The prevalence of mild behavioral impairment in older adults with mild cognitive impairment: A systematic review and meta-analysis

Abstract

Background

Mild behavioral impairment is a neurobehavioral symptom characterized by the onset of a new and persistent neuropsychiatric syndrome. Patients with co-occurring mild behavioral impairment and mild cognitive impairment have the relatively highest probability of developing dementia than sick mild behavioral impairment or mild cognitive impairment alone.

Objective

This study aimed to determine the currently available best estimate of mild behavioral impairment prevalence and clarify the reasons for the difference in estimates.

Methods

Data were retrieved and collected from five electronic databases. Two reviewers independently appraised the methodological quality of included studies. Heterogeneity was assessed by using the I² statistic and random effects models were employed. Sources of heterogeneity were investigated by subgroup analysis and meta-regression. All statistical analyses were conducted by Stata.

Results

A total of 23 reports involving 5397 participants were included in this systematic review. The pooled effect size for the overall mild behavioral impairment was 52% (95%CI 42-62%). In the subgroup analysis and regression analysis, we found that study type, study area, assessment tools, and study subject gender could explain part of the source of heterogeneity.

Conclusions

The results of this review suggest that 52% with mild cognitive impairment combined with mild behavioral impairment; there is a close relationship between the two. Future studies should pay more attention to the underlying mechanism between the two and provide a more scientific basis for early discrimination of clinical dementia and Alzheimer's disease.

Keywords

Alzheimer's disease dementia meta-analysis mild behavioral impairment mild cognitive impairment prevalence systematic review

Introduction

Mild behavioral impairment (MBI) is a neurobehavioral syndrome characterized by the onset of sustained and meaningful neuropsychiatric symptoms in later years.¹ It was formally proposed by Taragano and his colleagues as a relatively new concept in 2009.² In 2016, the International Society to Advance Alzheimer's Research and Treatment (ISTAART) NPS Professional Interest Area expanded the Taragano MBI diagnostic criteria and proposed new diagnostic criteria for research. The ISTART-AA MBI diagnostic criteria require observing behavioral or personality changes that start later in life (age ≥ 50 years). These changes are inconsistent with the person's usual behavior or personality and persist at least intermittently for ≥ 6 months.

MBI is present in the prodromal stage of dementia or the stage of mild cognitive impairment (MCI). More and more evidence suggests that neuropsychiatric syndromes in the elderly are early markers of cognitive decline and progression of neurodegenerative diseases. A community-based study³ reported that 38.9% of elderly people in the community have neuropsychiatric symptoms, and as cognitive function declines, the prevalence of neuropsychiatric symptoms increases. This study also found that the incidence of neuropsychiatric symptoms was 30.8% in cognitively normal people, compared to 80% in dementia patients.

Based on current research, we should be more concerned about those patients with co-occurring MBI and MCI who have the relatively highest probability of developing dementia than MBI or MCI alone.^4,5 MCI patients with neuropsychiatric symptoms are a high-risk group for developing dementia. The presence of neuropsychiatric symptoms in patients with MCI is associated with an increased risk of future dementia development compared to those without such symptoms.^6,7 Based on population^6,8 and clinical cohort studies,⁹ it was found that the estimated annual incidence of MCI to dementia is 10%–15%.¹⁰ In contrast, the annual progression rate for MCI plus neuropsychiatric symptoms is 25%.⁹ Similarly, neuropsychiatric symptoms in the elderly with normal cognition are more likely to lead to MCI and dementia.¹¹

Currently, the role of MBI in the prodromal stage of dementia and MCI stages is receiving increasing attention. Studies have found that MBI is associated with a significantly faster rate of cognitive decline and dementia progression compared to other late-life psychiatric disorders.¹² Patients with co-occurring MBI and MCI developed dementia faster than those with MCI alone [HR = 1.43, 95% CI (1.01 to 2.03).^2,13 MCI is a transitional stage between normal aging and Alzheimer's disease, and MCI with neuropsychiatric symptoms is a predictor of developing Alzheimer's disease.^13,14 As a transition stage between normal aging and Alzheimer's disease, the neuropsychiatric symptoms of mild cognitive impairment are a predictor of progression to Alzheimer's disease.^13,14 Research has found a significant increase in the risk of developing Alzheimer's disease in patients with MCI combined with neuropsychiatric syndromes.⁹ Neuropsychiatric symptoms may be one of the earliest symptoms of the preclinical stage of Alzheimer's disease, and treating these symptoms may delay the transition to dementia. Therefore, the identification and intervention of MBI in the prodromal stage of dementia is critical. Paying attention to the prevalence of MBI in MCI patients and taking available prevention strategies for risk factors can help reduce the incidence of dementia.

Although the association between MCI and MBI is essential, as far as we know, there is currently no consensus on the prevalence of MBI among MCI patients. Methodological problems, such as different definitions, tools used, and diagnostic criteria, may cause differences in prevalence. Therefore, conducting a meta-analysis of previously published studies is necessary to determine the best available estimates of MBI prevalence and clarify the reasons for differences in estimates. Therefore, this study aims to explore the prevalence of MBI in patients with MCI and to deepen the understanding of the factors influencing the prevalence based on previous studies to provide more reliable evidence for the early identification and diagnosis of clinical dementia.

Methods

We conducted this systematic review and meta-analysis by following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analysis) guidelines¹⁵ and the Meta-analysis and Systematic Reviews of Observational Studies guidelines.¹⁶ The protocol for this review has been registered in the International Prospective Register of Systematic Reviews (PROSPERO):CRD40224514406.

Search strategy and study selection

We searched PubMed, Web of Science, Embase, PsycINFO, and Cochrane Library from inception to 13 October 2023. We manually searched the reference list of relevant articles to identify additional articles. Our search terms were focused on the following three aspects: (1) cognition (cognitive dysfunction, mild cognitive impairment, MCI), (2) behavior (behavioral symptoms, behavior disorder, MBI), and (3) Prevalence (prevalence, incidence, rate). The details of the literature search strategy are described in Supplemental File 1.

We used EndNote X9 software to import and manage search results. After removing the duplicates, two reviewers independently assessed the studies by title and abstract and examined the full texts of the studies. All disagreements were resolved by discussion and, if needed, can be discussed with a third reviewer to reach a consensus.

Selection criteria

The inclusion criteria were: (1) participants should meet the diagnostic criteria for the MCI; (2) is the original study of human subjects of the cohort study design; (3) report the prevalence of MBI using one or more outcomes or having sufficient information to calculate the prevalence of MBI; (4) articles published in English only were included due to the lack of resources.

Studies were excluded if they met one of the following exclusion criteria: (1) patients with cognitive decline due to head trauma or brain tumor; (2) the participant was not diagnosed as having MCI; (3) case reports, conference abstract, letters, comments, editorials, animal studies; (4) data cannot be extracted.

Data extraction

Two reviewers independently extracted the data and discussed differences until a consensus was reached. Extracted information included characteristics of the studies(author, study design year and country of publication), participant characteristics (sample size, mean age, percentage of females), outcome characteristics (diagnostic criteria for MBI, MBI assessment tools, prevalence).In addition, we extracted in detail the prevalence of various domains in the Neuropsychiatric Inventory Questionnaire (NPI-Q), the Neuropsychiatric Inventory (NPI) and the Mild Behavioral Impairment Checklist (MBI-C). If data from the same population had been published more than once, the latest and complete studies were selected.

Quality assessment

The methodological quality of the studies was assessed using the risk of bias tool explicitly developed for prevalence studies.¹⁷ This 10-item measure examines each study's external (items 1-4) and internal (items 5-10) validity across four domains: selection bias, nonresponse bias, measurement bias, and analysis bias. Scores of 0-4, 5-7, and 8-10 represent high, moderate and low risk of bias, respectively. Two reviewers independently assessed the included studies’ quality, and consensus resolved discrepancies.

Statistical analysis

A meta-analysis was performed to aggregate the results of the included studies. All statistical analyses were conducted by Stata (version 15.0). Before pooling data, Freeman-Tukey double arcsine transformation was used to stabilize variance and improve statistical properties.¹⁸ Sensitivity analysis was performed, and Egger's and Begg's tests were used to assess publication bias. Heterogeneity was assessed using the I-squared statistic (I²), which describes the percentage of total variation across studies due to heterogeneity rather than chance. I² value of less than 25%, 25–75%, or more than 75% indicates low, moderate or high heterogeneity.¹⁹ All pooled means are expressed as weighted effect sizes of the 95% confidence interval (CI). A random effect model was employed if moderate or high heterogeneity was identified among studies. To examine the sources of heterogeneity among the different studies, predefined subgroup analyses and regression analyses were performed to assess the impact of study subject gender, study area, assessment tools and study type on the outcomes.

Results

Study selection

The initial search yielded 15458 citations; after duplicates were removed, 14380 titles and abstracts remained for screening. At the end of the titles and abstract review, 37 reports were taken to full-text review by excluding the irrelevant reports and reports that did not comply with the pre-specified eligibility criteria. After a full-text review, 16 reports were included. Seven additional reports were identified from the reference lists of included studies; all met the eligibility criteria. A total of 23 reports^{20212223242526272829303132333435363738394041–42} were included in this systematic review. The screening process of studies is depicted in Figure 1.

Figure 1.

The flow chart of studies.

Study characteristics

Supplemental File 2 describes the characteristics of the 23 included studies. The literature was published between 2002 and 2023. There were 5397 participants from 10 countries, and the sample sizes ranged from 28 to 1779. Most were from North America (n = 39.13%) and Asia (n = 34.78%). The rest are from Europe (n = 21.74%) and Oceania (n = 4.35% in Australia). The study design was mainly cross-sectional (n = 47.83%), followed by prospective (n = 26.09%), retrospective (n = 17.39%) and case-control (n = 8.70%). The main tools used to assess mild behavior impairment are MBI-C, NPI-Q, and NPI.

Table 1 shows the 11 included studies^{20212223242526272829–30} that reported the prevalence of MBI. Supplemental File 3 shows the 4 studies ^20,21,24,29 that reported data on prevalence in each domain using the MBI-C. Supplemental File 4 shows the 14 studies^{20,21,3132333435363738394041–42} reporting data on prevalence in each domain reported using the NPI or NPI-Q, nine of these studies^{323334–35,37383940–41} fully reported the prevalence of 12 subdomains using the NPI-Q, three studies^20,21,42 fully reported the prevalence in 10 subdomains using the NPI,2 additional studies^31,36 reported prevalence in some of the subdomains assessed using the NPI.

Table 1.

Characteristic of the 11 included studies.

Studies	Study design	Sample size, N	Age (y), mean (SD)	Female%	Criteria for MBI	Diagnostic Tools	prevalence
Sheikh et al., Canada, 2018 ²⁰	prospective study	163	64 (58–70)	42.3% (69/163)	NPI-Q (1-month symptom duration)	NPI-Q	85.3% (139/163)
Mortby et al., Australia, 2017 ²¹	cross-sectional study	133	75.2 (1.6)	42.1% (56/133)	NPI-Q (1-month symptom duration)	NPI	48.9% (65/133)
Mallo et al., Spain, 2018 ²²	cross-sectional study	106	70.04 (8.33)	64.2% (68/106)	Meeting all four ISTAART criteria	GDS-15, NPI-Q NPI, MBI-C	14.2% (15/106)
Matsuoka et al., Japan, 2019 ²³	retrospective study	180	/	/	Meeting all four ISTAART criteria	MBI-C	50.0% (90/180)
Yokoi et al., Japan, 2019 ²⁴	prospective study	234	72.79 ± 5.88	50.4% (118/234)	NPI-Q (1-month symptom duration)	NPI-Q	49.6% (116/234)
Naude et al., USA, 2020 ²⁵	prospective study	330	/	/	NPI-Q (1-month symptom duration)	NPI-Q	47.3% (156/330)
Soo et al., Singapore, 2021 ²⁶	cross-sectional study	93	69.07	/	/	MBI-C	34.4% (32/93)
Kianimehr et al., Iran, 2021 ²⁷	cross-sectional study	96	71.4 8 ± 9.3	58.3% (56/96)	MBI-C (6-month symptom duration)	MBI-C	50.0% (48/96)
Ghahremani et al., Canada, 2023 ²⁸	retrospective study	35	/	/	Measure emergent and persistent NPS per the MBI criteria	MBI-C	71.9% (23/35)
Rouse et al., USA, 2020 ²⁹	cross-sectional study	212	74.9	49.5% (105/212)	NPI-Q (1-month symptom duration)	NPI-Q	29.0% (144/212)
Sun et al., China, 2021 ³⁰	prospective study	543	72.04	42.5%	Meeting all four ISTAART criteria	NPI-Q	54.5% (296/543)

Risk of bias assessment of included studies

The risk of bias of external and internal validity criteria was assessed for all the included studies without considering whether the study had reported prevalence or incidence (Supplemental File 5).

Concerning external validity, the target population represented the national population well in 56.5% (n = 13) of studies (Item 1). The sampling frame closely represented the target population in 65.2% (n = 15) of all included studies (Items 2). 47.8% (n = 11) of included studies scored ‘yes’ for Item 3, which focused on a random sample selection, and 87% (n = 20) for Item 4, which focused on nonresponse bias, scored ‘yes’.

In terms of internal validity criteria, all (n = 23) studies used acceptable case definitions (item 6). The study instrument that measured the parameter of interest was shown to have reliability and validity (item 7), with the numerator(s) and denominator(s) for the parameter of interest appropriate (item 10). More than 80% (n = 19) of the studies used the same mode of data collection for all participants (item 8).73.9% (n = 17) of the studies collected data directly from participants (item 5). Most studies considered the shortest length of prevalence period for the parameter of interest (Item 9).

Meta-analysis of the prevalence of MBI

Prevalence of MBI in the MCI population. There were 11 studies,^{20212223242526272829–30} and 2125 patients with MCI participated in the prevalence of MBI. Regardless of the diagnostic criteria and tools, the prevalence of MBI in MCI ranged from 14% to 85%, 29% to 85.3% in North America, 34.4% to 54.5% in Asia, 14.2% to 50% in Europe, and 48.9% in Oceania (Australia). The pooled effect size for the MBI was 52% (95%CI 42-62%) (Figure 2). Due to the high heterogeneity, a random effects model was used (I²= 95.10%, p < 0.01). The sensitivity analysis of 11 studies found that 3 studies showed significant heterogeneity, and the difference between the comprehensive effect value and the total comprehensive effect value was not statistically significant, indicating that the results of this study had good stability. Visual inspection of the funnel plot was asymmetric (Supplemental File 6); Begg test (p = 1.000) and Egger test (p = 0.685) were more significant than 0.05 with no publication bias.

Figure 2.

The forest plot of the prevalence of MBI in the MCI population.

Prevalence of MBI domains in the MCI population

Four studies^20,21,24,29 reported the prevalence of MBI domains assessed using the MBI-C for 742 participants. Arrange in descending order, the prevalence of affective dysregulation was 38% (95%CI 17-62%, p = 0.00), impulse dyscontrol 36% (95CI% 22-52%, p = 0.00), decreased motivation 30% (95%CI 17-44% p < 0.01), social inappropriateness 10% (95%CI 2-21%, p < 0.01) and abnormal 5% (95%CI 2-9%, p < 0.01). The random effects model was chosen due to the high heterogeneity. All p-values were more significant than 0.05, with no publication bias.

A total of 14 studies^{20,21,3132333435363738394041–42} reported the prevalence of MBI domains assessed using the NPI or NPI-Q for a total of 3568 participants. Among them, the highest prevalence of depression was 36% (95%CI 24-49%, p < 0.01), and the lowest prevalence of hallucinations was 1% (95%CI 1-3%, p < 0.01). Large heterogeneity in all fields, a random effects model was used. In the Egger test results, in addition to the delusional domains, the p-value was more significant than 0.05, and there was no publication bias. Full results are given in Table 2.

Table 2.

Prevalence of MBI domains in the MCI population.

Items	Study (n)	Sample (n)	I²	p	Pooledestimates	95%CI	z	Egger test
MBI-C domains
Affective dysregulation	4	305/742	97.73%	<0.01	38%	17–62%	5.14	0.725
Impulse dyscontrol	4	264/742	94.55%	<0.01	36%	22–52%	7.70	0.532
Decreased motivation	4	212/742	94.15%	<0.01	30%	17–44%	7.07	0.266
Social inappropriateness	4	80/742	94.68%	<0.01	10%	2–21%	3.5	0.812
Abnormal	4	39/742	77.07%	<0.01	5%	2–9%	4.88	0.940
NPI-Q domains
Delusions	12	827/3321	98.85%	<0.01	8%	1–22%	2.60	0.013
Hallucinations	12	62/3321	59.14%	<0.01	1%	1–3%	4.86	0.531
Agitation	14	573/3568	95.18%	<0.01	17%	11–24%	8.55	0.419
Depression	14	1012/3568	97.79%	<0.01	36%	24–49%	9.14	0.217
Anxiety	13	703/3447	97.39%	<0.01	25%	15–36%	7.66	0.279
Elation	12	70/3321	83.88%	<0.01	2%	1–4%	4.21	0.140
Apathy	13	686/3447	96.79%	<0.01	28%	19–38%	9.14	0.053
Disinhibition	12	229/3321	92.48%	<0.01	7%	4–12%	5.91	0.484
Irritability	13	775/3447	96.16%	<0.01	25%	17–34%	9.25	0.505
Motor Disturbance	12	185/3321	89.19%	<0.01	6%	4–10%	6.49	0.227
Nightime Behaviors	10	610/3123	93.40%	<0.01	24%	17–31%	10.80	0.224
Appetite	10	336/3123	93.22%	<0.01	14%	9–21%	8.05	0.149

Subgroup analysis

To explore the sources of heterogeneity, we performed subgroup analyses based on study type, study area, assessment tools and study subject gender. When evaluating the study type, the highest pooled prevalence was prospective study, 60% (95%CI 45-74%), followed by retrospective study at 53% (95%CI 46-59%), and the cross-sectional study was lowest at 42% (95%CI 24-62%), with high heterogeneity within each group. By study area, the highest prevalence of mid behavioral impairment in North America was 68% (95%CI 44-87%), followed by 49% (95%CI 41-57%) in Oceania, 48% (95%CI 41-55%) in Asia, and 41% (95%CI 13-73%) in Europe. When evaluating the assessment tools, using NPI-Q had the highest pooled prevalence was 62% (95%CI 49-73%), followed by 49% (95%CI 41-57%) in studies using NPI, and the prevalence of MBI diagnosed using MBI-C was 42% (95%CI 25-59%, with high heterogeneity within each group. As the inclusion studies did not explicitly report the prevalence by gender, we divided subgroups according to whether the female proportion reached 50%. The pooled prevalence of MBI prevalence reported in studies with female percent <50% was 68% (95%CI 49-79%), significantly higher than the combined effect size of <50%, 37% (95%CI 15-61%) (Table 3).

Table 3.

Subgroup analysis of MBI prevalence.

Subgroups	Numbers of studies	Numbers of participant	MBI prevalence	95%CI	I²	p
Study design
Prospective study	4	1270	60%	45–74%	96.47%	<0.001
Cross-sectional study	5	640	42%	24–62%	96.07%	<0.001
Retrospective study	2	215	53%	46–59%	/	/
Study area
Asia	4	1050	48%	41–55%	77.51%	<0.001
Europe	3	237	41%	13–73%	/	/
North America	3	705	68%	44–87%	/	/
Oceania	1	133	49%	41–57%	/	/
Assessment tools
NPI-Q	5	1482	61%	49–73%	95.82%	<0.001
NPI	1	133	49%	41–57%	/	/
MBI-C	5	510	42%	25–59%	93.18%	<0.001
Study subject gender
Woman%<50%	4	1051	65%	49–79%	95.83%	<0.001
Woman%>50%	3	436	37%	15–61%	/	/

Meta-regression

The association between the prevalence of MBI and study characteristics (study type, study area, assessment tools, and study subject gender) were further assessed by meta-regression analysis to explore the sources of heterogeneity. Scatter plots are shown in Supplemental File 7. All four characteristics were statistically significant in the multivariate regression model. Study type, estimate:1.8108 (95%CI 1.2890-2.5437) p = 0.003; Study area, estimate: 1.4942 (95%CI 1.1594-1.9258) p = 0.006; Study assessment tools, estimate: 2.0055 (95%CI 1.5781-2.5486) p < 0.001；Study subject gender, estimate: 2.4468 (95%CI 1.4513-4.1249) p = 0.007.

Discussion

Summary of findings

We performed a systematic review and meta-analysis to assess the prevalence of MBI in the MCI population. We identified the results of 23 studies involving 5397 MCI subjects. The estimated pooled prevalence of MBI was 52% (95%CI 42-62%, p < 0.01). Due to differences between studies, the prevalence across studies varied from 14% to 85%.

We found that when assessing the prevalence of the five subdomains of MBI using the MBI-C scale, the highest prevalence of affective dysregulation was 38% (95%CI 17-62%, p < 0.01), and the domain of abnormal perception had the lowest prevalence of 5% (95%CI 2-9%, p < 0.01). At the prevalence of the twelve subdomains of MBI assessed using the NPI or NPI-Q scales, the highest prevalence of the depression domain was 36% (95%CI 24-49%, p < 0.01) and the hallucination domain was 1% (95%CI 1-3%, p < 0.01). Affective dysregulation and impulse dyscontrol were the two most common MBI domains, independent of the scale used.

In our study, we focused on the elderly with MCI. MCI is an intermediate state between normal aging and Alzheimer's disease, which is a dementia syndrome. Common reasons for the high cost and poor outcomes of clinical trials in Alzheimer's disease are screening failure and poor recruitment of early disease. Identifying sensitive and specific premorbid indicators of emergency pathology is imperative.⁴³ New evidence has found a correlation between MBI and Alzheimer's disease in terms of pathological mechanisms. Stronger genetic risk factors for Alzheimer's disease, such as APOE, MS4A, NME8, ZCWPW1, EPHA1, and FERMT2, are at the same time factors that contribute to the higher possibility of developing some of the domains of MBI. Additionally, MBI accounts for the neurobehavioral pre-dementia axis, complementing the classical neurocognitive pre-dementia axis of MCI.⁴⁴ In this context, assessing the MBI in the MCI population may provide a valid, relatively simple and inexpensive tool for the early identification of individuals with a high probability of progressing to Alzheimer's disease.

Two^45,46 systematic reviews of the prevalence of MBI have been published by the same author team. They estimated the prevalence of MBI in different cognitive domain populations,⁴⁵ to assess the impact of MBI on the deterioration of cognitive function and to explain its intrinsic mechanisms. In previous studies, the combined prevalence of MBI in MCI, cognitively normal, subjective cognitive impairment, and cognitively normal but at-risk population was 33.5% (95% CI: 22.6%-46.6%), the combined prevalence of MBI in the MCI population was 45.5% (95%CI: 36.1% −55.3%), lower than our estimated prevalence in this study. However, only a small number of studies were included; only seven were included for the MCI population, and more than half were of low quality. In addition, the results of the meta-regression of the study subject race, proportion of female subjects, duration of MBI, study design, and sample population did not indicate that any of these factors could account for the variance between the studies. Another⁴⁶ discusses the prevalence of various domains of MBI across different cognitive domains, using the NPI-Q to approximate MBI by mapping the 10 neuropsychiatric syndrome questions onto five MBI domains. However, NPI-Q is designed for dementia populations and has a reference time of 1 month, which is less than the 6-month requirement of the MBI criteria. For these problems, we separately used a pooled analysis of the prevalence of MBI measured using NPI or NPI-Q and the MBI-C scale to reduce the heterogeneity.

Results of subgroup analysis and meta-regression analysis

The study found significant heterogeneity in the meta-analysis of the prevalence of MBI among MCI patients. There was also specific heterogeneity in the results of MBI prevalence between study types, with cross-sectional studies having the lowest combined effect size of MBI of 42% (95% CI 24-62%), which may be due to the lack of follow-up time for the population in cross-sectional studies, limiting the opportunity to assess the temporal association between MBI and MCI. The analysis showed that North America had the highest prevalence of MBI, Oceania and Asia had similar prevalence, and Europe had the lowest prevalence. Differences in the level of development of countries, such as potential differences in demographics, socio-economics, education and local health care, may have contributed to this heterogeneity. Additionally, the use of different assessment tools also brought about a large discrepancy in the study results, probably due to the shorter reference ranges of the NPI and NPI-Q relative to the MBI-C requirement of a symptom duration of six months or more, which would increase the possibility of false positives.

This systematic review and meta-analysis demonstrated that the pooled prevalence of MBI prevalence reported in studies with female percent <50% was 68% (95%CI 49-79%), significantly higher than the combined effect size of <50%,37% (95%CI 15-61%). The prevalence of MBI in men was shown to be at higher levels than the prevalence in women.

Gender differences in MBI have been reported previously, with abnormal perception or thought content domains being more common symptoms in women, while decreased motivation and impulse dyscontrol domains are more common in men,²³ on the one hand, which may be closely related to emotional problems that predispose to agitated behaviors in the context of an inability to express normal physiological, psychological, and social needs. Male and female brains process and respond to stress, fear, and reward differently, and at the same time, social roles and social expectations may lead to differences in MBI.

On the other hand, it has been shown that elevated androgen levels tend to cause people to be more agitated and irritable, which may also be an essential reason for agitated behavior.²¹ It is critical in the body's metabolism, growth, development, and reproduction. When the nervous system deteriorates, androgen binding to the androgen receptor may be further dysregulated, resulting in greater emotional instability in men than in women, triggering impulse-control dysfunctions that can lead to agitated behavior.⁴⁷ In conclusion, men are more likely to develop MBI compared to women.

Strengths and limitations of the study

Overall, the strengths of our review included our comprehensive search of the literature to reduce the risk of missing studies (selection bias), limited to the MCI population based on the previous review, updating recent studies, and expanding the sample size. In addition, we performed sensitivity analyses, subgroup analyses, and meta-regression to investigate the possible causes of heterogeneity, which made our findings more rigorous. However, our study has some limitations; first, because the concept of MBI was introduced in 2009, there were fewer studies related to the MCI population and different cognitive subgroups, and we included a smaller number of studies. Second, non-English papers were excluded from this review due to a lack of resources. In addition, some studies lacked information on the age and sex of subjects at the beginning of the study or the end of the follow-up period. Finally, when subgroup analyses were conducted, considerable heterogeneity remained in the studies reviewed, as there are usually significant differences in epidemiologic studies due to geographic region, demographic characteristics, lifestyle, etc.

Clinical significance and implications

Future studies should include more detailed demographic information, especially the prevalence of MBI in different sex and age groups; recognizing the risks and differences in the MBI population is important for both clinicians and researchers, and observing these changes and differences can help researchers identify at-risk populations earlier and take specific actions.⁴⁸ In addition, there is growing attention on the role of MBI in the precursor of dementia or MCI stage; more researchers are needed to explore this area in the future, such as longitudinal studies of the validity of predictors of MBI, prevalence over time, will improve our understanding and treatment of associated psychiatric symptoms.

Conclusions

This systematic review and meta-analysis suggest that 52% (more than half) of patients with MCI have MBI, and there is a significant relationship between the two. Regardless of which scale is used to assess MBI, affective dysregulation and impulse dyscontrol are the most common MBI domains. Stratified analysis showed that MBI was more common in men than in women. In addition, the combined prevalence of MBI has increased in recent years. Our findings provide evidence-based and theoretical support that may help to promote research on MBI and the development of related public health policies and provide a more scientific basis for early diagnosis and treatment of clinical dementia.

Supplemental Material

sj-docx-1-alz-10.1177_13872877251328712 - Supplemental material for The prevalence of mild behavioral impairment in older adults with mild cognitive impairment: A systematic review and meta-analysis

Supplemental material, sj-docx-1-alz-10.1177_13872877251328712 for The prevalence of mild behavioral impairment in older adults with mild cognitive impairment: A systematic review and meta-analysis by *Yan Zhao, Chang Tan, Yingjing Lu, Yingling Ge, Na Zhao, Yajie Tian, Liuyang Hui, Xiaobei Feng, Zihan Liu, Sha Li and Huixian Cui in Journal of Alzheimer's Disease

Footnotes

Acknowledgments

We are grateful to the National Natural Science Foundation of China and the Natural Science Foundation of Hebei Province for their financial support. Furthermore, we genuinely appreciate the hard work from the distinguished editor and reviewers.

ORCID iDs

Yan Zhao

Chang Tan

Yingjing Lu

Yingling Ge

Na Zhao

Yajie Tian

Liuyang Hui

Xiaobei Feng

Sha Li

Ethical considerations

Not applicable.

Consent to participate

Not applicable.

Consent for publication

Not applicable.

Author contributions

Yan Zhao: Conceptualization; Data curation; Software; Validation; Writing – original draft.

Chang Tan: Conceptualization; Data curation; Methodology; Writing – original draft.

Yingjing Lu: Conceptualization; Data curation; Writing – original draft.

Yingling Ge: Methodology; Software; Writing – original draft.

Na Zhao: Methodology; Writing – original draft.

Yajie Tian: Conceptualization; Formal analysis; Writing – original draft.

Liuyang Hui: Conceptualization; Writing – original draft.

Xiaobei Feng: Investigation; Software; Writing – original draft.

Zihan Liu: Data curation; Writing – original draft.

Sha Li: Supervision; Validation; Visualization; Writing – review & editing.

Huixian Cui: Formal analysis; Supervision; Validation; Writing – review & editing.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the National Natural Science Foundation of China (grant no. 82171582), the Natural Science Foundation of Hebei Province (grant no. C2024206025), the Science and Technology Research Project of Higher Education Institutions in Hebei Province (grant no. ZD2020105), and the Health Commission of Hebei Province (grant no. 20220976).

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data availability

The data supporting the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.

Supplemental material

Supplemental material for this article is available online.

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Supplementary Material

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