Association between obesity-related anthropometric indices and multimorbidity among older adults in Shandong, China: a cross-sectional study

Interaction between depressive symptoms and obesity-related anthropometric measures on multimorbidity among community-dwelling older adults: evidence from India

BACKGROUND

This study aimed to examine the associations between depressive symptoms, body mass index (BMI), waist circumference, waist-hip ratio and multimorbidity among community-dwelling older adults. We also examine the interaction effects between depressive symptoms, BMI, waist circumference and waist-hip ratio on multimorbidity among older adults in India.

METHODS

A cross-sectional study was conducted, and the data were obtained from the Longitudinal Ageing Study in India (LASI) wave-1, with a sample of 31,464 older adults aged 60 years and above (men-15,098 and women-16,366). We used multinomial logistic regression to explore the independent associations between depressive symptoms, obesity-measures, and single and multimorbidity. We also estimated the interaction effects of depressive symptoms and obesity-measures on multimorbidity.

RESULTS

The prevalence of multimorbidity was higher among individuals with depressive symptoms (39.22%) than individuals with no depressive symptoms (29.94%). Adjusted models indicated that older adults with depressive symptoms had higher odds of single and multimorbidity [(AOR = 1.40, 95% CI: 1.17-1.68) and (AOR = 1.85, 95% CI: 1.58-2.16), respectively]. Similarly, in comparison to the normal BMI category, overweight and obese older adults were more likely to report single morbidity [(AOR = 1.62, 95% CI: 1.37-1.92 and (AOR = 2.14, 95% CI: 1.67-2.75), respectively] and multimorbidity [(AOR = 2.00, 95% CI: 1.72-2.33) and (AOR = 3.77, 95% CI: 2.94-4.82), respectively].

CONCLUSION

The findings revealed that the presence of depressive symptoms, overweight or obesity, and high-risk anthropometric measures such as high-risk waist circumference and high-risk waist to hip ratio significantly increased the risk of morbidity among older adults in India. Thus, it is suggested to adopt an integrated public health policy approach to control depressive symptoms and high-risk body composition to strategically prepare against the elevated risk of multimorbidity among ageing populations.

Differences in quality of life and fitness level among men and women in the adulthood: a cross-sectional analysis

BACKGROUND

This study aimed to examine the associations between physical fitness components and health-related quality of life (HRQoL) among adults stratified by sex and age. In addition, we aimed to examine whether these associations change based on socioeconomic, clinical, and biochemical characteristics.

METHODS

A total of 297 participants aged 47.41 (standard deviation: 9.08) years from the "Validity of a Model of Accelerated Vascular Aging as a Cardiovascular Risk Index in Healthy Adults: the EVasCu cross-sectional study" were included in this analysis. HRQoL, physical fitness, socioeconomic status (SES), waist circumference, and blood pressure were measured. Additionally, blood samples were extracted to determine cholesterol, triglyceride, and glycated hemoglobin A1c (HbA1c) levels. Analyses of covariance (ANCOVAs) were estimated to test mean differences in physical and mental health-related health measures (HRQoL) between fitness categories (fixed factors) by sex and age categories.

RESULTS

The physical HRQoL was related to the levels of fitness parameters among women, independent of age, while for men, it was related to better levels of general fitness and cardiorespiratory fitness among men aged < 50 and men aged ≥ 50, respectively. In contrast, mental HRQoL was related to cardiorespiratory fitness only among women aged < 50 years; speed/agility and flexibility among men aged < 50 years; and general fitness, strength, and flexibility among men aged ≥ 50 years. These data did not change when SES, clinical variables, or biochemical determinations were included in the analyses, neither for the physical nor for the mental HRQoL.

CONCLUSION

Gender and age are important factors to be considered when analysing health indicators and influences in the population. In addition, SES, clinical characteristics, and biochemical parameters do not seem to influence the relationship between HRQoL and fitness.

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.

Incidence, prevalence and characteristics of multimorbidity in different age groups among urban hospitalized patients in China

The aim of the study was to investigate the incidence, prevalence and characteristics of multimorbidity in urban inpatients of different age groups. This study used data from the National Insurance Claim for Epidemiology Research (NICER) to calculate the overall incidence, prevalence, geographic and age distribution patterns, health care burden, and multimorbidity patterns for multimorbidity in 2017. According to our study, the overall prevalence of multimorbidity was 6.68%, and the overall prevalence was 14.87% in 2017. The prevalence of multimorbidity increases with age. The pattern of the geographic distribution of multimorbidity shows that the prevalence of multimorbidity is relatively high in South East China. The average annual health care expenditure of patients with multimorbidity increased with age and rose rapidly, especially among older patients. Patients with cancer and chronic kidney disease have higher treatment costs. Patients with hypertension or ischemic heart disease had a significantly higher relative risk of multimorbidity than other included noncommunicable diseases (NCDs). Hyperlipidemia has generated the highest number of association rules, which may suggest that hyperlipidemia may be both a risk factor for other NCDs and an outcome of them.

Multimorbidity and complex multimorbidity in Brazilians with severe obesity

To investigate the prevalence of multimorbidity and complex multimorbidity and their association with sociodemographic and health variables in individuals with severe obesity. This is a baseline data analysis of 150 individuals with severe obesity (body mass index ≥ 35.0 kg/m2) aged 18-65 years. The outcomes were multimorbidity and complex multimorbidity. Sociodemographic, lifestyle, anthropometric and self-perceived health data were collected. Poisson multiple regression was conducted to identify multimorbidity risk factors. The frequency of two or more morbidities was 90.7%, three or more morbidities was 76.7%, and complex multimorbidity was 72.0%. Living with four or more household residents was associated with ≥ 3 morbidities and complex multimorbidity. Fair and very poor self-perceived health was associated with ≥ 2 morbidities, ≥ 3 morbidities and complex multimorbidity. A higher BMI range (45.0-65.0 kg/m2) was associated with ≥ 2 morbidities and ≥ 3 morbidities. Anxiety (82.7%), varicose veins of lower limbs (58.7%), hypertension (56.0%) were the most frequent morbidities, as well as the pairs and triads including them. The prevalence of multimorbidity and complex multimorbidity in individuals with severe obesity was higher and the risk for multimorbidity and complex multimorbidity increased in individuals living in households of four or more residents, with fair or poor/very poor self-perceived health and with a higher BMI.

Is there a ubiquitous association between sleep disorder and frailty? findings from LASI (2017-18)

BACKGROUND

Relatively little is known about how sleep disorders affect frailty of seniors. The study uses Fried's frailty index, to investigate the relationship between sleep disorder and frailty among older Indian adults.

METHODS

The study analysed Longitudinal Ageing Study in India (2017-18) data which uses a multistage stratified area probability cluster sampling design. The association between frailty was studied for which the total sample size was 31,902. The principal dependent variable was frailty. Descriptive statistics and cross-tabulation were presented in the study. A binary logistic regression analysis was used to fulfil the study objectives to find the possible association.

RESULTS

The prevalence of frailty in India was 21.3 percent. Older adults with sleep disorder had 66 percent higher likelihood to be frail than their counterparts. The benefits of physical activity in containing frailty is huge, the association were quite high. Poor Self-rated health was significantly associated with higher frailty (OR = 1.73; CI = 1.47-2.04).

CONCLUSIONS

Frailty is an enormously growing public health issue and has bi-directional relation with sleep disorders. The study has clinical relevance since sleep complaints offer a means for identifying those who are vulnerable to frailty and through appropriate intervention, the causes of sleep disorder would help to delay and in some cases reverse frailty.

The Multimorbidity and Lifestyle Correlates in Chinese Population Residing in Macau: Findings from a Community-Based Needs Assessment Study

Multimorbidity has become one of the most pressing public health concerns worldwide. The objectives of this study were to understand the prevalence of multimorbidity and its relationship with lifestyle factors among Chinese adults in Macau, and to investigate the combined contribution of common lifestyle factors in predicting multimorbidity. Data were collected through face-to-face interviews using a self-reported questionnaire on common chronic diseases, lifestyle factors and sociodemographics. BMI, physical activity, drinking status, smoking status and sleep quality were assessed, and a composite lifestyle score (0 to 9 points) was calculated, and the higher the score, the healthier the lifestyle. A total of 1443 participants were included in the analysis, of whom 55.2% were female, 51.8% were middle aged or elderly and 30.5% completed tertiary education or higher. The prevalence of multimorbidity was 10.3%. The combination of hypertension and hyperlipidaemia was the most common (22.2%) multimorbidity among the participants with multimorbidity. After the adjustment of the covariates, it was found that the participants who were overweight (OR: 1.95, 95% CI: 1.18-3.20, p = 0.009) or obese (OR: 3.76, 95% CI: 2.38-5.96, p < 0.001), former drinkers (OR: 2.43, 95% CI: 1.26-4.69, p = 0.008), and those who reported poor sleep quality (OR: 2.25, 95% CI: 1.49-3.40, p < 0.001) had a high risk of developing multimorbidity. A one-unit increase in the lifestyle score was associated with a 0.33-times reduction in the risk of developing multimorbidity (OR: 0.67; 95% CI: 0.59-0.77, p < 0.001). A combination of lifestyle factors can influence a variety of multimorbidity among the Chinese adults in Macau. Thus, comprehensively assessing the combined contribution of several lifestyle factors in predicting multimorbidity is important.

The prevalence and determinant of overweight and obesity among residents aged 40-69 years in high-risk regions for upper gastrointestinal cancer in southeast China

Being overweight or obese is one of the public health concerns worldwide, and its prevalence is gradually increasing. Obesity has been proven to be associated with some cancers, including upper gastrointestinal cancer (UGC). However, studies on the prevalence of obesity among residents of areas at high risk of UGC in China are minimal. The aim of this study is to assess the prevalence of obesity and its influencing factors among people aged 40-69 years (high-risk population) in high-risk areas for UGC in Jiangsu Province, southeast China. This cross-sectional study involved 45,036 subjects aged 40-69 years identified in the Rural Early Diagnosis and Treatment of UGC Project database in Jiangsu Province from 2017 to 2021. Differences in prevalence across gender and age were assessed using the Chi-square test. Using a multinomial logistic regression model, we examined independent risk factors for overweight/obesity and their gender and age differences. The prevalence of overweight, obesity, and overweight/obesity varied based on the standards used: Chinese standard (42.1%, 11.9%, and 54.0%) and WHO standard (34.7%, 4.7%, and 39.4%), respectively. Being overweight was more common in men than women, while obesity was more common in women than men. Age of 50-59 years, married, household size of 7-9, drinking, soy products, pickled food, and hot food intake were positively associated with overweight/obesity. Females, 60-69 years, higher education level, household size of 4-6, annual family income of more than 60,000 CNY, smoking, and fresh fruit intake were negatively associated with overweight/obesity. Stratified analysis showed that the effects of age, education and meat, egg and dairy products on overweight/obesity were different across gender. The impact of fresh fruit and vegetables on overweight/obesity was also heterogeneous between the younger (40-59 years) and older (60-69 years) groups. In conclusion, the prevalence of overweight and obesity is high among adults aged 40-69 years from high-risk areas for UGC of Jiangsu Province, southeast China. Independent influencing factors of being overweight/obese included gender, age, marital status, education, household size, annual family income, smoking, drinking, fresh fruit, soy products, pickled food and hot food intake, and may vary by gender and age. Screening-based interventions should be considered to control obesity levels among screened participants. Besides, heterogeneity of influencing factors across subgroups could be focused on to improve intervention effectiveness.

Cross-sectional associations between body mass index, waist circumference, and multimorbidity: Pró-Saúde study

Background

This study aimed (1) To investigate the association between the Body Mass Index (BMI) and waist circumference (WC) with multimorbidity (MM), and (2) To identify patterns of MM and investigate the relationship between BMI and WC with specific combinations of MM (patterns of MM).

Methods

A cross-sectional study was conducted with 2,698 participants of the fourth phase of the Brazilian Longitudinal Study of Adult Health (Pró-Saúde Study). MM was defined by the presence of two or more morbidities. MM patterns were identified by exploratory factor analysis based on tetrachoric correlations. Logistic regression models were used to assess associations (odds ratios (OR) with the respective confidence intervals (CI)).

Results

Of the total number of participants, 39.5% were overweight and 30.0% were obese; 89.0% (n = 1,468) of women and 77.0% (n = 952) of men were abdominally obese. Indeed, 60.7% (n = 1,635) was identified with MM. For the category four or more morbidities, OR values of 5.98 (95% CI 4.84-7.13) and 7.48 (95% CI 6.14-8.18) were found for each point of increase in BMI, and 6.74 (95% CI 5.48-7.99) and 8.48 (95% CI 7.64-9.29) for each additional centimeter in the WC, for female and male, respectively. Five patterns of MM were identified: respiratory, osteoarticular, cardiometabolic, gastric, and thyroid diseases (56.4% of the total variance). Positive associations were found between BMI and patterns of cardiometabolic, osteoarticular, thyroid and gastric diseases (higher OR of 1.09 [95% CI 1.04-1.14]) and less pronounced between WC and patterns of cardiometabolic and osteoarticular (higher OR of 1.04 [95% CI 1.03-1.04]).

Conclusions

The results showed that an increase of both BMI and WC was associated with a higher number of morbidities and with patterns of cardiometabolic and osteoarticular diseases.

Multivariate decomposition of gender differentials in successful aging among older adults in India

BACKGROUND

Rowe and Kahn define successful aging as a high physical, psychological, and social functioning in old age without major diseases. It is considered a viable solution to the burdens placed on healthcare systems and financial and social security in societies with aging population. The present study aimed to determine the prevalence of successful aging and explore the factors contributing to gender differentials in successful aging among older adults in India.

METHODS

This study utilized data from the nationally representative Longitudinal Ageing Study in India, conducted in 2017-18. The study is based on a sample of 15,098 older men and 16,366 older women aged 60 years and above. The outcome variable was a dichotomous measure of successful aging with six components including absence of chronic diseases, free from disability, high cognitive ability, free from depressive symptoms, active social engagement in life and free from obesity. Older adults satisfying all these conditions were considered aging successfully. Descriptive and bivariate analyses were carried out. Proportion test was used to evaluate the gender differentials and reflect the statistical significance in the associated factors. Multivariate decomposition analysis was conducted to identify covariates' contribution in explaining the gender differences in successful aging.

RESULTS

There was a significant gender difference in successful aging among older adults in India (Difference: 8.7%; p-value < 0.001] with 34.3% older men and 25.6% older women experiencing successful aging. A proportion of 88% of gender difference in successful aging was explained by the differences in the distribution of characteristics (Coef: 0.082; p-value < 0.05). Considerable gender gap in successful aging would be reduced if women had similar levels of work status (28% reduction) to their male counterparts. Bringing the level of frequent physical activity in women to the same levels observed in men would reduce the gender gap by 9%.

CONCLUSIONS

The findings suggest that women had a lower score in successful aging, which is attributed to several socioeconomic and behavioural factors including not working status and physical inactivity. More studies must be done to explore the reasons for such differences and what particular factors in low-income countries create differences among older men and women in achieving successful aging.

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

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.

The relationship between anthropometric indicators and health-related quality of life in a community-based adult population: A cross-sectional study in Southern China

Background

This study was designed to analyze the relationship of waist circumference (WC), body mass index (BMI), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), relative fat mass (RFM), lipid accumulation product (LAP) and health-related quality of life (HRQoL) in the community-dwelling population of southern China and to explore the independent contribution of socio-demographic characteristics, number of chronic diseases and anthropometric indicators to HRQoL in that population.

Methods

This community-based cross-sectional survey studied 2,663 adults aged 18 years and older. HRQoL was assessed by the 3-level EuroQol 5-dimensional scale (EQ-5D-3L), and HRQoL were calculated using the Chinese EQ-5D-3L value set. The outcome variable was the EQ-5D-3L score (HRQoL). Cluster regression was used to analyse the independent contribution of each obesity indicator to HRQoL.

Results

A total of 2,663 people participated in this study, and their mean EQ-5D-3L score was 0.938 ± 0.072. In this study, according to the results of the one-way ANOVA, HRQoL was significantly different between the groups of WHtR, WHR, RFM and LAP, respectively. The independent contributions of socio-demographic factors, number of chronic diseases and anthropometric measures to HRQoL in the whole population accounted for 76.2, 7.9, and 15.9% of the total effect, respectively.

Conclusion

RFM and LAP were found to have a previously unreported negative impact on HRQoL in a community-dwelling population. In future studies, RFM and LAP could be used as new indicators of obesity to predict quality of life in humans.

BMI mediates the association of family medical history with self-reported hypertension and diabetes among older adults: Evidence from baseline wave of the longitudinal aging study in India

Background

This study explored the association between family history of hypertension and diabetes with their diagnosis among older Indian adults. The study further examined the role of body mass index (BMI) as a potential mediator in these associations.

Methods

Data from the Longitudinal Ageing Study in India (LASI, 2017-18), wave-1 were used. The sample for the study included 31,464 older adults aged 60 years and above. Descriptive statistics and bivariate analysis has been conducted to assess the prevalence of self-reported hypertension and diabetes. Further, multivariable logistic regression models were used to test the research hypotheses of this study. The Karlson-Holm-Breen (KHB) mediation analysis was conducted to recover the direct and indirect effects of BMI in the association of family medical history and diagnosis of hypertension and diabetes.

Results

A proportion of 32.70% of older adults were diagnosed with hypertension and 14.23% of older adults were diagnosed with diabetes. A proportion of 19.48% and 14.69% of older adults had a family history of hypertension and diabetes, respectively. Also, 16.57% and 5.53% of older adults were overweight and obese, respectively in the current study. Older adults who had family history of hypertension had higher odds of being diagnosed with hypertension [aOR: 2.23, CI: 2.07-2.39] than those who had no such family history. This association was mediated by BMI (percent mediated: 6.31%). Similarly, older adults who had family history of diabetes had higher odds of being diagnosed with diabetes [aOR: 2.63, CI: 2.41-2.88] than those who had no such family history. This association was mediated by BMI (percent effect mediated: 6.66%).

Conclusion

The study highlights the relevance of using family medical history data along with information on BMI as potential source for the control and management of hypertension and diabetes among older population.

Examining sex disparity in the association of waist circumference, waist-hip ratio and BMI with hypertension among older adults in India

Hypertension is a public health issue touted as a “silent killer” worldwide. The present study aimed to explore the sex differential in the association of anthropometric measures including body mass index, waist circumference, and waist-hip ratio with hypertension among older adults in India. The study used data from the Longitudinal Aging Study in India (LASI) conducted during 2017–18. The sample contains 15,098 males and 16,366 females aged 60 years and above. Descriptive statistics (percentages) along with bivariate analysis were presented. Multivariable binary logistic regression analyses were used to examine the associations between the outcome variable (hypertension) and putative risk or protective factors. About 33.9% of males and 38.2% of females aged 60 years and above suffered from hypertension. After adjusting for the socioeconomic, demographic and health-behavioral factors, the odds of hypertension were 1.37 times (CI: 1.27–1.47), significantly higher among older adults who were obese or overweight than those with no overweight/obese condition. Older adults with high-risk waist circumference and waist-hip ratio had 1.16 times (CI: 1.08–1.25) and 1.42 times (CI: 1.32–1.51) higher odds of suffering from hypertension, respectively compared to their counterparts with no high-risk waist circumference or waist-hip ratio. The interaction effects showed that older females with overweight/obesity [OR: 0.84; CI: 0.61–0.74], high-risk waist circumference [OR: 0.89; CI: 0.78–0.99], and high-risk waist-hip ratio [OR: 0.90; CI: 0.83–0.97] had a lower chance of suffering from hypertension than their male counterparts with the similar anthropometric status. The findings suggested a larger magnitude of the association between obesity, high-risk waist circumference, high-risk waist-hip ratio and prevalent hypertension among older males than females. The study also highlights the importance of measuring obesity and central adiposity in older individuals and using such measures as screening tools for timely identification of hypertension.

Multivariate decomposition analysis of sex differences in functional difficulty among older adults based on Longitudinal Ageing Study in India, 2017-2018

OBJECTIVES

This study investigates the gender disparities in difficulty in activities of daily living (ADL) and instrumental activities of daily living (IADL) and explores its contributing factors among older adults in India.

DESIGN

A cross-sectional study was conducted using country representative survey data.

SETTING AND PARTICIPANTS

The present study uses the data from the Longitudinal Ageing Study in India, 2017-2018. Participants included 15 098 male and 16 366 female older adults aged 60 years and above in India.

PRIMARY AND SECONDARY OUTCOME MEASURES

Difficulty in ADL and IADL were the outcome variables. Descriptive statistics and bivariate analysis were carried out to present the preliminary results. Multivariate decomposition analysis was used to identify the contributions of covariates that explain the group differences to average predictions.

RESULTS

There was a significant gender differential in difficulty in ADL (difference: 4.6%; p value<0.001) and IADL (difference: 17.3%; p value<0.001). The multivariate analysis also shows significant gender inequality in difficulty in ADL (coefficient: 0.046; p value<0.001) and IADL (coefficient: 0.051; p value<0.001). The majority of the gender gap in difficulty in ADL was accounted by the male-female difference in levels of work status (18%), formal education (15% contribution), marital status (13%), physical activity (9%), health status (8%) and chronic morbidity prevalence (5%), respectively. Equivalently, the major contributors to the gender gap in difficulty in IADL were the level of formal education (28% contribution), marital status (10%), alcohol consumption (9%), health status (4% contribution) and chronic morbidity prevalence (2% contribution).

CONCLUSION

Due to the rapidly increasing ageing population, early detection and prevention of disability or preservation of daily functioning for older adults and women in particular should be the highest priority for physicians and health decision-makers.

Decomposing urban-rural differences in multimorbidity among older adults in India: a study based on LASI data

BACKGROUND

Multimorbidity is defined as the co-occurrence of two or more than two diseases in the same person. With rising longevity, multimorbidity has become a prominent concern among the older population. Evidence from both developed and developing countries shows that older people are at much higher risk of multimorbidity; however, urban-rural differential remained scarce. Therefore, this study examines urban-rural differential in multimorbidity among older adults by decomposing the risk factors of multimorbidity and identifying the covariates that contributed to the change in multimorbidity.

METHODS

The study utilized information from 31,464 older adults (rural-20,725 and urban-10,739) aged 60 years and above from the recent release cross-sectional data of the Longitudinal Ageing Study in India (LASI). Descriptive, bivariate, and multivariate decomposition analysis techniques were used.

RESULTS

Overall, significant urban-rural differences were found in the prevalence of multimorbidity among older adults (difference: 16.3; p < 0.001). The multivariate decomposition analysis revealed that about 51% of the overall differences (urban-rural) in the prevalence of multimorbidity among older adults was due to compositional characteristics (endowments). In contrast, the remaining 49% was due to the difference in the effect of characteristics (Coefficient). Moreover, obese/overweight and high-risk waist circumference were found to narrow the difference in the prevalence of multimorbidity among older adults between urban and rural areas by 8% and 9.1%, respectively. Work status and education were found to reduce the urban-rural gap in the prevalence of multimorbidity among older adults by 8% and 6%, respectively.

CONCLUSIONS

There is a need to substantially increase the public sector investment in healthcare to address the multimorbidity among older adults, more so in urban areas, without compromising the needs of older adults in rural areas.

Gender differences in the association of obesity-related measures with multi-morbidity among older adults in India: evidence from LASI, Wave-1

Background

Co-existence of multiple chronic diseases is increasingly becoming a norm among ageing population. The study aims to investigate the prevalence of multimorbidity and the association between anthropometric measures of obesity and multimorbidity among men and women aged 60 years and above in India.

Methods

The present study is based on the first wave of the Longitudinal Aging Study in India. The analytical sample size for the study was 28,050 older adults aged 60 years and above. Descriptive statistics and multivariable analysis using logistic regression models were conducted.

Results

Body Mass Index (BMI) based-obesity is more prevalent among older women than men (26.3% vs. 17.6%). Similarly, higher proportion of older women was at high-risk waist circumference (37.1% vs 8.9%) and waist-hip ratio (78.5 vs 75.4%) than men respectively. In Model-I, after controlling for several covariates, older adults with overweight/obesity were 1.6 times more likely to have multi-morbidity than non-obese older adults (Adjusted OR = 1.61; 95% CI: 1.48–1.74). Similarly, older adults with high-risk waist circumference [Adjusted OR: 1.66; 95% CI: 1.52–1.80] and waist-hip ratio [Adjusted OR: 1.45; 95% CI: 1.33–1.59] also had higher odds of having multi-morbidity in reference to their counterparts. In model-3 it was found that females with high-risk waist-hip ratio had 14% lower odds of multimorbidity than males with high-risk waist-hip ratio [Adjusted OR: 0.86; 95%CI: 0.78–0.94].

Conclusion

The findings of the study show significant gender difference in the prevalence of multimorbidity, men being at increased risk in the multivariate analysis which is uncommon in the existing epidemiological research. Interactive effect of male gender with anthropometric measures on multimorbidity reported in our study probably due to increased unhealthy behaviours among men requires further research.

Association of anthropometric measures of obesity and physical activity with cardio-vascular diseases among older adults: Evidence from a cross-sectional survey, 2017-18

BACKGROUND

With the increase in elderly population, the risk of cardiovascular diseases (CVD) among Indian older adults is also increasing. The present paper tries to assess how different anthropometric measures of obesity and physical activity affects cardiovascular disease risk among older adults in India.

METHODS

The data from Longitudinal Ageing Study in India (LASI) has been used. The total sample size for the present study is 31,464 older adults aged 60 years and above. Chi-square test and binary logistic regression has been used to measure the association of obesity measures and CVD prevalence.

RESULTS

About 35.2% (n = 11,058) of the older adults suffered from CVD. Moreover, 22.2% (n = 6,217) of the older adults were obese/overweight, 23.7% (n = 6,651) had high risk waist circumference and 77.0% (n = 21,593) had high risk waist-Hip ratio. The likelihood of CVD was 60%, 50%, and 34% significantly higher among older adults who were obese/overweight [Adjusted odds ratio (AOR): 1.60; CI: 1.48-1.72], had high risk waist circumference [AOR: 1.50; CI: 1.39-1.62] and high risk waist-Hip ratio [AOR: 1.34; CI: 1.25-1.44], respectively compared to older adults with normal BMI and those who do not have a high risk waist circumference and high risk waist hip ratio. Moreover, older adults who never did physical activity had 22 per cent higher risk of CVD than those who did frequent [AOR: 1.22; CI: 1.13-1.32] physical activity.

CONCLUSION

The burden of overweight and obesity along with physical inactivity increases the risk of CVD in older adults. These findings highlight the urgent need for framing direct and indirect strategies to control obesity in order to reduce the burden of CVD among older adults in India.

M, Murthy PV. Population attributable risk for multimorbidity among adult women in India: Do smoking tobacco, chewing tobacco and consuming alcohol make a difference?

BACKGROUND

The present study aims to estimate the prevalence and correlates of multimorbidity among women aged 15-49 years in India. Additionally, the population attributable risk for multi-morbidity in reference to those women who smoke tobacco, chew tobacco, and consume alcohol is estimated.

METHODS

The data was derived from the National Family Health Survey which was conducted in 2015-16. The effective sample size for the present paper 699,686 women aged 15-49 years in India. Descriptive statistics along with bivariate analysis were used to do the preliminary analysis. Additionally, binary logistic regression analysis was used to fulfil the objectives.

RESULTS

About 1.6% of women had multimorbidity in India. The prevalence of multimorbidity was high among women from southern region of India. Women who smoke tobacco, chew tobacco and consume alcohol had 87% [AOR: 1.87CI: 1.65, 2.10], 18% [AOR: 1.18; CI: 1.10, 1.26] and 18% [AOR: 1.18; CI: 1.04, 1.33] significantly higher likelihood to suffer from multi-morbidity than their counterparts respectively. Population Attributable Risk for women who smoke tobacco was 1.2% (p<0.001), chew tobacco was 0.2% (p<0.001) and it was 0.2% (p<0.001) among women who consumed alcohol.

CONCLUSION

The findings indicate the important role of lifestyle and behavioural factors such as smoking and chewing tobacco and consuming alcohol in the prevalence of multimorbidity among adult Indian women. The subgroups identified as at increased risk in the present study can be targeted while making policies and health decisions and appropriate comorbidity management can be implemented.

An assessment of anthropometric indices and its association with NCDs among the older adults of India: evidence from LASI Wave-1

BACKGROUND

The purpose of this study is to assess the status of physical body indices such as body mass index (BMI), waist circumference (WC), and waist-to-hip ratio (WHR) among the older adults aged 45 and above in India. Further, to explore the association of anthropometric indices with various non-communicable morbidities.

METHODS

The study uses secondary data of the Longitudinal Ageing Survey's first wave in India (2017-18). The national representative sample for older adults 45 and above (65,662) considered for the analysis. The prevalence of the non-communicable diseases (NCDs) included in the study is based on the self-reporting of the participants. Diseases included are among the top ten causes of death, such as cancer, hypertension, stroke, chronic heart diseases, diabetes, chronic respiratory diseases, and multi-morbidity. Multi-morbidity is a case of having more than one of the morbidities mentioned above. BMI-obese indicates an individual having a BMI ≥30, and the critical threshold value for high-risk WC for men is ≥102 cm while for women is ≥88 cm. The critical limit for the high-risk WHR for men and women is ≥0.90 and ≥ 0.85, respectively. Descriptive statistics and multiple logistic regressions are used to assess the association BMI, WC, and WHR with non-communicable morbidities.

RESULTS

Based on the multivariate-adjusted model, odds shows that an Indian older adult aged 45 and above is 2.3 times more likely (AOR: 2.33; 95% CI (2.2, 2.5)) by obesity, 61% more likely (AOR: 1.61; 95% CI (1.629, 1.631)) by high-risk WHR and 98% more likely (AOR: 1.98; 95% CI (1.9, 2.1)) by high-risk WC to develop CVDs than their normal counterparts. Similarly, significant positive associations of obesity, high-risk WC, and high-risk WHR were observed with other NCDs and multi-morbidity.

CONCLUSION

Our study shows that obesity, high-risk WC, and high-risk WHR are significant risks for developing NCDs and multi-morbidity among the older adults in India. There is a need for a multi-sectoral approach to reduce the share of the elderly population in high-risk groups of BMIs, WHR, and WC.

Interaction of physical activity on the association of obesity-related measures with multimorbidity among older adults: a population-based cross-sectional study in India

OBJECTIVE

To explore the associations between obesity-related measures and multimorbidity among older Indian adults and the interactive effects of physical activity in those associations.

DESIGN

A cross-sectional study was conducted using large representative survey data.

SETTING AND PARTICIPANTS

The present study used data from the Longitudinal Aging Study in India (LASI) conducted during 2017-2018. Participants included 15 098 male and 16 366 female older adults aged 60 years and above in India.

PRIMARY AND SECONDARY OUTCOME MEASURES

The outcome variable was multimorbidity among older adults coded as no and yes. Descriptive statistics along with bivariate analysis are presented in the paper. Additionally, binary logistic regression analysis was used to fulfil the study objectives.

RESULTS

About 24% of older adults in the LASI cohort suffered from multimorbidity. Older adults who were overweight/obese (adjusted OR (AOR): 1.61, CI 1.48 to 1.74), had high-risk waist circumference (AOR: 1.66, CI 1.52 to 1.80) and had high-risk waist to hip ratio (AOR: 1.45, CI 1.33 to 1.59) were significantly more likely to suffer from multimorbidity compared with their counterparts. Older adults who were obese and physically inactive had significantly increased odds of suffering from multimorbidity compared with older adults who were obese and physically active. Similarly, older adults with high-risk waist circumference (AOR: 1.30, CI 1.11 to 1.53) and high-risk waist to hip ratio (AOR: 1.32, CI 1.20 to 1.46) along with being physically inactive had significantly higher odds of suffering from multimorbidity in comparison with older adults with high-risk waist circumference and waist to hip ratio along with being physically active.

CONCLUSION

While developing health strategies for older adults, physical activity needs to be recognised as a way of minimising comorbidities. Further, the study highlights the importance of using multiple obesity-related measures to predict chronic conditions in the older population.

Health-Related Quality of Life and Health Service Use among Multimorbid Middle-Aged and Older-Aged Adults in China: A Cross-Sectional Study in Shandong Province

(1) Background: The management of multiple chronic diseases challenges China's health system, but current research has neglected how multimorbidity is associated with poor health-related quality of life (HRQOL) and high health service demands by middle-aged and older adults. (2) Methods: A cross-sectional study was conducted in Shandong province, China in 2018 across three age groups: Middle-aged (45 to 59 years), young-old (60 to 74 years), and old-old (75 or above years). The information about socio-economic, health-related behaviors, HRQOL, and health service utilization was collected via face-to-face structured questionnaires. The EQ-5D-3L instrument, comprising a health description system and a visual analog scale (VAS), was used to measure participants' HRQOL, and χ² tests and the one-way ANOVA test were used to analyze differences in socio-demographic factors and HRQOL among the different age groups. Logistic regression models estimated the associations between lifestyle factors, health service utilization, and multimorbidity across age groups. (3) Results: There were 17,867 adults aged 45 or above in our sample, with 9259 (51.82%) female and 65.60% living in rural areas. Compared with the middle-aged adults, the young-old and old-old were more likely to be single and to have a lower level of education and income, with the old-old having lower levels than the young-old (P < 0.001). We found that 2465 (13.80%) suffered multimorbidities of whom 75.21% were older persons (aged 60 or above). As age increased, both the mean values of EQ-5D utility and the VAS scale decreased, displaying an inverse trend to the increase in the number of chronic diseases (P < 0.05). Ex-smokers and physical check-ups for middle or young-old respondents and overweight/obesity for all participants (P < 0.05) were positively correlated with multimorbidity. Drinking within the past month for all participants (P < 0.001), and daily tooth-brushing for middle (P < 0.05) and young-old participants (P < 0.001), were negatively associated with multimorbidity. Multimorbidities increased service utilization including outpatient and inpatient visits and taking self-medicine; and the probability of health utilization was the lowest for the old-old multimorbid patients (P < 0.001). (4) Conclusions: The prevalence and decline in HRQOL of multimorbid middle-aged and older-aged people were severe in Shandong province. Old patients also faced limited access to health services. We recommend early prevention and intervention to address the prevalence of middle-aged and old-aged multimorbidity. Further, the government should set-up special treatment channels for multiple chronic disease sufferers, improve medical insurance policies for the older-aged groups, and set-up multiple chronic disease insurance to effectively alleviate the costs of medical utilization caused by economic pressure for outpatients and inpatients with chronic diseases.