^[1]Introduction

Improvement of socioeconomic circumstances, including nutrition, during the last two centuries has led to health improvements and increased life expectancy in the developed world. The increase in the absolute and relative numbers of the elderly in population is referred to as “population ageing”. However, most significant is the term “successful aging”, meaning not only increased life expectancy but also, and most importantly with a good quality of life; that is, maintenance of health and independence. [1] Ageing is associated with a loss of muscle mass and strength, called sarcopenia, originating from the Greek words sarx (flesh) and penia (loss), meaning “poverty of flesh”. Sarcopenic obesity consists of a disturbance, that combines sarcopenia with obesity. Sarcopenia and obesity in the third age may reinforce each other and act synergistically, maximizing their detrimental effects on disability and mortality. [2] According to Baumgartner [3] obesity, sarcopenia and sarcopenic obesity can be considered “syndromes of disordered body composition”.

Sarcopenia consists of a progressively increased catabolism and a decreased anabolism with a parallel reduction in the capacity for muscle regeneration. [4,5]  There is a loss of motor units that results in a decline in muscle power and predisposes an individual to the development of the metabolic syndrome [4]  .  The elderly who become frail and obese present with a low relative muscle mass, low muscle strength per muscle area (that is low muscle strength relative to their body size resulting in an increased need to carry a comparatively heavy body), an excess of body fat due to obesity and a parallel increase in weakness due to sarcopenia [6,7] . Goodpaster et al. [8]   provided evidence that, in the elderly, the decline in muscle strength is higher than the degree of muscle mass loss, thus provoking a deterioration also in muscle “quality”. Inactivity of the elderly, places them at a greater risk for sarcopenia because (a) there is a lack of the normal trophic effect of exercise on muscles and (b) it leads to weight gain, most of which appears to be fat and not free muscle mass [9]. A recent systematic review and meta-analysis conducted in 2019 with combined data of 41 studies and a total of 34,955 participants, concluded that the prevalence of sarcopenia in community-dwelling individuals was 11% of men and 9% of women. Amongst those in nursing-homes individuals sarcopenia was present in 51% of men and 31% of women and the respective gender values of hospitalized individuals was 23% and 24% [10].

Sarcopenia increases from 15% to 40%, between the ages of 60 and 80 years [11]. Similarly, sarcopenic obesity rises with age, and one study found that the prevalence of low lean mass and obesity in the elderly was 33.5% in females and 12.6% in males [12]. However, over the same age range, there was a decrease in obesity prevalence from 55% to 30%. These percentages could be an indication that the eldely maintain their fat mass while losing their muscle mass, and thus obesity may convert to sarcopenic obesity that does not necessarily involve excessive weight gain, among those in their sixties and eighties [13]. A logical explanation was given by Davison et al. [1], suggested a differential survivor effect according to weight status. In other words, the obese elderly had higher mortality rate, compared to non-obese and thus, those above 80 years of age represented an initially healthier group in comparison to the younger elderly [1,12,14].

This population group has the most rapid growth and also is the most vulnerable to the development of several diseases such as diabetes, cardiovascular diseases, stroke, osteoporosis and dementia. Physical activity has a positive effect on the cardiovascular, respiratory, gastrointestinal and musculoskeletal systems [15,16] as well as some types of cancers [17]. Current intense aerobic exercise during leisure time such as fast walking, jogging, racket games, cycling or swimming was found to be protective against CHD and heart attacks in middle and older age subjects [16]. Also, physical activity increases basal metabolism and contributes to regulation of appetite, control of body weight, maintenance of ideal body fat and, in the long-term, leads to a reduction of body weight [15,18]. Similarly, moderate-intensity exercise leads to a reduction in prevalence of diabetes [19-22], hypertension, hypercholesterolemia [21,22] and cardiovascular disease [23]. From the time of Hippocrates in Greece, and Susruta in India, physical activity has been recognised to be associated with physical and mental health [16].

Subjects above 65 years of age are recommended to follow the lifestyle that is suggested to younger populations [24]. An earlier study, conducted in Thessaloniki Greece, showed that both older males and females elderly had low physical activity levels, that was attributed to their sedentary lifestyles [25]. A similar result reported by Meijer et al. [26], showing that time spent on low level activities (like lying, sitting and standing) was related to low mean physical activity levels in the elderly.

The purpose of the present study is to estimate different modes of obesity in an older Greek population according and their relation to various anthropometric measurements and physical activity levels.

Materials And Methods

Out of the 200 hundred approached subjects, the study included 102 elderly subjects, 50 men and 52 women, (60–83 years). The mean age of the total sample was 68.11 ± 6.40 years, and participants were free-living and non-institutionalized from Thessaloniki, Northern Greece. Data was collected between May of 2017 and March of 2018. The response rate of the participants in this study was 51%.As an exclusion criteria, all the participants selected were healthy and were not taking any medication. Out of the total sample, 46 subjects (19 men and 27 women) were members of Rehabilitation Centers for the Elderly in Thessaloniki, while 56 persons (31 men and 25 women) were members of the municipal gymnasiums of Thessaloniki and exercised two to three times per week). The participants completed a specific questionnaire regarding their health status, their physical activity and their previous weight status [27]. More specifically, this questionnaire included specific questions in order to specify the health, physical activity and weight status of all the participants when they were 30 years old. The study was approved by the ethical committee of ATEI (No: 20102) and all participants provided a written informed consent form.

Anthropometric measurements were taken from all participants. Body weight was measured with a digital scale of an accuracy of ±100 g (Seca 707, Seca Corporation, Seca, Columbia) and body height was measured to the nearest 0.5 cm using a stadiometer, of 0.5 cm accuracy (SECA 220) and that was calibrated regularly. Body fat was assessed using two methods: (1) skinfold thickness method, and (2) bioelectrical impendence analysis (BIA). For bioelectrical impendence analysis (BIA), a Maltron 907 bioelectrical impendence analyser (Maltron, Rayleigh, Essex, UK) was used. Participants were abstained from exercising, eating or drinking for four hours, and from taking diuretics the previous week before BIA measurements were completed. Participants were asked to urinate 30 min before the measurement. Subjects lay in a supine position with legs and arms abducted. Electrodes were placed on the right hand (proximal to the third metacarpophalangeal joint) and one on the wrist (between the distal prominence of the radius and ulna) and one on the right foot (proximal to the third metatarsophalangeal joint) and one on the ankle (between the medial and the latearal maleoli).

Skinfold measurements were taken from the right side of the body, in two regions: triceps, and subscapular using a Harpenden skinfold caliper (British Indicators Ltd., London, UK). Measurements were carried out in duplicate and the mean recorded value was used, in order to avoid discrepancies of above 10% between duplicate measurements. Body fat was estimated using the specific age population equations [28].

BMI was categorized according to the WHO [29] standards. Body Mass Index (BMI), Fat Mass Index (FMI = Fat Mass (kg)/Height² (m)) and Fat Free Mass Index (FFMI = Fat Free Mass (kg)/Height² (m)), were calculated for each participant. Obesity, based on body mass, was defined as a BMI greater than 30 kg/m². Central obesity was defined as a waist circumference of > 102 cm in men and > 88 cm in women. Body fat status was categorized using the criteria of Lohman [30]. Muscle mass < 9.12 kg/m² for men and <6.53 kg/m² for women was used to identify the risk of sarcopenia [1]. Obesity was defined as body fat (% body weight) > 37.16 for the men and > 40.01 for the women [1]. Sarcopenic obesity risk was estimated in the participants with coexisting sarcopenia and obesity resulting in high fat mass (> 37.16 for men and > 40.01 for women) in combination with low lean body mass (< 9.12 kg/m² for men and < 6.53 kg/m² for women) [1,31]. Dietary food intake was recorded and analyzed using the Food Processor nutrition program (version 7.4, 1997, ESHA Research Salem, Oregon). Intake of micronutrients was expressed as a percentage of the Recommended Dietary Allowance (RDA) in order to estimate the adequacy of micronutrient intake. Verbal and written instructions on how to record the food intake were given by a dietitian.

Results

Table 1 presents the anthropometric characteristics of the sample.

Table 1. Anthropometric characteristics of the sample (mean ± SD).

*** Statistically significant compared with the women (p ≤ 0.001).† Statistically significant compared with when aged 30 years old (p ≤ 0.01). ^‡ Statistically significant compared with when aged 30 years old (p ≤ 0.001).

When aged 30 years old, 14 women and 5 men were overweight and none of the participants was obese. The women demonstrated more than twice the risk of abdominal obesity (OR:2.133, CI: 0.963–4.725) compared to men (Table 2).

Table 2. Modes of obesity between women and men (n (%).

Between sedentary and exercised elderly (Table 3), the first demonstrated increased odds for obesity according to body fat (%BW) (OR: 1.259, 95% CI: 0.576–2.750), double chances for obesity according to body mass (OR: 2.074, 95% CI: 0.765–5.622), and triple odds for abdominal obesity (OR: 3.701, 95% CI: 1.612–8.494).

Table 3. Modes of obesity between sedentary and exercised elders.

Anthropometric characteristics according to gender and exercise are presented at Table 4 while the percentage of obesity, central obesity and elevated fat levels, according to gender and exercise are presented in Table 5.

Table 4. Anthropometric characteristics according to gender and exercise.

* p < 0.05. a,b,c Different letters denote statistically significant differences among exercised and non-exercised groups.

Table 5. Percentage of obesity, central obesity and elevated fat levels, according to gender and exercise.

* p < 0.05 a,b Different letters denote statistically significant differences among exercised and non-exercised groups.

Energy intake was 1881 ± 436 Kcal for non-exercised elders and 2064 ± 767 Kcal for the exercised group. The contribution for macronutrients in energy intake was for carbohydrates was 41.74 ± 8.76%, for proteins it was 18.43 ± 5.93% and for fat was 39.68 ± 9.25% for the non-exercised elders. For elders in the exercised group the mean intake for carbohydrates was 42.36 ± 10.46%, proteins were 16.36 ± 4.22% and fat was 39.88 ± 11.49%. There was no significant difference between sexes. Both exercised and non-exercised elders had inadequate intake of several micronutrients such as biotin, vitamin D, folic acid, calcium and magnesium (Data not shown).v

Conclusions

Elderly individuals who were sedentary demonstrated statistically significant increased odds for abdominal obesity compared to those who exercised two-three times a week. Due to the fact that abdominal obesity is strongly associated with chronic disease, especially in the elderly, exercise, along with a healthy diet may be useful modalities for healthy ageing. The results of this analysis, are of great importance with potential clinical impact to public health and the elderly population. Hence, public health authorities could promote exercise, for community dwelling and institutionalized elderly, while health professionals could use exercise as a means of body weight control.