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1.
Int J Obes (Lond) ; 48(3): 433-436, 2024 Mar.
Artículo en Inglés | MEDLINE | ID: mdl-38042933

RESUMEN

INTRODUCTION: Metabolically healthy obesity may be a transient phenotype, but studies with long follow-up, especially covering late-life, are lacking. We describe conversions between cross-categories of body mass index (BMI) and metabolic health in 786 Swedish twins with up to 27 years of follow-up, from midlife to late-life. METHODS: Metabolic health was defined as the absence of metabolic syndrome (MetS). We first visualized conversions between BMI-metabolic health phenotypes in 100 individuals with measurements available at ages 50-64, 65-79, and ≥80. Next, we modeled conversion in metabolic health status by BMI category in the full sample using Cox proportional hazards regression. RESULTS: The proportion of individuals with MetS and with overweight or obesity increased with age. However, one-fifth maintained a metabolically healthy overweight or obesity across all three age categories. Among those metabolically healthy at baseline, 59% converted to MetS during follow-up. Conversions occurred 56% more often among individuals with metabolically healthy obesity, but not overweight, compared to normal weight. Among those with MetS at baseline, 60% regained metabolic health during follow-up, with no difference between BMI categories. CONCLUSIONS: Conversions between metabolically healthy and unhealthy status occurred in both directions in all BMI categories. While conversions to MetS were more common among individuals with obesity, many individuals maintained or regained metabolic health during follow-up.


Asunto(s)
Síndrome Metabólico , Obesidad Metabólica Benigna , Humanos , Sobrepeso/metabolismo , Obesidad Metabólica Benigna/epidemiología , Obesidad Metabólica Benigna/metabolismo , Factores de Riesgo , Obesidad/epidemiología , Obesidad/metabolismo , Síndrome Metabólico/epidemiología , Índice de Masa Corporal , Estado de Salud , Fenotipo
2.
BMC Public Health ; 22(1): 718, 2022 04 11.
Artículo en Inglés | MEDLINE | ID: mdl-35410261

RESUMEN

BACKGROUND: There is robust evidence that in midlife, higher body mass index (BMI) and metabolic syndrome (MetS), which often co-exist, are associated with increased mortality risk. However, late-life findings are inconclusive, and few studies have examined how metabolic health status (MHS) affects the BMI-mortality association in different age categories. We, therefore, aimed to investigate how mid- and late-life BMI and MHS interact to affect the risk of mortality. METHODS: This cohort study included 12,467 participants from the Swedish Twin Registry, with height, weight, and MHS measures from 1958-2008 and mortality data linked through 2020. We applied Cox proportional hazard regression with age as a timescale to examine how BMI categories (normal weight, overweight, obesity) and MHS (identification of MetS determined by presence/absence of hypertension, hyperglycemia, low HDL, hypertriglyceridemia), independently and in interaction, are associated with the risk of all-cause mortality. Models were adjusted for sex, education, smoking, and cardiovascular disease. RESULTS: The midlife group included 6,252 participants with a mean age of 59.6 years (range = 44.9-65.0) and 44.1% women. The late-life group included 6,215 participants with mean age 73.1 years (65.1-95.3) and 46.6% women. In independent effect models, metabolically unhealthy status in midlife increased mortality risks by 31% [hazard ratio 1.31; 95% confidence interval 1.12-1.53] and in late-life, by 18% (1.18;1.10-1.26) relative to metabolically healthy individuals. Midlife obesity increased the mortality risks by 30% (1.30;1.06-1.60) and late-life obesity by 15% (1.15; 1.04-1.27) relative to normal weight. In joint models, the BMI estimates were attenuated while those of MHS were less affected. Models including BMI-MHS categories revealed that, compared to metabolically healthy normal weight, the metabolically unhealthy obesity group had increased mortality risks by 53% (1.53;1.19-1.96) in midlife, and across all BMI categories in late-life (normal weight 1.12; 1.01-1.25, overweight 1.10;1.01-1.21, obesity 1.31;1.15-1.49). Mortality risk was decreased by 9% (0.91; 0.83-0.99) among those with metabolically healthy overweight in late-life. CONCLUSIONS: MHS strongly influenced the BMI-mortality association, such that individuals who were metabolically healthy with overweight or obesity in mid- or late-life did not carry excess risks of mortality. Being metabolically unhealthy had a higher risk of mortality independent of their BMI.


Asunto(s)
Síndrome Metabólico , Sobrepeso , Adulto , Anciano , Índice de Masa Corporal , Estudios de Cohortes , Femenino , Estudios de Seguimiento , Humanos , Masculino , Síndrome Metabólico/complicaciones , Síndrome Metabólico/epidemiología , Persona de Mediana Edad , Obesidad/complicaciones , Sobrepeso/complicaciones , Sobrepeso/epidemiología , Sistema de Registros , Factores de Riesgo , Suecia/epidemiología
3.
Geroscience ; 46(2): 2605-2617, 2024 04.
Artículo en Inglés | MEDLINE | ID: mdl-38102440

RESUMEN

Obesity and metabolic syndrome (MetS) share common pathophysiological characteristics with aging. To better understand their interplay, we examined how body mass index (BMI) and MetS jointly associate with physiological age, and if the associations changed from midlife to late-life. We used longitudinal data from 1,825 Swedish twins. Physiological age was measured as frailty index (FI) and functional aging index (FAI) and modeled independently in linear mixed-effects models adjusted for chronological age, sex, education, and smoking. We assessed curvilinear associations of BMI and chronological age with physiological age, and interactions between BMI, MetS, and chronological age. We found a significant three-way interaction between BMI, MetS, and chronological age on FI (p-interaction = 0·006), not FAI. Consequently, we stratified FI analyses by age: < 65, 65-85, and ≥ 85 years, and modeled FAI across ages. Except for FI at ages ≥ 85, BMI had U-shaped associations with FI and FAI, where BMI around 26-28 kg/m2 was associated with the lowest physiological age. MetS was associated with higher FI and FAI, except for FI at ages < 65, and modified the BMI-FI association at ages 65-85 (p-interaction = 0·02), whereby the association between higher BMI levels and FI was stronger in individuals with MetS. Age modified the MetS-FI association in ages ≥ 85, such that it was stronger at higher ages (p-interaction = 0·01). Low BMI, high BMI, and metabolic syndrome were associated with higher physiological age, contributing to overall health status among older individuals and potentially accelerating aging.


Asunto(s)
Síndrome Metabólico , Humanos , Anciano de 80 o más Años , Síndrome Metabólico/complicaciones , Índice de Masa Corporal , Obesidad , Fumar , Envejecimiento
4.
J Interpers Violence ; 35(19-20): 4083-4116, 2020 10.
Artículo en Inglés | MEDLINE | ID: mdl-29294780

RESUMEN

Intimate partner violence (IPV) is a critical public health issue that has reached epidemic proportions. Research investigating IPV among young women in India using large-scale population data is lacking. This study examined the prevalence and factors associated with IPV among women aged 15 to 24 years in India through a social-ecological approach. This cross-sectional study analyzed data from the National Family Health Survey, a population-based survey conducted in India from 2005 to 2006. The past-year prevalence of emotional, physical, and sexual forms of IPV, among ever-married women aged 15 to 24 years were computed. Multivariate logistic regression was conducted to evaluate the association of factors at various levels of the social-ecological framework with the past-year experience of emotional, physical, sexual, and any form of IPV. The past-year prevalence of IPV among women aged 15 to 24 years (n = 16,285) was 29%. Physical IPV was the most common, affecting 23% in the past year. The past-year prevalence of sexual IPV among women aged 15 to 24 years at 9.5% was higher than older women. Individual factors significantly associated with the past-year experience of all forms of IPV were the young age at first marriage, parental IPV, and ever had a terminated pregnancy. At the relationship level, husband's controlling behaviors, his consumption of alcohol, and experience of violence from other family members were positively associated with all forms of IPV in the past year. Poverty and acceptance of IPV increased the women's odds of experiencing IPV. IPV was associated with multiple factors occurring at all levels of the social-ecological framework. Actions to prevent and eliminate IPV in India demand multidisciplinary and collaborative efforts that are tailored specifically for adolescents and young women. It is imperative to protect the girls and young women from IPV; it protects the future of India.


Asunto(s)
Violencia de Pareja , Adolescente , Anciano , Estudios Transversales , Femenino , Humanos , India/epidemiología , Matrimonio , Prevalencia , Factores de Riesgo
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