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The objective of this study was to explore the impact of maternal AT during pregnancy on childhood asthma and wheezing, as well as the potential effect modifiers in this association. A cross-sectional study was implemented from December 2018 to March 2019 in Jinan to investigate the prevalence of childhood asthma and wheezing among aged 18 months to 3 years. Then, we conducted a case-control study based on population to explore the association between prenatal different AT exposure levels and childhood asthma and wheezing. The association was assessed by generalized additive models and logistic regression models, and stratified analyses were performed to explore potential effect modifiers. A total of 12,384 vaccinated children participated in screening for asthma and wheezing, 236 cases were screened, as well as 1445 controls were randomized. After adjusting for the covariates, childhood asthma and wheezing were significantly associated with cold exposure in the first trimester, with OR 1.731 (95% CI: 1.117–2.628), and cold exposure and heat exposure in the third trimester, with ORs 1.610 (95% CI: 1.030–2.473) and 2.039 (95% CI: 1.343–3.048). In the third trimester, enhanced impacts were found among girls, children whose distance of residence was close to the nearest main traffic road, and children whose parents have asthma. The study indicates that exposure to extreme AT during the first and third trimesters could increase the risk of childhood asthma and wheezing. [ABSTRACT FROM AUTHOR]

Subgroup meta-analysis can be used for comparing treatment effects between subgroups using information from multiple trials. If the effect of treatment is differential depending on subgroup, the results could enable personalization of the treatment. We propose using linear mixed models for estimating treatment effect modification in aggregate data meta-analysis. The linear mixed models capture existing subgroup meta-analysis methods while allowing for additional features such as flexibility in modeling heterogeneity, handling studies with missing subgroups and more. Reviews and simulation studies of the best suited models for estimating possible differential effect of treatment depending on subgroups have been studied mostly within individual participant data meta-analysis. While individual participant data meta-analysis in general is recommended over aggregate data meta-analysis, conducting an aggregate data subgroup meta-analysis could be valuable for exploring treatment effect modifiers before committing to an individual participant data subgroup meta-analysis. Additionally, using solely individual participant data for subgroup meta-analysis requires collecting sufficient individual participant data which may not always be possible. In this article, we compared existing methods with linear mixed models for aggregate data subgroup meta-analysis under a broad selection of scenarios using simulation and two case studies. Both the case studies and simulation studies presented here demonstrate the advantages of the linear mixed model approach in aggregate data subgroup meta-analysis. [ABSTRACT FROM AUTHOR]

Background: Instrumental variables (IVs) can be used to provide evidence as to whether a treatment X has a causal effect on an outcome Y. Even if the instrument Z satisfies the three core IV assumptions of relevance, independence, and exclusion restriction, further assumptions are required to identify the average causal effect (ACE) of X on Y. Sufficient assumptions for this include homogeneity in the causal effect of X on Y ; homogeneity in the association of Z with X ; and no effect modification. Methods: We describe the no simultaneous heterogeneity assumption, which requires the heterogeneity in the X - Y causal effect to be mean independent of (i.e., uncorrelated with) both Z and heterogeneity in the Z - X association. This happens, for example, if there are no common modifiers of the X - Y effect and the Z - X association, and the X - Y effect is additive linear. We illustrate the assumption of no simultaneous heterogeneity using simulations and by re-examining selected published studies. Results: Under no simultaneous heterogeneity, the Wald estimand equals the ACE even if both homogeneity assumptions and no effect modification (which we demonstrate to be special cases of—and therefore stronger than—no simultaneous heterogeneity) are violated. Conclusions: The assumption of no simultaneous heterogeneity is sufficient for identifying the ACE using IVs. Since this assumption is weaker than existing assumptions for ACE identification, doing so may be more plausible than previously anticipated. [ABSTRACT FROM AUTHOR]

Background: Physical activity has been shown to affect the mammalian target of rapamycin (mTOR) signaling pathway and consequently breast carcinogenesis. Given that Black women in the USA are less physically active, it is not well understood whether there are gene–environment interactions between mTOR pathway genes and physical activity in relation to breast cancer risk in Black women. Methods: The study included 1398 Black women (567 incident breast cancer cases and 831 controls) from the Women's Circle of Health Study (WCHS). We examined interactions between 43 candidate single-nucleotide polymorphisms (SNPs) in 20 mTOR pathway genes with levels of vigorous physical activity in relation to breast cancer risk overall and by ER-defined subtypes using Wald test with 2-way interaction term and multivariable logistic regression. Results: AKT1 rs10138227 (C > T) and AKT1 rs1130214 (C > A) were only associated with a decreased risk of ER + breast cancer among women with vigorous physical activity (odds ratio [OR] = 0.15, 95% confidence interval (CI) 0.04, 0.56, for each copy of the T allele, p-interaction = 0.007 and OR = 0.51, 95% CI 0.27, 0.96, for each copy of the A allele, p-interaction = 0.045, respectively). MTOR rs2295080 (G > T) was only associated with an increased risk of ER + breast cancer among women with vigorous physical activity (OR = 2.24, 95% CI 1.16, 4.34, for each copy of the G allele; p-interaction = 0.043). EIF4E rs141689493 (G > A) was only associated with an increased risk of ER- breast cancer among women with vigorous physical activity (OR = 20.54, 95% CI 2.29, 184.17, for each copy of the A allele; p-interaction = 0.003). These interactions became non-significant after correction for multiple testing (FDR-adjusted p-value > 0.05). Conclusion: Our findings suggest that mTOR genetic variants may interact with physical activity in relation to breast cancer risk in Black women. Future studies should confirm these findings. [ABSTRACT FROM AUTHOR]

Background: Obesity is known to stimulate the mammalian target of rapamycin (mTOR) signaling pathway and both obesity and the mTOR signaling pathway are implicated in breast carcinogenesis. We investigated potential gene-environment interactions between mTOR pathway genes and obesity in relation to breast cancer risk among Black women. Methods: The study included 1,655 Black women (821 incident breast cancer cases and 834 controls) from the Women's Circle of Health Study (WCHS). Obesity measures including body mass index (BMI); central obesity i.e., waist circumference (WC) and waist/hip ratio (WHR); and body fat distribution (fat mass, fat mass index and percent body fat) were obtained by trained research staff. We examined the associations of 43 candidate single-nucleotide polymorphisms (SNPs) in 20 mTOR pathway genes with breast cancer risk using multivariable logistic regression. We next examined interactions between these SNPs and measures of obesity using Wald test with 2-way interaction term. Results: The variant allele of BRAF (rs114729114 C > T) was associated with an increase in overall breast cancer risk [odds ratio (OR) = 1.81, 95% confidence interval (CI) 1.10–2.99, for each copy of the T allele] and the risk of estrogen receptor (ER)-defined subtypes (ER+ tumors: OR = 1.83, 95% CI 1.04,3.29, for each copy of the T allele; ER- tumors OR = 2.14, 95% CI 1.03,4.45, for each copy of the T allele). Genetic variants in AKT, AKT1, PGF, PRKAG2, RAPTOR, TSC2 showed suggestive associations with overall breast cancer risk and the risk of, ER+ and ER– tumors (range of p-values = 0.040–0.097). We also found interactions of several of the SNPs with BMI, WHR, WC, fat mass, fat mass index and percent body fat in relation to breast cancer risk. These associations and interactions, however, became nonsignificant after correction for multiple testing (FDR-adjusted p-value > 0.05). Conclusion: We found associations between mTOR genetic variants and breast cancer risk as well as gene and body fatness interactions in relation to breast cancer risk. However, these associations and interactions became nonsignificant after correction for multiple testing. Future studies with larger sample sizes are required to confirm and validate these findings. [ABSTRACT FROM AUTHOR]

Herpes Simplex Virus Type 2 (HSV-2) has been associated with depression, but the relationship has yet to be explored with respect to gender and sexual orientation in a nationally representative sample to help identify individuals at higher risk for depression. A dataset from National Health and Nutrition Examination Survey 2009–2014 was used in this study. Multivariable logistic regression models were constructed to test effect modification on both the multiplicative and additive scale using a sample of 57,684 subjects. Effect modification by sexual minority status was not significant on either the multiplicative scale (Ratio of ORs: 0.74, 95 % CI: 0.37–1.50, p = 0.395) or the additive scale (RERI: −0.22, 95%CI: −2.27–1.84, p = 0.833). Meanwhile, biological sex assigned at birth was a significant modifier only on the additive scale (RERI: 0.82, 95 % CI: 0.004–1.64, P = 0.049). Specifically, females (OR: 1.43, 95 % CI: 1.03–1.97, P = 0.032) had greater odds of having depressive symptoms compared with males (OR: 1.20, 95 % CI: 0.69–2.08, p = 0.509) after the HSV-2 infection. The analysis was based on a cross-sectional study; further investigation using longitudinal datasets might be beneficial. Sexual minority status did not modify the association between HSV-2 infection and having depressive symptoms. However, biological sex assigned at birth was a modifier only on the additive but not the multiplicative scale. Health workers should be alert for depression symptoms in females with HSV-2 infection. • Sexual minority status did not modify the association between HSV-2 infection and depression. • Biological sex was a modifier on the association between HSV-2 infection and depression only on the additive scale. • Females had greater odds of having depressive symptoms compared with males after the HSV-2 infection. [ABSTRACT FROM AUTHOR]

Effect modification (EM) may cause bias in network meta‐analysis (NMA). Existing population adjustment NMA methods use individual patient data to adjust for EM but disregard available subgroup information from aggregated data in the evidence network. Additionally, these methods often rely on the shared effect modification (SEM) assumption. In this paper, we propose Network Meta‐Interpolation (NMI): a method using subgroup analyses to adjust for EM that does not assume SEM. NMI balances effect modifiers across studies by turning treatment effect (TE) estimates at the subgroup‐ and study level into TE and standard errors at EM values common to all studies. In an extensive simulation study, we simulate two evidence networks consisting of four treatments, and assess the impact of departure from the SEM assumption, variable EM correlation across trials, trial sample size and network size. NMI was compared to standard NMA, network meta‐regression (NMR) and Multilevel NMR (ML‐NMR) in terms of estimation accuracy and credible interval (CrI) coverage. In the base case non‐SEM dataset, NMI achieved the highest estimation accuracy with root mean squared error (RMSE) of 0.228, followed by standard NMA (0.241), ML‐NMR (0.447) and NMR (0.541). In the SEM dataset, NMI was again the most accurate method with RMSE of 0.222, followed by ML‐NMR (0.255). CrI coverage followed a similar pattern. NMI's dominance in terms of estimation accuracy and CrI coverage appeared to be consistent across all scenarios. NMI represents an effective option for NMA in the presence of study imbalance and available subgroup data. [ABSTRACT FROM AUTHOR]

The gut microbiota is increasingly implicated in the health and metabolism of its human host. The host's diet is a major component influencing the composition and function of the gut microbiota, and mounting evidence suggests that the composition and function of the gut microbiota influence the host's metabolic response to diet. This effect of the gut microbiota on personalized dietary response is a growing focus of precision nutrition research and may inform the effort to tailor dietary advice to the individual. Because the gut microbiota has been shown to be malleable to some extent, it may also allow for therapeutic alterations of the gut microbiota in order to alter response to certain dietary components. This article is the second in a 2-part review of the current research in the field of precision nutrition incorporating the gut microbiota into studies investigating interindividual variability in response to diet. Part I reviews the methods used by researchers to design and carry out such studies as well as analyze the results subsequently obtained. Part II reviews the findings of these studies and discusses the gaps in our current knowledge and directions for future research. The studies reviewed provide the current understanding in this field of research and a foundation from which we may build, utilizing and expanding upon the methods and results they present to inform future studies.

Health care is increasingly focused on health at the individual level. In the rapidly evolving field of precision nutrition, researchers aim to identify how genetics, epigenetics, and the microbiome interact to shape an individual's response to diet. With this understanding, personalized responses can be predicted and dietary advice can be tailored to the individual. With the integration of these complex sources of data, an important aspect of precision nutrition research is the methodology used for studying interindividual variability in response to diet. This article stands as the first in a 2-part review of current research investigating the contribution of the gut microbiota to interindividual variability in response to diet. Part I reviews the methods used by researchers to design and carry out such studies as well as the statistical and bioinformatic methods used to analyze results. Part II reviews the findings of these studies, discusses gaps in our current knowledge, and summarizes directions for future research. Taken together, these reviews summarize the current state of knowledge and provide a foundation for future research on the role of the gut microbiome in precision nutrition.

Abstract Background Environmental exposures such as traffic may contribute to asthma morbidity including recurrent emergency department (ED) visits. However, these associations are often confounded by socioeconomic status and health care access. Objective This study aims to assess the association between traffic density and recurrence of asthma ED visits in the primarily low income Medicaid population in New York State (NYS) between 2005 and 2015. Methods The primary outcome of interest was a recurrent asthma ED visit within 1-year of index visit. Traffic densities (weighted for truck traffic) were spatially linked based on home addresses. Bivariate and multivariate logistic regression analyses were conducted to identify factors predicting recurrent asthma ED visits. Results In a multivariate model, Medicaid recipients living within 300-m of a high traffic density area were at a statistically significant risk of a recurrent asthma ED visit compared to those in a low traffic density area (OR = 1.31; 95% CI:1.24,1.38). Additionally, we evaluated effect measure modification for risk of recurrent asthma visits associated with traffic exposure by socio-demographic factors. The highest risk was found for those exposed to high traffic and being male (OR = 1.87; 95% CI:1.46,2.39), receiving cash assistance (OR = 2.11; 95% CI:1.65,2.72), receiving supplemental security income (OR = 2.21; 95% CI:1.66,2.96) and being in the 18.44 age group (OR = 1.59;95% CI 1.48,1.70) was associated with the highest risk of recurrent asthma ED visit. Black non-Hispanics (OR = 2.35; 95% CI:1.70,3.24), Hispanics (OR = 2.13; 95% CI:1.49,3.04) and those with race listed as “Other” (OR = 1.89 95% CI:1.13,3.16) in high traffic areas had higher risk of recurrent asthma ED visits as compared to White non-Hispanics in low traffic areas. Conclusion We observed significant persistent disparities in asthma morbidity related to traffic exposure and race/ethnicity in a low-income population. Our findings suggest that even within a primarily low-income study population, socioeconomic differences persist. These differences in susceptibility in the extremely low-income group may not be apparent in health studies that use Medicaid enrollment as a proxy for low SES.

Abstract Background Inorganic arsenic (iAs) is a ubiquitous metalloid and drinking water contaminant. Prenatal exposure is associated with birth outcomes across multiple studies. During metabolism, iAs is sequentially methylated to mono- and di-methylated arsenical species (MMAs and DMAs) to facilitate whole body clearance. Inefficient methylation (e.g., higher urinary % MMAs) is associated with increased risk of certain iAs-associated diseases. One-carbon metabolism factors influence iAs methylation, modifying toxicity in adults, and warrant further study during the prenatal period. The objective of this study was to evaluate folate, vitamin B12, and homocysteine as modifiers of the relationship between biomarkers of iAs methylation efficiency and birth outcomes. Methods Data from the Biomarkers of Exposure to ARsenic (BEAR) pregnancy cohort (2011–2012) with maternal urine and cord serum arsenic biomarkers and maternal serum folate, vitamin B12, and homocysteine concentrations were utilized. One-carbon metabolism factors were dichotomized using clinical cutoffs and median splits. Multivariable linear regression models were fit to evaluate associations between each biomarker and birth outcome overall and within levels of one-carbon metabolism factors. Likelihood ratio tests of full and reduced models were used to test the significance of statistical interactions on the additive scale (α = 0.10). Results Among urinary biomarkers, % U-MMAs was most strongly associated with birth weight (β = − 23.09, 95% CI: − 44.54, − 1.64). Larger, more negative mean differences in birth weight were observed among infants born to women who were B12 deficient (β = − 28.69, 95% CI: − 53.97, − 3.42) or experiencing hyperhomocysteinemia (β = − 63.29, 95% CI: − 154.77, 28.19). Generally, mean differences in birth weight were attenuated among infants born to mothers with higher serum concentrations of folate and vitamin B12 (or lower serum concentrations of homocysteine). Effect modification by vitamin B12 and homocysteine was significant on the additive scale for some associations. Results for gestational age were less compelling, with an approximate one-week mean difference associated with C-tAs (β = 0.87, 95% CI: 0, 1.74), but not meaningful otherwise. Conclusions Tissue distributions of iAs and its metabolites (e.g., % MMAs) may vary according to serum concentrations of folate, vitamin B12 and homocysteine during pregnancy. This represents a potential mechanism through which maternal diet may modify the harms of prenatal exposure to iAs.

BACKGROUND: High prepregnancy body mass index is one of the most common risk factors for adverse perinatal events. OBJECTIVE: This study aimed to assess whether the association between maternal body mass index and adverse perinatal outcome is modified by other concomitant maternal risk factors. STUDY DESIGN: This was a retrospective cohort study of all singleton live births and stillbirths in the United States from 2016 to 2017, using data from the National Center for Health Statistics. Logistic regression was used to estimate the adjusted odds ratios and 95% confidence intervals between prepregnancy body mass index and a composite outcome of stillbirth, neonatal death, and severe neonatal morbidity. Modification of this association by maternal age, nulliparity, chronic hypertension, and prepregnancy diabetes mellitus was assessed on both multiplicative and additive scales. RESULTS: The study population included 7,576,417 women with singleton pregnancy; 254,225 (3.5%) were underweight, 3,220,432 (43.9%) had normal body mass index, 1,918,480 (26.1%) were overweight, and 1,062,177 (14.4%), 516,693 (7.0%), and 365,357 (5.0%) had class I, II, and III obesity, respectively. Rates of the composite outcome increased with increasing body mass index above normal values, compared with women with normal body mass index. Nulliparity (289,776; 38.6%), chronic hypertension (135,328; 1.8%), and prepregnancy diabetes mellitus (67,744; 0.89%) modified the association between body mass index and the composite perinatal outcome on both the additive and multiplicative scales. Nulliparous (vs parous) women had a higher rate of increase in adverse outcomes with increasing body mass index. For example, in nulliparous women, class III obesity was associated with 1.8-fold higher odds compared with normal body mass index (adjusted odds ratio, 1.77; 95% confidence interval, 1.73–1.83), whereas in parous women, the adjusted odds ratio was 1.35 (95% confidence interval, 1.32–1.39). Women with chronic hypertension or prepregnancy diabetes mellitus had higher outcome rates overall; however, the dose-response relationship with increasing body mass index was absent. Although the composite outcome rates increased with maternal age, the risk curves were relatively similar across obesity classes in all maternal age groups. Overall, underweight women had 7% higher odds of the composite outcome, and this increased to 21% in parous women. CONCLUSION: Women with elevated prepregnancy body mass index are at increased risk of adverse perinatal outcomes, and the magnitude of these risks differs by concomitant risk factors, including prepregnancy diabetes mellitus, chronic hypertension, and nulliparity. In particular, in woman with chronic hypertension or prepregnancy diabetes mellitus, there is no impact of increasing body mass index on adverse perinatal outcomes. However, overall rates remain high, and prepregnancy prevention of hypertension and diabetes mellitus should be emphasized among all women irrespective of body mass index.

Background: Cardiovascular disease (CVD) mortality is associated with long-term particulate matter (PM) exposure. However, evidence from large, highly-exposed population cohort and observational-data-based causal inference approaches remains limited. Aims: We examined the potential causal links between PM exposure and the CVD mortality in South China. Methods: 580,757 participants were recruited during 2009–2015 and followed up through 2020. Satellite-based annual concentrations of PM2.5, PM10, and PMcoarse (i.e., PM10 - PM2.5) at 1 km2 spatial resolution were estimated and assigned to each participant. Marginal structural Cox models with time-varying covariates, adjusted using inverse probability weighting, were developed to evaluate the association between prolonged PM exposure and CVD mortality. Results: For overall CVD mortality, the hazard ratios and 95% confidence interval for each 1 μg/m3 increase in the annual average concentration of PM2.5, PM10, and PMcoarse were 1.033 (1.028–1.037), 1.028 (1.024–1.032), and 1.022 (1.012–1.033), respectively. All three PMs were linked to a higher mortality risk for myocardial infarction and ischemic heart disease (IHD). The mortality risk of chronic IHD and hypertension was linked to PM2.5 and PM10. Significant association between PMcoarse and other heart disease mortality was also observed. The older, women, less-educated participants, or inactive participants exhibited particularly higher susceptibility. Participants who were generally exposed to PM10 concentrations below 70 μg/m3 were more vulnerable to PM2.5-, PM10- and PMcoarse-CVD mortality risks. Conclusion: This large cohort study provides evidence for the potential causal links between increased CVD mortality and ambient PM exposure, as well as socio-demographics linked to the highest vulnerability.

Background: Evidence on the potential interactive effects of heat and ambient air pollution on cause-specific mortality is inconclusive and limited to selected locations. Objectives: We investigated the effects of heat on cardiovascular and respiratory mortality and its modification by air pollution during summer months (six consecutive hottest months) in 482 locations across 24 countries. Methods: Location-specific daily death counts and exposure data (e.g., particulate matter with diameters ≤ 2.5 µm [PM2.5]) were obtained from 2000 to 2018. We used location-specific confounder-adjusted Quasi-Poisson regression with a tensor product between air temperature and the air pollutant. We extracted heat effects at low, medium, and high levels of pollutants, defined as the 5th, 50th, and 95th percentile of the location-specific pollutant concentrations. Country-specific and overall estimates were derived using a random-effects multilevel meta-analytical model. Results: Heat was associated with increased cardiorespiratory mortality. Moreover, the heat effects were modified by elevated levels of all air pollutants in most locations, with stronger effects for respiratory than cardiovascular mortality. For example, the percent increase in respiratory mortality per increase in the 2-day average summer temperature from the 75th to the 99th percentile was 7.7% (95% Confidence Interval [CI] 7.6–7.7), 11.3% (95%CI 11.2–11.3), and 14.3% (95% CI 14.1–14.5) at low, medium, and high levels of PM2.5, respectively. Similarly, cardiovascular mortality increased by 1.6 (95%CI 1.5–1.6), 5.1 (95%CI 5.1–5.2), and 8.7 (95%CI 8.7–8.8) at low, medium, and high levels of O3, respectively. Discussion: We observed considerable modification of the heat effects on cardiovascular and respiratory mortality by elevated levels of air pollutants. Therefore, mitigation measures following the new WHO Air Quality Guidelines are crucial to enhance better health and promote sustainable development.

BackgroundAlthough the association between short-term air pollution exposure and certain hospitalizations has been well documented, evidence on the effect of longer-term (e. g., monthly) air pollution on a comprehensive set of outcomes is still limited.MethodA total of 68,416 people in South China were enrolled and followed up during 2019–2020. Monthly air pollution level was estimated using a validated ordinary Kriging method and assigned to individuals. Time-dependent Cox models were developed to estimate the relationship between monthly PM10 and O3 exposures and the all-cause and cause-specific hospitalizations after adjusting for confounders. The interaction between air pollution and individual factors was also investigated.ResultsOverall, each 10 μg/m3 increase in PM10 concentration was associated with a 3.1% (95%CI: 1.3%−4.9%) increment in the risk of all-cause hospitalization. The estimate was even greater following O3 exposure (6.8%, 5.5%−8.2%). Furthermore, each 10 μg/m3 increase in PM10 was associated with a 2.3%-9.1% elevation in all the cause-specific hospitalizations except for those related to respiratory and digestive diseases. The same increment in O3 was relevant to a 4.7%−22.8% elevation in the risk except for respiratory diseases. Additionally, the older individuals tended to be more vulnerable to PM10 exposure (Pinteraction: 0.002), while the alcohol abused and those with an abnormal BMI were more vulnerable to the impact of O3 (Pinteraction: 0.052 and 0.011). However, the heavy smokers were less vulnerable to O3 exposure (Pinteraction: 0.032).ConclusionWe provide comprehensive evidence on the hospitalization hazard of monthly PM10 and O3 exposure and their interaction with individual factors.

Background: Network meta-analysis (NMA) and indirect comparisons combine aggregate data (AgD) from multiple studies on treatments of interest but may give biased estimates if study populations differ. Population adjustment methods such as multilevel network meta-regression (ML-NMR) aim to reduce bias by adjusting for differences in study populations using individual patient data (IPD) from 1 or more studies under the conditional constancy assumption. A shared effect modifier assumption may also be necessary for identifiability. This article aims to demonstrate how the assumptions made by ML-NMR can be assessed in practice to obtain reliable treatment effect estimates in a target population. Methods: We apply ML-NMR to a network of evidence on treatments for plaque psoriasis with a mix of IPD and AgD trials reporting ordered categorical outcomes. Relative treatment effects are estimated for each trial population and for 3 external target populations represented by a registry and 2 cohort studies. We examine residual heterogeneity and inconsistency and relax the shared effect modifier assumption for each covariate in turn. Results: Estimated population-average treatment effects were similar across study populations, as differences in the distributions of effect modifiers were small. Better fit was achieved with ML-NMR than with NMA, and uncertainty was reduced by explaining within- and between-study variation. We found little evidence that the conditional constancy or shared effect modifier assumptions were invalid. Conclusions: ML-NMR extends the NMA framework and addresses issues with previous population adjustment approaches. It coherently synthesizes evidence from IPD and AgD studies in networks of any size while avoiding aggregation bias and noncollapsibility bias, allows for key assumptions to be assessed or relaxed, and can produce estimates relevant to a target population for decision-making. Highlights: Multilevel network meta-regression (ML-NMR) extends the network meta-analysis framework to synthesize evidence from networks of studies providing individual patient data or aggregate data while adjusting for differences in effect modifiers between studies (population adjustment). We apply ML-NMR to a network of treatments for plaque psoriasis with ordered categorical outcomes. We demonstrate for the first time how ML-NMR allows key assumptions to be assessed. We check for violations of conditional constancy of relative effects (such as unobserved effect modifiers) through residual heterogeneity and inconsistency and the shared effect modifier assumption by relaxing this for each covariate in turn. Crucially for decision making, population-adjusted treatment effects can be produced in any relevant target population. We produce population-average estimates for 3 external target populations, represented by the PsoBest registry and the PROSPECT and Chiricozzi 2019 cohort studies. [ABSTRACT FROM AUTHOR]

Race is a social construct, commonly used in epidemiologic research to adjust for confounding. However, adjustment of race may mask racial disparities, thereby perpetuating structural racism. We conducted a systematic review of articles published in Epidemiology and American Journal of Epidemiology between 2020 and 2021 to (1) understand how race, ethnicity, and similar social constructs were operationalized, used, and reported; and (2) characterize good and poor practices of utilization and reporting of race data on the basis of the extent to which they reveal or mask systemic racism. Original research articles were considered for full review and data extraction if race data were used in the study analysis. We extracted how race was categorized, used—as a descriptor, confounder, or for effect measure modification (EMM)—and reported if the authors discussed racial disparities and systemic bias–related mechanisms responsible for perpetuating the disparities. Of the 561 articles, 299 had race data available and 192 (34.2%) used race data in analyses. Among the 160 US-based studies, 81 different racial categorizations were used. Race was most often used as a confounder (52%), followed by effect measure modifier (33%), and descriptive variable (12%). Fewer than 1 in 4 articles (22.9%) exhibited good practices (EMM along with discussing disparities and mechanisms), 63.5% of the articles exhibited poor practices (confounding only or not discussing mechanisms), and 13.5% were considered neither poor nor good practices. We discuss implications and provide 13 recommendations for operationalization, utilization, and reporting of race in epidemiologic and public health research. [ABSTRACT FROM AUTHOR]

Health research often aims to investigate whether the effect of an exposure variable is common across different subgroups of individuals, but sometimes the variable defining subgroups is not recorded in all individuals. We propose and evaluate two methods for estimation of the marginal causal effect of an exposure variable within subgroups in the observational setting where the subgroup variable is incompletely observed. The first approach involves doubly weighted estimating functions with one weight based on a propensity score for exposure and a second weight addressing the selection bias when analyses are restricted to individuals with complete data. The second approach uses the inverse probability of exposure weights in conjunction with multiple imputation for the incomplete subgroup variable. The resulting estimators are consistent when the auxiliary models are correctly specified; we assess the finite sample performance via simulation. An illustrative analysis is provided involving patients with psoriatic arthritis treated with biologic therapy where interest lies in the effect of therapy according to the presence or absence of the human leukocyte antigen marker HLA-B27 which is incompletely observed. [ABSTRACT FROM AUTHOR]

Background: Early antenatal care (ANC) is essential for improving maternal and child health outcomes. The primary aims of this study were to 1) estimate the association between partners' education attainment and early ANC, and 2) determine whether partners' level of education modified the relationship between mothers' education, mothers' age, planned pregnancy, employment status and early ANC.Methods: Data were obtained from a cross-sectional study conducted from April to May 2021 among 519 mothers with a live birth in the past year in the Nabdam district in the Upper East Region in northern Ghana. Generalized estimating equations were used to assess whether partners' level of education modified the relationship between mothers' education, mothers' age, planned pregnancy, employment status and early ANC. Effect modification was assessed on the additive and multiplicative scales using adjusted prevalence ratios (aPR) and corresponding 95% confidence intervals.Results: Mothers whose partners had secondary or higher education had a 26% higher prevalence of early ANC compared to mothers whose partners had less than a secondary level of education (aPR: 1.26, 95% CI: 1.05,1.51). There was evidence of effect modification by partners' education on the relationship between planned pregnancy and early ANC on both the additive (Relative excess risk due to interaction [RERI]: 0.61, 95% CI: 0.07,0.99), and multiplicative (ratio of PRs: 1.64, 95% CI: 1.01,2.70) scales. Among mothers whose partners had less than secondary education, mothers who had teenage pregnancy (i.e., aged 18-19 years old during pregnancy) were less likely to have early ANC compared to those who did not have teenage pregnancy (aPR: 0.71, 95% CI: 0.53,0.97). Among mothers whose partners had a secondary or higher education, early ANC was more prevalent among employed mothers compared to those who were unemployed (aPR: 1.27, 95% CI: 1.02,1.57).Conclusions: Our findings suggest that whilst mothers whose partners had a secondary or higher education were more likely to initiate early ANC, supporting such women to plan their pregnancies can further increase the coverage of early ANC. [ABSTRACT FROM AUTHOR]

Abstract Background Early antenatal care (ANC) is essential for improving maternal and child health outcomes. The primary aims of this study were to 1) estimate the association between partners’ education attainment and early ANC, and 2) determine whether partners’ level of education modified the relationship between mothers’ education, mothers’ age, planned pregnancy, employment status and early ANC. Methods Data were obtained from a cross-sectional study conducted from April to May 2021 among 519 mothers with a live birth in the past year in the Nabdam district in the Upper East Region in northern Ghana. Generalized estimating equations were used to assess whether partners’ level of education modified the relationship between mothers’ education, mothers’ age, planned pregnancy, employment status and early ANC. Effect modification was assessed on the additive and multiplicative scales using adjusted prevalence ratios (aPR) and corresponding 95% confidence intervals. Results Mothers whose partners had secondary or higher education had a 26% higher prevalence of early ANC compared to mothers whose partners had less than a secondary level of education (aPR: 1.26, 95% CI: 1.05,1.51). There was evidence of effect modification by partners’ education on the relationship between planned pregnancy and early ANC on both the additive (Relative excess risk due to interaction [RERI]: 0.61, 95% CI: 0.07,0.99), and multiplicative (ratio of PRs: 1.64, 95% CI: 1.01,2.70) scales. Among mothers whose partners had less than secondary education, mothers who had teenage pregnancy (i.e., aged 18–19 years old during pregnancy) were less likely to have early ANC compared to those who did not have teenage pregnancy (aPR: 0.71, 95% CI: 0.53,0.97). Among mothers whose partners had a secondary or higher education, early ANC was more prevalent among employed mothers compared to those who were unemployed (aPR: 1.27, 95% CI: 1.02,1.57). Conclusions Our findings suggest that whilst mothers whose partners had a secondary or higher education were more likely to initiate early ANC, supporting such women to plan their pregnancies can further increase the coverage of early ANC.

• A nested case-control study was conducted within a large community-based cohort in China. • Plasma isoleucine and total branched-chain amino acids at baseline were significantly associated with risk of ischemic stroke in women, but not in men. • The findings highlight sex differences in BCAAs metabolism and their potential roles in stroke pathogenesis. The aim of this study was to investigate the prospective associations between plasma branched-chain amino acids (BCAAs) and the risk of ischemic stroke in men and women. We conducted a nested case-control study within a community-based cohort in China. The cohort consisted of 15,926 participants in 2013-2018. A total of 321 ischemic stroke cases were identified during the follow up and individually matched with 321 controls by date of birth (±1 year) and sex. Females accounted for 55.8% (n = 358, 179 cases vs 179 controls) of the study population. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to assess the association between plasma BCAAs and ischemic stroke risk by conditional logistic regression. Elevated plasma isoleucine was associated with a higher risk of ischemic stroke in women. The OR for the highest compared to the lowest quartile was 2.22 (95% CI: 1.11-4.44, P trend = 0.005) after adjustment for body mass index, education attainment, smoking, hypertension, renal function, menopause and physical activity. A similar association was found for total BCAAs (adjusted OR = 2.03, 95% CI: 1.05-3.95, P trend = 0.04). In contrast, no significant association of plasma BCAAs with ischemic stroke risk was observed in men. Plasma isoleucine and total BCAAs were significantly associated with ischemic stroke risk in women, but not in men, highlighting sex differences in BCAAs metabolism and stroke pathogenesis. [ABSTRACT FROM AUTHOR]

Abstract Background Hand, foot, and mouth disease (HFMD) is an epidemic infectious disease in China. Relationship of neighborhood greenness with human health has been widely studied, yet its association with severe HFMD has not yet been established. Methods Individual HFMD cases that occurred in Guangdong province in 2010 were recruited and were categorised into mild and severe cases. Residential greenness was assessed using global land cover data. We used a case-control design (i.e., severe versus mild cases) with logistic regression models to assess the association between neighborhood greenness and HFMD severity. Effect modification was also examined. Results A total of 131,606 cases were included, of whom 130,840 were mild cases and 766 were severe cases. In an unadjusted model, HFMD severity increased with higher proportion of neighborhood greenness (odds ratio, OR = 1.029, 95%CI: 1.009–1.050). The greenness-HFMD severity association remained (OR = 1.031, 95%CI: 1.006–1.057) after adjusting for population density, demographic variables and climate variables. Both population density (Z = 4.148, P 5 & ≤7: OR = 1.071, 95%CI: 1.024–1.120; subgroup of > 7: OR = 1.065, 95%CI: 1.034–1.097) on HFMD severity. As to relative humidity, statistically significant association between greenness and HFMD severity was only observed in the subgroup of being lower than and equal to 76% (OR = 1.059, 95%CI: 1.023–1.096). Conclusions Our study found that HFMD severity is associated with the neighborhood greenness in Guangdong, China. This study provides evidence on developing a prevention strategy of discouraging the high-risk groups from going to the crowded green spaces during the epidemic period.

Emerging evidence suggests residential surrounding green space is beneficial for human health. The association between green space and GDM showed inconsistent results, and potential effect modification of green space with air pollution is still unclear. This study aims to evaluate the association between green space and GDM, and further explore potential interaction and medication effects. Participants were recruited from a retrospective cohort study between 2015 and 2020 in Henan, China. Residential green space based on normalized difference vegetation index (NDVI) and air pollution exposure were estimated using spatial-statistical models. Multivariate logistic regression was applied to evaluate the association between per 0.1 unit increase in NDVI with 4 buffer sizes (250 m, 500 m, 1000 m, 2000 m) and GDM. We examined potential interaction of green space and air pollutants on GDM. Mediating effects of air pollution associated with green space exposure on GDM were also investigated by causal mediation analyses. A total of 46,665 eligible pregnant women were identified. There were 4092 (8.8 %) women diagnosed with GDM according to the IADPSG criteria. We found that per 0.1-unit increment in NDVI250 m, NDVI500 m, NDVI1000 m and NDVI2000 m in second trimester were associated with the decreased risk of GDM, with adjusted OR of 0.921(95 %CI: 0.890–0.953), 0.922 (95 %CI: 0.891–0.953), 0.921 (95 %CI: 0.892–0.952) and 0.921 (95 %CI: 0.892–0.951), respectively. We identified significant interactions between second trimester PM2.5 and O3 exposure and NDVI for GDM (Pinteraction < 0.001). The causal mediation analysis showed that PM2.5 mediated approximately 2.5–5.5 % of the association between green space and GDM, while the estimated mediating effect of O3 was approximately 30.1–38.5 %. In conclusion, our study indicates that residential green space was associated with a reduced risk of GDM, particularly second trimester. Green space may benefit to GDM partly mediated by a reduction in PM2.5 and O3.

A recently concluded randomized study in Tanzania found that short-term conditional cash and food transfers significantly improved HIV-infected patients’ possession of antiretroviral therapy (ART) and reduced patient loss to follow-up (LTFU) (McCoy, S. I., Njau, P. F., Fahey, C., Kapologwe, N., Kadiyala, S., Jewell, N. P., & Padian, N. S. (2017). Cash vs. food assistance to improve adherence to antiretroviral therapy among HIV-infected adults in Tanzania. AIDS, 31(6), 815–825. doi:10.1097/QAD.0000000000001406 ). We examined whether these transfers had differential effects within population subgroups. In the parent study, 805 individuals were randomized to one of three study arms: standard-of-care (SOC) HIV services, food assistance, or cash transfer. We compared achievement of the medication possession ratio (MPR) ≥ 95% at 6 and 12 months and patient LTFU at 12 months between those receiving the SOC and those receiving food or cash (combined). Using a threshold value of p

There have been recent proposals advocating the use of additive gene-environment interaction instead of the widely used multiplicative scale, as a more relevant public health measure. Using gene-environment independence enhances statistical power for testing multiplicative interaction in case-control studies. However, under departure from this assumption, substantial bias in the estimates and inflated type I error in the corresponding tests can occur. In this paper, we extend the empirical Bayes (EB) approach previously developed for multiplicative interaction, which trades off between bias and efficiency in a data-adaptive way, to the additive scale. An EB estimator of the relative excess risk due to interaction is derived, and the corresponding Wald test is proposed with a general regression setting under a retrospective likelihood framework. We study the impact of gene-environment association on the resultant test with case-control data. Our simulation studies suggest that the EB approach uses the gene-environment independence assumption in a data-adaptive way and provides a gain in power compared with the standard logistic regression analysis and better control of type I error when compared with the analysis assuming gene-environment independence. We illustrate the methods with data from the Ovarian Cancer Association Consortium.

Abstract Background During the COVID-19 pandemic, several illnesses were reduced. In Japan, heat-related illnesses were reduced by 22% compared to pre-pandemic period. However, it is uncertain as to what has led to this reduction. Here, we model the association of maximum temperature and heat-related illnesses in the 47 Japanese prefectures. We specifically examined how the exposure and lag associations varied before and during the pandemic. Methods We obtained the summer-specific, daily heat-related illness ambulance transport (HIAT), exposure variable (maximum temperature) and covariate data from relevant data sources. We utilized a stratified (pre-pandemic and pandemic), two-stage approach. In each stratified group, we estimated the 1) prefecture-level association using a quasi-Poisson regression coupled with a distributed lag non-linear model, which was 2) pooled using a random-effects meta-analysis. The difference between pooled pre-pandemic and pandemic associations was examined across the exposure and the lag dimensions. Results A total of 321,655 HIAT cases was recorded in Japan from 2016 to 2020. We found an overall reduction of heat-related risks for HIAT during the pandemic, with a wide range of reduction (10.85 to 57.47%) in the HIAT risk, across exposure levels ranging from 21.69 °C to 36.31 °C. On the contrary, we found an increment in the delayed heat-related risks during the pandemic at Lag 2 (16.33%; 95% CI: 1.00, 33.98%). Conclusion This study provides evidence of the impact of COVID-19, particularly on the possible roles of physical interventions and behavioral changes, in modifying the temperature-health association. These findings would have implications on subsequent policies or heat-related warning strategies in light of ongoing or future pandemics.

BackgroundChildren are vulnerable to the respiratory effects of air pollution, and their lung function has been associated with long-term exposure to low air pollution level in developed countries. However, the impact of contemporary air pollution level in developing countries as a result of recent efforts to improve air quality on children's lung function is less understood.MethodsWe obtained a cross-sectional sample of 617 schoolchildren living in three differently polluted areas in Anhui province, China. 2-year average concentrations of air pollutants at the year of spirometry and the previous year (2017–2018) obtained from district-level air monitoring stations were used to characterize long-term exposure. Forced vital capacity (FVC), forced expiratory volume in 1 second (FEV1), and forced expiratory flow between 25 and 75% of FVC (FEF25−75) were determined under strict quality control. Multivariable regression was employed to evaluate the associations between air pollution level and lung function parameters, overall and by demographic characteristics, lifestyle, and vitamin D that was determined by liquid chromatography tandem mass spectrometry.ResultsMean concentration of fine particulate matter was 44.7 μg/m3, which is slightly above the interim target 1 standard of the World Health Organization. After adjusting for confounders, FVC, FEV1, and FEF25−75 showed inverse trends with increasing air pollution levels, with children in high exposure group exhibiting 87.9 [95% confidence interval (CI): 9.5, 166.4] mL decrement in FEV1 and 195.3 (95% CI: 30.5, 360.1) mL/s decrement in FEF25−75 compared with those in low exposure group. Additionally, the above negative associations were more pronounced among those who were younger, girls, not exposed to secondhand smoke, non-overweight, physically inactive, or vitamin D deficient.ConclusionsOur study suggests that long-term exposure to relatively high air pollution was associated with impaired lung function in children. More stringent pollution control measures and intervention strategies accounting for effect modification are needed for vulnerable populations in China and other developing countries.

Background: Socioeconomic status (SES) was a crucial influencing factor of household air pollution (HAP). However, few studies have explored the potential effect modification of SES on the associations of HAP with type 2 diabetes mellitus (T2DM) and glucose homeostasis. Methods: A total of 20900 participants were obtained from the Henan Rural Cohort. HAP reflected by cooking fuel type and cooking duration was assessed via questionnaire. SES was evaluated by two dimensions: educational level and average monthly income. Associations of cooking fuel type, cooking duration with T2DM and glucose homeostasis indices (insulin, fasting plasma glucose (FPG), and HOMA-β) were assessed by the generalized linear model. Analyses were also conducted in different SES groups to explore the potential effect modification. Results: Significant negative association of cooking fuel type and cooking duration with T2DM, FPG, and HOMA-β was not observed. However, cooking with solid fuel and long-duration cooking were associated with decreased insulin level in women, and the adjusted coefficients were − 0.35 (95% confidence interval (95% CI): − 0.53, − 0.17) and − 0.36 (95% CI: −0.50, −0.21), respectively. Results from stratified analyses showed that these associations were more prominent in women with low average monthly income, with corresponding coefficient of − 0.57 (95% CI: −0.77, −0.37) for cooking with solid fuel and − 0.34 (95% CI: −0.52, −0.16) for long-duration cooking. Among women with low average monthly income, the largest decreased insulin level was observed in those who cooked with solid fuel, long-duration and poor kitchen ventilation, while the negative association of cooking fuel type and cooking duration with insulin level was slightly alleviated in the good kitchen ventilation group. Conclusions: Low average monthly income aggravated the negative association of HAP and insulin level among rural women, while improving kitchen ventilation may be a practical intervention. Trail registration: The Henan Rural Cohort Study has been registered at Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699). Date of registration: 06 July, 2015. http://www.chictr.org.cn/showproj.aspx?proj=11375.

In many biomedical studies, subgroup analyses are performed to identify subgroups of patients in whom a treatment is most effective, or a risk factor has the largest effect. While both are referred to as subgroup analysis, it is important to distinguish between the estimation of effects within subgroups and the comparison of effects across subgroups. Both are discussed, and we outline the implications regarding sample size and statistical methods for estimation of effects. Also, the risk of false-positive findings--which potentially increases with subgroup analysis--is discussed, as well as the distinction between effect modification and interaction. [ABSTRACT FROM AUTHOR]

Background: Associations between the built environment and physical activity (PA) may vary by sociodemographic factors. However, such evidence from international studies is limited. This study tested the moderating effects of sociodemographic factors on associations between perceived environment and self-reported total PA among adults from the International Prevalence Study. Methods: Between 2002 and 2003, adults from 9 countries (N = 10,258) completed surveys assessing total PA (International Physical Activity Questionnaire-short), perceived environment, and sociodemographics (age, gender, and education). Total PA was dichotomized as meeting/not meeting (a) high PA levels and (b) minimum PA guidelines. Logistic models tested environment by sociodemographic interactions (24 total). Results: Education and gender moderated the association between safety from crime and meeting high PA levels (interaction P < .05), with inverse associations found only among the high education group and men. Education and gender also moderated associations of safety from crime and the presence of transit stops with meeting minimum PA guidelines (interaction P < .05), with positive associations found for safety from crime only among women and presence of transit stops only among men and the high education group. Conclusions: The limited number of moderating effects found provides support for population-wide environment-PA associations. International efforts to improve built environments are needed to promote health-enhancing PA and maintain environmental sustainability. [ABSTRACT FROM AUTHOR]

Background and Purpose: Limited research focused on the association between household air pollution (HAP) and health-related quality of life (HRQoL). This study aimed to investigate the association of HAP with HRQoL and the effect modification of physical activity.Method: A total of 16,761 eligible participants were derived from the Henan Rural Cohort Study. Based on structured questionnaires, HAP was assessed by fuel type, cooking duration and kitchen ventilation; HRQoL was measured with utility index and VAS score from the European Quality of Life Five Dimension Five Level Scale (EQ-5D-5L); physical activity was assessed by the International Physical Activity Questionnaire. Generalized linear models and tobit regression models were utilized to explore the relationship of HAP with HRQoL. Further sensitivity analyses were conducted using structural equation models.Results: Compared with those who cooked with clean fuels, short-duration, or good kitchen ventilation, participants who cooked with solid fuels, long-duration, and poor ventilation had lower utility index and VAS score (All P < 0.001). The decrease in utility index for solid fuel users vs. clean fuel users were 0.06 [95%confidence interval (CI) 003, 0.08], 0.03 (95%CI 0.01, 0.04) and 0.02 (95%CI 0.01, 0.04) in low, moderate and high physical activity group, respectively, which decreased with physical activity levels (Pfor interaction < 0.05). Similar results were observed in associations of kitchen ventilation with utility index and VAS score.Conclusion: HAP negatively associated with HRQoL in rural population, and potential intervention aimed at maintaining adequate physical activity.Trail Registration: The Henan Rural Cohort Study has been registered at Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699). Date of registration: 06 July, 2015. http://www.chictr.org.cn/showproj.aspx?proj=11375 . [ABSTRACT FROM AUTHOR]

Effect modification occurs when the effect of a treatment on an outcome differsaccording to the level of some pre-treatment variable (the effect modifier). Assessing an effect modifier is not a straight-forward task even for a subject matter expert. In this paper, we propose a two-stageprocedure to automatically selecteffect modifying variables in a Marginal Structural Model (MSM) with a single time point exposure based on the two nuisance quantities (the conditionaloutcome expectation and propensity score). We highlight the performance of our proposal in a simulation study. Finally, to illustrate tractability of our proposed methods, we apply them to analyze a set of pregnancy data. We estimate the conditional expected difference in the counterfactual birth weight if all women were exposed to inhaled corticosteroids during pregnancy versus the counterfactual birthweight if all women were not, using data from asthma medications during pregnancy. [ABSTRACT FROM AUTHOR]

Female adolescents are less active than male peers in certain contexts including the neighborhood. Adolescents' physical activity can be explained by interactions between environmental and psychosocial factors, but few studies have tested such interactions in relation to context-specific behaviors. This study tested interactions between neighborhood environmental and psychosocial factors in relation to adolescents' context-specific physical activity. Data were collected in 2009-11 from 910 adolescents and a parent/guardian residing in the Baltimore/Seattle regions. Measures included adolescent-reported neighborhood leisure-time physical activity (LTPA) and non-neighborhood LTPA, accelerometer-based non-school moderate-to vigorous-physical activity (MVPA), psychosocial factors, and objective and parent-perceived neighborhood environmental factors. Gender-stratified mixed effects linear models tested associations of 6 environmental and 4 psychosocial factors and their interactions in relation to each physical activity outcome. The psychosocial factors had consistent associations with the physical activity outcomes but the environmental correlates were context-specific. Decisional balance (weighing of pros and cons of physical activity) moderated the association between recreation facility density and neighborhood LTPA among females, with a negative association only among those with high decisional balance (pros outweighed cons). Decisional balance also moderated associations of neighborhood walkability with non-school MVPA among females and non-neighborhood LTPA among males, with positive associations only among those with high decisional balance. Results support context-specific ecological models of physical activity. Targeting environmental factors that may promote opportunities for physical activity in specific contexts as well as adolescent decision-making may help promote their physical activity in those contexts, potentially leading to increased overall physical activity.

BackgroundParticipation in the Supplemental Nutrition Assistance Program (SNAP) has been linked to an increased risk of obesity, but not much is known about the mechanisms behind this association. The objective of this study was to determine if the neighborhood density of unhealthy food outlets modifies the association between obesity and participation in SNAP.MethodsData comes from the first wave of the Los Angeles Family and Neighborhood Survey; included are a subsample of adults (18+ years) who were SNAP participants or eligible non-participants (N = 1,176). We carried out multilevel analyses with obesity (BMI ≥ 30 Kg/m2), SNAP participation, and the neighborhood density of unhealthy food outlets as dependent, independent and modifying variables, respectively, controlling for age, gender, race/ethnicity, marital status, working status, mental health, and neighborhood poverty.ResultsSNAP participants had double the odds of obesity compared to eligible non-participants (OR = 2.02; 95%CI = 1.44-2.83). However, the neighborhood density of unhealthy food outlets did not modify this association.ConclusionsSNAP participation was associated with higher odds of obesity in our primarily Hispanic sample in Los Angeles County, with no effect modification found for the unhealthy portion of the food environment. More research is needed with additional food environment measures to confirm our null findings. Additional research is needed to elucidate the mechanisms linking SNAP participation and obesity as they remain unclear.

Few studies have examined individual socioeconomic status (SES) as a potential modifier of ambient temperature–health associations, especially for temperature-related hospitalizations. We fit penalized distributed lag non-linear models within generalized additive models to study the short-term associations (0–3 days) between temperature and hospital admissions stratified by common causes, age, and individual SES, as determined by whether patients received public assistance (PA) to cover their medical fee at the time of hospitalizations, during the hot season (May 15 to October 15) in Hong Kong for the years 2010–2019. We calculated the ratio of relative risk (RRR) and corresponding 95% confidence interval (CI) to statistically test the difference of the associations between PA groups. For 75 + patients, the PA group had significantly increased risks of hospitalizations at higher temperature for most causes, with relative risks (RR, 99th %ile vs. 25%ile) and 95% CIs of 1.138 (1.099, 1.179), 1.057 (1.008, 1.109), and 1.163 (1.094, 1.236) estimated for all non-cancer non-external, circulatory, and respiratory admissions, respectively. There were slight decreases of RRs with higher temperature for 75 + patients without PA. The strengths of temperature–hospitalization associations were strongly and significantly different between PA groups for all examined causes for 75 + patients, with the most considerable discrepancy found for ischemic heart disease (RRR = 1.266; 95% CI, 1.137, 1.410). Hospitalizations for patients aged 15–74 were less affected by heat, and the difference of the associations between groups was small. Individual SES is a significant modifier of high temperature–hospitalization associations in Hong Kong among the elderly. Public health interventions are needed to better protect this subpopulation from adverse health impacts of high temperature. [ABSTRACT FROM AUTHOR]

The odds ratio (OR) has been misunderstood in evidence based medicine and clinical epidemiology. Currently, "noncollapsibility" is considered a problem with interpretation of the OR and it is thought that the OR is rarely the parameter of interest for causal inference or interpretation of effect modification. The current focus on the relative risk (RR) and risk difference (RD) suffers from an important limitation: they are not solely measures of effect and vary numerically with baseline risk. In this paper, generalized linear models are examined in terms of the three binary effect measures commonly used in epidemiology to demonstrate that ORs may be the only way to interpret effect modification and have properties that should make them the parameter of interest for causal inference. We look forward to discussion, debate, and counter‐views on this issue from the epidemiology community. [ABSTRACT FROM AUTHOR]

Background: Previous studies have confirmed that both healthy diets and physical exercise have preventive effects with respect to cognitive decline with aging. The aim of this study was to investigate whether the associations of physical exercise with cognitive impairment differ in community-dwelling older adults with different dietary habits. Methods: In the 2008/2009 wave of the Chinese Longitudinal Healthy Longevity Survey, 14,966 community-dwelling older adults (≥65 years) were included for analyses. Dietary habits (including daily intake of fruits, vegetables, tea, meat, fish, eggs, food made from beans, salt-preserved vegetables, sugar, garlic, milk products, nut products, mushroom or algae, vitamins and medicinal plants) and physical exercise were assessed. Cognitive impairment was evaluated using the Chinese version of the MMSE in the 2008/2009 and 2011/2012 waves. The effect modifications of physical exercise on cognitive impairment by dietary habits were estimated using logistic regression models. Results: Older adults who practiced physical exercise exhibited a trend of decreased probability of cognitive impairment at baseline and follow-up (OR = 0.92, 95% CI = 0.80–1.06, p = 0.273; OR = 0.83, 95% CI = 0.65–1.05, p = 0.123, respectively) compared with those who did not practice physical exercise. When stratified by dietary habits, physical exercise had a protective effect with respect to prevalent cognitive impairment in older adults who ate fruits (OR = 0.74, 95% CI = 0.58–0.94, p = 0.016), ate food made from beans (OR = 0.76, 95% CI = 0.62–0.93, p = 0.007), did not eat sugar (OR = 0.81, 95% CI = 0.68–0.98, p = 0.028) and ate milk products (OR = 0.75, 95% CI = 0.57–0.97, p = 0.030); in the longitudinal analyses, physical exercise had a protective effect with respect to incident cognitive impairment in older adults who ate fruits (OR = 0.63, 95% CI = 0.41–0.98, p = 0.040) and milk products (OR = 0.57, 95% CI = 0.35–0.94, p = 0.027). Fruits, food made from beans and milk products modified the associations of physical exercise with prevalent cognitive impairment (p values for interaction = 0.008, 0.005 and 0.082, respectively). Conclusions: The associations of physical exercise with cognitive impairment could be modified by certain dietary habits. Physical exercise was not found to be significantly protective with respect to cognitive impairment in older adults unless they had specific dietary habits. Thus, dietary habits should be emphasized when investigating the beneficial effects of physical exercise on cognitive function in community-dwelling older adults. [ABSTRACT FROM AUTHOR]

Incense burning is common in Asia including China. Research investigating the association between household incense burning and children's neurodevelopment is scarce. We aimed to examine this association in Chinese children. In 2019, we randomly enrolled 8293 children aged 6–12 years from 5 elementary schools in Guangzhou, southern China. Information on duration and frequency of household incense burning was collected using a questionnaire. Children's executive function was evaluated using the parental report of the Behavioral Rating Inventory of Executive Function. A general linear model was used to assess the associations between incense burning and executive function. Children who occasionally and frequently exposed to incense burning exhibited worse performance on executive function. For example, frequent incense burning was associated with increases in behavioral regulation index (BRI) of 1.77 (95%CI: 0.97, 2.58) points and metacognition index (MI) of 1.40 (95%CI: 0.60, 2.20) points, compared to never incense burning group. Parental smoking and household income were significant modifiers of the associations, with the stronger associations were observed in children having smoking parent(s) and poorer household income. The findings suggest that household incense burning was associated with poorer executive function, especially in children whose parent(s) were smokers and in those with low household income. [ABSTRACT FROM AUTHOR]

Inference regarding exposure effects within subgroups of individuals and regarding the effect‐modifying role of some covariates plays a central role in research on stratified medicine. Large administrative databases offer an appealing basis for investigating these questions but causal inference can be challenging due to confounding and missing data. We consider the setting where subgroups are defined by the value of an incompletely observed potential effect modifier. We first formulate simple doubly inverse probability‐weighted estimating equations involving one weight to facilitate causal inference with complete data and another weight to adjust for the fact that the effect modifier is only partially observed. We then develop a nested doubly robust (NDR) estimating function which is shown to yield more efficient and robust estimators. In simulation studies, both approaches are shown to yield valid inference in finite samples, but the advantages of the NDR estimators are evident when one or more of the auxiliary models are misspecified. An application to a study of the effect of biological therapy on inflammation in a rheumatology cohort is given for illustration. [ABSTRACT FROM AUTHOR]

Lead exposure and neighborhoods can affect children's behavior, but it is unclear if neighborhood characteristics modify the effects of lead on behavior. Understanding these modifications has important intervention implications. Blood lead levels (BLLs) in children (~7 years) from Montevideo, Uruguay, were categorized at 2 µg/dL. Teachers completed two behavior rating scales (n = 455). At one-year follow-up (n = 380), caregivers reported child tantrums and parenting conflicts. Multilevel generalized linear models tested associations between BLLs and behavior, with neighborhood disadvantage, normalized difference vegetation index (NDVI), and distance to nearest greenspace as effect modifiers. No effect modification was noted for neighborhood disadvantage or NDVI. Children living nearest to greenspace with BLLs < 2 µg/dL were lower on behavior problem scales compared to children with BLLs ≥ 2 µg/dL. When furthest from greenspace, children were similar on behavior problems regardless of BLL. The probability of daily tantrums and conflicts was ~20% among children with BLLs < 2 µg/dL compared to ~45% among children with BLLs ≥ 2 µg/dL when closest to greenspace. Furthest from greenspace, BLLs were not associated with tantrums and conflicts. Effect modification of BLL on child behavior by distance to greenspace suggests that interventions should consider both greenspace access and lead exposure prevention. [ABSTRACT FROM AUTHOR]

Objectives: Evidence suggests that high levels of air pollution and less green space increase depressive symptoms in adults. However, results are mixed and cross-cohort comparisons are scarce, largely due to heterogeneity in exposure assessment. Also, the impact of these exposures on the trajectory of depressive symptoms over time has been less studied. We investigated the association of air pollution and green space with depressive symptoms in adulthood and whether these exposures modify the trajectory of depressive symptoms leveraging harmonized data from four population-based cohorts across the Netherlands and United Kingdom (UK)., Methods: We analyzed data from the Dutch Famine Birth Cohort (DFBC) (n = 840, baseline ages: 56-61), and the Rotterdam Study (RS) (RS-I n = 4,049, baseline ages: 61-101 and RS-II n = 2,861, baseline ages: 55-99), in the Netherlands, and the Avon Longitudinal Study of Parents and Children (ALSPAC) (n = 17,100, baseline ages: 18-71) in the UK, each using a different validated instrument for depressive symptoms, with 3-11 repeated measures. European-wide environmental data was linked to participants' addresses at baseline. Linear mixed-models were used to estimate associations of air pollution and green space with standardized cohort-specific depressive symptoms, and whether these exposures modify the trajectory of depressive symptoms., Results: Long-term exposure to fine particulate matter (PM 2.5 ) was positively associated with overall higher standardized depressive symptom scores in ALSPAC and RS-I (β per 10 μg/m 3 increase in PM 2.5 : 0.07 SD, 95%CI 0.02, 0.11 and 0.13 SD, 95%CI 0.02, 0.24, respectively). Exposure to higher normalized difference vegetation index (NDVI) at 300 m buffer was associated with lower depressive symptoms in DFBC (β per 0.1 increase in NDVI: 0.08, 95%CI -0.14, -0.01). In RS-II, the positive effect of higher NDVI at 300-m buffer on depressive symptoms decreased over time, but this effect was very small (β per 0.1 increase in NDVI: 0.01 SD per year, 95%CI 0.00, 0.01)., Conclusion: Air pollution in the form of particulate matter as well as green space were associated with depressive symptoms across multiple cohorts. In the majority of cohorts, depressive symptoms increased with age, but we found little evidence that trajectories of depressive symptoms are influenced by exposure to environmental variables., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: The underlying population of patients selected for each respiratory monoclonal antibody might change as other biologics are approved., Objective: To evaluate effect modification by calendar time of the effectiveness of each respiratory biologics in asthma., Methods: The Effectiveness of Respiratory biologics in Asthma (ERA) is a retrospective cohort of severe asthma patients from the Mass General Brigham clinics between January 2013 and September 2023. Periods were pre-specified as the anti-IgE (2013-2015), anti-IL5 (2016-2018), anti-IL4/13 (2019-2021) or anti-alarmin (2022-2023) era. We evaluated each biologic's effect on asthma-related exacerbations comparing the one-year period before and after therapy initiation using Poisson regression and Cox regression for time-to-first exacerbation., Results: Of 647 biologic-naïve patients, 165 initiated omalizumab, 235 anti-IL5, 227 dupilumab, and 20 tezepelumab. Omalizumab's effectiveness improved as more biologics were approved: incidence rate ratio (IRR) 1.16 [0.94-1.43] anti-IgE era vs. 0.54 [0.37-0.80] anti-IL4/13-alarmin era. Omalizumab patients in the anti-IL4/13-alarmin era had lower blood eosinophil counts and less chronic rhinosinusitis with nasal polyps (CRSwNP). For anti-IL5s, effectiveness peaked in the anti-IL4/13 era (IRR 0.52 [0.42-0.64]) when patients had higher BMI and less concomitant CRSwNP. Dupilumab was most effective in the anti-IL4/13 era (IRR 0.60 [0.50-0.72]). There were fewer current smokers in dupilumab patients in the anti-IL4/13 era. Results were similar in time-to-event analyses and in sensitivity analyses accounting for the COVID-19 pandemic., Conclusion: There are temporal variations in the effectiveness of biologics partly explained by the shift in the underlying population, particularly for omalizumab. Though having more choices was associated with better patient selection for omalizumab, this was inconsistent for other biologics., Competing Interests: Declaration of competing interest None., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Objective: To assess the impact of exposure to particulate matter with aerodynamic diameter ≤2.5 μm (PM 2.5 ) on non-accidental mortality under different apparent temperature levels and to further explore the modification effect of apparent temperature., Methods: This study used time-series design. Tianjin and Ningbo from China, Bangkok and Chiang Mai from Thailand were selected as the research sites, and the apparent temperature was applied as the exposure index. Through the quantitative estimation of the threshold temperature, the corresponding pollutant concentration was divided into high and low levels, and the generalized Poisson additive model was used to evaluate the association between PM 2.5 exposure and non-accidental death of residents at different temperature levels., Results: The ave-rage concentrations of PM 2.5 in Tianjin, Ningbo, Bangkok, and Chiang Mai during the study period were (73.6±35.6), (48.0±32.1), (33.5±28.4) and (32.6±28.6) μg/m 3 , respectively; the average daily non-accidental death counts were 148, 57, 28, and 8. The analysis of the generalized Poisson additive model showed that the daily non-accidental death counts increased by 0.43% (95% CI : 0.33%-0.54%) per 10 μg/m 3 increase of PM 2.5 in lag 0 day in Tianjin of China; 0.27% (95% CI : 0.08%-0.46%) per 10 μg/m 3 increase of PM 2.5 in lag 2 days in Ningbo of China. The effect was magnified in high temperature levels in Tianjin and in low temperatures in Ningbo and Bangkok. The mortality effect of PM 2.5 in various temperature levels stayed still in co-pollutant regression models., Conclusion: Exposure to fine particulate matter had an adverse effect on non-accidental mortality, which reminded us to give further attention to the pollution control. The findings also indicated that apparent temperature might modify mortality effects of PM 2.5 and the modification effect varied in different regions. Protective policies due to regional differences should be made and more scientific and social attention on mutual effect of air pollution and climate change needs to be appealed.

Background and Objectives: Neighborhood walkability can influence walking behaviors in older adults. However, its associations of walkability with walking may differ by demographic, socioeconomic, health, social, and residential characteristics due to factors such as increased vulnerability to environmental factors or increased resilience., Research Design and Methods: In a sample of older adults ( n  = 493, median age = 82 [range 78-89], 56% female, 31% Black), a walkability index was derived from audits of Google Street View images of participants' immediate neighborhoods. Walking was self-reported in the past week. Effect modifiers by demographic (age, race, gender, marital status), socioeconomic (education, income), health (gait speed, falls, knee pain, depressive symptoms, cognitive status, perceived energy), social (driving status, social engagement), and residential/neighborhood (residence type, neighborhood socioeconomic status [SES], population density) characteristics were assessed by interaction terms in logistic regression models, adjusted for gender, race, gait speed, prior falls, high depressive symptoms, currently driving, and cognitive status. When effect modification was suggested ( p for interaction <.1), adjusted analyses of walkability with walking stratified on the effect modifier were conducted., Results: In this sample, 59% walked in the past week and greater walkability was associated with greater odds of walking (odds ratio [OR] = 1.16, 95% confidence interval [CI]: 1.01-1.34). This association ( p for interaction range 0.002-0.07) was present for those who were not currently married (OR = 1.35, 95% CI: 1.17-1.56), who reported knee pain (OR = 1.40, 95% CI: 1.14-1.72) or high depressive symptoms (OR = 1.30, 95% CI: 1.06-1.60), or who had declining cognitive function (OR = 1.30, 95% CI: 1.09-1.55)., Discussion and Implications: High walkability may influence physical activity, particularly for those with vulnerabilities related to social, pain, and brain health characteristics. These results should inform neighborhood planning and targeted interventions for vulnerable older adults., Competing Interests: None., (© The Author(s) 2024. Published by Oxford University Press on behalf of The Gerontological Society of America.)

Background: Although the association between low ambient temperature and cardiovascular disease (CVD) is well-established, the effect of winter energy prices on this association remains unknown., Aim: This ecological study aimed to investigate whether changes in natural gas prices (NGP), which account for a significant portion of winter energy prices in Korea, affect the association of cold spells with hospital admissions and mortality due to CVD., Methods: Data from the National Health Insurance Service and Statistics Korea were used to determine the daily number of hospital admissions and mortality rates associated with CVD. From January 2012 to February 2017, the NGP continually increased by 24.1%. From January 2012 to December 2014 the NGP continually decreased by 32.6% owing to the Korea Gas Corporation's management decisions, independent of external socioeconomic factors. We investigated the differences in the associations between cold spells and CVD-related outcomes in price-increasing and price-decreasing periods using a Poisson regression with a distributed lag nonlinear model. Cold spells were assessed on two consecutive days at the 5th percentile of the temperature for each region., Results: The meteorological factors and air pollution levels were similar between the two periods. The association between cold spells and hospital admissions due to CVD was stronger during the price-increasing period than during the price-decreasing period [ratio of cumulative relative risk (RRR) = 1.71, 95% confidence interval (CI): 1.31-2.22]. The difference in the association with mortality due to CVD between the two periods was not significant, although the point estimate remained >1 (RRR = 1.11, 95% CI: 0.90-1.38)., Conclusions: Changes in energy prices may modify the cold spell-related CVD risk, possibly by inducing behavioral changes to manage energy expenditure. Policymakers should take into account the potential public health implications of changes in energy prices, alongside their economic effects., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:Hyung-Jin Yoon reports financial support was provided by National Research Foundation of Korea. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Background: Self-employment is a significant component of South Korea's labor force; yet, it remains relatively understudied in the context of occupational safety and health. Owing to different guidelines for health checkup participation among economically active individuals, disparities in health maintenance may occur across varying employment statuses., Objective: This study aims to address such disparities by comparing the risk of all-cause mortality and comorbidities between the self-employed and employee populations in South Korea, using nationwide data. We sought to provide insights relevant to other countries with similar cultural, social, and economic contexts., Methods: This nationwide retrospective study used data from the Korean National Health Insurance Service database. Participants (aged 20-59 y) who maintained the same insurance type (self-employed or employee insurance) for ≥3 years (at least 2008-2010) were recruited for this study and monitored until death or December 2021-whichever occurred first. The primary outcome was all-cause mortality. The secondary outcomes were ischemic heart disease, ischemic stroke, cancer, and hospitalization with a mental illness. Age-standardized cumulative incidence rates were estimated through an indirect method involving 5-unit age standardization. A multivariable Cox proportional hazards model was used to estimate the adjusted hazard ratio (HR) and 95% CI for each sex stratum. Subgroup analyses and an analysis of the effect modification of health checkup participation were also performed., Results: A total of 11,652,716 participants were analyzed (follow-up: median 10.92, IQR 10.92-10.92 y; age: median 42, IQR 35-50 y; male: n=7,975,116, 68.44%); all-cause mortality occurred in 1.27% (99,542/7,851,282) of employees and 3.29% (124,963/3,801,434) of self-employed individuals (P<.001). The 10-year cumulative incidence rates of all-cause mortality differed significantly by employment status (1.1% for employees and 2.8% for self-employed individuals; P<.001). The risk of all-cause mortality was significantly higher among the self-employed individuals when compared with that among employees, especially among female individuals, according to the final model (male: adjusted HR 1.44, 95% CI 1.42-1.45; female: adjusted HR 1.89, 95% CI 1.84-1.94; P<.001). The risk of the secondary outcomes, except all types of malignancies, was significantly higher among the self-employed individuals (all P values were <.001). According to subgroup analyses, this association was prominent in younger individuals with lower incomes who formed a part of the nonparticipation groups. Furthermore, health checkup participation acted as an effect modifier for the association between employment status and all-cause mortality in both sexes (male: relative excess risk due to interaction [RERI] 0.76, 95% CI 0.74-0.79; female: RERI 1.13, 95% CI 1.05-1.21)., Conclusions: This study revealed that self-employed individuals face higher risks of all-cause mortality, cardio-cerebrovascular diseases, and mental illnesses when compared to employees. The mortality risk is particularly elevated in younger, lower-income individuals who do not engage in health checkups, with health checkup nonparticipation acting as an effect modifier for this association., (© Byungyoon Yun, Heejoo Park, Jaesung Choi, Juyeon Oh, Juho Sim, Yangwook Kim, Jongmin Lee, Jin-Ha Yoon. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org).)

Abstract Background The treatment effects on hospitalization for heart failure (hHF) from sodium-glucose cotransporter 2 (SGLT2) inhibitors may vary among type 2 diabetes (T2D) patients depending on whether or not they have established atherosclerotic cardiovascular diseases (ASCVD). We aimed to examine differences in hHF outcomes after dapagliflozin or empagliflozin use between T2D patients with and without a history of established ASCVD. Methods We conducted a retrospective multi-institutional cohort study in Taiwan. We included T2D patients newly receiving dapagliflozin or empagliflozin during 2016–2019, and followed them up until December 31, 2020. We implemented 1:1 propensity score matching to create homogenous groups for comparisons. We generated Cox proportional hazard models to compare the risk of hHF between dapagliflozin and empagliflozin (reference group). We included interaction terms of SGLT2 inhibitor and ASCVD history in the regression models to examine effect modification by ASCVD. Results We included a total cohort of 9,586 dapagliflozin new users and 9,586 matched empagliflozin new users. The overall hHF risks were similar for dapagliflozin and empagliflozin (HR: 0.90, 95% CI 0.74–1.09). However, differential hHF risks between dapagliflozin and empagliflozin were observed only in the subgroup without ASCVD (HR: 0.67, 95% CI 0.49–0.90), while not in the subgroup with ASCVD (HR: 1.12, 95% 0.87–1.45), and the p-value for examining interaction was 0.0097. Conclusion In this study, history of established ASCVD was associated with different hHF risks among SGLT2 inhibitors. For T2D patients without ASCVD, dapagliflozin may offer a more favorable hHF reduction effect, compared to empagliflozin, in clinical practice. Future prospective studies should be conducted to validate our findings.

Introduction: The Frequent Hemodialysis Network (FHN) Daily and Nocturnal trials aimed to compare the effects of hemodialysis (HD) given 6 versus 3 times per week. More frequent in-center HD significantly reduced left-ventricular mass (LVM), with more pronounced effects in patients with low urine volumes. In this study, we aimed to explore another potential effect modifier: the predialysis serum sodium (SNa) and related proxies of plasma tonicity. Methods: Using data from the FHN Daily and Nocturnal Trials, we compared the effects of frequent HD on LVM among patients stratified by SNa, dialysate-to-predialysis serum-sodium gradient (GNa), systolic and diastolic blood pressure, time-integrated sodium-adjusted fluid load (TIFL), and extracellular fluid volume estimated by bioelectrical impedance analysis. Results: In 197 enrolled subjects in the FHN Daily Trial, the treatment effect of frequent HD on ∆LVM was modified by SNa. When the FHN Daily Trial participants are divided into lower and higher predialysis SNa groups (less and greater than 138 mEq/L), the LVM reduction in the lower group was substantially higher (−28.0 [95% CI −40.5 to −15.4] g) than in the higher predialysis SNa group (−2.0 [95% CI −15.5 to 11.5] g). Accounting for GNa, TIFL also showed more pronounced effects among patients with higher GNa or higher TIFL. Results in the Nocturnal Trial were similar in direction and magnitude but did not reach statistical significance. Discussion/Conclusion: In the FHN Daily Trial, the favorable effects of frequent HD on left-ventricular hypertrophy were more pronounced among patients with lower predialysis SNa and higher GNa and TIFL. Whether these metrics can be used to identify patients most likely to benefit from frequent HD or other dialytic or nondialytic interventions remains to be determined. Prospective, adequately powered studies studying the effect of GNa reduction on mortality and hospitalization are needed.