Log-linear Research Articles

Association of metals and bisphenols exposure with lipid profiles and dyslipidemia in Chinese adults: Independent, combined and interactive effects

BackgroundAlthough studies have assessed the association of metals and bisphenols with lipid metabolism, the observed results have been controversial, and limited knowledge exists about the combined and interactive effects of metals and bisphenols exposure on lipid metabolism. MethodsPlasma metals and serum bisphenols concentrations were evaluated in 888 participants. Multiple linear regression and logistic regression models were conducted to assess individual associations of 18 metals and 3 bisphenols with 5 lipid profiles and dyslipidemia risk, respectively. The dose-response relationships of targeted contaminants with lipid profiles and dyslipidemia risk were captured by applying a restriction cubic spline (RCS) function. The bayesian kernel machine regression (BKMR) model was used to assess the overall effects of metals and bisphenols mixture on lipid profiles and dyslipidemia risk. The interactive effects of targeted contaminants on interested outcomes were explored by constructing an interaction model. ResultsSingle-contaminant analyses revealed that exposure to iron (Fe), nickel (Ni), copper (Cu), arsenic (As), selenium (Se), strontium (Sr), and tin (Sn) was associated with elevated lipid levels. Cobalt (Co) showed a negative association with high density lipoprotein cholesterol (HDL-C). Bisphenol A (BPA) and bisphenol AF (BPAF) were associated with decreased HDL-C levels, with nonlinear associations observed. Vanadium (V), lead (Pb), and silver (Ag) displayed U-shaped dose-response relationships with most lipid profiles. Multi-contaminant analyses indicated positive trends between contaminants mixture and total cholesterol (TC), triglycerides (TG), low density lipoprotein cholesterol (LDL-C), and non-high-density lipoprotein cholesterol (non-HDL-C). The interaction analyses showed that Se-Fe exhibited synergistic effects on LDL-C and non-HDL-C, and Se-Sn showed a synergistic effect on HDL-C. ConclusionsOur study suggested that exposure to metals and bisphenols was associated with changes in lipid levels, and demonstrated their combined and interactive effects.

Efficiency of computerized adaptive testing with a cognitively designed item bank.

An item bank is key to applying computerized adaptive testing (CAT). The traditional approach to developing an item bank requires content experts to design each item individually, which is a time-consuming and costly process. The cognitive design system (CDS) approach offers a solution by automating item generation. However, the CDS approach has a specific way of calibrating or predicting item difficulty that affects the measurement efficiency of CAT. A simulation study was conducted to compare the efficiency of CAT using both calibration and prediction models. The results show that, although the predictive model (linear logistic trait model; LLTM) shows a higher root mean square error (RMSE) than the baseline model (Rasch), it requires only a few additional items to achieve comparable RMSE. Importantly, the number of additional items needed decreases as the explanatory rate of the model increases. These results indicate that the slight reduction in measurement efficiency due to prediction item difficulty is acceptable. Moreover, the use of prediction item difficulty can significantly reduce or even eliminate the need for item pretesting, thereby reducing the costs associated with item calibration.

Association between Transient-Continuous Hypotension during Mechanical Thrombectomy for Acute Ischemic Stroke and Final Infarct Volume in Patients with Proximal Anterior Circulation Large Vessel Occlusion.

Background/Objectives: Periprocedural blood pressure changes in stroke patients with a large vessel occlusion are a known modifiable risk factor of unfavorable treatment outcomes. We aimed to evaluate the association between pre-revascularization hypotension and the final infarct volume. Methods: In our retrospective analysis, we included 214 consecutive stroke patients with an anterior circulation large vessel occlusion that underwent mechanical thrombectomy under general anesthesia. Noninvasively obtained blood pressure values prior to symptomatic vessel recanalization were analyzed as a predictor of post-treatment infarct size. Linear logistic regression models adjusted for predefined factors were used to investigate the association between blood pressure parameters and the final infarct volume. Results: In our cohort, higher baseline systolic blood pressure (aβ = 8.32, 95% CI 0.93-15.7, p = 0.027), its maximal absolute drop (aβ = 6.98, 95% CI 0.42-13.55, p = 0.037), and >40% mean arterial pressure decrease (aβ = 41.77, CI 95% 1.93-81.61, p = 0.040) were independently associated with higher infarct volumes. Similarly, continuous hypotension measured as intraprocedural cumulative time spent below either 100 mmHg (aβ = 3.50 per 5 min, 95% CI 1.49-5.50, p = 0.001) or 90 mmHg mean arterial pressure (aβ = 2.91 per 5 min, 95% CI 0.74-5.10, p = 0.010) was independently associated with a larger ischemia size. In the subgroup analysis of 151 patients with an M1 middle cerebral artery occlusion, two additional factors were independently associated with a larger ischemia size: systolic blood pressure maximal relative drop and >40% drop from pretreatment value (aβ = 1.36 per 1% lower than baseline, 95% CI 0.04-2.67, p = 0.043, and aβ = 43.01, 95% CI 2.89-83.1, p = 0.036, respectively). No associations between hemodynamic parameters and post-treatment infarct size were observed in the cohort of intracranial internal carotid artery occlusion. Conclusions: In patients with ischemic stroke due to a proximal middle cerebral artery occlusion, higher pre-thrombectomy treatment systolic blood pressure is associated with a larger final infarct size. In patients treated under general anesthesia, hypotension prior to the M1 portion of middle cerebral artery recanalization is independently correlated with the post-treatment infarct volume. In this group, every 5 min spent below the mean arterial pressure threshold of 100 mmHg is associated with a 4 mL increase in ischemia volume on a post-treatment NCCT. No associations between blood pressure and final infarct volume were present in the subgroup of patients with an intracranial internal carotid artery occlusion.

Trends and projections in fall death in the Netherlands from 1990 to 2045

BackgroundIncreasing life expectancy in high-income countries has been linked to a rise in fall mortality. In the Netherlands, mortality rates from falls have increased gradually from the 1950s, with some...

Evolution of minimally invasive liver surgery in France over the last decade.

Despite evidence of benefits on postoperative outcomes, minimally invasive liver surgery (MILS) had a very low diffusion up to 2014, and recent evolution is unknown. Our aim was to analyze the recent diffusion and adoption of MILS and compare the trends in indications, extent of resection, and institutional practice with open liver surgery (OLS). We analyzed the French nationwide, exhaustive cohort of all patients undergoing a liver resection in France between January 1, 2013 and December 31, 2022. Average annual percentage changes (AAPC) in the incidence of MILS and OLS were compared using mixed-effects log-linear regression models. Time trends were analyzed in terms of extent of resection, indication, and institutional practice. MILS represented 25.2% of 74,671 liver resections and year incidence doubled from 16.5% in 2013 to 35.4% in 2022. The highest AAPC were observed among major liver resections [+ 22.2% (19.5; 24.9) per year], primary [+ 10.2% (8.5; 12.0) per year], and secondary malignant tumors [+ 9.9% (8.2; 11.6) per year]. The highest increase in MILS was observed in university hospitals [+ 14.7% (7.7; 22.2) per year] performing 48.8% of MILS and in very high-volume (> 150 procedures/year) hospitals [+ 12.1% (9.0; 15.3) per year] performing 19.7% of MILS. OLS AAPC decreased for all indications and institutions and accelerated over time from -1.8% (-3.9; -0.3) per year in 2013-2018 to -5.9% (-7.9; -3.9) per year in 2018-2022 (p = 0.013). This is the first reported trend reversal between MILS and OLS. MILS has considerably increased at a national scale, crossing the 20% tipping point of adoption rate as defined by the IDEAL framework.

Networks, Marriage, and Socioeconomics: Comparing the Men and Women of the Islamic State

Social networks, marriage, and socioeconomic deprivation are considered determinants of participation in political violence. But whether they equally impact men and women’s involvement is not known. This study uses log-linear models to compare 468 Western men and women who joined the Islamic State. Significant differences between them are found. Though their education and employment levels are similar, women are less likely than men to be connected to pro-IS networks and more likely to have already been married before joining. The findings suggest that men joined the IS through their existing social networks, while women joined by breaking away from them.

Health-related quality of life by veterans RAND 12 and healthcare resource utilization in cancer patients with sleep disorders: insights from the Medical Expenditure Panel Survey.

This study aims to investigate the joint effects of cancer and sleep disorders on the health-related quality of life (HRQoL), healthcare resource utilization, and expenditures among US adults. Utilizing the 2018-2019 Medical Expenditure Panel Survey (MEPS) database, a sample of 25,274 participants was categorized into four groups based on cancer and sleep disorder status. HRQoL was assessed using the VR-12 questionnaire. Generalized linear model (GLM) with a log-linear regression model combined gamma distribution was applied for the analysis of healthcare expenditure data. Individuals with both cancer and sleep disorders (C+/S+) exhibited notably lower physical health (PCS) and mental health (MCS) scores-1.45 and 1.87 points lower, respectively. They also showed significantly increased clinic visits (2.12 times), outpatient visits (3.59 times), emergency visits (1.69 times), and total medical expenditures (2.08 times) compared to those without cancer or sleep disorders (C-/S-). In contrast, individuals with sleep disorders alone (C-/S+) had the highest number of prescription drug usage (2.26 times) and home health care days (1.76 times) compared to the reference group (C-/S-). Regardless of cancer presence, individuals with sleep disorders consistently reported compromised HRQoL. Furthermore, those with cancer and sleep disorders experienced heightened healthcare resource utilization, underscoring the considerable impact of sleep disorders on overall quality of life. The findings of this study address the importance of sleep disorders among cancer patients and their potential implications for cancer care. Healthcare professionals should prioritize screening, education, and tailored interventions to support sleep health in this population.

Performance of logistic regression and support vector machine conjunction with the GIS and RS in the landslide susceptibility assessment: Case study in Nakhon Si Thammarat, southern Thailand

The occurrence of landslides has risen in the past few decades, particularly in mountainous regions worldwide, including Nakhon Si Thammarat, southern Thailand. Despite various methods being employed for the initial management of landslide disasters, none have proven universally effective. The goal of this research is to create and assess landslide susceptibility maps (LSMs) within this area by employing support vector machine (SVM) and logistic regression, together with Geographic Information System (GIS) and Remote Sensing (RS) techniques. Eleven factors contributing to landslides were identified as topographic, environmental, and geological influences. The 365 landslides in the past were aimlessly selected into training (70%) and testing (30%) datasets. The four LSMs indicated that approximately 13%–20% of this study area exhibit a high susceptibility to landslides corresponding to the regions of high elevation with relatively steep slope angles. To evaluate and compare LSM models, the AUC value for training dataset were 0.977, 0.975, 0.958, and 0.967 and testing dataset were 0.973, 0.969, 0.956, and 0.964 for SVM with the radial basis function (rbf) kernel, SVM with polynomial deg 2, SVM with linear kernel and logistic regression models, respectively. Among these models, SVMs with rbf demonstrated the highest prediction rate. However, it requires a significant amount of time to choose the best parameters for achieving the highest accuracy prediction. In summary, these maps are applicable at the regional level to enhance the management of landslide hazards.

Modeling the Thermal Inactivation of Monascus ruber Ascospores Isolated from Green Olive (Arauco Cultivar) Storage Brine: An Alternative Strategy to Reduce Antifungal Chemical Agents.

Monascus ruber is an important fungus that causes spoilage in table olives, resulting in the darkening of the brine, the softening of the fruit, increased pH, and apparent mycelial growth. This study aimed to evaluate this resistance, providing a model to determine the optimal processing conditions for mitigating fungal contamination and prolonging shelf life without antifungal agents while optimizing pasteurization to reduce energy consumption. The resistance in brine (3.5% NaCl; pH 3.5) from Arauco cultivar green olives imported from Argentina was assessed. Four predictive models (log linear, log linear + shoulder, log linear + tail, log linear + shoulder + tail) estimated kinetic parameters for each survival curve. Log linear + shoulder + tail provided the best fit for 70 °C and 75 °C, with low RMSE (0.171 and 0.112) and high R2 values (0.98 and 0.99), respectively, while the log linear model was used for 80 °C. Decimal reduction times at 70, 75, and 80 °C were 24.8, 5.4, and 1.6 min, respectively, with a z-value of 8.2 °C. The current regulatory processes are insufficient to eliminate M. ruber at requisite levels, considering reduced antifungal agents.

Activation and disease control of patients on chronic hemodialysis: An observational study

Background and objectivePatient activation is a concept that refers to the willingness to manage one's health and medical care. To assess it, a patient activation measure (PAM) has been developed and validated. Several studies report low activation in patients with chronic diseases. However, information on activation in hemodialysis patients is scarce. The aim of the present study is to describe the activation level of patients on chronic treatment in an HD unit and its relationship with disease control parameters. Materials and methodsCross-sectional observational study in patients with advanced chronic kidney disease on chronic HD treatment. Ninety-six patients were included. Activation was measured with the PAM-13 questionnaire. Its relationship with descriptive variables (age, sex, comorbidity, studies, habitat) and disease control variables (vascular access, blood flow, potassaemia, phosphataemia, interdialytic gain) was studied. For this purpose, Spearman's correlation test, multiple linear regression model and logistic model were used as statistical methods. ResultsThe mean (SD) PAM-13 score was 63.19 (15.21). Activation was significantly associated with vascular access (P = 0.003), blood flow (P = 0.024), and interdialytic gain of patients (P = 0.008). ConclusionsActivation in patients on chronic hemodialysis treatment is low. Higher activation is related having an arteriovenous fistula, higher blood flow and lower interdialytic gain. Future studies are needed to confirm and apply our results.

Microstructural causes and mechanisms of crack growth rate transition and fluctuation of additively manufactured titanium alloy

Wire and arc additive manufacturing (WAAM) enables rapid near-net-shape fabrications of large-size parts and in-situ remanufacturing in many industry sectors. A comprehensive understanding of the fatigue failure mechanism of WAAM titanium alloys is a prerequisite for their widespread use in critical structural components subject to fatigue load. Here, the fatigue crack growth behavior of WAAM TA15 material is investigated. Fatigue crack growth tests are performed using compact tension specimens sampled from different locations and with different crack orientations of the WAAM TA15 block. The fatigue crack growth rate (FCGR) data exhibit two governing rates separated by a transition stress intensity factor value, ΔKn, and the degrees of fluctuation of the FCGR data in the two regimes are notably different. A piecewise log-linear model is first proposed by incorporating the Heaviside step function and ΔKn into the classical Paris’ model, allowing for the transition ΔKn to be determined by the data. The potential causes of the transition ΔKn are phenomenologically inferred via fractography and surface roughness profiling results. The critical microstructure affecting the value of ΔKn is identified by relating the crack tip cyclic plastic zone size at ΔKn to the sizes of main microstructures. The cause of different degrees of fluctuations in the two regimes separated by ΔKn is inferred by examining the microstructures within the plastic zone. The microstructural mechanisms of the local FCGR reduction and fluctuation are further identified and explained.

Childhood maltreatment and risk of metabolic dysfunction-associated steatotic liver disease – Evidence of sex-specific associations in the general population

Background and aimsChildhood maltreatment (CM) is linked to self-reported liver disease in adulthood. However, specific diagnostic entities, e.g., metabolic dysfunction-associated steatotic liver disease (MASLD) as the most frequent chronic liver disease, and sex-differences have previously not been considered. MethodsCross-sectional analyses were conducted in 4188 adults from a population-based cohort in Northeastern Germany after excluding individuals with excessive alcohol consumption, cirrhosis, or chronic viral hepatitis. CM-exposure was assessed using the Childhood Trauma Questionnaire (CTQ). Liver-related outcomes included serologic liver enzymes, fibrosis-4 score (FIB-4) and, in 1863 subjects who underwent magnetic resonance imaging examination, liver fat content. Sex-stratified linear regression and logistic regression models predicting liver-related outcomes and risk for MASLD, respectively, from overall CTQ scores were adjusted for age, school education, alcohol consumption, and waist circumference. Exploratory analyses investigated effects of CTQ-subscales on liver-related outcomes and risk for MASLD. ResultsIn both sexes, overall CM-exposure was associated with higher levels of serum aspartate aminotransferase and FIB-4 score. In men, effects were mainly driven by physical abuse, and in women by emotional neglect. Only in men, overall CM-exposure (β = 0.70, 95%-CI 0.26–1.13, p = 0.002) and four CTQ-subscales were associated with greater liver fat content, and physical abuse (aOR = 1.22, 95%-CI 1.02–1.46, p = 0.034) and physical neglect (aOR = 1.25, 95%-CI 1.04–1.49, p = 0.015) were associated with higher risk for MASLD. ConclusionsThese results suggest sex differences in the association between CM and objective serum and imaging markers of MASLD in adulthood. For men especially, a history of CM-exposure may increase risk of developing MASLD in adulthood.

Association of healthy and unhealthy plant-based diets with telomere length

Background & aimsPrevious studies have shown that plant-rich dietary patterns, such as the Mediterranean diet, are associated with longer telomeres. However, no association has been found between vegetarian diet and telomere length. We hypothesized that the quality of plant-based diets plays an important role in telomere length. MethodsData were obtained from the National Health and Nutrition Examination Survey 1999–2002. Diet was assessed using a 24-hour recall method. Plant-based diet quality was assessed using the overall plant-based diet index (PDI), healthy PDI (hPDI), and unhealthy PDI (uPDI). Telomere length was measured using quantitative PCR. Linear and ordinal logistic regression models were used to assess the association of PDIs with log-transformed telomere length and ordinal quintiles of telomere length in descending order, respectively. ResultsIn both regression models, the overall PDI was not associated with telomere length. The hPDI was associated with longer telomere length [percentage change = 2.34%, 95% confidence interval (CI): 0.42%, 4.31%, Ptrend = 0.016; odds ratio (OR) = 0.81, 95% CI: 0.69, 0.95, Ptrend = 0.013]. However, uPDI was associated with shorter telomere length (percentage change = -3.17%, 95% CI: -5.65%, -0.62%, Ptrend = 0.017; OR = 1.25, 95% CI:1.03, 1.53, Ptrend = 0.014) and this inverse association was stronger in the non-Hispanic white population (Pinteraction = 0.001 in both regression models). ConclusionsA plant-based dietary pattern rich in healthy plant foods is associated with longer telomeres. However, plant-based dietary patterns rich in unhealthy plant-based foods are associated with shorter telomere lengths, especially in non-Hispanic white populations.

Generating contingency tables with fixed marginal probabilities and dependence structures described by loglinear models

We present a method to generate contingency tables that follow loglinear models with prescribed marginal probabilities and dependence structures. We make use of (loglinear) Poisson regression, where the dependence structures, described using odds ratios, are implemented using an offset term. Other statistical models related to loglinear models that fall into the scope of this paper, such as the logistic regression model, the latent class model and the extended Rasch are discussed as well. We apply this methodology to carry out simulation studies in the context of population size estimation using dual system and triple system estimators, popular in official statistics. These estimators use contingency tables that summarize the counts of elements enumerated or captured within lists that are linked. The simulation is used to investigate these estimators in the situation that the model assumptions are fulfilled, and the situation that the model assumptions are violated.

Sex-Specific Associations between Maternal Thyroid Peroxidase Antibodies and Cognitive Development in Preschool Children: A Prospective Cohort Study.

Background: An association between maternal thyroid dysfunction throughout pregnancy and the subsequent risk of neurodevelopmental abnormalities in offspring has been demonstrated. However, the potential effects of maternal thyroid autoimmunity on neurodevelopment in the absence of maternal hypothyroidism remain unclear. Therefore, in this study, we explored the association between maternal thyroid peroxidase antibody (TPOAb) positivity and cognitive development in preschool children. Methods: A total of 1849 mother-child pairs were recruited from the Ma'anshan Birth Cohort (MABC) Study. During the follow-up period, an electrochemiluminescence immunoassay was used to retrospectively measure serum TPOAb levels in pregnant women. The cognitive development of preschool children was evaluated by using the Chinese version of the Wechsler Preschool and Primary Scale of Intelligence-Fourth Edition (WPPSI-IV). A growth mixture model was used to fit the trajectory of TPOAb. Multiple linear regression and logistic regression models were used to explore the associations between the developmental trajectory of TPOAb-positivity at different gestational periods and the cognitive development of preschool children by sex. Results: A total of 1849 mother-child pairs (mean [SD] age: 26.7 [3.6] years) were enrolled in the final study. Maternal TPOAb positivity in the first trimester was associated with a risk of below-average processing speed index in girls (OR: 2.07; 95% CI 1.06 to 4.01) and below-average full-scale intelligence quotient (FSIQ) in boys (OR: 2.36; 95% CI: 1.10 to 5.05). Maternal TPOAb positivity in the third trimester (T3) was associated with below-average working memory index (WMI) (OR: 2.51; 95% CI: 1.02 to 6.20) in girls. In girls, the WMI (β = -3.17, 95% CI: -5.82 to -0.52), fluid reasoning index (FRI) (β = -4.49, 95% CI: -7.18 to -1.80), and FSIQ score (β = -2.43, 95% CI: -4.77 to -0.08) decreased, whereas in mothers, the level of log-transformed thyroid peroxidase antibody (lgTPOAb) increased during pregnancy. Conclusions: Positive maternal TPOAb levels during pregnancy may be associated with poorer cognitive development in preschool children. These findings require independent confirmation in other populations.

The interplay between teleworking choice and commute distance

In this study, we model the telework-commute distance decision process as a package choice, and use a latent segmentation approach to recognize that some individuals may choose their telework arrangement first and then choose their commute distance (their residential location), while others may adopt a reverse causal behavioral process. The latent segment modeling methodology combines a multiple discrete–continuous probit model for telework adoption/intensity as the proportion of monthly workdays worked from home, from the office, and from a variable third workplace, with a log-linear regression model for commute distance (the home-to-office distance). The data for our analysis is drawn from a 2022 survey of Texas residents. Results suggest that about 20% of the population are likely “movers”, whose telework choices led to a residential move that changed commute distance, while the other 80% are “stayers”, whose commute distance at their predetermined (to telework) residential location changed telework habits. We further quantify the impact of teleworking on commute distances by computing the expected commute distance for several telework distribution preferences. A shift from 100% in-person work to 100% home-based remote work increases average commute distance by 64.8%, while working from a third workplace for any portion of a month reduces commute lengths relative to only home-based telework. In terms of monthly commute vehicle miles traveled (VMT), working from home for less than 18.6% of the month (about once a week) per worker actually increases overall monthly commute VMT. Monthly commute VMT reductions become tangible only at about 30–40% telework for each worker (about two days of telework per week for full-time workers with 22 workdays per month). In general, between 0 and 40% home-based telework per worker (with the remaining percentage at the office), there is a 10% commute VMT reduction for each 10% increase in home-based telework. In the range of 40% to 80% home-based telework, there is about a 13% commute VMT reduction for every 10% increase in home-based telework. And in the range of 80%-100% home-based telework reduction, there is about a 15% commute VMT reduction for every 10% increase in home-based telework.

Symptom Clusters in Acute SARS-CoV-2 Infection and Long COVID Fatigue in Male and Female Outpatients.

(1) Background: After an acute SARS-CoV-2 infection, patients are at risk of developing Long COVID, with fatigue as a frequent and serious health problem. Objectives: To identify symptom clusters in acute SARS-CoV-2 infections and investigate their associations with the development of Long COVID fatigue, and to examine sex-specific differences. (2) Methods: The analysis included a total of 450 COVID-19 outpatients, of whom 54.4% were female. The median ages of the men and women were 51 years (IQR 36.0; 60.0) and 48 years (IQR 33.0; 57.0), respectively. Data collection took place between November 2020 and May 2021, with a median time between acute SARS-CoV-2 infection and examination in the study center of 240 days (IQR 133; 326). The Fatigue Assessment Scale (FAS) was used to identify fatigue and its severity. A multiple correspondence analysis was used to group forty-two COVID-19 symptoms into seven symptom clusters. Logistic and log-linear regressions were used to investigate associations between acute symptom clusters and Long COVID fatigue as dichotomous and continuous outcome, respectively. (3) Results: Fatigue occurred more frequently in women than in men (45% vs. 25%) and the median FAS score, indicating severity of fatigue, was higher in women than in men. The comparison between men and women revealed notable differences in four out of seven clusters. The strongest associations between symptom clusters in infection and Long COVID fatigue were identified for the cluster "cognitive and mental symptoms". In the log-linear regression model, each additional symptom in this cluster was associated with an increase of the FAS score by 5.13% (95% CI: [0.04; 0.07]; p < 0.001). The results of the logistic regression models supported this finding. Each additional symptom in this symptom cluster increased the odds of fatigue by 42% (95% CI: [1.23; 1.66]; p < 0.001). (4) Conclusions: In our study in COVID-19 outpatients, a strong association was observed between the number of symptoms in the cluster "cognitive and mental symptoms" during acute SARS-CoV-2 infection and the risk of developing fatigue months later. The consequent use of preventive and therapeutic strategies is necessary to decrease the burden of fatigue in the context of Long COVID.

Desempenho da atenção primária à saúde no estado de São Paulo, Brasil, no período de 2010-2019

Abstract This article presents the results of an analysis of the performance of primary health care in São Paulo state over the last decade against a backdrop of financial crisis and health funding cuts. We conducted a time series analysis (2010-2019) of performance indicators across the following dimensions based on an adapted conceptual framework: health service performance, health system, and determinants of health. Annual percentage change was calculated for each indicator using a log-linear model. Performance across the indicators was generally positive; however, there was a decline in performance across indicators of quality of care (congenital syphilis, cesarean section rate and cervical cancer screening). The findings also show a potential rise in demand for public services (due to population aging and a reduction in the percentage of the population with private health insurance) and increase in health expenditure against a backdrop of falling GDP per capita.

Performance of primary health care in São Paulo state, Brazil, during the period 2010-2019.

This article presents the results of an analysis of the performance of primary health care in São Paulo state over the last decade against a backdrop of financial crisis and health funding cuts. We conducted a time series analysis (2010-2019) of performance indicators across the following dimensions based on an adapted conceptual framework: health service performance, health system, and determinants of health. Annual percentage change was calculated for each indicator using a log-linear model. Performance across the indicators was generally positive; however, there was a decline in performance across indicators of quality of care (congenital syphilis, cesarean section rate and cervical cancer screening). The findings also show a potential rise in demand for public services (due to population aging and a reduction in the percentage of the population with private health insurance) and increase in health expenditure against a backdrop of falling GDP per capita.

Metabolomics signatures of air pollution mixtures and lung cancer risk: A large-scale metabolome-wide association study in the Cancer Prevention Study cohorts.

10571 Background: Despite the well-established link between air pollution exposure and lung carcinogenesis, the underlying mechanism remains underexplored. While metabolomics has provided valuable molecular insights, existing air pollution metabolomics studies only assess biological changes to single air pollutants, without examining the join effects of air pollutant mixtures. We sought to identify metabolic signatures mediating the association between ambient air pollution mixtures and lung cancer risk. Methods: A total of 603 matched lung cancer case-control pairs were selected from the Cancer Prevention Study cohorts. Controls were matched to cases on age at blood draw, sex, race/ethnicity, and blood draw date. Plasma metabolomics was conducted using ultrahigh-performance liquid chromatography-tandem mass spectrometry. Air pollution mixtures include carbon monoxide, nitrogen dioxide, particulate matter, sulfur dioxide, and ozone, matched to subjects’ residential address at blood draw. We conducted an untargeted metabolome-wide association study with multivariable-adjusted linear and conditional logistic regression models to assess associations between metabolites and individual air pollutants and lung cancer risk, respectively, adjusting for individual and lifestyle-related covariates. We used a meet-in-the-middle (MITM) approach to identify potential mediators. Quantile g-computation was used to examine the effects of air pollution mixtures on metabolome perturbations to analyze the collective effects of multiple air pollutants concurrently. Results: Among 1,138 extracted metabolic features, 162 were significantly associated with the combined mixture (false discovery rate &lt; 0.2). Using MITM, no metabolites were associated with both air pollution mixture and lung cancer risk at FDR &lt; 0.2. At raw p &lt; 0.05, 16 metabolites were identified as potential mediators of the air pollution mixture and lung cancer risk. These metabolites, including 4-hydroxyphenylacetylglutamine, glutamate, and 3-aminoisobutyrate, were also significantly associated with the mixture at FDR &lt; 0.2. Conclusions: Findings from this analysis demonstrate the feasibility of considering multiple air pollutants as mixtures when conducting air pollution-related metabolomics investigations. Future exploration of the underlying biological mechanisms will be critical for validating pathways that participate in air pollution carcinogenicity. As lung cancer cases in never smokers continue to increase, it is pertinent to study air pollution and other environmental risk factors on cancer incidence.