Multiple imputation for missing continuous and dichotomous data: The effects of patterns of missingness and variable correlations on type I error with small samples

The purpose of this study is to investigate the effects of predictor variable correlations and patterns of missingness with dichotomous and/or continuous data in small samples when missing data is multiply imputed. Missing data of predictor variables is multiply imputed under three different multivariate models: the multivariate normal model for continuous data, the multinomial model for dichotomous data and the general location model for mixed dichotomous and continuous data. Subsequent to the multiple imputation process, Type I error rates of the regression coefficients obtained with logistic regression analysis are estimated under various conditions of correlation structure, sample size, type of data and patterns of missing data. The distributional properties of average mean, variance and correlations among the predictor variables are assessed after the multiple imputation process. ^ For continuous predictor data under the multivariate normal model, Type I error rates are generally within the nominal values with samples of size n = 100. Smaller samples of size n = 50 resulted in more conservative estimates (i.e., lower than the nominal value). Correlation and variance estimates of the original data are retained after multiple imputation with less than 50% missing continuous predictor data. For dichotomous predictor data under the multinomial model, Type I error rates are generally conservative, which in part is due to the sparseness of the data. The correlation structure for the predictor variables is not well retained on multiply-imputed data from small samples with more than 50% missing data with this model. For mixed continuous and dichotomous predictor data, the results are similar to those found under the multivariate normal model for continuous data and under the multinomial model for dichotomous data. With all data types, a fully-observed variable included with variables subject to missingness in the multiple imputation process and subsequent statistical analysis provided liberal (larger than nominal values) Type I error rates under a specific pattern of missing data. It is suggested that future studies focus on the effects of multiple imputation in multivariate settings with more realistic data characteristics and a variety of multivariate analyses, assessing both Type I error and power. ^

Racial/ethnic disparities in colorectal cancer screening and survival in a large nationwide population-based cohort

Background. Colorectal cancer (CRC) is the third most commonly diagnosed cancer (excluding skin cancer) in both men and women in the United States, with an estimated 148,810 new cases and 49,960 deaths in 2008 (1). Racial/ethnic disparities have been reported across the CRC care continuum. Studies have documented racial/ethnic disparities in CRC screening (2-9), but only a few studies have looked at these differences in CRC screening over time (9-11). No studies have compared these trends in a population with CRC and without cancer. Additionally, although there is evidence suggesting that hospital factors (e.g. teaching hospital status and NCI designation) are associated with CRC survival (12-16), no studies have sought to explain the racial/ethnic differences in survival by looking at differences in socio-demographics, tumor characteristics, screening, co-morbidities, treatment, as well as hospital characteristics. ^ Objectives and Methods. The overall goals of this dissertation were to describe the patterns and trends of racial/ethnic disparities in CRC screening (i.e. fecal occult blood test (FOBT), sigmoidoscopy (SIG) and colonoscopy (COL)) and to determine if racial/ethnic disparities in CRC survival are explained by differences in socio-demographic, tumor characteristics, screening, co-morbidities, treatment, and hospital factors. These goals were accomplished in a two-paper format.^ In Paper 1, "Racial/Ethnic Disparities and Trends in Colorectal Cancer Screening in Medicare Beneficiaries with Colorectal Cancer and without Cancer in SEER Areas, 1992-2002", the study population consisted of 50,186 Medicare beneficiaries diagnosed with CRC from 1992 to 2002 and 62,917 Medicare beneficiaries without cancer during the same time period. Both cohorts were aged 67 to 89 years and resided in 16 Surveillance, Epidemiology and End Results (SEER) regions of the United States. Screening procedures between 6 months and 3 years prior to the date of diagnosis for CRC patients and prior to the index date for persons without cancer were identified in Medicare claims. The crude and age-gender-adjusted percentages and odds ratios of receiving FOBT, SIG, or COL were calculated. Multivariable logistic regression was used to assess race/ethnicity on the odds of receiving CRC screening over time.^ Paper 2, "Racial/Ethnic Disparities in Colorectal Cancer Survival: To what extent are racial/ethnic disparities in survival explained by racial differences in socio-demographics, screening, co-morbidities, treatment, tumor or hospital characteristics", included a cohort of 50,186 Medicare beneficiaries diagnosed with CRC from 1992 to 2002 and residing in 16 SEER regions of the United States which were identified in the SEER-Medicare linked database. Survival was estimated using the Kaplan-Meier method. Cox proportional hazard modeling was used to estimate hazard ratios (HR) of mortality and 95% confidence intervals (95% CI).^ Results. The screening analysis demonstrated racial/ethnic disparities in screening over time among the cohort without cancer. From 1992 to 1995, Blacks and Hispanics were less likely than Whites to receive FOBT (OR=0.75, 95% CI: 0.65-0.87; OR=0.50, 95% CI: 0.34-0.72, respectively) but their odds of screening increased from 2000 to 2002 (OR=0.79, 95% CI: 0.72-0.85; OR=0.67, 95% CI: 0.54-0.75, respectively). Blacks and Hispanics were less likely than Whites to receive SIG from 1992 to 1995 (OR=0.75, 95% CI: 0.57-0.98; OR=0.29, 95% CI: 0.12-0.71, respectively), but their odds of screening increased from 2000 to 2002 (OR=0.79, 95% CI: 0.68-0.93; OR=0.50, 95% CI: 0.35-0.72, respectively).^ The survival analysis showed that Blacks had worse CRC-specific survival than Whites (HR: 1.33, 95% CI: 1.23-1.44), but this was reduced for stages I-III disease after full adjustment for socio-demographic, tumor characteristics, screening, co-morbidities, treatment and hospital characteristics (aHR=1.24, 95% CI: 1.14-1.35). Socioeconomic status, tumor characteristics, treatment and co-morbidities contributed to the reduction in hazard ratios between Blacks and Whites with stage I-III disease. Asians had better survival than Whites before (HR: 0.73, 95% CI: 0.64-0.82) and after (aHR: 0.80, 95% CI: 0.70-0.92) adjusting for all predictors for stage I-III disease. For stage IV, both Asians and Hispanics had better survival than Whites, and after full adjustment, survival improved (aHR=0.73, 95% CI: 0.63-0.84; aHR=0.74, 95% CI: 0.61-0.92, respectively).^ Conclusion. Screening disparities remain between Blacks and Whites, and Hispanics and Whites, but have decreased in recent years. Future studies should explore other factors that may contribute to screening disparities, such as physician recommendations and language/cultural barriers in this and younger populations.^ There were substantial racial/ethnic differences in CRC survival among older Whites, Blacks, Asians and Hispanics. Co-morbidities, SES, tumor characteristics, treatment and other predictor variables contributed to, but did not fully explain the CRC survival differences between Blacks and Whites. Future research should examine the role of quality of care, particularly the benefit of treatment and post-treatment surveillance, in racial disparities in survival.^

SOCIAL, ATTITUDINAL AND BEHAVIORAL CORRELATES OF WEIGHT CHANGE AMONG MEXICAN AMERICAN WOMEN (OBESITY, DIET, TEXAS)

In industrialized countries the prevalence of obesity among women decreases with increasing socioeconomic status. While this relation has been amply documented, its explanation and implications for other causal factors of obesity has received much less attention. Differences in childbearing patterns, norms and attitudes about fatness, dietary behaviors and physical activity are some of the factors that have been proposed to explain the inverse relation.^ The objectives of this investigation were to (1) examine the associations among social characteristics and weight-related attitudes and behaviors, and (2) examine the relations of these factors to weight change and obesity. Information on social characteristics, weight-related attitudes, dietary behaviors, physical activity and childbearing were collected from 304 Mexican American women aged 19 to 50 living in Starr County, Texas, who were at high risk for developing diabetes. Their weights were recorded both at an initial physical examination and at a follow-up interview one to two and one-half years later, permitting the computation of current Body Mass Index (weight/height('2)) and weight change during the interval for each subject. Path analysis was used to examine direct and indirect relations among the variables.^ The major findings were: (1) After controlling for age, childbearing was not an independent predictor of weight change or Body Mass Index. (2) Neither planned exercise nor total daily physical activity were independent predictors of weight change. (3) Women with higher social characteristics scores reported less frequent meals and less use of calorically dense foods, factors associated with lower risk for weight gain. (4) Dietary intake measures were not significantly related to Body Mass Index. However, dietary behaviors (frequency of meals and snacks, use of high and low caloric density foods, eating restraint and disinhibition of restraint) did explain a significant portion (17.4 percent) of the variance in weight change, indicating the importance of using dynamic measures of weight status in studies of the development of obesity. This study highlights factors amenable to intervention to reverse or to prevent weight gain in this population, and thereby reduce the prevalence of diabetes and its sequelae. ^

Subjective well -being as predictor of mortality, heart disease, and obesity: Prospective evidence from the Alameda County Study

Based on the World Health Organization's (1965) definition of health, understanding of health requires understanding of positive psychological states. Subjective Well-being (SWB) is a major indicator of positive psychological states. Up to date, most studies of SWB have been focused on its distributions and determinants. However, study of its consequences, especially health consequences, is lacking. This dissertation research examined Subjective Well-being, as operationally defined by constructs drawn from the framework of Positive Psychology, and its sub-scores (Positive Feelings and Negative Feelings) as predictors of three major health outcomes—mortality, heart disease, and obesity. The research used prospective data from the Alameda County Study over 29 years (1965–1994), based on a stratified, randomized, representative sample of the general public in Alameda County, California (Baseline N = 6928). ^ Multivariate analyses (Survival analyses using sequential Cox Proportional Hazard models in the cases of mortality and heart disease, and sequential Logistic Regression analyses in the case of obesity) were performed as the main methods to evaluate the associations of the predictors and the health outcomes. The results revealed that SWB reduced risks of all-cause mortality, natural-cause mortality, and cardiovascular mortality. Positive feelings not only had an even stronger protective effect against all-cause, natural-cause and cardiovascular mortality, but also predicted decreased unnatural-cause mortality which includes deaths from suicide, homicide, accidents, mental disorders, drug dependency, as well as alcohol-related liver diseases. These effects were significant even after adjusted for age, gender, education, and various physical health measures, and, in the case of cardiovascular mortality, obesity and health practices (alcohol consumption, smoking, and physical activities). However, these two positive psychological indicators, SWB and positive feelings, did not predict obesity. And negative feelings had no significant effect on any of the health outcomes evaluated, i.e., all-cause mortality, natural- and unnatural-cause mortality, cardiovascular mortality, or obesity, after covariates were controlled. These findings were discussed (1) in comparison with relevant existing studies, (2) in terms of their implications in health research and promotion, (3) in terms of the independence of positive and negative feelings, and (4) from a Positive Psychology perspective and its significance in Public Health research and practice. ^