Understanding socioeconomic and racial differences in adult lung function

Using generative AI to investigate medical imagery models and datasets

BACKGROUND

AI models have shown promise in performing many medical imaging tasks. However, our ability to explain what signals these models have learned is severely lacking. Explanations are needed in order to increase the trust of doctors in AI-based models, especially in domains where AI prediction capabilities surpass those of humans. Moreover, such explanations could enable novel scientific discovery by uncovering signals in the data that aren't yet known to experts.

METHODS

In this paper, we present a workflow for generating hypotheses to understand which visual signals in images are correlated with a classification model's predictions for a given task. This approach leverages an automatic visual explanation algorithm followed by interdisciplinary expert review. We propose the following 4 steps: (i) Train a classifier to perform a given task to assess whether the imagery indeed contains signals relevant to the task; (ii) Train a StyleGAN-based image generator with an architecture that enables guidance by the classifier ("StylEx"); (iii) Automatically detect, extract, and visualize the top visual attributes that the classifier is sensitive towards. For visualization, we independently modify each of these attributes to generate counterfactual visualizations for a set of images (i.e., what the image would look like with the attribute increased or decreased); (iv) Formulate hypotheses for the underlying mechanisms, to stimulate future research. Specifically, present the discovered attributes and corresponding counterfactual visualizations to an interdisciplinary panel of experts so that hypotheses can account for social and structural determinants of health (e.g., whether the attributes correspond to known patho-physiological or socio-cultural phenomena, or could be novel discoveries).

FINDINGS

To demonstrate the broad applicability of our approach, we present results on eight prediction tasks across three medical imaging modalities-retinal fundus photographs, external eye photographs, and chest radiographs. We showcase examples where many of the automatically-learned attributes clearly capture clinically known features (e.g., types of cataract, enlarged heart), and demonstrate automatically-learned confounders that arise from factors beyond physiological mechanisms (e.g., chest X-ray underexposure is correlated with the classifier predicting abnormality, and eye makeup is correlated with the classifier predicting low hemoglobin levels). We further show that our method reveals a number of physiologically plausible, previously-unknown attributes based on the literature (e.g., differences in the fundus associated with self-reported sex, which were previously unknown).

INTERPRETATION

Our approach enables hypotheses generation via attribute visualizations and has the potential to enable researchers to better understand, improve their assessment, and extract new knowledge from AI-based models, as well as debug and design better datasets. Though not designed to infer causality, importantly, we highlight that attributes generated by our framework can capture phenomena beyond physiology or pathophysiology, reflecting the real world nature of healthcare delivery and socio-cultural factors, and hence interdisciplinary perspectives are critical in these investigations. Finally, we will release code to help researchers train their own StylEx models and analyze their predictive tasks of interest, and use the methodology presented in this paper for responsible interpretation of the revealed attributes.

FUNDING

Google.

Effect of Race and Ethnicity on Pulmonary Function Testing Interpretation: An American College of Chest Physicians (CHEST), American Association for Respiratory Care (AARC), American Thoracic Society (ATS), and Canadian Thoracic Society (CTS) Evidence Review and Research Statement

BACKGROUND

Calls have been made to discontinue the routine use of race and ethnicity in medicine. Specific to respiratory medicine, the use of race- and ethnicity-specific reference equations for the interpretation of pulmonary function test (PFT) results has been questioned.

RESEARCH QUESTIONS

Three key questions were addressed: (1) What is the current evidence supporting the use of race- and ethnicity-specific reference equations for the interpretation of PFTs? (2) What are the potential clinical implications of the use or nonuse of race and ethnicity in interpreting PFT results? and (3) What research gaps and questions must be addressed and answered to understand better the effect of race and ethnicity on PFT results interpretation and potential clinical and occupational health implications?

STUDY DESIGN AND METHODS

A joint multisociety (American College of Chest Physicians, American Association for Respiratory Care, American Thoracic Society, and Canadian Thoracic Society) expert panel was formed to undertake a comprehensive evidence review and to develop a statement with recommendations to address the research questions.

RESULTS

Several assumptions and gaps, both in the published literature and in our evolving understanding of lung health, were identified. It seems that many past perceptions and practices regarding the effect of race and ethnicity on PFT results interpretation are based on limited scientific evidence and measures that lack reliability.

INTERPRETATION

A need exists for more and better research that will inform our field about these many uncertainties and will serve as a foundation for future recommendations in this area. The identified shortcomings should not be discounted or dismissed because they may enable flawed conclusions, unintended consequences, or both. Addressing the identified research gaps and needs would allow a better-a more informed-understanding of the effects of race and ethnicity on PFT results interpretation.

Spirometry profiles among pregnant and non-pregnant African women: a cross-sectional study

BACKGROUND

Spirometry is a commonly used lung function test. It assesses respiratory functions by measuring the air volume and the rate at which a person can exhale from lungs filled to their total capacity. The most helpful spirometry parameters are: forced vital capacity (FVC), forced expiratory volume in one second (FEV1), and peak expiratory flow (PEF). Pregnancy derives an altered physiological state due to hormonal and anatomical changes that affect the respiratory system. Despite that, spirometry is less commonly done during pregnancy, and if done, test results are evaluated against non-pregnancy references.

OBJECTIVE

This study aimed to explore spirometry profiles in pregnant and non-pregnant women and describe their differences.

METHODOLOGY

This cross-sectional study involved age-matched pregnant and non-pregnant participants recruited from Mnazi Moja ANC and Muhimbili University (MUHAS). A digital spirometer was used to assess respiratory function. Data were entered and analyzed using SPSS version 23. The mean spirometry values of pregnant participants were compared to those of non-pregnant participants using an independent sample t-test. A p-value of < 0.05 was considered statistically significant.

RESULTS

The study included 92 pregnant and 98 non-pregnant participants subjected to spirometry. Both FVC and FEV1 values were significantly lower in pregnant than in non-pregnant participants (2.7 ± 0.5 L vs. 2.9 ± 0.5 L; p < 0.01 and 2.2 ± 0.4 L vs. 2.5 ± 0.4 L; p < 0.01 respectively). In addition, pregnant participants had significantly lower mean PEF values than their non-pregnant counterparts (303 ± 84 L/min versus 353 ± 64 L/min; p < 0.01).

CONCLUSION

Spirometry test values are lower in pregnancy than in non-pregnant participants.

RECOMMENDATIONS

Interpreting the spirometry test values of pregnant women using references obtained from non-pregnant women may be inappropriate. Future studies should evaluate the appropriateness of predicting spirometry values of pregnant women using reference equations derived from non-pregnant women.

Structural Inequities in Medicine that Contribute to Racial Inequities in Asthma Care

Structural inequities in medicine have been present for centuries in the United States, but only recently are these being recognized as contributors to racial inequities in asthma care and asthma outcomes. This chapter provides a systematic review of structural factors such as racial bias in spirometry algorithms, the history of systemic racism in medicine, workforce/pipeline limitations to the presence of underrepresented minority health care providers, bias in research funding awards, and strategies to solve these problems.

Race- and Ethnicity-Based Spirometry Reference Equations: Are They Accurate for Genetically Admixed Children?

BACKGROUND

Variation in genetic ancestry among genetically admixed racial and ethnic groups may influence the fit of guideline-recommended spirometry reference equations, which rely on self-identified race and ethnicity.

RESEARCH QUESTION

What is the influence of genetic ancestry on the fit of race- and ethnicity-based spirometry reference equations in populations of genetically admixed children?

STUDY DESIGN AND METHODS

Cross-sectional fit of guideline-recommended race- and ethnicity-based spirometry reference equations was evaluated in healthy control participants from case-control studies of asthma. Anthropometry, blood samples, and spirometric measurements were obtained for 599 genetically admixed children 8 to 21 years of age. Genetic ancestry was estimated using genome-wide genotype data. Equation fit, measured as a mean z score, was assessed in self-identified African American (n = 275) and Puerto Rican (n = 324) children as well as genetic ancestry-defined strata of each population.

RESULTS

For African American children, African American-derived equations fit for predicting FEV₁ and FVC in those with an African ancestry more than the median (81.4%-100.0%), whereas composite equations for "other/mixed" populations fit for predicting FEV₁ and FVC in those with African ancestry at or less than the median (30.7%-81.3%). For Puerto Rican children with African ancestry at or less than the median (6.4%-21.3%), White-derived equations fit both FEV₁ and FVC, whereas for those with African ancestry more than the median (21.4%-87.5%), White-derived equations fit the FEV₁ and the composite equations fit the FVC.

INTERPRETATION

Guideline-recommended spirometry reference equations yielded biased estimates of lung function in genetically admixed children with high variation of African ancestry. Spirometry could benefit from reference equations that incorporate genetic ancestry, either for more precise application of the current equations or the derivation and use of new equations.

Measuring the Overall Burden of Early Childhood Malnutrition in Ghana: A Comparison of Estimates From Multiple Data Sources

BACKGROUND

Childhood malnutrition contributes to nearly half (45%) of all deaths among children under 5 globally. The United Nations' Sustainable Development Goals (SDGs) aims to end all forms of malnutrition by 2030; however, measuring progress towards these goals is challenging, particularly in countries with emerging economies where nationally-representative data are limited. The primary objective of this study was to estimate the overall burden of childhood malnutrition in Ghana at national and regional levels using 3 data sources.

METHODS

Using data from the long-standing Ghana Demographic and Health Surveys (GDHS), Ghana Multiple Indicator Cluster Survey (GMICS), and the emerging Ghana Socioeconomic Panel Survey (GSPS), we compared the prevalence of malnutrition using the extended composite index of anthropometric failure (eCIAF) for the period 2008- 2011. This study included data for children aged 6-59 months and calculated all anthropometric z-scores based on the World Health Organization (WHO) Growth Standards. We tested for differences in malnutrition subtypes using two-group configural frequency analysis (CFA).

RESULTS

Of the 10 281 children (6532 from GMICS, 2141 from GDHS and 1608 from GSPS) included in the study, the only demographic difference observed was the children included in the GSPS were slightly older than those included in the GDHS and GMICS (median age of 36 vs 30 vs 33 months, P<.001). Based on the eCIAF, the overall prevalence of malnutrition at the national level was higher among children in the GSPS (57.3%, 95% CI: 53.9%-60.6%), followed by the GDHS (39.7%, 95% CI: 37.0%-42.5%), and then those in the GMICS (31.2%, 95% CI: 29.3%-33.1%). The two-group CFA showed that the 3 data sources also estimated different prevalence rates for most of the malnutrition subtypes included in the eCIAF.

CONCLUSION

Depending on the data source adopted, our estimates of eCIAF showed that between one-third and half of all Ghanaian children aged 6-59 months had at least one form of malnutrition over the period 2008-2011. These eCIAF estimates should complement the commonly reported measures such as stunting and wasting when interpreting the severity of malnutrition in the country to inform policy decisions.

Changes in regional knowledge bases and its effect on local labour markets in the midst of transition: Evidence from France over 1985-2015

In the 2000s, the European labour market experienced a number of significant changes including the transition to a more knowledge-intensive economy as well as the introduction of various economic policies (e.g. Eurozone, subsidized jobs, and social tax cuts). In times like these, the role of knowledge, which is essentially the driving force of innovation and thus promoting technological change and economic growth, is shifting due to new labour market conditions. The present study aims to explore how processes of local knowledge bases have been altered in this transformative environment and how these have impacted on local employment growth. The investigation considers three different knowledge bases in conjunction, incl. knowledge size, knowledge creation, and knowledge application. The study is based on an econometric analysis of a panel of 94 France NUTS-3 regions covering the period 1985-2015, utilizing patent data from European Patent Office (EPO) Statistical Patent Database (PATSTAT), and regional data from European Regional Database (ERD). The result shows that the role of knowledge for employment growth has indeed changed towards more specialized inputs in applications while the importance of greater knowledge size remains still important.

Prognostic implications of differences in forced vital capacity in black and white US adults: Findings from NHANES III with long-term mortality follow-up

BACKGROUND

Because Forced Vital Capacity (FVC) is reduced in Black relative to White Americans of the same age, sex, and height, standard lung function prediction equations assign a lower "normal" range for Black patients. The prognostic implications of this race correction are uncertain.

METHODS

We analyzed 5,294 White and 3,743 Black participants age 20-80 in NHANES III, a nationally-representative US survey conducted 1988-94, which we linked to the National Death Index to assess mortality through December 31, 2015. We calculated the FVC-percent predicted among Black and White participants, first applying NHANES III White prediction equations to all persons, and then using standard race-specific prediction equations. We used Cox proportional hazard models to calculate the association between race and all-cause mortality without and with adjustment for FVC (using each FVC metric), smoking, socioeconomic factors, and comorbidities.

FINDINGS

Black participants' age- and sex-adjusted mortality was greater than White participants (HR 1.46; 95%CI:1.29, 1.65). With adjustment for FVC in liters (mean 3.7 L for Black participants, 4.3 L for White participants) or FVC percent-predicted using White equations for everyone, Black race was no longer independently predictive of higher mortality (HR∼1.0). When FVC-percent predicted was "corrected" for race, Black individuals again showed increased mortality hazard. Deaths attributed to chronic respiratory disease were infrequent for both Black and White individuals.

INTERPRETATION

Lower FVC in Black people is associated with elevated risk of all-cause mortality, challenging the standard assumption about race-based normal limits. Black-White disparities in FVC may reflect deleterious social/environmental exposures, not innate differences.

FUNDING

No funding.

Socioeconomic Inequality in Respiratory Health in the US From 1959 to 2018

Importance

Air quality has improved and smoking rates have declined over the past half-century in the US. It is unknown whether such secular improvements, and other policies, have helped close socioeconomic gaps in respiratory health.

Objective

To describe long-term trends in socioeconomic disparities in respiratory disease prevalence, pulmonary symptoms, and pulmonary function.

Design, Setting, and Participants

This repeated cross-sectional analysis of the nationally representative National Health and Nutrition Examination Surveys (NHANES) and predecessor surveys, conducted from 1959 to 2018. included 160 495 participants aged 6 to 74 years.

Exposures

Family income quintile defined using year-specific thresholds; educational attainment.

Main Outcomes and Measures

Trends in socioeconomic disparities in prevalence of current/former smoking among adults aged 25 to 74 years; 3 respiratory symptoms (dyspnea on exertion, cough, and wheezing) among adults aged 40 to 74 years; asthma stratified by age (6-11, 12-17, and 18-74 years); chronic obstructive pulmonary disease ([COPD] adults aged 40-74 years); and 3 measures of pulmonary function (forced expiratory volume in 1 second [FEV1], forced vital capacity [FVC], and FEV1/FVC<0.70) among adults aged 24 to 74 years.

Results

Our sample included 160 495 individuals surveyed between 1959 and 2018: 27 948 children aged 6 to 11 years; 26 956 children aged 12 to 17 years; and 105 591 adults aged 18 to 74 years. Income- and education-based disparities in smoking prevalence widened from 1971 to 2018. Socioeconomic disparities in respiratory symptoms persisted or worsened from 1959 to 2018. For instance, from 1971 to 1975, 44.5% of those in the lowest income quintile reported dyspnea on exertion vs 26.4% of those in the highest quintile, whereas from 2017 to 2018 the corresponding proportions were 48.3% and 27.9%. Disparities in cough and wheezing rose over time. Asthma prevalence rose for all children after 1980, but more sharply among poorer children. Income-based disparities in diagnosed COPD also widened over time, from 4.5 percentage points (age- and sex-adjusted) in 1971 to 11.3 percentage points from 2013 to 2018. Socioeconomic disparities in FEV1 and FVC also increased. For instance, from 1971 to 1975, the age- and height-adjusted FEV1 of men in the lowest income quintile was 203.6 mL lower than men in the highest quintile, a difference that widened to 248.5 mL from 2007 to 2012 (95% CI, -328.0 to -169.0). However, disparities in rates of FEV1/FVC lower than 0.70 changed little.

Conclusions and Relevance

Socioeconomic disparities in pulmonary health persisted and potentially worsened over the past 6 decades, suggesting that the benefits of improved air quality and smoking reductions have not been equally distributed. Socioeconomic position may function as an independent determinant of pulmonary health.

Model choice for estimating the association between exposure to chemical mixtures and health outcomes: A simulation study

Challenges arise in researching health effects associated with chemical mixtures. Several methods have recently been proposed for estimating the association between health outcomes and exposure to chemical mixtures, but a formal simulation study comparing broad-ranging methods is lacking. We select five recently developed methods and evaluate their performance in estimating the exposure-response function, identifying active mixture components, and identifying interactions in a simulation study. Bayesian kernel machine regression (BKMR) and nonparametric Bayes shrinkage (NPB) were top-performing methods in our simulation study. BKMR and NPB outperformed other contemporary methods and traditional linear models in estimating the exposure-response function and identifying active mixture components. BKMR and NPB produced similar results in a data analysis of the effects of multipollutant exposure on lung function in children with asthma.

Race Correction and Spirometry: Why History Matters

In recent months, medical institutions across the United States redoubled their efforts to examine the history of race and racism in medicine, in classrooms, in research, and in clinical practice. In this essay, I explore the history of racialization of the spirometer, a widely used instrument in pulmonary medicine to diagnose respiratory diseases and to assess eligibility for compensation. Beginning with Thomas Jefferson, who first noted racial difference in what he referred to as "pulmonary dysfunction," to the current moment in clinical medicine, I interrogate the history of the idea of "correcting" for race and how researchers explained difference. To explore how race correction became normative, initially just for people labeled "black," I examine visible and invisible racialized processes in scientific practice. Over more than two centuries, as ideas of innate difference hardened, few questioned the conceptual underpinnings of race correction in medicine. At a moment when "race norming" is under investigation throughout medicine, it is essential to rethink race correction of spirometric measurements, whether enacted through the use of a correction factor or through the use of population-specific standards. Historical analysis is central to these efforts.

Science reflects history as society influences science: brief history of "race," "race correction," and the spirometer

Spirometers are used globally to diagnose respiratory diseases, and most commercially available spirometers "correct" for race. "Race correction" is built into the software of spirometers. To evaluate pulmonary function and to make recordings, the operator must enter the subject's race. In fact, the Joint Working Party of the American Thoracic Society/European Respiratory Society recommends the use of race- and ethnic-specific reference values. In the United States, spirometers apply correction factors of 10-15% for individuals labeled "Black" and 4-6% for people labeled "Asian." Thus race is purported to be a biologically important and scientifically valid category. However, history suggests that race corrections may represent an implicit bias, discrimination, and racism. Furthermore, this practice masks economic and environmental factors. The flawed logic of innate, racial difference is also considered with disability estimates, preemployment physicals, and clinical diagnoses that rely on the spirometer. Thomas Jefferson's Notes on the State of Virginia (1832) may have initiated this mistaken belief by noting deficiencies of the "pulmonary apparatus" of blacks. Plantation physicians used Jefferson's statement to support slavery, believing that forced labor was a way to "vitalize the blood" of deficient black slaves. Samuel Cartwright, a Southern physician and slave holder, was the first to use spirometry to record deficiencies in pulmonary function of blacks. A massive study by Benjamin Apthorp Gould (1869) during the Civil War validated his results. The history of slavery created an environment where racial difference in lung capacity become so widely accepted that race correction became a scientifically valid procedure.

Neighborhood Perceptions and Cumulative Impacts of Low Level Chronic Exposure to Fine Particular Matter (PM2.5) on Cardiopulmonary Health

Adverse perceptions of neighborhood safety, aesthetics and quality including access to resources can induce stress and may make individuals more sensitive to cardiopulmonary effects of air pollution exposure. Few studies have examined neighborhood perceptions as important and modifiable non-chemical stressors of the built environment that may exacerbate effects of air pollution on cardiopulmonary health outcomes, particularly among general population based cohorts. This study examined associations between low-level chronic exposure to fine particulate matter (PM2.5) and cardiopulmonary health, and the potential mediating or modifying effects of adverse neighborhood perceptions. Using data from the Survey of the Health of Wisconsin (SHOW), 2230 non-asthmatic adults age 21-74 were included in the analyses. The overall goals of this study were to assess if individuals who experience stress from neighborhood environments in which they live were more sensitive to low levels of fine particular matter (PM2.5 μg/m³). Demographic predictors of air pollution exposure included younger age, non-White race, lower education and middle class income. After adjustments, objective lung function measures (FEV1 and FEV1 to FVC ratio) were the only cardiopulmonary health indicators significantly associated with chronic three-year annual averages of PM2.5. Among all non-asthmatics, a ten unit increase in estimated three year annual average PM2.5 exposure was significantly associated with lower forced expiratory volume (L) in one second FEV1 (β = -0.40 μg/L; 95% CI -0.45, -0.06). Among all individuals, adverse perceptions of the neighborhood built environment did not appear to statistically moderate or mediate associations. However, stratified analysis did reveal significant associations between PM2.5 and lung function (FEV1) only among individuals with negative perceptions and increased reports of neighborhood stressors. These findings included individuals who felt their neighborhoods were poorly maintained (β = -0.82; 95% CI -1.35, -0.28), experienced stress from crime (β = -0.45; 95% CI -0.94, 0.04) or reported neighborhood is not well maintained (β = -1.13, CI -2.04, -0.24). These significant associations were similar for FEV1 to FVC ratio. Multi-pronged approaches addressing both neighborhood built environment aesthetics and air pollution regulation may be necessary to protect vulnerable and susceptible individuals and reduce persistent inequalities.

Explaining ethnic disparities in lung function among young adults: A pilot investigation

Background

Ethnic disparities in lung function have been linked mainly to anthropometric factors but have not been fully explained. We conducted a cross-sectional pilot study to investigate how best to study ethnic differences in lung function in young adults and evaluate whether these could be explained by birth weight and socio-economic factors.

Methods

We recruited 112 university students of White and South Asian British ethnicity, measured post-bronchodilator lung function, obtained information on respiratory symptoms and socio-economic factors through questionnaires, and acquired birth weight through data linkage. We regressed lung function against ethnicity and candidate predictors defined a priori using linear regression, and used penalised regression to examine a wider range of factors. We reviewed the implications of our findings for the feasibility of a larger study.

Results

There was a similar parental socio-economic environment and no difference in birth weight between the two ethnic groups, but the ethnic difference in FVC adjusted for sex, age, height, demi-span, father’s occupation, birth weight, maternal educational attainment and maternal upbringing was 0.81L (95%CI: -1.01 to -0.54L). Difference in body proportions did not explain the ethnic differences although parental immigration was an important predictor of FVC independent of ethnic group. Participants were comfortable with study procedures and we were able to link birth weight data to clinical measurements.

Conclusion

Studies of ethnic disparities in lung function among young adults are feasible. Future studies should recruit a socially more diverse sample and investigate the role of markers of acculturation in explaining such differences.

Reduced Forced Vital Capacity in an African Population. Prevalence and Risk Factors

RATIONALE

Black Africans have reduced FVC compared with white persons, but the prevalence and determinants of reduced values are not well understood.

OBJECTIVES

To evaluate the prevalence and factors leading to reduced FVC in a Nigerian population and to examine current theories regarding the determinants of this difference.

METHODS

We studied the ventilatory function of 883 adults aged 40 years or older participating in the Burden of Obstructive Lung Disease Study in Ile-Ife, Nigeria. Respondents completed pre- and post-bronchodilator spirometry test and provided information on their smoking history, respiratory symptoms, risk factors, and diagnoses, including anthropometric details. We used standard categories to define body mass index as either underweight, normal, overweight, or obese. We defined reduced FVC as a post-bronchodilator FVC below the lower limit of normal using National Health and Nutrition Examination Survey (NHANES) equations, Global Lung Function Initiative 2012 equations, and local reference equations based on nonsmoking study participants without a respiratory diagnosis. We fit multivariate linear regression models to FVC as a continuous measure, adjusting for age, sex, height, and other confounders.

RESULTS

The prevalence of reduced FVC was 70.4% for men and 72.8% for women when using NHANES values for white Americans, 17.8% for men and 14.4% for women using NHANES equations for African Americans, and 15.5% for men and 20.5% for women using the Global Lung Function Initiative 2012 equations. Using the equations derived from nonsmoking respondents in the survey without a respiratory diagnosis, the prevalence of reduced FVC was less than 4% for both men and women. FVC was lower in participants who had less than 7 years of education (FVC, -96 ml; 95% confidence interval [CI], -172 to -19), were underweight (FVC, -269 ml; 95% CI, -464 to -73), were overweight (FVC, -132 ml; 95% CI, -219 to -46), and were obese (FVC, -222 ml; 95% CI, -332 to -112).

CONCLUSIONS

There is a wide variation in the prevalence of reduced FVC based on the reference standard used. This variation is not satisfactorily explained by factors thought to affect FVC within individual populations. However, the prevalence strongly associates with both education level and body mass index in this population, regardless of the specific standard used.

Socioeconomic status is associated with reduced lung function in China: an analysis from a large cross-sectional study in Shanghai

BACKGROUND

An inverse association between socioeconomic status and pulmonary function has emerged in many studies. However, the mediating factors in this relationship are poorly understood, and might be expected to differ between countries. We sought to investigate the relationship between socioeconomic status and lung function in China, a rapidly industrializing nation with unique environmental challenges, and to identify potentially-modifiable environmental mediators.

METHODS

We used data from the Shanghai Putuo Study, a cross-sectional study performed in Shanghai, China. Participants completed a questionnaire and spirometry. The primary exposure was socioeconomic status, determined by education level. The primary outcomes were FEV1 and FVC percent predicted. Multiple linear regressions were used to test this association, and the percent explained by behavioral, environmental, occupational, and dietary variables was determined by adding these variables to a base model.

RESULTS

The study population consisted of a total of 22,878 study subjects that were 53.3 % female and had a mean age of 48. In the final multivariate analysis, the effect estimates for FEV1 and FVC percent predicted for low socioeconomic status (compared to high) were statistically significant at a p-value of <0.01. Smoking, biomass exposure, mode of transportation to work, a diet low in fruits or vegetables, and occupational category partially attenuated the relationship between SES and lung function. In a fully-adjusted age-stratified analysis, the socioeconomic disparity in lung function widened with increasing age.

CONCLUSIONS

We found cross-sectional evidence of socioeconomic disparities in pulmonary function in Shanghai. These differences increased with age and were partially explained by potentially modifiable exposures.

Prediction of anthropometric measurements from tooth length--A Dravidian study

BACKGROUND

Anthropometric measurement is essential for identification of both victims and suspects. Often, this data is not readily available in a crime scene situation. The availability of one data set should help in predicting the other. This study was hypothesised on the basis of a correlation and geometry between the tooth length and various body measurements.

AIM AND OBJECTIVE

To correlate face, palm, foot and stature measurements with tooth length. To derive a regression formula to estimate the various measurements from tooth length.

MATERIALS AND METHODS

The present study was conducted on Dravidian dental students in the age group 18 - 25 with a sample size of 372. All of the dental and physical parameters were measured using standard anthropometric equipments and techniques.

RESULTS

The data was analysed using SPSS software and the methods used for statistical analysis were linear regression analysis and Pearson correlation. The parameters (incisor height (IH), face height (FH), palm length (PL), foot length (FL) and stature (S) showed nil to mild correlation (R = 0.2 ≤ 0.4) except for palm length (PL) and foot length (FL). (R>0.6).

CONCLUSION

It is concluded that odontometric data is not a reliable source for estimating the face height (FH), palm length (PL), foot length (FL) and stature (S).

Total Exposure Study Analysis consortium: a cross-sectional study of tobacco exposures

BACKGROUND

The Total Exposure Study was a stratified, multi-center, cross-sectional study designed to estimate levels of biomarkers of tobacco-specific and non-specific exposure and of potential harm in U.S. adult current cigarette smokers (≥one manufactured cigarette per day over the last year) and tobacco product non-users (no smoking or use of any nicotine containing products over the last 5 years). The study was designed and sponsored by a tobacco company and implemented by contract research organizations in 2002-2003. Multiple analyses of smoking behavior, demographics, and biomarkers were performed. Study data and banked biospecimens were transferred from the sponsor to the Virginia Tobacco and Health Research Repository in 2010, and then to SRI International in 2012, for independent analysis and dissemination.

METHODS

We analyzed biomarker distributions overall, and by biospecimen availability, for comparison with existing studies, and to evaluate generalizability to the entire sample. We calculated genome-wide statistical power for a priori hypotheses. We performed clinical chemistries, nucleic acid extractions and genotyping, and report correlation and quality control metrics.

RESULTS

Vital signs, clinical chemistries, and laboratory measures of tobacco specific and non-specific toxicants are available from 3585 current cigarette smokers, and 1077 non-users. Peripheral blood mononuclear cells, red blood cells, plasma and 24-h urine biospecimens are available from 3073 participants (2355 smokers and 719 non-users). In multivariate analysis, participants with banked biospecimens were significantly more likely to self-identify as White, to be older, to have increased total nicotine equivalents per cigarette, decreased serum cotinine, and increased forced vital capacity, compared to participants without. Effect sizes were small (Cohen's d-values ≤ 0.11). Power for a priori hypotheses was 57 % in non-Hispanic Black (N = 340), and 96 % in non-Hispanic White (N = 1840), smokers. All DNA samples had genotype completion rates ≥97.5 %; 68 % of RNA samples yielded RIN scores ≥6.0.

CONCLUSIONS

Total Exposure Study clinical and laboratory assessments and biospecimens comprise a unique resource for cigarette smoke health effects research. The Total Exposure Study Analysis Consortium seeks to perform molecular studies in multiple domains and will share data and analytic results in public repositories and the peer-reviewed literature. Data and banked biospecimens are available for independent or collaborative research.

Determinants of Children's Exhaled Nitric Oxide: New Insights from Quantile Regression

While the fractional concentration of exhaled nitric oxide (FeNO) has proven useful in asthma research, its exact role in clinical care remains unclear, in part due to unexplained inter-subject heterogeneity. In this study, we assessed the hypothesis that the effects of determinants of the fractional concentration of exhaled nitric oxide (FeNO) vary with differing levels of FeNO. In a population-based cohort of 1542 school children aged 12–15 from the Southern California Children's Health Study, we used quantile regression to investigate if the relationships of asthma, socio-demographic and clinical covariates with FeNO vary across its distribution. Differences in FeNO between children with and without asthma increased steeply as FeNO increased (Estimated asthma effects (in ppb) at selected 20^th, 50^th and 80^th percentiles of FeNO are 2.4, 6.3 and 22.2, respectively) but the difference was steeper with increasing FeNO in boys and in children with active rhinitis (p-values<0.01). Active rhinitis also showed significantly larger effects on FeNO at higher concentrations of FeNO (Estimated active rhinitis effects (in ppb) at selected 20^th, 50^th and 80^th percentiles of FeNO are 2.1, 5.7 and 14.3, respectively). Boys and children of Asian descent had higher FeNO than girls and non-Hispanic whites; these differences were significantly larger in those with higher FeNO (p-values<0.01). In summary, application of quantile regression techniques provides new insights into the determinants of FeNO showing substantially varying effects in those with high versus low concentrations.

Pulmonary function of adolescents from Tripura, a North-eastern state of India

Objective:

Spirometric evaluation of pulmonary function has been evolved as clinical tool in diagnosis, management, and follow-up of respiratory disorders. There are very few studies on normative reference values of pulmonary function parameters for adolescents from Tripura, a North-eastern state of India. The present study was aimed to evaluate pulmonary function and their predictors in male and female adolescents of Tripura.

Materials and Methods:

A total of 640 (320 from tribal and 320 non-tribal) healthy, non-smoking male and female school children (age 10-14 years) from four different districts of Tripura were randomly sampled for the study. The pulmonary function parameters analysed included forced vital capacity (FVC), forced expiratory volume in 1 second (FEV₁), peak expiratory flow rate (PEFR), forced expiratory flow between 25% and 75% expired volume (FEF_25-75%), ratio of FEV₁/FVC and maximum voluntary ventilation (MVV).

Results:

The results revealed that body weight, body mass index (BMI), PEFR, FEF_25-75% and MVV are significantly high among male tribal children in comparison to non-tribal children. Height, weight, waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), PEFR and MVV were found to be significantly more in tribal girls. In case of adolescents from Tripura, most of the pulmonary function parameters correlated with anthropometric parameters of the subject like height, weight, BMI, WHR, and WHtR.

Conclusion:

From the present study, it can be concluded that both anthropometric and pulmonary function status of tribal and non-tribal adolescents from Tripura are comparable. The computed regression norms may be used to predict pulmonary function of adolescents from Tripura by using anthropometric indices.

African ancestry, lung function and the effect of genetics

African-Americans have smaller lung function compared with European-Americans. The aim of this study was to disentangle the contribution of genetics from other variables on lung function. A cohort was followed from birth to 30 years of age in Brazil. Several variables were collected: genomic analysis based on DNA; forced expiratory volume in 1 s (FEV1) and forced vital capacity (FVC) obtained by spirometry; height measured by anthropometrists; and thorax circumference evaluated by photonic scanner. Crude and adjusted linear regression models were calculated according to African ancestry. The sample comprised 2869 participants out of 3701 members of the cohort. Males with higher African ancestry by DNA analysis had a smaller FEV1 (-0.13 L, 95% CI -0.23- -0.03 L) and FVC (-0.21 L, 95% CI -0.32- -0.09 L) compared with those with less African ancestry, having accounted for height, sitting to standing height ratio and other confounders. Similar effects were seen in females. After adjustment, ancestry remained significantly associated with lung function, but the large effect of adjustment for confounding among males (but not females) does not allow us to exclude the possibility that residual confounding may still account for these findings.

Quantile regression in environmental health: Early life lead exposure and end-of-grade exams

Conditional means regression, including ordinary least squares (OLS), provides an incomplete picture of exposure-response relationships particularly if the primary interest resides in the tail ends of the distribution of the outcome. Quantile regression (QR) offers an alternative methodological approach in which the influence of independent covariates on the outcome can be specified at any location along the distribution of the outcome. We implemented QR to examine heterogeneity in the influence of early childhood lead exposure on reading and math standardized fourth grade tests. In children from two urban school districts (n=1,076), lead exposure was associated with an 18.00 point decrease (95% CI: -48.72, -3.32) at the 10th quantile of reading scores, and a 7.50 point decrease (95% CI: -15.58, 2.07) at the 90th quantile. Wald tests indicated significant heterogeneity of the coefficients across the distribution of quantiles. Math scores did not show heterogeneity of coefficients, but there was a significant difference in the lead effect at the 10th (β=-17.00, 95% CI: -32.13, -3.27) versus 90th (β=-4.50, 95% CI: -10.55, 4.50) quantiles. Our results indicate that lead exposure has a greater effect for children in the lower tail of exam scores, a result that is masked by conditional means approaches.

Admixture mapping identifies a quantitative trait locus associated with FEV1/FVC in the COPDGene Study

African Americans are admixed with genetic contributions from European and African ancestral populations. Admixture mapping leverages this information to map genes influencing differential disease risk across populations. We performed admixture and association mapping in 3,300 African American current or former smokers from the COPDGene Study. We analyzed estimated local ancestry and SNP genotype information to identify regions associated with FEV1 /FVC, the ratio of forced expiratory volume in one second to forced vital capacity, measured by spirometry performed after bronchodilator administration. Global African ancestry inversely associated with FEV1 /FVC (P = 0.035). Genome-wide admixture analysis, controlling for age, gender, body mass index, current smoking status, pack-years smoked, and four principal components summarizing the genetic background of African Americans in the COPDGene Study, identified a region on chromosome 12q14.1 associated with FEV1 /FVC (P = 2.1 × 10(-6) ) when regressed on local ancestry. Allelic association in this region of chromosome 12 identified an intronic variant in FAM19A2 (rs348644) as associated with FEV1 /FVC (P = 1.76 × 10(-6) ). By combining admixture and association mapping, a marker on chromosome 12q14.1 was identified as being associated with reduced FEV1 /FVC ratio among African Americans in the COPDGene Study.

Housing data-based socioeconomic index and risk of invasive pneumococcal disease: an exploratory study

We previously developed and validated an index of socioeconomic status (SES) termed HOUSES (housing-based index of socioeconomic status) based on real property data. In this study, we assessed whether HOUSES overcomes the absence of SES measures in medical records and is associated with risk of invasive pneumococcal disease (IPD) in children. We conducted a population-based case-control study of children in Olmsted County, MN, diagnosed with IPD (1995-2005). Each case was age- and gender-matched to two controls. HOUSES was derived using a previously reported algorithm from publicly available housing attributes (the higher HOUSES, the higher the SES). HOUSES was available for 92·3% (n = 97) and maternal education level for 43% (n = 45). HOUSES was inversely associated with risk of IPD in unmatched analysis [odds ratio (OR) 0·22, 95% confidence interval (CI) 0·05-0·89, P = 0·034], whereas maternal education was not (OR 0·77, 95% CI 0·50-1·19, P = 0·24). HOUSES may be useful for overcoming a paucity of conventional SES measures in commonly used datasets in epidemiological research.

Pragmatic research and outcomes in asthma and COPD

Asthma and chronic obstructive pulmonary disease (COPD) are common diseases which cause patients and society considerable difficulties. These are costly diseases which cause substantial morbidity and death. Health care policy makers have made improving outcomes in asthma and COPD a priority. Application of guideline recommended approaches to asthma and COPD care in the real-life setting has been emphasized but outcomes have not improved. Failure to improve outcomes may not be because of inconsistent applications of guideline recommendations, but rather because there are difficulties implementing the Expert Panel Report III (EPR 3) method for categorizing asthma severity and the Global Initiative for Obstructive Lung Disease (GOLD) method for diagnosing COPD. As these serve as the foundation for treatment recommendations for these diseases, alternative approaches should be considered for categorizing asthma severity and identifying COPD patients. Claims-based algorithms provide an intriguing option for identifying persistent asthma patients and symptomatic COPD patients in administrative databases. These methods could be used as the basis for pragmatic research, both retrospective and prospective, on assessing outcomes of guideline recommended treatment approaches in asthma and COPD. Important questions urgently need to be answered about how guideline recommended approaches regarding use of long-acting inhaled β-agonist/inhaled corticosteroid (LABA/ICS) in asthma and long-acting inhaled anti-muscarinic agent (LAMA) and LABA/ICS in COPD affect outcomes in real-life situations.