Abstract

The objective was to measure the Quality of Life (QoL) of the patients treated in Primary Health Care in the city of Rio de Janeiro and its own association with CMD, alcohol consumption and socio-demographic aspects. This is a cross-sectional study involving 624 patients in 2012/2013, using: General Health Questionnaire, Hospital Anxiety and Depression Scale, Screening for Somatoform Symptoms, Alcohol Use Disorder Identification Test e World Health Organization Quality of Life Instrument (bref version). There were conducted a bivariate analysis and a multiple linear regressions for each domain of QOL. The QoL score for the domains, physical, psychological, social relationships and environment were: 61,2; 62,6; 66 and 50,9. In multivariate analysis, the QOL was negatively associated to the CMD, especially in the psychological domain (β = -15,75; p-value = 0,00), and the dependence on physical (β = -5,38; p-value = 0,05). There was a positive and significant association of the QoL with the risk consumption (β = 5,77) and the harmful consumption (β = 6,15) in the environment domain, and with the first in the psychological domain (β = 7,08). CMD and alcohol dependence are associated with the loss of QOL, but other patterns of consumption, even being harmful are associated with higher QOL.

Quality of life; Alcohol-related disorders; Primary healthcare

Introduction

Alcohol abuse is a major public health problem and is associated with increased rates of mortality and morbidity due to its potential to cause disease and relationship with loss of quality of life (QoL)¹1. Organisation mondiale de la santé (OMS). Global status report on noncommunicable diseases 2014: attaining the nine global noncommunicable diseases targets; a shared responsibility. Geneva: OMS; 2014.. In 2008, alcohol abuse/dependence was the second, third, and sixth leading cause of Disability Adjusted Life Years or DALYs - years of life lost due to premature mortality and due to disability – among Brazilian men aged between 15-29, 30-44, and 45-59 years, respectively²2. Portugal FB, Campos MR, Carvalho JR, Flor LS, Schramm JMA, Costa MFS. Carga de doença no Brasil: um olhar sobre o álcool e a cirrose não viral. Cien Saude Colet 2015; 20(2):491-501.. The second National Alcohol and Drugs Survey conducted in 2012 showed that the prevalence of the harmful use of alcohol and alcohol dependence was 16% and 6.8%, respectively³3. Laranjeira R, Madruga CS, Pinsky I, Caetano R, Mitsuhiro SS. II Levantamento Nacional de Álcool e Drogas (LENAD) - 2012 [Internet]. São Paulo: Instituto Nacional de Ciência e Tecnologia para Políticas Públicas e Álcool e Outras Drogas (INPAD), UNIFESP; 2012. [acessado 2016 Jul 27]. Disponível em: http://inpad.org.br/wp-content/uploads/2014/03/Lenad-II-Relat%C3%B3rio.pdf
http://inpad.org.br/wp-content/uploads/2... , while a multicentric study conducted in the same year reported that alcohol abuse (9.8%) and alcohol dependence (3.3%) were the second and third most prevalent lifetime disorders, respectively⁴4. Viana MC, Andrade LH. Lifetime Prevalence, age and gender distribution and age-of-onset of psychiatric disorders in the São Paulo Metropolitan Area, Brazil: results from the São Paulo Megacity Mental Health Survey. Rev Bras Psiquiatr 2012; 34(3):249-260..

Mental disorders (MDs) also account for a significant portion of the burden of morbidity and mortality among the Brazilian and global population, especially in recent decades. National burden of disease studies undertaken in Brazil in 1998⁵5. Schramm JMA, Oliveira AF, Leite IC, Valente JG, Gadelha ÂMJ, Portela MC, Campos MR. Epidemiological transition and the study of burden of disease in Brazil. Cien Saude Colet 2004; 9(4):897-908. and 2008⁶6. Leite IC, Valente JG, Schramm JMA, Daumas RP, Rodrigues RN, Santos MF, Oliveira AE, Silva RS, Campos MR, Mota JC. Carga de doença no Brasil e suas regiões, 2008. Cad Saude Publica 2015; 31(7):1551-1564. and the Global Burden of Disease Study 2010⁷7. Murray CJL, Vos T, Lozano R, Naghavi M, Flaxman AD, Michaud C, Ezzati M, Shibuya K, Salomon JA, Abdalla S, Aboyans V, Abraham J, Ackerman I, Aggarwal R, Ahn SY, Ali MK, Alvarado M, Anderson HR, Anderson LM, Andrews KG, Atkinson C, Baddour LM, Bahalim AN, Barker-Collo S, Barrero LH, Bartels DH, Basáñez MG, Baxter A, Bell ML, Benjamin EJ, Bennett D, Bernabé E, Bhalla K, Bhandari B, Bikbov B, Bin Abdulhak A, Birbeck G, Black JA, Blencowe H, Blore JD, Blyth F, Bolliger I, Bonaventure A, Boufous S, Bourne R, Boussinesq M, Braithwaite T, Brayne C, Bridgett L, Brooker S, Brooks P, Brugha TS, Bryan-Hancock C, Bucello C, Buchbinder R, Buckle G, Budke CM, Burch M, Burney P, Burstein R, Calabria B, Campbell B, Canter CE, Carabin H, Carapetis J, Carmona L, Cella C, Charlson F, Chen H, Cheng AT, Chou D, Chugh SS, Coffeng LE, Colan SD, Colquhoun S, Colson KE, Condon J, Connor MD, Cooper LT, Corriere M, Cortinovis M, de Vaccaro KC, Couser W, Cowie BC, Criqui MH, Cross M, Dabhadkar KC, Dahiya M, Dahodwala N, Damsere-Derry J, Danaei G, Davis A, De Leo D, Degenhardt L, Dellavalle R, Delossantos A, Denenberg J, Derrett S, Des Jarlais DC, Dharmaratne SD, Dherani M, Diaz-Torne C, Dolk H, Dorsey ER, Driscoll T, Duber H, Ebel B, Edmond K, Elbaz A, Ali SE, Erskine H, Erwin PJ, Espindola P, Ewoigbokhan SE, Farzadfar F, Feigin V, Felson DT, Ferrari A, Ferri CP, Fèvre EM, Finucane MM, Flaxman S, Flood L, Foreman K, Forouzanfar MH, Fowkes FG, Fransen M, Freeman MK, Gabbe BJ, Gabriel SE, Gakidou E, Ganatra HA, Garcia B, Gaspari F, Gillum RF, Gmel G, Gonzalez-Medina D, Gosselin R, Grainger R, Grant B, Groeger J, Guillemin F, Gunnell D, Gupta R, Haagsma J, Hagan H, Halasa YA, Hall W, Haring D, Haro JM, Harrison JE, Havmoeller R, Hay RJ, Higashi H, Hill C, Hoen B, Hoffman H, Hotez PJ, Hoy D, Huang JJ, Ibeanusi SE, Jacobsen KH, James SL, Jarvis D, Jasrasaria R, Jayaraman S, Johns N, Jonas JB, Karthikeyan G, Kassebaum N, Kawakami N, Keren A, Khoo JP, King CH, Knowlton LM, Kobusingye O, Koranteng A, Krishnamurthi R, Laden F, Lalloo R, Laslett LL, Lathlean T, Leasher JL, Lee YY, Leigh J, Levinson D, Lim SS, Limb E, Lin JK, Lipnick M, Lipshultz SE, Liu W, Loane M, Ohno SL, Lyons R, Mabweijano J, MacIntyre MF, Malekzadeh R, Mallinger L, Manivannan S, Marcenes W, March L, Margolis DJ, Marks GB, Marks R, Matsumori A, Matzopoulos R, Mayosi BM, McAnulty JH, McDermott MM, McGill N, McGrath J, Medina-Mora ME, Meltzer M, Mensah GA, Merriman TR, Meyer AC, Miglioli V, Miller M, Miller TR, Mitchell PB, Mock C, Mocumbi AO, Moffitt TE, Mokdad AA, Monasta L, Montico M, Moradi-Lakeh M, Moran A, Morawska L, Mori R, Murdoch ME, Mwaniki MK, Naidoo K, Nair MN, Naldi L, Narayan KM, Nelson PK, Nelson RG, Nevitt MC, Newton CR, Nolte S, Norman P, Norman R, O’Donnell M, O’Hanlon S, Olives C, Omer SB, Ortblad K, Osborne R, Ozgediz D, Page A, Pahari B, Pandian JD, Rivero AP, Patten SB, Pearce N, Padilla RP, Perez-Ruiz F, Perico N, Pesudovs K, Phillips D, Phillips MR, Pierce K, Pion S, Polanczyk GV, Polinder S, Pope CA 3rd, Popova S, Porrini E, Pourmalek F, Prince M, Pullan RL, Ramaiah KD, Ranganathan D, Razavi H, Regan M, Rehm JT, Rein DB, Remuzzi G, Richardson K, Rivara FP, Roberts T, Robinson C, De Leòn FR, Ronfani L, Room R, Rosenfeld LC, Rushton L, Sacco RL, Saha S, Sampson U, Sanchez-Riera L, Sanman E, Schwebel DC, Scott JG, Segui-Gomez M, Shahraz S, Shepard DS, Shin H, Shivakoti R, Singh D, Singh GM, Singh JA, Singleton J, Sleet DA, Sliwa K, Smith E, Smith JL, Stapelberg NJ, Steer A, Steiner T, Stolk WA, Stovner LJ, Sudfeld C, Syed S, Tamburlini G, Tavakkoli M, Taylor HR, Taylor JA, Taylor WJ, Thomas B, Thomson WM, Thurston GD, Tleyjeh IM, Tonelli M, Towbin JA, Truelsen T, Tsilimbaris MK, Ubeda C, Undurraga EA, van der Werf MJ, van Os J, Vavilala MS, Venketasubramanian N, Wang M, Wang W, Watt K, Weatherall DJ, Weinstock MA, Weintraub R, Weisskopf MG, Weissman MM, White RA, Whiteford H, Wiebe N, Wiersma ST, Wilkinson JD, Williams HC, Williams SR, Witt E, Wolfe F, Woolf AD, Wulf S, Yeh PH, Zaidi AK, Zheng ZJ, Zonies D, Lopez AD, AlMazroa MA, Memish ZA. Disability-adjusted life years (DALYs) for 291 diseases and injuries in 21 regions, 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet 380(9859):2197-223.reported that non-communicable diseases accounted for the largest fraction of DALYs (around 75%), with neuropsychiatric disorders accounting for 34%. MDs generate large social and economic costs, demanding various care actions⁸8. Silva Júnior JS, Fischer FM, Junior S, Da JS, Fischer FM. Disability due to mental illness: social security benefits in Brazil 2008-2011. Rev Saude Publica 2014; 48(1):186-190.,⁹9. Barbosa-Branco A, Bültmann U, Steenstra I. Sickness benefit claims due to mental disorders in Brazil: associations in a population-based study. Cad Saude Publica 2012; 28(10):1854-1866.. A multicentric study conducted in 2012 reported that major depression (16.8%) and anxiety disorders (28.1%) were the most frequent lifetime disorders and group of disorders among participants⁴4. Viana MC, Andrade LH. Lifetime Prevalence, age and gender distribution and age-of-onset of psychiatric disorders in the São Paulo Metropolitan Area, Brazil: results from the São Paulo Megacity Mental Health Survey. Rev Bras Psiquiatr 2012; 34(3):249-260..

Common mental disorders (CMDs) are a subgroup of MDs normally treated by primary health care services encompassing both emotional suffering and depressive-anxiety disorders and somatization. The literature shows that CMDs are prevalent conditions among primary healthcare service users¹⁰10. Fortes S, Lopes CS, Villano LAB, Campos MR, Gonçalves DA, Mari JJ. Common mental disorders in Petrópolis-RJ: a challenge to integrate mental health into primary care strategies. Rev Bras Psiquiatr 2011; 33(2):150-156.

11. Portugal FB, Campos MR, Gonçalves DA, Mari JJ, Fortes SLCL. Qualidade de vida em pacientes da atenção primária do Rio de Janeiro e São Paulo, Brasil: associações com eventos de vida produtores de estresse e saúde mental. Cien Saude Colet 2016; 21(2):497-508.-¹²12. Gonçalves DA, Mari J de J, Bower P, Gask L, Dowrick C, Tófoli LF, Campos M, Portugal FB, Ballester D, Fortes S. Brazilian multicentre study of common mental disorders in primary care: rates and related social and demographic factors. Cad Saude Publica 2014; 30(3):623-632..

A study published in 2011 reported that prevalence of CMDs among patients receiving treatment in Family Health Program health centers in Petropolis, Rio de Janeiro¹³13. Fortes S, Villano LAB, Lopes CS. Nosological profile and prevalence of common mental disorders of patients seen at the Family Health Program (FHP) units in Petropolis, Rio de Janeiro. Rev Bras Psiquiatr 2008; 30(1):32-37. was 56%, while a multicentric epidemiological study conducted in four state capitals in 2014 showed that prevalence was over 50% in each of the cities¹²12. Gonçalves DA, Mari J de J, Bower P, Gask L, Dowrick C, Tófoli LF, Campos M, Portugal FB, Ballester D, Fortes S. Brazilian multicentre study of common mental disorders in primary care: rates and related social and demographic factors. Cad Saude Publica 2014; 30(3):623-632..

The prevalence of the harmful use of alcohol among both primary healthcare patients and the general population is cause for concern among health professionals¹⁴14. Jomar RT, Abreu ÂMM, Griep RH, Jomar RT, Abreu ÂMM, Griep RH. Patterns of alcohol consumption and associated factors among adult users of primary health care services of Rio de Janeiro, Brazil. Cien Saude Colet 2014; 19(1):27-38.

15. Vargas D, Oliveira MAF, Araújo EC. Prevalence of alcohol addiction among users of primary healthcare services in Bebedouro, São Paulo State, Brazil. Cad Saude Publica 2009; 25(8):1711-1720.-¹⁶16. Abreu ÂMM, Jomar RT, Souza MHN, Guimarães RM. Harmful consumption of alcoholic beverages among users of a Family Health Unit. Acta Paul Enferm 2012; 25(2):291-295.. A household survey that assessed users of the Family Health Strategy (ESF, acronym in Portuguese) in Rio de Janeiro showed that the prevalence of the harmful use of alcohol and probable alcohol dependence was 29.6% and 5.7%, respectively¹⁴14. Jomar RT, Abreu ÂMM, Griep RH, Jomar RT, Abreu ÂMM, Griep RH. Patterns of alcohol consumption and associated factors among adult users of primary health care services of Rio de Janeiro, Brazil. Cien Saude Colet 2014; 19(1):27-38., while a study in the same city with members of the general population observed a high prevalence harmful use of alcohol (31%)¹⁶16. Abreu ÂMM, Jomar RT, Souza MHN, Guimarães RM. Harmful consumption of alcoholic beverages among users of a Family Health Unit. Acta Paul Enferm 2012; 25(2):291-295..

Primary healthcare services are regarded as the main point of entry to Brazil’s Unified Health System (SUS). One of the underlying principles of primary healthcare is the promotion of bonding and accountability between health teams and service users¹⁷17. Brasil. Política Nacional de Promoção da Saúde [Internet]. Ministério da Saúde; 2014 [acessado 2016 Jul 27]. Disponível em: http://bases.bireme.br/cgi-bin/wxislind.exe/iah/online/?IsisScript=iah/iah.xis&src=google&base=REPIDISCA&lang=p&nextAction=lnk&exprSearch=36123&indexSearch=ID
http://bases.bireme.br/cgi-bin/wxislind.... . To promote bonding it is necessary to take effective steps to bring health professionals and users closer together, especially through effective listening, through which it is possible to share and detect health conditions that are often overlooked due to stigma and prejudice. It is therefore essential to provide this level of care to patients with CMDs and problematic alcohol use.

To establish a bond it is essential to value users’ experiences and values and their perceptions of their history, life, and health. As such, a strong bond and awareness of ‘problem issues’ from the user’s perspective can help health professionals to plan more effective interventions¹⁸18. Pereira ÉF, Teixeira CS, Santos A. Qualidade de vida: abordagens, conceitos e avaliação. Rev Bras Educ Física e Esporte 2012; 26(2):241-50..

Measuring quality of life (QoL), defined by the World Health Organization as “an individual’s perception of their position in life in the context of the culture and value systems in which they live and in relation to their goals, expectations, standards and concerns”, can help to systematize users’ perceptions of their health¹⁹19. The WHOQOL Group. The World Health Organization Quality of Life assessment (WHOQOL): position paper from the World Health Organization. Soc Sci Med 1995; 41(10):1403-1409..

CMDs and alcohol consumption reduce QoL and are prevalent conditions in primary healthcare patients. The aim of this study was therefore to measure the QoL of primary health care patients in Rio de Janeiro and determine the association between QoL and CMDs (depression, anxiety, and acute somatization), alcohol consumption, and sociodemographic characteristics.

Material and Methods

Study design and sample

A cross-sectional study was undertaken using data from the longitudinal survey “Avaliação do cuidado da depressão a partir da Atenção Primária na rede SUS da área programática (AP) 2.2 do município do Rio de Janeiro” (An evaluation of the treatment of depression in the primary healthcare services of the SUS network in the programmatic area (PA) 2.2 of the municipality of Rio de Janeiro”), conducted in 2012 and 2013²⁰20. Fortes S. Avaliação do cuidado da depressão a partir da Atenção Primária na Rede SUS da área programática 2.2 do município do Rio de Janeiro. Brasília: Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq); 2013.. This study was funded by the National Council for Scientific and Technological Development (CNPq, acronym in Portuguese) and approved by the research ethics committees of the Pedro Ernesto University Hospital and State University of Rio de Janeiro and by the Municipal Department of Health and Civil Defense (application number 78A/2011), in accordance with the provisions Resolution Nº 196/96²¹21. Brasil. Resolução nº 196, de 10 de outubro de 1996. Diário Oficial da União 1996; 11 out. (revoked by Resolution 466/2012)²²22. Brasil. Resolução no 466, de 12 de dezembro de 2012. Diário Oficial da União 2012; 13 dez. of the National Health Council dealing with research involving human beings.

The source survey screened primary healthcare patients for anxiety and depressive disorders and use of alcohol in two different health facilities: a traditional primary healthcare center (UBS, acronym in Portuguese) and an ESF care center, both located in the same geographic region of the municipality of Rio de Janeiro. Suspected cases were communicated to the health teams for follow-up. The participants were reassessed after 12 months using the same instruments and based on the analysis of their health records.

This article presents the findings of the first assessment of the participants (first cycle). Data was collected from patients in the waiting room while they were waiting to be seen by a health professional by a previously trained professional. All participants signed an informed consent form. Convenience sampling was used given that the aim of the study was to compare the treatment provided to patients with MDs in each service. The final sample was made up of 624 service users aged between 18 and 65 years, 309 of which from the UBS and 315 from the ESF center.

Instruments

a) Socioeconomic and demographic questionnaire

This instrument contained objective questions to obtain information about the participants’ social, economic, and demographic background. The questionnaire was used by two previous studies¹⁰10. Fortes S, Lopes CS, Villano LAB, Campos MR, Gonçalves DA, Mari JJ. Common mental disorders in Petrópolis-RJ: a challenge to integrate mental health into primary care strategies. Rev Bras Psiquiatr 2011; 33(2):150-156.,²³23. Gonçalves DA, Fortes S, Tófoli LF, Campos MR, Mari JJ. Determinants of common mental disorders detection by general practitioners in primary health care in Brazil. Int J Psychiatry Med 2011; 41(1):3-13..

Since the sample was homogenous, the socioeconomic and demographic characteristics were treated as dichotomous variables, making it possible to develop indicators capable of highlighting significant social differences. The following variables and respective categories were used: sex (male/female), age group (up to 39 years/over 39 years), marital status (without a partner/with a partner), race/color (nonwhite/white), schooling (completed primary education/primary education incomplete), frequency of religious activities (less than twice a month/more than twice a month), monthly per capita family income (over R$272.50/less than or equal to R$272.50, which is equivalent to half of the minimum salary in 2011).

b) Assessment of CMDs (anxiety, depression, and acute somatization)

• General Health Questionnaire (GHQ-12)

The GHQ-12 is a screening device used for identifying CMDs and has been successfully validated for use in primary healthcare settings in Brazil²⁴24. Goldberg DP. The detection of psychiatric illness by questionnaire: a technique for the identification and assessment of non-psychotic psychiatric illness [Internet]. Oxford University Press; 1972. (Maudsley monographs). [citado 2016 Out 27]. Disponível em: https://books.google.com.br/books?id=PbRrAAAAMAAJ
https://books.google.com.br/books?id=PbR... . For the purposes of this study, individuals who scored between three and four were suspected to have CMDs, while those who obtained a score of five or over were considered to be probable cases of severe CMDs.

• Hospital Anxiety and Depression Scale - HAD

Translated and validated for use in Brazil, the HAD is a 14-item scale with two subscales: depression and anxiety. The total score for each subscale ranges between 0 and 21, with a score of over eight indicating depression or anxiety²⁵25. Botega NJ, Bio MR, Zomignani MA, Garcia Júnior C, Pereira WAB. Transtornos do humor em enfermaria de clínica médica e validação de escala de medida (HAD) de ansiedade e depressão. Rev Saude Publica 1995; 29(5):359-363..

• Screening for Somatoform Symptoms – SOMS-2

The SOMS-2 is a screening device used to detect medically unexplained symptoms (MUSs). It comprises a list of 53 somatoform symptoms from the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) and International Classification of Diseases (CID-10)²⁶26. Fabião MCM. Rastreio e diagnóstico da somatização em cuidados primários: validação da screening for somatoform symptoms-2 [Internet]. 2011 [citado 2016 Out 27]. Disponível em: https://repositorio-aberto.up.pt/handle/10216/45217
https://repositorio-aberto.up.pt/handle/... . For the purposes of this study, patients who mentioned four or more symptoms without a medical diagnosis and showed some degree of disability due to the symptoms were considered to cases of acute somatization²⁶26. Fabião MCM. Rastreio e diagnóstico da somatização em cuidados primários: validação da screening for somatoform symptoms-2 [Internet]. 2011 [citado 2016 Out 27]. Disponível em: https://repositorio-aberto.up.pt/handle/10216/45217
https://repositorio-aberto.up.pt/handle/... .

c) Alcohol Use Disorder Identification Test - AUDIT

The AUDIT is a 10-item screening tool developed by the WHO to assess alcohol consumption in the last 12 months. The tool is indicated for use in primary healthcare settings to diagnose patterns of alcohol consumption²⁷27. Babor TF, Higgins-Biddle JC, Saunders JB, Monteiro MG. The alcohol use disorders identification test: guidelines for use in primary care [Internet]. World Health Organization; 2001. [citado 2016 Out 27]. Disponível em: http://www.talkingalcohol.com/files/pdfs/WHO_audit.pdf
http://www.talkingalcohol.com/files/pdfs... . The cut-off score for problematic alcohol use is eight²⁸28. Lima CT, Freire ACC, Silva APB, Teixeira RM, Farrell M, Prince M. Concurrent and construct validity of the audit in an urban brazilian sample. Alcohol Alcohol 2005; 40(6):584-589.. Individuals are classified into four “risk zones”:

Zone 1 – probable low-risk drinking or abstinence. Score between 0 and 7.

Zone 2– probable at risk drinking. Score between 8 and 15.

Zone 3– probable harmful drinking. Score between 16 and 19.

Zone 4 – probable alcohol dependence. Score between 20 and 40.

For the purpose of analysis, these zones were classified as dummy variables, creating the variables ‘at-risk alcohol use’, ‘harmful drinking’, and ‘alcohol dependence’, where YES corresponds to the pattern of consumption of interest and NO to the other patterns. For example, for the variable ‘at-risk alcohol use’, the group YES refers to the individuals in Zone 2 of the AUDIT (at-risk drinking), while the group NO refers to the other zones (1, 3 and 4).

d) World Health Organization Quality of Life Instrument (WHOQOL-BREF)

QoL was assessed using the WHOQOL-BREF developed by the WHO²¹21. Brasil. Resolução nº 196, de 10 de outubro de 1996. Diário Oficial da União 1996; 11 out.. The instrument contains 26 questions, consisting of two general questions and 24 questions grouped into four domains (physical, psychological, social relationships, and environmental). Each item is scored on a 5-point Likert scale and transformed to a 0-100 lineal scale, with higher scores denoting better quality of life. The final domain scores were calculated using the SPSS syntax file as recommended by the WHO²⁹29. SPSS Inc. Statistical Package for the Social Sciences para Windows. Chicago: SPSS Inc; 2007..

Statistical analysis

The data was analyzed using the Statistical Package for the Social Sciences version 17 (SPSS 17). A descriptive analysis of the outcome QoL was conducted calculating averages, standard deviation, and minimum and maximum values for each WHOQOL-BREF domain. Bivariate analysis was then performed using the t-test to determine the association between the socioeconomic and clinical exposure variables and the different domains of the outcome QoL (p-value < 0.05), except for the variable ‘alcohol consumption’, where ANOVA was conducted using the Bonferroni post-hoc test, also adopting a significance level of 0.05.

Finally, backward stepwise multiple linear regression was performed where the outcomes were the four WHOQOL-BREF domains, thus resulting in four multiple linear regression models. Explanatory variables that obtained a level of significance of less than 10% in the bivariate analysis were included in the final models.

The coefficients of determination (R²2. Portugal FB, Campos MR, Carvalho JR, Flor LS, Schramm JMA, Costa MFS. Carga de doença no Brasil: um olhar sobre o álcool e a cirrose não viral. Cien Saude Colet 2015; 20(2):491-501.), coefficients of the model (β), and their respective p-values for each explanatory variable were calculated and presented for each model. Finally, the residuals of each model were analyzed.

Results

The findings show that the majority of participants were female (72.6%), over 39 years age (64.5%), lived without a partner (57.6%), nonwhite (76%), and had not completed primary education (55%). The majority of interviewees frequented religious activities more than twice a month (64.6%). A little over half of the participants were patients at the UBS (51.1%), with the rest frequenting the ESF center. Almost a quarter of participants (23.7%) had a per capita family income of less than half a minimum salary (R$272.50) (Table 1). The sample was made up predominantly of low-income individuals, with 57.2% of participants having a per capita family of up to one minimum salary and 28.7% between one and two minimum salaries (data not shown).

The lowest average QoL score was obtained in the environmental domain (50.96), while the highest score was in the social relationships domain (66) (Table 1). The results show that being a woman decreased the QoL score by around eight points in all domains (p < 0.05), while being over 39 years reduced the score by 3.5 points in the physical (p = 0.027) and social relationships domains (p = 0.012). In the psychological and environmental domains, QoL was lower among patients with a partner and those with a per capita income of less than or equal to half a minimum salary (p < 0.05), respectively.

The most prevalent disorder was anxiety (42.3%). The prevalence of depression was 29.5%, while only 4% of the participants were shown to have acute somatization. It is interesting to note that the QoL score was lower (p < 0.05) in all domains among all individuals with these disorders (Table 2). Although acute somatization is the least prevalent outcome, the results show a reduction in the QoL score of almost 20 points in the physical domain in the presence of this disorder.

With respect to alcohol consumption, the results show that 4.2% of participants were in Zone 3 (harmful drinking) and 4.8% in Zone 4 (alcohol dependence). QoL scores were lower in all domains among individuals shown to be alcohol dependent by the AUDIT. The Bonferroni post-hoc test was performed after running ANOVA for the variable alcohol consumption (data not shown), followed by a two-by-two comparison with the categories of the AUDIT performed to identify the zones that show statistically significant differences in QoL.

The results show that average QoL scores in the physical domain obtained by individuals in Zone 4 (alcohol dependence) were lower than those obtained by individuals in Zone 3 (harmful drinking) (p-value = 0.06), while average scores in the psychological domain obtained by patients in Zone 2 (at risk drinking) were higher than those obtained by those in Zone 1 (low-risk drinking/abstinence) (p-value = 0.030). In the social relationships domain, scores obtained by individuals in Zone 4 (alcohol dependence) were lower than those obtained by low-risk drinkers/abstainers (p-value = 0.029) and at risk drinkers (p-value = 0.005). Finally, in the environmental domain, at risk drinkers obtained higher QoL scores than low-risk drinkers/abstainers (p-value = 0.000).

The results of the analysis of the AUDIT dummy variables showed a negative association between alcohol dependence and QoL in the social relationships domain and a positive association between at-risk drinking and QoL in all domains except social relationships and between harmful drinking and QoL in the physical and environmental domains (p-value < 5%).

The results of the multivariate analysis (Table 3) showed that the set of selected variables explained 37.8%, 40.6%, 14.5%, and 25.6% of the variation (R²2. Portugal FB, Campos MR, Carvalho JR, Flor LS, Schramm JMA, Costa MFS. Carga de doença no Brasil: um olhar sobre o álcool e a cirrose não viral. Cien Saude Colet 2015; 20(2):491-501.) of QoL in the physical, psychological, social relationships, and environmental domains, respectively. The analysis of the residuals of the multivariate models showed good diagnostic quality.

A statistically significant negative association was found between the variables sex, age group, marital status, per capita income, anxiety, depression, acute somatization, and alcohol dependence and QoL in at least one of the QoL domains. Conversely, a positive association was observed between at-risk drinking and harmful drinking and QoL.

At-risk drinking increased the average QoL score in the psychological domain by around five points (p-value = 0.001), while harmful drinking increased the score in the physical domain by seven points (p-value = 0.019). At-risk and harmful drinking increased the average QoL score in the environmental domain by around six points (p-value < 0.05 for both categories). No association was found between the variables schooling and type of service and the QoL domains in the multivariate analysis.

The variables that showed the strongest association with QoL in all domains (after controlling for the other model variables) were anxiety, depression, somatization, and alcohol consumption (at risk drinking, harmful drinking, and alcohol dependence). The factors that most decreased QoL in the physical domain were anxiety (β = -13.05), depression (β = -11.78), and acute somatization (β = -8.93) (p-value < 0.05), while the factors that most decreased QoL in the psychological, social relationships, and environmental domains were anxiety and depression (p-value < 0.05). The factors at risk drinking (β = 5.77; p-value = 0.000) and harmful drinking (β = 6.15; p-value=0.010) significantly increased QoL in the environmental domain.

Discussion

A statistically significant association was found between marital status, age group, and having a per capita income of less than half a minimum salary and lower QoL scores in at least one domain. A negative association was found between being female and QoL in all domains. Various studies have reported a negative association between QoL and these characteristics¹¹11. Portugal FB, Campos MR, Gonçalves DA, Mari JJ, Fortes SLCL. Qualidade de vida em pacientes da atenção primária do Rio de Janeiro e São Paulo, Brasil: associações com eventos de vida produtores de estresse e saúde mental. Cien Saude Colet 2016; 21(2):497-508.,³⁰30. Chazan ACS, Campos MR, Portugal FB. Qualidade de vida de estudantes de medicina da UERJ por meio do Whoqol-bref: uma abordagem multivariada. Cien Saude Colet 2015; 20(2):547-556.

31. Azevedo ALS, Silva RA, Tomasi E, Quevedo LÁ. Doenças crônicas e qualidade de vida na atenção primária à saúde. Cad Saude Publica 2013; 29(9):1774-1782.

32. Cruz LN, Polanczyk CA, Camey SA, Hoffmann JF, Fleck MP. Quality of life in Brazil: normative values for the WHOQOL-bref in a southern general population sample. Qual Life Res Int J Qual Life Asp Treat Care Rehabil 2011; 20(7):1123-1129.

33. Portugal FB, Campos MR, Gonçalves DA, Mari J de J, Gask L, Bower P, et al. Psychiatric morbidity and quality of life of primary care attenders in two cities in Brazil. J Bras Psiquiatr 2014; 63(1):23-32.-³⁴34. Oliveira-Campos M, Rodrigues-Neto JF, Silveira MF, Neves DMR, Vilhena JM, Oliveira JF, Magalhães JC, Drumond D. Impacto dos fatores de risco para doenças crônicas não transmissíveis na qualidade de vida. Cien Saude Colet 2013; 18(3):873-882..

Given that the individuals were primary healthcare patients, lower QoL in the physical domain was to be expected. Furthermore, greater occurrence of chronic diseases was expected with older age, as shown by other studies³¹31. Azevedo ALS, Silva RA, Tomasi E, Quevedo LÁ. Doenças crônicas e qualidade de vida na atenção primária à saúde. Cad Saude Publica 2013; 29(9):1774-1782.,³²32. Cruz LN, Polanczyk CA, Camey SA, Hoffmann JF, Fleck MP. Quality of life in Brazil: normative values for the WHOQOL-bref in a southern general population sample. Qual Life Res Int J Qual Life Asp Treat Care Rehabil 2011; 20(7):1123-1129.,³⁴34. Oliveira-Campos M, Rodrigues-Neto JF, Silveira MF, Neves DMR, Vilhena JM, Oliveira JF, Magalhães JC, Drumond D. Impacto dos fatores de risco para doenças crônicas não transmissíveis na qualidade de vida. Cien Saude Colet 2013; 18(3):873-882.. Poorer QoL was also expected among individuals with lower monthly salary. However, this was confirmed only in the environmental domain, where this facet of QoL is measured by a specific question, showing a negative association between having an income per capita of less than half a minimum salary and QoL. The environmental domain obtained the lowest score (50.9 points) of the four domains of the WHOQOL-BREF, which is consistent with the findings of various studies conducted in Brazil with populations of lower socioeconomic status¹¹11. Portugal FB, Campos MR, Gonçalves DA, Mari JJ, Fortes SLCL. Qualidade de vida em pacientes da atenção primária do Rio de Janeiro e São Paulo, Brasil: associações com eventos de vida produtores de estresse e saúde mental. Cien Saude Colet 2016; 21(2):497-508.,³⁰30. Chazan ACS, Campos MR, Portugal FB. Qualidade de vida de estudantes de medicina da UERJ por meio do Whoqol-bref: uma abordagem multivariada. Cien Saude Colet 2015; 20(2):547-556.

31. Azevedo ALS, Silva RA, Tomasi E, Quevedo LÁ. Doenças crônicas e qualidade de vida na atenção primária à saúde. Cad Saude Publica 2013; 29(9):1774-1782.-³²32. Cruz LN, Polanczyk CA, Camey SA, Hoffmann JF, Fleck MP. Quality of life in Brazil: normative values for the WHOQOL-bref in a southern general population sample. Qual Life Res Int J Qual Life Asp Treat Care Rehabil 2011; 20(7):1123-1129..

The results of the present study show that the prevalence of suspected cases of anxiety and depression is high. These findings are in line with studies that confirm that these disorders are frequent among primary healthcare patients¹⁰10. Fortes S, Lopes CS, Villano LAB, Campos MR, Gonçalves DA, Mari JJ. Common mental disorders in Petrópolis-RJ: a challenge to integrate mental health into primary care strategies. Rev Bras Psiquiatr 2011; 33(2):150-156.,¹²12. Gonçalves DA, Mari J de J, Bower P, Gask L, Dowrick C, Tófoli LF, Campos M, Portugal FB, Ballester D, Fortes S. Brazilian multicentre study of common mental disorders in primary care: rates and related social and demographic factors. Cad Saude Publica 2014; 30(3):623-632.,³³33. Portugal FB, Campos MR, Gonçalves DA, Mari J de J, Gask L, Bower P, et al. Psychiatric morbidity and quality of life of primary care attenders in two cities in Brazil. J Bras Psiquiatr 2014; 63(1):23-32.. The presence of anxiety, depression, and acute somatization was associated with lower QoL scores in all domains, which is corroborated by the literature¹¹11. Portugal FB, Campos MR, Gonçalves DA, Mari JJ, Fortes SLCL. Qualidade de vida em pacientes da atenção primária do Rio de Janeiro e São Paulo, Brasil: associações com eventos de vida produtores de estresse e saúde mental. Cien Saude Colet 2016; 21(2):497-508.,³¹31. Azevedo ALS, Silva RA, Tomasi E, Quevedo LÁ. Doenças crônicas e qualidade de vida na atenção primária à saúde. Cad Saude Publica 2013; 29(9):1774-1782.,³³33. Portugal FB, Campos MR, Gonçalves DA, Mari J de J, Gask L, Bower P, et al. Psychiatric morbidity and quality of life of primary care attenders in two cities in Brazil. J Bras Psiquiatr 2014; 63(1):23-32.,³⁵35. Corso AN, Costa LS, Fleck MP, Heldt E. [Impact of depressive symptoms in the quality of life of basic health care service users]. Rev Gaucha Enfermagem 2009; 30(2):257-262..

With respect to CMDs, an association was found between anxiety and depression and QoL in all domains, whereas with acute somatization an association was found between the disorder and QoL in only the physical and environmental domains. Acute somatization is defined by the presence of medically unexplained symptoms for at least two years, by the seriousness of such symptoms, and the disability they cause²⁶26. Fabião MCM. Rastreio e diagnóstico da somatização em cuidados primários: validação da screening for somatoform symptoms-2 [Internet]. 2011 [citado 2016 Out 27]. Disponível em: https://repositorio-aberto.up.pt/handle/10216/45217
https://repositorio-aberto.up.pt/handle/... . Disability caused by these symptoms may be related to a reduction in leisure activities and difficulty in engaging in paid activities, thus reducing individual income and explaining lower scores in the environmental domain.

The prevalence rates of harmful drinking and alcohol dependence observed by the present study are similar to those found by other studies conducted in Brazil with primary healthcare patients, which reported rates of between 3% and 10%¹⁴14. Jomar RT, Abreu ÂMM, Griep RH, Jomar RT, Abreu ÂMM, Griep RH. Patterns of alcohol consumption and associated factors among adult users of primary health care services of Rio de Janeiro, Brazil. Cien Saude Colet 2014; 19(1):27-38.,¹⁵15. Vargas D, Oliveira MAF, Araújo EC. Prevalence of alcohol addiction among users of primary healthcare services in Bebedouro, São Paulo State, Brazil. Cad Saude Publica 2009; 25(8):1711-1720.,³⁶36. King M, Nazareth I, Levy G, Walker C, Morris R, Weich S, Bellón-Saameño JA, Moreno B, Svab I, Rotar D, Rifel J, Maaroos HI, Aluoja A, Kalda R, Neeleman J, Geerlings MI, Xavier M, de Almeida MC, Correa B, Torres-Gonzalez F. Prevalence of common mental disorders in general practice attendees across Europe. Br J Psychiatry J Ment Sci 2008; 192(5):362-367..

With respect to the multivariate analysis, different independent variables explain the four QoL domains, which is expected given the WHOQOL-BREF’s objective to investigate different aspects of QoL. The association between schooling and type of service and QoL did not remain in the final regression model, probably due to the correlation between these variables and the other variables included in the analysis and the homogenous nature of the study sample. The proportion of explained variation was greatest for the psychological domain (R²2. Portugal FB, Campos MR, Carvalho JR, Flor LS, Schramm JMA, Costa MFS. Carga de doença no Brasil: um olhar sobre o álcool e a cirrose não viral. Cien Saude Colet 2015; 20(2):491-501. = 40.6%), possibly due to the presence of variables related to mental health and alcohol consumption, which have a stronger association with the facets of QoL assessed under this domain.

It is interesting to note that better QoL scores were obtained in the presence of harmful drinking and at-risk drinking. These findings are relevant to discussions regarding the various ways of understanding alcohol consumption in society. In this respect, although alcohol consumption is linked to cultural and social activities that generate individual pleasure, a significant proportion of research tends to focus on health issues, thus limiting the opportunity to discuss the leisure aspects of alcohol use and the pleasure and positive feelings derived from its consumption³⁷37. Romera LA, Marcellino NC. Lazer e uso de drogas: a partir do olhar sociológico. Impulso 2012; 20(49):75-84.. The psychological domain of the WHOQOL-BREF assesses particular facets of QoL, such as positive and negative feelings, self-esteem, body image and appearance, and personal beliefs. Therefore, individuals who use alcohol in social or recreational activities may have a more positive perception of QoL.

Participation in leisure and recreational activities and financial resources are some of the facets of QoL assessed in the environmental domain, which showed a positive association with at-risk drinking in the present study. Motives for drinking include leisure, recreation, and social interaction, which may be a possible explanation for the association between at risk drinking and QoL in this domain. Furthermore, alcoholic beverages have a financial cost, which is another possible explanation for this association. In other words, this finding may be a reflection of the relationship between higher socioeconomic status and QoL.

As expected, since it is often present when the physical or psychological effects of drug use are identified, alcohol dependence was associated with lower QoL scores in the physical domain. Conversely, an inverse association was found between QoL and harmful drinking.

However, it is important to highlight that the variable harmful drinking was a dummy variable comprising different patterns of alcohol consumption. Therefore the interpretation of this association with QoL in the physical domain should take into account this analysis method. In this respect, it is possible that the observed relationship is not explained exclusively by the presence of harmful drinking.

The findings of the present study in relation to alcohol consumption and QoL are not directly comparable to those of other studies because different methods were used to assess this variable and the outcome. However, our findings corroborate the literature in so much as they indicate that the association between alcohol consumption and QoL varies depending the domain and pattern of consumption.

A cross-sectional study conducted in Brazil with 648 participants using the Medical Outcomes Study 36- Item Short Form- Health Survey (SF-36) observed a statistically significant association between heavy drinking and the QoL dimension functional capacity, but failed to show an association with limitation due to physical aspects, general health status, pain, vitality, social aspects, emotional aspects, and mental health³⁴34. Oliveira-Campos M, Rodrigues-Neto JF, Silveira MF, Neves DMR, Vilhena JM, Oliveira JF, Magalhães JC, Drumond D. Impacto dos fatores de risco para doenças crônicas não transmissíveis na qualidade de vida. Cien Saude Colet 2013; 18(3):873-882.. A case-control study concluded that the QoL scores obtained by drug users (39% of participants used alcohol) were much lower than those obtained by individuals from the control group, except in the environmental domains, where drug users obtained better scores³⁸38. Moreira TC, Figueiró LR, Fernandes S, Justo FM, Dias IR, Barros HMT, Ferigolo M. Quality of life of users of psychoactive substances, relatives, and non-users assessed using the WHOQOL-BREF. Cien Saude Colet 2013; 18(7):1953-1962.. A population-based study conducted in the State of Minas Gerais showed that frequent drinkers obtained lower QoL scores in the physical component, but not in the mental component³⁹39. Noronha DD, Martins AMEBL, Dias DS, Silveira MF, Paula AMBD, Haikal DSA. Qualidade de vida relacionada à saúde entre adultos e fatores associados: um estudo de base populacional. Cien Saude Colet 2016; 21(2):463-474..

With respect to positive associations between alcohol consumption and QoL, our findings are in line with those obtained by some international studies. The “National Epidemiologic Survey on Alcohol and Related Conditions” (NESARC) conducted by the National Institute on Alcohol Abuse and Alcoholism (NIAAA) with 43,093 participants concluded that drinking was associated with better QoL in relation to physical and mental health⁴⁰40. Cougle JR, Hakes JK, Macatee RJ, Chavarria J, Zvolensky MJ. Quality of life and risk of psychiatric disorders among regular users of alcohol, nicotine, and cannabis: An analysis of the National Epidemiological Survey on Alcohol and Related Conditions (NESARC). J Psychiatr Res 2015; 66-67:135-141., while in another study, participants who reported binge drinking showed a higher percentage of physical QoL than participants who did not (no differences were found for mental QoL)⁴¹41. Dey M, Gmel G, Studer J, Mohler-Kuo M. Health-risk behaviors and quality of life among young men. Qual Life Res 2014; 23(3):1009-1017.. Finally, a study conducted in Norway with a random population-based sample of 4,000 individuals showed that nondrinkers reported poorer QoL in the physical health domain⁴²42. Mathiesen EF, Nome S, Eisemann M, Richter J. Drinking patterns, psychological distress and quality of life in a Norwegian general population-based sample. Qual Life Res 2012; 21(9):1527-1536..

One of the limitations of this study is the cross-sectional study design. In this respect, it is assumed that the associations between QoL and sociodemographic factors, alcohol consumption, and CMDs can occur in two directions and cross-sectional studies are limited in their ability to determine the cause-and-effect relationship between variables.

Furthermore, the fact that the study sample was a convenience sample made up of a specific sample of primary healthcare patients led to prevalence bias. This sampling bias meant that individuals with health problems and of lower socioeconomic status were more likely to be included in the sample, resulting in a higher than normal prevalence of CMDs and distorting associations between these variables and QoL.

Finally, diagnostic criteria, such as the DSM -IV or CID-10, were not used for the definition of CMDs and alcohol dependence. False positives may have occurred, given that the instruments used (GHQ-12, SOMs-2, HAD, AUDIT) were screening devices. However, this does not diminish the importance of the findings, given that high prevalence rates were detected and that primary care service plays an essential role in treating these disorders.

Final considerations

This study showed a high prevalence of mental health outcomes and a significant presence of different patterns of alcohol consumption, reiterating the importance of enhancing the capacity of health professionals and primary health services to manage these problems. Moreover, the findings show an association between lower QoL scores and certain socioeconomic factors (being female and aged over 39 years and having a partner and a per capita family income of under half a minimum salary) and health conditions (anxiety, depression, and somatization).

Although a number of studies have shown that alcohol consumption has a negative effect on QoL, the results show that harmful drinking and at-risk drinking are associated with a more positive perception of QoL (particularly in the psychological and environmental domains) among participants. The findings show that the association between alcohol consumption and QoL is not uniform, but rather dependent upon the pattern of consumption. Further research is therefore warranted to obtain a more in-depth understanding of the relationship between different patterns of alcohol consumption and QoL.

In light of the findings, with a view to improving the quality of life of patients, it is recommended that, without disregarding the harmful health effects of alcohol consumption, health professionals and services should adopt strategies where the focus is not exclusively abstinence.

Although QoL is a widely studied construct, this study makes an important contribution because it investigates the relationship between different patterns of alcohol consumption and the different QoL domains specifically in primary healthcare patients.

References

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