M Karvonen

National Institute for Health and Welfare, Finland, Helsinki, Province of Southern Finland, Finland

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Publications (73)442.47 Total impact

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    ABSTRACT: Background: From the mid-1980s to mid-1990s, the WHO MONICA Project monitored coronary events and classic risk factors for coronary heart disease (CHD) in 38 populations from 21 countries. We assessed the extent to which changes in these risk factors explain the variation in the trends in coronary-event rates across the populations. Methods: In men and women aged 35—64 years, non-fatal myocardial infarction and coronary deaths were registered continuously to assess trends in rates of coronary events. We carried out population surveys to estimate trends in risk factors. Trends in event rates were regressed on trends in risk score and in individual risk factors. Findings: Smoking rates decreased in most male populations but trends were mixed in women; mean blood pressures and cholesterol concentrations decreased, bodymass index increased, and overall risk scores and coronary-event rates decreased. The model of trends in 10-year coronary-event rates against risk scores and single risk factors showed a poor fit, but this was improved with a 4-year time lag for coronary events. The explanatory power of the analyses was limited by imprecision of the estimates and homogeneity of trends in the study populations. Interpretation: Changes in the classic risk factors seem to partly explain the variation in population trends in CHD. Residual variance is attributable to difficulties in measurement and analysis, including time lag, and to factors that were not included, such as medical interventions. The results support prevention policies based on the classic risk factors but suggest potential for prevention beyond these.
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    ABSTRACT: SUMMARY: The WHO MONICA Project is designed to measure the trends in mortality and morbidity from coronary heart disease (CHD) and stroke, and to assess the extent to which they are related to changes in known risk factors in different populations in 27 countries. Risk-factor data are collected from population samples examined in at least two population surveys (one at the beginning of the study and the other at the end). The results of the baseline population surveys are presented. In populations studied, the proportion of smokers varied between 34-62% among men and 3-52% among women. The population median of systolic blood pressure varied between 121-146 mmHg in men. In women the figures were 118 mmHg and 141 mmHg respectively. In diastolic blood pressure, the variation of median was from 74 mmHg to over 91 mmHg among men and from 72-89 mmHg among women. The third major risk factor considered was total cholesterol, with the population median ranging between 4.1-6.4 mmol/l among men and 4.2-6.3 mmol/l among women. Caution is required when making cross-sectional comparisons between the risk-factor levels as the MONICA Project was not designed for this purpose. Nevertheless, these data demonstrate clearly the large variety of baseline risk-factor patterns in populations studied in the MONICA Project. MeSH Terms: Adult; Australia; Blood Pressure; Body Weight; China; Cholesterol/blood; Coronary Disease/etiology*; Data Interpretation, Statistical; Europe; Female; Humans; Male; Middle Aged; Population Surveillance*; Quality Control; Risk Factors; Smoking/statistics & numerical data; USSR; World Health Organization; Substances: Cholesterol
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    ABSTRACT: To determine if there is a worldwide seasonal pattern in the clinical onset of Type 1 diabetes. Analysis of the seasonality in diagnosis of Type 1 diabetes was based on the incidence data in 0- to 14-year-old children collected by the World Health Organization Diabetes Mondiale (WHO DiaMond) Project over the period 1990-1999. One hundred and five centres from 53 countries worldwide provided enough data for the seasonality analysis. The incidence seasonality patterns were also determined for age- and sex-specific groups. Forty-two out of 105 centres exhibited significant seasonality in the incidence of Type 1 diabetes (P < 0.05). The existence of significant seasonal patterns correlated with higher level of incidence and of the average yearly counts. The correlation disappeared after adjustment for latitude. Twenty-eight of those centres had peaks in October to January and 33 had troughs in June to August. Two out of the four centres with significant seasonality in the southern hemisphere demonstrated a different pattern with a peak in July to September and a trough in January to March. The seasonality of the incidence of Type 1 diabetes mellitus in children under 15 years of age is a real phenomenon, as was reported previously and as is now demonstrated by this large standardized study. The seasonality pattern appears to be dependent on the geographical position, at least as far as the northern/southern hemisphere dichotomy is concerned. However, more data are needed on the populations living below the 30th parallel north in order to complete the picture.
    Diabetic Medicine 08/2009; 26(7):673-8. · 3.24 Impact Factor
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    ABSTRACT: The aim of this study was to examine the effects of childhood BMI growth dynamics on the risk of developing young adult-onset type 1 and type 2 diabetes. Finnish national healthcare registers were used to identify individuals with diabetes diagnosed between 1992 and 1996 at 15-39 years of age. Non-diabetic control participants were chosen from the National Population Registry. Anthropometric measurements were obtained from the original child welfare clinic records. Only the case-control pairs with sufficient growth data recorded were included in the analyses (218/1,388 for type 1 diabetes [16%] and 64/1,121 for type 2 diabetes [6%]). Two developmental stages in BMI growth (the points of infancy maximum BMI and the BMI rebound) were examined, and conditional logistic regression was applied to the variables of interest. The risk for type 1 diabetes increased 1.19-fold per 1 kg/m(2) rise in the infancy maximum BMI (p = 0.02). In addition, there was a 1.77-fold increase in the risk for type 2 diabetes per 1 kg/m(2) rise in the level of BMI at the BMI rebound (p = 0.04). Higher values of BMI at these points corresponded to a larger BMI gain from birth to that developmental stage. Age at the infancy maximum BMI or age at the BMI rebound did not affect the risk for either type of diabetes. The BMI gain in infancy among individuals who subsequently developed young adult-onset type 1 diabetes was faster than that of those who remained healthy. The excess BMI gain in individuals who developed young adult-onset type 2 diabetes could already be seen during early childhood.
    Diabetologia 02/2009; 52(3):408-14. · 6.49 Impact Factor
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    Diabetologia 06/2008; 51(5):897-9. · 6.49 Impact Factor
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    ABSTRACT: The protective role of water hardness and Mg in cardiovascular illness has been suggested in several epidemiological studies. In the present ecological study, the association of Ca, Mg, Al, Cu, F, Fe, Zn and NO3 in local ground water and spatial variation of acute myocardial infarction (AMI) incidence among men and women 35–74 years of age in rural Finland in 1991–2003 were examined. Data on AMI cases, 67,755 men and 25,450 women, were obtained from the Finnish Cardiovascular Disease Register. The statistical analysis was carried out using Bayesian modeling. 10 × 10 km grid cells were used instead of administrative boundaries to partition the study area. On average, 1 mg/L increment in Mg level in local ground water was associated with 2% (95% HDR −0.0391, −0.0028) decrease in incidence of AMI in the rural population. In conclusion, high AMI incidence in eastern Finland is associated with soft ground water, low in Mg.
    Applied Geochemistry. 04/2008;
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    ABSTRACT: The aim of this study was to examine the effects of birth order and parental age on the risk of type 1 and type 2 diabetes among Finnish individuals aged 15-39 years. Data on all cases of type 1 diabetes (n = 1,345) and type 2 diabetes (n = 1,072), diagnosed between 1992 and 1996, were collected from four sources: standardised national reports from diabetes nurses, the National Hospital Discharge Register, the Drug Prescription Register and the Drug Reimbursement Register. Information on matched controls and the family members of all study subjects were obtained from the National Population Registry. The odds ratios (ORs) for both types of diabetes were estimated using a conditional logistic regression model. There was a U-shaped relationship between maternal age and the risk of type 2 diabetes in the offspring: the risk was higher in children born to young and old mothers compared with children born to mothers aged around 30 years. The children born second (OR 0.76, 95% CI 0.62-0.94), third (OR 0.73, 95% CI 0.55-0.95), or fourth (OR 0.66, 95% CI 0.47-0.94) had a lower risk of type 2 diabetes than the first-born children. Maternal age, paternal age, and birth order did not have an effect on the risk of type 1 diabetes in the individuals aged 15-39 years at the time of diagnosis. Maternal age and birth order are both associated with the risk of early-onset type 2 diabetes. However, part of these associations may be due to low birthweight. In this study neither parental age nor birth order showed a significant association with the risk of type 1 diabetes diagnosed after 15 years of age.
    Diabetologia 01/2008; 50(12):2433-8. · 6.49 Impact Factor
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    ABSTRACT: The aim of this study was to examine the incidence and trends of type 1 and type 2 diabetes in the 15-39 year-old population between 1992 and 1996 in Finland. Data on the nationwide incidence of diabetes were obtained from four data sources: standardised reports from diabetes nurses, the Finnish National Hospital Discharge Register, the Drug Reimbursement Register and the Drug Prescription Register. The inclusion criterion was consistency in the diagnosis of diabetes across at least two data sources. The sex- and age-specific incidence was calculated for 5-year age groups, both for type 1 and type 2 diabetes. The effects of age, sex and year of diagnosis were assessed by fitting the linear regression model to the incidence data. Between 1992 and 1996 the age-adjusted incidence of type 1 diabetes among 15-39 year olds was 15.9 per 100,000/year. The incidence was highest among the 15-19 year olds and decreased with age. Conversely, the incidence of type 2 diabetes was very low among 15-19 year olds and increased with age. The total age-adjusted incidence of type 2 diabetes among 15-39 year olds was 11.8 per 100,000/year. The average annual increase in the incidence of type 2 diabetes was 7.9% (95% CI 3.7-12.2%). The age at which the Finnish population is at risk of type 1 diabetes extends into young adulthood. The rapid increase in the incidence of type 2 diabetes in the young adult population is a current public health problem.
    Diabetologia 08/2007; 50(7):1393-400. · 6.49 Impact Factor
  • E Moltchanova, A Penttinen, M Karvonen
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    ABSTRACT: Childhood diabetes is one of the major non-communicable diseases in children under 15 years of age. It requires a life-long insulin treatment and may lead to serious complications. Along with the worldwide increase in the incidence several countries have recently reported a decreasing trend in the age of onset of the disease. The aim of this study is to analyse long-term data on the incidence of the childhood diabetes in Finland from the birth cohorts perspective. The annual incidence data were available for the period 1965--1996 which translates into 1951--1996 birth cohorts. Hence the data consist of completely and partially observed cohorts. Bayesian modelling was employed in the analysis. Several different priors and cohort combinations were tried in order to determine the sensitivity of the results. The cumulative birth cohort incidence of diabetes was determined to have an increasing average annual trend of 2.5 per cent. Although the average birth cohort-specific age of onset was estimated to have decreased slightly over the years of observation, the trend could be a result of random variation.
    Statistics in Medicine 11/2005; 24(19):2989-3004. · 2.04 Impact Factor
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    ABSTRACT: In this paper present two methods of estimating the trend, seasonality and noise in time series of coronary heart disease events. In contrast to previous work we use a non-linear trend, allow multiple seasonal components, and carefully examine the residuals from the fitted model. We show the importance of estimating these three aspects of the observed data to aid insight of the underlying process, although our major focus is on the seasonal components. For one method we allow the seasonal effects to vary over time and show how this helps the understanding of the association between coronary heart disease and varying temperature patterns.
    Statistics in Medicine 11/2004; 23:3505-3523. · 2.04 Impact Factor
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    ABSTRACT: In Finland, the risk of childhood Type 1 diabetes varies geographically. Therefore we investigated the association between spatial variation of Type 1 diabetes and its putative environmental risk factors, zinc and nitrates. The association was evaluated using Bayesian modelling and the geo-referenced data on diabetes cases and population. Neither zinc nor nitrate nor the urban/rural status of the area had a significant effect on the variation in incidence of childhood Type 1 diabetes. The results showed that although there was no significant difference in incidence between rural and urban areas, there was a tendency to increasing risk of Type 1 diabetes with the increasing concentration of NO3 in drinking water. The fact that no significant effect was found may stem from the aggregated data being too crude to detect it.
    Diabetic Medicine 04/2004; 21(3):256-61. · 3.24 Impact Factor
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    ABSTRACT: To examine the association of spatial variation in acute myocardial infarction (AMI) incidence and its putative environmental determinants in ground water such as total water hardness, the concentration of calcium, magnesium, fluoride, iron, copper, zinc, nitrate, and aluminium. Small area study using Bayesian modelling and the geo-referenced data aggregated into 10 km x 10 km cells. The population data were obtained from Statistics Finland, AMI case data from the National Death Register and the Hospital Discharge Register, and the geochemical data from hydrogeochemical database of Geological Survey of Finland. A total of 18 946 men aged 35-74 years with the first AMI attack in the years 1983, 1988, and 1993. One unit (in German degree degrees dH) increment in water hardness decreased the risk of AMI by 1%. Geochemical elements in ground water included in this study did not show a statistically significant effect on the incidence and spatial variation of AMI, even though suggestive findings were detected for fluoride (protective), iron and copper (increasing). The results of this study with more specific Bayesian statistical analysis confirm findings from earlier observations of the inverse relation between water hardness and coronary heart disease. The role of environmental geochemistry in the geographical variation of the AMI incidence should be studied further in more detail incorporating the individual intake of both food borne and water borne nutrients. Geochemical-spatial analysis provides a basis for the selection of areas suitable for such research.
    Journal of Epidemiology &amp Community Health 03/2004; 58(2):136-9. · 3.39 Impact Factor
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    ABSTRACT: The aim of the study was to investigate the incidence of type 1 diabetes among children aged 14 years or under according to the level of urbanization of the place of residence of children at the time of diagnosis in Finland during 1987 to 1996. The analysis was carried out using a Bayesian approach and GIS. The incidence was the highest in the rural heartland areas while the increase in incidence was sharpest in urban areas. The level of urbanization seems to explain only a part of the spatial variation in the incidence in Finland. It is possible that some environmental risk factors for type 1 diabetes have been more prevalent in rural heartland areas than in the rest of the country. These factors might have increased in urban environments in Finland particularly during the first half of 1990s.
    Health & Place 01/2004; 9(4):315-25. · 2.42 Impact Factor
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    ABSTRACT: Background and Purpose— Mortality from stroke has been declining over recent decades in most countries, except in Eastern Europe. In this analysis, based on the World Health Organization Monitoring Trends and Determinants in Cardiovascular Disease (WHO MONICA) Project, we explored to what extent these trends are due to changes in stroke event rate and to changes in case fatality. Methods— The WHO MONICA Project collected standardized data from 14 populations in 9 countries. All acute strokes occurring in men and women 35 to 64 years of age were included. Registration was carried out between 1982 and 1995, resulting in time spans from 7 to 13 years. Trends in event rates and case fatality were calculated as average annual percentage change. Results— Up to 6-fold differences were observed in stroke mortality. Mortality declined in 8 of 14 populations in men and in 10 of 14 populations in women. An increase in mortality was observed in Eastern Europe. In the populations with a declining trend, about two thirds of the change could be attributed to a decline in case fatality. In populations with increasing mortality, the rise was explained by an increase in case fatality. Conclusions— In most populations, changes in stroke mortality, whether declining or increasing, were principally attributable to changes in case fatality rather than changes in event rates. Whether this was due to changes in the management of stroke or changes in disease severity cannot be established on the basis of these results.
    Stroke 07/2003; 34:1833-1840. · 6.16 Impact Factor
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    ABSTRACT: To provide age-gender standardized incidence rate, temporal trend and seasonal variation of Type 1 diabetes in Kuwaiti children aged < or = 14 years. Data were prospectively collected over a period of 6 years (1992-1997) according to the DiaMond Project protocol using the capture-recapture method of ascertainment. Data ascertainment varied between 90% and 96%. The incidence rate of Type 1 diabetes was 20.1 per 100,000 children 0-14 years (95% confidence interval (CI) 18.0-22.1); age-standardized incidence rate 20.9 (95% CI 18.8-23.0). The incidence rate among boys, 21.1 per 100,000 (95% CI 18.1-24.1) was slightly higher than that among girls, 19.0 per 100,000 (95% CI 16.1-21.8). The age-standardized incidence rate was 21.9 (95% CI 18.9-24.8) in boys, and 19.9 (95 CI 17.1-22.8) in girls. Incidence rates increased with age in both sexes (boys chi(2) for linear trend = 13.5, P < 0.001; and for girls chi(2) = 27.8, P < 0.0001). There was a significant trend towards increase in overall incidence during the 6-year period (chi(2) = 6.210, P = 0.013), and in age group 5-9 (chi(2) = 10.8, P = 0.001). Seasonality was demonstrated overall, in boys and girls (P < 0.001). The incidence of Type 1 diabetes in Kuwait is high compared with the neighbouring Arab countries, and it appears to be increasing as in many European populations.
    Diabetic Medicine 06/2002; 19(6):522-5. · 3.24 Impact Factor
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    Sa Muntoni, M Karvonen, J Tuomilehto
    The Lancet 05/2002; 359(9313):1246; author reply 1247-8. · 39.21 Impact Factor

Publication Stats

3k Citations
442.47 Total Impact Points

Institutions

  • 2009
    • National Institute for Health and Welfare, Finland
      • Department of Chronic Disease Prevention
      Helsinki, Province of Southern Finland, Finland
  • 1992–2009
    • National Public Health Institute
      Helsinki, Southern Finland Province, Finland
  • 2004
    • Geological Survey of Finland
      Esbo, Southern Finland Province, Finland
  • 2001
    • Helsinki University Central Hospital
      • Department of Otorhinolaryngology
      Helsinki, Province of Southern Finland, Finland
  • 2000–2001
    • University of Tartu
      • Department of Internal Medicine (ARSK)
      Dorpat, Tartu County, Estonia
  • 1991
    • Alimetrics Ltd, Espoo, Finland
      Helsinki, Southern Finland Province, Finland
  • 1988–1990
    • University of Tampere
      • Department of Public Health
      Tampere, Western Finland, Finland
  • 1989
    • University of Oulu
      • Department of Public Health Science and General Practice
      Oulu, Oulu, Finland
  • 1959
    • Finnish Institute of Occupational Health
      Helsinki, Southern Finland Province, Finland