Artigos

INTRODUCTION
Changes in health indicators, such as reduced mortality and fertility, and increased life expectancy characterize the demographic and epidemiological transition, factors that contribute to population aging¹. This phenomenon corresponds to the increase in the number of older people (?60 years in low- and middle-income countries and ?65 years in high-income countries) in relation to other age groups in the population¹. Unlike the aging process in high-income countries, which occurred slowly and was associated with improvements in general living conditions, in low- and middle-income countries this process has been occurring rather rapidly, with no time for social and health system reorganization to meet population demands². In Brazil, the number of older people has been growing at an accelerated pace, from 20.6 million in 2010 to approximately 32.1 million in 2022, and it is estimated that this number will approach 66 million in 2050³.
The increase in the number of older people in Brazil has been accompanied by several changes in household arrangements4,5. Household arrangements can be characterized by the composition of individuals living in the same household. These can be single person, when there is only one resident, or multi-person, when there are two or more residents, whether they are family members or not6,7,8. The structure of the household can influence and be influenced by behavioral, historical, sociocultural, political, economic and demographic factors6,7,8.
Changes in society, such as modernization and urbanization, favor the formation and growth of single-person households for the older people6,7,8. Older people living alone may be associated with better living conditions, such as good health and social integration9,10. On the other hand, living alone can characterize a greater degree of vulnerability and be an aggravating factor for the physical and mental health for the older people9,11,12. Thus, single-person household arrangements have been highlighted as important factors that may or may not contribute to healthy aging7,8 and to the quality of life of older people7,8,10,11.
In Brazil, based on data from the 2013 National Health Survey, Negrini et al.13observed that 15.3% of older people lived alone, with this prevalence being higher in regions with a higher Human Development Index and among individuals with lower incomes. In addition, the study found that living alone was associated with difficulties in instrumental activities of daily living, the presence of some disease, a higher frequency of falls in the previous year and worse lifestyle habits13.
Therefore, the aging pattern in Brazil and the possible changes in living arrangements reflect the need to evaluate the main characteristics of this group to enhance the development of actions to promote healthy aging. However, studies that address the home space of older people in Brazil are still scarce, so the objective of this study was to analyze the temporal trend of the prevalence of Brazilian older people in the state capitals who lived alone in the period 2006-2021.
METHODS
This is a time series study, representative of all 26 capitals of Brazil and the Federal District, based on data collected by the Surveillance of Risk and Protective Factors for Chronic Diseases by Telephone Survey (Vigitel, acronym in Portuguese) from 2006 to 202114.
The Vigitel sample included individuals aged 18 or over who had at least one fixed telephone line in their residence. The collection procedure was carried out in two stages. Briefly, the first stage consisted of drawing lots for telephone lines in the capital cities systematically based on the postal code (ZIP code) of the residence, with 5,000 lines being drawn per municipality. After this draw, a new draw was carried out and divided into replicates of 200 lines, reproducing the same proportion of lines per zip code. The second stage consisted of drawing an individual residing in the drawn household, with a factor for everyone that considers the number of telephone lines and residents in the household, allowing a correction to equalize the estimated sociodemographic composition for the population with telephone, thus providing everyone with the same chance of participating in the survey14.
Between 2006 and 2019, approximately 54,000 individuals were interviewed, and all estimates were weighted to be representative of the population in each city. To estimate the frequencies of the indicators, a 95% confidence interval and a maximum error of approximately three percentage points were considered. Between 2020 and 2021, the minimum sample size established was one thousand individuals in each city, totaling approximately 27,000 interviews. Further details are available in previous publications and in the Vigitel annual reports14. In the present study, the sample comprised individuals aged 60 or over.
Older people were considered to live alone when they lived in a single-person household. The sociodemographic characteristics analyzed were sex (male/female), age group (60-64, 65-69, 70-74 and ? 75 years), education level in years of study (0-8, 9-11, ? 12 years) and macro-regions of the country (North, Northeast, Midwest, South, and Southeast).
The data were statistically processed using Stata software (version 16.0). The complex
sample design and the sample-weighting factor were considered in all these analyses. Post-stratification weights were considered, calculated by the rake method, considering the variables sex, age group and education level, so that the samples are representative of the population evaluated in each city. The annual prevalence and 95% confidence intervals (95%CI) of the prevalence of older people living alone were calculated for the total sample and stratified by sex, age group, education level and regions. Python software, version 3.7.10, was used to present the prevalence and their respective 95%CI over the years, according to the variables analyzed.
For trend analysis, joinpoint regression was used, using the Joinpoint Regression Program software, version 4.9.0.0. Joinpoint regression or inflection point regression allows identifying points of change in relation to the variables and categorizing trends such as stability, increase or decrease. The assumptions of serial autocorrelation, normality and homoscedasticity of the residues were verified by the Durbin-Watson (DW), Shapiro-Wilk and Breusch-Pagan tests, respectively, using Stata software, version 16. In the presence of autocorrelation (DW<2), the correlated error model was used, and if the variable did not present a normal distribution, the Poisson model was used. If the variable did not present normality, the analysis was performed using the Poisson regression model. In cases where DW>2, it was necessary to evaluate the possibilities; in these cases, a graphical analysis of the residuals was also performed. A significant level of 5% was adopted. The annual prevalence rates of older people living alone were considered as dependent variables and survey years as independent variables. The Joinpoint model provides the Annual Percent Change (APC) for each segment and the Average Annual Percent Change (AAPC), and their respective 95%CI15,16. Significant changes (increasing or decreasing) in the variables were indicated when the regression coefficients were significantly different from zero (p < 0.05).
Vigitel was approved by the Comissão Nacional de Ética em Pesquisa para Seres Humyearsdo Ministério da Saúde (CAAE: 65610017.1.0000.0008). Free and informed consent was obtained orally, at the time of telephone contact, for all individuals interviewed.
RESULTS
From 2006 to 2021, Vigitel interviewed 227,051 (28,94%) older people, of which 48,543 (21,38%) were older people who lived alone. Of these older people who lived alone, 79.1% were female, 23% were between 60 and 64 years old, 18% between 65 and 69 years old, 19% between 70 and 74 years old, and 40% were 75 years old or older. Regarding education, 65.7% had up to 8 years of schooling, 18.2% between 8 and 12 years and 16.1%, 12 years or more. Regarding the region of residence, 3.2% were from the North Region, 14.1% from the Northeast Region, 13.2% from the South Region, 60.9% from the Southeast Region and 8.6% from the Midwest Region (data not shown).
The prevalence of older people living alone ranged from 8.4% in 2006 to 10.5% in 2021, with its highest value in 2015 (11.7%). The prevalence was significantly higher in females compared to males, in older people aged 75 years or older compared to other age groups, and in the South and Southeast regions. No significant difference was found by level of education during the period evaluated (Figure 1). Detailed prevalence rates with their respective 95%CI are presented according to sex and age group in Supplementary Table 1 and by level of education and macro-regions in Supplementary Table 2.
In Brazil, from 2006 to 2021, the prevalence of older people living alone remained stable. Significant increasing trends were observed for females from 2006 to 2015 (APC: 1.35%), for older people aged 70-74 from 2006 to 2015 (APC: 1.81%) and aged 75 or over from 2006 to 2021 (APC: 1.12%), with up to 8 years of education level from 2006 to 2021 (APC: 0.87%) and with 12 years or more of education level from 2006 to 2011 (APC: 4.86%), residents in the Northeast Region from 2006 to 2014 (APC: 5.10%), South from 2006 to 2010 (APC: 4.54%) and Midwest from 2006 to 2021 (APC: 1.33%). On the other hand, significant downward trends were observed for females from 2015 to 2021 (APC: -1.72%), for older people aged 70-74 from 2015 to 2021 (APC: -2.33%), with ? 12 years of education level from 2011 to 2021 (APC: -2.09%) and residents in the Northeast Region from 2014 to 2021 (APC: -2.52%). The other groups showed a stable trend in the period (Table 1).
DISCUSSION
Based on data from the Vigitel survey, it was possible to observe a stable trend in the prevalence of Brazilian older people in the state capitals who lived alone from 2006 to 2021. However, when considering sociodemographic characteristics, differences in this trend were observed. Long-lived older people (75 years of age or older), with 0-8 years of schooling and living in the Midwest Region showed an increasing trend in the period from 2006 to 2021. For women and older people between 70 and 74 years of age, there was an inflection point in 2015, with an increasing trend in the first period and a decreasing trend in the second. A similar trend was observed for older people with ? 12 years of schooling and living in the Northeast Region, however, with inflection points in 2011 and 2014, respectively. For the South Region, there was an increasing trend from 2006 to 2010 and a stable trend from 2010 to 2021. Additionally, the highest prevalence of older people living alone was observed among women, older people (75 years of age or older) and those living in the South and Southeast regions.
At an international level, studies that evaluated the living arrangements of older people found prevalence rates of older people living alone18-22similar to those of the present study, for example, Adana et al.22 when analyzing 6,244 older people (60 years or older) in Turkey found a prevalence of 9.79% of older people living alone.
However, other studies conducted in Brazil have shown higher prevalence rates of older people living alone5,13,20,23,24,25. Negrini et al.13 when analyzing the older people participating in the 2013 National Health Survey found that 15.3% lived alone, and These variations can be explained by the use of samples with national13 and local25 coverage, unlike Vigitel, which only includes the capitals and the Federal District14.
Ghahfarokhi20, after assessing the prevalence of older people living alone in Iran through five censuses, found a reduction in the prevalence of older people living alone between 1986 (9.1%) and 1996 (9.0%) and an increase between 2006 (10.9%) and 2016 (14.9%). These changes in prevalence, as identified in this study, can be explained by transformations that occurred over the period, as well as by the presence of changes in the country's economy.
Some studies indicate that living alone can be an indicator of good physical and mental health conditions, in addition to being a predictor of life satisfaction at older ages, as it is related to better health conditions, greater financial autonomy, independence and life expectancy3,6,13. Similarly, Virtuoso Júnior et al.26, evaluating older people from three regions of Brazil in 2009, observed a greater probability of functional disability among those who lived with children, grandchildren and others, compared to those who lived alone.
On the other hand, living alone has also been associated with situations of greater vulnerability and risk, due to the lack of home care services,13,23,25. The natural aging process involves physiological and immunological declines, increasing the likelihood of chronic non-communicable diseases and conditions, which impact functional capacity and cognitive function with advancing age, affecting quality of life, making the older people more susceptible to the need for support (functional, financial, and emotional)27.
Imamura et al.12, examining the relationship between living alone and social isolation on the mortality rate among the older people (65-84 years old) in 2012-2013 in Tokyo, observed that the coexistence of social isolation with the condition of living alone was associated with higher mortality rates, which points to the importance of investigating household arrangements, as well as the needs of the older people for home care and the quality of social relationships.
Several social, historical, cultural, political, economic and demographic factors influence living arrangements, including single-person households7,10. Hence, it is necessary to consider the change in the housing profile and the increase in single-person households in the coming years, as well as the reformulation of public policies to ensure a better quality of life for the older people7,10.
From 2006 to 2021, it was possible to observe a higher prevalence of women living alone compared to men. These findings are consistent with national and international literature10,13,18,20,22,23. This condition can be explained by differences associated with gender. Women are more concerned and careful with their health, which may be related to better health conditions, which contributes to a longer life expectancy3. In addition, distinct marital behaviors are found between the sexes, with higher rates of widowhood and a lower prevalence of remarriage among women older people28. Although a downward trend was observed in the present study between 2015-2021, the predominance of women living alone was constant throughout the time series.
During the period analyzed, there was a higher prevalence of older people who lived alone among the oldest age group. In the same way that the increase in life expectancy contributes to this finding10, the widowed marital status also seems to play a relevant role. The loss of a partner with an advancing age favors the formation of single-person households. In this context, many older people choose to remain in their homes after mourning, influenced by emotional attachment, socioeconomic adversities, emotional dysfunctions and preference, in addition to the desire for greater privacy and the perception of autonomy or not needing assistance29.
This study found no significant differences in education levels among older people living alone. Although Brazil exhibits high educational heterogeneity, especially regarding illiteracy rates across regions and age groups30, the presents results can be explained by the distribution of education in Vigitel, since most of them have similar levels of education, resulting in homogeneity14. Studies conducted in Iran and Turkey have shown a higher percentage of older people living alone among those with lower levels of education20,22. Silva et al.31, evaluating data from the second wave of the ELSI-Brasil study (conducted in 2019-2021) with individuals aged 50 or over, found greater chances of pre-frailty and frailty with increasing age and lower levels of education. The possibility of greater vulnerability in this group stands out, which makes the older people more susceptible to the need for daily care, especially at home.
In the present study, the prevalence and temporal trend of older people living alone varied according to the region of residence. Negrini et al.13 also found higher proportions of older people living alone in the South (17.8%), Northeast (15.9%) and Midwest (15.4%) regions. This can be partially explained by the extensive continental dimension of Brazil, with large demographic, economic and social differences between its regions32.
The South and Southeast regions have a higher life expectancy and proportion of older people, as well as higher Human Development Indexvalues32, which may contribute to older people living alone. This index presents and assesses the well-being of a population, and higher values mean better quality of life and access to services, while lower values indicate higher proportions of poverty and social inequalities32. In addition, the South and Southeast regions have larger population segments with greater urbanization and organization, which may contribute to the greater configuration of single-personarrangements32.
The trend of increasing numbers of older people living alone in the Midwest Region can be explained by both economic and population growth over the years, which have driven the development of the region, with the expansion of large urban centers, improvement of social indicators, increase in health systems and assistance, among others, which, in turn, contribute to improving the living conditions of the population and, consequently, to longevity and healthy aging32. Recognizing regional differences is essential to decentralizing actions so that they can be more effective.
Regarding the limitations of the study, the characterization of the living arrangement should be considered, since living alone was measured only by the absence of another resident in the household. Studies have shown an association not only between the type of living arrangement and the health of the older people, but also the configuration and presence of social interaction. Another limitation to be considered is the Vigitel sample restricted to individuals with a landline telephone. Although coverage is not universal, the application of post-stratification factors allowed the estimates to be corrected, adjusting the sociodemographic distribution and ensuring that they are more representative and reliable.
Among the strengths, the representativeness of the group of capitals stands out, which allows us to portray the sociodemographic profile of the Brazilian older people in the state capitals who lived alone in the period evaluated. In addition, this study presents, for the first time, the temporal trend over the course of 15 years in the single person living arrangement of the Brazilian older people in the state capitals, considering that other studies that investigated the living arrangement in the Brazilian older people do not present the same representativeness.
The COVID-19 pandemic has triggered a series of changes in society, such as the reduction of older people living in single-person households and new living arrangements, as many children returned to their parents' homes and vice versa, due to the situation of greater vulnerability, economic demand and care during this period17. However, in the present study, after sensitivity analysis considering the inclusion or not of the post-pandemic period, no significant differences were observed in the trend of Brazilian older people in the state capitals living alone according to sociodemographic variables.
The findings of the present study encourage reflection on the transformation of the sociodemographic profile of older people living alone and can serve as a basis for the development of new studies that explore the consequences for the live of Brazilian older people living in this type of arrangement, given the differences in cause and effect. In addition, it highlights the need to know the health characteristics of this group to better guide decision-making and develop interventions if necessary, aiming to promote the health and well-being of older people living alone.
CONCLUSION
The time series analysis made it possible to observe a stable trend in the prevalence of Brazilian older people in the state capitals living alone from 2006 to 2021. However, trends of increase and decrease were observed in specific groups, considering sociodemographic characteristics. Due to the possible vulnerability associated with living alone, it is necessary to formulate policies and programs to strengthen social support systems, especially for older people who live alone.
REFERENCES
1. Oliveira AS. Transição demográfica, transição epidemiológica e envelhecimento populacional no brasil. Hygeia .2019;15(31): 69-79.
2. Closs EV, Schwnake CHA. A evolução do índice de envelhecimento no Brasil, nas suas regiões e unidades federativas no período de 1970 a 2010. Rev Bras. Geriatr. Gerontol. 2012; 15(3): 443-458.
3. Instituto Brasileiro de Geografia e Estatística(IBGE). Diretoria de Pesquisas. Coordenação de População e Indicadores Sociais. Gerência de Estudos e Análises da Dinâmica Demográfica. Projeção da população do Brasil e Unidades da Federação por sexo e idade para o período 2010-2060. Rio de Janeiro: IBGE; 2022.
4. Instituto Brasileiro de Geografia e Estatística(IBGE). Diretoria de Pesquisas. Pesquisa Nacional por Amostra de Domicílios Contínua.Características gerais dos domicílios e dos moradores 2023.Rio de Janeiro: IBGE; 2024.
5. Becceneri LB, Brusse GP de L, Aparicio CAP. Uma análise espacial dos arranjos domiciliares da Região Metropolitana de São Paulo (1991-2010). Rev. Bras. Estud. Popul. 2021;38: 1-23.
6. Melo NCVD, Teixeira KMD, Barbosa TL, Montoya ÁJA, Silveira MB. Household arrangements of elderly persons in Brazil: analyses based on the national household survey sample (2009). Rev Bras. Geriatr. Gerontol. 2016; 19(1): 139-151.
7. Elias HC, Marzola TS, Molina NPFM, Assunção LMD, Rodrigues LR, Tavares DMDS. Relation between family functionality and the household arrangements of the elderly. Rev Bras. Geriatr. Gerontol. 2018; 21(5): 562-569.
8. Jiang Y, Li M, Chung T. Living alone and all-cause mortality in community-dwelling older adults: The moderating role of perceived neighborhood cohesion. Soc. Sci. Med. 2023; 317: 115568.
9. Cauduro A, Bós Ângelo JG, Cauduro MHF. Fatores associados a morar sozinho e suas diferenças regionais em idosos residentes de Porto Alegre e Manaus. Estud. Interdiscip. Envelhec. 2013;18(2): 349-365.
10. Almeida PKP de, Sena RM de C, Pessoa Júnior JM, Dantas JL de L, Trigueiro JG, Nascimento EGC do. Experiences of the old people living alone: arrangements, choices and challenges. Rev Bras. Geriatr. Gerontol. 2020;23(5):e200225.
11. Aguiar ACSA, Menezes TMO, Camargo CL. Arranjos familiares com pessoas idosas: fatores contributivos. Av. Enferm. 2018; 36(3): 292-301.
12. Imamura K, Kawai H, Ejiri M, Sasai H, Hirano H, Fujiwara Y, et al. Social isolation, regardless of living alone, is associated with mortality: the Otassha study. Front. Public Health. 2024;12: 1365943.
13. Negrini ELD, Nascimento CF do, Silva A da, Antunes JLF. Elderly persons who live alone in Brazil and their lifestyle. Rev. Bras. Geriatr. Gerontol. 2018; 21(5):523–531.
14. Ministério da Saúde. Secretaria de Vigilância em Saúde e Ambiente. Departamento de Análise Epidemiológica e Vigilância de Doenças Não Transmissíveis. Vigitel Brasil 2023: vigilância de fatores de risco e proteção para doenças crônicas por inquérito telefônico: estimativas sobre frequência e distribuição sociodemográfica de fatores de risco e proteção para doenças crônicas nas capitais dos 26 estados brasileiros e no Distrito Federal em 2023. Brasília: Ministério da Saúde; 2023. 131 p.
15. Kim HJ, Fay MP, Feuer EJ, Midthune DN. Permutation tests for joinpoint regression with applications to cancer rates. Stat Med. 2000;19(3):335-351.
16. Clegg LX, Hankey BF, Tiwari R, Feuer EJ, Edwards BK. Estimating average annual percent change intrend analysis. Stat Med. 2009;28(29): 3670-3682.
17. Camarano AA, Ferdandes D. Famílias: espaços de cuidados e espaços a serem cuidados. In: Camarano AA, Pinheiro L, organizadores. Cuidar, verbo transitivo: caminhos para a provisão de cuidados no Brasil. Rio de Janeiro: Ipea; 2023. p. 141-181.
18. Roh M; Weon S. Living arrangement and life satisfaction of the elderly in South Korea. Soc. Indic. Res. 2022; 160(2): 717-734.
19. Tang D, Lin Z, Chen F. Moving beyond living arrangements: the role of family and friendship ties in promoting mental health for urban and rural older adults in China. Aging Ment Health. 2019;24 (9): 1523–1532.
20. Ghahfarokhi MS. Rising living alone among the elderly in Iran: prevalence and associated factors. BMC Geriatr. 2022;22(1):622.
21. Wandera SO, Ddumba I, Akinyemi JO, Adedini AS, Odimegwu C. Living Alone among Older Persons in Uganda: Prevalence and Associated Factors. Ageing Int. 2017. 42: 429–446.
22. Adana F, Durmaz S, Özvurmaz S, Akp?nar CV, Yes?ilfidan D. Descriptors of living alone for elders: based on Turkey national data. BMC Geriatr. 2022; 22: 37-46.
23. Rabelo DF, Rocha NMFD, Pinto JM. Arranjos de moradia de idosos: associação com indicadores sociodemográficos e de saúde. Rev Subj. 2020; 20(1):2359-0769.
24. Bolina AF, Araújo MC, Hass VJ, Tavares DMS. Association between living arrangement and quality of life for older adults in the community. Rev. Latino-Am. Enfermagem. 2021;29:e3401.
25. Soler DFL, Santos MLSG, Sasaki NSGMS, Pancote CG, Louvison MCP, Silva AC, et al. Pessoas idosas que moram sozinhas: análise de demanda para os serviços sociais e saúde. Rev. Enferm. Cent.-Oeste Min. 2024;14.
26. Virtuoso?Júnior JS, Tribess S. Menezes AS, Meneguci J, Sasaki JE. . Fatores associados à incapacidade funcional em idosos brasileiros. Rev. Andal Med Deport. 2016; 7.
27. Organização Pan-Americana da Saúde (OPAS). Guia de adaptação e implementação de diretrizes baseadas em evidências. Segunda edição. A influência do ambiente no envelhecimento saudável. O desenvolvimento da Rede Mundial de Cidades e Comunidades Amigas das Pessoas Idosas da OMS. Washington, DC: OPAS; 2023.
28. Melo NCV, Teixeira KMD, Ferreira MAM, Silva NM. Consumo de bens e serviços por idosos nos arranjos domiciliares unipessoal e residindo com o cônjuge. SER Social. 2018; 20(42): 112-130.
29. Aclan R, George S, Block H, Lane R, Laver K. Middle aged and older adult’s perspectives of their own home environment: a review of qualitative studies and meta-synthesis. BMC Geriatr. 2023;23:707.
30. INSTITUTO BRASILEIRO DE GEOGRAFIA E ESTATÍSTICA (IBGE). Pesquisa Nacional por Amostra de Domicílios Contínua: Educação 2022. Rio de Janeiro: IBGE, 2024. Disponível em: https://biblioteca.ibge.gov.br/index.php/biblioteca-catalogo?view=detalhes&id=2102002.
31. Silva SLA,Brito GEG, Ygnatios NTM, Mambrini JVM, Lima-Costa MF, Torres JL. Diferenças entre homens e mulheres na prevalência da fragilidade e fatores associados entre adultos mais velhos: evidências do ELSI-Brasil. Cad Saúde Pública. 2024; 40(3).
32. Brasil. Construir caminhos, pactuando novos horizontes. Relatório especial (2023). 25 anos: desenvolvimento humano no Brasil:Brasília, Programa das Nações Unidas para o Desenvolvimento – PNUD; 2024.