The association between nutritional status and cognitive impairment in Brazilian community-dwelling older adults assessed using a range of anthropometric measures - the Bambui Study

Castro-Costa, Érico; Peixoto, Sérgio V.; Firmo, Josélia O.A.; Uchoa, Elizabeth; Lima-Costa, Maria Fernanda F.

doi:10.1590/S1980-57642013DN74000008

ABSTRACT

In most studies, body mass index (BMI) has been used as the main measurement of nutritional status. However, BMI does not differentiate between body fat and muscle mass.

Objective:

To investigate the association between nutritional status and cognitive impairment in a population of Brazilian elderly. Methods: Participants (n=1,496) from the Bambuí Cohort Study of Aging were selected based on the results for the two variables nutritional status and cognitive impairment (MMSE score). Gender, age, education, lifestyle, ApoE, chronic diseases, depressive symptoms, current use of hypnotic or sedative medication and functional disability were used as confounding factors for adjusting the logistic regression.

Results:

Cognitive impairment was associated with lower BMI (OR: 0.91; CI: 0.86-0.95), waist circumference (OR: 0.97; CI: 0.95-0.99), triceps skinfold thickness (OR: 0.92; CI: 0.89-0.96) among the younger participants (60-69 years), while lower arm muscle circumference (OR: 0.88; CI: 0.80-0.98) and corrected arm muscle area (OR: 0.96; CI: 0.93-0.99) were associated with cognitive impairment among the older participants (70 years and over).

Conclusion:

There was a difference of association between anthropometric measures and cognitive impairment after stratifying by age group. In the group aged between 60 and 69, cognitive impairment was associated with measures related to fat mass, while in the group aged over 70, cognitive impairment was associated with measures related to muscle mass. This finding suggests that investigation of nutritional status in the elderly using anthropometric measures should not be restricted only to the use of BMI, and should also, differ according to age.

Key words:
nutritional status; cognitive impairment; anthropometric measures; elderly; population-based.

RESUMO

Na maioria dos estudos o índice de massa corporal (IMC) é usado como a principal medida de avaliação do estudo nutricional. Entretanto, o IMC não apresenta capacidade de diferenciar a gordura corporal da massa muscular.

Objetivo:

Investigar a associação do estado nutricional e o comprometimento cognitivo na população idosa de Bambuí.

Métodos:

Participaram do estudo 1496 idosos que responderam simultaneamente as variáveis do estado nutricional e o comprometimento cognitivo (avaliado através do escore do MMSE). As seguintes variáveis: sexo, idade, educação, estilo de vida, ApoE, doenças crônicas, sintomas depressivos, uso de medicamentos hipnóticos e sedativos e incapacidade funcional foram utilizadas como fatores de confusão na regressão logística multivariada.

Resultados:

O comprometimento cognitivo foi associado com os baixos valores de: IMC (OR: 0.91; CI: 0.86-0.95), circunferência da cintura (OR: 0.97; CI: 0.95-0.99), dobra cutânea triciptal (OR: 0.92; CI: 0.89-0.96) entre os idosos mais jovens (60-69 anos). Enquanto que baixos valores da circunferência (OR: 0.88; CI: 0.80-0.98) e da area muscular do braço corrigida (OR: 0.96; CI: 0.93-0.99) foram associados com o comprometimento cognitivo entre os idosos mais velhos (70 anos ou mais).

Conclusão:

Existe uma diferença entre a associação das medidas antropométricas e o comprometimento cognitivo após a estratificação por idade. Nos participantes entre 60 a 69 anos, o comprometimento cognitivo foi associado a medidas relacionadas com o tecido adiposo enquanto que no grupo com 70 anos ou mais, o comprometimento cognitivo foi associado a medidas relacionadas com a massa muscular. Esses achados sugerem que a investigação do estado nutricional dos idosos não se deve restringir somente ao IMC, sendo necessário variações devido a idade.

Palavras-chave:
estado nutricional; comprometimento cognitivo; medidas antropométricas; idosos; base-populacional.

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REFERENCES

¹
Lee KS, Cheong HK, Kim EA, Kim KR, OH BH, Hong CH. Nutritional risk and cognitive impairment in the elderly. Arch Gerontol Geriatr 2009;48:95-99.
²
White H, Pieper C, Schmader K. The asociation of weight change in Alzheimer's disease with severity of disease and mortality:a longitudinal analysis. J Am Geriatr Soc 1998;46:1223-1227.
³
Saka B, Kaya O, Ozturk GB, Erten N, Karan MA. Malnutrition in the elderly and its relationship with other geriatric syndromes. Clin Nutr 2010;29:745-748.
⁴
Fagerstrom C, Palmqvist R, Johanna, Hellstrom Y. Malnutrition and cognitve impairment among people 60 years of age and above living in regular housing and in special housing in Sweden:a population-based cohort study. Int J Nurs Studies 2011;48:863-871.
⁵
World Health Organization. World Health Report 2003 - Shapping the future. WHO, Geneve, 2003.
⁶
Zekry D, Hermann FR, Grandjean R, et al. Demented versus non-demented very old inpatients:the same comorbidities but poorer functional and nutritional status. Age Ageing 2008;37:83-89.
⁷
Khater MS, Abouelezz NF. Nutritional status in older adults with mild cognitive impairment. J Nutr Health Aging 2011;15:104-108.
⁸
Beck AM, Ovesen L. At which body mass índex and degree of weight loss should hospitalized eldelry patients be considered at nutritional risk? Clin Nutr 1998;17:195-198.
⁹
Nutrition Screening Initiative. Nutrition interventions manual for professionals caring for older Americans. Washington DC:Nutrition Screening; 1994.
¹⁰
Lipschitz DA. Screening for nutritional status in the elderly. Prim Care 1994;21:55-67.
¹¹
World Health Organization. Obesity:preventing and managing the global epidemic. Reporto f a WHO Consultation on Obesity. Geneva:World Health Organization;1998.
¹²
Poulsen I. 2005. Functional and Nutritional Assessment in Geriatric Rehabilitation. A Feasibility Study. Lund University. Lund
¹³
Guo SS, Zeller C, Chumlea WC, Siervogel RM. Aging body composition and lifestyle:the Fels Longitudinal Study. Am J Clin Nutr 1999;70, 405-411.
¹⁴
Burns JM, Johnson DK, Watts A, et al. Reduced lean mass in early Alzheimer Disease and its association with brain atophy. Arch Neurol 2010;67:428-433
¹⁵
Nourhashemi F, Andrieu S, Gillette-Guyonnet S, et al. Is there a relationship between fat-free soft tissue mass and low cognitive function? Results from a study of 7,105 women. J Am Geriatr Soc 2002;50:1796-1801.
¹⁶
Frisancho AR. 1981. New norms of upper limb fat and muscle áreas for assessment of nutritional status. Am J Clin Nutr 1981;34:2540-2545.
¹⁷
Carlsson M, Gustafson Y, Eriksson S, Haglin L. Body composition in Swedish old people aged 65-99 years, living in residential care facilities. Arch Gerontol Geriatr 2009;49:98-107.
¹⁸
Costa MFFL, Uchoa E, Guerra HL, Firmo JOA, Vidigal PG, Barreto SM. The Bambui Health and Ageing Study (BHAS):methodological approach and preliminary results of a population-based study of the elderly in Brazil. Rev Saúde Publica 2000;34:126-135.
¹⁹
Lima-Costa MF, Firmo JO, Uchoa E .Cohort profile:the Bambui (Brazil) Cohort Study of Ageing. Int J Epidemiol 2011;40:862-867.
²⁰
Seabra MLV, Concilio G, Villares JB, et al. Avaliação do teste "Mini-mental state" em voluntários e pacientes brasileiros. Revista ABP-APL. 1990;12:1-29
²¹
Folstein MF, Folstein S, MCHugh PR. Mini-Mental State:a practical method for grading the cognitive state of patients for the clinician. J Psychiat Res 1975;12:189-198.
²²
Castro-Costa E, Fuzikawa C, Ferri CP, et al. Dimensions underlying the Mini-Mental State Examination in a sample with low-education levels:the Bambui Health and Aging Study. Am J Geriatr Psychiatry. 2009;17:863-872.
²³
Castro-Costa E, Fuzikawa C, Uchoa E, Firmo JOA, Lima-Costa MF. Norms for the Mini-Mental State Examination - Adjustment of the cut-off point in population-based studies (evidences of the Bambui health aging study). Arq Neuropsiquiatr 2008;66:524-528
²⁴
Gurney JM, Jelliffe DB. Arm anthropometry in nutritional assessment: nomogram for rapid calculation of muscle circumference and cross-sectional muscle and fat áreas. Am J Clin Nutr 1973;26:912-915.
²⁵
Heymsfield SB, McManus C, Smith J. Stevens V, Nixon DW. Anthropometric measurement of muscle mass: Revised equations for calculating bone-free arm muscle area. Am J Clin Nutr 1982;36:680-690.
²⁶
Chobanian AV, Bakris GL, Black HR, et al. The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report. JAMA 2003;289: 2560-2572.
²⁷
, Genuth S, Alberti KG, Bennett P, et al. Follow-up report on the diagnosis of diabetes mellitus. Diabetes Care. 2003;26:3160-3167.
²⁸
Costa E, Barreto SM, Uchoa E, Firmo JO, Lima-Costa MF. Prince M.Is the GDS-30 better than the GHQ-12 for screening depression in elderly people in the community? The Bambui Health Aging Study (BHAS). Int Psychogeriatr 2006;18:493-503.
²⁹
Loyola-Filho Al, Uchoa E, Guerra HL, Firmo JO, Lima-Costa MF. Prevalence and factors associated with self-medication:the Bambuí Health Survey. Rev Sauce Publica 2002;36:55-62.
³⁰
Katz S, Ford AB, Moskowitz RW, Jackson BA, Jaffe MW. Studies of Illness in the Aged. The Index of Adl:A Standardized Measure of Biological and Psychosocial Function. JAMA 1963;185:914-919.
³¹
StataCorp, Stata Statistical Software, RCS. TX:StataCorp LP. 2005.
³²
Vasconcelos FAG, Cordeiro BA, Rech CR, Petroski EL. Sensibilidade e especificidade do indice de massa corporal no diagnóstico de sobrepeso/obesidade em idosos. Cad Saude Publica, 2010;26:1519-1527.
³³
Albanese CV, Diessel E, Genant HK. Clinical applications of body composition measurements using DXA. J Clin Densitom 2003;6:75-85.
³⁴
Jebb S. Workshop on body composition methodology. Proc Soc 1995. 569-577.
³⁵
Brucki SMD, Nitrini R, Caramelli P, Bertolucci PHF, Okamato IH. Sugestões para o uso do Mini-Exame do Estado Mental no Brasil. Arq Neuropsiquiatr, 2003;61:777-781.
³⁶
Nitrini R, Lefevre BH, Mathias SC, et al. Testes neuropsicológicos de aplicação simples para o diagnóstico de demência. Arq Neuropsiquiatr 1994;52:457-465.
³⁷
Orsitto G. Different components of nutritional status in older inpatients with cognitive impairment. J Nutr Health Aging 2012;16:468-471.
³⁸
Ding J, Kritchevsky SB, Newman AB, et al. Effects of birth cohort and age on body composition in a sample of community-based elderly. Am J Clin Nutr 2007;85:405-410.
³⁹
Visser M, Kritchevsky SB, Goodpaster BH, et al. Leg muscle mass and composition in relation to lower extremity performance in men and women aged 70 to 79:the health, aging and body composition study. J Am Geriatr Soc 2002;50:897-904.

Publication Dates

Publication in this collection
Dec 2013

History

Received
10 Aug 2013
Accepted
15 Nov 2013

This is an open-access article distributed under the terms of the Creative Commons Attribution License

[1] ¹
Lee KS, Cheong HK, Kim EA, Kim KR, OH BH, Hong CH. Nutritional risk and cognitive impairment in the elderly. Arch Gerontol Geriatr 2009;48:95-99.

[2] ²
White H, Pieper C, Schmader K. The asociation of weight change in Alzheimer's disease with severity of disease and mortality:a longitudinal analysis. J Am Geriatr Soc 1998;46:1223-1227.

[3] ³
Saka B, Kaya O, Ozturk GB, Erten N, Karan MA. Malnutrition in the elderly and its relationship with other geriatric syndromes. Clin Nutr 2010;29:745-748.

[4] ⁴
Fagerstrom C, Palmqvist R, Johanna, Hellstrom Y. Malnutrition and cognitve impairment among people 60 years of age and above living in regular housing and in special housing in Sweden:a population-based cohort study. Int J Nurs Studies 2011;48:863-871.

[5] ⁵
World Health Organization. World Health Report 2003 - Shapping the future. WHO, Geneve, 2003.

[6] ⁶
Zekry D, Hermann FR, Grandjean R, et al. Demented versus non-demented very old inpatients:the same comorbidities but poorer functional and nutritional status. Age Ageing 2008;37:83-89.

[7] ⁷
Khater MS, Abouelezz NF. Nutritional status in older adults with mild cognitive impairment. J Nutr Health Aging 2011;15:104-108.

[8] ⁸
Beck AM, Ovesen L. At which body mass índex and degree of weight loss should hospitalized eldelry patients be considered at nutritional risk? Clin Nutr 1998;17:195-198.

[9] ⁹
Nutrition Screening Initiative. Nutrition interventions manual for professionals caring for older Americans. Washington DC:Nutrition Screening; 1994.

[10] ¹⁰
Lipschitz DA. Screening for nutritional status in the elderly. Prim Care 1994;21:55-67.

[11] ¹¹
World Health Organization. Obesity:preventing and managing the global epidemic. Reporto f a WHO Consultation on Obesity. Geneva:World Health Organization;1998.

[12] ¹²
Poulsen I. 2005. Functional and Nutritional Assessment in Geriatric Rehabilitation. A Feasibility Study. Lund University. Lund

[13] ¹³
Guo SS, Zeller C, Chumlea WC, Siervogel RM. Aging body composition and lifestyle:the Fels Longitudinal Study. Am J Clin Nutr 1999;70, 405-411.

[14] ¹⁴
Burns JM, Johnson DK, Watts A, et al. Reduced lean mass in early Alzheimer Disease and its association with brain atophy. Arch Neurol 2010;67:428-433

[15] ¹⁵
Nourhashemi F, Andrieu S, Gillette-Guyonnet S, et al. Is there a relationship between fat-free soft tissue mass and low cognitive function? Results from a study of 7,105 women. J Am Geriatr Soc 2002;50:1796-1801.

[16] ¹⁶
Frisancho AR. 1981. New norms of upper limb fat and muscle áreas for assessment of nutritional status. Am J Clin Nutr 1981;34:2540-2545.

[17] ¹⁷
Carlsson M, Gustafson Y, Eriksson S, Haglin L. Body composition in Swedish old people aged 65-99 years, living in residential care facilities. Arch Gerontol Geriatr 2009;49:98-107.

[18] ¹⁸
Costa MFFL, Uchoa E, Guerra HL, Firmo JOA, Vidigal PG, Barreto SM. The Bambui Health and Ageing Study (BHAS):methodological approach and preliminary results of a population-based study of the elderly in Brazil. Rev Saúde Publica 2000;34:126-135.

[19] ¹⁹
Lima-Costa MF, Firmo JO, Uchoa E .Cohort profile:the Bambui (Brazil) Cohort Study of Ageing. Int J Epidemiol 2011;40:862-867.

[20] ²⁰
Seabra MLV, Concilio G, Villares JB, et al. Avaliação do teste "Mini-mental state" em voluntários e pacientes brasileiros. Revista ABP-APL. 1990;12:1-29

[21] ²¹
Folstein MF, Folstein S, MCHugh PR. Mini-Mental State:a practical method for grading the cognitive state of patients for the clinician. J Psychiat Res 1975;12:189-198.

[22] ²²
Castro-Costa E, Fuzikawa C, Ferri CP, et al. Dimensions underlying the Mini-Mental State Examination in a sample with low-education levels:the Bambui Health and Aging Study. Am J Geriatr Psychiatry. 2009;17:863-872.

[23] ²³
Castro-Costa E, Fuzikawa C, Uchoa E, Firmo JOA, Lima-Costa MF. Norms for the Mini-Mental State Examination - Adjustment of the cut-off point in population-based studies (evidences of the Bambui health aging study). Arq Neuropsiquiatr 2008;66:524-528

[24] ²⁴
Gurney JM, Jelliffe DB. Arm anthropometry in nutritional assessment: nomogram for rapid calculation of muscle circumference and cross-sectional muscle and fat áreas. Am J Clin Nutr 1973;26:912-915.

[25] ²⁵
Heymsfield SB, McManus C, Smith J. Stevens V, Nixon DW. Anthropometric measurement of muscle mass: Revised equations for calculating bone-free arm muscle area. Am J Clin Nutr 1982;36:680-690.

[26] ²⁶
Chobanian AV, Bakris GL, Black HR, et al. The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report. JAMA 2003;289: 2560-2572.

[27] ²⁷
, Genuth S, Alberti KG, Bennett P, et al. Follow-up report on the diagnosis of diabetes mellitus. Diabetes Care. 2003;26:3160-3167.

[28] ²⁸
Costa E, Barreto SM, Uchoa E, Firmo JO, Lima-Costa MF. Prince M.Is the GDS-30 better than the GHQ-12 for screening depression in elderly people in the community? The Bambui Health Aging Study (BHAS). Int Psychogeriatr 2006;18:493-503.

[29] ²⁹
Loyola-Filho Al, Uchoa E, Guerra HL, Firmo JO, Lima-Costa MF. Prevalence and factors associated with self-medication:the Bambuí Health Survey. Rev Sauce Publica 2002;36:55-62.

[30] ³⁰
Katz S, Ford AB, Moskowitz RW, Jackson BA, Jaffe MW. Studies of Illness in the Aged. The Index of Adl:A Standardized Measure of Biological and Psychosocial Function. JAMA 1963;185:914-919.

[31] ³¹
StataCorp, Stata Statistical Software, RCS. TX:StataCorp LP. 2005.

[32] ³²
Vasconcelos FAG, Cordeiro BA, Rech CR, Petroski EL. Sensibilidade e especificidade do indice de massa corporal no diagnóstico de sobrepeso/obesidade em idosos. Cad Saude Publica, 2010;26:1519-1527.

[33] ³³
Albanese CV, Diessel E, Genant HK. Clinical applications of body composition measurements using DXA. J Clin Densitom 2003;6:75-85.

[34] ³⁴
Jebb S. Workshop on body composition methodology. Proc Soc 1995. 569-577.

[35] ³⁵
Brucki SMD, Nitrini R, Caramelli P, Bertolucci PHF, Okamato IH. Sugestões para o uso do Mini-Exame do Estado Mental no Brasil. Arq Neuropsiquiatr, 2003;61:777-781.

[36] ³⁶
Nitrini R, Lefevre BH, Mathias SC, et al. Testes neuropsicológicos de aplicação simples para o diagnóstico de demência. Arq Neuropsiquiatr 1994;52:457-465.

[37] ³⁷
Orsitto G. Different components of nutritional status in older inpatients with cognitive impairment. J Nutr Health Aging 2012;16:468-471.

[38] ³⁸
Ding J, Kritchevsky SB, Newman AB, et al. Effects of birth cohort and age on body composition in a sample of community-based elderly. Am J Clin Nutr 2007;85:405-410.

[39] ³⁹
Visser M, Kritchevsky SB, Goodpaster BH, et al. Leg muscle mass and composition in relation to lower extremity performance in men and women aged 70 to 79:the health, aging and body composition study. J Am Geriatr Soc 2002;50:897-904.

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