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De-confounding Causal Inference Using Latent Multiple-Mediator Pathways

JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION 2024年第547期119卷 2051-2065页

作者： Yuan, Yubai Qu, Annie Penn State Univ Dept Stat State Coll PA USA Univ Calif Irvine Dept Stat Irvine CA 92697 USA

Causal effect estimation from observational data is one of the essential problems in causal inference. However, most estimation methods rely on the strong assumption that all confounders are observed, which is impractical and untestable in the real world. We develop a mediation analysis framework inferring the latent confounder for debiasing both direct and indirect causal effects. Specifically, we introduce generalized structural equation modeling that incorporates structured latent factors to improve the goodness-of-fit of the model to observed data, and deconfound the mediators and outcome simultaneously. One major advantage of the proposed framework is that it uses the causal pathway structure from cause to outcome via multiple mediators to debias the causal effect without requiring external information on latent confounders. In addition, the proposed framework is flexible in terms of integrating powerful nonparametric prediction algorithms while retaining interpretable mediation effects. In theory, we establish the identification of both causal and mediation effects based on the proposed deconfounding method. Numerical experiments on both simulation settings and a normative aging study indicate that the proposed approach reduces the estimation bias of both causal and mediation effects. Supplementary materials for this article are available online.

关键词： Causal identification generalized additive model Latent factor modeling Mediation analysis Sequential ignorability

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Health effects of exposure to urban ambient particulate matter: A spatial-statistical study on 3rd-trimester pregnant women

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ENVIRONMENTAL POLLUTION 2024年 346卷 123518页

作者： Yousefzadeh, Elham Chamani, Atefeh Besalatpour, Aliasghar Islamic Azad Univ Environm Sci & Engn Dept Isfahan Khorasgan Branch Esfahan Iran Islamic Azad Univ Waste & Wastewater Res Ctr Environm Sci & Engn Dept Isfahan Khorasgan Branch Esfahan Iran Inter 3 GmbH Inst Ressource Management D-10585 Berlin Germany

Pregnant women are highly vulnerable to environmental stressors such as ambient particulate matter (PM). Particularly during their 3rd trimester, their bodies undergo significant oxidative stresses. To further consolidate this dialogue into practice, the current study evaluated healthy pregnant women (n = 150 housewives;18-40 years old;gestation age >36 weeks) from the highly polluted city of Yazd, Iran, from September to November 2021. The aerosol optical depth (AOD) data retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) were employed as influencing variables and validated using field-collected PM10 data (r = 0.62, p-value <0.01). The links between blood platelet count, enzymes (SGOT, SGPT, LDH, bilirubin), metabolic products (urea and acid uric) and different combinations of AOD data were assessed using the generalized additive model. The results showed a high temporal variability in AOD (0.94 +/- 0.51) but a spatially stable distribution pattern. The mean AOD during the 3rd trimester, followed by that of the three-month peak, were identified as the most significant non-linear predictors, while the mean AOD during the 1st trimester and throughout the entire pregnancy showed no significant associations with any of the biomarkers. Considering the associations found between AOD variables and maternal oxidative stresses, urgent planning is required to improve the urban air quality for sensitive subpopulations.

关键词： Oxidative stress MODIS generalized additive model Aerosol optical depth

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Quantifying geographical diversity in sexually transmitted infections using population attributable risk: results from HIV prevention trials in South Africa

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INTERNATIONAL JOURNAL OF STD & AIDS 2021年第7期32卷 600-608页

作者： Wand, Handan Ramjee, Gita Reddy, Tarylee Univ New South Wales Kirby Inst Kensington NSW Australia South African Med Res Council HIV Prevent Res Unit Westville South Africa South African Med Res Council Biostat Unit Durban South Africa

In this study, we investigated spatial diversities of sexually transmitted infections (STIs) and quantified their impacts on the STIs using population attributable risk (PAR%). The study population was 7,557 women who participated in several HIV prevention trials from KwaZulu-Natal, South Africa. Our results provide compelling evidence for substantial geographical diversities on STI incidence rates in the region. Their population-level impacts on the STIs exceeded the combined impacts of the individual risk factors considered in this study (PAR%: 41% (<25 years), 52% (25-34 years) and 34% (35+ years). When all these factors are considered together, PAR% was the highest among younger women (PAR%: 67%, 82% and 50% for <25, 25-34 and 35+ years old respectively). Results from our study will bring greater insight into the previous research by increasing our understanding of the impacts of the sub-geographical level variations of STI prevalence and incidence rates in the region.

关键词： Geographical disparity STI South Africa generalized additive model

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Predicting spatial distribution of plant functional traits in a forest-steppe zone

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POLISH JOURNAL OF ECOLOGY 2021年第1期69卷 1-13页

作者： Fan, Shunxiang Zhang, Zhidong China Agr Univ Coll Resources & Environm Sci Beijing 100193 Peoples R China Hebei Agr Univ Coll Forestry Hebei Prov Key Lab Forest Trees Germplasm Resourc 2596 Lekai South St Baoding 071000 Peoples R China Natl Long Term Sci Res Base Forest Cultivat Saiha Chengde 067000 Peoples R China

We investigated the response mechanisms of plant functional traits to environmental factors at the community level in order to elucidate the adaptive and survival strategies of plants in different environmental gradients. 184 vegetation sampling plots were laid by stratified random sampling in the Saihanba region of Hebei, China. Three functional traits (leaf nitrogen content, LNC;specific leaf area, SLA;leaf dry matter content, LDMC) were measured and the community-level weighted means of the trait values were calculated by the species coverage values. Climate and terrain data were generated from the climate model ClimateAP and using ArcGIS. Finally, eight environmental factors, including climate, topographical, and soil factor, were recorded and the association with functional traits was analysed using a generalized additive model. model testing indicated a good predictability for the SLA and LDMC while a relatively poor predictability was seen with LNC. Environmental factors that significantly impacted SLA included elevation, degree-days above 0 degrees C, mean annual precipitation and total soil nitrogen content. In contrast, LDMC was significantly influenced by elevation, total soil nitrogen and phosphorous content while LNC was affected by elevation and degree-days above 0 degrees C. High values of SLA and LNC were found in areas at lower elevations. The distribution of high LDMC values indicated that plant leaves have a relatively high tolerance and resistance to stress, which was better for plant to grow in the adverse environment. At the community level, clarifying plant functional traits distribution and their changes with environmental gradients is useful for the potential vegetation restoration.

关键词： leaf functional trait environmental factors generalized additive model distribution pattern

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Shallow-water habitat use and population parameters of rough-toothed dolphins, Steno bredanensis (G. Cuvier in Lesson, 1828) in southeastern Brazil

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MARINE MAMMAL SCIENCE 2021年第2期37卷 717-732页

作者： Carvalho, Rafael R. Lailson-Brito, Jose, Jr. Kajin, Maja Quintana, Carlos Eduardo P. Pereira, Karina S. Bisi, Tatiana L. Cunha, Haydee A. Azevedo, Alexandre F. Univ Estado Rio de Janeiro Fac Oceanog Lab Mamiferos Aquat & Bioindicadores Prof Izabel Rio De Janeiro Brazil Univ Estado Rio de Janeiro Programa Posgrad Ecol & Evolucao Rio De Janeiro Brazil

The rough-toothed dolphin (Steno bredanensis) is a poorly known species along its distribution especially in the Southern Hemisphere where data on habitat use and population parameters are scarce. Boat-based surveys were conducted from 2009 to 2017 in a shallow water environment in southeastern Brazil. During focal-group observations, S. bredanensis was more commonly found in mean depths of 22 m with varying group size and composition. generalized additive models showed that group size was influenced by environmental variables such as sea surface and bottom temperatures, depth, and season. Photo-identification effort allowed us to catalogue 173 well-distinct marked individuals. Estimates of population parameters showed high and constant survival (phi = 0.99) corroborating site fidelity but time varying capture probabilities (p = .03-.71). An open population model also indicated a small abundance estimate (Nt = 218) of S. bredanensis in the study area, improving knowledge for this species in shallow water environments of the southwestern Atlantic Ocean.

关键词： abundance cetacean Delphinidae generalized additive model mark‐ recapture occurrence population Rio de Janeiro State rough‐ toothed dolphin Steno bredanensis

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Assessment for the Correlation Between Diabetic Retinopathy and Metabolic Syndrome: A Cross-Sectional Study

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DIABETES METABOLIC SYNDROME AND OBESITY-TARGETS AND THERAPY 2021年 14卷 1773-1781页

作者： Sun, Qing Tang, Liang Zeng, Qiurong Gu, Mingjun Fuling Ctr Hosp Chongqing City Dept Clin Nutr Chongqing 408000 Peoples R China Fuling Ctr Hosp Chongqing City Dept Endocrinol 2 Fuling DistGaosuntang Rd Chongqing 408000 Peoples R China

Purpose: In this study, we explored the correlation between diabetic retinopathy (DR) and metabolic syndrome (MetS) among diabetes mellitus (DM) patients. Methods: Logistic regression analysis was utilized to test the effects of MetS and its indicators on the incidence of DR and vision-related functional burden. The spline smoothing functions of continuous indicators of MetS were used to establish the logistic generalized additive model (GAM). The effective degree of freedom (EDF) =1 was served as a sign of linear relationship. EDF>1 was a sign of a more complex association between MetS and DR. Results: The proportion of difficulties of looking for objects on the crowded shelves in the DR group was higher than that in the non-DR group (19.40 vs 12.10, P<0.05). Elevated fasting glucose (Glu) and blood pressure levels were related to the vision-related functional burden. The risk of DR development increased by 6% [95% confidence interval (CI): 1.03-1.09, P<0.001] and 1% (95% CI: 1.01-1.02, P=0.004) per 1 unit increase in Glu and systolic blood pressure (SBP) of DM patients, respectively. In the univariate GAM, Glu had a linear effect on DR (EDF=1, P<0.001) with a positive correlation after controlling SBP. And there was a nonlinear correlation between SBP and DR after controlling Glu (EDF=2.44, P=0.024). Conclusion: Both Glu and blood pressure were associated with the occurrence of DR and vision-related functional burden. Controlling the levels of Glu and blood pressure may reduce the risk of DR and vision loss among DM patients.

关键词： diabetic retinopathy generalized additive model glucose blood pressure

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Short-term effect of fine particulate matter and ozone on non-accidental mortality and respiratory mortality in Lishui district, China

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BMC PUBLIC HEALTH 2021年第1期21卷 1661-1661页

作者： Chen, Yuqi Jiao, Zhigang Chen, Ping Fan, Lijun Zhou, Xudan Pu, Yuepu Du, Wei Yin, Lihong Southeast Univ Sch Publ Hlth Key Lab Environm Med Engn Minist Educ Nanjing 210009 Peoples R China Lishui Smart City Operating Command Ctr Lishui 211200 Peoples R China

Background In recent years, air pollution has become an imminent problem in China. Few studies have investigated the impact of air pollution on the mortality of the middle-aged and elderly people. Therefore, this study aims to evaluate the impact of PM2.5 (fine particulate matter) and O-3 (ozone) on non-accidental mortality and respiratory mortality of the middle-aged and elderly people in Lishui District of Nanjing and provide the evidence for potential prevention and control measures of air pollution. Method Using daily mortality and atmospheric monitoring data from 2015 to 2019, we applied a generalized additive model with time-series analysis to evaluate the association of PM2.5 and O-3 exposure with daily non-accidental mortality and respiratory mortality in Lishui District. Using the population attributable fractions to estimate the death burden caused by short-term exposure to O-3 and PM2.5?. Result For every 10 mu g/m(3) increase in PM2.5, non-accidental mortality increased 0.94% with 95% confidence interval (CI) between 0.05 and 1.83%, and PM2.5 had a more profound impact on females than males. For every 10 mu g/m(3) increase in O-3, respiratory mortality increased 1.35% (95% CI: 0.05, 2.66%) and O-3 had a more profound impact on males than females. Compared with the single pollutant model, impact of the two-pollutant model on non-accidental mortality and respiratory mortality slightly decreased. In summer and winter as opposed to the other seasons, O-3 had a more obvious impact on non-accidental mortality. The population attributable fractions of non-accidental mortality were 0.84% (95% CI:0.00, 1.63%) for PM2.5 and respiratory mortality were 0.14% (95% CI:0.01, 0.26%) for O-3. For every 10 mu g/m(3) decrease in PM2.5, 122 (95% CI: 6, 237) non-accidental deaths could be avoided. For every 10 mu g/m(3) decrease in O-3, 10 (95% CI: 1, 38) respiratory deaths could be avoided. Conclusion PM2.5 and O-3 could significantly increase the risk of non-accidental and

关键词： Air pollution O-3 PM2.5 generalized additive model Mortality

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Non-linear relationships and interactions of meteorological factors on mumps in Jinan, China

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INTERNATIONAL JOURNAL OF BIOMETEOROLOGY 2021年第4期65卷 555-563页

作者： Lin, Shaoqian Ruan, Shiman Geng, Xingyi Song, Kaijun Cui, Liangliang Liu, Xiaoxue Zhang, Yingjian Cao, Meng Zhang, Ying Jinan Municipal Ctr Dis Control & Prevent 2 Weiliu Rd Jinan 250021 Peoples R China Univ Sydney Sch Publ Hlth Fac Med & Hlth Camperdown NSW 2006 Australia

Although vaccination is available, mumps remains a public health concern in many countries including China. Previous studies have indicated the impact of meteorological factors and mumps, but findings vary across different regions with limited evidence to inform local public health responses. We aim to examine the impacts of meteorological variables on mumps in Jinan, a temperate city of China, and explore the interactions of temperature with humidity or wind speed. Weekly meteorological data and notified cases of mumps in Jinan were collected for 2014-2018. Regression analyses using the generalized additive model were performed with considerations of multicollinearity, lag effects, school holidays, long-term trend, and seasonality. A stratification model was applied to investigate the interaction. We found a non-linear relationship between weekly mean temperature and the number of cases. Between 1.2 and 24.5 degrees C, the excess risk (ER) of mumps for a 1 degrees C increase in weekly mean temperature was 3.08% (95% CI 1.32 to 4.87%) at 0-week lag. The lagged effects could last for 3 weeks. There were interactions between mean temperature and relative humidity or wind speed. The effect of mean temperature was enhanced in days with low relative humidity or high wind speed. This study suggests that temperature is positively associated with mumps cases with thresholds in the temperate city of China, and the effect can be modified by relative humidity and wind speed and is independent of vaccine coverage. Findings could be integrated into current early warning systems of mumps in order to protect people's health from the risk of changing climate.

关键词： Meteorological factors Mumps generalized additive model Time series analysis

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Estimating model-based nonnegative population marginal means in application to medical expenditures covered by different health care policies - A study on Medical Expenditure Panel Survey

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STATISTICAL METHODS IN MEDICAL RESEARCH 2021年第1期30卷 299-315页

作者： Tian, Mingmei Yu, Jihnhee SUNY Buffalo Dept Biostat Buffalo NY USA

The medical care expenditure is historically an important public health issue, which greatly impacts the government's health policies as well as patients' financial and medical decisions. In population health research, we commonly discretize a numeric attribute to a few ordinal groups to examine population characteristics. Oftentimes, the population marginal mean estimation by the ANOVA approach is inflexible since it uses pre-defined grouping of the covariate. In this paper, we propose a method to estimate the population marginal mean using the B-spline-based regression in a manner of a generalized additive model as an alternative for the ANOVA. Since the medical expenditure is always nonnegative, a Bayesian approach is also implemented for the nonnegative constraint on the marginal mean estimates. The proposed method is flexible to estimate marginal means for user-specified grouping after model fitting in a post-hoc manner, a clear advantage over the ANOVA approach. We show that this method is inferentially superior to the ANOVA through theoretical investigations and an extensive Monte Carlo study. The real data analysis using Medical Expenditure Panel Survey data assisted by some visualization tools demonstrates an applicability of the proposed approach and leads us some interesting observations that may be relevant to public health discussions.

关键词： B-spline generalized additive model nonnegative constraints Bayesian method Medical Expenditure Panel Survey population marginal mean survey design

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Accurate estimation of lake levels by the spatio-temporal modeling of satellite altimetry data

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REMOTE SENSING OF ENVIRONMENT 2023年第1期295卷

作者： Hu, Yuanlin Zhou, Qi Li, Tao Wang, Hansheng Jiang, Liming Shen, Xiang Chinese Acad Sci Innovat Acad Precis Measurement Sci & Technol State Key Lab Geodesy & Earths Dynam Wuhan 430077 Hubei Peoples R China China Univ Geosci Sch Geog & Informat Engn Wuhan 430074 Hubei Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China

Satellite altimetry is currently one of the most widely used techniques for monitoring lake water levels. Raw altimetry measurements are generally delivered in an ellipsoid height system, while lake heights are finally required in a local level height system to ensure the lake surface being strictly flat under the physical constraints of both gravity and non-gravity factors. Therefore, there is always a need for height system transformation of altimetry data. Many of the previous studies have used orthometric heights in an approximate manner in the altimetric data processing. The geoid errors, together with other error sources, can introduce significant biases into water level estimations. In this paper, we propose a spatio-temporal regression method to calculate orthometric height to level height (O2L) differences, which can be used to yield accurate lake levels from satellite altimetry data. In the experiments conducted in this study, we chose ICESat-2 data to train the O2L bias correction model, and evaluated the algorithm performance on two large lakes in central Asian (Issyk-Kul and Baikal lakes) and one lake in North America (Lake Michigan). The experimental results indicate that the spatiotemporal modeling method performs better than the traditional spatial modeling method in terms of regression accuracy, and the water levels derived from the new method are much closer to in-situ gauging measurements. Influenced by O2L bias, there is often a jitter phenomenon in the time series of lake levels, and the results of different satellites are, accordingly, not mutually consistent. A visual analysis reveals that the spatio-temporal modeling method can greatly reduce the high-frequency bias.

关键词： Altimetry ICESat-2 Geoid Water level generalized additive model

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