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RELATION OF COMMON MENTAL DISORDER, PHYSICAL ACTIVITY AND BODY MASS INDEX IN WOMEN, POPULATION-BASED STUDY

RELAÇÃO ENTRE TRANSTORNO MENTAL COMUM, NÍVEL DE ATIVIDADE FÍSICA E ÍNDICE DE MASSA CORPORAL EM MULHERES, ESTUDO DE BASE POPULACIONAL

ABSTRACT

The literature has shown an increased prevalence of common mental disorder over the years, especially among women. Carrying out population surveys to investigate the prevalence of psychological morbidity and associated factors are relevant, allowing early identification of cases to suggest and/or forward to appropriate intervention strategies. This study aimed to estimate the prevalence of common mental disorders (CMD) and verify its relationship with physical activity levels (PAL), body mass index (BMI) and economic / demographic variables in adult and elderly women in Uberaba, Minas Gerais. The population sample (multistage and probabilistic) consisted by 1520 women. Data collection was carried out through home interviews. For investigation of the CMD it was used the Self-Report Questionnaire; the PAL was measured by long version of the International Physical Activity Questionnaire; to calculate BMI it was measured height and weight. The prevalence of CMD was 29.67%, no significant associations with PAL and BMI. On the other hand, CMD was associated with economic disadvantages (low income and low education) and sociodemographic questions (married and not to be the head of family).

Keywords:
Anxiety; Motor activity; Women’s health.

RESUMO

A literatura tem apontado um aumento da prevalência de Transtorno Mental Comum ao longo dos anos, especialmente entre o público feminino. A realização de levantamentos populacionais que investiguem a prevalência desta morbidade psíquica e fatores a ela associados mostra-se relevante, permitindo identificar precocemente os casos e sugerir e/ou encaminhar para estratégias de intervenção apropriadas. O objetivo do estudo foi estimar a prevalência de transtorno mental comum (TMC) e verificar sua relação com níveis de atividade física (NAF), índice de massa corporal (IMC) e variáveis sociodemográficas e econômicas, em mulheres adultas e idosas de Uberaba, Minas Gerais. A amostra populacional (probabilística em múltiplos estágios) foi composta por 1520 mulheres. A coleta de dados foi realizada por meio de entrevistas domiciliares. Para investigação dos TMC foi utilizada a escala Self-Report Questionnaire; para o NAF utilizou-se a versão longa do Questionário Internacional de Atividade Física; para cálculo do IMC mensurou-se peso e altura. A prevalência de TMC foi de 29,67%, sem associações significativas com o NAF e o IMC. Por outro lado, encontra-se associada às desvantagens socioeconômicas (baixa renda e baixa escolaridade) e a questões sociodemográficas (estar em união e não ser chefe de família).

Palavras-chave:
Ansiedade; Atividade física; Saúde da mulher.

Introduction

Goldberg and Huxley11. Goldberg DP, Huxley P. Common mental disorders: a bio-social model. London: Routledge, 1992. defined Common Mental Disorder (CMD), through a bio-social model, as those cases with non-psychotic symptoms, such as fatigue, irritability, insomnia, concentration difficulties, somatic complaints and depressive symptoms11. Goldberg DP, Huxley P. Common mental disorders: a bio-social model. London: Routledge, 1992., which result in the individual’s disability22. Lahelma E, Pietiläinen O, Rahkonen O, Lallukka T. Common mental disorders and cause-specific disability retirement. Occup Environ Med 2015;72(3):181-187..

CMDs do not meet the requirements to be classified under the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV)33. American Psychiatric Association. Manual diagnóstico e Estatístico de Transtornos Mentais-5: DSM-5.Porto Alegre: Artmed Editora; 2014.. Despite this, theyshow signs and symptoms that, if not identified in the early stages, they may probably evolve to a more advanced and chronic mental disorder, causing suffering that will generate mental, social and labor losses in the individuals' lives22. Lahelma E, Pietiläinen O, Rahkonen O, Lallukka T. Common mental disorders and cause-specific disability retirement. Occup Environ Med 2015;72(3):181-187.),(44. Murray C, Vos T, Lozano R, Naghavi M, Flaxman AD, Michaud D, et al. Disability-adjusted life years (DALYs) for 291 diseasesand injuries in 21 regions, 1990-2010: a systematicanalysis for the Global Burden of Disease Study 2010. Lancet 2012;380(9859):2197-2223..

Literature has shown an increase in the prevalence of CMD over the years44. Murray C, Vos T, Lozano R, Naghavi M, Flaxman AD, Michaud D, et al. Disability-adjusted life years (DALYs) for 291 diseasesand injuries in 21 regions, 1990-2010: a systematicanalysis for the Global Burden of Disease Study 2010. Lancet 2012;380(9859):2197-2223., especially among women55. Rocha SV, Araújo TM, Almeida MMG, Júnior JSV. Prática de atividade física no lazer e transtornos mentais comuns entre residentes de um município do Nordeste do Brasil. Rev Bras Epidemiol 2012;15(4):871-883.. In addition to gender issues, there are other factors that may be associated with CMD, such as low Level of Physical Activity (LPA)66. Harvey SB, Hotopf M, Overland S, Mykletun A. Physical activity and common mental disorders. Br J Psychiatry 2010;197(5):357-364. , high values of Body Mass Index (BMI)77. Kivimäki M, Batty GD, Singh-Manoux A, Nabi H, Sabia S, Tabak AG, et al. Association between common mental disorder and obesity over the adult life course. Br J Psychiatry 2009;195(2):149-155. and socioeconomic indicators such as low level of education and low income88. Shidhaye R, Patel V. Association of socio-economic, gender and health factors with common mental disorders in women: a population-based study of 5703 married rural women in India. Int J Epidemiol 2010;39(6):1510-1521..

Mental illnesses are, in general, neglected when compared to physical health, especially in underdeveloped countries, unrelated to adequate planning and investment in services and public health care within the psychic context99. Lund C, Breen A, Flisher AJ, Kakuma R, Corrigall J, Joska JA, Swartz L, Patel V. Poverty and common mental disorders in lowand middle income countries: A systematic review. Soc Sci Med 2010;71(3):517-528. . There is a mismatch between the demand and the supply of services in this sector. Therefore, only part of the existing cases are identified and adequately addressed,causing an increase in social and economic costs55. Rocha SV, Araújo TM, Almeida MMG, Júnior JSV. Prática de atividade física no lazer e transtornos mentais comuns entre residentes de um município do Nordeste do Brasil. Rev Bras Epidemiol 2012;15(4):871-883..

Population surveys investigating the prevalence of this psychiatric morbidity and their associated factors are relevant, allowing early identification of cases and suggesting and/or referring to appropriate intervention strategies1010. Ashraf K, Alexander CT, Crick LMT. Screening for common mental disorders in low resource settings: reasons for cautionand a wayforward. Int Health 2013;5(1):11-14.. Studies such ours may promote a better understanding of the distribution of this mental disorder in the population, implying in several positive aspects. Health professionals would be more informed about the health profile of people under their care, allowing adequate technical preparation for the health care needed for this population. From the population profile observed with this study, it is possible to mobilize health managers regarding investment priorities for the mental health sector, offering a service compatible with the demand needs. This preparation process can also be applied to the physical structure of the services offered by the health system, which could structure a care network in a way coherent with the health profile of its users. CMD patients wouldalso benefit, since they would have a better prepared health care networkat their disposal, with health services and professionals adequately trained and structured for health care. The general population would benefit from a service that could perform screenings for a mental health problem and, consequently, identify them atan early stage in positive cases, allowing faster care and avoiding their worsening. Population study of women’s mental health profile and physical activity levels could also be good for the research field of Physical Education and public health, as it presents elements for understanding the relationships between mental illness and physical activity level.

To date, studies verifying the concomitant relationship between CMD and LPAand CMD and BMIare unknown. Therefore, this work aimed at estimating the prevalence of CMD and its relations with LPA as well as BMI and, in a supportive way, the relations of this psychic disorder with socio-demographic and economic variables in adult and elderly women living in the urban area of the city of Uberaba, Minas Gerais.

Methods

This is a quantitative, analytical, observational and cross-sectional population-based study, focused on the identification of health profile. The data in this research come from a more comprehensive survey: the Women's Health Survey in the city of Uberaba, Minas Gerais (MG), 2014 (WHS-Woman, 2014), which investigated the general health profile of women residing in city of Uberaba, MG.

Population Characterization

Uberaba, MG is a city located in the TriânguloMineiro region, and currently has an estimated population of 322,126 inhabitants. The data used for the sample calculation were based on IBGE CENSO 2010, a period in which there was a total population of 296,000 inhabitants, of which 151,527 were women1111. Brasil[Internet]. Ministério do Planejamento Orçamento e Gestão. Instituto Brasileiro de Geografia e Estatística. Censo demográfico 2010: características da população e dos domicílios: resultados do universo. Rio de Janeiro: Instituto Brasileiro de Geografia e Estatística, 2011 [acesso em 15 jan 2016]. Disponível em: Disponível em: http://biblioteca.ibge.gov.br/visualizacao/periodicos/93/cd_2010_caracteristicas_populacao_domicilios.pdf
http://biblioteca.ibge.gov.br/visualizac...
.

Participants

The WHS-Woman sample consisted of women aged 18 years and over. However, only adult (20 to 59 years of age) and olderwomen (60 years of age or older) were considered for this study, according to the report "Women and Health: today’s evidence, tomorrow's agenda"1212. Organização Mundial da Saúde. Mulheres e saúde:evidências de hoje, agenda de amanhã. 2011..

The signing of the Informed Consent Form (TCLE) was a prerequisite for the women’s participation, who were informed about the research objectivesas well as the guarantee regarding the secrecy and confidentiality of the information collected. The research was analyzed by the Research Ethics Committee of the Federal University of TriânguloMineiro (UFTM) and was approved as the protocol number 1826/2010.

Sampling Process

We considered a probabilistic sampling in multiple stages, by census tracts and then by households for the participants’ selection. We randomly selected 24 of a total of 36 neighborhoodsin the first stage, respecting the population proportionality of each district in terms of the number of neighborhoods. In the second stage, we selected 25% of the census sectors within each previous neighborhood randomly assigned, respecting the population proportionality of each neighborhood in terms of the number of census sectors. Households were systematically selected within each census sector. The first domicile selected corresponded to the beginning of the sector. The other selected households obeyed a sampling interval (SI)=32, until reaching the desired quantity for each stratum of interest regarding the age group. If the end of the census sector was reached, but the maximum number of respondents for that sector had not been reached, we returned to the beginning of the sector, from the house following the first one selected.

We used the absence of a priori knowledge about the estimates of the prevalence of the events of interest to calculatethe sample size. Thus, all we adopted equal to 50%. To infer the estimates of interest found in the sample over the population, we used a confidence level of 95% and a margin of error of up to 2.5%, according to the formula:

Being Zα: normal distribution score considering the significance level (α= 0.05); me: margin of error for interval estimates; (: estimated proportion of the event of interest. The final sample size for women aged ≥ 18 years was n = 1530 plus 20% loss (n = 1530 + 306 = 1836).

We considered the same population proportions of these strata regarding age range, according to the Brazilian Institute of Geography and Statistics1111. Brasil[Internet]. Ministério do Planejamento Orçamento e Gestão. Instituto Brasileiro de Geografia e Estatística. Censo demográfico 2010: características da população e dos domicílios: resultados do universo. Rio de Janeiro: Instituto Brasileiro de Geografia e Estatística, 2011 [acesso em 15 jan 2016]. Disponível em: Disponível em: http://biblioteca.ibge.gov.br/visualizacao/periodicos/93/cd_2010_caracteristicas_populacao_domicilios.pdf
http://biblioteca.ibge.gov.br/visualizac...
2010 Census so that this study sample to be representative of the women population in the city of Uberaba in terms of age, income, level of education and skin color,

Tools

We used a questionnaire, which was previously tested in a pilot study, for the socio-demographic and economic identification and characterization. The questionnaire asked the following questions: date of birth; current marital status (single, stable union, separated, widow); level of education in full years of study (0; 1-4; 5-8; 9-11; ≥12)1313. Cunha RV, Bastos GAN, Duca GFD. Prevalência de depressão e fatores associados em comunidade de baixa renda de Porto Alegre, Rio Grande do Sul. Rev Bras Epidemiol 2012;15(2):346-354.; skin color (white, yellow, brown, black, red, other); monthly total family income categorized according to minimum wages (MW): <2 MW; ≥2 MW up to 3 MW; ≥4 MW up to 9 MW; ≥10 MW up to 19 MW; ≥20 MW) 1414. Instituto Brasileira de Geografia e Estatística [Internet]. Pesquisa Nacional por Amostra de Domicílios [acesso em 15 jan 2016] Disponível em: Disponível em: http://www.ibge.gov.br/home/estatistica/populacao/trabalhoerendimento/pnad98/saude/analise.shtm
http://www.ibge.gov.br/home/estatistica/...
; number of persons residing in the household; number of people helping with family income; whether or not he or she is the head of the family and whether or not being employed at the time of the survey.

The Self-Report Questionnaire (SRQ-20), developed by Harding et al1515. Harding TW, Arango MV, Baltazar J, Climent CE, Ibrahim HH, Ladrido-Ignacio L, et al. Mental disorders in primary health care: a study of their frequency and diagnosis in four developing countries. Psychol Med 1980;10(2):231-241. , and validated for Brazil by Mari and Williams1616. Mari JJ, Williams P. A validity study of a psychiatric screening questionnaire (SRQ-20) in primary care in the city of Sao Paulo. Br J Psychiatry 1986;148(1):23-26. and by Gonçalves et al1717. Gonçalves DM, Stein AT, Kapczinski F. Avaliação de desempenho do Self-Reporting Questionnaire como instrumento de rastreamento psiquiátrico: um estudo comparativo com o Structured Clinical Interview for DSM-IV-TR. Cad Saúde Pública 2008;24(2):380-390. was used to investigate CMD. It is a low-cost, easy-to-use instrument widely recommended for psychiatric screening1616. Mari JJ, Williams P. A validity study of a psychiatric screening questionnaire (SRQ-20) in primary care in the city of Sao Paulo. Br J Psychiatry 1986;148(1):23-26. of non-psychotic mental disorders1818. Ali Gemma-Claire, Ryan G, De Silva MJ. Validated Screening Tools for Common Mental Disorders in Lowand Middle Income Countries: A SystematicReview. PLoS One 2016;11(6):1-14. both in the clinical context and in epidemiological studies1717. Gonçalves DM, Stein AT, Kapczinski F. Avaliação de desempenho do Self-Reporting Questionnaire como instrumento de rastreamento psiquiátrico: um estudo comparativo com o Structured Clinical Interview for DSM-IV-TR. Cad Saúde Pública 2008;24(2):380-390.. It has categorical answers (yes=one point, no=zero point), and the final score is calculated by the sum of all answers1717. Gonçalves DM, Stein AT, Kapczinski F. Avaliação de desempenho do Self-Reporting Questionnaire como instrumento de rastreamento psiquiátrico: um estudo comparativo com o Structured Clinical Interview for DSM-IV-TR. Cad Saúde Pública 2008;24(2):380-390.. The cut-off point for women is 7/8 (up to seven positive responses=no risk for CMD, eight or more positive responses= risk for CMD)1717. Gonçalves DM, Stein AT, Kapczinski F. Avaliação de desempenho do Self-Reporting Questionnaire como instrumento de rastreamento psiquiátrico: um estudo comparativo com o Structured Clinical Interview for DSM-IV-TR. Cad Saúde Pública 2008;24(2):380-390., with a sensitivity of 86.3% and specificity of 89.3% 1616. Mari JJ, Williams P. A validity study of a psychiatric screening questionnaire (SRQ-20) in primary care in the city of Sao Paulo. Br J Psychiatry 1986;148(1):23-26.).(1818. Ali Gemma-Claire, Ryan G, De Silva MJ. Validated Screening Tools for Common Mental Disorders in Lowand Middle Income Countries: A SystematicReview. PLoS One 2016;11(6):1-14..

LPA was measured using the International Physical Activity Questionnaire (IPAQ), long version. It is a validated and useful tool in Brazil, used in epidemiological studies for all age groups, since it is precise and stable in its measures1919. Matsudo S, Araújo T, Matsudo V, Andrade D, Andrade E, Oliveira LC, et al. Questinário internacional de atividade física (IPAQ): estudo de validade e reprodutibilidade no Brasil. Rev Bras Ativ Fís Saúde 2001;6(2):5-18.. It aims to estimate the time spent weekly in physical activities of light, moderate and vigorous intensity in a wide range of domains (a=physical activity of leisure and recreation, b=domestic and gardening activities, c=work-related physical activity, d=physical activity related to transportation, and sitting time)1919. Matsudo S, Araújo T, Matsudo V, Andrade D, Andrade E, Oliveira LC, et al. Questinário internacional de atividade física (IPAQ): estudo de validade e reprodutibilidade no Brasil. Rev Bras Ativ Fís Saúde 2001;6(2):5-18.. The cut-off point used to classify the participants as physically active was 150 minutes or more spent on activities of moderate intensity2020. US Department and Health and Human Services. Physical activity and health:a report of the Surgeon General. U. S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion. Atlanta, 1996; p. 146-148, or 120 minutes or more spent on activities of vigorous intensity2121. Armstrong T, Bauman A, Davies J. Physical activity patterns of Australian adults: results of the 1999 National Physical Activity Survey. Australian Institute of Health and Welfare. Camberra: Australian Institute of Health and Welfare, 2000. . We considered the domains of work-related physical activity, domestic activities and physical activities of leisure and recreation for the calculation, as proposed by Abel et al2222. Abel T, Graf N, Niemann S. Gender bias in the assessment of physical activity in population studies. Soz Praventiv Med 2001;46(4):268-272. .

Anthropometric data were obtained through weight and height measurements. Weight was measured using the OMRON brand digital scale. Height was measured by means of a measuring tape attached to a wall, placing the women with their back against the wall with their feet together and their body completely erect. BMI was calculated using the weight (in kilograms) over the squared height (in meters). The sample was classified, according to the WHO recommendations2323. Organização Mundial da Saúde. Women’s mental health: An evidence based review. 2000. , as follows: low weight, eutrophic, overweight and obese. However, for women aged 60 years and over, we used the Lipschitz2424. Lipschitz DA. Screening for nutritional status in the elderly. Prim Care 1994;21(1):55-67. classification: low weight, eutrophic and overweight.

Procedures

Data was collected from March to October 2014 by means of home interviews, by female interviewers, who were previously trained in a pilot study. There was field supervision of the interviewers. 10% of the interviews conducted in each census section were randomly checked by telephone.

Data processing

Prior to the data tabulation, a mask was created in the EpiData® program to enter the data, with double typing.

Statistical analysis

For analysis, the women were allocated in the age groups: 20-29 years (young adult); 30-59 years (adult); 60-79 years (elderly)2525. Martins PC, Carvalho MB, Machado CJ. Uso de medidas autorreferidas de peso, altura e índice de massa corporal em uma população rural do nordeste brasileiro. Rev Bras Epidemiol 2015;18(1):137-148. and aged 80 years or over (very old)2626. Oliveira BI, de Oliveira ML, Formoso AMC. Dependência para a realização de atividades relacionadas à alimentação em idosos. Ciênc Saúde Coletiva 2016;21(4):1297-1308..

Statistical analyzes were conducted in the Stata 13 program. CMD positivity was considered as a predictive variable and LPA, age increase and BMI as outcome variables. The level of statistical significance adopted was 5% (p <0.05).

We first carried out a descriptive analysis in order to obtain the frequency and percentages of the studied variables. Subsequently, we performed the bivariate analysis (Chi-square test) to measure the association between the predictive variable (independent) and the outcome (dependent), as well as to verify the distribution of sociodemographic and economic variables. The confidence interval (CI=95%) was calculated to compare the prevalence between the variable categories.

A multivariate analysis was performed in order to establish the relationship between the variables and to obtain the estimates of the Prevalence Ratio (PR). To do so, we used Poisson regression model, using socio-demographic and economic variables as adjustment variables (5% <p <20%), .

Results

The final sample of the WHS-Woman, 2014 totaled 1,557 interviewees. Only women aged 20 years or more were considered in this study. Thus, the sample corresponded to 1,520 women.

The maximum age attained was 94 years (mean=50.67, SD=16.71), with a predominance in the age range between 30-59 years (53.16%). Further information about the sample characteristics is described in Table 1.

Approximately 30% of the women presented positive CMD; 90.26% were classified as active according to IPAQ, but most of them were overweight according to their BMI (38.54%) (Table 1).

Table 2 presents information regarding CMD presenceaccording to socio-demographic and economic characteristics. As for age, CMD occurrenceincreased until the age group of 30-59 years (30.80%). There was a significant difference between the CMD presence and the following variables: civil status (p=0.003); head of the household (p = 0.004); family income (p <0.001) and level of education (p <0.001).

Table 1
Socio-demographic/economic characterization and CMD, LPA, BMI prevalenceeamong women over 20 years old, Uberaba, Minas Gerais, Brazil, 2015
Table 2
CMD prevalence according to the soci-demographic and socio-economic variables among aged 20 or more. Uberaba, Minas Gerais, Brazil, 2015

CMD prevalence was higher among physically active women (88.68%). There were no records of CMD for the inactive category in the very old age group (≥ 80 years). There was a statistically significant association between CMDpresenceregardingLPA only for the age group 60-79 years (p = 0.027). However, there was no significance in the adjusted RP model for these variables (p = 0.235) (Table 3).

As for BMI, the highest CMD prevalencewas foundin overweight women (37.41%). There is a predominance of CMD in the age group of 30-59. There was no statistically significant difference between the CMD presence and the BMI and age groups (Table 4) and between the CMD Prevalence Ratio and BMI and age groups (Table 5).

Table 3
Prevalence ratio andConfidence Intervals of CMD according to LPAand age group of women aged 20 or more. Uberaba, Minas Gerais, Brasil, 2015
Table 4
CMD Prevalenceand Confidence Interval according BMI and age group of women aged 20 or more. Uberaba, Minas Gerais, Brazil, 2015
Table 5
CMD prevalence ratio and Confidence Intervalsaccording to BMI and age group of women aged 20 or more. Uberaba, Minas Gerais, Brazil, 2015

Discussion

The overall prevalence of CMD in this study was 29.67%. This finding is similar to the prevalence values ​​observed in other Brazilian epidemiological studies that investigated both genders (with predominance of women in both, the sample and in the CMD occurrence) and used the same instrument (SRQ-20) for CMD screening55. Rocha SV, Araújo TM, Almeida MMG, Júnior JSV. Prática de atividade física no lazer e transtornos mentais comuns entre residentes de um município do Nordeste do Brasil. Rev Bras Epidemiol 2012;15(4):871-883.. However, Araújoet al2727. Araújo TM, Pinho PS, Almeida MMG. Prevalência de transtornos mentais comuns em mulheres e sua relação com as características sociodemográficas e o trabalho doméstico. Rev Bras Saude Mater Infant 2005;5(3):337-348. and Ludermir and Mello-Filho2828. Ludermir AB, Mello-Filho D. Condições de vida e estrutura ocupacional associadas a transtornos mentais comuns. Rev Saúde Pública 2002;36(2):213-221. found a higher prevalence of CMD (39.4% and 35%, respectively). These divergences in prevalence rates can be explained by the different regional, contextual, target audience and cutoff points used to classify CMD presence/absence.

Regarding age, the literature points to an increase in CMD prevalence as age advances (over 40 years) for both genders55. Rocha SV, Araújo TM, Almeida MMG, Júnior JSV. Prática de atividade física no lazer e transtornos mentais comuns entre residentes de um município do Nordeste do Brasil. Rev Bras Epidemiol 2012;15(4):871-883.. In the present study, there was a higher prevalence in the 30-59 yearsage range, with a reduction in CMD among older women. It appears that over the age of 40 years is a factor associated with the CMD occurrence in women2727. Araújo TM, Pinho PS, Almeida MMG. Prevalência de transtornos mentais comuns em mulheres e sua relação com as características sociodemográficas e o trabalho doméstico. Rev Bras Saude Mater Infant 2005;5(3):337-348., possibly due to estrogen deficiency in advanced ages, which reduces the speed of brain processing, causing impairment of the cognitive function and triggering mood disorders2929. Graae L, Karlsson R, Paddock S. Significant Association of Estrogen Receptor Binding Site Variation with Bipolar Disorder in Females. PLoS ONE 2012;7(2):1-9.. These findings deserve special attention from health professionals since this group represents an economically productive part of society22. Lahelma E, Pietiläinen O, Rahkonen O, Lallukka T. Common mental disorders and cause-specific disability retirement. Occup Environ Med 2015;72(3):181-187., and a psychic ailment at this stage may compromise their work performance22. Lahelma E, Pietiläinen O, Rahkonen O, Lallukka T. Common mental disorders and cause-specific disability retirement. Occup Environ Med 2015;72(3):181-187.),(44. Murray C, Vos T, Lozano R, Naghavi M, Flaxman AD, Michaud D, et al. Disability-adjusted life years (DALYs) for 291 diseasesand injuries in 21 regions, 1990-2010: a systematicanalysis for the Global Burden of Disease Study 2010. Lancet 2012;380(9859):2197-2223.).

Regarding LPA, we observed that nearly 90% of the women were considered physically active. Most women with positive CMD were also physically active (88.68%). The literature points to divergent data, in which individuals with CMD (especially women) tend to be less active than the general population66. Harvey SB, Hotopf M, Overland S, Mykletun A. Physical activity and common mental disorders. Br J Psychiatry 2010;197(5):357-364. . However, the findings of these authors refer only to activities related to sports practice, while the high LPA in our study may be attributed to domestic activities2828. Ludermir AB, Mello-Filho D. Condições de vida e estrutura ocupacional associadas a transtornos mentais comuns. Rev Saúde Pública 2002;36(2):213-221.),(3030. Araújo TM, Almeida MMG, Santana CC, Araújo EM, Pinho PS. Transtornos mentais comuns em mulheres: estudo comparativo entre donas-de-casa e trabalhadoras. Rev Enferm UERJ 2006;14(2):260-269. , since most women are unemployed.

Regarding BMI for the general sample, there was a higher prevalence of overweight women (38.54%). The studies linking CMD and BMI3131. Kivimäki M, Lawlor DA, Singh-Manoux A, Batty GD, Ferrie JE, Shipley MJ, et al. Common mental disorder and obesity: insight from four repeat measures over 19 years: prospective Whitehall II cohort study. BMJ 2009;339:1-8. are scarce and represent results of investigations in both genders,with inconclusive and controversial results3333. Gariepy G, Nitka D, Schmitz N. The association between obesity and anxiety disorders in the population: a systematic review and meta-analysis. Int J Obes 2010;34(3):407-419.. Researches linking depression and BMI3232. Hung CF, Rivera M, Craddock N, Owen MJ, Gill M, Korszun A, et al. Relationship between obesity and the risk of clinically significant depression: Mendelian randomization study. Br J Psychiatry 2014;205(1):24-28. are more common. This is because the relationships between obesity and mental health are complex, and it is possible to establish a bidirectional relationship between CMD and obesity3131. Kivimäki M, Lawlor DA, Singh-Manoux A, Batty GD, Ferrie JE, Shipley MJ, et al. Common mental disorder and obesity: insight from four repeat measures over 19 years: prospective Whitehall II cohort study. BMJ 2009;339:1-8..

There was no significant association between BMI and the CMD positive cases. Goldneyet al3434. Goldney RD, Dunn KL, Air TM, dal Grande E, Taylor AW. Relationships between body mass index, mental health, and suicidal ideation: population perspective using two methods. Aust N Z J Psychiatry 2009;43(7):652-658. did not observe significance between BMI and psychic ailments (depression and suicidal ideation), thus contradicting the paradigm that the BMI increase is related to mental disorders in general.

However, the overweight category stood out over the others regarding the presence of CMD. When examining the relationships between BMI and mental health, one must consider the type and severity of the mental disorder in question3535. McLaren L, Beck CA, Patten SB, Fick GH, Adair CE. The relationship between body mass index and mental health. A population-based study of the effects of the definition of mental health. Soc Psychiatry Pshychiatr Epidemiol 2008;43(1):63-71.. Most of the studies that establish associations between these indicators focus on depression3232. Hung CF, Rivera M, Craddock N, Owen MJ, Gill M, Korszun A, et al. Relationship between obesity and the risk of clinically significant depression: Mendelian randomization study. Br J Psychiatry 2014;205(1):24-28.),(3636. Luppino FS, Wit LM, Bouvy PF, Stijnen T, Cuijpers P, Penninx BW, Zitman FG. Overweight, obesity, and depression: a systematic review and meta-analysis of longitudinal studies. Arch Gen Psychiatry 2010;67(3):220-229. , which is a psychic impairment with duration and symptomatology more intense than CMD. Thus, the data in the literature show that the significant associations between depression and BMI have non-linear tendencies3737. Wit LM, vanStraten A, van Herten M, Penninx BW, Cujipers P. Depression and body mass index, a u-shaped association. BMC Public Health 2009;9(1):14., which means that it is the extremes of BMI (low weight and obesity) that determine the associations between this indicator and the presence of this mental disorder3737. Wit LM, vanStraten A, van Herten M, Penninx BW, Cujipers P. Depression and body mass index, a u-shaped association. BMC Public Health 2009;9(1):14., especially in women3838. Ul-Haq Z, Mackay DF, Fenwick E, Pell JP. Association between body mass index and mental health among Scottish adult population: a cross-sectional study of 37272 participants. Psychol Med 2014;44(10):2231-2240..

Finally, as in our research, several other researchers have also investigated and found inverse associations between socioeconomic conditions (such as low income and low level of education) and CMD88. Shidhaye R, Patel V. Association of socio-economic, gender and health factors with common mental disorders in women: a population-based study of 5703 married rural women in India. Int J Epidemiol 2010;39(6):1510-1521.. According to Ludermir and Mello-Filho2828. Ludermir AB, Mello-Filho D. Condições de vida e estrutura ocupacional associadas a transtornos mentais comuns. Rev Saúde Pública 2002;36(2):213-221., this socioeconomic disadvantage makes individuals more subject to stress situations, contributing to the occurrence of CMD.

The results presented in this study - high prevalence of CMD (29.67%) and association with overweight (37.41%), economically productive age range (30-59 years old - 30.80%), women with low income and low levels of education - offer subsidies for health actions from the perspective of the National Health Promotion Policy in order to induce “social and environmental changes at the collective level to favor healthy choices at the individual level”. According to the National Mental Health Policy (Law No. 10.216/2001), which deals with the protection and rights of persons with mental disorders, it is the State’s responsibility to provide assistance to individuals with this impairment4040. Brasil [Internet]. Lei n. 10.216, de 6 de abril de 2001. Dispõe sobre a proteção e os direitos das pessoas portadoras de transtornos mentais e redireciona o modelo assistencial em saúde mental. Diário Oficial da União, Brasília, DF, 9 abr. 2001 [acesso em 15 jan 2016]. Disponível em: Disponível em: http://www.cress.belemvirtual.com.br/arquivos/File/legislacoes/11_Pol_SaudeMental.pdf
http://www.cress.belemvirtual.com.br/arq...
.

One of the limitations of this research is its design. Since it is a cross-sectional study, it is not possible to establish direct causal relationships between the studied variables. Nevertheless, the information obtained is useful and important to contribute to health care policies, in order to guide health interventions aimed at this population group. In this regard, gender issues need to be considered: women have different health determinants from men, which requires different policies and approaches. Modifying the current model of care to women's mental health is the first step to guarantee theirwholeness and a more humane, efficient and effective care, intervening positively on the reality of the women’s psychological suffering.

Conclusion

CMD prevalence among adult and elderly women in the city of Uberaba, MG was 29.67%. The majority of the women in this sample are physically active (90.26%) according to the IPAQ and 38.54% of the total are overweight, according to the BMI classification. Among women with CMD, the majority was physically active (88.68%) and overweight (37.41%). There were no significant associations between CMD andLPA and BMI. On the other hand, CMD prevalence is associated with socioeconomic disadvantages (low income and low level of education) and socio-demographic issues.

Acknowledgment:

Fundação de Amparo à Pesquisa de Minas Gerais - FAPEMIG, for the Project financing (APQ-01825-12).

References

  • 1. Goldberg DP, Huxley P. Common mental disorders: a bio-social model. London: Routledge, 1992.
  • 2. Lahelma E, Pietiläinen O, Rahkonen O, Lallukka T. Common mental disorders and cause-specific disability retirement. Occup Environ Med 2015;72(3):181-187.
  • 3. American Psychiatric Association. Manual diagnóstico e Estatístico de Transtornos Mentais-5: DSM-5.Porto Alegre: Artmed Editora; 2014.
  • 4. Murray C, Vos T, Lozano R, Naghavi M, Flaxman AD, Michaud D, et al. Disability-adjusted life years (DALYs) for 291 diseasesand injuries in 21 regions, 1990-2010: a systematicanalysis for the Global Burden of Disease Study 2010. Lancet 2012;380(9859):2197-2223.
  • 5. Rocha SV, Araújo TM, Almeida MMG, Júnior JSV. Prática de atividade física no lazer e transtornos mentais comuns entre residentes de um município do Nordeste do Brasil. Rev Bras Epidemiol 2012;15(4):871-883.
  • 6. Harvey SB, Hotopf M, Overland S, Mykletun A. Physical activity and common mental disorders. Br J Psychiatry 2010;197(5):357-364.
  • 7. Kivimäki M, Batty GD, Singh-Manoux A, Nabi H, Sabia S, Tabak AG, et al. Association between common mental disorder and obesity over the adult life course. Br J Psychiatry 2009;195(2):149-155.
  • 8. Shidhaye R, Patel V. Association of socio-economic, gender and health factors with common mental disorders in women: a population-based study of 5703 married rural women in India. Int J Epidemiol 2010;39(6):1510-1521.
  • 9. Lund C, Breen A, Flisher AJ, Kakuma R, Corrigall J, Joska JA, Swartz L, Patel V. Poverty and common mental disorders in lowand middle income countries: A systematic review. Soc Sci Med 2010;71(3):517-528.
  • 10. Ashraf K, Alexander CT, Crick LMT. Screening for common mental disorders in low resource settings: reasons for cautionand a wayforward. Int Health 2013;5(1):11-14.
  • 11. Brasil[Internet]. Ministério do Planejamento Orçamento e Gestão. Instituto Brasileiro de Geografia e Estatística. Censo demográfico 2010: características da população e dos domicílios: resultados do universo. Rio de Janeiro: Instituto Brasileiro de Geografia e Estatística, 2011 [acesso em 15 jan 2016]. Disponível em: Disponível em: http://biblioteca.ibge.gov.br/visualizacao/periodicos/93/cd_2010_caracteristicas_populacao_domicilios.pdf
    » http://biblioteca.ibge.gov.br/visualizacao/periodicos/93/cd_2010_caracteristicas_populacao_domicilios.pdf
  • 12. Organização Mundial da Saúde. Mulheres e saúde:evidências de hoje, agenda de amanhã. 2011.
  • 13. Cunha RV, Bastos GAN, Duca GFD. Prevalência de depressão e fatores associados em comunidade de baixa renda de Porto Alegre, Rio Grande do Sul. Rev Bras Epidemiol 2012;15(2):346-354.
  • 14. Instituto Brasileira de Geografia e Estatística [Internet]. Pesquisa Nacional por Amostra de Domicílios [acesso em 15 jan 2016] Disponível em: Disponível em: http://www.ibge.gov.br/home/estatistica/populacao/trabalhoerendimento/pnad98/saude/analise.shtm
    » http://www.ibge.gov.br/home/estatistica/populacao/trabalhoerendimento/pnad98/saude/analise.shtm
  • 15. Harding TW, Arango MV, Baltazar J, Climent CE, Ibrahim HH, Ladrido-Ignacio L, et al. Mental disorders in primary health care: a study of their frequency and diagnosis in four developing countries. Psychol Med 1980;10(2):231-241.
  • 16. Mari JJ, Williams P. A validity study of a psychiatric screening questionnaire (SRQ-20) in primary care in the city of Sao Paulo. Br J Psychiatry 1986;148(1):23-26.
  • 17. Gonçalves DM, Stein AT, Kapczinski F. Avaliação de desempenho do Self-Reporting Questionnaire como instrumento de rastreamento psiquiátrico: um estudo comparativo com o Structured Clinical Interview for DSM-IV-TR. Cad Saúde Pública 2008;24(2):380-390.
  • 18. Ali Gemma-Claire, Ryan G, De Silva MJ. Validated Screening Tools for Common Mental Disorders in Lowand Middle Income Countries: A SystematicReview. PLoS One 2016;11(6):1-14.
  • 19. Matsudo S, Araújo T, Matsudo V, Andrade D, Andrade E, Oliveira LC, et al. Questinário internacional de atividade física (IPAQ): estudo de validade e reprodutibilidade no Brasil. Rev Bras Ativ Fís Saúde 2001;6(2):5-18.
  • 20. US Department and Health and Human Services. Physical activity and health:a report of the Surgeon General. U. S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion. Atlanta, 1996; p. 146-148,
  • 21. Armstrong T, Bauman A, Davies J. Physical activity patterns of Australian adults: results of the 1999 National Physical Activity Survey. Australian Institute of Health and Welfare. Camberra: Australian Institute of Health and Welfare, 2000.
  • 22. Abel T, Graf N, Niemann S. Gender bias in the assessment of physical activity in population studies. Soz Praventiv Med 2001;46(4):268-272.
  • 23. Organização Mundial da Saúde. Women’s mental health: An evidence based review. 2000.
  • 24. Lipschitz DA. Screening for nutritional status in the elderly. Prim Care 1994;21(1):55-67.
  • 25. Martins PC, Carvalho MB, Machado CJ. Uso de medidas autorreferidas de peso, altura e índice de massa corporal em uma população rural do nordeste brasileiro. Rev Bras Epidemiol 2015;18(1):137-148.
  • 26. Oliveira BI, de Oliveira ML, Formoso AMC. Dependência para a realização de atividades relacionadas à alimentação em idosos. Ciênc Saúde Coletiva 2016;21(4):1297-1308.
  • 27. Araújo TM, Pinho PS, Almeida MMG. Prevalência de transtornos mentais comuns em mulheres e sua relação com as características sociodemográficas e o trabalho doméstico. Rev Bras Saude Mater Infant 2005;5(3):337-348.
  • 28. Ludermir AB, Mello-Filho D. Condições de vida e estrutura ocupacional associadas a transtornos mentais comuns. Rev Saúde Pública 2002;36(2):213-221.
  • 29. Graae L, Karlsson R, Paddock S. Significant Association of Estrogen Receptor Binding Site Variation with Bipolar Disorder in Females. PLoS ONE 2012;7(2):1-9.
  • 30. Araújo TM, Almeida MMG, Santana CC, Araújo EM, Pinho PS. Transtornos mentais comuns em mulheres: estudo comparativo entre donas-de-casa e trabalhadoras. Rev Enferm UERJ 2006;14(2):260-269.
  • 31. Kivimäki M, Lawlor DA, Singh-Manoux A, Batty GD, Ferrie JE, Shipley MJ, et al. Common mental disorder and obesity: insight from four repeat measures over 19 years: prospective Whitehall II cohort study. BMJ 2009;339:1-8.
  • 32. Hung CF, Rivera M, Craddock N, Owen MJ, Gill M, Korszun A, et al. Relationship between obesity and the risk of clinically significant depression: Mendelian randomization study. Br J Psychiatry 2014;205(1):24-28.
  • 33. Gariepy G, Nitka D, Schmitz N. The association between obesity and anxiety disorders in the population: a systematic review and meta-analysis. Int J Obes 2010;34(3):407-419.
  • 34. Goldney RD, Dunn KL, Air TM, dal Grande E, Taylor AW. Relationships between body mass index, mental health, and suicidal ideation: population perspective using two methods. Aust N Z J Psychiatry 2009;43(7):652-658.
  • 35. McLaren L, Beck CA, Patten SB, Fick GH, Adair CE. The relationship between body mass index and mental health. A population-based study of the effects of the definition of mental health. Soc Psychiatry Pshychiatr Epidemiol 2008;43(1):63-71.
  • 36. Luppino FS, Wit LM, Bouvy PF, Stijnen T, Cuijpers P, Penninx BW, Zitman FG. Overweight, obesity, and depression: a systematic review and meta-analysis of longitudinal studies. Arch Gen Psychiatry 2010;67(3):220-229.
  • 37. Wit LM, vanStraten A, van Herten M, Penninx BW, Cujipers P. Depression and body mass index, a u-shaped association. BMC Public Health 2009;9(1):14.
  • 38. Ul-Haq Z, Mackay DF, Fenwick E, Pell JP. Association between body mass index and mental health among Scottish adult population: a cross-sectional study of 37272 participants. Psychol Med 2014;44(10):2231-2240.
  • 39. Brasil. Ministério da Saúde. Secretaria de Vigilância da Saúde. Secretaria de Atenção a Saúde. Política Nacional de Promoção a Sáude. 3.ed. Brasília: Ministério da Saúde; 2010.
  • 40. Brasil [Internet]. Lei n. 10.216, de 6 de abril de 2001. Dispõe sobre a proteção e os direitos das pessoas portadoras de transtornos mentais e redireciona o modelo assistencial em saúde mental. Diário Oficial da União, Brasília, DF, 9 abr. 2001 [acesso em 15 jan 2016]. Disponível em: Disponível em: http://www.cress.belemvirtual.com.br/arquivos/File/legislacoes/11_Pol_SaudeMental.pdf
    » http://www.cress.belemvirtual.com.br/arquivos/File/legislacoes/11_Pol_SaudeMental.pdf

Publication Dates

  • Publication in this collection
    2017

History

  • Received
    20 Sept 2016
  • Reviewed
    02 Nov 2016
  • Accepted
    18 Dec 2016
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