ABSTRACT:

Objective:

This study aimed to identify the prevalence of multimorbidity and its associated factors in women in southern Brazil.

Methods:

We conducted a cross-sectional, population-based study with a sample of 1,128 women (age 20–69 years), living in São Leopoldo, southern Brazil. Multimorbidity was defined as two or more chronic conditions measured using the therapeutic and chemical anatomical classification of continuous use medications prescribed by a physician. Poisson regression model with robust variance was used to assess the association between sociodemographic and lifestyle variables and multimorbidity.

Results:

The prevalence of multimorbidity was 21.7% (95%CI 19.3–24.2), and 26 chronic conditions were identified. A direct linear association was observed with age and income and an inverse association with education. Being unemployed was a risk factor for multimorbidity (PR 1.95; 95%CI 1.51–2.52). Alcohol consumption (moderate or excessive) had a protective effect. Overweight and obese women were 53% (PR 1.53; 95%CI 1.09–2.15) and 76% (PR 1.76; 95%CI 1.27–2.45) more likely to have multimorbidity than eutrophic women.

Conclusion:

Over 20% of the adult women had multimorbidity, and its occurrence was strongly associated with socioeconomic characteristics, such as fewer years of schooling, higher income, and not having an occupation. The results regarding alcohol consumption are still insufficient to propose a public policy for the prevention of multimorbidity. Excess weight was an independent risk factor and should be addressed in public health policies for the prevention and management of multimorbidity.

Keywords:
Multimorbidity; Multiple chronic conditions; Chronic disease; Risk factors; Women

INTRODUCTION

The term “multimorbidity” is generally defined as the presence of two or more chronic health conditions in the same individual¹1 Johnston MC, Crilly M, Black C, Prescott GJ, Mercer SW. Defining and measuring multimorbidity: a systematic review of systematic reviews. Eur J Public Health 2019;29(1):182-9. https://doi.org/10.1093/eurpub/cky098
https://doi.org/10.1093/eurpub/cky098... ,²2 World Health Organization. Multimorbidity: technical series on safer primary care. Geneva: World Health Organanization; 2016. Available from: https://apps.who.int/iris/bitstream/handle/10665/252275/9789241511650-eng.pdf
https://apps.who.int/iris/bitstream/hand... . In the conception of multimorbidity, none of the diseases is understood as the main one, believing in the comprehensive management of all health problems that the individual presents³3 Broeiro P. Multimorbilidade e comorbilidade: duas perspectivas da mesma realidade. Rev Port Med Geral Fam 2015;31(3):158-60. https://doi.org/10.32385/rpmgf.v31i3.11520
https://doi.org/10.32385/rpmgf.v31i3.115... . The complexity of assisting patients with multiple chronic diseases brings multimorbidity as a major challenge, especially since health guidelines are usually based on treating isolated conditions⁴4 Onder G, Palmer K, Navickas R, Jurevic˘ienè E, Mammarella F, Strandzheva M, et al. Time to face the challenge of multimorbidity. A European perspective from the joint action on chronic diseases and promoting healthy ageing across the life cycle (JA-CHRODIS). Eur J Intern Med 2015;26(3):157-9. https://doi.org/10.1016/j.ejim.2015.02.020
https://doi.org/10.1016/j.ejim.2015.02.0... –⁹9 Boyd CM, Darer J, Boult C, Fried LP, Boult L, Wu AW. Clinical practice guidelines and quality of care for older patients with multiple comorbid diseases: implications for pay for performance. JAMA 2005;294(6):716-24. https://doi.org/10.1001/jama.294.6.716
https://doi.org/10.1001/jama.294.6.716... .

Epidemiological studies on multimorbidity have shown great methodological differences, which makes it difficult to compare them⁸8 Fortin M, Stewart M, Poitras ME, Almirall J, Maddocks H. A systematic review of prevalence studies on multimorbidity: toward a more uniform methodology. Ann Fam Med 2012;10(2):142-51. https://doi.org/10.1370/afm.1337
https://doi.org/10.1370/afm.1337... ,¹⁰10 Diederichs C, Berger K, Bartels DB. The measurement of multiple chronic diseases -- a systematic review on existing multimorbidity indices. J Gerontol A Biol Sci Med Sci 2011;66(3):301-11. https://doi.org/10.1093/gerona/glq208
https://doi.org/10.1093/gerona/glq208... . Even so, there is a consensus that multimorbidity has a high prevalence in both high-income countries and developing countries, such as Brazil, burdening health systems¹¹11 Garin N, Koyanagi A, Chatterji S, Tyrovolas S, Olaya B, Leonardi M, et al. Global multimorbidity patterns: a cross-sectional, population-based, multi-country study. J Gerontol A Biol Sci Med Sci 2016;71(2):205-14. https://doi.org/10.1093/gerona/glv128
https://doi.org/10.1093/gerona/glv128... –¹⁵15 Marengoni A, Angleman S, Melis R, Mangialasche F, Karp A, Garmen A, et al. Aging with multimorbidity: a systematic review of the literature. Ageing Res Rev 2011;10(4):430-9. https://doi.org/10.1016/j.arr.2011.03.003
https://doi.org/10.1016/j.arr.2011.03.00... .

In the adult population, multimorbidity reaches about 20% in most studies, affecting more women and those with unfavorable socioeconomic conditions¹¹11 Garin N, Koyanagi A, Chatterji S, Tyrovolas S, Olaya B, Leonardi M, et al. Global multimorbidity patterns: a cross-sectional, population-based, multi-country study. J Gerontol A Biol Sci Med Sci 2016;71(2):205-14. https://doi.org/10.1093/gerona/glv128
https://doi.org/10.1093/gerona/glv128... ,¹²12 Nunes BP, Camargo-Figuera FA, Guttier M, Oliveira PD, Munhoz TN, Matijasevich A, et al. Multimorbidity in adults from a southern Brazilian city: occurrence and patterns. Int J Public Health 2016;61(9):1013-20. https://doi.org/10.1007/s00038-016-0819-7
https://doi.org/10.1007/s00038-016-0819-... ,¹⁵15 Marengoni A, Angleman S, Melis R, Mangialasche F, Karp A, Garmen A, et al. Aging with multimorbidity: a systematic review of the literature. Ageing Res Rev 2011;10(4):430-9. https://doi.org/10.1016/j.arr.2011.03.003
https://doi.org/10.1016/j.arr.2011.03.00... –²¹21 Barnett K, Mercer SW, Norbury M, Watt G, Wyke S, Guthrie B. Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study. Lancet 2012;380(9836):37-43. https://doi.org/10.1016/S0140-6736(12)60240-2
https://doi.org/10.1016/S0140-6736(12)60... . Among the elderly, it affects the majority, reaching up to 98% of this group¹⁰10 Diederichs C, Berger K, Bartels DB. The measurement of multiple chronic diseases -- a systematic review on existing multimorbidity indices. J Gerontol A Biol Sci Med Sci 2011;66(3):301-11. https://doi.org/10.1093/gerona/glq208
https://doi.org/10.1093/gerona/glq208... ,¹³13 Nunes BP, Thumé E, Facchini LA. Multimorbidity in older adults: magnitude and challenges for the Brazilian health system. BMC Public Health 2015;15:1172. https://doi.org/10.1186/s12889-015-2505-8
https://doi.org/10.1186/s12889-015-2505-... ,¹⁵15 Marengoni A, Angleman S, Melis R, Mangialasche F, Karp A, Garmen A, et al. Aging with multimorbidity: a systematic review of the literature. Ageing Res Rev 2011;10(4):430-9. https://doi.org/10.1016/j.arr.2011.03.003
https://doi.org/10.1016/j.arr.2011.03.00... ,²²22 Held FP, Blyth F, Gnjidic D, Hirani V, Naganathan V, Waite LM, et al. Association rules analysis of comorbidity and multimorbidity: the concord health and aging in men project. J Gerontol A Biol Sci Med Sci 2016;71(5):625-31. https://doi.org/10.1093/gerona/glv181
https://doi.org/10.1093/gerona/glv181... . In southern Brazil, a population-based study carried out with adults and the elderly observed an overall prevalence of multimorbidity of almost 30%, while in the female population, the prevalence was over 35%¹²12 Nunes BP, Camargo-Figuera FA, Guttier M, Oliveira PD, Munhoz TN, Matijasevich A, et al. Multimorbidity in adults from a southern Brazilian city: occurrence and patterns. Int J Public Health 2016;61(9):1013-20. https://doi.org/10.1007/s00038-016-0819-7
https://doi.org/10.1007/s00038-016-0819-... .

Individuals with multimorbidity have a lower quality of life, lower functional capacity, reduced life expectancy, and a higher risk of mortality than those with isolated conditions¹²12 Nunes BP, Camargo-Figuera FA, Guttier M, Oliveira PD, Munhoz TN, Matijasevich A, et al. Multimorbidity in adults from a southern Brazilian city: occurrence and patterns. Int J Public Health 2016;61(9):1013-20. https://doi.org/10.1007/s00038-016-0819-7
https://doi.org/10.1007/s00038-016-0819-... ,¹⁵15 Marengoni A, Angleman S, Melis R, Mangialasche F, Karp A, Garmen A, et al. Aging with multimorbidity: a systematic review of the literature. Ageing Res Rev 2011;10(4):430-9. https://doi.org/10.1016/j.arr.2011.03.003
https://doi.org/10.1016/j.arr.2011.03.00... ,²³23 Di Angelantonio E, Kaptoge S, Wormser D, Willeit P, Butterworth AS, Bansal N, et al. Association of cardiometabolic multimorbidity with mortality. JAMA 2015;314(1):52-60. https://doi.org/10.1001/jama.2015.7008
https://doi.org/10.1001/jama.2015.7008... –²⁵25 Schmidt TP, Wagner KJP, Schneider IJC, Danielewicz AL. Padrões de multimorbidade e incapacidade funcional em idosos brasileiros: estudo transversal com dados da Pesquisa Nacional de Saúde. Cad Saúde Pública 2020;36(11):e00241619. https://doi.org/10.1590/0102-311X00241619
https://doi.org/10.1590/0102-311X0024161... . These individuals use health services more and receive complex and multiple treatments, which makes adherence to treatment difficult and increases the risk of adverse effects¹⁹19 Violán C, Foguet-Boreu Q, Roso-Llorach A, Rodriguez-Blanco T, Pons-Vigués M, Pujol-Ribera E, et al. Burden of multimorbidity, socioeconomic status and use of health services across stages of life in urban areas: a cross-sectional study. BMC Public Health 2014;14:530. https://doi.org/10.1186/1471-2458-14-530
https://doi.org/10.1186/1471-2458-14-530... ,²⁶26 Bähler C, Huber CA, Brüngger B, Reich O. Multimorbidity, health care utilization and costs in an elderly community-dwelling population: a claims data based observational study. BMC Health Serv Res 2015;15(23). https://doi.org/10.1186/s12913-015-0698-2
https://doi.org/10.1186/s12913-015-0698-... ,²⁷27 Calderón-Larrañaga A, Poblador-Plou B, González-Rubio F, Gimeno-Feliu LA, Abad-Díez JM, Prados-Torres A. Multimorbidity, polypharmacy, referrals, and adverse drug events: are we doing things well? Br J Gen Pract 2012;(605):e821-6. https://doi.org/10.3399/bjgp12X659295
https://doi.org/10.3399/bjgp12X659295... .

In this context, it is important to identify the factors associated with multimorbidity so that preventive measures may be applied effectively. It is already established that lifestyle factors such as smoking, unhealthy eating, alcohol consumption, physical inactivity, and being overweight are associated with the occurrence of many chronic diseases when they are assessed individually²⁸28 Malta DC, Silva Jr JB. O Plano de ações estratégicas para o enfrentamento das doenças crônicas não transmissíveis no Brasil e a definição das metas globais para o enfrentamento dessas doenças até 2025: uma revisão. Epidemiol Serv Saúde 2013;22(1):151-64. http://doi.org/10.5123/S1679-49742013000100016
http://doi.org/10.5123/S1679-49742013000... . Regarding multimorbidity, studies have shown that presenting with a combination of lifestyle factors that is considered unhealthy increases the chances of multimorbidity²⁹29 Dhalwani NN, Zaccardi F, O’Donovan G, Carter P, Hamer M, Yates T, et al. Association between lifestyle factors and the incidence of multimorbidity in an older english population. J Gerontol A Biol Sci Med Sci 2017;72(4):528-34. http://doi.org/10.1093/gerona/glw146
http://doi.org/10.1093/gerona/glw146... ,³⁰30 Fortin M, Haggerty J, Almirall J, Bouhali T, Sasseville M, Lemieux M. Lifestyle factors and multimorbidity: a cross sectional study. BMC Public Health 2014;14:686. http://doi.org/10.1186/1471-2458-14-686
http://doi.org/10.1186/1471-2458-14-686... ; but when evaluated separately, the literature is not consistent about the association of these behavioral characteristics with multimorbidity.

With regard to the above, this study aimed to identify the prevalence of multimorbidity and its associated factors in women in southern Brazil.

METHODS

We conducted a cross-sectional population-based study, with a representative sample of women living in urban areas in the city of São Leopoldo, RS. This research is part of a larger project entitled “Living conditions and health of adult women: population-based study in the Rio dos Sinos Valley – Evaluation after 10 years” carried out in 2015. This study employs multiple-stage sampling methods; details of the methodology used have already been published³¹31 Dias-da-Costa JS, Koltermann AP, Cappellesso B, Lisowski JF, Bernardelli M, Xavier PB, et al. Características das mulheres que não consultam com médico: estudo de base populacional. Rev Saude Publica 2018;52(54). https://doi.org/10.11606/S1518-8787.2018052000190
https://doi.org/10.11606/S1518-8787.2018... . The sample size was calculated based on the outcomes of interest; we chose the one that required a larger sample size. The total sample of 1,128 women made it possible to estimate the prevalence of multimorbidity, with a margin of error of 3% points. For associations, the chosen sample size allowed the detection of prevalence ratios (PR) of ≥1.4, with a power of 80%, using 95% confidence intervals (CIs).

Women who were residents of the urban area of São Leopoldo, residents of the sectors and households drawn, and aged between 20 and 69 years were eligible for inclusion in the study population. Those who may have been in the household drawn at the time of the study but were not residents of that household and pregnant women were excluded. A standardized and pretested questionnaire was administered to each participant in a pilot study. Data quality control was carried out using a shorter questionnaire, which was applied to 10% of the participants.

The outcome “multimorbidity” was assessed from the identification, classification, and usage of drugs prescribed by a doctor that the participant reported, through the question: “Are you (Mrs.) currently using any medication prescribed by a doctor?” To correctly register each medication, it was requested the presentation of the prescription, packaging, or package insert, when possible. To determine the health condition for which each medication was used, the following were taken into account:

1. Main therapeutic indication of the medication (established by the Anatomical Therapeutic Chemical [ATC] classification³²32 World Health Organization Collaborating Centre for Drug Statistics Methodology. Anatomical Therapeutic Chemical (ATC) classification index with Defined Daily Doses (DDD's). Geneva: World Health Organization; 2004., a system adopted by the World Health Organization [WHO] to classify drugs according to the organ or system on which they act);

2. The indication of use referred by the participant; and

3. Other medications used and their therapeutic indication.

When necessary, other auxiliary information was used, such as age and the Self-Reporting Questionnaire (SRQ-20) score³³33 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;148:23-6. https://doi.org/10.1192/bjp.148.1.23
https://doi.org/10.1192/bjp.148.1.23... , the latter being used to confirm the presence of common mental disorders (CMD). The drugs in use that were referred to for acute health conditions or occasional use were not included. Those who presented two or more chronic conditions were considered multimorbid²2 World Health Organization. Multimorbidity: technical series on safer primary care. Geneva: World Health Organanization; 2016. Available from: https://apps.who.int/iris/bitstream/handle/10665/252275/9789241511650-eng.pdf
https://apps.who.int/iris/bitstream/hand... .

The independent variables were classified as demographic, socioeconomic and lifestyle variables, and nutritional status. The demographic variables were age (categorized every 10 years), self-reported skin color (white, black, indigenous, yellow, and parda – the latter being Brazilians of mixed ethnic ancestries), and marital status (not having a partner and having a partner). Socioeconomic variables were education (≥15 years; 11–14 years; 8–10 years; 5–7 years; ≤4 years), household income per capita in quartiles (≤R$ 525.30; >R$ 525.30, and ≤R$ 869.00; >R$ 869.00 and ≤R$ 1,547.00; ≥R$ 1,547.01; corresponding to about two minimum wages, considering a national minimum wage of R$ 788.00, approximately U$ 245 at the time of the study), economic class (A+B; C; D+E; according to the economic classification criteria proposed by the Brazilian Association of Research Companies – which is based on the possession of certain material goods, the education of the head of the family, and the number of employees)³⁴34 Associação Brasileira de Empresas de Pesquisa. Critério de Classificação Econômica do Brasil. São Paulo: Associação Brasileira de Empresas de Pesquisa; 2014., and occupation (employed and unemployed).

Lifestyle variables assessed were smoking (non-smoker; former smoker; current smoker), alcohol consumption (does not consume; moderate consumption; excessive consumption), physical activity (active and inactive), and consumption of fruits and vegetables (adequate and inadequate). Alcohol consumption was established based on the frequency, type of drink, and quantity ingested³⁵35 Hartmann M, Dias-da-Costa JS, Olinto MTA, Pattussi MP, Tramontini Â. Prevalência de hipertensão arterial sistêmica e fatores associados: um estudo de base populacional em mulheres no Sul do Brasil. Cad Saúde Pública 2007;23(8):1857-66. https://doi.org/10.1590/S0102-311X2007000800012
https://doi.org/10.1590/S0102-311X200700... and was classified as excessive when consumption was ≥15 g of ethanol/day³⁶36 Malachias MVB, Souza WKSB, Plavnik FL, Rodrigues CIS, Brandão AA, Neves MFT, et al. 7a Diretriz Brasileira de Hipertensão Arterial. Arq Bras Cardiol 2016;107(Supl 3).. Only 60 (5.8%) women were in the excessive consumption category, and only 2 of these were multimorbid; for this reason, this category was incorporated into the category of moderate consumption in the multivariate analysis. Participants were considered physically active when they reached at least 150 min of weekly physical activity, verified by the International Physical Activity Questionnaire – IPAQ (short version)³⁷37 Matsudo S, Araújo T, Marsudo V, Andrade D, Andrade E, Oliveira L, et al. Questionário Internacional de Atividade Física (IPAQ). estudo de validade e reprodutibilidade no Brasil. Rev Bras Ativ Fís Saúde 2001;6(2):5-18. https://doi.org/10.12820/rbafs.v.6n2p5-18
https://doi.org/10.12820/rbafs.v.6n2p5-1... . The consumption of fruits and vegetables was considered adequate when ≥5 times/day²⁹29 Dhalwani NN, Zaccardi F, O’Donovan G, Carter P, Hamer M, Yates T, et al. Association between lifestyle factors and the incidence of multimorbidity in an older english population. J Gerontol A Biol Sci Med Sci 2017;72(4):528-34. http://doi.org/10.1093/gerona/glw146
http://doi.org/10.1093/gerona/glw146... ,³⁸38 Stables GJ, Subar AF, Patterson BH, Dodd K, Heimendinger J, Van Duyn MAS, et al. Changes in vegetable and fruit consumption and awareness among US adults: results of the 1991 and 1997 5 a day for better health program surveys. J Am Diet Assoc 2002;102(6):809-17. https://doi.org/10.1016/s0002-8223(02)90181-1
https://doi.org/10.1016/s0002-8223(02)90... .

Nutritional status was defined by the body mass index (BMI), which is given by the measurement of weight in kilograms divided by the square of the height in meters, and classified according to criteria from the WHO as follows: <18.5 kg/m²=low weight; ≥18.5 and ≤24.9 kg/m²=eutrophy; ≥25.0 and ≤29.9 kg/m²=overweight; and ≥30.0 kg/m²=obesity³⁹39 World Health Organization. Obesity: preventing and managing the global epidemic. Report of a WHO consultation. Geneva: World Health Organization; 2000.. Weight and height measurements were recorded by trained interviewers. Weight was measured with a portable analog scale, with the participant wearing light clothes and no shoes, and distributing their body weight equally between their feet. Height was measured with a portable stadiometer on the wall, with the interviewee in an upright posture and arms loose along the body. Both measurements were performed in duplicate, and the respective mean values were considered. Only 20 (1.8%) women in the study were classified as underweight, and none of them had multimorbidity. Thus, this category was incorporated into the eutrophic category for the multivariate analysis.

Statistical analysis of the data was performed using Stata version 12.0 statistical software (StataCorp LP, College Station, TX, USA). To verify the association of the exposures of interest with the presence of multimorbidity, a Poisson regression analysis with robust variance was performed⁴⁰40 Barros AJD, Hirakata VN. Alternatives for logistic regression in cross-sectional studies: an empirical comparison of models that directly estimate the prevalence ratio. BMC Med Res Methodol 2003;3:21. https://doi.org/10.1186/1471-2288-3-21
https://doi.org/10.1186/1471-2288-3-21... , according to the multivariable model of analysis⁴¹41 Victora CG, Huttly SR, Fuchs SC, Olinto MT. The role of conceptual frameworks in epidemiological analysis: a hierarchical approach. Int J Epidemiol 1997;26(1):224-7. https://doi.org/10.1093/ije/26.1.224
https://doi.org/10.1093/ije/26.1.224... . According to the model, the first level includes distal variables (sociodemographic), which can determine the intermediate variables (lifestyle variables). These, in turn, are interrelated and can determine the third-level variable (nutritional status), which proximally determines the outcome. All variables were adjusted to those at the same level and higher levels, considering a p-value <0.20. Variables with p-value <0.05 were considered to be associated with the outcome.

The project was approved by the Ethics and Research Committee of the University of Vale do Rio dos Sinos (protocol 650.443). All participants signed the informed consent form.

RESULTS

The prevalence of multimorbidity was 21.7% (95%CI 18.9–24.6). Among the 1,128 women interviewed, 9.5% (n=107) had two chronic conditions, 6.7% (n=76) had three chronic conditions, and 5.5% (n=62) had four or more chronic conditions. Table 1 shows the 26 chronic conditions found in the study population, with the most prevalent being hypertension (23.2%; 95%CI 20.8–25.8), followed by CMD (13.5%; 95%CI 11.5–15.6), which included anxiety and depression disorders.

Regarding sociodemographic characteristics, as seen in Table 2, there was a homogeneous distribution between the age categories, and the average age was 43.4 years (SD=13.4). Most women reported being white (74.5%), living with a partner (63.8%), having 8 or more years of education (59.5%), belonging to economic class C (53.1%), and being employed (58.1%). A quarter of the study population reported family income per capita up to R$ 525.30, and the average family income per capita was R$ 1,295 (SD=1,395).

The prevalence of multimorbidity increased with increasing age, with 59.2% of women between 60 and 69 years of age being multimorbid. Multimorbidity showed an inverse association with educational level, occurring in 38.2% of the population with less than 5 years of education and was also found in 35.8% of women who were unemployed. No statistically significant differences were found in the prevalence of multimorbidity according to skin color, marital status, economic class, and family income per capita.

In the context of lifestyle variables, most women reported an inadequate consumption of fruits and vegetables (56.3%), were inactive (85.6%), had a moderate consumption of alcohol (61.1%), and did not smoke (58.6%). Regarding nutritional status, 33.2% of women were overweight and 32.9% were obese. The prevalence of multimorbidity was higher among those who had an adequate consumption of fruits and vegetables, those who did not consume alcohol, and those who were ex-smokers. The prevalence also increased with an increase in BMI levels. There were no statistically significant differences in the prevalence of multimorbidity according to physical activity (Table 2).

Table 3 shows that after adjusting for potential confounding factors, age and income showed a direct linear association with multimorbidity. Those who aged 60–69 years were 26.5 times more likely to have multimorbidity than those who aged 20–29 years (PR 26.48; 95%CI 8.55–82.03), while those with higher income were 51% more likely (PR 1.51; 95%CI 1.11–2.05) to have multimorbidity than those with lower income. There was an inverse linear association between schooling and multimorbidity, where those with 0–4 years of schooling were 73% more likely (PR 1.73; 95%CI 1.03–2.89) to have multimorbidity than those who had ≥15 years of schooling. Those who were unemployed were almost twice as likely to have multimorbidity than those who were employed (PR 1.95; 95%CI 1.51–2.52). Women who consumed alcohol were 33% (PR 0.67; 95%CI 0.54–0.85) less likely to have multimorbidity than those who did not. Overweight and obese women were 53% (PR 1.53; 95%CI 1.09–2.15) and 76% (PR 1.76; 95%CI 1.27–2.45) more likely to have multimorbidity than eutrophic women, respectively.

DISCUSSION

We identified that one-fifth of the adult and elderly women had two or more chronic conditions, whereas when the category of elderly women was evaluated separately, individuals with multimorbidity represented the majority. Twenty-six chronic conditions were identified, the most prevalent being hypertension and CMD. The occurrence of multimorbidity was strongly associated with socioeconomic characteristics, such as fewer years of schooling, higher income, and not having an occupation. For the characteristics related to lifestyle, the study corroborated the association of multimorbidity with excess weight and found that alcohol consumption had a protective effect.

Our study's reported prevalence of multimorbidity (21.7%) was lower than that in the National Health Survey (PNS 2013), which evaluated a nationally representative sample and found multimorbidity in 26.1% of Brazilian women, considering 22 preestablished chronic conditions⁴²42 Nunes BP, Chiavegatto Filho ADP, Pati S, Teixeira DSC, Flores TR, Camargo-Figuera FA, et al. Contextual and individual inequalities of multimorbidity in Brazilian adults: a cross-sectional national-based study. BMJ Open 2017;7(6):e015885. https://doi.org/10.1136/bmjopen-2017-015885
https://doi.org/10.1136/bmjopen-2017-015... and was also lower than the prevalence found among Brazilian women in the Amazon region, northern Brazil, where multimorbidity reached 35.8%, considering 12 preestablished chronic conditions⁴³43 Araujo MEA, Silva MT, Galvao TF, Nunes BP, Pereira MG. Prevalence and patterns of multimorbidity in Amazon Region of Brazil and associated determinants: a cross-sectional study. BMJ Open 2018;8(11):e023398. https://doi.org/10.1136/bmjopen-2018-023398
https://doi.org/10.1136/bmjopen-2018-023... . These differences can be related to the method of identifying chronic conditions, since the two studies above used self-reported information regarding the presence of chronic conditions from a preestablished list. Our study adopted the use of medicines as a proxy for detecting multimorbidity and, therefore, newly diagnosed women without pharmacological treatment were not included. Thus, it can be assumed that the prevalence of multimorbidity in this population may be even higher.

The positive association between advancing age and multimorbidity has already been demonstrated in other studies¹⁴14 Afshar S, Roderick PJ, Kowal P, Dimitrov BD, Hill AG. Multimorbidity and the inequalities of global ageing: a cross-sectional study of 28 countries using the World Health Surveys. BMC Public Health 2015;15:776. https://doi.org/10.1186/s12889-015-2008-7
https://doi.org/10.1186/s12889-015-2008-... ,¹⁵15 Marengoni A, Angleman S, Melis R, Mangialasche F, Karp A, Garmen A, et al. Aging with multimorbidity: a systematic review of the literature. Ageing Res Rev 2011;10(4):430-9. https://doi.org/10.1016/j.arr.2011.03.003
https://doi.org/10.1016/j.arr.2011.03.00... ,¹⁹19 Violán C, Foguet-Boreu Q, Roso-Llorach A, Rodriguez-Blanco T, Pons-Vigués M, Pujol-Ribera E, et al. Burden of multimorbidity, socioeconomic status and use of health services across stages of life in urban areas: a cross-sectional study. BMC Public Health 2014;14:530. https://doi.org/10.1186/1471-2458-14-530
https://doi.org/10.1186/1471-2458-14-530... ,⁴⁴44 Wang SB, D’Arcy C, Yu YQ, Li B, Liu YW, Tao YC, et al. Prevalence and patterns of multimorbidity in northeastern China: a cross-sectional study. Public Health 2015;129(11):1539-46. https://doi.org/10.1016/j.puhe.2015.06.013
https://doi.org/10.1016/j.puhe.2015.06.0... ,⁴⁵45 Booth HP, Prevost AT, Gulliford MC. Impact of body mass index on prevalence of multimorbidity in primary care: cohort study. Fam Pract 2014;31(1):38-43. https://doi.org/10.1093/fampra/cmt061
https://doi.org/10.1093/fampra/cmt061... . However, our data highlight the fact that between 40 and 49 years old, the prevalence of multimorbidity was 16.3%, while at 50–59 years, it became 39%. Even considering that women consult the doctor more as they age and are, therefore, more likely to be diagnosed with health problems³¹31 Dias-da-Costa JS, Koltermann AP, Cappellesso B, Lisowski JF, Bernardelli M, Xavier PB, et al. Características das mulheres que não consultam com médico: estudo de base populacional. Rev Saude Publica 2018;52(54). https://doi.org/10.11606/S1518-8787.2018052000190
https://doi.org/10.11606/S1518-8787.2018... , it is observed that middle age has a significant impact on the occurrence of multimorbidity, which thus indicates an important avenue for prevention. Although it was not evaluated in our study, the hypothesis that our findings are related to the menopausal status of these women cannot be ruled out, since the post-menopause phase is associated with multimorbidity¹⁶16 Machado VSS, Valadares ALR, Costa-Paiva LS, Moraes SS, Pinto-Neto AM. Multimorbidity and associated factors in Brazilian women aged 40 to 65 years: a population-based study. Menopause 2012;19(5):569-75. https://doi.org/10.1097/gme.0b013e3182455963
https://doi.org/10.1097/gme.0b013e318245... . Nevertheless, it is also biologically plausible that the association between age and multimorbidity is related to an accumulation of stressors throughout life that favor illness and consequently the increase in the number of diseases⁴⁶46 Nunes BP, Batista SRR, Andrade FB, Souza Junior PRB, Lima-Costa MF, Facchini LA. Multimorbidity: the Brazilian Longitudinal Study of Aging (ELSI-Brazil). Rev Saude Publica 2018;52(Suppl 2):10s. https://doi.org/10.11606/S1518-8787.2018052000637
https://doi.org/10.11606/S1518-8787.2018... .

In alignment with literature¹⁴14 Afshar S, Roderick PJ, Kowal P, Dimitrov BD, Hill AG. Multimorbidity and the inequalities of global ageing: a cross-sectional study of 28 countries using the World Health Surveys. BMC Public Health 2015;15:776. https://doi.org/10.1186/s12889-015-2008-7
https://doi.org/10.1186/s12889-015-2008-... ,⁴⁷47 Wikström K, Lindström J, Harald K, Peltonen M, Laatikainen T. Clinical and lifestyle-related risk factors for incident multimorbidity: 10-year follow-up of finnish population-based cohorts 1982-2012. Eur J Intern Med 2015;26(3):211-6. https://doi.org/10.1016/j.ejim.2015.02.012
https://doi.org/10.1016/j.ejim.2015.02.0... , an inverse linear association between schooling and the occurrence of multimorbidity was observed. This is relevant because studies have shown that, in hypertensive patients, low education is associated with limited knowledge about the disease (most prevalent condition in our study), which can negatively affect its control and also contribute to the development of other diseases⁴⁸48 Motter FR, Olinto MTA, Paniz VMV. Conhecimento sobre a farmacoterapia por portadores de hipertensão arterial sistêmica. Ciênc Saúde Coletiva 2013;18(8):2263-74. https://doi.org/10.1590/S1413-81232013000800010
https://doi.org/10.1590/S1413-8123201300... ,⁴⁹49 Motter FR, Olinto MTA, Paniz VMV. Avaliação do conhecimento sobre níveis tensionais e cronicidade da hipertensão: estudo com usuários de uma Farmácia Básica no Sul do Brasil. Cad Saúde Pública 2015;31(2):395-404. https://doi.org/10.1590/0102-311X00061914
https://doi.org/10.1590/0102-311X0006191... . Besides, our finding also shows how exposure to a marker of a socioeconomic level that is difficult to reverse impacts the development of multimorbidity, increasing the need for public health measures aimed at reducing social inequalities.

On evaluating social inequality indicators, an association was observed between low-income or lower socioeconomic status and multimorbidity¹⁹19 Violán C, Foguet-Boreu Q, Roso-Llorach A, Rodriguez-Blanco T, Pons-Vigués M, Pujol-Ribera E, et al. Burden of multimorbidity, socioeconomic status and use of health services across stages of life in urban areas: a cross-sectional study. BMC Public Health 2014;14:530. https://doi.org/10.1186/1471-2458-14-530
https://doi.org/10.1186/1471-2458-14-530... ,²¹21 Barnett K, Mercer SW, Norbury M, Watt G, Wyke S, Guthrie B. Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study. Lancet 2012;380(9836):37-43. https://doi.org/10.1016/S0140-6736(12)60240-2
https://doi.org/10.1016/S0140-6736(12)60... ,⁴⁴44 Wang SB, D’Arcy C, Yu YQ, Li B, Liu YW, Tao YC, et al. Prevalence and patterns of multimorbidity in northeastern China: a cross-sectional study. Public Health 2015;129(11):1539-46. https://doi.org/10.1016/j.puhe.2015.06.013
https://doi.org/10.1016/j.puhe.2015.06.0... ,⁴⁵45 Booth HP, Prevost AT, Gulliford MC. Impact of body mass index on prevalence of multimorbidity in primary care: cohort study. Fam Pract 2014;31(1):38-43. https://doi.org/10.1093/fampra/cmt061
https://doi.org/10.1093/fampra/cmt061... ,⁵⁰50 Agborsangaya CB, Lau D, Lahtinen M, Cooke T, Johnson JA. Multimorbidity prevalence and patterns across socioeconomic determinants: a cross-sectional survey. BMC Public Health 2012;12:201. https://doi.org/10.1186/1471-2458-12-201
https://doi.org/10.1186/1471-2458-12-201... However, similar to our findings, data from the PNS 2013 showed that the southern states of Brazil, which are more developed in terms of both income and education, showed an increase in the occurrence of multimorbidity, possibly related to an increase in the life expectancy in these states in comparison with the others states⁴². Additionally, it is known that higher income is associated with greater access to health care services³¹, which may be related to a higher number of diagnoses and, therefore, a higher percentage of multimorbidity.

We found association between women who were unemployed and multimorbidity. PNS 2013 data also showed that unemployed adults were almost 20% more likely to have multimorbidity than those who were employed⁵¹51 Carvalho JN, Roncalli ÂG, Cancela MC, Souza DLB. Prevalence of multimorbidity in the Brazilian adult population according to socioeconomic and demographic characteristics. PLoS One 2017;12(4):e0174322. https://doi.org/10.1371/journal.pone.0174322
https://doi.org/10.1371/journal.pone.017... . The authors stated that it should be taken into account that primary health care services are only offered during weekdays and daytime hours in the Brazilian public health system, impairing the access of those who work, thereby impacting the diagnosis of multimorbidity, which should be considered when interpreting our results. However, we cannot rule out the possibility of reverse causality, since the presence of chronic diseases increases the chances of the individual not being able to work precisely because of poor health⁵²52 Smith P, Chen C, Mustard C, Bielecky A, Beaton D, Ibrahim S. Examining the relationship between chronic conditions, multi-morbidity and labour market participation in Canada: 2000-2005. Ageing and Society 2014;34(10):1730-48. https://doi.org/10.1017/S0144686X13000457
https://doi.org/10.1017/S0144686X1300045... . According to a national sample of American adults, as the level of multimorbidity increased, the chances of the individual not working significantly increased⁵³53 Frith E, Ramulu PY, Ashar B, Loprinzi PD. Association of single and multiple medical conditions with work status among adults in the United States. J Lifestyle Med 2019;9(1):15-26. https://doi.org/10.15280/jlm.2019.9.1.15
https://doi.org/10.15280/jlm.2019.9.1.15... .

The association between alcohol consumption and multimorbidity still remains controversial. While some studies have shown no association between these variables²⁹29 Dhalwani NN, Zaccardi F, O’Donovan G, Carter P, Hamer M, Yates T, et al. Association between lifestyle factors and the incidence of multimorbidity in an older english population. J Gerontol A Biol Sci Med Sci 2017;72(4):528-34. http://doi.org/10.1093/gerona/glw146
http://doi.org/10.1093/gerona/glw146... ,³⁰30 Fortin M, Haggerty J, Almirall J, Bouhali T, Sasseville M, Lemieux M. Lifestyle factors and multimorbidity: a cross sectional study. BMC Public Health 2014;14:686. http://doi.org/10.1186/1471-2458-14-686
http://doi.org/10.1186/1471-2458-14-686... , a Brazilian study conducted with individuals who aged 50 years or older found that those who did not consume alcohol had a higher prevalence of multimorbidity⁴⁶46 Nunes BP, Batista SRR, Andrade FB, Souza Junior PRB, Lima-Costa MF, Facchini LA. Multimorbidity: the Brazilian Longitudinal Study of Aging (ELSI-Brazil). Rev Saude Publica 2018;52(Suppl 2):10s. https://doi.org/10.11606/S1518-8787.2018052000637
https://doi.org/10.11606/S1518-8787.2018... . Along the same lines, we found alcohol consumption to be a protective factor for multimorbidity. Other evidence has also identified moderate alcohol consumption as a protective factor for chronic conditions⁵⁴54 Rehm J, Roerecke M. Cardiovascular effects of alcohol consumption. Trends Cardiovasc Med 2017;27(8):534-8. https://doi.org/10.1016/j.tcm.2017.06.002
https://doi.org/10.1016/j.tcm.2017.06.00... ,⁵⁵55 Kaluza J, Harris HR, Linden A, Wolk A. Alcohol consumption and risk of chronic obstructive pulmonary disease: a prospective cohort study of men. Am J Epidemiol 2019;188(5):907-16. https://doi.org/10.1093/aje/kwz020
https://doi.org/10.1093/aje/kwz020... . However, it is possible that women with multimorbidity stopped consuming alcoholic beverages after diagnosis of chronic diseases, and for this reason, the temporality of this association should be investigated in longitudinal studies.

Finally, our investigation pointed out a significant dose-response relationship between BMI categories and the prevalence of multimorbidity. This association is consistent with findings from several studies that have assessed the relationship between nutritional status and multimorbidity¹⁶16 Machado VSS, Valadares ALR, Costa-Paiva LS, Moraes SS, Pinto-Neto AM. Multimorbidity and associated factors in Brazilian women aged 40 to 65 years: a population-based study. Menopause 2012;19(5):569-75. https://doi.org/10.1097/gme.0b013e3182455963
https://doi.org/10.1097/gme.0b013e318245... ,³⁰30 Fortin M, Haggerty J, Almirall J, Bouhali T, Sasseville M, Lemieux M. Lifestyle factors and multimorbidity: a cross sectional study. BMC Public Health 2014;14:686. http://doi.org/10.1186/1471-2458-14-686
http://doi.org/10.1186/1471-2458-14-686... ,⁴⁴44 Wang SB, D’Arcy C, Yu YQ, Li B, Liu YW, Tao YC, et al. Prevalence and patterns of multimorbidity in northeastern China: a cross-sectional study. Public Health 2015;129(11):1539-46. https://doi.org/10.1016/j.puhe.2015.06.013
https://doi.org/10.1016/j.puhe.2015.06.0... ,⁴⁵45 Booth HP, Prevost AT, Gulliford MC. Impact of body mass index on prevalence of multimorbidity in primary care: cohort study. Fam Pract 2014;31(1):38-43. https://doi.org/10.1093/fampra/cmt061
https://doi.org/10.1093/fampra/cmt061... . In this context, it is known that the prevalence of excess weight has been increasing over the years⁵⁶56 Mitchell S, Shaw D. The worldwide epidemic of female obesity. Best Pract Res Clin Obstet Gynaecol 2015;29(3):289-99. https://doi.org/10.1016/j.bpobgyn.2014.10.002
https://doi.org/10.1016/j.bpobgyn.2014.1... . Therefore, one can speculate as to the negative impact this will have on the incidence of multimorbidity in the future. As it is also a chronic condition, some studies on multimorbidity have used the presence of obesity as part of the construction of the outcome, instead of as an exposure¹¹11 Garin N, Koyanagi A, Chatterji S, Tyrovolas S, Olaya B, Leonardi M, et al. Global multimorbidity patterns: a cross-sectional, population-based, multi-country study. J Gerontol A Biol Sci Med Sci 2016;71(2):205-14. https://doi.org/10.1093/gerona/glv128
https://doi.org/10.1093/gerona/glv128... ,⁵⁰50 Agborsangaya CB, Lau D, Lahtinen M, Cooke T, Johnson JA. Multimorbidity prevalence and patterns across socioeconomic determinants: a cross-sectional survey. BMC Public Health 2012;12:201. https://doi.org/10.1186/1471-2458-12-201
https://doi.org/10.1186/1471-2458-12-201... . However, given its established role as a risk factor for chronic noncommunicable diseases²⁸, we chose to assess the presence of excess weight as a risk factor for multimorbidity, thereby highlighting the importance of public policies in combating this pandemic.

This study has some limitations. The cross-sectional design did not allow us to establish a temporal relationship between the exposure and outcome, although it appears that the hierarchical model accounted for those variables with possible reverse causality. In relation to the external validity, this is a population-based study carried out in a city in southern Brazil, and for this reason, it is possible that the findings cannot be extrapolated to populations with characteristics different from this study population.

The lifestyle variables assessed were self-reported; therefore, it is possible that behaviors that are recognized as negative by the general population may have been underreported and, as a result, would be higher than those presented in the study. For the assessment of nutritional status, gauging weight and measuring height circumvented the possibility of this bias.

One of the criticisms made of the concept of multimorbidity is that it often does not take into account the severity of the health conditions⁵⁷57 Willadsen TG, Bebe A, Køster-Rasmussen R, Jarbøl DE, Guassora AD, Waldorff FB, et al. The role of diseases, risk factors and symptoms in the definition of multimorbidity – a systematic review. Scand J Prim Health Care 2016;34(2):112-21. https://doi.org/10.3109/02813432.2016.1153242
https://doi.org/10.3109/02813432.2016.11... . However, polypharmacy is common in multimorbidity and is associated with the occurrence of adverse effects due to drugs²⁷27 Calderón-Larrañaga A, Poblador-Plou B, González-Rubio F, Gimeno-Feliu LA, Abad-Díez JM, Prados-Torres A. Multimorbidity, polypharmacy, referrals, and adverse drug events: are we doing things well? Br J Gen Pract 2012;(605):e821-6. https://doi.org/10.3399/bjgp12X659295
https://doi.org/10.3399/bjgp12X659295... . Additionally, the initial conduct during the management of some chronic conditions is the adoption of healthy habits associated or not with pharmacological treatment. Thus, when we include women already using medication, it can be assumed that nonpharmacological management as an isolated therapy was not effective and, therefore, due to the requirement of medication, the disease being treated is likely to be severe.

To the best of our knowledge, this is the first population-based study conducted among women in southern Brazil where medication usage was employed to detect chronic conditions, enabling the identification of a wide range of diseases, and pointing out its severity. As per our understanding, the strategy used to classify morbidity by reporting the name of the drug contributed to better data quality. Since the current use of medicines was considered, these were classified according to their main therapeutic indication and confirmed by the self-report of the individuals interviewed. The evaluation of medication use also allowed an unlimited number of health conditions to be considered without restricting it to a specific number of preestablished diseases, as observed in most available studies¹⁴14 Afshar S, Roderick PJ, Kowal P, Dimitrov BD, Hill AG. Multimorbidity and the inequalities of global ageing: a cross-sectional study of 28 countries using the World Health Surveys. BMC Public Health 2015;15:776. https://doi.org/10.1186/s12889-015-2008-7
https://doi.org/10.1186/s12889-015-2008-... ,³⁰30 Fortin M, Haggerty J, Almirall J, Bouhali T, Sasseville M, Lemieux M. Lifestyle factors and multimorbidity: a cross sectional study. BMC Public Health 2014;14:686. http://doi.org/10.1186/1471-2458-14-686
http://doi.org/10.1186/1471-2458-14-686... ,⁵⁰50 Agborsangaya CB, Lau D, Lahtinen M, Cooke T, Johnson JA. Multimorbidity prevalence and patterns across socioeconomic determinants: a cross-sectional survey. BMC Public Health 2012;12:201. https://doi.org/10.1186/1471-2458-12-201
https://doi.org/10.1186/1471-2458-12-201... ,⁵¹51 Carvalho JN, Roncalli ÂG, Cancela MC, Souza DLB. Prevalence of multimorbidity in the Brazilian adult population according to socioeconomic and demographic characteristics. PLoS One 2017;12(4):e0174322. https://doi.org/10.1371/journal.pone.0174322
https://doi.org/10.1371/journal.pone.017... . Furthermore, the use of ATC classification has already been considered as an up-to-date mapping approach to identify patients with chronic diseases using pharmacy data⁵⁸58 Huber CA, Szucs TD, Rapold R, Reich O. Identifying patients with chronic conditions using pharmacy data in Switzerland: an updated mapping approach to the classification of medications. BMC Public Health 2013;13:1030. https://doi.org/10.1186/1471-2458-13-1030
https://doi.org/10.1186/1471-2458-13-103... , and other studies investigating multimorbidity have also used this methodology¹²12 Nunes BP, Camargo-Figuera FA, Guttier M, Oliveira PD, Munhoz TN, Matijasevich A, et al. Multimorbidity in adults from a southern Brazilian city: occurrence and patterns. Int J Public Health 2016;61(9):1013-20. https://doi.org/10.1007/s00038-016-0819-7
https://doi.org/10.1007/s00038-016-0819-... ,²⁶26 Bähler C, Huber CA, Brüngger B, Reich O. Multimorbidity, health care utilization and costs in an elderly community-dwelling population: a claims data based observational study. BMC Health Serv Res 2015;15(23). https://doi.org/10.1186/s12913-015-0698-2
https://doi.org/10.1186/s12913-015-0698-... ,⁵⁹59 Agrawal S, Agrawal PK. Association between body mass index and prevalence of multimorbidity in low-and middle-income countries: a cross-sectional study. Int J Med Public Health 2016;6(2):73-83. https://doi.org/10.5530/ijmedph.2016.2.5
https://doi.org/10.5530/ijmedph.2016.2.5... ,⁶⁰60 Marengoni A, von Strauss E, Rizzuto D, Winblad B, Fratiglioni L. The impact of chronic multimorbidity and disability on functional decline and survival in elderly persons. A community-based, longitudinal study. J Intern Med 2009;265(2):288-95. https://doi.org/10.1111/j.1365-2796.2008.02017.x
https://doi.org/10.1111/j.1365-2796.2008... . However, due to the absence of a validated instrument for screening the variety of chronic conditions addressed in studies on multimorbidity, the use of various methods limits the comparability of results among the available studies.

CONCLUSION

This study showed that the prevalence of multimorbidity in women increases significantly with increasing age and is not restricted only to the elderly population. Given the aging of the population, multimorbidity should be treated as a public health problem that is a cause for worry, especially since the prevention and management of multiple health conditions is a task of great complexity for health systems.

Our study identified a range of factors associated with increased multimorbidity, such as fewer years of education, higher income, and not having an occupation. Regarding nutritional status and lifestyle characteristics, excess weight was observed to be an independent risk factor for multimorbidity, while alcohol consumption displayed a protective effect. It is vital to understand the risk factors that must be addressed by both clinical guidelines and public health policies so that the strategies to be proposed address the challenge of preventing and managing multimorbidity.

ACKNOWLEDGMENTS

Franken received a scholarship from Brazilian Federal Agency for Support and Evaluation of Graduated Education (CAPES). Olinto received research productivity grants from the Brazilian Council for Scientific and Technological Development – CNPq (process no. 307257/2013-4 e 307175/2017-0). Dias-da-Costa received research productivity grants from CNPq (process no. 310595/2018-0). We also thank to the National Council for Scientific and Technological Development for the support that they are providing for development of this study.

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