Weights at each age are computed using predicted probability of retirement under each alternative setting.
Age-standardised mortality rates were computed, using the population of EU-15 plus Norway of 1995 as the standard.
US visit rates were computed using mid-year age, sex, race, ethnicity, region and metropolitan status-specific population estimates from the US Census Bureau; all rates were reported per 1,000 individuals in the US resident population per year [1].
Monthly hospitalization rates were computed using county population aged 65 or above as the denominator.
For all countries, rates for ages 95+ were computed using information from younger ages.
Nutritional status indices (Z-scores for length-for-age [LAZ], weight-for-length [WLZ], weight-for-age [WAZ]) were computed using World Health Organisation (WHO) 2005 Child Growth Standards in the ANTHRO Software v3.0.1 (ANTHRO, WHO, Geneva).
As a consequence, scaled scores for seven subjects younger than the age of 16 were computed using normative data for subjects aged 16 years.
Age-adjusted estimates were computed using the direct method, standardized to the 2000 U.S. census population with four age groups: 12 17, 18 44, 45 64, and ≥65 years.
Correlations among brain connectivity measures (z-scores) and raw behavioral scores (corrected for age and education) were computed using Pearson's correlation coefficients.
The odds ratio (OR) and relative risk (RR) for anaemia in relation to MMN supplement, age and ESR were computed using logistic regression.
Correlations between metacognitive efficiency (meta-d′/d′), age and neuropsychological measures were computed using Pearson's product-moment correlations implemented in R 3.0.1.
