With one-fifth of the world’s population predicted to be 65 or older by 2030, population aging is a global problem (Rudnicka et al., 2020). A steady decrease of physiological function is a hallmark of aging. It is believed to result from a build-up of molecular alterations or “hallmarks” that impair tissues’ and organs’ ability to function and recovery (Chakravarti et al., 2021; López-Otín et al., 2023). This, in turn, is thought to cause chronic morbidities, such as metabolic, cardiovascular, neoplastic, and neurodegenerative disorders, as well as geriatric symptoms like frailty and immobility (Abbasi et al., 2023; Wagner et al., 2023; Zhou et al., 2023; Iskusnykh et al., 2024; Montégut et al., 2024). An innate biological process that is adaptable and responsive to therapeutic interventions coexists with aging. Using of various genetic, nutritional, and pharmaceutical interventions, scientists have made impressive strides in the last few decades in extending the lifespan (Mkrtchyan et al., 2020; Sourada and Kuglík, 2020; Wang et al., 2022). Therefore, it is crucial to identify biomarkers that influence the aging process and associated health risks, given the growing severity of the global population aging issue. To uncover new insights into the management and delay of the aging process, this study intends to investigate possible associations between PA, a crucial marker of biological aging, and CMI.

PA is a crucial idea connected to biological aging (Liu et al., 2018; Kuo et al., 2021). Generally, chronological age (CA) and clinical biomarkers, and blood cell parameters are utilized to evaluate PA. Given that PA provides a more accurate representation of how the body ages than CA, studies have indicated that PA is a good predictor of death, chronic morbidities, and a decline in physical function (Kuo et al., 2022). Genetic predispositions and poor lifestyle choices, like heavy smoking, excessive alcohol use, chronic illnesses, and cancer, all contribute to an increased PA. On the other hand, living a healthy lifestyle that includes eating fruits and vegetables and engaging in moderate exercise might reduce PA (Noren Hooten et al., 2022; Li et al., 2024a; Wu et al., 2024).

CMI was introduced as a novel metric by Wakabayashi and Daimon (2015) to evaluate visceral obesity using blood lipid markers and the weight-to-height ratio (WHtR). WHtR, a measure of abdominal obesity that makes more sense than just measuring waist circumference (WC). It has been shown that WC or body mass index (BMI) as cardiovascular disease risk factors are less reliable discriminators than WHtR. Because BMI measurements do not distinguish between trunk and visceral obesity, whereas anatomical fat distribution is considered important because it produces different metabolic effects (Chen R. et al., 2022; Tao et al., 2024). However, CMI simultaneously takes into account triglyceride (TG) and high-density lipoprotein cholesterol (HDL-C), which are crucial indicators of cardiovascular risk and obesity (Liu C. et al., 2022; Baratta et al., 2023; Nussbaumerova and Rosolova, 2023). Survies indicate that the CMI is connected to cardiovascular illnesses, metabolic syndrome, and other conditions, implying the importance of it for linked disease screening (Lazzer et al., 2023; Miao et al., 2023; Sun et al., 2023; Ye et al., 2024). According to recent studies, people with high CMI may have more systemic inflammation (Carvalho et al., 2024; Xu B. et al., 2024). Conversely, regular exercise is linked to a large reduction in CMI (Xue et al., 2024). Moreover, elevated CMI is significantly correlated with insulin resistance (Feng et al., 2024; Song et al., 2024; Wu and Xu, 2024). However, physical activity, insulin resistance and inflammation are intimately associated with aging (Kurauti et al., 2021; Abbasi et al., 2023; Butt et al., 2024; Singh et al., 2024). Additionally, aging is significantly impacted by BMI (Etzel et al., 2022; Lundgren et al., 2022).

To our knowledge, no previous research has examined the relationship between biological aging and CMI. Thus, the objectives of our research were to assess the correlation between biological aging and CMI, to offer guidance on the prevention and management of aging.

According to our research, there is a positive correlation between biological aging and CMI. Furthermore, the link persisted even after controlling for other variables, suggesting that CMI was a detrimental element in the biological aging process. A non-linear relationship was identified through dose-response analysis. The inflection points was 1.10 according to threshold effect analysis. This finding can inform more accurate and effective prevention and treatment strategies for biological aging.

CMI is a novel anthropometric measure that shows a strong relationship to metabolic syndrome (Wakabayashi, 2022; Tamini et al., 2024). Numerous studies have shown that CMI is associated with various systemic diseases, highlighting its correlation with worse prognoses. Our results were in alignment with the previous research, which has demonstrated a positive association between biological aging and CMI. Metabolic syndrome is known as a group of risk factors for diabetes and cardiovascular diseases with a pathophysiology closely related to aging (Roddy, 2021; Li et al., 2024b; Oya et al., 2024). Nevertheless, no previous research has examined the relationships between CMI and biological aging. Numerous other anthropometric and metabolic markers, including BMI, triglyceride glucose (TyG) index, WHtR, and visceral adiposity index (VAI), have all been shown to be positively correlated with biological aging. According to a meta-analysis, the epigenetic age of the heavier twins in a BMI-discordant monozygotic twin pair (ΔBMI > 3 kg/m²) was 5.2 months older than that of their lighter cotwin (Lundgren et al., 2022). A higher BMI z-score was substantially linked to a faster speed of aging as measured by DunedinPoAm (b = 0.0017 adjusting for all covariates). In the relationship between obesity and aging has grown as higher BMI across the lifespan has been linked to early onset of age-related illnesses and mortality (Etzel et al., 2022). In middle-aged and older populations, Qiu et al. (2024) clarified a non-linear connection between the TyG index and the α-Klotho protein (the serum anti-aging protein). When the TyG indices were less than 9.7, no discernible association was seen. Nonetheless, for every unit rise in TyG index over 9.738 there was a corresponding increase in klotho levels of 106.44 pg/ml (Qiu et al., 2024). Additionally, every 0.1 unit rise in WHtR was inversely correlated with the Successful Aging Index (SAI), lowering SAI by nearly 0.5 units (Koloverou et al., 2020). Every additional unit increase in VAI was correlated with a 0.312-year increase in PhenoAgeAccel. Among cancer patients, this positive correlation was more statistically significant. Furthermore, a segmented correlation was observed between VAI and PhenoAgeAccel, with a turning point identified at 10.543 (Xu C. et al., 2024). Additionally, a saturation effect was demonstrated by a nonlinear association between the serum anti-aging protein klotho concentrations and the VAI score. It showed no discernible link when VAI was larger than 3.21, but they were negatively connected when VAI was less than 3.21 (Cui et al., 2023). In the current study, we introduced CMI as a novel predictor of biological aging. To date, this is the first study to evaluate the prognostic value of CMI as a metabolism-related index that is easy to obtain in the context of biological aging. However, additional research is necessary to validate the use of CMI in public health assessments of various specialized populations.

Although CMI is highly related to biological aging as elucidated by our study, the underlying biological mechanisms driving these associations are not fully deciphered. Chronic inflammation and reactive oxygen species (ROS) are thought to be significant factors in the progression of biological aging, which may explain the positive association between CMI and biological aging. The activation of the cyclic GMP-AMP synthase (cGAS)/stimulator of interferon genes (STING) pathway by mitochondria-derived cytosolic DNA (mt-DNA) has been found to produce inflammation factors. Previous studies highlight the crucial role that cytosolic mtDNA-induced cGAS-STING activation plays in the pathophysiology of obesity (Elzinga et al., 2023; Kim et al., 2023; Ma et al., 2023). Microglias exhibit cGAS activity in response to cytosolic DNA released from disrupted mitochondria, indicating a method by which cGAS-STING signaling is activated in the aging brain. Single-nucleus RNA-sequencing analysis of microglia in a cGAS gain-of-function mouse model demonstrates that engagement of cGAS in microglia is sufficient to direct aging-associated transcriptional states leading to bystander cell inflammation (Paul et al., 2021; Gulen et al., 2023; Jiménez-Loygorri et al., 2024). Furthermore, the positive energy balance typical of obesity worsens the excess deposition of ectopic fat with aging. Increased inflammatory cell infiltration and altered chemokine expression, including increased TNF-α and IL-6, are seen in visceral adipose tissue (Colleluori and Villareal, 2021). The increased adipose tissue inflammation with obesity and aging establishes the typical low-grade chronic inflammation observed in older adults (Villareal, 2023). These demonstrate the role of the inflammation in the aging and obesity. ROS as a physiologically significant cause of ribotoxic stress response activation and translational abnormalities (Lennicke and Cochemé, 2021). A significant fraction of the metabolic stress signals responsible for undesirable metabolic maladaptation in obesity and aging stem from damaged ribosomes (Shields et al., 2021; Hajam et al., 2022). ROS-induced ribosome impairment underlies ZAKα-mediated metabolic decline in obesity and aging (Snieckute et al., 2023). Excess calories raise the production of ROS, which harms the mitochondria, endoplasmic reticulum, and nucleus. ROS-induced DNA damage upregulates the cell cycle arrest-related proteins p16 and p21, which causes chromatin rearrangement, cellular senescence, and the release of proinflammatory mediators (Tam et al., 2020). As mentioned, the persistence of DNA damage is a common biological process linking aging and obesity. It is hypothesized that excess leptin synthesis, inflammation, and ROS cause adipose tissue to accumulate DNA damage, which then accumulates mutations in DNA repair genes. Senescence is further induced by the inadequate ability of DNA repair proteins to repair damaged DNA. Therefore, obesity speeds up the aging process by adding to the damage to DNA that comes with aging (Kasper et al., 2022; Kudabayeva et al., 2022; Chowdhury et al., 2023). More investigation is necessary because the precise molecular pathways are not fully understood.

There are various useful implications for this study. It has been discovered that a higher CMI significantly speeds up biological aging. Because the NHANES dataset, on which this study was based, used a fully random sampling procedure, our findings are guaranteed to be representative of the total population. People with high CMI may require additional interventions, such as nutrition, physical activity, and potentially medication-assisted dyslipidemia treatment, to slow down the aging process.

Firstly, despite adjusting for several confounders, unmeasured or residual confounding cannot be fully excluded. Secondly, treatment factors such oral antidiabetic drugs that could affect CMI were not taken into account. Thirdly, it should be mentioned that participant questionnaires were used to diagnose the study’s cases of hypertension, diabetes, heart failure, cancer, and stroke. This could introduce recollection bias and compromise the study’s ability to make accurate diagnoses. Finally, a number of blood biomarkers were used to determine PA. However, these biomarkers may not correctly reflect other measures of biological aging, such as DNA methylation, telomere length.

After adjusting for potential confounders, our research demonstrated a positive correlation between CMI and biological aging. CMI be integrated into routine health screenings or aging assessments by healthcare professionals. Further cohort studies or randomized controlled trials are desperately needed to validate this result to provide more effective prevention and treatment strategies for biological aging in the future.