Complementary Log Regression for Sufficient-Cause Modeling of Epidemiologic Data

Adolescent Psychotic Experiences and Adverse Mental Health Outcomes in Adulthood in a General Population Sample

Purpose This study estimated risk of incident mental disorders in adulthood associated with both transient and persistent adolescent psychotic experiences (PEs). Methods A nested case-control design was used within the Avon Longitudinal Study of Parents and Children (ALSPAC), a birth cohort study which recruited expectant mothers from 1991-1992. Participants consisted of 8822 offspring of ALSPAC mothers who completed the Psychosis-like Symptoms Interview Questionnaire (PLIKSi-Q). PEs were assessed using the PLIKSi-Q. Depressive disorders were assessed using the Short Mood and Feelings Questionnaire (SMFQ), anxiety disorders using the General Anxiety Disorder Assessment and the Clinical Interview Schedule-Revised, and psychotic disorder using the PLIKSi. Risk of incident depressive disorder, GAD, psychotic disorder, and past-year suicide attempts were compared amongst participants who had ever versus never reported a PE and those who reported persistent versus transient PEs. Results Adolescent PEs were associated with increased risk for incident depressive disorder (adjusted hazard ratio (aHR) = 1.62, 95% CI = 1.42, 1.84), GAD (aHR 1.23, 95% CI = 1.03, 1.47), psychotic disorder (adjusted odds ratio (aOR) = 5.08, 95% CI = 2.02, 12.79), and past-year suicide attempts (aHR = 2.56, 95% CI = 1.97, 3.25). Persistent PEs were associated with increased risk for depressive disorder (aHR = 1.81, 95% CI = 1.55, 2.12), generalized anxiety disorder (aHR = 1.34, 95% CI = 1.07, 1.68), and psychotic disorder (aOR = 7.39, 95% CI = 2.43, 22.19) but not past-year suicide attempts. Conclusion Adolescent PEs are a risk factor for multiple mental disorders and suicide attempts, with persistent PEs conferring greater risk. Identifying interventions for adolescents who report PEs, particularly persistent PEs, could lessen the burden of multiple mental health disorders and suicide attempts.

Bayesian estimation of the measurement of interactions in epidemiological studies

Background

Interaction identification is important in epidemiological studies and can be detected by including a product term in the model. However, as Rothman noted, a product term in exponential models may be regarded as multiplicative rather than additive to better reflect biological interactions. Currently, the additive interaction is largely measured by the relative excess risk due to interaction (RERI), the attributable proportion due to interaction (AP), and the synergy index (S), and confidence intervals are developed via frequentist approaches. However, few studies have focused on the same issue from a Bayesian perspective. The present study aims to provide a Bayesian view of the estimation and credible intervals of the additive interaction measures.

Methods

Bayesian logistic regression was employed, and estimates and credible intervals were calculated from posterior samples of the RERI, AP and S. Since Bayesian inference depends only on posterior samples, it is very easy to apply this method to preventive factors. The validity of the proposed method was verified by comparing the Bayesian method with the delta and bootstrap approaches in simulation studies with example data.

Results

In all the simulation studies, the Bayesian estimates were very close to the corresponding true values. Due to the skewness of the interaction measures, compared with the confidence intervals of the delta method, the credible intervals of the Bayesian approach were more balanced and matched the nominal 95% level. Compared with the bootstrap method, the Bayesian method appeared to be a competitive alternative and fared better when small sample sizes were used.

Conclusions

The proposed Bayesian method is a competitive alternative to other methods. This approach can assist epidemiologists in detecting additive-scale interactions.

Coverage-level and predictors of maternity continuum of care in Nigeria: implications for maternal, newborn and child health programming

BACKGROUND

Completing maternity continuum of care from pregnancy to postpartum is a core strategy to reduce the burden of maternal and neonatal mortality dominant in sub-Saharan Africa, particularly Nigeria. Thus, we evaluated the level of completion, dropout and predictors of women uptake of optimal antenatal care (ANC) in pregnancy, continuation to use of skilled birth attendants (SBA) at childbirth and postnatal care (PNC) utilization at postpartum in Nigeria.

METHODS

A cross-sectional analysis of nationally representative 21,447 pregnancies that resulted to births within five years preceding the 2018 Nigerian Demographic Health Survey. Maternity continuum of care model pathway based on WHO recommendation was the outcome measure while explanatory variables were classified as; socio-demographic, maternal and birth characteristics, pregnancy care quality, economic and autonomous factors. Descriptive statistics describes the factors, backward stepwise regression initially assessed association (p < 0.10), multivariable binary logistic regression and complementary-log-log model quantifies association at a 95% confidence interval (α = 0.05).

RESULTS

Coverage decrease from 75.1% (turn-up at ANC) to 56.7% (optimal ANC) and to 37.4% (optimal ANC and SBA) while only 6.5% completed the essential continuum of care. Dropout in the model pathway however increase from 17.5% at ANC to 20.2% at SBA and 30.9% at PNC. Continuation and completion of maternity care are positively drive by women; with at least primary education (AOR = 1.27, 95%CI = 1.01-1.62), average wealth index (AOR = 1.83, 95%CI = 1.48 -2.25), southern geopolitical zone (AOR = 1.61, 95%CI = 1.29-2.01), making health decision alone (AOR = 1.39, 95%CI = 1.16-1.66), having nurse as ANC provider (AOR = 3.53, 95%CI = 2.01-6.17) and taking at least two dose of tetanus toxoid vaccine (AOR = 1.25, 95%CI = 1.06-1.62) while women in rural residence (AOR = 0.78, 95%CI = 0.68-0.90) and initiation of ANC as late as third trimester (AOR = 0.44, 95%CI = 0.34-0.58) negatively influenced continuation and completion.

CONCLUSIONS

6.5% coverage in maternity continuum of care completion is very low and far below the WHO recommended level in Nigeria. Women dropout more at postnatal care than at skilled delivery and antenatal. Education, wealth, women health decision power and tetanus toxoid vaccination drives continuation and completion of maternity care. Strategies optimizing these factors in maternity packages will be supreme to strengthen maternal, newborn and child health.

A self-consistent probabilistic formulation for inference of interactions

Large molecular interaction networks are nowadays assembled in biomedical researches along with important technological advances. Diverse interaction measures, for which input solely consisting of the incidence of causal-factors, with the corresponding outcome of an inquired effect, are formulated without an obvious mathematical unity. Consequently, conceptual and practical ambivalences arise. We identify here a probabilistic requirement consistent with that input, and find, by the rules of probability theory, that it leads to a model multiplicative in the complement of the effect. Important practical properties are revealed along these theoretical derivations, that has not been noticed before.

A novel method for controlling unobserved confounding using double confounders

BACKGROUND

Controlling unobserved confounding still remains a great challenge in observational studies, and a series of strict assumptions of the existing methods usually may be violated in practice. Therefore, it is urgent to put forward a novel method.

METHODS

We are interested in the causal effect of an exposure on the outcome, which is always confounded by unobserved confounding. We show that, the causal effect of an exposure on a continuous or categorical outcome is nonparametrically identified through only two independent or correlated available confounders satisfying a non-linear condition on the exposure. Asymptotic theory and variance estimators are developed for each case. We also discuss an extension for more than two binary confounders.

RESULTS

The simulations show better estimation performance by our approach in contrast to the traditional regression approach adjusting for observed confounders. A real application is separately applied to assess the effects of Body Mass Index (BMI) on Systolic Blood Pressure (SBP), Diastolic Blood Pressure (DBP), Fasting Blood Glucose (FBG), Triglyceride (TG), Total Cholesterol (TC), High Density Lipoprotein (HDL) and Low Density Lipoprotein (LDL) with individuals in Shandong Province, China. Our results suggest that SBP increased 1.60 (95% CI: 0.99-2.93) mmol/L with per 1- kg/m2 higher BMI and DBP increased 0.37 (95% CI: 0.03-0.76) mmol/L with per 1- kg/m2 higher BMI. Moreover, 1- kg/m2 increase in BMI was causally associated with a 1.61 (95% CI: 0.96-2.97) mmol/L increase in TC, a 1.66 (95% CI: 0.91-55.30) mmol/L increase in TG and a 2.01 (95% CI: 1.09-4.31) mmol/L increase in LDL. However, BMI was not causally associated with HDL with effect value - 0.20 (95% CI: - 1.71-1.44). And, the effect value of FBG per 1- kg/m2 higher BMI was 0.56 (95% CI: - 0.24-2.18).

CONCLUSIONS

We propose a novel method to control unobserved confounders through double binary confounders satisfying a non-linear condition on the exposure which is easy to access.

Risk factors for lower limb lymphedema in gynecologic cancer patients after initial treatment

Background

Most studies on lower limb lymphedema have been conducted in gynecologic cancer patients who underwent surgery for gynecologic malignancy. This study aimed to evaluate the risk factors for lower limb lymphedema development in gynecologic cancer patients who underwent initial treatment.

Methods

A retrospective cohort design was used to follow 903 gynecologic cancer patients who underwent treatment at Kurume University Hospital between January 1, 2013 and December 31, 2015. Data analyses were performed in 356 patients, and the patients were followed up until December 31, 2017. The model comprised two components to facilitate statistical model construction. Specifically, a discrete survival time model was constructed, and a complementary log–log link model was fitted to estimate the hazard ratio. Associations between risk factors were estimated using generalized structural models.

Results

The median follow-up period was 1083 (range 3–1819) days, and 54 patients (15.2%) developed lower limb lymphedema, with a median onset period of 240 (range 3–1415) days. Furthermore, 38.9% of these 54 patients developed lower limb lymphedema within 6 months and 85.2% within 2 years. International Federation of Gynecology and Obstetrics stage, radiotherapy, and number of lymph node dissections (≥ 28) were significant risk factors.

Conclusion

Simultaneous examination of the relationship between lower limb lymphedema and risk factors, and analysis among the risk factors using generalized structural models, enabled us to construct a clinical model of lower limb lymphedema for use in clinical settings to alleviate this condition and improve quality of life.

Testing for Sufficient-Cause Interactions in Case-Control Studies of Non-Rare Diseases

Sufficient-cause interaction (also called mechanistic interaction or causal co-action) has received considerable attention recently. Two statistical tests, the ‘relative excess risk due to interaction’ (RERI) test and the ‘peril ratio index of synergy based on multiplicativity’ (PRISM) test, were developed specifically to test such an interaction in cohort studies. In addition, these two tests can be applied in case–control studies for rare diseases but are not valid for non-rare diseases. In this study, we proposed a method to incorporate the information of disease prevalence to estimate the perils of particular diseases. Moreover, we adopted the PRISM test to assess the sufficient-cause interaction in case–control studies for non-rare diseases. The Monte Carlo simulation showed that our proposed method can maintain reasonably accurate type I error rates in all situations. Its powers are comparable to the odds-scale PRISM test and far greater than the risk-scale RERI test and the odds-scale RERI test. In light of its desirable statistical properties, we recommend using the proposed method to test for sufficient-cause interactions between two binary exposures in case–control studies.