RESUMO
Few reliable estimates have been available for assessing the impact of the COVID-19 pandemic on mortality among Native Americans. Using deidentified publicly available data on deaths and populations by age, we estimated life expectancy for the years 2019-2022 for single-race non-Hispanic Native Americans. Life expectancy in 2022 was 67.8 years, 2.3 years higher than in 2021 but a huge 4-year loss from 2019. Although our life expectancy estimates for 2022 varied under different assumptions about racial/ethnic classification and age misreporting errors, all estimates were lower than the average for middle-income countries. Estimates of losses and gains in life expectancy were consistent across assumptions. Large reductions in COVID-19 death rates between 2021 and 2022 were largely offset by increases in rates of death from unintentional injuries (particularly drug overdoses), chronic liver disease, diabetes, and heart disease, underscoring the difficulties facing Native Americans in achieving reductions in mortality, let alone returning to levels of mortality prior to the pandemic. Serious data problems have persisted for many years, but the scarcity and inadequacy of estimates during the pandemic have underscored the urgent need for timely and accurate demographic data on the Native American population.
Assuntos
COVID-19 , Indígenas Norte-Americanos , Expectativa de Vida , Humanos , COVID-19/mortalidade , COVID-19/etnologia , Expectativa de Vida/etnologia , Expectativa de Vida/tendências , Pessoa de Meia-Idade , Idoso , Estados Unidos/epidemiologia , Adulto , Indígenas Norte-Americanos/estatística & dados numéricos , Masculino , Adolescente , Feminino , Idoso de 80 Anos ou mais , Adulto Jovem , Incerteza , Causas de Morte , Criança , SARS-CoV-2 , Pré-Escolar , Lactente , Recém-Nascido , PandemiasRESUMO
Background: Maintaining cardiovascular health (CVH) is critical for breast cancer (BC) survivors, particularly given the potential cardiotoxic effects of cancer treatments. Poor CVH among Black BC survivors may be influenced by various area-level social determinants of health, yet the impact of neighborhood archetypes in CVH among this population remains understudied. Objectives: This study aimed to characterize the neighborhood archetypes where Black BC survivors resided at diagnosis and evaluate their associations with CVH. Methods: We assessed CVH 24 months post-diagnosis in 713 participants diagnosed between 2012 and 2017 in the Women's Circle of Health Follow-Up Study, a population-based study of Black BC survivors in New Jersey. Neighborhood archetypes, identified via latent class analysis based on 16 social and built environment features, were categorized into tertiles. Associations between neighborhood archetypes and CVH scores were estimated using polytomous logistic regression. Results: CVH scores were assessed categorically (low, moderate, and optimal) and as continuous variables. On average, Black BC survivors achieved only half of the recommended score for optimal CVH. Among the 4 identified archetypes, women in the Mostly Culturally Black and Hispanic/Mixed Land Use archetype showed the lowest CVH scores. Compared to this archetype, Black BC survivors in the Culturally Diverse/Mixed Land Use archetype were nearly 3 times as likely to have optimal CVH (relative risk ratio: 2.92; 95% CI: 1.58-5.40), with a stronger association observed in younger or premenopausal women. No significant CVH differences were noted for the other 2 archetypes with fewer built environment features. Conclusions: Neighborhood archetypes, integrating social and built environment factors, may represent crucial targets for promoting CVH among BC survivors.
RESUMO
Objective. To determine whether disease predicts weight loss in population-based studies, as this may confound the relationship between weight and mortality. Materials and methods. We used longitudinal data from the Costa Rican Longevity and Healthy Aging Study (CRELES) and the English Longitudinal Study of Ageing (ELSA). We defined two overlapping outcomes of measured weight loss between waves: >1.0 point of body mass index (BMI) and >2.0 BMI points. Logistic regression models estimated the associations with disease, adjusting for age (range 52-79), sex, smoking, and initial BMI. Results. In ELSA, onset of diabetes, cancer, or lung disease is associated with loss >2.0 points (respectively, OR=2.25 [95%CI: 1.34-3.80]; OR=2.70 [95%CI: 1.49-4.89]; OR=1.82 [95%CI: 1.02-3.26]). In CRELES, disease-onset reports are not associated with weight loss at 5% significance, but statistical power to detect associations is poor. Conclusion. Although it is known that some diseases cause weight loss, at the population level these associations vary considerably across samples.
Objetivo. Determinar si las enfermedades predicen pérdida de peso a partir de encuestas poblacionales, debido a que esto podría confundir la relación entre peso y mortalidad. Material y métodos. Se utilizaron datos longitudinales de Costa Rica: Estudio de Longevidad y Envejecimiento Saludable (CRELES) y Estudio Longitudinal de Envejecimiento en Inglaterra (ELSA, por sus siglas en inglés). Se definieron dos indicadores de resultado no excluyentes de pérdida de peso entre rondas: >1.0 punto de índice de masa corporal (IMC) y >2.0 puntos de IMC. Las asociaciones de interés se estimaron con modelos de regresión logística, con controles para la edad (rango 52-79), sexo, tabaquismo actual e IMC inicial. Resultados. En el ELSA, la incidencia de diabetes, cáncer o enfermedad pulmonar está asociada con pérdida de >2.0 puntos de IMC (respectivamente: OR=2.25 [IC95%: 1.34-3.80]; OR=2.70 [IC95%: 1.49-4.89]; OR=1.82 [IC95%: 1.02-3.26]). En el CRELES, el reporte de diagnóstico de enfermedades no muestra asociación significativa a 5% con pérdida de peso, pero el poder estadístico de la muestra para detectar asociaciones es limitado. Conclusión. Aunque es conocido que ciertas enfermedades causan pérdida de peso, estas asociaciones a nivel poblacional varían considerablemente entre encuestas.