Sarcopenia among elderly retired soldiers attending the retiree's clinic in an army reference hospital in Kaduna, northwestern, Nigeria
Fidelis Onyekachi Ajuonuma, Benjamin Yakubu Ibrahim, Habiba Dabo Zubairu, Natie Nuhu Butawa
Corresponding author: Fidelis Onyekachi Ajuonuma, Department of Family Medicine, 44 Nigerian Army Reference Hospital, Kaduna, Nigeria
Received: 30 Jun 2024 - Accepted: 05 Sep 2024 - Published: 19 Sep 2024
Domain: Family Medicine,Geriatrics
Keywords: Sarcopenia, elderly, retired soldiers, Nigeria
©Fidelis Onyekachi Ajuonuma et al. PAMJ Clinical Medicine (ISSN: 2707-2797). This is an Open Access article distributed under the terms of the Creative Commons Attribution International 4.0 License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Cite this article: Fidelis Onyekachi Ajuonuma et al. Sarcopenia among elderly retired soldiers attending the retiree's clinic in an army reference hospital in Kaduna, northwestern, Nigeria. PAMJ Clinical Medicine. 2024;16:7. [doi: 10.11604/pamj-cm.2024.16.7.44488]
Available online at: https://www.clinical-medicine.panafrican-med-journal.com//content/article/16/7/full
Research
Sarcopenia among elderly retired soldiers attending the retiree's clinic in an army reference hospital in Kaduna, northwestern, Nigeria
Sarcopenia among elderly retired soldiers attending the retiree’s clinic in an army reference hospital in Kaduna, northwestern, Nigeria
Fidelis Onyekachi Ajuonuma1,&, Benjamin Yakubu Ibrahim2, Habiba Dabo Zubairu3, Natie Nuhu Butawa4
&Corresponding author
Introduction: sarcopenia is a muscle disease whose consequences lead to functional disabilities and loss of independence. Despite its significant impact, sarcopenia has not been extensively studied among elderly retired Nigerian soldiers. This study aimed to determine the prevalence of sarcopenia and the biopsychosocial factors associated with it in this specific population.
Methods: the study was a hospital-based cross-sectional study. Eligible participants were recruited for the study using a simple random sampling method. A total of 327 participants were recruited for the study. Data on sociodemographic characteristics and biopsychosocial risk factors of sarcopenia were obtained. The frequency of the risk factors was determined; the Chi-square test was used to test for the association between the risk factors and sarcopenia. Multivariable logistic regression analysis was used to identify the independent predictive risk factors associated with sarcopenia among the participants.
Results: the proportion of the study participants found to have sarcopenia was 21.1%. Biopsychosocial risk factors associated with sarcopenia (P < 0.05) include age, rank at retirement, type of family, post-retirement employment, nutritional status, and depression. Multivariable logistic regression analysis showed that the (85-105) age group, malnutrition, and depression were the independent predictors of sarcopenia among the study participants.
Conclusion: the prevalence of sarcopenia among elderly retired soldiers is high and advancing age, malnutrition and depression can independently predict its development in elderly retired soldiers. Therefore, elderly retired soldiers should be screened routinely for sarcopenia bearing in mind the above risk factors for prevention, early detection and treatment for a better health outcome.
Sarcopenia has been defined as an age-related progressive and diffuse loss of skeletal muscle mass, strength, and function [1]. Sarcopenia as a medical term was derived from the Greek root words sarx which means flesh and penia which means loss by Irwin Rosenberg in 1988 [2]. It is a geriatric syndrome because of its multifactorial pathogenesis [3]. It is a common but complex state of impaired health in the elderly which is associated with high morbidity and mortality [4]. Sarcopenia causes mobility disorders, increased risk of falls, fractures, impaired ability to perform activities of daily living, functional disabilities, and loss of independence [4]. It is a strong independent predictor of hospitalization, disability, and death in the elderly. Operationally, sarcopenia is defined by low skeletal muscle mass and either low muscle strength or low muscle performance. This is per the current consensus criteria of the European Working Group on Sarcopenia in Older People 2 (EWGSOP2) 2018 [5]. The biopsychosocial model as developed by Engel assumed that disease or illness outcome is attributed to the intricate blend of biological, psychological, and social factors [6].
Several studies have emphasized the biological factors associated with sarcopenia [7], yet psychological and social determinants of health are integral to the development and progression of sarcopenia in the elderly. Utilizing a biopsychosocial model to assess these risk factors of sarcopenia in the elderly offers a holistic approach to the prevention of this disease in our elderly population [7]. Most developing countries and the United Nations (UN) have defined the elderly as 60 years of age and above, although the World Health Organization (WHO) puts it at 65 years [8]. Nigerian soldiers retire from public service at 60 to join this growing population of elders [9]. They constitute a unique elderly population known to have lived active physical lives during their military career. As in most other countries, they are dignified and respected people of the society. At the extremes of their age, they are still dignified and self-sufficient. They benefit from post-service housing schemes, pension services, and health insurance however they are not immune to the challenges of ageing [10].
Studies have shown a high prevalence of sarcopenia in the elderly globally [4]. This ranges from 5.4% in South West Nigeria to 33.6% in Mexico [4]. There is a global demographic transition that has caused an unprecedented increase in the elderly population with a higher rate of increase among developing countries like Nigeria [11]. Nigeria's population was about 206 million in 2020, and 9.4 million people were 60 and older. Nigeria's elderly population experienced an increase of about 740 thousand people between 2018 and 2020 [12]. Although the cost of managing sarcopenia and its associated complications among Nigerian elderly has not been quantified, a report from the United States of America in 2004 estimated the cost at $18.5 billion [13]. This cost is huge for a developing nation like Nigeria. Sarcopenia has not been studied among the elderly retired Nigerian soldiers. This study aimed to determine the prevalence of sarcopenia and the biopsychosocial factors associated with it among elderly retired soldiers.
Study design, setting, and participants: the study was a hospital-based cross-sectional study at the Retiree´s Clinic of 44 Nigerian Army Reference Hospital Kaduna. 44 Nigerian Army Reference Hospital Kaduna is a 500-bed level IV Military Reference Hospital located in Kaduna the capital city of Kaduna State northwestern Nigeria. The hospital was established by the Nigerian Army and provides primary, secondary, and tertiary care to both serving and retired military personnel and their families as well as members of the civilian populace living within and outside Kaduna state. The study population comprised all the elderly retired soldiers aged (60 years and above) both males and females, who attended the Retiree's Clinic of 44 Nigerian Army Reference Hospital Kaduna during the study period (November 2022 - March 2023). The study participants included all those who gave their consent for the study while those who were severely sick and needed hospitalization, those with deformity, disability, or frankly psychosis were excluded from the study.
Variables: the study dependent variable was sarcopenia while the independent variables include the biopsychosocial factors - sociodemographic characteristics, nutritional status, depression, and perceived social support.
Study size: the sample size was calculated using the Kish Leslie formula for cross-sectional studies [14]. A total of 327 participants were recruited for this study after a pilot study using a simple random method [14].
Data sources and measurement: a pre-tested, semi-structured interviewer-administered questionnaire was used to obtain data from the participants.
Diagnosis of sarcopenia: this study adopted the operational definition of sarcopenia by the European working group on sarcopenia in older people (EWGSOP 2) and revised consensus criteria [5]. Male (low skeletal muscle mass index) ≤15.97kg/m2, female (low skeletal muscle mass index) ≤12.31kg/m2 male (low muscle strength) ≤34.49kg, female (low muscle strength) ≤22.64kg, male and female (low physical performance by gait speed) ≤0.8m/s. The muscle mass of the study participants was measured using the bioelectrical-impedance analyser (BIA) InnerScan™ body composition monitor Model BC-543 manufactured by TANITA Corporation, Tokyo, Japan which was an ISO 9001 certified instrument [11]. The skeletal muscle mass index (SMI) was calculated by dividing muscle mass by height in meters squared (muscle mass/(height)2). Their muscle strength was assessed by their hand grip strength as recommended by the EWGSOP2 [5]. This measurement was done with a digital hand-held dynamometer (Camry Electronic Hand Dynamometer Model: EH 101) [5], while the 4-meter walking test was used to assess physical performance as recommended by EWGSOP 2. Low physical performance was (low gait speed of < 0.8 m/s in the 4m walking test) [11,15]. The Patient Health Questionnaire-9 (PHQ-9) questionnaire was used to assess for depression [16]. The Multidimensional Scale of Perceived Social Support (MSPSS) was used to measure participants´ perception of support from 3 dimensions: family, friends, and significant other supports [17]. The Mini Nutritional Assessment® (MNA) questionnaire was used to assess their nutritional status [18].
Bias: the study participants were recruited using a simple random method to mitigate selection bias while trained interviewers administered the pre-tested semi-structured questionnaire to reduce information bias.
Data analysis (quantitative variables/statistical methods): the statistical package for social sciences SPSS (version 23.0, IBM Corp., Armonk, New York) was used for the data entry, cleaning, and analysis. There was no missing data. Descriptive statistics were summarised in tables and charts. Qualitative variables were expressed in proportions or frequency and quantitative variables were illustrated by means and standard deviations. Quantitative data (age) was subjected to normality testing using Shapiro Wilk test. Chi-square was used to test for associations between categorical variables. Logistic regression analysis was used to determine the independent predictors of sarcopenia among the identified significant variables. The confidence level was 95% and a p-value of < 0.05 was considered significant.
Ethical consideration: ethical clearance for this study was obtained from the ethical and research committee of 44 NARHK. Informed written consent was also obtained from participants after being duly informed about the study. The data obtained from the participants was handled with utmost confidentiality.
Characteristics of participants: the study participants included 327 elderly retired soldiers whose age range was (60-103) years. The majority 202(61.8%) belonged to the (60-74) year´s age group. Their mean age was 73.18 ±7.45 years. They comprised 317 (96.9%) males and 10 (3.1%) females. Their sociodemographic characteristics showed that members of the minority tribes in Nigeria 267 (81.7%) constituted the majority. They belonged to the two main religions in Nigeria, 200 (61.2%) were Christians while 127 (38.8%) were Muslims. The majority 284 (86.9%) still had and lived with their spouses while the rest 43 (13.1%) were widowed. Their family type was mostly nuclear 317 (96.9%) with only 10 (3.1%) in the extended family setting. Rank at retirement showed that the majority 285 (87.2%) were non-commissioned men, and 42 (12.8%) retired as officers. Only 170 (52.0%) of the participants engaged in post-retirement employment.
Biopsychosocial factors: the assessed biopsychosocial factors were nutritional status, depression, and social support. The majority 220 (67.2%) had normal nutritional status, 79 (24.2%) were at risk of malnutrition while 28 (8.6%) were already malnourished. In the area of social support, the majority 235 (71.9%) had moderate support, 58 (17.7%) had high support, and only 34 (10.4%) had low social support. Depression was reported by 66 (20.2%) of participants, while 261 (79.8%) did not report depression. The prevalence of sarcopenia was found to be 21.1%, leaving 78.9% without sarcopenia (Table 1). The Pearson Chi-square test was used to test the association of the assessed biopsychosocial factors with sarcopenia in the study participants. The factors of age, type of family, rank at retirement, post-retirement employment, nutritional status, and depression were found to have a significant association with sarcopenia with a p-value <0.05. As shown in Table 2, sarcopenia was found more with advancing age. The oldest old age group (85-105) had a frequency of 65% compared to 75-84 (22.9%) and 60-74 (15.8%). Participants who lived in an extended family setting had 70% sarcopenia frequency while those in nuclear family settings had 20%.
Similarly, those who retired as non-commissioned men had a greater frequency of 23% than 7% found in commissioned officers. Those who had no post-retirement employment were more affected (26%) by sarcopenia than the others who had post-retirement employment (16%). It was found that 100% of the malnourished participants had sarcopenia, 44% of those found to be at risk of malnutrition had sarcopenia while only 3% of those with normal nutrition had sarcopenia. Likewise, those with depression had a greater frequency 41% than 16% found in those without depression. The rest of the assessed factors sex, tribe, religion, marital status, and social support were not statistically significantly associated with sarcopenia. The logistic regression analysis carried out on the factors that were found to be significantly associated with sarcopenia showed that only the oldest old age group (85-105) OR=21.939 with 95% CI [3.024-158.204] P=0.002, malnutrition OR=48.094 with 95% CI [18.583-124.475] P=<0.001, and depression OR=5.702 with CI [1.429-22.745] P=0.014 were the predictors of sarcopenia among the study participants Table 3.
The prevalence of sarcopenia was 21.1% as found in this study confirming the fact that sarcopenia is prevalent among the elderly retired Nigerian soldiers. This is lower than the weighted African prevalence of 25.72% as reported in a recent systematic review [19]. In comparison with a similar study conducted within the same northwestern zone, Nigeria among non-veteran community-dwelling elderly people aged 60 years and older, Awotidebe et al. found a prevalence of 36.2% [20] which is still higher than the prevalence we found in this study. We believe that this difference might be a beneficial effect of the military career being a physically active career. It could also be due to the military physical fitness insistence through their military career, regular physical training and exercise even beyond retirement. Studies have shown that physical activity whether moderate or intensive has a positive correlation with sarcopenia prevention [21]. The effect of exercise on sarcopenia has been studied extensively and it is the most reliable means of combatting age-related sarcopenia [22]. This study also found a gender difference in sarcopenia prevalence. The elderly retired female soldiers were 40% while their male counterparts were 21%. The global prevalence of sarcopenia has a male predominance but has varied in the literature from study to study depending on the region, criteria used and cut marks [23]. Awotidebe et al. in their study in the same region and study criteria found a male predominance with 49.2% and 22.53% females [20]. Although the number of females in this study was small due to their limited number in the 63 Nigerian Army depot, we believe this might be due to the healthy worker effect that affects occupations differently. Hartal et al. found that 67.9% of retired military personnel lived longer than the average life expectancy of their birth-sex cohorts and that females benefited more from the protective effects of military service with relative longevity hence a higher prevalence of sarcopenia [24].
The assessed biopsychosocial risk factors which were found to have a significant association with sarcopenia among the participants included age, family type, rank at retirement, post-retirement employment, nutritional status, and depression. This study agreed with other sarcopenia studies that age is the primary risk factor for primary sarcopenia [11]. Compared with the young-old age group (60-74) those in their old-old age group (75-84) had about 5.8 times the odds of becoming sarcopenic while the oldest-old group had about 22 times the odds of sarcopenia. This is consistent with the homeostenosis associated with ageing [11]. Having an extended family setting was found to have 8.7 times the odds of developing sarcopenia when compared with the nuclear family setting. This may be associated with the economic hardship and psychological stress of managing large families in a depressed economy like Nigeria. Malnutrition was significantly associated with sarcopenia in this study. Malnourished participants were found to have 48 times the odds of sarcopenia than those with normal nutrition.
Many studies have underscored the association of nutrition and sarcopenia, certain nutrients as well as dietary patterns have been shown to offer protective effects against declines in strength and function associated with ageing hence increased protein intake, and higher consumption of fruits and vegetables have been associated with improved physical performance and protection against muscle wasting, sarcopenia, and frailty [25]. Depression was also found to have a significant association with sarcopenia with about 5.7 times odds compared with participants without depression. A recent review found that the prevalence of depression in patients with sarcopenia was high relatively, and there was a correlation between sarcopenia and depression due to their many similarities in clinical, aetiology, and prognosis [26]. The factors found to be predictive of sarcopenia among the elderly retired soldiers in this study include the oldest-old age group (85-105), malnutrition, and depression. The other factors were not predictive.
Limitation: this study is limited by the fact that it was a hospital-based study which did not reflect the true situation of sarcopenia among other retirees who did not come to the hospital and the cross-sectional study design used precluded causality of sarcopenia by the risk factors assessed in this research work.
The prevalence of sarcopenia among elderly retired soldiers is high and advancing age, malnutrition and depression can independently predict its development in elderly retired soldiers. Therefore, elderly retired soldiers should be screened routinely for sarcopenia bearing in mind the above risk factors for prevention, early detection and treatment for a better health outcome.
What is known about this topic
- It is known that sarcopenia is a complex muscle disease with multiple aetiology that is primarily associated with ageing and that it reduces the quality of life, increases hospitalisation, loss of independence and death;
- It is equally known that its prevalence and risk factors vary among different populations.
What this study adds
- To our knowledge, this study is the first to study sarcopenia among military veterans in Africa; it has provided data and bridged the knowledge gap about this geriatric syndrome, especially among this unique elderly population;
- The prevalence of sarcopenia and its associated risk factors among elderly retired Nigerian soldiers was not known, this finding will objectively guide defence ministries in Nigeria and Africa to appreciate the burden of sarcopenia among veterans and encourage active screening for prevention, early diagnosis and treatment.
The authors declare no competing interests.
Fidelis Onyekachi Ajuonuma and Benjamin Yakubu Ibrahim conceived the study. Fidelis Onyekachi Ajuonuma performed the data collection. Benjamin Yakubu Ibrahim supervised the data collection. Fidelis Onyekachi Ajuonuma, Natie Nuhu Butawa, and Habiba Dabo Zubairu analysed the data. Fidelis Onyekachi Ajuonuma drafted the manuscript. Benjamin Yakubu Ibrahim, and Habiba Dabo Zubairu critically revised the manuscript. All the authors read and approved the final version of this manuscript.
Table 1: sociodemographic characteristics and biopsychosocial factors of sarcopenia among the study participants
Table 2: association of sociodemographic characteristics and biopsychosocial factors with sarcopenia among the study participants
Table 3: logistic regression analysis of factors significantly associated with sarcopenia
- Buchard B, Boirie Y, Cassagnes L, Lamblin G, Coilly A, Abergel A. Assessment of Malnutrition, Sarcopenia and Frailty in Patients with Cirrhosis: Which Tools Should We Use in Clinical Practice? Nutrients. 2020 Jan 9;12(1):186. PubMed | Google Scholar
- Bauer J, Morley JE, Schols AMWJ, Ferrucci L, Cruz-Jentoft AJ, Dent E et al. Sarcopenia: A Time for Action. An SCWD Position Paper. J Cachexia Sarcopenia Muscle. 2019 Oct;10(5):956-961. PubMed | Google Scholar
- Liguori I, Russo G, Aran L, Bulli G, Curcio F, Della-Morte D et al. Sarcopenia: assessment of disease burden and strategies to improve outcomes. Clin Interv Aging. 2018 May 14;13:913-927. PubMed | Google Scholar
- Neves T, Ferriolli E, Lopes MBM, Souza MGC, Fett CA, Fett WCR. Prevalence and factors associated with sarcopenia and dynapenia in elderly people. J Frailty Sarcopenia Falls. 2018 Dec 1;3(4):194-202. PubMed | Google Scholar
- Cruz-Jentoft AJ, Bahat G, Bauer J, Boirie Y, Bruyère O, Cederholm T et al. Sarcopenia: Revised European consensus on definition and diagnosis. Age Ageing. 2019 Jan 1;48(1):16-31. PubMed | Google Scholar
- Blount AJ, Adams CR, Anderson-Berry AL, Hanson C, Schneider K, Pendyala G. Biopsychosocial factors during the perinatal period: Risks, preventative factors, and implications for healthcare professionals. Int J Environ Res Public Health. 2021 Aug 3;18(15):8206. PubMed | Google Scholar
- Kusnanto H, Agustian D, Hilmanto D. Biopsychosocial model of illnesses in primary care: A hermeneutic literature review. J Family Med Prim Care. 2018 May-Jun;7(3):497-500. PubMed | Google Scholar
- Animasahun VJ, Chapman HJ. Psychosocial health challenges of the elderly in Nigeria: a narrative review. Afr Health Sci. 2017 Jun;17(2):575-583. PubMed | Google Scholar
- Nwankwo CA, Oghogho DO. Retiring Civil Servants´ Attitude Towards Retirement In Edo State, Nigeria. Unizik J Educ Res Policy Stud. 2022;11(1):13-21. Google Scholar
- Khan MMI, Haque MA, Rashid R, Zafreen F. Common Health Problems of Retired Armed Forces Personnel Admitted In Combined Military Hospital. J Armed Forces Med Coll Bangladesh. 2019;15(1):45-7. Google Scholar
- Adebusoye L, Ogunbode A, Olowookere O, Ajayi S, Ladipo M. Factors associated with sarcopenia among older patients attending a geriatric clinic in Nigeria. Niger J Clin Pract. 2018 Apr;21(4):443-450. PubMed | Google Scholar
- Statista Research Department. Elderly population aged 60 years and older in Nigeria from 2018 to 2020. Nov 29, 2022. Accessed May 23, 2024.
- Darvishi A, Hemami MR, Shafiee G, Daroudi R, Mohseni M, Shekarabi FH et al. Sarcopenia screening strategies in older people: a cost effectiveness analysis in Iran. BMC Public Health. 2021 May 17;21(1):926. PubMed | Google Scholar
- Serdar CC, Cihan M, Yücel D, Serdar MA. Sample size, power and effect size revisited: Simplified and practical approachin pre-clinical, clinical and laboratory studies. Biochem Med (Zagreb). 2021 Feb 15;31(1):010502. PubMed | Google Scholar
- Tieland M, Trouwborst I, Clark BC. Skeletal muscle performance and ageing. J Cachexia Sarcopenia Muscle. 2018 Feb;9(1):3-19. PubMed | Google Scholar
- Levis B, Benedetti A, Thombs BD. Accuracy of Patient Health Questionnaire-9 (PHQ-9) for screening to detect major depression: Individual participant data meta-analysis. BMJ. 2019 Apr 9;365:l1476. PubMed | Google Scholar
- Mohammad AH, Sadat N Al, Yim LS, Chinna K. Validity and Reliability of the Hausa Version of Multidimensional Scale of Perceived Social Support Index. Iran Red Crescent Med J. 2015 Feb 21;17(2):e18776. PubMed | Google Scholar
- Adebusoye LA, Ajayi IO, Dairo MD, Ogunniyi AO. Nutritional status of older persons presenting in a primary care clinic in Nigeria. J Nutr Gerontol Geriatr. 2012;31(1):71-85. PubMed | Google Scholar
- Veronese N, Smith L, Koyanagi A, Hoffman J, Snoussi M, Prokopidis K et al. Prevalence of sarcopenia in Africa: a systematic review and meta-analysis of observational studies. Aging Clin Exp Res. 2024 Jan 28;36(1):12 PubMed | Google Scholar
- Awotidebe AW, Bala A, Abdulkarim K. Prevalence estimates of sarcopenia in community-dwelling older adults in Northern Nigeria according to revised European and Asian reference criteria. Physiother Q. 2022;30(4):65-71. Google Scholar
- Seo JH, Lee Y. Association of physical activity with sarcopenia evaluated based on muscle mass and strength in older adults: 2008-2011 and 2014-2018 Korea National Health and Nutrition Examination Surveys. BMC Geriatr. 2022 Mar 17;22(1):217. PubMed | Google Scholar
- Yoo SZ, No MH, Heo JW, Park DH, Kang JH, Kim SH et al. Role of exercise in age-related sarcopenia. J Exerc Rehabil. 2018 Aug 24;14(4):551-558. PubMed | Google Scholar
- Alodhayani AA. Sex-specific differences in the prevalence of sarcopenia among pre-frail community-dwelling older adults in Saudi Arabia. Saudi J Biol Sci. 2021 Jul;28(7):4005-4009. PubMed | Google Scholar
- Hartal M, Kreiss Y, Yavnai N. Relative longevity among retired military personnel: A historical-cohort study. Mil Med Res. 2015 Oct 30;2:29. PubMed | Google Scholar
- Ganapathy A, Nieves JW. Nutrition and Sarcopenia-What Do We Know? Nutrients. 2020 Jun 11;12(6):1755. PubMed | Google Scholar
- Li Z, Tong X, Ma Y, Bao T, Yue J. Prevalence of depression in patients with sarcopenia and correlation between the two diseases: systematic review and meta-analysis. J Cachexia Sarcopenia Muscle. 2022 Feb;13(1):128-144. PubMed | Google Scholar