Intrinsic capacity and mortality among older adults living in a health microregion of Minas Gerais

Abstract

Objective

To analyze intrinsic capacity and its ability to predict all-cause mortality in older adults living in a health microregion of Minas Gerais state, Brazil.

Method

A household survey study with a quantitative approach was conducted. Data were collected at homes using instruments validated for use in Brazil.

Results

Mean intrinsic capacity score was 5.8 (±1.63) points. During the follow-up period, with a mean follow-up time of 58.0 (±13.1) months, 142 deaths (16.4%) occurred. For each 1 point increase in intrinsic capacity score, there was a 21% reduction in the risk of mortality (p<0.001).

Conclusion

Intrinsic capacity served as a predictor of mortality in older adults.

Keywords
Aged; Healthy Aging; Mortality; Mortality Registries

Resumo

Objetivo

Analisar a capacidade intrínseca e sua capacidade preditiva sobre a mortalidade por todas as causas em pessoas idosas residentes em uma microrregião de saúde de Minas Gerais, Brasil.

Método

Estudo tipo inquérito domiciliar, de abordagem quantitativa. Os dados foram coletados no domicílio com instrumentos validados no país.

Resultados

A média do escore de capacidade intrínseca foi de 5,8 (±1,63) pontos. No período de acompanhamento, com média de tempo de seguimento de 58,0 (±13,1) meses, ocorreram 142 óbitos (16,4%). Observou-se que para cada acréscimo no escore de capacidade intrínseca, ocorreu diminuição do risco de mortalidade em 21% (p<0,001).

Conclusão

A capacidade intrínseca exerceu papel preditivo sobre a mortalidade das pessoas idosas.

Palavras-Chave:
Idoso; Envelhecimento Saudável; Mortalidade; Registros de Mortalidade

INTRODUCTION

In the field of epidemiology, quantitative indicators for describing health outcomes and their respective risk factors are indispensable, also helping to plan actions and designate public health resources¹. Mortality is one of the most commonly used measures in practice ²,³ and expresses the total number of deaths resulting from the health event assessed².

Mortality can be expressed in terms of proportions, rates or absolute numbers, and can provide not only demographic and geographic information, but also cause of death³. These data are useful because the age structure of the population is still undergoing a process of change¹ and indicators are needed to help characterize the evolution and intensity of repercussions of health events² in specific age groups, such as older adults.

One of the main lines of investigation in studies on mortality is cause of death by age group⁴. Specifically in older individuals, the presence of chronic diseases is considered one of the leading causes of death⁵, since age-related changes can cause a progressive decline in functions of organic systems, increasing predisposition to chronic health conditions, with consequent reduction in intrinsic capacity and, ultimately, death⁶.

Intrinsic capacity represents the composite of physical and mental capacities of an individual⁷, comprising the inter-related domains of cognition, psychological, sensory, locomotion and vitality⁷–⁹. It is regarded as a multi-dimensional indicator related to functional status, which can be used in planning and assessment of health care models recommended in the guidelines of the World Health Organization (WHO) on integrated care for older people⁷,⁹.

Thus, there is evidence that intrinsic capacity, as a composite score and/or its domains, predicts negative outcomes in community-dwelling older adults, such as transition of frailty conditions¹⁰, functional disability for activities of daily living ¹¹–¹³, time in long-term care facilities¹² and occurrence of falls¹³,¹⁴. However, where the death outcome is concerned, there is a dearth of studies investigating these pooled components among community-dwelling older adults¹⁵–¹⁷and knowledge gaps exist on the predictive value of intrinsic capacity for mortality, especially in Brazil, where no investigations on the subject were found.

Given the gap in scientific knowledge on the subject, the objective of the present study was to analyze intrinsic capacity and its ability to predict all-cause mortality in older adults living in a health microregion of Minas Gerais state, Brazil.

METHOD

An analytical, quantitative study was conducted, guided by the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) tool and drawing on the observable variables from the database of the project “Envelhecimento Ativo, Funcionalidade Global e Qualidade de Vida entre idosos da Microrregião de Saúde de Uberaba (MG)” (Active Aging, Global Functioning and Quality of Life among older Adults from the Uberaba health microregion) by the Public Health Research Group. The cited study was based on a multiple-stage cluster sample of 977 older adults interviewed in 2018. The sample included individuals aged ≥60 living in the urban area of the Health Microregion of Uberaba (Minas Gerais state), Brazil. Individuals exhibiting severe stroke complications with aphasia and localized loss of strength in upper and lower limbs; severe or unstable Parkinson´s disease with major impairment of motricity, speech or affectivity; and subjects with cognitive decline, were excluded. Cognitive decline was defined as having a classification of decline on the Mini-Mental State Exam (MMSE)¹⁸, and not having an informant to answer the Pfeffer Functional Activities Questionnaire (FAQ)¹⁹ and/or attaining a final score ≥6 points on the scale¹⁹.

Analysis of the database showed that, of the 977 older adults interviewed, 31 had cognitive decline on the Pfeffer FAQ and failed to complete the full interview. Thus, the base reference sample for the 2nd phase comprised 941 older adults, determined after adjusting for all deaths that had occurred between 31 January 2018 and 31 January 2023. On the living status follow-up, 77 participants were excluded, comprising 38 not found after 3 attempts at contact and 39 for absence of telephone (n=39). Thus, the final study sample included 864 older adults.

The initial data were collected during home visits by direct interview and by applying tests of physical performance using scales validated for use in Brazil. Ten interviewers from the health area were selected and underwent training, trials and received information on ethics issues related to the study. The interviewers were trained by the researchers from the research group and overseen until displaying competence in applying the scales.

Sociodemographic and economic data, along with number of morbidities, were collected using a structured questionnaire devised by members of the Public Health Research Group based on the scientific literature.

Intrinsic capacity was assessed for the domains cognition, psychological, sensory, locomotion and vitality⁷,⁹.

The cognitive domain was assessed by applying the MMSE, translated and validated for use in Brazil¹⁸, which provides information on different cognitive parameters. The score ranges from 0 points, indicating highest degree of cognitive impairment of the individual, to 30 points, indicating best cognitive capacity¹⁸.

The psychological domain was measured using the Short Form Geriatric Depression Scale (GDS-15) validated for use in Brazil, which has 15 items and an overall score ranging from 0 to 15 points²⁰.

Locomotion was assessed using the Brazilian version of the Short Physical Performance Battery (SPPB), comprising the sum of points on balance, gait speed and chair stand tests²¹. Total score ranges from 0 (disability) to 12 (best performance) points²¹. Subjects scoring 0-3 points were classified as having disability; 4-6 points, low physical performance; 7-9 points, moderate physical performance; and 10-12 points, good physical performance²¹. Thus, higher scores on the SPPB indicate greater physical performance.

With regard to the sensory domain, this was measured by posing the question: “How do you rate the functioning of your hearing, vision, taste, smell and touch?” with respondents choosing from the following options: very good, good, fair, poor and very poor.

The vitality domain was measured based on the following items: unintentional weight loss; exhaustion/fatigue; hand-grip strength; and body mass index (BMI), probed as follows: unintentional weight loss was assessed by the question: “In the past year, have you unintentionally lost more than 4.5kg or 5% of your body weight?”. Self-reported exhaustion/fatigue was measured using items 07 and 20 from the Brazilian version of the Center for Epidemiologic Studies Depression Scale. Participants scoring 2 or 3 on any of the questions met the criteria for this item²².

Decline in muscle strength was determined according to hand-grip strength, measured using a Jamar Saehan® hydraulic hand dynamometer. The recommendations of the American Society of Hand Therapists were adopted: the participant was seated comfortably on a chair without arm rests and both feet flat on the floor, shoulders adducted, elbows flexed to 90 degrees, and forearms neutral, and thumbs raised upward; and wrists in a comfortable position extended to 0-30º; with handle position II elected. The examiner provided a loud verbal stimulus prompting the subject to pull the dynamometer handle using their dominant hand, squeeze for 6 seconds and then relax. Three measures were obtained, expressed in kilograms/force (kgf), with a 1-minute interval between tries and mean value recorded²³.

Body weight was measured using a portable digital balance with a capacity of 150 kg and accuracy to the nearest 100 g. The subject wore light clothes and removed footwear. Height (m) was measured using a 2-meter flexible, inelastic measuring tape, with graduations in centimeters and subdivisions in millimeters, affixed to the wall in an area with a flat level floor without skirting board. With footwear removed, the subject was placed in an orthostatic position with feet together and their back against the marker and gaze to the horizon. BMI was calculated using the formula: BMI = weight (kg) / [height]² (m). Nutritional status was classified according to the following BMI cut-off values: underweight (≤22 kg/m²), normal weight (>22 and <27 kg/m²) and excess weight (≥27 kg/m²)²⁴.

Regarding deaths, this information was obtained by consulting the burial system of the City Authorities of Uberaba, Minas Gerais, Brazil²⁵ and the National Deaths Registry²⁶. In the event of doubts or disparities concerning the exact registry, telephone calls were made to the residence of the person in question using the contact number given at the time of data collection.

The sociodemographic variables collected were: sex (female; male); age group, in years (60├70; 70├80; ≥80; mean full years of life); education, in full years of formal study (none; 1├5; ≥5; mean full years of study); morbidities (0; 1├5; ≥5; mean number of morbidities) and death (yes; no). The variables measuring intrinsic capacity domains were represented on the same scale of values (1-10)²⁷. For cognitive capacity, a value of 1 was assigned to the lowest score on the MMSE (19 pontos), a value of 2 to the next, and so forth. The value of 10 was attributed for scores 28, 29 and 30. Scores on the GDS-15 (psychological capacity) ranging from 0 to 10 were used without modification, while a value of 10 was attributed for higher scores. These scores were subsequently transformed using the formula: score on GDS-15 =11 – original score. For the locomotion capacity, the values for classifications of physical performance were assigned: 1 for disability/poor; 3.5 for low ; 7.5 moderate; and 10 good. Similarly, for sensory capacity values were: 1 for very poor/poor; 3.5 for fair; 7.5 for good; and 10 for very good. Values assigned for the vitality domain variables were: unintentional weight loss, 0 for yes and 1 for no; the same for hand-grip strength (0 – decline; 1 – no decline), exhaustion/fatigue (0 – yes; 1 – no) and BMI (0 – normal weight; 1 – underweight/excess weight). Based on the values for each variable, vitality score was derived using weighting of indicators: unintentional weight loss x4; hand-grip strength x3; exhaustion/fatigue x2; BMI x1, such that final score ranged from 0 to 10²⁷. Final intrinsic capacity score was calculated as the arithmetic mean of scores on each domain, represented on a scale of 1 to 10²⁷.

The data were treated using descriptive analysis, with categorical variables expressed as absolute and relative frequency, and quantitative variables as mean and standard deviations. Analysis of intrinsic capacity and its value for predicting all-cause mortality was carried out using a fitted multivariate Cox regression model to calculate hazard ratios (p<0.05).

The project was approved by the Ethics Committee for Research in Humans of the Universidade Federal do Triângulo Mineiro (UFTM), under permit no. 2.053.520. Participants were explained the study goals and provided with pertinent information and the Free and Informed Consent Form. After agreement by participants to take part and signing of the form, interviews were conducted in compliance with Resolution no. 466/2012 of the National Board of Health, Ministry of Health.

RESULTS

Of the 864 participants studied, most were female (67.1%), aged 70├79 years (41.7%), had education of 1├4 years (52.5%) and ≥5 morbidities (67.6%) (Table 1).

Table 1
Distribution of sociodemographic and health variables of older adults (N = 864) living in the urban area of a health microregion of Minas Gerais state, Brazil, 2018.

Variables	n (%)	Mean and Standard Deviation
Sex
Male	284 (32.9)
Female	580 (67.1)
Age group (in full years)
60├ 69	324 (37.5)
70├ 79	360 (41.7)
≥80	180 (20.8)
Age (in full years)		73.2(±8.0)
Education (in full years)		4.5(±3.9)
None	151 (17.5)
1├ 4	454 (52.5)
≥5	259 (30.0)
Morbidities		6.5(±3.4)
None	12 (1.4)
1├ 4	268 (31.0)
≥5	584 (67.6)

Regarding cognitive capacity, mean score on the MMSE was 25.0 (±3.8) points. The assessment of psychological capacity showed that 24.0% of participants exhibited signs of depressive symptoms. For locomotion capacity, most participants had good physical performance (39.1%). On the evaluation of sensory capacity, the majority of participants rated the functioning of their senses as good (52.4%). For the vitality domain, 13.3% had unintentional weight loss, 37.2% exhibited reduced hand-grip strength; 36.9% exhaustion/fatigue and 44.2% excess weight (Table 2). Mean intrinsic capacity score was 5.8 (±1.6) points (Table 2).

Table 2
Distribution of intrinsic capacity domains and scores of older adults (N = 864) living in the urban area of a health microregion of Minas Gerais state, Brazil, 2018.

Variables	n (%)	Mean and Standard Deviation
Cognitive capacity		6.9(±3.1)
Psychological capacity (indicative of depressive symptoms)		7.3(±2.8)
Yes	207 (24.0)
No	657 (76.0)
Locomotion capacity (physical performance)		7.2(±3.0)
Poor	94 (10.9)
Low	109 (12.6)
Moderate	323 (37.4)
Good	338 (39.1)
Sensory capacity (functioning of senses)		6.2(±2.7)
Very poor/poor	110 (12.7)
Fair	187 (21.6)
Good	453 (52.4)
Very good	114 (13.3)
Vitality		6.9(±2.5)
Unintentional weight loss
Yes	115 (13.3)
No	749 (86.7)
Reduced hand-grip strength
Yes	321 (37.2)
No	543 (62.8)
Exhaustion/Fatigue
Yes	319 (36.9)
No	545 (63.1)
Body Mass Index
Underweight	213 (24.7)
Normal weight	269 (31.1)
Excess weight	382 (44.2)
Intrinsic capacity		5.8(±1.6)

During the mean follow-up time (58.0±13.1 months) for the study, there was a total of 142 deaths (16.4%).

With regard to the ability of intrinsic capacity to predict mortality, for every additional point on intrinsic capacity score, the risk of mortality was reduced by 21% (p<0.001). Moreover, female gender (p<0.001) and advanced age (p<0.001) were associated with greater risk of death (Table 3).

Table 3
Final Cox regression model for intrinsic capacity score for death in older adults (N = 864) living in the urban area of a health microregion of Minas Gerais state, Brazil, 2018-2023.

Variables	Death
	HR	CI (95%)	p*
Intrinsic capacity	0.79	0.71-0.88	<0.001
Age	1.05	1.03-1.07	<0.001
Morbidity	1.04	0.99-1.09	0.063
Sex
Male	1**	-	-
Female	1.87	1.33-2.63	<0.001

• HR: Hazard Ratio; CI: Confidence Interval; * p<0.05; ** 1 – reference value.

DISCUSSION

The aim of the present investigation was to analyze intrinsic capacity and its value for predicting all-cause mortality in older adults. Taken together, the results revealed that a higher composite score for intrinsic capacity was associated with a lower risk of mortality. To our knowledge, this is one of the first studies to investigate the effect of intrinsic capacity and other predictors on all-cause mortality in Brazilian community-dwelling older adults. To this end, the present study adopted the domains suggested by the WHO⁷ and used a similar approach to previous studies¹²,¹⁶,²⁸–³⁰, only with some differences in instruments and form of scoring.

The mean intrinsic capacity score found in this study was lower than the value reported in an earlier survey based on data from the Rede de Pesquisa e Fragilidade em Idosos do Brasil (Research Network and Frailty in Brazilian Older Adults)²⁷. In this context, it should be noted that older adults with low composite score, or classified as having impaired intrinsic capacity, also have higher risk of death¹²,¹⁵–¹⁷,²⁸–³².

The present study showed that 16.4% of the participants had died over the period, a similar rate to that found by the 10/66 Dementia Research Group (DRG). The cited investigation was conducted in geographic areas of 8 different countries, and found that 18.4% of the 14,923 participants had died within a period averaging 4.2 years³¹. During a 3-year follow-up of 220 Chinese older adults aged ≥75 years, 11.8% of the participants died³².

The main finding of the present study was a 21% reduction in mortality for every 1-point increase in intrinsic capacity score. A lower result was identified in the I-Lan Longitudinal Aging Study (ILAS), where an increase of 1 percentage point in intrinsic capacity score for 5 domains was associated with a 5% lower mortality hazard ratio (HR=0.95; 95%CI 0.93-0.97)²⁸. A study of 754 older adults in North America showed a 5% increase in the hazard ratio of death for every 1-point reduction in intrinsic capacity, comprising the 5 domains cognition, vitality, mobility, psychosocial and sensory¹².

In Belgium, an increase of 1 standard deviation in the Z-score of intrinsic capacity was associated with a 49% decrease in risk of death (HR=0.51; 95% 0.36-0.72)¹⁵. Despite this finding, the study noted that the sensory domain could not be assessed because of missing data, and so results apply only to the cognition, nutrition, mobility and psychosocial domains¹⁵.

Two studies which adopted the domains recommended by the WHO for intrinsic capacity (cognition, locomotion, sensory, psychological and vitality) also found an association of the construct with death¹⁶,³⁰. In Taiwan and China, individuals with low intrinsic capacity had a 2.19 and 2.56 times greater hazard ratio for death, respectively, compared to the high intrinsic capacity group¹⁶,³⁰.

Although the WHO defines 5 domains for intrinsic capacity⁷, previous studies have shown differences in the way each of these is assessed in terms of instruments employed ¹⁵,³³ and composite score calculation, possibly explaining the disparity in findings¹²,²⁹. In addition, there are numerous other factors that can contribute to decline in intrinsic capacity³⁴,³⁵ and impact the life course from birth to death⁹.

Despite the issues outlined, the body of scientific evidence suggests that intrinsic capacity plays a role in contributing to a high hazard ratio for mortality in community-dwelling older adults¹²,¹⁵,¹⁶,²⁸–³⁰, as demonstrated in the present study. The concept of intrinsic capacity is a key concept for promoting health aging⁶,⁷ and considered a better predictor of adverse health outcomes than the presence of comorbidities³².

The study has some limitations which should be taken into account when interpreting its findings. First, no tracking of intrinsic capacity at different timepoints was carried out, precluding the identification and elucidation of trajectories or the occurrence of possible changes. Second, there are issues in relation to the domains, such as sensory, in that these were obtained via self-report, potentially distorting results. Third, given that intrinsic capacity was regarded as a composite construct, no individual analysis of the effect of the different domains on the outcome was performed. Fourth, despite adoption of the intrinsic capacity domains according to the WHO, there were differences in the instruments. Nevertheless, strengths of the present study include the fact that the sample was a population of older adults living in the community, representing a potential target of interventions for promoting healthy aging. Further, given the study was conducted in a developing country, it can provide information for other regions with a similar profile and help inform the planning of individual and collective actions.

CONCLUSION

Intrinsic capacity played a predictive role regarding mortality among community-dwelling older adults, even after adjusting for potential confounding variables, showing that increased intrinsic capacity score was associated with a reduced risk of death.

Therefore, intrinsic capacity should be assessed and followed in communities and households so that declines, even if slight, can be detected and factored into individualized care plans. Hence, adverse health outcomes, such as mortality, can also be either averted or delayed.

• Funding: Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq). Under process no.: 303907/2022-3.

• DATA AVAILABILITY

  The dataset underpinning the study results are available upon request from the corresponding author.

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Edited by

Edited by: Letícia Sampaio Figueiredo

Data availability

The dataset underpinning the study results are available upon request from the corresponding author.

Publication Dates

• Publication in this collection
  08 July 2024
• Date of issue
  2024

History

• Received
  04 Dec 2023
• Accepted
  29 Apr 2024