Effects of aging on resting metabolic rate: A systematic review and - Brazilian Journals
←
→
Page content transcription
If your browser does not render page correctly, please read the page content below
Brazilian Journal of Health Review 17867
ISSN: 2595-6825
Effects of aging on resting metabolic rate: A systematic review and
meta-analysis
Efeito do envelhecimento na taxa metabólica de repouso: uma revisão
sistemática e meta-análise
DOI:10.34119/bjhrv4n4-266
Recebimento dos originais: 20/07/2021
Aceitação para publicação: 20/08/2021
Paulo Roberto Hernandes Júnior
Graduando em Medicina pela Universidade de Vassouras
Instituição: Universidade de Vassouras
Endereço: Av. Expedicionário Oswaldo de Almeida Ramos, 278, Centro, Vassouras,
RJ, Brasil, CEP: 27700-000
E-mail: paulorh.eng@gmail.com
Bruno Carvalho Brandão
Graduando em Medicina pela Universidade de Brasília
Instituição: Universidade de Brasília
Endereço: Campus Darcy Ribeiro, s/n, Asa Norte, Brasília, DF, Brasil, CEP: 70910-900
E-mail: bruno109medunb@gmail.com
Patrick de Abreu Cunha Lopes
Instituição: Universidade de Vassouras
Endereço: Av. Expedicionário Oswaldo de Almeida Ramos, 278, Centro, Vassouras,
RJ, Brasil, CEP: 27700-000
E-mail: patrick.abreu33@gmail.com
Amanda Veiga Sardeli
Doutora, pela Universidade Estadual de Campinas
Instituição: University of Birmingham
Endereço: Mindelsohn Way, Queen Elizabeth Hospital Research Labs, Birmingham,
Reino Unido, CEP: B15 2WB
E-mail: amandavsardeli@gmail.com
Paula Pitta de Resende Côrtes
Mestre, pela Universidade Federal Fluminense
Instituição: Universidade de Vassouras
Endereço: Av. Expedicionário Oswaldo de Almeida Ramos, 278, Centro, Vassouras,
RJ, Brasil, CEP: 27700-000
E-mail: paulapitta@yahoo.com.br
Brazilian Journal of Health Review, Curitiba, v.4, n.4, p.17867-17882 jul./aug. 2021Brazilian Journal of Health Review 17868
ISSN: 2595-6825
ABSTRACT
Objective. To meta-analyze previous literature in order to find a consensus regarding
aging effects on resting metabolic rate (RMR) and to identify the main players in this
process. Methods. Through a search on PubMed eighteen trials comparing RMR between
older and young adults were included for meta-analysis. Results. Older adults had
significantly lower RMR than young adults (-437 kJ/d [-591; 283], pBrazilian Journal of Health Review 17869
ISSN: 2595-6825
determining component of living. The theoretical expectation that individuals who are
most efficient at utilizing energy should survive the longest has been shown by the
negative association between RMR and longevity 2–4. In fact, when RMR is adjusted for
age, sex, and body composition, lower RMR predicts health and longevity, suggesting
that higher RMR is a risk factor for mortality in humans 3,5.
On the other hand, in human cohort studies show that aging per se reduces RMR,
which is contradictory to previous information, given that aging is the main independent
risk factor for mortality 6. Furthermore, not all studies agree that older adults have lower
RMR than young individuals. The variation in those differences may be related not just
by the known differences in RMR between men and women, but also due to differences
in body composition among older and young adults among the studies.
It is noteworthy that transient increases in metabolic rate promoted by physical
7,8
activity, for example, are expected to be beneficial . However, the persistently higher
basal metabolic rate may be harmful, accelerating the disease progression and anticipating
mortality 3,9.
Many confounding factors such as sex and body fat may lead to these inconclusive
results. Thus, the aim of this study is to meta-analyze previous literature in order to find
a consensus regarding aging effects on RMR, restricting the comparison to health subjects
at baseline condition. The results of this meta-analysis will support a wide range of
research focusing on metabolism, health, and longevity.
2 METHODS
This review was reported according to PRISMA (Preferred Reporting Items for
systematic Reviews and Meta-Analyses) Guidelines 10.
SEARCH STRATEGY
The search on PubMed was performed in February 2020. The search combined
the synonyms of aging and metabolism, in which the controlled descriptors were searched
accordingly (MeSh) and the non-controlled descriptors were searched in the titles and
abstracts of the studies. The search targeted cross-sectional studies comparing resting
metabolic rate assessed by indirect calorimetry between young and older adults. There
was no restriction for date of publication, nonetheless only studies written in English
language were selected.
Brazilian Journal of Health Review, Curitiba, v.4, n.4, p.17867-17882 jul./aug. 2021Brazilian Journal of Health Review 17870
ISSN: 2595-6825
STUDY SELECTION
Two reviewers worked on the selection of studies, considering the following
inclusion criteria: (Population) healthy adults; (Intervention/effect) age difference
between groups; (Comparator) younger group; (Outcome) Resting metabolic rate; (Study
type) Observational studies. The exclusion criteria were not original studies, not assessing
resting metabolic rate, comparing children or teenagers, not English Language, animal
study, acute effects, not testing ageing effects, and no access to full texts. Resting
11,12
metabolic rate assessed by equation estimates were not accepted to minimize bias
since these equations are not as reliable as indirect calorimetry 13,14. Details of this process
are described in Figure 1.
DATA COLLECTION
The data collection was performed by two independent reviewers. Means and a
measure of dispersion (standard deviation, standard error or 95%CI) of age and resting
metabolic rate were extracted for each age group. Mean, standard deviation (SD) and
sample number (n) were used for RMR analysis. Standard error (SE) was converted to
SD by the equation SD = SE × (√n) , if SD had not been provided in the original study.
The 95% confidence intervals were converted to SD considering the equation (√n ∗
(UL − LL)/[2 ∗ T. INV (0.05; n − 1)] , where n is the sample size, UL is the upper limit,
LL is the lower limit and T. INV is the function that calculates the left-tailed inverse of the
Student’s T distribution 15.
Most studies presented their results in kilojoule per day (kJ/d) and thus the main
results were presented in this unit measurement. When studies presented data in
kilocalorie per minute (kcal/min), it was converted to kJ/d by considering 1 kcal is equal
to 4.184 kilojoules, thus the equation was kJ/d = kcal/min * 6024.96 16.
For subgroup analysis, first, the difference between groups within each study for
mean age and body mass were calculated. These mean differences were clustered in
subgroups of “40yrs” according to proximity of the mean
differences.
Brazilian Journal of Health Review, Curitiba, v.4, n.4, p.17867-17882 jul./aug. 2021Brazilian Journal of Health Review 17871
ISSN: 2595-6825
STATISTICAL ANALYSIS
The outcome measurement was the raw mean difference in resting metabolic rate
(kJ/day) between older and young adults, with its respective 95% of confidence interval.
One main meta-analysis was performed using Comprehensive Meta-Analysis
software, version 3.3.070. When there was statistical significance for heterogeneity,
randomized effect models were selected and when there was no statistical significance
for heterogeneity, fixed effect models were selected. The inconsistency between studies
was presented as a percentage (I2), based on difference between expected heterogeneity
(df) and true heterogeneity (Q-value). Egger's tests were performed to check the risk of
publication bias in each meta-analysis 17.
Subgroup analyses were performed to compare sex (men and women), body mass
difference between groups (40yrs). Q tests were applied to group comparisons,
considering 95% confidence. Regression analyses were performed using one single
model for each continuous body composition variables: body mass, body mass index
(BMI), fat mass and fat free mass.
QUALITY OF THE EVIDENCE
The quality of evidence was assessed by GRADE approach, considering the
evaluation items for observational studies for each of the 3 meta-analyses 18. For meta-
analysis of observational studies, we begin with 2 points and add one or two points
according to effect size, dose-response gradient, and positive influence of confounding
factors. It will lead to a quality of evidence that ranges from very low (≤1) to high (4).
3 RESULTS
From 198 records initially identified, 5 studies leading to 18 subgroups comparing
the baseline metabolism in KJ/min or KJ/day between young and older adults were
included in the meta-analysis. Details of the selection of studies can be seen on Figure 1.
Brazilian Journal of Health Review, Curitiba, v.4, n.4, p.17867-17882 jul./aug. 2021Brazilian Journal of Health Review 17872
ISSN: 2595-6825
Figure 1. Flow diagram of studies selection. Legend: RMR: resting metabolic rate.
The studies included very different sample sizes in each group; with age
differences varying from right next year to 40 years difference; men, women and mixed
samples (Table 1). Table 2 shows the exact body mass difference between older and
younger ones in each study subgroup, that varied from around 2kg to near 10kg and were
clustered for analysis. The differences in other body composition components between
older and young adults were not clustered in categorical variables, but since they were
tested in regression analysis, their continuous differences used for analysis are detailed
on table 2.
All studies assessed RMR by indirect calorimetry, using open-circuit which is a
13,14
widely accepted method of measuring RMR . The assessments lasted from 25 to 45
min, in thermoneutral environments and, despite many studies did not describe their
orientation for participants fasting and refraining from physical activity, it is expected
that they recommended it as part of the RMR protocols. Usually, the first minutes of data
are discarded, and the remaining ones must be averaged to the final value of resting
19
metabolic rate. Weir formula was used to determine the energy equivalent of oxygen
volume in all studies.
Brazilian Journal of Health Review, Curitiba, v.4, n.4, p.17867-17882 jul./aug. 2021Brazilian Journal of Health Review 17873
ISSN: 2595-6825
Table 1. General characteristics of the studies included. Legend: B: Both sexes; M: Men; NR: not reported; W: women; diff: mean difference category between groups.
First author, year Subgroups Older Younger Age (y) Sex
Mean SD RMR n Mean SD RMR n Older Younger diff
RMR (KJ/d) RMR (KJ/d)
(KJ/d) (KJ/d)
Krems, 2005 Men 6720 686 84 7867 936 67 68.9 (5.1) 26.8 (3.4) >40 M
Krems, 2005 Women 5455 685 132 5809 680 159 69.9 (5.5) 24.8 (3.0) >40 W
Luhrmann, 2010 Men 6517 677 55 6809 704 55 76.3 (5.2) 66.3 (5.2) Right M
next
Luhrmann, 2010 Women 5476 697 107 5566 599 107 76.3 (5.2) 66.3 (5.2) Right W
next
Krems, 2004 Men 6353 725 107 7371 945 67 66.9 (5.1) 26.8 (3.4) >40 M
Krems, 2004 Women 5118 609 178 5374 560 154 67.8 (5.7) 24.8 (3.0) >40 W
Lührmann, 2002 Men (65-69yrs) 6762 881 38 6978 746 40 65-69 75Brazilian Journal of Health Review 17874
ISSN: 2595-6825
Table 2. Body composition of the studies included. Legend: NR: not reported; diff: mean difference between groups.
First author, year Subgroups Body mass (kg) BMI (kg/m2) fat mass (kg) Fat free mass (kg)
Older Younger diff Older Younger diff Older Younger diff Older Younger diff
Krems, 2005 Men 77.7 77 (9.6)Brazilian Journal of Health Review 17875
ISSN: 2595-6825
Alfonzo-González, Both (40-49.9yrs) 79.0 71.2 (19.6)Brazilian Journal of Health Review 17876
ISSN: 2595-6825
The 18 groups of comparison led to significant reduction of RMR in older adults
compared to younger ones (Figure 2). It was significantly heterogeneous (pBrazilian Journal of Health Review 17877
ISSN: 2595-6825
Table 3. Subgroup analysis. Legend: k= number of study groups; RMD=raw mean difference (KJ/day); p-
value = p-value for significance (PBrazilian Journal of Health Review 17878
ISSN: 2595-6825
the statistically significant and progressively higher magnitude of RMR reduction with
higher age differences between groups.
Despite changes in body mass account for some RMR reduction, the main reason
20
for this reduction might be the muscle mass loss . In fact, there is a strong correlation
between RMR and muscle mass, which is the main variable used to indirectly predict
RMR 20. The influence of muscle mass on RMR was also confirmed by our regression
analysis. While body mass, BMI, fat mass and even the age difference per se did not
explain the RMR difference between older and younger ones, muscle mass difference
significantly predicted it. Additionally, despite both men and women undergo muscle loss
along aging, men have greater relative and absolute muscle mass than women, and thus
it makes sense that men undergo a more prominent reduction (slope 0.18; women slope:
0.08) across lifespan 20,21.
Muscle loss becomes more evident after the 40th decade, mediated by mechanics
involving: (1) reduced number of satellite cells and its capability to proliferate; (2) loss
of balance between protein synthesis and degradation and responsiveness of anabolic
stimulus from nutrients; (3) infiltration of fat and connective tissue, reducing quality of
muscle and increasing stiffness; (4) changes in motor units axions and fiber type; (5)
increased production of reactive oxygen species and blunted antioxidant system; (6) and
inflammation in aging muscle, via production of cytokines which also increases ROS 22.
In this way, even among individuals who maintain exercise across the whole life span,
reduction in muscle mass is inevitable.
The maintenance of physical activity along the life span could be another factor
mediating age-induced reduction. The lower level of physical activity among older adults
is well known 23, Given the importance of muscle mass within this scenario, American
college of sports medicine have highlighted that not just the general physical activity
maintenance is important for older adults, but resistance training would be fundamental
24
to regulate RMR . They state that, although the energy expenditure associated with
resistance training is not large, increased muscle mass through resistance training is
24
determinant to increase RMR . The benefits of physical activity on RMR are
incompletely understood, nevertheless, exercise may prevent or at least attenuate
important age alterations such as increased oxidative stress, shifting of energetic needs
for other homeostatic mechanisms, rising catabolic state associated with weight loss, and
chronic fatigue 5.
Brazilian Journal of Health Review, Curitiba, v.4, n.4, p.17867-17882 jul./aug. 2021Brazilian Journal of Health Review 17879
ISSN: 2595-6825
Despite higher body mass might suggest higher muscle mass, it is very common
25
that obese individuals have also lower muscle mass than they pairs . The age-related
26
shifts in body composition that induce sarcopenia favor the development of obesity ,
which might explain the higher frequency of sarcopenic obesity among older adults. In
this way, we believe the association we found between larger body mass and lower RMR
in subgroup analysis is due to the lower muscle mass in heavier individuals. Furthermore,
since our regression analyses did not show association with body mass, or fat mass, but a
significant positive association with fat free mass difference between older and young
adults and their RMR difference (r2=0.55), it reinforces that muscle mass plays a
considerable role on aging RMR changes. Indirectly, our results suggest that therapies
designed to increase muscle mass such as exercise training, protein or other types of
supplementations could attenuate the reduction of RMR with age27,28.
A limitation of our analysis was the sample overlapping in some control groups,
11
such as in the studies of Lührmann et al. and Alfonzo-González et al. 29. It led to an
impression of larger sample number in younger control groups, but the number of older
and young adults in each group were in fact very well balanced.
5 CONCLUSION
RMR is progressively lower in older compared to younger adults, with a more
prominent reduction in men than women. The main player in this process is the age-
induced muscle loss. Future studies should investigate how much of this reduction can
account for poor health conditions in older adults and whether interventions for increase
muscle mass, such as resistance exercise could be a good strategy to oppose the natural
changes.
Brazilian Journal of Health Review, Curitiba, v.4, n.4, p.17867-17882 jul./aug. 2021Brazilian Journal of Health Review 17880
ISSN: 2595-6825
REFERENCES
1. Rubner M. Machinery of metabolism. JAMA J Am Med Assoc. 1916;66(24):1879.
2. Jumpertz R, Hanson RL, Sievers ML, Bennett PH, Nelson RG, Krakoff J. Higher
energy expenditure in humans predicts natural mortality. J Clin Endocrinol Metab
[Internet]. 2011 Jun [cited 2021 Mar 29];96(6). Available from:
https://pubmed.ncbi.nlm.nih.gov/21450984/
3. Ruggiero C, Metter EJ, Melenovsky V, Cherubini A, Najjar SS, Ble A, et al. High
basal metabolic rate is a risk factor for mortality: The Baltimore Longitudinal Study of
Aging. Journals Gerontol - Ser A Biol Sci Med Sci [Internet]. 2008 [cited 2020 Nov
12];63(7):698–706. Available from: https://pubmed.ncbi.nlm.nih.gov/18693224/
4. Lotka AJ. Contribution to the Energetics of Evolution. Proc Natl Acad Sci [Internet].
1922 Jun 1 [cited 2021 Mar 29];8(6):147–51. Available from:
https://www.pnas.org/content/8/6/147
5. Schrack JA, Knuth ND, Simonsick EM, Ferrucci L. “iDEAL” aging is associated
with lower resting metabolic rate: The baltimore longitudinal study of aging. J Am Geriatr
Soc [Internet]. 2014 [cited 2021 Apr 7];62(4):667–72. Available from:
/pmc/articles/PMC3989425/
6. Harman D. The aging process: Major risk factor for disease and death. Proc Natl
Acad Sci U S A. 1991;88(12):5360–3.
7. Duncan GE, Perri MG, Theriaque DW, Hutson AD, Eckel RH, Stacpoole PW.
Exercise training, without weight loss, increases insulin sensitivity and postheparin
plasma lipase activity in previously sedentary adults. Diabetes Care [Internet]. 2003 Mar
1 [cited 2021 Mar 29];26(3):557–62. Available from:
https://pubmed.ncbi.nlm.nih.gov/12610001/
8. Pan XR, Li GW, Hu YH, Wang JX, Yang WY, An ZX, et al. Effects of diet and
exercise in preventing NIDDM in people with impaired glucose tolerance: The Da Qing
IGT and diabetes study. Diabetes Care [Internet]. 1997 [cited 2021 Mar 29];20(4):537–
44. Available from: https://pubmed.ncbi.nlm.nih.gov/9096977/
9. Frisard M, Ravussin E. Energy metabolism and oxidative stress: Impact on the
metabolic syndrome and the aging process. Endocrine [Internet]. 2006 [cited 2020 Nov
12];29(1):27–32. Available from: https://pubmed.ncbi.nlm.nih.gov/16622290/
10. Moher D, Liberati A, Tetzlaff J, Altman DG, Altman D, Antes G, et al. Preferred
reporting items for systematic reviews and meta-analyses: The PRISMA statement. Vol.
6, PLoS Medicine. 2009.
11. Lührmann PM, Neuhäeuser Berthold M. Are the equations published in literature for
predicting resting metabolic rate accurate for use in the elderly? J Nutr Heal Aging.
2004;8(3):144–9.
12. Weiss CO, Cappola AR, Varadhan R, Fried LP. Resting metabolic rate in old-old
Brazilian Journal of Health Review, Curitiba, v.4, n.4, p.17867-17882 jul./aug. 2021Brazilian Journal of Health Review 17881
ISSN: 2595-6825
women with and without frailty: Variability and estimation of energy requirements. J Am
Geriatr Soc [Internet]. 2012 Sep [cited 2021 Mar 29];60(9):1695–700. Available from:
https://pubmed.ncbi.nlm.nih.gov/22985142/
13. Rumpler W V., Seale JL, Conway JM, Moe PW. Repeatability of 24-h energy
expenditure measurements in humans by indirect calorimetry. Am J Clin Nutr [Internet].
1990 [cited 2021 Mar 29];51(2):147–52. Available from:
https://pubmed.ncbi.nlm.nih.gov/2305701/
14. McAnena OJ, Harvey LP, Katzeff HL, Daly JM. Indirect calorimetry: comparison of
hood and mask systems for measuring resting energy expenditure in healthy volunteers.
JPEN J Parenter Enteral Nutr [Internet]. 1986 [cited 2021 Mar 29];10(6):555–7.
Available from: https://pubmed.ncbi.nlm.nih.gov/3795448/
15. Higgins J, Thomas J, Chandler J, Cumpston M, Li T, Page M, et al. Chapter 6:
Choosing effect measures and computing estimates of effect. In: Higgins J, Li T, Deeks
J, editors. Cochrane Handbook for Systematic Reviews of Interventions version
[Internet]. 2nd ed. Chichester (UK): John Wiley & Sons; 2020. Available from:
www.training.cochrane.org/handbook.
16. Leonard WR. Human Energetics. In: Reference Module in Earth Systems and
Environmental Sciences. Elsevier; 2014.
17. Egger M, Smith GD, Schneider M, Minder C. Bias in meta-analysis detected by a
simple , graphical test measures of funnel plot asymmetry. BMJ [Internet]. 1997 [cited
2020 Jan 13];315(7109):629–34. Available from:
http://www.ncbi.nlm.nih.gov/pubmed/9310563%0Ahttp://www.pubmedcentral.nih.gov/
articlerender.fcgi?artid=PMC2127453
18. Guyatt GH, Oxman AD, Vist GE, Kunz R, Falck-Ytter Y, Alonso-Coello P, et al.
GRADE: An emerging consensus on rating quality of evidence and strength of
recommendations. BMJ [Internet]. 2008 Apr 26 [cited 2021 Apr 3];336(7650):924–6.
Available from: https://pubmed.ncbi.nlm.nih.gov/18436948/
19. Weir JB d. V. New methods for calculating metabolic rate with special reference to
protein metabolism. J Physiol [Internet]. 1949 Aug 1 [cited 2021 Mar 29];109(1–2):1–9.
Available from: https://pubmed.ncbi.nlm.nih.gov/15394301/
20. Nelson KM, Weinsier RL, Long CL, Schutz Y. Prediction of resting energy
expenditure from fat-free mass and fat mass. Am J Clin Nutr [Internet]. 1992 [cited 2021
Mar 28];56(5):848–56. Available from: https://pubmed.ncbi.nlm.nih.gov/1415003/
21. Janssen I, Heymsfield SB, Wang ZM, Ross R. Skeletal muscle mass and distribution
in 468 men and women aged 18-88 yr. J Appl Physiol [Internet]. 2000 [cited 2021 Mar
28];89(1):81–8. Available from: https://pubmed.ncbi.nlm.nih.gov/10904038/
22. McCormick R, Vasilaki A. Age-related changes in skeletal muscle: changes to life-
style as a therapy. Biogerontology [Internet]. 2018 [cited 2021 Mar 28];19(6). Available
from: https://pubmed.ncbi.nlm.nih.gov/30259289/
Brazilian Journal of Health Review, Curitiba, v.4, n.4, p.17867-17882 jul./aug. 2021Brazilian Journal of Health Review 17882
ISSN: 2595-6825
23. Chodzko-Zajko WJ, Proctor DN, Fiatarone Singh MA, Minson CT, Nigg CR, Salem
GJ, et al. Exercise and Physical Activity for Older Adults. Med Sci Sport Exerc [Internet].
2009 Jul [cited 2021 Apr 7];41(7):1510–30. Available from:
https://journals.lww.com/00005768-200907000-00020
24. Donnelly JE, Blair SN, Jakicic JM, Manore MM, Rankin JW, Smith BK. Appropriate
physical activity intervention strategies for weight loss and prevention of weight regain
for adults [Internet]. Vol. 41, Medicine and Science in Sports and Exercise. Med Sci
Sports Exerc; 2009 [cited 2021 Apr 7]. p. 459–71. Available from:
https://pubmed.ncbi.nlm.nih.gov/19127177/
25. Barazzoni R, Bischoff S, Boirie Y, Busetto L, Cederholm T, Dicker D, et al.
Sarcopenic Obesity: Time to Meet the Challenge [Internet]. Vol. 11, Obesity Facts. S.
Karger AG; 2018 [cited 2021 Apr 7]. p. 294–305. Available from:
https://pubmed.ncbi.nlm.nih.gov/30016792/
26. Molino S, Dossena M, Buonocore D, Verri M. Sarcopenic obesity: An appraisal of
the current status of knowledge and management in elderly people [Internet]. Vol. 20,
Journal of Nutrition, Health and Aging. Springer-Verlag France; 2016 [cited 2021 Apr
7]. p. 780–8. Available from: https://link.springer.com/article/10.1007/s12603-015-0631-
8
27. Sardeli A, Griffth G, Santos M dos, Ito M, Chacon-MIkahil M. The effects of
exercise training on hypertensive older adults: an umbrella meta-analysis. Hypertens Res.
2021;44(8).
28. Silva G, Oliveira L, Rolim A, Santos N dos, Araújo L, Braga V, et al. Nutritional
intervention with emphasis on the supplementation of vitamin d, milk serum protein and
essensential amino acids in improving muscular health in sarcopenic elderly people: a
literature review. Brazilian J Heal Rev. 2021;4(3):11926–37.
29. Alfonzo-González G, Doucet E, Bouchard C, Tremblay A. Greater than predicted
decrease in resting energy expenditure with age: Cross-sectional and longitudinal
evidence. Eur J Clin Nutr [Internet]. 2006 Jan [cited 2021 Apr 21];60(1):18–24. Available
from: https://pubmed.ncbi.nlm.nih.gov/16151460/
Brazilian Journal of Health Review, Curitiba, v.4, n.4, p.17867-17882 jul./aug. 2021You can also read
