Executive Function and Physical Function Among Community-Dwelling Egyptian Older Adults

Abstract

Background:

The ongoing scientific debate regarding the association between physical function and cognitive impairment has focused mainly on global cognitive performance rather than specific cognitive functions tests and the importance of recognition of its associations and any factors that could play a role later in the prevention of such decline.

Objective:

This study examined the association between physical function, using handgrip strength (HGS) and Timed Up-and-Go test (TUGT), and executive function (EF), using Clock Drawing Test (CDT), among community-dwelling Egyptian elderly.

Methods:

A cross-sectional study was conducted in 5 social clubs in Cairo, Egypt and included a sample of 136 elderly males and females aged≥55 years old. All participants had their physical function assessed using TUGT, and measurement of HGS using a pneumatic hand-held dynamometer. Assessment of EF using CDT was also done.

Results:

Higher CDT scores were significantly associated with both better HGS, and lower TUGT (OR = 3.77, and 0.65 respectively). This persisted even after adjustment for age and gender (OR = 2.56, and 0.71 respectively) and after further adjustment for weight, systolic blood pressure, education, smoking, hyperlipidemia, hypothyroidism, and physical activity (O.R. = 4.79, and 0.76 respectively). Adjustment for both male and female genders showed an association between physical (HGS and TUGT) and EF was stronger among men.

Conclusion:

A strong association between CDT score and both of HGS and TUGT was found among the studied sample. Higher HGS and lower TUGT was significantly associated with better performance in the CDT. This association is stronger in males than in females for both HGS and TUGT.

Keywords

Clock Drawing Test elderly executive function handgrip strength Timed Up-and-Go test

INTRODUCTION

Physical functioning and cognitive abilities are im-portant areas of well-being in older adults; both are related to outcomes such as health and mortality [1]. Aging is associated with progressive muscle mass loss which results in decreased muscle strength. Decreased muscle strength is linked to disability, physical frailty, and other age-related health complications. Furthermore, maintaining muscle strength is crucial to reducing functional limitations among older people [2].

Handgrip strength (HGS) is used as an indicator of overall body muscle function and overall physical health status, particularly among older persons [3]. Timed Up-and-Go test (TUGT) is another important tool for assessment of physical performance in elderly [4].

Understanding age-related cognitive decline and the factors that could alleviate such decline for proper early intervention is warranted [5]. Clock drawing Test (CDT) is considered a sensitive and specific adjunct for detecting cognitive dysfunction, even with normal Mini-Mental State Examination (MMSE) [6]. It is also one of the most used tools for assessment of executive function (EF) [7].

Scientists have studied the link between cognitive and physical functioning (using TUGT) among eld-erly and found contradictory results [8, 9]. However, a connection between handgrip strength and certain cognitive abilities (e.g., processing speed, verbal ability, spatial ability, and memory) has been suggested [10]. Furthermore, two recent meta-analyses have linked HGS with global cognitive performance [11, 12]. Only a few studies focused on EF and its association with physical function. The current study aimed to assess whether physical function, assessed by HGS and TUGT, is associated with EF using CDT.

METHODS

This cross-sectional study ran from March to Sep-tember 2018. Older adults ≥55 years old, who received ≥4 years of education were recruited from 5 social clubs in Cairo, Egypt. Every 3rd participant was included in the study. If for any reason he/she was not included (refused to participate or did not fit the inclusion criteria), the next participant was chosen. Exclusion criteria included aphasia, severe visual or hearing impairment, inability to stand or walk, or presence of hand deformities or weakness.

Study tools

The following was done to all participants:

Structured interview questionnaire: This was used to collect sociodemographic characteristics, medical history, and review of medical records.

Weight, height, and body mass index (BMI) measurement: Standing height was measured to the nea-rest 0.5 cm using a stadiometer with a fixed vertical backboard and an adjustable headpiece. Weight was determined on a standardized scale placed on a hard-floor surface. Measurements were recorded to the nearest 0.5 kg. BMI was calculated as weight (in kg) divided by height squared (by m²).

Blood pressure measurement: Blood pressure was taken using a standard mercury sphygmomanometer in the right arm, in a sitting position after rest for 5 min. Systolic and diastolic blood pressures were recorded as the mean of two measurements.

Handgrip strength measurement: HGS is a simple, non-invasive, reliable, and low-cost screening technique which does not require extensive training [13]. Dominant handgrips strength was assessed using Baseline® pneumatic squeeze handheld dyn-amometer. All subjects were instructed to sit on the chair with a straight back, without armrest and with the feet flat on the floor, shoulder adducted, and neutrally rotated elbow flexed at 90, forearm in neutral position and wrist between 0–30 of extension and between 0–15 of ulnar deviation, as instructed by the American Society of Hand Therapy [14].

Timed Up-and-Go test (TUGT): Every participant was instructed to rise from a chair, walk three meters, turn around, walk back to the chair, and sit down. During the test, the person is expected to wear their regular footwear and use any mobility aids that they would normally require. A score of more than or equal to fourteen seconds was considered as indicative of high risk of falls [15].

Activity level: We used World Health Organization (WHO) classification of physical activity to categorize activity level: Inactive (zero min/week), less than minimum activity (<150 min/week), or sufficient activity (≥150 min/week) [16].

Cognitive assessment: The Mini-Cog Test using 3 words recall together with the Clock drawing test [17] that was scored according to Shua-Haim et al. simple scoring system was used. One point was awarded for each of the following: approximate drawing of the clock face; the presence of numbers in sequence; a correct spatial arrangement of numbers; presence of clock hands; hands showing approximately the correct time; and hands depicting the exact time [18]. This scoring method has sensitivity and specificity of 86%, which is among the highest values compared to other scoring methods [19].

Ethical considerations

This study was conducted according to the guidelines laid down in the Declaration of Helsinki. It was approved by the Ethical Committee of the Geriatrics and Gerontology Department. Informed consent was taken from all participants.

Table 2

Association between CDT and HGS, using unadjusted and adjusted models

Parameter	p	OR	95%CI for OR
			Lower	Upper
CDT, unadjusted	0.004	3.77	1.52	9.34
CDT interaction with male gender	<0.001	6.408	5.712	7.189
CDT interaction with female gender	<0.001	1.829	1.625	2.060
CDT, adjusted model^*	0.035	2.56	1.07	6.11
CDT interaction with male gender^*	<0.001	6.399	5.703	7.179
CDT interaction with female gender^*	<0.001	1.608	1.425	1.816
CDT, adjusted model^**	<0.001	4.79	4.11	5.58
CDT interaction with male gender^**	<0.001	5.481	4.836	6.212
CDT interaction with female gender^**	<0.001	1.320	1.149	1.516

CDT, clock drawing test; HGS, hand grip strength; ^* adjustment for age, gender, ^**adjustment for age, gender, weight, SBP, education level, smoking status, hyperlipidemia, hypothyroidism, and level of activity.

Statistical analysis

SPSS version 19 (SPSS Inc., Chicago, IL, USA) was used for data analysis. Quantitative data were expressed in the form of number and percentage. Qua-litative data were expressed in the form of mean±SD, or median (interquartile). Adjusted and unadjusted generalized linear models were used to assess the association between HGS of the dominant hand and CDT scores. The linear models were adjusted for age, gender, weight, systolic blood pressure (SBP), an education level (those with education less than secondary school versus higher education), smoking status, history of hyperlipidemia, or hypothyroidism and activity level.

RESULTS

Table 1

Description of the study sample sociodemographic and medical characteristics

Parameters	Value
Gender, male, n (%)	44 (32.4%)
Current smokers, n (%)	21 (15.4%)
Physical activity, n (%)
Sufficient activity	34 (25.0%)
Less than minimum activity	31 (22.8%)
Inactive	71 (52.2%)
DM, n (%)	34 (25.0%)
HTN, n (%)	76 (55.9%)
History of dyslipidemia, n (%)	28 (20.6%)
Hypothyroidism, n (%)	9 (6.6%)
Age, mean (±SD)	66.58(±6.87)
HGS dominant hand, median (interquartile)	11 (9–13.63)
HGS, nondominant hand, median (interquartile)	10 (7–13)
CDT, mean (±SD)	4.493 (±1.54)
SBP, mean (±SD)	131.65 (±17.80)
DBP, mean (±SD)	76.74 (±9.86)
TUGT, mean (±SD)	11.07 (±2.64)
Recall Test (3pointsrecall) mean (±SD)	2.41

CDT, clock drawing test; DBP, diastolic blood pressure; DM, diabetes mellitus; HGS, hand grip strength; HTN, hypertension; SBP, systolic blood pressure; TUGT, Timed Up-and-Go test.

The total number of participants was 136; 92 (67.6%) were females and 44 (32.4%) were males. Their mean age was 66.58±6.87 years old, and 25%were physically active (i.e., practicing exercise more than or equal to 150 min per week).

Higher CDT was associated significantly with bet-ter HGS of the dominant hand (Odds ratio (OR) = 3.77), this the association persisted even after adju-stment for age and gender (OR = 2.56) and with further adjustment for weight, SBP, education level (those with education less than secondary school versus higher education), smoking status, hyperlipi-demia, hypothyroidism, and activity level (p < 0.001, OR = 4.79, and 95%confidence interval (CI) = 4.11–5.58). Adjustment for both male and female genders in unadjusted and adjusted models revealed a stronger association among elderly males when compared to females (OR = 6.408, 6.399, 5.481 versus 1.829, 1.608, 1.320, respectively).

Higher CDT was associated significantly with lower TUGT (OR = 0.65), this association persisted even after adjustment for age and gender (OR = 0.71) and with further adjustment for weight, SBP, education level (those with education less than secondary school versus higher education), smoking status, hyp-erlipidemia, hypothyroidism, and activity level (OR = 0.76). Adjustment for both male and female genders in unadjusted and adjusted models revealed a stronger association among elderly females when compared to males (O.R. 0.626, 0.621, 0.708 versus 0.691, 0.728, 0.863, respectively).

Table 3

Association between CDT and TUGT, using unadjusted and adjusted models

Parameter	p	OR	95%CI for OR
			Lower	Upper
CDT, unadjusted	<0.001	0.652	0.58	0.73
CDT interaction with male gender	<0.001	0.626	0.557	0.704
CDT interaction with female gender	<0.001	0.691	0.612	0.781
CDT, adjusted model^*	<0.001	0.71	0.63	0.79
CDT interaction with male gender^*	<0.001	0.621	0.553	0.698
CDT interaction with female gender^*	<0.001	0.728	0.643	0.824
CDT, adjusted model^**	<0.001	0.76	0.66	0.88
CDT interaction with male gender^**	<0.001	0.708	0.624	0.803
CDT interaction with female gender^**	0.037	0.863	0.752	0.991

CDT, clock drawing test; TUGT, Timed Up-and-Go test; ^*adjustment for age, gender; ^**adjustment for age, gender, weight, SBP, education level, smoking status, hyperlipidemia, hypothyroidism, and level of activity.

Further interpretation of the results revealed positive correlation between CDT and Mini-Cog (r = 0.573) with high statistically significant difference and this correlates with good and intact cognitive function (Table 4).

Table 4

Association between CDT, HGS, TUGT, Recall and Mini-Cog

Parameter	p	OR	95%CI for OR
			Lower	Upper
Mini-Cog interaction with CDT	<0.001	0.573	0.446	0.675
Mini-Cog interaction with HGS	0.121	0.135	–0.036	0.297
Mini-Cog interaction with TUGT	<0.001	–0.295	–0,446	–0.127
Mini-Cog interaction with Recall	<0.001	0.778	0.700	0.836

CDT, clock drawing test; TUGT, Timed Up-and-Go test; HGS, Hand grip strength.

Association between Mini-Cog and physical function revealed negative correlation between Mini-Cog and TUGT (r = –0.295) with high statistically significant difference and positive correlation with handgrip strength (r = 0.135) with no statistically significant difference. Intact recall is associated with high Mini-Cog score (r = 0.778) with high statistically significant difference.

DISCUSSION

The current study revealed that HGS is strongly associated with executive function, assessed using CDT, but not with Mini-Cog test among community-dwelling Egyptian elderly in both unadjusted and adjusted models. TUGT was strongly associated with both CDT and Mini-Cog. Most studies examining the association between cognition and physical function used MMSE which indicates only global cognition [20]. Yet, this is not all-encompassing because cognition has multiple domains, [21] and EF (executive functions) is considered a crucial cognitive function for many aspects of life [22].

Many prospective studies examined the relation between physical function and global cognition. The study of Van Gelder et al. followed 295 elderly men born between 1900 and 1920 for more than ten years in the FINE Study, and they reported a 3.5-fold greater decline in cognition among individuals who walked less compared to those who walked more than 3 miles per day [23].

A follow-up study over 4.4 years also reported a significant association between physical function measures, including HGS, with the strongest association for walking speed with cognitive impairment as assessed by MMSE score < 24 [24].

All the previous studies applied global cognitive assessment tools. On the other hand, Malmstrom found a significant association between physical performance and both MMSE and animal fluency test among middle-aged African Americans [25].

Vaz-Patto and colleagues conducted a study am-ong centenarians and found a significant association between MMSE and physical activity assessed by HGS and time spent in the 3-meter walk as well [26]. The study of Jang and Kim among Korean elders reported a significant association between levels of higher HGS and reduced risk for mild cognitive impairment. Furthermore, better HGS was associated with higher cognitive performance, using Korea-MMSE, in cognitively intact elderly individuals [27].

Several meta-analyses addressed this. One rather recent one found that physical performance was associated with cognitive performance [12]. Another meta-analysis including 36 studies examined cohorts for the relation between physical function and cognition, 3 of which assessed executive function and revealed a significant association between executive function and gait speed. HGS was strongly correlated with MMSE in that meta-analysis [20].

An intervention study conducted by Scherder and col. involving light physical exercise in older old showed improvements in tests assessing executive functions, despite a casuistic of only forty-three participants [28].

Cross-sectional studies have linked decline in muscle mass or strength to global cognitive function [11, 30]. In an observational study on 120 elderly, Bixby and colleagues found a significant correlation between better performance on the Stroop test and higher levels of physical activity [29].

Chang and colleagues in their meta-analysis; including seven cross-sectional studies, found that sarcopenia (defined by low muscle mass or function; using HGS, time spent in the 3-meter walk or gait speed) was strongly associated with cognition ass-essed using different cognitive assessment tools [11].

Few researchers focused mainly on executive function as Kobayashi-Cuya et al. whose results were inconsistent with our data. Although they found HGS not associated with executive function, hand dexterity was. However, in their study among community-dwelling older adults, HGS was not associated with hand dexterity. They gave a possible attribution to the inclusion of high-functioning subjects with no significant differences in HGS. Even so the decrease in muscle mass was associated with diminished HGS [31].

As far as testing the association between recall and physical function, a 12-week physical intervention program was found to improve word recall among other cognitive function among 26 participants compared to controls [32].

We found that adjustment for both male and female genders in unadjusted and adjusted models revealed a stronger association between HGS and EF among elderly males when compared to females (O.R. 6.408, 6.399, 5.481 versus 1.829, 1.608, 1.320, respectively). This was also found in the association between TUGT and EF (O.R. 0.626, 0.621, 0.708 versus 0.691, 0.728, 0.863, respectively).

This association has been examined in male and female genders in other studies and has revealed contradictory results. None of these studies has examined EF using CDT and many used only global cognitive testing [33, 34].

Guo and colleagues in their cross-sectional study, for instance, found that in men, 30-s arm curl and language was most highly correlated with functional fitness and MMSE. While in women, they found 30 s arm curl and eight-foot Up-and-Go were most highly correlated with functional fitness, and orientation and recall were most highly correlated with MMSE [35]. Another study showing gender-specific differences is the study of Dougherty and colleagues, revealing significant positive associations between cardiorespiratory fitness and episodic memory among men but not for women. They also showed a significant association between cardiorespiratory fitness and hippocampal volume among women and not in men [36].

On the contrary, Fellendorf and colleagues found the association between cognitive performance and physical functioning stronger among females [33]. This difference could be since his comparisons were done on a sample of patients suffering from bipolar disorder. Further cohort studies are required to confirm this variability.

The limitation of the current work was the design of the cross-sectional study which could not declare causality; however, the strong association and the specific highlight on executive function are strength points.

CONCLUSIONS AND IMPLICATIONS

A strong association between Clock Drawing Test score and both HGS and TUGT was found among the studied sample. Higher HGS, and lower TUGT was significantly associated with higher performance in the Clock Drawing Test.

This association is stronger in males than in females for both HGS and TUGT. Mini-Cog is strongly associated with TUGT and not HGS. With little data about executive function and physical function (HGS and TUGT), the current results supported the presence of a significant association that should encourage a future cohort studies to prove causality between physical functioning and executive function in elderly subjects. Gender-related variabilities need to be further examined as well.

Footnotes

ACKNOWLEDGMENTS

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Authors’ disclosures available online ().

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