Ahmadi-Abhari Sara, Guzman-Castillo Maria, Bandosz Piotr, Shipley Martin J, Muniz-Terrera Graciela, Singh-Manoux Archana, Kivimäki Mika, Steptoe Andrew, Capewell Simon, O'Flaherty Martin, Brunner Eric J
Department of Epidemiology & Public Health, University College London WC1E 7HB, UK
Department of Public Health and Policy, University of Liverpool, UK.
BMJ. 2017 Jul 5;358:j2856. doi: 10.1136/bmj.j2856.
To forecast dementia prevalence with a dynamic modelling approach that integrates calendar trends in dementia incidence with those for mortality and cardiovascular disease. Modelling study. General adult population of England and Wales. The English Longitudinal Study of Ageing (ELSA) is a representative panel study with six waves of data across 2002-13. Men and women aged 50 or more years, selected randomly, and their cohabiting partners were recruited to the first wave of ELSA (2002-03). 11392 adults participated (response rate 67%). To maintain representativeness, refreshment participants were recruited to the study at subsequent waves. The total analytical sample constituted 17 906 people. Constant objective criteria based on cognitive and functional impairment were used to ascertain dementia cases at each wave. To estimate calendar trends in dementia incidence, correcting for bias due to loss to follow-up of study participants, a joint model of longitudinal and time-to-event data was fitted to ELSA data. To forecast future dementia prevalence, the probabilistic Markov model IMPACT-BAM (IMPACT-Better Ageing Model) was developed. IMPACT-BAM models transitions of the population aged 35 or more years through states of cardiovascular disease, cognitive and functional impairment, and dementia, to death. It enables prediction of dementia prevalence while accounting for the growing pool of susceptible people as a result of increased life expectancy and the competing effects due to changes in mortality, and incidence of cardiovascular disease. In ELSA, dementia incidence was estimated at 14.3 per 1000 person years in men and 17.0/1000 person years in women aged 50 or more in 2010. Dementia incidence declined at a relative rate of 2.7% (95% confidence interval 2.4% to 2.9%) for each year during 2002-13. Using IMPACT-BAM, we estimated there were approximately 767 000 (95% uncertainty interval 735 000 to 797 000) people with dementia in England and Wales in 2016. Despite the decrease in incidence and age specific prevalence, the number of people with dementia is projected to increase to 872 000, 1 092 000, and 1 205 000 in 2020, 2030, and 2040, respectively. A sensitivity analysis without the incidence decline gave a much larger projected growth, of more than 1.9 million people with dementia in 2040. Age specific dementia incidence is declining. The number of people with dementia in England and Wales is likely to increase by 57% from 2016 to 2040. This increase is mainly driven by improved life expectancy.
采用动态建模方法预测痴呆症患病率,该方法将痴呆症发病率的时间趋势与死亡率和心血管疾病的时间趋势相结合。建模研究。英格兰和威尔士的一般成年人口。英国老龄化纵向研究(ELSA)是一项具有代表性的队列研究,在2002年至2013年期间有六波数据。随机选择年龄在50岁及以上的男性和女性及其同居伴侣纳入ELSA的第一波研究(2002 - 2003年)。11392名成年人参与(应答率67%)。为保持代表性,在后续波次中招募补充参与者加入研究。总分析样本包括17906人。基于认知和功能损害的恒定客观标准用于在每一波次确定痴呆症病例。为估计痴呆症发病率的时间趋势,校正因研究参与者失访导致的偏差,将纵向数据和事件发生时间数据的联合模型应用于ELSA数据。为预测未来痴呆症患病率,开发了概率马尔可夫模型IMPACT - BAM(IMPACT - 更好的老龄化模型)。IMPACT - BAM对35岁及以上人群从心血管疾病、认知和功能损害以及痴呆状态到死亡的转变进行建模。它能够预测痴呆症患病率,同时考虑到由于预期寿命增加导致的易感人群数量增加以及死亡率和心血管疾病发病率变化产生的竞争效应。在ELSA中,2010年50岁及以上男性的痴呆症发病率估计为每1000人年14.3例,女性为每1000人年17.0例。在2002年至2013年期间,痴呆症发病率每年以2.7%(95%置信区间2.4%至2.9%)的相对速率下降。使用IMPACT - BAM,我们估计2016年英格兰和威尔士约有76.7万人(95%不确定区间73.5万至79.7万)患有痴呆症。尽管发病率和特定年龄患病率有所下降,但预计2020年、2030年和2040年痴呆症患者人数将分别增至87.2万、109.2万和120.5万。一项不考虑发病率下降的敏感性分析给出了大得多的预计增长,到2040年痴呆症患者超过190万。特定年龄的痴呆症发病率正在下降。英格兰和威尔士的痴呆症患者人数在2016年至2040年期间可能增加57%。这种增加主要是由预期寿命的提高推动的。