Age and Socioeconomic Gradients in Frailty Among Older Adults in India

Although individuals with frailty and lower socioeconomic status (SES) are vulnerable to morbidity and early mortality, few studies have investigated this association. We intend to fill this gap with a study using older adults aged ≥ 50 years from the SAGE WAVE II in India. The Aim of study is to examine the association of frailty with SES and how this association varies across different age groups. A modified Fried phenotype approach with five frailty indicators was used to categorize 6560 older adults as frail, pre-frail or robust who had more than two, one or zero indicators, respectively: grip strength, exhaustion, weight loss, walking speed and physical activity. Multinomial logistic regression estimated the likelihood of being pre-frail and frail for various levels of SES, controlling and not controlling for confounders. This study also shows the overall socioeconomic gradients and age patterns of socioeconomic gradients of frailty indicators using predicted probabilities. Approximately 26%, 55% and 20% participants were robust, pre-frail and frail, respectively. The number of frailty indicators was positively associated with lower income and education levels in the case of controlling and not controlling for confounders. Also, among the higher age groups, individuals with low SES had higher chances of being frail.Overall, the results in this research indicated a negative low SES and frailty association as found in previous studies worldwide. This highlights the need for comprehensive and centered public health interventions for older adults with low SES.

Pediatric metabolic syndrome definitions impact prevalence and socioeconomic gradients

Background The choice of pediatric metabolic syndrome (MetS) definition influences prevalence estimates, but further implications, especially on the association with socioeconomic status (SES), are not well-known. This hampers a synthesis of the evidence to help guide the relevant stakeholders. For this reason, we aim to assess the impact of alternative definitions on the prevalence of MetS, the children that are identified, and the association between SES and MetS. Methods Data were used from the Lifelines Cohort Study, a prospective multigenerational cohort in the Netherlands. At baseline 9,754 children participated, of which 5,085 (52.1%) were included in the longitudinal analyses. We computed the prevalence of MetS according to five published definitions and measured the observed positive agreement between pairs of definitions, indicating the proportion of agreement across the average number of MetS cases. Logistic regression was used to assess the association between SES and MetS. All models were adjusted for age and sex; the longitudinal models were also adjusted for baseline MetS status. Results The prevalence rates of MetS varied between definitions (0.7-3.0% at baseline), but positive agreement between MetS definitions was generally fair to good ranging from 0.34 (95% confidence interval (CI) 0.28; 0.41) to 0.66 (95%CI 0.58; 0.75) at baseline. At both assessments, we found an inverse association between baseline SES and MetS, which ranged from 0.81 (95%CI 0.70; 0.93) to 0.92 (95%CI 0.86; 0.98) per definition in the longitudinal analyses with a mean follow-up (SD) of 3.0 (0.75) years. Conclusions Alternative definitions of MetS lead to differing prevalence estimates, and they agreed on 50% of the average number of cases of MetS. The alternative definitions also lead to similar socioeconomic gradients; regardless of which definition was used we concluded low SES was a risk factor for developing MetS. Key messages Evidence regarding different definitions of metabolic syndrome in children can be combined because the agreement among definitions is generally fair to good. As low socioeconomic status is a consistent risk factor for developing metabolic syndrome, preventive interventions should preferentially target children from low socioeconomic backgrounds.