Risk Of Multiple Chronic Diseases Research Articles

Personalized prediction for multiple chronic diseases by developing the multi-task Cox learning model.

Personalized prediction of chronic diseases is crucial for reducing the disease burden. However, previous studies on chronic diseases have not adequately considered the relationship between chronic diseases. To explore the patient-wise risk of multiple chronic diseases, we developed a multitask learning Cox (MTL-Cox) model for personalized prediction of nine typical chronic diseases on the UK Biobank dataset. MTL-Cox employs a multitask learning framework to train semiparametric multivariable Cox models. To comprehensively estimate the performance of the MTL-Cox model, we measured it via five commonly used survival analysis metrics: concordance index, area under the curve (AUC), specificity, sensitivity, and Youden index. In addition, we verified the validity of the MTL-Cox model framework in the Weihai physical examination dataset, from Shandong province, China. The MTL-Cox model achieved a statistically significant (p<0.05) improvement in results compared with competing methods in the evaluation metrics of the concordance index, AUC, sensitivity, and Youden index using the paired-sample Wilcoxon signed-rank test. In particular, the MTL-Cox model improved prediction accuracy by up to 12% compared to other models. We also applied the MTL-Cox model to rank the absolute risk of nine chronic diseases in patients on the UK Biobank dataset. This was the first known study to use the multitask learning-based Cox model to predict the personalized risk of the nine chronic diseases. The study can contribute to early screening, personalized risk ranking, and diagnosing of chronic diseases.

Beyond survival: the lasting effects of premature birth.

Preterm birth, defined as birth before 37 weeks of gestation, is a major public health concern. It affects about 10% of all newborns globally and is the main cause of infant death and morbidity. Prematurity increases the likelihood of respiratory distress syndrome, cerebral palsy, and developmental abnormalities. Furthermore, premature newborns are at risk of acquiring chronic noncommunicable diseases later in life due to interference with organ system development during the in-utero and perinatal period. Because of the greater risk of long-term repercussions, preterm birth should be considered a chronic disorder, and gestational age and other birth histories should be included in all medical records for patients of all ages, especially when assessing the risk of multiple chronic diseases. Conventional methods for assessing preterm infant development, as well as reliable and precise growth monitoring, can lead to the early detection of growth decline and the adjustment of feeding regimens as needed. Because of its unique composition and useful components, human milk is a powerful tool for mitigating the negative outcomes associated with prematurity. It contains a variety of growth factors that promote the development of organs and systems, counteracting the negative effects of the abrupt interruption of intrauterine development and promoting better outcomes in all altered functions. Despite its multiple benefits, human milk cannot totally restore the lasting damage caused by premature birth. Premature infants cannot be completely overcome by nutrition alone, and yet adequate nutritional intake and human milk feeding are critical to their health and development.

Abstract P125: Patterns in Timing of Energy Intake and the Impact on Fat Mass in Adolescents

Introduction: Pediatric obesity is excessively high, tracks into adulthood, and increases the risk of multiple chronic diseases (e.g., heart disease). There are dietary guidelines to help prevent childhood obesity, but they do not account for the timing of energy intake, which may be associated with obesity, independent of diet content. We aimed to determine: 1) energy intake timing patterns in adolescents, 2) if energy intake timing patterns differed by sociodemographic factors, and 3) if energy intake timing patterns associated with obesity-related outcomes. Methods: The Sleep and Growth Study (S-Grow) assessed diet in adolescents using three 24hr diet recalls in 8 th and 9 th grade. Time-stamped meals were analyzed using Nutrient Data System for Research software. We calculated the average energy (kcal) consumed for two-hour intervals during the 24-hour day (e.g., 00:00-01:59, 02:00-03:59, etc.) and input the 12 energy intake timing variables into a principal component model to identify energy intake timing patterns. Principal components (PC) with an eigen value 1.0 were retained. Linear mixed effect models were used to determine if sociodemographic factors associated with standardized PC loading scores and if the standardized PC loading scores associated with body mass index (BMI) and fat mass index (FMI, measured by dual energy X-ray absorptiometry), adjusting for sociodemographic factors. Results: Five PCs were identified explaining 58.6% of variance in timing of energy intake. Compared to females, male adolescents were more likely to have a higher PC1 score, corresponding to a “low overnight, moderate morning, high daytime and early evening” intake pattern (beta=0.57, 95% CI=0.20, 0.94). Adolescents living in households with $40-69K (compared to &gt;$99K) annual income were more likely to have a higher PC4 score, corresponding to a “high later evening and overnight, moderate morning, low afternoon and early evening” intake pattern (beta=0.44, 95% CI=0.05, 0.83). Adolescents living in households with &lt;$40K (compared to &gt;$99K) annual income were more likely to have a higher PC5 score, corresponding to a “low overnight, high morning, moderate prolonged daytime and late evening” intake pattern (beta=-0.93, 95% CI=-1.66, -0.19). In addition, the PC5 loading score was associated with lower BMI (beta=-1.38, 95% CI=-2.18,-0.58) and lower FMI (beta=-0.94, 95% CI=-1.45,-0.43). Conclusion: We detected distinct energy intake timing patterns in adolescents. Demographic factors were associated with some of the energy intake patterns, and the energy intake pattern corresponding to “low overnight, high morning, moderate prolonged daytime and late evening” (PC5) was associated with obesity-related outcomes. These findings need to be replicated but point to future pediatric dietary guidelines considering the timing of energy intake for obesity prevention.

MicroRNAs as Mediators of Adipose Thermogenesis and Potential Therapeutic Targets for Obesity.

Obesity is a growing health problem worldwide, associated with an increased risk of multiple chronic diseases. The thermogenic activity of brown adipose tissue (BAT) correlates with leanness in adults. Understanding the mechanisms behind BAT activation and the process of white fat "browning" has important implications for developing new treatments to combat obesity. MicroRNAs (miRNAs) are small transcriptional regulators that control gene expression in various tissues, including adipose tissue. Recent studies show that miRNAs are involved in adipogenesis and adipose tissue thermogenesis. In this review, we discuss recent advances in the role of miRNAs in adipocyte thermogenesis and obesity. The potential for miRNA-based therapies for obesity and recommendations for future research are highlighted, which may help provide new targets for treating obesity and obesity-related diseases.

Association between Handgrip Strength and the Systemic Immune-Inflammation Index: A Nationwide Study, NHANES 2011-2014.

(1) Background: The Systemic immune-inflammatory index (SII) has been proven to be an effective biomarker of human immune and inflammatory levels and has prognostic significance for most diseases. Handgrip strength (HGS) is a simple and low-cost strength measurement method, which is not only highly correlated with overall muscle strength but also accurately and reliably predicts the risk of multiple chronic diseases and mortality; (2) Purpose: Association between HGS and the SII is unclear. The purpose of this study was to investigate the association between HGS and the SII in American adults; (3) Methods: We used the data from the 2011–2012 and 2013–2014 cycles of the National Health and Nutrition Examination Survey (NHANES), involving a total of 8232 American adults (aged 18–80 years). The SII was calculated as the Platelet count × Neutrophil count/Lymphocyte count; HGS was recorded as the ratio of the sum of the highest grip-strength values of each hand to body mass index taken as the relative grip strength. A weighted generalized linear regression model and analysis of restricted cubic spline regression, adjusted for confounding factors, were used in this study to assess associations between HGS and the SII in American adults; (4) Results: There was a negative correlation between the HGS and the SII of different sexes (p < 0.05), and there was a significant negative nonlinear relationship between the HGS and the SII in males (p for nonlinear = 0.0035), and the SII showed a downward trend with the increase in the HGS in males (Q2: β = −61.03, p = 0.01; Q3: β = −61.28, p = 0.04, Q4: β = −64.36, p = 0.03, p for trend = 0.04), when the HGS exceeds 3.16, with the HGS increasing, the downward trend of increasing the SII slowed down. The nonlinear relationship between the HGS and the SII in females was not significant (p for nonlinear = 0.1011), and the SII showed a linear downward trend with the increase in the HGS (Q2: β = −24.91, p = 0.25; Q3: β = −62.01, p = 0.03, Q4: β = −74.94, p = 0.03, p for trend = 0.01); (5) Conclusions: HGS is inversely and independently associated with SII levels, and although the limited cubic spline regression analysis showed gender differences, the overall trend of the HGS and the SII in different genders was consistent, with both showing that the SII decreased with increasing the HGS. In addition, HGS has high general applicability based on its ease of measurement; it is possible to understand one’s own grip-strength level through routine grip-strength tests, and to make preliminary predictions on the current level of immunity and inflammation in the body.

Effect of Shuddha Guggulu on Metabolic Syndrome - A Case Report

Metabolic syndrome is conglomeration of symptoms composed of impaired fasting glucose, abdominal obesity, hypertension and dyslipidemia. It is associated with cardio metabolic risk factors with increased risk of multiple chronic diseases, including cancer and cardiovascular disease because of the increased amount of visceral fat together with a chronic inflammatory state.&#x0D; Metabolic Syndrome is resulted by the causative factors which are Santarpanakaraka in nature leading to Medodushti, which in turn leads to Medoroga. The Santarpana karaka Nidanas include the food articles that are rich in Snigdhamsha, Madhura rasa, Guru and Pichchila gunas. By consuming the food rich in such qualities produces the Rasa dhatu which is excessively composed of the qualities like Ati Snehamsha and Madhuratara Guna which produces excess Medo dhatu and causes Sthoulya. Ama present in the Medodhatu leads to further Medo dushti and manifests Metabolic Syndrome.&#x0D; Shuddha Guggulu is potent Ama pachaka dravya and does Pachana of the circulating Atisnigdha Ama in the form of lipoproteins. And also Guggulu having Lekhaneeya Guna reduces deposition of Medo dhatu and prevents inflammatory process by its anti- inflammatory potential. Aim: To assess the effect of Shuddha Guggulu in Metabolic Syndrome, dyslipidaemia. Methodology: Oral administration of the preparation in the patient. Result: There was marked improvement in signs, symptoms and biochemical parameters after intervention. Conclusion: Shuddha Guggulu is significantly effective in reducing lipid levels and CRP

Theoretical attributable risk analysis and Disability Adjusted Life Years (DALYs) based on increased dairy consumption

BackgroundIdentification of modifiable risk factors that may impact chronic disease risk is critical to public health. Our study objective was to conduct a theoretical population attributable risk analysis to estimate the burden of disease from low dairy intake and to estimate the impact of increased dairy intake on United States (US)-based disability adjusted life years (DALYs).MethodsWe conducted a comprehensive literature review to identify statistically significant summary relative risk estimates (SRREs) from recent meta-analyses of dairy consumption and key chronic disease outcomes. The SRREs were applied to preventive fractions using a range of categories (low to high) for population consumption of dairy products. The preventive fraction estimates were then applied to the number of DALYs for each health outcome in the US based on 2019 WHO estimates. The population attributable risk proportion estimates were calculated using the inverse of the SRRE from each meta-analysis using the same range of categories of consumption. These values were subsequently applied to the DALYs estimates to estimate the theoretical burden of disease attributable to low dairy intake.ResultsStatistically significant SRREs were identified in recent meta-analyses of total dairy consumption in relation to breast cancer, colorectal cancer, cardiovascular disease (CVD), type 2 diabetes (T2D), stroke, and hypertension. In this theoretical analysis, nearly 850,000 DALYs (or 5.0% of estimated years of healthy life lost) due to CVD and 200,000 DALYs (4.5%) due to T2D may be prevented by increased dairy consumption. Approximately 100,000 DALYs due to breast cancer (7.5%) and approximately 120,000 DALYs (8.5%) due to colorectal cancer may be prevented by high dairy intake. The numbers of DALYs for stroke and hypertension that may be prevented by increased dairy consumption were approximately 210,000 (6.0%) and 74,000 (5.5%), respectively.ConclusionsConsumption of dairy products has been associated with decreased risk of multiple chronic diseases of significant public health importance. The burden of disease that may potentially be prevented by increasing dairy consumption is substantial, and population-wide improvement in meeting recommended daily dairy intake goals could have a notable public health impact. However, this analysis is theoretical, and thus additional studies providing empirical evidence are needed to further clarify potential relationships between dairy intake and various health outcomes.

Social Inequalities in Multiple Chronic Disease Risk Factors among a population-based Sample of Latinas in California

ABSTRACT Data from 1,248 Latina mothers who participated in the Geographic Research on Wellbeing (GROW) study were used to examine associations between SES, neighborhood-level Latinx concentration, neighborhood-level poverty and having two or more modifiable behavioral risk factors (e.g., smoking, drinking) for chronic disease. Logistic regression models were estimated stratified by nativity and adjusted for age and marital status. Among immigrants, low SES was associated with higher odds of multiple risk factors (Adjusted Odds Ratio [AOR] = 1.66, 95% Confidence Interval [CI] = 1.17–2.38). Among US-born women, low neighborhood-level Latinx concentration was associated with lower odds of multiple risk factors (AOR = 0.43, 95% CI = 0.22–0.84), and high neighborhood-level poverty (AOR = 2.83, 95% CI = 1.61–4.99) and low SES (AOR = 1.72, 95% CI = 1.02–2.92) were associated with higher odds, respectively. Heterogeneous effects between nativity and social factors may produce risk for chronic disease among Latinas.

Challenges in the management of older patients with inflammatory rheumatic diseases.

The rise in the number of people aged 65 years and older living with inflammatory rheumatic diseases such as rheumatoid arthritis is causing considerable challenges for clinicians. As patients get older, they are at an increased risk of multiple chronic diseases, a situation termed multimorbidity. Multimorbidity inevitably drives polypharmacy, where by a patient requires treatment with multiple medications. In addition, advancing age, multimorbidity and polypharmacy all place a patient at an increased risk of developing geriatric syndromes, which are clinical conditions in older people that do not fit into disease categories and include malnutrition, sarcopenia and frailty. Geriatric syndromes further increase the risk of adverse outcomes, including the accrual of additional morbidity, nursing home admission and mortality. Patients with inflammatory rheumatic diseases are especially prone to developing geriatric syndromes. Some predisposing risk factors for geriatric syndromes, such as joint swelling and functional limitations, are also inherent to rheumatic inflammatory disease itself. The frequent coexistence of multimorbidity, polypharmacy and geriatric syndromes in this patient group requires individually tailored interventions to preserve patient independence and overall functioning. To prepare for the changing demography, rheumatologists should gain more insight into the implications of multimorbidity, polypharmacy and geriatric syndromes for the management of older patients with inflammatory rheumatic diseases.

Preterm birth and the risk of chronic disease multimorbidity in adolescence and early adulthood: A population-based cohort study.

BackgroundPeople who were born prematurely have high risks of many individual diseases and conditions in the early part of the life course. However, our knowledge of the burden of multiple diseases (multimorbidity) among prematurely born individuals is limited. We aimed to investigate the risk and patterns of chronic disease multimorbidity in adolescence and early adulthood among individuals born across the spectrum of gestational ages, comparing preterm and full-term born individuals.Methods and findingsWe used individual-level data from linked nationwide registers to examine the associations of gestational age at birth with specialised healthcare records of ≥2 chronic diseases (multimorbidity) in adolescence (age 10–17 years) and early adulthood (age 18–30 years). Our study population comprised 951,116 individuals (50.2% females) born alive in Finland between 1st January 1987 and 31st December 2006, inclusive. All individuals were followed from age 10 years to the onset of multimorbidity, emigration, death, or 31 December 2016 (up to age 30 years). We estimated hazard ratios (HRs) and 95% confidence intervals (CIs) for multimorbidity using flexible parametric survival models. During 6,417,903 person-years at risk (median follow-up: 7.9 years), 11,919 individuals (1.3%) had multimorbidity in adolescence (18.6 per 10,000 person-years). During 3,967,419 person-years at risk (median follow-up: 6.2 years), 15,664 individuals (1.7%) had multimorbidity in early adulthood (39.5 per 10,000 person-years). Adjusted HRs for adolescent multimorbidity, comparing preterm to full-term born individuals, were 1.29 (95% CI: 1.22 to 1.36) and 1.26 (95% CI: 1.18 to 1.35) in females and males, respectively. The associations of preterm birth with early adult multimorbidity were less marked, with the adjusted HRs indicating 1.18-fold risk in females (95% CI: 1.12 to 1.24) and 1.10-fold risk in males (95% CI: 1.04 to 1.17). We observed a consistent dose-response relationship between earlier gestational age at birth and increasing risks of both multimorbidity outcomes. Compared to full-term born males, those born at 37–38 weeks (early term) had a 1.06-fold risk of multimorbidity in adolescence (95% CI: 0.98 to 1.14) and this risk increased in a graded manner up to 6.85-fold (95% CI: 5.39 to 8.71) in those born at 23–27 weeks (extremely premature), independently of covariates. Among females, the same risks ranged from 1.16-fold (95% CI: 1.09 to 1.23) among those born at 37–38 weeks to 5.65-fold (95% CI: 4.45 to 7.18) among those born at 23–27 weeks. The corresponding risks of early adult multimorbidity were similar in direction but less marked in magnitude, with little difference in risks between males and females born at 36–37 weeks but up to 3-fold risks observed among those born at 23–27 weeks.ConclusionsOur findings indicate that an earlier gestational age at birth is associated with increased risks of chronic disease multimorbidity in the early part of the life course. There are currently no clinical guidelines for follow-up of prematurely born individuals beyond childhood, but these observations suggest that information on gestational age would be a useful characteristic to include in a medical history when assessing the risk of multiple chronic diseases in adolescent and young adult patients.

Socio-Demographic Association of Multiple Risk Factors and Their Clustering in Urban Population of Adults

Introduction: The purpose of this study was to estimate the prevalence and identify factors associated with simultaneous risk factors occurrence (clustering) for chronic diseases among adults. Methods: A cross-sectional population-based study was carried out with 1977 adults in Sousse, Tunisia. The simultaneous occurrence of tobacco smoking, physical inactivity, inadequate or unhealthy diet, obesity, and high blood pressure was assessed. The independent variables were demographic and socioeconomic characteristics. Results: Overall, 61% of Tunisian adults had two or more unhealthy risk factors compared to only 11% with none of the five risk factors. Prevalence of risk factors was greater in older subjects, females, married, with lower education, unemployed, and those with high socioeconomic status. Risk factors clustered in multiple combinations. The simultaneous presence of all risk factors was 40% higher of what would be expected by combining the individual prevalence of these risk factors. Physical inactivity, unhealthy diet, obesity, and high blood pressure showed the strongest association among the clusters. Conclusion: Multiple chronic disease risk factors are frequent and occur more often than expected among Tunisian adults, especially women, married, older subjects, with low education and high socioeconomic level. Information on high risk groups will help in planning future preventive strategies.

Socio-Demographic Association of Multiple Risk Factors and Their Clustering in Urban Population of Adults

Introduction: The purpose of this study was to estimate the prevalence and identify factors associated with simultaneous risk factors occurrence (clustering) for chronic diseases among adults. Methods: A cross-sectional population-based study was carried out with 1977 adults in Sousse, Tunisia. The simultaneous occurrence of tobacco smoking, physical inactivity, inadequate or unhealthy diet, obesity, and high blood pressure was assessed. The independent variables were demographic and socioeconomic characteristics. Results: Overall, 61% of Tunisian adults had two or more unhealthy risk factors compared to only 11% with none of the five risk factors. Prevalence of risk factors was greater in older subjects, females, married, with lower education, unemployed, and those with high socioeconomic status. Risk factors clustered in multiple combinations. The simultaneous presence of all risk factors was 40% higher of what would be expected by combining the individual prevalence of these risk factors. Physical inactivity, unhealthy diet, obesity, and high blood pressure showed the strongest association among the clusters. Conclusion: Multiple chronic disease risk factors are frequent and occur more often than expected among Tunisian adults, especially women, married, older subjects, with low education and high socioeconomic level. Information on high risk groups will help in planning future preventive strategies.

Development of a prognostic prediction model to estimate the risk of multiple chronic diseases

IntroductionThe ability to estimate risk of multimorbidity will provide valuable information to patients and primary care practitioners in their preventative efforts. Current methods for prognostic prediction modelling are insufficient for the estimation of risk for multiple outcomes, as they do not properly capture the dependence that exists between outcomes. ObjectivesWe developed a multivariate prognostic prediction model for the 5-year risk of diabetes, hypertension, and osteoarthritis that quantifies and accounts for the dependence between each disease using a copula-based model. MethodsWe used data from the Canadian Primary Care Sentinel Surveillance Network (CPCSSN) from 2009 onwards, a collection of electronic medical records submitted by participating primary care practitioners across Canada. We identified patients 18 years and older without all three outcome diseases and observed any incident diabetes, osteoarthritis, or hypertension within 5-years, resulting in a large retrospective cohort for model development and internal validation (n=425228). First, we quantified the dependence between outcomes using unadjusted and adjusted ϕ coefficients. We then estimated a copula-based model to quantify the non-linear dependence between outcomes that can be used to derive risk estimates for each outcome, accounting for the observed dependence. Copula-based models are defined by univariate models for each outcome and a dependence function, specified by the parameter θ. Logistic regression was used for the univariate models and the Frank copula was selected as the dependence function. ResultsAll outcome pairs demonstrated statistically significant dependence that was reduced after adjusting for covariates. The copula-based model yielded statistically significant θ parameters in agreement with the adjusted and unadjusted ϕ coefficients. Our copula-based model can effectively be used to estimate trivariate probabilities. DiscussionQuantitative estimates of multimorbidity risk inform discussions between patients and their primary care practitioners around prevention in an effort to reduce the incidence of multimorbidity.

Development of a prognostic prediction model to estimate the risk of multiple chronic diseases: constructing a copula-based model using Canadian primary care electronic medical record data.

IntroductionThe ability to estimate risk of multimorbidity will provide valuable information to patients and primary care practitioners in their preventative efforts. Current methods for prognostic prediction modelling are insufficient for the estimation of risk for multiple outcomes, as they do not properly capture the dependence that exists between outcomes.ObjectivesWe developed a multivariate prognostic prediction model for the 5-year risk of diabetes, hypertension, and osteoarthritis that quantifies and accounts for the dependence between each disease using a copula-based model.MethodsWe used data from the Canadian Primary Care Sentinel Surveillance Network (CPCSSN) from 2009 onwards, a collection of electronic medical records submitted by participating primary care practitioners across Canada. We identified patients 18 years and older without all three outcome diseases and observed any incident diabetes, osteoarthritis, or hypertension within 5-years, resulting in a large retrospective cohort for model development and internal validation (n=425,228). First, we quantified the dependence between outcomes using unadjusted and adjusted Ø coefficients. We then estimated a copula-based model to quantify the non-linear dependence between outcomes that can be used to derive risk estimates for each outcome, accounting for the observed dependence. Copula-based models are defined by univariate models for each outcome and a dependence function, specified by the parameter θ. Logistic regression was used for the univariate models and the Frank copula was selected as the dependence function.ResultsAll outcome pairs demonstrated statistically significant dependence that was reduced after adjusting for covariates. The copula-based model yielded statistically significant θ parameters in agreement with the adjusted and unadjusted Ø coefficients. Our copula-based model can effectively be used to estimate trivariate probabilities.DiscussionQuantitative estimates of multimorbidity risk inform discussions between patients and their primary care practitioners around prevention in an effort to reduce the incidence of multimorbidity.

A Web-Based Intervention to Prevent Multiple Chronic Disease Risk Factors Among Adolescents: Co-Design and User Testing of the Health4Life School-Based Program.

BackgroundChronic diseases are the leading cause of death worldwide. Addressing key lifestyle risk factors during adolescence is critical for improving physical and mental health outcomes and reducing chronic disease risk. Schools are ideal intervention settings, and electronic health (eHealth) interventions afford several advantages, including increased student engagement, scalability, and sustainability. Although lifestyle risk behaviors tend to co-occur, few school-based eHealth interventions have targeted multiple behaviors concurrently.ObjectiveThis study aims to summarize the co-design and user testing of the Health4Life school-based program, a web-based cartoon intervention developed to concurrently prevent 6 key lifestyle risk factors for chronic disease among secondary school students: alcohol use, smoking, poor diet, physical inactivity, sedentary recreational screen time, and poor sleep (the Big 6).MethodsThe development of the Health4Life program was conducted over 18 months in collaboration with students, teachers, and researchers with expertise relevant to the Big 6. The iterative process involved (1) scoping of evidence and systematic literature review; (2) consultation with adolescents (N=815) via a cross-sectional web-based survey to identify knowledge gaps, attitudes, barriers, and facilitators in relation to the Big 6; (3) content and web development; and (4) user testing of the web-based program with students (n=41) and teachers (n=8) to evaluate its acceptability, relevance, and appeal to the target audience.ResultsThe co-design process resulted in a six-module, evidence-informed program that uses interactive cartoon storylines and web-based delivery to engage students. Student and teacher feedback collected during user testing was positive in terms of acceptability and relevance. Commonly identified areas for improvement concerned the length of modules, age appropriateness of language and alcohol storyline, the need for character backstories and links to syllabus information, and feasibility of implementation. Modifications were made to address these issues.ConclusionsThe Health4Life school-based program is the first universal, web-based program to concurrently address 6 important chronic disease risk factors among secondary school students. By adopting a multiple health behavior change approach, it has the potential to efficiently modify the Big 6 risk factors within one program and to equip young people with the skills and knowledge needed to achieve and maintain good physical and mental health throughout adolescence and into adulthood.

Metabolic Impacts of Confinement during the COVID-19 Pandemic Due to Modified Diet and Physical Activity Habits.

While the detrimental effects of a chronic positive energy balance due to a sedentary lifestyle have been well established, the impacts of a short period of abruptly reduced physical activity and overeating arising from strict confinement due to the COVID-19 pandemic will soon start to emerge. To reasonably anticipate major consequences according to the available evidence, we hereby review the literature for studies that have explored the health impacts of several weeks of a reduction in physical activity and daily step-count combined with modified eating habits. These studies identify as main metabolic consequences increases in insulin resistance, total body fat, abdominal fat and inflammatory cytokines. All these factors have been strongly associated with the development of metabolic syndrome, which in turn increases the risk of multiple chronic diseases. A plausible mechanism involved in these impacts could be a positive energy balance promoted by maintaining usual dietary intake while reducing energy expenditure. This means that just as calorie intake restriction could help mitigate the deleterious impacts of a bout of physical inactivity, overeating under conditions of home confinement is very likely to exacerbate these consequences. Moreover, hypertension, diabetes, and cardiovascular disease have been identified as potential risk factors for more severely ill patients with COVID-19. Thus, adequate control of metabolic disorders could be important to reduce the risk of severe COVID-19.

Clustering of Multiple Chronic Disease Risk Behaviors among Middle School Youth

Clustering of Multiple Chronic Disease Risk Behaviors among Middle School Youth

Metabolic Syndrome Prevalence by Race/Ethnicity and Sex in the United States, National Health and Nutrition Examination Survey, 1988-2012.

IntroductionMetabolic syndrome is a cluster of cardiometabolic risk factors associated with increased risk of multiple chronic diseases, including cancer and cardiovascular disease. The objectives of this study were to estimate the prevalence of metabolic syndrome overall, by race and sex, and to assess trends in prevalence from 1988 through 2012.MethodsWe analyzed data from the National Health and Nutrition Examination Survey (NHANES) for 1988 through 2012. We defined metabolic syndrome as the presence of at least 3 of these components: elevated waist circumference, elevated triglycerides, reduced high-density lipoprotein cholesterol, high blood pressure, and elevated fasting blood glucose. Data were analyzed for 3 periods: 1988–1994, 1999–2006, and 2007–2012.ResultsAmong US adults aged 18 years or older, the prevalence of metabolic syndrome rose by more than 35% from 1988–1994 to 2007–2012, increasing from 25.3% to 34.2%. During 2007–2012, non-Hispanic black men were less likely than non-Hispanic white men to have metabolic syndrome (odds ratio [OR], 0.77; 95% confidence interval [CI], 0.66–0.89). However, non-Hispanic black women were more likely than non-Hispanic white women to have metabolic syndrome (OR, 1.20; 95% CI, 1.02–1.40). Low education level (OR, 1.56; 95% CI, 1.32–1.84) and advanced age (OR, 1.73; 95% CI, 1.67–1.80) were independently associated with increased likelihood of metabolic syndrome during 2007–2012.ConclusionMetabolic syndrome prevalence increased from 1988 to 2012 for every sociodemographic group; by 2012, more than a third of all US adults met the definition and criteria for metabolic syndrome agreed to jointly by several international organizations.

Mediterranean and western dietary patterns are related to markers of testicular function among healthy men.

Are there any associations of dietary patterns with semen quality, reproductive hormone levels, and testicular volume, as markers of testicular function? These results suggest that traditional Mediterranean diets may have a positive impact on male reproductive potential. The Mediterranean diet has been related to lower risk of multiple chronic diseases, but its effects on reproduction potential are unclear. Cross-sectional sample of 215 male university students recruited from October 2010 to November 2011 in Murcia Region (Spain). Two hundred and nine healthy men aged 18-23 years were finally included in this analysis. Diet was assessed using a validated food frequency questionnaire, and dietary patterns were identified by factor analysis. Linear regression was used to analyze the relation between diet patterns with semen quality parameters, reproductive hormone levels and testicular volume adjusting for potential confounders. We identified two dietary patterns: a Mediterranean (characterized by high intakes of vegetables, fruits and seafood) and a Western pattern (characterized by high intakes of processed meats, French fries and snacks). The Mediterranean pattern was positively associated with total sperm count (P, trend = 0.04). The Western pattern was positively related to the percentage of morphologically normal sperm (P, trend = 0.008). We found an inverse association between adherence to the Western pattern and sperm concentration among overweight or obese men (P, trend = 0.04). As with all cross-sectional studies, causal inference is limited. However, participants were blinded to the study outcomes thus reducing the potential influenced their report of diet. Although we adjusted for a large number of known and suspected confounders, we cannot exclude the possibility of residual confounding or chance findings. This study was carried out on healthy and young men, so it is difficult to predict whether and how the observed differences in semen quality translate into reproductive success for men in couples trying to conceive. These results suggest that traditional Mediterranean diets may have a positive impact on male reproductive potential.

Investigation of an urban farm intervention for a low income Hispanic population with multiple risk factors for diabetes (624.3)

Background: Obesity and chronic disease are highly prevalent in the United States, particularly among low‐income Hispanic populations. Innovative approaches to changing social, behavioral and nutritional risk factors are crucially needed.Objectives: To implement and refine a pilot intervention to address chronic disease risk factors in an urban low income population.Methods: The New Haven Farms Fresh Produce Prescription program provided fresh produce, nutrition education, gardening education and cooking demonstrations weekly during sixteen weeks of the agriculture season. Participants were recruited through a community health center and came to a central urban agriculture site each week. Participants completed baseline and follow up assessments of dietary diversity, chronic disease risk, food security and physical activity, as well as weekly surveys on use of the fresh produce.Results: 51 people completed the baseline survey, and 40 people completed the follow up survey. Preliminary analyses show that approximately 30% show some food insecurity at baseline.Conclusions: This pilot study reports on the development of a complex intervention to address multiple chronic disease risk factors through agriculture‐based activities in an urban setting.