Recurrence of postpartum hemorrhage, maternal and paternal contribution, and the effect of offspring birthweight and sex: a population-based cohort study

Purpose This study examines individual aggregation of postpartum hemorrhage (PPH), paternal contribution and how offspring birthweight and sex influence recurrence of PPH. Further, we wanted to estimate the proportion of PPH cases attributable to a history of PPH or current birthweight. Methods We studied all singleton births in Norway from 1967 to 2017 using data from Norwegian medical and administrational registries. Subsequent births in the parents were linked. Multilevel logistic regression was used to calculate odds ratios (ORs) with 95% confidence intervals (CI) for PPH defined as blood loss > 500 ml, blood loss > 1500 ml, or the need for blood transfusion in parous women. Main exposures were previous PPH, high birthweight, and fetal sex. We calculated adjusted population attributable fractions for previous PPH and current high birthweight. Results Mothers with a history of PPH had three- and sixfold higher risks of PPH in their second and third deliveries, respectively (adjusted OR 2.9; 95% CI 2.9–3.0 and 6.0; 5.5–6.6). Severe PPH (> 1500 ml) had the highest risk of recurrence. The paternal contribution to recurrence of PPH in deliveries with two different mothers was weak, but significant. If the neonate was male, the risk of PPH was reduced. A history of PPH or birthweight ≥ 4000 g each accounted for 15% of the total number of PPH cases. Conclusion A history of PPH and current birthweight exerted strong effects at both the individual and population levels. Recurrence risk was highest for severe PPH. Occurrence and recurrence were lower in male fetuses, and the paternal influence was weak.

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.

Overall and Sex-Specific Risk Factors for Subjective Cognitive Decline: Findings From the 2015–2018 Behavioral Risk Factor Surveillance System Survey

Background Prior research indicates that at least 35% of Alzheimer’s disease and related dementia risk may be amenable to prevention. Subjective cognitive decline is often the first indication of preclinical dementia, with the risk of subsequent Alzheimer’s disease in such individuals being greater in women than men. We wished to understand how modifiable factors are associated with subjective cognitive decline, and whether differences exist by sex. Methods Data were collected from men and women (45 years and older) who completed the U.S. Behavioral Risk Factor Surveillance System Cognitive Decline Module (2015–2018), n=216,838. We calculated population attributable fractions for subjective cognitive decline, stratified by sex, of the following factors: limited education, deafness, social isolation, depression, smoking, physical inactivity, obesity, hypertension, and diabetes. Our models were adjusted for age, race, income, employment, marital and Veteran status, and accounted for communality among risk factors. Results The final study sample included more women (53.7%) than men, but both had a similar prevalence of subjective cognitive decline (10.6% of women versus 11.2% of men). Women and men had nearly equivalent overall population attributable fractions to explain subjective cognitive decline (39.7% for women versus 41.3% for men). The top three contributing risk factors were social isolation, depression, and hypertension, which explained three-quarters of the overall population attributable fraction. Conclusions While we did not identify any differences in modifiable factors between men and women contributing to subjective cognitive decline, other factors including reproductive or endocrinological health history or biological factors that interact with sex to modify risk warrant further research.

Hospitalisations for pelvic inflammatory disease in young Aboriginal women living in remote Australia: the role of chlamydia and gonorrhoea

ObjectiveAboriginal women living in remote Australia experience a high burden of both chlamydia and gonorrhoea infections and disproportionately high rates of pelvic inflammatory disease (PID). We estimated for the first time the fraction of PID attributable to these infections in young Aboriginal women living in these settings.MethodsUsing published data from two large Australian studies (2002–2013; 2010–2014), we calculated the fraction of emergency department presentations and hospitalisations for PID attributable to chlamydia and/or gonorrhoea infection in Aboriginal women aged 16–29 years living in remote Australia. We used a Monte Carlo simulation to estimate the mean and 95% CIs for the assumed prevalence and population attributable fractions for PID for infection stratifications (chlamydia only, gonorrhoea only and dual infection) as well as for any infection (chlamydia and/or gonorrhoea). Additional outputs were calculated for chlamydia infection with/without gonorrhoea coinfection, and vice versa.ResultsThe prevalence of chlamydia only was 12.9% (95% CI: 11.6% to 14.2%), gonorrhoea only was 7.8% (95% CI: 6.6% to 8.9%) and dual infection was 6.5% (95% CI: 5.8% to 7.2%); rate ratios of PID were 1.9 (95% CI: 1.5 to 2.3), 5.2 (95% CI: 4.3 to 6.4) and 4.6 (95% CI: 3.8 to 5.5), respectively. The overall fraction of PID attributable to chlamydia and/or gonorrhoea was 40.2% (95% CI: 36.0% to 44.4%); any gonorrhoea was 33.4% (95% CI: 29.2% to 37.8%) and any chlamydia was 20.6% (95% CI: 16.9% to 24.6%).ConclusionOur study demonstrates the importance of calculating the fraction of PID related to chlamydia and gonorrhoea in the local context, demonstrating the major contribution gonorrhoea makes to PID hospitalisations among Australian Aboriginal women living in remote settings. To significantly and sustainably reduce the unacceptable rate of PID in this population, strategies are urgently needed to improve timely testing and treatment and recognition and management of PID in primary care.

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.

Contribution of causal factors to disease burden: how to interpret attributable fractions

What proportion of the risk in a given population is attributable to a risk factor? The population attributable fraction (PAF) answers this question. “Attributable to” is understood as “due to”, which makes PAFs closely related to the concept of potential impact or potential benefits of reducing the exposure. The PAF is a tool at the border between science and decision making. PAFs are estimated based on strong assumptions and the calculations are data intensive, making them vulnerable to gaps in knowledge and data. Current misconceptions include summing up PAFs to 100% or subtracting a PAF for a factor from 100% to deduce what proportion is left to be explained or prevented by other factors. This error is related to unrecognised multicausality or shared causal responsibility in disease aetiology. Attributable cases only capture cases in excess and should be regarded as a lower bound for aetiological cases, which cannot be estimated based on epidemiological data alone (exposure-induced cases). The population level might not be relevant to discuss prevention priorities based on PAFs, for instance when exposures concentrate in a subgroup of the population, as for occupational lung carcinogens and other workplace hazards. Alternative approaches have been proposed based on absolute rather than relative metrics, such as estimating potential gains in life expectancy that can be expected from a specific policy (prevention) or years of life lost due to a specific exposure that already happened (compensation).

Risk Classification for Metabolic Syndrome and the Incidence of Cardiovascular Disease in Japan With Low Prevalence of Obesity: A Pooled Analysis of 10 Prospective Cohort Studies

Background It is uncertain whether risk classification under the nationwide program on screening and lifestyle modification for metabolic syndrome captures well high‐risk individuals who could benefit from lifestyle interventions. We examined the validity of risk classification by linking the incidence of cardiovascular disease (CVD). Methods and Results Individual‐level data of 29 288 Japanese individuals aged 40 to 74 years without a history of CVD from 10 prospective cohort studies were used. Metabolic syndrome was defined as the presence of high abdominal obesity and/or overweight plus risk factors such as high blood pressure, high triglyceride or low high‐density lipoprotein cholesterol levels, and high blood glucose levels. The risk categories for lifestyle intervention were information supply only, motivation‐support intervention, and intensive support intervention. Sex‐ and age‐specific hazard ratios and population attributable fractions of CVD, which were also further adjusted to consider non–high density lipoprotein cholesterol levels, were estimated with reference to nonobese/overweight individuals, using Cox proportional hazard regression. Since the reference category included those with risk factors, we set a supernormal group (nonobese/overweight with no risk factor) as another reference. We documented 1023 incident CVD cases (565 men and 458 women). The adjusted CVD risk was 60% to 70% higher in men and women aged 40 to 64 years receiving an intensive support intervention, and 30% higher in women aged 65 to 74 years receiving a motivation‐support intervention, compared with nonobese/overweight individuals. The population attributable fractions in men and women aged 40 to 64 years receiving an intensive support intervention were 17.7% and 6.6%, respectively, while that in women aged 65 to 74 years receiving a motivation‐support intervention was 9.4%. Compared with the supernormal group, nonobese/overweight individuals with risk factors had similar hazard ratios and population attributable fractions as individuals with metabolic syndrome. Conclusions Similar CVD excess and attributable risks among individuals with metabolic syndrome components in the absence and presence of obesity/overweight imply the need for lifestyle modification in both high‐risk groups.