Abstract
The study aimed to estimate the prevalence of alcohol use disorder (AUD) and associated factors in Brazilian adults that reported chronic noncommunicable diseases (NCDs), mental disorders (MDs), and infectious diseases (IDs). This was a secondary analysis of the 3rd National Survey on Drug Use by the Brazilian Population in which the principal outcome was presence of AUD. Prevalence of AUD was estimated for three subgroups: individuals that reported NCDs, MDs, and IDs. Factors associated with AUD in each group were analyzed using logistic regression models. Of the 15,645 adults interviewed, 30.5% (95%CI: 29.4-31.5) reported NCDs, 17.6% (95%CI: 16.5-18.7) MDs, and 1.6% (95%CI: 1.2-1.9) IDs. Considering comorbidities, the analytical sample was 6,612. No statistically significant difference was found in the prevalence of AUD between individuals with NCDs (7.5% [95%CI: 6.1- 8.7]), MDs (8.4% [95%CI: 6.7-10.2]), and IDs (12.4% [95%CI: 7.0-17.8]). The main factors associated with AUD in all the groups were male sex and young adult age. Considering the high prevalence of AUD in all the groups, systematic screening of AUD is necessary in health services that treat NCDs, MDs, and IDs.
Key words:
Epidemiological surveys; Alcohol use disorder; Chronic diseases; Mental disorders; Infectious diseases
Resumo
O objetivo do artigo é estimar a prevalência de transtornos relacionados ao uso de álcool (TRA) e fatores associados entre indivíduos da população brasileira que reportaram doenças crônicas não-transmissíveis (DCNT), transtornos mentais (TM) e doenças infeciosas (DI). Análise secundária do III Levantamento Nacional sobre o Uso de Drogas pela População Brasileira, cujo desfecho principal foi a presença de TRA. A prevalência de TRA foi estimada para três subgrupos: indivíduos que reportaram DCNT, TM e DI. Os fatores associados a TRA dentro de cada grupo foram analisados utilizando modelos de regressão logística. Dos 15.645 adultos entrevistados, 30,5% (IC95%: 29,4-31,5) reportaram DCNT, 17,6% (IC95%: 16,5-18,7) TM e 1,6% (IC95%: 1,2-1,9) DI. Considerando as comorbidades, a amostra analítica foi de 6.612. Não foi encontrada diferença estatisticamente significativa na prevalência de TRA entre indivíduos com DCNT (7,5% [IC95% 6,1-8,7]), TM (8,4% [IC95% 6,7-10,2]) e DI (12,4% [IC95% 7,0-17,8]). Os principais fatores associados a TRA, em todos os grupos, foram ser do sexo masculino e jovem. Considerando a alta prevalência de TRA em todos os grupos é necessário seu rastreio sistemático em serviços de saúde que atendam DCNT, TM e DI.
Palavras-chave:
Inquéritos epidemiológicos; Transtornos relacionados ao uso de álcool; Doenças crônicas; Transtornos mentais
Introduction
Harmful alcohol use is both a public health problem11 GBD 2016 Alcohol Collaborators. Alcohol use and burden for 195 countries and territories, 1990-2016: A systematic analysis for the Global Burden of Disease Study 2016. Lancet 2018; 392(10152):1015-1035.
2 Institute for Health and Metrics Evaluation. Global Burden of Diseases [Internet]. 2019. [cited 2023 jun 11]. Available from: https://ghdx.healthdata.org/gbd-2019
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-33 World Health Organization (WHO). Global status report on alcohol and health 2018 [Internet]. 2018. [cited 2023 ou 13]. Available from: http://www.who.int/substance_abuse/publications/global_alcohol_report/en/
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and a risk factor for infectious and chronic diseases and mental disorders33 World Health Organization (WHO). Global status report on alcohol and health 2018 [Internet]. 2018. [cited 2023 ou 13]. Available from: http://www.who.int/substance_abuse/publications/global_alcohol_report/en/
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,44 World Health Organization (WHO). Global Status Report on Noncommunicable Diseases 2014. Geneva: WHO; 2014.. The potential consequences of alcohol use feature alcohol use disorder (AUD), which can be classified according to two distinct strategies: the International Classification of Diseases (ICD) and the Diagnostic and Statistical Manual of Mental Disorders (DSM)55 De Boni RB. Understanding alcohol-related indicators from population surveys: answering the "Five W's of Epidemiology". Cad Saude Publica 2022; 38(8):e00238321.. Briefly, ICD-11 classified AUD as harmful alcohol use and dependence66 World Health Organization (WHO). ICD-11: International Classification of Diseases (11th revision). Geneva: WHO; 2019.,77 Centro de Informações sobre Saúde e Álcool (CISA). Transtornos por uso de álcool na CID-11: passado, presente e futuro [Internet]. 2022. [acessado 2023 set 19]. Disponível em: https://cisa.org.br/pesquisa/artigos-cientificos/artigo/item/343-transtornos-por-uso-de-alcool-na-cid-11-passado-presente-e-futuro
https://cisa.org.br/pesquisa/artigos-cie...
; DSM-IV88 American Psychiatric Association (APS). Diagnostic and Statistical Manual of Mental Disorder (DSM-IV) [Internet]. 1994. [cited 2022 out 18]. Available from: https://psychiatryonline.org/doi/epdf/10.1176/appi.books.9780890420614.dsm-iv
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classified it as abuse and dependence; and DSM-V as mild, moderate, and severe AUD99 American Psychiatric Association (APS). Diagnostic and Statistical Manual of Mental Disorders (DSM-V) [Internet]. 2000. [cited 2022 out 18]. Available from: https://psychiatryonline.org/doi/epdf/10.1176/appi.books.9780890420249.dsm-iv-tr
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. Despite the different nomenclatures, AUD is understood as “a pattern of compulsive heavy alcohol use and loss of control over alcohol intake (combining the definitions from Carvalho et al.’s paper“1010 Carvalho AF, Heilig M, Perez A, Probst C, Rehm J. Alcohol use disorders. Lancet 2019; 394(10200):781-792. and the official statement by the NIH [https://www.niaaa.nih.gov/publications/brochures-and-fact-sheets/understanding-alcohol-use-disorder]).
AUD is believed to result from the interaction of a series of individual and contextual risk factors. The individual risk factors frequently include male sex, low socioeconomic status1111 Collins SE. Associations between socioeconomic factors and alcohol outcomes. Alcohol Res 2016; 38(1):83.,1212 Lewer D, Meier P, Beard E, Boniface S, Kaner E. Unravelling the alcohol harm paradox: a population-based study of social gradients across very heavy drinking thresholds. BMC Public Health 2016; 16:599., lack of religiousness/spirituality1313 Castaldelli-Maia JM, Bhugra D. Investigating the interlinkages of alcohol use and misuse, spirituality and culture - insights from a systematic review. Int Rev Psychiatry 2014; 26(3):352-367., impulsivity, and behavioral and mood disorders1414 Chartier KG, Hesselbrock MN, Hesselbrock VM. Development and vulnerability factors in adolescent alcohol use. Child Adolesc Psychiatr Clin N Am 2010; 19(3):493-504.,1515 Yang P, Tao R, He C, Liu S, Wang Y, Zhang X. The risk factors of the alcohol use disorders: through review of its comorbidities. Front Neurosci 2018; 12:303.. Among the contextual factors, according to the theory of alcohol availability99 American Psychiatric Association (APS). Diagnostic and Statistical Manual of Mental Disorders (DSM-V) [Internet]. 2000. [cited 2022 out 18]. Available from: https://psychiatryonline.org/doi/epdf/10.1176/appi.books.9780890420249.dsm-iv-tr
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, the greater the availability of alcoholic beverages in a given population (whether physical, social, subjective, or economic availability)1616 Paul J. Gruenewald, Alex B. Millar, Andrew J. Treno. Alcohol availability and the ecology of drinking behavior. Alcohol Heal Res World 1993; 17(1):39-45., the greater the consumption and the higher the prevalence of negative consequences, including AUD.
In Brazil, the 3 rd National Survey on Drug Use by the Brazilian Population (III LNUD) in 2015 estimated the prevalence of AUD in the general population at 8.6% (95%CI:7.7-9.7), while prevalence of the most severe form (dependence) was 1.5% (95%CI:1.2-1.8)1717 De Boni RB, Vasconcellos MTL, Silva PN, Coutinho C, Mota J, Peixoto JNB, Bertoni N, Bastos FI. Reproducibility on science: challenges and advances in Brazilian alcohol surveys. Int J Drug Policy 2019: 74:285-291.. These prevalence rates tend to be substantially higher in clinical populations, due to both the juxtaposition of disorders and more systematic and careful detection than in the general population. For example: the prevalence of positive screening results for AUD was some 13.0% in patients seen in primary care in Rio de Janeiro1818 Cruz IO, Cruz FO, Jomar RT, Abreu AMM, Griep RH. Padrões de consumo de álcool e fatores associados entre adultos usuários de serviço de atenção básica do Rio de Janeiro, RJ, Brasil. Cien Saude Colet 2014; 19(1):27-38.. Meanwhile, the prevalence rates of positive screening for alcohol dependence ranged from 2.0%1919 Silva CM, Mendoza-Sassi RA, Mota LD, Nader MM, Martinez AMB. Alcohol use disorders among people living with HIV/AIDS in Southern Brazil: prevalence, risk factors and biological markers outcomes. BMC Infect Dis 2017; 17(1):263.,2020 De Boni RB, Shepherd BE, Grinsztejn B, Cesar C, Cortés C, Padgett D, Gotuzzo E, Belaunzarán-Zamudio PF, Rebeiro PF, Duda SN, McGowan CC. Substance Use and adherence among people living with HIV/AIDS receiving cART in Latin America. AIDS Behav 2016; 20(11):2692-2699. to 14%2121 Almeida-Filho N, Lessa I, Magalhães L, Araújo MJ, Aquino E, Jesus Mari J. Co-occurrence patterns of anxiety, depression and alcohol use disorders. Eur Arch Psychiatry Clin Neurosci 2007; 257(7):423-431. according the type of service, region, and users’ comorbidities. Note that these studies used different screening instruments, and none of them used validated scales for AUD diagnosis.
According to international evidence, individuals with certain clinical conditions present higher alcohol intake than others. However, we found no Brazilian study that compared frequency of AUD (using validated diagnostic criteria) among groups of individuals with specific diseases2222 Sterling SA, Palzes VA, Lu Y, Kline-Simon AH, Parthasarathy S, Ross T, Elson J, Weisner C, Maxim C, Chi FW. Associations between medical conditions and alcohol consumption levels in an adult primary care population. JAMA Netw Open 2020; 3(5):e204687.. Despite the high prevalence, the resulting harms, and the availability of treatment, AUD is still rarely or ever evaluated by health teams2323 Mitchell AJ, Meader N, Bird V, Rizzo M. Clinical recognition and recording of alcohol disorders by clinicians in primary and secondary care: meta-analysis. Br J Psychiatry 2012; 201(2):93-100.. It is important to identify the prevalence among individuals with different conditions and who are thus seen at different health services in the Unified Health System (SUS), to orient priorities for training and budget funding. The current study thus seeks to estimate the prevalence of AUD and associated factors in individuals that reported diagnosis and/or treatment of infectious and chronic diseases and mental disorders in the Brazilian population.
Methods
Study design
This cross-sectional study used data from the III LNUD2424 Bastos FIPM, Vasconcellos MTL, De Boni RB, Reis NB, Coutinho CFS. III Levantamento Nacional sobre o Uso de Drogas pela População Brasileira [Internet]. 2017. [acessado 2023 ago 3]. Available from: https://www.arca.fiocruz.br/handle/icict/34614
https://www.arca.fiocruz.br/handle/icict...
, a population survey in 2015 that included a probabilistic sample of 16,273 individuals 12 to 65 years of age from urban and rural areas of Brazil1717 De Boni RB, Vasconcellos MTL, Silva PN, Coutinho C, Mota J, Peixoto JNB, Bertoni N, Bastos FI. Reproducibility on science: challenges and advances in Brazilian alcohol surveys. Int J Drug Policy 2019: 74:285-291.,2525 De Boni RB, Mota JC, Coutinho C, Bastos FI. Would the Brazilian population support the alcohol policies recommended by the World Health Organization? Rev Saude Publica 2022; 56:66.
26 Krawczyk N, Mota JC, Coutinho C, Bertoni N, Vasconcellos MTL, Silva PLN, De Boni RB, Cerdá M, Bastos FI. Polysubstance use in a Brazilian national sample: Correlates of co-use of alcohol and prescription drugs. Subst Abus 2022; 43(1):520-526.
27 De Boni RB, Vasconcellos MTL, Pedro Luis NS, Silva KML, Bertoni N, Coutinho CFS, Mota JC, Bastos FI. Substance use, self-rated health and HIV status in Brazil. AIDS Care 2020; 33(10):1358-1362.
28 Rakovski C, Cardoso TA, Mota JC, Bastos FI, Kapczinski F, De Boni RB. Underage drinking in Brazil: findings from a community household survey. Brazilian J Psychiatry 2021; 44(3):257-263.
29 Krawczyk N, Silva PLN, De Boni RB, Mota J, Vascncellos M, Bertoni N, Coutinho C, Bastos FI. Non-medical use of opioid analgesics in contemporary Brazil: Findings from the 2015 Brazilian National Household Survey on Substance Use. Glob Public Health 2019; 15(2):299-306.-3030 Bertoni N, Szklo A, De Boni R, Coutinho C, Vasconcellos M, Silva PN, Almeida LM, Bastos FI. Electronic cigarettes and narghile users in Brazil: Do they differ from cigarettes smokers? Addict Behav 2019; 98:106007., using a four-stage stratified cluster sample. All the methodological details were described in the survey’s original report, available at: https://www.arca.fiocruz.br/handle/icict/34614. .
Participants
The analysis only included individuals 18 years or older that presented some infectious or chronic disease or mental disorder (= 6,612). Three non-mutually exclusive subgroups were defined, considering individuals that reported:
Chronic noncommunicable diseases (diabetes, cardiac diseases, hypertension, asthma, cirrhosis, kidney disease, and/or cancer);
Infectious diseases (HIV/AIDS, hepatitis B or C, sexually transmissible infections such as chlamydia, genital herpes, syphilis, etc., and/or tuberculosis);
Mental disorders (depression, anxiety, schizophrenia, bipolar disorder, and eating disorders).
Each of the above-mentioned conditions was assessed with the following question: “Has a doctor or other healthcare professional ever told you that you have...?”3131 Instituto Brasileiro de Geografia e Estatística (IBGE). Pesquisa Nacional de Saúde 2013: percepção do estado de saúde, estilos de vida e doenças crônicas. Rio de Janeiro: IBGE; 2014.. The possible answers were: “No”, “Yes”, “I don’t know”, and “I prefer not to answer”. The option “yes” was considered a positive diagnosis, and all the other options were considered negative diagnosis.
The decision to create non-exclusive categories was because most of the individuals presented some comorbidity, so that exclusive categories would have generated “artificial” groups, inconsistent with spontaneous report by participants and with Brazil’s public health reality.
Outcome
The principal outcome was dichotomous: presence or absence of AUD. For the purposes of this study, AUD was operationalized by adding the diagnoses of abuse and dependence as measured by the DSM-IV criteria88 American Psychiatric Association (APS). Diagnostic and Statistical Manual of Mental Disorder (DSM-IV) [Internet]. 1994. [cited 2022 out 18]. Available from: https://psychiatryonline.org/doi/epdf/10.1176/appi.books.9780890420614.dsm-iv
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. Assessment of the diagnostic criteria used the standardized questions from the U.S. Substance Abuse and Mental Health Services Administration for the National Survey on Drug Use and Health (2014)3232 Center for Behavioral Health Statistics and Quality (CBHSQ). National Survey on Drug Use and Health: Summary of Methodological Studies, 1971-2014. Rockville: CBHSQ; 2014., validated in the 2nd Household Survey on Psychoactive Drug Use in Brazil3333 Carlini E, supervisão. II Levantamento domiciliar sobre o uso de drogas psicotrópicas no Brasil: estudo envolvendo as 108 maiores cidades do país, 2005. São Paulo: CEBRID; 2006.. According to the DSM-IV, diagnosis of abusive use was defined as the presence of one or more of the four criteria for abuse, and diagnosis of dependence was defined as the presence of three or more of the seven criteria for dependence.
Independent variables
The variables included in the analysis were sex at birth (male/female), gender (heterosexual/LGBTQ+, doesn’t know/prefers not to answer), age group (18 to 24, 25 to 34, 35 to 34, 35 to 44, 45 to 54, or 55 years and older), monthly income (zero to BRL 1,500.00 versus greater than BRL R$ 1,500.00), skin color (white/non-white), fixed partner (yes/no), religion (none, Catholic, Evangelical/Protestant, other), schooling (up to 8 years, 8 to 12 years, 12 years or more), self-rated health status at the time of the interview (very good or good, fair or doesn’t know, bad or very bad), and self-rated consumption of alcoholic beverages (abstemious, doesn’t drink, occasional drinker, light drinker, social drinker, heavy drinker/alcoholic).
Statistical analysis
All the analyses were performed for each of the three subgroups (i.e., infectious diseases, chronic diseases, and mental disorders) and considered the sample design, weighting, and calibration of the weights, in keeping with the original analytical plan, described in detail in the respective report and in an extensive series of publication55 De Boni RB. Understanding alcohol-related indicators from population surveys: answering the "Five W's of Epidemiology". Cad Saude Publica 2022; 38(8):e00238321.,1717 De Boni RB, Vasconcellos MTL, Silva PN, Coutinho C, Mota J, Peixoto JNB, Bertoni N, Bastos FI. Reproducibility on science: challenges and advances in Brazilian alcohol surveys. Int J Drug Policy 2019: 74:285-291.,2424 Bastos FIPM, Vasconcellos MTL, De Boni RB, Reis NB, Coutinho CFS. III Levantamento Nacional sobre o Uso de Drogas pela População Brasileira [Internet]. 2017. [acessado 2023 ago 3]. Available from: https://www.arca.fiocruz.br/handle/icict/34614
https://www.arca.fiocruz.br/handle/icict...
25 De Boni RB, Mota JC, Coutinho C, Bastos FI. Would the Brazilian population support the alcohol policies recommended by the World Health Organization? Rev Saude Publica 2022; 56:66.
26 Krawczyk N, Mota JC, Coutinho C, Bertoni N, Vasconcellos MTL, Silva PLN, De Boni RB, Cerdá M, Bastos FI. Polysubstance use in a Brazilian national sample: Correlates of co-use of alcohol and prescription drugs. Subst Abus 2022; 43(1):520-526.
27 De Boni RB, Vasconcellos MTL, Pedro Luis NS, Silva KML, Bertoni N, Coutinho CFS, Mota JC, Bastos FI. Substance use, self-rated health and HIV status in Brazil. AIDS Care 2020; 33(10):1358-1362.
28 Rakovski C, Cardoso TA, Mota JC, Bastos FI, Kapczinski F, De Boni RB. Underage drinking in Brazil: findings from a community household survey. Brazilian J Psychiatry 2021; 44(3):257-263.
29 Krawczyk N, Silva PLN, De Boni RB, Mota J, Vascncellos M, Bertoni N, Coutinho C, Bastos FI. Non-medical use of opioid analgesics in contemporary Brazil: Findings from the 2015 Brazilian National Household Survey on Substance Use. Glob Public Health 2019; 15(2):299-306.-3030 Bertoni N, Szklo A, De Boni R, Coutinho C, Vasconcellos M, Silva PN, Almeida LM, Bastos FI. Electronic cigarettes and narghile users in Brazil: Do they differ from cigarettes smokers? Addict Behav 2019; 98:106007.,3434 Carvalho AM, Bertoni N, Coutinho C, Bastos FI, Fonseca VM. Tobacco use by sexual and gender minorities: findings from a Brazilian national survey. BMJ Open 2023; 13(4):e065738..
Population totals were estimated with their respective standard errors (SE) for each independent variable in each of the three subgroups. Next, a bivariate analysis was performed with the independent variables according to alcohol use disorder (AUD) for the three subgroups, estimating the prevalence and respective 95% confidence intervals. To verify the associations between the independent variables and AUD, the chi-square test was calculated with Rao-Scott correction, considering significance at 5%.
All the variables were tested for collinearity before the data modeling phase, with cutoff point at 0.60, using Cramer’s V test from the MASS package.
Finally, to assess factors associated with AUD, unconditional logistic regression models were performed, using the backward stepwise strategy for the elaboration of the intermediate and final models. Variables with p-value < 0.2 in the bivariate analysis were included, in addition to the variables “sex” and “age” (defined a priori). Age was included in the models as a continuous variable. Dummy variables were created to control the effect of each disease group, indicating their presence or absence. These variables were included according to each respective subgroup. For example, the model for the subgroup of individuals with infectious diseases included the dummy variables “chronic disease” and “mental disorder”. Odds ratios and 95% confidence intervals were calculated. The analyses were performed in the R software version 3.6.1 using the Survey and Survyer libraries3535 R Core Team. R: a language and environment for statistical computing [Internet]. 2013. [cited 2023 ago 3]. Available from: http://www.r-project.org
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.
Ethical considerations
The current analysis was approved by the Institutional Review Board of the Brazilian National Institute of Infectious Diseases “Evandro Chagas” on February 13, 2020 (CAAE: 23232019.8.0000.5262). The original study was approved on April 1st, 2015, by the Ethics Committee for Research in Human Beings of FIOCRUZ (review no. 902.763 by CEP/EPSJV - CAAE: 35283814.4.0000.5241).
Results
The sample initially included 15,645 individuals 18 years or older, in which prevalence of self-reported infectious diseases was 1.6% (95%CI: 1.2-1.9), chronic diseases 30.5% (95%CI: 29.4-31.5), and mental disorders 17.6% (95%CI: 16.5-18.7). Considering the intersections between the groups (comorbidities), the sample for analysis consisted of 6,612 individuals who reported any infectious or chronic disease or mental disorder, which represent 52 million Brazilians (Graph 1 and Figure 1). Of these, an estimated two million reported some infectious disease, 40.5 million some chronic disease, and 23.5 million some mental disorder.
Intersection of subgroups of individuals 18 years or older reporting infectious diseases, chronic diseases, and mental disorders. 3rd National Survey on Drug Use by the Brazilian Population, n = 6,612, Brazil, 2015.
Flowchart of inclusion of subgroups with prevalence of diseases (% and standard error) in individuals 18 years or older that reported infectious diseases (n = 249), chronic diseases (n = 5,219), and mental disorders (n = 2,915) in a representative Brazilian sample estimated at 52 million individuals, Brazil, 2015.
There was a high presence of comorbidities between subgroups. In the subgroup of individuals with infectious diseases, 59.8% also reported chronic diseases and 42.7% mental disorders. In the subgroup of individuals with chronic diseases, 3.1% reported infectious diseases and 30.1% mental disorders. In the subgroup with mental disorders, 3.8% reported infectious diseases and 52.1% chronic disorders (Table 1).
Table 1 shows the sociodemographic and health characteristics according to the subpopulations. In the subgroup of infectious diseases, 52.0% of the participants were males (95%CI: 45.0-59.0), while men were the minority in the subgroups that reported chronic diseases (42.9% [95%CI: 41.3-44.5]) and mental disorders (30.5% [95%CI: 28.3 -32.7]).
Prevalence of AUD in the subgroups was 12.4% (95%CI: 7.0-17.8) in individuals that reported infectious diseases, 8.4% (95%CI: 6.7-10.2) in individuals with mental disorders, and 7.5% (95%CI: 6.1- 8.7) in individuals with chronic diseases. Considering the overlapping confidence intervals, it is not possible to infer statistically significant differences between the subgroups.
Table 2 shows the characteristics of individuals with AUD in each subgroup and the result of the bivariate analyses. In all the subgroups, AUD was more frequent in men, in individuals 18 to 34 years of age, without fixed partners, with good/very good self-rated health, and that considered themselves heavy drinkers or alcoholics (p < 0.05). In the subgroups with chronic diseases and mental disorders, AUD was also more frequent among individuals without a religion.
Table 3 shows the factors associated with AUD in the three subgroups. Male sex was associated with higher odds of AUD in the three subgroups, and the odds of AUD decreased with age. In subgroups of chronic diseases and mental disorders, belonging to an Evangelical, Protestant, or other religion appeared as a protective factor against AUD.
In the subgroup of individuals that reported mental disorders, not having a partner was associated statistically with AUD. No evidence was found of a statistically significant association between presence of comorbidities and AUD.
Discussion
In this article, prevalence of alcohol use disorder ranged from 7.5% (95%CI: 6.1- 8.7) in individuals that reported chronic diseases to 12.4% (95%CI: 7.0-17.8) in those that reported infectious diseases, while the difference between point prevalence rates cannot be considered statistically significant. The main factors independently associated with AUD were male sex and young age. We found no evidence that the presence of comorbidities was associated with higher odds of AUD.
Prevalence of AUD in all the groups resembled that of the general population in the III LNUD (8.6%; 95%CI: 7.7-9.7), which in turn was higher than the WHO estimate (4.2%) (3). The comparison of prevalence rates with national and international studies is challenging, mainly for three methodological reasons. The first is the way AUD is measured: most of the studies use screening tools rather than diagnostic tools, which may underestimate the results. The second reason is the non-probabilistic design of most of the studies, which introduces a selection bias. Finally, when the objective is to assess the prevalence of AUD among individuals with some comorbidity, most of the studies do so in a clinical setting, where there is also a selection bias. Our findings are counter to those of Manthey et al.3636 Manthey J, Gual A, Jakubczyk A, Pieper L, Probst C, Struzzo P, Trapencieres M, Wojnar M, Rehm J. Alcohol use disorders in Europe: a comparison of general population and primary health care prevalence rates. J Subst Use 2016; 21(5):478-484. and Nalwadda et al.3737 Nalwadda O, Rathod SD, Nakku J, Lund C, Prince M, Kigozi F. Alcohol use in a rural district in Uganda: findings from community-based and facility-based cross -sectional studies. Int J Ment Health Syst 2018; 12:12., pertaining to Europe and Uganda, in which the AUD prevalence rates were higher in users of primary care than in the general population. In both, the data were collected in health services and in the general population, and there was no specification of the type of condition that was being treated in primary care. In general, chronic diseases are treated in primary care, and the literature in this context is vast. In Russia, for example, a country with one of the highest AUD prevalence rates in the world, AUD prevalence in primary care was estimated at 12.2% for both sexes (95%CI: 10.8-13.6%), or 6.1% in women and 19.5% in men3838 Rehm J, Shield KD, Bunova A, Ferreira-Borges C, Franklin A, Gornyi B, Rovira P, Neufeld M. Prevalence of alcohol use disorders in primary health-care facilities in Russia in 2019. Addiction 2022; 117(6):1640-1646..
The type of condition is determinant for planning treatment strategies, including harm reduction strategies. In the context of infectious diseases, for example, harmful alcohol use is associated with lower risk perception, thereby increasing the odds of unprotected sex and STDs3939 Hahn JA, Woolf-King SE, Muyindike W. Adding fuel to the fire: alcohol's effect on the HIV epidemic in Sub-Saharan Africa. Curr HIV/AIDS Rep 2011; 8(3):172-180.,4040 Rehm J, Shield KD, Joharchi N, Shuper PA. Alcohol consumption and the intention to engage in unprotected sex: systematic review and meta-analysis of experimental studies. Addiction 2012; 107(1):51-59.. Likewise, among individuals living with HIV/AIDS, alcohol use is associated with higher odds of poor adherence to antiretroviral therapy (ART)2020 De Boni RB, Shepherd BE, Grinsztejn B, Cesar C, Cortés C, Padgett D, Gotuzzo E, Belaunzarán-Zamudio PF, Rebeiro PF, Duda SN, McGowan CC. Substance Use and adherence among people living with HIV/AIDS receiving cART in Latin America. AIDS Behav 2016; 20(11):2692-2699. and losses to follow-up4141 De Boni RB, Peratikos MB, Shepherd BE, Grinsztejn B, Cortés C, Padgett D, Gotuzzo E, Belaunzarán-Zamudio PF, Rebeiro PF, Duda SN, McGowan CC; for CCASAnet. Is substance use associated with HIV cascade outcomes in Latin America? PLoS One 2018; 13(3):e0194228.. Individuals with mental disorders show increased risk of aggressive behaviors, suicide, and higher odds of homelessness4242 Alves H, Kessler F, Caldas Ratto LR. Comorbidade: uso de álcool e outros transtornos psiquiátricos. Braz J Psychiatry 2004; 26(Suppl.):51-53.. Finally, among individuals with chronic diseases, AUD can increase both the risk of hospitalizations and readmissions, as well as length of hospital stay4343 MacMurdo M, Lopez R, Udeh BL, Zein JG. Alcohol use disorder and healthcare utilization in patients with chronic asthma and obstructive lung disease. Alcohol 2021; 93:11-16., thus increasing the costs for the health system and the level of complexity for patients in the system. This is particularly relevant in Brazil, which is experiencing a period of epidemiological transition, with increasing prevalence of chronic noncommunicable diseases4444 Monteiro MFG. Transição demográfica e epidemiológica. In: Barata RB, Barreto ML, Almeida Filho N, Veras RP. Equidade e saúde: contribuições da epidemiologia. Rio de Janeiro: Fiocruz; 1997.. Our results thus highlight the importance of considering any healthcare encounter as an opportunity to screen for AUD, where the lack of screening is a missed opportunity for counseling and treatment4545 Mushi D, Moshiro C, Hanlon C, Francis JM, Teferra S. Missed opportunity for alcohol use disorder screening and management in primary health care facilities in northern rural Tanzania: a cross-sectional survey. Subst Abus Treat Prev Policy 2022; 17(1):50., since most individuals with AUD do not seek care for the condition until more advanced stages of the disease (when prognosis is usually worse)4646 Rehm J, Allamani A, Vedova R Della, Elekes Z, Jakubczyk A, Landsmane I, Manthey J, Moreno-España J, Pieper L, Probst C, Snikere S, Struzzo P, Voller F, Wittchen HU, Gual A, Wojnar M. General practitioners recognizing alcohol dependence: a large cross-sectional study in 6 European countries. Ann Fam Med 2015; 13(1):28-32..
As for factors associated with AUD, our results corroborate the national and international literature. Male individuals have higher odds of AUD than females1010 Carvalho AF, Heilig M, Perez A, Probst C, Rehm J. Alcohol use disorders. Lancet 2019; 394(10200):781-792.,4747 Plens JA, Valente JY, Mari JJ, Ferrari G, Sanchez ZM, Rezende LFM. Patterns of alcohol consumption in Brazilian adults. Sci Rep 2022; 12(1):8603.. Despite biological differences between men and women that influence the absorption and effects of alcohol on their bodies, it is believed that differences in consumption patterns result mainly from cultural variations, where alcohol use is associated with gender roles (bolstering men’s masculinity and maintaining the female caregiver role, since women are often in charge of moderating alcohol consumption by other family members)4848 Holmila M, Raitasalo K. Gender differences in drinking: why do they still exist? Addiction 2005; 100(12):1763-1769.. Unfortunately, due to the sample size, it was not possible to extend the analysis of possible differences in consumption patterns according to sexual orientation. This is a relevant question for future studies, and considering the theories on stress in minorities and self-medication, it is possible that individuals from vulnerable populations use alcohol and other substances as a way of coping with the serious adversities they suffer4949 Schuler MS, Rice CE, Evans-Polce RJ, Collins RL. Disparities in substance use behaviors and disorders among adult sexual minorities by age, gender, and sexual identity. Drug Alcohol Depend 2018; 189:139-146..
As in other studies4747 Plens JA, Valente JY, Mari JJ, Ferrari G, Sanchez ZM, Rezende LFM. Patterns of alcohol consumption in Brazilian adults. Sci Rep 2022; 12(1):8603.,5050 Moura EC, Malta DC. Alcoholic beverage consumption among adults: sociodemographic characteristics and trends. Rev Bras Epidemiol 2011; 14(3):61-70., younger adults also showed higher odds of harmful alcohol consumption. Younger individuals may have greater expectations in relation to alcohol consumption (leading them to drink more frequently and increasing the risk of abusive use)5151 Nicolai J, Moshagen M, Demmel R. Patterns of alcohol expectancies and alcohol use across age and gender. Drug Alcohol Depend 2012; 126(3):347-353., but there may also be a survival bias (since alcohol is a leading cause of premature death)5252 Naimi TS, Stockwell T, Zhao J, Xuan Z, Dangardt F, Saitz R, Liang W, Chikritzhs T. Selection biases in observational studies affect associations between 'moderate' alcohol consumption and mortality. Addiction 2017; 112(2):207-214., especially since we are analyzing individuals that already present some health problem.
In this study, we observed two differences between the groups in the factors associated with AUD. The lack of a fixed partner was only associated with higher odds of AUD in individuals that reported mental disorders, which may be related to greater difficulties in interpersonal relations caused by such disorders. We also found that Evangelical or Protestant religion was only associated with lower odds of AUD in individuals with chronic diseases or mental disorders, but it is possible that the sample of individuals with infectious diseases was not sufficiently robust to detect an association in this group. Although not statistically significant in the final model, it is important to note that in all the groups, most of the individuals with AUD considered themselves “heavy drinkers” or “alcoholics”. This perception may be a cue for health professionals to recommend interventions for diminishing/ceasing alcohol consumption (according to the severity of the clinical condition and patients’ motivation). It is thus essential for health professionals to be properly trained. This need for training is consistent with the proposal by the WHO in the SAFER initiative, consisting of a set of five strategies aimed at reducing alcohol consumption. One of the interventions is encouragement for screening, brief intervention, and treatment of substance abuse5353 Organização Pan-Americana da Saúde (OPAS). Pacote técnico SAFER: um mundo livre dos danos relacionados ao álcool. Cinco áreas de intervenção em âmbito nacional e estadual [Internet]. 2020. [acessado 2023 out 13]. Disponível em: https://iris.paho.org/handle/10665.2/51903
https://iris.paho.org/handle/10665.2/519...
.
Our approach to the definition of population subgroups, which indicates the high prevalence of multiple simultaneous diagnoses, can back the importance of patient-centered health approaches rather than focusing on one specific disease5454 Whitty CJM, MacEwen C, Goddard A, Alderson D, Marshall M, Calderwood C, Atherton F, McBride M, Atherton J, Stokes-Lampard H, Reid W, Powis S, Marx C. Rising to the challenge of multimorbidity. BMJ 2020; 368;l6964.
55 Whitty CJM, Watt FM. Map clusters of diseases to tackle multimorbidity. Nature; 579(7800):494-496.
56 Gaulin M, Simard M, Candas B, Lesage A, Sirois C. Combined impacts of multimorbidity and mental disorders on frequent emergency department visits: a retrospective cohort study in Quebec, Canada. CMAJ 2019; 191(26):E724-E732.
57 Šprah L, Dernovšek MZ, Wahlbeck K, Haaramo P. Psychiatric readmissions and their association with physical comorbidity: a systematic literature review. BMC Psychiatry 2017; 17(1):2.
58 Björk Brämberg E, Torgerson J, Norman Kjellström A, Welin P, Rusner M. Access to primary and specialized somatic health care for persons with severe mental illness: a qualitative study of perceived barriers and facilitators in Swedish health care. BMC Fam Pract 2018; 19(1):12.
59 De Hert M, Correll CU, Bobes J, Cetkovich-Bakmas M, Cohen DAN, Asai I, Detraux J, Gautam S, Möller HJ, Ndetei DM, Newcomer JW, Uwakwe R, Leucht S. Physical illness in patients with severe mental disorders. I. Prevalence, impact of medications and disparities in health care. World Psychiatry 2011; 10(1):52-77.
60 Cassell A, Edwards D, Harshfield A, Rhodes K, Brimicombe J, Payne R, Griffin S. The epidemiology of multimorbidity in primary care: a retrospective cohort study. Br J Gen Pract 2018; 68(669):e245-e251.
61 Forslund T, Carlsson AC, Ljunggren G, Ärnlöv J, Wachtler C. Patterns of multimorbidity and pharmacotherapy: a total population cross-sectional study. Fam Pract 2021; 38(2):132-140.
62 Zhu Y, Edwards D, Mant J, Payne RA, Kiddle S. Characteristics, service use and mortality of clusters of multimorbid patients in England: a population-based study. BMC Med 2020; 18(1):78.-6363 Rodrigues M, Wiener JC, Stranges S, Ryan BL, Anderson KK. The risk of physical multimorbidity in people with psychotic disorders: a systematic review and meta-analysis. J Psychosom Res 2021; 140:110315.. Future studies with larger samples of individuals seen at healthcare services are necessary to assess whether there are clusters of conditions in which harmful alcohol consumption and/or AUD are more frequent.
The study has some limitations that should be addressed when interpreting the findings. The first is that the diagnoses of infectious and chronic diseases and mental disorders were self-reported. This may underestimate the real prevalence of these conditions (or, less frequently, overestimate them, especially if individuals believe, even erroneously, that they may derive some secondary benefit from an exaggerated list of conditions6464 Latkin CA, Edwards C, Davey-Rothwell MA, Tobin KE, Latkin CA. The relationship between social desirability bias and self-reports of health, substance use, and social network factors among urban substance users in Baltimore, Maryland HHS Public Access. Addict Behav 2017; 73:133-136.), whether because they decline to report or lack access to health services. In addition, by dividing subgroups for analytical purposes, the events necessarily become sparse, which may not allow distinguishing between lack of association and lack of statistical power or precision 6565 Rothman KJ, Greenland S. Planning Study size based on precision rather than power. Epidemiology 2018; 29(5):599-603. to assess certain strata. Third, the study design does not allow making causal inferences (which, at any rate, is not the purpose of population-based studies). Finally, the data were collected in 2015, before the COVID-19 pandemic, and it is essential to consider the possible effect of the health crisis on alcohol consumption patterns in populations, especially clinical populations.
Despite these limitations, specifically the high prevalence of self-reported comorbidities, which include AUD, in a representative sample of the Brazilian population, the results are relevant and unprecedented and can serve to back health services planning.
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37Nalwadda O, Rathod SD, Nakku J, Lund C, Prince M, Kigozi F. Alcohol use in a rural district in Uganda: findings from community-based and facility-based cross -sectional studies. Int J Ment Health Syst 2018; 12:12.
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38Rehm J, Shield KD, Bunova A, Ferreira-Borges C, Franklin A, Gornyi B, Rovira P, Neufeld M. Prevalence of alcohol use disorders in primary health-care facilities in Russia in 2019. Addiction 2022; 117(6):1640-1646.
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39Hahn JA, Woolf-King SE, Muyindike W. Adding fuel to the fire: alcohol's effect on the HIV epidemic in Sub-Saharan Africa. Curr HIV/AIDS Rep 2011; 8(3):172-180.
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40Rehm J, Shield KD, Joharchi N, Shuper PA. Alcohol consumption and the intention to engage in unprotected sex: systematic review and meta-analysis of experimental studies. Addiction 2012; 107(1):51-59.
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41De Boni RB, Peratikos MB, Shepherd BE, Grinsztejn B, Cortés C, Padgett D, Gotuzzo E, Belaunzarán-Zamudio PF, Rebeiro PF, Duda SN, McGowan CC; for CCASAnet. Is substance use associated with HIV cascade outcomes in Latin America? PLoS One 2018; 13(3):e0194228.
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42Alves H, Kessler F, Caldas Ratto LR. Comorbidade: uso de álcool e outros transtornos psiquiátricos. Braz J Psychiatry 2004; 26(Suppl.):51-53.
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43MacMurdo M, Lopez R, Udeh BL, Zein JG. Alcohol use disorder and healthcare utilization in patients with chronic asthma and obstructive lung disease. Alcohol 2021; 93:11-16.
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44Monteiro MFG. Transição demográfica e epidemiológica. In: Barata RB, Barreto ML, Almeida Filho N, Veras RP. Equidade e saúde: contribuições da epidemiologia. Rio de Janeiro: Fiocruz; 1997.
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45Mushi D, Moshiro C, Hanlon C, Francis JM, Teferra S. Missed opportunity for alcohol use disorder screening and management in primary health care facilities in northern rural Tanzania: a cross-sectional survey. Subst Abus Treat Prev Policy 2022; 17(1):50.
-
46Rehm J, Allamani A, Vedova R Della, Elekes Z, Jakubczyk A, Landsmane I, Manthey J, Moreno-España J, Pieper L, Probst C, Snikere S, Struzzo P, Voller F, Wittchen HU, Gual A, Wojnar M. General practitioners recognizing alcohol dependence: a large cross-sectional study in 6 European countries. Ann Fam Med 2015; 13(1):28-32.
-
47Plens JA, Valente JY, Mari JJ, Ferrari G, Sanchez ZM, Rezende LFM. Patterns of alcohol consumption in Brazilian adults. Sci Rep 2022; 12(1):8603.
-
48Holmila M, Raitasalo K. Gender differences in drinking: why do they still exist? Addiction 2005; 100(12):1763-1769.
-
49Schuler MS, Rice CE, Evans-Polce RJ, Collins RL. Disparities in substance use behaviors and disorders among adult sexual minorities by age, gender, and sexual identity. Drug Alcohol Depend 2018; 189:139-146.
-
50Moura EC, Malta DC. Alcoholic beverage consumption among adults: sociodemographic characteristics and trends. Rev Bras Epidemiol 2011; 14(3):61-70.
-
51Nicolai J, Moshagen M, Demmel R. Patterns of alcohol expectancies and alcohol use across age and gender. Drug Alcohol Depend 2012; 126(3):347-353.
-
52Naimi TS, Stockwell T, Zhao J, Xuan Z, Dangardt F, Saitz R, Liang W, Chikritzhs T. Selection biases in observational studies affect associations between 'moderate' alcohol consumption and mortality. Addiction 2017; 112(2):207-214.
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53Organização Pan-Americana da Saúde (OPAS). Pacote técnico SAFER: um mundo livre dos danos relacionados ao álcool. Cinco áreas de intervenção em âmbito nacional e estadual [Internet]. 2020. [acessado 2023 out 13]. Disponível em: https://iris.paho.org/handle/10665.2/51903
» https://iris.paho.org/handle/10665.2/51903 -
54Whitty CJM, MacEwen C, Goddard A, Alderson D, Marshall M, Calderwood C, Atherton F, McBride M, Atherton J, Stokes-Lampard H, Reid W, Powis S, Marx C. Rising to the challenge of multimorbidity. BMJ 2020; 368;l6964.
-
55Whitty CJM, Watt FM. Map clusters of diseases to tackle multimorbidity. Nature; 579(7800):494-496.
-
56Gaulin M, Simard M, Candas B, Lesage A, Sirois C. Combined impacts of multimorbidity and mental disorders on frequent emergency department visits: a retrospective cohort study in Quebec, Canada. CMAJ 2019; 191(26):E724-E732.
-
57Šprah L, Dernovšek MZ, Wahlbeck K, Haaramo P. Psychiatric readmissions and their association with physical comorbidity: a systematic literature review. BMC Psychiatry 2017; 17(1):2.
-
58Björk Brämberg E, Torgerson J, Norman Kjellström A, Welin P, Rusner M. Access to primary and specialized somatic health care for persons with severe mental illness: a qualitative study of perceived barriers and facilitators in Swedish health care. BMC Fam Pract 2018; 19(1):12.
-
59De Hert M, Correll CU, Bobes J, Cetkovich-Bakmas M, Cohen DAN, Asai I, Detraux J, Gautam S, Möller HJ, Ndetei DM, Newcomer JW, Uwakwe R, Leucht S. Physical illness in patients with severe mental disorders. I. Prevalence, impact of medications and disparities in health care. World Psychiatry 2011; 10(1):52-77.
-
60Cassell A, Edwards D, Harshfield A, Rhodes K, Brimicombe J, Payne R, Griffin S. The epidemiology of multimorbidity in primary care: a retrospective cohort study. Br J Gen Pract 2018; 68(669):e245-e251.
-
61Forslund T, Carlsson AC, Ljunggren G, Ärnlöv J, Wachtler C. Patterns of multimorbidity and pharmacotherapy: a total population cross-sectional study. Fam Pract 2021; 38(2):132-140.
-
62Zhu Y, Edwards D, Mant J, Payne RA, Kiddle S. Characteristics, service use and mortality of clusters of multimorbid patients in England: a population-based study. BMC Med 2020; 18(1):78.
-
63Rodrigues M, Wiener JC, Stranges S, Ryan BL, Anderson KK. The risk of physical multimorbidity in people with psychotic disorders: a systematic review and meta-analysis. J Psychosom Res 2021; 140:110315.
-
64Latkin CA, Edwards C, Davey-Rothwell MA, Tobin KE, Latkin CA. The relationship between social desirability bias and self-reports of health, substance use, and social network factors among urban substance users in Baltimore, Maryland HHS Public Access. Addict Behav 2017; 73:133-136.
-
65Rothman KJ, Greenland S. Planning Study size based on precision rather than power. Epidemiology 2018; 29(5):599-603.
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Funding
Fundação Oswaldo Cruz (Fiocruz-SENAD 08/2014), Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ - #E-26/010.002428/2019 and #E-26/203.154/2017), Conselho Nacional de Desenvolvimento Científi co e Tecnológico (CNPq - # 312543-2020/4).
Chief editors:
Publication Dates
-
Publication in this collection
26 Aug 2024 -
Date of issue
Sept 2024
History
-
Received
30 Jan 2023 -
Accepted
13 Sept 2023 -
Published
15 Sept 2023