Association of anthropometric indices with the development of multimorbidity in middle-aged and older adults: A retrospective cohort study

Body mass index and multimorbidity risk: A systematic review and dose-response meta-analysis

OBJECTIVE

To verify the dose-response relationship between body mass index (BMI) and multimorbidity risk.

METHODS

PubMed, CINAHL, and Embase were systematically studied until January 25, 2023. Original articles on BMI and multimorbidity risk were included. Random effects model and dose-response meta-analysis were used to estimate the pooled odds ratio (OR) with 95 % confidence interval (CI). Subgroup analysis was performed to explore potential heterogeneity.

RESULTS

A total of 43 studies involving 969,130 patients (94,978 with multimorbidity) were involved in the meta-analysis. In the longitudinal studies, the pooled results showed that, compared to being a normal BMI, being overweight was much similar with 1.32 times possibility of getting multimorbidity; in persons with obesity the risk was 1.93 times higher; and the risk decreased 0.80 times among underweight persons. Additionally, obesity was 1.75 times as likely to be multimorbidity than those non-obese persons. In the cross-sectional studies, the pooled results demonstrated that persons with overweight and obesity had a 1.38-fold and 2.38-fold risk for multimorbidity, respectively; and the risk decreased 0.90 times among underweight persons compared to those with normal BMI. Besides, obese people are 1.89 times more likely to have multimorbidity than non-obese people. Dose response analysis found the linear connection between BMI and multimorbidity risk (Pnon-linearity=0.762), that for each 1 kg/m2 and 5 kg/m2 increase in BMI, the multimorbidity risk increased by 6 % and 35 %, respectively.

CONCLUSIONS

Multimorbidity increased linearly with an increase in BMI. Clinicians should pay attention to persons with abnormal weight, to help them achieve normal BMI.

Adiposity indicators exhibit depot- and sex-specific associations with multimorbidity onset: A cohort study of the UK Biobank

AIM

This study investigated the depot- and sex-specific associations of adiposity indicators with incident multimorbidity and comorbidity pairs.

MATERIALS AND METHODS

We selected 382 678 adults without multimorbidity (≥2 chronic diseases) at baseline from the UK Biobank. General obesity, abdominal obesity and body fat percentage indices were measured.

RESULTS

Cox proportional hazard regression analyses of general obesity indices revealed that for every one-unit increase in body mass index, the risk of incident multimorbidity increased by 5.2% (95% confidence interval 5.0%-5.4%). A dose-response relationship was observed between general obesity degrees and incident multimorbidity. The analysis of abdominal obesity indices showed that for every 0.1 increment in waist-to-height ratio and waist-to-hip ratio, the risk of incident multimorbidity increased by 42.0% (37.9%-46.2%) and 27.9% (25.7%-30.0%), respectively. Central obesity, as defined by waist circumference, contributed to a 23.2% increased risk of incident multimorbidity. Hip circumference and hip-to-height ratio had protective effects on multimorbidity onset. Consistent findings were observed for males and females. Body fat percentage elevated 3% (0.2%-5.9%) and 5.3% (1.1%-9.7%) risks of incident multimorbidity in all adults and females, respectively. Arm fat percentages elevated 5.3% (0.8%-9.9%) and 19.4% (11.0%-28.5%) risks of incident multimorbidity in all adults and males, respectively. The general obesity indices, waist circumference, waist-to-height ratio, waist-to-hip ratio and central obesity increased the onset of comorbidity pairs, whereas hip circumference and hip-to-height ratio decreased the onset of comorbidity pairs. These adiposity indicators mainly affect diabetes mellitus-related comorbidity onset in males and hypertensive-related comorbidity onset in females.

CONCLUSIONS

Adiposity indicators are predictors of multimorbidity and comorbidity pairs and represent a promising approach for intervention.

Assessing the modifiable and non-modifiable risk factors associated with multimorbidity in reproductive aged women in India

BACKGROUND

Reproductive span is the foundation of every woman's health in later life. India is currently facing a growing burden of multiple morbidities among the women in their reproductive age group which may further increase over the coming decades. The purpose of the present study aimed to identify different modifiable and non-modifiable risk factors affecting multimorbidity among the women in reproductive age group in Indian context.

METHODS

Secondary data were obtained from the Demography and Health Survey (DHS), conducted in India during 2019-2021. A total of 671,967 women aged 15-49 years were selected for this present study. Descriptive, association studies and multinominal logistic regression analyses were performed to accomplish the objectives.

RESULTS

Currently, 6.3% of total study participant's reproductive age group women suffered from multimorbidity in India. Never consuming protein, fruits, vegetables and milk increase the chances of developing multimorbidity. Consumption of fried foods, aerated drinks and addiction towards tobacco and alcohol also has a greater influence on the prevalence of multimorbidity. The prevalence of multimorbidity is sharply increased with increasing age and Body Mass Index (BMI). Regionally, the prevalence of multimorbidity was found more among the women hailed from eastern and north-eastern India.

CONCLUSION

To reduce the risk of developing multimorbidity, targeted interventions are needed in the form of educating every woman concerning the importance of having minimum health-related knowledge, maintaining healthy lifestyle, weight management and having proper and balanced diet.

Association of changes in waist circumference, waist-to-height ratio and weight-adjusted-waist index with multimorbidity among older Chinese adults: results from the Chinese longitudinal healthy longevity survey (CLHLS)

BACKGROUND

The association of changes in waist circumference (WC), waist-to-height ratio (WHtR) and weight-adjusted-waist index (WWI) with subsequent risk of multimorbidity remains unclear among older Chinese adults. Therefore, we aimed to assess this association by utilizing data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS).

METHODS

Our study was based on the 2011/2012 wave of the CLHLS whose follow-up surveys were conducted in 2014 and 2017/2018. A total of 2900 participants aged 65 and above at baseline were enrolled. WC, WHtR, and WWI were calculated from measured height, weight, and waist circumference. Multimorbidity refers to the coexistence of two or more of 18 chronic diseases. Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (95%CIs) to evaluate the effect of three-year changes in WC, WHtR, and WWI on the risk of multimorbidity.

RESULTS

During a mean follow-up time of 4.2 (2.0) years, 906 multimorbidity cases were identified. Compared to participants in the persistently low WC group, those in the WC gain group and the persistently high WC group had a higher multimorbidity risk with adjusted HRs (95%CI) of 1.23 (1.01-1.50) and 1.34(1.14-1.58), respectively. Participants in the WHtR gain group and the persistently high WHtR group also had higher risks of multimorbidity with HRs (95%CI) of 1.35 (1.08-1.67) and 1.27 (1.05-1.53), respectively, relative to the persistently low WHtR group. Compared to the persistently low WWI group, those in the WWI loss group had a lower risk of multimorbidity with HRs (95%CI) of 0.80 (0.66-0.98). For every standard deviation increase in WC, WHtR, and WWI over three years, the risk of multimorbidity was higher by 12% (95%CI: 1.05-1.19), 13% (95%CI: 1.06-1.20), and 12% (95%CI: 1.05-1.20), respectively.

CONCLUSIONS

Associations of changes in WC, WHtR and WWI with multimorbidity are significant among older Chinese adults. The findings highlight the importance of evaluating changes in WC, WHtR, and WWI in screening and prevention of multimorbidity in older adults.

Waist-to-Height Ratio: A Sensitive Tool for Assessing the Need for Nutritional Risk Management in Elderly Populations from Brazil

INTRODUCTION

Nutritional status assessment commonly relies on body mass index (BMI), which overlooks lean mass and adipose tissue distribution. However, waist circumference (WC) and waist-to-height ratio (WHtR) provide additional insights into fat accumulation. By combining these indices, it may be possible to identify older adults needing weight management interventions.

OBJECTIVES

To assess the WC and WHtR as strategies for identifying individuals requiring weight management.

METHODS

A cross-sectional study was conducted with 509 elderly individuals in Northeast Brazil. Weight, height, hip circumference, and waist circumference were measured, and combined with indices such as BMI WC, WHR, and WHtR to identify those who require weight management. The DeLong test compared areas under the curves using receiver operating characteristic curves and statistical significance. Sensitivity, specificity, and positive and negative predictive values were calculated to verify usefulness for clinical application. A validation sample of 599 elderly individuals from the country's Southern region was used to confirm the results.

RESULTS

Both WC and WHtR showed adequate diagnostic accuracy with no statistically significant difference in AUCs. WHtR ≥ 0.50 had 92% sensitivity in identifying men and women requiring nutritional management. WC presented lower sensitivity but 93% specificity, useful for excluding elderly individuals from the nutritional risk category. These results were consistent in the validation sample.

CONCLUSION

WHtR is a valuable index for screening nutritional risk management in the elderly population, applicable to men and women. Conversely, WC performs better in excluding individuals who do not need nutritional risk management.