UNASSIGNED: Hypertension (HTN) is a prevalent global health concern. From the standpoint of preventive and personalized medicine (PPPM/3PM), early detection of HTN offers a crucial opportunity for targeted prevention and personalized treatment. This study aimed to evaluate the association between the weight-adjusted waist index (WWI) and HTN risk.
UNASSIGNED: A case-control study using data from the National Health and Nutrition Examination Survey (NHANES) from 2005 to 2018 was conducted. Logistic regression models assessed the association between WWI and HTN. Subgroup analyses explored differences in age, sex, ethnicity, and diabetes status. Restricted cubic spline (RCS) analyses examined potential nonlinear relationships.
UNASSIGNED: A total of 32,116 participants, with an average age of 49.28 ± 17.56 years, were included in the study. A significant positive association between WWI and the risk of HTN was identified (odds ratio [OR], 2.49; 95% CI, 2.39-2.59; P < 0.001). When WWI was categorized into quartiles (Q1-Q4), the highest quartile (Q4) exhibited a stronger association compared to Q1 (OR, 2.94; 95% CI, 2.65-3.27; P < 0.001). Subgroup analyses indicated that WWI was a risk factor for HTN across different populations, although variations in the magnitude of effect were observed. Furthermore, the findings from the RCS elucidated a nonlinear positive correlation between WWI and HTN.
UNASSIGNED: WWI is independently associated with HTN risk, highlighting its potential as a risk assessment tool in clinical practice. Incorporating WWI into early detection strategies enhances targeted prevention and personalized management of HTN.
UNASSIGNED: The online version contains supplementary material available at 10.1007/s13167-024-00375-3.

OBJECTIVE: Current measures of frailty often rely on subjective assessments or complex scoring systems. This study aims to investigate the utility of a novel anthropometric measure, the Weight-Adjusted Waist Index (WWI), as a simple and objective predictive marker for frailty in older adults.
METHODS: This cross-sectional study included 847 patients aged 65 years and older. Comprehensive geriatric assessments and anthropometric measurements were conducted. Frailty was diagnosed using the Clinical Frailty Scale (CFS). The association between WWI and frailty was analyzed using multivariate logistic regression analysis.
RESULTS: The mean age of the participants was 74.9 ± 6 years, with 56.3% (n = 477) being women and 14.8% (n = 125) classified as frail. The frail group had a significantly higher WWI than the non-frail group (p < 0.001). In multivariate logistic regression analysis, WWI remained significantly associated with frailty, even after adjusting for other potential confounding factors (OR = 2.51, 95% CI 1.77-3.57, p < 0.001). The predictive ability of WWI for frailty was measured by the area under the receiver operating characteristic (ROC) curve, which was 0.705 (95% CI 0.67-0.73; p < 0.001). The optimal WWI threshold for predicting frailty was identified as > 12.
CONCLUSIONS: The Weight-Adjusted Waist Index shows significant potential as a simple and objective predictive marker for frailty in older adults.

OBJECTIVE: The weight-adjusted waist index (WWI) is a recently developed index for measuring obesity. The aim of this study was to investigate the association between WWI levels and overactive bladder (OAB) in a nationally representative population.
METHODS: This cross-sectional study used data from the National Health and Nutrition Examination Survey (NHANES) database between 2007 and 2016. OAB was defined as the Overactive Bladder Syndrome Symptom Score (OABSS, score ≥ 3). The WWI index was calculated as the square root of waist circumference (WC, cm) divided by body weight (kg). We used weighted logistic regression models to assess the relationship between the WWI index and OAB in adult women. The reliability of the findings was assessed using restricted cubic spline, subgroup analysis.
RESULTS: A total of 10,563 individuals were included in the study, and the prevalence of OAB was 18.6%. Higher WWI was associated with an increased risk of overactive bladder syndrome. In model 1 with unadjusted variables (OR = 1.148; 95% CI = 1.148-1.149, p < 0.001), model 2 (OR = 1.253; 95% CI = 1.253-1.254, p < 0.001) and model 3 with fully adjusted variables (OR = 1.215; 95% CI = 1.214-1.215, p < 0.001) in which the association was significant. The results of the subgroup analyses showed that age stratification and stroke status could modify this association between WWI and OAB. Restricted cubic spline showed a nonlinear relationship between WWI and OAB (p for nonlinear < 0.05).
CONCLUSIONS: Weight-adjusted waist circumference index (WWI) values are positively associated with the risk of developing OAB in adult women in the United States, but further studies are needed to elucidate the causal relationship between WWI and OAB.

BACKGROUND: The relationship between obesity and type 2 diabetes with bone health has always been a topic of debate. The weight-adjusted waist index has become a commonly used indicator for assessing central obesity, fat, and muscle mass. However, currently there is no research reporting the association between weight-adjusted waist index and risk of osteoporosis in populations of type 2 diabetes. Therefore, this study aims to provide new information on the association between weight-adjusted waist index and risk of osteoporosis in type 2 diabetes.
METHODS: This cross-sectional study involved 963 patients with type 2 diabetes who were admitted to the Department of Endocrinology of Cangzhou Central Hospital. Multivariate logistic regression models were used to assess the association between weight-adjusted waist index and osteoporosis. The potential nonlinear association was evaluated. The effects of interaction between subgroups were assessed using the likelihood ratio test.
RESULTS: Weight-adjusted waist index was positively associated with the risk of osteoporosis, regardless of traditional confounding factors. For each 1 unit increased in weight-adjusted waist index, the risk of osteoporosis increased by 67%. Furthermore, there was a nonlinear relationship between weight-adjusted waist index and osteoporosis. The subgroup analysis did not reveal any significant interactions.
CONCLUSIONS: Our study indicated a positive association between weight-adjusted waist index and the risk of osteoporosis in adult Chinese type 2 diabetes patients, and this relationship was nonlinear.

OBJECTIVE: Identifying a more suitable marker among various measures of adiposity, demonstrating strong associations and predictive ability for clinical use, remains a topic of debate. Weight-adjusted waist index (WWI) has been proposed as a novel index of adiposity, yet its exploration is limited, especially in Chinese populations. This study seeks to examine the associations between body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHTR), weight-adjusted waist index (WWI), waist circumference divided by body mass to the power of 0.333 (WC/M0.333), visceral adiposity index (VAI), lipid accumulation product (LAP), and the incidence of diabetes, cardiovascular disease, and non-accidental mortality in Chinese populations. Furthermore, our goal is to compare the respective predictive values of these measures for these health outcomes.
RESULTS: This prospective cohort study included 21,750 subjects with a 9-year follow-up period. Cox proportional hazard models were used to investigate the relationship between eight anthropometric indexes and the incidence of diabetes, cardiovascular disease, and non-accidental mortality. The predictive value of these eight indexes was compared using the area under the curve metric. Significant positive associations were found between WWI and the risk of diabetes. Using the first quartile (Q1) of WWI as the reference group, hazard ratios with 95% confidence intervals for the risk of diabetes were 1.58 (0.98-2.55) for Q2, 2.18 (1.34-3.35) for Q3, and 2.27 (1.41-3.67) for Q4. Significant associations were observed with the highest quartile of WWI for the risk of cardiovascular disease [Q2: HR 1.45 (95% CI 1.06-1.98); Q3: 1.33 (0.97-1.83); Q4: 1.55 (1.13-2.14)] and risk of non-accidental mortality [Q2: 0.94 (0.80-1.11); Q3: 1.24 (1.04-1.48); Q4: 1.44 (1.16-1.79)]. Receiver operating characteristic analysis revealed that WWI exhibited superior discrimination and accuracy in predicting cardiovascular disease and non-accidental mortality compared to other adiposity indexes (BMI, WC, WHR, WHTR, WC/M0.333, VAI, and LAP).
CONCLUSIONS: WWI exhibited the most robust and consistent association with the incidence of cardiovascular disease and non-accidental mortality. Given its simplicity and widespread use, WWI emerges as a novel and practical predictor of diabetes, cardiovascular disease, and non-accidental mortality among the eight adiposity indexes investigated in this study.

OBJECTIVE: This study aimed to investigate the association between weight-adjusted waist index (WWI) and trabecular bone score (TBS) and to assess the ability of WWI to identify individuals with degraded bone microarchitecture (DBMA).
METHODS: This cross-sectional study included participants aged 20 and older from the National Health and Nutrition Examination Survey. Furthermore, WWI was calculated by waist circumference and body weight. In addition, linear regression models were employed to investigate the association between WWI and TBS, while logistic regression models were employed to determine the association between WWI and the risk of DBMA. Finally, the performance of WWI in identifying individuals with DBMA was using the receiver operating characteristic (ROC) curves with area under the ROC curve.
RESULTS: A total of 4,179 participants with a mean age of 49.90 years were included in the final analysis. WWI was negatively associated with TBS and positively associated with an increased risk of DBMA. Furthermore, the associations between WWI and TBS, as well as DBMA risk, were stable regardless of stratification by age, sex, race, or body mass index (BMI). Moreover, WWI achieved good performances in identifying individuals with DBMA or low TBS. In addition, the combination of WWI and BMI showed better performances in identifying individuals with DBMA or low TBS than WWI or BMI alone.
CONCLUSIONS: WWI established a negative association with TBS and a positive association with the risk of DBMA. Clinicians should be alert to the potential risk of DBMA among individuals with high WWI. Moreover, WWI, alone or in combination with BMI, has the potential to serve as an early screening strategy in identifying individuals with DBMA.

UNASSIGNED: The development of multiple system diseases is increased by obesity. However, the connection between obesity and developmental disabilities (DDs) in children is unclear. As an obesity index, the weight-adjusted waist index (WWI) assessed fat distribution and muscle mass. In this study, we examined the correlation between WWI and DDs among children 6 to 17 years of age.
UNASSIGNED: This study used data from the National Health and Nutrition Examination Survey database (NHANES) covering 2003 to 2018, which included the data of 17,899 participants between 6 and 17 years of age. Data regarding their waist circumference, weight, and DDs were collected via physical examinations and questionnaire, respectively. A person\'s WWI is calculated by dividing their waist circumference by their weight squared. The correlation between WWI and DDs was studied using weighted multiple logistic regression models. Additionally, a sensitivity analysis was conducted utilizing a generalized additive model and smooth curve fitting.
UNASSIGNED: After adjusting for all covariates, WWI was positively related to DDs in children ages 6-17. Based on the sensitivity analysis, the correlation between the WWI and prevalence of DDs remained consistent across subgroups. Additionally, there was a J-shaped correlation between the WWI and the prevalence of DDs in children ages 6 through 11.
UNASSIGNED: Children 6-17 years of age with a high WWI were at greater risk for DDs; however, the causal relationships and potential mechanisms require further exploration.

BACKGROUND: The association between obesity and depressive symptoms remains controversial. The Weight-adjusted waist index (WWI) shows advantages in assessing central obesity. This study aimed to investigate the longitudinal relationship between WWI and depressive symptoms.
METHODS: This prospective cohort study utilized data from the China Health and Retirement Longitudinal Study (CHARLS) spanning 2011-2020. Depressive symptoms were assessed using the 10-item Center for Epidemiological Studies Depressive Symptoms Scale (CESD-10) scores. Linear mixed models were used to examine longitudinal associations.
RESULTS: A total of 6835 participants over the age of 45 were included. WWI was positively associated with CESD-10 scores (β per 1 SD increase = 0.052SD; 95%CI: 0.021 to 0.083SD) and was linked to a faster increase in CESD-10 scores over time (β = 0.095SD/year; 95%CI: 0.090 to 0.100 SD/year). Conversely, BMI was negatively associated with CESD-10 scores (β per 1 SD increase = -0.067SD; 95%CI: -0.097 to -0.038SD). However, the negative association between BMI and CESD-10 scores weakened over time (β per 1 SD increase = 0.008SD/y; 95%CI: 0.003 to 0.013 SD/y). Nonlinear associations were detected between both WWI and BMI with CESD-10 scores.
CONCLUSIONS: Self-reported depressive symptoms assessments may have introduced information bias. The observational design limits ruling out unobserved confounding factors.
CONCLUSIONS: Our findings highlight the association between WWI and the long-term progression of depressive symptoms in middle-aged and older adults. WWI may enhance our understanding of the link between obesity and depressive symptoms and could be superior to BMI in predicting depressive symptom progression.

BACKGROUND: There is a close relationship between obesity and the occurrence of asthma.The weight-adjusted waist index (WWI) is a relatively novel anthropometric parameter that reflects obesity.
OBJECTIVE: We aimed to explore the association between WWI and mortality in the asthma population.
METHODS: We included adult with asthma from NHANES 1999-2018. WWI = Waist circumference (cm)/square root of body weight (kg). Current asthma was determined by the participant\'s responses in standardized questionnaires. All-cause, cardiovascular disease (CVD), cancer, and respiratory disease mortality information was obtained by prospectively matching these data to the National Death Index. Multivariate-adjusted Cox proportional hazards regression analyses, Kaplan Meier survival analyses, restricted cubic spline (RCS) analyses, stratified analyses, and sensitivity analyses were used to clarify these associations.
RESULTS: A total of 101,316 participants were included in the study, and 3223 were diagnosed with asthma.WWI was independently and positively associated with all-cause and all factor-specific mortality in asthma. In fully adjusted models, each unit increase in WWI was associated with 43 % (hazard ratio [HR] and 95 % confidence interval [CI] = 1.43 [1.25,1.64], p < 0.0001), 58 % (1.58 [1.25, 1.99], p < 0.001), 50 % (1.50 [1.19, 1.90], p < 0.001), and 79 % (1.79 [1.34, 2.39], p < 0.0001) increased all-cause, CVD, cancer, and respiratory disease mortality, respectively. RCS analyses showed largely linear associations between WWI and all mortality risks. Stratified analyses indicated that these associations were influenced by multiple factors, and that age was consistently the effect modifier across all associations.
CONCLUSIONS: WWI is an independent predictor of all-cause, CVD, cancer, and respiratory-related mortality in the adult asthma population. These findings highlight that WWI may have novel prognostic value as a simple and easily accessible obesity parameter in asthma patients.

BACKGROUND: Since cardiovascular disease (CVD) stands as the primary cause of death in those with diabetes, and given the substantial influence of obesity as a common risk factor for both diabetes and atherosclerotic conditions, this investigation sought to find the relationship between anthropometric indicators and CVD risk within these populations.
METHODS: Our study examined 36,329 adults, including those with diagnosed diabetes, pre-diabetes, and without diabetes from National Health and Nutrition Examination Survey (NHANES) data spanning 1999 to 2018. Various anthropometric indicators such as body mass index (BMI), waist circumference, weight-adjusted waist index (WWI), waist-to-height ratio (WHtR), weight, and height were assessed. Baseline characteristics were compared among the three groups after weighting. Participants were then grouped based on anthropometric indicators, and logistic regression models were used to analyze the association between these indicators and CVD risk in the total diabetes group (including diabetic and pre-diabetic individuals). Threshold effect analysis was conducted to explore nonlinear relationships, and mediation analyses assessed whether serum parameters influenced these relationships.
RESULTS: This cross-sectional study involved 36,329 participants, weighted to a count of approximately 160.9 million, including over 45.9 million pre-diabetic individuals and around 16.6 million diabetic individuals. Baseline analysis showed significant associations between all six anthropometric indicators and CVD risk across patients with different diabetes statuses. Weighted restricted cubic spline (RCS) curve analysis highlighted increased CVD risk among the total diabetes group for each anthropometric indicator compared to the non-diabetic group. Anthropometric indicators were then divided into quartiles, and after adjusting for confounders, Model 3 revealed that the highest BMI group had a heightened risk of CVD compared to the lowest BMI group. Similar trends were observed in the WWI and WHtR subgroups. Threshold effect analysis of anthropometric indicators unveiled nonlinear associations between waist circumference, height, WWI and CVD risk. Mediation analysis suggested that lipid parameters, especially HDL, significantly mediated these relationships.
CONCLUSIONS: In individuals with diabetes and pre-diabetes, BMI, weight, and WHtR displayed a consistent, linear increase correlation with CVD risk. Conversely, the link between waist circumference, height, and WWI and CVD risk showcased a more complex, nonlinear pattern. Moreover, HDL level emerged as notable mediator in the association between anthropometric indicators and the risk of CVD.