Journal of Epidemiology and Community Health

A lack of large-scale, individually linked data often has impeded efforts to disentangle individual-level variability in outcomes from area-level variability in studies of many diseases and conditions. This study investigated individual and county-level variability in outcomes following non-fatal overdose in a state-wide cohort of opioid overdose patients.

Participants were 24 031 patients treated by emergency medical services or an emergency department for opioid-involved overdose in Indiana between 2014 and 2017. Outcomes included repeat non-fatal overdose, fatal overdose and death. County-level predictors included sociodemographic, socioeconomic and treatment availability indicators. Individual-level predictors included age, race, sex and repeat non-fatal opioid-involved overdose. Multilevel models examined outcomes following non-fatal overdose as a function of patient and county characteristics.

10.9% (n=2612) of patients had a repeat non-fatal overdose, 2.4% (n=580) died of drug overdose and 9.2% (n=2217) died overall. Patients with a repeat overdose were over three times more likely to die of drug-related causes (OR=3.68, 99.9% CI 2.62 to 5.17, p<0.001). County-level effects were limited primarily to treatment availability indicators. Higher rates of buprenorphine treatment providers were associated with lower rates of mortality (OR=0.82, 95% CI 0.68 to 0.97, p=0.024), but the opposite trend was found for naltrexone treatment providers (OR=1.20, 95% CI 1.03 to 1.39, p=0.021). Cross-level interactions showed higher rates of Black deaths relative to White deaths in counties with high rates of naltrexone providers (OR=1.73, 95% CI 1.09 to 2.73, p=0.019).

Although patient-level differences account for most variability in opioid-related outcomes, treatment availability may contribute to county-level differences, necessitating multifaceted approaches for the treatment and prevention of opioid abuse.

Early-life socioeconomic circumstances (SEC) are associated with health in old age. However, epidemiological evidences on the influence of these early-life risk factors on trajectories of healthy ageing are inconsistent, preventing drawing solid conclusion about their potential influence. Here, to fill this knowledge gap, we used a statistical approach adapted to estimating change over time and an outcome-wide epidemiology approach to investigate whether early-life SEC were associated with the level of and rate of decline of physical, cognitive and emotional functioning over time.

We used data on more than 23 000 adults in older age from the Survey of Health, Ageing and Retirement in Europe, a 12-year large-scale longitudinal study with repeated measurements of multiple health indicators of the same participants over time (2004 –2015, assessments every 2 years). Confounder-adjusted linear growth curve models were used to examine the associations of early-life SEC with the evolution of muscle strength, lung function, cognitive function, depressive symptoms and well-being over time.

We consistently found an association between early-life SEC and the mean levels of all health indicators at age 63.5, with a critical role played by the cultural aspect of disadvantage. These associations were only partly explained by adult-life SEC factors. By contrast, evidences supporting an association between early-life SEC and the rate of change in health indicators were weak and inconsistent.

Early-life SEC are associated with health in old age, but not with trajectories of healthy ageing. Conceptual models in life course research should consider the possibility of a limited influence of early-life SEC on healthy ageing trajectories.

Previous studies have proposed that higher blood pressure (BP) in winter is an important cause of increased mortality from cardiovascular disease during the winter. Some observational and physiological studies have shown that cold exposure increases BP, but evidence from a randomised controlled study assessing the effectiveness of intensive room heating for lowering BP was lacking.

The present study aimed to determine whether intensive room heating in winter decreases ambulatory BP as compared with weak room heating resulting in a 10°C lower target room temperature when sufficient clothing and bedclothes are available.

We conducted a parallel group, assessor blinded, simple randomised controlled study with 1:1 allocation among 146 healthy participants in Japan from November 2009 to March 2010. Ambulatory BP was measured while the participants stayed in single experimental rooms from 21:00 to 8:00. During the session, participants could adjust the amount of clothing and bedclothes as required. Compared with the weak room heating group (mean temperature±SD: 13.9±3.3°C), systolic morning BP (mean BP 2 h after getting out of bed) of the intensive room heating group (24.2±1.7°C) was significantly lower by 5.8 mm Hg (95% CI 2.4 to 9.3). Sleep-trough morning BP surges (morning BP minus lowest night-time BP) in the intensive room heating group were significantly suppressed to about two thirds of the values in the weak room heating group (14.3 vs 21.9 mm Hg; p<0.01).

Intensive room heating decreased morning BP and the morning BP surge in winter.