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BACKGROUND: Undiagnosed type 2 diabetes (T2D) is a global problem. Current strategies for diagnosis in Sweden include screening individuals within primary healthcare who are of high risk, such as those with hypertension, obesity, prediabetes, family history of diabetes, or those who smoke daily. In this study, we aimed to estimate the proportion of individuals with undiagnosed T2D in Stockholm County and factors associated with T2D being diagnosed by healthcare. This information could improve strategies for detection. METHODS: We used data from the Stockholm Diabetes Prevention Programme (SDPP) cohort together with information from national and regional registers. Individuals without T2D aged 35-56 years at baseline were followed up after two ten-year periods. The proportion of diagnosed T2D was based on register information for 7664 individuals during period 1 and for 5148 during period 2. Undiagnosed T2D was assessed by oral glucose tolerance tests at the end of each period. With logistic regression, we analysed factors associated with being diagnosed among individuals with T2D. RESULTS: At the end of the first period, the proportion of individuals with T2D who had been diagnosed with T2D or not was similar (54.0% undiagnosed). At the end of the second period, the proportion of individuals with T2D was generally higher, but they were less likely to be undiagnosed (43.5%). The likelihood of being diagnosed was in adjusted analyses associated with overweight (OR=1.85; 95% CI 1.22-2.80), obesity (OR=2.73; 95% CI 1.76-4.23), higher fasting blood glucose (OR=2.11; 95% CI 1.67-2.66), and self-estimated poor general health (OR=2.42; 95% CI 1.07-5.45). Socioeconomic factors were not associated with being diagnosed among individuals with T2D. Most individuals (>71%) who developed T2D belonged to risk groups defined by having at least two of the prominent risk factors obesity, hypertension, daily smoking, prediabetes, or family history of T2D, including individuals with T2D who had not been diagnosed by healthcare. CONCLUSIONS: Nearly half of individuals who develop T2D during 10 years in Stockholm County are undiagnosed, emphasizing a need for intensified screening of T2D within primary healthcare. Screening can be targeted to individuals who have at least two prominent risk factors.
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Diabetes Mellitus Tipo 2 , Hipertensão , Estado Pré-Diabético , Humanos , Diabetes Mellitus Tipo 2/diagnóstico , Diabetes Mellitus Tipo 2/epidemiologia , Estado Pré-Diabético/diagnóstico , Estado Pré-Diabético/epidemiologia , Suécia/epidemiologia , Programas de Rastreamento , Fatores de Risco , Obesidade/diagnóstico , Obesidade/epidemiologia , Obesidade/complicações , Hipertensão/complicaçõesRESUMO
Background Colon cancer incidence is rising globally, and factors pertaining to urbanization have been proposed involved in this development. Traffic noise may increase colon cancer risk by causing sleep disturbance and stress, thereby inducing known colon cancer risk-factors, e.g. obesity, diabetes, physical inactivity, and alcohol consumption, but few studies have examined this. Objectives The objective of this study was to investigate the association between traffic noise and colon cancer (all, proximal, distal) in a pooled population of 11 Nordic cohorts, totaling 155,203 persons. Methods We identified residential address history and estimated road, railway, and aircraft noise, as well as air pollution, for all addresses, using similar exposure models across cohorts. Colon cancer cases were identified through national registries. We analyzed data using Cox Proportional Hazards Models, adjusting main models for harmonized sociodemographic and lifestyle data. Results During follow-up (median 18.8 years), 2757 colon cancer cases developed. We found a hazard ratio (HR) of 1.05 (95% confidence interval (CI): 0.99-1.10) per 10-dB higher 5-year mean time-weighted road traffic noise. In sub-type analyses, the association seemed confined to distal colon cancer: HR 1.06 (95% CI: 0.98-1.14). Railway and aircraft noise was not associated with colon cancer, albeit there was some indication in sub-type analyses that railway noise may also be associated with distal colon cancer. In interaction-analyses, the association between road traffic noise and colon cancer was strongest among obese persons and those with high NO2-exposure. Discussion A prominent study strength is the large population with harmonized data across eleven cohorts, and the complete address-history during follow-up. However, each cohort estimated noise independently, and only at the most exposed façade, which may introduce exposure misclassification. Despite this, the results of this pooled study suggest that traffic noise may be a risk factor for colon cancer, especially of distal origin.
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Poluição do Ar , Neoplasias do Colo , Ruído dos Transportes , Humanos , Estudos de Coortes , Fatores de Risco , Exposição Ambiental/análise , Dinamarca/epidemiologiaRESUMO
BACKGROUND: The prevention of type 2 diabetes is challenging due to the variable effects of risk factors at an individual level. Data-driven methods could be useful to detect more homogeneous groups based on risk factor variability. The aim of this study was to derive characteristic phenotypes using cluster analysis of common risk factors and to assess their utility to stratify the risk of type 2 diabetes. METHODS: Data on 7317 diabetes-free adults from Sweden were used in the main analysis and on 2332 diabetes-free adults from Mexico for external validation. Clusters were based on sex, family history of diabetes, educational attainment, fasting blood glucose and insulin levels, estimated insulin resistance and ß-cell function, systolic and diastolic blood pressure, and BMI. The risk of type 2 diabetes was assessed using Cox proportional hazards models. The predictive accuracy and long-term stability of the clusters were then compared to different definitions of prediabetes. RESULTS: Six risk phenotypes were identified independently in both cohorts: very low-risk (VLR), low-risk low ß-cell function (LRLB), low-risk high ß-cell function (LRHB), high-risk high blood pressure (HRHBP), high-risk ß-cell failure (HRBF), and high-risk insulin-resistant (HRIR). Compared to the LRHB cluster, the VLR and LRLB clusters showed a lower risk, while the HRHBP, HRBF, and HRIR clusters showed a higher risk of developing type 2 diabetes. The high-risk clusters, as a group, had a better predictive accuracy than prediabetes and adequate stability after 20 years. CONCLUSIONS: Phenotypes derived using cluster analysis were useful in stratifying the risk of type 2 diabetes among diabetes-free adults in two independent cohorts. These results could be used to develop more precise public health interventions.
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Diabetes Mellitus Tipo 2 , Estado Pré-Diabético , Glicemia , Diabetes Mellitus Tipo 2/diagnóstico , Diabetes Mellitus Tipo 2/epidemiologia , Humanos , Insulina , Medição de Risco , Fatores de RiscoRESUMO
Background: Many individuals with hypertension remain undiagnosed. We aimed to develop a predictive model for hypertension using diagnostic codes from prevailing electronic medical records in Swedish primary care. Methods: This sex- and age-matched case-control (1:5) study included patients aged 30-65 years living in the Stockholm Region, Sweden, with a newly recorded diagnosis of hypertension during 2010-19 (cases) and individuals without a recorded hypertension diagnosis during 2010-19 (controls), in total 507,618 individuals. Patients with diagnoses of cardiovascular diseases or diabetes were excluded. A stochastic gradient boosting machine learning model was constructed using the 1,309 most registered ICD-10 codes from primary care for three years prior the hypertension diagnosis. Results: The model showed an area under the curve (95 % confidence interval) of 0.748 (0.742-0.753) for females and 0.745 (0.740-0.751) for males for predicting diagnosis of hypertension within three years. The sensitivity was 63 % and 68 %, and the specificity 76 % and 73 %, for females and males, respectively. The 25 diagnoses that contributed the most to the model for females and males all exhibited a normalized relative influence >1 %. The codes contributing most to the model, all with an odds ratio of marginal effects >1 for both sexes, were dyslipidaemia, obesity, and encountering health services in other circumstances. Conclusions: This machine learning model, using prevailing recorded diagnoses within primary health care, may contribute to the identification of patients at risk of unrecognized hypertension. The added value of this predictive model beyond information of blood pressure warrants further study.
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Background: Available evidence suggests a link between exposure to transportation noise and an increased risk of obesity. We aimed to assess exposure-response functions for long-term residential exposure to road traffic, railway and aircraft noise, and markers of obesity. Methods: Our cross-sectional study is based on pooled data from 11 Nordic cohorts, including up to 162,639 individuals with either measured (69.2%) or self-reported obesity data. Residential exposure to transportation noise was estimated as a time-weighted average Lden 5 years before recruitment. Adjusted linear and logistic regression models were fitted to assess beta coefficients and odds ratios (OR) with 95% confidence intervals (CI) for body mass index, overweight, and obesity, as well as for waist circumference and central obesity. Furthermore, natural splines were fitted to assess the shape of the exposure-response functions. Results: For road traffic noise, the OR for obesity was 1.06 (95% CI = 1.03, 1.08) and for central obesity 1.03 (95% CI = 1.01, 1.05) per 10 dB Lden. Thresholds were observed at around 50-55 and 55-60 dB Lden, respectively, above which there was an approximate 10% risk increase per 10 dB Lden increment for both outcomes. However, linear associations only occurred in participants with measured obesity markers and were strongly influenced by the largest cohort. Similar risk estimates as for road traffic noise were found for railway noise, with no clear thresholds. For aircraft noise, results were uncertain due to the low number of exposed participants. Conclusion: Our results support an association between road traffic and railway noise and obesity.
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BACKGROUND: Transportation noise may induce cardiovascular disease, but the public health implications are unclear. OBJECTIVES: The study aimed to assess exposure-response relationships for different transportation noise sources and ischemic heart disease (IHD), including subtypes. METHODS: Pooled analyses were performed of nine cohorts from Denmark and Sweden, together including 132,801 subjects. Time-weighted long-term exposure to road, railway, and aircraft noise, as well as air pollution, was estimated based on residential histories. Hazard ratios (HRs) were calculated using Cox proportional hazards models following adjustment for lifestyle and socioeconomic risk factors. RESULTS: A total of 22,459 incident cases of IHD were identified during follow-up from national patient and mortality registers, including 7,682 cases of myocardial infarction. The adjusted HR for IHD was 1.03 [95% confidence interval (CI) 1.00, 1.05] per 10 dB Lden for both road and railway noise exposure during 5 y prior to the event. Higher risks were indicated for IHD excluding angina pectoris cases, with HRs of 1.06 (95% CI: 1.03, 1.08) and 1.05 (95% CI: 1.01, 1.08) per 10 dB Lden for road and railway noise, respectively. Corresponding HRs for myocardial infarction were 1.02 (95% CI: 0.99, 1.05) and 1.04 (95% CI: 0.99, 1.08). Increased risks were observed for aircraft noise but without clear exposure-response relations. A threshold at around 55 dB Lden was suggested in the exposure-response relation for road traffic noise and IHD. DISCUSSION: Exposure to road, railway, and aircraft noise in the prior 5 y was associated with an increased risk of IHD, particularly after exclusion of angina pectoris cases, which are less well identified in the registries. https://doi.org/10.1289/EHP10745.
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Infarto do Miocárdio , Isquemia Miocárdica , Ruído dos Transportes , Humanos , Ruído dos Transportes/efeitos adversos , Exposição Ambiental , Isquemia Miocárdica/epidemiologia , Infarto do Miocárdio/epidemiologia , Angina PectorisRESUMO
BACKGROUND: Environmental noise is an important environmental exposure that can affect health. An association between transportation noise and breast cancer incidence has been suggested, although current evidence is limited. We investigated the pooled association between long-term exposure to transportation noise and breast cancer incidence. METHODS: Pooled data from eight Nordic cohorts provided a study population of 111,492 women. Road, railway, and aircraft noise were modelled at residential addresses. Breast cancer incidence (all, estrogen receptor (ER) positive, and ER negative) was derived from cancer registries. Hazard ratios (HR) were estimated using Cox Proportional Hazards Models, adjusting main models for sociodemographic and lifestyle variables together with long-term exposure to air pollution. RESULTS: A total of 93,859 women were included in the analyses, of whom 5,875 developed breast cancer. The median (5th-95th percentile) 5-year residential road traffic noise was 54.8 (40.0-67.8) dB Lden, and among those exposed, the median railway noise was 51.0 (41.2-65.8) dB Lden. We observed a pooled HR for breast cancer (95 % confidence interval (CI)) of 1.03 (0.99-1.06) per 10 dB increase in 5-year mean exposure to road traffic noise, and 1.03 (95 % CI: 0.96-1.11) for railway noise, after adjustment for lifestyle and sociodemographic covariates. HRs remained unchanged in analyses with further adjustment for PM2.5 and attenuated when adjusted for NO2 (HRs from 1.02 to 1.01), in analyses using the same sample. For aircraft noise, no association was observed. The associations did not vary by ER status for any noise source. In analyses using <60 dB as a cutoff, we found HRs of 1.08 (0.99-1.18) for road traffic and 1.19 (0.95-1.49) for railway noise. CONCLUSIONS: We found weak associations between road and railway noise and breast cancer risk. More high-quality prospective studies are needed, particularly among those exposed to railway and aircraft noise before conclusions regarding noise as a risk factor for breast cancer can be made.
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Neoplasias da Mama , Ruído dos Transportes , Humanos , Feminino , Ruído dos Transportes/efeitos adversos , Estudos de Coortes , Neoplasias da Mama/epidemiologia , Neoplasias da Mama/etiologia , Fatores de Risco , Estudos Prospectivos , Exposição Ambiental/efeitos adversos , Exposição Ambiental/análiseRESUMO
Although exposure to overweight and obesity at different ages is associated to a higher risk of type 2 diabetes, the effect of different patterns of exposure through life remains unclear. We aimed to characterize life-course trajectories of weight categories and estimate their impact on the incidence of type 2 diabetes. We categorized the weight of 7203 participants as lean, normal or overweight at five time-points from ages 7-55 using retrospective data. Participants were followed for an average of 19 years for the development of type 2 diabetes. We used latent class analysis to describe distinctive trajectories and estimated the risk ratio, absolute risk difference and population attributable fraction (PAF) associated to different trajectories using Poisson regression. We found five distinctive life-course trajectories. Using the stable-normal weight trajectory as reference, the stable overweight, lean increasing weight, overweight from early adulthood and overweight from late adulthood trajectories were associated to higher risk of type 2 diabetes. The estimated risk ratios and absolute risk differences were statistically significant for all trajectories, except for the risk ratio of the lean increasing trajectory group among men. Of the 981 incident cases of type 2 diabetes, 47.4% among women and 42.9% among men were attributable to exposure to any life-course trajectory different from stable normal weight. Most of the risk was attributable to trajectories including overweight or obesity at any point of life (36.8% of the cases among women and 36.7% among men). The overweight from early adulthood trajectory had the highest impact (PAF: 23.2% for woman and 28.5% for men). We described five distinctive life-course trajectories of weight that were associated to increased risk of type 2 diabetes over 19 years of follow-up. The variability of the effect of exposure to overweight and obesity on the risk of developing type 2 diabetes was largely explained by exposure to the different life-course trajectories of weight.
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Trajetória do Peso do Corpo , Diabetes Mellitus Tipo 2/epidemiologia , Obesidade/epidemiologia , Sobrepeso/epidemiologia , Adolescente , Adulto , Criança , Feminino , Seguimentos , Humanos , Incidência , Estudos Longitudinais , Masculino , Pessoa de Meia-Idade , Obesidade/diagnóstico , Sobrepeso/diagnóstico , Distribuição de Poisson , Estudos Retrospectivos , Fatores de Risco , Autorrelato/estatística & dados numéricos , Adulto JovemRESUMO
(1) Background: Cardiometabolic diseases are the most common cause of death worldwide. As part of a collaborative European study, this paper aims to explore the implementation of primary care selective-prevention services in five European countries. We assessed the implementation process of the selective-prevention services, participants' cardiometabolic profile and risk and participants' evaluation of the services, in terms of feasibility and impact in promoting a healthy lifestyle. (2) Methods: Eligible participants were primary care patients, 40-65 years of age, without any diagnosis of cardiometabolic disease. Two hundred patients were invited to participate per country. The extent to which participants adopted and completed the implementation of selective-prevention services was recorded. Patient demographics, lifestyle-related cardiometabolic risk factors and opinions on the implementation's feasibility were also collected. (3) Results: Acceptance rates varied from 19.5% (n = 39/200) in Sweden to 100% (n = 200/200) in the Czech Republic. Risk assessment completion rates ranged from 65.4% (n = 70/107) in Greece to 100% (n = 39/39) in Sweden. On a ten-point scale, the median (25-75% quartile) of participant-reported implementation feasibility ranged from 7.4 (6.9-7.8) in Greece to 9.2 (8.2-9.9) in Sweden. Willingness to change lifestyle exceeded 80% in all countries. (4) Conclusions: A substantial variation in the implementation of selective-prevention receptiveness and patient risk profile was observed among countries. Our findings suggest that the design and implementation of behavior change cardiometabolic programmes in each country should be informed by the local context and provide some background evidence towards this direction, which can be even more relevant during the current pandemic period.
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Doenças Cardiovasculares , Atenção Primária à Saúde , Adulto , Idoso , Doenças Cardiovasculares/epidemiologia , Doenças Cardiovasculares/prevenção & controle , República Tcheca , Europa (Continente) , Feminino , Grécia , Humanos , Masculino , Pessoa de Meia-Idade , Suécia/epidemiologiaRESUMO
INTRODUCTION: Previous Icelandic studies have reported higher prevalence of obesity among women residing outside the capital area but no comparable information is available for men. The aim of this study was to assess diet and body mass index (BMI) of adult men and women residing within and outside the capital area. MATERIAL AND METHODS: Participants were 1312 men and women,18-80 years, from a random sample of the national registry, response rate 68.6%. Diet was assessed during years 2010 to 2011 using repeated 24-hour recall, weight and height self-reported. OR of BMI≥25 kg/m2 was calculated according to residence and education. RESULTS: Women≥46 years within the capital area had lower BMI, or 25.7 kg/m2 vs 28.4 kg/m2 p=0.007, and were less likely to have BMI>25 kg/m2, OR=0.64; CI 0.41-1.0 than those outside the area. No difference was found between the areas among men or younger women. Diets outside the capital had higher percentage of total fat compared than inside the capital. Saturated fatty acid (SFA) were 15.7E% vs 13.9E% for men, p<0.001 and 14.8E% vs 14.0E%, p=0.007 for women and trans fatty acids (TFA) were 0.9E% vs 0.7E% p%lt;0.001 and 0.8E% vs 0.7E% p=0.001 for men and women respectively. CONCLUSIONS: Women's BMI is less associated with residence than in former Icelandic studies. Men's BMI is not associated with residence. Diets within the capital area are closer to recommended intake compared with diets outside the area.