Abstracts

Introduction

Mental disorders often coexist with noncommunicable diseases (NCDs). Depression tends to be classified as a mental NCD ¹1. Pryor L, Da Silva MA, Melchior M. Mental health and global strategies to reduce NCDs and premature mortality. Lancet 2017; 2:e350. and have a bidirectional association with other NCDs ²2. Anwar N, Kuppili PP, Balhara YPS. Depression and physical noncommunicable diseases: the need for an integrated approach. WHO South East Asia J Public Health 2017; 6:12-7.. Social determinants of poverty act primarily on depression and increase the future risk of other NCDs ³3. Stein DJ, Benjet C, Gureje O, Lund C, Scott KM, Poznyak V, et al. Integrating mental health with other non-communicable diseases. BMJ 2019; 365 Suppl 1:13-6. whereas side effects of antidepressants may cause weight gain ²2. Anwar N, Kuppili PP, Balhara YPS. Depression and physical noncommunicable diseases: the need for an integrated approach. WHO South East Asia J Public Health 2017; 6:12-7.. Moreover, NCDs can increase morbidity and drugs used for their treatment could aggravate psychiatric symptoms ⁴4. National Collaborating Centre for Mental Health. Depression in adults with a chronic physical health problem: treatment and management. Leicester: British Psychological Society/Royal College of Psychiatrists; 2010. (National Clinical Practice Guideline, 91)., especially in adulthood.

Considering the bidirectional relationships between depression and other NCDs, obesity emerges as a metabolic risk factor for NCDs of physical scope ⁵5. Sharma V, Susanne C, Jane N, Sharples L, Hamilton-Shield J, Rutter H, et al. A systematic review and meta-analysis estimating the population prevalence of comorbidities in children and adolescents aged 5 to 18 years. Obes Rev 2019; 20:1341-9. which is consistently associated with depression ⁶6. Mannan M, Mamun A, Doi S, Clavarino A. Prospective associations between depression and obesity for adolescent males and females: a systematic review and metaanalysis of longitudinal studies. PLoS One 2016; 11:e0157240.. Common risk factors could therefore be involved in the complex relationships between obesity, depression, and NCDs in adolescents.

According to the World Health Organization (WHO), NCDs are mostly driven by four major risk factors: unhealthy diet, physical inactivity, smoking, and the harmful use of alcohol ⁷7. World Health Organization. Noncommunicable diseases. https://www.who.int/news-room/fact-sheets/detail/noncommunicable-diseases (accessed on 10/Dec/2018).
https://www.who.int/news-room/fact-sheet... . These factors increase metabolic risk and are associated with mental disorders, depression, and suicide risk ⁸8. Danqing H, Lixiao C, Wenjie J. Sugar-sweetened beverages consumption and the risk of depression: a meta-analysis of observational studies. J Affect Disord 2019; 245:348-55. in individuals, including adolescents ⁹9. Jacob L, Stubbs B, Koyanagi A. Consumption of carbonated soft drinks and suicide attempts among 105,061 adolescents aged 12 and 15 years from 6 high-income, 22 middle-income, and 4 low-income countries. Clin Nutr 2019; 39:886-92.. They can also induce inflammation, which is an underlying mechanism of all of these diseases ¹⁰10. Bennett JM, Reeves G, Billman GE, Sturmberg JP. Inflammation-nature's way to efficiently respond to all types of challenges: implications for understanding and managing "the epidemic" of chronic diseases. Front Med 2018; 5:316., and thus triggering or aggravating depression and suicide risk ¹¹11. Hryhorczuk C, Sharma S, Fulton SE. Metabolic disturbances connecting obesity and depression. Front Neurosci 2013; 7:177.^,1212. Batty GD, Jung KJ, Lee S, Back JH, Jee SH. Systemic inflammation and suicide risk: cohort study of 419 527 Korean men and women. J Epidemiol Community Health 2018; 72:572-4..

The cooccurence of risk factors for NCDs characterizes an unhealthy lifestyle ⁸8. Danqing H, Lixiao C, Wenjie J. Sugar-sweetened beverages consumption and the risk of depression: a meta-analysis of observational studies. J Affect Disord 2019; 245:348-55.^,1313. Gobbi G, Atkin T, Zytynski T, Wang S, Askari S, Boruff J, et al. Association of cannabis use in adolescence and risk of depression, anxiety, and suicidality in young adulthood: a systematic review and meta-analysis. JAMA Psychiatry 2019; 76:426-34.^,1414. Xu H, Guo J, Wan Y, Zhang S, Yang R, Xu H, et al. Association between screen time, fast foods, sugar-sweetened beverages and depressive symptoms in Chinese adolescents. Front Psychiatry 2020; 11:458.. The cross-sectional, nationwide, school-based study found that 5.7% of adolescents smoked ¹⁵15. Figueiredo VC, Szklo AS, Costa LC, Kuschnir MCC, Silva TLN, Bloch KV, et al. ERICA: prevalência de tabagismo em adolescentes brasileiros. Rev Saúde Pública 2016; 50 Suppl 1:12s., 21% had consumed alcohol on at least one occasion in the last 30 days ¹⁶16. Coutinho ESF, França-Santos D, Magliano ES, Bloch KV, Barufaldi LA, Cunha CF, et al. ERICA: padrões de consumo de bebidas alcoólicas em adolescentes brasileiros. Rev Saúde Pública 2016; 50 Suppl 1:8s., and 52.4% were physically inactive ¹⁷17. Bezerra MKAB, Carvalho EF, Oliveira JS, Cesse EÂP, Lira PICl, Cavalcante JGT. Estilo de vida de adolescentes estudantes de escolas públicas e privadas em Recife: ERICA. Ciênc Saúde Colet 2021; 26:221-32.. Data from the Brazilian Household Budget Survey (POF) 2017/2018 ¹⁸18. Instituto Brasileiro de Geografia e Estatística. Pesquisa de Orçamentos Familiares 2017-2018: análise do consumo alimentar pessoal no Brasil. Rio de Janeiro: Instituto Brasileiro de Geografia e Estatística; 2020. show that adolescents have lower nutritional quality diet markers per capita and a higher consumption of sandwich biscuit, soft drinks, dairy beverages, chips, sandwiches, and pizzas.

Risk factors associated with depression and suicide risk in complex relationships must be further investigated. Regarding limitations, previous studies often selected only one risk factor as exposure without adjusting for the other risk factors for NCDs. Furthermore, many studies based on self-reports or symptoms and not on diagnostic measures could make inconsistent associations between major risk factors for NCDs and depression or suicide risk ⁸8. Danqing H, Lixiao C, Wenjie J. Sugar-sweetened beverages consumption and the risk of depression: a meta-analysis of observational studies. J Affect Disord 2019; 245:348-55.^,1313. Gobbi G, Atkin T, Zytynski T, Wang S, Askari S, Boruff J, et al. Association of cannabis use in adolescence and risk of depression, anxiety, and suicidality in young adulthood: a systematic review and meta-analysis. JAMA Psychiatry 2019; 76:426-34..

Depression is a known risk factor for suicide risk and the second leading cause of death among young people aged from 15 to 29 years worldwide ¹⁹19. Pan American Health Organization. Social determinants and health risks, chronic non-communicable diseases and mental health. https://www.paho.org/bra/index.php?option=com_content&view=article&id=5671:folha-informativa-suicidio&Itemid=839 (accessed on 02/Nov/2019).
https://www.paho.org/bra/index.php?optio... . Death rates are increasing among adolescents and suicide has become a major preventable public health problem. Adolescents aged 10 to 19 years in Brazil have a 8.25% ²⁰20. Cicogna JIR, Hillesheim D, Hallal ALLC. Mortalidade por suicídio de adolescentes no Brasil: tendência temporal de crescimento entre 2000 e 2015. J Bras Psiquiatr 2019; 68:1-7. prevalence of suicide and 17% prevalence of depression ²¹21. Munhoz TN, Santos IS, Matijasevich A. Depression among Brazilian adolescents: a cross-sectional population-based study. J Affect Disord 2015; 175:281-6.. We hypothesize that the major risk factors for NCDs are associated with depression and suicide risk in adolescence, which could cause clusters of NCDs and mental health disorders in adulthood. Therefore, this study estimated the association of the major risk factors for NCDs with depression and suicide risk by structural equation modeling (SEM) considering pathways triggered by social vulnerability or mediated by obesity.

Methods

Study design

This cross-sectional study was conducted using a population-based sample derived from the RPS Brazilian Birth Cohorts Consortium (Ribeirão Preto, Pelotas and São Luís) follow-up at 18-19 years old. This study used data from the 1997 São Luís Birth Cohort obtained during the follow-up of adolescents (18-19 years old) from January to November 2016.

The sample included all participants from the original cohort who participated in the follow-up (n = 687). At that time, more adolescents born in São Luís (Maranhão State) in 1997 were included to increase sample power and prevent future losses (n = 1,828). These adolescents were selected from a random sample (n = 1,133) using the Brazilian Information System on Live Births (SINASC) database or among volunteers identified in schools and universities (n = 695), as long as they were in the SINASC database. This population-based study included 2,515 Brazilian adolescents.

Data collection procedures

The following information was collected using questionnaires: adolescent’s sex, schooling level, economic class, monthly household income, cigarette smoking, illicit drug use, consumption of alcoholic beverages, physical activity, food intake, and diagnosis of depression and suicide risk, and schooling level of the head of household.

Sex was dichotomized into male and female. The schooling level of the head of household and of the adolescent was categorized into elementary school, high school, and higher education. The economic class was categorized into A, B, C, and D/E based on the Brazilian Economic Classification Criteria (CCEB) ²²22. Associação Brasileira de Empresas de Pesquisa. Critério de Classificação Econômica Brasil. http://www.abep.org/criterio-brasil (accessed on 20/Dec/2019).
http://www.abep.org/criterio-brasil... . Monthly household income was based on the Brazilian minimum wage in 2016 (USD 270.76).

Cigarette smoking was dichotomized into no and yes. Substance use (never used, previously used, or currently using) and consumption of alcoholic beverages were evaluated using the Alcohol Use Disorders Identification Test (AUDIT) and divided into low and high risk ²³23. Moretti-Pires RO, Corradi-Webster CM. Adaptação e validação do Alcohol Use Disorder Identification Test (AUDIT) para população ribeirinha do interior da Amazônia, Brasil. Cad Saúde Pública 2011; 27:497-509..

Physical activity was assessed by the Self-Administered Physical Activity Checklist (SAPAC) ²⁴24. Sallis JF, Strikmiller PK, Harsha DW, Feldman HA, Ehlinger S, Stone EJ, et al. Validation of interviewer-and self-administered physical activity checklists for fifth grade students. Med Sci Sports Exerc 1996; 28:840-51.. The adolescents were classified as physically active (≥ 150 minutes of physical activity/week) or physically inactive (< 150 minutes of physical activity/week).

Food intake was obtained with a validated food frequency questionnaire (FFQ) containing 106 items ²⁵25. Schneider BC, Motta JVDS, Muniz LC, Bielemann RM, Madruga SW, Orlandi SP, et al. Desenho de um questionário de frequência alimentar digital autoaplicado para avaliar o consumo alimentar de adolescentes e adultos jovens: coortes de nascimentos de Pelotas, Rio Grande do Sul. Rev Bras Epidemiol 2016; 19:419-32.. Details of the FFQ methodology were published by Sousa et al. ²⁶26. Sousa RS, Bragança MLBM, Oliveira BR, Coelho CCNS, Silva AAM. Association between the degree of processing of consumed foods and sleep quality in adolescents. Nutrients 2020; 12:462.. Unhealthy eating markers were added sugar and saturated fat consumption. Added sugar intake was the percentage of calories from sugar of the total daily energy intake, found in soft drinks, fruit-flavored juice, chocolate drinks, energy drinks, and in a wide range of food groups, including dairy products, bread, cookies, breakfast cereals, desserts, chocolate, mayonnaise, salty snacks, and cold cuts. Saturated fat intake was also estimated as the percentage of calories from saturated fat of total daily energy intake, found in fast food, salty snacks, sweets, meat, chicken, fish, eggs, and milk and dairy products. Added sugar and saturated fat intake were analyzed as continuous variables.

Fat mass was determined by dual-energy X-ray absorptiometry (DXA) and height was measured with a stadiometer (Altura Exata; http://www.alturexata.com.br/). The fat mass index (FMI), corresponding to fat mass (kg) calculated by DXA and divided by the height in square meters (m²), was used to measure obesity.

Depression and suicide risk were diagnosed by the Mini-International Neuropsychiatric Interview (MINI) ²⁷27. Amorim P. Mini International Neuropsychiatric Interview (MINI): validation of a short structured diagnostic psychiatric interview. Rev Bras Psiquiatr 2000; 22:106-15.. Participants were diagnosed with depression based on the occurrence of major depressive and recurrent major depressive episodes. Suicide risk was categorized as low (score ranging 1-5) and high (score ≥ 6).

Latent variables

The following latent variables were used:

Socioeconomic status: deduced from the shared variance of the head of household’s and the adolescent’s schooling level, economic class according to CCEB criterion, and monthly household income;

Substance use behaviors: deduced from the shared variance of cigarette smoking, illicit drug use, and consumption of alcoholic beverages.

Proposed theoretical model

The latent variable socioeconomic status was considered as a more distal determinant that affects other variables of the model. Sex also affects socioeconomic status, substance use behaviors, physical inactivity, added sugar, saturated fat, FMI, depression, and suicide risk. The following exposures of interest were the major risk factors for NCDs: substance use behaviors, physical inactivity, and unhealthy eating markers. Obesity - represented by FMI - was considered a mediator since it could be chain linking the risk factors for NCDs to depression or suicide risk (Figure 1).

Statistical analysis

The descriptive data were analyzed using the Stata software, version 14.0 (https://www.stata.com). Categorical variables were described by absolute and relative frequencies. Depression and suicide risk were assessed in separate models by SEM. Factor loadings > 0.5 were considered as an indication that the factor influences the variable in the confirmatory factor analysis. The root mean square error of approximation (RMSEA) with an upper limit of the 90% confidence interval (90%CI) < 0.08 and a comparative fit index (CFI) and Tucker-Lewis index (TLI) > 0.95 were considered as indicators of adequate model fit. The weighted least squares means and variance adjusted (WLSMV) estimator and theta parameterization were used. The goodness-of-fit of the structural equation model was assessed based on the same estimates as described for the confirmatory factor analysis ²⁸28. Byrne BM. Structural equation modeling with Mplus: basic concepts, applications and programming. New York: Routledge; 2012. using the Mplus 7.0 software (https://www.statmodel.com/).

Firstly, to represent the unhealthy diet, added sugar and saturated fat consumption was analyzed, considering that these are the main components of the investigated diet associated with mental disorders ⁸8. Danqing H, Lixiao C, Wenjie J. Sugar-sweetened beverages consumption and the risk of depression: a meta-analysis of observational studies. J Affect Disord 2019; 245:348-55.^,1414. Xu H, Guo J, Wan Y, Zhang S, Yang R, Xu H, et al. Association between screen time, fast foods, sugar-sweetened beverages and depressive symptoms in Chinese adolescents. Front Psychiatry 2020; 11:458.^,2929. Mikolajczyk RT, Ansari WE, Maxwell AE. Food consumption frequency and perceived stress and depressive symptoms among students in three European countries. Nutr J 2009; 8:31.^,3030. Jacob L, Stubbs B, Firth J, Smith L, Haro JM, Koyanagi A. Fast food consumption and suicide attempts among adolescents aged 12-15 years from 32 countries. J Affect Disord 2020; 266:63-70.. Then, sugar was analyzed as a separate component of diet because of its addictive potential in the central nervous system ³¹31. Jacques A, Chaaya N, Beechera K, Ali SA, Belmera A, Bartletta S. The impact of sugar consumption on stress driven, emotional and addictive behaviors. Neuros Biob Rev 2019; 103:178-99.. Furthermore, latent variables of healthy diet components (fiber [g], fruits [g], and vegetables [g]) and unhealthy diet components (fast food [g], salty snacks [g], sweet foods [g], and sugar-sweetened beverages [g]) were tested as analyses of consistency, replacing added sugar and saturated fat consumption in the theoretical model associated with depression and suicide risk, and analyzed by SEM (Supplementary Material; http://cadernos.ensp.fiocruz.br/static//arquivo/suppl-e00055621_6499.pdf).

This project was approved by the Research Ethics Committee of the University Hospital of the Federal University of Maranhão (HU-UFMA; approval n. 1,302,489, on October 29, 2015) and all participants signed an informed consent form.

Results

Among the 2,515 adolescents included in the study, 3.6% (n = 89) smoked, 19.4% (n = 489) consumed high levels of alcohol, 18.1% (n = 450) were using or had used illicit drugs before, and 44.9% (n = 1,123) were physically inactive. Regarding mental disorders, 11.8% (n = 296) of the adolescents were diagnosed with depression and 5.5% (n = 139) had a high suicide risk (Table 1). The mean percent of total calories per day from added sugar consumption was 8.76%Kcal (SD±4.66) and the mean percent of total calories per day from saturated fat was 8.82%Kcal (SD±2.18).

Both the depression model (RMSEA = 0.043; 90%CI: 0.039-0.048; CFI = 0.988; TLI = 0.981) and the suicide risk model (RMSEA = 0.043; 90%CI: 0.039-0.048; CFI = 0.988; TLI = 0.980) showed good fit (Table 2). All effect indicators of the latent variables (socioeconomic status and substance use behaviors) showed good convergent validity, with factor loadings higher than 0.5 in the two models (Table 3).

In the depression model, a better household socioeconomic status was inversely associated with depression (standardized coefficient [SC] = -0.110; p = 0.006) whereas substance use behaviors (SC = 0.304; p < 0.001), higher added sugar consumption (SC = 0.094; p = 0.005), and females (SC = 0.310; p < 0.001) were positively associated with depression. Saturated fat consumption was not associated with depression (Table 4). Socioeconomic status increased the values of FMI (SC = 0.116; p < 0.001) and of saturated fat consumption (SC = 0.097; p < 0.001), but was not associated with added sugars (SC = -0.019; p = 0.441) (data not shown).

Similarly, in the suicide risk model, a better household socioeconomic status was inversely associated with suicide risk (SC = -0.090; p = 0.040) whereas substance use behaviors (SC = 0.356; p < 0.001), higher added sugar consumption (SC = 0.100; p = 0.012), and the female sex (SC = 0.207; p < 0.001) were positively associated with suicide risk. Saturated fat consumption was not associated with suicide risk (Table 4). Socioeconomic status increased the values of FMI (SC = 0.116; p ≤ 0.001) and of saturated fat consumption (SC = 0.097; p ≤ 0.001), but was not associated with added sugars (SC = -0.019; p = 0.441) (data not shown).

The unhealthy eating markers were correlated with each other in the depression (SC = 0.408; p ≤ 0.001) and suicide risk model (SC = 0.408; p < 0.001).

During consistency analyses, we regressed the model using the healthy diet and unhealthy diet latent variables and found that unhealthy diet was associated with depression (SC = 0.142; p = 0.004) and the risk of suicide (SC = 0.207; p = 0.010) (Supplementary Material; http://cadernos.ensp.fiocruz.br/static//arquivo/suppl-e00055621_6499.pdf). Then, we analyzed each component of unhealthy diet (fast food, salty snacks, sweet foods, sugar-sweetened beverages) in the proposed model, replacing added sugar and saturated fat, and found that they were all associated with depression (p < 0.05) and suicide risk (p < 0.05). However, when fast food and salty snacks were assessed in the model using a correlation command to sugar consumption, neither were associated to depression and suicide risk (Supplementary Material; http://cadernos.ensp.fiocruz.br/static//arquivo/suppl-e00055621_6499.pdf).

Discussion

The major risk factors for NCDs (substance use behaviors and added sugar consumption) were associated with both depression and suicide risk in adolescents. Regarding unhealthy eating markers, only added sugar consumption was associated with mental disorders. The female sex was also associated with depression and suicide risk. As a more distal determinant, a better socioeconomic status protected individuals against both depression and suicide risk.

Substance use behaviors composed a latent variable deduced from the shared variance of cigarette smoking, illicit drug use, and consumption of alcoholic beverages. This variable was strongly associated with both depression and suicide risk in adolescents. The early use of psychoactive substances has also been shown to be related to depression and suicide risk ¹³13. Gobbi G, Atkin T, Zytynski T, Wang S, Askari S, Boruff J, et al. Association of cannabis use in adolescence and risk of depression, anxiety, and suicidality in young adulthood: a systematic review and meta-analysis. JAMA Psychiatry 2019; 76:426-34.^,3232. Kokkevi A, Richardson C, Olszewski D, Matias J, Monshouwer K, Bjarnason T. Multiple substance use and self-reported suicide attempts by adolescents in 16 European countries. Eur Child Adolesc Psychiatry 2012; 21:443-50.^,3333. Nyundo A, Manu A, Regan M, Ismail A, Chukwu A, Dessie Y. Factors associated with depressive symptoms and suicidal ideation and behaviours amongst sub-Saharan African adolescents aged 10-19 years: cross-sectional study. Trop Med Int Health 2020; 25:54-69.. One explanatory mechanism is that smoking leads to dysregulation of the hypothalamic-pituitary-adrenal axis and to hypersecretion of cortisol, which can induce depression ³⁴34. Rose JE, Behm FM, Ramsey C, Ritchie Jr. JC. Platelet monoamine oxidase, smoking cessation, and tobacco withdrawal symptoms. Nicotine Tob Res 2001; 3:383-90.. However, we cannot rule out a reverse causality, in which depressed individuals are at higher risk of cigarette smoking and psychoactive substance use ³⁵35. Pedrelli P, Shapero B, Archibald A, Dale C. Alcohol use and depression during adolescence and young adulthood: a summary and interpretation of mixed findings. Curr Addict Rep 2016; 3:91-7..

Our study found that added sugar consumption was associated with depression and suicide risk, corroborating with previous reports ⁸8. Danqing H, Lixiao C, Wenjie J. Sugar-sweetened beverages consumption and the risk of depression: a meta-analysis of observational studies. J Affect Disord 2019; 245:348-55.^,99. Jacob L, Stubbs B, Koyanagi A. Consumption of carbonated soft drinks and suicide attempts among 105,061 adolescents aged 12 and 15 years from 6 high-income, 22 middle-income, and 4 low-income countries. Clin Nutr 2019; 39:886-92.^,3636. Michael SL, Lowry R, Merlo C, Cooper AC, Hyde ET, McKeon R. Physical activity, sedentary, and dietary behaviors associated with indicators of mental health and suicide risk. Prev Med Rep 2020; 19:101153.^,3737. Ati NAL, Paraswati MD, Windarwati HD. What are the risk factors and protective factors of suicidal behavior in adolescents? A systematic review. J Child Adolesc Psychiatr Nurs 2021;34:7-18.. Consuming added sugars induces addiction and is correlated with other addictive behaviors, including alcoholism, smoking, and illicit drug use ³⁸38. Kearns CE, Lisha NE, Ling PM. Soda intake and tobacco use among young adult bar patrons: a cross-sectional study in seven cities. Prev Med Rep 2018; 10:195-9.; the exposure to these addictive substances is, in turn, associated with depression and suicide risk ³²32. Kokkevi A, Richardson C, Olszewski D, Matias J, Monshouwer K, Bjarnason T. Multiple substance use and self-reported suicide attempts by adolescents in 16 European countries. Eur Child Adolesc Psychiatry 2012; 21:443-50.^,3333. Nyundo A, Manu A, Regan M, Ismail A, Chukwu A, Dessie Y. Factors associated with depressive symptoms and suicidal ideation and behaviours amongst sub-Saharan African adolescents aged 10-19 years: cross-sectional study. Trop Med Int Health 2020; 25:54-69.^,3535. Pedrelli P, Shapero B, Archibald A, Dale C. Alcohol use and depression during adolescence and young adulthood: a summary and interpretation of mixed findings. Curr Addict Rep 2016; 3:91-7..

A meta-analysis indicated that the higher the frequency of sugar-sweetened beverages consumption, the higher the risk of having depression; however, this analysis found inconsistencies in the diagnosis of depression and emphasized the need to better adjust for confounders ⁸8. Danqing H, Lixiao C, Wenjie J. Sugar-sweetened beverages consumption and the risk of depression: a meta-analysis of observational studies. J Affect Disord 2019; 245:348-55.. A population-based study involving adolescents found an association between a higher frequency of sugar-sweetened beverages consumption and suicidal behavior ⁹9. Jacob L, Stubbs B, Koyanagi A. Consumption of carbonated soft drinks and suicide attempts among 105,061 adolescents aged 12 and 15 years from 6 high-income, 22 middle-income, and 4 low-income countries. Clin Nutr 2019; 39:886-92.. Our study corroborates with the topic since depression and suicide risk outcomes were measured using a validated diagnostic instrument MINI ²⁷27. Amorim P. Mini International Neuropsychiatric Interview (MINI): validation of a short structured diagnostic psychiatric interview. Rev Bras Psiquiatr 2000; 22:106-15.. Moreover, SEM allowed adjusting for confounders, including other diet components and direct path analysis.

Added sugar consumption could be associated with depression and suicide risk in adolescents because the fructose in these beverages affects the hypothalamus-pituitary-adrenal axis ³⁹39. DiNicolantonio JJ, Mehta V, Onkaramurthy N, O'Keefe JH. Fructose-induced inflammation and increased cortisol: a new mechanism for how sugar induces visceral adiposity. Prog Cardiovasc Dis 2018; 61:3-9.. Furthermore, sugar-rich diets can increase inflammation and neurodegeneration ⁴⁰40. van der Borght K, Köhnke R, Göransson N, Deierborg T, Brundin P, Erlanson-Albertsson C, et al. Reduced neurogenesis in the rat hippocampus following high fructose consumption. Regul Pept 2011; 167:26-30.. Persistent hyperglycemia can lead to the synthesis of reactive oxygen species that exert neurotoxic effects on the brain ⁴¹41. Beckhauser TF, Francis-Oliveira J, De Pasquale R. Reactive oxygen species: physiological and physiopathological effects on synaptic plasticity. J Exp Neurosci 2016; 10 Suppl 1:S23-48.. The consumption of added sugar can cause insulin resistance, which is also a known risk factor for depression ⁴²42. Bruce DG, Davis WA, Starkstein SE, Davis TME. Clinical risk factors for depressive syndrome in type 2 diabetes: the Fremantle Diabetes Study. Diabet Med 2018; 35:903-10. and suicidal behavior ⁴³43. Koponen H, Kautiainen H, Leppanen E, Mäntyselkä P, Vanhala M. Association between suicidal behaviour and impaired glucose metabolism in depressive disorders. BMC Psychiatry 2015; 15:163..

Saturated fats, fast foods, and salty snacks were not associated with depression or suicide risk when the model adjustment included added sugar consumption. These findings are contrary to previous studies, which show that the consumption of food rich in trans and saturated fats are associated with symptoms of depression ²⁹29. Mikolajczyk RT, Ansari WE, Maxwell AE. Food consumption frequency and perceived stress and depressive symptoms among students in three European countries. Nutr J 2009; 8:31. and suicide risk ³⁰30. Jacob L, Stubbs B, Firth J, Smith L, Haro JM, Koyanagi A. Fast food consumption and suicide attempts among adolescents aged 12-15 years from 32 countries. J Affect Disord 2020; 266:63-70.. One study grouped foods to reduce the correlation among unhealthy items (sweets, cake/cookies, snacks, and fast food) in multiple logistic regression models to depression ²⁹29. Mikolajczyk RT, Ansari WE, Maxwell AE. Food consumption frequency and perceived stress and depressive symptoms among students in three European countries. Nutr J 2009; 8:31.. Another study included soft drink adjustment in the association between foods rich in trans/saturated fats with suicide risk ³⁰30. Jacob L, Stubbs B, Firth J, Smith L, Haro JM, Koyanagi A. Fast food consumption and suicide attempts among adolescents aged 12-15 years from 32 countries. J Affect Disord 2020; 266:63-70., without considering the correlation among these components. A high correlation between added sugar consumption and saturated fat consumption was observed in the depression model (SC = 0.408; p < 0.001) and in the suicide risk models (SC = 0.408; p < 0.001) (data not shown). Altogether, these findings allowed us to speculate that added sugar consumption is the main component of an unhealthy diet associated with depression and suicide risk.

Studies have shown that physical activity is a protective factor against depression ⁴⁴44. Schuch FB, Vancampfort D, Firth J, Rosenbaum S, Ward PB, Silva ES, et al. Physical activity and incident depression: a meta-analysis of prospective cohort studies. Am J Psychiatr 2018; 175:631-48. and suicide risk in youngsters ⁴⁵45. Pfledderer CD, Burns RD, Brusseau TA. School environment, physical activity, and sleep as predictors of suicidal ideation in adolescents: evidence from a national survey. J Adolesc 2019; 74:83-90. which adjusts to smoking but not to other behavioral risks, including unhealthy diet and alcohol. In depressed individuals, physical activity can increase neurogenesis and hippocampal volume ⁴⁶46. Erickson KI, Leckie RL, Weinstein AM. Physical activity, fitness and gray matter volume. Neurobiol Aging 2014; 35 Suppl 2:S20-8. and balance anti-inflammatory and proinflammatory markers ⁴⁷47. Toups MSP, Rethorst C, Carmody T, Trivedi MH. Cytokines in the relationship between exercise treatment and anhedonia and changes in arousal in depressed subjects. Biol Psychiatry 2014; 75:48S.. However, physical inactivity in adolescents was not associated with depression and suicide risk in our study. This could be because of the model adjustment to components of unhealthy lifestyle and the correlation among them in adolescence. A study which showed that physical activity protects against the risk of suicide ⁴⁵45. Pfledderer CD, Burns RD, Brusseau TA. School environment, physical activity, and sleep as predictors of suicidal ideation in adolescents: evidence from a national survey. J Adolesc 2019; 74:83-90. did not adjust the model to unhealthy diet, alcohol consumption, and smoking.

Higher body fat levels were not associated with depression or suicide risk in adolescents. Other studies showed that obesity was associated with depression ⁴⁸48. Quek YH, Tam WWS, Zhang MWB, Ho RCM. Exploring the association between childhood and adolescent obesity and depression: a meta-analysis. Obes Rev 2017; 18:742-54. and suicide risk ⁴⁹49. Perera S, Eisen RB, Dennis BB, Bawor M, Bhatt M, Bhatnagar N, et al. Body mass index is an important predictor for suicide: results from a systematic review and meta-analysis. Suicide Life Threat Behav 2016; 46:697-736. since visceral fat increases the levels of inflammation ¹¹11. Hryhorczuk C, Sharma S, Fulton SE. Metabolic disturbances connecting obesity and depression. Front Neurosci 2013; 7:177.^,1212. Batty GD, Jung KJ, Lee S, Back JH, Jee SH. Systemic inflammation and suicide risk: cohort study of 419 527 Korean men and women. J Epidemiol Community Health 2018; 72:572-4. and because obese adolescents with depression had insulin resistance and lower hippocampal volume ⁵⁰50. Singh MK, Leslie SM, Packer MM, Zaiko YV, Phillips OR, Weisman EF, et al. Brain and behavioral correlates of insulin resistance in youth with depression and obesity. Horm Behav 2019; 108:73-83.. However, common causes of insulin resistance, including added sugar consumption and alcohol abuse, were consistently associated with depression and suicide risk in our results and could precede the association between obesity and mental disorders.

A better household socioeconomic status protected individuals against depression and suicide risk. The effect of socioeconomic status was direct and not mediated by the major risk factors for NCDs. Other untested paths could explain the association between social vulnerability and increased depression and suicide risk, including a greater exposure to violence and epigenetic inflammatory mechanisms that can occur in deprived environments throughout life.

This study has some limitations. The cross-sectional design of the study does not allow us to affirm temporality between the major risk factors for NCDs and mental disorders nor to rule out reverse causality or bidirectionality in the associations found. However, to the best of our knowledge, this is the first study to analyze all the major behavior risk factors for NCDs according to WHO, showing that substance use behaviors and added sugar intake already affect depression and increase suicide risk in adolescents, regardless of the social vulnerability. These findings could help explain the clustering of mental health disorders and NCDs in adulthood. A strong point of our study is the use of fat mass index, and not body mass index, to measure obesity.

The major risk factors for NCDs, including substance use behaviors and added sugar consumption, were associated with depression and suicide risk behavior in adolescents. Our results indicate that coordinated actions are essential to surveil, to prevent, and to control NCDs and mental disorders according to the WHO Cluster of Noncommunicable Diseases and Mental Health (NMH) ⁵¹51. World Health Organization. About noncommunicable diseases and mental health. https://www.who.int/nmh/about/en/ (accessed on 14/Jun/2020).
https://www.who.int/nmh/about/en/... , including the behavior risk factors for NCDs and beginning at the earliest possible age. Further studies must explore the extent to which modifications on the risk factors for NCD can affect mental disorders.

Acknowledgments

This work was supported by the Brazilian Ministry of Health/Department of Science and Technology (DECIT), Maranhão State Research Foundation (FAPEMA), São Paulo State Research Foundation (FAPESP), Brazilian National Research Council (CNPq), and Brazilian Graduate Studies Coordinating Board (CAPES).

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