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ObjectiveType 2 diabetes (T2D) has heterogeneous patient clinical characteristics and outcomes. In previous work, we investigated the genetic basis of this heterogeneity by clustering 94 T2D genetic loci using their associations with 47 diabetes-related traits and identified five clusters, termed β-cell, proinsulin, obesity, lipodystrophy, and liver/lipid. The relationship between these clusters and individual-level metabolic disease outcomes has not been assessed.Research design and methodsHere we constructed individual-level partitioned polygenic scores (pPS) for these five clusters in 12 studies from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank (n = 454,193) and tested for cross-sectional association with T2D-related outcomes, including blood pressure, renal function, insulin use, age at T2D diagnosis, and coronary artery disease (CAD).ResultsDespite all clusters containing T2D risk-increasing alleles, they had differential associations with metabolic outcomes. Increased obesity and lipodystrophy cluster pPS, which had opposite directions of association with measures of adiposity, were both significantly associated with increased blood pressure and hypertension. The lipodystrophy and liver/lipid cluster pPS were each associated with CAD, with increasing and decreasing effects, respectively. An increased liver/lipid cluster pPS was also significantly associated with reduced renal function. The liver/lipid cluster includes known loci linked to liver lipid metabolism (e.g., GCKR, PNPLA3, and TM6SF2), and these findings suggest that cardiovascular disease risk and renal function may be impacted by these loci through their shared disease pathway.ConclusionsOur findings support that genetically driven pathways leading to T2D also predispose differentially to clinical outcomes.

Abstract Background Multimorbidity is increasingly recognized as a major public health challenge of modern societies. However, knowledge about the size of the population suffering from multimorbidity and the type of multimorbidity is scarce. The objective of this study was to present an overview of the prevalence of multimorbidity and comorbidity of chronic diseases in the Dutch population and to explore disease clustering and common comorbidities. Methods We used 7 years data (2002–2008) of a large Dutch representative network of general practices (212,902 patients). Multimorbidity was defined as having two or more out of 29 chronic diseases. The prevalence of multimorbidity was calculated for the total population and by sex and age group. For 10 prevalent diseases among patients of 55 years and older (N = 52,014) logistic regressions analyses were used to study disease clustering and descriptive analyses to explore common comorbid diseases. Results Multimorbidity of chronic diseases was found among 13% of the Dutch population and in 37% of those older than 55 years. Among patients over 55 years with a specific chronic disease more than two-thirds also had one or more other chronic diseases. Most disease pairs occurred more frequently than would be expected if diseases had been independent. Comorbidity was not limited to specific combinations of diseases; about 70% of those with a disease had one or more extra chronic diseases recorded which were not included in the top five of most common diseases. Conclusion Multimorbidity is common at all ages though increasing with age, with over two-thirds of those with chronic diseases and aged 55 years and older being recorded with multimorbidity. Comorbidity encompassed many different combinations of chronic diseases. Given the ageing population, multimorbidity and its consequences should be taken into account in the organization of care in order to avoid fragmented care, in medical research and healthcare policy.

Introduction: Chronic diseases and multimorbidity are common and expected to rise over the coming years. The objective of this study is to examine the time trend in the prevalence of chronic diseases and multimorbidity over the period 2001 till 2011 in the Netherlands, and the extent to which this can be ascribed to the aging of the population. Methods: Monitoring study, using two data sources: 1) medical records of patients listed in a nationally representative network of general practices over the period 2002–2011, and 2) national health interview surveys over the period 2001–2011. Regression models were used to study trends in the prevalence-rates over time, with and without standardization for age. Results: An increase from 34.9% to 41.8% (p<0.01) in the prevalence of chronic diseases was observed in the general practice registration over the period 2004–2011 and from 41.0% to 46.6% (p<0.01) based on self-reported diseases over the period 2001–2011. Multimorbidity increased from 12.7% to 16.2% (p<0.01) and from 14.3% to 17.5% (p<0.01), respectively. Aging of the population explained part of these trends: about one-fifth based on general practice data, and one-third for chronic diseases and half of the trend for multimorbidity based on health surveys. Conclusions: The prevalence of chronic diseases and multimorbidity increased over the period 2001–2011. Aging of the population only explained part of the increase, implying that other factors such as health care and society-related developments are responsible for a substantial part of this rise. [ABSTRACT FROM AUTHOR]

Background Multimorbidity is common among ageing populations and it affects the demand for health services. The objective of this study was to examine the relationship between multimorbidity (i.e. the number of diseases and specific combinations of diseases) and the use of general practice services in the Dutch population of 55 years and older. Methods Data on diagnosed chronic diseases, contacts (including face-to-face consultations, phone contacts, and home visits), drug prescription rates, and referral rates to specialised care were derived from the Netherlands Information Network of General Practice (LINH), limited to patients whose data were available from 2006 to 2008 (N = 32,583). Multimorbidity was defined as having two or more out of 28 chronic diseases. Multilevel analyses adjusted for age, gender, and clustering of patients in general practices were used to assess the association between multimorbidity and service utilization in 2008. Results Patients diagnosed with multiple chronic diseases had on average 18.3 contacts (95%CI 16.8 19.9) per year. This was significantly higher than patients with one chronic disease (11.7 contacts (10.8 12.6)) or without any (6.1 contacts (5.6 6.6)). A higher number of chronic diseases was associated with more contacts, more prescriptions, and more referrals to specialized care. However, the number of contacts per disease decreased with an increasing number of diseases, patients with a single disease had between 9 to 17 contacts a year and patients with five or more diseases had 5 or 6 contacts per disease per year. Contact rates for specific combinations of diseases were lower than what would be expected on the basis of contact rates of the separate diseases. Conclusion Multimorbidity is associated with increased health care utilization in general practice, yet the increase declines per additional disease. Still, with the expected rise in multimorbidity in the coming decades more extensive health resources are required. [ABSTRACT FROM AUTHOR]

Background: Chronic mucus hypersecretion (CMH) is associated with an increased frequency of respiratory infections, excess lung function decline, and increased hospitalisation and mortality rates in the general population. It is associated with smoking, but it is unknown why only a minority of smokers develops CMH. A plausible explanation for this phenomenon is a predisposing genetic constitution. Therefore, we performed a genome wide association (GWA) study of CMH in Caucasian populations. Methods: GWA analysis was performed in the NELSON-study using the Illumina 610 array, followed by replication and meta-analysis in 11 additional cohorts. In total 2,704 subjects with, and 7,624 subjects without CMH were included, all current or former heavy smokers (≥20 pack-years). Additional studies were performed to test the functional relevance of the most significant single nucleotide polymorphism (SNP). Results: A strong association with CMH, consistent across all cohorts, was observed with rs6577641 (p = 4.25×10−6, OR = 1.17), located in intron 9 of the special AT-rich sequence-binding protein 1 locus (SATB1) on chromosome 3. The risk allele (G) was associated with higher mRNA expression of SATB1 (4.3×10−9) in lung tissue. Presence of CMH was associated with increased SATB1 mRNA expression in bronchial biopsies from COPD patients. SATB1 expression was induced during differentiation of primary human bronchial epithelial cells in culture. Conclusions: Our findings, that SNP rs6577641 is associated with CMH in multiple cohorts and is a cis-eQTL for SATB1, together with our additional observation that SATB1 expression increases during epithelial differentiation provide suggestive evidence that SATB1 is a gene that affects CMH. [ABSTRACT FROM AUTHOR]

Objectives. To study the prevalence of cardiovascular risk factors among patients attending a rheumatology outpatient clinic in comparison with the general population.Methods. Cross-sectional comparison between a rheumatic outpatient cohort of consecutive patients (n = 1233) between 36 and 75 years of age attending the Arthritis Center Twente (ACT) in the year 2009: RA (n = 546), gout (n = 129), OA (n = 168), CTD (n = 85), PMR (n = 91) and chronic localized or generalized pain syndromes (CPSs; n = 214) and a random sample from a long-lasting population-based health study in the Netherlands (n = 4523). The main outcome measures were hypertension (systolic blood pressure &geq; 140 mmHg and/or a diastolic blood pressure &geq; 90 mmHg and/or the use of antihypertensive medication), abnormal cholesterol profile (total cholesterol &geq; 6.5 mmol/l, and/or high-density lipoprotein < 0.9 mmol/l and/or use of lipid lowering medication), overweight (BMI &geq; 25 kg/m2), obesity (BMI &geq; 30 kg/m2) and cigarette smoking habits (self-reported current smoking).Results. Compared with the general population, patients with rheumatic diseases have a significantly higher prevalence of hypertension (PACT = 68%, Pgeneral = 57%), being overweight (PACT = 72%, Pgeneral = 62%), obesity (PACT = 30%, Pgeneral = 17%) and cigarette smoking (PACT = 26%, Pgeneral = 21%). The worst risk profile was found in gout patients, with higher prevalence of all cardiovascular risk factors studied.Conclusion. Lifestyle-associated potentially modifiable cardiovascular risk factors are over-represented along the whole spectrum of chronic rheumatic diseases, and not only in RA, as suggested by preceding studies. [ABSTRACT FROM PUBLISHER]

Objectives. Data from the Netherlands indicate a recent increase in prevalence of chronic diseases and a stable prevalence of disability, suggesting that diseases have become less disabling. We studied the association between chronic diseases and activity limitations in the Netherlands from 1990 to 2008. Methods. Five surveys among noninstitutionalized persons aged 55 to 84 years (n=54847) obtained self-reported data on chronic diseases (diabetes, heart disease, peripheral arterial disease, stroke, lung disease, joint disease, back problems, and cancer) and activity limitations (Organisation for Economic Cooperation and Development [OECD] long-term disability questionnaire or 36- item Short Form Health Survey [SF-36]). Results. Prevalence rates of chronic diseases increased over time, whereas prevalence rates of activity limitations were stable (OECD) or slightly decreased (SF-36). Associations between chronic diseases and activity limitations were also stable (OECD) or slightly decreased (SF-36). Surveys varied widely with regard to disease and limitation prevalence rates and the associations between them. Conclusions. The hypothesis that diseases became less disabling from 1990 to 2008 was only supported by results based on activity limitation data as assessed with the SF-36. Further research on how diseases and disability are associated over time is needed. [ABSTRACT FROM AUTHOR]

Abstract: Background: The long-term course of long-standing low back pain is largely unknown since long-term data are scarce. Objective: We examined the course of self-reported low back pain in the prospective population-based Doetinchem cohort over a period of 10years. Methods: Between 1993 and 2007, around 5700 randomly selected men and women in four age groups of originally 20–29, 30–39, 40–49, 50–59years were measured three times. Logistic regression analysis was used to study the association of sociodemographic (gender, age, education, work status) and lifestyle characteristics (BMI, smoking, physical activity) with persistent and new episodes of long-standing low back pain. Results: The prevalence of long-standing low back pain is quite stable over a 10year period, approximately 20% on population level. On individual level, around 30% of the population was completely free of low back pain during the entire period, 6% can be characterized as persistent back pain sufferers. Individuals with persistent and a varying pattern have a more unhealthy lifestyle (BMI and smoking) than those without low back pain. Age, smoking, obesity and not having a paid job are associated with 10-year persistent back pain in the general population, whereas age and not having a paid job are associated in those with long-lasting back pain at baseline. New episodes of long-standing back pain are relatively frequent among women and smokers. Conclusions: Low back pain in the population is characterized as very dynamic which challenges epidemiological studies highly. Long-term information on the course of back pain is needed to define severe subgroups. [Copyright &y& Elsevier]

The article presents a study concerning the change in the levels of leisure time physical activity among adults in the Netherlands from 1993-1997, 1998-2002 and 2003-2007. It utilized detailed information from the population-based Doetinchem Cohort Study to define being active. It mentions that 31.4% of the population were active at the three measurement periods, 3.6 were inactive, and 45% changed their physical activity levels. It notes the association of adults staying active with not smoking and high socioeconomic status. It also cites that the change in the level of being active to inactive or vice versa affects the interpretation of the long-term impacts of physical activity. Moreover, it stresses the importance of maintaining a physically active lifestyle.