This study examines the link between early-onset diabetes and health factors in South Korean young adults (20-39) using data from the Korea National Health and Nutrition Examination Survey (2010-2020).

A matched case-control study was conducted in 2022 with 103 patients with diabetes and 103 controls, matched by age, gender, and BMI. All data, including socioeconomic status (income, education, occupation), health behaviors (smoking, alcohol consumption, physical activity), and medical histories, were extracted from the KNHANES database. We analyzed socioeconomic status, health behaviors, and medical histories using descriptive statistics, chi-square tests, and binary logistic regression.

The study revealed that educational attainment and economic status are substantial predictors of diabetes, with those holding only a high school diploma showing a nearly threefold increased risk compared to college graduates (OR = 2.986; 95% CI = 1.334-6.687). Additionally, participants with a higher number of chronic diseases (OR = 3.534; 95% CI: 1.547-8.073) and those who felt unwell in the past two weeks (OR = 4.010; 95% CI: 1.388-11.585) also demonstrated significantly increased odds of diabetes. And having a parent with diabetes was an exceptionally strong predictor, with these participants having a significantly increased risk of diabetes (OR = 47.022; 95% CI = 4.206-525.704).

The study emphasizes that improving educational and economic conditions, coupled with targeted screening programs for individuals with a family history of diabetes, may be effective in curbing the tide of early-onset diabetes in South Korea. These strategies may have profound implications for public health policies aimed at mitigating the risk in this increasingly vulnerable group.

Diabetes mellitus (DM) is a growing public health concern globally, particularly in Saudi Arabia, where increasing prevalence is associated with significant morbidity. This study aimed to assess the prevalence of diabetes-related complications among patients in Riyadh and examine the impact of sociodemographic factors, comorbidities, and lifestyle habits on these complications. A cross-sectional study was conducted with 980 diabetic patients attending health centers in Riyadh from March to April 2023. Data were collected via a validated bilingual questionnaire that captured sociodemographic information, diabetes-related variables, comorbid conditions, lifestyle habits, and complications. Statistical analyses, including descriptive statistics, chi-square tests, and binary regression, were performed via SPSS to identify significant associations. A p-value less than 0.05 was considered significant for all comparisons. Among the participants (980), 38% (378) reported diabetes-related complications, primarily neuropathy (30%), retinopathy (25%), and cardiovascular diseases (20%). Complications were significantly associated with older age (p < 0.001) and longer diabetes duration (more than 5 years; p < 0.001). Individuals with hypertension, hyperlipidemia, heart disease, kidney disease, and obesity had significantly higher complication rates than those without these conditions (p < 0.05). The most pronounced association was observed in participants with heart disease (85% vs. 15%; RR = 1.506), highlighting the need for better management of these comorbidities. Consuming fruits and vegetables, milk, and regular exercise were inversely associated with the risk of complications (p < 0.05). Conversely, sugary drinks, white bread, sheesha/vaping, and inadequate sleep were linked to increased risk (p < 0.05), highlighting the protective role of healthy dietary and lifestyle habits. This study highlights the impact of sociodemographic factors and lifestyle choices-such as age, education, family history, comorbidities, and poor diet-on diabetes complications. While early detection and lifestyle interventions are vital, a cautious approach is needed when applying these findings to other regions, given differences in socioeconomic circumstances.

The aim of this study was to determine prevalence of smokers and ex-smokers in the older diabetes population in Europe and to evaluate the relationship with various sociodemographic and lifestyle risk factors. This epidemiological study used Wave 8 of the multidisciplinary and cross-national SHARE database, which includes cross-sectional data on health, socio-economic status and social and family networks of individuals aged 50 and over from 27 European countries. Among the 6,903 participants with diabetes, 12.2% were current smokers, 29.9% were former smokers and 57.9% had never smoked. Among countries' diabetes populations, the highest prevalence of ex-smokers (57.6%) with a low prevalence of smokers (9.5%) was seen in the Netherlands. The highest prevalence of never-smokers (84.2%) was found in Latvia, with the lowest prevalence of ex-smokers (7.9%). Austria had the highest prevalence of current smokers (17.9%) along with a below-average prevalence of ex-smokers (26.5%) was seen in Austria. Normal weight, being overweight, lower education, living without a partner, living in larger cities, drinking alcohol in the last 7 days, lower age, and being male were associated with a higher risk of being a current smoker. The study shows high prevalence of smoking among the older diabetes population in Europe and provides data on the association of smoking with several risk factors and country-specific differences in smoking prevalence.

Early age at menarche (AAM) is a risk factor for type 2 diabetes later in life, but the pathogenic pathways that confer increased risk remain unknown.

We examined the associations between AAM and inflammatory and glucose metabolism biomarkers among US adult women who were free of diabetes.

Using the National Health and Nutrition Examination Survey (NHANES) 1999-2018, 19 228 women over 20 years old who were free of self-reported cancer and diabetes were included in this cross-sectional analysis. AAM was the self-reported age at first menstruation. C-reactive protein (CRP), fasting glucose, fasting insulin, and ferritin levels were measured as biomarkers of inflammation and glucose metabolism in adult blood samples using latex-enhanced nephelometry, enzymatic, and immunoassay methods. Multiple linear regression was used to relate AAM to the biomarkers.

The median age at the time of blood sample collection was 44 years (interquartile range, 33-62). After age adjustment, there was an association between a lower AAM and higher CRP (P-trend = .006), fasting glucose (P-trend < .0001), fasting insulin (P-trend < .0001), and ferritin (P-trend < .0001). These remained significant after additional adjustment for demographic, reproductive, lifestyle, and adiposity variables, except for ferritin. Smoking modified the effect of AAM on CRP (P-interaction = .014), fasting insulin (P-interaction < .001), and fasting glucose (P-interaction < .001). In stratified analysis, the observed associations became more pronounced in nonsmokers, while they were attenuated to nonsignificance in active smokers.

Earlier age at menarche is associated with an unfavorable inflammatory and glucose metabolic biomarker profile in a nationally representative sample of adult women free of diabetes, especially among nonsmokers.

Objectives: Obesity is a significant public health concern, as it is associated with the development of numerous chronic diseases. The prevalence of obesity and attendant diseases has been increasing over recent years. This study attempted to ascertain the frequency of chronic diseases in obese patients in Türkiye for the first time on this scale. Methods: A retrospective study was conducted, with patients admitted to the internal medicine outpatient clinics or obesity centers between December 2023 and December 2024 included in this study. Participants were recruited from seven regions, 20 provinces, and 28 centers, and the inclusion criteria were met by those aged 18 years and over with a body mass index (BMI) of 30 kg per square meter (kg/m2) or above. Their status, with respect to chronic diseases, and their anthropometric parameters were documented. Results: The total number of patients was 10,121, with a mean age of 45.2 ± 13.92. Of these, 7222 (71.35%) were female. The prevalence of type 2 diabetes mellitus (T2DM), hypertension (HT), dyslipidemia (DL), coronary artery disease (CAD), obstructive pulmonary disease (OPD), obstructive sleep apnea syndrome (OSAS), and fatty liver disease (FLD) was found to be 35.01%, 78.19%, 12.37%, 10.32%, 5.88%, and 75.12%, respectively. A subsequent analysis of the prevalence of these diseases by region revealed a statistically significant variation between regions (p < 0.001 for all regions). Conclusions: This study represents a substantial contribution to the existing body of knowledge in this field, particularly with regard to the identification of the current chronic disease rate of obese patients in Türkiye.

Smoking is a risk factor for cardiovascular complications and can promote a severe course of COVID-19 infection. The aim of this study was to compare smoking habits of young people with diabetes with the general population.

We analyzed smoking behavior in the Diabetes Prospective Follow-up Registry (DPV) cohort (type 1 (T1D) and type 2 diabetes (T2D) from Germany and T1D from Austria aged 14-24 years) and compared it to data from the German survey on smoking behavior (DEBRA study) of the general population. Data were aggregated per year and patient for 2016-2023. Logistic regression models adjusted for gender and migration background were calculated stratified by age groups (14-17; 18-24 years), taking repeated measurements into account. Smoking behavior between T1D and T2D or between Germany and Austria was compared with similar regression models.

Thirty-four thousand two hundred seventy-five patients from the DPV cohort were included in data analysis. The overall proportion of people who smoked was lower in DPV than in the general population (13.4% vs. 24.0%), with the exception of young adults with T2D at the beginning of the pandemic (36.7% vs. 33.4%). For T1D, there was a significant upward trend in the number of patients who smoked in the group of 14-17 years (2.86%, CI 1.21-4.55 per year, p < 0.001) and also in the group of 18-24 years (4.94 per year, CI 1.37-8.63; p < 0.01) between 2016 and 2023. The proportion of smokers and the number of smoked cigarettes was higher in Austria than in Germany (10.7% vs. 8.0%; OR with 95%-CI 1.38 [1.22-1.56], p < 0.001; and 7.5 [6.8-8.1] vs. 5.9 [5.7-6.0] cigarettes/day, p < 0.001) and in T2D than T1D (11.0% vs. 7.9%; OR 1.44 [1.23-1.68], p < 0.001 and 8.0 [7.2-8.8] vs. 5.9 [5.7-6.1] cigarettes/day, p < 0.001).

The reported proportion of smokers among young people with diabetes was lower than in the general population. Only young adults with T2D temporarily smoked more than the general population at the beginning of the pandemic. This could be explained by stress, but also by a changed daily structure during the lockdown.

The etiology of type 2 diabetes mellitus (T2DM) is complex, with environmental factors playing a significant role in its pathophysiology. Nonsteroidal anti-inflammatory drugs usage and Helicobacter pylori infection are the two most frequent causes of peptic ulcer disease (PUD). The link between PUD and T2DM is unclear, and comprehensive analyses of anti-PUD medications' impact on T2DM risk, especially in Asian populations, are lacking. This study aimed to determine the relationship between PUD, anti-PUD medications, and the likelihood of developing T2DM.

Using a population-based cohort study conducted in Taiwan, we investigated the impact of PUD and anti-PUD medications on the risk of T2DM.

This is a retrospective, population-based cohort study using the largest database used in Taiwan.

An 18-year follow-up period study was conducted on a cohort of patients with PUD diagnosed between 2001 and 2018 using the Taiwan National Health Insurance Research Database. The risk of PUD as well as anti-PUD medications use were examined using Cox proportional regression model.

Based on multivariable Cox proportional hazards regression analysis, patients with PUD had a higher overall T2DM incidence (22.7 vs 21.3 per 1000 person-years) than patients without PUD. The adjusted hazard ratio was 1.12 (95% confidence interval = 1.10, 1.13). Patients with PUD have a higher risk of T2DM in both genders and age groups. Patients with anti-PUD medications, such as H2 receptor antagonists, proton-pump inhibitors, antibiotics, prostaglandin analogs, anticholinergics, and antacids usage, are associated with a lower risk of developing T2DM than those without. Patients with PUD who underwent surgery were found to have a higher risk of T2DM.

Patients with PUD are more likely to develop T2DM. Nevertheless, patients receiving anti-PUD medications have a lower incidence of T2DM.

This study examines the risk factors associated with non-communicable diseases (NCDs), specifically diabetes mellitus (DM) and hypertension (HTN), among adults in Bangladesh, a lower-middle-income country. Given the rising prevalence of DM and HTN and their significant public health burden, this research aims to identify key socioeconomic, demographic and lifestyle-related determinants to inform targeted interventions.

The study used nationally representative cross-sectional data extracted from the Bangladesh Demographic and Health Survey conducted in 2017-2018.

Bangladesh.

The study included 8013 women and 6691 men aged 18 and older who were eligible for blood pressure and blood glucose measurements.

Type 2 DM, HTN.

HTN was significantly associated with higher odds of diabetes (adjusted OR (AOR)=1.28, 95% CI: 1.14 to 1.43), while diabetes was associated with increased odds of HTN (AOR=1.24, 95% CI: 1.11 to 1.39). Individuals aged 40 years and older had 74.8% higher odds of diabetes (AOR=1.748, 95% CI: 1.58 to 1.993) and were 3.21 times more likely to have HTN (AOR=4.208, 95% CI: 3.781 to 4.685). Overweight individuals had 2.15 times higher odds of HTN compared with those with normal weight (AOR=2.154, 95% CI: 1.98 to 2.34). Wealthier individuals also showed significantly higher odds of both DM and HTN.

This study highlights the strong association between DM and HTN and identifies age, overweight status and higher socioeconomic class as key risk factors. These findings underscore the need for integrated public health strategies targeting NCD prevention and management in Bangladesh. Further research should explore longitudinal trends and the impact of targeted interventions on reducing the burden of NCDs.

Chronic Obstructive Pulmonary Disease (COPD) usually presents joined to other pathologies we call comorbidities. The more frequent of them are those related to cardiovascular risk, either its risk factors or its clinical manifestations. Cardiovascular risk of these patients grows up with the severity of the airflow obstruction, specially during and after an exacerbation of COPD. Patients with COPD have between 2 and 5 times more risk of ischaemic heart disease than people without COPD, even after adjusting for cofounding factors. Cardiovascular diseases are up to the second cause of mortality in these patients, close to those due to the lung disease. Although COPD is associated to several cardiovascular risk factors such as tobacco, arterial hypertension or Diabetes Mellitus, they don't explain all the excess in cardiovascular risk these patients have. Despite that excess of cardiovascular risk in COPD patients, most widely used cardiovascular risk scores don't include COPD as a risk factor itself, so global risk is understimated in these patients. In this review, we make a bibliography revision of the avaliable evidence about COPD and cardiovascular risk factors as well as the excess of cardiovascular risk COPD itself involves.

The prevalence of type-2 diabetes mellitus (T2DM) has increased over 10-fold in the past 40 years in China, which now has the largest T2DM population in the world. Insulin resistance and β-cell dysfunction are the typical features of T2DM. Although both factors play a role, decreased β-cell function and β-cell mass are the predominant factors for progression to T2DM. Considering the differences between Chinese T2DM patients and those of other ethnicities, it is important to characterize β-cell dysfunction in Chinese patients during T2DM progression. Herein, we reviewed the studies on the relationships between β-cell function and T2DM progression in the Chinese population and discussed the differences among individuals of varying ethnicities. Meanwhile, we summarized the risk factors and current treatments of T2DM in Chinese individuals and discussed their impacts on β-cell function with the hope of identifying a better T2DM therapy.

This study aimed to identify the distinct change trajectories of the Chinese visceral adiposity index (CVAI) over time and to investigate their associations with risk of type 2 diabetes mellitus (T2DM).

This study included 52 394 participants from the prospective project, the Prediction for Atherosclerotic Cardiovascular Disease Risk in China (China-PAR). The CVAI was calculated using measures of age, body mass index, waist circumference, triglycerides and high-density lipoprotein cholesterol. Latent mixture modelling was conducted to fit distinct trajectory patterns. The logistic regression model was applied to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for the risk of T2DM with various CVAI trajectory patterns.

Four distinct CVAI trajectory patterns were identified: low-increasing, moderate-increasing, moderate high-increasing and high-increasing. Compared with low-increasing CVAI, participants with moderate-increasing (OR 1.73, 95% CI 1.49-2.00), moderate high-increasing (3.48, 3.01-4.03) and high-increasing CVAI (5.50, 4.67-6.47) had a significantly increased risk of T2DM. Similar trajectory patterns were identified in both men and women. The ORs (95% CI) for moderate-increasing, moderate high-increasing and high-increasing groups were 3.28 (2.56-4.19), 7.85 (6.09-10.13) and 13.21 (9.98-17.49) in women respectively, and 1.20 (0.99-1.45), 2.18 (1.82-2.62) and 3.60 (2.93-4.43) in men respectively, when compared to the low-increasing CVAI group. Further, significant effect modifications for age, smoking and physical activity (all Pinteraction <0.05) were observed in the relationship between CVAI trajectory patterns and T2DM.

Initially high and persistently elevated CVAI is significantly associated with an increased risk of T2DM, with a particular focus on women, younger people, nonsmokers and physically inactive individuals. Continuous monitoring of CVAI levels will benefit effective identification, early intervention and management of individuals at high risk of T2DM.

Cholelithiasis are a condition that creates an economic and medical burden on society, and women are more susceptible to gallbladder stones. However, the effect of smoking on the development of gallstones remains controversial. No studies, to our knowledge, have discussed the association between smoke exposure and gallstones separately in men and women. We evaluated the association between smoking and gallstones in both sexes.

We conducted a cross-sectional analysis using data obtained from the National Health and Nutrition Examination Survey from 2017 to March 2020. The analysis was limited to individuals aged ≥ 20 years with complete information available. Self-reported smoking status, serum cotinine concentration, and self-reported gallstones conditions were combined to analyze the association of gallstones with smoking and cotinine concentration.

Of the 6,982 participants, a total of 6.2% (212) men and 14.5% (512) women reported having gallstones. Logistic regression analysis showed smoking and high serum cotinine level were risk factors associated with gallstones among women, both in the model 1 (current smoker: odds ratio [OR] = 1.563, 95% confidence interval [CI] = 1.044-2.339, p = 0.032; former smoker: OR = 1.434, 95% CI = 1.116-1.842, p = 0.007; cotinine ≥ 3 ng/mL: OR = 1.800, 95% CI = 1.247-2.596, p = 0.005; and cotinine 0.05-2.99 ng/mL: OR = 1.640, 95% CI = 1.188-2.263, p = 0.005) and model 2 (current smoker: OR = 1.588, 95% CI = 1.015-2.483, p = 0.044; cotinine ≥ 3 ng/mL: OR = 1.825; 95% CI = 1.181-2.821, p = 0.011; and cotinine 0.05-2.99 ng/mL: OR = 1.509, 95% CI = 1.075-2.126, p = 0.022). However, the association was statistically insignificant in men. The subgroup analysis showed the robustness of the association.

This study indicates smoking and elevated serum cotinine levels may be risk factors associated with the development of gallstones. Notably, the associations were specifically observed among women. The findings suggest the significance of smoking in the incidence of gallstones, which may potentially provide insights for future research on strategies to prevent gallstones, particularly among women. The validation of these findings necessitates the conduction of large-scale, high-quality prospective studies.

Prediabetes increases the risk of type 2 diabetes, metabolic syndrome, chronic renal disease, and cardiovascular disease in a person. In current practice, five alternative definitions of prediabetes are utilized, each based on different HbA1c, fasting glucose, and 2-hour glucose cut points. Prediabetes is a common condition that occurs between normal glycemia and diabetes. It is more common in elderly and obese people. The prevalence of prediabetes and diabetes can be influenced by a variety of individual, family, and societal variables. Additionally, as diabetes is the primary contributor to non-communicable diseases (NCD), it is crucial to identify the key temporal variables for diabetes early diagnosis. In turn, effective prediabetes and diabetes awareness, control, and preventive programs may be created by policymakers and public health professionals worldwide. Popular pathogenic pathways in prediabetes include insulin resistance, inflammation, and sensitivity to insulin. HBA1c, OGTT, and FPG are discussed as the diagnostic criteria in order of frequency. The most commonly researched therapies in the realm of prediabetes are metformin, exercise, and physical activity. Physiological markers including BMI, blood pressure, and waist circumference prompted relatively significant concern. Despite declining trends, the study demonstrates that prediabetes and diabetes are widely prevalent. In order to prevent non-communicable illnesses, the research suggests encouraging healthy lifestyles and regular screenings.

To provide insight on targeted approach to mitigate diabetes burden, this research aims to analyze the trends of prevalence, mortality, and disability attributable to risk factors for type 2 diabetes mellitus (T2DM) from 1990 to 2019 in the Southeast Asia (SEA) region.

Age-standardized rates for prevalence (ASPR), mortality (ASMR), and disability-adjusted life years (DALYs) from 1990 to 2019 from the Global Burden of Disease Study were assessed. DALYs-related risk factors were estimated using multivariate regression analysis and estimated annual percentage change (EAPC) was calculated to quantify the temporal trends. Over 30 years, the SEA region experienced a 59.5 % rise in T2DM ASPR, 17.33 % in ASMR, and 26.97 % in DALYs. The T2DM DALYs rate per 100,000 population was 1002.91 (885.23-1132.40) in 1990 and 1273.42 (1103.92-1452.41) in 2019, increasing by 27 %. Cambodia and Indonesia had the highest worsening in three parameters, while most significant improvement in all parameters was observed in Singapore. The curvilinear association was demonstrated between ASMR and DALYs to Gross Domestic Product (GDP) per capita. Prominent risk factors affecting DALYs increase were high fasting plasma glucose (FPG) (p < 0.001), high body mass index (BMI) (p < 0.001), tobacco use (p = 0.012), and household pollution (p = 0.03). Men were more affected than women.

The burden of T2DM in the SEA region has increased significantly during the 30-year period. Policymakers should address high BMI, high FPG, smoking, and air pollution to regulate T2DM burden in SEA.

Smoking is widely regarded as a risk factor for type 2 diabetes because nicotine contributes to insulin resistance by desensitizing the insulin receptors in muscle, liver, or fat. Little is known, however, about the immediate regulation of islet hormonal output by nicotine, an agonist of ionotropic cholinergic receptors. We investigated this by imaging cytosolic Ca2+ dynamics in mouse and human islets using confocal microscopy and measuring glucagon secretion in response to the alkaloid from isolated mouse islets. Nicotine acutely stimulated cytosolic Ca2+ in glucagon-secreting α-cells but not in insulin-secreting β-cells. The 2.8- ± 0.5-fold (P < 0.05) increase in Ca2+, observed in >70% of α-cells, correlated well with a 2.5- ± 0.3-fold stimulation of glucagon secretion. Nicotine-induced elevation of cytosolic Ca2+ relied on influx from the extracellular compartment rather than release of the cation from intracellular depots. Metabotropic cholinergic signaling, monitored at the level of intracellular diacylglycerol, was limited to 69% of α-cells versus 94% of β-cells. We conclude that parasympathetic regulation of pancreatic islet hormone release uses different signaling pathways in β-cells (metabotropic) and α-cells (metabotropic and ionotropic), resulting in the fine-tuning of acetylcholine-induced glucagon exocytosis. Sustained nicotinic stimulation is, therefore, likely to attenuate insulin sensitivity by increasing glucagon release.

Noncommunicable chronic diseases (NCDs) are a rapidly growing global public health concern, posing substantial challenges to healthcare systems. The presence of multiple (≥2) chronic conditions (MCC) exacerbates these challenges. In this study, we constructed an integrated MCC network to comprehensively evaluate the impact of NCD prevalence and associated factors on MCC patterns. We identified four distinct MCC patterns, each with its unique set of associated risk factors. Firstly, we found that race, sedentary lifestyles, and smoking habits were significant contributors to the co-occurrence of diabetes, chronic kidney disease, and cancer. Secondly, smoking habits and mental health were identified as risk factors associated with the clusters of high cholesterol, hypertension, coronary heart disease, and arthritis. Furthermore, the comorbidity of chronic obstructive pulmonary disease and asthma was affected by socioeconomic status, smoking habits, and educational attainment, and a noteworthy reciprocal relationship existed between these two MCC combinations. Thirdly, the combination of asthma and obesity is associated with risk factors such as mental health, smoking habits, sedentary lifestyles, and binge drinking behaviors. Finally, the pattern of depression-stroke comorbidity was influenced by risk factors including mental health, age, and sleep duration. Our findings hold valuable implications for healthcare system optimization, offering a pathway to mitigate the escalating burden of NCDs. Additionally, they provide a foundation for scientific strategies aimed at the joint prevention and management of these complex conditions, ultimately enhancing public health and safety on a global scale.

Background: The study investigates the association between lipid accumulation product (LAP) and the risk of prediabetes and diabetes. LAP, a measure indicating lipid overaccumulation, is hypothesized to be a significant predictor for these conditions. This research utilizes data from the National Health and Nutrition Examination Survey (NHANES) conducted between 1999 and 2018. Methods: The study followed a structured methodology, starting with data extraction from the NHANES database. Participants' eligibility was determined based on specific inclusion and exclusion criteria, resulting in a final sample size of 24,121 individuals. LAP was calculated using established formulas for men and women. The diagnosis of prediabetes and diabetes was based on standard medical criteria, including HbA1c levels, fasting plasma glucose, and oral glucose tolerance test (OGTT) results. Covariates like demographic variables, lifestyle factors, and other health indicators were also considered. Statistical analysis involved categorizing LAP into quartiles and employing logistic regression models to examine the relationship between LAP and the risk of prediabetes and diabetes. Results: Participants in the highest LAP quartile exhibited distinct characteristics: older age, lower education levels, more former smokers and drinkers, higher blood pressure and cholesterol levels, and greater use of medications. A positive association was observed between LAP and the incidence of prediabetes and diabetes across all models. Specifically, each 10-unit increase in LAP was linked to a 22% increase in risk. Nonlinear relationships were also explored, revealing an inflection point in the risk correlation at an LAP value of 68.1. Conclusion: The study concludes that LAP is a significant predictor of prediabetes and diabetes risk, with higher LAP levels correlating with increased risk. This finding underscores the potential of LAP as a useful marker in identifying individuals at higher risk for these conditions. It also highlights the importance of considering LAP in preventive health strategies.

Diabetes and its complications pose a significant threat to global health. Various factors contribute to the development of diabetes, with diet being an important trigger. The Dietary Quality Index-International (DQI-I) serves as an indicator of changes in diet and its association with chronic diseases, including diabetes. The aim of this study is to examine the association between DQI-I and diabetes in adults. Data from the first phase of the Ravansar Non-Communicable Disease Cohort Study (RaNCD) were used for this cross-sectional study. The study included individuals from western Iran aged between 35 and 65 years. The DQI-I was used to assess diet quality and the essential aspects of a healthy diet. Multiple logistic regression analyses were performed to compare DQI-I total score and diabetes. A total of 7,079 individuals were included, including 608 diabetic and 6,471 healthy individuals. The mean DQI-I score was 60.51 ± 8.47 in healthy individuals and 63.12 ± 8.64 in diabetics. The odds of developing diabetes were higher in individuals with a higher DQI-I (adjusted odds ratio: 1.49, 95% CI: 1.30-1.73). The variety was 13.43 ± 4.47 in diabetics and 12.59 ± 4.79 in healthy individuals. Adequacy was 33.23 ± 3.71 in diabetics and 33.79 ± 3.37 in healthy individuals. Moderation was 13.27 ± 6.05 in diabetics and 11.79 ± 5.47 in healthy individuals. The overall balance was 2.88 ± 2.21 in the healthy group and 2.61 ± 2.13 in the diabetics. The macronutrient ratio was 2.15 ± 1.88 in the healthy group and 2.04 ± 1.84 in the diabetics. The fatty acid ratio was 0.72 ± 1.29 in the healthy group and 0.56 ± 1.17 in the diabetic group. The overall balance score was higher in the healthy subjects. The DQI-I total score was higher in diabetics, indicating a positive association between diabetes and the DQI-I. Therefore, the importance of continuous dietary management and education of diabetic patients should be emphasized.

The cardiometabolic index (CMI) is a novel metric for assessing cardiometabolic health and type 2 diabetes mellitus (DM), yet its relationship with insulin resistance (IR) and prediabetes (preDM) is not well-studied. There is also a gap in understanding the nonlinear associations between CMI and these conditions. Our study aimed to elucidate these associations.

We included 13,142 adults from the National Health and Nutrition Examination Survey (NHANES) 2007-2020. CMI was calculated by multiplying the triglyceride-to-high density lipoprotein cholesterol (TG/HDL-C) by waist-to-height ratio (WHtR). Using weighted multivariable linear and logistic regression explored the relationships of CMI with glucose metabolism markers, IR, preDM, and DM. Nonlinear associations were assessed using generalized additive models (GAM), smooth curve fittings, and two-piecewise logistic regression.

Multivariate regression revealed positive correlations between CMI and glucose metabolic biomarkers, including FBG (β = 0.08, 95% CI: 0.06-0.10), HbA1c (β = 0.26, 95% CI: 0.22-0.31), FSI (β = 4.88, 95% CI: 4.23-5.54), and HOMA-IR (β = 1.85, 95% CI: 1.56-2.14). There were also significant correlations between CMI and increased risk of IR (OR = 3.51, 95% CI: 2.94-4.20), preDM (OR = 1.49, 95% CI: 1.29-1.71), and DM (OR = 2.22, 95% CI: 2.00-2.47). Inverse nonlinear L-shaped associations were found between CMI and IR, preDM, and DM, with saturation inflection points at 1.1, 1.45, and 1.6, respectively. Below these thresholds, increments in CMI significantly correlated with heightened risks of IR, preDM, and DM.

CMI exhibited inverse L-shaped nonlinear relationships with IR, preDM, and DM, suggesting that reducing CMI to a certain level might significantly prevent these conditions.

Evidence on the role of smoking in the development of chronic kidney disease (CKD) has mostly relied on self-reported smoking status. We aimed to compare the associations of smoking status as assessed by self-reports and urine cotinine with CKD risk.

Using the PREVEND prospective study, smoking status was assessed at baseline using self-reports and urine cotinine in 4333 participants (mean age, 52 years) without a history of CKD at baseline. Participants were classified as never, former, light current, and heavy current smokers according to self-reports and comparable cutoffs for urine cotinine. Hazard ratios (HRs) with 95% confidence intervals (CIs) were estimated for CKD.

The percentages of self-reported and cotinine-assessed current smokers were 27.5% and 24.0%, respectively. During a median follow-up of 7.0 years, 593 cases of CKD were recorded. In analyses adjusted for established risk factors, the HRs (95% CI) of CKD for self-reported former, light current, and heavy current smokers compared with never smokers were 1.17 (0.95-1.44), 1.48 (1.10-2.00), and 1.48 (1.14-1.93), respectively. On further adjustment for urinary albumin excretion (UAE), the HRs (95% CI) were 1.07 (0.87-1.32), 1.26 (0.93-1.70), and 1.20 (0.93-1.57), respectively. For urine cotinine-assessed smoking status, the corresponding HRs (95% CI) were 0.81 (0.52-1.25), 1.17 (0.92-1.49), and 1.32 (1.02-1.71), respectively, in analyses adjusted for established risk factors plus UAE.

Self-reported current smoking is associated with increased CKD risk, but dependent on UAE. The association between urine cotinine-assessed current smoking and increased CKD risk is independent of UAE. Urine cotinine-assessed smoking status may be a more reliable risk indicator for CKD incidence than self-reported smoking status.

Prolonging life is a global trend, and more medical expenditure is being spent on chronic diseases owing to population aging. Diseases commonly seen in middle-aged and elderly people, such as heart disease and diabetes, have slowed mortality improvement in recent years. Diabetes is a common chronic disease and comorbidity of many serious health conditions. The total estimated cost of diabetes in the United States was $327 billion in 2017. However, many people are unaware that diabetes is common, and at least 21.4% of adults do not know that they have diabetes. The number of diabetes-related deaths has been increasing, and diabetes was the 5th cause of death in Taiwan in 2019. In this study, we explore the trend and influence of diabetes in Taiwan and apply mortality models, such as the Lee-Carter and Age-Period-Cohort models, using data from Taiwan's National Insurance to model the incidence and mortality rates of diabetes. We found that the Lee-Carter model provides fairly satisfactory estimates and that people with diabetes regularly taking diabetes medication have lower mortality rates. Moreover, we demonstrate how these results can be used to design diabetes related insurance products and prepare the insured to face the impact of incurring diabetes. In addition, we consider different criteria for judging whether people have diabetes (as there is no consensus on these criteria) and investigate the issue of moral hazard in designing diabetes insurance products.

Smoking significantly impacts oral health, causing periodontal disease, oral cancer, tooth discoloration, halitosis, and impaired wound healing. Nicotine replacement therapy (NRT), particularly nicotine patches, is widely used for smoking cessation. This review evaluates the literature regarding nicotine patches and their implications for oral and gum health. Nicotine patches deliver controlled nicotine doses transdermally, alleviating cravings and withdrawal symptoms. While nicotine can negatively affect oral health through vasoconstriction and reduced salivary flow, the overall impact of patches is generally positive compared to continued smoking. The primary benefit is the elimination of exposure to harmful chemicals and heat from cigarette smoke, significantly decreasing oral cancer risk and periodontal disease progression. Nicotine patches are associated with improved periodontal treatment outcomes, better wound healing, and potential anti-inflammatory effects. They may also promote improved oral hygiene practices. However, limitations include uncertain long-term effects and potential side effects like xerostomia. In conclusion, while nicotine patches may have some oral health effects, their use generally leads to significant improvements compared to continued smoking, making them valuable for promoting better oral health in individuals quitting smoking.

We evaluated the association between smoking and diabetes, as well as the effects of gender differences and hidden smoking among females on this association using nationally representative data. Analyzing data from 44,049 individuals aged 19 and older, we utilized multivariable logistic regression to investigate associations, controlling for sociodemographic factors. Subgroup analysis based on smoking status determined factors associated with diabetes. To better our understanding of the smoking-diabetes relationship, we introduced a new variable, survey-cotinine verified smoking status (SCS). This study provides valuable insight by exploring the correlation between smoking and diabetes using different definitions of smoking status. Both male and female smokers showed correlations with diabetes according to cotinine-verified smoking status (OR: 1.22 and 1.48, respectively). According to smoking amount, cotinine-verified heavy smokers correlated with diabetes in males (OR: 1.37), while light smokers exhibited a negative correlation with diabetes in females for both cotinine-verified smoking status (OR: 0.60) and survey-cotinine verified status (OR: 0.58) Smoking was associated with diabetes in the overall population, with gender differences observed. When evaluating this association, we should consider variables of smoking amount, passive and intermittent smoking, and specifically, account for the influence of hidden smoking among females, particularly when utilizing self-reported questionnaires in Korea.

This study aims to develop and externally validate a clinically plausible Bayesian network structure to predict one-year erectile dysfunction in prostate cancer patients by combining expert knowledge with evidence from data using clinical and Patient-reported outcome measures (PROMs) data. In addition, compare and contrast structures that stem from PROM information and routine clinical data.

For men with localized prostate cancer, choosing the optimal treatment can be challenging since each option comes with different side effects, such as erectile dysfunction, which negatively impacts their quality of life. Our previous findings demonstrate that logistic regression models are able to identify patients at high risk of erectile dysfunction. However, methods such as Bayesian networks may be more successful, as they intricately represent the causal relations between the variables.

946 prostate cancer patients from 65 Dutch hospitals were considered to develop the Bayesian network structure. Continuous variables were discretized before analysis based on expert opinions and literature. Patients with missing information and variables with more than 25% of missing information were excluded. Prostate cancer treating physicians first determined the relationships (arcs) between the available variables. The structures were then modified based on algorithmically derived structures using the hill-climbing algorithm. Structural Performance was evaluated based on the area under the curve (AUC) values and calibration plots on the training and test data.

BMI and prostate volume via MRI were excluded from this analysis due to their high percentage of missingness (>45 %). The final cohort was reduced to 505 and 216 after excluding 157 and 68 patients with missing information, respectively. The AUC of the PROM structure was better than the clinical structure in both the train and test data. The structure that combined both sources of information had an AUC value of 0.94 (0.92 - 0.96) and 0.84171 (0.77 91) in the train and test data, respectively.

Bayesian network structures derived from PROM information by complimenting expert knowledge with evidence from the data produce a clinically plausible structure that is more performant than structures from clinical data. Our study supports the growing global recognition of incorporating the patient's perspective in outcomes research for better decision-making and optimal outcomes. However, a structure that combines both sources of information gives a more holistic view of the patient with actionable insights and improved discriminative power.

Background: We aimed to explore the still-debated association between smoking and hyperglycaemia in pregnancy (HIP). Methods: A multiethnic prospective study of 15,801 women who delivered at Jean Verdier University Hospital between 2012 and 2018. Of these, 13,943 (88.2%) were non-smokers, 624 (4.5%) former smokers, and 1234 (7.8%) current smokers. Universal HIP screening was proposed to the entire sample (IADPSG/WHO criteria). Results: A total of 13,958 women were screened for HIP. Uptake differed between non-smokers, former smokers, and current smokers (89.5%, 88.3%, and 75.7%, respectively, p < 0.0001). HIP prevalence in these groups was 19.9%, 15.4%, and 12.3%, respectively (p < 0.0001). After adjusting for age, body mass index, family history of diabetes, history of HIP, history of macrosomic baby, and ethnicity, current (odds ratio 0.790 [95% confidence interval 0.636-0.981], p < 0.05) but not former (1.017 [0.792-1.306]) smokers were less likely to have HIP than non-smokers. Furthermore, 1 h and 2 h oral plasma glucose test values were lower in current smokers than in non-smokers (p < 0.01). To exclude potential selection bias, we compared risk factors for HIP and HIP-related adverse pregnancy outcomes in current smokers according to HIP screening status. Compared with screened current smokers (n = 934), their unscreened counterparts (n = 300) were younger, less frequently employed, and more likely to be of non-European origin. Moreover, infant birthweight was lower in this group, and preterm deliveries and perinatal deaths were more likely (all p < 0.01). Conclusions: Smoking during pregnancy was independently associated with lower HIP prevalence. The low HIP screening rate in current smokers did not explain this finding.

Anastomotic leak after esophagectomy is a major contributor to surgery-related morbidity and mortality. The purpose of this systematic review was to evaluate if positive-smoking status is associated with the incidence of this complication.

A systematic search of MEDLINE, EMBASE, Scopus, Web of Science and Cochrane Library was performed on April 4th, 2023. Inclusion criteria comprised human participants undergoing esophagectomy, age ≥ 18, n ≥ 5, and identification of smoking status. The primary outcome was incidence of anastomotic leak. Sub-group analysis by ex- or current smoking status was performed. Meta-analysis was performed with RevMan 5.4.1 using a Mantel-Haenszel random-effects model. Publication bias was evaluated visually with funnel plots and through the Egger test.

A total of 220 abstracts were screened, of which 69 full-text studies were assessed for eligibility, with 13 studies selected for final inclusion. This included 16,103 patients, of which 4433 were ex- or current smokers, and 9141 were never smokers. Meta-analysis revealed an increased odds of anastomotic leak in patients with a positive-smoking status (current or ex-smokers) compared to never smokers (OR 1.44, 95% CI 1.18-1.76, I2 = 44%, p < 0.001. Meta-analysis of six studies comparing active smokers alone to never smokers identified a significant increased odds of anastomotic leak (OR 1.80, 95% CI 1.25-2.59, p = 0.002, I2 = 0%). Meta-analysis of five studies comparing ex-smokers to never smokers identified a significant increased odds of anastomotic leak (OR 1.36, 95% CI 1.02-1.82, p = 0.04, I2 = 0%). The odds of anastomotic leak decreased among ex-smokers compared to active smokers.

The findings of this systematic review and meta-analysis support the association between positive-smoking status and the risk of anastomotic leak after esophagectomy. Results further emphasize the importance of preoperative smoking cessation to reduce post-operative morbidity.

Background/Objectives: Smoking cessation is acknowledged for its health benefits. However, it paradoxically increases diabetes mellitus (DM) risk shortly after quitting due to weight gain. This research aimed to investigate how smoking status could affect the development of DM, focusing on how the risk of acquiring diabetes changed over time after quitting smoking, independent of variables such as weight gain. Methods: The data of 386,558 participants of the Kangbuk Samsung Health Study, excluding those with pre-existing DM, were examined. Smoking status and its long-term effects on DM risk were assessed using multivariate Cox proportional hazards models. Lifestyle factors, including weight change, physical activity levels, and alcohol intake, were adjusted as time-varying covariates throughout the follow-up period. Results: Modified hazard ratios (HRs) indicated no notable disparity in DM risk between individuals who previously smoked and those who had never smoked (HR: 1.04, 95% CI: 0.999-1.08, p-value < 0.001). In contrast, current smokers exhibited a significantly increased DM risk (HR: 1.29, 95% CI: 1.24-1.35, p-value < 0.001). Within the first six years post-cessation, former smokers initially faced a higher DM risk than never smokers (0-2 years, HR: 1.22, 95% CI: 1.15-1.31, p-value < 0.001; 3-5 years, HR: 1.11, 95% CI: 1.04-1.20, p-value < 0.001). After 12 years, they realigned with never smokers (12-46 years, HR: 0.92, 95% CI: 0.86-0.98, p-value = 0.002). Current smokers consistently showed a higher DM risk (0-9 years, HR: 1.29, 95% CI: 1.14-1.46, p-value < 0.001). Adjusting for covariates such as weight change and physical activity did not alter these findings. Conclusions: Our results indicated that former smokers initially experienced an elevated risk of DM relative to never smokers. This increased risk aligned with the risk of never smokers after six years, and the risk continued to improve after 12 years compared to never smokers. This contrasted with current smokers, who maintained a heightened risk of DM, even when adjustments were made for weight change, physical activity, and alcohol intake as time-varying covariates.

To prospectively assess the association of smoking timing with the risk of type 2 diabetes (T2D) and examine whether smoking amount or genetic susceptibility might modify the relationship.

A total of 294 815 participants without diabetes from the UK Biobank, including non-smokers and smokers with data on the time from waking to first cigarette, were included. Cox proportional hazards models were used to evaluate the association between smoking timing and the risk of incident T2D.

During a median follow-up time of 12 years, a total of 9937 incident cases of T2D were documented. Compared with non-smokers, a shorter time from waking to first cigarette was significantly associated with a higher risk of incident T2D (P for trend < .001). In the fully adjusted model, the hazard ratios (HRs) (95% confidence interval) associated with smoking timing were 1.46 (1.17-1.81) for more than 2 hours, 1.51 (1.21-1.87) for 1-2 hours, 1.58 (1.34-1.85) for 30-60 minutes, 1.86 (1.57-2.21) for 5-15 minutes and 2.01 (1.60-2.54) for less than 5 minutes. We found that even among those who reported being light smokers, those with the shortest time from waking to first cigarette had a 105% higher risk of T2D with an HR of 2.05 (1.52-2.76), which was comparable with heavy smokers. The genetic risk score for T2D did not modify this association (P-interaction = .51).

Our findings indicate that shorter time from waking to first cigarette is significantly associated with a higher risk of incident T2D.

Thioredoxin-interacting protein (TXNIP) plays an important role in glucose metabolism, and its expression is regulated by DNA methylation (DNAm). Although the association between TXNIP DNAm and type 2 diabetes mellitus has been demonstrated in studies with a cross-sectional design, prospective studies are needed. We therefore examined the association between TXNIP DNAm levels and longitudinal changes in glycemic traits by conducting a longitudinal study involving 169 subjects who underwent two health checkups in 2015 and 2019. We used a pyrosequencing assay to determine TXNIP DNAm levels in leukocytes (cg19693031). Logistic regression analyses were performed to assess the associations between dichotomized TXNIP DNAm levels and marked increases in glycemic traits. At four years, the TXNIP DNA hypomethylation group had a higher percentage of changes in fasting plasma glucose (FPG) and hemoglobin A1c (HbA1c) compared to those in the hypermethylation group. The adjusted odds ratios for FPG and HbA1c levels were significantly higher in the TXNIP DNA hypomethylation group than in the hypermethylation group. We found that TXNIP DNA hypomethylation at baseline was associated with a marked increase in glycemic traits. Leukocyte TXNIP DNAm status could potentially be used as an early biomarker for impaired glucose homeostasis.

Objective This longitudinal study aimed to clarify the changes in the medical treatment behavior of Japanese patients with chronic diseases during the early phase of the coronavirus disease 2019 (COVID-19) pandemic and examine the factors associated with disease worsening. Methods Subjects with chronic diseases were selected from a panel survey that started at the beginning of the COVID-19 pandemic consists of 2,400 participants recruited via the Internet. Medical treatment behaviors (decrease in medical visit frequency, inability to take regular medications, and utilization of telephone/online medical care), psychological distress, and sociodemographic factors were evaluated at baseline (May 2020) and at the follow-up survey (February 2021). A worsening of chronic diseases was defined as those who answered "yes" to the question, "Has-the-condition-of-the-chronic-disease-worsened?". The factors related to the worsening of chronic diseases at follow-up were examined. Results A total of 514 participants (mean age 61.6±12.9 years) were analyzed. The percentage of participants who reported decreasing medical visit frequency was 34% at the baseline and 16.5% at follow-up, and those who reported a worsening of chronic diseases was 5.1% and 5.1%, respectively. A worsening of chronic diseases at follow-up was significantly associated with a younger age, a decreased frequency of medical visits, unemployment, a history of smoking, and psychological distress. Conclusions A decreased frequency of medical visits was observed among one-third of the participants with chronic disease in the early stage of the pandemic, and it reduced by half at follow-up. In the early stages of an emerging infectious disease pandemic, decreased regular hospital/clinic visits can lead to a worsening of chronic diseases. Those who had psychological distress, unemployment, and a history of smoking were vulnerable to a worsening chronic disease.

To assess the effectiveness of different machine learning models in estimating the pharmaceutical and non-pharmaceutical expenditures associated with Diabetes Mellitus type II diagnosis, based on the clinical risk index determined by the analysis of comorbidities.

In this cross-sectional study, we have used data from 11,028 anonymized records of patients admitted to a high-complexity hospital in Bogota, Colombia between 2017-2019 with a primary diagnosis of Diabetes. These cases were classified according to Charlson's comorbidity index in several risk categories. The main variables analyzed in this study are hospitalization costs (which include pharmaceutical and non-pharmaceutical expenditures), age, gender, length of stay, medicines and services consumed, and comorbidities assessed by the Charlson's index. The model's dependent variable is expenditure (composed of pharmaceutical and non-pharmaceutical expenditures). Based on these variables, different machine learning models (Multivariate linear regression, Lasso model, and Neural Networks) were used to estimate the pharmaceutical and non-pharmaceutical expenditures associated with the clinical risk classification. To evaluate the performance of these models, different metrics were used: Mean Absolute Percentage Error (MAPE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and Coefficient of Determination (R2).

The results indicate that the Neural Networks model performed better in terms of accuracy in predicting pharmaceutical and non-pharmaceutical expenditures considering the clinical risk based on Charlson's comorbidity index. A deeper understanding and experimentation with Neural Networks can improve these preliminary results, therefore we can also conclude that the main variables used and those that were proposed can be used as predictors for the medical expenditures of patients with diabetes type-II.

With the increase of technology elements and tools, it is possible to build models that allow decision-makers in hospitals to improve the resource planning process given the accuracy obtained with the different models tested.

Diabetes mellitus (DM) is known to be a cause of cervical internal carotid artery stenosis (ICS). In this study, we investigated the natural history of asymptomatic ICS in DM patients without surgical intervention.

We conducted a retrospective study of 148 DM patients with asymptomatic ICS treated medically at the Kansai Electric Power Hospital from April 2013 to March 2023, inclusive. We examined the incidence of ischemic stroke with ICS and evaluated the patients' clinical characteristics and imaging findings.

Ischemic stroke with ICS occurred in 7 patients (4.7 %), and only smoking history was significantly correlated with the incidence of ischemic stroke (p = 0.04).

The incidence rate of ischemic stroke with ICS in this study (4.7%) was comparable to the previous report. The result that, the correlated factors of the incidence of ischemic stroke in DM patients with ICS was only smoking history, seemed acceptable. However, prospective studies with a larger number of cases may be needed in the future to determine the correlated factors more eligibly.

Tobacco exposure is known to be associated with a higher prevalence and incidence of liver diseases. Cotinine, a metabolite of nicotine, is a typical indicator of tobacco exposure. However, the relationship of serum cotinine levels with hepatic steatosis and liver fibrosis remains controversial and these relationships need more research to explored in American teenagers. Cross-sectional data included 1433 participants aged 12-19 from the National Health and Nutrition Examination Survey (NHANES) from 2017 to 2020 were thoroughly used for this study. The linear relationships between serum cotinine levels and the Liver Stiffness Measurement (LSM) and Controlled Attenuation Parameter (CAP) were examined using multiple linear regression models. Subgroup analysis, interaction tests, and nonlinear interactions were also carried out. Serum cotinine levels > 2.99 ng/ml [β = 0.41 (0.07, 0.76), p = 0.018] and 0.05-2.99 ng/ml [β = 0.24 (0.00, 0.49), p = 0.048] showed a significant positive connection with LSM in multivariate linear regression analysis when compared to serum cotinine levels ≤ 0.05 ng/ml (p for trend = 0.006). Moreover, we discovered an inverted U-shaped association of log2-transformed cotinine with LSM with an inflection point of 4.53 using a two-stage linear regression model. However, according to multiple regression analysis, serum cotinine and CAP did not significantly correlate (p = 0.512). In conclusion, this study demonstrated that smoking cessation and keep away from secondhand smoking may beneficial for liver health in American teenagers.

Motoric cognitive risk syndrome (MCR) is a newly proposed pre-dementia syndrome characterized by subjective cognitive complaints (SCCs) and slow gait (SG). Increasing evidence links MCR to several adverse health outcomes, but the specific relationship between MCR and the risk of frailty, Alzheimer's disease (AD), and vascular dementia (VaD) remains unclear. Additionally, literature lacks analysis of MCR's components and associated health outcomes, complicating risk identification. This systematic review and meta-analysis aimed to provide a comprehensive overview of MCR's predictive value for adverse health outcomes.

Relevant cross-sectional, cohort, and longitudinal studies examining the association between MCR and adverse health outcomes were extracted from ten electronic databases. The Newcastle-Ottawa Scale (NOS) and modified NOS were used to assess the risk of bias in studies included in the analysis. Relative ratios (RRs) and 95% confidence intervals (CIs) were pooled for outcomes associated with MCR.

Twenty-eight longitudinal or cohort studies and four cross-sectional studies with 1,224,569 participants were included in the final analysis. The risk of bias in all included studies was rated as low or moderate. Pooled analysis of RR indicated that MCR had a greater probability of increased the risk of dementia (adjusted RR = 2.02; 95% CI = 1.94-2.11), cognitive impairment (adjusted RR = 1.72; 95% CI = 1.49-1.99), falls (adjusted RR = 1.32; 95% CI = 1.17-1.50), mortality (adjusted RR = 1.66; 95% CI = 1.32-2.10), and hospitalization (adjusted RR = 1.46; 95% CI = 1.16-1.84); MCR had more prominent predictive efficacy for AD (adjusted RR = 2.23; 95% CI = 1.81-2.76) compared to VaD (adjusted RR = 3.78; 95% CI = 0.49-28.95), while excluding analyses from the study that utilized the timed-up-and-go test and one-leg-standing to evaluate gait speed. One study examined the association between MCR and disability (hazard ratios [HR] = 1.69; 95% CI = 1.08-2.02) and frailty (OR = 5.53; 95% CI = 1.46-20.89). SG was a stronger predictor of the risk for dementia and falls than SCC (adjusted RR = 1.22; 95% CI = 1.11-1.34 vs. adjusted RR = 1.19; 95% CI = 1.03-1.38).

MCR increases the risk of developing any discussed adverse health outcomes, and the predictive value for AD is superior to VaD. Additionally, SG is a stronger predictor of dementia and falls than SCC. Therefore, MCR should be routinely assessed among adults to prevent poor prognosis and provide evidence to support future targeted interventions.

Using blood sample data we exploit an arbitrary cut-off of diabetes risk and through a fuzzy regression kink design we estimate the effect of a diabetes diagnosis on own and partner health-related behaviours. Diabetes diagnosis increases the probability of exercising, both for those diagnosed with diabetes and their partner. We also conduct mediation analysis which suggests that joint household participation is the channel behind this effect. Our results have significant implications for the understanding of the channels that induce behavioural change, and household decision making, as well as, for the evaluation of diabetes related policies.

α-klotho is an anti-aging protein. The correlation between smoking, smoking cessation and serum α-klotho levels remains controversial. The aim of this study was to investigate the association between smoking, smoking cessation and serum α-klotho levels. This cross-sectional study finally included 4877 participants, aged 40-79 years, who participated in the National Health and Nutrition Examination Survey studies from 2013 to 2016. Of these, 2312 (47.4%) were men and 894 (18.3%) were current smokers, and the mean age of the participants was 57.8±10.7 years. Multivariate linear regression modeling was used to assess the association between smoking, smoking cessation and serum α-klotho levels. After adjustment for multiple confounders, this study observed that smoking was negatively associated with serum α-klotho levels (β: -58.3; 95% confidence interval CI: -82.0 to -34.6; p<0.001), whereas smoking cessation was positively associated with serum α-klotho levels (β: 52.3; 95% CI: 24.1 to 80.6; p<0.001). In subgroup and interaction analyses, p-value for the interaction between smoking and race on serum klotho levels was found to be less than 0.001. The correlation between smoking, smoking cessation and serum α-klotho levels remained stable after propensity score matching (β: -54.1; 95% CI: -81.5 to -26.7; p<0.001, β: 54.8; 95% CI: 24.2 to 85.4; p<0.001). In a large sample population, the present study found that smoking, smoking cessation and serum α-klotho levels were associated in opposite directions.