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Background The burden of frailty in developing countries and its relationship with complex social structures, such as caste, religion and regional healthcare differences and its effect on healthcare outcomes are not well characterized. The aim of the study was to estimate frailty prevalence and its relationship with the socio-economic and regional factors and healthcare outcomes. Methods In this study, participants from the harmonized Diagnostic Assessment of Dementia for the Longitudinal Aging Study in India (LASI-DAD) were included. The frailty index (FI) was calculated using a 32-variable deficit model, with a value of ≥ 25% considered as frail. Data on demographic (including caste and religion) and socioeconomic profiles and healthcare utilization were obtained. The state-wise health index maintained by the government based on various health-related parameters was used to group the participants’ residential states into high-, intermediate-, and low-performing states. Multivariable and zero-inflated negative binomial regression was used to assess the relationship of frailty index with socio-demographic characteristics, health index and healthcare expenditure or hospitalization. Results Among the 3,953 eligible participants, the prevalence of frailty was 42.34% (men: 34.99%; women: 49.35%). Compared to high-performing states, intermediate- and low-performing states had a higher proportion of frail individuals (49.7% vs. 46.8% vs. 34.5%, p

Objectives Determinants of mortality may depend on the time and place where they are examined. China provides an important context in which to study the determinants of mortality at older ages because of its unique social, economic, and epidemiological circumstances. This study uses a nationally representative sample of persons in China to determine how socioeconomic characteristics, early-life conditions, biological and physical functioning, and disease burden predict 4-year mortality after age 60. Methods We used data from the China Health and Retirement Longitudinal Study. We employed a series of Cox proportional hazard models based on exact survival time to predict 4-year all-cause mortality between the 2011 baseline interview and the 2015 interview. Results We found that rural residence, poor physical functioning ability, uncontrolled hypertension, diabetes, cancer, a high level of systemic inflammation, and poor kidney functioning are strong predictors of mortality among older Chinese. Discussion The results show that the objectively measured indicators of physical functioning and biomarkers are independent and strong predictors of mortality risk after accounting for several additional self-reported health measures, confirming the value of incorporating biological and performance measurements in population health surveys to help understand health changes and aging processes that lead to mortality. This study also highlights the importance of social and historical context in the study of old-age mortality.

Background Significant gains in life expectancy have been achieved, but living longer does not necessarily mean the years gained are productive and healthy. Different theories predict different patterns of time trends in old-age disability prevalence. Methods Using the Gateway to Global Aging Data, which provides internationally harmonized longitudinal data from the Health and Retirement Study and its sister surveys, we compare time trends (from 2004 to 2014) in disability prevalence across countries. Results Disability prevalence varies greatly across countries, and divergent time trends are observed across countries. For countries such as Belgium, Czechia, and Mexico, we observe an increase of disability prevalence, whereas in countries such as Denmark, England, Greece, Korea, Poland, and Sweden, we observe a substantial decrease in disability prevalence. Looking further into the severity of disability, we often observe differential trends in prevalence, but there is no evidence supporting the dynamic equilibrium hypothesis that predicts increased prevalence of modest disability but a decrease in severe disability prevalence. Conclusions Significant gains in life expectancy have translated into different gains in healthy years of life across different countries. Diverse time trends in disability prevalence across countries reaffirm that the expansion of late-life disability is not inevitable.

OBJECTIVES To investigate how cardiometabolic-inflammatory risk factors are related to cognition among older adults in India and the United States. DESIGN The Longitudinal Aging Study in India-Diagnostic Assessment of Dementia (LASI-DAD) and the Harmonized Cognitive Assessment Protocol of the Health and Retirement Study (HRS-HCAP) in the United States conducted an in-depth assessment of cognition, using protocols designed for international comparison. SETTING Cognitive tests were conducted in hospital or household settings in India and in household settings in the United States. PARTICIPANTS Respondents aged 60 years and older from LASI-DAD (N = 1,865) and respondents aged 65 years and older from HRS-HCAP (N = 2,111) who provided venous blood specimen. MEASUREMENTS We used total composite scores from the common cognitive tests administered. Cardiovascular risk was indicated by systolic and diastolic blood pressure, pulse rate, pro-B-type natriuretic peptide (proBNP), and homocysteine. Metabolic risk was measured by body mass index, glycosylated hemoglobin (HbA1c), high-density lipoprotein cholesterol, and lipoprotein (a) (only in India). Inflammatory risk was indicted by white blood cell count, C-reactive protein, albumin, and uric acid (only in India). RESULTS The distribution of both total cognition scores and of cardiometabolic risk factors differed significantly between India and the United States. In both countries, lower cognition was associated with older age, lower education, elevated homocysteine, elevated proBNP, and lower albumin levels. The associations between HbA1c levels and cognitive measures were statistically significant in both countries, but in the opposite direction, with a coefficient of 1.5 (P

Background Inequality in gender varies across social contexts, which may influence the health of both men and women. Based on theories of gender as a social system, we examine whether systematic gender inequality at the macro-level influences health of men and women. Method Using harmonized panel data from the Gateway to Global Aging Data in 23 high- and middle-income countries (N = 168 873), we estimate disability prevalence and incidence for men and women ages 55–89 (2000–2016). Within each country or geographic region, we also investigate gender differences in age gradients of the probability of disability onset. We, then, pool data from all countries and test the hypothesis that gender inequality increases the probability of disability onset. Results We found substantial cross-country variation in disability incidence rates, and this variation is greater for women than for men. Among ages 65–69, disability incidence rates ranged from 0.4 to 5.0 for men and from 0.5 to 9.4 for women. Our within-country analysis showed significant gender differences in age gradients of the probability of disability onset in the United States, Korea, Southern Europe, Mexico, and China, but not in Northern, Central, and Eastern Europe, England, and Israel. Testing hypothesized effects of gender inequality, we find that gender inequality is significantly associated with the probability of disability onset for women, but not for men. Conclusions Macro-level societal gender inequality is significantly associated with the probability of disability onset for women. Reducing and eliminating gender inequality is crucial to achieving good health for women.

The Harmonized Diagnostic Assessment of Dementia for Longitudinal Aging Study in India (LASI-DAD) is a population-representative, prospective cohort study of late-life cognition and dementia. It is part of an ongoing international research collaboration that aims to measure and understand cognitive impairment and dementia risk by collecting a set of cognitive and neuropsychological assessments and informant reports, referred to as the Harmonized Cognitive Assessment Protocol (HCAP). LASI-DAD provides nationally representative data drawn from a subsample of the ongoing Longitudinal Aging Study in India (LASI). One of LASI-DAD's distinctive features is its rich geriatric assessment, including the collection of venous blood samples and brain imaging data for a subsample of respondents. In this paper, we discuss the methodological considerations of developing and implementing the HCAP protocol in India. The lessons we learned from translating and applying the HCAP protocol in an environment where illiteracy and innumeracy are high will provide important insights to researchers interested in measuring and collecting data on late-life cognition and dementia in developing countries. We further developed an innovative blood management system that enables us to follow the collection, transportation, assay, and storage of samples. Such innovation can benefit other population surveys collecting biomarker data.

Background: Inequality in gender varies across social contexts, which may influence the health of both men and women. Based on theories of gender as a social system, we examine whether systematic gender inequality at the macro level influences health of men and women in 23 countries. Methods: Using harmonized panel data from the Gateway to Global Aging Data in 23 high and middle income countries (N=168,873), we estimate disability incidence over a 16 year time period for men and women (2000–2016). We first investigate gender differences in age gradients of disability onset within each country or geographic region. We then pool data from all countries and test the hypothesis that gender inequality increases the risk of disability incidence for men and women. Results: We found substantial cross-country variation in disability incidence rates, and this variation is greater for women than for men. Among ages 65-69, disability incidence rates ranged from 0.4 to 5.0 for men and from 0.5 to 9.4 for women. Our within-country analysis showed significant gender differences in age gradients of disability incidence in the U.S., Korea, Southern Europe, Mexico, and China, but not in Northern, Central, and Eastern Europe, England and Israel. Testing hypothesized effects of gender inequality, we find that gender inequality is significantly associated with disability incidence for women, but not for men. Conclusions: Macro-level societal gender inequality is significantly associated with risk of disability onset for women. Reducing and eliminating gender inequality is crucial to achieving good health for women.

Absorption mode display of Fourier transform mass spectrometry (FTMS) data is known to improve both peak shape and resolution. Most FTMS data, however, are shown in magnitude mode due to the lack of a routine for determining the phase of ions that are necessary for absorption mode display. Despite the recent development of phase calibration methods, the use of absorption mode processing as a routine has been inhibited by the lack of a good phase calibration standard, particularly a standard that can be used as both a mass and a phase calibrant. A dual-role calibrant will enable the consolidation of mass and phase calibration into a single step making phase calibration as accessible as mass calibration without any incremental increase in complexity in the calibration procedure. We tested a series of detergents and found Triton QS-15, an anionic detergent, suitable as a dual-role calibrant. Additionally, Triton QS-15 produces both positive and negative ion series and thus can be used as a calibrant in both ionization modes. The establishment of a phase calibration routine helps to enable the application of FTMS in areas that require extreme mass resolution. One of the areas is the separation of the fine isotopic peaks of molecules with a large molecular mass (e.g., > 500 u). For data acquired using an ion cyclotron resonance instrument with a small magnet (e.g., 7 Tesla), there may not be adequate mass resolution to establish a useful isotopic fine structure if the data is displayed in the historical magnitude mode. A mere switch to the absorption mode display makes the isotopic fine structure (IFS) readily available for molecular formula determination. x

ObjectivesCardiovascular disease has become a major public health challenge in developing countries. The goal of this study is to compare socioeconomic status (SES) gradients of cardiovascular risk factors (CVRF) both within and between China and India.MethodsWe used multivariable logistic regression models to examine the associations between SES and CVRF, using data from the China health and retirement longitudinal study and the longitudinal aging study in India.ResultsThe results showed that, compared to illiteracy, the odds ratios of completing junior high school for high-risk waist circumference were 4.99 (95% confidence interval: 1.77-14.06) among Indian men, 3.42 (95% confidence interval: 1.66-7.05) among Indian women, but 0.74 (95% confidence interval: 0.59-0.92) among Chinese women. Similar patterns were observed between educational attainment and high-risk body mass index, and between education and hypertension, based on self-reported physician diagnosis and direct blood pressure measurements.ConclusionsSES is associated with CVRF in both China and India. However, this relationship showed opposite patterns across two countries, suggesting that this association is not fixed, but is subjective to underlying causal pathways, such as patterns of risky health behaviors and different social and health policies.

Using new biomarker data from the 2010 pilot round of the Longitudinal Aging Study in India (LASI), we investigate education, gender, and state-level disparities in health. We find that hemoglobin level, a marker for anemia, is lower for respondents with no schooling (0.7 g/dL less in the adjusted model) compared to those with some formal education and is also lower for females than for males (2.0 g/dL less in the adjusted model). In addition, we find that about one third of respondents in our sample aged 45 or older have high C-reaction protein (CRP) levels (>3 mg/L), an indicator of inflammation and a risk factor for cardiovascular disease. We find no evidence of educational or gender differences in CRP, but there are significant state-level disparities, with Kerala residents exhibiting the lowest CRP levels (a mean of 1.96 mg/L compared to 3.28 mg/L in Rajasthan, the state with the highest CRP). We use the Blinder–Oaxaca decomposition approach to explain group-level differences, and find that state-level disparities in CRP are mainly due to heterogeneity in the association of the observed characteristics of respondents with CRP, rather than differences in the distribution of endowments across the sampled state populations.

Background Verbal autopsy is designed to ascertain causes of death that are not registered or certified. Verbal autopsy has been validated in multiple settings but has not been as widely evaluated for older populations as for younger age groups. Objective This study aims to provide empirical evidence of the value of verbal autopsy interviews in the context of population-based surveys of older adults by comparing the cause-of-death assignments derived from two methods of interpreting verbal autopsy data. Methods Data used in this study come from the China Health and Retirement Longitudinal Study, a nationally representative longitudinal survey of older Chinese. We compared 407 causes of death determined using InterVA, which is a computer-coded method, and causes of death as assigned by experts; then evaluated factors that affect the results of the two approaches. Results Among the 407 deaths, neoplasms, cardiac disease, and stroke are the leading causes of death according to both approaches. The consistency of the two approaches is about 45% at the individual level. The primary reason for the mismatch is that no cause of death could be assigned for more than 25% of the sample based on expert review. A higher likelihood of mismatch is associated with advanced age and a long period between death and verbal autopsy interview. Conclusion Both approaches identify the same leading causes of death at the aggregate level, but consistency is relatively low at the individual level. InterVA works well when causes of death are characterized by distinctive signs and symptoms. Grouping the various causes of death with shared etiology or common risk factors may help improve the quality of the ascertainment of causes of death. Open-ended narratives are helpful because they provide information about the circumstances surrounding the death that are not available in the structured verbal autopsy interviews.

Glycated hemoglobin (HbA1c) measured using high-performance liquid chromatography (HPLC) assays with venous blood and dried blood spots (DBS) are compared for 143 paired samples collected in Aceh, Indonesia. Relative to gold-standard venous-blood values, DBS-based values reported by the HPLC are systematically upward biased for HbA1c8% and the fraction diabetic (HbA1c ≥ 6.5%) is overstated almost five-fold. Inspection of chromatograms from DBS assays indicates the % glycosylated calculated by the HPLC excludes part of the hemoglobin A which is misidentified as a hemoglobin variant. Taking this into account, unbiased DBS-based values are computed using data from the machine-generated chromatograms. When the DBS are collected in a clinic-like setting, under controlled humidity/temperature conditions, the recalculated values are almost identical to venous-based values. When DBS are collected under field conditions, the recalculated values are unbiased, but only about half the HbA1c values are measured reliably, calling into question the validity of the other half. The results suggest that collection conditions, particularly humidity, affect the quality of the DBS-based measures. Cross-validating DBS-based HbA1c values with venous samples collected under exactly the same environmental conditions is a prudent investment in population-based studies.

Determinants of mortality may differ depending on context. This study uses a nationally representative sample of persons aged 60 and over in China to determine if socioeconomic factors, early life conditions, community characteristics, biological and physical functioning, and disease burden predict four-year all-cause mortality. We employed a series of Weibull hazard models based on exact survival time to predict mortality. We find that current education and place of residence, physical functioning, uncontrolled hypertension, diabetes, cancer, a high level of systemic inflammation, and poor kidney functioning are strong predictors of mortality among older Chinese. We did not find linkages between early-life experiences or community infrastructure to mortality at older ages. Results from this study highlight the value of incorporating biological and performance measurements and the importance of social and historical context in studying old-age mortality.

Objectives This study aims to validate a modified dried blood spot (DBS)-based glycosylated hemoglobin (HbA1c) assay protocol, after a pretest in India showed poor correlation between the original DBS-based protocol and venous results.

To estimate prevalence of diabetes mellitus (DM), success in diagnosing, and methods of diabetes management in China. China Health and Retirement Longitudinal Study, a representative survey of the Chinese population at least 45 years old, is used to estimate diabetes and prediabetes prevalence, diagnosis, and treatment and their associations with residence, socioe-conomic, and demographic factors. Almost 60 % of middle-aged and elderly Chinese have prediabetes or diabetes in 2011–2012. DM prevalence increases with age, but the oldest group is least likely to be diagnosed. Prevalence is higher with higher body mass index, fasting cholesterol, and larger waist circumference. Higher prevalence is found in urban areas among residents with urban registration status (the Chinese administrative registration system or hukou), especially in coastal regions. Better rates of diagnosis, management, and education regarding diabetes are strongly associated with urban hukou, living in coastal areas, and in families with higher per capita expenditures, the appropriate economic resources measure in China. Diagnosis and management of diabetes is highly differential within China but recent efforts to improve health systems are succeeding in reducing undiagnosed disease. Current high prevalence of prediabetes suggests a more intensive effort is required in the future.

Objectives: Cardiovascular disease has become a major public health challenge in developing countries. The goal of this study is to compare socioeconomic status (SES) gradients of cardiovascular risk factors both within and between China and India. Methods: We used data from the China Health and Retirement Longitudinal Study (CAHRLS) and the Longitudinal Aging Study in India (LASI) to analyze the associations between cardiovascular risk factors (waist circumference, body mass index, and hypertension) and SES, particularly education attainment and per capita expenditure. Results: The multivariate logistic regression analyses showed that obesity, defined by either waist circumference or body mass index, was positively correlated with higher education levels in Indian men and women, but inversely associated with education levels among Chinese women. Similar pattern was observed between education attainment and hypertension based on self-reported physician diagnosis and direct blood pressure measurements. Conclusions: SES is associated with cardiovascular risk factors in both China and India. However, the direction of this relationship varies across these two countries, suggesting that this association is not fixed, but is subjective to time and context-dependent causal pathways.

We present a flow analysis technique for detecting unreachable states and actions in concurrent systems. It is an enhancement of the approach by Cheung and Kramer. Each process of a concurrent system is modeled as a finite state machine, whose states represent process execution states and whose transitions are labeled by actions. We construct dependency sets incrementally and eliminate spurious paths by checking the execution sequences of actions. We prove mathematically that our algorithm can detect more unreachability faults than the well-known Reif/Smolka and Cheung/Kramer algorithms. The algorithm is easy to manage and its complexity is still polynomial to the system size. Case studies on two commonly used communication protocols show that the technique is effective.

An approach to the application of bandwidth-oriented signal timing has been proposed based on a group partition method for coordinated arterials. Firstly, the approach is an improved and detailed bandwidth optimization method, including detail steps to calculate upper/lower influences and relative offset for intersections, with different conditions. A window program BOTSD (Bandwidth Optimization and Time-Space Diagram) was developed to obtain optimal progression bandwidth and draw time-space diagram for an arterial. Secondly, a group partition method of coordinated arterials to get optimal bandwidth has been developed. In the case study, after calculating valid and optimal bandwidth for every possible subgroup, arterial progression bandwidth for every combination of possible subgroups can be obtained using the improved bandwidth optimization and group partition method. The results of intersection control delay and progression bandwidth for every combination of possible subgroups show that bandwidth-based solutions generally outperform delay-based solutions. Meanwhile, the signal timing plan from improved bandwidth optimization and group partition method is much better than the result from Synchro 6.0 optimization function and Messer's method.

N-acetyltryptophan (NAT) has long been used as a stabilizer in some protein solutions, such as human serum albumin, to prevent oxidative protein degradation. However, the fate of NAT has not been discussed in literature. Two NAT degradation products have been observed in concentrated albumin solutions (20% and 25%) and identified as 1-acetyl-3a-hydroxy-1,2,3,3a,8,8a-hexahydropyrrolo[2,3-b]indole-2-carboxylic acid and 1-acetyl-3a,8a-dihydroxy-1,2,3,3a,8,8a-hexahydropyrrolo[2,3-b]indole-2-carboxylic acid. To monitor the levels of these two previously unidentified NAT degradation products in concentrated albumin solutions, a fully automated method, incorporating online size exclusion chromatography (SEC) trapping and reversed-phase high performance liquid chromatography-mass spectrometry (HPLC-MS) with multiple reaction monitoring (MRM) analysis, has been developed and validated for their quantitative analysis. The method does not require an internal standard. The only sample manipulation is to obtain an albumin concentration of 4% in all standards and test HPLC samples. A limit of quantitation (LOQ) as low as 20 ng/mL has been achieved for both compounds. This method can readily be adopted for the quantitative determination of other small molecules in concentrated protein solutions.

Fault localization is a major activity in program debugging. To automate this time-consuming task, many existing fault-localization techniques compare passed executions and failed executions, and suggest suspicious program elements, such as predicates or statements, to facilitate the identification of faults. To do that, these techniques propose statistical models and use hypothesis testing methods to test the similarity or dissimilarity of proposed program features between passed and failed executions. Furthermore, when applying their models, these techniques presume that the feature spectra come from populations with specific distributions. The accuracy of using a model to describe feature spectra is related to and may be affected by the underlying distribution of the feature spectra, and the use of a (sound) model on inapplicable circumstances to describe real-life feature spectra may lower the effectiveness of these fault-localization techniques. In this paper, we make use of hypothesis testing methods as the core concept in developing a predicate-based fault-localization framework. We report a controlled experiment to compare, within our framework, the efficacy, scalability, and efficiency of applying three categories of hypothesis testing methods, namely, standard non-parametric hypothesis testing methods, standard parametric hypothesis testing methods, and debugging-specific parametric testing methods. We also conduct a case study to compare the effectiveness of the winner of these three categories with the effectiveness of 33 existing statement-level fault-localization techniques. The experimental results show that the use of non-parametric hypothesis testing methods in our proposed predicate-based fault-localization model is the most promising.

Attempts are often made to find an optimal coordinated control plan for a group of traffic signals in urban areas, such that platoons of vehicles can proceed through a continuous series of green lights without stopping, thereby reducing considerable unnecessary delay. One main objective of coordinated control is to provide the maximum bandwidth progression by adjusting the offset and phase sequence pattern for each signalized intersection. Most models and methods currently being used are based on mixed-integer linear programming (MILP), which is a mathematical optimization model originally formulated by Little et al. in 1966. A basic limitation of the MILP is that it adds a large number of complex constraints for traffic control networks. In this paper, a new simple method is introduced for finding the optimization plan of arterial and network control by maximization of variable bandwidth. This method has not any “loop” constraints and a completely new approach compares to the MILP method applied in this field. In addition, the results of two examples this paper provided validity and feasibility of this new approach in real applications of traffic signal coordination control.

This paper documents the evaluation of Sydney Coordinated Adaptive Traffic System (SCATS) at a major signalized arterial in Las Vegas. The evaluation was based on various performance measures, including primarily travel times and stops at selected routes along the arterial. Extensive travel time runs were conducted during the weekday and weekend peak periods. Arterial performance was compared between SCATS and conventional time-of-day (TOD) coordination plans. Based on the data and analysis results, a general conclusion was reached that no significant improvement on arterial progression was achieved with SCATS under normal traffic conditions. However, this conclusion was made based on a major limitation of using video detection in the field, which may have significantly limited SCATS from achieving its best performance.

From late December 2007 to February 2008, the number of adverse responses to heparin infusions rose noticeably above baseline levels in North America, ultimately resulting in a widespread recall of all heparin vial products made by Baxter Healthcare. Using various analytical techniques and the de novo synthesis of a fully sulfated chondroitin sulfate (FSCS) derivative, the authors have confirmed the identity of the contaminant as an oversulfated chondroitin sulfate (OSCS) and have also defined the heterogeneity and concentration of this contaminant in various lots of heparin. Using both contaminated heparin products and the synthetically produced derivative, the authors have shown that the OSCS produces a dose-dependent hypotension in both pigs and rats and that the response in rats can be abrogated with bradyzide, a rodent-selective B(2) bradykinin receptor antagonist. The no observed effect level (NOEL) for this contaminant appears to be approximately 1 mg/kg, corresponding to a contamination level in finished lots of heparin of approximately 3%. Using human plasma, the OSCS derivative was shown to activate kallikrein. These data provide insight into the etiology of the adverse events, particularly refractory hypotension, observed in patients who were exposed to heparin contaminated with OSCS.

A test oracle in software testing is a mechanism for checking whether the program under test behaves correctly for any execution. In some practical situations, oracles can be unavailable or too expensive to apply. Metamorphic testing (MT) was proposed to alleviate this problem so that software can be delivered under the time-to-market pressure. However, the effectiveness of MT has not been studied adequately. This paper conducts a controlled experiment to investigate the cost effectiveness of using MT. The fault detection capability and time cost of MT are compared with the standard assertion checking method. Our results show that MT has potentials to detect more faults than the assertion checking method. The experiment results also show a trade-off between the two testing methods: MT can be less efficient but more effective, and can be defined at a coarser level of granularity than

Fault localization is one of the most difficult activities in software debugging. Many existing statistical fault-localization techniques estimate the fault positions of programs by comparing the program feature spectra between passed runs and failed runs. Some existing approaches develop estimation formulas based on mean values of the underlying program feature spectra and their distributions alike. Our previous work advocates the use of a non-parametric approach in estimation formulas to pinpoint fault-relevant positions. It is worthy of further study to resolve the two schools of thought by examining the fundamental, underlying properties of distributions related to fault localization. In particular, we ask: Can the feature spectra of program elements be safely considered as normal distributions so that parametric techniques can be soundly and powerfully applied? In this paper, we empirically investigate this question from the program predicate perspective. We conduct an experimental study based on the Siemens suite of programs. We examine the degree of normality on the distributions of evaluation biases of the predicates, and obtain three major results from the study. First, almost all examined distributions of evaluation biases are either normal or far from normal, but not in between. Second, the most fault-relevant predicates are less likely to exhibit normal distributions in terms of evaluation biases than other predicates. Our results show that normality is not common as far as evaluation bias can represent. Furthermore, the effectiveness of our non-parametric predicate-based fault-localization technique weakly correlates with the distributions of evaluation biases, making the technique robust to this type of uncertainty in the underlying program spectra.

Using data from large scale, nationally representative sample surveys, we tested the hypothesis that prenatal exposure to famine increases schizophrenia risk at adulthood by studying the Great Leap Forward Famine in China (1959-1961). Our results show that, in the urban population, being conceived and born during the famine increased the risk of developing schizophrenia at early adulthood as compared to both the pre-famine and post-famine cohorts. In the rural population, however, the post-famine cohort had the highest risk of developing schizophrenia, and there was virtually no difference in schizophrenia risk between the pre-famine and the famine cohort. This finding contrasts sharply with previous studies on the Dutch Hunger Winter as well as with smaller scale local studies in China based on hospital records. We offer an explanation for the urban-rural difference in the schizophrenia-famine relationship based on population selection by differential excess mortality and provide supportive evidence through province- and cohort-level ecological analysis.

The classification standards of levels of service (LOSs) for urban rail transit platforms are the foundation of platform design and evaluation. To study platform LOSs in urban rail transit, the passenger perception method and stated preference investigation concept were adopted, and a questionnaire was designed to investigate the factors influencing LOSs. The survey results showed that the congestion level of the platform was the most important factor influencing the LOS of the platform, followed by passenger order, air quality, information signs, and waiting time. On the basis of the results of the survey, the congestion level was used as the basis for the development of a LOS standard for platforms. A stated preference questionnaire was designed to investigate platform LOSs by using photos showing different congestion levels. According to the survey results, the membership curve of different LOSs was drawn, and the perceived LOS of the platform was classified into five levels on the basis of the congestion level. With linear interpolation, critical values of pedestrian density corresponding to different LOSs were calculated. Finally, the LOS standards developed for transit platforms were compared with the LOS criteria for pedestrian queuing areas offered by the Highway Capacity Manual, and possible reasons for the differences were analyzed. The proposed LOS standards for urban rail transit platforms can be used as a reference for transit design and evaluation.

Unsignalized intersections consist of three types–-two-way stop-controlled, all-way stop-controlled, and uncontrolled intersections–- all with different priority relationships between traffic movements according to traffic laws. A conflict technique method was used to develop capacity models for the three types of unsignalized intersections under mixed traffic conditions involving vehicular, bicycle, and pedestrian movements. With field data collected from several unsignalized intersections, the model parameters were calibrated by a comparison analysis of traffic conditions in China and were modified on the basis of actual traffic conditions. The capacities obtained by the proposed models matched well with the observed capacities and the capacities calculated by conventional methods, both of which verified the effectiveness of the proposed models. The models proved to be valuable tools for determining capacities of vehicular movements at unsignalized intersections.

Inflammation has been hypothesized to be related to Alzheimer’s disease (AD) and vascular dementia (1), but its relationship to cognitive decline in healthy older persons remains a topic of debate. Serum levels of inflammatory markers have been related cross-sectionally to cognitive function (2–4) and longitudinally to risk of AD and other dementia (5–7). However, less is known about the role of inflammation in the rate of cognitive decline in complex cognitive tasks or in healthy older persons. Several studies have reported that inflammation is related to risk of cognitive decline (8–10), whereas others have found no difference in the rate of decline by inflammatory status (11,12). Differences in the methods used may explain some of this variation in findings. Studies reporting greater declines among persons with high inflammation have tended to look at the dichotomous risk of decline over some threshold (8–10) or to use measures like the Mini-Mental State Examination (MMSE) (8), designed primarily to detect dementia (13), rather than to observe changes in higher-level cognitive function among healthy individuals. It is possible that findings using these methods reflect a relationship between inflammation and cognitive impairment or dementia, rather than the impact of inflammation on early, subclinical cognitive change among healthy older persons. Evidence from Dik and colleagues (11) supports this view; although interleukin-6 (IL-6) and C-reactive protein (CRP) were not associated with the rate of cognitive decline in their full sample, they were strongly associated with cognitive decline among persons impaired at baseline. The MacArthur study measured cognition in multiple domains using a battery of tests among participants selected for high cognitive functioning at baseline, providing the opportunity to study the effect of inflammation across a range of cognitive scores. Previous findings from the MacArthur Studies of Successful Aging have documented an association between high baseline IL-6 levels and risk of large incident cognitive declines (9) but have not explored the nature of the relationship between levels of inflammation and rate of cognitive change across their full ranges. Because the MacArthur sample includes a group of healthy older adults nondemented at baseline, who were tested on a range of cognitively complex tasks, it is well-suited to an examination of the effects of inflammation on decline in higher-order cognitive tasks. Identifying the particular cognitive domains most associated with inflammation may shed light on the ways in which inflammation affects the rate of cognitive decline. The purpose of this study was to determine whether inflammation, as measured by serum IL-6 and CRP levels, is related to baseline cognitive function and the rate of cognitive change on a set of complex cognitive tasks in a sample of high-functioning older adults over 7 years.

Measurement of C-reactive protein, a marker of inflammation, in dried blood spots has been increasingly incorporated in community-based social surveys internationally. Although the dried blood spot based CRP assay protocol has been validated in the United States, it remains unclear whether laboratories in other less developed countries can generate C-reactive protein results of similar quality. We therefore conducted external quality monitoring for dried blood spot based C-reactive protein measurement for the Indonesia Family Life Survey and the Longitudinal Aging Study in India. Our results show that dried blood spot based C-reactive protein results in these two countries have excellent and consistent correlations with serum-based values and dried blood spot based results from the reference laboratory in the United States. Even though the results from duplicate samples may have fluctuations in absolute values over time, the relative order of C-reactive protein levels remains similar and the estimates are reasonably precise for population-based studies that investigate the association between socioeconomic factors and health.

C-reactive protein (CRP), a marker of inflammation, has been identified as a risk factor for cardiovascular disease and mortality. Using data on adults aged 20 and over from the fourth National Health and Nutrition Examination Survey, a nationally representative cross-sectional survey, we examined the association between socioeconomic status and CRP in US adults (N=7634). Socioeconomic variation in CRP occurred only at very high levels of CRP (>10.0 mg/L). There was no significant difference in the prevalence of moderate (1.1-3.0 mg/L) or high values of CRP (3.1-10.0mg/L) by socioeconomic status; however, among those with family income at or below the poverty level, 15.7% had very high levels of CRP (greater than 10.0 mg/L), compared to only 9.1% of those in families above the poverty level. Logistic regression results indicate that acute illness, chronic conditions, and differential health behaviors account for about two-thirds of this association. African Americans, Hispanics, and women were more likely to have high levels of CRP. Obesity was the largest risk factor for every level of CRP above normal. Results suggest that differences in very high CRP may be due to factors beyond acute illness and may also reflect chronic health, behavioral and disease processes associated with low socioeconomic status.