Jack Baker

Brains versus brawn: An empirical test of Barker's brain sparing model

The Barker model of the in utero origins of diminished muscle mass in those born small invokes the adaptive “sparing” of brain tissue development at the expense of muscle. Though compelling, to date this model has not been directly tested. This article develops an allometric framework for testing the principal prediction of the Barker model—that among those born small muscle mass is sacrificed to spare brain growth—then evaluates this hypothesis using data from the third National Health and Nutrition Examination Survey (NHANES III). The results indicate clear support for a negative relationship between the allometric development of the two tissues; however, a further consideration of conserved mammalian fetal circulatory patterns suggests the possibility that system‐constrained patterns of developmental damage and “bet‐hedging” responses in affected tissues may provide a more adequate explanation of the results. Far from signaling the end of studies of adaptive developmental programming, this perspective may open a promising new avenue of inquiry within the fields of human biology and the developmental origins of health and disease. Am. J. Hum. Biol., 2010.

Low birth weight does not predict the ontogeny of relative leg length of infants and children: An allometric analysis of the NHANES III sample

Previous research links both low birth weight (LBW) and relative leg length (RLL) to a similar set of adult pathologies, including type II diabetes, coronary vascular disease, and some cancers. Historically, LBW has been frequently used as a broad indicator of the quality of the intrauterine environment, while RLL has been considered a sensitive measure of childhood environmental quality. While these observations have been taken to suggest that these measures reflect independent exposures at different life-stages, their mutual association with a similar set of later pathologies makes this assumption less certain than it may have previously seemed. Nationally representative data from the Third National Health and Nutrition Examination Survey (NHANES III) are used to test the hypothesis that LBW predicts reductions in the development of leg length relative to stature. After controls for important socioeconomic exposures that might confound measurement of such a relationship, we find statistical and biological evidence that variation in birth weight and variation in the development of leg length relative to stature (RLL) are independent. The results suggest that these two measures may represent independent information on prenatal and postnatal environmental quality.

Developmental plasticity in fat patterning of Ache children in response to variation in interbirth intervals: a preliminary test of the roles of external environment and maternal reproductive strategies.

A firm link between small size at birth and later more centralized fat patterning has been established in previous research. Relationships between shortened interbirth intervals and small size at birth suggest that maternal energetic prioritization may be an important, but unexplored determinant of offspring fat patterning. Potential adaptive advantages to centralized fat storage (Baker et al., 2008 : In: Trevathan W, McKenna J, Smith EO, editors. Evolutionary Medicine and Health: New Perspectives. New York: Oxford) suggest that relationships with interbirth intervals may reflect adaptive responses to variation in patterns of maternal reproductive effort. Kuzawa ( 2005 : Am J Hum Biol 17:5–21; 2008 : In: Trevathan W, McKenna J, Smith EO, editors. Evolutionary Medicine and Health: New Perspectives. New York: Oxford) has argued that maternal mediation of the energetic quality of the environment is a necessary component of developmental plasticity models invoking predictive adaptive responses (Gluckman and Hanson 2004 : Trends Endocrinol Metab 15:183–187). This study tested the general hypothesis that shortened interbirth intervals would predict more centralized fat patterning in offspring. If long‐term maternally mediated signals are important determinants of offspring responses, then we expected to observe a relationship between the average interbirth interval of mothers and offspring adiposity, with no relationship with the preceding interval. Such a finding would suggest that maternal, endogenous resource allocation decisions are related to offspring physiology in a manner consistent with Kuzawas description. We observed exactly such a relationship among the Ache of Paraguay, suggesting that maternally mediated in utero signals of postnatal environments may be important determinants of later physiology. The implications of these findings are reviewed in light of life history and developmental plasticity theories and ourability to generalize the results to other populations. Recommendations for further empirical research are briefly summarized. Am. J. Hum. Biol., 2009.

The effects of socioeconomic status, clinical factors, and genetic ancestry on pulmonary tuberculosis disease in northeastern Mexico.

Diverse socioeconomic and clinical factors influence susceptibility to tuberculosis (TB) disease in Mexico. The role of genetic factors, particularly those that differ between the parental groups that admixed in Mexico, is unclear. The objectives of this study are to identify the socioeconomic and clinical predictors of the transition from latent TB infection (LTBI) to pulmonary TB disease in an urban population in northeastern Mexico, and to examine whether genetic ancestry plays an independent role in this transition. We recruited 97 pulmonary TB disease patients and 97 LTBI individuals from a public hospital in Monterrey, Nuevo León. Socioeconomic and clinical variables were collected from interviews and medical records, and genetic ancestry was estimated for a subset of 142 study participants from 291,917 single nucleotide polymorphisms (SNPs). We examined crude associations between the variables and TB disease status. Significant predictors from crude association tests were analyzed using multivariable logistic regression. We also compared genetic ancestry between LTBI individuals and TB disease patients at 1,314 SNPs in 273 genes from the TB biosystem in the NCBI BioSystems database. In crude association tests, 12 socioeconomic and clinical variables were associated with TB disease. Multivariable logistic regression analyses indicated that marital status, diabetes, and smoking were independently associated with TB status. Genetic ancestry was not associated with TB disease in either crude or multivariable analyses. Separate analyses showed that LTBI individuals recruited from hospital staff had significantly higher European genetic ancestry than LTBI individuals recruited from the clinics and waiting rooms. Genetic ancestry differed between individuals with LTBI and TB disease at SNPs located in two genes in the TB biosystem. These results indicate that Monterrey may be structured with respect to genetic ancestry, and that genetic differences in TB susceptibility in parental populations may contribute to variation in disease susceptibility in the region.

Indirect estimates of total fertility rate using child woman/ratio: a comparison with the Bogue-Palmore method.

Indirect estimation methodologies of the total fertility rate (TFR) have a long history within demography and have provided important techniques applied demographers can use when data is sparse or lacking. However new methodologies for approximating the total fertility rate have not been proposed in nearly 30 years. This study presents a novel method for indirectly approximating the total fertility rate using an algebraic rearrangement of the general fertility rate (GFR) through the known relationship between GFR and TFR. It then compares the proposed method to the well-known Bogue-Palmore method. These methods are compared in 196 countries and include overall errors as well as characteristics of the countries that contribute to fertility behavior. Additionally, these methods were compared geographically to find any geographical patterns. We find this novel method is not only simpler than the Bogue-Palmore method, requiring fewer data inputs, but also has reduced algebraic and absolute errors when compared with the Bogue-Palmore method and specifically outperforms the Bogue-Palmore method in developing countries. We find that our novel method may be useful estimation procedure for demographers.

Exploring Stable Population Concepts from the Perspective of Cohort Change Ratios: Estimating the Time to Stability and Intrinsic r from Initial Information and Components of Change

Cohort Change Ratios (CCRs) appear to have been overlooked in regard to a major canon of formal demography, stable population theory. CCRs are explored here as a tool for examining the transient dynamics of a population as it moves toward the stable equivalent that is captured in most formal demographic models based on asymptotic population dynamics. We employ simulation and a regression-based approach to model trajectories toward this stability. This examination is done in conjunction with the Leslie Matrix and data for 62 countries selected from the US Census Bureau’s International Data Base. We use an Index of Stability (S), which defines stability as the point when S is equal zero (operationalized as S = 0.000000). The Index also is used to define initial stability for a given population and four subsequent “quasi-stable” points on the temporal path to stability (S = .01, S = .05, S = .001, and S = .0005). The regression-based analysis reveals that the initial conditions as defined by the initial Stability Index along with fertility and migration play a role in determining time to stability up until the quasi-stable point of S = .0005 is reached. After this point, the initial conditions are no longer a factor and mortality joins the fertility and migration components in determining the remaining time to stability. Overall all, we find that fertility and mortality have an inverse relationship with time to stability while migration has a positive relationship. The initial Stability Index has an inverse relationship with time to quasi-stability at S = .01, S = .005, S = .001, and S = .0005. We also find that a regression model works very well in estimating the intrinsic rate of increase from the initial rate of increase, but that this model can be improved by adding the components of change. We also compare time to stability and intrinsic r as estimated using the CCR Leslie Matrix approach to, respectively, estimates of time to stability and intrinsic r found using analytic methods and find that the former are consistent with the latter.

Social and clinical predictors of drug-resistant tuberculosis in a public hospital, Monterrey, Mexico

PURPOSE Drug-resistant tuberculosis (DRTB) is steadily increasing in Mexico, but little is known of patient risk factors in the Mexico-United States border region. This preliminary case-control study included 95 patients with active pulmonary TB with drug susceptibility results attending the José E. González University Hospital in the urban hub of Nuevo León-the Monterrey Metropolitan Area. We report potential social and clinical risk factors of DRTB among this hospital-based sample. METHODS We collected data through face-to-face interviews and medical record reviews from 25 cases with DRTB and 70 drug-sensitive controls. DNA was collected to assess an effect of genetic ancestry on DRTB by using a panel of 291,917 genomic markers. We calculated crude and multivariate logistic regression. RESULTS After adjusting for potential confounding factors, we found that prior TB treatment (odds ratio, 4.5; 95% confidence interval, 0.9-21.1) and use of crack cocaine (odds ratio, 4.6; 95% confidence interval, 1.1-18.7) were associated with DRTB. No other variables, including genetic ancestry and comorbidities, were predictive. CONCLUSIONS Health care providers may benefit from recognizing predictors of DRTB in regions where routine drug susceptibility testing is limited. Prior TB treatment and illicit drug use, specifically crack cocaine, may be important risk factors for DRTB in this region.

A stochastic version of the brass PF ratio adjustment of age-specific fertility schedules.

Estimates of age-specific fertility rates based on survey data are known to suffer down-bias associated with incomplete reporting. Previously, William Brass (1964, 1965, 1968) proposed a series of adjustments of such data to reflect more appropriate levels of fertility through comparison with data on children-ever-born by age, a measure of cohort-specific cumulative fertility. His now widely-used Parity/Fertility or PF ratio method makes a number of strong assumptions, which have been the focus of an extended discussion in the literature on indirect estimation. However, while it is clear that the measures used in making adjusted age-specific fertility estimates with this method are captured with statistical uncertainty, little discussion of the nature of this uncertainty around PF-ratio based estimates of fertility has been entertained in the literature. Since both age-specific risk of childbearing and cumulative parity (children ever born) are measured with statistical uncertainty, an unknown credibility interval must surround every PF ratio-based estimate. Using the standard approach, this is unknown, limiting the ability to make statistical comparisons of fertility between groups or to understand stochasticity in population dynamics. This paper makes use of approaches applied to similar problems in engineering, the natural sciences, and decision analysis—often discussed under the title of uncertainty analysis or stochastic modeling—to characterize this uncertainty and to present a new method for making PF ratio-based fertility estimates with 95 percent uncertainty intervals. The implications for demographic analysis, between-group comparisons of fertility, and the field of statistical demography are explored.

Sub-County Population Estimates Using Administrative Records: A Municipal-Level Case Study in New Mexico

This chapter explores the possibility of using administrative records to produce sub-county, municipal-level population estimates. Geocoding of vital records data is combined with IRS summary statistics on filers and dependents at the zip-code level to produce two sets of vintage 2010 Component 1 estimates for all 103 municipalities within the State of New Mexico; one made with no remediation for incomplete geocoding and the other remediated for observed biases in geocoding experiments conducted at the zip-code level. These estimates are compared against the results of the 2010 Census using an ex-post-facto evaluation strategy and standard measures of error and bias. The performance of the non-remediated and remediated estimates are compared to a null model of holding the 2000 Census constant and to a vintage 2010 set of estimates produced by the U.S. Census Bureau using their distributive housing unit method (D-HUM). The results suggest that spatial remediation does little to improve accuracy at the municipal level, and although both sets of component estimates represented significant improvements over the Census 2000 constant estimates, neither out-performed the (D-HUM) procedure, which was considerably more accurate and less biased–especially within the most rapidlygrowing municipalities. While the production of the component method-based estimates might permit the estimation of sub-county components of change, the results of this research suggest that this potential improvement would come at the cost of overall accuracy.

Geography is Destiny: Spatial Correlations in Poverty and Educational Attainment in a New Mexico School District

New Mexico’s urban communities mirror a national trend of resegregation clustered by socioeconomic status and race. Previous research suggests a clear relationship between such clustering and measures of both poverty and educational attainment. This research explores the effect of spatially concentrated poverty on academic achievement in a New Mexico School District, utilizing spatial regression to test hypotheses concerning neighborhood clustering effects on school performance. Proficiency scores for reading, math, and science were collected for the 2004–2006 school years and linked to data on poverty from the 2005–2009 American Community Survey as well as from National Center for Education Statistics (NCES) reporting of the proportion of students receiving free or reduced lunch. Next, following the elementary school students in a pseudo-cohort fashion, it is seen that geography plays an important role on how, on the average, the probability of successful high school graduation depends on high-, middle-, and elementary-school parameters as well as community variables. The implications of the results for understanding relationships between poverty and academic achievement, and the geographic clustering of these patterns, are reviewed.