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Aims To determine (1) whether prescription opioid poisoning (PO) hospital discharges spread across space over time, (2) the locations of 'hot-spots' of PO-related hospital discharges, (3) how features of the local environment contribute to the growth in PO-related hospital discharges and (4) where each environmental feature makes the strongest contribution. Design Hierarchical Bayesian Poisson space-time analysis to relate annual discharges from community hospitals to postal code characteristics over 10 years. Setting California, USA. Participants Residents of 18 517 postal codes in California, 2001-11. Measurements Annual postal code-level counts of hospital discharges due to PO poisoning were related to postal code pharmacy density, measures of medical need for POs (i.e. rates of cancer and arthritis-related hospital discharges), economic stressors (i.e. median household income, percentage of families in poverty and the unemployment rate) and concentration of manual labor industries. Findings PO-related hospital discharges spread from rural and suburban/exurban 'hot-spots' to urban areas. They increased more in postal codes with greater pharmacy density [rate ratio (RR) = 1.03; 95% credible interval (CI) = 1.01, 1.05], more arthritis-related hospital discharges (RR = 1.08; 95% CI = 1.06, 1.11), lower income (RR = 0.85; 95% CI = 0.83, 0.87) and more manual labor industries (RR = 1.15; 95% CI = 1.10, 1.19 for construction; RR = 1.12; 95% CI = 1.04, 1.20 for manufacturing industries). Changes in pharmacy density primarily affected PO-related discharges in urban areas, while changes in income and manual labor industries especially affected PO-related discharges in suburban/exurban and rural areas. Conclusions Hospital discharge rates for prescription opioid (PO) poisoning spread from rural and suburban/exurban hot-spots to urban areas, suggesting spatial contagion. The distribution of age-related and work-place-related sources of medical need for POs in rural areas and, to a lesser extent, the availability of POs through pharmacies in urban areas, partly explain the growth of PO poisoning across California, USA. [ABSTRACT FROM AUTHOR]

Abstract: Understanding current patterns of population smoking by socioeconomic position (SEP) can be substantially enhanced by research that follows birth cohorts over long periods of time, yet such data in the US are rare. Information from birth cohorts followed during critical time periods when the health consequences of smoking became widely known can inform the ways in which current smoking prevalence has been shaped by the historical processes that preceded it. The present study utilizes data from a substudy of the Child Health and Development Study pregnancy cohort (N =1612). Women were queried about smoking status in 1959–1962, 1971–1972 and 1977–1980. Women were divided into three cohorts based on date of birth. Offspring represented another birth cohort assessed for smoking in 1977–1980. Results indicated that the overall prevalence of smoking exhibited cohort-specific patterns that persisted across time. Notably, the youngest maternal cohort (born 1937–1946) had high smoking prevalence throughout and showed no appreciable decrease (44.7%, 41.4%, 40.1% for 1959–1962, 1971–1972, and 1977–1980). Results also indicated that the relation of smoking to SEP exhibited cohort-specific patterns over time. Among the oldest birth cohort (born 1914–1930), no inverse relation of SEP to smoking was observed at any time; in contrast, an inverse relation emerged by 1959–1962 among the youngest cohort of mothers. Among the adolescent offspring, there was a strong SEP gradient (OR=2.0, 95% CI=1.4–3.0) that was stronger than in any maternal birth cohort at any assessment (β =0.40, SE=0.1, p <0.01). We conclude that SEP gradients in smoking emerge across birth cohorts rather than time alone, with increasingly strong gradients across time especially among younger cohorts. [Copyright &y& Elsevier]

Background The incidence and prevalence of autism have dramatically increased over the last 20 years. Decomposition of autism incidence rates into age, period and cohort effects disentangle underlying domains of causal factors linked to time trends. We estimate an age-period-cohort effect model for autism diagnostic incidence overall and by level of functioning.Methods Data are drawn from sequential cohorts of all 6 501 262 individuals born in California from 1992 to 2003. Autism diagnoses from 1994 to 2005 were ascertained from the California Department of Development Services Client Development and Evaluation Report.Results Compared with those born in 1992, each successively younger cohort has significantly higher odds of an autism diagnosis than the previous cohort, controlling for age and period effects. For example, individuals born in 2003 have 16.6 times the odds of an autism diagnosis compared with those born in 1992 [95% confidence interval (CI) 7.8–35.3]. The cohort effect observed in these data is stronger for high than for low-functioning children with an autism diagnosis.Discussion Autism incidence in California exhibits a robust and linear positive cohort effect that is stronger among high-functioning children with an autism diagnosis. This finding indicates that the primary drivers of the increases in autism diagnoses must be factors that: (i) have increased linearly year-to-year; (ii) aggregate in birth cohorts; and (iii) are stronger among children with higher levels of functioning. [ABSTRACT FROM AUTHOR]