Cognitive impairment is a major contributor to disability and has become a critical global public health concern (Alzheimer’s Association, 2015; Llibre Rodriguez et al., 2008; Roberts and Knopman, 2013). According to the World Health Organization, cognitive impairment represents a substantial threat to healthy aging among middle-aged and older populations (Ping et al., 2020). As of 2010, it was estimated that approximately 38.77 million individuals in China were living with mild cognitive impairment, while 15.07 million were affected by dementia (Jia et al., 2020). Despite its significance, there remains a lack of effective treatments for cognitive impairment. Therefore, early identification and timely intervention are essential for mitigating the risk and progression of cognitive impairment.

Numerous studies have demonstrated that metabolic disorders, such as dyslipidemia, are significant risk factors for cognitive impairment (Bai et al., 2024; Farr et al., 2008; Feinkohl et al., 2019; Kivipelto and Solomon, 2006; Ma et al., 2017). Several lipid markers, including total cholesterol, triglycerides (TG), and high-density lipoprotein cholesterol (HDL-C), have been associated with the risk of cognitive impairment (Bai et al., 2024; Feinkohl et al., 2019; Reynolds et al., 2010; Shao et al., 2017; Whitmer et al., 2005); however, their predictive accuracy remains limited. The atherogenic index of plasma (AIP), defined as the logarithmic ratio of TG to HDL-C, is a sensitive marker reflecting the lipoprotein profile of plasma lipids and is considered a more robust indicator of dyslipidemia than either TG or HDL-C alone (Dobiásová and Frohlich, 2001; McLaughlin et al., 2003; Onat et al., 2010; Zhu et al., 2015). The AIP has been found to be significantly associated with various diseases, including cardiovascular disease, diabetes, and other metabolic disorders (Jiang et al., 2024; Qu et al., 2024). However, the relationship between AIP and cognitive impairment remains uncertain. Given its cost-effectiveness and ease of accessibility as a routine clinical measure, the AIP stands out as a simple, reliable, and affordable tool. Its straightforward implementation offers a clear advantage over more complex and costly methods, making it an efficient option for routine clinical practice.

Thus, based on data from the China Health and Retirement Longitudinal Study (CHARLS), this study investigates the relationship between the AIP and cognitive impairment in middle-aged and older individuals to provide population-based evidence for the association between the AIP and cognitive impairment. We hypothesize that elevated AIP, indicative of dyslipidemia marked by elevated TG and reduced HDL-C levels, may contribute to cognitive impairment by promoting inflammation, oxidative stress, and vascular damage, all of which are increasingly recognized as central mechanisms in the pathogenesis of cognitive impairment.

In this nationwide longitudinal cohort study of middle-aged and older individuals undergoing health examinations, we investigated the association between the AIP and cognitive impairment. Our findings revealed a significant positive correlation between higher baseline AIP levels and an increased risk of developing cognitive impairment, as well as a non-linear relationship between the AIP and cognitive impairment. To the best of our knowledge, this is one of the first studies to explore this association, suggesting that the AIP could be a valuable biomarker for the stratification of cognitive impairment risk, and maintaining lower AIP levels may help prevent cognitive impairment.

Cognitive decline has become a significant public health challenge globally, posing serious threats to both individual well-being and broader health outcomes (Alzheimer’s Association, 2015; Llibre Rodriguez et al., 2008; Roberts and Knopman, 2013). Cognitive impairment can emerge years before the clinical onset of dementia, yet effective therapeutic options to reverse this decline remain limited. Thus, there is an urgent need to determine the mechanisms and risk factors underlying cognitive impairment. Early identification of individuals at high risk, combined with timely and targeted interventions, is critical in mitigating the onset and progression of cognitive decline. Proactive measures in this respect are not only essential for delaying disease progression but also for reducing the substantial burden placed on healthcare systems and families.

Several studies have established a connection between metabolic disorders and cognitive impairment. A study in Korea, focusing on individuals aged 65 and older, identified metabolic disorders as an independent risk factor for cognitive impairment (Lee et al., 2017). Similarly, a systematic review of prospective cohort studies revealed that individuals with metabolic syndrome face a 1–2 times higher risk of cognitive decline compared to those without metabolic issues (Hao et al., 2011). A Chinese study further supported this by reporting a significant correlation between metabolic disorders and cognitive impairment (Wang et al., 2019). Among the components of metabolic disorders, dyslipidemia has emerged as a particularly important risk factor for cognitive impairment (Bai et al., 2024; Farr et al., 2008; Feinkohl et al., 2019; Kivipelto and Solomon, 2006; Ma et al., 2017). Elevated TG levels have been specifically associated with cognitive impairment, with research linking higher TG levels to cognitive impairment in various neurological and psychiatric conditions (Farr et al., 2008; Gonzalez-Escamilla et al., 2016; Lindenmayer et al., 2012). Recent findings suggest that elevated TG levels can negatively affect memory performance in middle-aged and older adults (Leritz et al., 2016), and TG levels are notably higher in older individuals with mild cognitive impairment compared to those without cognitive issues (Yao et al., 2016). These results suggest that TG levels are closely linked to cognitive impairment. In contrast, low levels of HDL-C have been identified as an independent risk marker for cognitive impairment in older adults (Feinkohl et al., 2019). HDL-C, commonly known as “good” cholesterol, is widely recognized for its protective effects on brain health (Ito and Ito, 2020). A recent study found a positive association between white matter volume and HDL-C levels, indicating that higher HDL-C levels may benefit cognitive function (Livingston et al., 2020). The AIP, calculated as the logarithmic ratio of triglycerides to HDL-C, serves as a sensitive marker of lipid and lipoprotein profiles (Dobiásová and Frohlich, 2001) and is considered a more reliable indicator of dyslipidemia than TG or HDL-C levels alone (McLaughlin et al., 2003; Onat et al., 2010; Zhu et al., 2015). It has also been strongly linked to various other conditions, including cardiovascular diseases, diabetes, and other metabolic disorders (Jiang et al., 2024; Qu et al., 2024).

Building on these findings, we conducted a follow-up observational study using data from the CHARLS database, focusing on middle-aged and older individuals. Taking advantage of the longitudinal cohort data, we gathered information from the 2018 cognitive function assessments to explore the relationship between AIP levels and cognitive impairment. The results revealed a significant positive association between baseline AIP levels and cognitive impairment in individuals aged 45 and above in China. The highest AIP quartile was associated with a 68% increased risk of cognitive impairment compared to the lowest quartile. Furthermore, the P for trend across AIP quartiles was <0.001 for all models, suggesting a significant and consistent trend, reinforcing a dose-response relationship between AIP levels and cognitive impairment risk. Although these effect sizes are moderate, they are clinically meaningful given the progressive nature of cognitive impairment, with even moderate increases in risk having important public health implications. Subgroup analysis, stratified by factors such as age and gender, also yielded consistent outcomes. Thus, AIP has the potential to be a novel lipid metabolism biomarker for cognitive impairment. And there is a non-linear relationship between AIP levels and the risk of cognitive impairment. The risk of cognitive impairment demonstrated a clear increase with higher AIP levels below the median value of 0.337. However, beyond this threshold, the rate at which the risk of cognitive impairment escalates appeared to slightly decelerate. This non-linear relationship may be attributed to the presence of additional comorbidities, such as cardiovascular diseases, diabetes, and chronic inflammation, which become more prominent as AIP levels increase. These factors could contribute to the attenuation of the direct impact of AIP on cognitive impairment, thereby leading to a less pronounced increase in cognitive impairment risk at higher AIP levels.

The underlying mechanisms linking the AIP and cognitive impairment are complex and remain incompletely understood, though several potential pathways may explain this association. One widely accepted explanation is that the relationship between lipids and cognitive function arises from dyslipidemia being a risk factor for stroke and cerebral hypoperfusion, both of which are closely linked to cognitive impairment (Wendell et al., 2009; Wright et al., 2008). Additionally, elevated cholesterol levels may have a more direct effect on cognitive function. While high cholesterol is involved in synaptogenesis and may initially aid in compensatory neural repair in the context of cognitive impairment (Mauch et al., 2001), it also contributes to the accumulation of β-amyloid peptides, which accelerates the progression of cognitive decline (Burns and Duff, 2002). Moreover, recent studies have identified the AIP as a robust biomarker of dyslipidemia, with higher levels suggesting more severe insulin resistance (IR) (Shi and Wen, 2023; Yin et al., 2023). There is also increasing evidence of a strong connection between IR and a heightened risk of cognitive decline (Hong et al., 2021; Hooshmand et al., 2019; Neergaard et al., 2017). IR is a distinctive metabolic disorder, typically characterized by elevated insulin levels. Prolonged exposure of brain neurons to elevated insulin may lead to neurodegeneration and persistent memory impairment (Blázquez et al., 2014). Additionally, IR can reduce glucose metabolism in specific regions of the brain, potentially adversely affecting memory function (Willette et al., 2015). Several clinical studies have suggested that TG can cross the blood-brain barrier, potentially impairing cognitive function by inducing insulin receptor resistance (Banks et al., 2018). Moreover, the AIP not only reflects elevated TG levels but also indicates reduced HDL-C levels. Low HDL-C may diminish its neuroprotective effects, such as anti-inflammatory actions and the inhibition of β-amyloid aggregation, while high TG levels can further damage neurons, exacerbating cognitive decline (Cockerill et al., 1995; Cockerill et al., 2001; McGeer and McGeer, 1998). TG levels may impair cognition through several mechanisms. TG metabolites can influence glutamate release and alter N-methyl-D-aspartate receptor-mediated calcium influx, potentially disrupting synaptic plasticity in the hippocampus. Additionally, TG-induced oxidative stress and chronic inflammation may damage neuronal signaling. Elevated TG levels could also hinder leptin from crossing the blood-brain barrier, thereby reducing its cognitive-enhancing effects (Chang et al., 2004; McGeer and McGeer, 1998).

Cognitive impairment has become an increasingly prominent issue, strongly associated with poor outcomes and significantly impacting individuals’ quality of life, while also placing a considerable burden on families and society. The early prevention of cognitive impairment is thus of critical importance. Our findings offer valuable clinical insights into reducing the incidence of cognitive impairment. Our study specifically found that the AIP holds significant clinical value as a predictor of cognitive impairment in the Chinese population aged 45 years and older. Because the AIP is calculated from routine lipid measurements (TG and HDL-C), it is a simple, cost-effective marker that accurately reflects an individual’s lipid metabolism. Our results indicate a clear positive correlation between elevated AIP levels and the risk of developing cognitive impairment, suggesting that the AIP may serve as a practical and reliable lipid-based biomarker for predicting cognitive decline. The clinical advantages of the AIP include its ease of measurement, reproducibility, and robust predictive capacity. Compared to other more complex or less widely applicable biomarkers, the AIP, as part of standard lipid testing, offers the potential for large-scale screening and early intervention. As such, the AIP has the potential to be a valuable tool in clinical practice for assessing cognitive impairment risk, facilitating the early identification of high-risk individuals, and enabling timely preventive measures. However, further rigorous and large-scale prospective studies are needed to confirm the clinical utility of the AIP as an early predictor of cognitive impairment and to establish its applicability across different populations.

This study has several limitations. First, as an observational study, although we attempted to control for known confounders, unmeasured confounding factors may still have influenced the results. As our study relied on existing data from CHARLS, the availability of certain variables was limited, which may have further contributed to unmeasured confounding. Secondly, we only examined the impact of baseline AIP levels from 2011 on subsequent cognitive impairment, without considering the potential effects of dynamic changes in the AIP over time on cognitive function. Future studies incorporating repeated measurements of AIP and its contributing lipid components would allow for a more comprehensive assessment of its long-term impact on cognitive health and help determine whether cumulative exposure or temporal changes in AIP play a significant role in cognitive impairment. And participant attrition may introduce bias and affect the generalizability of the findings. However, we have made adjustments for baseline characteristics and potential confounders to minimize this impact. Additionally, test-retest reliability for the cognitive measures has not been reported in the CHARLS dataset. while we evaluated cognitive function using episodic memory and mental acuity—reliable screening tools widely used in clinical practice—a more comprehensive assessment across multiple cognitive domains would be necessary to fully understand overall cognitive function. Moreover, the study did not differentiate between the underlying causes of cognitive impairment, and all participants were from China. Future research should aim to expand the scope of data collection to include a more diverse range of participants and conduct more detailed analysis of different types of cognitive impairment across various ethnic groups to strengthen our findings.

The study demonstrates that elevated AIP levels are associated with an increased risk of cognitive impairment in middle-aged and older adults, showing a non-linear dose-response relationship between the AIP and cognitive function. This suggests that targeted interventions aimed at managing dyslipidemia may play a beneficial role in reducing the incidence of cognitive impairment.