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The Metabolic Syndrome: A Risk Factor for the Frailty Syndrome?
JAMDA xxx (2016) 1e2
JAMDA journal homepage: www.jamda.com
Letter to the Editor
The Metabolic Syndrome: A Risk Factor for the Frailty Syndrome? To the Editor: Frailty is a condition resulting from age-related decline in multiple physiological domains, clinically typified by physical weakness, in which individuals have increased the risk of adverse health outcomes and mortality when exposed to a stressor.1 Frailty affects 7% of individuals age 65 years and approximately 30% of those age 80.1 Paralleling with the population aging, Westernized societies are also facing a pandemic of obesity- and sedentaryrelated disorders. The metabolic syndrome (MetS), with its nexus of metabolic and cardiovascular traits, might predict risk of ageassociated conditions other than cardiovascular (CV) diseases, such as dementia, depression, and functional disability.2 No study has specifically explored hypothetical associations between MetS and the frailty phenotype in older adults. There might be common etiological aspects.3,4 Our study preliminarily assessed associations between MetS and frailty in a sample of older noninstitutionalized individuals. Older community-dwelling individuals referred to our ambulatory clinic for a comprehensive geriatric assessment (JuneeDecember 2015) were considered. Exclusion criteria were the following: dementia (DSM-IV), inability to walk, sensorial deficits, active malignancies, peripheral neuropathy, recent hospitalization, heart/respiratory failure, and clinical CV disease (coronary heart disease, stroke/transient ischemic attack, symptomatic carotid plaques, or peripheral artery disease). Written informed consent was required. Data collection and physical examinations were performed by trained staff using standardized questionnaires. The Mini-Mental State Examination and the Mini-Nutritional Assessment were administered. MetS was defined using the National Cholesterol
Education ProgrameAdult Treatment Panel III criteria, as described in detail elsewhere.5 Frailty was defined, according to criteria of Fried et al,1 as the presence of 3 or more of the following: (1) unintentional weight loss (>4.5 kg in the past year); (2) slow gait (requiring more than 7 minutes to walk a path of 5 meters, excluding space used for acceleration and deceleration); (3) reduced handgrip strength (assessed using a Martin hand dynamometer; cutoffs were <5.58 kPa for men and <3.37 kPa for women); (4) fatigability in performing usual daily activities (assessed by administration of 2 items of the Center for Epidemiologic Studies-Depression scale: “I felt that everything I did was an effort”; “I could not get going”); (5) reduced physical activity (self-reported). Statistical analyses were performed via SPSS 17.0 (SPSS Inc, Chicago, IL). Characteristics of participants were compared according to the presence of frailty. Logistic regression models were constructed to estimate independent association between MetS and frailty. Statistical significance was set at P .05; 118 individuals (76.1 5.0 years, 60% women) were studied. Frail participants (n ¼ 42) were significantly older (82.2 4.8 vs 73.7 5.0 years, P < .001) and more likely to have MetS (81.2% vs 29.2%, P < .001) than robust participants. As shown in Table 1, after simultaneous multiple adjustment, MetS as an entity was robustly associated with frailty, as well as with specific traits of frailty. Interestingly, such associations were not driven by specific altered components of MetS or by their sum. No association was found with weight loss and reduced physical activity. This preliminary study indicates that MetS is associated with the frailty phenotype in a sample of older community-dwelling individuals free of clinical CV disease, after adjustment for a range of potentially confounding variables. Interestingly, such associations were not explained by the effects of specific individual altered components of MetS, or by MetS severity, suggesting that MetS as an entity, rather than the sum of its parts, might increase the odds of frailty in late life.
Table 1 Logistic Models: Independent Associations Between MetS and the Frailty Phenotype
MetS Central obesity Blood pressure HDL cholesterol Triglycerides Glucose No. of MetS components
Frailty OR (95% CI)
Gait OR (95% CI)
Exhaustion OR (95% CI)
1.53 0.99 1.01 0.99 1.00 1.00 0.98
1.37 0.99 1.00 0.99 1.00 0.99 0.98
1.21 0.98 1.00 1.00 1.00 1.00 1.02
(1.33e1.76)* (0.98e1.01) (0.98e1.02) (0.98e1.01) (1.00e1.01) (0.98e1.02) (0.82e1.06)
(1.13e1.64)* (0.97e1.01) (0.98e1.02) (0.98e1.01) (0.99e1.01) (0.98e1.01) (0.88e1.12)
(1.02e1.45)y (0.95e1.01) (0.98e1.02) (0.98e1.01) (1.00e1.01) (0.99e1.01) (0.99e1.09)
Handgrip OR (95% CI) 1.31 0.99 1.01 0.98 1.00 1.01 0.97
(1.07e1.60)y (0.98e1.01) (0.98e1.03) (0.97e1.01) (0.99e1.01) (0.99e1.03) (0.93e1.02)
CI, confidence interval; HDL, high-density lipoprotein; OR, odds ratio. MetS and its individual altered components were entered as yes/no variables. The number of MetS components was entered as a continuous variable, from 0 to 5. Models adjusted for age (years, continuous), education (years, continuous), marital status (married, yes/no), current smoking (yes/no), Mini-Mental State Examination score (continuous, 0e30), Mini-Nutritional Assessment score (continuous, 0e30), diabetes mellitus (yes/no), and use of antihypertensive, antiplatelet, and lipid-lowering drugs (yes/ no). *P < .001. y P ¼ .001. http://dx.doi.org/10.1016/j.jamda.2016.01.005 1525-8610/Ó 2016 AMDA e The Society for Post-Acute and Long-Term Care Medicine.
2
Letter to the Editor / JAMDA xxx (2016) 1e2
The cross-sectional nature of this analysis does not allow us to elucidate what the direction of the association is, or what the underlying etiological mechanisms are; however, we can speculate about possible mechanisms linking MetS to greater risk of frailty. In addition to its classical diagnostic features, MetS is accompanied by peripheral insulin resistance, chronic micro-inflammation, activation of oxidative and prothrombotic mechanisms, and deregulation of the renin-angiotensin axis. All such mechanisms may potentially have a detrimental effect on various physiological domains, such as nutrition, neuromuscular system, and cognition.2e4 In particular, aging-associated skeletal muscle wasting, or sarcopenia, is among those central to the frailty syndrome. Pieces of evidence indicate a strong association between insulin resistance and chronic inflammation with accelerated sarcopenia, which may underlie the relationship between MetS and frailty.3,4 Furthermore, MetS has been associated with greater occurrence and severity of cerebral microvascular damage, a condition that may accelerate age-associated cognitive and functional decline, leading individuals to frailty. Frail persons are high users of health care resources, hospitalization, and nursing homes. Thus, identification of potentially preventable and modifiable risk factors for the condition is crucial. MetS affects 25% of people in the general adult population and 40% of those ages 65 years and older. Due to this huge prevalence, even a modest association with frailty would have great relevance. This preliminary study encourages the initiation of further larger investigations to assess whether MetS is an independent predictor of frailty.
References 1. Fried LP, Tangen CM, Walston J, et al. Frailty in older adults: Evidence for a phenotype. J Gerontol A Biol Sci Med Sci 2001;56:M146eM156. 2. Carriere I, Pérès K, Ancelin ML, et al. Metabolic syndrome and disability: Findings from the prospective three-city study. J Gerontol A Biol Sci Med Sci 2014;69: 79e86. 3. Barzilay JI, Blaum C, Moore T, et al. Insulin resistance and inflammation as precursors of frailty: The Cardiovascular Health Study. Arch Intern Med 2007; 167:635e641. 4. Abbatecola AM, Paolisso G. Is there a relationship between insulin resistance and frailty syndrome? Curr Pharm Des 2008;14:405e410. 5. The Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults. Executive summary of the third report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). JAMA 2001;285:2486e2497.
Giovanni Viscogliosi, MD Department of Epidemiology Surveillance and Promotion of Health National Institute of Health Rome, Italy Division of Gerontology Department of Cardiovascular Respiratory, Nephrologic Anesthesiologic and Geriatric Sciences “Sapienza” University Rome, Italy
JAMDA journal homepage: www.jamda.com
Letter to the Editor
The Metabolic Syndrome: A Risk Factor for the Frailty Syndrome? To the Editor: Frailty is a condition resulting from age-related decline in multiple physiological domains, clinically typified by physical weakness, in which individuals have increased the risk of adverse health outcomes and mortality when exposed to a stressor.1 Frailty affects 7% of individuals age 65 years and approximately 30% of those age 80.1 Paralleling with the population aging, Westernized societies are also facing a pandemic of obesity- and sedentaryrelated disorders. The metabolic syndrome (MetS), with its nexus of metabolic and cardiovascular traits, might predict risk of ageassociated conditions other than cardiovascular (CV) diseases, such as dementia, depression, and functional disability.2 No study has specifically explored hypothetical associations between MetS and the frailty phenotype in older adults. There might be common etiological aspects.3,4 Our study preliminarily assessed associations between MetS and frailty in a sample of older noninstitutionalized individuals. Older community-dwelling individuals referred to our ambulatory clinic for a comprehensive geriatric assessment (JuneeDecember 2015) were considered. Exclusion criteria were the following: dementia (DSM-IV), inability to walk, sensorial deficits, active malignancies, peripheral neuropathy, recent hospitalization, heart/respiratory failure, and clinical CV disease (coronary heart disease, stroke/transient ischemic attack, symptomatic carotid plaques, or peripheral artery disease). Written informed consent was required. Data collection and physical examinations were performed by trained staff using standardized questionnaires. The Mini-Mental State Examination and the Mini-Nutritional Assessment were administered. MetS was defined using the National Cholesterol
Education ProgrameAdult Treatment Panel III criteria, as described in detail elsewhere.5 Frailty was defined, according to criteria of Fried et al,1 as the presence of 3 or more of the following: (1) unintentional weight loss (>4.5 kg in the past year); (2) slow gait (requiring more than 7 minutes to walk a path of 5 meters, excluding space used for acceleration and deceleration); (3) reduced handgrip strength (assessed using a Martin hand dynamometer; cutoffs were <5.58 kPa for men and <3.37 kPa for women); (4) fatigability in performing usual daily activities (assessed by administration of 2 items of the Center for Epidemiologic Studies-Depression scale: “I felt that everything I did was an effort”; “I could not get going”); (5) reduced physical activity (self-reported). Statistical analyses were performed via SPSS 17.0 (SPSS Inc, Chicago, IL). Characteristics of participants were compared according to the presence of frailty. Logistic regression models were constructed to estimate independent association between MetS and frailty. Statistical significance was set at P .05; 118 individuals (76.1 5.0 years, 60% women) were studied. Frail participants (n ¼ 42) were significantly older (82.2 4.8 vs 73.7 5.0 years, P < .001) and more likely to have MetS (81.2% vs 29.2%, P < .001) than robust participants. As shown in Table 1, after simultaneous multiple adjustment, MetS as an entity was robustly associated with frailty, as well as with specific traits of frailty. Interestingly, such associations were not driven by specific altered components of MetS or by their sum. No association was found with weight loss and reduced physical activity. This preliminary study indicates that MetS is associated with the frailty phenotype in a sample of older community-dwelling individuals free of clinical CV disease, after adjustment for a range of potentially confounding variables. Interestingly, such associations were not explained by the effects of specific individual altered components of MetS, or by MetS severity, suggesting that MetS as an entity, rather than the sum of its parts, might increase the odds of frailty in late life.
Table 1 Logistic Models: Independent Associations Between MetS and the Frailty Phenotype
MetS Central obesity Blood pressure HDL cholesterol Triglycerides Glucose No. of MetS components
Frailty OR (95% CI)
Gait OR (95% CI)
Exhaustion OR (95% CI)
1.53 0.99 1.01 0.99 1.00 1.00 0.98
1.37 0.99 1.00 0.99 1.00 0.99 0.98
1.21 0.98 1.00 1.00 1.00 1.00 1.02
(1.33e1.76)* (0.98e1.01) (0.98e1.02) (0.98e1.01) (1.00e1.01) (0.98e1.02) (0.82e1.06)
(1.13e1.64)* (0.97e1.01) (0.98e1.02) (0.98e1.01) (0.99e1.01) (0.98e1.01) (0.88e1.12)
(1.02e1.45)y (0.95e1.01) (0.98e1.02) (0.98e1.01) (1.00e1.01) (0.99e1.01) (0.99e1.09)
Handgrip OR (95% CI) 1.31 0.99 1.01 0.98 1.00 1.01 0.97
(1.07e1.60)y (0.98e1.01) (0.98e1.03) (0.97e1.01) (0.99e1.01) (0.99e1.03) (0.93e1.02)
CI, confidence interval; HDL, high-density lipoprotein; OR, odds ratio. MetS and its individual altered components were entered as yes/no variables. The number of MetS components was entered as a continuous variable, from 0 to 5. Models adjusted for age (years, continuous), education (years, continuous), marital status (married, yes/no), current smoking (yes/no), Mini-Mental State Examination score (continuous, 0e30), Mini-Nutritional Assessment score (continuous, 0e30), diabetes mellitus (yes/no), and use of antihypertensive, antiplatelet, and lipid-lowering drugs (yes/ no). *P < .001. y P ¼ .001. http://dx.doi.org/10.1016/j.jamda.2016.01.005 1525-8610/Ó 2016 AMDA e The Society for Post-Acute and Long-Term Care Medicine.
2
Letter to the Editor / JAMDA xxx (2016) 1e2
The cross-sectional nature of this analysis does not allow us to elucidate what the direction of the association is, or what the underlying etiological mechanisms are; however, we can speculate about possible mechanisms linking MetS to greater risk of frailty. In addition to its classical diagnostic features, MetS is accompanied by peripheral insulin resistance, chronic micro-inflammation, activation of oxidative and prothrombotic mechanisms, and deregulation of the renin-angiotensin axis. All such mechanisms may potentially have a detrimental effect on various physiological domains, such as nutrition, neuromuscular system, and cognition.2e4 In particular, aging-associated skeletal muscle wasting, or sarcopenia, is among those central to the frailty syndrome. Pieces of evidence indicate a strong association between insulin resistance and chronic inflammation with accelerated sarcopenia, which may underlie the relationship between MetS and frailty.3,4 Furthermore, MetS has been associated with greater occurrence and severity of cerebral microvascular damage, a condition that may accelerate age-associated cognitive and functional decline, leading individuals to frailty. Frail persons are high users of health care resources, hospitalization, and nursing homes. Thus, identification of potentially preventable and modifiable risk factors for the condition is crucial. MetS affects 25% of people in the general adult population and 40% of those ages 65 years and older. Due to this huge prevalence, even a modest association with frailty would have great relevance. This preliminary study encourages the initiation of further larger investigations to assess whether MetS is an independent predictor of frailty.
References 1. Fried LP, Tangen CM, Walston J, et al. Frailty in older adults: Evidence for a phenotype. J Gerontol A Biol Sci Med Sci 2001;56:M146eM156. 2. Carriere I, Pérès K, Ancelin ML, et al. Metabolic syndrome and disability: Findings from the prospective three-city study. J Gerontol A Biol Sci Med Sci 2014;69: 79e86. 3. Barzilay JI, Blaum C, Moore T, et al. Insulin resistance and inflammation as precursors of frailty: The Cardiovascular Health Study. Arch Intern Med 2007; 167:635e641. 4. Abbatecola AM, Paolisso G. Is there a relationship between insulin resistance and frailty syndrome? Curr Pharm Des 2008;14:405e410. 5. The Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults. Executive summary of the third report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). JAMA 2001;285:2486e2497.
Giovanni Viscogliosi, MD Department of Epidemiology Surveillance and Promotion of Health National Institute of Health Rome, Italy Division of Gerontology Department of Cardiovascular Respiratory, Nephrologic Anesthesiologic and Geriatric Sciences “Sapienza” University Rome, Italy