Extrinsic Calibration of Multiple 3D LiDAR Sensors by the Use of Planar Objects.

Three-dimensional light detection and ranging (LiDAR) sensors have received much attention in the field of autonomous navigation owing to their accurate, robust, and rich geometric information. Autonomous vehicles are typically equipped with multiple 3D LiDARs because there are many commercially available low-cost 3D LiDARs. Extrinsic calibration of multiple LiDAR sensors is essential in order to obtain consistent geometric information. This paper presents a systematic procedure for the extrinsic calibration of multiple 3D LiDAR sensors using plane objects. At least three independent planes are required within the common field of view of the LiDAR sensors. The planes satisfying the condition can easily be found on objects such as the ground, walls, or columns in indoor and outdoor environments. Therefore, the proposed method does not require environmental modifications such as using artificial calibration objects. Multiple LiDARs typically have different viewpoints to reduce blind spots. This situation increases the difficulty of the extrinsic calibration using conventional registration algorithms. We suggest a plane registration method for cases in which correspondences are not known. The entire calibration process can easily be automated using the proposed registration technique. The presented experimental results clearly show that the proposed method generates more accurate extrinsic parameters than conventional point cloud registration methods.

Frequent and Automatic Update of Lane-Level HD Maps with a Large Amount of Crowdsourced Data Acquired from Buses and Taxis in Seoul.

Recently, HD maps have become important parts of autonomous driving, from localization to perception and path planning. For the practical application of HD maps, it is significant to regularly update environmental changes in HD maps. Conventional approaches require expensive mobile mapping systems and considerable manual work by experts, making it difficult to achieve frequent map updates. In this paper, we show how frequent and automatic updates of lane marking in HD maps are made possible with enormous crowdsourced data. Crowdsourced data is acquired from onboard low-cost sensing devices installed on many city buses and taxis in Seoul, South Korea. A large amount of crowdsourced data is daily accumulated on the server. The quality of sensor measurement is not very high due to the limited performance of low-cost devices. Therefore, the technical challenge is to overcome the uncertainty of the crowdsourced data. Appropriately filtering out a large amount of low-quality data is a significant problem. The proposed HD map update strategy comprises several processing steps including pose correction, observation assignment, observation clustering, and landmark classification. The proposed HD map update strategy is experimentally verified using crowdsourced data. If the changed environments are successfully extracted, then precisely updated HD maps are generated.

Trajectory Planner CDT-RRT* for Car-Like Mobile Robots toward Narrow and Cluttered Environments.

In order to achieve the safe and efficient navigation of mobile robots, it is essential to consider both the environmental geometry and kinodynamic constraints of robots. We propose a trajectory planner for car-like robots on the basis of the Dual-Tree RRT (DT-RRT). DT-RRT utilizes two tree structures in order to generate fast-growing trajectories under the kinodynamic constraints of robots. A local trajectory generator has been newly designed for car-like robots. The proposed scheme of searching a parent node enables the efficient generation of safe trajectories in cluttered environments. The presented simulation results clearly show the usefulness and the advantage of the proposed trajectory planner in various environments.

Factors contributing to educational differences in obesity among women: evidence from South Korea.

BACKGROUND: Obesity is more prevalent among less-educated women than highly-educated women around the world. However, little is known about the factors which cause this difference in obesity, and almost nothing is known about how the individual factors which explain differences in education among women alone contribute to obesity. In this study, we identified the factors which help explain the relationship between education and obesity in women, and quantified their separate contributions to obesity. METHODS: We analyzed information on 14,577 women aged 25 years or over using datasets from the Korea National Health and Nutrition Examination Survey (2010-2014). We divided the women into two education groups: women who had, at most, finished high school (less-educated women), and women who had college degrees and beyond (highly-educated women). Using an extended Oaxaca-Blinder method, we decomposed the difference in obesity prevalence between the two education groups into the contributions (%) due to two effects: composition effect and association effect. RESULTS: Obesity was more than twice as prevalent among the less-educated women (34.3%) than it was among the highly-educated women (16.0%). The composition effect-contribution of differences in the distribution of observed characteristics compared to that of the difference in obesity prevalence between the two education groups-was 38.2%. The association effect-contributions of differences in the estimated coefficients of characteristics compared to that of the difference in obesity prevalence between the two education groups-was 55.8%, of which lifestyle factors were the most important contributor (43.6%). Of the separate contributions of each factor, the association effect of the factor related to women's stress exhibited the largest contribution (23.0%). CONCLUSION: We suggest that to effectively mitigate the high prevalence of obesity among less-educated women, it may be necessary to help low-educated women who do not feel stressful develop strategies to combat their higher risk of obesity. We also suggest the need to conduct decomposition studies in countries which show significant relationships between education and obesity among women, and to create targeted policies to reduce this population's overall risk of obesity.

Associations of socioeconomic and religious factors with health: a population-based, comparison study between China and Korea using the 2010 East Asian social survey.

BACKGROUND: Cross-national comparisons of the associations of socioeconomic and religious factors with health can facilitate our understanding of differences in health determinants between countries and the development of policies to reduce health differentials appropriate to each country. However, very few such studies have been conducted in East Asia. METHODS: This study set out to compare the associations of socioeconomic and religious factors with health in China and Korea using the 2010 East Asian Social Survey, which was based on nationally representative samples. The study participants included 4980 individuals, 3629 in China and 1351 in Korea, aged ≥20 years. The dependent variable, individuals' self-rated health, was categorized into poor, good, and excellent. Socioeconomic (education, employment, household income, and self-assessed social class) and religious factors (affiliation) were used as independent variables of interest. A multinomial logistic regression was performed with and without adjustments for factors such as demographics, health-related risks, the health system, and social capital. RESULTS: According to the results, China had a higher proportion of individuals who reported excellent health than did Korea (57.4% vs. 52.0%). After adjusting for all studied confounders, we found that the employment, household income, and social class gradient in health were significant in China, whereas the education and religion gradients in health were significant in Korea. For example, the odds ratio for poor health versus excellent health among those in the highest social class was 0.47 (95% CI, 0.27-0.84), compared to that of people in the lowest social class in China; and this odds ratio in people with college education or higher was 0.28 (95% CI, 0.14-0.59) compared to that of people with elementary school education or lower in Korea. CONCLUSIONS: These findings demonstrate the important role of socioeconomic and religious factors in health in China and Korea as well as clear differences in this regard. Further cross-national studies are needed to provide a better understanding of the relationship between socioeconomic and religious factors and health and to draft appropriate health improvement policies in both countries.

Obstacle Avoidance of Two-Wheel Differential Robots Considering the Uncertainty of Robot Motion on the Basis of Encoder Odometry Information.

It is important to overcome different types of uncertainties for the safe and reliable navigation of mobile robots. Uncertainty sources can be categorized into recognition, motion, and environmental sources. Although several challenges of recognition uncertainty have been addressed, little attention has been paid to motion uncertainty. This study shows how the uncertainties of robot motions can be quantitatively modeled through experiments. Although the practical motion uncertainties are affected by various factors, this research focuses on the velocity control performance of wheels obtained by encoder sensors. Experimental results show that the velocity control errors of practical robots are not negligible. This paper proposes a new motion control scheme toward reliable obstacle avoidance by reflecting the experimental motion uncertainties. The presented experimental results clearly show that the consideration of the motion uncertainty is essential for successful collision avoidance. The presented simulation results show that a robot cannot move through narrow passages owing to a risk of collision when the uncertainty of motion is high. This research shows that the proposed method accurately reflects the motion uncertainty and balances the collision safety with the navigation efficiency of the robot.

Heuristics for Two Depot Heterogeneous Unmanned Vehicle Path Planning to Minimize Maximum Travel Cost.

A solution to the multiple depot heterogeneous traveling salesman problem with a min-max objective is in great demand with many potential applications of unmanned vehicles, as it is highly related to a reduction in the job completion time. As an initial idea for solving the min-max multiple depot heterogeneous traveling salesman problem, new heuristics for path planning problem of two heterogeneous unmanned vehicles are proposed in this article. Specifically, a task allocation and routing problem of two (structurally) heterogeneous unmanned vehicles that are located in distinctive depots and a set of targets to visit is considered. The unmanned vehicles, being heterogeneous, have different travel costs that are determined by their motion constraints. The objective is to find a tour for each vehicle such that each target location is visited at least once by one of the vehicles while the maximum travel cost is minimized. Two heuristics based on a primal-dual technique are proposed to solve the cases where the travel costs are symmetric and asymmetric. The computational results of the implementation have shown that the proposed algorithms produce feasible solutions of good quality within relatively short computation times.

Practical Modeling of GNSS for Autonomous Vehicles in Urban Environments.

Autonomous navigation technology is used in various applications, such as agricultural robots and autonomous vehicles. The key technology for autonomous navigation is ego-motion estimation, which uses various sensors. Wheel encoders and global navigation satellite systems (GNSSs) are widely used in localization for autonomous vehicles, and there are a few quantitative strategies for handling the information obtained through their sensors. In many cases, the modeling of uncertainty and sensor fusion depends on the experience of the researchers. In this study, we address the problem of quantitatively modeling uncertainty in the accumulated GNSS and in wheel encoder data accumulated in anonymous urban environments, collected using vehicles. We also address the problem of utilizing that data in ego-motion estimation. There are seven factors that determine the magnitude of the uncertainty of a GNSS sensor. Because it is impossible to measure each of these factors, in this study, the uncertainty of the GNSS sensor is expressed through three variables, and the exact uncertainty is calculated. Using the proposed method, the uncertainty of the sensor is quantitatively modeled and robust localization is performed in a real environment. The approach is validated through experiments in urban environments.

Self-Diagnosis of Localization Status for Autonomous Mobile Robots.

It is essential to provide reliable localization results to allow mobile robots to navigate autonomously. Even though many state-of-the-art localization schemes have so far shown satisfactory performance in various environments, localization has still been difficult under specific conditions, such as extreme environmental changes. Since many robots cannot diagnose for themselves whether the localization results are reliable, there can be serious autonomous navigation problems. To solve this problem, this study proposes a self-diagnosis scheme for the localization status. In this study, two indicators are empirically defined for the self-diagnosis of localization status. Each indicator shows significant changes when there are difficulties in light detection and ranging (LiDAR) sensor-based localization. In addition, the classification model of localization status is trained through machine learning using the two indicators. A robot can diagnose the localization status itself using the proposed classification model. To verify the usefulness of the proposed method, we carried out localization experiments in real environments. The proposed classification model successfully detected situations where the localization accuracy is significantly degraded due to extreme environmental changes.

Modifying effects of education on the association between lifestyle behaviors and the risk of obesity: evidence from South Korea.

BACKGROUND: No previous study has explored the interactions between education and lifestyle in relation to obesity. This study hypothesized that education may be obesogenic through its interplay with lifestyle behaviors. METHODS: Data for a nationally representative sample (6937 men and 9333 women) from the Korea National Health and Nutrition Examination Survey (2010-2012) were analyzed. Multivariate logistic regressions were performed for three education levels and six lifestyle behaviors, each of which comprised two groups. RESULTS: Interactions between education and lifestyle behaviors in relation to obesity were observed for all lifestyle behaviors in women (p for interaction <0.001) and for three lifestyle behaviors in men. Education appeared obesogenic for three groups of lifestyle behaviors in men (p for trend <0.05), but was protective against obesity for 11 groups in women. Each one-unit increase in education level in men increased the odds of obesity by 1.29-fold among under-reported energy intake groups (95 % confidence interval: 1.16, 1.44). CONCLUSIONS: Education may be a risk factor for obesity through its interplay with lifestyle behaviors. Further research is required to examine these findings in different socio-cultural settings.

Deconstructing subjective unmet healthcare needs: a South Korean case study with policy implications.

Background: Despite widespread efforts by many countries to reduce the prevalence of unmet healthcare needs within their populations, there remains a scarcity of research systematically exploring the components of these needs. Objectives: This study aims to deconstruct subjective unmet healthcare needs into two distinct components: the experience of subjective healthcare needs (the "Needs" component) and the experience of unmet needs contingent on those healthcare needs (the "Unmet" component). Methods: This analysis utilizes data from 13,359 adults aged 19 or older, collected through the 2018 Korea Health Panel survey, with the aim of minimizing the influence of the coronavirus disease 19 pandemic. The two dependent variables are the experience of subjective healthcare needs and whether these needs have been met. The independent variables include 15 socio-demographic, health, and functional characteristics. The study employs both a population proportion analysis and a multivariable bivariate probit model with sample selection. Results: In South Korea, 11.6% (CI [confidence interval] = 11.0-12.3%) of the population experienced subjective unmet healthcare needs. Upon deconstructing these, 96.7% (CI = 96.2-97.1%) of the population exhibited the Needs component, and 12.0% (CI = 11.4-12.7%) displayed the Unmet component. Each independent variable showed different associations between the two components. Furthermore, effective interventions targeting the characteristics associated with each component could reduce the proportion of the population experiencing subjective unmet healthcare needs from 11.6 to 4.0%. Conclusion: South Korea faces a significant challenge due to the considerable prevalence of subjective unmet healthcare needs. To address this challenge effectively, the universal healthcare coverage system should adapt its approach based on the characteristics associated with both the Needs and Unmet components of subjective unmet healthcare needs. To achieve this goal, it is highly recommended that the government prioritize strengthening community-based primary healthcare, which currently suffers from insufficient resources.

Optimization of gearbox housing shape for agricultural UTV using structural-acoustic coupled analysis.

In this study, gearbox radiated noise was successfully reduced through housing shape optimization. First, dynamic and structural-acoustic coupled analysis models of an agricultural UTV gearbox were developed. Then, the test equipment was configured to match that of the simulation model, and a test was conducted. The analysis and test results showed errors within 0.1 dB for vibration and 0.2 dB(A) for noise, indicating that the models were reliable. The housing design was then optimized using topology optimization based on the developed structural-acoustic coupling analysis model. The sound pressure level around the housing was used as an objective function for topology optimization. The optimal distribution of materials for the housing was also derived to reduce the radiated noise. Lastly, the housing rib was designed based on the optimization result, and an improvement in the radiated noise by approximately 2.43 dB(A) was confirmed in the operation area.

Optimizing methanol synthesis from CO2 using graphene-based heterogeneous photocatalyst under RSM and ANN-driven parametric optimization for achieving better suitability.

Assessment of the performance of linear and nonlinear regression-based methods for estimating in situ catalytic CO2 transformations employing TiO2/Cu coupled with hydrogen exfoliation graphene (HEG) has been investigated. The yield of methanol was thoroughly optimized and predicted using response surface methodology (RSM) and artificial neural network (ANN) model after rigorous experimentation and comparison. Amongst the different types of HEG loading from 10 to 40 wt%, the 30 wt% in the HEG-TiO2/Cu assisted photosynthetic catalyst was found to be successful in providing the highest conversion efficiency of methanol from CO2. The most influencing parameters, HEG dosing and inflow rate of CO2, were found to affect the conversion rate in the acidic reaction regime (at pH of 3). According to RSM and ANN, the optimum methanol yields were 36.3 mg g-1 of catalyst and 37.3 mg g-1 of catalyst, respectively. Through the comparison of performances using the least squared error analysis, the nonlinear regression-based ANN showed a better determination coefficient (overall R2 > 0.985) than the linear regression-based RSM model (overall R2 ∼ 0.97). Even though both models performed well, ANN, consisting of 9 neurons in the input and 1 hidden layer, could predict optimum results closer to RSM in terms of agreement with the experimental outcome.

Effects of manufacturing errors of gear macro-geometry on gear performance.

In gear design, gear performance metrics such as safety factors for tooth root stress and surface durability, peak-to-peak static transmission error (PPSTE), efficiency, mass, and volume are considered. They are calculated by the geometric parameters of gear macro- and micro-geometry, and manufacturing errors related to gear geometry significantly affect gear performance. However, previous studies have only focused on the micro-geometry errors. In this study, Monte Carlo-type robustness analysis was performed considering the manufacturing errors for tooth thickness, tip diameter, and center distance. Gear performance metrics except PPSTE were calculated based on the international standards and geometric characteristics. PPSTE was evaluated analytically due to lack of standards. When the errors were considered, two gear pairs with the safety factors satisfying the design requirements and similar performance for PPSTE, efficiency, mass, and volume showed different gear performances. There were many samples in gear pair 1 that could not satisfy the design requirements of safety factors, and gear pair 2 had the robustness of PPSTE not only at the specific torque but also with wide torque range when compared to gear pair 1. These results imply that considering the gear macro-geometry errors and robustness of PPSTE is significantly important when designing gears.

Rice Husk-Cellulose-Based Agricultural Waste Enhances the Degradation of Synthetic Dyes Using Multiple Enzyme-Producing Extremophiles.

The brightly colored synthetic dyes used in the textile industry are discharged at high concentrations-for example, various azo dyes including Methylene Blue (MB) and Methyl Orange (MO)-which is a matter of global concern, as such dyes are harmful to humans and the environment. Microbial degradation is considered an efficient alternative for overcoming the disadvantages of conventional physical and chemical dye removal methods. In this study, we investigated the potential of multiple types of the enzyme-producing extremophilic bacteria Bacillus FW2, isolated from food waste leachate, for the decolorization and bioremediation of artificial synthetic dyes. The screening of enzyme production and assaying of bacterial strain enzymes are essential for enhancing the breakdown of azo bonds in textile azo dyes. The degradation efficiencies of the water-soluble dyes MB and MO were determined at different concentrations using rice husk, which is an efficient substrate. Using the rice husks, the MO was removed completely within 20 h, and an estimated 99.8% of MB was degraded after 24 h by employing shaking at 120 rpm at 40 °C-whereas a removal efficiency of 98.9% was achieved for the combination of MB + MO. These results indicate the possibility of applying an extremophilic bacterial strain, Bacillus sp., for large-scale dye degradation in the future.

Dissemination of sulfonamide resistance genes in digester microbiome during anaerobic digestion of food waste leachate.

The preeminence of sulfonamide drug resistance genes in food waste (FW) and the increased utilization of high-strength organic FW in anaerobic digestion (AD) to enhance methane production have raised severe public health concerns in wastewater treatment plants worldwide. In this regard, the dissemination patterns of different sulfonamide resistance genes (sul1 and sul2) and their impact on the digester core microbiota during AD of FW leachate (FWL) were evaluated. The presence of various sulfonamide antibiotics (SAs) in FWL digesters improved the final methane yield by 37 % during AD compared with FWL digesters without SAs. Microbial population shifts towards hydrolytic, acidogenic, and acetogenic bacteria in the phyla Actinobacteriota, Bacteroidota, Chloroflexi, Firmicutes, Proteobacteria, and Synergistota occurred due to SA induced substrate digestion and absorption through active transport; butanoate, propanoate, and pyruvate metabolism; glycolysis; gluconeogenesis; the citrate cycle; and pentose phosphate pathway. The initial dominance of Methanosaeta (89-96 %) declined to 47-53 % as AD progressed and shifted towards Methanosarcina (40 %) in digesters with the highest SA concentrations at the end of AD. Dissemination of sul1 depended on class 1 integron gene (intl1)-based horizontal gene transfer to pathogenic members of Chloroflexi, Firmicutes, and Patescibacteria, whereas sul2 was transmitted to Synergistota independent of intl1. Low susceptibility and ability to utilize SAs during methanogenesis shielded methanogenic archaea against selection pressure, thus preventing them from interacting with sul or intl1 genes, thereby minimizing the risk of antibiotic resistance development. The observed emergence of cationic antimicrobial peptide, vancomycin, and ß-lactam resistance in the core microbiota during AD of FWL in the presence of SAs suggests that multidrug resistance caused by bacterial transformation could lead to an increase in the environmental resistome through wastewater sludge treatment.

Why is high-risk drinking more prevalent among men than women? Evidence from South Korea.

BACKGROUND: It is important to identify and quantify the factors that affect gender differences in high-risk drinking (HRD), from both an academic and a policy perspective. However, little is currently known about them. This study examines these factors and estimates the percentage contribution each makes to gender differences in HRD. METHODS: This study analyzed information on 23,587 adults obtained from the Korea National Health and Nutrition Surveys of 1998, 2001, and 2005. It found that the prevalence of HRD was about 5 times higher among men (0.37) than women (0.08). Using a decomposition approach extended from the Oaxaca-Blinder method, we decomposed the gender difference in HRD to an "overall composition effect" (contributions due to gender differences in the distribution of observed socio-economic characteristics), and an "overall HRD-tendency effect" (contributions due to gender differences in tendencies in HRD for individuals who share socio-economic characteristics). RESULTS: The HRD-tendency effect accounted for 96% of the gender difference in HRD in South Korea, whereas gender differences in observed socio-economic characteristics explained just 4% of the difference. Notably, the gender-specific HRD-tendency effect accounts for 90% of the gender difference in HRD. CONCLUSION: We came to a finding that gender-specific HRD tendency is the greatest contributor to gender differences in HRD. Therefore, to effective reduce HRD, it will be necessary to understand gender differences in socioeconomic characteristics between men and women but also take notice of such differences in sociocultural settings as they experience. And it will be also required to prepare any gender-differentiated intervention strategy for men and women.

Characteristics Associated With Financial or Non-financial Barriers to Healthcare in a Universal Health Insurance System: A Longitudinal Analysis of Korea Health Panel Survey Data.

While many studies have explored the financial barriers to healthcare, there is little evidence regarding the non-financial barriers to healthcare. This study identified characteristics associated with financial and non-financial barriers to healthcare and quantified the effects of these characteristics in South Korea, using a nationally representative longitudinal survey dataset. Overall, 68,930 observations of 16,535 individuals aged 19 years and above were sampled from Korea Health Panel survey data (2014-2018). From self-reported information about respondents' experiences of unmet healthcare needs, a trichotomous dependent variable-no barrier, non-financial barrier, and financial barrier-was derived. Sociodemographics, physical and health conditions were included as explanatory variables. The average adjusted probability (AAP) of experiencing each barrier was predicted using multivariable and panel multinomial logistic regression analyses. According to the results, the percentage of people experiencing non-financial barriers was much higher than that of people experiencing financial barriers in 2018 (9.6 vs. 2.5%). Women showed higher AAPs of experiencing both non-financial (9.9 vs. 8.3%) and financial barriers (3.6 vs. 2.5%) than men. Men living in the Seoul metropolitan area showed higher AAPs of experiencing non-financial (8.7 vs. 8.0%) and financial barriers (3.4 vs. 2.1%) than those living outside it. Household income showed no significant associations in the AAP of experiencing a non-financial barrier. People with a functional limitation exhibited a higher AAP of experiencing a non-financial barrier, for both men (17.8 vs. 7.8%) and women (17.4 vs. 9.0%), than those without it. In conclusion, people in South Korea, like those in most European countries, fail to meet their healthcare needs more often due to non-financial barriers than financial barriers. In addition, the characteristics associated with non-financial barriers to healthcare differed from those associated with financial barriers. This finding suggests that although financial barriers may be minimised through various policies, a considerable degree of unmet healthcare needs and disparity among individuals is very likely to persist due to non-financial barriers. Therefore, current universal health insurance systems need targeted policy instruments to minimise non-financial barriers to healthcare to ensure effective universal health coverage.

Changes in Barriers That Cause Unmet Healthcare Needs in the Life Cycle of Adulthood and Their Policy Implications: A Need-Selection Model Analysis of the Korea Health Panel Survey Data.

Using 68,930 observations selected from 16,535 adults in the Korea Health Panel Survey (2014-2018), this study explored healthcare barriers that prevent people from meeting their healthcare needs most severely during adulthood, and the characteristics that are highly associated with the barrier. This study derived two outcome variables: a dichotomous outcome variable on whether an individual has experienced healthcare needs, and a quadchotomous outcome variable on how an individual's healthcare needs ended. An analysis was conducted using a multivariable panel multinomial probit model with sample selection. The results showed that the main cause of unmet healthcare needs was not financial difficulties but non-financial barriers, which were time constraints up to a certain age and the lack of caring and support after that age. People with functional limitations were at a high risk of experiencing unmet healthcare needs due to a lack of caring and support. To reduce unmet healthcare needs in South Korea, the government should focus on lowering non-financial barriers to healthcare, including time constraints and lack of caring and support. It seems urgent to strengthen the foundation of "primary care", which is exceptionally scarce now, and to expand it to "community-based integrated care" and "people-centered care".

Effect of Aging on Educational Differences in the Risk of Cognitive Impairment: A Gender-Specific Analysis Using Korean Longitudinal Study of Aging (2006-2016).

This study examined the effect of aging on gender-specific educational differences in the risk of cognitive impairment using a nationally representative sample of 4278 men and 5495 women aged 45 years and older from the dataset of the Korean Longitudinal Study of Aging. Sociodemographics, lifestyle, and medical conditions were included as covariates in the mixed logistic regression analysis models. The prevalence of cognitive impairment was higher in women than in men at baseline. The risk of cognitive impairment in each age group decreased with education in both men and women. The risk by educational rank was worse at lower levels and increased with age, more so for women than men. Aging appears to widen the impact of educational differences on the risk of cognitive impairment and is more unfavorable for women than for men. Public health policies regarding population aging need to consider this and identify the target population to reduce both the level of and the difference in the risk of cognitive impairment.