Introduction

The Latin American population (LA) is aging rapidly, and it is estimated that in the year 2025, approximately 100.5 million older people will live in this region. The Economic Commission of LA and the Caribbean estimates that by the year 2050, 25% of the population (188 million people) will be over 60 years old (1). In addition, the Latin America and Caribbean population are aging faster than those of developed countries (2).

Among the factors related to greater longevity of the older adults, physical activity level stands out. Observational studies have shown that older adults who report lower physical activity levels have a higher risk of mortality, when compared to those who moderate or high physical activity levels (3). However, this information does not provide an accurate estimate of the activity absolute amount (kilocalories / day), and thus cannot be used to determine whether higher levels of activity, resulting in greater energy expenditure, promote advantages in survival of this population (3, 4).

There are highly sensitive yet complex techniques for assessing the daily energy expenditure and body composition accurately and precisely (5), which allow for precise comparisons between countries. Total energy expenditure (TEE) in free living conditions is considered the gold standard for measuring energy expenditure during daily life, and the doubly labelled water (DLW) method is the most accurate method for measuring energy expenditure in free living conditions (6). Water labelled with deuterium and oxygen-18 (“doubly labelled”) is neither radioactive nor toxic in trace amounts. It is a non-invasive method and has been widely used to measure total body water and energy expenditure in individuals (7). It has been shown that the higher total energy expenditure measured by doubly labelled water in free living conditions is associated with the lower risk of mortality in healthy older adults, and that energy expenditure regardless of any activity can influence older adults survival.

Muscle function can also be used to assess the risk of mortality without considering the amount of muscle mass or energy expenditure (3). Newman et al. (8) suggests that reduction in lean mass alone is not a predictor of mortality, and therefore, it cannot explain the association between strength and mortality in isolation. There are other factors that support muscle quality, including composition, metabolism, aerobic capacity, among other conditions, which can also play a role in the muscle function decline and mobility loss associated with aging.

Although different studies have shown association between both energy expenditure and muscle performance with survival, there is a lack of studies verifying potential associations between muscle function and total energy expenditure. If this association is confirmed, a worse performance in standardized tests could indicate lower energy expenditure and support interventions to improve both muscle function and energy expenditure once the latter is difficult to measure with precision in daily clinical practice.

Therefore, the aim our study was to verify the association between the total energy expenditure measured by doubly labelled water and the functional performance of older adults in widely used tests. Our hypothesis was that older adults with lower functional performance would present a lower energy expenditure.

Methods

Design and Study Population

This study was approved by the Human Research Ethics Committee of the Clinics Hospital of the Ribeirao Preto Medical School, University of Sao Paulo (n° 1.059.547) It is part of a cross-sectional study with data from a sample of Brazilian older adults, participants in a multicentre project supported by the International Atomic Energy Agency - IAEA. The study was developed in two phases. A total of 102 older adults participated in the first phase (when socio-economic, clinical, nutritional assessments were performed, as well as the measurement of body composition and performance in functional tests) and from there, a subgroup of 56 individuals were recruited for the second phase (doubly labelled water study and physical activity monitoring, figure 1). Community-dwelling older adults (aged 65 years or over) that were healthy or had stable controlled chronic diseases, without oedema clinically detectable through the Godet sign and able to walk, were included. Exclusion criteria were having malignancies, uncontrolled chronic diseases such as heart failure, kidney failure, stroke sequelae, weight loss greater than 3 kg in the last three months, cognitive impairment identified by the Mini Mental State Examination - MMSE (9) considering the cutoff point for cognitive screening <14 points (10), orthopaedic problems and use of orthoses and orthopedic prostheses that would interfere with gait.

Figure 1
figure 1

How diagram of the participants selection process and the study phases

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Participants were invited to participate in the second phase if they had participated in the first phase more than 30 days before, to avoid residual deuterium labelling (convenience sample, ordered according to the order of participation in the first phase). Participants with any health status change between phases 1 and 2 were excluded (figure 1). This phase was concluded after 56 participants were included and studied.

Data collection was performed from October 2016 to May 2017. The individuals were recruited weekly at a University Health Centre in the city of Ribeirão Preto and at the Geriatrics and Gerontology Outpatient Clinic of the University Hospital.

Demographic, socioeconomic and health conditions assessment

The assessment was performed using a questionnaire containing the following variables: age, marital status, gender, years of study and income. The use of medications was also verified, with the use of 4 or more medications being defined as polypharmacy. The presence of depressive symptoms was assessed by Geriatric Depression Scale (GDS-15) abbreviated from Yesavage, et al. (11) and validated by Paradela, et al. (12).

Anthropometric and body composition characteristics

Weight and height were performed according to the recommendations of Gordon, et al. (13).

The body composition was assessed by isotopic dilution of deuterium oxide. This method is based on stable isotopes and consists of ingesting a deuterium oxide dose and determining, by mass spectrometry, deuterium enrichment in a sample of body water (e.g., saliva). Due to difference in enrichment before and after ingestion of the dose, the total body water is precisely determined (14) by which lean mass can be estimated (15). Each volunteer had an 8-hour overnight fast, and before the dose was administered, a saliva basal sample was collected. After, a fixed dose of 70 ml of 7% deuterium oxide was consumed, followed by 50 ml of water to rinse the mouth, repeating the process thus ensuring that there was no water left in the bottle. Saliva samples were collected before ingesting the deuterium oxide dose (basal) and 3 hours later. Deuterium enrichment was determined by isotopic ratio mass spectrometry (IRMS Hydra, Europa Scientific, Cheshire, United Kingdom).

The fat-free body mass (FFM) calculation was considered by a hydration coefficient of 0.732, therefore, FFM = total body water (TBW) / 0.732 (16). The fat mass (kg) was obtained by difference in total weight (kg) - FFM (kg).

Functional performance and physical capacity assessment

The Lawton and Brody scale (17, 18) was used to assess the older adults autonomy in performing Instrumental Activities of Daily Living (IADL). It includes the following tasks: using the telephone, shopping, preparing meals, housework, washing clothes, using means of transport, handling medication and responsibility for financial matters. The final score results from the sum of the eight IADL scores and varies between 0 and 8 points. The best functional performance corresponds to the highest score.

The gait speed test was assessed through a 4-meter walk at a usual speed, and the time spent on its execution was measured (19). The test was performed in a 7-meter hall, and the central 4 meters were recorded, ensuring the acceleration and deceleration exclusion in the data record. The mean of two trials was considered.

The 6-minute walk test was used to assess walking capacity over long distances. It is a submaximal test related not only to cardiorespiratory fitness and oxygen consumption, but also to the functional status and mobility of the older adults (20, 21). The test was performed in a space of 30 meters in length. Participants were instructed to walk as fast as possible for 6 minutes. During the test, participants were informed that they could, if necessary, reduce speed or even stop to rest, returning to the test, although time is not stopped. Heart rate (HR) and blood pressure parameters were monitored before the test start (10 minutes before the test) and at the test end (end, 2- and 4-minutes post-test). During the test only HR was monitored. The Borg scale (22) was also used to assess the subjective effort after the test. The final measure was considered as being the total distance covered in 6 minutes.

The handgrip strength was measured by using a Saehan® manual hydraulic dynamometer (model SH 5001, Korea), and the protocol followed the American Society of Hand Therapists (ASTH) recommendations (23). Participants were verbally stimulated for 6 seconds, with three measurements taken in both hands, with a one-minute rest between attempts. The highest measured value of the dominant hand was considered (HSmax.).

The time taken to get up from a chair, walk three meters, rotate 180 °, return and sit again, was assessed by “Timed Up and Go test” (TUG) (24). Two measurements were taken and the mean performance, in seconds, was considered.

Total energy expenditure

For the assessment of total energy expenditure, the doubly labelled water (DLW) method was used. It is a type of indirect calorimetry used to assess CO2 production under normal conditions (25), using stable isotopes. This is possible because the isotopes used in this method, 180 and H2 (deuterium) are eliminated as carbon dioxide and water, or just as water in the deuterium case. Thus, the difference measure between the elimination rate of 180 and 2H in urine samples allows to calculation of the CO2 production rate and, therefore, the energy expenditure calculation. Multiple point analysis was used for the evaluations (26). The dose of DLW administered was fixed at 70g (2H2 18O, composed of 66g of 10% H2 18O and 4g of 99.8% 2H2O). The dose was ingested by the participant after a basal urine sample was collected, and subsequent urine samples were obtained from the 1st day to the 14th day after ingesting the dose. Although the method that uses multiple points allows collection on selected days, daily collections were adopted to improve adherence and minimize confusion related to “collection days”. However, only urine samples from the 1st, 2nd, 3rd, 7th, 12th, 13th, 14th day were used in the analyses. Urine samples were analysed by a mass spectrometer (Callisto System, ANCA 20–22, SERCON, Cheshire, United Kingdom) in the Isotopic Ratio Mass Spectrometry laboratory of the Ribeirão Preto Medical School of the University of Sao Paulo, adopting a protocol previously established according to the recommendations of Scrimgeour et al.,; Wong; Lee; Klein, ; Wong; Schoeller, (27–29).

Spontaneous physical activity assessment

The monitoring of habitual physical activity profile was performed using a triaxial accelerometer (ActivPALTM, PAL Technologies Ltd., Glasgow, United Kingdom), able to measure timing sitting, lying, standing, number of steps, number of sitting to standing transitions for seven days and estimating energy expenditure in METs. Monitoring was carried out for 24 continuous hours and 7 consecutive days. After the tracking was finished, the information was transferred via a USB interface to a specific software (version 5.8.2.3 ActivPAL™ Professional, Research edition, ActivPAL™, Glasgow, United Kingdom). For data analysis, the active time of older adults was considered (06:00 to 22:30 - according to the previous interpretation of the data), that is, the sleeping time was excluded. The first and last day of registration (installation and removal of the monitor) were disregarded.

Statistical analysis

Statistical analyses were performed using the STATA 13.0 program and statistical significance was set at p ≤ 0.05. Socioeconomic and health characteristics, body composition, energy expenditure and functional status were summarized using means and standard deviations or frequencies and percentages as appropriate. Differences between groups, divided by sex, were analysed using the t-test or Man-Whitney for continuous variables and Fisher’s exact test for categorical variables, according to type of distribution.

The association between the dependent variable, total energy expenditure and the physical and functional tests (independent variables) was determined using Pearson’s correlation test, followed by Multivariate Regression analysis. The standardized regression coefficient was used to determine the association between variables and each multivariate model was considered significant if p ≤ 0.05. The general performance in the final model was evaluated by the R-square (R2), which estimates the variation in the measures explained by the model.

Results

Participants characteristics

The socioeconomic, demographic, health, anthropometric, body composition characteristics and energy expenditure are shown in table 1. In comparison between the genders, no significant difference was observed among the socioeconomic and health variables. On the other hand, statistically significant differences were found in FFM and FM, with higher FFM in men and higher FM in women.

Table 1 Participants characteristics, by gender and total
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The participants had a mean energy expenditure of 1990 kcal / day. When comparing the sexes, women had significantly lower energy expenditure values than men (p = 0.023).

Functional performance and physical capacity

Considering the functional status, the average of tests scores were within the predicted and values considered good for older adults’ population. In general, the individuals had a walking speed of 1.28 m / s, walked 455.93 meters in the 6-minute walk test and performed the TUG in 9.91 seconds. In addition, they presented a higher score (7.82 ± 0.69) in the Lawton scale, characterizing themselves as independent individuals for IADL. In the comparison between genders, there was no statistical difference in physical and functional tests, except for the HSmax, which were significantly stronger (p <0.001) among men, as described and detailed in table 2.

Table 2 Physical and functional tests of the participants, by gender and total (mean + SD)
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Spontaneous physical activity

Regarding the spontaneous physical activity profile, the participants had an average of 9 hours (9.58 ± 1.99) of an active day in sitting or lying positions, walked about 7,500 steps per day (7562 ± 2633) and had a cost of 25 METs on average (25.09 ± 1.14). In the comparison between genders, women had a higher physical activity level, evidenced by statistically significant differences in sitting or lying time (p = 0.009), in the number of steps (p = 0.022), number of MET’s (p = 0.012). Data is presented in table 3.

Table 3 Spontaneous physical activity profile by gender and total (mean ± SD)
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Total energy expenditure and functional status

Significant and positive correlation was found between total energy expenditure and fat-free mass (r 0.716; p <0.001), walking speed (r 0.266; p = 0.047), 6-minute walk test (r 0.424; p = 0.001) maximum handgrip strength (r 0.478; p <0.001). The higher total energy expenditure, the better the performance in these tests (table 4).

Table 4 Correlation between total energy expenditure and physical and functional tests
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Multiple linear regression was used to verify whether physical and functional tests would be predictors of total energy expenditure. The analysis resulted in a statistically significant model adjusted for sex and fat-free mass (F (9.41) = 11.257; p = 0.000; R2 = 0.712). The 6-minute walk test (β = 1.790; t = 2.080; p = 0.044), and the number of sedentary events (β = 6.389; t = 2.147; p = 0.038) were predictors of energy expenditure (table 5).

Table 5 Multiple linear regression - dependent variable: total energy expenditure
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Discussion

This study verified the association of total energy expenditure with the functional status of older adults, using the doubly labelled water method, which is a “gold standard” tool for measuring energy expenditure in free life. Authors (30, 31) have reported the lack of normative parameters for total energy expenditure in the older adults population, mainly based on studies that use the doubly marked water method. In addition, these authors have reinforced the need for research that investigates the associations between energy expenditure and physical function among older adults. To the authors’ knowledge, this is one of the few studies that verified the possible associations of energy expenditure in free living conditions with the functional performance in standardized tests among older adults. The results showed that higher total energy expenditure correlated with best performance in the gait speed tests, 6-minute walk test and maximum handgrip strength, partially confirming our hypothesis. Multivariate regression model adjusted by sex and fat-free mass revealed association between total energy expenditure and the 6-minute walk test and the number of sedentary events.

It is known that the aging process is associated with a decrease in total energy expenditure, since it results in a decline in the resting metabolic rate and energy expenditure per activity (32, 33). This decrease generates changes in body composition and increases the risk for comorbidities, in addition to cognitive and physical impairments (34, 35). Previous studies (36–39) assessing total energy expenditure in older population found values that ranged from 2011 kcal / day to 2523 kcal / day. These authors used doubly marked water method, although not with the “multiple points” technique used in our study. On the other hand, in a study carried out in Latin America (40) comparing the energy expenditure of institutionalized older adults and in free living conditions with young people aged 27 to 30 years, found a daily total energy expenditure of 1706 kcal / day for those older adults in free living conditions.

In agreement with the literature, our results showed a tendency for men to present a greater energy expenditure in relation to women. This difference can be explained by physiological issues, as well as differences in organ weight or specific metabolic rates of organs that affect the basal metabolic rate differently (41–43); thus, sex is an influencing factor in energy expenditure (44–46). In addition, the difference between genders may be due in part to body mass, mainly due to differences related to composition by fat-free mass (47, 48). In fact, our data showed a strong correlation between fat-free mass and total energy expenditure, supporting this statement.

Regarding functional status, the participants performed well in physical and functional capacity tests, considering the classifications and reference values proposed by the literature. No statistical differences were found between genders in physical and functional tests, except for HSmax, in which greater strength was observed among men. Despite this difference, both men and women achieved mean HSmax above cut-off values established in the literature (men 27 kgf and women 16 kgf) (49). The HSmax is associated with both upper and lower limbs muscular strength (50). The participants also performed well in the physical tests that demand the use of lower limb, reaching values recommended for the older adults population (TUG: 9.4 s; VM: 0.8 m / s) (24, 51).

Observing the walking speed of participants, it can be seen that they walked at a speed higher than the values considered as predictors of negative outcomes such as: reduced mobility, difficulties for IADLs, hospitalizations, cognitive deficit, and frailty (51). In addition, in the 6-minute walk test, participants walked within the predicted range for sex, age, even submitted to submaximal effort, since the 6-minute test is a good predictor of functional status and mortality (52). These results, taken together, suggest that this sample of older adults has good physical and cardiorespiratory fitness.

In our study, an association was observed between physical performance (walking speed; HSmax; 6-minute walk test) and total energy expenditure. This suggests that, in clinical practice, to older adults with poor performance on these physical tests, promoting an increase in total energy expenditure could be important for the prevention of possible problems related to low energy expenditure. Importantly, the 6MWT was significant in the regression model, demonstrating its association with the variability of energy expenditure. This may mean that good cardiorespiratory conditioning really plays an important role in maintaining greater energy expenditure. However, future longitudinal studies are necessary to understand the causal mechanisms of this association.

An interesting result observed in our study was the association of the number of sedentary events with energy expenditure. Interestingly, the number of sedentary events is a variable that is not commonly explored in studies using accelerometery, although many devices provide this data. The number of sedentary events is determined by the number of times the individual leaves the standing posture or walking to a sitting / lying posture, that is, this variable can indicate the number of times the individual fragmented their sitting time. However, only the fragmentation index is commonly used in studies to represent the pattern of SB accumulation, that is, how much the SB is interrupted during an active day. The higher numerical value of this index, the greater number of interruptions in the SB. The fragmentation index (FI) is the ratio between the number of sedentary events and the total sedentary time (53). Although the mean fragmentation index found in our study was high (5.12 + 1.63) when compared with others studies such as that performed by Cardon-Thomas et al., (54) who found an equal FI at 3.1 + 1.0, this variable was not associated with energy expenditure or other clinical variables. Honda et al., (55), in a longitudinal study, observed that individuals with a longer period of prolonged sitting and who had a lower FI, had a higher risk of developing metabolic syndrome, which in turn, is also one of the consequences of low energy expenditure. However, since the number of sedentary events is a component of the FI formula, we must look at this variable more carefully and understand it as a possible influential factor in energy expenditure. As already reported, interruption of SB is a beneficial factor for health in general, for reducing cardiovascular risk and for chronic diseases such as type II Diabetes Mellitus.

Finally, it is necessary to expose some limitations of this study. The sample was composed in its majority by individuals with excellent physical and functional performance caution, being necessary in the extrapolation of data for the older adults population in general. Considering the sample size, two factors must be considered. The high cost of the doubly labelled water assessment technique has limited the number of participants who could be subjected to the procedure. However, because it is a technique of high accuracy and precision in measuring energy expenditure, this bias may have been mitigated. The second factor was the timeframe of the multicentre study that made it impossible to reach the 60 older adults proposed for the second phase. It is also important to highlight that the resistance of men to participate in the research contributed to the lower number in the male group. Finally, the cross-sectional design does not allow the conclusion of the cause-effect relationship from the results.

In conclusion, better physical performance in standardized tests may be associated with higher total daily energy expenditure. Slower gait speed, worst muscle strength and worst performance in the 6-minute walk test may also indicate lower total energy expenditure. Maintaining good physical performance and increasing energy expenditure aim to promote healthy aging, with greater autonomy and better insertion in society, preventing or minimizing the harmful effects of the natural aging process on functional fitness.