Costa Rican Longitudinal Mortality Study creles.berkeley/

1. Costa Rican Longitudinal Mortality Studyhttp://www.creles.berkeley.edu/ William H. Dow, UC-Berkeley (CEDA, SPH) Luis Rosero-Bixby, University of Costa Rica Support from NIA

2. Figure 2. Time trends in life expectancy, 1910-2010

4. Data Limitations • Individual-level correlates of adult mortality documented only in rich countries until recently (e.g., U.S. NLMS). • In developing countries, SES gradients mainly for child mortality (Brass & DHS-type data). • Problems with vital statistics: • Vital statistics contain no SES info • Mortality crossover => assumption that adult mortality estimates are not good • Selective migration and residence mis-reporting: wrong rural/urban differentials? • Age mis-reporting • Under-registration of deaths

5. Background about Costa Rica: A health over-achiever

6. Life expectancy and GDP by 2005

8. Costa Rica: middle income country, high social development, strong public sector, advanced demographic transition Source: World Bank

11. Rosero-Bixby, Dow, Lacle (JBS 2005): Coronado study • Panel of 876 individuals aged 60+ in 1984 • Semi urban community near San Jose (100% sample from the 1984 census) • Observed from June 1984 to December 2001 • Interview data from the 1984 census and visits in 1985 and 1986 • Survival from 1988 and 2002 contacts, and computer follow up in the civil registration.

12. Coronado result: No clear SES mortality gradient

13. Rosero-Bixby and Dow (JGSS 2009) CRELES: Costa Rican Study of Longevity and Healthy Aging • National sample of 8,000 born before 1946, from the 2000 census. • 6-year survival follow up • Sub-sample: 2,800 interviewed in 2005 • First wave of a panel (resurvey 2007,2009) • 90 minute interview and 10 minute diet • Anthropometry, fasting blood and overnight urine samples

14. The puzzling SES gradient:mortality vs. self-reported health(controlling for age, sex, marital)

15. The Costa Rican longitudinal mortality study (CR-LMS)

16. Description of the CR-LMS • Sample 20,000 Costa Ricans 30+ from 1984 census • With full ID of individuals in the sample (name and unique ID number.) • Minimal age and residence misreporting • Follow up in the death and voting databases • Mortality analyses with survival-time methods, by 1984 census SES characteristics

17. Failures Censored observations

18. Linkage with Civil Registry • Name chopped in 3-letter segments • Probability each person in Registry of having same name • Census age +- 2 years vs. birth date in Registry • Place residing in census vs. place registered to vote in 1990. • 18.500 (87%) linkages census-registry • 13.500 (73%) were “optimal” linkages • Weighting factors correct differences in linkage rate (lower in women, old age, low education)

19. The CR-LMS sample by age

20. Explanatory variables

21. The deaths Cause of death Medical attention

22. Mortality rates by age

23. Life expectancy at ages 45 and 75, CR-LMS, USA, and Japan 2000-05

24. Sensitivity to possible wrong linkages and attrition

25. All-cause death rate ratios by SES

26. Exploring why Costa Rica outperforms the U.S. in life expectancy:A tale of two inequality gradients Rosero-Bixby and Dow PNAS 2016

27. Data • Longitudinal mortality studies, ages 40-89: • U.S. 1993-98, N=288,000 p., 22,400 deaths (Hispanic: 25,000 p. 1,100 d.) • Costa Rica: 1990-2001, N=17.500 p, 2,400 d. • Health risk factors surveys ages 55-79, 2007-10: • U.S. NHANES: N=4,200 • CRELES 2007-10: N=3,800 • SES-rank 0 to 1: samples sorted by education and income, -slope is the Relative Inequality Index RII

28. Costa Rican advantage also among low SES males

29. Gracias!Users welcomedCRELES data at:http://www.creles.berkeley.edu/or ICPSR