Biomaterial Database

Lowering infant mortality in western Europe: national health service vs social security systems. 1996

S G Grubaugh, and R E Santerre

UI	MeSH Term	Description	Entries
D007223	Infant	A child between 1 and 23 months of age.	Infants
D007226	Infant Mortality	Postnatal deaths from BIRTH to 365 days after birth in a given population. Postneonatal mortality represents deaths between 28 days and 365 days after birth (as defined by National Center for Health Statistics). Neonatal mortality represents deaths from birth to 27 days after birth.	Neonatal Mortality,Mortality, Infant,Postneonatal Mortality,Infant Mortalities,Mortalities, Infant,Mortalities, Neonatal,Mortalities, Postneonatal,Mortality, Neonatal,Mortality, Postneonatal,Neonatal Mortalities,Postneonatal Mortalities
D007231	Infant, Newborn	An infant during the first 28 days after birth.	Neonate,Newborns,Infants, Newborn,Neonates,Newborn,Newborn Infant,Newborn Infants
D009313	National Health Programs	Components of a national health care system which administer specific services, e.g., national health insurance.	National Health Insurance, Non-U.S.,Health Services, National,National Health Insurance,National Health Insurance, Non U.S.,National Health Services,Services, National Health,Health Insurance, National,Health Program, National,Health Programs, National,Health Service, National,Insurance, National Health,National Health Program,National Health Service,Program, National Health,Programs, National Health,Service, National Health
D012044	Regression Analysis	Procedures for finding the mathematical function which best describes the relationship between a dependent variable and one or more independent variables. In linear regression (see LINEAR MODELS) the relationship is constrained to be a straight line and LEAST-SQUARES ANALYSIS is used to determine the best fit. In logistic regression (see LOGISTIC MODELS) the dependent variable is qualitative rather than continuously variable and LIKELIHOOD FUNCTIONS are used to find the best relationship. In multiple regression, the dependent variable is considered to depend on more than a single independent variable.	Regression Diagnostics,Statistical Regression,Analysis, Regression,Analyses, Regression,Diagnostics, Regression,Regression Analyses,Regression, Statistical,Regressions, Statistical,Statistical Regressions
D005060	Europe	The continent north of AFRICA, west of ASIA and east of the ATLANTIC OCEAN.	Northern Europe,Southern Europe,Western Europe
D006801	Humans	Members of the species Homo sapiens.	Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D012943	Social Security	Government sponsored social insurance programs.	Aid to the Blind,Aid to the Totally Disabled,Social Insurance,Aid to Totally Disabled Persons,Aid to Visually Impaired,Aid to Visually Impaired Persons,Insurance, Social,Security, Social
D015233	Models, Statistical	Statistical formulations or analyses which, when applied to data and found to fit the data, are then used to verify the assumptions and parameters used in the analysis. Examples of statistical models are the linear model, binomial model, polynomial model, two-parameter model, etc.	Probabilistic Models,Statistical Models,Two-Parameter Models,Model, Statistical,Models, Binomial,Models, Polynomial,Statistical Model,Binomial Model,Binomial Models,Model, Binomial,Model, Polynomial,Model, Probabilistic,Model, Two-Parameter,Models, Probabilistic,Models, Two-Parameter,Polynomial Model,Polynomial Models,Probabilistic Model,Two Parameter Models,Two-Parameter Model
D015986	Confounding Factors, Epidemiologic	Factors that can cause or prevent the outcome of interest but are not intermediate variables of the factor(s) under investigation.	Confounding Factor, Epidemiologic,Confounding Factors, Epidemiological,Confounding Factors, Epidemiology,Confounding Variables,Confounding Variables, Epidemiologic,Confounding Variables, Epidemiological,Confounding Factor, Epidemiological,Confounding Factor, Epidemiology,Confounding Variable,Confounding Variable, Epidemiologic,Confounding Variable, Epidemiological,Epidemiologic Confounding Factor,Epidemiologic Confounding Factors,Epidemiologic Confounding Variable,Epidemiologic Confounding Variables,Epidemiological Confounding Factor,Epidemiological Confounding Factors,Epidemiological Confounding Variable,Epidemiological Confounding Variables,Epidemiology Confounding Factor,Epidemiology Confounding Factors,Variable, Confounding,Variable, Epidemiologic Confounding,Variable, Epidemiological Confounding,Variables, Confounding,Variables, Epidemiologic Confounding,Variables, Epidemiological Confounding