Regression with autocorrelated data: A study of time trend of global infant mortality rate

The infant mortality rate (IMR) is considered to be one of the most important indices of a country's well-being. Countries around the world and other health organizations like the World Health Organization are dedicating their resources, knowledge and energy to reduce the infant mortality rates. The well-known Millennium Development Goal 4 (MDG 4), whose aim is to archive a two thirds reduction of the under-five mortality rate between 1990 and 2015, is an example of the commitment. ^ In this study our goal is to model the trends of IMR between the 1950s to 2010s for selected countries. We would like to know how the IMR is changing overtime and how it differs across countries. ^ IMR data collected over time forms a time series. The repeated observations of IMR time series are not statistically independent. So in modeling the trend of IMR, it is necessary to account for these correlations. We proposed to use the generalized least squares method in general linear models setting to deal with the variance-covariance structure in our model. In order to estimate the variance-covariance matrix, we referred to the time-series models, especially the autoregressive and moving average models. Furthermore, we will compared results from general linear model with correlation structure to that from ordinary least squares method without taking into account the correlation structure to check how significantly the estimates change.^

Indigent care and infant mortality in Texas

Infant Mortality has been made a point of emphasis by the Department of Health and Human Services in the Healthy People 2000, 2010, and 2020 priorities. This study used the Behavioral Model for Vulnerable Populations to consider a number of factors which impact infant mortality in the indigent populations in the State of Texas. The primary focus of this study was the enabling factor of community resources, specifically the program used by each county to provide care to their indigent population. The Legislature of the State of Texas requires that each state have a program set up within a Hospital District, Public Hospital or develop a County Indigent Health Care Program (CIHCP) in order to provide the basic health care needs of their most vulnerable residents. We sought to determine whether the development of a CICHP without an appointed hospital to provide the care would have an adverse effect on residents seeking care and increase infant mortality. A Poisson Regression Analysis was used to analyze incidence rate ratios adjusting for race/ethnicity and wealth/poverty variables. Our study showed that counties using a CIHCP had significantly lower infant mortality rates when compared to counties using a hospital district and were statistically equivalent to counties using a public hospital program or a combination of service programs. This relationship was maintained when adjusted incidence rate ratios were calculated. This may give evidence that counties struggling to fund a public hospital or hospital district may be able to find a more cost-effective alternative in the CIHCP without adversely affecting the health status of their residents. More cost-benefit analysis and controlling analysis must be done to further characterize this relationship. ^