Comprehensive assessment of depression risk and its behavioral determinants among adolescents: a multi-country study

Comprehensive assessment of depression risk and its behavioral determinants among adolescents: a multi-country study | 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 Comprehensive assessment of depression risk and its behavioral determinants among adolescents: a multi-country study Sabera Sultana, Md. Mizanur Rahman, Masahiro Hashizume This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1402117/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Mental illness has become a widespread public health concern internationally. This study aimed to generate a depression risk index for adolescents. Furthermore, we developed risk indexes for potential lifestyle and social risk factors of depression among adolescents. In addition, we investigated the country-specific prevalence for each risk index. Finally, we conducted comprehensive assessment of the associations between depression risk and lifestyle and social risk factors. Methods: We used the most recent data available from 20 nationally representative Global School-based Student Health Surveys. Our analytical sample included 51,597 adolescents. The outcome of interest was depression risk, which considered feelings of anxiety, loneliness, and suicidal attempts or tendencies. We developed four lifestyle risk indexes (dietary habits, physical activity, sedentary behavior, and tobacco use) and three social risk indexes (exposure to school violence, interactions with parents, and interactions with friends) which were considered as exposure variables in this study. Multilevel logistic regression models were used to estimate adjusted odds ratios (ORs) with 95% confidence intervals (CIs). Results: In total, 26.4% of the participants had a risk of depression. Increased odds of depression risk were found among participants with high risk index values for unhealthy dietary habits (OR, 1.15; 95% CI, 1.07–1.23), unhealthy sedentary behavior (OR, 1.53; 95% CI, 1.43–1.63), tobacco use (OR, 1.57; 95% CI, 1.41–1.76), exposure to school violence (OR, 3.06; 95% CI, 2.88–3.26), insufficient interactions with parents (OR, 2.09; 95% CI, 1.92–2.28), and insufficient interactions with friends (OR, 1.82; 95% CI, 1.69–1.96) compared with participants with low risk index values. However, there were no significant associations between physical inactivity and risk of depression among adolescent boys or girls. Conclusions: High prevalence rates for depression risk, as well as unhealthy lifestyle factors and social behaviors among adolescents were found in every country, and higher risk index values were associated with increased risk of depression. Sedentary behavior dietary habit tobacco use peer and family relationships school violence Figures Figure 1 Introduction The global prevalence of depression among adolescents is increasing internationally,[1] with an increase of 18% between 2005 and 2015.[2] Because of stark differences between countries, depression was traditionally considered to be a problem that primarily affected first world countries. However, recent studies have reported that most countries have relatively similar rates of depression, but social stigma, lack of data availability, and non-recognition of mental illness are more common in developing countries.[3-4] Previous research indicated that the regions with the highest rates of depression were eastern Europe, North Africa and the Middle East, and, by country, the highest number of years lost because of depression-related disability was in Afghanistan.[4] Mental health conditions account for 16% of the global burden of disease and injury in people 10–19 years of age.[5] Depression is the leading cause of global disability, and unipolar depression is the 10th leading cause of early death.[5] A clear link has been established between depression and suicide, which is the third leading cause of death for young people aged 15–29 years.[5] Depression not only affects psychological health but also increases the risk of cardiovascular disease, diabetes and cancer.[6-7] Depression can also lead to serious social and educational impairments, smoking, substance abuse, and obesity among adolescents.[8-11] Moreover, depression takes an economic toll on individuals, families, organizations, and society. On the basis of data from 2010, the World Economic Forum estimated that the combined direct and indirect cost of mental disorders was US$2.5 trillion, and this cost is predicted to reach US$6.1 trillion by 2030.[12] Depression results from complex interactions between social, psychological, and biological factors. Increased access to and use of technology, peer and family relationships, quality of home life, unhealthy lifestyle behavior, violence and socioeconomic problems, and poor physical health are recognized as risk factors for adolescent depression.[5,13-15] Although adolescent depression is treatable, it often remains untreated because of difficulty in diagnosis and a lack of treatment services.[5,16] Between 76% and 85% of people with depression in low- and middle-income countries receive no treatment for their disorder.[16] In 2018, the American Academy of Pediatrics recommended regular depression screening for all adolescents 12 and over.[17] Early recognition of the risk of depression and identification of modifiable risk factors is critically needed to reduce the burden of depression. Therefore, the current study aimed to develop a depression risk index by combining several psychological signs of adolescent depression, providing a quick and comprehensive tool for self-screening of depression risk. Furthermore, we generated risk indexes for potential lifestyle and social risk factors of depression among adolescents using cross-country data and assessed their relationships with depression risk index values. These findings will provide guidelines to reduce the risk of depression among adolescents through lifestyle and social behavioral modifications. Methods Data sources We used data from the Global School-based Student Health Survey (GSHS) for this study. The data were downloaded from the Centers for Disease Control and Prevention (CDC) website (CDC Global School-based Student Health Survey (GSHS)). All countries with data available for 2013 or later were included, resulting in a total of 20 countries. For each country, we used only the latest available dataset in the study period. The GSHS used a two-stage cluster design to produce a nationally representative sample of all students enrolled in grades 7 to 11. The participants’ ages ranged from 13 to 17 years. In the first stage of sampling, schools were selected with probability proportional to student enrollment. In the second stage, systematic random sampling was used to select classes from each sampled school. All students in the selected classes were eligible to participate. Survey procedures were designed to protect students’ privacy by allowing for anonymous and voluntary participation. Details survey procedure of GSHS is available on WHO’s website (Bangladesh - Global School-Based Student Health Survey 2014 (who.int)).[ 18 ] Participants who had missing values for any variable of interest were excluded from the study. The basic survey characteristics of the GSHS datasets are presented in Table 1 . We used the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines for reporting. Because we used secondary data, public and patient involvement was not possible. Our study was exempted by the ethics committee of the university of Tokyo as we employed secondary data that are available for public use. Legend: CI: confidence interval 1 Countries with Global School-based Student Health Survey data available for 2013 or later. 2 Descriptive analyses were used to estimate mean age and percentage of depression risk among adolescents. Probability sampling weights were applied in all analyses. Outcome variable The outcome variable in this study was the risk of depression among adolescents. According to the CDC, anxiety and self-harming behaviors, including suicide, are common depressive symptoms among adolescents.[ 19 ] Another previous study reported that approximately 50% of all people diagnosed with depression are also diagnosed with anxiety disorder.[ 20 ] Moreover, one study reported that young people who are lonely are as much as three times more likely to develop depression in the future, and this finding was supported by subsequent studies.[ 21 – 23 ] Hence, we considered four components while developing a depression risk index for adolescents: frequency of anxiety, loneliness, thoughts of suicide, and suicide attempts in the last 1 year. Anxiety and loneliness had three cut-off points while thoughts of or attempts of suicide had two cutoff points because suicide was a severe indicator of depression. One risk score corresponded to each cut-off point. Risk scores ranged from healthy (0) to unhealthy (2). The risk scores for each component were combined to produce a risk score range for each risk index. The risk score range was then categorized into three risk levels.[ 24 ] Lower risk index values represented lower risk levels, whereas higher risk index values represented higher risk levels. Table 2 shows the components and composition of the depression risk index. Exposure variables Four risk indexes were developed for four lifestyle risk factors: dietary habits, physical activity, sedentary behavior and tobacco use. Three risk indexes were developed for three social risk factors: exposure to school violence, interactions with parents, and interactions with friends. These risk indexes were considered as the primary exposure variables in this study. The dietary risk index included four components: fruit, vegetables, fast foods, and carbonated soft drinks. Cut-off points were determined using World Health Organization (WHO) guidelines where available, or in accordance with previous literature.[ 25 – 27 ] To determine the risk index for physical activity, we used the WHO guidelines, which categorized adolescents as physically active if they were involved in vigorous physical movement for at least 60 minutes each day.[ 28 ] The risk index for sedentary behavior was generated using the amount of time each day participants spent watching television, looking at tablets, or playing video games. We used the American Association of Pediatrics’ recommendations for adolescent media use to set the cut-off points for different risk levels of unhealthy sedentary behavior.[ 29 ] The tobacco use risk index was developed using two components: cigarette smoking and the use of any other tobacco products. For adolescents, there are no safe limits, and there are no clear guidelines for classifying the use of tobacco products. We defined occasional, irregular, and frequent users of tobacco following a previous study and assigned three risk levels.[ 30 ] The risk index for exposure to school violence was developed using four components: physical attacks, fights, injuries, and bullying.[ 31 – 32 ] The risk index for interactions with parents was developed considering two components: how frequently participants missed school without permission and how often they felt that their parents understood their problems. The risk index for interactions with friends was generated using two components: how frequently participants found their classmates to be kind and helpful, and the number of close friends they had. Table 3 shows the components and composition of these risk indexes. Detailed information regarding the four lifestyle risk indexes (dietary habits, physical activity, sedentary behavior and tobacco use) were provided elsewhere.[ 33 ] Covariates Covariates included the student’s age (13–17 years), sex (boys or girls), and the experience of hunger in the past 30 days (never, rarely, sometimes, most of the time, or always), as well as the national literacy rate. Consistent with a previous study, the frequency of hunger because of insufficient food at home in the past 30 days was treated as a proxy variable for socioeconomic status.[ 34 ] Data analyses We used Cronbach’s alpha to assess the internal reliability of the risk indexes ( supplementary table 1 ). A descriptive analysis was performed to estimate summary statistics such as means, percentages, and 95% confidence interval (CIs). Following previous studies, we used multilevel logistic regression models to estimate odds ratios (ORs) and corresponding 95% CIs to assess the relationships between depression risk and its behavioral determinants among adolescents.[ 14 – 15 ] Let j denote the level-two units (countries) and let i denote the level-one units (items or observations). Assume that there are j = 1, 2, ..., C countries and i = 1, 2, …, \({N}_{j}\) individuals in each country. The multilevel regression model can be written as $$\text{log}\left(\frac{{\pi }_{ij}}{1-{\pi }_{ij}}\right)= {y}_{ij} = {X}_{ij}\beta + {Z}_{j}\gamma + {u}_{j} + {\epsilon }_{ij}$$ , where outcome \({y}_{ij}\) for each adolescent i in country j is assumed to depend on both observed predictors and unobserved factors, \({y}_{ij}\) is the log odds of adolescent i in country, and j being overweight or obese. \(\beta\) represents a vector of regression coefficients associated with the individual-level variables \({X}_{ij}\) . These individual-level characteristics were the seven risk scores, age, gender, and socioeconomic status. \({Z}_{j}\) contains variables summarizing the country-level characteristics such as the literacy rate in the study context. Unobserved individual effects are represented as \({\epsilon }_{ij}\) , and country effects are represented as \({u}_{j}\) . In the multilevel model, \({\epsilon }_{ij}\) and \({u}_{j}\) are assumed to be normally distributed and uncorrelated individual-level ( \({X}_{ij}\) ) and country-level ( \({Z}_{j}\) ) predictors. The parameters associated with the observed predictors \(\beta\) and \(\gamma\) are fixed regression parameters. Parameters \({\epsilon }_{ij}\) and \({u}_{j}\) are treated as random terms. Stata/SE 15.0 (StataCorp, College Station, TX, USA) was used in this study for data management, statistical analysis, and graph generation. Probability sampling weights were applied in all descriptive analyses. Results Sample characteristics A total of 83,695 adolescents aged 13–17 years were surveyed. Participants with missing values for any of the variables of interest were excluded from the analysis. This resulted in an analytical sample size of 51,597, representing a total adolescent population of 22,945,384 individuals, after applying the sampling weights. As shown in Table 1, 45% of the participants were boys, and the mean age was 14.8 years. Country-specific scenarios of depression risk As shown in Table 1, 26.4% of adolescents had risk of depression. The highest proportion of adolescents with a risk of depression was found in Afghanistan (50%), followed by Namibia (43%), Benin (40%), Kuwait (37%), Bahrain (37%), Yemen (37%), and Timor-Leste (32%). The lowest prevalence of depression risk was reported in Laos (12%) followed by Indonesia (13%) and Bangladesh (18%). Supplementary Fig. 1 shows that depression risk among girls was highest in Afghanistan (59%), followed by Kuwait (44%), Bahrain (43%), Benin (43%), Yemen (42%), the Bahamas (36%), Mongolia (35%), and the Philippines (34%). In the countries included in this study, the risk of depression was reported to be higher among girls than among boys, except in Timor-Leste (boys: 26%; girls: 12%). Country-specific scenarios of lifestyle and social risk indexes Figure 1 shows the percentage of lifestyle and social risk indexes among adolescents in each country. The prevalence of unhealthy (moderate and high risk) dietary habits ranged from 77% (the Cook Islands) to 94% (Timor-Leste, Mongolia, Nepal). The highest percentage of physical inactivity was observed in the Philippines (91%) followed by Thailand (87%), Timor-Leste (87%), Tuvalu (86%), Indonesia (85%), and Brunei (85%), whereas the lowest percentage was seen in Bangladesh (48%). The prevalence of unhealthy (moderate and high risk) sedentary behavior varied from 34% (Nepal) to 88% (Kuwait). The prevalence of high-risk unhealthy sedentary behavior (daily sedentary time ≥ 4 hours) was highest in Kuwait (42.0%), followed by Bahrain (37.2%), the Bahamas (34.4%), Thailand (31.1%), and Brunei (27.3%). Approximately 15% of adolescents in Kuwait, Bahrain, and Polynesia used tobacco. In the other countries in this study, less than 10% of adolescents reported using tobacco. Overall, 27% of the participants were exposed to school violence (moderate and high risk). The prevalence of exposure to school violence (moderate and high risk) varied from 7% (Laos) to as high as 47% (Tuvalu). Around 25% adolescents in Nepal and Tuvalu, and around 20% adolescents in Namibia, Afghanistan, the Philippines, Timor-Leste, Yemen, and Bangladesh reported a high risk of exposure to school violence. Furthermore, 71% of participants had insufficient interactions with parents (moderate and high risk). The prevalence of insufficient interactions with parents (moderate and high risk) was lowest in Nepal (56%) and highest in Timor-Leste (93%). Around 20% adolescents in Bahrain, Kuwait, Timor-Leste, Laos, Tuvalu, Yemen, Brunei, and the Philippines had a high risk of insufficient interactions with parents. 62% of participants had insufficient interactions with friends (moderate and high risk). The highest proportions of adolescents with insufficient interactions with friends (moderate and high risk) were observed in Benin and Laos (82%) and the lowest proportion was observed in Bahrain (37%). Around 17% adolescents in Tuvalu, Namibia, Afghanistan, and Benin reported a high risk of insufficient interactions with friends. Gender-based lifestyle factors and social risk index values The prevalence of unhealthy dietary habits was similar for boys and girls, but in most examined countries, girls were 5–20% more physically inactive than boys. The largest gender differences in physical inactivity were observed in Laos (boys: 73% vs. girls: 91%), followed by Brunei (boys: 78% vs. girls: 93%), Polynesia (boys: 69% vs. girls: 84%), the Cook Islands (boys: 69% vs. girls: 84%), and Thailand (boys: 78% vs. girls: 94%). See supplementary table 2 , available online, for gender-specific prevalence of unhealthy dietary habits and insufficient physical activity by country. No gender-based differences were found in sedentary behavior, except in Bahrain, where the percentage of unhealthy sedentary behavior was substantially higher among girls than among boys (boys: 77% vs. girls: 91%). The use of tobacco was higher among boys (10%) than that among girls (3%), except in Polynesia, where the percentage of tobacco use was much higher among girls than that among boys (boys: 11% vs. girls: 18%). Significant gender differences in tobacco use were found in Bahrain (boys: 25% vs. girls: 4%), Kuwait (boys: 22% vs. girls: 6%), and Timor-Leste (boys: 18% vs. girls: 4%). See supplementary table 3 , available online, for gender-specific prevalence of unhealthy sedentary behavior and tobacco use by country. The prevalence of exposure to school violence was 5–15% higher among boys than that among girls across countries. The largest gender differences in exposure to school violence were found in Mongolia (boys, 38.0% vs girls, 14.0%), followed by Tuvalu (boys, 62.0% vs girls, 34.0%), Thailand (boys, 30.0% vs girls, 13.0%), Kuwait (boys, 37.0% vs girls, 22.0%), Yemen (boys, 47.0% vs girls, 19.0%), and Bahrain (boys, 42.0% vs girls, 21.0%). The prevalence of insufficient interactions with parents was higher among boys than that among girls. Major gender differences for insufficient interactions with parents were observed in Bangladesh (boys, 67.7% vs girls, 57.2%), Benin (boys, 76.0% vs girls, 69.4%), Fiji (boys, 63.0% vs girls, 55.2%), Mongolia (boys, 78.7% vs girls, 71.6%), and Afghanistan (boys, 55.4% vs girls, 40.7%). There were no gender-specific differences in the prevalence of insufficient interactions with friends. Significant gender differences in insufficient interactions with friends were observed in Bangladesh (boys, 53.0% vs girls, 63.4%), the Cook Islands (boys, 50.3% vs girls, 57.4%), Indonesia (boys, 66.0% vs girls, 57.0%), Tuvalu (boys, 80.0% vs girls, 70.0%), Thailand (boys, 69.4% vs girls, 56.3%), Bahrain (boys, 41.4% vs girls, 32.0%), and Yemen (boys, 71.0% vs girls, 63.0%). See supplementary table 4 , available online, for gender-specific prevalence of exposure to school violence and insufficient interactions with parents and friends by country. Associations between the risk of depression and lifestyle and social risk index values A multilevel logistic regression analysis was performed to determine the associations between the four lifestyle and three social risk indexes and the risk of depression among adolescents. Total and gender specific ORs with 95% CIs for overweightor obese status in relation to different lifestyle risk scores are presented in Table 4 . Regarding the dietary risk index, the odds of depression risk were 15% (OR = 1.15; 95% CI, 1.07–1.23) higher for participants with high risk index values compared with those with a low dietary risk index. However, for total samples and each subgroup, there were no significant associations between physical inactivity and the risk of depression. Regarding unhealthy sedentary behavior, participants with high risk index values had 53% (OR = 1.53; 95% CI, 1.43–1.63) higher odds of depression risk than those with a low risk score for unhealthy sedentary behavior. The association between unhealthy sedentary behavior and depression risk was stronger among girls (OR = 1.65; 95% CI, 1.51–1.80) than among boys (OR = 1.33; 95% CI, 1.21–1.47). Participants with moderate and high risk scores for tobacco use had 65% (OR = 1.65; 95% CI, 1.46–1.86) and 57% (OR = 1.57; 95% CI, 1.41–1.76) higher odds of depression risk, respectively, compared with those with a low risk score of tobacco use. The association between tobacco use and depression risk was stronger among girls (OR = 2.54; 95% CI, 2.01–3.22) than among boys (OR = 1.44; 95% CI, 1.26–1.64). Compared with participants with a low risk score of exposure to school violence, those with moderate (OR = 1.79; 95% CI, 1.69–1.90) or high (OR = 3.06; 95% CI, 2.88–3.26) risk scores of exposure to school violence had higher odds of depression risk. Participants with high risk scores for insufficient interactions with parents (OR = 2.09; 95% CI: 1.92–2.28) and friends (OR = 1.82; 95% CI: 1.69–1.96) showed higher odds of depression risk than those with low risk scores of insufficient interactions with parents and friends, respectively. Associations between insufficient interactions with parents and depression risk were stronger among boys (OR = 2.33; 95% CI: 2.05–2.65) than among girls (OR = 1.95; 95% CI: 1.74–2.19), whereas associations between insufficient interactions with friends and depression risk were stronger among girls (OR = 2.24; 95% CI: 2.03–2.48) than among boys (OR = 1.39; 95% CI: 1.25–1.55). Discussion The aim of the current study was to provide a comprehensive assessment of depression risk and its behavioral determinants (unhealthy dietary habits, physical inactivity, unhealthy sedentary behavior, tobacco use, exposure to school violence, insufficient interactions with parents, and insufficient interactions with friends) among adolescents under 18 years of age. The results revealed that the prevalence of depression risk and unhealthy lifestyle and social behaviors was relatively high, although it varied widely by country and gender. Multilevel analyses showed that, except for insufficient physical activity, having higher risk scores for lifestyle and social behavior increased adolescents’ odds of depression risk. The current results revealed that more than one in every four adolescents was at risk of depression. We found that Afghanistan had the highest prevalence of adolescent depression risk, which was in line with a previous study reporting that depression rate was highest among Afghan adults.[ 5 ] War and conflict, domestic violence, child sexual abuse, poverty, and unavailability of adolescent counselling services could be contributing factors for high depression risk in Afghanistan.[ 35 ] The current study found a high prevalence of depression risk in Middle Eastern countries (Kuwait, Bahrain, and Yemen), in accord with the results of a previous study.[ 36 ] Developmentally and culturally appropriate community-based detection efforts may be helpful for addressing depression among adolescents in Arab countries.[ 36 ] In the current study, the prevalence of depression risk was higher among girls (28%) than among boys (23%), in accord with the findings of several previous studies.[ 4 , 35 , 36 ] Social roles, socialization differences, coping style, and response to stressful life events have been reported to make girls more vulnerable to depression than boys.[ 37 ] The current study revealed that four out of five adolescents exhibited unhealthy dietary habits, and this increased the odds of depression risk among girls, although there was no significant association among boys. A previous study also found a positive association between unhealthy dietary habits and the risk of depression.[ 38 ] There are several potential pathways of influence between unhealthy dietary habit and depression. For example, people who consume foods that are high in sodium and low in potassium are more likely to develop symptoms of depression.[ 39 ] Furthermore, a lack of amino acids and zinc in the diet may cause depression because of enhanced levels of serotonin and dopamine in the body.[ 38 ] These findings suggest that countries should reconsider their existing policies and initiate programs for promoting healthy dietary habits among adolescents. For example, several studies have found that school-based nutrition education programs increase healthy eating habits, including more fresh fruit and vegetable consumption.[ 40 – 41 ] Thus, school-based nutrition education programs might provide a useful tool for improving dietary habits among adolescents. The current study revealed no significant associations between physical inactivity and depression risk among adolescents, which was similar to previously reported findings.[ 42 ] Although another previous study found that physical activity played a protective role against depression among adolescents.[ 43 ] Therefore, further research into this issue may be valuable. The current results revealed that two out of three adolescents exhibited an unhealthy level of sedentary behavior, which increased the odds of depression risk for boys and for girls, in accord with several previous reports.[ 14 , 42 ] Plausible biological pathways for this effect include central nervous system arousal, sleep disturbances, and poor metabolic health resulting from prolonged sedentary behavior.[ 44 ] In addition, extended periods of sedentary behavior, such as television viewing and playing video games, has been found to lead to social solitude and withdrawal from interpersonal relationships, which has been linked to increased feelings of anxiety.[ 44 ] Our results revealed that one in four adolescents spent more than 4 hours of daily sedentary time in the Bahamas, Thailand, Bahrain, Brunei, and Kuwait, which warrants immediate action. Programs for promoting awareness among adolescents and parents about the harmful effects of unhealthy sedentary behavior may help to limit adolescents’ daily sedentary time. The current study revealed that the use of tobacco was positively associated with depression risk, which is consistent with a previous report.[ 11 ] Moreover, we found that the use of tobacco was considerably higher among boys than that among girls, but the association between tobacco use and depression risk was stronger among girls than that among boys. Therefore, it may be valuable to emphasize community and school-based tobacco awareness and cessation programs in Kuwait, Bahrain and Polynesia to suppress the use of tobacco among adolescents. In the current study, 27% adolescents reported exposure to school violence. In addition, we found a strong association between exposure to school violence and depression risk among adolescents. A previous study also revealed that children who had high levels of exposure to school violence were more likely to experience depression.[ 15 ] A new United Nations Educational Scientific and Cultural Organization study reported that effective systems for reporting and monitoring school violence and bullying, evidence-based programs and interventions, training and support for teachers, support and referral for affected students can reduce the prevalence of school violence.[ 45 ] Therefore, the countries in our study that showed a high prevalence of school violence (Nepal, Tuvalu, Namibia, the Philippines, and Timor-Leste) may find it useful to implement interventions to provide a safe and positive school climate and classroom environment. The current findings revealed that two out of three adolescents had insufficient interactions with friends, and three out of four adolescents had insufficient interactions with parents. Importantly, insufficient interactions with parents and friends increased the risk of depression among adolescents. This finding is consistent with the results of a previous study reporting that parents and peers could provide supportive environments to offset stressors such as loneliness.[ 13 ] Moreover, rapid urbanization and the changing social and economic context and technological advancement have caused drastic lifestyle changes. For example, one recent study reported that many teens did not socialize in the real world, and that this behavior pattern caused severe loneliness.[ 46 ] A recent survey of parents reported that 25% children were addicted to devices and games and in the home, and that the constant use of devices among family members can cause children to feel lonely and isolated.[ 47 ] Therefore, in Bahrain, Kuwait, Timor-Leste, Laos, Tuvalu, Yemen, Brunei, the Philippines, and the Cook Islands, improved relationships between adolescents and their parents should be emphasized. One possible mechanism might be parental involvement in school activity on a voluntary basis. Furthermore, our study revealed that insufficient interactions with friends made girls more vulnerable to depression risk than boys. One possible reason is that, during adolescence, girls have tighter, more cohesive friendship networks than boys, which consequently elevates the risk of expulsion from their social network. According to the current study findings, a focus on improved peer relationships among adolescents may be helpful in Benin, Tuvalu, and Namibia. We conducted comprehensive assessment of depression risk and its modifiable risk factors among adolescents. Additionally, we reported country-specific scenarios of adolescent lifestyle factors and social behaviors. We used the most recent available nationally representative data from multiple countries with different ethnic and cultural compositions, with a large sample size (> 50,000), and the results are likely to be generalizable to other countries with high rates of schooling. However, the GSHS only included adolescents who were enrolled in school, and school-going adolescents may not be representative of all adolescents in a country. Despite this limitation, because school enrollment rates among adolescents were high in most of the included countries, the results are unlikely to be severely affected by sample selection bias.[ 48 ] Furthermore, because of the self-reported nature of the data, misreporting is possible, although this should be minimized by the anonymity of the questionnaire and the data cleaning techniques used. In conclusion, widespread prevalence of depression risk and its behavioral determinants were observed among adolescents in most of the countries studied. Moreover, higher lifestyle and social risk scores considerably increased the odds of depression risk. The current findings will increase awareness of adolescent depression and consequently may help to reduce stigma related to depression. Moreover, our findings may facilitate early recognition and cost-effective management of adolescent depression. These outcomes can also inform population-based interventions to improve lifestyles and social behaviors among adolescents. Abbreviations GSHS Global School-based Student Health Survey OR Odds Ratio CI Confidence Interval WHO World Health Organization CDC Center for Disease Control and Prevention Declarations Ethics approval and consent to participate: Our study was exempted by the ethics committee of the university of Tokyo as we employed secondary data that are available for public use. Consent for publication: Not applicable Availability of data and materials: The data used in this study was downloaded from the website ( CDC Global School-based Student Health Survey (GSHS) ) of Centers for Disease Control and Prevention (CDC). Analysis sheets are presented in the manuscript and also as supplementary files. The code book, and analytic code will be made available upon request to the corresponding author. Conflict of interest: None of the authors had any biomedical financial interests or potential conflicts of interest or personal affiliation that compromised the scientific integrity of this work. Fund: This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Authors contributions: SS, MMR, and MH conceived the article. SS carried out the background study, data extraction, statistical analysis, and interpretation of the data under the supervision of MMR. SS conducted the quality assessment, in consultation with MH. SS wrote the manuscript. MH and MMR checked the consistency of the study. MH and MMR revised it critically for intellectual content. All authors have reviewed and approved the final manuscript. Acknowledgments: We thank the WHO, the Centers for Disease Control and Prevention, and the Ministries of Health and Education in all the selected countries for conducting this survey and for making the data available at no cost. We thank Benjamin Knight, MSc., from Edanz (https://jp.edanz.com/ac) for editing a draft of this manuscript. References World Health Organization. Depression and other common mental disorders: global health estimates. Geneva. 2017 Feb, Licence: CC BY-NC-SA 3.0 IGO. Available from: WHO-MSD-MER-2017.2-eng.pdf;sequence=1 Mojtabai R, Olfson M, Han B. National Trends in the Prevalence and Treatment of Depression in Adolescents and Young Adults. Pediatrics. 2016 Dec;138(6):e20161878. Doi:10.1542/peds.2016-1878. Shorey S, Ng ED, Wong CH. Global prevalence of depression and elevated depressive symptoms among adolescents: A systematic review and meta-analysis. Br J Clin Psychol. 2021 Sep. Doi: 10.1111/bjc.12333. Dewey C. A stunning map of depression rates around the world. The Washington Post [Internet]. 2013 Nov [cited 2020 Dec 15]. Available from: A stunning map of depression rates around the world - The Washington Post World Health Organization. Adolescent mental health [Internet]. 2021 Nov [cited 2021 Dec 15]. Available from: Adolescent mental health (who.int) . Ahn HK, Bae JH, Ahn HY, Hwang IC. Risk of cancer among patients with depressive disorder: a meta-analysis and implications. Psychooncology. 2016 Dec;25(12):1393-1399. Doi: 10.1002/pon.4084. Whang W, Kubzansky LD, Kawachi I, Rexrode KM, Kroenke CH, Glynn RJ, et al. Depression and risk of sudden cardiac death and coronary heart disease in women: results from the Nurses' Health Study. J Am Coll Cardiol. 2009 Mar;53(11):950-958. Doi:10.1016/j.jacc.2008.10.060. Fletcher JM. Adolescent depression: diagnosis, treatment, and educational attainment. Health Econ. 2008 Nov;17(11):1215-1235. Doi:10.1002/hec.1319. Mannan M, Mamun A, Doi S, Clavarino A. Prospective associations between depression and obesity for adolescent males and females- a systematic review and meta-analysis of longitudinal studies. PLoS One. 2016 Jun;11(6):e0157240. Doi:10.1371/journal.pone.0157240. Hernandez L, Cancilliere MK, Graves H, Chun TH, Lewander W, Spirito A. Substance use and depressive symptoms among adolescents treated in a pediatric emergency department. J Child Adolesc Subst Abuse. 2016 Mar;25(2):124-133. Doi: 10.31234/osf.io/eq9jf . Audrain-McGovern J, Rodriguez D, Kassel JD. Adolescent smoking and depression: evidence for self-medication and peer smoking mediation. Addiction. 2009 Oct ;104(10): 1743-1756. Doi:10.1111/j.1360-0443.2009.02617.x. Trautmann S, Rehm J, Wittchen HU. The economic costs of mental disorders: Do our societies react appropriately to the burden of mental disorders? EMBO Rep. 2016 Sep;17(9):1245-1249. D oi: 10.15252/embr.201642951 . Oppenheimer W, Hankin BL, Young J. Effect of Parenting and Peer Stressors on Cognitive Vulnerability and Risk for Depression among Youth. J Abnorm Child Psychol. 2018 Apr;46(3):597-612. Doi: 10.1007/s10802-017-0315-4. Cabello M, Miret M, Caballero FF, Chatterji S, Naidoo N, Kowal P, et al. The role of unhealthy lifestyles in the incidence and persistence of depression: A longitudinal general population study in four emerging countries. Global Health. 2017 Mar;13(1):18. Doi: 10.1186/s12992-017-0237-5 . Flannery DJ, Wester KL, Singer MI. Impact of exposure to violence in school on child and adolescent mental health and behavior. J Community Psychol. 2004 Aug;32(5):559-573. Doi: 10.1002/jcop.20019. Wang PS, Aguilar-Gaxiola S, Alonso J, Angermeyer MC, Borges G, Bromet EJ, et al. Use of mental health services for anxiety, mood, and substance disorders in 17 countries in the WHO world mental health surveys. The Lancet. 2007 Sep;370(9590):841-50. D oi:10.1016/S0140-6736(07)61414-7 . Zuckerbrot RA, Cheung A, Jensen PS, Stein RE, Laraque D, GLAD-PC STEERING GROUP. Guidelines for adolescent depression in primary care (GLAD-PC): part I. practice preparation, identification, assessment, and initial management. Pediatrics 2018 Mar;141(3):e20174081. Doi:10.1542/peds.2017-4081. World Health Organization. NCD microdata repository . Global School-Based Student Health Survey 2014, Bangladesh [Internet]. 2019 Jun [cited 2021 Dec 20]. Available from: Bangladesh - Global School-Based Student Health Survey 2014 (who.int) Centers for Disease Control and Prevention. Children’s mental health. Anxiety and depression in children [Internet]. 2021 Mar [cited 2021 Dec 20]. Available from: Anxiety and Depression in Children | CDC . Morin A. Depression statistics everyone should know [Internet]. Verywell Mind. 2021 May [cited 2021 Dec 20]. Available from: https://www.verywellmind.com/depression-statistics-everyone-should-know-4159056 . Loades ME, Chatburn E, Higson-sweeney N, Reynolds S, Shafran R, Brigden A, et al. Rapid systematic review: the impact of social isolation and loneliness on the mental health of children and adolescents in the context of COVID-19. J Am Acad Child Adolesc Psychiatry. 2020 Nov;59(11):1218-1239.e3. Doi:10.1016/j.jaac.2020.05.009. Lasgaard M, Goossens L, Elklit A. Loneliness, depressive symptomatology, and suicide ideation in adolescence: cross-sectional and longitudinal analyses. J Abnorm Child Psychol 2011 Jan;39(1):137–50. Doi:10.1007/s10802-010-9442-x. Vanhalst J, Klimstra TA, Luyckx K, et al. The interplay of loneliness and depressive symptoms across adolescence: exploring the role of personality traits. J Youth Adolesc. 2011 Nov;41(6):776–87. Doi:10.1007/s10964-011-9726-7. Oellingrath IM, Bortoli MMD, Svendsen MV, Fell AKM. Lifestyle and work ability in a general working population in Norway: a cross-sectional study. BMJ Open. 2019 APR;9(4):p.e026215. Doi:10.1136/bmjopen-2018-026215. World Health Organization. Global strategy on diet, physical activity, and health [Internet]. 2004 May [cited 2021 Dec 20]. Available from: WHO | The Global Strategy on Diet, Physical Activity and Health (DPAS) . Miller G, Merlo C, Demissie Z, Sliwa S, Park S. Trends in Beverage Consumption among high school students — United States, 2007-2015. MMWR Morb Mortal Wkly Rep. 2017 Feb;66(4):112–116. Doi: 10.15585/mmwr.mm6604a5external icon . Braithwaite I, Stewart AW, Hancox RJ, Beasley R, Murphy R, Mitchell EA, et al. Fast food consumption and body mass index in children and adolescents: an international cross-sectional study. BMJ Open 2014 Nov;4:e005813 doi:10.1136/bmjopen-2014- 005813. World Health Organization. Global Recommendations on Physical Activity for Health [Internet]. Switzerland. 2010 [cited 2021 Dec 20]. Available from: global-PA-recs-2010.pdf (who.int) . American Academy of Paediatrics. New Recommendations for Children’s Media Use. J Pediatr. 2016 Nov;38(5):e20162592. Doi: 10.1542/peds.2016-2592. Paavola M, Vartiainen E, Puska P. Smoking cessation between teenage years and adulthood. Health Edu Res. 2001 Feb;16(1):p.49-57. Doi: 10.1093/her/16.1.49 Atalay BI, Unal E, Onsuz MF, Isikli B, Yenilmez C, Metintas S. Violence and related factors among high school students in semirural areas of Eskisehir. North Clin Istanb. 2018 Apr;5(2):125-131. Doi: 10.14744/nci.2017.91259. Faria CS and Martins CBG.Violence among adolescent students: conditions of vulnerability [Internet]. Enfermeria Global. 2016 Apr [cited 2021 Dec 20];185-98. Available from: Violence among adolescent students: conditions of vulnerability (studylib.es) Sultana S, Rahman MM, Masahiro H, Sigel B. Associations of lifestyle risk factors with overweight or obesity among adolescents: a multi-country analysis. Am J Clin Nutr. 2021 Mar;113(3):742-750. Doi: 10.1093/ajcn/nqaa337 . Park SH. Smoking and adolescent health. Korean J pediatr. 2011 Oct;54(10):401-404. Doi: 10.3345/kjp.2011.54.10.401 . Panter-Brick C, Eggerman M, Gonzalez V, Safdar S. Violence, suffering, and mental health in Afghanistan: a school-based survey. The Lancet. 2009 Sep;374(9692):807-816. Doi: 10.1016/s0140-6736(09)61080-1 . Dardas L, Bailey DE, Simmons LA. Adolescent depression in the Arab region: a systematic literature review. Issues Ment Health Nurs. 2016 Aug;37(8):569-585. Doi: 10.1080/01612840.2016.1177760 . Schimelpfening N. Why depression is more common in women than in men? [Internet]. Verywell Mind. 2020 Dec [cited 2021 Dec 20]. Available from: Why Depression Is More Common in Women Than in Men (verywellmind.com) Rao TS, Asha MR, Ramesh BN and Rao KS. Understanding nutrition, depression and mental illnesses. Indian J Psychiatry. 2008 Apr;50(2):77-82. Doi:10.4103/0019-5545.42391. Mrug S, Orihuela C, Mrug M, Sanders PW. Sodium and potassium excretion predict increased depression in urban adolescents. Physiol Rep. 2019 Aug;7(16):e14213. Doi: 10.14814/phy2.14213 . Meiklejohn S, Ryan L, Palermo C. A systematic review of the impact of multi-strategy nutrition education programs on health and nutrition of adolescents. J Nutr Educ Behav. 2016 Oct;48(9):631-646. Doi: 10.1016/j.jneb.2016.07.015. Wang D, Stewart D. The implementation and effectiveness of school-based nutrition promotion programmes using a health-promoting schools approach: a systematic review. Public Health Nutr. 2013 Jun;16(6):1082-1100. Doi:10.1017/S1368980012003497. Nystrom MBT, Hassmen P, Sorman DE,Wigforss T, Andersson G, Carlbring P. Are physical activity and sedentary behavior related to depression? Cogent Psychology. 2019 Jul;6(1):1633810. Doi: 10.1080/23311908.2019.1633810. Korczak DJ, Madigan S, ColasantoM. Children's Physical Activity and Depression: A Meta-analysis. Pediatrics. 2017 Apr;139(4):e20162266. Doi: 10.1542/peds.2016-2266. Dworak M, Schierl T, Bruns T, Struder HK. Impact of singular excessive computer game and television exposure on sleep patterns and memory performance of school-aged children. Pediatrics. 2007 Nov;120(5):978-985. Doi:10.1542/peds.2007-0476. United Nations Educational Scientific and Cultural Organization. Behind the numbers: ending school violence and bullying [Internet].France, Paris. 2019 [cited 2021 Dec 20]. Available from: UNESCO_Bullying.pdf (end-violence.org) . O'donnell J. Teens aren't socializing in the real world. And that's making them super lonely [Internet]. USA Today. 2019 Mar [cited 2021 Dec 21]. Available from: Loneliness soars among teens along with social media use, study says (usatoday.com) Quinlan A. How technology and social media is undermining family relationships [Internet]. The Irish Times. 2018 Jul [cited 2021 Dec 21]. Available from: How technology and social media is undermining family relationships (irishtimes.com) Education statistics-All indicators. World Bank group. 2020 Dec [cited 2021 Dec 21]. Available from: Education Statistics - All Indicators | DataBank (worldbank.org) Tables Table 1 Survey characteristics of the Global School-based Student Health Survey datasets for the selected countries. Country 1 (n=20) Survey year Survey sample size (n=83,695) Analysis sample size (n=51,597) Response rate (%) % Boys (95% CI) (n=23,192) Mean age 2 , (years) (95% CI) Prevalence of depression 2 (95% CI) (n=13,635) Afghanistan 2014 2579 1,048 79 56.6 (53.7, 59.7) 15.2 (15.1, 15.3) 49.9 (46.5, 53.2) Bahamas 2013 1357 786 78 45.4 (41.8, 48.9) 13.4 (13.3, 13.5) 31.4 (28.1, 34.9) Bahrain 2016 7141 2,515 89 47.9 (46.0, 49.9) 14.4 (14.4, 14.5) 37.1 (35.2, 39.0) Bangladesh 2014 2989 1,909 91 66.6 (64.2, 68.9) 14.1 (14.2, 14.2) 18.5 (16.1, 21.2) Benin 2016 2536 1,840 78 72.9 (71.0, 74.8) 16.4 (16.3, 16.5) 39.8 (37.3, 42.4) Brunei 2014 2599 1,961 65 49.0 (46.7, 51.4) 14.6 (14.6, 14.7) 23.9 (21.9, 26.0) Cook Islands 2015 701 521 65 48.1 (43.8, 52.4) 15.4 (15.3, 15.6) 29.1 (25.2, 33.2) Fiji 2016 3705 2,432 79 46.2 (44.2, 48.2) 15.8 (15.8, 15.9) 27.6 (25.8, 29.5) Indonesia 2015 11,142 8,251 94 46.5 (45.4, 47.7) 14.0 (14.0, 14.1) 12.9 (12.2, 13.8) Kuwait 2015 3637 2,018 78 50.1 (48.0, 52.3) 15.1 (15.0, 15.2) 37.3 (35.1, 39.5) Laos 2013 3683 2,853 70 53.1 (51.1, 55.1) 15.6 (15.6, 15.7) 11.7 (10.5, 13.1) Mongolia 2013 5393 4,189 88 47.4 (45.9, 49.0) 14.5 (14.5, 14.6) 30.2 (28.8, 31.7) Namibia 2013 4531 2,861 89 46.2 (44.4, 48.1) 15.8 (15.8, 15.9) 43.0 (41.2, 44.9) Nepal 2015 6529 4,189 69 48.7 (47.0, 50.6) 14.4 (14.4, 14.5) 19.8 (18.3, 21.4) Philippines 2015 8761 5,790 79 49.1 (47.8, 50.6) 14.5 (14.6, 14.6) 30.2 (28.9, 31.6) Polynesia 2015 3216 2,298 70 48.2 (46.1, 50.4) 15.1 (15.0, 15.2) 27.1 (25.2, 29.1) Thailand 2015 5894 3,521 89 43.2 (41.1, 45.5) 14.5 (14.5, 14.6) 21.4 (19.7, 23.3) Timor-Leste 2015 3704 1,011 79 53.4 (50.4, 56.5) 15.5 (15.4, 15.6) 32.2 (29.2, 35.3) Tuvalu 2013 943 207 90 42.9 (37.7, 48.4) 13.9 (13.9, 14.1) 18.4 (13.6, 24.3) Yemen 2014 2655 1,397 75 54.5 (51.9, 57.1) 14.9 (14.8, 15.0) 37.3 (34.6, 40.1) Legend: CI: confidence interval 1 Countries with Global School-based Student Health Survey data available for 2013 or later. 2 Descriptive analyses were used to estimate mean age and percentage of depression risk among adolescents. Probability sampling weights were applied in all analyses. Table 2 Development of depression risk variable for adolescents. Variable Components Frequency (Last 1 year) Risk index Risk index range Risk levels 1 Low Moderate High No risk group At risk group Risk of depression 1. Feel lonely 3 Rarely 0 0-8 0-2 2 2 2 -3 4-8 Sometimes 1 Always 2 2. Too worried 3 Rarely 0 Sometimes 1 Always 2 3. Considered suicide 3 Never 0 1 2 4. Attempted suicide 3 Never 0 1 2 Legend: Depression risk variable was developed for adolescents (aged 13–17 years) using the Global School-based Student Health Survey datasets for 20 countries with survey data available for 2013 or later. 1 This method of grouping composite risk indexes to produce risk levels has been used in another study.[23] 2 The composite risk index could equal two 1) if any two of the four components were at moderate risk (0+0+1+1) or 2) if any one of the four components were at high risk (0+0+0+2). The former criterion was included as a low risk index and the latter criterion was included as a moderate risk index. The reason was participants with low risk indexes should not have any component assessed as high risk. 3 Cut-off points were determined based on previous studies. Table 3 Composition of lifestyle and social risk indexes for adolescents. Risk indexes Components Frequency Risk index Risk index range Risk level 1 Low Medium High Dietary habits 1. Fruits, times/d 2 ≥ 3 0 0-8 0-2 6 2 6 -3 4-8 2 1 ≤ 1 2 2. Vegetables, times/d 2 ≥ 3 0 2 1 ≤ 1 2 3. Fast food, d/w 3 ≤ 1 0 ≥ 2 & ≤ 3 1 ≥ 4 2 4. Soft drinks, times/d 3 ≤ 1 0 2 1 ≥ 3 2 Physical activity 1. 60 minutes per day, d/w 4 ≥ 6 0 0-2 0 1 2 ≥ 3 & ≤ 5 1 ≤ 2 2 Sedentary behavior 1. Daily sedentary time, h/d 5 < 1 0 0-2 0 1 2 ≥ 1 & < 4 1 ≥ 4 2 Tobacco use 1. Cigarette, days last month 3 ≤ 2 0 0-4 0 1 2-4 ≥ 3 & ≤ 19 1 ≥ 20 2 2. Other tobacco products, days last month 3 ≤ 2 0 ≥ 3 & ≤ 19 1 ≥ 20 2 Exposure to school violence 1. Physically attacked, times last year 3 0 0 0-8 0-2 6 2 6 -3 4-8 ≥ 1 & ≤ 2 1 ≥ 3 2 2. Physical fight, times last year 3 0 0 ≥ 1 & ≤ 2 1 ≥ 3 2 3. Seriously injured, times last year 3 0 0 ≥ 1 & ≤ 2 1 ≥ 3 2 4. Bullied, days last month 3 0 0 ≥ 1 & ≤ 2 1 ≥ 3 2 Interactions with parents 1. Missed school without permission, days last month 3 0 0 0-4 0 1-2 3-4 ≥ 1 & ≤ 2 1 ≥ 3 2 2. Parents understand problems, times last month 3 Always 0 Sometimes 1 Rare 2 Interactions with friends 1. Students being helpful, times last month 3 Always 0 0-4 0 1-2 3-4 Sometimes 1 Rare 2 2. Number of close friends 3 2 0 1 1 0 2 Legend: Risk indexes were developed for adolescents (aged 13–17 years) using the Global School-based Student Health Survey datasets for 20 countries with survey data available for 2013 or later. 1 This method of grouping risk indexes to produce risk levels was used in another study.[23] 2 2006 World Health Organization dietary guidelines.[24] 3 Based on previous studies. 4 2010 World Health Organization physical activity guidelines.[27] 5 American Association of Pediatrics’ 2016 recommendation on screen time for adolescents.[28] 6 The composite risk indexes could equal two 1) if any two of the four components were at moderate risk (0+0+1+1) or 2) if any one of the four components were at high risk (0+0+0+2). The former criterion was included as a low risk index and the latter criterion was included as a moderate risk index. The reason was participants with low risk indexes should not have any component assessed as high risk. Table 4 Associations between lifestyle and social risk indexes and risk of depression among adolescents. Risk indexes Total sample (n=51,597) Boys (n=23,192) Girls (n=28,405) OR (95% CI) P for trend OR (95% CI) P for trend OR (95% CI) P for trend Unhealthy dietary habit 1 <0.001 0.184 <0.001 Low 1 1 1 Moderate 1.13 (1.05, 1.22) 1.08 (0.97, 1.21) 1.17 (1.07, 1.29) High 1.15 (1.07, 1.23) 1.09 (0.98, 1.21) 1.20 (1.10, 1.31) Physical inactivity 2 0.114 0.055 0.934 Low 1 1 1 Moderate 1.03 (0.96, 1.11) 1.02 (0.93, 1.13) 1.03 (0.93, 1.14) High 1.04 (0.98, 1.10) 1.07 (0.99, 1.17) 1.00 (0.92, 1.09) Unhealthy sedentary behavior 3 <0.001 <0.001 <0.001 Low 1 1 1 Moderate 1.06 (1.01, 1.11) 0.98 (0.91, 1.06) 1.12 (1.04, 1.19) High 1.53 (1.43, 1.63) 1.33 (1.21, 1.47) 1.65 (1.51, 1.80) Tobacco use 4 <0.001 <0.001 <0.001 Low 1 1 1 Moderate 1.65 (1.46, 1.86) 1.49 (1.28, 1.73) 2.14 (1.73, 2.65) High 1.57 (1.41, 1.76) 1.44 (1.26, 1.64) 2.54 (2.01, 3.22) Exposure to school violence 5 <0.001 <0.001 <0.001 Low 1 1 1 Moderate 1.79 (1.69, 1.90) 1.58 (1.45, 1.73) 2.07 (1.90, 2.25) High 3.06 (2.88, 3.26) 2.83 (2.61, 3.07) 3.40 (3.10, 3.73) Insufficient interaction with parents 6 <0.001 <0.001 <0.001 Low 1 1 1 Moderate 1.17 (1.12, 1.23) 1.16 (1.08, 1.25) 1.18 (1.11, 1.26) High 2.09 (1.92, 2.28) 2.33 (2.05, 2.65) 1.95 (1.74, 2.19) Insufficient interaction with friends 7 <0.001 <0.001 <0.001 Low 1 1 1 Moderate 1.39 (1.32, 1.47) 1.21 (1.12, 1.32) 1.51 (1.41, 1.62) High 1.82 (1.69, 1.96) 1.39 (1.25, 1.55) 2.24 (2.03, 2.48) Notes: OR: odds ratio; CI: confidence interval. Multilevel logistic regression models were used to estimate the ORs and corresponding 95% CIs. The total sample analysis was adjusted for age, sex, socioeconomic status, and national literacy rate. The subgroup analyses used the same model and was adjusted for age, socioeconomic status, and national literacy rate. 1 Unhealthy dietary habit considered intake of fruits, vegetables, fast food, and soft drinks. 2 Low risk of physical inactivity for adolescents was defined as engaging in vigorous physical activity for at least 1 hour 6 days per week. 3 Low risk of unhealthy sedentary behavior for adolescents was defined as having less than 1 hour of screen time per day. 4 Low risk of tobacco use for adolescents was defined as using cigarettes or any other form of tobacco on fewer than 3 days last month. 5 Exposure to school violence considered physical attack, fight, injury, and bulling. 6 Interactions with parents considered frequency of missing school without permission and participants think their parents understand problems. 7 Interactions with friends considered number of close friends and if participants found their classmates kind and helpful. Additional Declarations No competing interests reported. Supplementary Files supplementaryfigure1.docx supplementarytable1.docx supplementarytable2.docx supplementarytable3.docx supplementarytable4.docx Cite Share Download PDF Status: Posted Version 1 posted 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-1402117","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":89502572,"identity":"88a2cd53-bcce-410f-b781-d65ae6c8cabd","order_by":0,"name":"Sabera Sultana","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyUlEQVRIiWNgGAWjYNACA4l6fgYGNpK0WCRINpCmhaEiweAAsVrkZ+Q+/MxTIJFnfCP52YMPFQzy/GIHCDjpRrqxNI+BRLHZjTRzwxlnGAxnzk4goEUijUFyhoEE47YbCWbSvG0MCQa3CWiRn5HG/BOkZfOM9G/EaWG4kcYm8cFAInGDRA6RthicecZmAdRiLHHmTZnkjDMShP0i357GfCPhT50cf3v6NokPFTby/NKEHAYHAmCVEsQqBwH+A6SoHgWjYBSMgpEEAC+zPOZXXEeaAAAAAElFTkSuQmCC","orcid":"","institution":"The University of Tokyo","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Sabera","middleName":"","lastName":"Sultana","suffix":""},{"id":89502573,"identity":"9d3e270c-8459-4f18-b569-e9854e6e7901","order_by":1,"name":"Md. Mizanur Rahman","email":"","orcid":"","institution":"The University of Tokyo","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Md.","middleName":"Mizanur","lastName":"Rahman","suffix":""},{"id":89502574,"identity":"79609df9-87f7-48d4-9569-fa0a53e8db73","order_by":2,"name":"Masahiro Hashizume","email":"","orcid":"","institution":"The University of Tokyo","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Masahiro","middleName":"","lastName":"Hashizume","suffix":""}],"badges":[],"createdAt":"2022-02-28 02:44:02","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1402117/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1402117/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":19136393,"identity":"bf09522e-4cdb-4b0c-a5ed-a84fde958947","added_by":"auto","created_at":"2022-03-11 16:35:17","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":4543372,"visible":true,"origin":"","legend":"\u003cp\u003ePrevalence of lifestyle and social risk indexes among adolescents by country.\u003c/p\u003e\u003cp\u003eSubtitles:\u003c/p\u003e\u003cp\u003eA.\u0026nbsp;\u0026nbsp;\u0026nbsp;Unhealthy dietary habits\u0026nbsp;\u0026nbsp;\u003c/p\u003e\u003cp\u003eB.\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;Insufficient physical activity\u003c/p\u003e\u003cp\u003eC.\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;Unhealthy sedentary behavior\u003c/p\u003e\u003cp\u003eD.\u0026nbsp;\u0026nbsp;\u0026nbsp;Tobacco use\u003c/p\u003e\u003cp\u003eE.\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;Exposure to school violence\u003c/p\u003e\u003cp\u003eF.\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;Insufficient interactions with parents\u003c/p\u003e\u003cp\u003eG.\u0026nbsp;\u0026nbsp;\u0026nbsp;Insufficient interactions with friends\u003c/p\u003e\u003cp\u003eColour legend:\u003c/p\u003e\u003cp\u003e\u0026nbsp;\u003c/p\u003e\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp;\u003c/p\u003e\u003cp\u003e\u0026nbsp;\u003c/p\u003e\u003cp\u003en/Country: 1048/Afghanistan, 786/The Bahamas, 2515/Bahrain, 1909/Bangladesh, 1840/Benin, 1961/Brunei, 521/The Cook Islands, 2432/Fiji, 2298/ Polynesia, 8251/Indonesia, 2018/ Kuwait, 2853/Laos, 4189/Mongolia, 2861/Namibia, 4189/ Nepal, 5790/The Philippines, 3521/Thailand, 1011/Timor-Leste, 207/Tuvalu, 1397/Yemen.\u003c/p\u003e\u003cp\u003e\u0026nbsp;\u003c/p\u003e\u003cp\u003eSelection and sequence of the countries: Countries with Global School-based Student Health Survey data available for 2013 or later were included. Countries have been arranged in graph by the prevalence of high-risk index from the largest to the smallest.\u003c/p\u003e\u003cp\u003e\u0026nbsp;\u003c/p\u003e\u003cp\u003eDescriptive analyses were used to estimate medium and high-risk proportions. Probability sampling weights were applied in all analyses.\u003c/p\u003e","description":"","filename":"fig.png","url":"https://assets-eu.researchsquare.com/files/rs-1402117/v1/5364631da853b36938c3c024.png"},{"id":21372026,"identity":"26a32921-a18d-4b66-998b-80230a994e5f","added_by":"auto","created_at":"2022-05-12 06:44:23","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1169026,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1402117/v1/c39df709-e9ff-44e1-a57b-9362b64db8c6.pdf"},{"id":19136388,"identity":"72331aa2-2528-47ed-9d19-84659bcfedc7","added_by":"auto","created_at":"2022-03-11 16:35:17","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":18983,"visible":true,"origin":"","legend":"","description":"","filename":"supplementaryfigure1.docx","url":"https://assets-eu.researchsquare.com/files/rs-1402117/v1/4bf321c8d0c52c14df1f8ae1.docx"},{"id":19136958,"identity":"b423a5cc-ffb6-4bd5-82c4-c5afdb07f91e","added_by":"auto","created_at":"2022-03-11 16:41:17","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":13301,"visible":true,"origin":"","legend":"","description":"","filename":"supplementarytable1.docx","url":"https://assets-eu.researchsquare.com/files/rs-1402117/v1/9d984252bd8bf37fa920dec8.docx"},{"id":19136392,"identity":"c1de922b-5daa-4115-9cf7-1f86bf35e0c9","added_by":"auto","created_at":"2022-03-11 16:35:17","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":16675,"visible":true,"origin":"","legend":"","description":"","filename":"supplementarytable2.docx","url":"https://assets-eu.researchsquare.com/files/rs-1402117/v1/f997b413098a4d0c8fecdd4d.docx"},{"id":19136774,"identity":"b04fdb88-a0a0-4a08-bf4e-9887663076eb","added_by":"auto","created_at":"2022-03-11 16:38:17","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":16693,"visible":true,"origin":"","legend":"","description":"","filename":"supplementarytable3.docx","url":"https://assets-eu.researchsquare.com/files/rs-1402117/v1/385c337c5468f550015442b9.docx"},{"id":19136391,"identity":"1748dd9d-0d0b-43ef-b9f0-56885c6d5f14","added_by":"auto","created_at":"2022-03-11 16:35:17","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":18129,"visible":true,"origin":"","legend":"","description":"","filename":"supplementarytable4.docx","url":"https://assets-eu.researchsquare.com/files/rs-1402117/v1/14d52e44d1ab372fd5bd51a1.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Comprehensive assessment of depression risk and its behavioral determinants among adolescents: a multi-country study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe global prevalence of depression among adolescents is increasing internationally,[1] with an increase of 18% between 2005 and 2015.[2]\u0026nbsp;Because of stark differences between countries, depression was traditionally considered to be a problem that primarily affected first world countries. However, recent studies have reported that most countries have relatively similar rates of depression, but social stigma, lack of data availability, and non-recognition of mental illness are more common in developing countries.[3-4] Previous research indicated that the regions with the highest rates of depression were eastern Europe, North Africa and the Middle East, and, by country, the highest number of years lost because of depression-related disability was in Afghanistan.[4]\u003c/p\u003e\n\u003cp\u003eMental health conditions account for 16% of the global burden of disease and injury in people 10\u0026ndash;19 years of age.[5] Depression is the leading cause of global disability, and unipolar depression is the 10th leading cause of early death.[5]\u003csup\u003e\u0026nbsp;\u003c/sup\u003eA clear link has been established between depression and suicide, which is the third leading cause of death for young people aged 15\u0026ndash;29 years.[5]\u0026nbsp;Depression not only affects psychological health but also increases the risk of cardiovascular disease, diabetes and cancer.[6-7]\u003csup\u003e\u0026nbsp;\u003c/sup\u003eDepression can also lead to serious social and educational impairments, smoking, substance abuse, and obesity among adolescents.[8-11]\u0026nbsp;Moreover, depression takes an economic toll on individuals, families, organizations, and society. On the basis of data from 2010,\u0026nbsp;the World Economic Forum estimated that the combined direct and indirect cost of mental disorders was US$2.5 trillion, and this cost is predicted to reach US$6.1 trillion by 2030.[12]\u003c/p\u003e\n\u003cp\u003eDepression results from complex interactions between social, psychological, and biological factors.\u003csup\u003e\u0026nbsp;\u003c/sup\u003eIncreased access to and use of technology, peer and family relationships, quality of home life, unhealthy lifestyle behavior, violence and socioeconomic problems, and poor physical health are recognized as risk factors for adolescent depression.[5,13-15] Although adolescent depression is treatable, it often remains untreated because of difficulty in diagnosis and a lack of treatment services.[5,16] Between 76% and 85% of people with depression in low- and middle-income countries receive no treatment for their disorder.[16] In 2018, the American Academy of Pediatrics recommended regular depression screening for all adolescents 12 and over.[17] Early\u0026nbsp;recognition of the risk of depression\u0026nbsp;and identification of modifiable risk factors is critically needed to reduce the burden of depression.\u003c/p\u003e\n\u003cp\u003eTherefore, the current study aimed to develop a depression risk index by combining several psychological signs of adolescent depression, providing a quick and comprehensive tool for self-screening of depression risk. Furthermore, we generated risk indexes for potential lifestyle and social risk factors of depression among adolescents using cross-country data and assessed their relationships with depression risk index values. These findings will provide guidelines to reduce the risk of depression among adolescents through lifestyle and social behavioral modifications.\u003c/p\u003e"},{"header":"Methods","content":"\u003ch2\u003e\u003cstrong\u003eData sources\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eWe used data from the Global School-based Student Health Survey (GSHS) for this study. The data were downloaded from the Centers for Disease Control and Prevention (CDC) website (CDC Global School-based Student Health Survey (GSHS)). All countries with data available for 2013 or later were included, resulting in a total of 20 countries. For each country, we used only the latest available dataset in the study period. The GSHS used a two-stage cluster design to produce a nationally representative sample of all students enrolled in grades 7 to 11. The participants\u0026rsquo; ages ranged from 13 to 17 years. In the first stage of sampling, schools were selected with probability proportional to student enrollment. In the second stage, systematic random sampling was used to select classes from each sampled school. All students in the selected classes were eligible to participate. Survey procedures were designed to protect students\u0026rsquo; privacy by allowing for anonymous and voluntary participation. Details survey procedure of GSHS is available on WHO\u0026rsquo;s website (Bangladesh - Global School-Based Student Health Survey 2014 (who.int)).[\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e] Participants who had missing values for any variable of interest were excluded from the study. The basic survey characteristics of the GSHS datasets are presented in \u003cstrong\u003eTable\u0026nbsp;1\u003c/strong\u003e. We used the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines for reporting. Because we used secondary data, public and patient involvement was not possible. Our study was exempted by the ethics committee of the university of Tokyo as we employed secondary data that are available for public use.\u003c/p\u003e\n\u003cp\u003eLegend:\u003c/p\u003e\n\u003cp\u003eCI: confidence interval\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003e Countries with Global School-based Student Health Survey data available for 2013 or later.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2\u003c/sup\u003e Descriptive analyses were used to estimate mean age and percentage of depression risk among adolescents. Probability sampling weights were applied in all analyses.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eOutcome variable\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe outcome variable in this study was the risk of depression among adolescents. According to the CDC, anxiety and self-harming behaviors, including suicide, are common depressive symptoms among adolescents.[\u003cspan class=\"CitationRef\"\u003e19\u003c/span\u003e] Another previous study reported that approximately 50% of all people diagnosed with depression are also diagnosed with anxiety disorder.[\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e] Moreover, one study reported that young people who are lonely are as much as three times more likely to develop depression in the future, and this finding was supported by subsequent studies.[\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e] Hence, we considered four components while developing a depression risk index for adolescents: frequency of anxiety, loneliness, thoughts of suicide, and suicide attempts in the last 1 year. Anxiety and loneliness had three cut-off points while thoughts of or attempts of suicide had two cutoff points because suicide was a severe indicator of depression.\u003c/p\u003e\n\u003cp\u003eOne risk score corresponded to each cut-off point. Risk scores ranged from healthy (0) to unhealthy (2). The risk scores for each component were combined to produce a risk score range for each risk index. The risk score range was then categorized into three risk levels.[\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e] Lower risk index values represented lower risk levels, whereas higher risk index values represented higher risk levels. \u003cstrong\u003eTable\u0026nbsp;2\u003c/strong\u003e shows the components and composition of the depression risk index.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eExposure variables\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eFour risk indexes were developed for four lifestyle risk factors: dietary habits, physical activity, sedentary behavior and tobacco use. Three risk indexes were developed for three social risk factors: exposure to school violence, interactions with parents, and interactions with friends. These risk indexes were considered as the primary exposure variables in this study. The dietary risk index included four components: fruit, vegetables, fast foods, and carbonated soft drinks. Cut-off points were determined using World Health Organization (WHO) guidelines where available, or in accordance with previous literature.[\u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e] To determine the risk index for physical activity, we used the WHO guidelines, which categorized adolescents as physically active if they were involved in vigorous physical movement for at least 60 minutes each day.[\u003cspan class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/p\u003e\n\u003cp\u003eThe risk index for sedentary behavior was generated using the amount of time each day participants spent watching television, looking at tablets, or playing video games. We used the American Association of Pediatrics\u0026rsquo; recommendations for adolescent media use to set the cut-off points for different risk levels of unhealthy sedentary behavior.[\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e] The tobacco use risk index was developed using two components: cigarette smoking and the use of any other tobacco products. For adolescents, there are no safe limits, and there are no clear guidelines for classifying the use of tobacco products. We defined occasional, irregular, and frequent users of tobacco following a previous study and assigned three risk levels.[\u003cspan class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/p\u003e\n\u003cp\u003eThe risk index for exposure to school violence was developed using four components: physical attacks, fights, injuries, and bullying.[\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e] The risk index for interactions with parents was developed considering two components: how frequently participants missed school without permission and how often they felt that their parents understood their problems. The risk index for interactions with friends was generated using two components: how frequently participants found their classmates to be kind and helpful, and the number of close friends they had. \u003cstrong\u003eTable\u0026nbsp;3\u003c/strong\u003e shows the components and composition of these risk indexes.\u003c/p\u003e\n\u003cp\u003eDetailed information regarding the four lifestyle risk indexes (dietary habits, physical activity, sedentary behavior and tobacco use) were provided elsewhere.[\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eCovariates\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eCovariates included the student\u0026rsquo;s age (13\u0026ndash;17 years), sex (boys or girls), and the experience of hunger in the past 30 days (never, rarely, sometimes, most of the time, or always), as well as the national literacy rate. Consistent with a previous study, the frequency of hunger because of insufficient food at home in the past 30 days was treated as a proxy variable for socioeconomic status.[\u003cspan class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eData analyses\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eWe used Cronbach\u0026rsquo;s alpha to assess the internal reliability of the risk indexes (\u003cstrong\u003esupplementary table 1\u003c/strong\u003e). A descriptive analysis was performed to estimate summary statistics such as means, percentages, and 95% confidence interval (CIs). Following previous studies, we used multilevel logistic regression models to estimate odds ratios (ORs) and corresponding 95% CIs to assess the relationships between depression risk and its behavioral determinants among adolescents.[\u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e] Let \u003cem\u003ej\u003c/em\u003e denote the level-two units (countries) and let \u003cem\u003ei\u003c/em\u003e denote the level-one units (items or observations). Assume that there are \u003cem\u003ej\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1, 2, ..., C countries and \u003cem\u003ei\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1, 2, \u0026hellip;, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({N}_{j}\\)\u003c/span\u003e\u003c/span\u003e individuals in each country. The multilevel regression model can be written as\u003c/p\u003e\n\u003cdiv class=\"Equation\" id=\"Equa\"\u003e\n \u003cdiv class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e$$\\text{log}\\left(\\frac{{\\pi }_{ij}}{1-{\\pi }_{ij}}\\right)= {y}_{ij} = {X}_{ij}\\beta + {Z}_{j}\\gamma + {u}_{j} + {\\epsilon }_{ij}$$\u003c/div\u003e\n\u003c/div\u003e\n\u003cp\u003e,\u003c/p\u003e\n\u003cp\u003ewhere outcome \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({y}_{ij}\\)\u003c/span\u003e\u003c/span\u003e for each adolescent \u003cem\u003ei\u003c/em\u003e in country \u003cem\u003ej\u003c/em\u003e is assumed to depend on both observed predictors and unobserved factors, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({y}_{ij}\\)\u003c/span\u003e\u003c/span\u003e is the log odds of adolescent \u003cem\u003ei\u003c/em\u003e in country, and \u003cem\u003ej\u003c/em\u003e being overweight or obese. \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\beta\\)\u003c/span\u003e\u003c/span\u003e represents a vector of regression coefficients associated with the individual-level variables \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({X}_{ij}\\)\u003c/span\u003e\u003c/span\u003e. These individual-level characteristics were the seven risk scores, age, gender, and socioeconomic status. \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({Z}_{j}\\)\u003c/span\u003e\u003c/span\u003e contains variables summarizing the country-level characteristics such as the literacy rate in the study context. Unobserved individual effects are represented as \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\epsilon }_{ij}\\)\u003c/span\u003e\u003c/span\u003e, and country effects are represented as \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({u}_{j}\\)\u003c/span\u003e\u003c/span\u003e. In the multilevel model, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\epsilon }_{ij}\\)\u003c/span\u003e\u003c/span\u003e and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({u}_{j}\\)\u003c/span\u003e\u003c/span\u003eare assumed to be normally distributed and uncorrelated individual-level (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({X}_{ij}\\)\u003c/span\u003e\u003c/span\u003e) and country-level (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({Z}_{j}\\)\u003c/span\u003e\u003c/span\u003e) predictors. The parameters associated with the observed predictors \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\beta\\)\u003c/span\u003e\u003c/span\u003e and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\gamma\\)\u003c/span\u003e\u003c/span\u003e are fixed regression parameters. Parameters \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\epsilon }_{ij}\\)\u003c/span\u003e\u003c/span\u003e and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({u}_{j}\\)\u003c/span\u003e\u003c/span\u003e are treated as random terms. Stata/SE 15.0 (StataCorp, College Station, TX, USA) was used in this study for data management, statistical analysis, and graph generation. Probability sampling weights were applied in all descriptive analyses.\u003c/p\u003e"},{"header":"Results","content":"\u003ch2\u003e\u003cstrong\u003eSample characteristics\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eA total of 83,695 adolescents aged 13\u0026ndash;17 years were surveyed. Participants with missing values for any of the variables of interest were excluded from the analysis. This resulted in an analytical sample size of 51,597, representing a total adolescent population of 22,945,384 individuals, after applying the sampling weights. As shown in Table\u0026nbsp;1, 45% of the participants were boys, and the mean age was 14.8 years.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eCountry-specific scenarios of depression risk\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eAs shown in Table 1, 26.4% of adolescents had risk of depression. The highest proportion of adolescents with a risk of depression was found in Afghanistan (50%), followed by Namibia (43%), Benin (40%), Kuwait (37%), Bahrain (37%), Yemen (37%), and Timor-Leste (32%). The lowest prevalence of depression risk was reported in Laos (12%) followed by Indonesia (13%) and Bangladesh (18%). \u003cstrong\u003eSupplementary Fig.\u0026nbsp;1\u003c/strong\u003e shows that depression risk among girls was highest in Afghanistan (59%), followed by Kuwait (44%), Bahrain (43%), Benin (43%), Yemen (42%), the Bahamas (36%), Mongolia (35%), and the Philippines (34%). In the countries included in this study, the risk of depression was reported to be higher among girls than among boys, except in Timor-Leste (boys: 26%; girls: 12%).\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eCountry-specific scenarios of lifestyle and social risk indexes\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003e\u003cstrong\u003eFigure 1\u003c/strong\u003e shows the percentage of lifestyle and social risk indexes among adolescents in each country. The prevalence of unhealthy (moderate and high risk) dietary habits ranged from 77% (the Cook Islands) to 94% (Timor-Leste, Mongolia, Nepal). The highest percentage of physical inactivity was observed in the Philippines (91%) followed by Thailand (87%), Timor-Leste (87%), Tuvalu (86%), Indonesia (85%), and Brunei (85%), whereas the lowest percentage was seen in Bangladesh (48%). The prevalence of unhealthy (moderate and high risk) sedentary behavior varied from 34% (Nepal) to 88% (Kuwait). The prevalence of high-risk unhealthy sedentary behavior (daily sedentary time\u0026thinsp;\u0026ge;\u0026thinsp;4 hours) was highest in Kuwait (42.0%), followed by Bahrain (37.2%), the Bahamas (34.4%), Thailand (31.1%), and Brunei (27.3%). Approximately 15% of adolescents in Kuwait, Bahrain, and Polynesia used tobacco. In the other countries in this study, less than 10% of adolescents reported using tobacco.\u003c/p\u003e\n\u003cp\u003eOverall, 27% of the participants were exposed to school violence (moderate and high risk). The prevalence of exposure to school violence (moderate and high risk) varied from 7% (Laos) to as high as 47% (Tuvalu). Around 25% adolescents in Nepal and Tuvalu, and around 20% adolescents in Namibia, Afghanistan, the Philippines, Timor-Leste, Yemen, and Bangladesh reported a high risk of exposure to school violence. Furthermore, 71% of participants had insufficient interactions with parents (moderate and high risk). The prevalence of insufficient interactions with parents (moderate and high risk) was lowest in Nepal (56%) and highest in Timor-Leste (93%). Around 20% adolescents in Bahrain, Kuwait, Timor-Leste, Laos, Tuvalu, Yemen, Brunei, and the Philippines had a high risk of insufficient interactions with parents. 62% of participants had insufficient interactions with friends (moderate and high risk). The highest proportions of adolescents with insufficient interactions with friends (moderate and high risk) were observed in Benin and Laos (82%) and the lowest proportion was observed in Bahrain (37%). Around 17% adolescents in Tuvalu, Namibia, Afghanistan, and Benin reported a high risk of insufficient interactions with friends.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eGender-based lifestyle factors and social risk index values\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe prevalence of unhealthy dietary habits was similar for boys and girls, but in most examined countries, girls were 5\u0026ndash;20% more physically inactive than boys. The largest gender differences in physical inactivity were observed in Laos (boys: 73% vs. girls: 91%), followed by Brunei (boys: 78% vs. girls: 93%), Polynesia (boys: 69% vs. girls: 84%), the Cook Islands (boys: 69% vs. girls: 84%), and Thailand (boys: 78% vs. girls: 94%). See \u003cstrong\u003esupplementary table 2\u003c/strong\u003e, available online, for gender-specific prevalence of unhealthy dietary habits and insufficient physical activity by country. No gender-based differences were found in sedentary behavior, except in Bahrain, where the percentage of unhealthy sedentary behavior was substantially higher among girls than among boys (boys: 77% vs. girls: 91%). The use of tobacco was higher among boys (10%) than that among girls (3%), except in Polynesia, where the percentage of tobacco use was much higher among girls than that among boys (boys: 11% vs. girls: 18%). Significant gender differences in tobacco use were found in Bahrain (boys: 25% vs. girls: 4%), Kuwait (boys: 22% vs. girls: 6%), and Timor-Leste (boys: 18% vs. girls: 4%). See \u003cstrong\u003esupplementary table 3\u003c/strong\u003e, available online, for gender-specific prevalence of unhealthy sedentary behavior and tobacco use by country.\u003c/p\u003e\n\u003cp\u003eThe prevalence of exposure to school violence was 5\u0026ndash;15% higher among boys than that among girls across countries. The largest gender differences in exposure to school violence were found in Mongolia (boys, 38.0% vs girls, 14.0%), followed by Tuvalu (boys, 62.0% vs girls, 34.0%), Thailand (boys, 30.0% vs girls, 13.0%), Kuwait (boys, 37.0% vs girls, 22.0%), Yemen (boys, 47.0% vs girls, 19.0%), and Bahrain (boys, 42.0% vs girls, 21.0%). The prevalence of insufficient interactions with parents was higher among boys than that among girls. Major gender differences for insufficient interactions with parents were observed in Bangladesh (boys, 67.7% vs girls, 57.2%), Benin (boys, 76.0% vs girls, 69.4%), Fiji (boys, 63.0% vs girls, 55.2%), Mongolia (boys, 78.7% vs girls, 71.6%), and Afghanistan (boys, 55.4% vs girls, 40.7%). There were no gender-specific differences in the prevalence of insufficient interactions with friends. Significant gender differences in insufficient interactions with friends were observed in Bangladesh (boys, 53.0% vs girls, 63.4%), the Cook Islands (boys, 50.3% vs girls, 57.4%), Indonesia (boys, 66.0% vs girls, 57.0%), Tuvalu (boys, 80.0% vs girls, 70.0%), Thailand (boys, 69.4% vs girls, 56.3%), Bahrain (boys, 41.4% vs girls, 32.0%), and Yemen (boys, 71.0% vs girls, 63.0%). See \u003cstrong\u003esupplementary table 4\u003c/strong\u003e, available online, for gender-specific prevalence of exposure to school violence and insufficient interactions with parents and friends by country.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eAssociations between the risk of depression and lifestyle and social risk index values\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eA multilevel logistic regression analysis was performed to determine the associations between the four lifestyle and three social risk indexes and the risk of depression among adolescents. Total and gender specific ORs with 95% CIs for overweightor obese status in relation to different lifestyle risk scores are presented in \u003cstrong\u003eTable 4\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003eRegarding the dietary risk index, the odds of depression risk were 15% (OR\u0026thinsp;=\u0026thinsp;1.15; 95% CI, 1.07\u0026ndash;1.23) higher for participants with high risk index values compared with those with a low dietary risk index. However, for total samples and each subgroup, there were no significant associations between physical inactivity and the risk of depression. Regarding unhealthy sedentary behavior, participants with high risk index values had 53% (OR\u0026thinsp;=\u0026thinsp;1.53; 95% CI, 1.43\u0026ndash;1.63) higher odds of depression risk than those with a low risk score for unhealthy sedentary behavior. The association between unhealthy sedentary behavior and depression risk was stronger among girls (OR\u0026thinsp;=\u0026thinsp;1.65; 95% CI, 1.51\u0026ndash;1.80) than among boys (OR\u0026thinsp;=\u0026thinsp;1.33; 95% CI, 1.21\u0026ndash;1.47). Participants with moderate and high risk scores for tobacco use had 65% (OR\u0026thinsp;=\u0026thinsp;1.65; 95% CI, 1.46\u0026ndash;1.86) and 57% (OR\u0026thinsp;=\u0026thinsp;1.57; 95% CI, 1.41\u0026ndash;1.76) higher odds of depression risk, respectively, compared with those with a low risk score of tobacco use. The association between tobacco use and depression risk was stronger among girls (OR\u0026thinsp;=\u0026thinsp;2.54; 95% CI, 2.01\u0026ndash;3.22) than among boys (OR\u0026thinsp;=\u0026thinsp;1.44; 95% CI, 1.26\u0026ndash;1.64).\u003c/p\u003e\n\u003cp\u003eCompared with participants with a low risk score of exposure to school violence, those with moderate (OR\u0026thinsp;=\u0026thinsp;1.79; 95% CI, 1.69\u0026ndash;1.90) or high (OR\u0026thinsp;=\u0026thinsp;3.06; 95% CI, 2.88\u0026ndash;3.26) risk scores of exposure to school violence had higher odds of depression risk. Participants with high risk scores for insufficient interactions with parents (OR\u0026thinsp;=\u0026thinsp;2.09; 95% CI: 1.92\u0026ndash;2.28) and friends (OR\u0026thinsp;=\u0026thinsp;1.82; 95% CI: 1.69\u0026ndash;1.96) showed higher odds of depression risk than those with low risk scores of insufficient interactions with parents and friends, respectively. Associations between insufficient interactions with parents and depression risk were stronger among boys (OR\u0026thinsp;=\u0026thinsp;2.33; 95% CI: 2.05\u0026ndash;2.65) than among girls (OR\u0026thinsp;=\u0026thinsp;1.95; 95% CI: 1.74\u0026ndash;2.19), whereas associations between insufficient interactions with friends and depression risk were stronger among girls (OR\u0026thinsp;=\u0026thinsp;2.24; 95% CI: 2.03\u0026ndash;2.48) than among boys (OR\u0026thinsp;=\u0026thinsp;1.39; 95% CI: 1.25\u0026ndash;1.55).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe aim of the current study was to provide a comprehensive assessment of depression risk and its behavioral determinants (unhealthy dietary habits, physical inactivity, unhealthy sedentary behavior, tobacco use, exposure to school violence, insufficient interactions with parents, and insufficient interactions with friends) among adolescents under 18 years of age. The results revealed that the prevalence of depression risk and unhealthy lifestyle and social behaviors was relatively high, although it varied widely by country and gender. Multilevel analyses showed that, except for insufficient physical activity, having higher risk scores for lifestyle and social behavior increased adolescents\u0026rsquo; odds of depression risk.\u003c/p\u003e\n\u003cp\u003eThe current results revealed that more than one in every four adolescents was at risk of depression. We found that Afghanistan had the highest prevalence of adolescent depression risk, which was in line with a previous study reporting that depression rate was highest among Afghan adults.[\u003cspan class=\"CitationRef\"\u003e5\u003c/span\u003e] War and conflict, domestic violence, child sexual abuse, poverty, and unavailability of adolescent counselling services could be contributing factors for high depression risk in Afghanistan.[\u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e] The current study found a high prevalence of depression risk in Middle Eastern countries (Kuwait, Bahrain, and Yemen), in accord with the results of a previous study.[\u003cspan class=\"CitationRef\"\u003e36\u003c/span\u003e] Developmentally and culturally appropriate community-based detection efforts may be helpful for addressing depression among adolescents in Arab countries.[\u003cspan class=\"CitationRef\"\u003e36\u003c/span\u003e] In the current study, the prevalence of depression risk was higher among girls (28%) than among boys (23%), in accord with the findings of several previous studies.[\u003cspan class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e36\u003c/span\u003e] Social roles, socialization differences, coping style, and response to stressful life events have been reported to make girls more vulnerable to depression than boys.[\u003cspan class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/p\u003e\n\u003cp\u003eThe current study revealed that four out of five adolescents exhibited unhealthy dietary habits, and this increased the odds of depression risk among girls, although there was no significant association among boys. A previous study also found a positive association between unhealthy dietary habits and the risk of depression.[\u003cspan class=\"CitationRef\"\u003e38\u003c/span\u003e] There are several potential pathways of influence between unhealthy dietary habit and depression. For example, people who consume foods that are high in sodium and low in potassium are more likely to develop symptoms of depression.[\u003cspan class=\"CitationRef\"\u003e39\u003c/span\u003e] Furthermore, a lack of amino acids and zinc in the diet may cause depression because of enhanced levels of serotonin and dopamine in the body.[\u003cspan class=\"CitationRef\"\u003e38\u003c/span\u003e] These findings suggest that countries should reconsider their existing policies and initiate programs for promoting healthy dietary habits among adolescents. For example, several studies have found that school-based nutrition education programs increase healthy eating habits, including more fresh fruit and vegetable consumption.[\u003cspan class=\"CitationRef\"\u003e40\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e41\u003c/span\u003e] Thus, school-based nutrition education programs might provide a useful tool for improving dietary habits among adolescents.\u003c/p\u003e\n\u003cp\u003eThe current study revealed no significant associations between physical inactivity and depression risk among adolescents, which was similar to previously reported findings.[\u003cspan class=\"CitationRef\"\u003e42\u003c/span\u003e] Although another previous study found that physical activity played a protective role against depression among adolescents.[\u003cspan class=\"CitationRef\"\u003e43\u003c/span\u003e] Therefore, further research into this issue may be valuable.\u003c/p\u003e\n\u003cp\u003eThe current results revealed that two out of three adolescents exhibited an unhealthy level of sedentary behavior, which increased the odds of depression risk for boys and for girls, in accord with several previous reports.[\u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e42\u003c/span\u003e] Plausible biological pathways for this effect include central nervous system arousal, sleep disturbances, and poor metabolic health resulting from prolonged sedentary behavior.[\u003cspan class=\"CitationRef\"\u003e44\u003c/span\u003e] In addition, extended periods of sedentary behavior, such as television viewing and playing video games, has been found to lead to social solitude and withdrawal from interpersonal relationships, which has been linked to increased feelings of anxiety.[\u003cspan class=\"CitationRef\"\u003e44\u003c/span\u003e] Our results revealed that one in four adolescents spent more than 4 hours of daily sedentary time in the Bahamas, Thailand, Bahrain, Brunei, and Kuwait, which warrants immediate action. Programs for promoting awareness among adolescents and parents about the harmful effects of unhealthy sedentary behavior may help to limit adolescents\u0026rsquo; daily sedentary time.\u003c/p\u003e\n\u003cp\u003eThe current study revealed that the use of tobacco was positively associated with depression risk, which is consistent with a previous report.[\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e] Moreover, we found that the use of tobacco was considerably higher among boys than that among girls, but the association between tobacco use and depression risk was stronger among girls than that among boys. Therefore, it may be valuable to emphasize community and school-based tobacco awareness and cessation programs in Kuwait, Bahrain and Polynesia to suppress the use of tobacco among adolescents.\u003c/p\u003e\n\u003cp\u003eIn the current study, 27% adolescents reported exposure to school violence. In addition, we found a strong association between exposure to school violence and depression risk among adolescents. A previous study also revealed that children who had high levels of exposure to school violence were more likely to experience depression.[\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e] A new United Nations Educational Scientific and Cultural Organization study reported that effective systems for reporting and monitoring school violence and bullying, evidence-based programs and interventions, training and support for teachers, support and referral for affected students can reduce the prevalence of school violence.[\u003cspan class=\"CitationRef\"\u003e45\u003c/span\u003e] Therefore, the countries in our study that showed a high prevalence of school violence (Nepal, Tuvalu, Namibia, the Philippines, and Timor-Leste) may find it useful to implement interventions to provide a safe and positive school climate and classroom environment.\u003c/p\u003e\n\u003cp\u003eThe current findings revealed that two out of three adolescents had insufficient interactions with friends, and three out of four adolescents had insufficient interactions with parents. Importantly, insufficient interactions with parents and friends increased the risk of depression among adolescents. This finding is consistent with the results of a previous study reporting that parents and peers could provide supportive environments to offset stressors such as loneliness.[\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e] Moreover, rapid urbanization and the changing social and economic context and technological advancement have caused drastic lifestyle changes. For example, one recent study reported that many teens did not socialize in the real world, and that this behavior pattern caused severe loneliness.[\u003cspan class=\"CitationRef\"\u003e46\u003c/span\u003e] A recent survey of parents reported that 25% children were addicted to devices and games and in the home, and that the constant use of devices among family members can cause children to feel lonely and isolated.[\u003cspan class=\"CitationRef\"\u003e47\u003c/span\u003e] Therefore, in Bahrain, Kuwait, Timor-Leste, Laos, Tuvalu, Yemen, Brunei, the Philippines, and the Cook Islands, improved relationships between adolescents and their parents should be emphasized. One possible mechanism might be parental involvement in school activity on a voluntary basis. Furthermore, our study revealed that insufficient interactions with friends made girls more vulnerable to depression risk than boys. One possible reason is that, during adolescence, girls have tighter, more cohesive friendship networks than boys, which consequently elevates the risk of expulsion from their social network. According to the current study findings, a focus on improved peer relationships among adolescents may be helpful in Benin, Tuvalu, and Namibia.\u003c/p\u003e\n\u003cp\u003eWe conducted comprehensive assessment of depression risk and its modifiable risk factors among adolescents. Additionally, we reported country-specific scenarios of adolescent lifestyle factors and social behaviors. We used the most recent available nationally representative data from multiple countries with different ethnic and cultural compositions, with a large sample size (\u0026gt;\u0026thinsp;50,000), and the results are likely to be generalizable to other countries with high rates of schooling. However, the GSHS only included adolescents who were enrolled in school, and school-going adolescents may not be representative of all adolescents in a country. Despite this limitation, because school enrollment rates among adolescents were high in most of the included countries, the results are unlikely to be severely affected by sample selection bias.[\u003cspan class=\"CitationRef\"\u003e48\u003c/span\u003e] Furthermore, because of the self-reported nature of the data, misreporting is possible, although this should be minimized by the anonymity of the questionnaire and the data cleaning techniques used.\u003c/p\u003e\n\u003cp\u003eIn conclusion, widespread prevalence of depression risk and its behavioral determinants were observed among adolescents in most of the countries studied. Moreover, higher lifestyle and social risk scores considerably increased the odds of depression risk. The current findings will increase awareness of adolescent depression and consequently may help to reduce stigma related to depression. Moreover, our findings may facilitate early recognition and cost-effective management of adolescent depression. These outcomes can also inform population-based interventions to improve lifestyles and social behaviors among adolescents.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eGSHS Global School-based Student Health Survey\u003c/p\u003e\n\u003cp\u003eOR Odds Ratio\u003c/p\u003e\n\u003cp\u003eCI Confidence Interval\u003c/p\u003e\n\u003cp\u003eWHO World Health Organization\u003c/p\u003e\n\u003cp\u003eCDC Center for Disease Control and Prevention\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthics approval and consent to participate:\u003c/h2\u003e\n\u003cp\u003eOur study was exempted by the ethics committee of the university of Tokyo as we employed secondary data that are available for public use.\u003c/p\u003e\n\u003ch2\u003eConsent for publication:\u003c/h2\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003ch2\u003eAvailability of data and materials:\u003c/h2\u003e\n\u003cp\u003eThe data used in this study was downloaded from the website (\u003ca href=\"https://www.cdc.gov/gshs/index.htm\"\u003eCDC Global School-based Student Health Survey (GSHS)\u003c/a\u003e) of Centers for Disease Control and Prevention (CDC). Analysis sheets are presented in the manuscript and also as supplementary files. The code book, and analytic code will be made available upon request to the corresponding author.\u003c/p\u003e\n\u003ch2\u003eConflict of interest:\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eNone of the authors had any biomedical financial interests or potential conflicts of interest or personal affiliation that compromised the scientific integrity of this work.\u003c/p\u003e\n\u003ch2\u003eFund:\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003ch2\u003eAuthors contributions:\u003c/h2\u003e\n\u003cp\u003eSS, MMR, and MH conceived the article. SS carried out the background study, data extraction, statistical analysis, and interpretation of the data under the supervision of MMR. SS conducted the quality assessment, in consultation with MH. SS wrote the manuscript. MH and MMR checked the consistency of the study. MH and MMR revised it critically for intellectual content.\u0026nbsp;All authors have reviewed and approved the final manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgments:\u003c/h2\u003e\n\u003cp\u003eWe thank the WHO, the Centers for Disease Control and Prevention, and the Ministries of Health and Education in all the selected countries for conducting this survey and for making the data available at no cost. We thank Benjamin Knight, MSc., from Edanz (https://jp.edanz.com/ac) for editing a draft of this manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eWorld Health Organization. Depression and other common mental disorders: global health estimates. Geneva. 2017 Feb, Licence: CC BY-NC-SA 3.0 IGO. Available from: \u0026nbsp;\u003ca href=\"https://apps.who.int/iris/bitstream/handle/10665/254610/WHO-MSD-MER-2017.2-eng.pdf;sequence=1\"\u003eWHO-MSD-MER-2017.2-eng.pdf;sequence=1\u003c/a\u003e\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eMojtabai R, Olfson M, Han B. National Trends in the Prevalence and Treatment of Depression in Adolescents and Young Adults.\u0026nbsp;Pediatrics. 2016 Dec;138(6):e20161878. Doi:10.1542/peds.2016-1878.\u003c/li\u003e\n \u003cli\u003eShorey S, Ng ED, Wong CH. Global prevalence of depression and elevated depressive symptoms among adolescents: A systematic review and meta-analysis. Br J Clin Psychol. 2021 Sep. Doi: 10.1111/bjc.12333.\u003c/li\u003e\n \u003cli\u003eDewey C. A stunning map of depression rates around the world. The Washington Post [Internet]. 2013 Nov [cited 2020 Dec 15]. Available from:\u0026nbsp;\u003ca href=\"https://www.washingtonpost.com/news/worldviews/wp/2013/11/07/a-stunning-map-of-depression-rates-around-the-world/\"\u003eA stunning map of depression rates around the world - The Washington Post\u003c/a\u003e\u003c/li\u003e\n \u003cli\u003eWorld Health Organization. Adolescent mental health [Internet]. 2021 Nov [cited 2021 Dec 15]. Available from:\u0026nbsp;\u003ca href=\"https://www.who.int/news-room/fact-sheets/detail/adolescent-mental-health\"\u003eAdolescent mental health (who.int)\u003c/a\u003e.\u003c/li\u003e\n \u003cli\u003eAhn HK, Bae JH, Ahn HY, Hwang IC. Risk of cancer among patients with depressive disorder: a meta-analysis and implications. Psychooncology. 2016 Dec;25(12):1393-1399.\u0026nbsp;Doi: 10.1002/pon.4084.\u003c/li\u003e\n \u003cli\u003eWhang W, Kubzansky LD, Kawachi I, Rexrode KM, Kroenke CH, Glynn RJ, et al. Depression and risk of sudden cardiac death and coronary heart disease in women: results from the Nurses\u0026apos; Health Study.\u0026nbsp;J Am Coll Cardiol. 2009 Mar;53(11):950-958. Doi:10.1016/j.jacc.2008.10.060.\u003c/li\u003e\n \u003cli\u003eFletcher JM. Adolescent depression: diagnosis, treatment, and educational attainment.\u0026nbsp;Health Econ. 2008 Nov;17(11):1215-1235. Doi:10.1002/hec.1319.\u003c/li\u003e\n \u003cli\u003eMannan M, Mamun A, Doi S, Clavarino A. Prospective associations between depression and obesity for adolescent males and females- a systematic review and meta-analysis of longitudinal studies.\u0026nbsp;PLoS One. 2016 Jun;11(6):e0157240. Doi:10.1371/journal.pone.0157240.\u003c/li\u003e\n \u003cli\u003eHernandez L, Cancilliere MK, Graves H, Chun TH, Lewander W, Spirito A. Substance use and depressive symptoms among adolescents treated in a pediatric emergency department.\u0026nbsp;J Child Adolesc Subst Abuse. 2016 Mar;25(2):124-133. Doi:\u003ca href=\"https://www.researchgate.net/deref/http%3A%2F%2Fdx.doi.org%2F10.31234%2Fosf.io%2Feq9jf\" target=\"_blank\"\u003e10.31234/osf.io/eq9jf\u003c/a\u003e.\u003c/li\u003e\n \u003cli\u003eAudrain-McGovern J, Rodriguez D, Kassel JD. Adolescent smoking and depression: evidence for self-medication and peer smoking mediation.\u0026nbsp;Addiction. 2009 Oct ;104(10): 1743-1756. Doi:10.1111/j.1360-0443.2009.02617.x.\u003c/li\u003e\n \u003cli\u003eTrautmann S, Rehm J, Wittchen HU. The economic costs of mental disorders: Do our societies react appropriately to the burden of mental disorders? EMBO Rep. 2016 Sep;17(9):1245-1249. D\u003ca href=\"https://doi.org/10.15252/embr.201642951\"\u003eoi: 10.15252/embr.201642951\u003c/a\u003e.\u003c/li\u003e\n \u003cli\u003eOppenheimer W, Hankin BL, Young J. Effect of Parenting and Peer Stressors on Cognitive Vulnerability and Risk for Depression among Youth. J Abnorm Child Psychol. 2018 Apr;46(3):597-612. Doi:\u0026nbsp;10.1007/s10802-017-0315-4.\u003c/li\u003e\n \u003cli\u003eCabello M, Miret M, Caballero FF, Chatterji S, Naidoo N, Kowal P, et al. The role of unhealthy lifestyles in the incidence and persistence of depression: A longitudinal general population study in four emerging countries. Global Health. 2017 Mar;13(1):18. Doi:\u003ca href=\"http://doi.org/10.1186/s12992-017-0237-5\" target=\"_blank\"\u003e10.1186/s12992-017-0237-5\u003c/a\u003e.\u003c/li\u003e\n \u003cli\u003eFlannery DJ, Wester KL, Singer MI. Impact of exposure to violence in school on child and adolescent mental health and behavior. J Community Psychol. 2004 Aug;32(5):559-573. Doi: 10.1002/jcop.20019.\u003c/li\u003e\n \u003cli\u003eWang PS, Aguilar-Gaxiola S, Alonso J, Angermeyer MC, Borges G, Bromet EJ, et al. Use of mental health services for anxiety, mood, and substance disorders in\u0026nbsp;17 countries in the WHO world mental health surveys. The Lancet.\u0026nbsp;2007 Sep;370(9590):841-50. D\u003ca href=\"https://doi.org/10.1016/S0140-6736(07)61414-7\" target=\"_blank\" title=\"Persistent link using digital object identifier\"\u003eoi:10.1016/S0140-6736(07)61414-7\u003c/a\u003e.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eZuckerbrot RA, Cheung A,\u0026nbsp;Jensen PS, Stein RE, Laraque D, GLAD-PC STEERING GROUP.\u0026nbsp;Guidelines for adolescent depression in primary care (GLAD-PC): part I. practice preparation, identification, assessment, and initial management.\u0026nbsp;Pediatrics\u0026nbsp;2018 Mar;141(3):e20174081.\u0026nbsp;Doi:10.1542/peds.2017-4081.\u003c/li\u003e\n \u003cli\u003eWorld Health Organization.\u0026nbsp;\u003ca href=\"https://extranet.who.int/ncdsmicrodata/index.php\"\u003eNCD microdata repository\u003c/a\u003e.\u0026nbsp;Global School-Based Student Health Survey 2014, Bangladesh [Internet]. 2019 Jun [cited 2021 Dec 20]. Available from:\u0026nbsp;\u003ca href=\"https://extranet.who.int/ncdsmicrodata/index.php/catalog/485/data-dictionary/F1?file_name=BGD2014_Public_Use\"\u003eBangladesh - Global School-Based Student Health Survey 2014 (who.int)\u003c/a\u003e\u003c/li\u003e\n \u003cli\u003eCenters for Disease Control and Prevention. Children\u0026rsquo;s mental health. Anxiety and depression in children [Internet]. 2021 Mar [cited 2021 Dec 20]. Available from:\u0026nbsp;\u003ca href=\"https://www.cdc.gov/childrensmentalhealth/depression.html\"\u003eAnxiety and Depression in Children | CDC\u003c/a\u003e.\u003c/li\u003e\n \u003cli\u003eMorin A. Depression statistics everyone should know [Internet]. Verywell Mind. 2021 May [cited 2021 Dec 20]. Available from:\u0026nbsp;\u003ca href=\"https://www.verywellmind.com/depression-statistics-everyone-should-know-4159056\" target=\"_blank\"\u003ehttps://www.verywellmind.com/depression-statistics-everyone-should-know-4159056\u003c/a\u003e.\u003c/li\u003e\n \u003cli\u003eLoades ME, Chatburn E, Higson-sweeney N, Reynolds S, Shafran R, Brigden A, et al. Rapid systematic review: the impact of social isolation and loneliness on the mental health of children and adolescents in the context of COVID-19. J Am Acad Child Adolesc Psychiatry. 2020 Nov;59(11):1218-1239.e3. Doi:10.1016/j.jaac.2020.05.009.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eLasgaard M, Goossens L, Elklit A. Loneliness, depressive symptomatology, and suicide ideation in adolescence: cross-sectional and longitudinal analyses.\u0026nbsp;J Abnorm Child Psychol\u0026nbsp;2011 Jan;39(1):137\u0026ndash;50. Doi:10.1007/s10802-010-9442-x.\u003c/li\u003e\n \u003cli\u003eVanhalst J, Klimstra TA, Luyckx K, et al. The interplay of loneliness and depressive symptoms across adolescence: exploring the role of personality traits.\u0026nbsp;J Youth Adolesc.\u0026nbsp;2011 Nov;41(6):776\u0026ndash;87. Doi:10.1007/s10964-011-9726-7.\u003c/li\u003e\n \u003cli\u003eOellingrath IM, Bortoli MMD, Svendsen MV, Fell AKM. Lifestyle and work ability in a general working population in Norway: a cross-sectional study. BMJ Open. 2019 APR;9(4):p.e026215. Doi:10.1136/bmjopen-2018-026215.\u003c/li\u003e\n \u003cli\u003eWorld Health Organization. Global strategy on diet, physical activity, and health [Internet]. 2004 May [cited 2021 Dec 20]. Available from:\u0026nbsp;\u003ca href=\"https://www.who.int/nmh/wha/59/dpas/en/\"\u003eWHO | The Global Strategy on Diet, Physical Activity and Health (DPAS)\u003c/a\u003e.\u003c/li\u003e\n \u003cli\u003eMiller G, Merlo C, Demissie Z, Sliwa S, Park S. Trends in Beverage Consumption among high school students \u0026mdash; United States, 2007-2015. MMWR Morb Mortal Wkly Rep. 2017 Feb;66(4):112\u0026ndash;116. Doi:\u0026nbsp;\u003ca href=\"http://dx.doi.org/10.15585/mmwr.mm6604a5\" target=\"_blank\"\u003e10.15585/mmwr.mm6604a5external icon\u003c/a\u003e.\u003c/li\u003e\n \u003cli\u003eBraithwaite\u0026nbsp;I,\u0026nbsp;Stewart\u0026nbsp;AW,\u0026nbsp;Hancox\u0026nbsp;RJ, Beasley R, Murphy R, Mitchell EA, et al. Fast food consumption and body mass index in children and adolescents: an international cross-sectional study. BMJ Open\u0026nbsp;2014 Nov;4:e005813 doi:10.1136/bmjopen-2014- 005813.\u003c/li\u003e\n \u003cli\u003eWorld Health Organization. Global Recommendations on Physical Activity for Health [Internet]. Switzerland. 2010 [cited 2021 Dec 20]. Available from:\u0026nbsp;\u003ca href=\"https://www.who.int/dietphysicalactivity/global-PA-recs-2010.pdf\"\u003eglobal-PA-recs-2010.pdf (who.int)\u003c/a\u003e.\u003c/li\u003e\n \u003cli\u003eAmerican Academy of Paediatrics. New Recommendations for Children\u0026rsquo;s Media Use. J Pediatr. 2016 Nov;38(5):e20162592. Doi: 10.1542/peds.2016-2592.\u003c/li\u003e\n \u003cli\u003ePaavola M, Vartiainen E, Puska P. Smoking cessation between teenage years and adulthood. Health Edu Res. 2001 Feb;16(1):p.49-57. Doi:\u0026nbsp;\u003ca href=\"https://doi.org/10.1093/her/16.1.49\"\u003e10.1093/her/16.1.49\u003c/a\u003e\u003c/li\u003e\n \u003cli\u003eAtalay BI, Unal E, Onsuz MF, Isikli B, Yenilmez C, Metintas S. Violence and related factors among high school students in semirural areas of Eskisehir.\u0026nbsp;North Clin Istanb. 2018 Apr;5(2):125-131. Doi: 10.14744/nci.2017.91259.\u003c/li\u003e\n \u003cli\u003eFaria CS and Martins CBG.Violence among adolescent students: conditions of vulnerability [Internet]. Enfermeria Global. 2016 Apr [cited 2021 Dec 20];185-98. Available from:\u0026nbsp;\u003ca href=\"https://studylib.es/doc/6414202/violence-among-adolescent-students--conditions-of-vulnera...\"\u003eViolence among adolescent students: conditions of vulnerability (studylib.es)\u003c/a\u003e\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eSultana S, Rahman MM, Masahiro H, Sigel B. Associations of lifestyle\u0026nbsp;risk factors\u0026nbsp;with overweight or obesity among adolescents: a multi-country analysis.\u0026nbsp;\u003cstrong\u003eAm J Clin Nutr. 2021 Mar;113(3):742-750. Doi:\u003c/strong\u003e\u003ca href=\"https://doi.org/10.1093/ajcn/nqaa337\"\u003e10.1093/ajcn/nqaa337\u003c/a\u003e.\u003c/li\u003e\n \u003cli\u003ePark SH. Smoking and adolescent health. Korean J pediatr. 2011 Oct;54(10):401-404. Doi:\u003ca href=\"https://www.researchgate.net/deref/http%3A%2F%2Fdx.doi.org%2F10.3345%2Fkjp.2011.54.10.401\" target=\"_blank\"\u003e10.3345/kjp.2011.54.10.401\u003c/a\u003e.\u003c/li\u003e\n \u003cli\u003ePanter-Brick C, Eggerman M, Gonzalez V, Safdar S. Violence, suffering, and mental health in Afghanistan: a school-based survey.\u0026nbsp;The Lancet. 2009 Sep;374(9692):807-816. Doi:\u003ca href=\"https://doi.org/10.1016/s0140-6736(09)61080-1\" target=\"_blank\"\u003e10.1016/s0140-6736(09)61080-1\u003c/a\u003e.\u003c/li\u003e\n \u003cli\u003eDardas L, Bailey DE, Simmons LA. Adolescent depression in the Arab region: a systematic literature review.\u0026nbsp;Issues Ment Health Nurs. 2016 Aug;37(8):569-585. Doi:\u003ca href=\"https://www.researchgate.net/deref/http%3A%2F%2Fdx.doi.org%2F10.1080%2F01612840.2016.1177760\" target=\"_blank\"\u003e10.1080/01612840.2016.1177760\u003c/a\u003e.\u003c/li\u003e\n \u003cli\u003eSchimelpfening N. Why depression is more common in women than in men? [Internet]. Verywell Mind. 2020 Dec [cited 2021 Dec 20]. Available from:\u0026nbsp;\u003ca href=\"https://www.verywellmind.com/why-is-depression-more-common-in-women-1067040\"\u003eWhy Depression Is More Common in Women Than in Men (verywellmind.com)\u003c/a\u003e\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eRao TS, Asha MR, Ramesh BN and Rao KS. Understanding nutrition, depression and mental illnesses.\u0026nbsp;Indian J Psychiatry. 2008 Apr;50(2):77-82. Doi:10.4103/0019-5545.42391.\u003c/li\u003e\n \u003cli\u003eMrug S, Orihuela C, Mrug M, Sanders PW. Sodium and potassium excretion predict increased depression in urban adolescents.\u0026nbsp;Physiol Rep. 2019 Aug;7(16):e14213. Doi:\u003ca href=\"https://doi.org/10.14814/phy2.14213\" target=\"_blank\"\u003e10.14814/phy2.14213\u003c/a\u003e.\u003c/li\u003e\n \u003cli\u003eMeiklejohn S, Ryan L, Palermo C. A systematic review of the impact of multi-strategy nutrition education programs on health and nutrition of adolescents. J Nutr Educ Behav. 2016 Oct;48(9):631-646. Doi: 10.1016/j.jneb.2016.07.015.\u003c/li\u003e\n \u003cli\u003eWang D, Stewart D. The implementation and effectiveness of school-based nutrition promotion programmes using a health-promoting schools approach: a systematic review. Public Health Nutr. 2013 Jun;16(6):1082-1100. Doi:10.1017/S1368980012003497.\u003c/li\u003e\n \u003cli\u003eNystrom MBT, Hassmen P, Sorman DE,Wigforss T, Andersson G, Carlbring P.\u0026nbsp;Are physical activity and sedentary behavior related to depression?\u0026nbsp;Cogent Psychology. 2019 Jul;6(1):1633810. Doi: 10.1080/23311908.2019.1633810.\u0026nbsp; \u0026nbsp;\u003c/li\u003e\n \u003cli\u003eKorczak DJ, Madigan S, ColasantoM. \u0026nbsp;Children\u0026apos;s Physical Activity and Depression: A Meta-analysis. Pediatrics. 2017 Apr;139(4):e20162266. Doi: 10.1542/peds.2016-2266. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/li\u003e\n \u003cli\u003eDworak M, Schierl T, Bruns T, Struder HK. Impact of singular excessive computer game and television exposure on sleep patterns and memory performance of school-aged children.\u0026nbsp;Pediatrics. 2007 Nov;120(5):978-985. Doi:10.1542/peds.2007-0476.\u003c/li\u003e\n \u003cli\u003eUnited Nations Educational Scientific and Cultural Organization. Behind the numbers: ending school violence and bullying [Internet].France, Paris. 2019 [cited 2021 Dec 20]. Available from:\u0026nbsp;\u003ca href=\"https://www.end-violence.org/sites/default/files/paragraphs/download/UNESCO_Bullying.pdf\"\u003eUNESCO_Bullying.pdf (end-violence.org)\u003c/a\u003e.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eO\u0026apos;donnell J. Teens aren\u0026apos;t socializing in the real world. And that\u0026apos;s making them super lonely [Internet]. USA Today. 2019 Mar [cited 2021 Dec 21]. Available from:\u0026nbsp;\u003ca href=\"https://www.usatoday.com/story/news/health/2019/03/20/teen-loneliness-social-media-cell-phones-suicide-isolation-gaming-cigna/3208845002/\"\u003eLoneliness soars among teens along with social media use, study says (usatoday.com)\u003c/a\u003e\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eQuinlan A. How technology and social media is undermining family relationships [Internet]. The Irish Times. 2018 Jul [cited 2021 Dec 21]. Available from: \u0026nbsp;\u003ca href=\"https://www.irishtimes.com/life-and-style/health-family/parenting/how-technology-and-social-media-is-undermining-family-relationships-1.3568291\"\u003eHow technology and social media is undermining family relationships (irishtimes.com)\u003c/a\u003e\u003c/li\u003e\n \u003cli\u003eEducation statistics-All indicators. World Bank group. 2020 Dec [cited 2021 Dec 21]. Available from: \u0026nbsp;\u003ca href=\"https://databank.worldbank.org/source/education-statistics-%5e-all-indicators\"\u003eEducation Statistics - All Indicators | DataBank (worldbank.org)\u003c/a\u003e\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003ctable border=\"0\" cellpadding=\"0\" cellspacing=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" style=\"width: 99.125%;\" width=\"84.84848484848484%\"\u003e\n \u003cp style=\"text-align: center;\"\u003eTable 1\u003c/p\u003e\n \u003cp style=\"text-align: center;\"\u003e\u0026nbsp;Survey characteristics of the Global School-based Student Health Survey datasets for the selected countries.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"22\" width=\"0%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCountry\u003csup\u003e1\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=20)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"8.24742268041237%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSurvey year\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSurvey sample size (n=83,695)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"10.309278350515465%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnalysis sample size (n=51,597)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"8.24742268041237%\"\u003e\n \u003cp\u003e\u003cstrong\u003eResponse rate (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"15.463917525773196%\"\u003e\n \u003cp\u003e\u003cstrong\u003e% Boys (95% CI) (n=23,192)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean age\u003csup\u003e2\u003c/sup\u003e, (years) (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"15.463917525773196%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevalence of depression\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;(95% CI) (n=13,635)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" width=\"0%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd height=\"31\" width=\"NaN%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003eAfghanistan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e2014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e2579\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e1,048\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e56.6 (53.7, 59.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e15.2 (15.1, 15.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.463917525773196%\"\u003e\n \u003cp\u003e49.9 (46.5, 53.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"22\" width=\"0%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003eBahamas\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e2013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e1357\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e786\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e45.4 (41.8, 48.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e13.4 (13.3, 13.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.463917525773196%\"\u003e\n \u003cp\u003e31.4 (28.1, 34.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"22\" width=\"0%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003eBahrain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e2016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e7141\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e2,515\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e47.9 (46.0, 49.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e14.4 (14.4, 14.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.463917525773196%\"\u003e\n \u003cp\u003e37.1 (35.2, 39.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"22\" width=\"0%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003eBangladesh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e2014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e2989\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e1,909\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e66.6 (64.2, 68.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e14.1 (14.2, 14.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.463917525773196%\"\u003e\n \u003cp\u003e18.5 (16.1, 21.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"22\" width=\"0%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003eBenin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e2016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e2536\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e1,840\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e72.9 (71.0, 74.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e16.4 (16.3, 16.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.463917525773196%\"\u003e\n \u003cp\u003e39.8 (37.3, 42.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"22\" width=\"0%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003eBrunei\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e2014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e2599\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e1,961\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e49.0 (46.7, 51.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e14.6 (14.6, 14.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.463917525773196%\"\u003e\n \u003cp\u003e23.9 (21.9, 26.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"22\" width=\"0%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003eCook Islands\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e701\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e521\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e48.1 (43.8, 52.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e15.4 (15.3, 15.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.463917525773196%\"\u003e\n \u003cp\u003e29.1 (25.2, 33.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"22\" width=\"0%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003eFiji\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e2016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e3705\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e2,432\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e46.2 (44.2, 48.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e15.8 (15.8, 15.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.463917525773196%\"\u003e\n \u003cp\u003e27.6 (25.8, 29.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"22\" width=\"0%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003eIndonesia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e11,142\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e8,251\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e46.5 (45.4, 47.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e14.0 (14.0, 14.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.463917525773196%\"\u003e\n \u003cp\u003e12.9 (12.2, 13.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"22\" width=\"0%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003eKuwait\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e3637\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e2,018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e50.1 (48.0, 52.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e15.1 (15.0, 15.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.463917525773196%\"\u003e\n \u003cp\u003e37.3 (35.1, 39.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"22\" width=\"0%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003eLaos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e2013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e3683\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e2,853\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e53.1 (51.1, 55.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e15.6 (15.6, 15.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.463917525773196%\"\u003e\n \u003cp\u003e11.7 (10.5, 13.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"22\" width=\"0%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003eMongolia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e2013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e5393\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e4,189\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e47.4 (45.9, 49.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e14.5 (14.5, 14.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.463917525773196%\"\u003e\n \u003cp\u003e30.2 (28.8, 31.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"22\" width=\"0%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003eNamibia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e2013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e4531\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e2,861\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e46.2 (44.4, 48.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e15.8 (15.8, 15.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.463917525773196%\"\u003e\n \u003cp\u003e43.0 (41.2, 44.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"22\" width=\"0%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003eNepal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e6529\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e4,189\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e48.7 (47.0, 50.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e14.4 (14.4, 14.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.463917525773196%\"\u003e\n \u003cp\u003e19.8 (18.3, 21.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"22\" width=\"0%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003ePhilippines\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e8761\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e5,790\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e49.1 (47.8, 50.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e14.5 (14.6, 14.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.463917525773196%\"\u003e\n \u003cp\u003e30.2 (28.9, 31.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"22\" width=\"0%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003ePolynesia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e3216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e2,298\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e48.2 (46.1, 50.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e15.1 (15.0, 15.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.463917525773196%\"\u003e\n \u003cp\u003e27.1 (25.2, 29.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"22\" width=\"0%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003eThailand\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e5894\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e3,521\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e43.2 (41.1, 45.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e14.5 (14.5, 14.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.463917525773196%\"\u003e\n \u003cp\u003e21.4 (19.7, 23.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"22\" width=\"0%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003eTimor-Leste\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e3704\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e1,011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e53.4 (50.4, 56.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e15.5 (15.4, 15.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.463917525773196%\"\u003e\n \u003cp\u003e32.2 (29.2, 35.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"22\" width=\"0%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003eTuvalu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e2013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e943\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e207\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e42.9 (37.7, 48.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e13.9 (13.9, 14.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.463917525773196%\"\u003e\n \u003cp\u003e18.4 (13.6, 24.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"22\" width=\"0%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003eYemen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e2014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e2655\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e1,397\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e54.5 (51.9, 57.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003e14.9 (14.8, 15.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.463917525773196%\"\u003e\n \u003cp\u003e37.3 (34.6, 40.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"22\" width=\"0%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\" style=\"width: 99.875%;\"\u003e\n \u003cp style='margin-bottom: 10px !important; color: rgb(0, 0, 0); font-family: \"Times New Roman\"; font-size: medium; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; text-decoration-style: initial; text-decoration-color: initial;'\u003eLegend:\u003c/p\u003e\n \u003cp style='margin-bottom: 10px !important; color: rgb(0, 0, 0); font-family: \"Times New Roman\"; font-size: medium; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; text-decoration-style: initial; text-decoration-color: initial;'\u003eCI: confidence interval\u003c/p\u003e\n \u003cp style='margin-bottom: 10px !important; color: rgb(0, 0, 0); font-family: \"Times New Roman\"; font-size: medium; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; text-decoration-style: initial; text-decoration-color: initial;'\u003e\u003csup\u003e1\u0026nbsp;\u003c/sup\u003eCountries with Global School-based Student Health Survey data available for 2013 or later.\u003c/p\u003e\n \u003cp style='margin-bottom: 10px !important; color: rgb(0, 0, 0); font-family: \"Times New Roman\"; font-size: medium; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; text-decoration-style: initial; text-decoration-color: initial;'\u003e\u003csup\u003e2\u0026nbsp;\u003c/sup\u003eDescriptive analyses were used to estimate mean age and percentage of depression risk among adolescents. Probability sampling weights were applied in all analyses.\u003c/p\u003e\u003cbr\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp style=\"text-align: center;\"\u003eTable 2\u003c/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u0026nbsp;Development of depression risk variable for adolescents.\u003c/p\u003e\n\u003ctable border=\"0\" cellpadding=\"0\" cellspacing=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" width=\"15.625%\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" width=\"15.625%\"\u003e\n \u003cp\u003e\u003cstrong\u003eComponents\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" width=\"13.541666666666666%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFrequency\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(Last 1 year)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" width=\"9.375%\"\u003e\n \u003cp\u003e\u003cstrong\u003eRisk index\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" width=\"11.458333333333334%\"\u003e\n \u003cp\u003e\u003cstrong\u003eRisk index range\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" width=\"34.375%\"\u003e\n \u003cp\u003e\u003cstrong\u003eRisk levels\u003csup\u003e1\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"43.75%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLow\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.375%\"\u003e\n \u003cp\u003e\u003cstrong\u003eModerate\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.875%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHigh\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"43.75%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo risk group\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"56.25%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAt risk group\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"10\" width=\"15.789473684210526%\"\u003e\n \u003cp\u003eRisk of depression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" width=\"15.789473684210526%\"\u003e\n \u003cp\u003e1. Feel lonely\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.68421052631579%\"\u003e\n \u003cp\u003eRarely\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"10\" width=\"11.578947368421053%\"\u003e\n \u003cp\u003e0-8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"10\" width=\"14.736842105263158%\"\u003e\n \u003cp\u003e0-2\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"10\" width=\"11.578947368421053%\"\u003e\n \u003cp\u003e2\u003csup\u003e2\u003c/sup\u003e-3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"10\" width=\"7.368421052631579%\"\u003e\n \u003cp\u003e4-8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"59.09090909090909%\"\u003e\n \u003cp\u003eSometimes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.90909090909091%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"59.09090909090909%\"\u003e\n \u003cp\u003eAlways\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.90909090909091%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" width=\"40.54054054054054%\"\u003e\n \u003cp\u003e2. Too worried\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"35.13513513513514%\"\u003e\n \u003cp\u003eRarely\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.324324324324323%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"59.09090909090909%\"\u003e\n \u003cp\u003eSometimes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.90909090909091%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"59.09090909090909%\"\u003e\n \u003cp\u003eAlways\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.90909090909091%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" width=\"40.54054054054054%\"\u003e\n \u003cp\u003e3. Considered suicide\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"35.13513513513514%\"\u003e\n \u003cp\u003eNever\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.324324324324323%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"59.09090909090909%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003ctable border=\"0\" cellpadding=\"0\" cellspacing=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"100%\"\u003e\n \u003cp\u003e\u003cimg src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAA8AAAAbCAIAAAAs80KQAAAAAXNSR0IArs4c6QAAAAlwSFlzAAASdAAAEnQB3mYfeAAAAJFJREFUOE/VU8ENgCAMFHdxCdgHh/GDy+AwZRekkACmQUqMD/oi7V17PVLhvV/YsbKRCJwa7ZzjLYtbOjg2IZTaz6vHCn6nAGu0lIEstbEAOV8/FpItrEh71CmazKqGtdFFIOqTBqd87c3TzfUErEZl1ALiV9QNDXsJWgxdA/YGg1/4HsnBsd5T307PkFz/c8sbznBrh1FpSrkAAAAASUVORK5CYII=\" alt=\"image\"\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.90909090909091%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" width=\"40.54054054054054%\"\u003e\n \u003cp\u003e4. Attempted suicide\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"35.13513513513514%\"\u003e\n \u003cp\u003eNever\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.324324324324323%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"59.09090909090909%\"\u003e\n \u003cp\u003e\u003cimg src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAA8AAAAbCAIAAAAs80KQAAAAAXNSR0IArs4c6QAAAAlwSFlzAAASdAAAEnQB3mYfeAAAAJFJREFUOE/VU8ENgCAMFHdxCdgHh/GDy+AwZRekkACmQUqMD/oi7V17PVLhvV/YsbKRCJwa7ZzjLYtbOjg2IZTaz6vHCn6nAGu0lIEstbEAOV8/FpItrEh71CmazKqGtdFFIOqTBqd87c3TzfUErEZl1ALiV9QNDXsJWgxdA/YGg1/4HsnBsd5T307PkFz/c8sbznBrh1FpSrkAAAAASUVORK5CYII=\" alt=\"image\"\u003e\u003c/p\u003e\n \u003ctable border=\"0\" cellpadding=\"0\" cellspacing=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.90909090909091%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eLegend: Depression risk variable was developed for adolescents (aged 13\u0026ndash;17 years) using the Global School-based Student Health Survey datasets for 20 countries with survey data available for 2013 or later.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003csup\u003e1\u003c/sup\u003e This method of grouping composite risk indexes to produce risk levels has been used in another study.[23]\u003csup\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 2\u0026nbsp;\u003c/sup\u003eThe composite risk index could equal two 1) if any two of the four components were at moderate risk (0+0+1+1) or 2) if any one of the four components were at high risk (0+0+0+2). The former criterion was included as a low risk index and the latter criterion was included as a moderate risk index. The reason was participants with low risk indexes should not have any component assessed as high risk.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e3\u0026nbsp;\u003c/sup\u003eCut-off points were determined based on previous studies.\u003c/p\u003e\n\u003cp style=\"text-align: center;\"\u003eTable 3\u003c/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u0026nbsp;Composition of lifestyle and social risk indexes for adolescents.\u003c/p\u003e\n\u003ctable border=\"0\" cellpadding=\"0\" cellspacing=\"0\" width=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" width=\"17.862838915470494%\"\u003e\n \u003cp\u003e\u003cstrong\u003eRisk indexes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" width=\"21.850079744816586%\"\u003e\n \u003cp\u003e\u003cstrong\u003eComponents\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" width=\"16.108452950558213%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFrequency\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" width=\"8.293460925039872%\"\u003e\n \u003cp\u003e\u003cstrong\u003eRisk index\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" width=\"9.569377990430622%\"\u003e\n \u003cp\u003e\u003cstrong\u003eRisk index range\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" width=\"26.31578947368421%\"\u003e\n \u003cp\u003e\u003cstrong\u003eRisk level\u003csup\u003e1\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.272727272727273%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLow\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.63636363636363%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedium\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHigh\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"12\" width=\"17.862838915470494%\"\u003e\n \u003cp\u003eDietary habits\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" width=\"21.850079744816586%\"\u003e\n \u003cp\u003e1. Fruits, times/d\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.108452950558213%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u0026ge; 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.293460925039872%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"12\" width=\"9.569377990430622%\"\u003e\n \u003cp\u003e0-8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"12\" width=\"7.177033492822966%\"\u003e\n \u003cp\u003e0-2\u003csup\u003e6\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"12\" width=\"11.483253588516746%\"\u003e\n \u003cp\u003e2\u003csup\u003e6\u003c/sup\u003e-3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"12\" width=\"7.655502392344498%\"\u003e\n \u003cp\u003e4-8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"66.01307189542484%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.98692810457516%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"66.01307189542484%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u0026le; 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.98692810457516%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" width=\"47.241379310344826%\"\u003e\n \u003cp\u003e2. Vegetables, times/d\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.827586206896555%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026ge; 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.93103448275862%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"66.01307189542484%\"\u003e\n \u003cp\u003e\u0026nbsp; 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.98692810457516%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"66.01307189542484%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u0026le; 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.98692810457516%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" width=\"47.241379310344826%\"\u003e\n \u003cp\u003e3. Fast food, d/w\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.827586206896555%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026le; 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.93103448275862%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"66.01307189542484%\"\u003e\n \u003cp\u003e\u0026ge; 2 \u0026amp; \u0026le; 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.98692810457516%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"66.01307189542484%\"\u003e\n \u003cp\u003e\u0026ge; 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.98692810457516%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" width=\"47.241379310344826%\"\u003e\n \u003cp\u003e4. Soft drinks, times/d\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.827586206896555%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026le; 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.93103448275862%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"66.01307189542484%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.98692810457516%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"66.01307189542484%\"\u003e\n \u003cp\u003e\u0026ge; 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.98692810457516%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" width=\"17.862838915470494%\"\u003e\n \u003cp\u003ePhysical activity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" width=\"21.850079744816586%\"\u003e\n \u003cp\u003e1. 60 minutes per day, d/w\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.108452950558213%\"\u003e\n \u003cp\u003e\u0026ge; 6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.293460925039872%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" width=\"9.569377990430622%\"\u003e\n \u003cp\u003e0-2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" width=\"7.177033492822966%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" width=\"11.483253588516746%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" width=\"7.655502392344498%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"66.01307189542484%\"\u003e\n \u003cp\u003e\u0026ge; 3 \u0026amp; \u0026le; 5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.98692810457516%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"66.01307189542484%\"\u003e\n \u003cp\u003e\u0026le; 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.98692810457516%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" width=\"17.862838915470494%\"\u003e\n \u003cp\u003eSedentary behavior\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" width=\"21.850079744816586%\"\u003e\n \u003cp\u003e1. Daily sedentary time, h/d\u003csup\u003e5\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.108452950558213%\"\u003e\n \u003cp\u003e\u0026lt; 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.293460925039872%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" width=\"9.569377990430622%\"\u003e\n \u003cp\u003e0-2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" width=\"7.177033492822966%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" width=\"11.483253588516746%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" width=\"7.655502392344498%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"66.01307189542484%\"\u003e\n \u003cp\u003e\u0026ge; 1 \u0026amp; \u0026lt; 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.98692810457516%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"66.01307189542484%\"\u003e\n \u003cp\u003e\u0026ge; 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.98692810457516%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"6\" width=\"17.862838915470494%\"\u003e\n \u003cp\u003eTobacco use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" width=\"21.850079744816586%\"\u003e\n \u003cp\u003e1. Cigarette, days last month\u003csup\u003e3\u003c/sup\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.108452950558213%\"\u003e\n \u003cp\u003e\u0026le; 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.293460925039872%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" width=\"9.569377990430622%\"\u003e\n \u003cp\u003e0-4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" width=\"7.177033492822966%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" width=\"11.483253588516746%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" width=\"7.655502392344498%\"\u003e\n \u003cp\u003e2-4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"66.01307189542484%\"\u003e\n \u003cp\u003e\u0026ge; 3 \u0026amp; \u0026le; 19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.98692810457516%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"66.01307189542484%\"\u003e\n \u003cp\u003e\u0026ge; 20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.98692810457516%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" width=\"47.241379310344826%\"\u003e\n \u003cp\u003e2. Other tobacco products, days last month\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.827586206896555%\"\u003e\n \u003cp\u003e\u0026le; 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.93103448275862%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"66.01307189542484%\"\u003e\n \u003cp\u003e\u0026ge; 3 \u0026amp; \u0026le; 19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.98692810457516%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"66.01307189542484%\"\u003e\n \u003cp\u003e\u0026ge; 20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.98692810457516%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"12\" width=\"17.862838915470494%\"\u003e\n \u003cp\u003eExposure to school violence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" width=\"21.850079744816586%\"\u003e\n \u003cp\u003e1. \u0026nbsp; \u0026nbsp; Physically attacked, times last year\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.108452950558213%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.293460925039872%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"12\" width=\"9.569377990430622%\"\u003e\n \u003cp\u003e0-8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"12\" width=\"7.177033492822966%\"\u003e\n \u003cp\u003e0-2\u003csup\u003e6\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"12\" width=\"11.483253588516746%\"\u003e\n \u003cp\u003e2\u003csup\u003e6\u003c/sup\u003e-3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"12\" width=\"7.655502392344498%\"\u003e\n \u003cp\u003e4-8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"66.01307189542484%\"\u003e\n \u003cp\u003e\u0026ge; 1 \u0026amp; \u0026le; 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.98692810457516%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"66.01307189542484%\"\u003e\n \u003cp\u003e\u0026ge; 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.98692810457516%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" width=\"47.241379310344826%\"\u003e\n \u003cp\u003e2. Physical fight, times last year\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.827586206896555%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.93103448275862%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"66.01307189542484%\"\u003e\n \u003cp\u003e\u0026ge; 1 \u0026amp; \u0026le; 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.98692810457516%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"66.01307189542484%\"\u003e\n \u003cp\u003e\u0026ge; 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.98692810457516%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" width=\"47.241379310344826%\"\u003e\n \u003cp\u003e3. Seriously injured, times last year\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.827586206896555%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.93103448275862%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"66.01307189542484%\"\u003e\n \u003cp\u003e\u0026ge; 1 \u0026amp; \u0026le; 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.98692810457516%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"66.01307189542484%\"\u003e\n \u003cp\u003e\u0026ge; 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.98692810457516%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" width=\"47.241379310344826%\"\u003e\n \u003cp\u003e4. Bullied, days last month\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.827586206896555%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.93103448275862%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"66.01307189542484%\"\u003e\n \u003cp\u003e\u0026ge; 1 \u0026amp; \u0026le; 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.98692810457516%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"66.01307189542484%\"\u003e\n \u003cp\u003e\u0026ge; 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.98692810457516%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"6\" width=\"17.862838915470494%\"\u003e\n \u003cp\u003eInteractions with parents\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" width=\"21.850079744816586%\"\u003e\n \u003cp\u003e1. Missed school without permission, days last month\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.108452950558213%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.293460925039872%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" width=\"9.569377990430622%\"\u003e\n \u003cp\u003e0-4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" width=\"7.177033492822966%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" width=\"11.483253588516746%\"\u003e\n \u003cp\u003e1-2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" width=\"7.655502392344498%\"\u003e\n \u003cp\u003e3-4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"66.01307189542484%\"\u003e\n \u003cp\u003e\u0026ge; 1 \u0026amp; \u0026le; 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.98692810457516%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"66.01307189542484%\"\u003e\n \u003cp\u003e\u0026ge; 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.98692810457516%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" width=\"47.241379310344826%\"\u003e\n \u003cp\u003e2. Parents understand problems, times last month\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.827586206896555%\"\u003e\n \u003cp\u003eAlways\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.93103448275862%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"66.01307189542484%\"\u003e\n \u003cp\u003eSometimes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.98692810457516%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"66.01307189542484%\"\u003e\n \u003cp\u003eRare\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.98692810457516%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"6\" width=\"17.862838915470494%\"\u003e\n \u003cp\u003eInteractions with friends\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" width=\"21.850079744816586%\"\u003e\n \u003cp\u003e1. Students being helpful, times last month\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.108452950558213%\"\u003e\n \u003cp\u003eAlways\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.293460925039872%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" width=\"9.569377990430622%\"\u003e\n \u003cp\u003e0-4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" width=\"7.177033492822966%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" width=\"11.483253588516746%\"\u003e\n \u003cp\u003e1-2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" width=\"7.655502392344498%\"\u003e\n \u003cp\u003e3-4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"66.01307189542484%\"\u003e\n \u003cp\u003eSometimes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.98692810457516%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"66.01307189542484%\"\u003e\n \u003cp\u003eRare\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.98692810457516%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" width=\"47.241379310344826%\"\u003e\n \u003cp\u003e2. Number of close friends\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.827586206896555%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.93103448275862%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"66.01307189542484%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.98692810457516%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"66.01307189542484%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.98692810457516%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eLegend: Risk indexes were developed for adolescents (aged 13\u0026ndash;17 years) using the Global School-based Student Health Survey datasets for 20 countries with survey data available for 2013 or later.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003csup\u003e1\u003c/sup\u003e This method of grouping risk indexes to produce risk levels was used in another study.[23]\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2 \u0026nbsp;\u0026nbsp;\u003c/sup\u003e2006 World Health Organization dietary guidelines.[24]\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e3\u003c/sup\u003e Based on previous studies.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003csup\u003e4\u0026nbsp;\u003c/sup\u003e2010 World Health Organization physical activity guidelines.[27]\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003csup\u003e5\u0026nbsp;\u003c/sup\u003eAmerican Association of Pediatrics\u0026rsquo; 2016 recommendation on screen time for adolescents.[28]\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003csup\u003e6\u003c/sup\u003e The composite risk indexes could equal two 1) if any two of the four components were at moderate risk (0+0+1+1) or 2) if any one of the four components were at high risk (0+0+0+2). The former criterion was included as a low risk index and the latter criterion was included as a moderate risk index. The reason was participants with low risk indexes should not have any component assessed as high risk.\u003c/p\u003e\n\u003cp style=\"text-align: center;\"\u003eTable 4\u003c/p\u003e\n\u003cp style=\"text-align: center;\"\u003eAssociations between lifestyle and social risk indexes and risk of depression among adolescents.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellpadding=\"0\" cellspacing=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" width=\"12.244897959183673%\"\u003e\n \u003cp\u003e\u003cstrong\u003eRisk indexes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"27.551020408163264%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal sample (n=51,597)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"30.612244897959183%\"\u003e\n \u003cp\u003e\u003cstrong\u003eBoys (n=23,192)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"29.591836734693878%\"\u003e\n \u003cp\u003e\u003cstrong\u003eGirls (n=28,405)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.294117647058824%\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.294117647058824%\"\u003e\n \u003cp\u003e\u003cstrong\u003eP for trend\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.647058823529413%\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.647058823529413%\"\u003e\n \u003cp\u003e\u003cstrong\u003eP for trend\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.647058823529413%\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.470588235294116%\"\u003e\n \u003cp\u003e\u003cstrong\u003eP for trend\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003eUnhealthy dietary habit\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e0.184\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.463917525773196%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Low\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.463917525773196%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"14.43298969072165%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Moderate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e1.13 (1.05, 1.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e1.08 (0.97, 1.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.463917525773196%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e1.17 (1.07, 1.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"14.43298969072165%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;High\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e1.15 (1.07, 1.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e1.09 (0.98, 1.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.463917525773196%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e1.20 (1.10, 1.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"14.43298969072165%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003ePhysical inactivity\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e0.114\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.463917525773196%\"\u003e\n \u003cp\u003e0.055\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"14.43298969072165%\"\u003e\n \u003cp\u003e0.934\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Low\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.463917525773196%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"14.43298969072165%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Moderate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e1.03 (0.96, 1.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e1.02 (0.93, 1.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.463917525773196%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e1.03 (0.93, 1.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"14.43298969072165%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;High\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e1.04 (0.98, 1.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e1.07 (0.99, 1.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.463917525773196%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e1.00 (0.92, 1.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"14.43298969072165%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003eUnhealthy sedentary behavior\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Low\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.463917525773196%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"14.43298969072165%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Moderate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e1.06 (1.01, 1.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e0.98 (0.91, 1.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.463917525773196%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e1.12 (1.04, 1.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"14.43298969072165%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;High\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e1.53 (1.43, 1.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e1.33 (1.21, 1.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.463917525773196%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e1.65 (1.51, 1.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"14.43298969072165%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003eTobacco use\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Low\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.463917525773196%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"14.43298969072165%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Moderate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e1.65 (1.46, 1.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e1.49 (1.28, 1.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.463917525773196%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e2.14 (1.73, 2.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"14.43298969072165%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;High\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e1.57 (1.41, 1.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e1.44 (1.26, 1.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.463917525773196%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e2.54 (2.01, 3.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"14.43298969072165%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003eExposure to school violence\u003csup\u003e5\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Low\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.463917525773196%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"14.43298969072165%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Moderate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e1.79 (1.69, 1.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e1.58 (1.45, 1.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.463917525773196%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e2.07 (1.90, 2.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"14.43298969072165%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;High\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e3.06 (2.88, 3.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e2.83 (2.61, 3.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.463917525773196%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e3.40 (3.10, 3.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"14.43298969072165%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003eInsufficient interaction with parents\u003csup\u003e6\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Low\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.463917525773196%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"14.43298969072165%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Moderate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e1.17 (1.12, 1.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e1.16 (1.08, 1.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.463917525773196%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e1.18 (1.11, 1.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"14.43298969072165%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;High\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e2.09 (1.92, 2.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e2.33 (2.05, 2.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.463917525773196%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e1.95 (1.74, 2.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"14.43298969072165%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003eInsufficient interaction with friends\u003csup\u003e7\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Low\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.463917525773196%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"14.43298969072165%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Moderate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e1.39 (1.32, 1.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e1.21 (1.12, 1.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.463917525773196%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e1.51 (1.41, 1.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"14.43298969072165%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;High\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e1.82 (1.69, 1.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e1.39 (1.25, 1.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.463917525773196%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e2.24 (2.03, 2.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"14.43298969072165%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNotes: OR: odds ratio; CI: confidence interval. Multilevel logistic regression models were used to estimate the ORs and corresponding 95% CIs. The total sample analysis was adjusted for age, sex, socioeconomic status, and national literacy rate. The subgroup analyses used the same model and was adjusted for age, socioeconomic status, and national literacy rate.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003eUnhealthy dietary habit considered intake of fruits, vegetables, fast food, and soft drinks.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2\u003c/sup\u003eLow risk of physical inactivity for adolescents was defined as engaging in vigorous physical activity for at least 1 hour 6 days per week.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e3\u003c/sup\u003eLow risk of unhealthy sedentary behavior for adolescents was defined as having less than 1 hour of screen time per day.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e4\u003c/sup\u003eLow risk of tobacco use for adolescents was defined as using cigarettes or any other form of tobacco on fewer than 3 days last month. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e5\u003c/sup\u003e Exposure to school violence considered physical attack, fight, injury, and bulling.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e6\u003c/sup\u003e Interactions with parents considered frequency of missing school without permission and participants think their parents understand problems.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e7\u003c/sup\u003eInteractions with friends considered number of close friends and if participants found their classmates kind and helpful.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Sedentary behavior, dietary habit, tobacco use, peer and family relationships, school violence","lastPublishedDoi":"10.21203/rs.3.rs-1402117/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1402117/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Mental illness has become a widespread public health concern internationally. This study aimed to generate a depression risk index for adolescents. Furthermore, we developed risk indexes for potential lifestyle and social risk factors of depression among adolescents. In addition, we investigated the country-specific prevalence for each risk index. Finally, we conducted comprehensive assessment of the associations between depression risk and lifestyle and social risk factors.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eWe used the most recent data available from 20 nationally representative Global School-based Student Health Surveys. Our analytical sample included 51,597 adolescents. The outcome of interest was depression risk, which considered feelings of anxiety, loneliness, and suicidal attempts or tendencies. We developed four lifestyle risk indexes (dietary habits, physical activity, sedentary behavior, and tobacco use) and three social risk indexes (exposure to school violence, interactions with parents, and interactions with friends) which were considered as exposure variables in this study. Multilevel logistic regression models were used to estimate adjusted odds ratios (ORs) with 95% confidence intervals (CIs).\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e In total, 26.4% of the participants had a risk of depression. Increased odds of depression risk were found among participants with high risk index values for unhealthy dietary habits (OR, 1.15; 95% CI, 1.07–1.23), unhealthy sedentary behavior (OR, 1.53; 95% CI, 1.43–1.63), tobacco use (OR, 1.57; 95% CI, 1.41–1.76), exposure to school violence (OR, 3.06; 95% CI, 2.88–3.26), insufficient interactions with parents (OR, 2.09; 95% CI, 1.92–2.28), and insufficient interactions with friends (OR, 1.82; 95% CI, 1.69–1.96) compared with participants with low risk index values. However, there were no significant associations between physical inactivity and risk of depression among adolescent boys or girls. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e High prevalence rates for depression risk, as well as unhealthy lifestyle factors and social behaviors among adolescents were found in every country, and higher risk index values were associated with increased risk of depression.\u003c/p\u003e","manuscriptTitle":"Comprehensive assessment of depression risk and its behavioral determinants among adolescents: a multi-country study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-03-11 16:35:15","doi":"10.21203/rs.3.rs-1402117/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"cf19c17c-1abf-4e2c-95e1-c0bf88f60d4f","owner":[],"postedDate":"March 11th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2022-05-12T06:44:13+00:00","versionOfRecord":[],"versionCreatedAt":"2022-03-11 16:35:15","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1402117","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1402117","identity":"rs-1402117","version":["v1"]},"buildId":"rHA-KDH7Qsr4HCuvH75dn","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}