Dataset Information

Novel anthropometric indices are superior adiposity indexes to portend visual impairment in middle-aged and older Chinese population.

ABSTRACT:

Objective

To investigate differential associations of traditional and novel adiposity indices with visual impairment (VI) in the middle-aged and older Chinese population.

Methods and analysis

Based on the China Health and Retirement Longitudinal Study, 7750 Chinese older adults aged over 45 were included at baseline 2011, and 4133 participants who accomplished all three interviews from 2011 to 2015 were adapted for longitudinal analyses. We enrolled six adiposity indices, including the body mass index (BMI), waist-to-height ratio (WHtR), weight-adjusted-waist index (WWI), a body shape index (ABSI), body roundness index (BRI) and conicity index (ConI). Visual status and other covariates included sociodemographic characteristics, medical supports and lifestyle-related factors. Cross-sectional correlations were assessed using univariate and multivariate logistic regression analyses. For longitudinal analysis, generalised linear models with generalised estimating equations were used to determine the association between time-varying adiposity and visual status.

Results

Higher levels of WHtR/WWI/ABSI/BRI/ConI were significantly associated with an increased prevalence of VI, whereas a higher BMI was associated with a decreased prevalence of VI. Only WWI was significantly related to the prevalence of VI after adjustment for multiple confounders in both cross-sectional and longitudinal analyses (all p values <0.05). The multivariable-adjusted OR (95% CI) of VI associated with the highest (vs lowest) quintile of WWI was 1.900 (1.407 to 2.565).

Conclusion

WWI is a reliable alternative adiposity index that exhibits a dose-response association with the prevalence of VI in the Chinese population. The WWI-VI correlation may eliminate the obesity paradox in the ophthalmic epidemiological area and indicate the detrimental impact of changes in body composition on VI.

SUBMITTER: Zhou Y

PROVIDER: S-EPMC11253769 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature

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Publications

Novel anthropometric indices are superior adiposity indexes to portend visual impairment in middle-aged and older Chinese population.

Zhou Yifan Y Chen Qing Q Abuduxukuer KaiweiSa K Wang Chuchu C Dong Jialong J Wang Yiting Y Shi Wenming W Hou Yanan Y Shi Fei F Luo Jianfeng J Peng Qing Q

BMJ open ophthalmology 20240715 1

<h4>Objective</h4>To investigate differential associations of traditional and novel adiposity indices with visual impairment (VI) in the middle-aged and older Chinese population.<h4>Methods and analysis</h4>Based on the China Health and Retirement Longitudinal Study, 7750 Chinese older adults aged over 45 were included at baseline 2011, and 4133 participants who accomplished all three interviews from 2011 to 2015 were adapted for longitudinal analyses. We enrolled six adiposity indices, includin ...[more]

PMID: 39009464

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Project description:Background Previous studies have explored the relationship between body mass index (BMI) and multimorbidity. However, the relationship between other obesity indicators and their dynamic changes and multimorbidity has not been systematically estimated. Therefore, we aimed to investigate the association of BMI and other obesity indicators, including waist circumference (WC), waist-to-height ratio (WHtR), waist divided by height0.5 (WHT.5R), and body roundness index (BRI) and their changes and the risk of multimorbidity in middle-aged and older adults through a retrospective cohort study. Methods Data collected from annual health examination dataset in the Jinshui during 2017 and 2021. Cox regression models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) to evaluate the effect of baseline and dynamic changes in the anthropometric indices on the risk of multimorbidity. Results A total of 75,028 individuals were included in the study, and 5,886 participants developed multimorbidity during the follow-up. Multivariate Cox regression analysis revealed a progressive increase in the risk of multimorbidity with increasing anthropometric indicators (BMI, WC, WHtR, WHT.5R, and BRI) (all P<0.001). Regardless of general obesity status at baseline, increased WC was associated with a high risk of multimorbidity. Compared to the subjects with baseline BMI<24 kg/m2 and WC<90 (men)/80 (women), the HRs (95% CI) of the baseline BMI<24 kg/m2 and WC≥90 (men)/80 (women) group and BMI≥24 kg/m2 and WC≥90 (men)/80 (women) group were 1.31 (1.08, 1.61) and 1.82 (1.68, 1.97), respectively. In addition, the dynamics of WC could reflect the risk of multimorbidity. When subjects with baseline WC<90 (men)/80 (women) progressed to WC≥90 (men)/80 (women) during follow-up, the risk of multimorbidity significantly increased (HR = 1.78; 95% CI, 1.64, 1.95), while the risk of multimorbidity tended to decrease when people with abnormal WC at baseline reversed to normal at follow-up (HR = 1.40; 95% CI, 1.26, 1.54) compared to those who still exhibited abnormal WC at follow-up (HR = 2.00; 95% CI, 1.82, 2.18). Conclusions Central obesity is an independent and alterable risk factor for the occurrence of multimorbidity in middle-aged and elderly populations. In addition to the clinical measurement of BMI, the measurement of the central obesity index WC may provide additional benefits for the identification of multimorbidity in the Chinese middle-aged and elderly populations.

Project description:BackgroundVisual impairment (VI) is a prevalent global health issue, affecting over 2.2 billion people worldwide, with nearly half of the Chinese population aged 60 years and older being affected. Early detection of high-risk VI is essential for preventing irreversible vision loss among Chinese middle-aged and older adults. While machine learning (ML) algorithms exhibit significant predictive advantages, their application in predicting VI risk among the general middle-aged and older adult population in China remains limited.ObjectiveThis study aimed to predict VI and identify its determinants using ML algorithms.MethodsWe used 19,047 participants from 4 waves of the China Health and Retirement Longitudinal Study (CHARLS) that were conducted between 2011 and 2018. To envisage the prevalence of VI, we generated a geographical distribution map. Additionally, we constructed a model using indicators of a self-reported questionnaire, a physical examination, and blood biomarkers as predictors. Multiple ML algorithms, including gradient boosting machine, distributed random forest, the generalized linear model, deep learning, and stacked ensemble, were used for prediction. We plotted receiver operating characteristic and calibration curves to assess the predictive performance. Variable importance analysis was used to identify key predictors.ResultsAmong all participants, 33.9% (6449/19,047) had VI. Qinghai, Chongqing, Anhui, and Sichuan showed the highest VI rates, while Beijing and Xinjiang had the lowest. The generalized linear model, gradient boosting machine, and stacked ensemble achieved acceptable area under curve values of 0.706, 0.710, and 0.715, respectively, with the stacked ensemble performing best. Key predictors included hearing impairment, self-expectation of health status, pain, age, hand grip strength, depression, night sleep duration, high-density lipoprotein cholesterol, and arthritis or rheumatism.ConclusionsNearly one-third of middle-aged and older adults in China had VI. The prevalence of VI shows regional variations, but there are no distinct east-west or north-south distribution differences. ML algorithms demonstrate accurate predictive capabilities for VI. The combination of prediction models and variable importance analysis provides valuable insights for the early identification and intervention of VI among Chinese middle-aged and older adults.

Dataset Information

Novel anthropometric indices are superior adiposity indexes to portend visual impairment in middle-aged and older Chinese population.

Objective

Methods and analysis

Results

Conclusion

Publications

Novel anthropometric indices are superior adiposity indexes to portend visual impairment in middle-aged and older Chinese population.

Similar Datasets

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