Effects of contingent television on physical activity and television viewing in obese children

OBJECTIVE

Elevated television (TV) viewing and physical inactivity promote obesity in children. Thus, changes in physical activity and sedentary behavior seem critical to treating childhood obesity. PRESENT STUDY: Using a randomized, 2-arm design, this pilot study tested the effects of contingent TV on physical activity and TV viewing in 10 obese children. TV viewing was contingent on pedaling a stationary cycle ergometer for experimental participants but was not contingent on pedaling for control participants. The study was conducted over 12 weeks, including a 2-week baseline period.

RESULTS

Multivariate analyses indicated that the intervention significantly increased pedaling and reduced TV-viewing time. During the treatment phase, the experimental group pedaled 64.4 minutes per week on average, compared with 8.3 minutes by controls. The experimental group watched 1.6 hours of TV per week on average, compared with 21.0 hours per week on average by controls during this phase. Secondary analyses indicated that the experimental group showed significantly greater reductions in total body fat and percent leg fat. Total pedaling time during intervention correlated with greater reductions in percent body fat (r = -0.68).

CONCLUSIONS

Contingencies in the home environment can be arranged to modify physical activity and TV viewing and may have a role in treating childhood obesity. Contingent TV may be one method to help achieve this goal.

Estimating the consequences of anti-psychotic induced weight gain on health and mortality rate

Many anti-psychotic medications produce marked weight gain. In this study, we estimate the expected impact of degrees of antipsychotic-induced weight gain on selected mortality rate and incidence rates of impaired glucose tolerance (IGT) and hypertension (HTN) among US adults. Using raw data from 5209 respondents from the Framingham Heart Study's public use data set and national statistics on population demographics, we estimated the expected effect of weight gain on number of deaths and incident cases of IGT and HTN for a 10-year period commencing in 1999. Results indicated that the estimated deleterious effects of weight gain were greater for people with higher BMIs at baseline, for greater degrees of weight gain, for men than women, and for older than younger persons. Because there is a 'U-shaped' relation between BMI and mortality rate, small to moderate weight gains among people with baseline BMIs less than 23 were predicted to decrease mortality rates, whereas weight gains among people with baseline BMIs above that level were expected to increase mortality rates. However, the relations of IGT and HTN with BMI are monotonically increasing. Thus, the anticipated effect of weight gain on IGT and HTN is deleterious regardless of baseline BMI. Because it is unclear whether the beneficial effects of the atypical agents on, for example, reducing suicide mortality, outweigh the putative increase in mortality due to weight gain, we estimate the beneficial effects due to decreased death from suicide with the potential deleterious effects due to a 10-kg weight gain. We found that 492 suicide deaths per 100,000 schizophrenic patients would be prevented over 10 years with the use of clozapine compared to 416 additional deaths due to antipsychotic induced weight gain. Although this estimate is rather crude and should be seen only as offering a sense of the likely situation, results suggest that the lives saved via clozapine may essentially be offset by the deaths due to weight gain. As we discuss, it is not possible to provide definitive estimates of the effect of antipsychotic-induced weight gain on health and mortality, but our findings suggest that the magnitude of weight gains induced by many antipsychotic agents is likely to have important deleterious effects on mortality and health.

Lower limb skeletal muscle mass: development of dual-energy X-ray absorptiometry prediction model

Although magnetic resonance imaging (MRI) can accurately measure lower limb skeletal muscle (SM) mass, this method is complex and costly. A potential practical alternative is to estimate lower limb SM with dual-energy X-ray absorptiometry (DXA). The aim of the present study was to develop and validate DXA-SM prediction equations. Identical landmarks (i.e., inferior border of the ischial tuberosity) were selected for separating lower limb from trunk. Lower limb SM was measured by MRI, and lower limb fat-free soft tissue was measured by DXA. A total of 207 adults (104 men and 103 women) were evaluated [age 43 +/- 16 (SD) yr, body mass index (BMI) 24.6 +/- 3.7 kg/m(2)]. Strong correlations were observed between lower limb SM and lower limb fat-free soft tissue (R(2) = 0.89, P < 0.001); age and BMI were small but significant SM predictor variables. In the cross-validation sample, the differences between MRI-measured and DXA-predicted SM mass were small (-0.006 +/- 1.07 and -0.016 +/- 1.05 kg) for two different proposed prediction equations, one with fat-free soft tissue and the other with added age and BMI as predictor variables. DXA-measured lower limb fat-free soft tissue, along with other easily acquired measures, can be used to reliably predict lower limb skeletal muscle mass.

Total-body skeletal muscle mass: development and cross-validation of anthropometric prediction models

BACKGROUND

Skeletal muscle (SM) is a large body compartment of biological importance, but it remains difficult to quantify SM with affordable and practical methods that can be applied in clinical and field settings.

OBJECTIVE

The objective of this study was to develop and cross-validate anthropometric SM mass prediction models in healthy adults.

DESIGN

SM mass, measured by using whole-body multislice magnetic resonance imaging, was set as the dependent variable in prediction models. Independent variables were organized into 2 separate formulas. One formula included mainly limb circumferences and skinfold thicknesses [model 1: height (in m) and skinfold-corrected upperarm, thigh, and calf girths (CAG, CTG, and CCG, respectively; in cm)]. The other formula included mainly body weight (in kg) and height (model 2). The models were developed and cross-validated in nonobese adults [body mass index (in kg/m(2)) < 30].

RESULTS

Two SM (in kg) models for nonobese subjects (n = 244) were developed as follows: SM = Ht x (0.00744 x CAG(2) + 0.00088 x CTG(2) + 0.00441 x CCG(2)) + 2.4 x sex - 0.048 x age + race + 7.8, where R:(2) = 0.91, P: < 0.0001, and SEE = 2.2 kg; sex = 0 for female and 1 for male, race = -2.0 for Asian, 1.1 for African American, and 0 for white and Hispanic, and SM = 0.244 x BW + 7.80 x Ht + 6.6 x sex - 0.098 x age + race - 3.3, where R:(2) = 0.86, P: < 0.0001, and SEE = 2.8 kg; sex = 0 for female and 1 for male, race = -1.2 for Asian, 1.4 for African American, and 0 for white and Hispanic.

CONCLUSION

These 2 anthropometric prediction models, the first developed in vivo by using state-of-the-art body-composition methods, are likely to prove useful in clinical evaluations and field studies of SM mass in nonobese adults.

Healthy percentage body fat ranges: an approach for developing guidelines based on body mass index

BACKGROUND

Although international interest in classifying subject health status according to adiposity is increasing, no accepted published ranges of percentage body fat currently exist. Empirically identified limits, population percentiles, and z scores have all been suggested as means of setting percentage body fat guidelines, although each has major limitations.

OBJECTIVE

The aim of this study was to examine a potential new approach for developing percentage body fat ranges. The approach taken was to link healthy body mass index (BMI; in kg/m(2)) guidelines established by the National Institutes of Health and the World Health Organization with predicted percentage body fat.

DESIGN

Body fat was measured in subjects from 3 ethnic groups (white, African American, and Asian) who were screened and evaluated at 3 universities [Cambridge (United Kingdom), Columbia (United States), and Jikei (Japan)] with use of reference body-composition methods [4-compartment model (4C) at 2 laboratories and dual-energy X-ray absorptiometry (DXA) at all 3 laboratories]. Percentage body fat prediction equations were developed based on BMI and other independent variables.

RESULTS

A convenient sample of 1626 adults with BMIs < or =35 was evaluated. Independent percentage body fat predictor variables in multiple regression models included 1/BMI, sex, age, and ethnic group (R: values from 0.74 to 0.92 and SEEs from 2.8 to 5.4% fat). The prediction formulas were then used to prepare provisional healthy percentage body fat ranges based on published BMI limits for underweight (<18.5), overweight (> or =25), and obesity (> or =30).

CONCLUSION

This proposed approach and initial findings provide the groundwork and stimulus for establishing international healthy body fat ranges.

Testing the robustness of the new Haseman-Elston quantitative-trait loci-mapping procedure

Variance components (VC) techniques have emerged as among the more powerful methods for detection of quantitative-trait loci (QTL) in linkage analysis. Allison et al. found that, with particularly marked leptokurtosis in the phenotypic distribution and moderate-to-high residual sibling correlation, maximum likelihood (ML) VC methods may produce a severe excess of type I errors. The new Haseman-Elston (NHE) method is a least-squares-based VC method for mapping of QTL in sib pairs (Elston et al.). Using simulation, we investigate the robustness of the NHE to marked nonnormality, by means of the same distributions and worst-case conditions identified by Allison et al. for the ML approach (i.e., 100 pairs; high residual sibling correlation). Results showed that, when marked nonnormality is present, the NHE can be used without severe type I error-rate inflation, even at very small alpha levels.

Antipsychotic-induced weight gain: a comprehensive research synthesis

OBJECTIVE

The purpose of this study was to estimate and compare the effects of antipsychotics-both the newer ones and the conventional ones-on body weight.

METHOD

A comprehensive literature search identified 81 English- and non-English-language articles that included data on weight change in antipsychotic-treated patients. For each agent, a meta-analysis and random effects metaregression estimated the weight change after 10 weeks of treatment at a standard dose. A comprehensive narrative review was also conducted on all articles that did not yield quantitative information but did yield important qualitative information.

RESULTS

Placebo was associated with a mean weight reduction of 0.74 kg. Among conventional agents, mean weight change ranged from a reduction of 0.39 kg with molindone to an increase of 3.19 kg with thioridazine. Among newer antipsychotic agents, mean increases were as follows: clozapine, 4.45 kg; olanzapine, 4.15 kg; sertindole, 2.92 kg; risperidone, 2.10 kg; and ziprasidone, 0.04 kg. Insufficient data were available to evaluate quetiapine at 10 weeks.

CONCLUSIONS

Both conventional and newer antipsychotics are associated with weight gain. Among the newer agents, clozapine appears to have the greatest potential to induce weight gain, and ziprasidone the least. The differences among newer agents may affect compliance with medication and health risk.

Meta-analysis of the effect of excluding early deaths on the estimated relationship between body mass index and mortality

OBJECTIVES

Prospective cohort studies typically observe U- or J-shaped relationships between body mass index (BMI) (kg/m2) and mortality. However, some studies suggest that the elevated mortality at lower BMIs is due to confounding by pre-existing occult disease and recommend eliminating subjects who die during the first several (k) years of follow-up. This meta-analysis tests the effects of such early death exclusion on the BMI-mortality association.

RESEARCH METHODS AND PROCEDURES

Studies identified from MEDLINE, review articles, ancestry analyses, and the "invisible college."

INCLUDED STUDIES

1) measured relative body weight at baseline; 2) included at least 1000 subjects; 3) reported results with and without early-death exclusion, or relevant data; and 4) did not study exclusively diseased populations. Blank tables were mailed to 131 investigators covering 59 databases. Completed tables (n = 16 databases), electronic raw data (n = 7 databases), and original articles (n = 6 databases) provided final data. Meta-analytic regressions compared the BMI-mortality association with and without early death exclusion. The sample included 29 studies and 1,954,345 subjects.

RESULTS

The effect of eliminating early deaths was statistically significant but minuscule in magnitude. Implementation of early death exclusion was estimated to shift the BMI associated with minimum mortality only 0.4 units for men and 0.6 units for women at age 50. Even at a BMI 16, the estimated relative risk (compared to BMI 25) decreased only 0.008 units for men and 0.076 units for women at age 50.

DISCUSSION

Results indicate that either pre-existing disease does not confound the BMI-mortality association or eliminating early deaths is inefficient for reducing that confounding.

Evidence for independent genetic influences on fat mass and body mass index in a pediatric twin sample

OBJECTIVE

Insight into genetic and environmental influences on fat mass, independent of body mass index (BMI; kg/m2), is expected to enhance methods for treating pediatric obesity. However, few studies have estimated the heritability of fat mass in pediatric samples, and those conducted have relied primarily on BMI measurements. PRESENT STUDY: Using bioimpedance analysis, the present study tested a series of hypotheses predicting significant genetic and environmental influences on percent body fat (PBF) above and beyond BMI. Subjects were 66 pairs of twins, including 41 monozygotic and 25 dizygotic pairs, from 3 to 17 years of age. Structural equation modeling tested hypotheses, adjusting for demographic variables.

RESULTS

Analyses indicated significant genetic influences on PBF, with genes estimated to account for 75% to 80% of the phenotypic variation. The remaining variation was attributable to nonshared environmental influences. Multivariate analyses revealed sizable genetic correlations and environmental correlations between BMI and PBF (rg =.74 and re =.67, respectively), suggesting that some genes and environmental experiences influence both phenotypes. However, analyses confirmed genetic and environmental influences on PBF above and beyond BMI. For example, 62.5% of the total genetic variation in PBF was attributable to genes that influenced PBF but not BMI.

CONCLUSION

There seems to be a substantial genetic contribution to fat mass distinct from BMI in a sample of children and adolescents. Studies testing putative genetic or environmental determinants of pediatric obesity might be strengthened further by including research-based body composition methods.

Weight loss increases and fat loss decreases all-cause mortality rate: results from two independent cohort studies

OBJECTIVE

In epidemiological studies, weight loss is usually associated with increased mortality rate. Contrarily, among obese people, weight loss reduces other risk factors for disease and death. We hypothesised that this paradox could exist because weight is used as an implicit adiposity index. No study has considered the independent effects of weight loss and fat loss on mortality rate. We studied mortality rate as a function of weight loss and fat loss.

DESIGN

Analysis of 'time to death' in two prospective population-based cohort studies, the Tecumseh Community Health Study (1890 subjects; 321 deaths within 16y of follow-up) and the Framingham Heart Study (2731 subjects; 507 deaths within 8y of follow-up), in which weight and fat (via skinfolds) loss were assessable.

RESULTS

In both studies, regardless of the statistical approach, weight loss was associated with an increased, and fat loss with a decreased, mortality rate (P < 0.05). Each standard deviation (s.d.) of weight loss (4.6 kg in Tecumseh, 6.7 kg in Framingham) was estimated to increase the hazard rate by 29% (95% confidence interval CI), (14%, 47%, respectively) and 39% (95% CI, 25%, 54% respectively), in the two samples. Contrarily, each s.d. of fat loss (10.0 mm in Tecumseh, 4.8 mm in Framingham) was estimated to reduce the hazard rate 15% (95% CI, 4%, 25%) and 17% (95% CI, 8%, 25%) in Tecumseh and Framingham, respectively. Generalisability of these results to severely (that is, body mass index BMI) > or = 34) obese individuals is unclear.

CONCLUSIONS

Among individuals that are not severely obese, weight loss is associated with increased mortality rate and fat loss with decreased mortality rate.

The long isoform uncoupling protein-3 (UCP3L) in human energy homeostasis

The biological role(s) proposed for UCP3 in energy homeostasis have been based primarily upon amino acid sequence homology to UCP1. Spontaneous mutations of UCP3> have been described in humans, but not in rodents. The functional consequences-or lack thereof-of these mutations in humans will be of great importance in elucidating the biology of this protein. The results of two such studies are summarized here.

Sibling-based tests of linkage and association for quantitative traits

The transmission/disequilibrium test (TDT) developed by Spielman et al. can be a powerful family-based test of linkage and, in some cases, a test of association as well as linkage. It has recently been extended in several ways; these include allowance for implementation with quantitative traits, allowance for multiple alleles, and, in the case of dichotomous traits, allowance for testing in the absence of parental data. In this article, these three extensions are combined, and two procedures are developed that offer valid joint tests of linkage and (in the case of certain sibling configurations) association with quantitative traits, with use of data from siblings only, and that can accommodate biallelic or multiallelic loci. The first procedure uses a mixed-effects (i.e., random and fixed effects) analysis of variance in which sibship is the random factor, marker genotype is the fixed factor, and the continuous phenotype is the dependent variable. Covariates can easily be accommodated, and the procedure can be implemented in commonly available statistical software. The second procedure is a permutation-based procedure. Selected power studies are conducted to illustrate the relative power of each test under a variety of circumstances.

Fragmentation of percolation clusters in general dimensions

The scaling behavior for binary fragmentation of critical percolation clusters in general dimensions is investigated by Monte Carlo simulation as well as by exact series expansions. We obtain values of critical exponents lambda and phi describing the scaling of the fragmentation rate and the distribution of cluster masses produced by binary fragmentation. Our results for lambda and phi in two to nine dimensions agree with the conjectured scaling relation sigma=1+lambda-phi by Edwards and co-workers [Phys. Rev. Lett. 68, 2692 (1992); Phys. Rev. A 46, 6252 (1992)], which in turn excludes the other scaling relations suggested by Gouyet (for d=2), and by Roux and Guyon [J. Phys. A 22, 3693 (1989)], where sigma is the crossover exponent for the cluster numbers in percolation theory.

The distribution of body mass index among individuals with and without schizophrenia

OBJECTIVE

The objective of this study was to estimate and compare the distributions of body mass index (BMI: kg/m2) among individuals with and without schizophrenia, and, thereby, place the weight gain-inducing effects of antipsychotic drugs into context.

METHOD

Data sources were (1) the mental health supplement of the 1989 National Health Interview Survey (NHIS; N = 80,130 nonschizophrenic and 150 self-reported schizophrenic individuals), (2) baseline BMI data from a drug trial of the anti-psychotic ziprasidone supplied by Pfizer Inc (420 noninstitutionalized individuals with chronic psychotic disorders [DSM-IV schizophrenia or schizoaffective disorder]) and (3) data from the National Health and Nutrition Examination Survey III (NHANES III; N = 17,689 nonschizophrenic individuals) to act as a control group for the ziprasidone trial data.

RESULTS

After age-adjusting BMI in each data set, the NHIS data revealed that men with schizophrenia have mean BMIs similar to those of men without schizophrenia (26.14 vs. 25.63, respectively). In contrast, women with schizophrenia in the NHIS data set had a significantly (p<.001) higher mean BMI than did women without schizophrenia (27.36 vs. 24.50, respectively). Moreover, each decile was higher for women with schizophrenia than for women without schizophrenia. Analysis of the ziprasidone and NHANES III data sets revealed that, on average, men with schizophrenia have mean BMIs comparable to those of men without schizophrenia (26.79 vs. 26.52, respectively). In these 2 data sets, women with schizophrenia also had a mean BMI similar to those of women without schizophrenia (27.29 vs. 27.39, respectively).

CONCLUSION

Although there may be a small subpopulation of schizophrenic individuals who are underweight, individuals with schizophrenia were, on the whole, as obese as or more obese than individuals without schizophrenia, suggesting that weight gain induced by antipsychotic agents is an important concern for many individuals.

Relative influences of sex, race, environment, and HIV infection on body composition in adults

BACKGROUND

The factors that control body composition in disease are uncertain.

OBJECTIVE

We planned to compare the relative influences of HIV infection, sex, race, and environment on body composition.

METHODS

We analyzed results of body composition studies performed by bioelectrical impedance analysis in 1415 adults from 2 cohorts: white and African American men and women from the United States, and African men and women (279 HIV-infected and 1136 control). The effects of sex and HIV infection on weight, body cell mass, and fat-free mass were analyzed by using both unadjusted and age-, weight-, and height-adjusted data.

RESULTS

Control men weighed more and had more body cell mass and fat-free mass than did control women, although control women had more fat. The strongest correlates with body composition were height and weight, followed by sex. HIV infection, age, environment, and race. Control men and women weighed more and had more body cell mass, fat-free mass, and fat than did HIV-infected men. However, differences in body composition between HIV-infected and control groups were strongly influenced by sex. Of the differences in weight between HIV-infected and uninfected subjects, fat-free mass accounted for 51% in men but only 18% in women, in whom the remainder was fat. Sex effects were similar in African and American groups.

CONCLUSIONS

Sex has a marked effect on the changes in body composition during HIV infection, with women losing disproportionately more fat than men. Sex-related differences in body composition were narrower in the HIV-infected groups. Race and environment had smaller effects than sex and HIV infection.

Simulation study of the effects of excluding early deaths on risk factor-mortality analyses in the presence of confounding due to occult disease: the example of body mass index

PURPOSE

Estimating the effects of continuous chronic disease risk factors on mortality is an area that generates confusion and controversy. The frequently observed U-shaped or J-shaped relationships between the risk factors and mortality are often in contrast with presumed monotone relationships. Therefore, some investigators 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. The rationale for this approach is that subjects dying during the first k years of follow-up are likely to have some pre-existing occult disease that confounds the relationship between the risk factors and mortality. Excluding such subjects purportedly reduces bias due to this confounding. The purpose of this study was to test the effects of excluding subjects who die during the first k years of follow-up on the reduction of bias under a variety of situations.

METHODS

Using body mass index (BMI; kg/m2) as an example, we conducted Monte Carlo simulations to investigate such effects.

RESULTS

Results suggest that under the conditions investigated, the method of excluding early deaths does not reliably or substantially reduce bias due to confounding introduced by occult disease.

CONCLUSION

Excluding subjects dying during the first k years of follow-up may not be a judicious strategy for handling confounding due to occult disease. Investigators are encouraged to develop alternative methods.

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.

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.

Power and sample size for survival analysis under the Weibull distribution when the whole lifespan is of interest

Accessible and readily utilized software, tables and approximation formulae have been developed to estimate power and sample size for studies of time to event (survival times) when the survival times are assumed to be exponential. These methods can markedly misestimate power when the distribution is Weibull and not exponential. The Weibull distribution with increasing hazard is common in aging research, especially when the whole life span of the subjects is of interest. This note considers an extension of power and sample size calculations, previously developed under the exponential distributional assumption, to the more general case of the Weibull distribution for a prospective comparative follow-up study. The hypotheses are defined in terms of the ratio of the median survival times between two groups. It is shown that the power and sample sizes are heavily dependent on the shape parameter of the Weibull distribution. Using the extensions developed, investigators can use existing software and tables to calculate power and sample size under the assumption of a Weibull distribution.

Extreme selection strategies in gene mapping studies of oligogenic quantitative traits do not always increase power

It is well known that obtaining adequate statistical power to detect linkage to or association with genes for complex quantitative traits can be very difficult. In response, investigators have developed a number of power-enhancing strategies that consider restraints such as genotyping (and/or phenotyping) costs. In the context of both association and sib pair linkage studies of quantitative traits, one of the most widely discussed techniques is the selective sampling of phenotypically extreme individuals. Several papers have demonstrated that such extreme sampling can markedly increase power (under certain circumstances). However, the parenthetical phrase in the previous sentence has generally not been made explicit and it appears to be implied that the more phenotypically extreme the individuals, the more power one has. In this paper, we show by simulation that this is not true under all circumstances. In particular, we show that under oligogenic models, where some biallelic quantitative trait loci (QTLs) have markedly asymmetric allele frequencies and large mean displacement among genotypes, and others have less asymmetric allele frequencies and smaller mean displacement among genotypes, power to detect linkage to or association with the latter QTL can actually decrease by sampling more extreme sib pairs. This suggests that more extreme sampling is not always better. The 'optimal' sampling scheme may depend on both what one suspects the underlying genetic architecture to be and which of the oligogenic QTL one has greatest interest in detecting.

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]).

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.

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.

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.

Improved survival with an implanted defibrillator in patients with coronary disease at high risk for ventricular arrhythmia. Multicenter Automatic Defibrillator Implantation Trial Investigators

BACKGROUND

Unsustained ventricular tachycardia in patients with previous myocardial infarction and left ventricular dysfunction is associated with a two-year mortality rate of about 30 percent. We studied whether prophylactic therapy with an implanted cardioverter-defibrillator, as compared with conventional medical therapy, would improve survival in this high-risk group of patients.

METHODS

Over the course of five years, 196 patients in New York Heart Association functional class I, II, or III with prior myocardial infarction; a left ventricular ejection fraction < or = 0.35; a documented episode of asymptomatic unsustained ventricular tachycardia; and inducible, nonsuppressible ventricular tachyarrhythmia on electrophysiologic study were randomly assigned to receive an implanted defibrillator (n = 95) or conventional medical therapy (n=101). We used a two-sided sequential design with death from any cause as the end point.

RESULTS

The base-line characteristics of the two treatment groups were similar. During an average follow-up of 27 months, there were 15 deaths in the defibrillator group (11 from cardiac causes) and 39 deaths in the conventional-therapy group (27 from cardiac causes) (hazard ratio for overall mortality, 0.46; 95 percent confidence interval, 0.26 to 0.82; P=0.009). There was no evidence that amiodarone, beta-blockers, or any other antiarrhythmic therapy had a significant influence on the observed hazard ratio.

CONCLUSIONS

In patients with a prior myocardial infarction who are at high risk for ventricular tachyarrhythmia, prophylactic therapy with an implanted defibrillator leads to improved survival as compared with conventional medical therapy.