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PubMedDate not supplied

Intestinal colonization with Enterobacteriaceae in Pakistani and Swedish hospital-delivered infants.

Rectal cultures from Swedish and Pakistani hospital-delivered newborn infants were analysed regarding the early acquisition of enterobacteria. Swedish infants were delivered vaginally, Pakistani infants were delivered either vaginally or by caesarean section. The Swedish infants were all breast-fed, whereas breastfeeding was incomplete and often started late among the Pakistani infants. Both groups of Pakistani infants were more rapidly colonized with enterobacteria than were the Swedish infants. Cultures from Swedish infants seldom yielded more than one kind of enterobacteria; E. coli and Klebsiella were most frequently isolated. E. coli dominated in both Pakistani groups, but especially caesarean section delivered infants were in addition often colonized with Proteus, Klebsiella, Enterobacter or Citrobacter species. Breastfeeding from the first day of life reduced colonization with Klebsiella/Enterobacter/Citrobacter. The results suggest that environmental exposure, delivery mode and early feeding habits all influence the early intestinal colonization with enterobacteria.

Breast Feeding↗
PubMed1998

Galton's law of ancestral heredity.

Galton's ancestral law states that the two parent contribute between them on average one-half of the total heritage of the offspring, the four grandparents one-quarter, and so on. He interpreted this law both as a representation of the separate contributions of each ancestor to the heritage of the offspring and as a multiple regression formula for predicting the value of a trait from ancestral values. Logical reconstruction of the law is presented based on formalizing Galton's model of heredity outlined in Natural Inheritance (Galton, 1889). The resulting law has a free parameter to be empirically estimated which represents the frequency of latent hereditary elements that are not expressed in a particular individual but are capable of transmission to the next generation. The equation representing ancestral contributions to the heritage of the offspring differs from the multiple regression equation for predicting the value of a trait from ancestral values. The former equation reduces to Galton's ancestral law when the proportion of latent elements is 0.5, the latter when this proportion 0.6. Galton's rather different derivations of the law in 1885 and 1897 are described, and their shortcomings are discussed in the light of these results (Galton, 1885, 1897).

Animals↗
PubMedDate not supplied

Modelling the growth curve of Maine-Anjou beef cattle using heteroskedastic random coefficients models.

A heteroskedastic random coefficients model was described for analyzing weight performances between the 100th and the 650th days of age of Maine-Anjou beef cattle. This model contained both fixed effects, random linear regression and heterogeneous variance components. The objective of this study was to analyze the difference of growth curves between animals born as twin and single bull calves. The method was based on log-linear models for residual and individual variances expressed as functions of explanatory variables. An expectation-maximization (EM) algorithm was proposed for calculating restricted maximum likelihood (REML) estimates of the residual and individual components of variances and covariances. Likelihood ratio tests were used to assess hypotheses about parameters of this model. Growth of Maine-Anjou cattle was described by a third order regression on age for a mean growth curve, two correlated random effects for the individual variability and independent errors. Three sources of heterogeneity of residual variances were detected. The difference of weight performance between bulls born as single and twin bull calves was estimated to be equal to about 15 kg for the growth period considered.

Algorithms↗
PubMedDate not supplied

Studying the relationship between change and initial value in longitudinal studies.

Blomqvist's problem of studying the relationship between change and initial value in a linear growth curve setting is reformulated from a random effects model perspective. First, a maximum likelihood estimate of the between-individual covariance matrix for a simple linear regression model with stochastic parameters is obtained via an EM algorithm as discussed by Laird and Ware. Second, the regression coefficient of the individual-specific slopes on the individual-specific intercepts is estimated as a ratio of elements of the between-individual covariance matrix as discussed by Zucker et al. Then a Fieller's type confidence interval for this ratio is proposed. Discussion is facilitated by recognizing the Laird-Ware model as a special case of a more general model discussed by Hocking.

Algorithms↗
PubMed1991

Hereditary and environmental influences on blood pressure values of premenopausal women and their college-age daughters.

Blood pressure (BP) and environmental (dietary/lifestyle) variables were measured in 62 healthy normotensive pairs of premenopausal mothers (44.3 years) and their college-age consanguineous daughters (18.7 years) to estimate the relative contributions of genetic vs environmental factors on BP. As expected, the mothers had significantly higher systolic (SBP) and diastolic (DBP) blood pressures than the daughters (p less than 0.004 and 0.012, respectively). Among the dietary/lifestyle variables measured, mothers were found to have significantly higher mean weight and body mass index (BMI) (p less than 0.009 and 0.001, respectively), and significantly lower lean body mass (LBM) and calcium intake than their daughters (p less than 0.003 and 0.037, respectively). Significant correlations were found between mean BP of the mothers and their mean weight and BMI. No significant correlations existed for the daughters. The familial resemblances between BP of the mothers and daughters were relatively low, i.e., 0.14 for SBP and 0.19 for DBP. From these findings we conclude that the higher BP values with increased age among this healthy female population primarily result from an increase in BMI and a shift from lean to fat mass, as measured by midarm circumference. Our results suggest that environmental factors, i.e., excessive energy intake over time, accompanied by decreased physical activity, are primarily responsible for the greater indices of body fat and the higher BPs observed in this sample of healthy premenopausal women.

Adipose Tissue↗
PubMed1999

The effects of cognitive and somatic anxiety and self-confidence on components of performance during competition.

This study considered the influence of competitive anxiety and self-confidence state responses upon components of performance. Basketball players (n = 12) were trained to self-report their cognitive anxiety, somatic anxiety and self-confidence as a single response on several occasions immediately before going on court to play. Performance was video-recorded and aspects of performance that could be characterized as requiring either largely anaerobic power (height jumped) or working memory (successful passes and assists) were measured. Intra-individual performance scores were computed from these measures and the data from seven matches were subjected to regression analyses and then hierarchical regression analyses. The results indicated that, as anticipated, somatic anxiety positively predicted performance that involved anaerobic demands. Self-confidence, and not cognitive anxiety, was the main predictor of performance scores with working memory demands. It would appear that different competitive state responses exert differential effects upon aspects of actual performance. Identifying these differences will be valuable in recommending intervention strategies designed to facilitate performance.

Adolescent↗
PubMed2001

Parameter estimation procedure for complex non-linear systems: calibration of ASM No. 1 for N-removal in a full-scale oxidation ditch.

When applied to large simulation models, the process of parameter estimation is also called calibration. Calibration of complex non-linear systems, such as activated sludge plants, is often not an easy task. On the one hand, manual calibration of such complex systems is usually time-consuming, and its results are often not reproducible. On the other hand, conventional automatic calibration methods are not always straightforward and often hampered by local minima problems. In this paper a new straightforward and automatic procedure, which is based on the response surface method (RSM) for selecting the best identifiable parameters, is proposed. In RSM, the process response (output) is related to the levels of the input variables in terms of a first- or second-order regression model. Usually, RSM is used to relate measured process output quantities to process conditions. However, in this paper RSM is used for selecting the dominant parameters, by evaluating parameters sensitivity in a predefined region. Good results obtained in calibration of ASM No. 1 for N-removal in a full-scale oxidation ditch proved that the proposed procedure is successful and reliable.

Automation↗
PubMedDate not supplied

Estimation by data augmentation in regression models with continuous and discrete covariates measured with error.

Estimation methods are considered for regression models which have both misclassified discrete covariates and continuous covariates measured with error. Adjusted parameter estimates are obtained using the method of data augmentation, where the true values of the covariates measured with error are regarded as missing data. Validation data on the covariates are assumed to be available. The distinction between internal and external validation data is emphasized, and its effects on the analysis are examined. The method is illustrated with simulated data.

Algorithms↗
PubMedDate not supplied

Unplanned childbearing and family size: their relationship to child neglect and abuse.

Mothers from 198 low-income, female-headed families enrolled in child protective services because of child abuse or neglect were compared with an equal number of age-matched controls, to determine if unplanned childbearing and family size increase the risk of child neglect or abuse. Logistic regression analyses suggest that unplanned childbearing increases the risk of child abuse but not of child neglect. Large family size significantly raises the risk of both types of maltreatment, although this factor had a greater effect on the risk of abuse than on the risk of neglect. Finally, unplanned childbearing appears to be indirectly related to abuse through its effect on family size.

Adult↗
PubMed1991

The impact of a health education course on maternal knowledge: a comparative study in a low socioeconomic rural region.

A comprehensive health education course was designed for mothers in West Bank villages, a relatively low socioeconomic population. The course focused on nutrition, hygiene, child development, and first aid. It was taught by specially trained local instructors in small classes characterized by an individualized teaching method. To evaluate the contribution of the course, the level of knowledge in topics taught in the course was tested. The test was personally administered by trained interviewers to 241 course participants and to a comparison group of 284 mothers who had not participated. As expected, participants demonstrated higher level of knowledge than nonparticipants, regardless of the time since having taken the course. The course seems to have contributed to all participants, but mostly to women of lower education. In a multiple linear regression the two most significant predictors of knowledge were course participation and level of maternal formal education.

Educational Status↗
PubMed1994

Selecting the best dose when a monotonic dose-response relation exists.

We propose a method for selecting the best treatment when a monotonic dose-response relationship exists. Because of side effects associated with higher doses, the highest dose may not be the optimum, particularly when a lower dose gives a similar response. Rather than assume a particular functional relationship of dose to response, we use isotonic regression techniques. We consider the case of three treatment levels, which is applicable to many clinical trials. The lowest treatment level may represent a placebo or no treatment control. While we focus primarily on Bernoulli response variables, we also discuss a model for normally distributed data. We suggest a two-stage procedure that we have investigated via simulation.

Clinical Trials, Phase II as Topic↗
PubMed1992

Transfer of DDT used in malaria control to infants via breast milk.

The transfer of p,p'-DDT (1,1,1-tricholoro-2,2-bis(4-chlorophenyl)ethane) and its metabolites to infants via breast-feeding was studied in an area of KwaZulu, South Africa, where DDT is used to interrupt malaria transmission. Samples of whole blood were collected from 23 infants, together with samples of breast milk from their respective mothers. The mean sigma DDT (total DDT) in the whole blood was 127.03 micrograms.l-1 and that in the breast milk, 15.06 mg.kg-1 (milk fat). The % DDT (% DDT of sigma DDT) was significantly higher in the infant blood than in the breast milk (P less than 0.05). A multiplicative regression analysis indicated that sigma DDT increased significantly (P less than 0.01) in infant whole blood with infant age. Multiple regression showed that 70.0% of the variation in sigma DDT was due to the variation in parity of the mother, age of the infant, and the sigma DDT in breast milk. These variables accounted also for 76.3% of the variation in p,p'-DDE but only for 38.2% of that in p,p'-DDT. Organochlorines were therefore largely transferred to the infant from the mother, with DDT in the environment playing a secondary role.

Age Factors↗
PubMed1990

Regression modelling of HLA haplotype sharing in affected siblings.

A link between the HLA system and disease susceptibility can be assessed through the observation of families containing two or more affected siblings. Departures from Mendelian inheritance of the parental haplotypes among the affected siblings are an indication of such a relationship. Other variables, such as environmental factors, may also be related to disease susceptibility. An approach to examining the degree of haplotype sharing and the effect of other variables of interest on observed sharing is presented and two examples analyzed.

Biometry↗
PubMed1991

Health perceptions and survival: do global evaluations of health status really predict mortality?

Self-evaluations of health status have been shown to predict mortality, above and beyond the contribution to prediction made by indices based on the presence of health problems, physical disability, and biological or life-style risk factors. Several possible reasons for this association are discussed: (a) methodological shortcomings of previous studies render the association spurious; (b) other psychosocial influences on mortality are involved and explain the association; and (c) self-evaluations of health status have a direct and independent effect of their own. Four-year follow-up mortality data from the Yale Health and Aging Project (N = 2812) are used to explore these possibilities. The analysis controls for the contribution of numerous indicators of health problems, disability and risk factors, and also makes adjustments of standard errors for the complex sample design. The findings favor the third possibility, an independent effect, to the extent that the particular set of psychosocial factors examined did not explain the basic association, and to the extent that the control variables were an adequately comprehensive set.

Activities of Daily Living↗
PubMed2000

Strategies for estimating the parameters needed for different test-day models.

Currently, most analyses of parameters in test-day models involve two types of models: random regression, where various functions describe variability of (co)variances with regard to days in milk, and multiple traits, where observations in adjacent days in milk are treated as one trait. The methodologies used for estimation of parameters included Bayesian via Gibbs sampling, and REML in the form of derivative-free, expectation-maximization, or average-information algorithms. The first method is simpler and uses less memory but may need many rounds to produce posterior samples. In REML, however, the stopping point is well established. Because of computing limitations, the largest estimations of parameters were on fewer than 20,000 animals. The magnitude and pattern of heritabilities varied widely, which could be caused by simplifications in the model, overparameterization, small sample size, and unrepresentative samples. Patterns of heritability differ among random regression and multiple-trait models. Accurate parameters for large multi-trait random regression models may be difficult to obtain at the present time. Parameters that are sufficiently accurate in practice may be obtained outside the complete prediction model by a constructive approach, where parameters averaged over the lactation would be combined with several typical curves for (co)variances for days in milk. Obtained parameters could be used for any model, and could also aid in comparison of models.

Analysis of Variance↗
PubMedDate not supplied

Spatial regression models for large-cohort studies linking community air pollution and health.

Cohort study designs are often used to assess the association between community-based ambient air pollution concentrations and health outcomes, such as mortality, development and prevalence of disease, and pulmonary function. Typically, a large number of subjects are enrolled in the study in each of a small number of communities. Fixed-site monitors are used to determine long-term exposure to ambient pollution. The association between community average pollution levels and health is determined after controlling for risk factors of the health outcome measured at the individual level (i.e., smoking). We present a new spatial regression model linking spatial variation in ambient air pollution to health. Health outcomes can be measured as continuous variables (pulmonary function), binary variables (prevalence of disease), or time-to-event data (survival or development of disease). The model incorporates risk factors measured at the individual level, such as smoking, and at the community level, such as air pollution. We demonstrate that the spatial autocorrelation in community health outcomes, an indication of not fully characterizing potentially confounding risk factors to the air pollution--health association, can be accounted for through the inclusion of location in the deterministic component of the model assessing the effects of air pollution on health or through a distance-decay spatial autocorrelation function in the stochastic component of the model, or both. We present a statistical approach that can be implemented for very large cohort studies. Our methods are illustrated with an analysis of the American Cancer Society cohort to determine whether the prevalence of heart disease is associated with concentrations of sulfate particles. From a statistical point of view, it appears that a location surface in the deterministic component of the model was preferred to a distance-decay autocorrelation structure in the model's stochastic component.

Air Pollution↗
PubMed1998

Exploring the combined action of lifetime alcohol intake and chronic hepatotropic virus infections on the risk of symptomatic liver cirrhosis. Collaborative Groups for the Study of Liver Diseases in Italy.

Although alcohol intake and hepatitis B and C virus (HBV and HCV) infections are the major determinants of liver cirrhosis (LC) in western countries, the joint effect of these factors on LC risk has not yet been adequately studied. Data from three case-control studies performed in Italy were used. Cases were 462 cirrhotic patients admitted to Hospitals for liver decompensation. Controls were 651 inpatients admitted for acute diseases unrelated to alcohol. Alcohol consumption was expressed as lifetime daily alcohol intake (LDAI). Three approaches were used to explore the interaction structure. The Breslow and Storer parametric family of relative risk functions showed that an intermediate structure of interaction from additive to multiplicative was the most adequate one. The Rothman synergism index showed that the interaction structure between LDAI and viral status differed significantly from the additive model in particular for high levels of alcohol intake. When multiple regression additive and multiplicative models were compared after adjustment for the known confounding variables. a trend of the interaction structure towards the multiplicative model was observed at increasing levels of consumption. Better methods are needed for assessing mixed interaction structures in conditions characterized by multifactorial etiologies like cirrhosis of the liver.

Adolescent↗