16 research outputs found
Kernel density graph of zBMI and the difference in zBMI (95% confidence interval for difference) for the least and most deprived groups in 2007 to 2008 and 2011 to 2012 for boys and girls 4 to 5 years of age.
<p>Vertical dashed lines on kernel density graphs show the UK 1990 definitions for underweight (2<sup>nd</sup> centile), overweight (85<sup>th</sup>), obesity for population monitoring (95<sup>th</sup>), obesity for clinical classifications (98<sup>th</sup>) and morbid obesity (99.6<sup>th</sup>).</p
Kernel density graph of zBMI and the difference in zBMI (95% confidence interval for difference) for the least and most deprived groups in 2007 to 2008 and 2011 to 2012 for boys and girls 10 to 11 years of age.
<p>Vertical dashed lines on kernel density graphs show the UK 1990 definitions for underweight (2<sup>nd</sup> centile), overweight (85<sup>th</sup>), obesity for population monitoring (95<sup>th</sup>), obesity for clinical classifications (98<sup>th</sup>) and morbid obesity (99.6<sup>th</sup>).</p
The average remaining life expectancies and remaining years in poverty.
<p>Average remaining life expectancies (solid lines) and expected years in poverty (dashed lines) conditional on surviving to age <i>x</i> based on state at age <i>x</i> (red = below threshold, blue = above threshold). a, c, and e, differ in the threshold income used to define poverty, 1×, 2×, and 3× the ‘official’ poverty income level, respectively. The ratio of the average remaining life in poverty (or below 2× poverty or 3× the ‘official’ poverty threshold) to total average remaining life are graphed in panels (b), (d) and (f). In other words, this is the proportion of average remaining life below a specified threshold. All values are calculated from the fundamental matrix (see section B of <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0195734#pone.0195734.s001" target="_blank">S1 Theory</a>). The dashed green vertical lines in each panel are the seams between data-sets utilized: NLSY79 pre-1994, NLSY79 post-1994 and HRS (at age 33 and 50).</p
Predicted proportion of individuals that are below the poverty threshold.
<p>Black lines are the predicted proportion of individuals of age <i>x</i> that are below the poverty threshold according to the dominant eigenvector of the cumulative <b>Q</b>(<i>x</i>) matrix <b>Qcum</b>(<i>x</i>), the cumulative unconditional state transition matrix for age <i>x</i>. Red lines represent population projections for those below poverty with five different initial cohort distributions: (from top to bottom) 970,000, 750,000, 500,000, 250,000, and 30,000 individuals below poverty threshold in an initial cohort of 1,000,000 individuals. Regardless of initial cohort, the proportion of individuals below poverty (red lines) converge to the dominant eigenvector of <b>Qcum</b>(<i>x</i>) with age. a, b, and c, differ in the threshold income used to define poverty, 1×, 2×, and 3× the ‘official’ poverty income level, respectively. The green vertical lines in each panel are the seams between data-sets utilized: NLSY79 pre-1994, NLSY79 post-1994 and HRS (at age 33 and 50).</p
Age-specific annual survival probabilities.
<p>Annual survival (the number alive at age <i>x</i> + 1/ the number alive at <i>x</i>) for those above (red) and below (blue) the poverty threshold at age <i>x</i>. a, b and c differ in threshold income used to define poverty, 1×, 2×, and 3× the ‘official’ poverty income level, respectively. The green vertical lines in each panel are the seams between data-sets utilized: NLSY79 pre-1994, NLSY79 post-1994 and HRS (at age 33 and 50).</p
Cohort simulations of 10,000 individuals lifetime trajectories.
<p>The right column is a ‘snapshot’ of 100 individuals between the ages of 50 and 60 with mortality around 60. Red is the above income threshold state, green is below the income threshold, and blue is death. The first column is the entire cohort and is in the shape of a survivorship curve for all three rows. The first row of panels has a threshold at 1× poverty income threshold, second row is 2× and third row is 3× poverty income threshold.</p
Poverty dynamics, poverty thresholds and mortality: An age-stage Markovian model
<div><p>Recent studies have examined the risk of poverty throughout the life course, but few have considered how transitioning in and out of poverty shape the dynamic heterogeneity and mortality disparities of a cohort at each age. Here we use state-by-age modeling to capture individual heterogeneity in crossing one of three different poverty thresholds (defined as 1×, 2× or 3× the “official” poverty threshold) at each age. We examine age-specific state structure, the remaining life expectancy, its variance, and cohort simulations for those above and below each threshold. Survival and transitioning probabilities are statistically estimated by regression analyses of data from the Health and Retirement Survey RAND data-set, and the National Longitudinal Survey of Youth. Using the results of these regression analyses, we parameterize discrete state, discrete age matrix models. We found that individuals above all three thresholds have higher annual survival than those in poverty, especially for mid-ages to about age 80. The advantage is greatest when we classify individuals based on 1× the “official” poverty threshold. The greatest discrepancy in average remaining life expectancy and its variance between those above and in poverty occurs at mid-ages for all three thresholds. And fewer individuals are in poverty between ages 40-60 for all three thresholds. Our findings are consistent with results based on other data sets, but also suggest that dynamic heterogeneity in poverty and the transience of the poverty state is associated with income-related mortality disparities (less transience, especially of those above poverty, more disparities). This paper applies the approach of age-by-stage matrix models to human demography and individual poverty dynamics. In so doing we extend the literature on individual poverty dynamics across the life course.</p></div
Cohort simulations of 10,000 individuals: Distributions of residence times and ages of transitions.
<p>The initial cohort is the same for each row but each row is a separate simulation with a particular income threshold in place. Distributions of the years an individual spends in the lower income state are depicted in panels a, d, and g. The panels in the second column are distributions of ages of entry into the lower income state. The panels in the third column are distributions of ages of exit from the lower income state. The first row of panels has a threshold at 1× poverty income threshold, second row is 2× and third row is 3× poverty income threshold. The dashed green vertical lines in panels in the last two columns are the seams between data-sets utilized: NLSY79 pre-1994, NLSY79 post-1994 and HRS (at age 33 and 50).</p
The variance of remaining life expectancy, conditional on surviving to a specific age.
<p>a, c, and e depict the variance of remaining life expectancy conditional on surviving to age <i>x</i> based on state at age <i>x</i> (red = below threshold, blue = above threshold). The age-specific coefficient of variation (the standard deviation divided by the mean) for state (red = below threshold, blue = above threshold) at age <i>x</i> are graphed in panels (b), (d) and (f). The dashed green vertical lines in each panels are the seams between data-sets utilized: NLSY79 pre-1994, NLSY79 post-1994 and HRS (at age 33 and 50).</p
Structure of state transition matrices, Q(x).
<p>Structure of state transition matrices, Q(x).</p