Health Study Research Articles

Changes in Dental Care Use Following Marital Status Change in the Health and Retirement Study.

Previous studies have indicated that married people are generally healthier than unmarried people, with lower mortality rates. Most work in this area has employed cross-sectional data, and few studies have examined change in marital status from married to unmarried as a potential social ecological determinant of dental health behavior. Here we used longitudinal data to examine change in dental behavior over time following marital status change, and to explore whether self-reported gender may play a modifying role in any behavioral change. Employing panel data from the Healthy Retirement Study (1996-2018) to follow all individuals who entered the study in married/partnered status, and using both two-way fixed effects and group-time average difference-in-difference models, we analyzed the association between any change in marital status and dental care use, compared to individuals who remained married. All analyses were stratified by gender. Both types of difference-in-difference analyses indicated that both widowhood and divorce were associated with a decrease in dental care use in both genders. Divorced men saw the greatest decrease in dental care use. We found gender had a moderating effect on strength of association in all analyses. This research suggests that any change in marital status from married to unmarried has a detrimental effect on dental health behavior for both genders. Future research might investigate other potential barriers to dental care access these populations might face, in order to develop effective interventions.

Association of estimated glucose disposal rate with incident cardiovascular disease under different metabolic and circadian rhythm states: findings from a national population-based prospective cohort study

BackgroundRecent studies have shown that both metabolic syndrome and circadian rhythm syndrome are firmly associated with the occurrence of cardiovascular disease (CVD), with insulin resistance playing a significant role. The estimated glucose disposal rate (eGDR) is considered to be a reliable surrogate marker for insulin resistance. However, the relationship between eGDR and CVD under different metabolic and circadian rhythm states has not been thoroughly studied, and large-scale prospective cohort studies are needed to clarify this relationship.MethodsThis study is based on the China Health and Retirement Longitudinal Study (CHARLS), recruiting individuals aged 45 and above with complete eGDR data. The eGDR was calculated by the formula: eGDR(mg/kg/min) = 21.158 − (0.09 × WC) − (3.407 × hypertension) − (0.551 × HbA1c) [WC (cm), hypertension (yes = 1/no = 0), and HbA1c (%)] (Zabala et al. in Cardiovasc Diabetol 20(1):202; 2021).Participants were divided into four subgroups based on the quartiles (Q) of eGDR.The cumulative incidence rates and hazard ratios (HR) with 95% confidence intervals (CI) were calculated, with the lowest eGDR quartile (representing the highest degree of insulin resistance) as the reference. Participants were further divided into subgroups based on the diagnosis of Metabolic syndrome (MetS) or circadian syndrome (CircS) to explore the relationship between eGDR and CVD under different metabolic and circadian rhythm conditions. The dose–response relationship between eGDR and CVD incidence was investigated using a restricted cubic spline (RCS) based on a Cox regression model. Receiver operating characteristic (ROC) curves were generated to assess the predictive value of eGDR for CVD incidence. A clinical decision curve analysis (DCA) was also conducted to assess the clinical utility of the basic model.Results6507 participants were included, with a median age of 58 years [52 years, 64 years], and 55% were female. Over a median follow-up duration of 87 months, 679 first-episode CVD events were recorded, including heart disease and stroke. The RCS curves demonstrated a significant dose–response relationship between eGDR and the incidence of first-presentation CVD in different metabolic and circadian rhythm subgroups (all P-values < 0.001, non-linearity P > 0.05). eGDR exhibited a significant linear relationship with all outcomes (non-linearity P < 0.05). The Kaplan–Meier cumulative incidence curves showed that as eGDR levels increased, the cumulative incidence rates of first CVD, heart disease, and stroke gradually decreased from Q1 to Q4 groups. Significant differences were observed across all metabolic and circadian rhythm subgroups (log-rank test P < 0.001). Through the Cox proportional hazards model, we confirmed a significant association between baseline eGDR levels and first-onset CVD, heart disease, and stroke. Subgroup analyses indicated that the predictive ability of eGDR for CVD risk varied across different Body mass index (BMI) (P for interaction = 0.025) and age (P for interaction = 0.045) subgroups. Mediation analysis revealed that CircS partially mediated this association. Furthermore, time-dependent ROC curves demonstrated the potential of eGDR as a predictor of CVD risk, revealing possible differences in the model's application across different cardiovascular conditions.ConclusioneGDR is an independent predictor of CVD risk, with lower eGDR levels being closely associated with a higher risk of CVD (including heart disease and stroke). In populations with MetS or CircS, the association between lower eGDR levels and increased risk is more pronounced.

Adult intergenerational proximity and parents’ depressive symptoms: A bidirectional approach

To date, only a few studies have investigated the bidirectional relationship in the intergenerational proximity-health nexus, specifically how geographic proximity affects older parents' depressive symptoms and vice versa. Drawing on eight waves (2004–2018) of the U.S. Health and Retirement Study (n = 17,671), we examine several mechanisms (‘mobilization’, ‘social support’, and ‘social breakdown’) that drive the complex relationship between intergenerational proximity and parental depressive symptoms. Dynamic panel models with fixed effects in a structural equation modeling context provided some weak evidence of a ‘mobilization effect’ (that is, parents', especially fathers', depression triggering greater proximity, including coresidence) and somewhat clearer evidence for a ‘social breakdown effect’ of coresidential transitions on parents' depressive symptoms (particularly among ‘Whites’ and fathers). We found no evidence to support the notion of a ‘social support mechanism’ (predicting that greater proximity or the transition to coresidence would decrease the number of parents' depressive symptoms).

Risks and Outcomes of New Onset of Unmet Need for Mobility and Self-care Daily Activities.

Among community-living older adults who have limitations in completing Activities of Daily Living (ADLs), unmet need occurs when they cannot complete an ADL task because no one was available to help. Prior research described correlates of existing unmet needs but did not consider which older adults are at risk for new onset of unmet needs. This study assessed health characteristics that increased risk for new onset of unmet needs within a year and subsequent health outcomes. Data are from the 2011-2019 annual interviews of the National Health and Aging Trends Study. For each pair of two consecutive annual interviews, we determined whether new onset of unmet needs occurred between the first and second consecutive interviews. Mixed effects logistic regression models were computed to assess risks for new onset of unmet need across 14,890 paired observations from persons who needed help with mobility tasks and 12,514 paired observations from persons who needed help with self-care tasks. Although demographic characteristics and chronic conditions had modest associations with new onset of unmet need, hospitalization between the two consecutive interviews was associated with a two-fold increase in risk for new onset of unmet need. New onset of unmet need was associated with hospitalization, nursing home placement, and death in the year following the two consecutive annual interviews. The findings inform the need for frequent assessments of ADL care needs with the goal of preventing new onset of unmet needs, especially after hospitalization.

Analysis of factors influencing students’ decisions in choosing a specialization in the Public Health Study Program, Faculty of Public Health, Halu Oleo University, 2024

Analysis of factors influencing students’ decisions in choosing a specialization in the Public Health Study Program, Faculty of Public Health, Halu Oleo University, 2024

Cumulative Socioeconomic Status Risk is Associated with Greater Increase in Serum Neurofilament Light Chain Levels Among Middle-Aged Black Adults.

This study examined the longitudinal relationship between cumulative socioeconomic status (SES) risk and serum neurofilament light chain (NfL) levels to better understand the association between social factors and a biomarker of neurodegeneration. We used data from the Family and Community Health Study (FACHS), collecting psychosocial and blood data at two waves (2008) and (2019) from 254 Black Americans (43 males and 211 females). Blood samples were analyzed at each wave for serum NfL concentrations. Regression analysis and mixed-effect modeling examined relationships between cumulative SES risk and serum NfL, controlling for covariates and assessing time effects. Utilizing 11-year longitudinal data, serum NfL levels increased with age. Higher cumulative SES risk at baseline correlated with elevated serum NfL at the 11-year follow-up and predicted a greater increase in NfL levels. Clinically, NfL is a sensitive biomarker for axonal injury and neurodegeneration, commonly used to detect early and preclinical stages of conditions such as Alzheimer's disease (AD), multiple sclerosis, and other neurodegenerative disorders. Our results suggest that exposure to cumulative SES risk among Black adults may contribute to elevated levels of NfL, indicating potential early neurodegeneration. Given the established role of NfL in detecting neurodegenerative processes, these findings underscore the importance of interventions that bolster social safety nets and social connectedness to enhance brain health and mitigate neurodegenerative risks.

Fear of COVID-19 Diagnosis and Cannabis Use Patterns Among Adults with Chronic Health Conditions: Results from COVID-19 Cannabis Health Study

ABSTRACT Given the scarcity of literature regarding COVID-19 impacts on cannabis consumers with chronic illnesses who widely use cannabis to manage their health conditions, we aim to assess the effect of COVID-19 on cannabis use patterns among adults living with chronic diseases. Cannabis consumers with a chronic disease (N = 1,466) from COVID-19 Cannabis Health Study were included in this analysis. The primary outcomes were change in cannabis dosage, past 30-day cannabis usage, and change in route of cannabis administration, with the main exposure being self-reported fear of COVID-19 diagnosis. Significant differences were found between changes in cannabis dose by fear of COVID-19 diagnosis (p = .03) where 41.5% of adults fearing diagnosis reported an increase in their cannabis dosage since the pandemic. Multinomial logistic regression showed that individuals who feared COVID-19 diagnosis had 50% greater odds [aOR = 1.50, 95% CI: 1.02–2.24 of decreasing their cannabis in reference to their dose staying the same, than those without fear of COVID-19, adjusting for socio-demographics. Our findings highlight the significant association between fear of COVID-19 diagnosis and changes in cannabis usage patterns among adults with chronic diseases. This underscores the pandemic’s impact on health-related behaviors and the role of cannabis as a coping mechanism during uncertain times.

Dual group-based trajectories of physical activity and cognitive function in aged over 55: a nationally representative cohort study

BackgroundAs individuals age, they commonly experience reduced physical activity and cognitive decline. While evidence, there is limited trajectory research on their concurrent progression and interrelation in individuals over 55 years old.MethodsThe data was collected from 5,765 individuals aged over 55 years who participated in the China Health and Retirement Longitudinal Study (CHARLS) between 2011 and 2020. Physical activity was measured by IPAQ, cognitive function by episodic memory, and mental intactness score. Separate sets of group-based trajectory models were fitted to identify physical activity trajectories and cognitive function trajectories. Multivariate logistic regression was used to estimate the association between baseline characteristics and each set of trajectories. Group-based dual trajectory modeling (GBDTM) was applied to quantify these associations.ResultsGBDTM identified three distinct trajectory groups for physical activity and cognitive outcomes. The physical activity trajectories were classified as “Persistently low physical activity” (74.2%), “Decreasing physical activity” (13.7%), and “Rising physical activity” (12.1%). Similarly, cognitive function trajectories were categorized as “Persistently low cognitive function” (22.2%), “Persistently moderate cognitive function” (37.9%), and “Persistently high cognitive function” (39.9%). Notably, 15.6% of participants followed the trajectories of “Persistently low physical activity” and “Persistently low cognitive function.” The presence of a severe decline in physical activity was associated with an increased likelihood of poor cognitive function and vice versa. Age, sex, education, residential status, BMI, and visual impairment were identified as significant predictors for physical activity and cognitive decline.ConclusionThis study found that the GBDTM can determine the consistent trajectories of physical activity and cognitive function trajectories that persistently decline in individuals over 55 years. Analyses of predictive factors can be instrumental in promoting physical activity and delaying cognitive decline.

Risk for Financial Precarity From Hospitalization: Implications for Targeting Financial Assistance in Medicare.

High out-of-pocket costs in Medicare may leave many beneficiaries in financial precarity. Beneficiaries with modest incomes are often ineligible for Medicaid (which covers most out-of-pocket Medicare costs) and may have insufficient resources to pay an unexpected health care bill. This has prompted calls to improve financial protections, but the target population remains uncharacterized. To identify beneficiaries who would face financial precarity if exposed to the Medicare Part A hospital deductible ($1600). Cross-sectional study of the 2018 wave of the Health and Retirement Study. United States. Community-dwelling Medicare beneficiaries with incomes greater than 100% to 400% or less of the federal poverty level. Nationally representative estimates of financial precarity, defined as having insufficient funds to pay the deductible, examined across 4 scenarios that considered checking and savings account balances, total liquid assets (with a reserve for future living costs), and supplemental insurance. Among 4881 beneficiaries (population weighted n = 26 619 823), 45.0% had insufficient funds in checking and savings accounts to pay the Medicare hospital deductible. Financial precarity was more prevalent among Black and Hispanic versus White beneficiaries (73.5% and 76.2% vs. 36.2%), those with less versus more than high school education (70.0% vs. 37.1%), and those with 3 or more versus 2 or fewer chronic conditions (49.2% vs. 39.1%). In defining financial precarity to include beneficiaries with insufficient liquid assets to pay the deductible while maintaining a $5000 reserve for future living expenses, 50.7% were financially precarious. Building off this definition to assume supplemental insurance covered the deductible, 39.0% remained financially precarious. Cost-sharing exposure is limited to hospitalization. Many Medicare beneficiaries with modest incomes are at risk for financial hardship from costs of a single hospital stay. National Institute on Aging.

Economic disadvantage during childhood, obesity, and diabetes across three birth cohorts of older Mexicans.

Diabetes prevalence has increased markedly in Mexico. We examined the individual and joint contributions of economic disadvantage during childhood (EDDC) and elevated body weight on diabetes prevalence in three cohorts of Mexican adults. Data on those 60-69 years old from the 1930-39, 1940-49, and 1950-59 birth cohorts in Waves 1 (2001), 3 (2012), and 5 (2018) of the Mexican Health and Aging Study were used. EDDC was defined as the absence of a toilet in the household before age 10. Body mass status was defined using self-reported perceived body image at age 50. Diabetes was based on respondent reports. Supplementary analyses using HbA1c as a criterion for diabetes were conducted. A regression-decomposition approach was implemented. Logistic regression models included adjustments for sociodemographic characteristics and access to medical care. Diabetes prevalence was 23% overall and 11%, 25%, and 26% in the 1930-39, 1940-49, and 1950-59 cohorts, respectively. EDDC declined across successive cohorts, while the prevalence of overweight/obesity at age 50 increased. EDDC and overweight/obesity were associated with higher odds of reporting diabetes. A scenario that eliminates disadvantaged EDDC reduced diabetes prevalence by 11% in a pooled sample, while eliminating overweight/obesity reduced it by 30%. Overweight/obesity explained 42% of the rise in diabetes prevalence between the 1930-39 and 1950-59 cohorts. Improvement in EDDC explained 18% of the rise in diabetes prevalence between 1930-39 and 1950-59 cohorts. High body weight across Mexican birth cohorts seemed to offset the potential benefits from improvements in childhood conditions on adult diabetes risk.

Association between possible sarcopenia, all-cause mortality, and adverse health outcomes in community-dwelling older adults in China

The relationship between possible sarcopenia and mortality remains ambiguous within Asian populations. To clarify this, we investigated the association in older adults residing in Chinese communities. Utilizing data from the China Health and Retirement Longitudinal Study, this population-based cohort study included individuals aged ≥ 60 years, followed from 2011 to 2012 through 2020. Possible sarcopenia was defined in accordance with the Asian Working Group on Sarcopenia 2019 criteria, and Cox proportional hazards regression was used to analyze its impact on mortality, while exploratory analyses were conducted to investigate the associations of possible sarcopenia with chronic diseases, functional independence, and hospitalization frequency. The study encompassed 5,160 participants (median age: 66 years), nearly half of whom (48.8%) were identified with possible sarcopenia. Over a 9-year follow-up period, there were 1216 recorded deaths. Analysis indicated that individuals with possible sarcopenia faced a significantly elevated mortality risk compared to their counterparts (HR: 1.79, 95% CI: 1.58–2.03; P < 0.001). Further, subgroup analyses confirmed a strong association between possible sarcopenia and all-cause mortality across various subgroups, including those related to sex, obesity status, and living environment. Additionally, exploratory analyses revealed that possible sarcopenia was significantly associated with an increased likelihood of heart disease (OR = 1.18, 95% CI: 1.03–1.34, P = 0.014) and stroke (OR = 1.41, 95% CI: 1.19–1.68, P < 0.001), as well as reduced functional independence (β = -0.17, 95% CI: -0.24–-0.10, P < 0.001). Possible sarcopenia was also associated with a higher frequency of hospitalizations at baseline (Exp(β) = 1.50, 95% CI: 1.25–1.81, P < 0.001), although this association was no longer significant during the follow-up period. In conclusion, in Chinese community-dwelling older adults, possible sarcopenia was associated with an increased risk of all-cause mortality, several chronic diseases, and functional dependence. Thus, alleviating or preventing possible sarcopenia may improve health outcomes and extend the lifespan of these individuals.

Home Mortgage Lending and Neighborhood Mental Health: A Spatial Econometric Analysis of 18 U.S. Metropolitan Statistical Areas.

This study investigates the relationship between home mortgages and neighborhood mental health across the 18 largest metropolitan statistical areas (MSAs) in the United States. Home mortgages, a primary avenue to homeownership, contribute to housing security and stability. Moreover, their issuance reflects local investment and potential improvements in the built environment, hypothesized to positively influence community mental well-being. Using census tract-level data from multiple sources, we employed a spatial econometric approach, specifically spatial error modeling, to account for spatial dependency and estimate the association between home mortgage lending (2011 to 2020) and the prevalence of self-reported poor mental health in 2020. Our findings indicate a statistically significant negative association between mortgage issuance and self-reported poor mental health across all 18 MSAs, suggesting that increased mortgage lending is associated with improved neighborhood mental health. Comparisons between standard linear models and spatial error models highlight the influence of unmeasured, spatially correlated factors on neighborhood mental health outcomes. This study underscores mortgage lending as a crucial factor in community well-being and emphasizes the necessity of addressing spatial dependency in neighborhood health studies for accurate estimations. The findings offer valuable insights for researchers and policymakers aiming to enhance community mental health and address health disparities through informed housing policies.

Novel metabolomic predictors of incident colorectal cancer in men and women.

Metabolomic profiles may influence colorectal cancer (CRC) development. Few studies have performed pre-diagnostic metabolome-wide analyses with CRC risk. We conducted a nested case-control study among women (Nurses' Health Study (NHS)) and men (Health Professionals Follow-up Study (HPFS)) who provided blood between 1989 and 1995. Over 22.9 years, 684 (409 NHS, 275 HPFS) incident CRC cases occurred and were matched 1:1 to controls. Liquid chromatography-mass spectrometry (LC-MS) identified 255 plasma metabolites after quality control. Cohort-specific and combined metabolite association analyses were performed using conditional logistic regression. Metabolite set enrichment analysis (MSEA) was used to identify differential abundance in metabolite classes. Weighted Correlation Network Analysis (WGCNA) provided modules of covarying metabolites, which were tested for CRC association. MSEA identified specific acylcarnitines associated with higher CRC risk and triacylglycerols with lower CRC risk among women and men. Further, phosphatidylcholines were associated with a higher risk of CRC among men. In an analysis restricted to CRC cases diagnosed two years after blood draw, myristoleic acid (OR = 1.37; 95%CI = 1.15-1.62; FDR = 0.072) and C60:12 triacylglycerol (OR = 0.75; 95%CI = 0.64-0.88; FDR = 0.072 were associated with CRC risk in women. WGCNA identified amino acids associated with CRC in men, fatty acid esters (carnitines) with distal CRC in men, and triradylcglycerols inversely associated with CRC in women. We identified pre-diagnostic CRC-associated metabolites with distinct sex-specific profiles. These results provide insight into CRC etiopathogenesis and have implications for risk prediction strategies.

Sleep characteristics in relation to cardiovascular disease incidence and mortality in individuals with diabetes

Abstract Background/Introduction Evidence regarding the potential health effects of sleep characteristics among individuals with type 2 diabetes (T2D) is limited. Purpose We aimed to examine sleep characteristics in relation to subsequent risk of cardiovascular disease (CVD), including coronary heart disease (CHD), and stroke, and all-cause and cause-specific mortality among individuals with T2D. Methods We prospectively followed 21,902 men and women with T2D at baseline or diagnosed during follow-up (Nurses' Health Study: 1986-2018, Health Professionals Follow-Up Study: 1986-2018). Sleep characteristics, including sleep duration, snoring, sleep apnea, and sleep quality, were repeatedly assessed using self-reported questionnaires at baseline and follow-up. Associations of sleep characteristics with CVD risk and mortality were assessed using Cox proportional hazards models with adjustments for demographic, dietary and lifestyle factors, and medical history. Results During 170,355 and 196,458 person-years of follow-up in participants with T2D, there were 2,486 incident CVD events and 3,922 deaths, respectively. Compared with sleeping for 7-8 h/day, the multivariable-adjusted hazard ratios (HRs) of sleeping for ≤5 h/day were 1.21 (1.02, 1.45) for CVD incidence, 1.24 (1.20, 1.51) for CHD incidence, 1.40 (1.24, 1.58) for total mortality, 1.52 (1.20, 1.92) for CVD mortality, and 1.27 (1.01, 1.61) for other non-CVD and non-cancer mortality, while the HRs of ≥10 h/day were 1.42 (1.21, 1.66) for total mortality, and 1.63 (1.20, 2.10) for other non-CVD and non-cancer mortality. Furthermore, compared with participants without habitual snoring, those with habitual snoring had a 21%, 24%, 18%, and 33% higher risk for CVD incidence, CHD incidence, CVD mortality, and total mortality, respectively. Compared with participants without diagnosed sleep apnea, those with sleep apnea had a 27%-58% higher risk for CVD incidence, CVD mortality, and total mortality. In addition, lower habitual sleep quality, including sleep difficulties and restless sleep, was associated with a substantially higher risk of CVD, CHD, or CVD mortality. No associations were observed between sleep characteristics with risk of stroke and cancer mortality in individuals with T2D. Conclusions Short and long sleep durations as well as habitual snoring, sleep apnea, and lower sleep quality were independently associated with higher risks of CVD incidence and mortality, particularly CVD mortality in individuals with T2D.

Improving cardiovascular risk stratification with ECG-predicted risk factors in primary prevention

Abstract Background Cardiovascular risk- and screening scores guide clinical practice. Built upon simple risk factors, they could benefit from information on actual, subclinical cardiac changes. The ECG provides proxies for various cardiac states, which can be detected using machine learning. We systematically assess the added value of ECG-based cardiovascular risk factor estimates for six outcomes in two population-based cohorts: Study of Health in Pomerania (SHIP-Start) and UK Biobank (UKB). Methods We employed convolutional neural networks to analyze ECGs from the Hamburg City Health Study (HCHS) for the assessment of multiple risk factors, including age, weight, diabetes, atrial fibrillation (AF) and heart failure. Cox models were fitted on UKB and SHIP to predict 5 and 15 year time-to-event. Endpoints were death, cardiovascular death, AF, stroke, heart failure and myocardial infarction. Covariates were sex, age, body mass index, diabetes, hypertension and smoking (Cox-RF), ECG-predicted risk factors (Cox-AI), and a combination (Cox-RF/AI). Stratified Monte Carlo cross-validation was used as validation and groups of C-indices were compared using Mann-Whitney U tests. Results The study included 9103 HCHS participants (mean age 62.0±8.4 years, 51% women), 3546 SHIP participants (age 49.7±16.4, 51% women), and 32828 UKB participants (age 64±7.6 years, 52% women). Cox-AI performed comparable or better than Cox-RF for AF (SHIP: 0.88 vs. 0.84, UKB: 0.71 vs. 0.72) and heart failure (SHIP: 0.8 vs. 0.79, UKB: 0.76 vs. 0.75), but was less strong for the other outcomes. The combination of information on cardiovascular risk factors and ECG information (Cox-RF/AI) significantly improved the predictive ability compared to risk factors alone (Cox-RF) for AF (SHIP: 0.89 vs. 0.84, UKB: 0.76 vs. 0.72), cardiovascular death (SHIP: 0.90 vs. 0.89, UKB: 0.75 vs. 0.74) and heart failure (SHIP: 0.81 vs. 0.79, UKB: 0.80 vs. 0.75). Discussion ECG-based risk factors complement risk stratification by incorporating nuanced information on cardiac function and structure, improving risk prediction and thus possibly clinical decision making and patient outcomes.

Diagnostic and prognostic value of ECG-predicted hypertension mediated left ventricular hypertrophy using machine learning

Abstract Background Hypertension is the commonest cause of left ventricular hypertrophy (LVH). Using cardiac magnetic resonance (CMR) imaging, four distinct hypertension mediated LVH phenotypes have been reported: normal LV, LV remodelling, eccentric LVH and concentric LVH. Early detection of hypertensives with LVH can enable timely initiation of therapy however a CMR based screening strategy is costly, particularly in low resource settings. The electrocardiogram (ECG) is an inexpensive screening tool and can detect LVH but its capacity to discriminate between the 4 phenotypes is unknown. Purpose To classify hypertension mediated LVH phenotypes from the ECG using machine learning (ML) and test for associations of ECG predicted LVH phenotypes with incident cardiovascular outcomes. Methods ECG markers with a known physiological association with LVH (including QRS markers, Sokolow-Lyon, and Cornell) were extracted from the 12-lead ECG of 20,439 hypertensive participants in UK Biobank. Three classification models, logistic regression, support vector machine (SVM) and random forest, were trained in 80% of the participants using extracted ECG markers and clinical variables. The remaining 20% individuals were included in the test set for performance measurement. External validation was sought in 877 hypertensives from the Study of Health in Pomerania (SHIP). Subsequently, we tested for associations between the four ECG-predicted LVH phenotypes and incident major adverse cardiovascular events (MACE) and heart failure using Cox proportional hazard regression in the UK Biobank test set with median follow-up of 4.2 years. Results Among UK Biobank participants (mean age ± standard deviation 65 ± 7.4 years), 23,190 had normal LV, 894 LV remodelling, 218 eccentric and 103 concentric LVH. Classification performance of the three models was comparable, but SVM showed consistent results (accuracy 0.79, sensitivity 0.59, specificity 0.87, AUC 0.69) and superior prediction of eccentric LVH (AUC 0.86). In SHIP (55 ± 12.7 years), 704 had normal LV, 134 LV remodelling, 12 eccentric and 24 concentric LVH. In the external validation performed in SHIP, SVM had accuracy of 0.75 (sensitivity 0.51, specificity 0.85, AUC 0.65), with superior prediction of eccentric LVH (AUC 0.76), as shown in Figure 1. Ventricular rate and QRS amplitude (P&amp;lt;0.001) were the features most strongly associated with LVH. In the test set of UK Biobank, setting normal LV as the reference group, the ECG predicted eccentric LVH group was associated with heart failure (Hazard Ratio 3.42, confidence interval 1.06-9.86), there were no associations with MACE (Figure 2). Conclusions ECG-based ML classifiers were able to discriminate the four hypertension mediated LVH phenotypes with external validation demonstrating robustness. This automated approach enhances capabilities of non-specialists and potentially represents an accessible screening strategy for the early detection of hypertensives with LVH.

Sense of community, life satisfaction and psychological distress among seniors – HUNT4 study, Norway

Abstract Background Strong sense of community with one’s neighbors may benefit psychosocial well-being. Moreover, local communities with high level of belonging and social cohesion can have a positive impact on public mental health. This study aims to investigate associations between sense of community and life satisfaction - at both an individual and local community level in a Norwegian county. Methods Data from Trøndelag Health Study 4 (HUNT4: 2017-2019) on 22 939 participants were linked to geographic data of residence from Statistics Norway. The basic statistical unit in Norwegian, known as “grunnkrets,” serves to identify participants’ local communities. These units are subdivisions of municipalities, covering geographically contiguous areas that typically include a few hundred inhabitants. This population-based study enables investigation of variation in sense of community, trust, life satisfaction and psychological distress on individual and community level. Results Seniors (median age 70.3 years) with strong sense of community with their neighbors had more than three times higher odds (95%CI 3.08-3.93) of high level of life satisfaction and less than 0.3 times lower odds (95%CI 0.26-0.33) of psychological distress symptoms vs those with low sense of community, adjusted to sociodemographic variables. The average sense of community varied between local communities (N = 284). At this local geographical unit, strong sense of community was associated with high level of trust, enjoying the neighborhood and high life satisfaction. Conclusions The study can inform public health policy to consider development of social infrastructures that bolster sense of community among seniors within neighborhoods. Policy and action plans targeting to increase the overall sense of community in neighborhoods may contribute to create mental health-promoting and age-friendly local communities in Norway. Key messages • At individual level, sense of community with neighbors are associated with life satisfaction and psychological distress among Norwegian seniors. • The average sense of community varies between geographic local areas and are associated with level of trust, enjoying the neighborhood, average life satisfaction, and psychological distress.

Exposure to antibiotics and risk of latent autoimmune diabetes in adults and type 2 diabetes: results from a Swedish case-control study (ESTRID) and the Norwegian HUNT study.

Some studies find an increased risk of type 1 diabetes in children exposed to antibiotics. We investigated if exposure to antibiotics increases the risk of latent autoimmune diabetes in adults (LADA) and type 2 diabetes. We used data from a Swedish case-control study (Epidemiological Study of Risk Factors for LADA and Type 2 Diabetes [ESTRID]: LADA, n=597; type 2 diabetes, n=2065; control participants matched on participation time, n=2386) and a case-control study nested within the Norwegian Trøndelag Health Study (HUNT) (n=82/1279/2050). Anatomical Therapeutic Chemical (ATC) codes indicating antibiotic dispensations were retrieved from the Swedish National Prescribed Drug Register and Norwegian Prescription Database. Multivariable adjusted ORs with 95% CIs were estimated by conditional logistic regression and pooled using fixed-effects inverse-variance weighting. We observed no increased risk of LADA with exposure to antibiotics up to 1 year (ORpooled 1.15, 95% CI 0.93, 1.41) or 1-5 years (ORpooled 0.98, 95% CI 0.80, 1.20) prior to diagnosis/matching for one or more vs no dispensation of any type of antibiotic. An increased risk was observed for one or more vs no dispensations of narrow-spectrum antibiotics, but not broad-spectrum antibiotics, 6-10 years prior to LADA diagnosis (ORpooled 1.39, 95% CI 1.01, 1.91), which was driven by the Swedish data. There was little evidence of an increased risk of type 2 diabetes associated with antibiotic exposure 1-10 years prior to diagnosis. We found no evidence that exposure to broad-spectrum antibiotics up to 10 years prior to diagnosis increases the risk of LADA. There was some indication of increased LADA risk with exposure to narrow-spectrum antibiotics, which warrants further investigation.

Indoor Air Quality and health of older people: a pilot study

Abstract Background Older people often experience one or more chronic conditions, including respiratory conditions. Indoor air quality may (IAQ) may elevate symptoms of respiratory disease such as coughing. Consequently, people may experience a lower Health Related Quality of Life (HR-QoL). The objective of the Rotterdam K-HEALTHinAIR pilot site is to study IAQ and health among elderly: this study presents the design of the study and preliminary baseline results of IAQ and health. Methods A observational study is performed among n = 110 older people living in the broader Rotterdam-area, the Netherlands, recruited via opportunity sampling, hospitals and senior-residential corporations. Participants provide informed consent to participate in the study. IAQ is assessed near real-time using home sensors. An observation checklist captures environmental characteristics of the home. Participants complete a diary every 3 months and a self-report questionnaire at baseline, 6- and 12-months; measures include Health-Related Quality of Life, well-being and respiratory symptoms. Preliminary baseline data (n = 30 baseline questionnaires, n = 25 sensors) were analyzed using descriptive statistics and regression analyses. Results The mean age was 74.3 (SD: 6.3). Average concentrations were 684 ppm CO2 (SD: 723), PM2.5 was 4.8 µg/m3 (SD: 34.5) and average temperature 19.9 °C (SD:1.6). In total 40.0% participants were experiencing asthma and 43.3% COPD. Participants rated their general well-being 72.6 (SD: 18.6) (0-100). No associations were observed between indicators of IAQ and participant self-rated health and health symptoms in this preliminary dataset. Conclusions Future data collection will allow for overtime associations between IAQ and a broad range of health outcomes. In the second and third phase of the study we aim to deepen findings and develop interventions.

An intergenerational study of mental health among parents and adolescents

Abstract Background The aim of this study was to examine the association between parents’ mental disorders and adolescents’ self-rated health, using both subjective and objective assessment of parents’ mental health status. Methods This cohort study was based on the Danish Future Occupation of Children and Adolescents cohort. Study population 25,891parents (biological parents or registered guardians) linked to 13,067 adolescents. Survey data were merged with register data on parent mental health, and logistic regression was used to analyse association between the register- and self-report data on parents mental health, and self-rated global health among their offspring. Results Adolescents’ self-rated health was associated with their parents’ mental disorders, showing an unadjusted OR of 1.5 (95% CI 1.4-1.6) when assessing parental mental disorders using ICD-10 diagnoses and an unadjusted OR of 2.0 (95% CI 1.8-2.2) when using the adolescents’ self-reported measure on the parental mental disorder. Adjustment for adolescents’ sex, adolescents’ mental disorders during childhood, parental education, and parental labour market attachment led to a decreased association between parents’ mental disorders and adolescents’ self-rated health in both analyses with an adjusted OR of 1.2 (95% CI 1.1-1.4) when assessing parents’ mental disorders using ICD-10 diagnoses and an adjusted OR of 1.8 (95% CI 1.6-2.0) when using the adolescents’ self-reported measure on parental mental disorder. Conclusions This study documents a clear pattern in mental disorders across generations and that parental labour market attachment as well as mental disorders in earlier life phases are risk factors for developing mental disorders in adolescence. The results point to the importance of public health interventions aimed at the more vulnerable group of adolescents, where mental health problems are observed over two generations. Key messages • There is a clear pattern in mental disorders across generations. • Parental labour market attachment are risk factors for developing mental disorders among their offspring.