RESUMO
We consider measurement error models for two variables observed repeatedly and subject to measurement error. One variable is continuous, while the other variable is a mixture of continuous and zero measurements. This second variable has two sources of zeros. The first source is episodic zeros, wherein some of the measurements for an individual may be zero and others positive. The second source is hard zeros, i.e., some individuals will always report zero. An example is the consumption of alcohol from alcoholic beverages: some individuals consume alcoholic beverages episodically, while others never consume alcoholic beverages. However, with a small number of repeat measurements from individuals, it is not possible to determine those who are episodic zeros and those who are hard zeros. We develop a new measurement error model for this problem, and use Bayesian methods to fit it. Simulations and data analyses are used to illustrate our methods. Extensions to parametric models and survival analysis are discussed briefly.
Assuntos
Teorema de Bayes , Modelos Estatísticos , Humanos , Simulação por Computador , Análise de Sobrevida , Consumo de Bebidas Alcoólicas , Interpretação Estatística de DadosRESUMO
BACKGROUND: Self-reported health (SRH) is an important indicator of mental health outcomes. More information, however, is needed on whether this association varies by birthplace (defined as US-born or non-US-born) and citizenship status (i.e., non-US-born citizen, non-US citizen, and US-born citizen). METHODS: We examined the associations between SRH and depression among non-US-born US citizens, non-US citizens, and US-born citizens aged 18 years and older using weighted cross-sectional data from the 2010-2018 National Health Interview Survey (n = 139,884). Logistic regression models were used to assess the association between depression and SRH by citizenship status, adjusting for covariates. RESULTS: US-born citizens reported the highest prevalence of depression (40.3 %), and non-US-born citizens reported the highest prevalence of poor/fair SRH (14.5 %). Individuals with fair/poor SRH had a significantly increased likelihood of depression relative to those with good/very good/excellent for non-US-born US citizens (Adjusted Odds Ratio [AOR] = 2.42, 95 % Confidence Interval [95 % CI] = 2.04-2.88), non-US citizens (AOR = 2.80, 95 % CI = 2.31-3.40), and US-born citizens (AOR = 2.31, CI = 2.18-2.45). LIMITATIONS: The study is cross-sectional, reducing the strength of determining causal relationships. Also, there is a possible response bias due to the self-reported nature of the data. CONCLUSIONS: Our study indicates that fair/poor SRH is significantly associated with an increased likelihood of depression regardless of an individual citizenship status. Additionally, immigrants with fair/poor SRH had higher increased odds of depression. Therefore, mental healthcare interventions tailored for immigrants can reduce mental health problems and disparities among immigrants.