Associations between Socioeconomic Status and Adverse Childhood Experiences with Multidimensional Healthy Aging: Findings from the ELSI-Brazil

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Leist This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7879466/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 30 Apr, 2026 Read the published version in BMC Public Health → Version 1 posted 12 You are reading this latest preprint version Abstract Background By 2050, the global population aged 65 years and older is projected to double, reaching 1.5 billion, with the most rapid growth occurring in Latin America and the Caribbean. In Brazil, this demographic shift is advancing quickly within a context marked by profound social inequalities and insufficient preparation to address the challenges of an aging society. For this reason, this study aimed to estimate the prevalence of healthy aging in a representative sample of the Brazilian population and explore the role of socioeconomic conditions and adverse childhood experiences. Methods We analyzed data from 9,908 participants aged 50 and older from the 2019–2021 follow-up of the Brazilian Longitudinal Study of Aging (ELSI-Brazil). Participants were classified into healthy and less healthy aging based on the World Health Organization’s multidimensional definition of healthy aging. Logistic regression models were employed to identify sociodemographic and early-life predictors of healthy aging. Results Only 19.69% of the sample met the employed criteria for healthy aging. Women, older individuals, those self-identifying as mixed race (compared to those self-identifying as White), participants with no schooling or fewer than four years of education, and widowed individuals were more likely to not meet the criteria for healthy aging than their counterparts. Logistic regressions revealed that men are more likely to show healthy aging, as well as younger respondents, those with five years or more of education, and participants receiving two or more minimum wages. With respect to childhood experiences, those reporting poor health and who reported famine during childhood were less likely to meet the criteria for healthy aging. Conclusions The findings suggest that not only socioeconomic factors but also childhood experiences contribute to disparities in healthy aging in Brazil. These results underscore the importance of implementing early-life health and nutrition programs, advancing gender equity, and improving access to education and economic resources throughout the life course to support healthier aging for future generations. Clinical trial number: not applicable healthy aging socioeconomic factors inequalities childhood experiences Background The United Nations predicts that by 2050, the global population aged 65 or older will double to 1.5 billion, with the fastest growth occurring in Latin America and the Caribbean. In Latin America, the complexities of aging are manifested in varied life expectancies across cities and countries because of different social environments ( 1 ), such as economic inequalities and access to health care, education, and others. In Brazil, the increase in the number of older people is occurring rapidly, yet in a society that is not well prepared for such a transition ( 2 ). Nevertheless, it is important to mention that this demographic transformation is occurring in a country marked by profound socioeconomic inequalities, limited healthcare infrastructure ( 3 , 4 ), and historically low levels of education among older adults ( 5 ). As such, Brazil offers a valuable context in which to investigate and understand how socioeconomic status and early-life adversity shape aging trajectories. Healthy Aging: Evolving Perspectives The concept of healthy aging has evolved significantly over the last few decades, challenging traditional views that associated aging solely with losses and declines. Rowe and Kahn’s model of usual and successful aging was introduced three decades ago, with successful aging being characterized by three factors: a low likelihood of illness and disability related to diseases, strong cognitive and physical capabilities, and active participation in social life ( 6 , 7 ). Nevertheless, an important criticism from the World Health Organization ( 8 ) regarding Rowe and Kahn’s model is that identifying individuals on the basis of only health, that is, the absence of diseases, is extremely problematic, since some diseases may be treated and not limit individual capacities. Therefore, the WHO ( 8 ) defined healthy aging as the process of cultivating and sustaining the ability to function effectively, ensuring a sense of well-being during old age. In accordance with the WHO, recent studies have further broadened the understanding of healthy aging, recognizing it as a complex construct with multiple dimensions ( 9 – 11 ). In a recent umbrella review, the authors showed that studies related to healthy aging, which are mostly carried out in developed countries, used heterogeneous conceptualization and operationalization. In addition, they highlight the importance of assuming context-specific conceptual guidance to fill gaps in the operationalization of healthy aging, notably with respect to gender, disabilities, and ethnicity ( 9 ). According to the WHO ( 8 ), a multidimensional model must consider intrinsic capacity, social and political environments, and the interaction of older adults with their surroundings. This multidimensional perspective aligns with evolving concepts of healthy aging and highlights the interplay of individual, social, and environmental factors in the aging process‎. Building on this approach, recent systematic review studies have proposed operational models that reflect the complexity of aging ( 12 ). For example, Rivadeneira et al. ( 11 ) proposed a multidimensional framework that includes three components: ( 1 ) intrinsic capacity, comprising geriatric syndromes, physiological health, risk factors, i.e., alcohol consumption, smoking, lack of physical activity, cognitive functioning, well-being, i.e., depression, and physical capacity; ( 2 ) social and political environments, such as participation in the community; and ( 3 ) interactions with the environment, including assistance offered by them to others. This model was developed and tested on nationally representative data from Ecuador. The WHO defines healthy aging as intrinsic capacity combined with functional ability in the given environment of an individual, which Rivadaneira et al. ( 11 ) combined into one multidimensional score to indicate the presence or absence of healthy aging. Their results revealed that women and individuals with lower incomes were less likely to meet the criteria for healthy aging. Owing to similar levels of socioeconomic inequalities and similar social and economic profiles, this model is suitable for application in other countries, such as Brazil. Healthy aging and inequalities in different health outcomes in Latin America Despite the growing interest in healthy aging, research employing a multidimensional framework remains scarce in Latin America. While multidimensional healthy aging as a concept has rarely been used in the Latin American context, with exceptions such as Rivadeneira et al.( 11 ), several studies point to low prevalence and socioeconomic gradients in older-age health outcomes in Latin America and the Caribbean (LAC) ( 13 , 14 ). A recent systematic review exploring gradients and inequalities in dementia prevalence in 15 LAC countries on the basis of age, sex, rurality, and education revealed an overall pooled prevalence of all-cause dementia of 10.66%. Women, individuals with lower educational levels, and rural residents were identified as particularly vulnerable groups with higher dementia prevalence. The study emphasized the need for targeted public health efforts to address the unequal burden of dementia in these populations ( 15 ). Furthermore, a recent study ( 16 ) comprising data from a Brazilian representative sample revealed a significant increase in health risk factors among the older adult population from 2000 to 2015, specifically, overweight/obesity, as well as diabetes and hypertension. The review by Nitrini et al. ( 17 ) stressed the modifiable nature of factors contributing to dementia, offering hope for preventive actions, and highlighted the importance of education and socioeconomic status. Educational attainment emerged as a positive factor, aligning with previous studies highlighting education's role in accessing health services and improving overall quality of life. Conversely, economic status plays a pivotal role, with those in the worst economic situation being less likely to experience healthy aging, underscoring the importance of addressing socioeconomic inequalities ( 11 ). Likewise, living as a rural resident was found to be positively associated with a higher level of dementia, especially among women ( 18 ). Notably, childhood adversity, including hunger and poor access to education, has also been linked to worse aging outcomes ( 19 ). Fair or poor childhood health is also considered an adverse childhood experience, but there is little research on how this and other adverse childhood experiences impact healthy aging over the long term in contexts such as Brazil. Gender, Social Roles, and the Aging Process Gender represents another important, yet often underexplored, dimension in aging research in Latin America, particularly given that many LAC countries are characterized by high levels of gender inequality. Importantly, studies have shown that gender inequalities might shape the aging experience through social roles, cultural expectations, and structural disadvantages across the whole life course ( 20 ). In Brazil, older women born in the 1940s and 1950s faced profound constraints on formal education, limited formal labor market participation ( 21 ), and restricted financial autonomy ( 22 ) due to prevailing patriarchal norms. In addition, labor policies and cultural messages have reinforced the role of women as caregivers and homemakers ( 23 , 24 ). As a consequence, these gendered social roles have had lasting implications, with women predominantly in low-paid, insecure work or unpaid domestic labor, entering retirement with insufficient pension benefits and financial reserves ( 25 , 26 ). Nevertheless, the biomedical literature further highlights gender differences in morbidity, showing women's greater susceptibility to various health issues, even when reproductive conditions are excluded ( 27 ). This disadvantage persists up to older age, with men maintaining better functioning and lower disability rates than women do. Gender differences also manifest in the experience of specific diseases and psychological well-being, with women reporting higher levels of anxiety and stress ( 27 ) and higher levels of depression and loneliness ( 28 ). The association between age and health-related quality of life remains debated, with complex intersections of race, ethnicity, and gender influencing these dynamics ( 29 ). Regarding early life adversity, greater disparity in educational opportunities during schooling was consistently linked to diminished cognitive performance scores in older individuals, particularly among women, in a European sample ( 30 ). Moreover, adverse childhood experiences, such as famine, can lead to chronic diseases later in life; for instance, Félix-Beltrán and Seixas ( 19 ) reported that childhood hunger was associated with diabetes and osteoporosis later in life on the basis of ELSI-Brazil data. However, they did not explore other childhood experiences on a multidimensional model of healthy aging. Since adversities can influence biological aging, it is crucial to understand how these early experiences contribute to health disparities. Early life adversity together with gender stereotypes across the life course might lead to cumulative social and biological disadvantages that unfold over the life course. Importantly, these gendered pathways intersect with socioeconomic status and childhood experiences in unique ways in high-inequality contexts such as Brazil ( 20 ). From the social environment influencing mortality in Latin American cities to the unequal burden of dementia based on education and gender, understanding the gender differences in healthy aging requires a multidimensional and context-sensitive approach. Additionally, recognizing the role of socio-economic status and early life experiences in shaping the aging trajectory further underscores the need for holistic interventions to promote healthy aging and reduce disparities. Current Research Our objective was to explore the prevalence of healthy aging via a multidimensional framework in a nationally representative sample of older Brazilian adults. Furthermore, we also aim to examine the role of environmental elements such as socioeconomic status, education, and childhood experiences. Finally, we also extend our investigation by incorporating the sex/gender dimension, enriching our understanding of the interplay between these factors and healthy aging. Methods Participants In this study, we used data from the population-representative Brazilian Longitudinal Study of Aging (ELSI-Brazil) ( 31 ). ELSI-Brazil has been carried out with adults aged 50 years and older residing in diverse communities across different regions of Brazil. The first wave of data collection occurred from 2015–2016, and the second wave was conducted between 2019 and 2021. For the present analysis, we used data from the most recent wave to estimate the current prevalence of healthy aging. This sample consisted of 9,949 adults aged 50 years or more, of whom 9,908 participants (M age = 66; SD = 10,06; max. = 109 years) had complete information on the relevant variables and were included in the analyses. The study sampling was conducted by conglomerates, and Brazilian Institute of Geography and Statistics (IBGE) data were used for stratification and selection of regions. To guarantee a comprehensive representation of urban and rural areas across municipalities of varying sizes, ELSI-Brazil employed a multistage sampling approach. This method involves stratifying primary sampling units (municipalities) and further selection stages, including census tracts and households. For more details regarding the sampling methodology, see ( 31 ). In-person assessments were conducted in Portuguese, the official language of Brazil, by trained interviewers. Measures Operationalization of Healthy Aging According to the WHO ( 8 ), healthy aging is a multidimensional concept that includes an individual’s intrinsic capacity and functional ability to address given environmental factors. Given that there is no clear definition of which variables should comprise healthy aging components, we adapted the multidimensional model proposed by Rivadeneira et al. ( 11 ) on the basis of the variables available in the ELSI-Brazil database (see Table 01 ). The composite score of intrinsic capacity included domains such as physical health, geriatric syndromes, physical capacity, cognitive ability, psychological well-being, and environmental aspects, including social participation. Following the operationalization by Rivadeneira et al. ( 11 ), individuals were classified into a healthy aging group or a less healthy aging group , as described in Table 1 . We summed the scores for each domain and then recoded the results into a dichotomous variable. The specific variables used for each component are described in detail below. Physical health To be considered healthy, participants were assessed on the basis of the absence of diabetes, hypertension, cardiovascular disease, stroke, lung disease, vision, and hearing problems or whether participants with the diagnosis received treatment, i.e., if the disease was managed. However, owing to limitations in the dataset, we were unable to determine whether participants were receiving treatment or had limitations caused by arthritis, rheumatism, osteoporosis, renal insufficiency, Parkinson's disease, and Alzheimer's disease. For this reason, participants who reported any of these conditions were included in the less healthy aging group. Physical health conditions were self-reported by the following question: “ Has a doctor or nurse ever told you that you had...? ” Geriatric syndrome This factor comprises three variables: 1) whether participants had polypharmacy (according to the World Health Organization, polypharmacy is the concomitant and routine use of 4 or more medications with or without a prescription); 2) whether participants self-reported urinary or fecal incontinence; and 3) whether the respondent self-reported a fall in the last 12 months. Functional Capacity Functional capacity was assessed by self-perceived inability to perform basic activities of daily living (BADL) via the Katz Index ( 32 ), adapted for Brazil by Lino et al. ( 33 ). Subjects who did not need help with any of the activities assessed were considered independent. Disabilities related to instrumental activities of daily living (IADL) were assessed via the Lawton Scale ( 34 ), adapted in Brazil by Lopes and Virtuoso-Júnior ( 35 ). The subjects were considered independent and had no difficulty except with heavy domestic activities. Psychological well-being To create the well-being variable, two scales were considered: 1) Life satisfaction, which is the following response instruction from the individual ELSI-Brazil questionnaire, which has, as response options, increasing measures from 1 to 10 in the form of a MacArthur Scale ladder: "Please think about your level of satisfaction with life and point to the corresponding rung". Answers of 6 or above were considered ‘high’ satisfaction, and answers below or equal to 5 were considered ‘low’ satisfaction. Depressive symptoms were assessed via the CES-D8 scale (an eight-item version of the Center for Epidemiological Studies Depression Scale). The affirmative answers to the items describing depressive symptoms were added. The cutoff point for categorizing depression was ≥ 4, which was based on the criteria adopted by Sandy Junior ( 36 ). Cognitive functioning Cognitive functioning was measured by four tasks as follows: 1) In the first task, participants were required to recall a list of 10 words immediately after hearing them. 2) The second task involved recalling the same set of 10 words after a 5-minute delay, following the completion of other cognitive tests. In both tasks, participants received one point for each correct answer, with a maximum score of 10 points. 3) The third assessment evaluated participants' awareness of the date, including the day, month, and year, as well as the day of the week. Each accurate response earned one point, with a total possible score of four points. 4) The fourth measure, focusing on language and processing speed, required participants to recall the names of the animals within a 1-minute timeframe. The participants received one point for each correctly remembered animal name. The four cognitive measures were z-standardized, averaged and restandardized to calculate a global z score with a mean of zero and a standard deviation of 1. Cognitive impairment was determined for a global z score lower than or equal to -1.5, which is equal to -1.5 SD from the overall mean. Environment The environment comprises many factors, including the extrinsic world that forms the context of an individual’s life. These include the microlevel (e.g., home) to the macrolevel (e.g., community and broader society). In this study, we included social participation and other activities (i.e., social, productive, and entertainment activities), as assessed by the Advanced Activities of Daily Living (AADL, ( 37 )). For the present study, the total number of activities that each participant reported doing from a total of 13 activities in the scale was calculated. The participants were classified into two groups according to their total score: more active, with greater participation in AADL, or less active. Those who performed four or more activities were considered more active, and those who reported performing three or fewer activities were considered less active. Table 1 Criteria for Defining Healthy Aging Dimension of healthy aging Domain Presence of Healthy Aging Absence of healthy aging Intrinsic capacity Physical health Absence of the following diagnoses or the presence of diseases that are managed (treated) and do not limit the functioning of the participant: Diabetes, hypertension, cardiovascular disease, stroke, lung disease, vision and hearing problems. arthritis, rheumatism, osteoporosis, renal insufficiency, Parkinson's, and Alzheimer's. Diagnoses with at least one of the mentioned diseases that are not controlled or are limiting the functioning of the participant. Geriatric syndromes Absence of polypharmacy, urinary and fecal incontinence, and no falls syndrome Presence of the cited factors Functional capacity Absence of disability according to the Instrumental activities of daily living and Basic Activities of Daily Living Physical activity Presence of disabilities according to the cited tests. Cognitive ability Absence of cognitive impairment assessed by global Z score. Presence of cognitive impairment, values of Z scores < = -1.5. Psychological well-being Global satisfaction with life and Absence of depression by using the Center for Epidemiological Studies Depression Scale Presence of low satisfaction or/and symptoms of depression. Environment Social Participation Advanced Activities of Daily Living. Involvement in less than three Advanced Activities of Daily Living Note: Variables adapted from Rivadeneira et al. (2021) Covariates (Independent variables) Socioeconomic characteristics included gender/sex (women/men), age groups (50–59 years, 60–69 years, 70–79 years, and 80 years of age or older), rurality (urban/rural), race (white, black, mixed), education levels (no school, 1–4 years, 5–8 years, 9–12 years, and 12 years or more), marital status (single, married/stable union, divorced/separated, widowed), and income calculated as multiples of the minimum wage (wage 4). The individual income was computed on the basis of the national minimum wage (NMW) applicable in the year of the interview. Childhood experiences included three variables: health in childhood (excellent/very good, good, fair, and poor); hunger during childhood (no/yes); and living in rural areas until the age of 15 (no/yes). Race categories were determined on the basis of participants' self-identification from a list of options aligning with the official classification of self-reported skin color in Brazil (Silva, 1997): white, brown or mixed, black, yellow, and indigenous. However, in this study, we included only participants who self-reported as white, black, or mixed since there were not enough cases in the other categories to fit the model. Statistical analysis First, we carried out descriptive analyses to observe the percentage distributions of all the study variables. Rao Scott's chi-square tests were subsequently used to assess potential differences in socioeconomic and childhood experiences between the healthy and less healthy aging groups. Second, we ran logistic regression analyses to assess which independent variables influence healthy aging, which was treated as a dichotomous dependent variable. The reference group was the healthy aging group. In addition, we included sampling weights in all analyses to adjust the complex sampling design of the ELSI-Brazil. STATA (release 17, Stata Corp.) software was used for the statistical analyses. Results As shown in Table 2 , 59.33% of the study participants were women. In terms of age, 65.24% were between 50 and 69 years old. Most participants lived in urban regions (83.8%), had 1–4 years of education (40.51%), and had up to 2 wages as income (57.03%). For the prevalence of healthy aging according to the adapted criteria, only 19.69% of the respondents were categorized as healthy aging, whereas 80.31% were categorized as less healthy aging. Table 2 Socioeconomic and childhood characteristics of the study sample (N = 9,908). Variables Number of Participants % Gender/Sex Women 5,819 59.33 Men 3,989 40.67 Age Groups 50–59 years 2,984 30.42 60–69 years 3,415 34.82 70–79 years 2,252 22.96 80 years or more 1,157 11.80 Rurality Urban 8,219 83.80 Rural 1,589 16.20 Race White 4,587 46.77 Black 1,052 10.73 Mixed 4,169 42.51 Education no schooling 1,552 16.02 1–4 years 3,924 40.51 5–8 years 1,854 19.14 9–12 years 1,705 17.6 12 years or more 651 6.72 Marital Status Single 1,195 12.18 Married/Stable union 5,212 53.14 Divorced/Separated 1,229 12.53 Widowed 2,172 22.15 Income Wage 4 1,405 15.12 Brazilian Regions North 709 7.23 Northeast 2,659 27.11 Southeast 4,060 41.39 South 1,331 13.57 Midwest 1,049 10.70 Childhood experiences Health in childhood Excellent/Very good 2,236 22.96 Good 5,758 59.12 Fair 1,240 12.73 Poor 506 5.20 Hunger during childhood No 7,293 75.41 Yes 2,378 24.59 Lived in rural areas until the age of 15 No 4,200 42.82 Yes 5,577 56.86 Healthy classification Healthy 1,931 19,69 Less healthy 7,877 80,31 Table 2 Table 3 shows that there was a greater prevalence of healthy aging among men (55.1%) than among women (42.8%). Participants who did not meet the criteria for healthy aging were more likely to be older and have no schooling or up to four years of education. Moreover, participants reporting being widowed were more likely to be less healthy. Those receiving more than three wages a month were more likely to meet the criteria for healthy aging. With respect to childhood experiences, those who self-reported poor health in childhood and who experienced hunger during childhood were more likely to be allocated to the less healthy aging group. Table 3 Weighted Analyses of Socioeconomic and Childhood Characteristics across Aging Health Categories. Variables Healthy Less healthy p Gender/Sex Women 44.9 (41.9–47.9) 57.2 (55.7–58.7) < 0 .001* Men 55.1 (52.1–58.1) 42.8 (41.3–44.3) Age Groups 50–59 years 58.4 (55.1–61.5) 44.2 (42.1–46.2) < 0 .001* 60–69 years 28.6 (26.7–30.5) 29.2 (28.1–30.4) 70–79 years 10.7 (9.3–12.2) 17.6 (16.5–18.6) 80 years or more 2.4 (1.7–3.2) 9.0 (8.3–9.8) Rurality Urban 87.9 (79.8–93.0) 83.4 (75.7–89.0) 0.02* Rural 12.1(7.0–20.2) 16.6(11.0–24.3) Race White 51.2 (46.6–55.9) 45.3 (40.4–50.2) < 0 .001* Black 8.8(6.9–11.2) 11.5(9.7–13.6) Mixed 39.9(36.0–44.0) 43.2 (39.2–47.4) Education no school 6.4(5.0–8.2) 14.4 (10.4–19.8) < 0 .001* 1–4 years 29.5(23.6–36.3) 41.1 (37.6–44.7) 5–8 years 22.7(19.5–26.4) 19.9 (17.1–23.0) 9–12 years 29.6 (25.9–33.7) 18.5 (15.0–22.5) 12 years or more 11.6 (9.7–13.9) 6.1(4.4–8.3) Marital Status Single 12.1(10.4–14.1) 12.8 (11.2–14.7) < 0 .001* Married/Stable union 66.6 (62.7–70.2) 59.0 (56.5–61.4) Divorced/Separated 11.7 (9.2–14.7) 10.9 (9.7–12.3) Widowed 9.7(7.8–11.9) 17.3 (16.0–18.6) Income Wage < 1 13.6 (11.1–16.5) 20.2 (17.4–23.3) 4 27.3 (24.0–30.8) 14.8 (12.3–17.7) Childhood experiences Health in childhood Excellent/Very good 26.7 (21.4–32.8) 23.1 (20.8–25.6) < 0 .001* Good 59.1 (54.0–64.0) 56.7 (54.9–58.6) Fair 11.6 (10.2–13.2) 13.9 (12.8–15.1) Poor 2.6 (1.8–3.6) 6.3 (5.6–7.0) Hunger during childhood No 80.6 (76.9–83.9) 73.7 (71.0–76.3) < 0.001* Yes 19.4(16.1–23.1) 26.3 (23.7–29.0) Lived in rural areas until the age of 15 No 50.0 (37.0–63.1) 43.1 (33.3–53.4) 0.007* Yes 49.9 (36.9–62.9) 56.7 (46.3–66.6) Note: Weighted P values were determined via the Rao‒Scott test. Differences among groups were confirmed by nonoverlapping confidence intervals. * P < .05 Rao-Scott analyses were carried out whether the experience of hunger during childhood was distributed differently across Brazilian regions. Participants living in the North (31.4%; I -23.7-40.3) and Northeast (33.4%; CI -29.1-38.0) regions were more likely to report famine during childhood compared to participants with residence in the Southeast of the country (20.4%; CI -18.0-23.0), p < .001. Table 3 Table 4 displays the results of the logistic regression analyses with healthy aging as a dependent variable that showed that men were more likely to belong to the healthy aging group than women. Furthermore, older participants, especially those aged 80 or more, were more likely to be in the less healthy aging group. Older adults having five years or more of education were more likely to be healthily aging. Regarding childhood experiences, we detected that respondents who self-reported fair or poor health during childhood and suffered from hunger were less likely to meet the criteria for healthy aging. Table 4 Associations between Healthy Aging, Socioeconomic Status, and Childhood Factors Variables Odds Ratio 95% CI p Gender/Sex Women (Reference) Men 0.63 0.56–0.71 < 0.001* Age Groups 50–59 years (Reference) 60–69 years 1.29 1.11–1.51 0.002* 70–79 years 1.92 1.62–2.26 < 0.001* 80 years or more 4.08 2.91–5.71 < 0.001* Rurality Urban (Reference) Rural 1.08 0.77–1.47 0.68 Race White (Reference) Black 1.19 0.93–1.52 0.15 Mixed 1.12 0.97–1.29 0.12 Education no school (Reference) 1–4 years 0.85 0.55–1.31 0.45 5–8 years 0.62 0.43–0.88 0.008* 9–12 years 0.52 0.33–0.82 0.006* 12 years or more 0.45 0.25–0.80 0.008* Marital Status Single (Reference) Married/Stable union 0.91 0.75–1.08 0.35 Divorced/Separated 0.84 0.53–1.34 0.45 Widowed 0.94 0.77–1.13 0.50 Income Wage < 1 (reference) 1–2 wages 0.98 0.78–1.23 0.85 2–3 wages 0.69 0.57–0.83 < 0.001* 3–4 wages 0.63 0.48–0.82 4 0.53 0.43–0.66 < 0.001* Childhood experiences Health in childhood Excellent/Very good (Reference) Good 0.92 0.78–1.09 0.34 Fair 1.31 1.01–1.69 0.04* Poor 2.35 1.66–3.33 < 0.001* Hunger during childhood No (Reference) Yes 1.25 1.07–1.46 0.007* Lived in rural areas until the age of 15 No (Reference) Yes 0.89 0.77–1.03 0.12 * P < .05 Table 4 Discussion This study investigated the prevalence of healthy aging in a nationally representative sample of older adults in Brazil and explored the effects of socioeconomic conditions and childhood experiences in explaining the health of older adults. With a more comprehensive and thus less narrow view of healthy aging, considering multiple dimensions and whether diseases were treated or controlled, our findings suggest that more than four-fifths (80.3%) of our sample did not meet the criteria for healthy aging, suggesting that a substantial proportion of older Brazilian people must cope with many health challenges as they age. Our findings on a Brazilian population-representative sample contrast with the findings of Rivadeneira et al. ( 11 ) for a sample from Ecuador, roughly half of which were found to be aging healthily (53.15% of the sample), even though their sample was aged 65 years or older, in contrast with our data from ELSI-Brazil, which comprised adults aged 50 and older. A more favorable socioeconomic profile of the Ecuadorian sample may have contributed to the differences in prevalence estimates. Furthermore, period effects may be partly responsible for the differences in findings; the data of the SABE Ecuador study of Rivadeneira et al., 2021 were collected in 2010, whereas the present study used 2019–2021 data from ELSI-Brazil. Similarly, earlier research revealed sharp increases in health risk factors such as obesity in Brazil over the period 2000–2015 ( 16 ). Finally, differences in socioeconomic conditions and healthcare access may have played a role, as Brazil has historically exhibited greater inequality and regional disparities ( 21 ). On the basis of our data, older individuals with four years of formal education or less and household incomes lower than two wages are much less likely to meet the criteria for healthy aging, suggesting that these groups are particularly vulnerable. These findings align with prior research in Latin America and globally, which suggests that socioeconomic disadvantages accumulate across the life course and manifest in worse health outcomes in old age ( 14 – 16 , 38 ), similar to the findings of other studies in other regions of the world ( 39 , 40 ). The strong links between formal education and healthy aging are suggested to come from increased exposure to various risk factors; lower resources in terms of money, knowledge, prestige, power, and beneficial social connections ( 41 , 42 ); higher stress levels; other biological mechanisms of ‘embodiment’ ( 43 ); and possibly limited access to (preventive) healthcare services starting from a younger age. As discussed by previous studies ( 15 , 20 ), gender inequality might lead to pronounced sex/gender differences in healthy aging, as men tend to be highly educated, perform cognitively demanding jobs, and are offered more strategies and opportunities to cope with the adverse external environment. Additionally, men and women who were born in the 1940s and 1950s played very different social roles, which deferentially impacted their mental health during their lifespan, with women being more likely to experience negative outcomes in mental health ( 28 ). Women also live longer, meaning that they spend more time coping with stressful life transitions, such as losing a spouse, caring for other people, and living with their own chronic illnesses ( 44 ). Moreover, our results reinforce the impact of famine during childhood on healthy aging shown by Félix-Beltrán and Seixas ( 19 ). Self-reported lower health during childhood is associated with less healthy aging, given that a lack of nutrients during childhood could lead to epigenetic changes leading to metabolic dysfunction. These outcomes may reflect the long-term biological consequences of early nutritional deprivation and stress, including epigenetic changes linked to chronic disease later in life ( 45 ). Moreover, such early-life adversity was more commonly reported by participants from Brazil’s North and Northeast Regions, areas historically marked by higher poverty levels and food insecurity, underscoring the geographical dimension of inequality in aging trajectories. Interestingly, no differences between groups were observed in urban versus rural residences. This suggests that environmental factors associated with locality, such as pollution or infrastructure, may be less predictive of healthy aging than broader structural inequalities, such as income, education, and life-course exposures. Future research could explore more nuanced aspects of the built and social environment, such as neighborhood safety, healthcare accessibility, and pollution exposure. Strengths and limitations A major strength of this study was the operationalization of a multidimensional framework to assess healthy aging, which is consistent with recent recommendations from the WHO ( 8 ) and prior empirical work ( 11 ) and provides a more holistic view of the intrinsic capacity of older adults in Brazil. Another strength is the use of recent nationally representative data from ELSI-Brazil, with a multistage sampling process and the use of weights to arrive at population-representative estimates. However, limitations should be acknowledged. First, owing to differences in data collection, we had to slightly adapt the operationalization of intrinsic capacity used by Rivadeneira et al. ( 11 ). While some dimensions of healthy aging are more standardized, e.g., the classification of polypharmacy or the presence of chronic conditions, other dimensions are based on conventions that are sometimes less stringently used in the literature, such as the classification as cognitively impaired, with a score of 1.5 SD below the sample mean. The prevalence of healthy aging consequently is sensitive to changes in the operationalization of the different dimensions, including possible underreporting of chronic conditions, due to a lack of diagnosis, which may have led to an overestimation of healthy aging. Additionally, the domains constituting healthy aging may have differential importance, and different operationalizations exist in the literature; however, other studies have used country-specific operationalizations of intrinsic capacity as well ( 46 ), and we defined the concept as congruent as possible with existing studies in comparable contexts ( 9 ). Second, not all determinants of healthy aging found in earlier research were available in the data used from the ELSI-Brazil. Third, our estimates of the socioeconomic determinants of healthy aging may be impacted by premature mortality, which is still rather high in the Brazilian context ( 47 ). This selective attrition may have biased our estimates toward the null. Policy implications Gender-responsive policies are essential, as older women in Brazil face a double burden of socioeconomic disadvantage and greater longevity, leading to long periods of managing chronic illness while still fulfilling important family functions such as caregiving responsibilities. In this sense, some policy recommendations based on our findings might include macrolevel interventions that prioritize initiatives to promote access to education for future generations and support those in less favorable economic situations, optimizing the social and psychological environment, fostering a supportive social atmosphere through media campaigns, and promoting an appropriate understanding of family development laws ( 48 ). Moreover, community care for older people is crucial, especially among women, who represent the larger proportion of older adults in Brazil, emphasizing preventive services for their physical and mental health and the establishment of an effective old-age security system ( 48 ). Encouraging the development of human resources among older people involves promoting their participation in social activities, amplifying their network of social support, and leveraging their knowledge in community initiatives ( 48 ). In addition, childhood health and nutrition must be core components of aging policy, given the long-term impact of early adversity on later-life outcomes. Investments in maternal and child health, nutrition programs, and poverty alleviation can have intergenerational effects on healthy aging ( 20 ). On a micro level, mastering skills to understand the psychological functioning of older women is crucial, emphasizing respectful communication and active listening to promote happiness and confidence ( 48 ). Additionally, addressing the prevalence of dementia is imperative, considering its impact on dependence among older adults and the substantial medical and care costs involved ( 49 – 52 ). Finally, while this study did not directly assess loneliness or social participation, our findings still suggest that psychosocial conditions, such as widowhood and poor mental health, are important domains for policy intervention. However, the central policy message should not be about promoting social participation per se , as structural influences shape downstream conditions and opportunities for social participation. Thus, addressing the structural inequalities that shape healthy aging trajectories from birth to old age is essential. Conclusion This study operationalized healthy aging with a comprehensive and multidimensional score. A large majority (80%) of respondents in a population-representative sample of the older Brazilian population did not meet the criteria for healthy aging. Our findings highlight substantial gaps in health equity by gender, socioeconomic status, and childhood adversity across aging individuals. As Brazil continues to age, ensuring that longer lives are accompanied by better health will require integrated, equity-focused public policies. Without addressing the root causes of inequality across the life course, gains in life expectancy may not translate into gains in health and quality of life for most of the population. Abbreviations LAC - Latin America and the Caribbean WHO - World Health Organization ELSI-Brazil - Brazilian Longitudinal Study of Aging IBGE - Brazilian Institute of Geography and Statistics BADL - Basic Activities of Daily Living IADL - Disabilities related to instrumental activities of daily living CES-D8 - Center for Epidemiological Studies Depression Scale NMW - National minimum wage Declarations Ethics approval and consent to participate The ELSI-Brazil study was approved by the Ethics Committee of the Oswaldo Cruz Foundation-Minas Gerais, and the process is registered on Plataforma Brasil (CAAE: 34649814.3.0000.5091). The participants signed separate informed consent forms for each of the research procedures and authorized access to corresponding secondary databases. This study received ethics approval from the Ethics Review Committee of the ERC in November 2018. Consent for publication Not applicable Availability of data and materials The data supporting the findings of this study are available from the ELSI-Brazil repository [http://elsi.cpqrr.fiocruz.br]. Access can be obtained upon reasonable request and with permission from the ELSI-Brazil coordination. Competing interests The authors declare that they have no competing interests. Funding ELSI-Brazil was supported by the Brazilian Ministry of Health: DECIT/SCTIE (Grants: 404965/2012-1 and TED 28/2017) and COPID/DECIV/SAPS (Grants: 20836, 22566, 23700, 25560, 25552, and 27510). Moreover, part of this work was supported by the National Council for Scientific and Technological Development (CNPq; Novation Process: 229520/2013-8), and it is part of the CRISP project funded by the European Research Council (ERC; grant agreement no. 803239). Authors' contributions Research design and data analysis by FR; FR, GB, AL wrote the article and were responsible for the final content; and FR, GB, HF, and AL assisted in the interpretation of the results and critical revision of the manuscript. All the authors contributed substantially to the development of the manuscript and approved its final version. Acknowledgments The authors express their gratitude to all the researchers, interviewers, and participants of ELSI-Brazil. References Bilal U, Hessel P, Perez-Ferrer C, Michael YL, Alfaro T, Tenorio-Mucha J, et al. Life expectancy and mortality in 363 cities of Latin America. Nat Med. 2021;27(3):463–70. Kirby T. Brazil facing ageing population challenges. Lancet. 2023;402(10415):1821. de Barros RP, de Carvalho M, Franco S, de Mendonça RSP. Determinantes imediatos da queda da desigualdade de renda brasileira. 2007 Jan [cited 2025 Oct 1]; Available from: http://repositorio.ipea.gov.br/handle/11058/2161 Pimentel FG, Buchweitz C, Onocko Campos RT, Hallal PC, Massuda A, Kieling C. Realising the future: Health challenges and achievements in Brazil. SSM - Ment Health. 2023;4:100250. Travassos GF, Coelho AB, Arends-Kuenning MP. The elderly in Brazil: demographic transition, profile, and socioeconomic condition. Rev Bras Estud Popul. 2020;37:e0129. Rowe JW, Kahn RL. Human Aging: Usual and Successful. Science [Internet]. 1987 July 10 [cited 2025 Oct 1]; Available from: https://www.science.org/doi/ 10.1126/science.3299702 Rowe JW, Kahn RL. Successful Aging1. Gerontologist. 1997;37(4):433–40. WHO. World report on ageing and health [Internet]. 2015 [cited 2025 Oct 1]. Available from: https://iris.who.int/items/5db2c88f-941a-472d-ac6e-f08a7e9ae20b Menassa M, Stronks K, Khatami F, Díaz ZMR, Espinola OP, Gamba M et al. Concepts and definitions of healthy ageing: a systematic review and synthesis of theoretical models. eClinicalMedicine [Internet]. 2023 Feb 1 [cited 2025 Oct 1];56. Available from: https://www.thelancet.com/journals/eclinm/article/PIIS2589-5370(22)00550-8/fulltext Michel JP, Sadana R. Healthy Aging Concepts and Measures. J Am Med Dir Assoc. 2017 June;1(6):460–4. Rivadeneira MF, Mendieta MJ, Villavicencio J, Caicedo-Gallardo J, Buendía P. A multidimensional model of healthy ageing: proposal and evaluation of determinants based on a population survey in Ecuador. BMC Geriatr. 2021;21(1):615. Piriu AA, Bufali MV, Cappellaro G, Compagni A, Torbica A. Conceptualisation and measurement of healthy ageing: Insights from a systematic literature review. Soc Sci Med. 2025 June;1:374:117933. Castillo-Riquelme M, Yamada G, Diez Roux AV, Alfaro T, Flores-Alvarado S, Barrientos T, et al. Aging and self-reported health in 114 Latin American cities: gender and socio-economic inequalities. BMC Public Health. 2022;22(1):1499. Santamaria-Garcia H, Sainz-Ballesteros A, Hernandez H, Moguilner S, Maito M, Ochoa-Rosales C, et al. Factors associated with healthy aging in Latin American populations. Nat Med. 2023 Sept;29(9):2248–58. Ribeiro FS, Teixeira-Santos AC, Leist AK. The prevalence of mild cognitive impairment in Latin America and the Caribbean: a systematic review and meta-analysis. Aging Ment Health [Internet]. 2022 Aug 24 [cited 2025 Oct 1]; Available from: https://www.tandfonline.com/doi/abs/ 10.1080/13607863.2021.2003297 Ribeiro FS, de Oliveira Duarte YA, Santos JLF, Leist AK. Changes in prevalence of cognitive impairment and associated risk factors 2000–2015 in São Paulo, Brazil. BMC Geriatr. 2021;21(1):609. Nitrini R, Barbosa MT, Dozzi Brucki SM, Yassuda MS, Caramelli P. Current trends and challenges on dementia management and research in Latin America. J Glob Health. 2020;10(1):010362. Prina AM, Stubbs B, Veronese N, Guerra M, Kralj C, Llibre Rodriguez JJ, et al. Depression and Incidence of Frailty in Older People From Six Latin American Countries. Am J Geriatr Psychiatry Off J Am Assoc Geriatr Psychiatry. 2019;27(10):1072–9. Félix-Beltrán L, Seixas BV. Childhood hunger experiences and chronic health conditions later in life among Brazilian older adults. Rev Panam Salud Publica Pan Am J Public Health. 2021;45:e39. Ribeiro FS, Crivelli L, Leist AK. Gender inequalities as contributors to dementia in Latin America and the Caribbean: what factors are missing from research? Lancet Healthy Longev. 2023 June 1;4(6):e284–91. World Bank. Inequality and Economic Development in Brazil [Internet]. Ferreira FHG, Velez CE, Paes. De Barros R, editors. The World Bank; 2004 [cited 2025 Oct 1]. (Country Studies). Available from: https://documents.worldbank.org/en/publication/documents-reports/documentdetail/456611468744062519/Inequality-and-economic-development-in-Brazil Gacitua-Mario E, Woolcock M, editors. Social Exclusion and Mobility in Brazil [Internet]. The World Bank; 2008 [cited 2025 Oct 1]. Available from: https://documents.worldbank.org/en/publication/documents-reports/documentdetail/551501468227638533/social-exclusion-and-mobility-in-brazil Berquó E. Considerações sobre o envelhecimento da população no Brasil. In: Velhice e Sociedade. Papirus; 1999. Nicodemo D, Godoi MP. Youth in the 1960’s-70’s and elderly: case study on feminization and rights of elderly women. Rev Ciênc Em Ext. 2010;6(1):40–53. OECD. Towards Improved Retirement Savings Outcomes for Women [Internet]. 2021 Mar [cited 2025 Oct 1]. Available from: https://www.oecd.org/en/publications/towards-improved-retirement-savings-outcomes-for-women_f7b48808-en/full-report.html Garnick D. Gender Retirement Gap [Internet]., Rochester NY. Social Science Research Network; 2016 [cited 2025 Oct 1]. Available from: https://papers.ssrn.com/abstract=2888911 Carmel S. Health and Well-Being in Late Life: Gender Differences Worldwide. Front Med [Internet]. 2019 Oct 10 [cited 2025 Oct 1];6. Available from: https://www.frontiersin.org/journals/medicine/articles/10.3389/fmed .2019.00218/full. Ferreira HG. Gender Differences in Mental Health and Beliefs about Covid-19 among Elderly Internet Users. Paid Ribeirão Preto. 2021;31:e3110. Lee KH, Xu H, Wu B. Gender differences in quality of life among community-dwelling older adults in low- and middle-income countries: results from the Study on global AGEing and adult health (SAGE). BMC Public Health. 2020;20(1):114. Leist AK, Bar-Haim E, Chauvel L. Inequality of educational opportunity at time of schooling predicts cognitive functioning in later adulthood. SSM - Popul Health. 2021 Sept 1;15:100837. Lima-Costa MF, de Andrade FB, de Souza PRB, Neri AL, Duarte YA, de O, Castro-Costa E et al. The Brazilian Longitudinal Study of Aging (ELSI-Brazil): Objectives and Design. Am J Epidemiol. 2018 July 1;187(7):1345–53. Katz S, Ford AB, Moskowitz RW, Jackson BA, Jaffe MW. STUDIES OF ILLNESS IN THE AGED. THE INDEX OF ADL: A STANDARDIZED MEASURE OF BIOLOGICAL AND PSYCHOSOCIAL FUNCTION. JAMA 1963 Sept 21;185:914–9. Lino VTS, Pereira SRM, Camacho LAB, Ribeiro Filho ST, Buksman S. Adaptação transcultural da Escala de Independência em Atividades da Vida Diária (Escala de Katz). Cad Saúde Pública. 2008;24:103–12. Lawton MP, Brody EM. Assessment of older people: self-maintaining and instrumental activities of daily living. Gerontologist. 1969;9(3):179–86. dos Santos RL, Júnior JSV. Confiabilidade da versão brasileira da escala de atividades instrumentais da vida diária. Rev Bras Em Promoção Saúde. 2008;21(4):290–6. Sandy Júnior PA, Borim FSA, Neri AL. Solidão e sua associação com indicadores sociodemográficos e de saúde em adultos e idosos brasileiros: ELSI-Brasil. Cad Saúde Pública. 2023;39:e00213222. Reuben DB, Laliberte L, Hiris J, Mor V. A hierarchical exercise scale to measure function at the Advanced Activities of Daily Living (AADL) level. J Am Geriatr Soc. 1990;38(8):855–61. Alvarado BE, Zunzunegui MV, Béland F, Bamvita JM. Life Course Social and Health Conditions Linked to Frailty in Latin American Older Men and Women. J Gerontol Ser A. 2008;63(12):1399–406. Kollia N, Caballero FF, Sánchez-Niubó A, Tyrovolas S, Ayuso-Mateos JL, Haro JM, et al. Social determinants, health status and 10-year mortality among 10,906 older adults from the English longitudinal study of aging: the ATHLOS project. BMC Public Health. 2018;18(1):1357. Zhao B, Liu Z, Fu Y, Zhang H, Wu J, Lai C, et al. Social Determinants of Intrinsic Capacity: A National Cohort Study. Am J Prev Med. 2024;66(3):559–67. Masters RK, Link BG, Phelan JC. Trends in education gradients of ‘preventable’ mortality: A test of fundamental cause theory. Soc Sci Med. 2015;127:19–28. Phelan JC, Link BG, Tehranifar P. Social Conditions as Fundamental Causes of Health Inequalities: Theory, Evidence, and Policy Implications. J Health Soc Behav [Internet]. 2010 Oct 8 [cited 2025 Oct 1]; Available from: https://journals.sagepub.com/doi/ 10.1177/0022146510383498 Krieger N. Embodiment: a conceptual glossary for epidemiology. J Epidemiol Community Health. 2005;59(5):350–5. Languirand M. Who I was, who I am: Gender and generativity in the assessment of older adults. Handbook of gender and sexuality in psychological assessment. New York, NY, US: Routledge/Taylor & Francis Group; 2016. pp. 578–602. Abeliansky AL, Strulik H. Hungry children age faster - ScienceDirect. Economics & Human Biology [Internet]. 2018 [cited 2025 Oct 1]; Available from: https://www.sciencedirect.com/science/article/pii/S1570677X17302757?via%3Dihub Beard JR, Hanewald K, Si Y, Amuthavalli Thiyagarajan J, Moreno-Agostino D. Cohort trends in intrinsic capacity in England and China. Nat Aging. 2025;5(1):87–98. de Azeredo Passos VM, Champs APS, Teixeira R, Lima-Costa MFF, Kirkwood R, Veras R, et al. The burden of disease among Brazilian older adults and the challenge for health policies: results of the Global Burden of Disease Study 2017. Popul Health Metr. 2020 Sept;30(1):14. Sarkar SM, Dhar BK, Crowley SS, Ayittey FK, Gazi MAI. Psychological Adjustment and Guidance for Ageing Urban Women. Ageing Int. 2023;48(1):222–30. Custodio N, Duque L, Montesinos R, Alva-Diaz C, Mellado M, Slachevsky A. Systematic Review of the Diagnostic Validity of Brief Cognitive Screenings for Early Dementia Detection in Spanish-Speaking Adults in Latin America. Front Aging Neurosci. 2020;12:270. Ibáñez A, Pina-Escudero SD, Possin KL, Quiroz YT, Peres FA, Slachevsky A, et al. Dementia caregiving across Latin America and the Caribbean and brain health diplomacy. Lancet Healthy Longev. 2021;2(4):e222–31. Parra MA, Baez S, Allegri R, Nitrini R, Lopera F, Slachevsky A, et al. Dementia in Latin America. Neurology. 2018;90(5):222–31. Prince MJ, Wu F, Guo Y, Gutierrez Robledo LM, O’Donnell M, Sullivan R, et al. The burden of disease in older people and implications for health policy and practice. Lancet Lond Engl. 2015;385(9967):549–62. Additional Declarations No competing interests reported. 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In Latin America, the complexities of aging are manifested in varied life expectancies across cities and countries because of different social environments (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e), such as economic inequalities and access to health care, education, and others. In Brazil, the increase in the number of older people is occurring rapidly, yet in a society that is not well prepared for such a transition (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eNevertheless, it is important to mention that this demographic transformation is occurring in a country marked by profound socioeconomic inequalities, limited healthcare infrastructure (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e), and historically low levels of education among older adults (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). As such, Brazil offers a valuable context in which to investigate and understand how socioeconomic status and early-life adversity shape aging trajectories.\u003c/p\u003e\n\u003ch3\u003eHealthy Aging: Evolving Perspectives\u003c/h3\u003e\n\u003cp\u003eThe concept of healthy aging has evolved significantly over the last few decades, challenging traditional views that associated aging solely with losses and declines. Rowe and Kahn\u0026rsquo;s model of usual and successful aging was introduced three decades ago, with successful aging being characterized by three factors: a low likelihood of illness and disability related to diseases, strong cognitive and physical capabilities, and active participation in social life (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eNevertheless, an important criticism from the World Health Organization (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e) regarding Rowe and Kahn\u0026rsquo;s model is that identifying individuals on the basis of only health, that is, the absence of diseases, is extremely problematic, since some diseases may be treated and not limit individual capacities. Therefore, the WHO (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e) defined healthy aging as the process of cultivating and sustaining the ability to function effectively, ensuring a sense of well-being during old age.\u003c/p\u003e\u003cp\u003eIn accordance with the WHO, recent studies have further broadened the understanding of healthy aging, recognizing it as a complex construct with multiple dimensions (\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). In a recent umbrella review, the authors showed that studies related to healthy aging, which are mostly carried out in developed countries, used heterogeneous conceptualization and operationalization. In addition, they highlight the importance of assuming context-specific conceptual guidance to fill gaps in the operationalization of healthy aging, notably with respect to gender, disabilities, and ethnicity (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAccording to the WHO (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e), a multidimensional model must consider intrinsic capacity, social and political environments, and the interaction of older adults with their surroundings. This multidimensional perspective aligns with evolving concepts of healthy aging and highlights the interplay of individual, social, and environmental factors in the aging process\u0026lrm;.\u003c/p\u003e\u003cp\u003eBuilding on this approach, recent systematic review studies have proposed operational models that reflect the complexity of aging (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). For example, Rivadeneira et al. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e) proposed a multidimensional framework that includes three components: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) intrinsic capacity, comprising geriatric syndromes, physiological health, risk factors, i.e., alcohol consumption, smoking, lack of physical activity, cognitive functioning, well-being, i.e., depression, and physical capacity; (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) social and political environments, such as participation in the community; and (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) interactions with the environment, including assistance offered by them to others. This model was developed and tested on nationally representative data from Ecuador. The WHO defines healthy aging as intrinsic capacity combined with functional ability in the given environment of an individual, which Rivadaneira et al. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e) combined into one multidimensional score to indicate the presence or absence of healthy aging. Their results revealed that women and individuals with lower incomes were less likely to meet the criteria for healthy aging. Owing to similar levels of socioeconomic inequalities and similar social and economic profiles, this model is suitable for application in other countries, such as Brazil.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eHealthy aging and inequalities in different health outcomes in Latin America\u003c/h2\u003e\u003cp\u003eDespite the growing interest in healthy aging, research employing a multidimensional framework remains scarce in Latin America. While multidimensional healthy aging as a concept has rarely been used in the Latin American context, with exceptions such as Rivadeneira et al.(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e), several studies point to low prevalence and socioeconomic gradients in older-age health outcomes in Latin America and the Caribbean (LAC) (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eA recent systematic review exploring gradients and inequalities in dementia prevalence in 15 LAC countries on the basis of age, sex, rurality, and education revealed an overall pooled prevalence of all-cause dementia of 10.66%. Women, individuals with lower educational levels, and rural residents were identified as particularly vulnerable groups with higher dementia prevalence. The study emphasized the need for targeted public health efforts to address the unequal burden of dementia in these populations (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Furthermore, a recent study (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e) comprising data from a Brazilian representative sample revealed a significant increase in health risk factors among the older adult population from 2000 to 2015, specifically, overweight/obesity, as well as diabetes and hypertension.\u003c/p\u003e\u003cp\u003eThe review by Nitrini et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) stressed the modifiable nature of factors contributing to dementia, offering hope for preventive actions, and highlighted the importance of education and socioeconomic status. Educational attainment emerged as a positive factor, aligning with previous studies highlighting education's role in accessing health services and improving overall quality of life. Conversely, economic status plays a pivotal role, with those in the worst economic situation being less likely to experience healthy aging, underscoring the importance of addressing socioeconomic inequalities (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Likewise, living as a rural resident was found to be positively associated with a higher level of dementia, especially among women (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Notably, childhood adversity, including hunger and poor access to education, has also been linked to worse aging outcomes (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Fair or poor childhood health is also considered an adverse childhood experience, but there is little research on how this and other adverse childhood experiences impact healthy aging over the long term in contexts such as Brazil.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eGender, Social Roles, and the Aging Process\u003c/h3\u003e\n\u003cp\u003eGender represents another important, yet often underexplored, dimension in aging research in Latin America, particularly given that many LAC countries are characterized by high levels of gender inequality. Importantly, studies have shown that gender inequalities might shape the aging experience through social roles, cultural expectations, and structural disadvantages across the whole life course (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn Brazil, older women born in the 1940s and 1950s faced profound constraints on formal education, limited formal labor market participation (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e), and restricted financial autonomy (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e) due to prevailing patriarchal norms. In addition, labor policies and cultural messages have reinforced the role of women as caregivers and homemakers (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAs a consequence, these gendered social roles have had lasting implications, with women predominantly in low-paid, insecure work or unpaid domestic labor, entering retirement with insufficient pension benefits and financial reserves (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). Nevertheless, the biomedical literature further highlights gender differences in morbidity, showing women's greater susceptibility to various health issues, even when reproductive conditions are excluded (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). This disadvantage persists up to older age, with men maintaining better functioning and lower disability rates than women do. Gender differences also manifest in the experience of specific diseases and psychological well-being, with women reporting higher levels of anxiety and stress (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e) and higher levels of depression and loneliness (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). The association between age and health-related quality of life remains debated, with complex intersections of race, ethnicity, and gender influencing these dynamics (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eRegarding early life adversity, greater disparity in educational opportunities during schooling was consistently linked to diminished cognitive performance scores in older individuals, particularly among women, in a European sample (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). Moreover, adverse childhood experiences, such as famine, can lead to chronic diseases later in life; for instance, F\u0026eacute;lix-Beltr\u0026aacute;n and Seixas (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e) reported that childhood hunger was associated with diabetes and osteoporosis later in life on the basis of ELSI-Brazil data. However, they did not explore other childhood experiences on a multidimensional model of healthy aging. Since adversities can influence biological aging, it is crucial to understand how these early experiences contribute to health disparities.\u003c/p\u003e\u003cp\u003eEarly life adversity together with gender stereotypes across the life course might lead to cumulative social and biological disadvantages that unfold over the life course. Importantly, these gendered pathways intersect with socioeconomic status and childhood experiences in unique ways in high-inequality contexts such as Brazil (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). From the social environment influencing mortality in Latin American cities to the unequal burden of dementia based on education and gender, understanding the gender differences in healthy aging requires a multidimensional and context-sensitive approach. Additionally, recognizing the role of socio-economic status and early life experiences in shaping the aging trajectory further underscores the need for holistic interventions to promote healthy aging and reduce disparities.\u003c/p\u003e\n\u003ch3\u003eCurrent Research\u003c/h3\u003e\n\u003cp\u003eOur objective was to explore the prevalence of healthy aging via a multidimensional framework in a nationally representative sample of older Brazilian adults. Furthermore, we also aim to examine the role of environmental elements such as socioeconomic status, education, and childhood experiences. Finally, we also extend our investigation by incorporating the sex/gender dimension, enriching our understanding of the interplay between these factors and healthy aging.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003eParticipants\u003c/h2\u003e\u003cp\u003eIn this study, we used data from the population-representative Brazilian Longitudinal Study of Aging (ELSI-Brazil) (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). ELSI-Brazil has been carried out with adults aged 50 years and older residing in diverse communities across different regions of Brazil. The first wave of data collection occurred from 2015\u0026ndash;2016, and the second wave was conducted between 2019 and 2021. For the present analysis, we used data from the most recent wave to estimate the current prevalence of healthy aging. This sample consisted of 9,949 adults aged 50 years or more, of whom 9,908 participants (M\u003csub\u003eage\u003c/sub\u003e = 66; SD\u0026thinsp;=\u0026thinsp;10,06; max. = 109 years) had complete information on the relevant variables and were included in the analyses.\u003c/p\u003e\u003cp\u003eThe study sampling was conducted by conglomerates, and Brazilian Institute of Geography and Statistics (IBGE) data were used for stratification and selection of regions. To guarantee a comprehensive representation of urban and rural areas across municipalities of varying sizes, ELSI-Brazil employed a multistage sampling approach. This method involves stratifying primary sampling units (municipalities) and further selection stages, including census tracts and households. For more details regarding the sampling methodology, see (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). In-person assessments were conducted in Portuguese, the official language of Brazil, by trained interviewers.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eMeasures\u003c/h2\u003e\u003cdiv id=\"Sec9\" class=\"Section3\"\u003e\u003ch2\u003eOperationalization of Healthy Aging\u003c/h2\u003e\u003cp\u003eAccording to the WHO (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e), healthy aging is a multidimensional concept that includes an individual\u0026rsquo;s intrinsic capacity and functional ability to address given environmental factors. Given that there is no clear definition of which variables should comprise healthy aging components, we adapted the multidimensional model proposed by Rivadeneira et al. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e) on the basis of the variables available in the ELSI-Brazil database (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e01\u003c/span\u003e). The composite score of \u003cem\u003eintrinsic capacity\u003c/em\u003e included domains such as physical health, geriatric syndromes, physical capacity, cognitive ability, psychological well-being, and environmental aspects, including social participation. Following the operationalization by Rivadeneira et al. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e), individuals were classified into a \u003cem\u003ehealthy aging\u003c/em\u003e group or a \u003cem\u003eless healthy aging group\u003c/em\u003e, as described in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. We summed the scores for each domain and then recoded the results into a dichotomous variable. The specific variables used for each component are described in detail below.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\n\u003ch3\u003ePhysical health\u003c/h3\u003e\n\u003cp\u003eTo be considered healthy, participants were assessed on the basis of the absence of diabetes, hypertension, cardiovascular disease, stroke, lung disease, vision, and hearing problems or whether participants with the diagnosis received treatment, i.e., if the disease was managed.\u003c/p\u003e\u003cp\u003eHowever, owing to limitations in the dataset, we were unable to determine whether participants were receiving treatment or had limitations caused by arthritis, rheumatism, osteoporosis, renal insufficiency, Parkinson's disease, and Alzheimer's disease. For this reason, participants who reported any of these conditions were included in the less healthy aging group.\u003c/p\u003e\u003cp\u003ePhysical health conditions were self-reported by the following question: \u0026ldquo;\u003cem\u003eHas a doctor or nurse ever told you that you had...?\u003c/em\u003e\u0026rdquo;\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eGeriatric syndrome\u003c/h2\u003e\u003cp\u003eThis factor comprises three variables: 1) whether participants had polypharmacy (according to the World Health Organization, polypharmacy is the concomitant and routine use of 4 or more medications with or without a prescription); 2) whether participants self-reported urinary or fecal incontinence; and 3) whether the respondent self-reported a fall in the last 12 months.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eFunctional Capacity\u003c/h2\u003e\u003cp\u003eFunctional capacity was assessed by self-perceived inability to perform basic activities of daily living (BADL) via the Katz Index (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e), adapted for Brazil by Lino et al. (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). Subjects who did not need help with any of the activities assessed were considered independent. Disabilities related to instrumental activities of daily living (IADL) were assessed via the Lawton Scale (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e), adapted in Brazil by Lopes and Virtuoso-J\u0026uacute;nior (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). The subjects were considered independent and had no difficulty except with heavy domestic activities.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003ePsychological well-being\u003c/h2\u003e\u003cp\u003eTo create the well-being variable, two scales were considered: 1) Life satisfaction, which is the following response instruction from the individual ELSI-Brazil questionnaire, which has, as response options, increasing measures from 1 to 10 in the form of a MacArthur Scale ladder: \"Please think about your level of satisfaction with life and point to the corresponding rung\". Answers of 6 or above were considered \u0026lsquo;high\u0026rsquo; satisfaction, and answers below or equal to 5 were considered \u0026lsquo;low\u0026rsquo; satisfaction.\u003c/p\u003e\u003cp\u003eDepressive symptoms were assessed via the CES-D8 scale (an eight-item version of the Center for Epidemiological Studies Depression Scale). The affirmative answers to the items describing depressive symptoms were added. The cutoff point for categorizing depression was \u0026ge;\u0026thinsp;4, which was based on the criteria adopted by Sandy Junior (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eCognitive functioning\u003c/h2\u003e\u003cp\u003eCognitive functioning was measured by four tasks as follows:\u003c/p\u003e\u003cp\u003e 1) In the first task, participants were required to recall a list of 10 words immediately after hearing them.\u003c/p\u003e\u003cp\u003e2) The second task involved recalling the same set of 10 words after a 5-minute delay, following the completion of other cognitive tests. In both tasks, participants received one point for each correct answer, with a maximum score of 10 points.\u003c/p\u003e\u003cp\u003e3) The third assessment evaluated participants' awareness of the date, including the day, month, and year, as well as the day of the week. Each accurate response earned one point, with a total possible score of four points.\u003c/p\u003e\u003cp\u003e4) The fourth measure, focusing on language and processing speed, required participants to recall the names of the animals within a 1-minute timeframe. The participants received one point for each correctly remembered animal name.\u003c/p\u003e\u003cp\u003eThe four cognitive measures were z-standardized, averaged and restandardized to calculate a global z score with a mean of zero and a standard deviation of 1. Cognitive impairment was determined for a global z score lower than or equal to -1.5, which is equal to -1.5 SD from the overall mean.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eEnvironment\u003c/h2\u003e\u003cp\u003eThe environment comprises many factors, including the extrinsic world that forms the context of an individual\u0026rsquo;s life. These include the microlevel (e.g., home) to the macrolevel (e.g., community and broader society). In this study, we included social participation and other activities (i.e., social, productive, and entertainment activities), as assessed by the Advanced Activities of Daily Living (AADL, (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e)).\u003c/p\u003e\u003cp\u003eFor the present study, the total number of activities that each participant reported doing from a total of 13 activities in the scale was calculated. The participants were classified into two groups according to their total score: more active, with greater participation in AADL, or less active. Those who performed four or more activities were considered more active, and those who reported performing three or fewer activities were considered less active.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCriteria for Defining Healthy Aging\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDimension of healthy aging\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDomain\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePresence of Healthy Aging\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAbsence of healthy aging\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIntrinsic capacity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePhysical health\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAbsence of the following diagnoses or the presence of diseases that are managed (treated) and do not limit the functioning of the participant:\u003c/p\u003e\u003cp\u003eDiabetes, hypertension, cardiovascular disease, stroke, lung disease, vision and hearing problems. arthritis, rheumatism, osteoporosis, renal insufficiency, Parkinson's, and Alzheimer's.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eDiagnoses with at least one of the mentioned diseases that are not controlled or are limiting the functioning of the participant.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGeriatric syndromes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAbsence of polypharmacy, urinary and fecal incontinence, and no falls syndrome\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePresence of the cited factors\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFunctional capacity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAbsence of disability according to the Instrumental activities of daily living and Basic Activities of Daily Living\u003c/p\u003e\u003cp\u003ePhysical activity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePresence of disabilities according to the cited tests.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCognitive ability\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAbsence of cognitive impairment assessed by global Z score.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePresence of cognitive impairment, values of Z scores \u0026lt; = -1.5.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePsychological well-being\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGlobal satisfaction with life and Absence of depression by using the Center for Epidemiological Studies Depression Scale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePresence of low satisfaction or/and symptoms of depression.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEnvironment\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSocial Participation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAdvanced Activities of Daily Living.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eInvolvement in less than three Advanced Activities of Daily Living\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eNote: Variables adapted from Rivadeneira et al. (2021)\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eCovariates (Independent variables)\u003c/h2\u003e\u003cp\u003eSocioeconomic characteristics included gender/sex (women/men), age groups (50\u0026ndash;59 years, 60\u0026ndash;69 years, 70\u0026ndash;79 years, and 80 years of age or older), rurality (urban/rural), race (white, black, mixed), education levels (no school, 1\u0026ndash;4 years, 5\u0026ndash;8 years, 9\u0026ndash;12 years, and 12 years or more), marital status (single, married/stable union, divorced/separated, widowed), and income calculated as multiples of the minimum wage (wage\u0026thinsp;\u0026lt;\u0026thinsp;1, 1\u0026ndash;2 wages, 2\u0026ndash;3 wages, 3\u0026ndash;4 wages, and wages\u0026thinsp;\u0026gt;\u0026thinsp;4). The individual income was computed on the basis of the national minimum wage (NMW) applicable in the year of the interview.\u003c/p\u003e\u003cp\u003eChildhood experiences included three variables: health in childhood (excellent/very good, good, fair, and poor); hunger during childhood (no/yes); and living in rural areas until the age of 15 (no/yes).\u003c/p\u003e\u003cp\u003eRace categories were determined on the basis of participants' self-identification from a list of options aligning with the official classification of self-reported skin color in Brazil (Silva, 1997): white, brown or mixed, black, yellow, and indigenous. However, in this study, we included only participants who self-reported as white, black, or mixed since there were not enough cases in the other categories to fit the model.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eFirst, we carried out descriptive analyses to observe the percentage distributions of all the study variables. Rao Scott's chi-square tests were subsequently used to assess potential differences in socioeconomic and childhood experiences between the healthy and less healthy aging groups.\u003c/p\u003e\u003cp\u003eSecond, we ran logistic regression analyses to assess which independent variables influence healthy aging, which was treated as a dichotomous dependent variable. The reference group was the healthy aging group.\u003c/p\u003e\u003cp\u003eIn addition, we included sampling weights in all analyses to adjust the complex sampling design of the ELSI-Brazil.\u003c/p\u003e\u003cp\u003eSTATA (release 17, Stata Corp.) software was used for the statistical analyses.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, 59.33% of the study participants were women. In terms of age, 65.24% were between 50 and 69 years old. Most participants lived in urban regions (83.8%), had 1\u0026ndash;4 years of education (40.51%), and had up to 2 wages as income (57.03%). For the prevalence of healthy aging according to the adapted criteria, only 19.69% of the respondents were categorized as healthy aging, whereas 80.31% were categorized as less healthy aging.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSocioeconomic and childhood characteristics of the study sample (N\u0026thinsp;=\u0026thinsp;9,908).\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNumber of Participants\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e%\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eGender/Sex\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWomen\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5,819\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e59.33\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMen\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3,989\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e40.67\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eAge Groups\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e50\u0026ndash;59 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2,984\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e30.42\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e60\u0026ndash;69 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3,415\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e34.82\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e70\u0026ndash;79 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2,252\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22.96\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e80 years or more\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,157\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11.80\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eRurality\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUrban\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8,219\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e83.80\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRural\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,589\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16.20\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eRace\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWhite\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4,587\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e46.77\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBlack\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,052\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10.73\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMixed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4,169\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e42.51\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eEducation\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eno schooling\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,552\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16.02\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u0026ndash;4 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3,924\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e40.51\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u0026ndash;8 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,854\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19.14\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e9\u0026ndash;12 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,705\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e12 years or more\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e651\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.72\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eMarital Status\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSingle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,195\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12.18\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarried/Stable union\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5,212\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e53.14\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDivorced/Separated\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,229\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12.53\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWidowed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2,172\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22.15\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eIncome\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWage\u0026thinsp;\u0026lt;\u0026thinsp;1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,905\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20.50\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u0026ndash;2 wages\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3,394\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e36.53\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u0026ndash;3 wages\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,714\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18.45\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u0026ndash;4 wages\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e874\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9.41\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWages\u0026thinsp;\u0026gt;\u0026thinsp;4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,405\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15.12\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eBrazilian Regions\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNorth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e709\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.23\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNortheast\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2,659\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27.11\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSoutheast\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4,060\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e41.39\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSouth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,331\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13.57\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMidwest\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,049\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10.70\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cem\u003eChildhood experiences\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eHealth in childhood\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eExcellent/Very good\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2,236\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22.96\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGood\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5,758\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e59.12\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFair\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,240\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12.73\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePoor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e506\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.20\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eHunger during childhood\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7,293\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e75.41\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2,378\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24.59\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cem\u003eLived in rural areas until the age of 15\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4,200\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e42.82\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5,577\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e56.86\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eHealthy classification\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHealthy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,931\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19,69\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLess healthy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7,877\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e80,31\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows that there was a greater prevalence of healthy aging among men (55.1%) than among women (42.8%). Participants who did not meet the criteria for healthy aging were more likely to be older and have no schooling or up to four years of education. Moreover, participants reporting being widowed were more likely to be less healthy. Those receiving more than three wages a month were more likely to meet the criteria for healthy aging. With respect to childhood experiences, those who self-reported poor health in childhood and who experienced hunger during childhood were more likely to be allocated to the less healthy aging group.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eWeighted Analyses of Socioeconomic and Childhood Characteristics across Aging Health Categories.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHealthy\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLess healthy\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eGender/Sex\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWomen\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e44.9 (41.9\u0026ndash;47.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e57.2 (55.7\u0026ndash;58.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0 .001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMen\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e55.1 (52.1\u0026ndash;58.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e42.8 (41.3\u0026ndash;44.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eAge Groups\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e50\u0026ndash;59 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e58.4 (55.1\u0026ndash;61.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e44.2 (42.1\u0026ndash;46.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0 .001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e60\u0026ndash;69 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e28.6 (26.7\u0026ndash;30.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e29.2 (28.1\u0026ndash;30.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e70\u0026ndash;79 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10.7 (9.3\u0026ndash;12.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e17.6 (16.5\u0026ndash;18.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e80 years or more\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.4 (1.7\u0026ndash;3.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e9.0 (8.3\u0026ndash;9.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eRurality\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUrban\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e87.9 (79.8\u0026ndash;93.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e83.4 (75.7\u0026ndash;89.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.02*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRural\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e12.1(7.0\u0026ndash;20.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e16.6(11.0\u0026ndash;24.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eRace\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWhite\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e51.2 (46.6\u0026ndash;55.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e45.3 (40.4\u0026ndash;50.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0 .001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBlack\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e8.8(6.9\u0026ndash;11.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e11.5(9.7\u0026ndash;13.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMixed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e39.9(36.0\u0026ndash;44.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e43.2 (39.2\u0026ndash;47.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eEducation\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eno school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6.4(5.0\u0026ndash;8.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e14.4 (10.4\u0026ndash;19.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0 .001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u0026ndash;4 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e29.5(23.6\u0026ndash;36.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e41.1 (37.6\u0026ndash;44.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u0026ndash;8 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e22.7(19.5\u0026ndash;26.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e19.9 (17.1\u0026ndash;23.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e9\u0026ndash;12 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e29.6 (25.9\u0026ndash;33.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e18.5 (15.0\u0026ndash;22.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e12 years or more\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e11.6 (9.7\u0026ndash;13.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e6.1(4.4\u0026ndash;8.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eMarital Status\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSingle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e12.1(10.4\u0026ndash;14.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e12.8 (11.2\u0026ndash;14.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0 .001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarried/Stable union\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e66.6 (62.7\u0026ndash;70.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e59.0 (56.5\u0026ndash;61.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDivorced/Separated\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e11.7 (9.2\u0026ndash;14.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e10.9 (9.7\u0026ndash;12.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWidowed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e9.7(7.8\u0026ndash;11.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e17.3 (16.0\u0026ndash;18.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eIncome\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWage\u0026thinsp;\u0026lt;\u0026thinsp;1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e13.6 (11.1\u0026ndash;16.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e20.2 (17.4\u0026ndash;23.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0 .001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u0026ndash;2 wages\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e26.0 (21.6\u0026ndash;31.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e36.7 (34.6\u0026ndash;38.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u0026ndash;3 wages\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e20.7 (17.8\u0026ndash;23.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e18.6 (16.6\u0026ndash;20.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u0026ndash;4 wages\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e12.5 (9.6\u0026ndash;16.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e9.7 (8.3\u0026ndash;11.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWages\u0026thinsp;\u0026gt;\u0026thinsp;4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e27.3 (24.0\u0026ndash;30.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e14.8 (12.3\u0026ndash;17.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eChildhood experiences\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eHealth in childhood\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eExcellent/Very good\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e26.7 (21.4\u0026ndash;32.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e23.1 (20.8\u0026ndash;25.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0 .001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGood\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e59.1 (54.0\u0026ndash;64.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e56.7 (54.9\u0026ndash;58.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFair\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e11.6 (10.2\u0026ndash;13.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e13.9 (12.8\u0026ndash;15.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePoor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.6 (1.8\u0026ndash;3.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e6.3 (5.6\u0026ndash;7.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eHunger during childhood\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e80.6 (76.9\u0026ndash;83.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e73.7 (71.0\u0026ndash;76.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e19.4(16.1\u0026ndash;23.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e26.3 (23.7\u0026ndash;29.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eLived in rural areas until the age of 15\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e50.0 (37.0\u0026ndash;63.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e43.1 (33.3\u0026ndash;53.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.007*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e49.9 (36.9\u0026ndash;62.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e56.7 (46.3\u0026ndash;66.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eNote: Weighted \u003cem\u003eP\u003c/em\u003e values were determined via the Rao‒Scott test. Differences among groups were confirmed by nonoverlapping confidence intervals.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003e* \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.05\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eRao-Scott analyses were carried out whether the experience of hunger during childhood was distributed differently across Brazilian regions. Participants living in the North (31.4%; I -23.7-40.3) and Northeast (33.4%; CI -29.1-38.0) regions were more likely to report famine during childhood compared to participants with residence in the Southeast of the country (20.4%; CI -18.0-23.0), \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001.\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e displays the results of the logistic regression analyses with healthy aging as a dependent variable that showed that men were more likely to belong to the healthy aging group than women. Furthermore, older participants, especially those aged 80 or more, were more likely to be in the less healthy aging group. Older adults having five years or more of education were more likely to be healthily aging. Regarding childhood experiences, we detected that respondents who self-reported fair or poor health during childhood and suffered from hunger were less likely to meet the criteria for healthy aging.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAssociations between Healthy Aging, Socioeconomic Status, and Childhood Factors\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOdds Ratio\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eGender/Sex\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWomen (Reference)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMen\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.56\u0026ndash;0.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eAge Groups\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e50\u0026ndash;59 years (Reference)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e60\u0026ndash;69 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.11\u0026ndash;1.51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.002*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e70\u0026ndash;79 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.62\u0026ndash;2.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e80 years or more\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.91\u0026ndash;5.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eRurality\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUrban (Reference)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRural\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.77\u0026ndash;1.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.68\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eRace\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWhite (Reference)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBlack\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.93\u0026ndash;1.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.15\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMixed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.97\u0026ndash;1.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eEducation\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eno school (Reference)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u0026ndash;4 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.55\u0026ndash;1.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.45\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u0026ndash;8 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.43\u0026ndash;0.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.008*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e9\u0026ndash;12 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.33\u0026ndash;0.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.006*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e12 years or more\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.25\u0026ndash;0.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.008*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eMarital Status\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSingle (Reference)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarried/Stable union\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.75\u0026ndash;1.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.35\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDivorced/Separated\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.53\u0026ndash;1.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.45\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWidowed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.77\u0026ndash;1.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.50\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eIncome\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWage\u0026thinsp;\u0026lt;\u0026thinsp;1 (reference)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u0026ndash;2 wages\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.78\u0026ndash;1.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.85\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u0026ndash;3 wages\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.57\u0026ndash;0.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u0026ndash;4 wages\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.48\u0026ndash;0.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWages\u0026thinsp;\u0026gt;\u0026thinsp;4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.43\u0026ndash;0.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eChildhood experiences\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eHealth in childhood\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eExcellent/Very good (Reference)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGood\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.78\u0026ndash;1.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.34\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFair\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.01\u0026ndash;1.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.04*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePoor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.66\u0026ndash;3.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eHunger during childhood\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo (Reference)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.07\u0026ndash;1.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.007*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eLived in rural areas until the age of 15\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo (Reference)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.77\u0026ndash;1.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003e* \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.05\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study investigated the prevalence of healthy aging in a nationally representative sample of older adults in Brazil and explored the effects of socioeconomic conditions and childhood experiences in explaining the health of older adults. With a more comprehensive and thus less narrow view of healthy aging, considering multiple dimensions and whether diseases were treated or controlled, our findings suggest that more than four-fifths (80.3%) of our sample did not meet the criteria for healthy aging, suggesting that a substantial proportion of older Brazilian people must cope with many health challenges as they age.\u003c/p\u003e\u003cp\u003eOur findings on a Brazilian population-representative sample contrast with the findings of Rivadeneira et al. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e) for a sample from Ecuador, roughly half of which were found to be aging healthily (53.15% of the sample), even though their sample was aged 65 years or older, in contrast with our data from ELSI-Brazil, which comprised adults aged 50 and older. A more favorable socioeconomic profile of the Ecuadorian sample may have contributed to the differences in prevalence estimates. Furthermore, period effects may be partly responsible for the differences in findings; the data of the SABE Ecuador study of Rivadeneira et al., 2021 were collected in 2010, whereas the present study used 2019\u0026ndash;2021 data from ELSI-Brazil. Similarly, earlier research revealed sharp increases in health risk factors such as obesity in Brazil over the period 2000\u0026ndash;2015 (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Finally, differences in socioeconomic conditions and healthcare access may have played a role, as Brazil has historically exhibited greater inequality and regional disparities (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eOn the basis of our data, older individuals with four years of formal education or less and household incomes lower than two wages are much less likely to meet the criteria for healthy aging, suggesting that these groups are particularly vulnerable. These findings align with prior research in Latin America and globally, which suggests that socioeconomic disadvantages accumulate across the life course and manifest in worse health outcomes in old age (\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e), similar to the findings of other studies in other regions of the world (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). The strong links between formal education and healthy aging are suggested to come from increased exposure to various risk factors; lower resources in terms of money, knowledge, prestige, power, and beneficial social connections (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e); higher stress levels; other biological mechanisms of \u0026lsquo;embodiment\u0026rsquo; (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e); and possibly limited access to (preventive) healthcare services starting from a younger age.\u003c/p\u003e\u003cp\u003eAs discussed by previous studies (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e), gender inequality might lead to pronounced sex/gender differences in healthy aging, as men tend to be highly educated, perform cognitively demanding jobs, and are offered more strategies and opportunities to cope with the adverse external environment. Additionally, men and women who were born in the 1940s and 1950s played very different social roles, which deferentially impacted their mental health during their lifespan, with women being more likely to experience negative outcomes in mental health (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). Women also live longer, meaning that they spend more time coping with stressful life transitions, such as losing a spouse, caring for other people, and living with their own chronic illnesses (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eMoreover, our results reinforce the impact of famine during childhood on healthy aging shown by F\u0026eacute;lix-Beltr\u0026aacute;n and Seixas (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Self-reported lower health during childhood is associated with less healthy aging, given that a lack of nutrients during childhood could lead to epigenetic changes leading to metabolic dysfunction. These outcomes may reflect the long-term biological consequences of early nutritional deprivation and stress, including epigenetic changes linked to chronic disease later in life (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e). Moreover, such early-life adversity was more commonly reported by participants from Brazil\u0026rsquo;s North and Northeast Regions, areas historically marked by higher poverty levels and food insecurity, underscoring the geographical dimension of inequality in aging trajectories.\u003c/p\u003e\u003cp\u003eInterestingly, no differences between groups were observed in urban versus rural residences. This suggests that environmental factors associated with locality, such as pollution or infrastructure, may be less predictive of healthy aging than broader structural inequalities, such as income, education, and life-course exposures. Future research could explore more nuanced aspects of the built and social environment, such as neighborhood safety, healthcare accessibility, and pollution exposure.\u003c/p\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003eStrengths and limitations\u003c/h2\u003e\u003cp\u003eA major strength of this study was the operationalization of a multidimensional framework to assess healthy aging, which is consistent with recent recommendations from the WHO (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e) and prior empirical work (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e) and provides a more holistic view of the intrinsic capacity of older adults in Brazil. Another strength is the use of recent nationally representative data from ELSI-Brazil, with a multistage sampling process and the use of weights to arrive at population-representative estimates.\u003c/p\u003e\u003cp\u003eHowever, limitations should be acknowledged. First, owing to differences in data collection, we had to slightly adapt the operationalization of intrinsic capacity used by Rivadeneira et al. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). While some dimensions of healthy aging are more standardized, e.g., the classification of polypharmacy or the presence of chronic conditions, other dimensions are based on conventions that are sometimes less stringently used in the literature, such as the classification as cognitively impaired, with a score of 1.5 SD below the sample mean. The prevalence of healthy aging consequently is sensitive to changes in the operationalization of the different dimensions, including possible underreporting of chronic conditions, due to a lack of diagnosis, which may have led to an overestimation of healthy aging. Additionally, the domains constituting healthy aging may have differential importance, and different operationalizations exist in the literature; however, other studies have used country-specific operationalizations of intrinsic capacity as well (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e), and we defined the concept as congruent as possible with existing studies in comparable contexts (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Second, not all determinants of healthy aging found in earlier research were available in the data used from the ELSI-Brazil. Third, our estimates of the socioeconomic determinants of healthy aging may be impacted by premature mortality, which is still rather high in the Brazilian context (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e). This selective attrition may have biased our estimates toward the null.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003ePolicy implications\u003c/h2\u003e\u003cp\u003eGender-responsive policies are essential, as older women in Brazil face a double burden of socioeconomic disadvantage and greater longevity, leading to long periods of managing chronic illness while still fulfilling important family functions such as caregiving responsibilities. In this sense, some policy recommendations based on our findings might include macrolevel interventions that prioritize initiatives to promote access to education for future generations and support those in less favorable economic situations, optimizing the social and psychological environment, fostering a supportive social atmosphere through media campaigns, and promoting an appropriate understanding of family development laws (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e). Moreover, community care for older people is crucial, especially among women, who represent the larger proportion of older adults in Brazil, emphasizing preventive services for their physical and mental health and the establishment of an effective old-age security system (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eEncouraging the development of human resources among older people involves promoting their participation in social activities, amplifying their network of social support, and leveraging their knowledge in community initiatives (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e). In addition, childhood health and nutrition must be core components of aging policy, given the long-term impact of early adversity on later-life outcomes. Investments in maternal and child health, nutrition programs, and poverty alleviation can have intergenerational effects on healthy aging (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eOn a micro level, mastering skills to understand the psychological functioning of older women is crucial, emphasizing respectful communication and active listening to promote happiness and confidence (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e). Additionally, addressing the prevalence of dementia is imperative, considering its impact on dependence among older adults and the substantial medical and care costs involved (\u003cspan additionalcitationids=\"CR50 CR51\" citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e). Finally, while this study did not directly assess loneliness or social participation, our findings still suggest that psychosocial conditions, such as widowhood and poor mental health, are important domains for policy intervention. However, the central policy message should not be about promoting social participation \u003cem\u003eper se\u003c/em\u003e, as structural influences shape downstream conditions and opportunities for social participation. Thus, addressing the structural inequalities that shape healthy aging trajectories from birth to old age is essential.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study operationalized healthy aging with a comprehensive and multidimensional score. A large majority (80%) of respondents in a population-representative sample of the older Brazilian population did not meet the criteria for healthy aging. Our findings highlight substantial gaps in health equity by gender, socioeconomic status, and childhood adversity across aging individuals. As Brazil continues to age, ensuring that longer lives are accompanied by better health will require integrated, equity-focused public policies. Without addressing the root causes of inequality across the life course, gains in life expectancy may not translate into gains in health and quality of life for most of the population.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eLAC - Latin America and the Caribbean\u003c/p\u003e\n\u003cp\u003eWHO - World Health Organization\u003c/p\u003e\n\u003cp\u003eELSI-Brazil - Brazilian Longitudinal Study of Aging\u003c/p\u003e\n\u003cp\u003eIBGE - Brazilian Institute of Geography and Statistics\u003c/p\u003e\n\u003cp\u003eBADL - Basic Activities of Daily Living\u003c/p\u003e\n\u003cp\u003eIADL - Disabilities related to instrumental activities of daily living\u003c/p\u003e\n\u003cp\u003eCES-D8 - Center for Epidemiological Studies Depression Scale\u003c/p\u003e\n\u003cp\u003eNMW - National minimum wage\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe ELSI-Brazil study was approved by the Ethics Committee of the Oswaldo Cruz Foundation-Minas Gerais, and the process is registered on \u003cem\u003ePlataforma Brasil\u003c/em\u003e (CAAE: 34649814.3.0000.5091). The participants signed separate informed consent forms for each of the research procedures and authorized access to corresponding secondary databases.\u0026nbsp;This study received ethics approval from the Ethics Review Committee of the ERC in November 2018.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data supporting the findings of this study are available from the ELSI-Brazil repository [http://elsi.cpqrr.fiocruz.br]. Access can be obtained upon reasonable request and with permission from the ELSI-Brazil coordination.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eELSI-Brazil was supported by the Brazilian Ministry of Health: DECIT/SCTIE (Grants: 404965/2012-1 and TED 28/2017) and COPID/DECIV/SAPS (Grants: 20836, 22566, 23700, 25560, 25552, and 27510). Moreover, part of this work was supported by the National Council for Scientific and Technological Development (CNPq; Novation Process: 229520/2013-8), and it is part of the CRISP project funded by the European Research Council (ERC; grant agreement no. 803239).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eResearch design and data analysis by FR; FR, GB, AL wrote the article and were responsible for the final content; and FR, GB, HF, and AL assisted in the interpretation of the results and critical revision of the manuscript. All the authors contributed substantially to the development of the manuscript and approved its final version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors express their gratitude to all the researchers, interviewers, and participants of ELSI-Brazil.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBilal U, Hessel P, Perez-Ferrer C, Michael YL, Alfaro T, Tenorio-Mucha J, et al. Life expectancy and mortality in 363 cities of Latin America. Nat Med. 2021;27(3):463\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKirby T. Brazil facing ageing population challenges. Lancet. 2023;402(10415):1821.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ede Barros RP, de Carvalho M, Franco S, de Mendon\u0026ccedil;a RSP. Determinantes imediatos da queda da desigualdade de renda brasileira. 2007 Jan [cited 2025 Oct 1]; Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://repositorio.ipea.gov.br/handle/11058/2161\u003c/span\u003e\u003cspan address=\"http://repositorio.ipea.gov.br/handle/11058/2161\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePimentel FG, Buchweitz C, Onocko Campos RT, Hallal PC, Massuda A, Kieling C. Realising the future: Health challenges and achievements in Brazil. SSM - Ment Health. 2023;4:100250.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTravassos GF, Coelho AB, Arends-Kuenning MP. The elderly in Brazil: demographic transition, profile, and socioeconomic condition. Rev Bras Estud Popul. 2020;37:e0129.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRowe JW, Kahn RL. Human Aging: Usual and Successful. Science [Internet]. 1987 July 10 [cited 2025 Oct 1]; Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.science.org/doi/\u003c/span\u003e\u003cspan address=\"https://www.science.org/doi/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1126/science.3299702\u003c/span\u003e\u003cspan address=\"10.1126/science.3299702\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRowe JW, Kahn RL. Successful Aging1. Gerontologist. 1997;37(4):433\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWHO. World report on ageing and health [Internet]. 2015 [cited 2025 Oct 1]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://iris.who.int/items/5db2c88f-941a-472d-ac6e-f08a7e9ae20b\u003c/span\u003e\u003cspan address=\"https://iris.who.int/items/5db2c88f-941a-472d-ac6e-f08a7e9ae20b\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMenassa M, Stronks K, Khatami F, D\u0026iacute;az ZMR, Espinola OP, Gamba M et al. Concepts and definitions of healthy ageing: a systematic review and synthesis of theoretical models. eClinicalMedicine [Internet]. 2023 Feb 1 [cited 2025 Oct 1];56. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.thelancet.com/journals/eclinm/article/PIIS2589-5370(22)00550-8/fulltext\u003c/span\u003e\u003cspan address=\"https://www.thelancet.com/journals/eclinm/article/PIIS2589-5370(22)00550-8/fulltext\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMichel JP, Sadana R. Healthy Aging Concepts and Measures. J Am Med Dir Assoc. 2017 June;1(6):460\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRivadeneira MF, Mendieta MJ, Villavicencio J, Caicedo-Gallardo J, Buend\u0026iacute;a P. A multidimensional model of healthy ageing: proposal and evaluation of determinants based on a population survey in Ecuador. BMC Geriatr. 2021;21(1):615.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePiriu AA, Bufali MV, Cappellaro G, Compagni A, Torbica A. Conceptualisation and measurement of healthy ageing: Insights from a systematic literature review. Soc Sci Med. 2025 June;1:374:117933.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCastillo-Riquelme M, Yamada G, Diez Roux AV, Alfaro T, Flores-Alvarado S, Barrientos T, et al. Aging and self-reported health in 114 Latin American cities: gender and socio-economic inequalities. BMC Public Health. 2022;22(1):1499.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSantamaria-Garcia H, Sainz-Ballesteros A, Hernandez H, Moguilner S, Maito M, Ochoa-Rosales C, et al. Factors associated with healthy aging in Latin American populations. Nat Med. 2023 Sept;29(9):2248\u0026ndash;58.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRibeiro FS, Teixeira-Santos AC, Leist AK. The prevalence of mild cognitive impairment in Latin America and the Caribbean: a systematic review and meta-analysis. Aging Ment Health [Internet]. 2022 Aug 24 [cited 2025 Oct 1]; Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.tandfonline.com/doi/abs/\u003c/span\u003e\u003cspan address=\"https://www.tandfonline.com/doi/abs/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/13607863.2021.2003297\u003c/span\u003e\u003cspan address=\"10.1080/13607863.2021.2003297\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRibeiro FS, de Oliveira Duarte YA, Santos JLF, Leist AK. Changes in prevalence of cognitive impairment and associated risk factors 2000\u0026ndash;2015 in S\u0026atilde;o Paulo, Brazil. BMC Geriatr. 2021;21(1):609.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNitrini R, Barbosa MT, Dozzi Brucki SM, Yassuda MS, Caramelli P. Current trends and challenges on dementia management and research in Latin America. J Glob Health. 2020;10(1):010362.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePrina AM, Stubbs B, Veronese N, Guerra M, Kralj C, Llibre Rodriguez JJ, et al. Depression and Incidence of Frailty in Older People From Six Latin American Countries. Am J Geriatr Psychiatry Off J Am Assoc Geriatr Psychiatry. 2019;27(10):1072\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eF\u0026eacute;lix-Beltr\u0026aacute;n L, Seixas BV. Childhood hunger experiences and chronic health conditions later in life among Brazilian older adults. Rev Panam Salud Publica Pan Am J Public Health. 2021;45:e39.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRibeiro FS, Crivelli L, Leist AK. Gender inequalities as contributors to dementia in Latin America and the Caribbean: what factors are missing from research? Lancet Healthy Longev. 2023 June 1;4(6):e284\u0026ndash;91.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWorld Bank. Inequality and Economic Development in Brazil [Internet]. Ferreira FHG, Velez CE, Paes. De Barros R, editors. The World Bank; 2004 [cited 2025 Oct 1]. (Country Studies). Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://documents.worldbank.org/en/publication/documents-reports/documentdetail/456611468744062519/Inequality-and-economic-development-in-Brazil\u003c/span\u003e\u003cspan address=\"https://documents.worldbank.org/en/publication/documents-reports/documentdetail/456611468744062519/Inequality-and-economic-development-in-Brazil\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGacitua-Mario E, Woolcock M, editors. Social Exclusion and Mobility in Brazil [Internet]. The World Bank; 2008 [cited 2025 Oct 1]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://documents.worldbank.org/en/publication/documents-reports/documentdetail/551501468227638533/social-exclusion-and-mobility-in-brazil\u003c/span\u003e\u003cspan address=\"https://documents.worldbank.org/en/publication/documents-reports/documentdetail/551501468227638533/social-exclusion-and-mobility-in-brazil\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBerqu\u0026oacute; E. Considera\u0026ccedil;\u0026otilde;es sobre o envelhecimento da popula\u0026ccedil;\u0026atilde;o no Brasil. In: Velhice e Sociedade. Papirus; 1999.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNicodemo D, Godoi MP. Youth in the 1960\u0026rsquo;s-70\u0026rsquo;s and elderly: case study on feminization and rights of elderly women. Rev Ci\u0026ecirc;nc Em Ext. 2010;6(1):40\u0026ndash;53.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOECD. Towards Improved Retirement Savings Outcomes for Women [Internet]. 2021 Mar [cited 2025 Oct 1]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.oecd.org/en/publications/towards-improved-retirement-savings-outcomes-for-women_f7b48808-en/full-report.html\u003c/span\u003e\u003cspan address=\"https://www.oecd.org/en/publications/towards-improved-retirement-savings-outcomes-for-women_f7b48808-en/full-report.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGarnick D. Gender Retirement Gap [Internet]., Rochester NY. Social Science Research Network; 2016 [cited 2025 Oct 1]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://papers.ssrn.com/abstract=2888911\u003c/span\u003e\u003cspan address=\"https://papers.ssrn.com/abstract=2888911\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCarmel S. Health and Well-Being in Late Life: Gender Differences Worldwide. Front Med [Internet]. 2019 Oct 10 [cited 2025 Oct 1];6. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.frontiersin.org/journals/medicine/articles/10.3389/fmed\u003c/span\u003e\u003cspan address=\"https://www.frontiersin.org/journals/medicine/articles/10.3389/fmed\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.2019.00218/full.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFerreira HG. Gender Differences in Mental Health and Beliefs about Covid-19 among Elderly Internet Users. Paid Ribeir\u0026atilde;o Preto. 2021;31:e3110.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLee KH, Xu H, Wu B. Gender differences in quality of life among community-dwelling older adults in low- and middle-income countries: results from the Study on global AGEing and adult health (SAGE). BMC Public Health. 2020;20(1):114.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLeist AK, Bar-Haim E, Chauvel L. Inequality of educational opportunity at time of schooling predicts cognitive functioning in later adulthood. SSM - Popul Health. 2021 Sept 1;15:100837.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLima-Costa MF, de Andrade FB, de Souza PRB, Neri AL, Duarte YA, de O, Castro-Costa E et al. The Brazilian Longitudinal Study of Aging (ELSI-Brazil): Objectives and Design. Am J Epidemiol. 2018 July 1;187(7):1345\u0026ndash;53.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKatz S, Ford AB, Moskowitz RW, Jackson BA, Jaffe MW. STUDIES OF ILLNESS IN THE AGED. THE INDEX OF ADL: A STANDARDIZED MEASURE OF BIOLOGICAL AND PSYCHOSOCIAL FUNCTION. JAMA 1963 Sept 21;185:914\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLino VTS, Pereira SRM, Camacho LAB, Ribeiro Filho ST, Buksman S. Adapta\u0026ccedil;\u0026atilde;o transcultural da Escala de Independ\u0026ecirc;ncia em Atividades da Vida Di\u0026aacute;ria (Escala de Katz). Cad Sa\u0026uacute;de P\u0026uacute;blica. 2008;24:103\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLawton MP, Brody EM. Assessment of older people: self-maintaining and instrumental activities of daily living. Gerontologist. 1969;9(3):179\u0026ndash;86.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003edos Santos RL, J\u0026uacute;nior JSV. Confiabilidade da vers\u0026atilde;o brasileira da escala de atividades instrumentais da vida di\u0026aacute;ria. Rev Bras Em Promo\u0026ccedil;\u0026atilde;o Sa\u0026uacute;de. 2008;21(4):290\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSandy J\u0026uacute;nior PA, Borim FSA, Neri AL. Solid\u0026atilde;o e sua associa\u0026ccedil;\u0026atilde;o com indicadores sociodemogr\u0026aacute;ficos e de sa\u0026uacute;de em adultos e idosos brasileiros: ELSI-Brasil. Cad Sa\u0026uacute;de P\u0026uacute;blica. 2023;39:e00213222.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eReuben DB, Laliberte L, Hiris J, Mor V. A hierarchical exercise scale to measure function at the Advanced Activities of Daily Living (AADL) level. J Am Geriatr Soc. 1990;38(8):855\u0026ndash;61.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAlvarado BE, Zunzunegui MV, B\u0026eacute;land F, Bamvita JM. Life Course Social and Health Conditions Linked to Frailty in Latin American Older Men and Women. J Gerontol Ser A. 2008;63(12):1399\u0026ndash;406.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKollia N, Caballero FF, S\u0026aacute;nchez-Niub\u0026oacute; A, Tyrovolas S, Ayuso-Mateos JL, Haro JM, et al. Social determinants, health status and 10-year mortality among 10,906 older adults from the English longitudinal study of aging: the ATHLOS project. BMC Public Health. 2018;18(1):1357.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhao B, Liu Z, Fu Y, Zhang H, Wu J, Lai C, et al. Social Determinants of Intrinsic Capacity: A National Cohort Study. Am J Prev Med. 2024;66(3):559\u0026ndash;67.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMasters RK, Link BG, Phelan JC. Trends in education gradients of \u0026lsquo;preventable\u0026rsquo; mortality: A test of fundamental cause theory. Soc Sci Med. 2015;127:19\u0026ndash;28.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePhelan JC, Link BG, Tehranifar P. Social Conditions as Fundamental Causes of Health Inequalities: Theory, Evidence, and Policy Implications. J Health Soc Behav [Internet]. 2010 Oct 8 [cited 2025 Oct 1]; Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://journals.sagepub.com/doi/\u003c/span\u003e\u003cspan address=\"https://journals.sagepub.com/doi/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/0022146510383498\u003c/span\u003e\u003cspan address=\"10.1177/0022146510383498\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKrieger N. Embodiment: a conceptual glossary for epidemiology. J Epidemiol Community Health. 2005;59(5):350\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLanguirand M. Who I was, who I am: Gender and generativity in the assessment of older adults. Handbook of gender and sexuality in psychological assessment. New York, NY, US: Routledge/Taylor \u0026amp; Francis Group; 2016. pp. 578\u0026ndash;602.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAbeliansky AL, Strulik H. Hungry children age faster - ScienceDirect. Economics \u0026amp; Human Biology [Internet]. 2018 [cited 2025 Oct 1]; Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.sciencedirect.com/science/article/pii/S1570677X17302757?via%3Dihub\u003c/span\u003e\u003cspan address=\"https://www.sciencedirect.com/science/article/pii/S1570677X17302757?via%3Dihub\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBeard JR, Hanewald K, Si Y, Amuthavalli Thiyagarajan J, Moreno-Agostino D. Cohort trends in intrinsic capacity in England and China. Nat Aging. 2025;5(1):87\u0026ndash;98.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ede Azeredo Passos VM, Champs APS, Teixeira R, Lima-Costa MFF, Kirkwood R, Veras R, et al. The burden of disease among Brazilian older adults and the challenge for health policies: results of the Global Burden of Disease Study 2017. Popul Health Metr. 2020 Sept;30(1):14.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSarkar SM, Dhar BK, Crowley SS, Ayittey FK, Gazi MAI. Psychological Adjustment and Guidance for Ageing Urban Women. Ageing Int. 2023;48(1):222\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCustodio N, Duque L, Montesinos R, Alva-Diaz C, Mellado M, Slachevsky A. Systematic Review of the Diagnostic Validity of Brief Cognitive Screenings for Early Dementia Detection in Spanish-Speaking Adults in Latin America. Front Aging Neurosci. 2020;12:270.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eIb\u0026aacute;\u0026ntilde;ez A, Pina-Escudero SD, Possin KL, Quiroz YT, Peres FA, Slachevsky A, et al. Dementia caregiving across Latin America and the Caribbean and brain health diplomacy. Lancet Healthy Longev. 2021;2(4):e222\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eParra MA, Baez S, Allegri R, Nitrini R, Lopera F, Slachevsky A, et al. Dementia in Latin America. Neurology. 2018;90(5):222\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePrince MJ, Wu F, Guo Y, Gutierrez Robledo LM, O\u0026rsquo;Donnell M, Sullivan R, et al. The burden of disease in older people and implications for health policy and practice. Lancet Lond Engl. 2015;385(9967):549\u0026ndash;62.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"healthy aging, socioeconomic factors, inequalities, childhood experiences","lastPublishedDoi":"10.21203/rs.3.rs-7879466/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7879466/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eBy 2050, the global population aged 65 years and older is projected to double, reaching 1.5\u0026nbsp;billion, with the most rapid growth occurring in Latin America and the Caribbean. In Brazil, this demographic shift is advancing quickly within a context marked by profound social inequalities and insufficient preparation to address the challenges of an aging society. For this reason, this study aimed to estimate the prevalence of healthy aging in a representative sample of the Brazilian population and explore the role of socioeconomic conditions and adverse childhood experiences.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eWe analyzed data from 9,908 participants aged 50 and older from the 2019\u0026ndash;2021 follow-up of the Brazilian Longitudinal Study of Aging (ELSI-Brazil). Participants were classified into healthy and less healthy aging based on the World Health Organization\u0026rsquo;s multidimensional definition of healthy aging. Logistic regression models were employed to identify sociodemographic and early-life predictors of healthy aging.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eOnly 19.69% of the sample met the employed criteria for healthy aging. Women, older individuals, those self-identifying as mixed race (compared to those self-identifying as White), participants with no schooling or fewer than four years of education, and widowed individuals were more likely to not meet the criteria for healthy aging than their counterparts. Logistic regressions revealed that men are more likely to show healthy aging, as well as younger respondents, those with five years or more of education, and participants receiving two or more minimum wages. With respect to childhood experiences, those reporting poor health and who reported famine during childhood were less likely to meet the criteria for healthy aging.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eThe findings suggest that not only socioeconomic factors but also childhood experiences contribute to disparities in healthy aging in Brazil. These results underscore the importance of implementing early-life health and nutrition programs, advancing gender equity, and improving access to education and economic resources throughout the life course to support healthier aging for future generations.\u003c/p\u003e\u003ch2\u003eClinical trial number:\u003c/h2\u003e\u003cp\u003enot applicable\u003c/p\u003e","manuscriptTitle":"Associations between Socioeconomic Status and Adverse Childhood Experiences with Multidimensional Healthy Aging: Findings from the ELSI-Brazil","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-13 17:44:19","doi":"10.21203/rs.3.rs-7879466/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-12T03:59:34+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-07T05:06:05+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-20T13:38:07+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-17T18:21:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"295678119734303488060140847478813631695","date":"2025-12-17T15:38:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"313763101118866491595271936674568390921","date":"2025-11-29T12:04:39+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"65912863629089993805088213181411409088","date":"2025-11-23T09:49:23+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-11-04T09:30:15+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-10-18T08:13:02+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-17T04:28:18+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-17T04:26:58+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2025-10-16T15:50:31+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"67af3c4b-7b9b-437b-8739-74fdf22b063f","owner":[],"postedDate":"November 13th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-05-04T17:19:21+00:00","versionOfRecord":{"articleIdentity":"rs-7879466","link":"https://doi.org/10.1186/s12889-026-27596-7","journal":{"identity":"bmc-public-health","isVorOnly":false,"title":"BMC Public Health"},"publishedOn":"2026-04-30 15:57:32","publishedOnDateReadable":"April 30th, 2026"},"versionCreatedAt":"2025-11-13 17:44:19","video":"","vorDoi":"10.1186/s12889-026-27596-7","vorDoiUrl":"https://doi.org/10.1186/s12889-026-27596-7","workflowStages":[]},"version":"v1","identity":"rs-7879466","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7879466","identity":"rs-7879466","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}