RESUMO
AIM: This study examined the associations of high allostatic load (h_ALS) and metabolic syndrome (MetS) with and self-rated poor health (SRPH) in overweight/obese non-Hispanic White (NHW), non-Hispanic Black (NHB), and Mexican American (MA) adults. METHODS: The 2015-16 and 2017-18 US National Health and Nutrition Examination Survey data (n = 4403) were used for this study. RESULTS: Rates of h_ALS in overweight/obese NHW, NHW, and MA participants were 56.9%, 58.8%, and 51.9%, respectively (P < .05). The corresponding rates for MetS were 26.9%, 31.9%, and 46.5%, respectively. High ALS was associated with 2.19 (95% CI: 1.87-4.59), 1.82 (1.42-2.58), and 1.47 (95% CI: 1.08-1.64) increased odds of SRPH in overweight/obese NHW, NHB, and MA, respectively, after adjusting for age, education, gender, income, lifestyle behaviors, and marital status. The corresponding values for MetS were 1.86 (95% CI: 1.54-2.40), 2.77 (95% CI: 1.36-5.63), and 1.22 (95% CI: 1.06-2.32), respectively. CONCLUSIONS: The effect of h_ALS on SRPH was much stronger in NHW, while the effect of MetS was strongest among NHB overweight/obese adults. The result of this study provides further evidence in favor of race/ethnic-tailored interventions, including education and weight control to reduced risks of bodywear and tear and SRPH.
Assuntos
Alostase , Síndrome Metabólica/etnologia , Obesidade/etnologia , Sobrepeso/etnologia , Adulto , Negro ou Afro-Americano , Idoso , Estudos Transversais , Autoavaliação Diagnóstica , Feminino , Nível de Saúde , Humanos , Estilo de Vida , Masculino , Americanos Mexicanos , Pessoa de Meia-Idade , Inquéritos Nutricionais , População BrancaRESUMO
AIM: To compare the strength of associations between surrogate indexes of insulin resistance (sIR) and risk of metabolic syndrome (MetS) in non-Hispanic White (NHW), non-Hispanic Black (NHB) and Mexican American (MA) adults. METHODS: The 2013-2016 US National Health and Nutrition Examination Survey data (n = 3435) were used for this study. The associations between sIR that includes Triglyceride/HDL cholesterol ratio (TG/HDL-C), triglyceride glucose (TG) index, visceral adiposity index (VAI), lipid accumulation product (LAP), TG-body mass index (TG-BMI), and TG-waist circumference (TG-WC) and risk for MetS were determined using the prevalence odds ratio (OR) from the logistic regression analyses. Pseudo-R-squared tests were used to estimate the proportion of variance in MetS accounted for by each sIR. Akaike Information Criterion and Bayesian Information Criterion from the multinomial logistic regression analysis were used to compare models that included each sIR and its components separately as predictors of MetS. Areas under curves (AUC) from the receiver-operating characteristic (ROC) were used to detect their diagnostic capabilities. RESULTS: Compared with other sIR, TG-WC (AUC = 0.899; 95% CI: 0.884-0.913 in NHW) and (AUC = 0.893; 95% CI:0.871-0.915 in NHB), and LAP (AUC = 877; 95% CI: 0.861-0.894 in MA) exhibited the highest diagnostic and predictive accuracy for MetS. Compared with other sIR, TG-WC (OR = 22.8; 95% CI:16.6-31.0 in NHW) and (OR = 22.7; 95% CI:13.1-39.3 in NHB), and LAP (OR = 10.6; 95%:6.6-17.0 in MA) were most significantly associated with increased odds of MetS, adjusting for eGFR, age, marital status, CHD, CHF, income, education, physical activity, alcohol use, smoking and use of cholesterol-lowering medication. CONCLUSIONS: TG-WC in NHW and NHB, and LAP in MA are more powerful than other proxies of IR in predicting MetS. TG-WC and LAP can serve as adjunctive tools for screening for MetS in NHW, NHB, and MA.
Assuntos
Negro ou Afro-Americano/estatística & dados numéricos , Índice de Massa Corporal , Resistência à Insulina , Síndrome Metabólica/diagnóstico , Americanos Mexicanos/estatística & dados numéricos , Obesidade Abdominal/complicações , População Branca/estatística & dados numéricos , Adiposidade , Biomarcadores/análise , Estudos Transversais , Feminino , Seguimentos , Humanos , Masculino , Síndrome Metabólica/epidemiologia , Síndrome Metabólica/etiologia , Pessoa de Meia-Idade , Prognóstico , Fatores de Risco , Estados Unidos/epidemiologiaRESUMO
BackgroundLittle is known about the joint mental health effects of air pollution and tobacco smoking in low- and middle-income countries.AimsTo investigate the effects of exposure to ambient fine particulate matter pollution (PM2.5) and smoking and their combined (interactive) effects on depression.MethodMultilevel logistic regression analysis of baseline data of a prospective cohort study (n = 41 785). The 3-year average concentrations of PM2.5 were estimated using US National Aeronautics and Space Administration satellite data, and depression was diagnosed using a standardised questionnaire. Three-level logistic regression models were applied to examine the associations with depression.ResultsThe odds ratio (OR) for depression was 1.09 (95% C11.01-1.17) per 10 µg/m3 increase in ambient PM2.5, and the association remained after adjusting for potential confounding factors (adjusted OR = 1.10, 95% CI 1.02-1.19). Tobacco smoking (smoking status, frequency, duration and amount) was also significantly associated with depression. There appeared to be a synergistic interaction between ambient PM2.5 and smoking on depression in the additive model, but the interaction was not statistically significant in the multiplicative model.ConclusionsOur study suggests that exposure to ambient PM2.5 may increase the risk of depression, and smoking may enhance this effect.