Demmer, Ryan T.

ABSTRACT Cohort studies are vulnerable to confounding and time‐related biases. Recent advances emphasize the importance of emulating a hypothetical target trial to minimize several of these biases. The target trial framework is a critical tool for designing cohort studies. It requires explicit specification of protocol components: eligibility criteria, treatment strategies, outcomes, timing of follow‐up (time zero), and the causal contrast to be estimated. Critical to this framework is defining “time zero” when treatment assignment takes place and follow‐up begins, which prevents prevalent user and immortal time bias and ensures proper temporal sequencing of confounders, exposure, and outcome. By guiding design, data collection, and analysis, the target trial framework helps align observational studies with the principles of randomized trials, improving the validity and interpretability of their findings. While it cannot eliminate unmeasured confounding, this approach promotes transparent, bias‐conscious cohort design, minimizes time‐related bias, and supports more robust causal inference with observational data.

Background: Periodontitis is a potential modifiable factor influencing dementia risk. We examined whether improving periodontal health via regular flossing is associated with lower dementia risk. Methods: A total of 9,766 Atherosclerosis Risk in Communities (ARIC) study participants with teeth were followed from visit 4 (1996-1998) through 2021. Cox proportional hazards regression was used to estimate associations between regular dental flossing (≥1/week) and incident dementia. Covariates included age, race, gender, hypertension, diabetes, alcohol use, smoking status, obesity, physical activity, education level, income, insurance status, brushing frequency, regular dental care use and apolipoprotein E4 (APOE4) allele status . Cumulative incidence functions were estimated using death as a competing event. Results: Participants had mean age 62.6 years (SD = 5.6), 56% female, 79% white, 21% black, 63% reported regular flossing and 29.2% participants carry at least one APOE4 allele. The cumulative incidence of dementia was 52.6 % overall over 25 years. Regular flossing was independently and significantly associated with a lower hazard of developing dementia (HR = 0.90, 95% CI: 0.82–0.98, p = 0.02) after adjustment for all the covariates. In contrast, tooth brushing frequency (p=0.55) and regular dental care visit (p=0.22) were not significantly associated with dementia risk. By 25 years of follow-up, the cumulative incidence of dementia was 50% among flossers compared with 57% among non-flossers (Gray’s test p<0.0001, Figure). This translated to an Absolute Risk Reduction of 7%, Relative Risk Reduction of 12%, Number Needed to Floss 14. Conclusion: Flossing, but not tooth brushing or regular dental care, is independently associated with a reduced hazard of incident dementia. Dental flossing may be an additional strategy to reduce dementia risk. For every 14 individuals who floss ≥1/week, one fewer person will develop dementia.

ABSTRACT Cross‐sectional studies capture health states, exposures, and risk factors at a single time point, providing essential data for estimating disease prevalence and informing public health planning. These studies serve multiple epidemiological purposes: characterizing population health, monitoring temporal trends through repeated surveys, and evaluating interventions via interrupted time series designs. They also offer practical advantages for validating self‐reported measures and creating diagnostic models. Cross‐sectional designs are efficient and well‐suited to descriptive epidemiology, but they have limited utility for causal inference. The simultaneous measurement of exposures and outcomes creates temporal ambiguity that fundamentally constrains etiologic interpretation. However, causal inferences can be strengthened under specific conditions—when temporal sequence is unambiguous (e.g., genetic variants preceding outcomes) or when valid instrumental variables are available. This methodological tutorial equips readers with concepts and tools to critically appraise cross‐sectional studies across the application domains outlined and to design and analyze their own cross‐sectional studies that yield high‐quality epidemiologic descriptions.

ABSTRACT Aims To investigate whether the association between the nitrite‐generating capacity of the subgingival microbiome and early cardiometabolic risk biomarkers varies by dietary nitrate intake. Materials and Methods Cross‐sectional data from 668 participants (mean age 31 ± 9 years, 73% women) were analysed. Dietary nitrate intake was calculated from food frequency questionnaires. Subgingival 16S rRNA sequencing (Illumina, MiSeq) and PICRUSt2 estimated microbial genes. The Microbiome‐Induced Nitric Oxide Enrichment Score (MINES) was calculated as a ratio of microbial gene abundances representing enhanced net capacity for NO generation. Adjusted multivariable linear models regressed cardiometabolic risk biomarkers (HbA1c, glucose, insulin, insulin resistance (HOMA‐IR), blood pressure) on nitrate intake and MINES together with a MINES × nitrate intake interaction term. Results Mean nitrate intake was 190 ± 171 mg/day. Significant interactions of MINES and nitrate intake were observed for insulin and HOMA‐IR ( p < 0.05). Among participants with a low MINES, higher nitrate intake was associated with lower HOMA‐IR (1.2 [1.1–1.4] vs. 1.5 [1.3–1.6]; p = 0.002), but levels were similar in those with high MINES ( p = 0.84). Conclusions A biomarker of higher microbial NO‐generating capacity in subgingival plaque is associated with lower insulin and insulin resistance among individuals with lower dietary nitrate intake. Future trials evaluating the cardiometabolic benefits of nitrate‐rich diets should incorporate measures of the entire oral microbiome.

Diabetes mellitus (DM) and periodontitis share a complex, bidirectional relationship, with each condition exacerbating the other. Diabetes, particularly when poorly controlled, significantly increases the risk, severity, and progression of periodontitis. The biological mechanisms involved are complex and numerous. Hyperglycemia in diabetes is linked to oral microbial dysbiosis, which is in turn associated with increased inflammation, epithelial barrier dysfunction, impaired neutrophil and macrophage function, altered T-cell profiles, and cytokine imbalance, collectively fostering chronic inflammation and immune dysregulation. Moreover, diabetes alters bone metabolism, promoting osteoclastogenesis and reducing reparative bone regeneration by limiting coupled bone formation through an effect on growth factor production, mesenchymal stems cells, and osteoblasts. Conversely, periodontitis is strongly linked to poor glycemic control. Clinical studies and longitudinal meta-analyses report consistent positive associations, while randomized controlled trials show that periodontal therapy reduces HbA1c by ~0.43%. Emerging evidence suggests that periodontitis and oral preclinical dysbiosis contribute to diabetogenesis, although causality remains uncertain. Periodontitis may drive metabolic dysfunction through several biological mechanisms. The dysbiotic oral microbiome and subsequent periodontitis may promote systemic inflammation and subsequent insulin resistance and glucose intolerance. Moreover, oral dysbiosis may deplete nitrate-reducing taxa and impair nitric oxide pathways, which has relevance to both periodontal and cardiometabolic health. Accordingly, periodontal treatment in diabetic populations has shown potential health care savings. Nevertheless, trials assessing the influence of periodontitis treatment on systemic outcomes consistently show significant treatment heterogeneity, which requires explication in future studies. This review underscores the systemic implications of periodontitis in diabetes and highlights the value of integrating periodontal care into diabetes management. A better understanding of the shared pathophysiology between these diseases supports interdisciplinary approaches and points toward novel preventive and therapeutic strategies targeting inflammation, microbial balance, and host response modulation to jointly benefit periodontal and cardiometabolic health.

Abstract Background Although periodontitis and oral microbiota are linked to cardiometabolic diseases (CMD), it is unclear if they similarly predict CMD mortality. We compared the predictive ability of salivary microbiota and periodontal disease measures for CMD mortality in the National Health and Nutrition Examination Survey (NHANES). Methods We included 5,037 adults aged ≥30 years (mean age [± standard deviation (SD)]: 48[± 14]; 50% male) from the 2009–2010 and 2011–2012 NHANES cycles. We used 16S rRNA sequencing data from saliva to operationalize microbial composition and diversity. We calculated the relative abundance log‐ratio of Treponema (linked with periodontal disease) to Corynebacterium (linked with periodontal health) to compute the Microbial Indicator of Periodontitis (MIP). Interproximal periodontal probing depth and clinical attachment loss were measured from periodontal examinations. Mortality was ascertained through 2019. Survey‐weighted Cox models regressed mortality rates on MIP, microbial diversity, and periodontal measures to estimate hazard ratios and 95% confidence intervals (HR [95% CI]). Results Over 8.8 median follow‐up years, there were 81 CMD and 267 all‐cause deaths. After multivariable adjustment, MIP was associated with increased CMD mortality risk (HR per 1‐SD: 2.10 [1.30–3.38]). Neither microbial diversity nor periodontitis measures were associated with CMD mortality. MIP was associated with periodontitis in multivariable modeling (risk ratio per 1‐SD: 1.29 [1.22–1.39]). Conclusions In a nationally representative cohort, greater baseline salivary Treponema to Corynebacterium ratio predicted increased CMD mortality risk, while microbial diversity metrics and periodontal parameters were not significantly associated with CMD mortality. Longitudinal studies that further contextualize the oral microbiota are warranted. Plain Language Summary Bacteria in the mouth that cause gum disease are linked to cardiometabolic diseases (e.g., diabetes, cardiovascular disease, kidney disease). However, it is not well understood if bacteria of the mouth can predict the risk of death due to cardiometabolic diseases. We used data from a nationwide survey of US adults to explore whether bacteria from saliva, collected from a single time point, are associated with the future risk of cardiometabolic disease death. We found that people with higher levels of gum disease bacteria were more likely to die from cardiometabolic diseases. Future studies are needed to better understand the role of gum disease bacteria in the development of cardiometabolic diseases and the risk of death.

Importance SARS-CoV-2 infection has been linked to neurotoxic effects and cognitive deficits. Objective To determine whether decreases in cognitive function were accelerated after SARS-CoV-2 infection compared with individuals not infected. Design, Setting, and Participants Multicenter, prospective cohort study from 2016 to 2022 among 3525 participants alive on March 1, 2020, and enrolled in The Atherosclerosis Risk in Communities (ARIC) study and the Collaborative Cohort of Cohorts for COVID-19 Research study who completed a prepandemic cognitive assessment and a pandemic-era assessment of SARS-CoV-2 infection. Final analyses performed in November 2024. Exposure SARS-CoV-2 infection determined via self-report of a positive SARS-CoV-2 test or health care professional diagnosis of COVID-19, a positive SARS-CoV-2 antinucleocapsid antibody response, or presence of an administrative code for COVID-19 on medical records. Main outcomes and measures A neuropsychological battery assessed multiple cognitive domains, and a cocalibrated confirmatory factor analysis generated factor scores for global cognitive function. The primary outcome was the rate of excess change in cognitive function. Results The 3525 eligible participants had a mean (SD) age of 80.8 (4.7) years, 2085 (59.1%) were female, 752 (21.4%) were Black, and 2773 (78.6%) were White. SARS-CoV-2 infection was detected among 307 participants (8.7%), 103 of whom (33.6%) were hospitalized. Among uninfected participants, the mean annualized change in cognitive function was −0.09 (95% CI, −0.13 to −0.04). Compared with this rate, change was faster (β = −0.06; 95% CI, −0.09 to −0.02) among participants hospitalized for infection, but not different from participants who were infected but not hospitalized (β = 0.00; 95% CI, −0.02 to 0.03). The association among participants hospitalized for infection was evident in the cognitive domains of memory and executive function, but not language. Conclusions and relevance This cohort study of older participants found accelerated decreases in cognition among individuals hospitalized for SARS-CoV-2 infection, but not nonhospitalized infection, in comparison with individuals not yet infected.

Abstract Aims While intentional weight loss achieved through cardiometabolic medications has been associated with robust salutary effects in heart failure (HF) with preserved ejection fraction (HFpEF), the clinical significance of unintentional weight loss in this setting remains unclear. Methods and results This retrospective cohort study included 434 overweight or obese patients with invasively proven HFpEF (67 ± 11 years, 236 female), without weight-reducing therapies or known malignancy, who underwent invasive hemodynamic cardiopulmonary testing and long-term clinical follow-up. The annualized weight change from index to final evaluation for the tertiles was: −21.1 to −1.8 kg/year (tertile 1); −1.8 to 0 kg/year (tertile 2); and 0 to +17.0 kg/year (tertile 3). Patients in tertile 1 had subtle abnormalities in ventilatory control at baseline, but there were no other significant differences between groups across a vast array of haemodynamic and metabolic parameters, both at rest and during exercise. Baseline weight was directly correlated with right and left heart filling pressures (r = 0.23–0.34, p &lt; 0.001), but annualized weight change showed no correlation with any baseline haemodynamic measurements (all p &gt; 0.05). Over a median follow-up of 4.7 years (interquartile range 2.3–6.5), patients in tertile 1 had higher risk of all-cause death (hazard ratio [HR] 3.36, 95% confidence interval [CI] 1.77–6.39, p &lt; 0.001), all-cause death or HF hospitalization (HR 2.49, 95% CI 1.53–4.04, p &lt; 0.001) and cardiac death or HF hospitalization (HR 2.28, 95% CI 1.28–4.07, p = 0.005) compared with those in tertile 2 or 3. These findings were consistent after multivariable adjustment. Conclusions Unintentional weight loss is associated with worse prognosis in patients with HFpEF and overweight or obesity, even as haemodynamics, exercise capacity, and gas exchange are not different from patients with stable or increasing weight. These data underline important and fundamental differences between therapeutic and unintended weight loss in HFpEF.

Background Heart failure (HF) is a growing public health burden. Systemic inflammation is commonly observed in patients with HF and believed to be related to disease pathogenesis. Infection is a potential acute trigger of chronic inflammation. Our objective was to examine the relationship between infection‐related hospitalization (IRH) and HF. Methods and Results We studied beneficiaries with at least 15 months of continuous enrollment in the US‐based MarketScan databases during 2013 to 2019. We included n=152 008 patients with an inpatient or outpatient HF International Classification of Diseases, Ninth Revision/Tenth Revision ( ICD‐9/10 ) code in the primary position. Among patients with HF, IRH was identified using select ICD‐9/10 codes. We used a case‐crossover design to compare the frequency of IRH occurring within 3 months of the index HF event (case period) versus the frequency of IRH occurring 12 to 15 months before the index HF event (control period). Logistic models regressed the log‐odds of having an IRH during the case versus control periods; odds ratios (ORs; 95% CIs) are presented. Among 152 008 beneficiaries, 53% were male with a mean±SD age of 56(±11) years. The odds of having an IRH during the case (versus control) period was elevated for both the 3‐month case period (OR, 4.39 [95% CI, 4.18–4.60]), and 1‐month case period (OR, 7.39 [95% CI, 6.88–7.94]), after adjusting for the total number of hospitalizations. This relationship persisted across different types of infections. Conclusions IRH was associated with incident HF after both 1 and 3 months and may represent a modifiable risk factor for HF.

Abstract RATIONALE: Chronic lower respiratory diseases (CLRD) confer higher risks from respiratory viral infections, hence CLRD patients are prioritized for influenza, pneumococcal, and COVID-19 vaccination. Nonetheless, vaccine deferral and declination remain common. Given that COVID-19 vaccination is particularly polarizing, and attitudes toward it may differ from other vaccines, we assessed COVID-19 vaccination behaviors and attitudes in adults with versus without CLRD and/or smoking history, which is strongly associated with CLRD risk. METHODS: We pooled data from 10 cohorts participating in the Collaborative Cohort of Cohorts for COVID-19 Research (C4R) that collected pre-pandemic data on self-reported physician diagnosis of asthma or COPD. C4R assessed COVID-19 vaccination status through three waves of standardized questionnaires (2020-2022, 2021-2023, 2023-2024). Prompt COVID-19 vaccination was defined as self-report of receiving at least one COVID-19 vaccine by May 1, 2021. Cumulative COVID-19 vaccine count was self-reported on the Wave 3 Questionnaire. Vaccine attitudes and receipt of influenza and/or pneumococcal vaccines were self-reported on the Wave 1 or 2 Questionnaire. Age-adjusted Poisson regression was used to test associations of vaccination behaviors with CLRD and smoking status at the most recent pre-pandemic exam. RESULTS: Of 20,034 participants (pre-pandemic COPD, 9.3%; asthma, 11.7%; current smoking, 13.4%; former smoking, 36.3%), 64.2% reported prompt COVID-19 vaccination. Among the subset of 10,626 participants completing the Wave 3 Questionnaire in 2023-24, the median COVID-19 vaccine count was 3 (Q1:2, Q3:4). Compared to participants without CLRD, prompt vaccination was more likely in those with asthma (RR=1.04, 95%CI:1.01-1.07, p=0.008) and less likely with COPD (RR=0.94, 95%CI:0.91-0.98, p=0.001), but there were no differences in doses for asthma and COPD. Compared to never smokers, former smoking participants were more likely to receive prompt vaccination (RR=1.11, 95%CI:1.08-1.13, p&lt;0.0001) and more vaccine doses (RR=1.03, 95%CI:1.01-1.05, p=0.015); conversely, current smoking was inversely associated with prompt vaccination (RR=0.94, 95%CI:0.91-0.97, p=0.001) and was associated with fewer doses (RR=0.93, 95%CI:0.89-0.96, p&lt;0.0001). Participants with CLRD versus without CLRD were more likely to report receiving influenza and pneumococcal vaccines, but they were more likely to believe that vaccines are unsafe or ineffective (figure). CONCLUSIONS: COPD was associated with lower likelihood of prompt COVID-19 vaccination. Current smoking was associated with both lower likelihood of prompt COVID-19 vaccination and a lower number of COVID-19 vaccine doses by 2023-24. These associations may be partly attributed to negative vaccine attitudes and beliefs. How the COVID-19 pandemic may have influenced vaccine behaviors and attitudes merits additional study.