Adriano Florencio Vilaçaa; Bárbara Cristina de Souza Pedrosaa; Emanuelle Rocha Tenório de Françab; Thamara Cunha Nascimento Amarala; Maria do Amparo Andradeb; Célia Maria Machado Barbosa de Castroc; Eduardo Eriko Tenório de Françad
OBJECTIVE: To verify the effect of change and/or maintenance of poor sociodemographic factors, lifestyle and health conditions on the incidence of functional dependence for instrumental activities of daily living (lADLs) in people aged 50 years or older living in urban settings.
METHODS: The relationship between IADLs and risk factors was analyzed in a prospective 4-year follow-up study involving 412 participants. Relative risk (RR) and 95% confidence intervals (95%CI) were calculated using Poisson regression models, adjusted for sex, age and education.
RESULTS: The incidence of dependence for IADLs was 18.9%. Functional dependence was independently associated with lower socioeconomic status (RR = 2.03, 95%CI 1.24-3.32), lack of occupational activity (RR = 2.46, 95%CI 1.31-4.61), inadequate fruit and vegetable intake (RR = 1.90, 95%CI 1.06-3.38) and poor performance in the Mini Mental "State Examination (RR = 2.52, 95%CI 1.53-4.17). The association between functional dependence and diabetes mellitus approached statistical significance (RR = 1.39, 95%CI 0.92-2.10).
CONCLUSIONS: The results showed that worse socioeconomic conditions and chronic health issues were associated with the incidence of dependence for IADLs. These findings highlight the importance of comprehensive and interdisciplinary health care for populations with these characteristics.
Keywords: prospective studies; disability; middle age; risk factors.
OBJETIVO: Verificar o efeito de alterações de fatores sociodemográficos, estilo de vida e condições de saúde na incidência de dependência funcional para as atividades instrumentais de vida diária (AIVD) em pessoas de 50 anos ou mais em área urbana.
MÉTODO: A relação entre AIVD e fatores de risco foi analisada em 412 indivíduos por meio de estudo longitudinal prospectivo com seguimento de quatro anos usando o cálculo do risco relativo (RR) e intervalo de confiança 95% (IC95%) em modelos de regressão de Poisson, ajustados por sexo, faixa etária e escolaridade.
RESULTADO: A incidência de dependência de IAVD foi de 18,9% e estava associada de maneira independente a indivíduos com pior condição socioeconômica (RR = 2,03, IC95% 1,24-3,32), ausência de atividade laboral (RR = 2,46, IC95% 1,31-4,61), consumo irregular de frutas e vegetais (RR = 1,90, IC95% 1,063,38), e pior perfomance no miniexame do estado mental (RR = 2,52, IC95% 1,53-4,17). A diabetes apresentou uma tendência de associação com a incidência de dependência funcional (RR = 1,39, IC95% 0,92-2,10).
CONCLUSÃO: Os resultados demonstram que piores condições socioeconômicas e de saúde estão associadas a maior incidência de dependência funcional por AIVD. Esses achados contribuem na elaboração de programas de promoção de saúde mais abrangentes e efetivos para esta população.
Palavras-chave: estudos prospectivos; pessoas com deficiência; pessoas de meia-idade; fatores de risco.
Population aging around the world and especially in low-and middle-income countries has highlighted the importance of ensuring the quality of life of older adults. The World Health Organization (WHO) recommends a series of initiatives to promote health, prevent disease and provide equitable access to primary and long-term care, in order to help preserve functional independence, an important indicator of quality of life in old age.1
A core dimension of functional capacity is the independence to perform instrumental activities of daily living (IADLs), which enable an individual to manage their environment and maintain social interactions in order to ensure independent community living. These activities include using the telephone, going shopping, preparing meals, getting dressed, doing housework, taking medication and balancing checkbooks.2 The prevalence of disability in IADLs among older adults in Brazil is estimated to be 30.1%,3 while in Spain, England and the United States, this figure is estimated to be 23.5, 26.0 and 40.0%, respectively, in individ-uals aged 50 years or older.4 These disabilities result in the increased use of health services, higher financial costs for the family and community and reduced quality of life, in addition to higher odds of dementia.
Disability in IADLs is multifactorial, and results from a combination of variables which affect different areas of life, including health conditions, lifestyle and sociodemographic characteristics.1 Though a sizeable number of longitudinal studies in the international literature have sought to identify the main predictors of dependence for IADLs,5-8 these studies are still scarce in the national lit-erature, with most investigations adopting cross-sectional designs which cannot provide information about changes over time, or identify predictors of functional dependence.9-11 Longitudinal studies are therefore necessary to provide a deeper understanding of this issue and serve as a basis for future interventions.
Another important aspect of dependence for IADLs is that its predictors and associated risk factors are specific to sociocultural contexts. In high income countries, the main predictors and associated risk factors for functional dependence are health conditions and/or lifestyle factors7,8 whereas in Brazil, possibly due to social inequality, the most significant factors in this regard are sociodemographic variables such as low income, low education levels, gender, old age and chronic illnesses.11 It is important to note that studies on the topic conducted in Brazil involved older adults only. Studies of middle-aged adults which could allow for the early detection of predictors of functional dependence are still lacking.
Therefore, the aim of this study was to investigate the effects of changes or maintenance of low socioeconomic status, lifestyle factors and health conditions on the incidence of functional dependence for IADLs in individuals aged 50 years or older in the northern region of the state of Paraná, Brazil.
This was a prospective, longitudinal study conducted as part of a project named "Incidence of mortality, morbidity, hospitalization and modification of risk factors for cardiovascular disease in a sample of adults aged 40 years or older in a medium-sized city in Southern Brazil: The 2011-2015 Vigicardio Cohort study" (VIGICARDIO).
Data for this study were collected in two stages: baseline in 2011 and follow-up in 2015. The baseline sample size was calculated based on a prevalence of 50%, a 95% confidence interval and a margin of error of 3%. To account for drop-out and participant withdrawal, the required sample size was increased by 25%, resulting in a total of 1,332 individuals aged 40 years or older. To ensure the sample was representative of the target population, the number of individuals to be interviewed in each of the 86 census sectors in the city was calculated based on the gender and age structure of the population. Census sectors were divided into districts, streets and blocks. The final sample was composed of 1,180 participants.
All participants interviewed at baseline who could be located by the research team were invited to take part in the follow-up interview. No exclusion criteria were applied at this point in the study. Data at baseline and follow-up were collected during home visits.
All participants who were younger than 50 years and/or reported difficulties with for two or more IADLs at baseline were excluded from the present study. According to these criteria, 535 of the 1180 participants interviewed in 2011 were eligible for this study. After the loss of 123 participants for a variety of different reasons, the final sample consisted of 412 individuals (response rate = 77%) (Figure 1).
The main outcome of this study was dependence for IADLs, as determined by the Lawton and Brody Scale.2 Eight instrumental activities were investigated (using the telephone, using transportation to go places outside the home, shopping, doing housework, getting dressed, preparing own meals, taking prescription medication and managing finances). Three response alternatives were available for each activity:
Needs no assistance;
Needs some assistance;
Needs complete assistance or cannot perform the task.
When participants reported they did not usually perform any of the activities investigated, they were asked to consider whether they could do so without help, if necessary. Functional dependence for IADLs was defined as a need for some or complete assistance for at least two activities.
The following sociodemographic variables were analyzed in the sample: gender; education, as measured by full years of study (≤ 3 years or ≥ 4 years); age (50-59 years or ≥ 60 years); marital status (no partner or with partner); employment status, as determined by self-reported occupational activity (yes or no) and socioeconomic status as determined by the Brazilian Economic Classification Criteria (Critério de Classificação Econômica Brasil; CCEB), developed by the Brazilian Association of Market Research Companies (Associação Brasileira de Empresas e Pesquisas; ABEP), which provides a score ranging from 0 to 100. This score was used to divide the sample into thirds, which were later classified into two categories: lower third (score ≤ 21), composed of individuals with the lowest socioeconomic status, and higher thirds (score ≥ 22), which included participants whose socioeconomic status was classified into the two highest thirds.
The following lifestyle variables were investigated in the present study: physical activity during leisure time at least once a week; smoking status; and insufficient fruit and/or vegetable intake, defined as a frequency of fewer than five days a week.
The health conditions investigated in this study included cognitive performance as well as major cardiovascular risk factors (hypertension, diabetes, dyslipidemia and central obesity).
Cognitive performance was assessed using the Mini Mental State Examination (MMSE), which evaluates global and domain-specific cognitive functioning. Scores range from 0 to 30, with higher values indicating better cognitive performance.12 The scores obtained by participants were ranked in ascending order and the 25th percentile was used to create two categories: lower cognitive performance (score ≤ 22) and higher cognitive performance (score ≥ 23).
Participants were classified as having hypertension if they took medication for this condition, or had a mean diastolic blood pressure ≥ 90 mmHg and/or systolic blood pressure ≥ 140 mmHg. Blood pressure was measured three times, and the mean of the last two measurements was taken.
Diabetes was defined as a fasting blood sugar level of ≥ 126 mg/dL and/or use of prescribed medication for diabetes.
Dyslipidemia was defined based on the use of prescription medication and/or alterations in one or more of the following measures: LDL cholesterol (LDL-L), HDL cholesterol, (HDL-C) and triglycerides (TGL). Lipid reference values were drawn from the V Brazilian Guidelines for Dyslipidemia and Atherosclerosis Prevention. These values are LDL-C ≥ 160 mg/dL; HDL-C < 40 or 50 mg/dL for men and women, respectively; and TGL ≥ 150 mg/dl.
These data were used to classify individuals according to the presence or absence of dyslipidemia.
Central obesity was defined based on waist circumference. Values higher than 88cm for women and 102cm among men were indicative of central obesity.
The study was conducted according to Resolutions 196/6 and 466/2012 which regulate research involving human participants. Both the baseline and follow-up stages were approved by the Research Ethics Committee of the Universidade Estadual de Londrina. At both timepoints, participants were given detailed information about the goals and procedures of the study, and were guaranteed anonymity, voluntary participation and the possibility of withdrawal from the study at any time. They also provided written consent to participation.
At baseline and follow-up, the data were collected using paper forms and entered in duplicate into a Microsoft Office Excel® 2010 spreadsheet. The two versions were compared using Epi Info® v. 3.5.3 (in 2011) and Microsoft Office SpreadSheet Compare® (in 2015) in order to identify and correct any inconsistencies. Information in the follow-up stage was also collected using Open Data Kit (ODK) Collect and exported into Microsoft Office Excel®.
The first analysis involved the association between dependence for IADLs and the variables expected to remain constant (gender and education) or change over time (age). These were used as adjustment variables in the second analysis, which examined the relationship between dependence for IADLs and independent variables which could also change over time (marital status, socioeconomic scores, employment status, smoking, alcohol use, fruit/vegetable intake, cognitive performance and chronic illnesses). These potentially changing variables were then dichotomized for analysis. Variables were coded as follows:
Remained in the best possible condition at both baseline and follow-up (reference);
Worsened over time or remained consistently poor (comparison group).
Variables were described using frequencies and percentages, as well as mean and standard deviation values. Inferential procedures involved a χ2 test to evaluate the association between the outcome and each independent variable, as well as bivariate and multivariate Poisson regression models with robust error variance to calculate the RR for dependence for IADLs for each risk factor. All analyses were conducted using IBM SPSS, version 19.0 for Windows, with results considered significant at 5%.
Most of the 412 participants interviewed at baseline were women (59.2%) with partners (72.1%), at least four years of education (68.9%) and 50 to 59 years of age (57.8%) (mean: 59.8; standard deviation: 7.2).
The comparison between participants (n = 412) and those lost to follow-up (n = 123) revealed no significant differences on any variables with the exception of smoking, which was less frequent among participants (15.3%) than those lost to follow-up (25.2%). However, the comparison of participants (n = 412) to the group of individuals eligible for follow-up (n = 535) revealed no significant differences in the proportion of smokers in each group (15.3 and 17.6%) (Table 1).
A total of 78 (18.9%) participants became dependent for IADLs over the four-year follow-up period. Data collected in 2011 (baseline) revealed that older participants (≥ 60 years) with lower education levels (≤ 3 years) were, respectively, 1.87 (95% confidence interval [CI] 1.25-2.80) and 2.34 (95%CI 1.58-3.46) times more likely to be dependent for IADLs. After statistical adjustments, only education remained associated with a higher incidence of dependence for IADLs (RR = 1.99; 95%CI 1.32-3.00) (Table 2).
The bivariate analysis revealed that the loss of a partner, a low socioeconomic status (lower third), lack of occupational activity, insufficient fruit and vegetable intake, diabetes and low scores on the MEEM (< 23) were predictors of dependence for IADLs (Table 3). After adjusting for potential confounds (gender, age and education), dependence for IADLs remained associated with a low socioeconomic status (RR = 2.03; 95%CI 1.24-3.32), lack of occupational activity (RR = 2.46; 95%CI 1.31-4.61), insufficient fruit and vegetable intake (RR = 1.90; 95%CI 1.06-3.38) and lower scores on the MMSE (RR = 2.52; 95%CI 1.53-4.17) (Table 3). The presence of diabetes was also associated with a higher incidence of dependence for IADLs (RR = 1.39; 95%CI 0.92-2.10), though this finding did not achieve statistical significance.
This prospective, observational, epidemiological cohort study revealed that low socioeconomic status and some health habits and conditions were significantly associated with an increased risk of dependence for IADLs, even after adjusting for confounding variables. Functional dependence was significantly more frequent in individuals with low socioeconomic status, low education levels, no current occupation, low fruit and vegetable intake and poor cognitive performance. Dependence for IADLs was also associated with diabetes. These findings suggest that the incidence of dependence was higher among individuals living under adverse conditions.
After four years, the incidence of dependence for IADLs among individuals aged 50 years or older was 18.9%. This figure is similar to that obtained in another Brazilian study, conducted in São Paulo, where the incidence of functional dependence after eight years of follow-up was 17.8% in individuals aged 60 years or older.13 However, given the scarcity of longitudinal studies of functional dependence for Brazil, their predominant focus on older populations, and methodological variations in the assessment of dependence, it is difficult to compare findings across investigations.
The characteristics which affect functional dependence for Brazil appear to be distinct from those observed in higher-income countries, where the most significant predictors of dependence are usually related health and life-style7,8 rather than modifiable socioeconomic factors and chronic illness.11,13
The present study also revealed a higher rate of functional dependence for IADLs among individuals with three or fewer years of education. IADLs are complex activities which rely on the interplay between several different cognitive skills, whose development is positively associated with education.14 As such, the association between education and functioning may be attributable to the negative impact of low education levels on executive functioning, which results in decreased functional capacity and more difficulty performing IADLs. Low education levels may also be associated with restricted access to socioeconomic resources and lower socioeconomic status. In light of this observation, it is also possible that education is associated with dependence for IADLs due to the scarcity of resources available to these individuals, which increases the likelihood of illness and functional impairment. It is therefore possible that investment in education could prevent or delay functional dependence by addressing the unfavorable circumstances associated with low education such as poor health, cognitive decline and lower socio-economic status.
The incidence of dependence for IADLs was higher in participants whose socioeconomic status worsened or remained consistently low throughout the study, relative to individuais whose socioeconomic status remained high at both time points. The national literature suggests that socioeconomic inequality is a major contributor to health inequities, so that individuals with lower socioeconomic status have a greater risk of illness and functional dependence relative to those with better socioeconomic conditions.9,15 Though this pattern is more typical of developing countries, social inequality has also been found to affect functioning in international studies conducted in developed countries.5,16 As such, low socioeconomic status may restrict access to resources which help preserve health and wellbeing, thereby contributing to functional dependence. Another important observation is that socioeconomic status in middle age may reflect the occupational and academic achievements of earlier stages of life, and the negative effects of adverse conditions may be aggravated by retirement, increasing the risk of dependence.
Dependence for IADLs was also associated with a lack of occupational activity. A higher number of new cases of functional dependence was observed in individuals with no occupational activity or who interrupted their occupational activities during the follow-up period, relative to individuals who remained employed throughout the study. The lack of occupational activity restricts the opportunities for social interaction, increasing the likelihood of functional dependence. On a similar note, Escobar and colleagues found that the loss of every node of the social network (work, church, friend groups, etc.) increases the likelihood of dependence for IADLs.17 Another possible explanation for the association between these variables is that the executive dysfunction that accompanies cognitive decline and impairs IADLs may also interfere with occupational activities. This is supported by the findings of Marshall et al., who found that executive dysfunction is the main contributor to functional impairment, leading to early loss of productivity and preventing occupational activities.18
Ji et al. demonstrated that limitations caused by the loss of functional ability for IADLs can impact on quality of life, which includes the ability to remain employed.19 On the other hand, the absence of occupational activities may reflect a physically inactive lifestyle and an unwillingness to engage in activities such as leaving the house, interacting with others and carrying out IADLs such as using transportation, using the telephone and managing finances. Therefore, it is possible that the absence of occupational activities reduces the opportunities to practice IADLs.
The risk of developing dependence for IADLs was higher among individuals with irregular fruit and vegetable intake relative to those who consumed these foods regularly. This finding corroborates that of a previous investigation involving the same population as the present study, which found that irregular fruit and vegetable intake may be the result of social inequality, since the main barriers to the consumption of these items were cost, lack of knowledge and family habits.20 Additionally, Soares et al. found that the inadequate intake of these items can lead to nutritional deficiencies, which are associated with chronic illness and poor functional performance.21
Hardman et al. found that the Mediterranean diet helped reduce the progression of neurodegenerative diseases and was strongly associated with the prevention and treatment of chronic conditions which led to functional dependence.22 These benefits were observed in both younger and older adults living in Mediterranean countries or other parts of the world.
In the present study, diabetes was associated with a higher incidence of dependence for IADLs. These findings corroborate the existing literature, which finds diabetes to be one of the conditions most commonly associated with functional dependence.23 This may be explained by the complications associated with diabetes, which include:
vascular disorders that interfere with circulation, oxygenation and cell metabolism, with significant effects on cognition, especially memory and the executive functions, both of which are crucial for the IADLs;24
obesity and heart disease, which in severe cases can be incapacitating;23
visual impairment, amputations and lower limb ulcers which interfere with mobility and prevent the unassisted completion of IADLs.25
The strength of the association between dependence for IADLs and diabetes underscores the need for primary care initiatives to reduce the burden of this disease. Examples of such initiatives include finding ways to manage risk factors for diabetes and understanding the impact of this condition on the progression to functional dependence.
The incidence of dependence for IADLs was also higher among those with lower scores on the MMSE. This association has been consistently reported in previous studies in Brazil11,13 and elsewhere.8,26,27 This finding may be attributable to the impairments observed in patients with cognitive decline, which often include alterations in at least one executive function (working memory, inhibitory control or cognitive flexibility),28 as well as attention, learning, memory, motor perception, language and social cognition. Difficulties in reasoning, planning and problem-solving skills can compromise the ability to complete IADLs with no help. These findings suggest that cognitive decline may precede functional impairment, which corroborates the conclusions of a systematic review performed in 2015.29 These observations also agree with those of the American Psychiatric Association, which identify cognitive decline as a predictor of functional dependence and suggest that the combination of these conditions increases the likeli-hood of progression to major neurocognitive disorder, or dementia.27 These findings underscore the importance of cognitive and functional screening in the primary care network, since early detection is crucial for the implementation of strategies to prevent dementia.
A strength of this study was its prospective longitudinal design, which allowed for the identification of temporal associations between risk factors and functional disability for IADLs in the Brazilian population, a topic which has not been extensively studied in the literature. The low dropout rate was also a strength of this study, since it increased the likelihood that participants eligible for follow-up were representative of the target population. The present study also makes an important contribution to the literature by identifying risk factors for functional dependence for a medium-sized city in Brazil, since most studies are conducted in large population centers and little epidemiological data are available from other regions in the country.
The following aspects of may be considered limitations of this study:
The relatively short follow-up period (four years) may have caused an underestimation of the deleterious effects of risk factors on functional dependence;
The information was obtained from self-report questionnaires, and therefore, may have been influenced by cultural barriers, as well as participants’ cognition and mood; this type of bias may have led to errors in the classification of dependence status.
The results may only apply to populations with a similar sociocultural profile, with low education levels and poor socioeconomic conditions.
This study found that poverty and chronic illness were significantly associated with an increased risk of dependence for IADLs in individuals aged 50 years or older. These data highlight the importance of social determinants of health as a target for research and interventions.30 There is a need for public policies to improve social conditions and provide access to comprehensive health care and multidisciplinary teams. Though some of the risk factors for functional impairment are inevitable, some of the variables identified in the present study can be modified by educational, occupational, economic and health interventions.
1. Organização Mundial da Saúde. Envelhecimento ativo: uma política de saúde. Brasília: Organização Pan-Americana da Saúde; 2005.
2. Santos RL, Virtuoso Júnior JS. Confiabilidade da versão brasileira da escala de atividades instrumentais da vida diária. Rev Bras Promoção Saúde. 2008;21(4):290-6.
3. Silva AMM, Mambrini JVM, Peixoto SV, Malta DC, Lima-Costa MF. Uso de serviços de saúde por idosos brasileiros com e sem limitação funcional. Rev Saúde Pública. 2017;51(Supl. 1):1-10. https://doi.org/10.1590/S1518-8787.2017051000243
4. Sole-Auro A, Crimmins EM. Who cares? A comparison of informal and formal care provision in Spain, England and the USA. Ageing Soc. 2014;34(3):495- 517. https://dx.doi.org/10.1017%2FS0144686X12001134
5. Wahrendorf M, Reinhardt JD, Siegrist J. Relationships of disability with age among adults aged 50 to 85: evidence from the United States, England and continental Europe. PloS One. 2013;8(8):e71893. https://doi.org/10.1371/journal.pone.0071893
6. Qian J, Ren X. Association between comorbid conditions and BADL/ IADL disability in hypertension patients over age 45: Based on the China health and retirement longitudinal study (CHARLS). Medicine. 2016;95(31):e4536. https://doi.org/10.1097/MD.0000000000004536
7. Torres JL, Lima-Costa MF, Marmot M, Oliveira C. Wealth and disability in later life: the English Longitudinal Study of Ageing (ELSA). PloS One. 2016;11(11):e0166825. https://doi.org/10.1371/journal.pone.0166825
8. Hajek A, Luck T, Brettschneider C, Posselt T, Lange C, Wiese B, et al. Factors affecting functional impairment among elderly Germans - Results of a longitudinal study. J Nutr Health Aging. 2017;21(3):299- 306. https://doi.org/10.1007/s12603-016-0771-5
9. Pinto AH, Lange C, Pastore CA, Llano PMPD, Castro DP, Santos FD. Capacidade funcional para atividades da vida diária de idosos da Estratégia de Saúde da Família da zona rural. Ciên Saúde Coletiva. 2016;21(11):3545- 55. http://dx.doi.org/10.1590/1413-812320152111.22182015
10. Nunes JD, Saes MDO, Nunes BP, Siqueira FCV, Soares DC, Fassa MGE, et al. Indicadores de incapacidade funcional e fatores associados em idosos: estudo de base populacional em Bagé, Rio Grande do Sul. Epidemiol Serv Saúde. 2017;26(2):295-304. http://dx.doi.org/10.5123/s1679-49742017000200007
11. Figueiredo CS, Assis MG, Silva SL, Dias RC, Mancini MC. Functional and cognitive changes in community-dwelling elderly: Longitudinal study. Braz J Phys Ther. 2013;17(3):297-306. http://dx.doi.org/10.1590/S1413-35552012005000094
12. Folstein MF, Folstein SE, McHugh PR. “Mini-mental state”: a practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975;12(3):189-98. https://doi.org/10.1016/0022-3956(75)90026-6
13. d’Orsi E, Xavier AJ, Ramos LR. Trabalho, suporte social e lazer protegem idosos da perda funcional: Estudo Epidoso. Rev Saúde Pública. 2011;45(4):685-692. http://dx.doi.org/10.1590/S0034-89102011000400007
14. Santos AAD, Pavarini SCI. Functionality of elderly people with cognitive impairments in different contexts of social vulnerability. Acta Paul Enferm. 2011;24(4):520-6. http://dx.doi.org/10.1590/S0103-21002011000400012
15. Lima-Costa MF, Facchini LA, Matos DL, Macinko J. Changes in ten years of social inequalities in health among elderly Brazilians (1998-2008). Rev Saúde Pública. 2012;46(Supl. 1):100-7. http://dx.doi.org/10.1590/S0034-89102012005000059
16. Chen CM, Chang WC, Lan TY. Identifying factors associated with changes in physical functioning in an older population. Geriatr Gerontol Int. 2015;15(2):156-64. https://doi.org/10.1111/ggi.12243
17. Escobar-Bravo MÁ, Puga-González D, Martín-Baranera M. Protective effects of social networks on disability among older adults in Spain. Arch Gerontol Geriatr. 2012;54(1):109-16. https://doi.org/10.1016/j.archger.2011.01.008
18. Marshall GA, Rentz DM, Frey MT, Locascio JJ, Johnson KA, Sperling RA. Executive function and instrumental activities of daily living in mild cognitive impairment and Alzheimer’s disease. Alzheimers Dement. 2011;7(3):300-8. https://doi.org/10.1016/j.jalz.2010.04.005
19. Ji J, Zhang L, Zhang Q, Yin R, Fu T, Li L, et al. Functional disability associated with disease and quality-of-life parameters in Chinese patients with rheumatoid arthritis. Health and quality of life outcomes. 2017;15(1):89. https://doi.org/10.1186/s12955-017-0659-z
20. Santos GMGC, Silva AMR, Carvalho WO, Rech CR, Loch MR. Barreiras percebidas para o consumo de frutas e de verduras ou legumes em adultos brasileiros. Ciên Saúde Coletiva. 2019; 24(7):2461-70. http://dx.doi.org/10.1590/1413-81232018247.19992017
21. Soares LDDA, Campos FDAC, Araújo MDGRD, Falcão APST, Lima BRDA, Siqueira DF, et al. Análise do desempenho motor associado ao estado nutricional de idosos cadastrados no Programa Saúde da Família, no município de Vitória de Santo Antão-PE. Ciên Saúde Coletiva. 2012;17(5):1297-304. http://dx.doi.org/10.1590/S1413-81232012000500023
22. Hardman RJ, Kennedy G, Macpherson H, Scholey AB, Pipingas A. Adherence to a Mediterranean-style diet and effects on cognition in adults: a qualitative evaluation and systematic review of longitudinal and prospective trials. Front Nutr. 2016;3:22. https://doi.org/10.3389/fnut.2016.00022
23. Kalyani RR, Saudek CD, Brancati FL, Selvin E. Association of diabetes, comorbidities, and hemoglobin A1c with functional disability in older adults: results from the National Health and Nutrition Examination Survey (NHANES), 1999-2006. Diabetes care. 2010;33(5):1055-60. https://doi.org/10.2337/dc09-1597
24. Ryan JP, Fine DF, Rosano C. Type 2 diabetes and cognitive impairment: contributions from neuroimaging. J Geriatr Psychiatry Neurol. 2014;27(1):47-55. https://doi.org/10.1177/0891988713516543
25. Aguiar ACDSA, Martins LA, Reis LA, Barbosa TSM, Camargo CL, Alves MA. Alterações ocorridas no cotidiano de pessoas acometidas pela úlcera venosa: contribuições à Enfermagem. Rev Cubana Enferm. 2015;30(3):1-10.
26. Atlas A, Grimmer K, Kennedy K. Early indications that low mental quality of life scores in recently unwell older people predict downstream functional decline. Clin Interv Aging. 2015;10:703-12. https://doi.org/10.2147/CIA.S74613
27. Connolly D, Garvey J, McKee G. Factors associated with ADL/IADL disability in community dwelling older adults in the Irish longitudinal study on ageing (TILDA). Disabil Rehabil. 2017;39(8):809-16. https://doi.org/10.3109/09638288.2016.1161848
28. Paula JJD, Malloy-Diniz LF. Executive functions as predictors of functional performance in mild Alzheimer’s dementia and mild cognitive impairment elderly. Estud Psicol. 2013;18(1):117-24. https://psycnet.apa.org/doi/10.1590/S1413-294X2013000100019
29. Giebel CM, Challis D, Montaldi D. Understanding the cognitive underpinnings of functional impairments in early dementia: a review. Aging Ment Health. 2015;19(10):859-75. https://doi.org/10.1080/13 607863.2014.1003282
30. Davidson KW, McGinn T. Screening for Social Determinants of Health: The Known and Unknown. JAMA. 2019;322(11):1037-8. https://doi.org/10.1001/jama.2019.10915
August 30 2019.
Accepted em September 19 2019.