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medicine

Impact of population aging on trends in diabetes prevalence: A meta-regression analysis of 160,000 Japanese adults

Journal of Diabetes Investigation, Volume 6, No. 5, Year 2015

Aims/Introduction: To provide age- and sex-specific trends, age-standardized trends, and projections of diabetes prevalence through the year 2030 in the Japanese adult population. Materials and Methods: In the present meta-regression analysis, we included 161,087 adults from six studies and nine national health surveys carried out between 1988 and 2011 in Japan. We assessed the prevalence of diabetes using a recorded history of diabetes or, for the population of individuals without known diabetes, either a glycated hemoglobin level of ≥6.5% (48 mmol/mol) or the 1999 World Health Organization criteria (i.e., a fasting plasma glucose level of ≥126 mg/dL and/or 2-h glucose level of ≥200 mg/dL in the 75-g oral glucose tolerance test). Results: For both sexes, prevalence appeared to remain unchanged over the years in all age categories except for men aged 70 years or older, in whom a significant increase in prevalence with time was observed. Age-standardized diabetes prevalence estimates based on the Japanese population of the corresponding year showed marked increasing trends: diabetes prevalence was 6.1% among women (95% confidence interval [CI] 5.5-6.7), 9.9% (95% CI 9.2-10.6) among men, and 7.9% (95% CI 7.5-8.4) among the total population in 2010, and was expected to rise by 2030 to 6.7% (95% CI 5.2-9.2), 13.1% (95% CI 10.9-16.7) and 9.8% (95% CI 8.5-12.0), respectively. In contrast, the age-standardized diabetes prevalence using a fixed population appeared to remain unchanged. Conclusions: This large-scale meta-regression analysis shows that a substantial increase in diabetes prevalence is expected in Japan during the next few decades, mainly as a result of the aging of the adult population.
Statistics
Citations: 115
Authors: 14
Affiliations: 12
Identifiers
Research Areas
Health System And Policy
Noncommunicable Diseases
Study Design
Cross Sectional Study
Study Approach
Quantitative
Participants Gender
Male
Female