Vascular risk factors and stroke risk across the life span: A population-representative study of half a million people

Background: The incidence of stroke in developed countries is increasing selectively in young individuals, but whether this is secondary to traditional vascular risk factors is unknown. Methods: We used the Canadian Community Health Survey from 2000 to 2016 to create a large population-representative cohort of individuals over the age of 30 and free from prior stroke. All analyses were stratified by age decile. We linked with administrative databases to determine emergency department visits or hospitalizations for acute stroke until December 2017. We calculated time trends in risk factor prevalence (hypertension, diabetes, obesity, and smoking) using meta-regression. We used Cox proportional hazard models to evaluate the association between vascular risk factors and stroke risk, adjusted for demographic, co-morbid, and social variables. We used competing risk regression to account for deaths and calculated population-attributable fractions. In a sensitivity analysis, we excluded those with prior heart disease or cancer. Results: We included 492,400 people in the analysis with 8865 stroke events over a median follow-up time of 8.3 years. Prevalence of hypertension, diabetes, and obesity increased over time while smoking decreased. Associations of diabetes, hypertension, and obesity with stroke risk were progressively stronger at younger age (adjusted hazard ratio for diabetes was 4.47, 95% confidence interval (CI) = 1.95–10.28 at age 30–39, vs 1.21, 95% CI = 0.93–1.57 at age 80+), although the obesity association was attenuated with adjustment. Smoking was associated with higher risk of stroke without a gradient across age deciles, although had the greatest population-attributable fraction at younger age. The hazard ratio for stroke with multiple concurrent risk factors was much higher at younger age (adjusted hazard ratio for 3–4 risk factors was 8.60, 95% CI = 2.97–24.9 at age 30–39 vs 1.61, 95% CI = 0.88–2.97 at age 80+) and results were consistent when accounting for the competing risk of death and excluding those with prior heart disease or cancer. Conclusions: Diabetes and hypertension were associated with progressively elevated relative risk of stroke in younger individuals and prevalence was increasing over time. The association of obesity with stroke was not significant after adjustment for other factors. Smoking had the greatest prevalence and population-attributable fraction for stroke at younger age. Our findings assist in understanding the relationship between vascular risk factors and stroke across the life span and planning public health measures to lower stroke incidence in the young.

Hospitalization Costs of Respiratory Diseases Attributable to Temperature in the Context of Climate Change in Australia

Background: The association between temperatures and respiratory diseases has been extensively reported. However, the associated healthcare costs and attributable fractions due to temperature have scarcely been explored. The aims of this study were to estimate respiratory disease hospitalization costs attributable to non-optimum ambient temperature, to quantify the attributable fraction from cold and hot temperatures, and to estimate the future hospitalization costs in two Australian cities. Methods: The associations between daily hospitalization costs for respiratory diseases and temperatures in Sydney and Perth over the study period of 2010-2016 were analyzed using distributed lag non-linear models. Future hospitalization costs for respiratory diseases were estimated based on three predicted climate change scenarios - RCP2.6, RCP4.5 and RCP8.5. Results: The estimated respiratory disease hospitalization costs attributable to non-optimum ambient temperatures increased from 493.2 million Australian dollars (AUD) in 2010s to more than 700 million AUD in 2050s in Sydney, and from 98.0 million AUD to about 150 million AUD during the same period in Perth, in large part due to population growth. In the context of climate change, the current cold attributable fraction in Sydney (23.7%) and Perth (11.2%) is estimated to decline by the middle of this century to (18.1-20.1%) and (5.1-6.6%) respectively, while the heat-attributable fraction for respiratory disease is expected to gradually increase from 2.6% up to 5.5% in Perth. Conclusions: This study found both cold and hot temperatures increased the overall hospitalization costs for respiratory diseases in two major Australian cities, although the attributable fractions varied. The largest contributor was cold temperatures. While respiratory disease hospitalization costs will increase in the future, climate change will result in a decrease in the cold attributable fraction and an increase in the heat attributable fraction, depending on the location.

Attributable is Preventable: Corrected and revised estimates of population attributable fraction of TB related to undernutrition in 30 high TB burden countries

IntroductionThe Global TB Report 2020 estimated the population attributable fractions (PAF) for the major risk factors of TB. Undernourishment emerged as the leading risk factor accounting for 19% of the cases. The WHO however used the terms undernourishment and undernutrition interchangeably in its computation of PAF. Undernourishment is an indirect model derived estimate of decreased per capita energy availability, while undernutrition is defined by direct anthropometric measurements of nutritional status.MethodsWe re-estimated the PAF of undernutrition (instead of undernourishment) in 30 high TB burden countries, using the prevalence of undernutrition (age standardized estimate of BMI < 18.5 kg/m2 in adults for both sexes), and the relative risk (RR) of 3.2. Further, we revised PAF estimates of undernutrition with an RR of 4.49, in light of recent evidence.FindingsTwenty four percent of TB in high burden countries is attributable to undernutrition. The PAF of undernutrition was highest in Asian countries, unlike the PAF of undernourishment that was highest in Africa. The corrected estimate led up to 65% increase in number of cases attributable to undernutrition in Asian countries. More than one-third to nearly half of TB cases in India could be attributable to undernutrition.InterpretationEstimation of the PAF of TB related to undernutrition is methodologically valid and operationally relevant, rather than PAF related to undernourishment. Addressing undernutrition, the leading driver of TB in high TB burden countries (especially Asia) could enable achievement of END TB milestones of TB incidence for 2025.

Differences in the Racial Contribution of Dementia and Chronic Conditions to Hospitalization, SNF Admission

We estimate the contribution for experiencing hospitalization, skilled nursing facility admission and mortality using a measure of attributable fraction that incorporates both the prevalence, incidence and risk called Longitudinal Extension of the Average Attributable Fraction (LE-AAF). We estimate the LE-AAF for Non-Hispanic whites and Non-Hispanic Blacks for dementia and 10 chronic conditions, for three outcomes. This approach analyses the temporal relationships among conditions to estimate their population-level average attributable fractions. Unlike standard measures of attributable fraction, the sum of the contribution of each condition based on the LE-AAF will not exceed 100 percent, enabling us to compute the contribution of pairs, triads or any combination of conditions. Furthermore, in studying multimorbidity, the LE-AAF has the desirable feature of being based on all combinations of the risk factors and covariates present in the data with final values for the individual LE-AAFs obtained by averaging across these observed combinations of predictors.

The effect of inter-pregnancy interval on stillbirth in urban South Ethiopia: a community-based prospective cohort study

Background Stillbirth is an invisible and poorly understood adverse pregnancy outcome that remains a challenge in clinical practice in low-resource settings. It is also a key concern in Ethiopia where more than half of pregnancies occur shortly after preceding childbirth. Whether the interval between pregnancies has an effect on stillbirth or not is unclear. Therefore, we aimed to assess the effect of inter-pregnancy interval on stillbirth in urban South Ethiopia. Methods A community-based prospective cohort study was conducted among 2578 pregnant women and followed until delivery. Baseline data were collected at the household level during registration and enrolment. End-line data were collected from hospitals during delivery. Exposed groups were pregnant women with inter-pregnancy intervals < 18 months and 18–23 months. Unexposed group contains women with inter-pregnancy intervals 24–60 months. A generalized linear model for binary outcome was applied, using R version 4.0.5 software. Relative risk (RR) was used to estimate the effect size with a 95% confidence level. Attributable fraction (AF) and population attributable fraction (PAF) were used to report the public health impact of exposure. Results The overall incidence of stillbirth was 15 per 1000 total births, (95% CI: 11, 20%). However, the incidence was varied across months of inter-pregnancy intervals; 30 (< 18 months), 8 (18–23 months) and 10 (24–60 months) per 1000 total births. The risk of stillbirth was nearly four times (ARR = 3.55, 95%CI: 1.64, 7.68) higher for women with inter-pregnancy interval < 18 months as compared to 24–60 months. This means, about 72% (AF = 72, 95%CI: 39, 87%) of stillbirth among the exposed group (inter-pregnancy interval < 18 months category) and 42% (PAF = 42, 95%CI: 23, 50%) of stillbirth in the study population were attributed to inter-pregnancy interval < 18 months. These could be prevented with an inter-pregnancy interval that is at least 18 months or longer. Conclusions Inter-pregnancy interval under 18 months increases the risk of stillbirth in this population in urban South Ethiopia. Interventions targeting factors contributing to short inter-pregnancy intervals could help in reducing the risk of stillbirth. Improving contraceptive utilization in the community could be one of these interventions.

Risk‐Attributable Burden of Ischemic Heart Disease in 137 Low‐ and Middle‐Income Countries From 2000 to 2019

Background Ischemic heart disease (IHD) imposes the greatest disease burden globally, especially in low‐ and middle‐income countries (LMICs). We aim to examine the population‐attributable fraction and risk‐attributable death and disability‐adjusted life years (DALYs) for IHD in 137 low‐ and middle‐income countries. Methods and Results Using comparative risk assessment framework from the 2019 Global Burden of Disease study, the population‐attributable fraction and IHD burden (death and DALYs) attributable to risk factors in low‐income countries, lower‐middle‐income countries (LMCs), and upper‐middle‐income countries were assessed from 2000 to 2019. In 2019, the population‐attributable fraction (%) of IHD deaths in relation to all modifiable risk factors combined was highest in lower‐middle‐income countries (94.2; 95% uncertainty interval, 91.9–96.2), followed by upper‐middle‐income countries (93.5; 90.4–95.8) and low‐income countries (92.5; 90.0–94.7). There was a >13‐fold difference between Peru and Uzbekistan in age‐standardized rates (per 100 000) of attributable death (44.3 versus 660.4) and DALYs (786.7 versus 10506.1). Dietary risks accounted for the largest proportion of IHD’s behavioral burden in low‐ and middle‐income countries, primarily attributable to diets low in whole grains. High systolic blood pressure and high low‐density lipoprotein cholesterol remained the 2 leading causes of DALYs, with the former topping the list in 116 countries, while the latter led in 21 of the 137 countries. Compared with 2000 to 2010, the increases in risk‐attributable deaths and DALYs among upper‐middle income countries were slower from 2010 to 2019, while the trends in low‐income countries and lower‐middle income countries were opposite. Conclusions IHD’s attributable burden remains high in low‐ and middle‐income countries. Considerable heterogeneity was observed among different income‐classified regions and countries.