Temporal shifts in cardiovascular risk factor distribution.
BACKGROUND
Complementary strategies to shift risk factor population distributions and target high-risk individuals are required to reduce the burden of type 2 diabetes and cardiovascular disease (CVD).


OBJECTIVE
To examine secular changes in glucose and CVD risk factors over 20 years during an individual and population-based CVD prevention program in Västerbotten County, Sweden.


METHODS
Population-based health promotion intervention was conducted and annual invitation for individuals turning 40, 50, and 60 years to attend a health assessment, including an oral glucose tolerance test, biochemical measures, and a questionnaire. Data were collected between 1991 and 2010, analyzed in 2012 and available for 120,929 individuals. Linear regression modeling examined age-adjusted differences in CVD risk factor means over time. Data were direct-age-standardized to compare disease prevalence.


RESULTS
Between 1991-1995 and 2006-2010, mean age-adjusted cholesterol (men=-0.53, 95% CI=-0.55, -0.50 mmol/L; women=-0.48, 95% CI=-0.50, -0.45 mmol/L) and systolic blood pressure declined (men=-3.06, 95% CI=-3.43, -2.70 mm Hg; women=-5.27, 95% CI=-5.64, -4.90 mm Hg), with corresponding decreases in the age-standardized prevalence of hypertension and hyperlipidemia. Mean age-adjusted 2-hour plasma glucose (men=0.19, 95% CI=0.15, 0.23 mmol/L; women=0.08, 95% CI=0.04, 0.11 mmol/L) and BMI increased (men=1.12, 95% CI=1.04, 1.21; women=0.65, 95% CI=0.55, 0.75), with increases in the age-standardized prevalence of diabetes and obesity.


CONCLUSIONS
These data demonstrate the potential of combined individual- and population-based approaches to CVD risk factor control and highlight the need for additional strategies addressing hyperglycemia and obesity.
MRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom.
Gráinne H
GH
Long
MRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom.
Rebecca K
RK
Simmons
Department of Public Health and Clinical Medicine, Epidemiology and Global Health, Umeå University, Umeå, Sweden; Centre for Population Studies, Ageing and Living Conditions Programme, Umeå University, Umeå, Sweden.
Margareta
M
Norberg
Department of Public Health and Clinical Medicine, Family Medicine, Umeå University, Umeå, Sweden.
Patrik
P
Wennberg
Department of Public Health and Clinical Medicine, Occupational and Environmental Medicine, Umeå University, Umeå, Sweden.
Bernt
B
Lindahl
Department of Public Health and Clinical Medicine, Epidemiology and Global Health, Umeå University, Umeå, Sweden.
Olov
O
Rolandsson
MRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom.
Simon J
SJ
Griffin
Department of Public Health and Clinical Medicine, Epidemiology and Global Health, Umeå University, Umeå, Sweden. Electronic address: lars.weinehall@epiph.umu.se.
Lars
L
Weinehall
D000328:Adult; D001786:Blood Glucose; D001794:Blood Pressure; D015992:Body Mass Index; D002318:Cardiovascular Diseases / Q000097:blood / Q000453:epidemiology / Q000517:prevention & control*; D002784:Cholesterol / Q000097:blood*; D005260:Female; D006293:Health Promotion; D006801:Humans; D008297:Male; D008659:Metabolic Diseases / Q000097:blood / Q000453:epidemiology / Q000517:prevention & control; D008875:Middle Aged; D009765:Obesity / Q000097:blood / Q000453:epidemiology / Q000517:prevention & control; D015995:Prevalence; D012307:Risk Factors; D013548:Sweden / Q000453:epidemiology
D001786:Blood Glucose; D002784:Cholesterol