Biomedical subjects

D B Allison

Publications and source records attributed to D B Allison.

At least 109 records · Page 6Linked to original sources

PubMed1998

Body mass index as a measure of adiposity among children and adolescents: a validation study.

OBJECTIVES: To test the hypothesis that in a healthy pediatric population body mass index (BMI) (kilograms per meter square) is a valid measure of fatness that is independent of age for both sexes. METHODS: Total body fat (TBF) (in kilograms) and percent of body weight as fat (PBF) were estimated by dual energy x-ray absorptiometry (DXA) in 198 healthy Italian children and adolescents between 5 and 19 years of age. We developed multiple regression analysis models with TBF and percent body fat as dependent variables and BMI, age, and interaction terms as independent variables. Separate analyses were conducted for boys and girls. RESULTS: BMI was strongly associated with TBF (R2 = 0.85 and 0.89 for boys and girls, respectively) and PBF (R2 =0.63 and 0.69 for boys and girls, respectively). Confidence limits on BMI-fatness association were wide, with individuals of similar BMI showing large differences in TBF and in PBF. Age was a significant covariate in all regression models. Addition of nonlinear terms for BMI did not substantially increase the R2 for TBF and PBF models in boys and girls. CONCLUSION: Our results support the use of BMI as a fatness measure in groups of children and adolescents, although interpretation should be cautious when comparing BMI across groups that differ in age or when predicting a specific individual's TBF or PBF.

Absorptiometry, Photon↗

PubMed1998

Meta-analysis of the association of the Trp64Arg polymorphism in the beta3 adrenergic receptor with body mass index.

OBJECTIVE: As a result of efforts to isolate obesity-promoting genes, the Trp64Arg polymorphism in the beta3 adrenergic receptor locus, has been studied by many investigators. Results of the studies have varied in statistical significance and magnitude of the association of the polymorphism with body mass index (BMI: kg/m2). This has led to controversy about whether this polymorphism is associated with meaningful changes in BMI. To clarify the possible association, we conducted a meta-analysis. DESIGN: Meta-analytic study. MEASUREMENTS: For each genotype of the beta3 adrenergic receptor (Trp/Trp; Trp/Arg; Arg/Arg), we extracted the number of subjects, mean and standard deviation of BMI from 23 studies, including 36 different subgroups with a total of 7399 subjects. Other indices and obesity-related variables were not considered. RESULTS: No significant association of the Trp64Arg polymorphism with BMI was found. The weighted mean BMI difference between Trp/Trp homozygotes and Trp/Arg heterozygotes was 0.19 (s.e. = 0.11; P = 0.07). In addition, the distribution of effect sizes was not significantly heterogeneous (chi2=38.68; df 35; P = 0.31) suggesting that the variation of the effect sizes across the subgroups is not significant. A further weighted regression analysis, utilizing all three genotypes and adjusting for the random subgroup effect, also showed the effect of the polymorphism on BMI is not significant (F = 1.72, df = (2,54), P = 0.19). CONCLUSION: Based on existing data, the Trp64Arg polymorphism does not appear to be significantly associated with BMI. Moreover, we found no evidence for effect heterogeneity, suggesting that the effect of the polymorphism is not moderated by ethnicity or diabetic status.

Arginine↗

PubMed1998

Multiple phenotype modeling in gene-mapping studies of quantitative traits: power advantages.

Genomewide searches for loci influencing complex human traits and diseases such as diabetes, hypertension, and obesity are often plagued by low power and interpretive difficulties. Attempts to remedy these difficulties have typically relied on, and have promoted the use of, novel subject-ascertainment schemes, larger sample sizes, a greater density of DNA markers, and more-sophisticated statistical modeling and analysis strategies. Many of these remedies can be costly to implement. We investigate the utility of a simple statistical model for the mapping of quantitative-trait loci that incorporates multiple phenotypic or diagnostic endpoints into a gene-mapping analysis. The approach considers finding a linear combination of multiple phenotypic values that maximizes the evidence for linkage to a locus. Our results suggest that substantial increases in the power to map loci can be obtained with the proposed technique, although the increase in power obtained is a function of the size and direction of the residual correlation among the phenotypes used in the analysis. Extensive simulation studies are described that justify these claims, for cases in which two phenotypic measures are analyzed. This approach can be easily extended to cover more-complex situations and may provide a basis for more insightful genetic-analysis paradigms.

Chromosome Mapping↗

PubMed1998

Estimating African American admixture proportions by use of population-specific alleles.

We analyzed the European genetic contribution to 10 populations of African descent in the United States (Maywood, Illinois; Detroit; New York; Philadelphia; Pittsburgh; Baltimore; Charleston, South Carolina; New Orleans; and Houston) and in Jamaica, using nine autosomal DNA markers. These markers either are population-specific or show frequency differences >45% between the parental populations and are thus especially informative for admixture. European genetic ancestry ranged from 6.8% (Jamaica) to 22.5% (New Orleans). The unique utility of these markers is reflected in the low variance associated with these admixture estimates (SEM 1.3%-2.7%). We also estimated the male and female European contribution to African Americans, on the basis of informative mtDNA (haplogroups H and L) and Y Alu polymorphic markers. Results indicate a sex-biased gene flow from Europeans, the male contribution being substantially greater than the female contribution. mtDNA haplogroups analysis shows no evidence of a significant maternal Amerindian contribution to any of the 10 populations. We detected significant nonrandom association between two markers located 22 cM apart (FY-null and AT3), most likely due to admixture linkage disequilibrium created in the interbreeding of the two parental populations. The strength of this association and the substantial genetic distance between FY and AT3 emphasize the importance of admixed populations as a useful resource for mapping traits with different prevalence in two parental populations.

Africa↗

PubMed1998

Body mass index, smoking, and mortality among older American women.

The relationship among body mass index (BMI, kg/m2), smoking status, and overall mortality remains controversial. To assess this relationship in a representative sample of older women, we used data from the Panel Study of Income Dynamics (PSID). The PSID (begun in 1968) is a prospective longitudinal cohort study designed to examine economic and demographic behavior. Respondents were 1355 women age > or = 50 when they initially completed the Self-Administered Health Questionnaire in 1990. Data collected included self-reported height and weight, years of completed education, smoking status (never versus ever), and responses to four health-related questions (e.g., retired due to ill health, difficulty eating). Respondents were followed, including the date of death if respondent died, through 1994. Cox proportional hazard regression revealed a U-shaped relationship irrespective of whether smoking was included in the model. The base of the curve was fairly wide, suggesting that a broad range of BMI is well tolerated by older women. The minimum mortality (estimated from fitted proportional hazard models) for both the smoking and nonsmoking models occurred at a BMI of approximately 34. When interactions between smoking status and BMI terms were added to the model, the interactions were not jointly significant (p = 0.071). Moreover an exploratory plot of the BMI-mortality curve among never smokers (n = 800) revealed a curve that moved away from being U-shaped toward being more monotonically decreasing. It is concluded that these data suggest that there is no evidence that the U-shaped BMI-mortality relationship observed is caused by confounding by smoking status.

Aged↗

PubMed1998

Meta-analysis of linkage data under worst-case conditions: a demonstration using the human OB region.

To date, few methods have been developed explicitly for meta-analysis of linkage analyses. Moreover, the methods that have been developed or suggested generally depend on certain ideal situations and have not been widely applied. In this article, we apply standard statistical theory and meta-analytic techniques in novel ways to five published papers discussing the evidence of linkage of body mass index (BMI) to the region of the human genome containing the OB gene. These methods are "inference based," meaning that they allow one to make statements about the statistical significance of the entire body of evidence. As currently developed, they do not allow specific statements to be made about the amount of variance explained by any putative locus or allow precise confidence intervals to be placed around the putative location of a linked locus. By applying these techniques to the literature on linkage in the human OB gene region, we are able to show that the evidence for linkage somewhere in the region is extremely strong (P = 1.5 x 10[-5]).

Body Mass Index↗

PubMed1997

Examination of "early mortality exclusion" as an approach to control for confounding by occult disease in epidemiologic studies of mortality risk factors.

Methods for the estimation of the effects of chronic disease risk factors on mortality continue to be an area that generates confusion and controversy. In response to the frequently observed U- or J-shaped relations between risk factors and mortality, some authors suggest that subjects dying during the first k years of follow-up (where k is some positive number less than the total length of follow-up) be excluded from statistical analyses. By excluded, the authors mean completely removed from the data set. The rationale is that persons dying during the first k years are likely to have a preexisting occult disease that confounds the relation between the risk factor under study and mortality. Excluding persons dying during the first k years of follow-up purportedly reduces this confounding. However, the authors are aware of no demonstration that this procedure effectively accomplishes its goal. They show that excluding subjects who die during the first k years of follow-up does not necessarily lead to a reduction in bias in the estimated effect of a risk factor on mortality when this relation is confounded by the presence of occult disease. Moreover, it is possible for such exclusion to exacerbate the confounding due to preexisting disease. Thus, excluding subjects dying during the first k years of follow-up is not necessarily an effective strategy for dealing with confounding due to occult disease. Investigators are encouraged to pursue alternative methods.

Confounding Factors, Epidemiologic↗

PubMed1997

Hypothesis concerning the U-shaped relation between body mass index and mortality.

Numerous studies have documented a U- or J-shaped association between body mass index (BMI) (kg/m2) and mortality, such that increased mortality rate is associated with relatively low and high BMI values. It has been argued elsewhere that the elevated mortality rate observed at lower BMI values actually results from the effects of unmeasured confounding variables, in particular smoking status and preexisting disease. In this paper, the authors present an additional explanation for the phenomenon, i.e., nonspecific measurement. They propose that differential health consequences of fat mass and fat-free mass can be masked by the use of BMI when studied in relation to mortality. To illustrate this point, they use body composition data from 1,137 healthy adults and specify a hypothetical underlying BMI-mortality model in which the logit of death increased linearly with fat mass and decreased linearly with fat-free mass, and % fat increased monotonically with BMI. The results indicate that, even under these specifications, the authors can recover a U-shaped association between BMI and mortality. Consistent with previous suggestions in the literature, future epidemiologic studies that examine the association between adiposity and mortality should prioritize the use of body composition measures.

Adolescent↗

PubMed1997

Putting the behavior into the behavior genetics of obesity.

Tremendous advances in the genetic underpinnings of obesity have emerged in recent years. Curiously, behavioral genetic methods have provided relatively less information on the environmental influences and intermediary behaviors which promote human obesity. This situation in unfortunate since human obesity is, in part, environmentally determined and the result of behaviors such as eating and physical (in)activity. This article has several goals. First, it outlines reasons why behavior qua behavior should be a specific focus of obesity-oriented behavioral genetic designs. Second, possible explanations for why behavior has been underinvestigated are explored. Third, data regarding the genetic/ environmental architecture of various obesity-related phenotypes (e.g., food intake, physical activity, etc.) are reviewed. Fourth, a commentary on the importance of gene-environment interactions is offered. Finally, suggestions for future research, including a list of possible "candidate environments" and "candidate intermediary behaviors," are offered.

Adolescent↗

PubMed1997

A proposed heuristic for communicating heritability estimates to the general public, with obesity as an example.

It is well established that many continuously distributed traits have a heritable component. However, it is often difficult to communicate to the general public the meaning of quantitative estimates of heritability. To address this problem, the present paper introduces a heuristic for communicating heritability to nonscientific audiences. This heuristic involves adopting an extremely simplified model of inheritance and artificially (and somewhat arbitrarily) defining a cutoffs of "low environmental risk" and "affectation status." Using body weight and obesity as an example, we present a table which gives estimates of the proportion of obese persons who are "genetically obese" assuming varying levels of "environmental risk" for obesity and relative body weight scores for defining obesity. The resulting statistic may prove useful for lay audiences in understanding a heritability estimate.

Body Mass Index↗

PubMed1997

Selected methodological issues in meiotic mapping of obesity genes in humans: issues of power and efficiency.

This paper focuses on methods for mapping novel obesity genes in humans via meiotic mapping techniques. By novel we mean genes that are as yet unidentified as playing a role in obesity. We begin by presenting a discussion of why we believe it is important to seek out novel obesity genes and, in particular, novel genes of small effect. In light of the arguably Herculean task of finding genes of small effect with conventional gene mapping methods, we discuss alternative methods and procedures that may enhance our ability to map novel obesity genes of small effect. Many of these methods have been discussed previously in the literature and are summarized here. These include reconceptualizing power in the context of genomewide scans, multivariate linkage approaches, the use of phenotypically extreme subjects, and the use of large sibships. These are discussed in the context of linkage studies. Association studies and disequilibrium mapping are also discussed, and again, issues involving the use of extreme phenotypes and multiple testing are included. We also provide a brief discussion of DNA pooling and transmission disequilibrium tests for quantitative traits. Finally, we advocate data pooling techniques (e.g., meta-analysis) to enhance the power and efficiency of the entire field of the genetics of obesity.

Chromosome Mapping↗

PubMed1997

Body mass index and all-cause mortality among people age 70 and over: the Longitudinal Study of Aging.

OBJECTIVES: To assess the relationship between body mass index (BMI; kg/m2) and mortality in a large nationally representative sample of US adults over age 70 years. DESIGN: Prospective longitudinal cohort study, the Longitudinal Study of Aging (LSOA). Subjects were all those 7260 black and white people (2769 men, 4491 women) initially interviewed in 1984 for whom height and weight were available. These subjects were followed through to 1990. MEASUREMENTS: Measurements included self-reported height and weight, date of death if subjects died, sex, age, race, measures of socio-economic status, number of living first degree relatives, and responses to questions asking whether the subject had retired due to poor health, had difficulty eating, worried about their health, and felt their health was worse than during the prior year. Smoking status was not assessed. RESULTS: When analyzed via Cox proportional hazard regression, the relationship between BMI and mortality, represented by means of hazard ratio, was clearly U-shaped for both men and women. The base of the curves was fairly wide suggesting that a broad range of BMIs are well tolerated by older adults. The minimum mortality (estimated from the fitted proportional hazard models) occurred at a BMI of approximately 31.7 for women and 28.8 for men. The results were essentially unchanged, if analyses were weighted, if various disease states were controlled for, and if apparently unhealthy subjects were excluded. CONCLUSIONS: The finding of the relatively high BMI (27-30 for men, 30-35 for women) associated with minimum hazard in persons older than seventy years supports some previously documented findings and opposes others and, if confirmed in future research, has implications for public health and clinical recommendations.

Aged↗

PubMed1997

Predicting treatment attendance and weight loss: assessing the psychometric properties and predictive validity of the Dieting Readiness Test.

The Dieting Readiness Test (DRT) has been recommended by the Institute of Medicine as a measure of diet and exercise-related motivation and attitudes in those about to embark on a weight loss program. However, little research is available regarding the psychometric properties of this instrument. We conducted a study to assess the psychometric properties and predictive validity of the DRT. A group of 410 obese adults seeking outpatient treatment at a university-based weight management center completed the DRT prior to engaging in a comprehensive medically monitored program. Principal-components factor analysis indicated a five-factor solution and acceptable internal consistency for the resulting scales. The Bingeing and Eating cues scale was negatively associated with program attendance. None of the four remaining scales correlated with either attendance or weight loss. We conclude that although the DRT possesses a stable and interpretable structure and adequate internal consistency, it does not appear to be a strong predictor of weight loss or treatment attendance.

Adult↗

PubMed1997

Transmission-disequilibrium tests for quantitative traits.

The transmission-disequilibrium test (TDT) of Spielman et al. is a family-based linkage-disequilibrium test that offers a powerful way to test for linkage between alleles and phenotypes that is either causal (i.e., the marker locus is the disease/trait allele) or due to linkage disequilibrium. The TDT is equivalent to a randomized experiment and, therefore, is resistant to confounding. When the marker is extremely close to the disease locus or is the disease locus itself, tests such as the TDT can be far more powerful than conventional linkage tests. To date, the TDT and most other family-based association tests have been applied only to dichotomous traits. This paper develops five TDT-type tests for use with quantitative traits. These tests accommodate either unselected sampling or sampling based on selection of phenotypically extreme offspring. Power calculations are provided and show that, when a candidate gene is available (1) these TDT-type tests are at least an order of magnitude more efficient than two common sib-pair tests of linkage; (2) extreme sampling results in substantial increases in power; and (3) if the most extreme 20% of the phenotypic distribution is selectively sampled, across a wide variety of plausible genetic models, quantitative-trait loci explaining as little as 5% of the phenotypic variation can be detected at the .0001 alpha level with <300 observations.

Genetic Markers↗

PubMed1997

Issues in mapping genes for eating disorders.

Recent twin studies show that both genetic and environmental factors contribute to the development of eating disorders. As in many other fields, there is much enthusiasm regarding the possibility of locating the specific genes that influence the risk of eating disorders. Advances in molecular and statistical technology have made this task more feasible than it was in the past, and continued enhancements in new technology are expected in the future. Despite these advances, the resources required to map a gene for traits as complex as eating disorders are likely to be enormous. Researchers considering such an undertaking may wish to look for ways to reduce this demand, such as (1) using multivariate analyses, (2) studying intermediate quantitative phenotypes, (3) using large sibships, (4) analytic enhancements (e.g., multipoint analyses), (5) reconceptualizing power, (6) data pooling, and (7) disequilibrium mapping.

Chromosome Mapping↗

PubMed1996

Assortative mating for relative weight: genetic implications.

Most work on the genetics of relative weight has not considered the role of assortative mating, i.e., mate selection based on similarity between mates. We investigated the extent to which engaged men and women in an archival longitudinal database were similar to each other in relative body weight prior to marriage and cohabitation. After controlling for age, a small but statistically significant mate correlation was found for relative weight (r=.13, p=.023), indicating some assortative mating. Furthermore, we examined whether mate similarity in relative weight prior to marriage predicts survival of the marriage. No significant effects were found. In sum, these results are consistent with those of other studies in suggesting that there is a small but significant intermate correlation for relative weight. However, they are unique in showing that these results cannot be explained on the basis of (a) cohabitation, (b) age similarity, or (c) selective survival of marriages between couples more similar in relative weight. The implications of these findings for heritability studies, linkage studies, and the estimation of shared environmental effects are discussed.

Adult↗

PubMed1996

Hypnosis as an adjunct to cognitive-behavioral psychotherapy for obesity: a meta-analytic reappraisal.

I. Kirsch, G. Montgomery, and G. Sapirstein (1995) meta-analyzed 6 weight-loss studies comparing the efficacy of cognitive-behavior therapy (CBT) alone to CBT plus hypnotherapy and concluded that "the addition of hypnosis substantially enhanced treatment outcome" (p.214). Kirsch reported a mean effect size (expressed as d) of 1.96. After correcting several transcription and computational inaccuracies in the original meta-analysis, these 6 studies yield a smaller mean effect size (.26). Moreover, if 1 questionable study is removed from the analysis, the effect sizes become more homogeneous and the mean (.21) is no longer statistically significant. It is concluded that the addition of hypnosis to CBT for weight loss results in, at most, a small enhancement of treatment outcome.

Cognitive Behavioral Therapy↗

PubMed1996

Mixture distributions in human genetics research.

The use of mixture distributions in genetics research dates back to at least the late 1800s when Karl Pearson applied them in an analysis of crab morphometry. Pearson's use of normal mixture distributions to model the mixing of different species of crab (or 'families' of crab as he referred to them) within a defined geographic area motivated further use of mixture distributions in genetics research settings, and ultimately led to their development and recognition as intuitive modelling devices for the effects of underlying genes on quantitative phenotypic (i.e. trait) expression. In addition, mixture distributions are now used routinely to model or accommodate the genetic heterogeneity thought to underlie many human diseases. Specific applications of mixture distribution models in contemporary human genetics research are, in fact, too numerous to count. Despite this long, consistent and arguably illustrious history of use, little mention of mixture distributions in genetics research is made in many recent reviews on mixture models. This review attempts to rectify this by providing insight into the role that mixture distributions play in contemporary human genetics research. Tables providing examples from the literature that describe applications of mixture models in human genetics research are offered as a way of acquainting the interested reader with relevant studies. In addition, some of the more problematic aspects of the use of mixture models in genetics research are outlined and addressed.

Genetic Heterogeneity↗