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Objective: To clarify whether the increase in childhood type 1 diabetes is mirrored by a decrease in older age-groups, resulting in younger age at diagnosis.Research Design and Methods: We used data from two prospective research registers, the Swedish Childhood Diabetes Register, which included case subjects aged 0-14.9 years at diagnosis, and the Diabetes in Sweden Study, which included case subjects aged 15-34.9 years at diagnosis, covering birth cohorts between 1948 and 2007. The total database included 20,249 individuals with diabetes diagnosed between 1983 and 2007. Incidence rates over time were analyzed using Poisson regression models.Results: The overall yearly incidence rose to a peak of 42.3 per 100,000 person-years in male subjects aged 10-14 years and to a peak of 37.1 per 100,000 person-years in female subjects aged 5-9 years and decreased thereafter. There was a significant increase by calendar year in both sexes in the three age-groups <15 years; however, there were significant decreases in the older age-groups (25- to 29-years and 30- to 34-years age-groups). Poisson regression analyses showed that a cohort effect seemed to dominate over a time-period effect.Conclusions: Twenty-five years of prospective nationwide incidence registration demonstrates a clear shift to younger age at onset rather than a uniform increase in incidence rates across all age-groups. The dominance of cohort effects over period effects suggests that exposures affecting young children may be responsible for the increasing incidence in the younger age-groups. [ABSTRACT FROM AUTHOR]

OBJECTIVE: To explore whether perinatal factors are associated with the development of childhood type 1 diabetes. RESEARCH DESIGN AND METHODS: We studied hospital records from 892 cases of childhood type 1 diabetes compared with 2,291 population-based control subjects in seven study centers in Europe. RESULTS: In a pooled analysis incorporating stratification by center, we confirmed the previous findings that older maternal age, maternal preeclampsia, neonatal respiratory disease, and jaundice caused by blood group incompatibility are significant risk factors for type 1 diabetes, whereas being a firstborn child, having a low birth weight, or having a short birth length were protective. Cesarean section delivery and neonatal infectious diseases were not significantly associated with the risk of type 1 diabetes in this study. The strongest association was found for blood group incompatibility (AB0 and Rh factor) with an odds ratio (OR) of 2.96 (95% CI 1.88-4.65). AB0 incompatibility (OR = 3.92) was a more common and also a stronger risk factor than Rh incompatibility (OR = 1.62). The effect of AB0 blood group incompatibility was independent of treatment effects in logistical regression analysis. CONCLUSIONS: Different perinatal events are associated with an increased risk of type 1 diabetes. The effect of maternal-child blood group incompatibility is strong and indicates a true effect that must be further explored. [ABSTRACT FROM AUTHOR]

Background: Stillbirths and neonatal deaths are often the result of a complicated chain of events. For epidemiological purposes a classification into single cause of death groups is essential. For large-scale studies, a method is needed which enables such grouping based on available register data.Methods: A cause of death classification system called NICE is presented. It is hierarchical and is aetiologically orientated. A computerized method is adapted which makes use of data in four central Swedish registries. A validation of the computer method has been made from the medical records on a 10% sample of all stillbirths and neonatally dead infants in Sweden from 1983 to 1990.Results: The specificity of the computer method is high, sensitivity is less satisfactory for some subgroups. A time trend analysis illustrates the usefulness of the classification system and shows a decline with time for two groups: placental abruption and obstetric complications.Conclusions: The NICE classification system fulfils the criteria of an aetiologically orientated classification system which can be used in a computerized environment. [ABSTRACT FROM AUTHOR]

Background: In large-scale epidemiological studies of stillbirths and neonatal deaths a method is needed to replace detailed medical record audits in order to determine the cause of death.Methods: A computer-based method is presented for determination of the cause of death in stillbirths and in neonatal deaths. It utilizes information in the Swedish medical registries. The study comprises 6044 dead infants born in Sweden from 1983-1990. For each infant the program determines 31 basic characteristics which are important in deciding the cause of death. Based on these characteristics a modified Wigglesworth's classification is used to find the cause of death. The validity of the method was checked by comparing the computer generated information with information obtained by scrutinizing medical records for a 10% representative sample (603 infants).Results: Specificity and sensitivity for each basic characteristic varied, but for the modified Wigglesworth cause of death classification the concordance was 88%. The weakest data refer to intrauterine deaths, where pertinent information was often missing in the medical registries.Conclusion: The method can be used for large-scale epidemiological studies. [ABSTRACT FROM AUTHOR]

Aims/hypothesis: The aim of the study was to describe 20-year incidence trends for childhood type 1 diabetes in 23 EURODIAB centres and compare rates of increase in the first (1989-1998) and second (1999-2008) halves of the period., Methods: All registers operate in geographically defined regions and are based on a clinical diagnosis. Completeness of registration is assessed by capture-recapture methodology. Twenty-three centres in 19 countries registered 49,969 new cases of type 1 diabetes in individuals diagnosed before their 15th birthday during the period studied., Results: Ascertainment exceeded 90% in most registers. During the 20-year period, all but one register showed statistically significant changes in incidence, with rates universally increasing. When estimated separately for the first and second halves of the period, the median rates of increase were similar: 3.4% per annum and 3.3% per annum, respectively. However, rates of increase differed significantly between the first half and the second half for nine of the 21 registers with adequate coverage of both periods; five registers showed significantly higher rates of increase in the first half, and four significantly higher rates in the second half., Conclusions/interpretation: The incidence rate of childhood type 1 diabetes continues to rise across Europe by an average of approximately 3-4% per annum, but the increase is not necessarily uniform, showing periods of less rapid and more rapid increase in incidence in some registers. This pattern of change suggests that important risk exposures differ over time in different European countries. Further time trend analysis and comparison of the patterns in defined regions is warranted.

Background: The incidence of type 1 diabetes in children younger than 15 years is increasing. Prediction of future incidence of this disease will enable adequate fund allocation for delivery of care to be planned. We aimed to establish 15-year incidence trends for childhood type 1 diabetes in European centres, and thereby predict the future burden of childhood diabetes in Europe., Methods: 20 population-based EURODIAB registers in 17 countries registered 29 311 new cases of type 1 diabetes, diagnosed in children before their 15th birthday during a 15-year period, 1989-2003. Age-specific log linear rates of increase were estimated in five geographical regions, and used in conjunction with published incidence rates and population projections to predict numbers of new cases throughout Europe in 2005, 2010, 2015, and 2020., Findings: Ascertainment was better than 90% in most registers. All but two registers showed significant yearly increases in incidence, ranging from 0.6% to 9.3%. The overall annual increase was 3.9% (95% CI 3.6-4.2), and the increases in the age groups 0-4 years, 5-9 years, and 10-14 years were 5.4% (4.8-6.1), 4.3% (3.8-4.8), and 2.9% (2.5-3.3), respectively. The number of new cases in Europe in 2005 is estimated as 15 000, divided between the 0-4 year, 5-9 year, and 10-14 year age-groups in the ratio 24%, 35%, and 41%, respectively. In 2020, the predicted number of new cases is 24 400, with a doubling in numbers in children younger than 5 years and a more even distribution across age-groups than at present (29%, 37%, and 34%, respectively). Prevalence under age 15 years is predicted to rise from 94 000 in 2005, to 160 000 in 2020., Interpretation: If present trends continue, doubling of new cases of type 1 diabetes in European children younger than 5 years is predicted between 2005 and 2020, and prevalent cases younger than 15 years will rise by 70%. Adequate health-care resources to meet these children's needs should be made available., Funding: European Community Concerted Action Program.

Aims/hypothesis: We investigated the association between type 1 diabetes and birthweight by age at disease onset., Methods: This population-based case-referent study used data from two nationwide case registers that are linked to the Swedish Medical Birth Registry and cover incident cases of type 1 diabetes in the 0- to 14-year (since 1 July 1977) and 15- to 34-year age groups (since 1 January 1983). Of the cases linked to the Medical Birth Registry, a total of 9,283 cases with onset before 15 years of age was recorded before 1 January 2003, and 1,610 cases were recorded with onset before 30 years of age and born after 1973 (together 95% of eligible cases). Multiple births and babies of diabetic mothers were excluded. Sex-specific birthweight by gestational week is expressed as multiples of the standard deviation (SDS) and adjusted for year of birth, maternal age and parity., Results: Cases with onset before 10 years of age (n = 5,792) showed a significant linear trend in odds ratio (OR) by SDS of adjusted birthweight (OR by SDS: 0.062; 95% CI: 0.037-0.086; p < 0.0001), while cases with onset at the age of 10-29 years showed no significant trend (OR by SDS: 0.004; 95% CI: -0.007 to 0.0014; p = 0.22)., Conclusions/interpretation: The association between type 1 diabetes risk and birthweight seems to be limited to cases with disease onset in younger years.

Objective: Type 1 diabetes has been associated with factors related to welfare and social class. During the past decade, Lithuania has experienced a transition period, leading to dramatic changes in the socioeconomic structure of the society., Research Design and Methods: Incidence in the group aged 0-39 years by urban-rural setting (cities >100000 inhabitants, towns, and rural areas), period (1991-1995 and 1996-2000), age, and sex were studied using Poisson regression., Results: The age- and sex-standardized incidence per 100000 inhabitants per year was higher in men aged 0-39 years than in women (9.5 and 6.9, respectively, incidence rate ratio [IRR] = 1.39, P < 0.001). Incidence was lower in rural areas than in towns and cities (7.1, 9.0, and 8.8, respectively, P < 0.001). The urban-rural differences in incidence were most marked among children aged 0-9 years. From 1991-1995 to 1996-2000, the overall incidence increased from 8.7 to 10.5 (IRR = 1.22, P = 0.001) in men and from 6.2 to 7.8 (IRR = 1.25, P = 0.002) in women. For men, the increase over time occurred predominantly in the cities, from 8.4 to 11.8 (IRR = 1.40, P < 0.001), and in the older age-groups. In contrast, for women, the incidence increased more in small towns and rural areas, from 5.8 to 7.7 (IRR = 1.33, P = 0.003), and in the younger age-groups., Conclusions: The incidence of type 1 diabetes in Lithuania differs depending on the urban-rural setting, and the pattern of change over time differs between the sexes, both by urban-rural setting and age-group. The findings support the theory that lifestyle-related factors connected to socioeconomic status are important for the occurrence of type 1 diabetes.

Objective: To examine the influence of dietary intake from various protein and fat sources on the occurrence of microalbuminuria in type 1 diabetic patients., Research Design and Methods: In this nested case control study, 1,150 patients with diabetes duration >5 years reported dietary habits for the previous 12 months and submitted urinary samples for the analysis of albumin excretion rate (AER). A total of 75 cases of albuminuria (overnight AER > or = 15 microg/min) were identified and compared with 225 duration-matched control subjects., Results: Neither mean protein, fat intake, average fish protein intake (control subjects 4.56 +/- 3.83 g/day and cases 3.82 +/- 2.87 g/day; P = 0.12), nor intake of meat and vegetable protein differed between the cases of albuminuria and the control subjects. High consumers of fish protein (greater than the 75th percentile) (12 cases and 63 control subjects, mean intake 9.35 g fish protein/day, i.e., approximately 53 g fish/day) had lower odds ratios (ORs) for microalbuminuria than individuals consuming less fish protein (mean 2.72 g/day) (crude OR 0.49 and 95% CI 0.25-0.97). When adjusted for known confounding factors, such as HbA1c, mean arterial pressure, diabetes duration, age, sex, smoking, BMI, country region, and total energy, individuals with a high intake of fish protein and fish fat showed a reduction in the risk for microalbuminuria (OR 0.22 and 0.31, respectively; 95% CI 0.09-0.56 and 0.13-0.76, respectively). When fish protein and fat were adjusted for each other, a high intake of fish protein but not of fish fat was still significantly associated with a decrease in the risk for microalbuminuria., Conclusions: Total protein and fat intake were not associated with the presence of microalbuminuria, but a diet including a high amount of fish protein seemed to lessen the risk.

Over the past decade, a large part of type 1 diabetes research has focused on the possibility of preventing the disease. The objective of this article is to analyze which potential and pitfalls different preventive strategies may involve from the individual, epidemiological, and ethical perspectives. Two potential prevention strategies are considered: l) to try to arrest or delay an already ongoing immune destruction of the beta-cells, and 2) to try to intervene with exposures that may initiate this process. In addition to the potential effects of immune modulation, this prevention strategy depends on screening for risk markers. There are inherent ethical problems with screening because of the introduction of awareness of risk in healthy individuals and also because false positivity, the rate of which differs tremendously in high- and low-risk groups. Because of these latter circumstances, the most promising low-risk preventive treatments presently used in trials, i.e., nicotinamide and insulin, will probably only be feasible in high-risk groups, such as family members, though this group covers only 10-15% of potential cases. The second strategy aiming at eradicating environmental initiators of the beta-cell destruction will avoid the problem of screening and approach a total population at risk. Potential risk factors, such as food components (cow's milk proteins, gliadin or nitroso products) or different viruses, are indicated by animal and epidemiological studies. So far, however, no single environmental risk factor has been proven to be necessary and certainly not sufficient for the disease causation, and the etiological fractions estimated in population-based studies are low. It is concluded that more basic research is warranted before effective and safe prevention can be introduced for type 1 diabetes. Most probably, different preventive strategies must be applied to different groups and populations and in different phases of the beta-cell destruction.

There is strong evidence that the aetiology of insulin-dependent diabetes mellitus (IDDM) is due to a complex interaction between genes and the environment and that the pathogenesis is autoimmune. In early perinatal life the immune system is induceable and exposures in this period may initiate autoimmunity. Recent findings of time and space clustering of birth dates for later diabetic cases together with the early observation of a very high prevalence of diabetes in cases with rubella embryopathy suggest that foetal virus exposure may be important. Recent findings from Sweden and Finland suggest that enterovirus exposure during foetal life may initiate autoimmunity which may lead to diabetes. Other immune events, such as maternal-foetal blood group incompatibility and pre-eclampsia in the mother have also been associated with IDDM risk. Other more unspecific events in the perinatal period, such as a short gestational age, caesarean section and neonatal respiratory disease, are also indicated to increase the risk. In addition, food components such as nitrosamine components, cow's milk protein and gliadin have been proposed to initiate the slowly progressing autoimmune beta-cell destruction. Most of these epidemiological findings are supported by experimental studies in the nonobese diabetic mice but their exact mechanisms of action are still unclear. It is concluded that new evidence is accumulating indicating that perinatal exposures may be important for the initiation of beta-cell destruction. As such risk factors may be targets for primary prevention strategies further studies are urgently warranted.

Objective: To investigate whether there was a temporal and geographical clustering of time of birth for infants with childhood-onset diabetes., Research Design and Methods: The nationwide Swedish Childhood Diabetes Registry, which ascertains 99% of children with recent-onset diabetes (0-14 years), was linked with the Swedish Medical Birth Registry. Clustering of 3,725 patients as to place and time of birth was studied compared with the general population. For each municipality (and in the three large cities of Sweden for each parish), the observed number of patients was compared with the expected number calculated from the average total rate and the number of births in that municipality. Clustering in time of birth within municipality was analyzed using a modification of a set technique by Chen (14)., Results: There was no consistent variability in diabetes risk by calendar birth month, but for specific years, the risk varied during the year. When geographic localization for place of birth was studied on a municipality level, four municipalities showed a statistically significant case excess while one would have been expected by chance. When we looked for clusters in both time and space for date of birth, clearly more clusters than expected were identified (P < 0.01). Of the total of 198 primary clusters, 42 included three or more patients being born in the same municipality within an unlikely short period always < 2 years., Conclusions: This is the first study indicating a clustering according to place and time of birth for later risk to develop type I diabetes. Such a phenomenon would agree with the hypothesis that infections in early life, including fetal infections, can increase the risk for diabetes.

Objective: To compare characteristics at clinical onset of childhood-onset diabetes patients with and without a first-degree relative with childhood-onset insulin-dependent diabetes mellitus (IDDM)., Research Design and Methods: In a nationwide continuous incident diabetes register covering patients from 0 to 14 years of age with a high level of ascertainment, we compared 687 patients who at onset had at least one first-degree relative with insulin-treated diabetes with 5,137 patients without such relatives., Results: The pattern of change over the 15-year period was similar among familial- and sporadic-case patients. The seasonal pattern, with a lower incidence during the warmer period of the year, was similar in both groups. Age at clinical onset was also similar in both groups in either sex. When the proband had a sibling who already had the disease, the mean age at onset was significantly higher when compared with sporadic-case or other familial-case patients., Conclusions: This analysis of a very large set of population-based cases of childhood diabetes showed that patients who had one first-degree relative with insulin-treated diabetes at onset shared the onset characteristics of those without such family members, including age at onset, sex ratio, seasonality, and secular trend. The findings may indicate that the complex interactions between genetic and nongenetic risk factors subsequently leading to IDDM are mainly shared by familial- and sporadic-case patients.

Glucose-stimulated insulin and proinsulin responses, and insulin sensitivity, were studied in 30 HLA identical, 38 HLA haplo-identical, and 25 HLA non-identical, healthy islet-cell-antibody negative siblings of Type 1 diabetic patients. The results were compared with 41 age- and sex-matched healthy subjects with no diabetes in the family. The proinsulin-corrected insulin response to an intravenous glucose infusion test was significantly lower among siblings when insulin sensitivity was taken into account (1.65 (inter-quartile range 1.20-2.64) vs 2.18 (1.65-3.28) nmol mmol-1 min, p = 0.04). Proinsulin values were consistently higher among siblings than among control subjects (peak values 50.0 vs 38.0 pmol l-1 (p = 0.004)). When proinsulin release was corrected for individual insulin sensitivity this difference remained. The results suggest disturbed islet B-cell function, unrelated to HLA identity or the presence of circulating islet cell antibodies.

Objective: To study different nutrients and food additives as risk factors for insulin dependent diabetes mellitus in childhood., Design: Prospective case-control study. Parents of the children being studied were asked to fill in a questionnaire regarding the children's frequency of consumption of various foods. Parents of children with diabetes were asked about the period before onset of the disease., Setting: Population based study throughout Sweden., Subjects: 339 Children aged 0-14 who had recently developed insulin dependent diabetes mellitus and 528 control children matched for age, sex, and county of residence who were traced through the official Swedish population register., Main Outcome Measures: Foods were classified according to their content of protein, fat, carbohydrates, monosaccharides or disaccharides, nitrosamines, nitrates or nitrites, vitamin C, and fibres. The frequency of intake was categorised as high, medium, and low and the relative risk for developing insulin dependent diabetes was estimated for the three frequencies of intake and calculated as odds ratios., Results: Significant linear trends for dose response in odds ratios by frequency of intake were shown for solid foods containing high amounts of protein (odds ratio for low frequency of intake 1.0; medium 2.3; and high 5.5), and nitrosamines (1.0; 1.7; 2.6) and significant but non-linear trends were found for carbohydrates (1.0; 1.3; 4.4) and nitrates or nitrites (1.0; 0.8; 2.4). The significant trends were not affected when the results were standardised for possible confounders. No significant increases in odds ratios were found for protein, monosaccharides and disaccharides, vitamin C, and fibres., Conclusion: Nutrients and food additives such as protein, carbohydrate, and nitrosamine compounds may influence the risk of developing insulin dependent diabetes in childhood and significant trends in odds ratios indicate a causal relation.