Association between cognitive impairment and eating habits in elderly Chinese subjects over 90 years of age

Abstract

Objective

Eating habits may have a key influence on cognitive function, however, the relationship between dietary intake and cognitive impairment in the elderly Chinese population has not been explored. The present study investigated the association between cognitive impairment and eating habits in elderly Chinese subjects >90 years of age.

Methods

This study comprised data from subjects included in the 2005 Project of Longevity and Ageing in Dujiangyan, China. Subjects were divided into two groups: cognitive impairment group and normal group. Sociodemographic and dietary habit data were collected and cognitive function was assessed in all subjects using the Mini-Mental State Examination.

Results

Data from 763 subjects (249 men, 514 women) were included. There was no statistically significant difference in eating habits between the two groups. Education level in the cognitive impairment group was significantly lower than in the normal group. Significant between-group differences were detected in factors relating to subjects’ professions.

Conclusions

Eating habits were not related to cognitive impairment in elderly Chinese people >90 years of age.

Keywords

Cognitive impairment eating habits Mini-Mental State Examination Alzheimer’s disease

Introduction

By 2050, 115 million people worldwide are expected to have some form of cognitive impairment, including mild cognitive impairment and Alzheimer’s disease, which is the most common form in the aged. ¹ Cognition in the elderly ranges from cognitive changes associated with normal ageing to dementia, with a transitional stage of mild cognitive impairment that may indicate early signs of Alzheimer’s disease. ² Studies have suggested that cognitive impairment is related to lack of variety in dietary nutrients ^3,4 and eating habits are considered to be one of the most influential factors relating to cognitive function.^3,5,6 In addition, a well-balanced diet may play a role in preventing decline in cognitive function.^7–13 One study found that patients with Alzheimer’s disease had a high intake of meat, sweets and sweetened beverages, compared with healthy volunteers who had a high intake of fruits, vegetables, and whole grains.¹⁴ Another study found that vegetables, unsaturated fats and a high Mediterranean-diet score may be beneficial to cognitive function.¹⁵ Intake of certain nutrients or dietary antioxidant supplements are thought to have a direct role in the prevention of cognitive decline and dementia.¹⁶ Diet is closely related to senile cognitive function: dietary intervention based on an understanding of the relationship between diet and health improved health-related quality of life and reduced complications in patients with Alzheimer’s disease, in a nursing home or hospital environment.¹⁷ Reducing the incidence of cognitive impairment and improving health-related quality of life in patients with dementia is becoming an increasingly important area of research. The association between cognitive impairment and the intake frequencies of different food items has been reported previously.¹⁸ However, cooking methods may also play an important role in the Chinese population. The primary aim of the present study was to investigate the association between cognitive impairment, eating habits and cooking methods in elderly (>90 years of age) Chinese subjects.

Subjects and methods

Study population and study design

The present questionnaire-based, cross-sectional study was performed between April 2005 and September 2009 in Dujiangyan, Chengdu, China, as part of the Project of Longevity and Ageing in Dujiangyan (PLAD).¹⁸ The study aimed to include all nonagenarians and centenarians in the area of Dujiangyan, although subjects with post-stroke related disease or Parkinson's disease, or who did not complete the MMSE test, were excluded. The study protocol was approved by the research Ethics Committee of Sichuan University. All participants (and their legal proxies) provided written informed consent.

Data collection

Trained medical personnel visited all recruits at their homes for data collection. All data relating to cognitive function, sociodemographics and dietary habits (including age, sex, education level, cognitive function, food consumption, vegetable consumption, nutritional status and other items) were collected. All information was checked and confirmed by family members who usually lived with the participant.

Assessment of cognitive function

Cognitive function was assessed using a Mini-Mental State Examination (MMSE)⁹ which included 30 items, each having a 1-point score. Any score ≥25 points (out of 30) indicated normal cognition. Below this, scores could indicate severe (≤9 points), moderate (10–20 points) or mild (21–24 points) cognitive impairment. In the present study, some items were modified on the basis that the modification would not change the meaning of the test, as described in a previous study.¹⁹ Subjects were categorized as follows: cognitive impairment, scores <17; normal, scores between 17 and 30.^9,18,20

Assessment of eating habits

All participants completed a questionnaire relating to eating habits, including questions on: food intake (very satiated, 70–80% satiated, 50% satiated, variable); component of each food item (primarily vegetarian, primarily meat, completely vegetarian); frequency of breakfast intake (daily, usually [>three times per week], occasionally [<three times per week], never); main cooking methods (fried, steamed, mixed cooking, others); speed of eating (slow, moderate, fast); eating habits (sweets preference, spicy hot preference, other preference, no preference).

Statistical analyses

Data were presented as mean ± SD or number and percentage. All data were computerized for statistical analysis using the SPSS® software package, version 17.0 (SPSS Inc., Chicago, IL, USA) for Windows®. Baseline characteristics and food consumption were analysed using χ²-test or Fisher’s exact test; Multivariate logistic regression analysis was performed using the first item in each category as the reference value. All tests were two tailed and a P-value ≤ 0.05 was considered statistically significant.

Results

Out of 870 Dujiangyan inhabitants ≥90 years of age, 23 males and 31 females were excluded due to post-stroke related disease or Parkinson's disease and 38 males and 15 females were excluded because they did not complete the MMSE test. A total of 763 participants from the PLAD study (249 [32.6%] males, 514 [67.4%] females) were included in the present analysis. Subjects were divided into two groups: cognitive impairment group (MMSE score < 17, n = 436) and normal group (MMSE score ≥ 17, n = 327). In the cognitive impairment group, the mean age of participants was 94.95 years (range, 90–108 years, 341 females and 95 males). In the normal group, mean age was 92.95 years (range, 90–105 years, 173 females and 154 males). The mean ± SD MMSE score was 10.90 ± 4.13 in the cognitive impairment group and 20.37 ± 2.78 in the normal group.

Education levels in the cognitive impairment group were significantly lower than levels reported in the normal group (P < 0.05, overall value): 375 (86.0%) versus 181 (55.4%) were illiterate; 42 (9.6%) versus 90 (27.5%) were literate; 16 (3.7%) versus 38 (11.6%) were educated to primary school level; three (0.7%) versus 12 (3.7%) were educated to junior high school level; none (0.0%) versus six (1.8%) were educated to high school level or above (cognitive impairment group versus normal group, respectively). Single factor analysis revealed that there were significantly more farmers in the cognitive impairment group (355 [81.4%]) compared with the normal group (241 [73.7%], P < 0.05). There were significantly fewer industrial workers (10 [2.3%] versus 18 [5.5%]), professional and technical workers (four [0.9%] versus 15 [4.6%]), and workers who had administrative or other functions (18 [4.1%] versus 27 [8.3%]) in the cognitive impairment group compared with the normal group, (P < 0.05, single factor analysis). No statistically significant between-group difference was found in relation to those who performed domestic duties (49 [11.2%] versus 26 [8.0%]).

The analysis of dietary related data included the following participant numbers: 752 participants in food intake category; 757 in dietary content of food category; 760 in breakfast consumption category; 754 in cooking methods category; 751 in speed of eating category; 750 in eating habits category. No significant association was found between eating habits and cognitive impairment (Table 1, single factor analysis). Using multivariate logistic regression analysis, no statistically significant association was found between each eating habit variable and cognitive function (Table 2). Using single factor analysis, statistically significant between-group differences were found in terms of cooking methods (P = 0.026, Table 1). Using multivariate logistic regression analysis, no statistically significant association was found between the two groups in terms of cooking methods (Table 2).

Table 1.

Characteristics of eating behaviours in 763 elderly Chinese subjects (>90 years of age) divided into two groups (cognitive impairment or normal).

Characteristic	Total subjects	Cognitive impairment group MMSE score < 17	Normal group MMSE score ≥ 17
Food intake, n = 752	n = 427	n = 325	NS
Very satiated	72	38 (8.9)	34 (10.5)
70–80% satiated	598	336 (78.7)	262 (80.6)
50% satiated	75	47 (11.0)	28 (8.6)
Variable	7	6 (1.4)	1 (0.3)
Dietary content of food, n = 757	n = 433	n = 324	NS
Primarily vegetarian	596	350 (80.8)	246 (75.9)
Primarily meat	153	78 (18.0)	75 (23.1)
All vegetarian	8	5 (1.2)	3 (0.9)
Breakfast consumption, n = 760	n = 434	n = 326	NS
Daily	720	412 (94.9)	308 (94.5)
Usually, >3 times/week	21	14 (3.2)	7 (2.1)
Occasionally, <3 times/week	15	6 (1.4)	9 (2.8)
Never	4	2 (0.5)	2 (0.6)
Main cooking method, n = 754	n = 430	n = 324	P = 0.026
Fried	85	52 (12.1)	33 (10.2)
Steam	408	233 (54.2)	175 (54.0)
Other	14	13 (3.0)	1 (0.3)
Mixed cooking	247	132 (30.7)	115 (35.5)
Speed of eating, n = 751	n = 427	n = 324	NS
Slow	151	84 (19.7)	67 (20.7)
Moderate	252	151 (35.4)	101 (31.2)
Faster	348	192 (45.0)	156 (48.1)
Eating habits, n = 750	n = 428	n = 322	NS
Sweet preference	294	155 (36.2)	139 (43.2)
Spicy hot preference	88	51 (11.9)	37 (11.5)
No preference	31	18 (4.2)	13 (4.0)
Other preference	337	204 (47.7)	133 (41.3)

Data expressed as n (%) of subjects.

NS, No statistically significant between-group differences (P ≥ 0.05), χ²-test or Fisher’s exact test.

MMSE, Mini-Mental State Examination.

Table 2.

Multivariate logistic regression analysis of sociodemographic data and eating habits in elderly Chinese subjects (>90 years of age) divided into two groups (cognitive impairment or normal).

Characteristic	B	SB	OR	95% CI
Characteristic	B	SB	OR	Lower	Upper
Demographic
Sex, male/female	−0.38	0.24	0.68	0.42	1.10
Age < 95 years
Age ≥ 95 – < 100 years	−0.40	0.22	0.67	0.43	1.04
Age ≥ 100 years	−0.90	0.45	0.41	0.17	1.00
Education level
Illiterate
Literate	1.16	0.29	3.19	1.82	5.60
Primary school education	1.44	0.43	4.23	1.83	9.77
Junior high school education	1.36	0.77	3.91	0.87	17.68
High school education and above	20.98	22008.01	1.30	0	–
Work history
Farmer
Domestic worker	−0.22	0.36	0.80	0.39	1.63
Industrial worker	0.00	0.54	1.05	0.36	3.00
Professional and technical worker	0.85	0.76	2.35	0.53	10.42
Administrative worker	36.66	21077.03	8.35	0	–
Others	−0.08	0.46	0.92	0.37	2.29
Food intake
Very satiated
70–80% satiated	−0.44	0.33	0.64	0.34	1.22
50% satiated	−0.67	0.45	0.51	0.21	1.22
Variable	−2.15	1.27	0.12	0.01	1.39
Dietary content of food
Primarily vegetarian
Primarily meat	0.10	.251	1.11	0.68	1.81
All vegetarian	−0.76	1.08	0.47	0.06	3.85
Breakfast consumption
Daily
Usually, >3 times/week	−0.11	0.57	0.90	0.29	2.75
Occasionally, <3 times/week	1.48	0.77	4.38	0.96	19.97
Never	−18.96	14903.71	0	0
Main cooking method
Frying
Steaming	0.47	0.32	1.61	0.85	3.02
Other	−1.43	1.14	0.24	0.03	2.25
Mixed cooking	0.56	0.34	1.76	0.90	3.43
Speed of eating
Slow
Moderate	0.05	0.27	1.05	0.62	1.78
Fast	0.27	0.26	1.32	0.80	2.17
Eating habits
Sweet preference
Spicy hot preference	−0.19	0.31	0.82	0.45	1.50
No preference	−0.35	0.54	0.70	0.25	2.01
Other preference	−0.40	0.21	0.67	0.44	1.02

Reference values for multivariate logistic regression analysis in each category were: female; age < 95 years; illiterate; farmer; very satiated; primarily vegetarian; every day; fried; slow; sweet preference.

OR, Odds Ratio; CI, confidence interval.

Discussion

There are many studies relating to the common problem of cognitive impairment in the elderly^3,8,9,12 and it has been reported that ∼5% of people with dementia are >65 years of age.¹⁰ Malnutrition was first proposed as a clinical manifestation of Alzheimer’s disease at the beginning of the last century, with a close relationship between malnutrition and Alzheimer’s disease found in a number of observational studies.^21–23 There is increasing evidence to support the role of caloric intake in the relative risk for Alzheimer’s disease clinical dementia.^11,24 Several aspects of diet have been researched in detail; results have provided support for potential dietary mechanisms that may improve cognition.¹² Supplementary analysis of clinical trial data has shown many minimal benefits of dietary intervention,¹² and there is continuing work to define the mechanisms and improve knowledge of dietary benefits.¹¹ One study suggested that lack of dietary energy intake was the main reason for cognitive impairment.¹³

In the present study, subjects were categorized into a cognitive impairment group (MMSE scores < 17) and normal group (MMSE scores between 17 and 30). The MMSE score level was set according to the fact that most participants in a previous PLAD study had no formal education.^9,18,20 The main difference between the present study and the original analyses and report on the PLAD study was that the original report focused on minor cognitive impairment, and excluded the normal and the dementia group.¹⁸

The present study found no statistically significant differences in terms of food intake, nutritional content of each food item, frequency of consuming breakfast, main cooking methods or eating habits between the two groups, after adjusting for independent variable factors (sex, age, education level and major occupation before 60 years of age). It has been reported that a higher intake of fruits, vegetables, fish, nuts and legumes, and a lower intake of meats, high fat dairy and sweets appears to be associated with lower odds of cognitive deficits or reduced risk of Alzheimer’s disease.²⁵ In the present study, no significant association was found between dietary intake (primarily vegetables, primarily meat, or completely vegetarian) and cognitive function, suggesting that vegetable or meat intake may have little or no effect on cognitive function in Chinese elderly people >90 years of age. It has been suggested that intake of sweets is significantly associated with Alzheimer’s disease type dementia.^25,26 Although the present study found a preference for eating sweet food in the cognitive impairment group, this was not shown to be statistically significant after independent variable factors in eating habits had been added, suggesting that a preference for eating sweet food may not be related to decline in cognitive function in the Chinese elderly >90 years of age.

Consuming or missing breakfast and the speed of eating were not factors associated with cognitive function in the present study. Methods of cooking, including frying or steaming food, were also not associated with cognitive function. These results may reflect the fact that midlife eating habits are more important in terms of subsequent cognitive performance than diet in later life.²⁷

The present study was limited by a number of factors: most of the participants lived in the countryside and this population might not be representative of the urban population; as part of the PLAD study, there might be a survival bias, however, this was an unavoidable study characteristic; the number of participants was relatively small, due to the difficulty of collecting data from very elderly participants in one area.

In conclusion, decline in cognitive function is a public health concern that is related to serious physical and mental health problems in aged people. Cognitive decline in the elderly is particularly important for the individuals themselves, but also places a heavy burden on family members. Studies into the impact of eating habits on cognitive function are becoming increasingly important, although in the present study eating habits were not found to be related to cognitive impairment in Chinese elderly people >90 years of age.

Footnotes

Acknowledgements

The authors thank the staff of the Department of Geriatrics Medicine, West China Hospital, Dujiangyan Government and Dujjiangyan People’s Hospital, and all participants (as well as their legal proxies) for their great contributions.

Declaration of conflicting interest

The authors declare that there are no conflicts of interest.

Funding

This work was supported by the Discipline Construction Foundation of Sichuan University, and by grants from the Project of Science and Technology Bureau of Sichuan Province (No. 2006Z09-006-4) and the Construction Fund for Subjects of West China Hospital of Sichuan University (No. XK05001).

References

Prince

Jackson

. Alzheimer’s Disease International World Alzheimer Report 2009 Executive Summary, London: Alzheimer’s disease International, 2009.

Kelley

Petersen

. Alzheimer’s disease and mild cognitive impairment. Neurol Clin 2007; 25: 577–609.

Féart

Samieri

Barberger-Gateau

. Mediterranean diet and cognitive function in older adults. Curr Opin Clin Nutr Metab Care 2010; 13: 14–18.

Scarmeas

. Dietary patterns in Alzheimer’s disease and cognitive aging. Curr Alzheimer Res 2011; 8: 510–519.

Luchsinger

Tang

Miller

. Higher folate intake is related to lower risk of Alzheimer’s disease in the elderly. J Nutr Health Aging 2008; 12: 648–650.

Ikeda

Brown

Holland

. Changes in appetite, food preference, and eating habits in front temporal dementia and Alzheimer’s disease. J Neurol Neurosurg Psychiatry 2002; 73: 371–376.

Gustaw–Rothenberg

. Dietary patterns associated with Alzheimer’s disease: population based study. Int J Environ Res Public Health 2009; 6: 1355–1340.

Roberts

Geda

Cerhan

. Vegetables, unsaturated fats, moderate alcohol intake, and mild cognitive impairment. Demen Geriatr Cogn Disord 2010; 29: 413–423.

Folstein

McHugh

. “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 1975; 12: 189–198.

10.

Antuono

Beyer

. The burden of dementia: a medical and research perspective. Theor Med Bioeth 1999; 20: 3–13.

11.

Pasinetti

Zhao

Qin

. Caloric intake and Alzheimer’s disease. Experimental approaches and therapeutic implications. Interdiscip Top Gerontol 2007; 35: 159–175.

12.

Van Dyk

Sano

. The impact of nutrition on cognition in the elderly. Neurochem Res 2007; 32: 893–904.

13.

Riviere

Lauque

Vellas

. Health promotion programme: nutrition and Alzheimer’s disease. J Nutr Health Aging 1998; 2: 101–106.

14.

Hogervorst

Sadjimim

Yesufu

. High tofu intake is associated with worse memory in elderly Indonesian men and women. Dement Geriatr Cogn Disord 2008; 26: 50–57.

15.

Pasinetti

Eberstein

. Metabolic syndrome and the role of dietary lifestyles in Alzheimer’s disease. J Neurochem 2008; 106: 1503–1514.

16.

Meydani

. Nutrition interventions in aging and age-associated disease. Ann N Y Acad Sci 2001; 928: 226–235.

17.

Shatenstein

Kergoat

Reid

. Dietary intervention in older adults with early-stage Alzheimer dementia: Early lessons learned. J Nutr Health Aging 2008; 12: 461–469.

18.

Wang

Dong

Zeng

. Is there an association between mild cognitive impairment and dietary pattern in Chinese elderly? Results from a cross-sectional population study. BMC Public Health 2010; 10: 595–595.

19.

Zhu

Tian

Zhong

. A clinical study on a randomized, double-blind control of Chinese medicine granules in treatment of vascular dementia. Zhongguo Zhong Yao Za. Zhi 2006; 31: 1722–1725. in Chinese, English abstract).

20.

Tombaugh

McIntyre

. The mini-mental state examination: a comprehensive review. J Am Geriatr Soc 1992; 40: 922–935.

21.

Sato

Hirano

Watanabe

. Relation between nutrition and oral function in elderly Japanese with alzheimer's disease. Clin Nutr Suppl 2012; 7: 49–49.

22.

Orsitto

. Different components of nutritional status in older inpatients with cognitive impairment. J Nutr Health Aging 2012; 16: 468–471.

23.

Villegas Sordo

Rubio Mier

Villegas Sordo

. Depression-malnutrition-risk relationship in geriatric home residents. Eur Geriatr Med 2011; 2: S69–S69.

24.

Roberts

Geda

. Relative intake of macronutrients impacts risk of mild cognitive impairment or dementia. J Alzheimers Dis 2012; 32: 329–339.

25.

Nieves

Stern

. Food combination and Alzheimer disease risk: a protective diet. Arch Neurol 2010; 67: 699–706.

26.

Niino

Iijima

Mizoguchi

. A case-control study of clinically diagnosed Alzheimer type dementia. Nihon Ronen Igakkai Zasshi 1990; 27: 693–698. in Japanese, English abstract).

27.

Kesse-Guyot

Andreeva

Jeandel

. A healthy dietary pattern at midlife is associated with subsequent cognitive performance. J Nutr 2012; 142: 909–915.