Sample Size and Power Calculations for Additive Interactions

Clinical Predictors and Outcomes of Invasive Anal Cancer for People With Human Immunodeficiency Virus in an Inception Cohort

BACKGROUND

Due to the heterogeneity of risk for invasive anal cancer (IAC) among people with human immunodeficiency virus (PWH), we investigated predictors of IAC and described outcomes among those with a cancer diagnosis.

METHODS

Using a longitudinal inception cohort of anal cancer screening, we evaluated risk factors and outcome probabilities for incident IAC in Cox models. Screening included anal cytology and digital anorectal examination, and, if results of either were abnormal, high-resolution anoscopy.

RESULTS

Between 30 November 2006 and 3 March 2021, a total of 8139 PWH received care at the University of California, San Diego, with 4105 individuals undergoing screening and subsequently followed up over a median of 5.5 years. Anal cancer developed in 33 of them. IAC was more likely to develop in patients with anal high-grade squamous intraepithelial lesions (aHSILs) on initial or subsequent follow-up cytology (hazard ratio, 4.54) and a nadir CD4 cell count ≤200/µL (2.99). The joint effect of aHSILs and nadir CD4 cell count ≤200/µL amplified the hazard of IAC by 9-fold compared with the absence of both. PWH with time-updated cytology aHSIL and CD4 cell counts ≤200/µL had 5- and 10-year probabilities of IAC of 3.40% and 4.27%, respectively. Twelve individuals with cancer died, 7 (21% of the total 33) due to cancer progression, and they had clinical stage IIIA or higher cancer at initial diagnosis.

CONCLUSIONS

PWH with both aHSIL and a nadir CD4 cell count ≤200/µL have the highest risk of IAC. PWH who died due to IAC progression had clinical stage IIIA cancer or higher at diagnosis, highlighting the importance of early diagnosis through high-resolution anoscopic screening.

Contributions of residential traffic noise to depression and mental wellbeing in Hong Kong: A prospective cohort study

Prior studies on the association between traffic noise and mental health have been mostly conducted in settings with lower population densities. However, evidence is lacking in high population-density settings where traffic noise is more pervasive and varies by topography and the vertical elevation of the residential unit. This study aimed to assess the mental health impact of residential traffic noise in one of the world's most urbanised populations. Data were analysed from 13,401 participants aged ≥15 years in a prospective cohort in Hong Kong from 2009 to 2014. Residential traffic noise level was estimated using 3D-geocoding and validated models that accounted for sound propagation in a highly vertical landscape. The 24-h day-night exposure to traffic noise, denoted as Ldn, was estimated with a 10-dB(A) penalty for night hours. Probable depression and mental wellbeing were assessed using the Patient Health Questionnaire-9 and the Short Form Health Questionnaire SF-12v2, respectively. Mixed effect regressions with random intercepts were used to examine the association between traffic noise and mental health outcomes. Residential road traffic noise (for each increment of 10 A-weighted decibels [dB(A)] 24-h average exposure) was associated with probable depression (odds ratio (OR) = 1.17, 95% CI: 1.05, 1.31), and poorer mental wellbeing (mean difference = -0.19, 95% CI: 0.31, -0.06), adjusting for sociodemographics, smoking, body mass index, self-reported health, proximity to green space, and neighbourhood characteristics (average household income, population density, and Gini coefficient). The results were robust to further adjustment for air pollution. In stratified analyses, residential traffic noise was associated with probable depression and poorer mental wellbeing among students and individuals aged 15-34 years. Residential traffic noise was associated with probable depression and poorer mental wellbeing in a highly urbanised setting. As traffic noise is increasing in urban settings, the public health impact of noise pollution could be substantial.

HIV Prevention and Care Among Black Cisgender Sexual Minority Men and Transgender Women: Protocol for an HIV Status-Neutral Cohort Study Using an Observational-Implementation Hybrid Approach

BACKGROUND

Black cisgender gay, bisexual, and other sexual minority men (SMM) and transgender women (TW) continue to be heavily affected by HIV. Further research is needed to better understand HIV prevention and care outcomes in this population. In particular, there is a need for research examining the impact of substance use and sleep health on HIV prevention and treatment outcomes among Black SMM and TW.

OBJECTIVE

This paper outlines the study methods being used in the recently launched follow-up study to the Neighborhoods and Networks (N2) study, which we refer to as N2 Part 2 (N2P2). N2P2 aims to address this gap in the literature, build off the findings of the original N2 study, and identify socioenvironmental determinants of health, including whether neighborhood and network factors mediate and moderate these relationships.

METHODS

Building on the N2 cohort study in Chicago from 2018 to 2022, N2P2 used a prospective longitudinal cohort design and an observational-implementation hybrid approach. With sustained high levels of community engagement, we aim to recruit a new sample of 600 Black SMM and TW participants residing in the Chicago metropolitan statistical area. Participants are asked to participate in 3 study visits across an 18-month study period (1 visit every 9 months). Four different forms of data are collected per wave: (1) an in-person survey, (2) biological specimen collection, (3) a daily remote ecological momentary assessment for 14 days after each study visit, and (4) data from electronic health records. These forms of data collection continue to assess neighborhood and network factors and specifically explore substance use, sleep, immune function, obesity, and the implementation of potential interventions that address relevant constructs (eg, alcohol use and pre-exposure prophylaxis adherence).

RESULTS

The N2P2 study was funded in August 2021 by the National Institute of Drug Abuse (R01DA054553 and R21DA053156) and National Heart, Lung, and Blood Institute (R01HL160325). This study was launched in November 2022. Recruitment and enrollment for the first wave of data collection are currently ongoing.

CONCLUSIONS

The N2P2 study is applying innovative methods to comprehensively explore the impacts of substance use and sleep health on HIV-related outcomes among an HIV status-neutral cohort of Black SMM and TW in Chicago. This study is applying an observational-implementation hybrid design to help us achieve findings that support rapid translation, a critical priority among populations such as Black SMM and TW that experience long-standing inequities with regard to HIV and other health-related outcomes. N2P2 will directly build off the findings that have resulted from the original N2 study among Black SMM and TW in Chicago. These findings provide a better understanding of multilevel (eg, individual, network, and neighborhood) factors that contribute to HIV-related outcomes and viral suppression among Black SMM and TW.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/48548.

Periodontitis and systemic inflammation as independent and interacting risk factors for mortality: evidence from a prospective cohort study

BACKGROUND

Recent studies have highlighted the role of low-grade systemic inflammation in linking periodontitis to cardiovascular disease (CVD) outcomes, but many aspects remain unclear. This study examines the independent and reciprocal associations of periodontitis and low-grade systemic inflammation with all-cause and CVD mortality in a large-scale cohort.

METHODS

A total of 3047 participants from the prospective, population-based Study of Health in Pomerania (SHIP-START) were followed for a period of 13.0 ± 2.4 years. For the association between various inflammation/periodontitis measures and mortality, hazard ratios (HRs) were obtained from covariate-adjusted Cox proportional hazards models. Interactions were analysed in joint models: on the multiplicative scale, HRs were reported and on the additive scale, relative excess risks due to interaction (RERI) were calculated. Subject and variable-specific interval records were used to account for time-varying exposures and covariates.

RESULTS

During the observation period, 380 (12.5%) individuals died from CVD (n = 125) or other causes (n = 255). All markers of periodontitis and inflammation showed apparent associations with all-cause mortality (HRs per SD-increase: mean PPD: 1.068 (95% confidence interval (CI): 0.988-1.155), mean CAL: 1.205 (95% CI: 1.097-1.323), missing teeth: 1.180 (95% CI: 1.065-1.307), periodontitis score: 1.394 (95% CI: 1.202-1.616), leukocytes: 1.264 (95% CI: 1.163-1.374), fibrinogen: 1.120 (95% CI: 1.030-1.218), CRP: 1.231 (95% CI: 1.109-1.366), inflammation score: 1.358 (95% CI: 1.210-1.523)). For CVD mortality, all PPD related variables showed significant associations. Interaction modelling revealed some variation with respect to mortality type and exposure combinations. On the additive scale, RERIs for periodontitis score and inflammation score implied 18.9% and 27.8% excess mortality risk for all-cause and CVD mortality, respectively. On the multiplicative scale, the HRs for interaction were marginal.

CONCLUSIONS

Both periodontitis and inflammation were significantly associated with all-cause mortality and CVD mortality. On the additive scale, a substantial excess risk was observed due to the interaction of periodontitis and inflammation, suggesting that the greatest treatment benefit may be achieved in patients with both periodontitis and high systemic inflammation. As periodontal therapy has been reported to also reduce systemic inflammation, the possibility of a reduction in CVD mortality risk by anti-inflammatory treatments, including periodontal interventions, seems worthy of further investigation.

Antenatal Steroids, Prophylactic Indomethacin, and the Risk of Spontaneous Intestinal Perforation

OBJECTIVE

To estimate if the odds of spontaneous intestinal perforation (SIP) are increased when antenatal steroids (ANS) given close to delivery are combined with indomethacin on day 1 after birth (Indo-D1).

STUDY DESIGN

A retrospective cohort study using the Neonatal Research Network (NRN) database of inborn infants, gestational age 220-286 weeks or birth weight of 401-1000 g, born between January 1, 2016 and December 31, 2019, and surviving >12 hours. The primary outcome was SIP through 14 days. Time of last ANS dose prior to delivery was analyzed as a continuous variable (using 169 hours for durations >168 hours or no steroid exposure). Associations between ANS, Indo-D1, and SIP were obtained from a multilevel hierarchical generalized linear mixed model after covariate adjustment. This yielded aOR and 95% CI.

RESULTS

Of 6851 infants, 243 had SIP (3.5%). ANS exposure occurred in 6393 infants (93.3%) and IndoD1 was given to 1863 infants (27.2%). The time (median, IQR) from last dose of ANS to delivery was 32.5 hours (6-81) vs 37.1 hours (7-110) for infants with or without SIP, respectively (P = .10). Indo-D1 was given to 51.9 vs 26.3% of infants with SIP vs no SIP, respectively (P < .0001). Adjusted analysis indicated no interaction between time of last ANS dose and Indo-D1 for SIP (P = .7). Indo-D1 but not ANS was associated with increased odds of SIP (aOR: 1.73, 1.21-2.48, P = .003).

CONCLUSION

The odds of SIP were increased after receipt of Indo-D1. Exposure to ANS prior to Indo-D1 was not associated with an increase in SIP.

Examining racial and ethnic differences in disability among older adults: A polysocial score approach

OBJECTIVES

Racial and ethnic disparities in disability in activities of daily living (ADL) continue to be a public concern. We evaluated whether the polysocial score approach could provide a more comprehensive method for modifying racial and ethnic differences in such disability.

STUDY DESIGN

Cohort study.

MAIN OUTCOME MEASURES

We included 5833 participants from the Health and Retirement Study, who were aged 65 years or more and were initially free of ADL disability. We considered six ADLs: bathing, eating, using the toilet, dressing, walking across a room, and getting in/out of bed. We included 20 social factors spanning economic stability, neighborhood and physical environment, education, community and social context, and health system. We used forward stepwise logistic regression to derive a polysocial score for ADL disability. We created a polysocial score using 12 social factors and categorized the score as low (0-19), intermediate (20-30), and high (31+). We used multivariable logistic regression to estimate the incident risk of ADL disability and examine additive interactions between race/ethnicity and polysocial score.

RESULTS

A higher polysocial score is associated with a lower incidence of ADL disability among older adults in the United States. We found additive interactions between race/ethnicity and polysocial score categories. In the low polysocial score category, White and Black/Hispanic participants had a 18.5 % and 24.4 % risk of ADL disability, respectively. Among White participants, the risk of ADL disability decreased to 14.1 % and 12.1 % in the intermediate and high polysocial score categories, respectively; among Black/Hispanic participants, those in the intermediate and high categories had a 11.9 % and 8.7 % risk of ADL disability, respectively.

CONCLUSIONS

The polysocial score approach provides a new opportunity for explaining racial/ethnic disparities in functional capacity among older adults.

Study protocol of the Berlin Research Initiative for Diagnostics, Genetics and Environmental Factors in Schizophrenia (BRIDGE-S)

BACKGROUND

Large-scale collaborative efforts in the field of psychiatric genetics have made substantial progress in unraveling the biological architecture of schizophrenia (SCZ). Although both genetic and environmental factors are known to play a role in schizophrenia etiology our mechanistic understanding of how they shape risk, resilience and disease trajectories remains limited.

METHODS

Here, we present the study protocol of the Berlin Research Initiative for Diagnostics, Genetic and Environmental Factors of Schizophrenia (BRIDGE-S), which aims to collect a densely phenotyped genetic cohort of 1,000 schizophrenia cases and 1,000 controls. The study's main objectives are to build a resource for i) promoting genetic discoveries and ii) genotype-phenotype associations to infer specific disease subtypes, and iii) exploring gene-environment interactions using polyrisk models. All subjects provide a biological sample for genotyping and complete a core questionnaire capturing a variety of environmental exposures, demographic, psychological and health data. Approximately 50% of individuals in the sample will further undergo a comprehensive clinical and neurocognitive assessment.

DISCUSSION

With BRIDGE-S we created a valuable database to study genomic and environmental contributions to schizophrenia risk, onset, and outcomes. Results of the BRIDGE-S study could yield insights into the etiological mechanisms of schizophrenia that could ultimately inform risk prediction, and early intervention and treatment strategies.

Interaction of HPV16 and Cutaneous HPV in Head and Neck Cancer

Simple Summary

Infection with human papillomaviruses (HPV) increases the risk of developing head and neck cancer (HNC). There are over 200 known genotypes of HPV, but only a minority are carcinogenic. Cutaneous genotypes, which are traditionally isolated from the skin, were thought to be benign. However, recent evidence shows that they could be related to some cancers including HNC. Our goal in this study has been to investigate if there is an interaction between HPV16, a high-risk genotype from the alpha genus, with cutaneous HPV (beta and gamma genera) in HNC. We found preliminary evidence that among those infected with HPV16, co-infection with beta HPV could weaken the carcinogenic effect whereas coinfection with gamma HPV could strengthen the carcinogenic effect. While our findings show there might be an interaction between HPV16 and cutaneous HPV, these results are not conclusive and warrant further investigation. Future studies with larger sample sizes are needed.

Abstract

Objectives: Human papillomavirus 16 (HPV16) is an established risk factor for Head and Neck Cancer (HNC). Recent reports have shown that genotypes from the beta (β) and gamma (γ) genera, also known as cutaneous HPV, can be found in the oral cavity, but their role is largely unidentified. We investigated the interaction between oral HPV16 and cutaneous HPV in HNC. Methods: We use data on incident HNC cases (n = 384) and frequency-matched hospital-based controls (n = 423) from the HeNCe Life study in Montreal, Canada. Participants were tested for alpha HPV and cutaneous genera using oral mouth rinse and brush samples. We used unconditional logistic regression to obtain adjusted odds ratios (aOR) and 95% confidence interval (CI) as a measure of the effect between HPV and HNC and assessed the interaction between HPV genotypes on the multiplicative and additive scales. Results: Prevalence of HPV infection was higher among cases (73%) than controls (63.4%), with cases more likely to be coinfected with more than a single genotype, 52.9% vs. 43.5%, respectively. Infection with HPV16 alone had a strong effect on HNC risk aOR = 18.2 [6.2, 53.2], while infection with any cutaneous HPV, but not HPV16, appeared to have the opposite effect aOR = 0.8 [0.6, 1.1]. The observed effect of joint exposure to HPV16 and any cutaneous HPV (aOR = 20.4 [8.3, 50.1]) was stronger than the expected effect based on an assumption of independent exposures but was measured with considerable imprecision. While the point estimate suggests a positive interaction between HPV16 and cutaneous HPV, results were imprecise with relative excess risk due to interaction (RERI) = 2.4 [−23.3, 28.2]. Conclusion: There could be biologic interaction between HPV16 and genotypes from cutaneous genera, which warrants further investigation. Although cutaneous HPVs are not usually found in tumor tissues, they are cofactors that could interact with HPV16 in the oral cavity and thus strengthen the latter’s carcinogenic effect.

BCG and the risk of leprosy in Ciudad del Este, Paraguay, 2016-2017

OBJECTIVES

Paraguay has experienced a 35% reduction in the detected incidence of leprosy during the last ten years, as the vaccination coverage against tuberculosis (Bacillus of Calmette and Guérin [BCG] vaccine) reached ≥95% among infants. The objective of this case-control study was to evaluate the protective effect of BCG on the risk of leprosy.

METHODS

We used a population-based case-control study of 20 leprosy confirmed cases reported among residents of Ciudad del Este, Paraguay, diagnosed in 2016–2017. Three controls were selected from a random sample of households from the city. We assessed vaccine effectiveness using 1- odds ratio [OR], and confounding for age, gender, education, occupation, and marital status using stratified and exact logistic regression, and explored if there was effect modification calculating the synergy factor (SF) and relative excess risk due to interaction (RERI).

RESULTS

After controlling for age, gender, education, occupation and marital status, the OR of BCG scar on the risk of leprosy was 0.10 (95% confidence interval [CI], 0.02 to 0.45), for an estimate of vaccine effectiveness of 89.5% reduced risk of leprosy (95% CI, 55.2 to 98.1). There was evidence of heterogeneity by which the effectiveness of BCG seemed stronger among younger persons (Breslow-Day and Z-test of the SF had a p<0.05), and both the RERI and SF indicated a less then multiplicative and additive interaction of BCG and younger age.

CONCLUSIONS

BCG vaccination was associated with a decreased risk of leprosy in the study population, particularly in persons born after 1980.

The Mediterranean diet and physical activity: better together than apart for the prevention of premature mortality

Diet and physical activity (PA) have been studied extensively in epidemiology as single or combined lifestyle factors; however, their interaction has not been studied thoroughly. Studying potential synergisms between lifestyle components with a comprehensive interaction analysis, including additive measures of interaction, provides key insights into the nature of their joint effect and helps target interventions more effectively. First, a comprehensive review was conducted to assess the potential research gap regarding reported interaction analyses conducted in studies assessing the Mediterranean diet (MedDiet) in combination with PA on all-cause mortality. Thereafter, we prospectively assessed the joint association of the MedDiet with PA on all-cause mortality in the Seguimiento Universidad de Navarra (SUN) cohort, followed by both multiplicative and additive interaction analyses. The conjoint effect of low adherence to the MedDiet and low PA observed an increased risk greater than the individual risk factors, suggesting a potential additive interaction or synergism between both exposures, with relative risk due to interaction (RERI) and (95 % confidence interval (95 % CI)) = 0·46 (–0·83 to 1·75) and attributable proportion (95 % CI) due to interaction of 36 % (–0·62, 1·34). No multiplicative interaction was detected. Studying interactions between lifestyle factors, such as the MedDiet and PA, is particularly relevant given the current research gaps in studying the complexities of combined aspects of lifestyle in comparison with isolated behaviours. Our findings underline the important public health message of adhering to both the MedDiet and PA for the prevention of premature mortality.

No effect modification of influenza virus vaccine effectiveness by age or chronic condition was observed in the 2010/11 to 2017/18 seasons

PURPOSE

Most European influenza vaccine strategies target individuals at higher risk of complications, which include, among others, individuals aged ≥65 years and with chronic conditions. These individuals not only have a high-risk of post-infection complications but also could have lower capacity of acquiring adequate vaccine-induced protection. As such, chronic conditions and age could modify the effect of vaccines. This study aimed at assessing the potential effect modification of influenza vaccine effectiveness (IVE) by age and chronic conditions.

METHODS

We used eight-season data from the Portuguese vaccine effectiveness study. Every season, physicians at primary care units recruited patients with influenza-like illness. Clinical data and swabs were collected for Reverse Transverse Polymerase Chain Reaction (RT-PCR) detection of influenza. Trivalent inactivated IVE was estimated as 1 - odds ratio (OR) of being vaccinated in cases (RT-PCR positive for influenza) versus negative controls. ORs were obtained using a multivariable conditional logistic regression model, paired by week of onset within each season. Confounders were assessed by designing a specific causal diagram. Age (< 65 or ≥65 years) and chronic conditions (diabetes, cardiovascular disease, chronic renal disease, chronic hepatic disease, obesity, chronic respiratory disease, and congenital or acquired immunodeficiency) were studied as effect modifiers by including an interaction term in the regression models. Significance was established at 5%.

RESULTS

Point estimates indicate a higher IVE in the chronic condition strata compared to that in the no chronic condition strata. Regarding age, different results were obtained considering the virus type and (sub)type. When comparing the ≥65 years with the <65 years of age strata, we observed a higher IVE against A(H1N1)pdm09, an equal IVE against A(H3N2) and a lower IVE against B virus. However, all interaction terms were statistically insignificant, and this may be due to a small sample size.

CONCLUSION

The potential effect modification of age or chronic condition was not observed within our study.

Determinants of physical, mental and social well-being: a longitudinal environment-wide association study

BACKGROUND

Although the World Health Organization (WHO) has defined health as a state of physical, mental and social well-being, public health strategies have primarily focused on one domain of well-being. We sought to systematically and simultaneously identify and validate associations of behavioural patterns, psychosocial factors, mental and physical health conditions, access to and utilization of health care and anthropometrics with physical, mental and social well-being.

METHODS

We conducted a longitudinal environment-wide association study (EWAS) with a training and testing set approach, accounting for multiple testing using a false discovery rate control. We used multivariate multilevel regression to examine the association of each exposure at wave 1 with the three outcomes at wave 2 in the Hong Kong FAMILY Cohort (n = 10 484).

RESULTS

Out of 194 exposures, we identified and validated 14, 5 and 5 exposures that were individually associated with physical, mental and social well-being, respectively. We discovered three factors, namely depressive symptoms, life satisfaction and happiness, that were simultaneously associated with the three domains that define health.

CONCLUSIONS

These associations, if verified to be causal, could become intervention targets to holistically improve population health. Our findings provide empirical support for placing mental health at the forefront of the public health agenda, and also support recent calls to use life satisfaction and happiness to guide public policy.

Moving from two- to multi-way interactions among binary risk factors on the additive scale

Many studies have focused on investigating deviations from additive interaction of two dichotomous risk factors on a binary outcome. There is, however, a gap in the literature with respect to interactions on the additive scale of >2 risk factors. In this paper, we present an approach for examining deviations from additive interaction among three or more binary exposures. The relative excess risk due to interaction (RERI) is used as measure of additive interaction. First, we concentrate on three risk factors – we propose to decompose the total RERI to: the RERI owned to the joint presence of all three risk factors and the RERI of any two risk factors, given that the third is absent. We then extend this approach, to >3 binary risk factors. For illustration, we use a sample from data from the Greek EPIC cohort and we investigate the association with overall mortality of Mediterranean diet, body mass index , and smoking. Our formulae enable better interpretability of any evidence for deviations from additivity owned to more than two risk factors and provide simple ways of communicating such results from a public health perspective by attributing any excess relative risk to specific combinations of these factors.

Abbreviations: BMI: Body Mass Index; ERR: excess relative risk; EPIC: European Prospective Investigation into Cancer and nutrition; MD: Mediterranean diet; RERI: relative excess risk due to interaction; RR: relative risk; TotRERI: total relative excess risk due to interaction

Synergistic association of high-sensitivity C-reactive protein and body mass index with insulin resistance in non-diabetic adults

Epidemiological evidence has indicated that inflammatory markers and obesity are strongly correlated with insulin resistance (IR). However, there is a paucity of studies assessing the complex interaction between elevated hs-CRP and body mass index (BMI), particularly among Asians. This study investigated the additive interaction between hs-CRP and BMI on IR, using cross-sectional data from the 7th Korea National Health and Nutrition Examination Survey (2016–2018). A total of 5706 men and 6707 women aged 20 years or older were evaluated, and a multiple logistic regression analysis was used to assess the association of serum hs-CRP and BMI with IR, as measured by the triglyceride-glucose index (TyG index). Sex-specific median values were used to dichotomise the continuous TyG index variable into insulin-sensitive and IR categories. Biological interaction was evaluated using the Relative excess risk due to interaction (RERI), attributable proportion due to interaction (AP), and synergy index (SI). The joint effects of high hs-CRP and overweight/obesity on IR were greater than would be expected from the effects of the individual exposures alone. Relative to those with low hs-CRP and BMI < 23, having both exposures was related to increased IR with an adjusted OR of 2.97 (95% CI 2.50–3.52) in men and 3.08 (95% CI 2.67–3.56) in women with significant additive interactions. These findings demonstrate that IR prevention strategies that reduce both systematic inflammation and BMI may exceed the expected benefits based on targeting these risk factors separately.

Anthocyanin Intake and Physical Activity: Associations with the Lipid Profile of a US Working Population

While growing evidence exists on the independent associations between anthocyanins and physical activity on cardiovascular disease (CVD) risk determinants, the possible interaction between these exposures has not yet been studied. We aimed to study the potential synergism between anthocyanin intake and physical activity on lipid profile measures. This cross-sectional study was conducted among 249 US career firefighters participating in the Feeding America's Bravest trial. Anthocyanin intake was calculated using a validated food frequency questionnaire (FFQ) and physical activity level by a validated questionnaire. Multivariable linear regression models determined the extent to which anthocyanin intake and physical activity predicted lipid parameters. Generalized linear models were used for joint effect and interaction analyses on the multiplicative and additive scales. Both anthocyanins and physical activity were independently inversely associated with total cholesterol:high density lipoprotein (HDL) cholesterol. Only physical activity was inversely associated with triglycerides, low density lipoprotein (LDL) cholesterol:HDL, and triglycerides (TG):HDL. Although the combined exposure of low anthocyanin intake and low physical activity was associated with lower (RR = 2.83; 95% CI: 1.42 to 5.67) HDL cholesterol <40 mg/dL, neither multiplicative (p = 0.72) nor additive interactions were detected (relative excess risk due to interaction (RERI): 0.02; 95% CI: -1.63 to 1.66; p = 0.98). Our findings provide insight on the potential synergism between anthocyanin intake and physical activity on the lipid profile.

Biannual azithromycin distribution and child mortality among malnourished children: A subgroup analysis of the MORDOR cluster-randomized trial in Niger

BACKGROUND

Biannual azithromycin distribution has been shown to reduce child mortality as well as increase antimicrobial resistance. Targeting distributions to vulnerable subgroups such as malnourished children is one approach to reaching those at the highest risk of mortality while limiting selection for resistance. The objective of this analysis was to assess whether the effect of azithromycin on mortality differs by nutritional status.

METHODS AND FINDINGS

A large simple trial randomized communities in Niger to receive biannual distributions of azithromycin or placebo to children 1-59 months old over a 2-year timeframe. In exploratory subgroup analyses, the effect of azithromycin distribution on child mortality was assessed for underweight subgroups using weight-for-age Z-score (WAZ) thresholds of -2 and -3. Modification of the effect of azithromycin on mortality by underweight status was examined on the additive and multiplicative scale. Between December 2014 and August 2017, 27,222 children 1-11 months of age from 593 communities had weight measured at their first study visit. Overall, the average age among included children was 4.7 months (interquartile range [IQR] 3-6), 49.5% were female, 23% had a WAZ < -2, and 10% had a WAZ < -3. This analysis included 523 deaths in communities assigned to azithromycin and 661 deaths in communities assigned to placebo. The mortality rate was lower in communities assigned to azithromycin than placebo overall, with larger reductions among children with lower WAZ: -12.6 deaths per 1,000 person-years (95% CI -18.5 to -6.9, P < 0.001) overall, -17.0 (95% CI -28.0 to -7.0, P = 0.001) among children with WAZ < -2, and -25.6 (95% CI -42.6 to -9.6, P = 0.003) among children with WAZ < -3. No statistically significant evidence of effect modification was demonstrated by WAZ subgroup on either the additive or multiplicative scale (WAZ < -2, additive: 95% CI -6.4 to 16.8, P = 0.34; WAZ < -2, multiplicative: 95% CI 0.8 to 1.4, P = 0.50, WAZ < -3, additive: 95% CI -2.2 to 31.1, P = 0.14; WAZ < -3, multiplicative: 95% CI 0.9 to 1.7, P = 0.26). The estimated number of deaths averted with azithromycin was 388 (95% CI 214 to 574) overall, 116 (95% CI 48 to 192) among children with WAZ < -2, and 76 (95% CI 27 to 127) among children with WAZ < -3. Limitations include the availability of a single weight measurement on only the youngest children and the lack of power to detect small effect sizes with this rare outcome. Despite the trial's large size, formal tests for effect modification did not reach statistical significance at the 95% confidence level.

CONCLUSIONS

Although mortality rates were higher in the underweight subgroups, this study was unable to demonstrate that nutritional status modified the effect of biannual azithromycin distribution on mortality. Even if the effect were greater among underweight children, a nontargeted intervention would result in the greatest absolute number of deaths averted.

TRIAL REGISTRATION

The MORDOR trial is registered at clinicaltrials.gov NCT02047981.

Role of Rare and Low-Frequency Variants in Gene-Alcohol Interactions on Plasma Lipid Levels

BACKGROUND

Alcohol intake influences plasma lipid levels, and such effects may be moderated by genetic variants. We aimed to characterize the role of aggregated rare and low-frequency protein-coding variants in gene by alcohol consumption interactions associated with fasting plasma lipid levels.

METHODS

In the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium, fasting plasma triglycerides and high- and low-density lipoprotein cholesterol were measured in 34 153 individuals with European ancestry from 5 discovery studies and 32 277 individuals from 6 replication studies. Rare and low-frequency functional protein-coding variants (minor allele frequency, ≤5%) measured by an exome array were aggregated by genes and evaluated by a gene-environment interaction test and a joint test of genetic main and gene-environment interaction effects. Two dichotomous self-reported alcohol consumption variables, current drinker, defined as any recurrent drinking behavior, and regular drinker, defined as the subset of current drinkers who consume at least 2 drinks per week, were considered.

RESULTS

We discovered and replicated 21 gene-lipid associations at 13 known lipid loci through the joint test. Eight loci (PCSK9, LPA, LPL, LIPG, ANGPTL4, APOB, APOC3, and CD300LG) remained significant after conditioning on the common index single-nucleotide polymorphism identified by previous genome-wide association studies, suggesting an independent role for rare and low-frequency variants at these loci. One significant gene-alcohol interaction on triglycerides in a novel locus was significantly discovered (P=6.65×10^-6 for the interaction test) and replicated at nominal significance level (P=0.013) in SMC5.

CONCLUSIONS

In conclusion, this study applied new gene-based statistical approaches and suggested that rare and low-frequency genetic variants interacted with alcohol consumption on lipid levels.

A comprehensive gene-environment interaction analysis in Ovarian Cancer using genome-wide significant common variants

As a follow-up to genome-wide association analysis of common variants associated with ovarian carcinoma (cancer), our study considers seven well-known ovarian cancer risk factors and their interactions with 28 genome-wide significant common genetic variants. The interaction analyses were based on data from 9971 ovarian cancer cases and 15,566 controls from 17 case-control studies. Likelihood ratio and Wald tests for multiplicative interaction and for relative excess risk due to additive interaction were used. The top multiplicative interaction was noted between oral contraceptive pill (OCP) use (ever vs. never) and rs13255292 (p value = 3.48 × 10-4 ). Among women with the TT genotype for this variant, the odds ratio for OCP use was 0.53 (95% CI = 0.46-0.60) compared to 0.71 (95%CI = 0.66-0.77) for women with the CC genotype. When stratified by duration of OCP use, women with 1-5 years of OCP use exhibited differential protective benefit across genotypes. However, no interaction on either the multiplicative or additive scale was found to be statistically significant after multiple testing correction. The results suggest that OCP use may offer increased benefit for women who are carriers of the T allele in rs13255292. On the other hand, for women carrying the C allele in this variant, longer (5+ years) use of OCP may reduce the impact of carrying the risk allele of this SNP. Replication of this finding is needed. The study presents a comprehensive analytic framework for conducting gene-environment analysis in ovarian cancer.

Predictors of Hepatitis C Treatment Failure After Using Direct-Acting Antivirals in People Living With Human Immunodeficiency Virus

BACKGROUND

Little is known about the influence of ongoing barriers to care in the persistence of hepatitis C virus (HCV) viremia after treatment with direct-acting antivirals (DAAs) among people living with human immunodeficiency virus (PLWH).

METHODS

We conducted a retrospective cohort analysis of PLWH treated through the standard of care in 3 Western countries, to investigate the predictors of HCV treatment failure (clinical or virologic), defined as having a detectable serum HCV ribonucleic acid within 12 weeks after DAA discontinuation. In addition to HCV and liver-related predictors, we collected data on ongoing illicit drug use, alcohol abuse, mental illness, and unstable housing. Logistic regression analyses were used to identify predictors of HCV treatment failure.

RESULTS

Between January 2014 and December 2017, 784 PLWH were treated with DAA, 7% (n = 55) of whom failed HCV therapy: 50.9% (n = 28) had a clinical failure (discontinued DAA therapy prematurely, died, or were lost to follow-up), 47.3% (n = 26) had an HCV virologic failure, and 1 (1.8%) was reinfected with HCV. Ongoing drug use (odds ratio [OR] = 2.60) and mental illness (OR = 2.85) were independent predictors of any HCV treatment failure. Having both present explained 20% of the risk of any HCV treatment failure due to their interaction (OR = 7.47; P < .0001). Predictors of HCV virologic failure were ongoing illicit drug use (OR = 2.75) and advanced liver fibrosis (OR = 2.29).

CONCLUSIONS

People living with human immunodeficiency virus with ongoing illicit drug use, mental illness, and advanced liver fibrosis might benefit from enhanced DAA treatment strategies to reduce the risk of HCV treatment failure.

Considerations when assessing heterogeneity of treatment effect in patient-centered outcomes research

When baseline risk of an outcome varies within a population, the effect of a treatment on that outcome will vary on at least one scale (e.g., additive, multiplicative). This treatment effect heterogeneity is of interest in patient-centered outcomes research. Based on a literature review and solicited expert opinion, we assert the following: (1) Treatment effect heterogeneity on the additive scale is most interpretable to health-care providers and patients using effect estimates to guide treatment decision-making; heterogeneity reported on the multiplicative scale may be misleading as to the magnitude or direction of a substantively important interaction. (2) The additive scale may give clues about sufficient-cause interaction, although such interaction is typically not relevant to patients' treatment choices. (3) Statistical modeling need not be conducted on the same scale as results are communicated. (4) Statistical testing is one tool for investigations, provided important subgroups are identified a priori, but test results should be interpreted cautiously given nonequivalence of statistical and clinical significance. (5) Qualitative interactions should be evaluated in a prespecified manner for important subgroups. Principled analytic plans that take into account the purpose of investigation of treatment effect heterogeneity are likely to yield more useful results for guiding treatment decisions.

Robust Tests for Additive Gene-Environment Interaction in Case-Control Studies Using Gene-Environment Independence

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.

Evaluating Public Health Interventions: 6. Modeling Ratios or Differences? Let the Data Tell Us

We provide an overview of the relative merits of ratio measures (relative risks, risk ratios, and rate ratios) compared with difference measures (risk and rate differences). We discuss evidence that the multiplicative model often fits the data well, so that rarely are interactions with other risk factors for the outcome observed when one uses a logistic, relative risk, or Cox regression model to estimate the intervention effect. As a consequence, additive models, which estimate the risk or rate difference, will often exhibit interactions. Under these circumstances, absolute measures of effect, such as years of life lost, disability- or quality-adjusted years of life lost, and number needed to treat, will not be externally generalizable to populations other than those with similar risk factor distributions as the population in which the intervention effect was estimated. Nevertheless, these absolute measures are often of the greatest importance in public health decision-making. When studies of high-risk study populations are used to more efficiently estimate effects, these populations will not be representative of the general population's risk factor distribution. The relative homogeneity of ratio versus absolute measures will thus have important implications for the generalizability of results across populations.

Are major behavioral and sociodemographic risk factors for mortality additive or multiplicative in their effects?

All individuals are subject to multiple risk factors for mortality. In this paper, we consider the nature of interactions between certain major sociodemographic and behavioral risk factors associated with all-cause mortality in the United States. We develop the formal logic pertaining to two forms of interaction between risk factors, additive and multiplicative relations. We then consider the general circumstances in which additive or multiplicative relations might be expected. We argue that expectations about interactions among socio-demographic variables, and their relation to behavioral variables, have been stated in terms of additivity. However, the statistical models typically used to estimate the relation between risk factors and mortality assume that risk factors act multiplicatively. We examine empirically the nature of interactions among five major risk factors associated with all-cause mortality: smoking, obesity, race, sex, and educational attainment. Data were drawn from the cross-sectional NHANES III (1988-1994) and NHANES 1999-2010 surveys, linked to death records through December 31, 2011. Our analytic sample comprised 35,604 respondents and 5369 deaths. We find that obesity is additive with each of the remaining four variables. We speculate that its additivity is a reflection of the fact that obese status is generally achieved later in life. For all pairings of socio-demographic variables, risks are multiplicative. For survival chances, it is much more dangerous to be poorly educated if you are black or if you are male. And it is much riskier to be a male if you are black. These traits, established at birth or during childhood, literally result in deadly combinations. We conclude that the identification of interactions among risk factors can cast valuable light on the nature of the process being studied. It also has public health implications by identifying especially vulnerable groups and by properly identifying the proportion of deaths attributable to a risk factor.

Population Density, Poor Sanitation, and Enteric Infections in Nueva Santa Rosa, Guatemala

Poor sanitation could pose greater risk for enteric pathogen transmission at higher human population densities because of greater potential for pathogens to infect new hosts through environmentally mediated and person-to-person transmission. We hypothesized that incidence and prevalence of diarrhea, enteric protozoans, and soil-transmitted helminth infections would be higher in high-population-density areas compared with low-population-density areas, and that poor sanitation would pose greater risk for these enteric infections at high density compared with low density. We tested our hypotheses using 6 years of clinic-based diarrhea surveillance (2007–2013) including 4,360 geolocated diarrhea cases tested for 13 pathogens and a 2010 cross-sectional survey that measured environmental exposures from 204 households (920 people) and tested 701 stool specimens for enteric parasites. We found that population density was not a key determinant of enteric infection nor a strong effect modifier of risk posed by poor household sanitation in this setting.

Testing for Sufficient-Cause Gene-Environment Interactions Under the Assumptions of Independence and Hardy-Weinberg Equilibrium

To detect gene-environment interactions, a logistic regression model is typically fitted to a set of case-control data, and the focus is on testing of the cross-product terms (gene × environment) in the model. A significant result is indicative of a gene-environment interaction under a multiplicative model for disease odds. Based on the sufficient-cause model for rates, in this paper we put forward a general approach to testing for sufficient-cause gene-environment interactions in case-control studies. The proposed tests can be tailored to detect a particular type of sufficient-cause gene-environment interaction with greater sensitivity. These tests include testing for autosomal dominant, autosomal recessive, and gene-dosage interactions. The tests can also detect trend interactions (e.g., a larger gene-environment interaction with a higher level of environmental exposure) and threshold interactions (e.g., gene-environment interaction occurs only when environmental exposure reaches a certain threshold level). Two assumptions are necessary for the validity of the tests: 1) the rare-disease assumption and 2) the no-redundancy assumption. Another 2 assumptions are optional but, if imposed correctly, can boost the statistical powers of the tests: 3) the gene-environment independence assumption and 4) the Hardy-Weinberg equilibrium assumption. SAS code (SAS Institute, Inc., Cary, North Carolina) for implementing the methods is provided.

Does neighborhood deprivation modify the effect of preterm birth on children's first grade academic performance?

Children's cognitive development and academic performance are linked to both fetal and early childhood factors, including preterm birth and family socioeconomic status. We evaluated whether the relationship between preterm birth (PTB) and first grade standardized test performance among Georgia public school students was modified by neighborhood deprivation in early childhood. The Georgia Birth to School cohort followed 327,698 children born in Georgia from 1998 to 2002 through to end-of-year first grade standardized tests. Binomial and log-binomial generalized estimating equations were used to estimate risk differences and risk ratios for the associations of both PTB and the Neighborhood Deprivation Index for the census tract in which each child's mother resided at the time of birth with test failure (versus passing). The presence of additive and multiplicative interaction was assessed. PTB was strongly associated with test failure, with increasing risk for earlier gestational ages. There was positive additive interaction between PTB and neighborhood deprivation. The main effect of PTB versus term birth increased risk of mathematics failure: 15.9% (95%CI: 13.3-18.5%) for early, 5.0% (95% CI: 4.1-5.9%) for moderate, and 1.3% (95%CI: 0.9-1.7%) for late preterm. Each 1 standard deviation increase in neighborhood deprivation was associated with 0.6% increased risk of mathematics failure. For children exposed to both PTB and higher neighborhood deprivation, test failure was 4.8%, 1.5%, and 0.8% greater than the sum of two main effects for early, moderate, and late PTB, respectively. Results were similar, but slightly attenuated, for reading and English/language arts. Our results suggest that PTB and neighborhood deprivation additively interact to produce greater risk among doubly exposed children than would be predicted from the sum of the effects of the two exposures. Understanding socioeconomic disparities in the effect of PTB on academic outcomes at school entry is important for targeting of early childhood interventions.

A Tutorial on Interaction

In this tutorial, we provide a broad introduction to the topic of interaction between the effects of exposures. We discuss interaction on both additive and multiplicative scales using risks, and we discuss their relation to statistical models (e.g. linear, log-linear, and logistic models). We discuss and evaluate arguments that have been made for using additive or multiplicative scales to assess interaction. We further discuss approaches to presenting interaction analyses, different mechanistic forms of interaction, when interaction is robust to unmeasured confounding, interaction for continuous outcomes, qualitative or “crossover” interactions, methods for attributing effects to interactions, case-only estimators of interaction, and power and sample size calculations for additive and multiplicative interaction.

Invited commentary: assessing mechanistic interaction between coinfecting pathogens for diarrheal disease

The interaction estimates from Bhavnani et al. (Am J Epidemiol. 2012;176(5):387-395) are used to evaluate evidence for mechanistic interaction between coinfecting pathogens for diarrheal disease. Mechanistic interaction is said to be present if there are individuals for whom the outcome would occur if both of 2 exposures are present but would not occur if 1 or the other of the exposures is absent. In the epidemiologic literature, mechanistic interaction is often conceived of as synergism within Rothman's sufficient-cause framework. Tests for additive interaction are sometimes used to assess such synergism or mechanistic interaction, but testing for positive additive interaction only allows for the conclusion of mechanistic interaction under fairly strong "monotonicity" assumptions. Alternative tests for mechanistic interaction, which do not require monotonicity assumptions, have been developed more recently but require more substantial additive interaction to draw the conclusion of the presence of mechanistic interaction. The additive interaction reported by Bhavnani et al. is of sufficient magnitude to provide strong evidence of mechanistic interaction between rotavirus and Giardia and between rotavirus and Escherichia. coli/Shigellae, even without any assumptions about monotonicity.

Causation and causal inference for genetic effects

Over the past three decades, substantial developments have been made on how to infer the causal effect of an exposure on an outcome, using data from observational studies, with the randomized experiment as the golden standard. These developments have reshaped the paradigm of how to build statistical models, how to adjust for confounding, how to assess direct effects, mediated effects and interactions, and even how to analyze data from randomized experiments. The congruence of random transmission of alleles during meiosis and the randomization in controlled experiments/trials, suggests that genetic studies may lend themselves naturally to a causal analysis. In this contribution, we will reflect on this and motivate, through illustrative examples, where insights from the causal inference literature may help to understand and correct for typical biases in genetic effect estimates.