scholarly journals Obtaining multistate life table distributions for highly refined subpopulations from cross-sectional data: A bayesian extension of sullivan’s method

Demography ◽  
2010 ◽  
Vol 47 (4) ◽  
pp. 1053-1077 ◽  
Author(s):  
Scott M. Lynch ◽  
J. Scott Brown
Keyword(s):  
Life Table ◽  
Cross Sectional ◽  
Multistate Life Table

scholarly journals Children’s Financial Dependence on Mothers: Propensity and Duration

2021 ◽  
Vol 7 ◽  
pp. 237802312110552
Author(s):  
Jennifer L. Glass ◽  
R. Kelly Raley ◽  
Joanna R. Pepin
Keyword(s):  
Life Table ◽  
Financial Support ◽  
Longitudinal Survey ◽  
Program Participation ◽  
First Birth ◽  
Birth Mothers ◽  
Cross Sectional ◽  
American Children ◽  
Multistate Life Table

Over 40 percent of American children rely primarily on their mothers’ earnings for financial support in cross-sectional surveys. Yet these data understate mothers’ role as their family’s primary earner. Using longitudinal Survey of Income and Program Participation panels beginning in 2014, we create multistate life table estimates of mothers’ duration as primary earner as well as single-decrement life table estimates of their chance of ever being the primary earner over the first 18 years of motherhood. Using a threshold of 60 percent of household earnings to determine primary earning status, mothers average 4.19 years as their families’ primary earner in the 18 years following first birth. Mothers with some college but no degree spent the most years as primary earners, about 5.09 years on average, as did mothers with nonmarital first births, about 5.69 years. Around 70 percent of American mothers can reasonably expect to be their household’s primary earner at some point during their first 18 years of motherhood.

Multistate life tables using Stata

2020 ◽  
Vol 20 (3) ◽  
pp. 721-745
Author(s):  
Jerônimo Oliveira Muniz
Keyword(s):  
Life Table ◽  
Input Data ◽  
Average Duration ◽  
Transition Rates ◽  
Absorbing State ◽  
Multistate Life Tables ◽  
The Mean ◽  
Time Specific ◽  
Number Of Individuals ◽  
Multistate Life Table

The mslt command calculates the functions of a multistate life table and plots a graph of conditional and unconditional life expectancies by time. The command provides linear and exponential solutions to estimate the number of individuals, transitions, probabilities, person-years, and years of life in a given cohort and state of occupancy. The input data are time-specific transition rates (or survivorship proportions) between nonabsorbing and at most one absorbing state. In addition to the mean age at transfer between states, mslt calculates the following summary measures: the mean age, the probability of dying, the average duration, and the proportion of life spent in a specific state.

scholarly journals Estimation of the Distribution of Duration of Breastfeeding from Cross-Sectional Data: Some Methodological Issue

2021 ◽  
Author(s):  
Anup Kumar ◽  
Sachin Kumar ◽  
Jai Kishun ◽  
Uttam Singh ◽  
Pushpraj .
Keyword(s):  
Life Table ◽  
Current Status Data ◽  
Current Status ◽  
Life Table Analysis ◽  
Cross Sectional ◽  
Kaplan Meier ◽  
Table Analysis ◽  
Duration Of Breastfeeding ◽  
Status Data ◽  
The Impact

Background: Duration of breastfeeding is an important health indicator of mother and child. There are various indirect epidemiological methods available to estimate the duration of breastfeeding from cross sectional data. Objective: To estimate the distribution of duration of breastfeeding at national level cross sectional data and compare various available technique. The impact of the sampling frame (ascertain of the individual understudy) is also evaluated. Method: National Family Health Survey (NFHS-IV) data is used. Duration of breastfeeding of only those children who were born before 60 months from survey date were included in the study. The technique of Current Status Data, Life Table Analysis, and Kaplan Meier (KM) estimator is applied to assess the distribution of duration of breastfeeding. Result: The mean estimate is 32.84, 33.14 and 33.64 months by Kaplan Maier Estimator, Current Status Data and Life Table Analysis respectively. The Current Status and Life Table method are better than Kaplan Meier Estimator as it is doesn’t based on recall data and heaping present in the data. Conclusion: One must be very cautions while estimating the various epidemiological parameters from cross section data set. The assumptions of the methodology as per data available should be evaluate. If such data is not available, the available methodology may be modified. Regression analysis based on Current Status data technique may be used to assess the impact of various clinical and epidemiological factors (such as nutrition of mother, health status of mother etc.) on duration of breastfeeding

scholarly journals 377Smoking, blood pressure, and body mass index to estimate healthy life expectancy: NIPPON DATA90

2021 ◽  
Vol 50 (Supplement_1) ◽  
Author(s):  
Rumi Tsukinoki ◽  
Takehito Hayakawa ◽  
Aya Kadota ◽  
Yoshitaka Murakami ◽  
Katsuyuki Miura ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Body Mass Index ◽  
Life Expectancy ◽  
Life Table ◽  
Body Mass ◽  
Smoking Status ◽  
Healthy Life Expectancy ◽  
Ageing Society ◽  
Healthy Life ◽  
Multistate Life Table

Abstract Background Healthy life expectancy (HLE) is an important measure of an ageing society. We estimated HLE based on combinations of smoking, blood pressure (BP), and body mass index (BMI) in the Japanese population using a multistate life table. Methods A nationwide cohort study of Japan was performed using NIPPON DATA90 (N = 6,676) with the Katz Activities of Daily Living Index as the HLE endpoint. Combinations of smoking (non-smokers and smokers), BP (2018 ESC/ESH Guidelines classification), and BMI (underweight, normal, and overweight) were developed, and the group-specific HLEs were calculated using a multistate life table. Results At age 65, smokers had shorter HLE than non-smokers for all BMI and BP groups. The HLE of men who were overweight, hypertensive (Grade 2 or 3), and smokers was 14.05 years (95% confidence interval: 15.77-21.36); in contrast, the HLE of men who were normal weight, normotensive, and non-smokers was 19.04 years (16.46-21.61). Among all BMI and smoking status groups, HLE decreased linearly as BP increased regardless of sex. The HLE distribution showed a slight inverted U-shape as BMI increased in both sexes. Conclusions This study showed that HLE at age 65 was considerably shorter in smokers and individuals with higher BP. Furthermore, both underweight and overweight had modest effects on HLE at age 65. Key messages HLE was considerably shorter in smokers and individuals with higher BP. In addition, both underweight and overweight had modest effects on HLE.

Abstract 043: Leisure-Time Physical Activity in Adulthood and Region of Interest (ROI) Brain Volumes: The Atherosclerosis Risk in Communities Neurocognitive Study (ARIC-NCS)

Circulation ◽  
2018 ◽  
Vol 137 (suppl_1) ◽  
Author(s):  
Priya Palta ◽  
A R Sharrett ◽  
Kelly R Evenson ◽  
Clifford R Jack ◽  
Pamela L Lutsey ◽  
...  
Keyword(s):  
Physical Activity ◽  
Cognitive Impairment ◽  
Life Table ◽  
Brain Mri ◽  
Late Life ◽  
Intracranial Volume ◽  
Reverse Causality ◽  
Cross Sectional ◽  
Brain Volumes ◽  
Age Related

Introduction: Several studies report late-life physical activity (PA) to be associated with less brain atrophy. Associations of PA and subclinical brain markers evaluated at older ages may be subject to reverse causality due to comorbidity, age-related changes in lifestyle, or incipient cognitive impairment. Therefore, we aimed to compare late-life cross-sectional estimates of PA and ROI brain volumes to those using prospective PA measures from mid- to late-life. Methods: Participants (n=1549, mean age: 75, 39% male, 20% Black) with repeat assessments of PA from visit 1 (1987-1989) and a brain magnetic resonance imaging (MRI) in 2011-2013 were included. Total volume of PA in metabolic equivalent-min/week was estimated using the Baecke Physical Activity Questionnaire and classified as no, low, middle or high at each visit. Based on visit 1 and 3 (1993-1995) PA assessments, a subset of participants (n=663) were further categorized as habitually inactive or having habitually low, middle, or high PA in mid-life. Brain MRI using 3D-1.5T equipment quantified ROI volumes following a standardized protocol. Weighted linear regression adjusted for intracranial volume, demographics, select cardiovascular risk factors and ApoE4 estimated the standardized difference in ROI volumes. Results: Compared to no PA, high PA was associated with larger ROI brain volumes cross-sectionally in late-life (Table). High mid-life PA was only modestly associated with larger frontal cortical and deep gray matter volumes in late-life (Table). Habitually high PA in mid-life was not associated with less atrophy across brain regions in late-life. Conclusions: Our results do not support a causal interpretation of the cross-sectional associations between PA and brain volumes reported in late-life. Drawing on long-term population-based data, this study provides novel information on the associations of PA across life epochs with brain health, which can inform translational and intervention efforts to reduce age-related cognitive impairment.

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