Cognitive plasticity, cognitive functioning and quality of life (QoL) in a sample of young-old and old-old adults in southern Spain

Calero, M. Dolores; Pérez-Díaz, Ángel G. López; Navarro, Elena; Calero-García, María José

doi:10.1007/s40520-013-0012-2

Cited by 7 publications

(6 citation statements)

References 30 publications

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“…Also, changes in body weight have an impact on the rate of bone loss in the sense that “skinny” women (BMI <18.5 kg/m 2 ) more rapidly lose bone mass than women with stable body weight (0.8% annually), while women whose body weight increased with the time does not losing bone mass significantly (0.1%) (11, 12). Obesity has for years been considered as a protective factor for the development of the skeleton and osteoporosis, but recent clinical studies indicate that obesity has a negative effect on the quality of the bone despite normal values of bone density measured by densitometry of what is considered to be the result of increased mechanical pressure on the bone (13, 14). A significant percentage of fractures exactly happens in obese women because of the body structure or mechanism of injury (15).…”

Section: Discussionmentioning

confidence: 99%

Correlation of the Lipid Profile, BMI and Bone Mineral Density in Postmenopausal Women

Bijelic¹,

Balaban

Miličević

2016

Mater Sociomed

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Introduction:To the reduction of bone density and osteoporosis in postmenopausal women contribute elevated lipid parameters and Body Mass Index (BMI).Goal:The goal of our study was to determine the correlation between lipid parameters, BMI and osteoporosis in postmenopausal women.Material and methods:The study was carried out by matched type between experimental group and controls. The experimental group consisted of 100 females at postmenopausal age, in which by the DEXA method was diagnosed osteoporosis at the Department of Endocrinology, Diabetes and Metabolic Diseases, University Medical Center of RS during 2015-2016, while the control group consisted of 100 females in a postmenopausal age but without diagnosed osteoporosis. The groups were matched by age (± 2 years). To all participants of the study were carried out biochemical analysis of blood, or the analysis of the lipid profile that included total cholesterol, LDL cholesterol, triglycerides (TG) and HDL cholesterol, and was determined the values of BMI and waist circumference (WC).Results:Analysis of the data of our research shows that by the univariate logistic regression the values of lipid parameters total cholesterol (p=0.000), LDL (p=0.005) and TG (p=0.033) were significantly associated with osteoporosis, while in multivariate logistic model only total cholesterol (p= 0.018) was found as an independent risk factor for osteoporosis in postmenopausal women. BMI values were not statistically significantly associated with osteoporosis (p=0.727).Conclusion:On the decrease in bone mineral density and osteoporosis in postmenopausal women influence many risk factors whose identification has the aim to develop more effective prevention of this disease in the elderly.

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Section: Discussionmentioning

confidence: 99%

Correlation of the Lipid Profile, BMI and Bone Mineral Density in Postmenopausal Women

Bijelic¹,

Balaban

Miličević

2016

Mater Sociomed

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“…Thus, the model of third versus fourth age (Baltes, 1998; Baltes & Smith, 2003) argues that aging in advanced age is not a continuous process, but that instead one needs to qualitatively differentiate between young-old and old-old age groups due to discontinuity in aging. Empirically, this conceptual distinction between young-old and old-old age groups has been adopted in many research areas including psychology, epidemiology, physiology, demography, and sociology (e.g., Abdel-Ghany & Sharpe, 1997; Adams et al, 2011; Alterovitz & Mendelsohn, 2013; Ansah et al, 2015; Bodner et al, 2013; Buch et al, 1999; Calero et al, 2013; Gavazzi et al, 2002; Kvavilashvili et al, 2013; Menec & Chipperfield, 1997; Vaupel et al, 1998; Wright & Holliday, 2007; Wu et al, 2015; Yoshimura et al, 2013; Zinke et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Lower executive functioning predicts steeper subsequent decline in well-being only in young-old but not old-old age

Ihle

Ghisletta

Gouveia

et al. 2020

International Journal of Behavioral Development

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Objectives: From a longitudinal perspective, the direction of the relationship between cognitive functioning and well-being in old age, both conceptually and empirically, is still under debate. Therefore, we aimed to disentangle the different longitudinal relationship patterns proposed and whether those differed between young-old and old-old adults. Methods: We used latent change score modeling based on longitudinal data from 1,040 older adults ( M = 74.54 years at Time 1 [T1], median = 73 years) to analyze reciprocal lead–lag relationships over 6 years in executive functioning (trail making test [TMT] completion time) and well-being (life satisfaction), taking into account chronological age, sex, education, leisure activities, and chronic diseases. Results: In young-old adults (<73 years), longer TMT completion time at T1 (i.e., lower executive functioning status) significantly predicted steeper subsequent decline in well-being. This was not the case for old-old adults (≥73 years), for whom this relationship was significantly different from that of the young-old (moderation effect). In either group, well-being status at T1 did not predict changes in TMT completion time. Discussion: Lower executive functioning may predict a subsequent decline in well-being in young-old adults only. Wider implications in a context of promotion of healthy aging are discussed.

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“…For a sample selection, researchers have often to return to “practical” strategies such as splitting the available old age sample into two halves. Therefore, in most studies comparing young-old and old-old adults, the decision had to remain rather arbitrary and the old-old age group was stratified to be at least 75 years [7,16,17,18,19], 80 years [10,20,21,22,23,24], or 81 years [25,26], with the young-old age group being respectively below this age. Yet, in comparison to that, in some studies the old-old age group was relatively young, stratified to be at least 70 years [27] or 71 years [28].…”

Section: Introductionmentioning

confidence: 99%

“…Specifically, we investigated the domains cognitive abilities (i.e., processing speed and verbal abilities as markers for fluid and crystallized intelligence), general health status, activity participation, and life satisfaction as they concern important aspects of everyday functioning in old age [1,2,3,4,5,6,7,8,9,10,11,12,22,24,25,26,27,28,29,30,31,32,33,34,35]. For processing speed, verbal abilities, general health status, and activity participation, evidence typically shows a decline in old age, with sharp gradients in old-old age [1,2,3,10,30,31,32].…”

Section: Introductionmentioning

confidence: 99%

Investigating Discontinuity of Age Relations in Cognitive Functioning, General Health Status, Activity Participation, and Life Satisfaction between Young-Old and Old-Old Age

Ihle

Jopp

Fagot

et al. 2016

IJERPH

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Health research suggests that findings on young-old adults cannot be generalized to old-old adults and thus that old-old age seems not a simple continuation of young-old age due to qualitative changes that result in a discontinuity in old age. Specifically, it would be of conceptual and methodological importance to inform research regarding estimates around which chronological age the beginning of old-old age could be placed at a population level, and whether this is universal or domain-specific. To derive such criteria, we investigated potential discontinuity of age relations between young-old and old-old age in a large population-based sample considering measures in different domains (processing speed, verbal abilities, general health status, activity participation, and life satisfaction). For processing speed, verbal abilities, general health status, and life satisfaction we observed some very small indication that there might be a discontinuity of age relations at the end of individuals’ eighties, and for activity participation already at the beginning of individuals’ eighties. In conclusion, models conceptualizing aging as a gradual development might not suffice to adequately represent the differences between the stages of young-old and old-old age due to some very small indication that there might be discontinuity in late adulthood.

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Cognitive plasticity, cognitive functioning and quality of life (QoL) in a sample of young-old and old-old adults in southern Spain

Cited by 7 publications

References 30 publications

Correlation of the Lipid Profile, BMI and Bone Mineral Density in Postmenopausal Women

Correlation of the Lipid Profile, BMI and Bone Mineral Density in Postmenopausal Women

Lower executive functioning predicts steeper subsequent decline in well-being only in young-old but not old-old age

Investigating Discontinuity of Age Relations in Cognitive Functioning, General Health Status, Activity Participation, and Life Satisfaction between Young-Old and Old-Old Age

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