Osteoporosis, a systemic skeletal disorder that increases the risk of fractures, is characterized by a decrease in bone mass and the deterioration of bone tissue microstructure (1). The economy and public health are greatly impacted by osteoporosis as the global populace ages (2). This impact is largely driven by the increased healthcare costs associated with managing fractures, loss of mobility, and long-term care, which are common consequences of osteoporosis (3). Previous research has indicated an annual increase in the prevalence of osteoporosis among middle-aged and older adults (4, 5). This increase can be attributed to factors such as longer life expectancy, declining physical activity levels, and inadequate intake of calcium and vitamin D, which are critical for maintaining bone health (6). A decreased bone mineral density (BMD), a well-established marker of osteoporosis, is associated with an elevated risk of fractures (7). As a result, there is growing emphasis on identifying new risk factors for low bone mineral density in osteoporosis, which could lead to the development of new preventative strategies.

Obesity is defined as abnormal or excessive body fat and has a detrimental impact on health, being strongly associated with the onset of various chronic diseases (8). Obesity influences skeletal homeostasis in a complex manner, exerting both positive and negative effects on the development of osteoporosis. Although it was once widely accepted that obesity was positively associated with bone mass or density (9, 10), recent studies suggest a more nuanced relationship (11, 12). Body mass index (BMI) and waist circumference (WC) are currently the most widely used clinical markers for assessing obesity. Many experts consider BMI to be a relatively crude and controversial method for assessing the risk of various diseases and mortality, as it only reflects overall obesity and cannot account for other body components such as muscle mass, bone density, and fat distribution (13, 14). WC measures the extent of central or abdominal obesity, which contributes to metabolic abnormalities and increases the risk of diabetes, non-alcoholic fatty liver disease (NAFLD), and metabolic syndrome (MetS) (15). However, WC cannot differentiate between visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT); the former refers to ectopic fat accumulation, which leads to insulin resistance and organ dysfunction (16).

In the field of metabolic research, the lipid accumulation product (LAP) index has gained increasing attention. The LAP index, calculated by combining triglyceride (TG) levels and waist circumference (WC), is used to assess and reflect the extent of abdominal lipid accumulation (17). Compared to conventional lipid profiles, the LAP index demonstrates significant predictive power for chronic kidney disease, diabetes, and other related disorders (18–20). Compared to conventional measures such as waist-to-height ratio, BMI, and WC, the LAP index exhibits greater predictive efficiency (21, 22), and it has demonstrated strong predictive ability in in various clinical settings (23, 24). According to several studies, LAP may be a sign of NAFLD, heart disease, type 2 diabetes, and MetS (21, 25–27).

In addition, obesity (generally meaning high LAP index) is associated with higher incomes for people (28, 29), which may lead to a higher poverty-income ratio (PIR). On the other hand, Wang et al. employed multiple linear regression to examine the relationship between PIR and BMD in women, identifying a strong positive correlation (30). This association was further confirmed by a recent cross-sectional study conducted on adult men, which also highlighted the importance of socioeconomic status in managing osteoporosis (31). The relationship between socioeconomic status (SES) and health outcomes, including BMD and obesity, is well-documented (32). Low socioeconomic status (SES) is frequently associated with food insecurity, limited access to nutritious foods, and environments that discourage physical activity, all of which collectively contribute to obesity and poor bone health. Previous studies have highlighted that a lower poverty-income ratio (PIR) is associated with higher rates of obesity, due to increased exposure to food swamps—areas characterized by a high density of fast food outlets and limited access to fresh produce (33). Furthermore, poverty can limit opportunities for physical activity, a situation exacerbated by high crime rates and poorly designed built environments, both of which act as barriers to maintaining a healthy weight and preserving bone density (34). In light of these correlations, PIR is thought to mediate the link between BMD and the LAP index.

Currently, there is insufficient evidence to establish a connection between the LAP index and total femur BMD. The aim of our study was to address these knowledge gaps by investigating the association between the LAP index and femur BMD in adult U.S. participants, and by quantifying the role of PIR in mediating the relationship between the LAP index and total femur BMD.

This investigation of 3,223 participants demonstrated a positive, nonlinear correlation between the LAP index and total femur BMD. Notably, the total femur BMD for all participants revealed a LAP index saturation point of 16.05. Beyond this threshold, the rate of increase in total femur BMD naturally declined, which is crucial for maintaining BMD at an optimal level. Consequently, the current study identifies the LAP index as an appropriate metric for clinically assessing total femur BMD. To our knowledge, this is the first study to demonstrate a saturation effect between baseline LAP index and total femur BMD levels.

Osteoporosis and obesity have become a global epidemic, but the link between the two is unclear. Osteoporosis is a biological disorder that weakens and increases the brittleness of bones over time, increasing the chance that they may fracture (35). One essential marker for osteoporosis diagnosis is a low BMD. Epidemiological research indicates that as the global population ages, lifestyle changes, economic growth, osteoporosis, and inadequate bone density are becoming increasingly common. According to reports, osteoporosis affects more than one-third of older adults in the United States, and its prevalence is steadily increasing (36). With regard to the skeletal system as a whole, a study has shown that body fat is one of the most significant predictors of BMD (31). Several metrics are used to assess obesity, particularly given the known harmful effects of intra-abdominal fat. BMI and WC are globally accepted standards for defining obesity (37–40). We found that BMI was positively associated with BMD in numerous studies (41, 42). That being said, some studies indicate that WC, a metric used to assess abdominal obesity, is negatively correlated with BMD (43), backed up by relevant research (44–46). Furthermore, several studies have shown that VAT is negatively correlated with BMD (47–50). Additionally, Kim et al. found that triglycerides were negatively correlated with BMD in both men and women (51). Despite mounting evidence from several epidemiological studies showing that traditional anthropometric parameters are related to BMD, the obesity conundrum remains unresolved. Therefore, identifying an obesity indicator that addresses the obesity paradox is crucial. Furthermore, although WC and BMI are commonly used as standard measures to describe obesity, they cannot differentiate between lean and fat tissue. Because of doubts about the reliability of these traditional indicators, researchers have recently developed new adiposity indices (52, 53). The LAP index was developed to provide a comprehensive measure that accounts for anatomical and physiological changes associated with visceral fat accumulation (25, 26, 54). Kahn is credited with developing the LAP index, a marker for assessing excessive lipid accumulation (21). In a cross-sectional study, Taverna et al. demonstrated that the LAP index showed a high level of accuracy in diagnosing MetS (55). The findings of Shi et al.’s study supported the notion that arterial stiffness is positively correlated with the LAP index (56). The study by Kim et al. revealed a strong correlation between the LAP index and both hyperuricemia and cardiovascular risk, compared to other adiposity measures such as the visceral adiposity index and body roundness index (57). Additionally, methods such as computed tomography and magnetic resonance imaging are frequently used for the sensitive detection of visceral fat. However, these techniques have several drawbacks, including high costs, lengthy procedures, and potential radiation risks. These methods are therefore impractical for extensive population screens. In contrast to conventional lipid profiles, LAP may evaluate a wide range of metabolic disease syndromes and offer a thorough evaluation of an individual’s metabolic health (58–60). Our investigation identified a saturation association between the LAP index and total femur BMD, the breakpoint at 16.05 indicates a substantial threshold influence.

The mechanisms underlying the observed positive correlation between BMD and the LAP index are not yet fully understood. However, this relationship may be explained by several hypothesized mechanisms. Firstly, obese or overweight individuals may produce higher levels of insulin, estrogen, and other endocrine hormones, which inhibit bone remodeling and resorption, thereby helping to maintain bone mass (61–64). Secondly, the accumulation of excess fat can alter the mechanical properties of the skeleton, leading to changes in bone tissue (65, 66). Thirdly, activation of the Wnt/β-catenin signaling pathway has been shown to effectively inhibit adipocyte proliferation and differentiation, leading to reduced visceral fat deposition (67). The enhancement of osteoblast function depends on the successful initiation and activation of the Wnt/β-catenin signaling pathway, with mutations in the LRP5 gene within this pathway recognized as a significant contributor to the development of osteoporosis (68). Thus, it is reasonable to suggest that a high LAP index or severe obesity may influence the development of osteoporosis by interfering with the Wnt/β-catenin signaling pathway. Lastly, obesity may promote the differentiation of bone mesenchymal stem cells into adipocytes, increasing the number of adipocytes and reducing the number of osteoblasts (69).

The results of this investigation demonstrated a non-linear relationship between the LAP index and total femur BMD, both before and after applying a generalized additive model to account for confounding factors. This study is notable for being the first to identify threshold and saturation effects, as well as a non-linear relationship between the LAP index and total femur BMD. These findings provide medical professionals with additional tools to help obese patients maintain a healthy LAP index (around 16.05), support optimal bone mineral density, and reduce the risk of obesity-related illnesses and complications. However, further research is needed to better understand the mechanisms behind the LAP index’s saturation effects on BMD. VAT plays a crucial role in the relationship between the LAP index and BMD (70–72). VAT is metabolically active and has been associated with increased inflammation, which can negatively affect bone health and lead to lower BMD (73). As the LAP index is an indicator of VAT, it is reasonable to hypothesize that individuals with a LAP > 16 have higher VAT levels, and consequently, a higher risk of reduced BMD. However, it is also noteworthy that obesity, characterized by a higher LAP index, has paradoxically been associated with increased BMD. This suggests a complex interplay in which the protective effects of mechanical loading from increased body weight may be offset by the detrimental effects of VAT-induced inflammation. In addition, the differential impact of VAT and SAT on BMD provides insight into the results observed at the LAP index turning point (74). As the LAP index increases, indicating higher VAT, one might expect a corresponding decrease in BMD due to the inflammatory and metabolic effects of VAT. However, not all obese individuals have high levels of VAT; some may predominantly have SAT, which could explain the observed variation in BMD at similar LAP levels (75). This complexity suggests that the LAP index is an imperfect proxy for VAT and that the relationship between adiposity, fat distribution, and bone health is multifaceted. The results indicating a turning point in the relationship between the LAP index and BMD could be partially explained by the differential distribution of fat tissue in obese individuals. While a higher LAP index generally reflects higher VAT, which is associated with lower BMD, the presence of significant SAT may mitigate this effect. This variability in fat distribution among individuals with similar LAP values could account for the observed inconsistencies in BMD outcomes (76). Therefore, further research is necessary to explore the nuances of fat distribution and its specific impact on bone health. Another factor contributing to the LAP index saturation effects is the presence of a unique bone-fat axis that exists between bone and adipose tissue in vivo, along with various bioactive compounds that help maintain bone homeostasis (77). In addition, we conducted a mediation analysis that found PIR partially mediated the relationship between a high LAP index and increased bone mineral density. In recent years, researchers have conducted several studies on the relationship between PIR and BMD. Data from the Louisiana Osteoporosis Study suggest that SES and BMD are positively correlated in the general population (78). Additionally, Xiao et al. demonstrated that PIR is positively associated with total spine BMD (31). A meta-analysis of eight epidemiological studies supports the hypothesis that individuals with higher income levels are more likely to have greater BMD, as evidenced by the majority of population-based research (79). This cross-sectional study, which included 3,223 representative U.S. subjects, similarly corroborated this conclusion. Given this research, it is believed that PIR may have partially mediated the positive correlation between the LAP index and total femur BMD, and the findings of this study’s mediation analysis lend support to this notion. This mediation can be explained through several social mechanisms. For example, individuals with lower PIR are more likely to live in food swamps, which increases the risk of obesity due to the high availability of energy-dense, nutrient-poor foods. Additionally, low PIR is associated with higher crime rates, which can limit outdoor physical activity and further contribute to obesity and poor bone health. These factors highlight the complex interplay between socioeconomic status (SES), environmental factors, and health outcomes (32–34).

The sample size is large and representative, which is one of the key strengths of this research. The study also carefully adjusted for several confounding variables, ensuring that the results are reliable and applicable to a broad population. Additionally, by employing the LAP index, this study effectively explores the relationship between the LAP index and clinical outcomes. However, it is important to acknowledge certain limitations of the present research. The primary issue is that it remains uncertain whether the observed decrease in femur bone mineral density was directly caused by the LAP index. Furthermore, this study cannot fully rule out residual confounding from unknown factors, even after adjusting for several likely confounders. Moreover, we acknowledge that PIR, as a standalone socioeconomic indicator, has limitations in accurately reflecting an individual’s specific nutritional status. More comprehensive indicators are needed to better assess the nutritional status of individuals. Lastly, while a broad range of study populations was included in this research, the findings may not be applicable to certain populations—such as cancer patients—since they were not part of the current study.

We identified a curvilinear relationship, more specifically a saturation effect, between the LAP index and total femur BMD in U.S. adults. According to the present study, individuals over the age of 20 may be able to achieve an optimal LAP/BMD balance by maintaining a modest LAP index (around 16.05), which would promote healthy bone formation. Moreover, the positive correlation between the LAP index and total femur BMD is partially mediated by PIR. Looking ahead, the LAP index offers a simple and affordable tool to help obese individuals maintain optimal BMD and reduce their risk of obesity-related illnesses.