Weight loss during prolonged lactation in rural Bangladeshi mothers

To determine the duration of lactation which is associated with weight loss in rural Bangladeshi mothers and also to determine the relationship with consumption patterns of principal food items, a cross-sectional study was carried out among 791 lactating rural Bangladeshi mothers aged 18-40 years. Results were compared with 333 non-pregnant and non-lactating mothers of a similar age group. The duration of lactation was up to 60 months. The mean difference in body-weight and body mass index (BMI) of lactating mothers who breastfed their children up to 24 months was significantly lower compared to non-lactating mothers of the same age group, but no differences were observed for those who breastfed beyond 24 months. The frequency of consumption of principal food items was comparable between the non-lactating and the lactating mothers who breastfed beyond 24 months. Results of multiple linear regression analysis showed that body-weight of mothers was negatively correlated with 1-12 month(s) and 13-24 months of lactation after controlling for height, education, and food consumption (slope -1.04, p < 0.05 and slope -1.23, p < 0.05 respectively). Height and consumption of meat and milk were significantly positively correlated with body-weight (slope 0.53, p < 0.001; slope 1.44, p < 0.001; and slope 0.75, p < 0.05 respectively). The study concluded that Bangladeshi women who breastfed up to 24 months were of lower weight than non-lactating mothers, most likely due to the effect of lactation. These mothers were not taking any additional foods during their lactating period. Based on the findings of the study, it is recommended that mothers consume additional energy-rich foods during the first 24 months of lactation to prevent weight loss.

Self-reported calcium intake and bone mineral content in children and adolescents

Objective: We examined the relationship between self-reported calcium (Cal intake and bone mineral content (BMC) in children and adolescents. We hypothesized that an expression of Ca adjusted for energy intake (El), i.e., Ca density, would be a better predictor of BMC than unadjusted Ca because of underreporting of EI. Methods: Data were obtained on dietary intakes (repeated 24-hour recalls) and BMC (by DEXA) in a cross-section of 227 children aged 8 to 17 years. Bivariate and multivariate analyses were used to examine die relationship between Ca, Ca density, and the dependent variables total body BMC and lumbar spine BMC. Covariates included were height, weight, bone area, maturity age, activity score and El. Results: Reported El compared to estimated basal metabolic rate suggested underreporting of El. Total body and lumbar spine BMC were significantly associated with El, but not Ca or Ca density, in bivariate analyses. After controlling for size and maturity, multiple linear regression analysis revealed unadjusted Ca to be a predictor of BMC in males in the total body (p = 0.08) and lumbar spine (p = 0.01). Unadjusted Ca was not a predictor of BMC at either site in females. Ca density was not a better predictor of BMC at either site in males or females. Conclusions: The relationship observed in male adolescents in this study between Ca intake and BMC is similar to that seen in clinical trials. Ca density did not enable us to see a relationship between Ca intake and BMC in females, which may reflect systematic reporting errors or that diet is not a limiting factor in this group of healthy adolescents.

Determinants of exercise capacity in patients with type 2 diabetes

OBJECTIVE - Type 2 diabetes is associated with reduced exercise capacity, but the cause of this association is unclear. We sought the associations of impaired exercise capacity in type 2 diabetes. RESEARCH DESIGN AND METHODS - Subclinical left ventricular (LV) dysfunction was sought from myocardial strain rate and the basal segmental diastolic velocity (Em) of each wall in 170 patients with type 2 diabetes (aged 56 +/- 10 years, 91 men), good quality echocardiographic images, and negative exercise echocardiograms. The same measurements were made in 56 control subjects (aged 53 +/- 10 years, 29 men). Exercise capacity was calculated in metabolic equivalents, and heart rate recovery (HRR) was measured as the heart rate difference between peak and 1 min after exercise. In subjects with type 2 diabetes, exercise capacity was correlated with clinical, therapeutic, biochemical, and echocardiographic variables, and significant independent associations were sought using a multiple linear regression model. RESULTS - Exercise capacity, strain rate, Em, and HRR were significantly reduced in type 2 diabetes. Exercise capacity was associated with age (r- = -0.37, P < 0.001), male sex (r = 0.26, P = 0.001), BMI (r = -0.19, P = 0.012), HbA(1c) (AlC; r = -0.22, P = 0.009), Em (r = 0.43, P < 0.001), HRR (r = 0.42, P < 0.001), diabetes duration (r = -0.18, P = 0.021), and hypertension history (r = -0.28, P < 0.001). Age (P < 0.001), male sex (P = 0.007), BMI (P = 0.001), Em (P = 0.032), HRR (P = 0.013), and AlC (P = 0.0007) were independent predictors of exercise capacity. CONCLUSIONS - Reduced exercise capacity in patients with type 2 diabetes is associated with diabetes control, subclinical LV dysfunction, and impaired HRR.

Predicting the solvent accessibility of transmembrane residues from protein sequence

In this study, we propose a novel method to predict the solvent accessible surface areas of transmembrane residues. For both transmembrane alpha-helix and beta-barrel residues, the correlation coefficients between the predicted and observed accessible surface areas are around 0.65. On the basis of predicted accessible surface areas, residues exposed to the lipid environment or buried inside a protein can be identified by using certain cutoff thresholds. We have extensively examined our approach based on different definitions of accessible surface areas and a variety of sets of control parameters. Given that experimentally determining the structures of membrane proteins is very difficult and membrane proteins are actually abundant in nature, our approach is useful for theoretically modeling membrane protein tertiary structures, particularly for modeling the assembly of transmembrane domains. This approach can be used to annotate the membrane proteins in proteomes to provide extra structural and functional information.

Whose socioeconomic status influences a woman's obesity risk: her mother's, her father's, or her own?

Background Evidence on the relative influence of childhood vs adulthood socioeconomic conditions on obesity risk is limited and equivocal. The objective of this study was to investigate associations of several indicators of mothers', fathers', and own socioeconomic status, and intergenerational social mobility, with body mass index (BMI) and weight change in young women. Methods This population-based cohort study used survey data provided by 8756 women in the young cohort (aged 18-23 years at baseline) of the Australian Longitudinal Study on Women's Health. In 1996 and 2000, women completed mailed surveys in which they reported their height and weight, and their own, mother's, and father's education and occupation. Results Multiple linear regression models showed that both childhood and adulthood socioeconomic status were associated with women's BMI and weight change, generally in the hypothesized (inverse) direction, but the associations varied according to socioeconomic status and weight indicator. Social mobility was associated with BMI (based on father's socioeconomic status) and weight change (based on mother's socioeconomic status), but results were slightly less consistent. Conclusions Results suggest lasting effects of childhood socioeconomic status on young women's weight status, independent of adult socioeconomic status, although the effect may be attenuated among those who are upwardly socially mobile. While the mechanisms underlying these associations require further investigation, public health strategies aimed at preventing obesity may need to target families of low socioeconomic status early in children's lives.

Predicting sprint running times from isokinetic and squat lift tests: A regression analysis

This study examined the relationship between isokinetic hip extensor/hip flexor strength, 1-RM squat strength, and sprint running performance for both a sprint-trained and non-sprint-trained group. Eleven male sprinters and 8 male controls volunteered for the study. On the same day subjects ran 20-m sprints from both a stationary start and with a 50-m acceleration distance, completed isokinetic hip extension/flexion exercises at 1.05, 4.74, and 8.42 rad.s(-1), and had their squat strength estimated. Stepwise multiple regression analysis showed that equations for predicting both 20-m maximum velocity nm time and 20-m acceleration time may be calculated with an error of less than 0.05 sec using only isokinetic and squat strength data. However, a single regression equation for predicting both 20-m acceleration and maximum velocity run times from isokinetic or squat tests was not found. The regression analysis indicated that hip flexor strength at all test velocities was a better predictor of sprint running performance than hip extensor strength.

Epidermal iontophoresis: II. Application of the ionic mobility-pore model to the transport of local anesthetics

Purpose, An in vitro study was carried out to determine the iontophoretic permeability of local anesthetics through human epidermis. The relationship between physicochemical structure and the permeability of these solutes was then examined using an ionic mobility-pore model developed to define quantitative relationships. Methods. The iontophoretic permeability of both ester-type anesthetics (procaine, butacaine, tetracaine) and amide-type anesthetics (prilocaine, mepivacaine, lidocaine, bupivacaine, etidocaine, cinchocaine) were determined through excised human epidermis over 2 hrs using a constant d.c. current and Ag/AgCl electrodes. Individual ion mobilities were determined from conductivity measurements in aqueous solutions. Multiple stepwise regression was applied to interrelate the iontophoretic permeability of the solutes with their physical properties to examine the appropriateness of the ionic mobility-pore model and to determine the best predictor of iontophoretic permeability of the local anesthetics. Results. The logarithm of the iontophoretic permeability coefficient (log PCj,iont) for local anesthetics was directly related to the log ionic mobility and MW for the free volume form of the model when other conditions are held constant. Multiple linear regressions confirmed that log PCj,iont was best defined by ionic mobility (and its determinants: conductivity, pK(a) and MW) and MW. Conclusions. Our results suggest that of the properties studied, the best predictors of iontophoretic transport of local anesthetics are ionic mobility (or pK(a)) and molecular size. These predictions are consistent with the ionic mobility pore model determined by the mobility of ions in the aqueous solution, the total current, epidermal permselectivity and other factors as defined by the model.

Interindividual Differences in Leg Muscle Mass and Pyruvate Kinase Activity Correlate with Interindividual Differences in Jumping Performance of Hyla multilineata

Frog jumping is an excellent model system for examining the structural basis of interindividual variation in burst locomotor performance. Some possible factors that affect jump performance, such as total body size, hindlimb length, muscle mass, and muscle mechanical and biochemical properties, were analysed at the interindividual (intraspecies) level in the tree frog Hyla multilineata. The aim of this study was to determine which of these physiological and anatomical variables both vary between individuals and are correlated with interindividual variation in jump performance. The model produced via stepwise linear regression analysis of absolute data suggested that 62% of the interindividual variation in maximum jump distance could be explained by a combination of interindividual variation in absolute plantaris muscle mass, total hindlimb muscle mass ( excluding plantaris muscle), and pyruvate kinase activity. When body length effects were removed, multiple regression indicated that the same independent variables explained 43% of the residual interindividual variation in jump distance. This suggests that individuals with relatively large jumping muscles and high pyruvate kinase activity for their body size achieved comparatively large maximal jump distances for their body size.

Predicting residue-wise contact orders in proteins by support vector regression

Background: The residue-wise contact order (RWCO) describes the sequence separations between the residues of interest and its contacting residues in a protein sequence. It is a new kind of one-dimensional protein structure that represents the extent of long-range contacts and is considered as a generalization of contact order. Together with secondary structure, accessible surface area, the B factor, and contact number, RWCO provides comprehensive and indispensable important information to reconstructing the protein three-dimensional structure from a set of one-dimensional structural properties. Accurately predicting RWCO values could have many important applications in protein three-dimensional structure prediction and protein folding rate prediction, and give deep insights into protein sequence-structure relationships. Results: We developed a novel approach to predict residue-wise contact order values in proteins based on support vector regression (SVR), starting from primary amino acid sequences. We explored seven different sequence encoding schemes to examine their effects on the prediction performance, including local sequence in the form of PSI-BLAST profiles, local sequence plus amino acid composition, local sequence plus molecular weight, local sequence plus secondary structure predicted by PSIPRED, local sequence plus molecular weight and amino acid composition, local sequence plus molecular weight and predicted secondary structure, and local sequence plus molecular weight, amino acid composition and predicted secondary structure. When using local sequences with multiple sequence alignments in the form of PSI-BLAST profiles, we could predict the RWCO distribution with a Pearson correlation coefficient (CC) between the predicted and observed RWCO values of 0.55, and root mean square error (RMSE) of 0.82, based on a well-defined dataset with 680 protein sequences. Moreover, by incorporating global features such as molecular weight and amino acid composition we could further improve the prediction performance with the CC to 0.57 and an RMSE of 0.79. In addition, combining the predicted secondary structure by PSIPRED was found to significantly improve the prediction performance and could yield the best prediction accuracy with a CC of 0.60 and RMSE of 0.78, which provided at least comparable performance compared with the other existing methods. Conclusion: The SVR method shows a prediction performance competitive with or at least comparable to the previously developed linear regression-based methods for predicting RWCO values. In contrast to support vector classification (SVC), SVR is very good at estimating the raw value profiles of the samples. The successful application of the SVR approach in this study reinforces the fact that support vector regression is a powerful tool in extracting the protein sequence-structure relationship and in estimating the protein structural profiles from amino acid sequences.

Likelihood-based estimation of the regression model with scrambled responses

A significant problem in the collection of responses to potentially sensitive questions, such as relating to illegal, immoral or embarrassing activities, is non-sampling error due to refusal to respond or false responses. Eichhorn & Hayre (1983) suggested the use of scrambled responses to reduce this form of bias. This paper considers a linear regression model in which the dependent variable is unobserved but for which the sum or product with a scrambling random variable of known distribution, is known. The performance of two likelihood-based estimators is investigated, namely of a Bayesian estimator achieved through a Markov chain Monte Carlo (MCMC) sampling scheme, and a classical maximum-likelihood estimator. These two estimators and an estimator suggested by Singh, Joarder & King (1996) are compared. Monte Carlo results show that the Bayesian estimator outperforms the classical estimators in almost all cases, and the relative performance of the Bayesian estimator improves as the responses become more scrambled.

Regional and total body bone mineral density in elite collegiate male swimmers

Back,ground To examine the role of long-term swimming exercise on regional and total body bone mineral density (BMD) in men. Methods. Experimental design: Cross-sectional. Setting: Musculoskeletal research laboratory at a medical center, Participants:We compared elite collegiate swimmers (n=11) to age-, weight-, and height-matched non-athletic controls (n=11), Measures: BMD (g/cm(2)) of the lumbar spine L2-4, proximal femur (femoral neck, trochanter, Ward's triangle), total body and various subregions of the total body, as well as regional and total body fat and bone mineral-free lean mass (LM) was assessed by dual-energy X-ray absorptiometry (DXA, Hologic QDR 1000/W). Results. Swimmers, who commenced training at 10.7+/-3.7 yrs (mean+/-SD) and trained for 24.7+/-4.2 hrs per week, had a greater amount of LM (p<0.05), lower fat mass (p<0.001) and percent body fat (9.5 vs 16.2 %, p<0.001) than controls. There was no significant difference between groups for regional or total body BRID, In stepwise multiple regression analysis, body weight was a consistent independent predictor of regional and total body BMD, Conclusions. These results suggest that long-term swimming is not an osteogenic mode of training in college-aged males. This supports our previous findings in young female swimmers who displayed no bone mass benefits despite long-standing athletic training.

Bridging the gap between different statistical approaches: An integrated framework for modelling

This paper proposes a template for modelling complex datasets that integrates traditional statistical modelling approaches with more recent advances in statistics and modelling through an exploratory framework. Our approach builds on the well-known and long standing traditional idea of 'good practice in statistics' by establishing a comprehensive framework for modelling that focuses on exploration, prediction, interpretation and reliability assessment, a relatively new idea that allows individual assessment of predictions. The integrated framework we present comprises two stages. The first involves the use of exploratory methods to help visually understand the data and identify a parsimonious set of explanatory variables. The second encompasses a two step modelling process, where the use of non-parametric methods such as decision trees and generalized additive models are promoted to identify important variables and their modelling relationship with the response before a final predictive model is considered. We focus on fitting the predictive model using parametric, non-parametric and Bayesian approaches. This paper is motivated by a medical problem where interest focuses on developing a risk stratification system for morbidity of 1,710 cardiac patients given a suite of demographic, clinical and preoperative variables. Although the methods we use are applied specifically to this case study, these methods can be applied across any field, irrespective of the type of response.

Effects of rock properties on specific cutting energy in linear cutting of sandstones by picks

Specific cutting energy (SE) has been widely used to assess the rock cuttability for mechanical excavation purposes. Some prediction models were developed for SE through correlating rock properties with SE values. However, some of the textural and compositional rock parameters i.e. texture coefficient and feldspar, mafic, and felsic mineral contents were not considered. The present study is to investigate the effects of previously ignored rock parameters along with engineering rock properties on SE. Mineralogical and petrographic analyses, rock mechanics, and linear rock cutting tests were performed on sandstone samples taken from sites around Ankara, Turkey. Relationships between SE and rock properties were evaluated using bivariate correlation and linear regression analyses. The tests and subsequent analyses revealed that the texture coefficient and feldspar content of sandstones affected rock cuttability, evidenced by significant correlations between these parameters and SE at a 90% confidence level. Felsic and mafic mineral contents of sandstones did not exhibit any statistically significant correlation against SE. Cementation coefficient, effective porosity, and pore volume had good correlations against SE. Poisson's ratio, Brazilian tensile strength, Shore scleroscope hardness, Schmidt hammer hardness, dry density, and point load strength index showed very strong linear correlations against SE at confidence levels of 95% and above, all of which were also found suitable to be used in predicting SE individually, depending on the results of regression analysis, ANOVA, Student's t-tests, and R2 values. Poisson's ratio exhibited the highest correlation with SE and seemed to be the most reliable SE prediction tool in sandstones.

Effects of rock properties on specific cutting energy in linear cutting of sandstones by picks

Specific cutting energy (SE) has been widely used to assess the rock cuttability for mechanical excavation purposes. Some prediction models were developed for SE through correlating rock properties with SE values. However, some of the textural and compositional rock parameters i.e. texture coefficient and feldspar, mafic, and felsic mineral contents were not considered. The present study is to investigate the effects of previously ignored rock parameters along with engineering rock properties on SE. Mineralogical and petrographic analyses, rock mechanics, and linear rock cutting tests were performed on sandstone samples taken from sites around Ankara, Turkey. Relationships between SE and rock properties were evaluated using bivariate correlation and linear regression analyses. The tests and subsequent analyses revealed that the texture coefficient and feldspar content of sandstones affected rock cuttability, evidenced by significant correlations between these parameters and SE at a 90% confidence level. Felsic and mafic mineral contents of sandstones did not exhibit any statistically significant correlation against SE. Cementation coefficient, effective porosity, and pore volume had good correlations against SE. Poisson's ratio, Brazilian tensile strength, Shore scleroscope hardness, Schmidt hammer hardness, dry density, and point load strength index showed very strong linear correlations against SE at confidence levels of 95% and above, all of which were also found suitable to be used in predicting SE individually, depending on the results of regression analysis, ANOVA, Student's t-tests, and R-2 values. Poisson's ratio exhibited the highest correlation with SE and seemed to be the most reliable SE prediction tool in sandstones.

Dependence of public support for survival of wildlife species on their likeability

We surveyed a sample of 204 individuals selected from the public in Brisbane, Australia, to ascertain the extent to which they like or dislike 24 species of wildlife present in tropical Australia. The species belong to three classes: mammals, birds and reptiles. We calculated likeability indices for each of these species. We also asked respondents if they favoured the survival of each of these species and so the percentage of respondents favouring survival of each of these species could be calculated. Thus, using linear regression analysis, the percentage of respondents favouring survival of each of the species was related to their indices of likeability. In addition, the data enables the average likeability of species in the three classes (mammals, birds and reptiles) to be compared with the average support for survival of species in each of these three classes. As a result, we are able to assess how important stated likeability seems to be for preferences for survival of species, and to reconsider the hypothesis in the literature that there is likely to be more public support for the survival of mammals than for birds than for reptiles.