@article {9582,
	title = {Lifestyle index for mortality prediction using multiple ageing cohorts in the USA, UK and Europe.},
	journal = {Scientific Reports},
	volume = {8},
	year = {2018},
	pages = {6644},
	abstract = {Current mortality prediction indexes are mainly based on functional morbidity and comorbidity, with limited information for risk prevention. This study aimed to develop and validate a modifiable lifestyle-based mortality predication index for older adults. Data from 51,688 participants (56\% women) aged >=50 years in 2002 Health and Retirement Study, 2002 English Longitudinal Study of Ageing and 2004 Survey of Health Ageing and Retirement in Europe were used to estimate coefficients of the index with cohort-stratified Cox regression. Models were validated across studies and compared to the Lee index (having comorbid and morbidity predictors). Over an average of 11-year follow-up, 10,240 participants died. The lifestyle index includes smoking, drinking, exercising, sleep quality, BMI, sex and age; showing adequate model performance in internal validation (C-statistic 0.79; D-statistic 1.94; calibration slope 1.13) and in all combinations of internal-external cross-validation. It outperformed Lee index (e.g. differences in C-statistic = 0.01, D-statistic = 0.17, P < 0.001) consistently across health status. The lifestyle index stratified participants into varying mortality risk groups, with those in the top quintile having 13.5\% excess absolute mortality risk over 10 years than those in the bottom 50th centile. Our lifestyle index with easy-assessable behavioural factors and improved generalizability may maximize its usability for personalized risk management.},
	keywords = {Cross-National, Functional status, Mortality},
	issn = {2045-2322},
	doi = {10.1038/s41598-018-24778-1},
	author = {Liao, Jing and Muniz-Terrera, Graciela and Shaun Scholes and Hao, Yuantao and Chen, Yu-Ming}
}
@article {7630,
	title = {A comparison of response rates in the English Longitudinal Study of Ageing and the Health and Retirement Study.},
	journal = {Longit Life Course Stud},
	volume = {2},
	year = {2011},
	month = {2011 May 01},
	pages = {127-144},
	publisher = {2},
	abstract = {<p>Survey response rates are an important measure of the quality of a survey; this is true for both longitudinal and cross-sectional surveys. However, the concept of a response rate in the context of a panel survey is more complex than is the case for a cross-sectional survey. There are typically many different response rates that can be calculated for a panel survey, each of which may be relevant for a specific purpose. The main objective of our paper is to document and compare response rates for two long-term panel studies of ageing, the English Longitudinal Study of Ageing (ELSA) and the Health and Retirement Study (HRS) in the United States. To guide our selection and calculation of response rates for the two studies, we use a framework that was developed by Peter Lynn (2005) and present several different types of longitudinal response rates for the two surveys. We discuss similarities and differences in the study designs and protocols and how some of the differences affect comparisons of response rates across the two studies.</p>},
	issn = {1757-9597},
	doi = {10.14301/llcs.v2i2.118},
	author = {Hayley Cheshire and Mary Beth Ofstedal and Shaun Scholes and Mathis Schroeder}
}
