more common, and the need to estimate the impacts of this overlap becomes important. The hypothesis of this study is that exposure to overlapping meteorological and biological disasters leads to an increase in mental health care utilization among adolescents. The objective was to estimate the impact of overlapping biological and meteorological disasters on the number of mental health care visits by adolescents in the municipality of Petr\u0026oacute;polis, Rio de Janeiro.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003eThis article was prepared following the Equator Network's STROBE guidelines for reporting observational studies in epidemiology (Elm, von et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2007\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design\u003c/h2\u003e \u003cp\u003e This research employed an analytical approach and followed an ecological, cross-sectional study design with comparative time-series analysis.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy location\u003c/h3\u003e\n\u003cp\u003eThe research took place in Petr\u0026oacute;polis, a city situated in the mountain area of Rio de Janeiro state, Brazil. In 2022, the municipality experienced several disasters when severe rainfall, a meteorological event, happened simultaneously with the COVID-19 pandemic, which is classified as a biological disaster. Compound disasters refer to the co-occurrence or sequential occurrence of two or more extreme events that interact and produce substantial impacts (Zscheischler et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHeavy rainfall led to flash floods, landslides, and flooding throughout various parts of the municipality, causing a meteorological disaster. The initial event took place on 15 February 2022, when 259 mm of rain fell in just three hours\u0026mdash;an amount equal to the average monthly rainfall\u0026mdash;which led to 242 fatalities. A second event occurred on 20 March 2022, causing seven additional deaths. The Civil Defense reported 6,293 incidents across both events, noting that more than 5,000 of these cases involved properties affected by or at risk from landslides. Approximately 3,500 individuals either lost their homes or had to move elsewhere. Structural damage affected 22.7% of local health facilities, including 13 Primary Health Care services and one Emergency Department. The disaster also caused an estimated loss of R\u003cspan\u003e$\u003c/span\u003e700\u0026nbsp;million to the municipal Gross Domestic Product.\u003c/p\u003e \u003cp\u003eDuring the same period, the municipality was experiencing a wave of COVID-19 cases and deaths associated with the Omicron variant of SARS-CoV-2. Public health measures included restrictions on in-person activities and population mobility, with a reported transmission rate (Rt) ranging from 0.29 to 0.44, indicating that every one hundred infected individuals transmitted the virus to 29 to 44 others.\u003c/p\u003e\n\u003ch3\u003eData studied\u003c/h3\u003e\n\u003cp\u003eThe study analyzed the monthly number of individual visits by adolescents aged 10 to 17 years who received mental health\u0026ndash;related diagnoses during consultations in Primary Health Care (PHC) services. The data came from the Primary Care Information System (Sistema de Informa\u0026ccedil;\u0026atilde;o em Sa\u0026uacute;de para a Aten\u0026ccedil;\u0026atilde;o B\u0026aacute;sica \u0026ndash; SISAB), overseen by Brazil's Ministry of Health.\u003c/p\u003e \u003cp\u003eSISAB is the official information system used for financing and monitoring adherence to programs and strategies under the National Primary Care Policy (\u003cem\u003ePol\u0026iacute;tica Nacional de Aten\u0026ccedil;\u0026atilde;o B\u0026aacute;sica\u003c/em\u003e \u0026ndash; PNAB). It receives mandatory monthly production records (number of consultations) from all PHC teams nationwide, which municipalities must submit by the tenth business day of the month following service delivery. The data covered the period from January 2018 to July 2022, which is six months after the overlap. The initial data selection considered periods with greater regularity in monthly reporting by municipalities, in accordance with previous methodological recommendations (Cavalcante et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe analysis included adolescents in early and middle adolescence, defined as ages 10\u0026ndash;13 years and 14\u0026ndash;17 years, respectively. During this stage of development, individuals experience major changes physically, emotionally, and socially, which may heighten their risk of mental health challenges.\u003c/p\u003e\n\u003ch3\u003eData collection\u003c/h3\u003e\n\u003cp\u003eIn April 2023, data was systematically gathered from the SISAB platform (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://sisab.saude.gov.br/\u003c/span\u003e\u003cspan address=\"https://sisab.saude.gov.br/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) following a standardized protocol. SISAB collected monthly data using Brazil as the geographic unit. The extracted reports organized municipalities in rows, with columns indicating production types as defined by the Ministry of Health's twenty-two established \"Problems or conditions assessed,\" which also included mental health. The \"Problem or condition assessed \u0026ndash; mental health\" variable is based on consultations that included any diagnosis listed in Supplementary Material 1. Additional filters included sex (female and male) and age group (10\u0026ndash;13 years and 14\u0026ndash;17 years).\u003c/p\u003e \u003cp\u003eThe data collection process generated 268 consolidated monthly production reports in .xlsx format for all Brazilian municipalities. This study included only data from the municipality of Petr\u0026oacute;polis. A thorough examination of all extracted files confirmed their consistency, with no discrepancies detected. The analysis kept header details such as year, month, sex, and age group, but left out footer data like source, extraction date, and extraction time.\u003c/p\u003e \u003cp\u003eAfter extraction and verification, the data underwent these processing steps: coding of year, month, sex, and age group variables into columns; and removal of unnecessary header and footer information. Following processing, the datasets underwent a second review, and no errors were found. All spreadsheets were subsequently merged into a single database using the Power Query function in Microsoft Excel.\u003c/p\u003e\n\u003ch3\u003eVariables studied\u003c/h3\u003e\n\u003cp\u003eThe outcome variable was the monthly rate of mental health\u0026ndash;related visits per 10,000 adolescent inhabitants, stratified by sex and age group. Estimates of the population from the Brazilian Ministry of Health served as the denominators. Since there were inconsistencies between the 2022 national census and earlier projections, population estimates for 2022 relied on data from 2021.\u003c/p\u003e \u003cp\u003eThe exposure variable was the overlap of rainfall-related meteorological disasters and the biological disaster associated with the COVID-19 pandemic, categorized into three periods:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003ePre-disaster period: February\u0026ndash;July 2018 and 2019.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eFirst six months of the biological disaster: March\u0026ndash;August 2020; and\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eFirst six months following the overlap of meteorological and biological disasters: February\u0026ndash;July 2022.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eThe covariates was sex (male, female) and age group (10\u0026ndash;13 years and 14\u0026ndash;17 years).\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003eWe conducted statistical analyses with IBM SPSS (version 27). The Kolmogorov\u0026ndash;Smirnov test (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) confirmed that the data were not normally distributed when analyzed by sex and age group. Descriptive analyses included absolute and relative frequencies, as well as medians and interquartile ranges for the number and rates of visits.\u003c/p\u003e \u003cp\u003eNonparametric Mann\u0026ndash;Whitney U test to compare median monthly visit rates from the first six months after the overlap with those from both the pre-disaster period and the initial six months of the pandemic. The percentage differences in median rates were determined for the following: 1) the period after the overlap compared with the pre-disaster period; and 2) the period after the overlap compared with the first six months of the biological disaster. All analyses used a two-sided significance threshold of p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eEthical aspects\u003c/h3\u003e\n\u003cp\u003e As this study used publicly available, anonymized data with unrestricted access, it was exempt from review by a Research Ethics Committee, in accordance with Brazilian regulations. The Research Ethics Committee at Universidade Federal de Minas Gerais (CAAE: 46914221.5.0000.5149) approved the exemption.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eThe analysis included 2,591 visits related to adolescent mental health. Of these adolescents, just over half were male (54.1%), and the majority (64.1%) were between 10 and 13 years old. When comparing the study periods separately, the highest proportion of visits (36.4%) occurred during the period of overlapping meteorological and biological disasters (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistribution of cases studied in which the problem or condition assessed was adolescent mental health, according to sex and age. Petr\u0026oacute;polis, Brazil.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eBefore the disasters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSix first months of the biological disaster\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFirst six months after the overlap\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eFeb-Jul\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMar-Aug\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFeb-Jul\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e187 (15.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e361 (30.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e232 (19.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e411 (34.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,191\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e239 (17.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e395 (28.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e233 (16.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e533 (38.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,400\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10 to 13 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e275 (16.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e485 (29.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e309 (18.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e592 (35.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,661\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14 to 17 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e151 (16.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e271 (29.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e156 (16.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e352 (37.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e930\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e426 (16.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e756 (29.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e465 (17.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e944 (36.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2,591\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eDuring the first six months following the overlap, there was a statistically significant increase in the median monthly rates of mental health\u0026ndash;related visits across sex and age groups, compared with both the pre-disaster period and the first six months of the biological disaster. Boys aged 14\u0026ndash;17 years experienced the highest relative increase, with rates rising by 166.2% compared to the period before the disaster and by 318.4% compared to the first six months following the biological disaster (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). There was also a notable rise of 114.9% (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) among girls aged 10\u0026ndash;13 years when comparing the period after the overlap to the time before the biological disaster. In addition, when comparing the period after the overlap with the first six months of the biological disaster, the increase reached 116.1% among boys aged 10\u0026ndash;13 years (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). When differences between groups were examined according to sex and age, it was observed that, despite the greater relative increase among older male adolescents, the absolute median rate of visits in the six months following the overlap was significantly lower among boys aged 14\u0026ndash;17 years than among younger adolescents (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u0026ndash; Differences between monthly rates of medical visits (per 10,000) in the first six months after the overlapping disasters compared to before the meteorological and biological disasters and during the first six months of the biological disaster. Petr\u0026oacute;polis, Brazil, n\u0026thinsp;=\u0026thinsp;2,591.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBefore the\u003c/p\u003e \u003cp\u003edisasters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFirst six months of the biological disaster\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFirst six months after the overlap\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eAfter the overlap vs. Before the disaster biological\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eAfter the overlap vs. During the disaster biological\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eMedian (P25 \u0026ndash; P75)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDif.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eDif.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28.2 (22.6\u0026ndash;52.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e31.7 (13.3\u0026ndash;55.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e60.6 (42.1\u0026ndash;75.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e114.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.019\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e91.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25.5 (16.7\u0026ndash;39.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22.1 (6.6\u0026ndash;32.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e42.6 (18.8\u0026ndash;56.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e67.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.160\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e92.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.150\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10 to 13 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e44 (38.6\u0026ndash;61.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36 (20.1\u0026ndash;56.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e77.8 (59.7-101.4) \u003cb\u003e*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e76.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.019\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e116.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.016\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14 to 17 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15.4 (10.6\u0026ndash;20.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.8 (6.2\u0026ndash;26.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e41.0 (24.9\u0026ndash;55.1) \u003cb\u003e*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e166.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.005\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e318.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.016\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eNotes: Diff\u0026thinsp;=\u0026thinsp;Difference; p\u0026thinsp;=\u0026thinsp;Mann-Whitney U test; P25\u0026ndash;P75\u0026thinsp;=\u0026thinsp;interquartile ranges; *significant differences between groups.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eOur results showed substantial and statistically significant increases in monthly rates of visits in which the problem or condition assessed was adolescent mental health during the first six months following the overlap of meteorological and biological disasters, compared with both the pre-disaster period and the first six months of the biological disaster (COVID-19 pandemic). In most studies examining the mental health impacts of compound disasters, methodological approaches typically compare the risks associated with exposure to compound disaster with those associated with exposure to a single disaster (Leppold et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In the present study, we extended this approach by comparing exposure not only to the compound (overlapping) disaster but also to the absence of disaster, represented by the pre-disaster period.\u003c/p\u003e \u003cp\u003eMental health care usage rose most sharply among older male adolescents aged 14 to 17, indicating an increased demand in this group. But there were also notable increases among younger adolescents between the ages of 10 and 13. Overall, consistent with findings from other studies on compound disasters, our results evidence of increased demand for mental health care (Campbell, Edwards and Gray, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Edwards, Taylor and Gray, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Gargano et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Leppold et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Rafaloski et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The higher mental health care utilization rates observed following the overlap underscore the multi-risk context generated by the co-occurrence of extreme events (Simonovic, Kundzewicz and Wright, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHowever, it is important to note that the overlap of the meteorological disaster with the COVID-19 pandemic occurred at a time when demand for adolescent mental health care in the municipality was already increasing. Evidence suggests that adolescents\u0026rsquo; mental health showed relative improvement during the first year of the pandemic but deteriorated during the second and third years (Kim et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Consequently, the overlapping meteorological disaster affected a population that was already psychologically vulnerable due to prolonged pandemic-related stressors. In this context, the risks associated with exposure to compound disasters exceed those linked to exposure to a single disaster, potentially resulting in both short- and long-term psychological distress (Leppold et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDisasters disrupt daily routines, which can result in heightened psychological vulnerabilities, including negative thoughts and emotions, fear, anxiety, hopelessness, and uncertainty (Cianconi, Betr\u0026ograve; and Janiri, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Among adolescents exposed to multiple disasters within a short time frame, studies have reported higher levels of psychological distress, including acute stress reactions, post‑traumatic stress disorder, depression, panic disorders, and an increased risk of suicidal behavior (Leppold et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAnother key finding of the results is that the observed increases in mental health care utilization rates reflect only adolescents who were able to access care, and not all those who required it. Despite considerable barriers to access typically seen during disaster recovery periods, service usage increased substantially. Barriers to health care access to care following disasters are often widespread and include damage to or destruction of health care infrastructure, as well as reductions in the health workforce available to provide care (Hertelendy et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Such barriers may persist for more than one year (Leppold et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The fact that many adolescents unable to access needed care underscores the considerable challenges faced by Primary Health Care (PHC) services in the context of intersecting and threat-multiplying events. In such scenarios, two potentially severe public health emergencies may unfold simultaneously, placing additional strain on already overstretched health systems.\u003c/p\u003e \u003cp\u003eRegarding the differences in the magnitude of impacts on mental health care utilization according to demographic characteristics (sex and age), comparisons with the existing literature reveal a mixed finding (Leppold et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Nevertheless, the more pronounced increase in service utilization among male adolescents warrants attention, particularly given that female adolescents exhibit higher overall health care-seeking behavior (Oliveira et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). This pattern may be partly explained by prevailing social norms related to masculinity, which often discourage emotional expression and delay help‑seeking, thereby worsening mental health outcomes after disaster exposure (Rahman et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDuring the period of overlap, the lower number of observed visits among older male adolescents and girls may be related to socially constructed roles and responsibilities. Older girls often remain in shelters, where they take care of younger children and assist with domestic tasks, whereas boys, in addition to providing support at home or in shelters, frequently accompany family members in cleaning activities and in the recovery of debris. Older adolescents of both sexes also tend to enter the labor market or seek informal work to support household income, particularly in the context of material losses and the loss of family providers, thereby assuming adult responsibilities prematurely (Corrochano and Tar\u0026aacute;bola, 2023).\u003c/p\u003e \u003cp\u003eStudies have suggested that mental health outcomes may vary according to the severity of exposure to multiple disasters, which can be characterized by one or more of the following factors: extent of loss, level of damage, barriers to accessing essential resources, perceived threat, and physical injuries sustained (Leppold et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In the context of the present study, the severity of both disasters was substantial. At the national level, the country experienced fragile political leadership and weaknesses in social protection and pandemic management, resulting in one of the highest COVID-19 mortality rates worldwide, while at the local level, the municipality endured one of the deadliest rainfall-related disasters in Brazil\u0026rsquo;s history.\u003c/p\u003e \u003cp\u003eIt is important to acknowledge that this study has limitations. Because the study was based on municipal data, it was not possible to evaluate differences between the neighborhoods that were most impacted. Nevertheless, this approach enabled the inclusion of a larger volume of data over a shorter time, without requiring financial resources for primary data collection. Another limitation relates to the use of population estimates from the Ministry of Health for 2021 as proxies for 2022, due to the unavailability of official population estimates for 2022 at the time of analysis. On the other hand, this study draws on the only nationwide Brazilian database that is sensitive to short- and medium-term changes in health service utilization following disasters, which made it possible to quantify the impacts of overlapping disasters on mental health care utilization.\u003c/p\u003e \u003cp\u003eOur findings underscore the need to rethink and strengthen disaster preparedness and response models. Preparedness strategies should directly address the complex and interacting risks from both rainfall-related disasters and pandemics, focusing on comprehensive approaches to effectively manage these compound threats (Ishiwatari et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Izumi et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Communities and health systems should enhance resilience to respond not only to isolated disasters but also to the increasing likelihood of compound disaster scenarios.\u003c/p\u003e \u003cp\u003eStrategies aimed at reorganizing PHC services in the post-disaster period, with a focus on adolescent mental health, alongside policies to reduce the risks of global health emergencies and climate change\u0026ndash;related meteorological disasters, may help mitigate the impacts of disaster overlap. In this context, the present study aligns with and supports the United Nations Sustainable Development Goals, particularly Goal 3 (Good Health and Well-Being), which seeks to ensure access to quality health care and promotes well-being for all, at all ages.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eDuring the time when both meteorological and biological disasters occurred together, monthly mental health\u0026ndash;related visits among adolescents rose notably across all sexes and age groups compared to each disaster period on its own. Older male adolescents experienced the highest rise, but every other group showed increases as well\u0026mdash;though these were less pronounced\u0026mdash;when compared to both reference periods.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003ePHC: Primary Health Care\u003c/p\u003e\n\u003cp\u003eSISAB: Primary Care Information System (\u003cem\u003eSistema de Informa\u0026ccedil;\u0026atilde;o em Sa\u0026uacute;de para a Aten\u0026ccedil;\u0026atilde;o B\u0026aacute;sica\u003c/em\u003e)\u003c/p\u003e\n\u003cp\u003ePNAB: National Primary Care Policy (\u003cem\u003ePol\u0026iacute;tica Nacional de Aten\u0026ccedil;\u0026atilde;o B\u0026aacute;sica\u003c/em\u003e)\u003c/p\u003e\n\u003cp\u003eIBM SPSS: IBM Statistical Package for the Social Sciences\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Research Ethics Committee at the Federal University of Minas Gerais (CAAE: 46914221.5.0000.5149) decided that a review was unnecessary. \u0026nbsp;\u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the\u0026nbsp;Brazilian National Council for Scientific and Technological Development (\u003cem\u003eConselho Nacional de Desenvolvimento Científico e Tecnológico\u003c/em\u003e – CNPq), grant number 408968/2025-7 and the Minas Gerais Research Foundation (\u003cem\u003eFundação de Amparo à Pesquisa do Estado de Minas Gerais\u003c/em\u003e – FAPEMIG), grant number APQ-00209-24.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJ.A.P. Contributed to data collection, analysis, and interpretation; manuscript writing; and approval of the definitive version. M.A.S., J.S., and M.C.C.R. contributed to writing the manuscript and approving the definitive version. E.W.R.V. contributed to the design, planning, and coordination of the study; data collection, analysis, and interpretation; writing of the manuscript; and approval of the definitive version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eCampbell, P., B. Edwards and M. Gray (2024) Exposure to multiple natural disasters and externalizing and internalizing behavior: A longitudinal study of adolescents. \u003cem\u003eJournal of Adolescent Health\u003c/em\u003e. October.\u003c/li\u003e\n\u003cli\u003eCavalcante, R.B. et al. (2018) Computerization of primary health care information systems: Advances and challenges. \u003cem\u003eCogitare Enfermagem\u003c/em\u003e. 23(3). 8 August.\u003c/li\u003e\n\u003cli\u003eCentre for Research on the Epidemiology of Disasters (2022) \u003cem\u003eNatural hazards \u0026amp; disasters: An overview of the first half of 2022\u003c/em\u003e. https://bit.ly/3OmBQyl (last accessed on 22 November 2024).\u003c/li\u003e\n\u003cli\u003eCianconi, P., S. Betr\u0026ograve; and L. Janiri (2020) \u0026lsquo;The impact of climate change on mental health: A systematic descriptive review\u0026rsquo;. \u003cem\u003eFrontiers in Psychiatry\u003c/em\u003e. 11. 6 March.\u003c/li\u003e\n\u003cli\u003eCorrochano, M.C. and F. de S. Tarabola (2023) Neoliberalism, work and pandemic: Experiences and coping strategies of youth from urban peripheries. \u003cem\u003eEduca\u0026ccedil;\u0026atilde;o \u0026amp; Sociedade\u003c/em\u003e. 44.\u003c/li\u003e\n\u003cli\u003eEdwards, B., M. Taylor and M. Gray (2024) \u0026lsquo;The influence of natural disasters and multiple natural disasters on self-harm and suicidal behavior: Findings from a nationally representative cohort study of Australian adolescents. \u003cem\u003eSSM \u0026ndash; Population Health\u003c/em\u003e. 25. p. 101576. March.\u003c/li\u003e\n\u003cli\u003eElm, E. von et al. (2007) The strengthening the reporting of observational studies in epidemiology (STROBE) statement: Guidelines for reporting observational studies. \u003cem\u003ePLoS Medicine\u003c/em\u003e. 4(10). p. e296. 16 October.\u003c/li\u003e\n\u003cli\u003eFakhruddin, B., K. Blanchard and D. Ragupathy (2020) Are we there yet? The transition from response to recovery for the COVID-19 pandemic\u0026rsquo;. \u003cem\u003eProgress in Disaster Science\u003c/em\u003e. 7. p. 100102. October.\u003c/li\u003e\n\u003cli\u003eGargano, L.M. et al. (2019) Comorbid posttraumatic stress disorder and lower respiratory symptoms in disaster survivors: Qualitative results of a 17-year follow-up of World Trade Center disaster survivors. \u003cem\u003eProgress in Disaster Science\u003c/em\u003e. 4. p. 100050. 1 December.\u003c/li\u003e\n\u003cli\u003eHertelendy, A.J. et al. (2025) Strengthening healthcare system resilience: A comprehensive framework for tropical cyclone preparedness and response\u0026rsquo;. \u003cem\u003eThe Lancet Regional Health \u0026ndash; Americas\u003c/em\u003e. 48. p. 101205. August.\u003c/li\u003e\n\u003cli\u003eIshiwatari, M. et al. (2020) Managing disasters amid COVID-19 pandemic: Approaches of response to flood disasters. \u003cem\u003eProgress in Disaster Science\u003c/em\u003e. 6. p. 100096. April.\u003c/li\u003e\n\u003cli\u003eIzumi, T. et al. (2022) \u0026lsquo;Managing compound hazards: Impact of COVID-19 and cases of adaptive governance during the 2020 Kumamoto flood in Japan\u0026rsquo;. \u003cem\u003eInternational Journal of Environmental Research and Public Health\u003c/em\u003e. 19(3). p. 1188. 21 January.\u003c/li\u003e\n\u003cli\u003eKamalrathne, T. et al. (2024) Managing compound events in the COVID-19 era: A critical analysis of gaps, measures taken, and challenges. \u003cem\u003eInternational Journal of Disaster Risk Reduction\u003c/em\u003e. 112. p. 104765. October.\u003c/li\u003e\n\u003cli\u003eKim, Y. et al. (2024) \u0026lsquo;Changes in mental health among adolescents in South Korea before and after COVID-19: An interrupted time series analysis from 2015 to 2022\u0026rsquo;. \u003cem\u003eJournal of Adolescent Health\u003c/em\u003e. October.\u003c/li\u003e\n\u003cli\u003eLeppold, C. et al. (2022) Public health implications of multiple disaster exposures. \u003cem\u003eThe Lancet Public Health\u003c/em\u003e. 7(3). p. e274\u0026ndash;e286. March.\u003c/li\u003e\n\u003cli\u003eOliveira, M.M. de et al. (2018) \u0026lsquo;Seeking health services or professionals among Brazilian adolescents, according to the 2015 National School Health Survey\u0026rsquo;. \u003cem\u003eRevista Brasileira de Epidemiologia\u003c/em\u003e. 21(suppl 1).\u003c/li\u003e\n\u003cli\u003ePaiva, V. et al. (2021) \u0026lsquo;Youth and the COVID-19 crisis: Lessons learned from a human rights-based prevention program for youths in S\u0026atilde;o Paulo, Brazil\u0026rsquo;. \u003cem\u003eGlobal Public Health\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003ePei, S. et al. (2020) \u0026lsquo;Compound risks of hurricane evacuation amid the COVID-19 pandemic in the United States\u0026rsquo;. \u003cem\u003eGeoHealth\u003c/em\u003e. 4(12). 30 December.\u003c/li\u003e\n\u003cli\u003eRafaloski, A.R. et al. (2020) Mental health of people affected by natural disasters from the perspective of involved workers. \u003cem\u003eSa\u0026uacute;de em Debate\u003c/em\u003e. 44(spe2). p. 230\u0026ndash;241. July.\u003c/li\u003e\n\u003cli\u003eRahman, M.M. et al. (2025) \u0026lsquo;Flood impact on men\u0026rsquo;s mental health: Evidence from flood-prone areas of Bangladesh\u0026rsquo;. \u003cem\u003eFrontiers in Public Health\u003c/em\u003e. 13. 3 April.\u003c/li\u003e\n\u003cli\u003eSimonovic, S.P., Z.W. Kundzewicz and N. Wright (2021) Floods and the COVID-19 pandemic: A new double hazard problem\u0026rsquo;. \u003cem\u003eWIREs Water\u003c/em\u003e. 8(2). 10 March.\u003c/li\u003e\n\u003cli\u003eUnited Nations Office for Disaster Risk Reduction (2020) \u003cem\u003e2020: The non-COVID year in disasters\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eWorld Health Organization (2024) \u003cem\u003eWHO Coronavirus (COVID-19) Dashboard\u003c/em\u003e. https://covid19.who.int/ (last accessed on 22 February 2026).\u003c/li\u003e\n\u003cli\u003eZscheischler, J. et al. (2018) Future climate risk from compound events. \u003cem\u003eNature Climate Change\u003c/em\u003e. 8(6). p. 469\u0026ndash;477. 14 June.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Impact of disasters, Effects of disasters on health, Natural disasters, Climate change, Adolescents, Mental health","lastPublishedDoi":"10.21203/rs.3.rs-9124398/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9124398/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e \u003cp\u003eBiological and meteorological disasters can have negative impacts on the mental health of adolescents. However, little is known about the impact of overlapping disasters. The objective of this study was to estimate the impact of the overlap of biological and meteorological disasters on adolescent mental health.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe overlap studied occurred in February 2022, when Petr\u0026oacute;polis, Brazil, suffered a meteorological disaster related to rainfall during the biological disaster of the COVID-19 pandemic. The data consisted of the number of visits by adolescents aged 10 to 17 years in which the problem or condition evaluated involved mental health diagnoses in the municipality's Primary Health Care (PHC) services. The monthly rates of health care usage were measured by municipality over the six months following the overlap period, which spanned from February to July 2022. These rates were then compared with those from the first six months of the biological disaster (March\u0026ndash;August 2020) and with the same period prior to the disaster (February\u0026ndash;July 2018\u0026ndash;2019). The Mann\u0026ndash;Whitney U test and percentage differences were used to analyze these comparisons.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eA total of 2,591 visits were analyzed, with 36.4% occurring after the overlap. Just over half of the consultations were for male adolescents (54.1%), and most were for adolescents aged 10 to 13 years (64.1%). Consultation rates, by sex and age, were higher after the overlap when compared with the periods before and during the pandemic (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The relative increase in rates was 166.2% higher than in the pre-disaster period and 318.4% higher than during the first six months of the pandemic among older male adolescents aged 14 to 17 years (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe overlap of biological and meteorological disasters impacts adolescents' demand for mental health care in PHC. Preparing for and coping with the impacts of disasters must consider the additional pressure on the health system imposed by the mental health needs of affected adolescents.\u003c/p\u003e","manuscriptTitle":"Compound Disasters and Adolescent Mental Health: Increased Primary Health Care Demand After the Overlap of the Covid-19 Pandemic and A Rainfall Disaster in Brazil","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-08 13:41:56","doi":"10.21203/rs.3.rs-9124398/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-30T03:39:17+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-22T20:00:51+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-09T13:55:48+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"304211619180647084929294597891606446044","date":"2026-04-09T12:10:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"235948898560425711994192721453586425068","date":"2026-04-06T16:37:46+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-02T13:01:31+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-24T17:35:44+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-19T07:59:58+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-19T07:59:28+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2026-03-14T18:05:37+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fcb2b2ed-a209-4ec8-9d77-e699afee698b","owner":[],"postedDate":"April 8th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Revision requested","date":"2026-04-30T03:39:17+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-14T14:08:24+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-08 13:41:56","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9124398","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9124398","identity":"rs-9124398","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}