Estimation of Generalized Impact Fraction and Population Attributable Fraction of Hypertension Based on JNC-IV and 2017 ACC/AHA Guidelines for Cardiovascular Diseases Using Parametric G-Formula: Tehran Lipid and Glucose Study (TLGS)

The potential impact fraction of population weight reduction scenarios on non-communicable diseases in Belgium: application of the g-computation approach

BACKGROUND

Overweight is a major risk factor for non-communicable diseases (NCDs) in Europe, affecting almost 60% of all adults. Tackling obesity is therefore a key long-term health challenge and is vital to reduce premature mortality from NCDs. Methodological challenges remain however, to provide actionable evidence on the potential health benefits of population weight reduction interventions. This study aims to use a g-computation approach to assess the impact of hypothetical weight reduction scenarios on NCDs in Belgium in a multi-exposure context.

METHODS

Belgian health interview survey data (2008/2013/2018, n = 27 536) were linked to environmental data at the residential address. A g-computation approach was used to evaluate the potential impact fraction (PIF) of population weight reduction scenarios on four NCDs: diabetes, hypertension, cardiovascular disease (CVD), and musculoskeletal (MSK) disease. Four scenarios were considered: 1) a distribution shift where, for each individual with overweight, a counterfactual weight was drawn from the distribution of individuals with a "normal" BMI 2) a one-unit reduction of the BMI of individuals with overweight, 3) a modification of the BMI of individuals with overweight based on a weight loss of 10%, 4) a reduction of the waist circumference (WC) to half of the height among all people with a WC:height ratio greater than 0.5. Regression models were adjusted for socio-demographic, lifestyle, and environmental factors.

RESULTS

The first scenario resulted in preventing a proportion of cases ranging from 32.3% for diabetes to 6% for MSK diseases. The second scenario prevented a proportion of cases ranging from 4.5% for diabetes to 0.8% for MSK diseases. The third scenario prevented a proportion of cases, ranging from 13.6% for diabetes to 2.4% for MSK diseases and the fourth scenario prevented a proportion of cases ranging from 36.4% for diabetes to 7.1% for MSK diseases.

CONCLUSION

Implementing weight reduction scenarios among individuals with excess weight could lead to a substantial and statistically significant decrease in the prevalence of diabetes, hypertension, cardiovascular disease (CVD), and musculoskeletal (MSK) diseases in Belgium. The g-computation approach to assess PIF of interventions represents a straightforward approach for drawing causal inferences from observational data while providing useful information for policy makers.

Estimates of the global burden of non-Hodgkin lymphoma attributable to HIV: a population attributable modeling study

Background

Human immunodeficiency virus (HIV) significantly increases the risk of non-Hodgkin lymphoma (NHL) development, yet the population-level impact on NHL burden is unquantified. We aim to quantify this association and estimate the global burden of HIV-associated NHL.

Methods

In this meta-analysis, we searched five databases (PubMed, EMBASE, Cochrane Library, Web of Science, Scopus) from database inception up to September 13, 2023, identifying cohort, case-control, or cross-sectional studies with an effective control group to assess NHL risk among individuals with HIV infection, with two authors extracting summary data from reports. Global and regional HIV-associated population attributable fraction (PAF) and NHL disease burden were calculated based on the pooled risk ratio (RR). HIV prevalence and NHL incidence were obtained from the Joint United Nations Programme on HIV/AIDS (UNAIDS) and Global Burden of Diseases, Injuries, and Risk Factors Study 2019. Trends in NHL incidence due to HIV were assessed using age-standardised incidence rate (ASIR) and estimated annual percentage change (EAPC). This study was registered with PROSPERO (CRD42023404150).

Findings

Out of 14,929 literature sources, 39 articles met our inclusion criteria. The risk of NHL was significantly increased in the population living with HIV (pooled RR 23.51, 95% CI 17.62-31.37; I2 = 100%, p < 0.0001), without publication bias. Globally, 6.92% (95% CI 2.18%-11.57%) of NHL new cases in 2019 were attributable to HIV infection (30,503, 95% CI 9585-52,209), which marked a more than three-fold increase from 1990 (8340, 95% CI 3346-13,799). The UNAIDS region of Eastern and Southern Africa was the highest affected region, with 44.46% (95% CI 19.62%-58.57%) of NHL new cases attributed to HIV infection. The Eastern Europe and Central Asia region experienced the highest increase in ASIR of NHL due to HIV in the past thirty years, wherein the EAPC was 8.74% (95% CI 7.66%-9.84%), from 2010 to 2019.

Interpretation

People with HIV infection face a significantly increased risk of NHL. Targeted prevention and control policies are especially crucial for countries in Eastern and Southern Africa, Eastern Europe and Central Asia, to achieve the UNAIDS's '90-90-90' Fast-Track targets. Limited studies across diverse regions and heterogeneity between research have hindered precise estimations for specific periods and regions.

Funding

Sichuan Provincial People's Hospital, Chengdu, China; Health Care for Cadres of Sichuan Province, Chengdu, China; Science and Technology Department of Sichuan Province, Chengdu, China.

Impact of Alcohol Consumption on Multiple Sclerosis Using Model-based Standardization and Misclassification Adjustment Via Probabilistic Bias Analysis

BACKGROUND

The etiology of multiple sclerosis (MS) is still not well-demonstrated, and assessment of some risk factors like alcohol consumption has problems like confounding and measurement bias. To determine the causal effect of alcohol consumption on MS after adjusting for alcohol consumption misclassification bias and confounders.

METHODS

In a population-based incident case-control study, 547 patients with MS and 1057 healthy people were recruited. A minimally sufficient adjustment set of confounders was derived using the causal directed acyclic graph. The probabilistic bias analysis method (PBAM) using beta, logit-logistic, and triangular probability distributions for sensitivity/specificity to adjust for misclassification bias in self-reporting alcohol consumption and model-based standardization (MBS) to estimate the causal effect of alcohol consumption were used. Population attributable fraction (PAF) estimates with 95% Monte Carlo sensitivity analysis (MCSA) intervals were calculated using PBAM and MBS analysis. Bootstrap was used to deal with random errors.

RESULTS

The adjusted risk ratio (95% MCSA interval) from the probabilistic bias analysis and MBS between alcohol consumption and MS using the three distribution was in the range of 1.93 (1.07 to 4.07) to 2.02 (1.15 to 4.69). The risk difference (RD) in all three scenarios was 0.0001 (0.0000 to 0.0005) and PAF was in the range of 0.15 (0.010 to 0.50) to 0.17 (0.001 to 0.47).

CONCLUSION

After adjusting for measurement bias, confounding, and random error alcohol consumption had a positive causal effect on the incidence of MS.

Population attributable fraction estimates of cardiovascular diseases in different blood pressure levels in a large-scale cross-sectional study: a focus on prevention strategies and treatment coverage

OBJECTIVE

Hypertension is one of the major modifiable risk factors in developing cardiovascular diseases (CVD). Hence, we aimed to ascertain age- and sex-specific population attributable fraction (PAF) for CVD in different blood pressure levels to implement efficient preventive strategies at the population level.

METHODS

Participants' data were obtained from the Iranian stepwise approach for surveillance of noncommunicable disease risk factors (STEPs) survey to calculate PAF in four subsequent phases. In phase 0, PAF was measured, irrespective of the diagnosis status. In phase 1, the theoretical minimum range of 115 ≤SBP less than 130 mmHg was considered as the low-risk and measurements equal to or higher than 130 mmHg as the high-risk group. Across phase 2, patients were divided into normal and hypertensive groups based on the American College of Cardiology/American Heart Association guideline. In phase 3, patients were divided into two categories based on treatment coverage.

RESULTS

A total number of 27 165 participants aged ≥25 years had valid blood pressure measurements and were enrolled. Phase 0: PAF generally had an upward trend with age advancing. Phase 1: participants with BP ≥130 mmHg comprised the largest PAF, extending from 0.31 (0.25-0.37) in older male individuals to 0.85 (0.79-0.91) in younger females. Phase 2: higher values were found in younger ages for hypertension. Phase 3 represented that attributable fractions among hypertensive patients who received treatment were much lower than drug-naïve hypertensive participants.

CONCLUSION

Our study enlightens the necessity for implementing effective screening strategies for the younger generation and providing adequate access to antihypertensive medications for the low-risk population.