Abstract Background Chronic kidney disease (CKD) is a growing public health concern, closely linked to aging and chronic conditions such as diabetes, cardiovascular disease, and hypertension. Diet is a modifiable risk factor for kidney function, but evidence on how specific dietary patterns (DPs) relate to kidney health in healthy populations remains limited. To address this, we evaluated associations between DPs and kidney function, considering sex and menstrual status. DPs were derived using both an a priori approach (DASH) and a hybrid method (RRR), capturing established dietary recommendations as well as population-specific behaviours relevant to kidney health. Methods We analysed cross-sectional data from 6133 healthy adult participants of the Cooperative Health Research In South Tyrol (CHRIS) study. Participants self-reporting previous diagnoses of any kidney disease, hypertension, or diabetes were excluded. Using self-reported food frequency questionnaire data, we derived the DASH-score and two RRR-based sex-specific DP-scores based on nine cardio-renal-metabolic parameters. We applied sex-stratified linear and non-linear models to examine associations with creatinine-based eGFR, including interaction and stratified analyses by menstrual status in females. Results In males, a DP reflecting high intake of cereals, whole grains, sugar, fruits, and legumes, and low intake of beer, red and processed meat was associated with higher eGFR levels (β = 0.75, p = 0.0001). Similarly, higher adherence to the DASH diet was also positively associated with eGFR (β = 0.64, p = 0.0029). In females, the associations varied by menstrual status. Among those with ceased menstruation, a DP reflecting low intake of meat, spirits, and refined grains, and high intake of whole grains and dairy products was associated with higher eGFR (β = 1.11, p = 0.0049). In females still experiencing regular menstruation, a DP reflecting high intake of beef, nuts, beer, and legumes, and low intake of refined grains was associated with lower eGFR (β = −0.43, p = 0.0326). No association was observed with the DASH score in females. Conclusions The DASH-style diet is associated with better kidney function in males, but not in females. Identifying sex-specific kidney function-oriented DPs using RRR provides new insights into the diet-eGFR relationship, suggesting potential effect modification by menstrual status.

BACKGROUND:Affective temperaments predispose to life adaptation and affective disorders. The relationship between temperaments and sleep quality is rarely investigated in community-based studies. We hypothesized that cyclothymic-related temperaments relate to worse sleep quality, whereas the hyperthymic temperament favours sleep quality. METHOD:We investigated 3701 18 to 65 years old adults from the population-based CHRIS study in Italy. Participants were 54 % females, mean age 38.5 years. The Pittsburgh Sleep Quality Index (PSQI) was the primary outcome score. Five affective temperaments split into quartiles for direct comparison from the TEMPS-M questionnaire were the exposures of interest. Additional covariates comprised sex, age, trait anxiety, and sleep quality-related lifestyles assessed via interviews, self-administered questionnaires or instrumental measurements. RESULTS:The hyperthymic temperament showed a negative association (better sleep quality) with the global PSQI, whereas the cyclothymic-related temperaments had all associations in opposite direction. While inclusion of trait anxiety appeared to mediate some results, the anxious and other cyclothymic related temperaments were still directly associated with multiple dimensions of poor sleep quality. LIMITATIONS:The cross-sectional design, possible selection into the study by temperamental background or sleep disorders, and no clinically validated self-assessed psychiatric constructs represent possible weaknesses. CONCLUSIONS:Our findings support the hypothesis of a biological binary diathesis of affective temperaments, with hyperthymic and cyclothymic-related temperaments predisposing sleep quality in an antithetical way.

Introduction Fine motor function, which integrates motor control and cognitive processing, has emerged as a promising non-invasive marker for neurodegenerative diseases and cognitive impairment.[1] However population-based reference data on fine motor patterns across adulthood are limited, making it difficult to distinguish physiological aging from pathological decline. The population-based Cooperative Health Research in South Tyrol (CHRIS) study, includes detailed assessments of fine motor function using digital spiral analysis (DSA).[2,3] DSA is a scalable and valid approach that captures the dynamics of hand drawing movements. It enables the quantification of multiple dimensions of fine motor control by extracting a range of spatiotemporal and frequency-based features from the drawing. These features provide a rich, multidimensional profile of neuromotor performance and hold promises for capturing early age-related deviations or subtle motor impairments associated with neurodegenerative processes. Objectives The objectives of this investigation were to characterize normative, age-dependent patterns of fine motor function across adulthood using spiral-derived kinematic metrics. Specifically, we aimed to estimate age-, sex-, and hand-specific centile curves for multiple motor parameters using flexible distributional modelling that captures central tendency, variability, and skewness. In addition, we sought to identify age of peak performance, inflection points in motor trajectories, and the age of steepest decline through derivative-based analysis. Methods All participants from the CHRIS study who completed three digital spiral drawings per hand (six in total) by alternating hands at each repetition were included in this investigation. Five spiral-derived metrics were analyzed, representing distinct domains of fine motor function: spatial properties (trace length), temporal measures (drawing time), kinematic features (drawing speed and acceleration), and markers of movement irregularity (tremor amplitude estimated from pen displacement and deviations from the ideal spiral path). Separate models were fitted for dominant and non-dominant hands, and all models incorporated sex-specific smooth age trends to account for biological differences in motor aging. To characterize age-normative patterns, the mean and degree of dispersion of each metrics were modeled as functions of age using the Box-Cox Cole and Green (BCCG) distribution within the Generalized Additive Models for Location, Scale, and Shape (GAMLSS) framework.[4] This approach enabled estimation of age-dependent centile curves for each metric while simultaneously modeling changes in dispersion and skewness. The BCCG distribution estimates three parameters: the median (μ), the coefficient of variation (σ), and the skewness (ν). To allow for greater distributional flexibility, we also fit models using the Box-Cox Power Exponential (BCPE) distribution, which includes a fourth parameter to capture kurtosis (τ). Improvements in model fit were evaluated using Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), and visual diagnostics. To further characterize the shape and timing of age-related changes, we conducted inflection point analysis based on the fitted μ (median) curves. First and second derivatives were computed to identify key ages of interest, including the age of peak performance, the inflection point (change in curvature), and the age of steepest change (maximum slope). This analysis complements centile modeling by highlighting potential transition points or acceleration peaks in fine motor decline. As a sensitivity analysis, we repeated the modeling using only the second spiral drawing from each participant to minimize potential practice or fatigue effects. Results A total of 8,707 participants (53.6% female) aged 18 to 94 years (mean = 44.8, SD = 16.7) returned 6 valid spirals. After exclusion of a minority of spirals with inconsistent metrics, there were 50,299 valid spirals for the analysis. Across all spiral-derived metrics, the BCCG distribution provided evidence of better fit than the normal distribution, effectively capturing age-related skewness in motor performance. The BCPE distribution further improved fit for selected metrics, namely spiral length and tremor amplitude, by modelling excess kurtosis. Model comparisons using AIC and BIC consistently favored flexible models. Derivative-based inflection point analysis identified distinct phases of motor change, with peak performance typically occurring in the late 30s to early 40s and accelerated decline between ages 60 and 70. For example, centile modeling of tremor amplitude (mm) at peak performance age 40, mean dominant hand values were 0.15 for males and 0.14 for females (5th–95th percentile: 0.08–0.33 and 0.07–0.30, respectively); by age 65, medians rose to 0.25 and 0.24, with broader ranges of 0.12–0.72 and 0.11–0.70, reflecting increased tremor and variability with age (Figure). These patterns remained consistent across sensitivity analyses supporting the robustness of the estimated age trends. Conclusions Digital spiral analysis revealed age-normative patterns of fine motor function across adulthood, with peak performance during advanced young adulthood and accelerated decline after age 60. Flexible GAMLSS modelling effectively captured age-related changes in central tendency, variability, and skewness across metrics, by sex and dominance of the drawing hand. These sex-age-specific centile curves offer a robust normative reference for evaluating fine motor performance and may support future applications in the early detection of motor dysfunction and neurodegenerative disease.

Background Kidney diseases are a public health burden but are poorly investigated in the general population. In light of inadequate survey tools, we developed a novel questionnaire for use in population-based studies, to retrospectively assess kidney diseases. Methods The questionnaire covered general kidney diseases, reduced kidney function, and renal surgeries. It was administered between 2011 and 2018 to 11,684 participants (median age = 45 years) of the Cooperative Health Research in South Tyrol (CHRIS) study. Fasting estimated glomerular filtration rate (eGFR) and urinary albumin-to-creatinine ratio (UACR) were measured. By factor analysis we contextualized the questionnaire content with respect to the biochemical measurements. We estimated overall and sex-stratified prevalence of kidney diseases, including possible CKD, calibrating them to the general target population via relative sampling weights. Results Population-representative prevalence of glomerulonephritis, pyelonephritis, and congenital kidney diseases was 1.0%, 3.0%, and 0.2%, respectively, with corresponding odds ratios for females versus males of 1.4 (95% confidence interval: 1.0, 2.0), 8.7 (6.2, 12.3), and 0.7 (0.3, 1.6), respectively. Prevalence of kidney dysfunction (eGFR < 60 mL/min/1.73 m(2) or UACR > 30 mg/g) was 8.59%, while prevalence of self-reported CKD was 0.69%, indicating 95.3% of lack of disease awareness, with a similar figure in people with diabetes or hypertension. Overall, 15.76% of the population was affected by a kidney disease of any kind. Conclusion In the Val Venosta/Vinschgau alpine district, CKD prevalence aligned with Western European estimates. Kidney health questionnaire implementation in population studies is feasible and valuable to assess CKD awareness, which we found to be dramatically low.

Background Reduced kidney function is a risk factor of cardiovascular and all-cause mortality. This association was demonstrated for several kidney function markers, but it is unclear whether integrating multiple measured markers may improve mortality risk prediction.Methods We conducted an exploratory factor analysis (EFA) of serum creatinine- and cystatin C-based estimated glomerular filtration rate [eGFRcre and eGFRcys; derived by the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) and European Kidney Function Consortium (EKFC) equations], blood urea nitrogen (BUN), uric acid and serum albumin among 366 758 participants in the UK Biobank without a history of kidney failure. Fitting Cox proportional hazards models, we compared the ability of the identified latent factors to predict overall mortality and mortality by cardiovascular disease (CVD), also considering CVD-specific causes like coronary heart disease (CHD) and cerebrovascular disease.Results During 12.5 years of follow-up, 26 327 participants died from any cause, 5376 died from CVD, 2908 died from CHD and 1116 died from cerebrovascular disease. We identified two latent factors, EFA1 and EFA2, both representing kidney function variations. When using the CKD-EPI equation, EFA1 performed like eGFRcys, with EFA1 showing slightly larger hazard ratios for overall and CVD-related mortality. At 10 years of follow-up, EFA1 and eGFRcys showed moderate discrimination performance for CVD-related mortality, outperforming all other kidney indices. eGFRcre was the least predictive marker across all outcomes. When using the EKFC equation, eGFRcys performed better than EFA1 while all other results remaining similar.Conclusions While EFA is an attractive approach to capture the complex effects of kidney function, eGFRcys remains the most practical and effective measurement for all-cause and CVD mortality risk prediction. Graphical Abstract

Identifying biomarkers able to discriminate individuals on different health trajectories is crucial to understand the molecular basis of age-related morbidity. We investigated multi-omics signatures of general health and organ-specific morbidity, as well as their interconnectivity. We examined cross-sectional metabolome and proteome data from 3,142 adults of the Cooperative Health Research in South Tyrol (CHRIS) study, an Alpine population study designed to investigate how human biology, environment, and lifestyle factors contribute to people’s health over time. We had 174 metabolites and 148 proteins quantified from fasting serum and plasma samples. We used the Cumulative Illness Rating Scale (CIRS) Comorbidity Index (CMI), which considers morbidity in 14 organ systems, to assess health status (any morbidity vs. healthy). Omics-signatures for health status were identified using random forest (RF) classifiers. Linear regression models were fitted to assess directionality of omics markers and health status associations, as well as to identify omics markers related to organ-specific morbidity. Next to age, we identified 21 metabolites and 10 proteins as relevant predictors of health status and results confirmed associations for serotonin and glutamate to be age-independent. Considering organ-specific morbidity, several metabolites and proteins were jointly related to endocrine, cardiovascular, and renal morbidity. To conclude, circulating serotonin was identified as a potential novel predictor for overall morbidity.

BACKGROUND:Tremor is commonly found among healthy humans or prevalently a symptom of neurological dysfunctions. However, the distinction between physiological and pathological tremor is dependent on the examiner's competence. Archimedes Spiral Rating (ASR) is a valid and reproducible semi-quantitative method to assess the severity of action tremor. OBJECTIVES:(1) To assess the range and percentiles of ASR in a large sample seemingly free of tremor-related conditions or symptoms from the population-based CHRIS-study. (2) To analyze the influence of sex, age, and the drawing hand on ASR. (3) To define ASR limits of normal. (4) To supply exemplary Archimedes spiral drawings by each rating to favor consistent and proficient clinical evaluation. METHODS:Accurately investigated participants were randomly sampled over 14 sex-age strata. 2686 paired spirals drawn with both hands by 1343 participants were expertly assessed on a tremor rating scale from 0 to 9. RESULTS:ASR had a quadratic increase with age in both sexes, while it was relatively lower in the dominant compared to the non-dominant hand and in women compared to men. ASRs above sex-age specific 97.5th percentiles of 4 and 5, below and above 60 years of age, respectively, were conceivably of non-physiological nature. CONCLUSIONS:In a large population-based sample we show a steeper increase of action tremor by age as age progresses. Relatively higher ratings among the elderly, males and the non-dominant hands, appear compatible with ASR limits of "normal" across sex-age groups. The current operational evidence may support practitioners differentiating physiological and pathological hand tremor.

Objective: While diet plays a key role in chronic kidney disease (CKD) management, the potential for diet to impact CKD prevention in the general population is less clear. Using a priori knowledge, we derived disease-related dietary patterns (DPs) through reduced rank regression (RRR) and investigated associations with kidney function, separately focusing on generally healthy individuals and those with self-reported kidney diseases, hypertension, or diabetes mellitus. Methods: Eight thousand six hundred eighty-six participants from the population-based Cooperative Health Research in South Tyrol study were split into a group free of kidney disease, hypertension and diabetes (n = 6,133) and a group with any of the 3 conditions (n = 2,553). Diet was assessed through the self-administered Global Allergy and Asthma Network of Excellence food frequency questionnaire and DPs were derived through RRR selecting food frequency questionnaire-derived sodium, potassium, phosphorus, and protein intake as mediators. Outcomes were creatinine-based estimated glomerular filtration rate, urinary albumin-to-creatinine ratio, CKD and microalbuminuria. Multiple linear and logistic models were used to assess associations between RRR-based DPs and kidney outcomes separately in the 2 analytic groups. Results: We identified 3 DPs, where high adherence reflected high levels of all nutrients (DP1), high potassium-phosphorus and low protein-sodium levels (DP2), and low potassium-sodium and high protein-phosphorus levels (DP3), respectively. We observed heterogeneous associations with kidney outcomes, varying by analytic group and sex. Kidney outcomes were much more strongly associated with DPs than with single nutrients. Conclusion: RRR is a feasible approach to estimate disease-related DPs and explore the combined effects of nutrients on kidney health. Heterogeneous associations across kidney outcomes suggest possible specificity to kidney function or damage. In individuals reporting kidney disease, hypertension or diabetes, specific dietary habits were associated with better kidney health, indicating that disease-specific dietary interventions can be effective for disease control.

AbstractIdentifying biomarkers able to discriminate individuals on different health trajectories is crucial to understand the molecular basis of age-related morbidity. We investigated multi-omics signatures of general health and organ-specific morbidity, as well as their interconnectivity. We examined cross-sectional metabolome and proteome data from 3,142 adults of the Cooperative Health Research in South Tyrol (CHRIS) study, an Alpine population study designed to investigate how human biology, environment, and lifestyle factors contribute to people’s health over time. We had 174 metabolites and 148 proteins quantified from fasting serum and plasma samples. We used the Cumulative Illness Rating Scale (CIRS) Comorbidity Index (CMI), which considers morbidity in 14 organ systems, to assess health status (any morbidity vs. healthy). Omics-signatures for health status were identified using random forest (RF) classifiers. Linear regression models were fitted to assess directionality of omics markers and health status associations, as well as to identify omics markers related to organ-specific morbidity.Next to age, we identified 21 metabolites and 10 proteins as relevant predictors of health status and results confirmed associations for serotonin and glutamate to be age-independent. Considering organ-specific morbidity, several metabolites and proteins were jointly related to endocrine, cardiovascular, and renal morbidity. To conclude, circulating serotonin was identified as a potential novel predictor for overall morbidity.

Abstract Background and Aims The estimated glomerular filtration rate (eGFR) and other kidney function markers are associated with cardiovascular disease (CVD) mortality [1]. It remains unclear whether integrating multiple kidney markers together can improve CVD mortality risk prediction and what would be an appropriate method of integration. In a small general population sample, we recently showed that confirmatory factor analysis (CFA) may predict CVD risk better than single markers, but it did not outperform cystatin C-based eGFR (eGFRcys) [2]. To assess whether our findings were context-dependent and to which extent they may extend to mortality risk assessment, we applied CFA and exploratory factor analysis (EFA), integrating five kidney function markers in the UK Biobank (UKBB) study, comparing risk discrimination for CVD mortality and renal failure mortality versus established eGFR formulas. Method We analyzed data from 366,758 UKBB participants (mean age 56.6 years; females 53.7%) without clinical history of kidney failure at baseline. Information on participants’ mortality was collected from the National Health System registry, using ICD-10 codes I00-I99 and N17-N19 to identify CVD mortality and renal failure mortality. We applied CFA and EFA to creatinine-based estimated glomerular filtration rate (eGFRcre), eGFRcys, blood urea nitrogen (BUN), uric acid (UA), and serum albumin (Alb). EFA was fitted using maximum likelihood. Promax rotation was then applied. We fitted Cox regression models to examine the associations of mortality with kidney markers: CFA-based kidney index [CFA]; 1st EFA-based kidney index [EFA1]; 2nd EFA-based kidney index [EFA2]; eGFRcre; eGFRcys; and creatinine- and cystatin C-based eGFR (eGFRcrecys). Models were adjusted for sex, age, body mass index, education, self-reported ancestry, hypertension, diabetes, and tobacco smoking. The receiver operating characteristics (ROC) curve and the DeLong test were used to compare discriminatory ability of each index. Results CFA standardized factor loadings (λ) of eGFRcre, eGFRcys, BUN, UA and Alb were 0.81, 0.73, -0.55, -0.39, and 0.12, respectively. EFA identified two factors: EFA1, largely dependent on eGFRcys (λ = 0.85), and EFA2, reflecting BUN (λ = 0.88), eGFRcre (λ = -0.55) and UA (λ = 0.36). Over a median follow-up of 12.5 years, we observed 26,327mortality cases, of which 5,376 and 45 were related to CVD and renal failure. The hazard ratios (HR) and 95% confidence intervals (CI) for CVD mortality and renal failure mortality per each standard deviation change were of 1.22 (1.19–1.25) and 3.53 (2.98–4.18) for eGFRcre, 1.62 (1.57–1.67) and 7.34 (5.82–9.27) for eGFRcys, 1.47 (1.43–1.51) and 4.82 (4.04–5.76) for eGFRcrecys, 1.38 (1.34–1.41) and 2.94 (2.63–3.29) for CFA, 1.61 (1.56–1.66) and 7.54 (5.90–9.64) for EFA1, and 1.33 (1.30–1.35) and 1.98 (1.85–2.12) for EFA2. The area under the curve (AUC) for CVD mortality risk was higher for EFA1 (0.706, 0.699–0.713) than for any other kidney marker, except for eGFRcys (0.709, 0.702–0.716). The kidney failure mortality AUC of EFA1 (0.936, 0.901–0.972) was similar to that of eGFRcys (0.939, 0.905–0.972). Conclusion To assess the contribution of kidney function to CVD-related mortality in general population studies of mainly healthy individuals, EFA is a better way than using single markers. However, EFA does not outperform eGFRcys, which, being based on a simpler calculation, remains a better choice for CVD and renal failure mortality risk prediction.

Lower kidney function is known to enhance cardiovascular disease (CVD) risk. It is unclear which estimated glomerular filtration rate (eGFR) equation best predict an increased CVD risk and if prediction can be improved by integration of multiple kidney function markers. We performed structural equation modeling (SEM) of kidney markers and compared the performance of the resulting pooled indexes with established eGFR equations to predict CVD risk in a 10-year longitudinal population-based design. We split the study sample into a set of participants with only baseline data (n = 647; model-building set) and a set with longitudinal data (n = 670; longitudinal set). In the model-building set, we fitted five SEM models based on serum creatinine or creatinine-based eGFR (eGFRcre), cystatin C or cystatin-based eGFR (eGFRcys), uric acid (UA), and blood urea nitrogen (BUN). In the longitudinal set, 10-year incident CVD risk was defined as a Framingham risk score (FRS)>5% and a pooled cohort equation (PCE)>5%. Predictive performances of the different kidney function indexes were compared using the C-statistic and the DeLong test. In the longitudinal set, a SEM-based estimate of latent kidney function based on eGFRcre, eGFRcys, UA, and BUN showed better prediction performance for both FRS>5% (C-statistic: 0.70; 95% CI: 0.65–0.74) and PCE>5% (C-statistic: 0.75; 95%CI: 0.71–0.79) than other SEM models and different eGFR formulas (DeLong test p-values<3.21×10−6 for FRS>5% and <1.49×10−9 for PCE>5%, respectively). However, the new derived marker could not outperform eGFRcys (DeLong test p-values = 0.88 for FRS>5% and 0.20 for PCE>5%, respectively). SEM is a promising approach to identify latent kidney function signatures. However, for incident CVD risk prediction, eGFRcys could still be preferrable given its simpler derivation.

Background: Previous studies have proposed different formulas of estimating glomerular filtration rate (eGFR) among clinical patients. The comprehensive comparison of eGFR formulas is not well established in a Japanese population. We compared eGFR values and chronic kidney disease (CKD) classification of nine different eGFR in a Japanese general population sample.Methods: We analyzed 469 Japanese community-dwelling adults (184 men) without any self-reported kidney disease. GFR estimated using the 4- and 6-parameter Modification of Diet in Renal Disease (MDRD) formulas (MDRD4 and MDRD6); the CKD-EPI formulas based on creatinine with (CKD-EPI-2009) and without race coefficient (CKD-EPI-2021), on cystatin C (CKD-EPI-Cys), on both (CKD-EPI-CreCys); the Japanese creatinine-based formula (JPN-Cre), cystatin C-based formula (JPN-Cys), and modified CKD-EPI formula (JPN-CKD-EPI). CKD stages were defined by KDIGO guidelines (eGFR < 60 ml/min/1.73 m2).Results: eGFRJPN-Cre (mean = 71.2; SD = 14.3) were much lower than eGFRCKD-EPI-2021 (mean = 94.2; SD =12.7), while eGFRJPN-Cys (mean = 102.8; SD = 24.2) was comparable to the MDRD and CKD-EPI formulas. The difference between eGFRCKD-EPI-2021 and eGFRJPN-Cre showed a V-shaped distribution across eGFR levels, indicating complex errors between these formulas. We observed very low agreement in CKD classification between eGFRJPN-Cre and the eGFRCKD-EPI-2021 (kappa = 0.13; 95% confidence interval: 0.06, 0.23).Conclusions: JPN-Cre was substantially different from the CKD-EPI formula without race term (CKD-EPI-2021), which means that it is impossible to recalibrate those with a simple coefficient. Although a comparison with measured GFR should be necessary, choice of the estimation method needs caution in clinical decision-making and academic research.

Abstract Background and Aims Chronic kidney disease (CKD) is a public health burden affecting >10% of the population worldwide. Population-based studies are essential to assess CKD prevalence and its determinants. However, questionnaires to survey CKD and other kidney diseases in the general population are scarce. We developed a novel questionnaire to identify several types of kidney disease in the general population and implemented it in a large central-European population study. We integrated questionnaire responses with standard renal biochemical measurements to estimate CKD prevalence in the Val Venosta/Vinschgau district. We aimed to assess the degree of CKD underdiagnosis and to describe the kidney health status of study participants. Method Within the Cooperative Health Research In South Tyrol (CHRIS) study, we conducted a cross-sectional assessment of kidney health on 11684 adults (mean age 45 years; females 53.8%) with interviewer-administered kidney questionnaire and measured fasting serum creatinine and albuminuria. The questionnaire covered retrospectively various kidney diseases, including reduced renal function and renal surgeries (Fig. 1). Questions asked if a doctor had ever diagnosed the specific condition and the age at diagnosis. We defined CKD based on combinations of self-reported diagnosis of reduced kidney function (Q6), CKD-EPI 2021 estimated glomerular filtration rate (eGFR) levels, and microalbuminuria (Table 1). Prevalence was estimated via the Clopper-Pearson method and adjusted to the general target population via relative sampling weights. Using factor analysis we explored the underlying correlation structures within and between questionnaire items and laboratory markers. Results Participants had median eGFR and urinary albumin-to-creatinine ratio (UACR) of 98.4 ml/min/1.73 m2 (IQR: 87.8-108.8) and 5.7 mg/g (IQR: 3.8-10.0), respectively. Overall, 744 reported only one and 179 reported at least two types of kidney diseases (Fig. 1). Glomerulonephritis (n = 359; 3.14%), kidney stones (n = 311; 2.93%) and other kidney diseases (n = 200; 1.91%) were the most frequent types. Males reported kidney stones (M: 3.2%; F: 2.2%; p-value = 0.0013) and renal surgeries (M: 0.9%; F: 0.5%; p-value = 0.0116) more frequently than females. Females reported a higher proportion of glomerulonephritis (M: 0.6%; F: 5.2%; p-value<0.0001). The population-weighted CKD prevalence varied between 0.71% to 9.29% depending on the definition (Table 1), with a KDIGO estimate of 8.79% (95%CI 8.28%-9.31%). Questionnaire items showed low sensitivity and high specificity to identify low eGFR or high UACR levels. Factor analysis revealed two clearly separated latent factors: one representing “reduced renal function”, which included eGFR, UACR, and the question Q6 on reduced kidney function; and one representing “all other kidney diseases”. Conclusion In the Val Venosta/Vinschgau district, CKD prevalence is aligned to Western-European countries. In general population studies, questionnaire-based CKD assessment may severely underestimate CKD prevalence as compared to eGFR- and UACR-based estimates. Our analysis highlights that the large majority of individuals with CKD according to KDIGO guidelines were unaware of the disease. On the other hand, the questionnaire has allowed identifying several specific kidney diseases that usually go undetected in population studies. The limited discriminant ability of questionnaire items and the identifiable correlation structure support the use of the survey questionnaire as an integrative tool to study the kidney health status in general population.

Objectives The continuous monitoring of SARS-CoV-2 infection waves and the emergence of novel pathogens pose a challenge for effective public health surveillance strategies based on diagnostics. Longitudinal population representative studies on incident events and symptoms of SARS-CoV-2 infection are scarce. We aimed at describing the evolution of the COVID-19 pandemic during 2020 and 2021 through regular monitoring of self-reported symptoms in an Alpine community sample. Design To this purpose, we designed a longitudinal population representative study, the Cooperative Health Research in South Tyrol COVID-19 study. Participants and outcome measures A sample of 845 participants was retrospectively investigated for active and past infections with swab and blood tests, by August 2020, allowing adjusted cumulative incidence estimation. Of them, 700 participants without previous infection or vaccination were followed up monthly until July 2021 for first-time infection and symptom self-reporting: COVID-19 anamnesis, social contacts, lifestyle and sociodemographic data were assessed remotely through digital questionnaires. Temporal symptom trajectories and infection rates were modelled through longitudinal clustering and dynamic correlation analysis. Negative binomial regression and random forest analysis assessed the relative importance of symptoms. Results At baseline, the cumulative incidence of SARS-CoV-2 infection was 1.10% (95% CI 0.51%, 2.10%). Symptom trajectories mimicked both self-reported and confirmed cases of incident infections. Cluster analysis identified two groups of high-frequency and low-frequency symptoms. Symptoms like fever and loss of smell fell in the low-frequency cluster. Symptoms most discriminative of test positivity (loss of smell, fatigue and joint-muscle aches) confirmed prior evidence. Conclusions Regular symptom tracking from population representative samples is an effective screening tool auxiliary to laboratory diagnostics for novel pathogens at critical times, as manifested in this study of COVID-19 patterns. Integrated surveillance systems might benefit from more direct involvement of citizens' active symptom tracking.

The oral microbiota plays an important role in the exogenous nitrate reduction pathway and is associated with heart and periodontal disease and cigarette smoking. We describe smoking-related changes in oral microbiota composition and resulting potential metabolic pathway changes that may explain smoking-related changes in disease risk. We analyzed health information and salivary microbiota composition among 1601 Cooperative Health Research in South Tyrol participants collected 2017–2018. Salivary microbiota taxa were assigned from amplicon sequences of the 16S-V4 rRNA and used to describe microbiota composition and predict metabolic pathways. Aerobic taxa relative abundance decreased with daily smoking intensity and increased with years since cessation, as did inferred nitrate reduction. Former smokers tended to be more similar to Never smokers than to Current smokers, especially those who had quit for longer than 5 years. Cigarette smoking has a consistent, generalizable association on oral microbiota composition and predicted metabolic pathways, some of which associate in a dose-dependent fashion. Smokers who quit for longer than 5 years tend to have salivary microbiota profiles comparable to never smokers.

Abstract Background and Aims Chronic kidney disease (CKD) is a severe public health burden, characterized by a gradual loss of kidney function over time. Diet is a modifiable lifestyle-related risk factor for CKD. However, there is uncertainty about which specific dietary patterns (DPs) are more beneficial or detrimental in CKD prevention. We aimed at deriving DPs using an hybrid approach that combines a priori knowledge and data-driven methods to identify dietary factors that may affect kidney function in healthy and diseased subjects. Method We analysed data of 8686 adults participating in the population-based Cooperative Health Research In South Tyrol (CHRIS) study. Kidney function was multiply assessed by the estimated glomerular filtration rate (eGFR), based on serum creatinine, using the 2021 CKD-EPI equation, the urinary albumin-to-creatinine ratio (UACR), and a kidney disease questionnaire. Participants were split between those free of diagnosed kidney disease, hypertension or diabetes (Group1, n = 6133) and those diagnosed with any of the three conditions (Group2, n = 2553). Diet was assessed through the self-administered and validated GA2LEN food frequency questionnaire (FFQ). The individual consumption of each food group was converted into portions per week and adjusted for total energy intake. DPs were estimated using reduced rank regression (RRR), based on four FFQ-derived nutrient mediators (total daily dietary protein; potassium; sodium; and phosphorus intake) selected based on known effects on kidney health. Generalized cross-validation identified an optimal number of 3 DPs. Factor Loading (FL)-based scores, either as continuous or stratified into sex-stratified tertiles (T1-T2-T3), were included in multiple-adjusted linear regression models for eGFR and log(UACR). Results Group1 participants (53.4% females) were younger and presented better kidney health (median, Mdn age 39.7 years; Mdn eGFR 101.8 ml/min/1.73m2, interquartile range, IQR 91.5-112.1; Mdn UACR 5.2 mg/g, IQR 3.5-8.8) than Group2 participants (Mdn age 57.2 years; Mdn eGFR 90.8 ml/min/1.73 m2, IQR 80.4-100.3; Mdn UACR 6.5 mg/g, IQR 4.1-12). The identified DPs were (Figure 1): DP1, reflecting greater consumption of all nutrients; DP2, reflecting increased potassium and phosphorus intake and lower sodium and protein intake; and DP3, reflecting increased intake of protein and phosphorus and lower intake of potassium and sodium. The 3 DPs presented stable FLs across groups. In Group1, DP1 was negatively associated with eGFR (larger effect size in males) both as linear score and in the 3rd tertile (Figure 2); DP2 was positively associated with eGFR in males and with UACR both at low and high levels of the score, with heterogeneous effects between males and females; DP3 was positively associated with UACR overall in the 3rd tertile. In Group 2, we observed protective effects of diet on eGFR, especially at lower DP1 and DP3 levels, and at high levels of DP2 (Figure 2). Similar to Group1, also in Group2 DP2 was positively associated with UACR both at low and high level of the score, but not in males. In its 3rd tertile, DP3 was negatively associated with UACR in females. Conclusion Using RRR proved to be a valid approach to integrate a priori knowledge about nutrients in the estimation of kidney function-oriented DPs. Our results showed heterogeneous effects of the DPs across kidney outcomes, possibly reflecting specificity to kidney function or damage. In individuals affected by any kidney disease, hypertension or diabetes, the effects of DPs on eGFR reflected possible benefits of specific diets, suggesting that disease-specific dietary interventions can be a fundamental and effective approach for disease control.

To characterize COVID-19 epidemiology, numerous population-based studies have been undertaken to model the risk of SARS-CoV-2 infection. Less is known about what may drive the probability to undergo testing. Understanding how much testing is driven by contextual or individual conditions is important to delineate the role of individual behavior and to shape public health interventions and resource allocation. In the Val Venosta/Vinschgau district (South Tyrol, Italy), we conducted a population-representative longitudinal study on 697 individuals susceptible to first infection who completed 4,512 repeated online questionnaires at four-week intervals between September 2020 and May 2021. Mixed-effects logistic regression models were fitted to investigate associations of self-reported SARS-CoV-2 testing with individual characteristics (social, demographic, and biological) and contextual determinants. Testing was associated with month of reporting, reflecting the timing of both the pandemic intensity and public health interventions, COVID-19-related symptoms (odds ratio, OR:8.26; 95% confidence interval, CI:6.04-11.31), contacts with infected individuals within home (OR:7.47, 95%CI:3.81-14.62) or outside home (OR:9.87, 95%CI:5.78-16.85), and being retired (OR:0.50, 95%CI:0.34-0.73). Symptoms and next within- and outside-home contacts were the leading determinants of swab testing predisposition in the most acute phase of the pandemics. Testing was not associated with age, sex, education, comorbidities, or lifestyle factors. In the study area, contextual determinants reflecting the course of the pandemic were predominant compared to individual sociodemographic characteristics in explaining the SARS-CoV-2 probability of testing. Decision makers should evaluate whether the intended target groups were correctly prioritized by the testing campaign.