Population Health Metrics最新文献

Background: Although chronic diseases represent a growing global health priority, significant gaps remain in understanding the burden of multimorbidity. This study developed an original methodology to estimate the burden of thirty major chronic diseases at the individual patient level, in terms of Disability-Adjusted Life years (DALYs), Years Lived with Disability (YLD), and Years of Life Lost due to premature death (YLL).

Methods: The Disability weights (DWs) estimated by the Global Burden of Disease (GBD) study were integrated with information from healthcare databases. A panel of medical specialists established the criteria for assigning the level of severity, and thus a specific DW, to each chronic disease. The patient-centred YLD metric was estimated as the cumulative of the combined DWs over the previous ten years. We also measured the Disability Weight Fraction of each coexisting disease (DWF). We illustrated this method using healthcare databases from a large Italian region to assess the impact of chronic diseases and multimorbidity at progressive levels of analysis: health status of the regional chronic disease population, burden of individual chronic diseases and patient clinical complexity.

Results: Unlike the standard GBD estimates, the new method provided precise metrics for multimorbidity, as shown by the comparison on the disability calculated for 4 main chronic diseases. Real-world estimates from the new method highlighted that comorbidity accounted for most of the YLD: for instance, about 88% of the YLD of patients with heart failure was explained by concomitant conditions. DALYs were higher among females than males in most age groups. In the younger groups, psychiatric conditions explained approximately 40% and 25% of YLD among males and females, respectively. Finally, the patient-centred YLD metric was a good predictor of death (c-statistic = 0.779).

Conclusions: This novel method provides insights into the measurement of multimorbidity, based on the disability fraction of each concomitant health condition, which is crucial for defining priority areas for healthcare interventions. The patient-centred estimates may serve to identify subgroups of chronic disease patients with specific healthcare needs and trajectories among a given population. Importantly, measuring the relative contribution of each disease to the patient's burden of multimorbidity favours the planning of multidisciplinary care pathways that are more responsive to individual needs.

Background: Life's Crucial 9 (LC9), an extension for Life's Essential 8 with the addition of psychological health, provides a new tool for assessing cardiovascular health. However, the association between LC9 and cardiovascular diseases (CVD) in elderly hypertensive patients remains unclear.

Methods: A cross-sectional survey was carried out among elderly hypertensive patients from the National Basic Public Health Service Programs in Jia County, Henan Province, from July 1 to August 31, 2023. The primary outcome was defined as a composite CVD (coronary heart disease and stroke). The LC9 consisted of 9 metrics (diet, physical activity, nicotine exposure, sleep, psychological health, body mass index, blood pressure, fasting blood glucose, and non-high-density lipoprotein cholesterol). The logistic regression model was established to estimate the odds ratio (OR) and 95% CI of CVD across different LC9 groups.

Results: A total of 13,032 elderly hypertensive patients (mean age: 73.45) were analyzed. 5,664 (43.46%) patients were diagnosed with CVD (including 4,455 coronary heart disease and 2,062 stroke). The median (interquartile range) of the LC9 score in all patients, those without CVD, and those with CVD were 65.56 (58.33-72.22), 66.67 (59.44-73.33), and 64.44 (56.67-71.11), respectively. As the number of ideal LC9 metrics increased, the prevalence of CVD decreased (P_trend <0.05). After adjusting for potential confounders, the OR (95%CI) of CVD in the LC9 score was 0.80 (0.76 - 0.83). Compared with the low group, the OR (95%CI) of CVD in the moderate group was 0.66 (0.58-0.76), and 0.49 (0.41-0.59) for the high group, respectively. Notably, there was a negative dose-response relationship between LC9 and its domain scores and CVD (P-nonlinear > 0.05).

Conclusion: Higher LC9 scores and more ideal health metrics, including psychological health, are associated with lower CVD risk in elderly hypertensive patients, highlighting the need for policy efforts to strengthen primary healthcare, expand access to preventive services, and promote comprehensive CVH management in this high-risk population.

Background: High health risk and low management compliance pose significant challenges in controlling hypertensive patients' blood pressure. Therefore, this study aims to investigate the impact of follow-up services on blood pressure control at the primary level.

Methods: A total of 871 hypertensive patients consecutively enrolled from 2016 to 2021 were randomly selected from Qianjiang County, Hubei Province and Changsha County, Hunan Province of China. Blood pressure measurements (systolic blood pressure, SBP, and diastolic blood pressure, DBP) were defined as outcome variables, whereas the interval and regularity of follow-up visits served as key explanatory variables. A fixed-effects model was used to examine the influence of follow-up behaviors on blood pressure control among hypertensive patients.

Results: An increased frequency of follow-up visits, particularly those closer to or above the minimum threshold outlined in the 2020 Guidelines for Prevention and Control of Hypertension in China, was found to be beneficial for blood pressure control. The effectiveness of blood pressure control further improved with shorter follow-up intervals. However, when the number of follow-up visits deviated significantly from the minimum threshold, optimizing blood pressure control was achievable by extending follow-up intervals.

Conclusions: A moderate increase in follow-up visits may be more effective in reducing hypertension patients' blood pressure than limiting follow-up intervals. It is suggested that primary hypertension management should focus on the regularity and intervals of follow-up visits and flexibly complete follow-up tasks. Moreover, the formal review of follow-up frequency and intervals, along with the efficiency of interventions implemented, should not be overlooked in hypertension control.

Background: Evidence suggests that the COVID-19 pandemic has exacerbated social and demographic inequalities in the communities through pathways of unequal exposure, vulnerability, and susceptibility. In Tanzania, evidence on COVID-19-related mortality is limited to health facility data, with little to no information on the mortality patterns in the general population. This study assessed sociodemographic inequalities in all-cause mortality during the COVID-19 period in north-western Tanzania.

Methods: We utilized available longitudinal data from the Magu Health and Demographic Surveillance System (HDSS) from January 2018 to December 2021. We compared the crude death rates between subgroups of age, sex, area of residence, and wealth index for a period before (2018/2019) and during (2020/2021) the COVID-19 pandemic. To quantify how mortality risk varies across the subgroups we fitted a Cox proportional hazard model with an interaction of the COVID-19 period.

Results: Overall mortality declined from 5.9 in 2018/2019 to 5.4 and 5.5 deaths per 1000 person-years in 2020 and 2021, respectively. We observed an increase in differences in crude death rates by age groups, area of residence, and wealth quintiles during the COVID-19 period. In the Cox proportional hazards model, compared to adults aged 15-49, we observed greater mortality risk in children under five (AHR:2.9; 95%CI: 2.2-3.9), older individuals aged 50-64 years (AHR:3.02; 95%CI:2.11-4.33) and 65 + (AHR:18.65; 95%CI:14.28-24.35) during COVID-19 period. Males were also at greater risk of death compared to females (AHR:1.30; 95%CI:1.06-1.59).

Conclusion: Despite the overall mortality decline during the pandemic, we observed an increased risk of mortality among vulnerable subgroups (aged < 5 years and > 60 years) in the population. This highlights the need to take into account vulnerable subpopulations when addressing major public health issues in communities.

Effective identification and correction of diabetes mellitus (DM)-related garbage codes (GCs) in mortality surveillance data is crucial for accurately estimating regional DM mortality rates. This study applied a structured, three-step approach-using standard WHO ICD-10 mortality coding rules, coarsened exact matching (CEMM), and fixed proportion reassignment (FPRM)-to redistribute diabetes-related GCs in Weifang's mortality data (2010-2022). Using ICD-10 coding rules, we reclassified 29 deaths originally assigned to DM as the underlying cause of death (UCD) to other causes, and reassigned 1,945 records previously not attributed to DM to DM as the UCD. CEMM then reclassified 283 DM-related GC records to DM, followed by FPRM, which reassigned 160 "unknown cause" records to DM. Together, these steps increased the number of DM deaths by 22.82%. Based on the reallocated data, crude DM mortality rates rose from 7.64 to 17.75 per 100,000 between 2010 and 2022, with males experiencing a greater overall increase than females. While no new algorithms were developed, this study demonstrates how internationally recommended coding standards-often neglected in routine subnational settings-can be systematically and rigorously applied to improve DM mortality surveillance. This work highlights operational gaps in local death certification and presents a replicable protocol for enhancing mortality data reliability using existing tools.

Background: Utilization of unhygienic menstrual products has been associated with various adverse health consequences, particularly in many low- and middle-income countries (LMICs), including Bangladesh. In this context, this study attempted to measure socioeconomic inequalities in sanitary napkin use among women aged 15-49 and assess its spatial pattern at the disaggregated level (district).

Methods: We used the latest available nationally representative cross-sectional Bangladesh Multiple Indicator Cluster Survey (MICS) 2019 data. The analytical sample size was 54,702 reproductive-aged (15-49 years) women. The Erreygers Index (EI) and the Wagstaff Index (WI) were employed to measure and decompose the socioeconomic inequalities in sanitary napkin use. Natural Break (Jenks) classification method, Global Moran's I and the Cluster and Outlier Analysis were used to analyze the spatial pattern of socioeconomic inequalities at the district level.

Results: The findings reveal that approximately 26.22% of women used sanitary napkins at the national level. Both the EI (0.41208; p-value < 0.001) and the WI (0.53251; p-value < 0.001) indicate a pro-rich inequality in sanitary napkin use. Decomposition results indicated that wealth status, educational attainment, household characteristics (particularly educational attainment of household head) and exposure to media were the most important factors accounting for socioeconomic inequalities. From the spatial analyses, we found significant district-level variations in both sanitary napkin use and its socioeconomic inequalities. Global Moran's I value indicated positive spatial autocorrelation, meaning that similar values tend to cluster together. Notably, a northwestern and southeastern divide was found between High-High and Low-Low clusters of socioeconomic inequalities.

Conclusions: Our study provides evidence for informed policymaking targeting women from the lower socioeconomic stratum, especially those living in the northwestern and southeastern regions to increase sanitary napkin use.

Background: Climatic factors have been associated with the occurrence of several diseases known as climate-sensitive diseases (CSDs). We selected the following categories of disease to represent CSDs for this study: vector-borne diseases (dengue, leishmaniasis, malaria, schistosomiasis, yellow fever, and zika), infectious-diseases (respiratory infections), non-communicable diseases (chronic respiratory and cardiovascular diseases) and water-borne diseases (diarrhea). This study aimed to describe the historical trends and spatial distribution of mortality and morbidity of these selected Climate Sensitive Diseases in Brazil between 1990 and 2017. The analysis is based on findings obtained by the 2017 Brazilian Global Burden of Diseases (GBD) Study.

Methods: Yearly CSD data was taken from the 2017 Brazilian GBD Study for the years between 1990 and 2017. This data was organized by age group and sex at the country level, for 26 states and one Federal District (known as Federative Units), and at the regional level.

Results: Cardiovascular and respiratory diseases presented the greatest disability adjusted life-years (DALYs) in Brazil, followed by chronic and infectious respiratory diseases, although only a small fraction could be attributed to climate changes. Among the vector-borne diseases, the burden of leishmaniasis and malaria have decreased since 1990, while the burden of dengue has increased. The burden of other vector-borne diseases (malaria and yellow fever) increased since 2015, in addition to the recent introduction of zika virus in Brazil. The GBD rates of infectious diseases were greater in predominately the Amazon and northeast regions. This finding contrasts with dengue and zika for which an increase in DALYs rate was observed southeast and central-west, besides the northeast region. The lowest DALYs rates for dengue were observed in the south region, which also experiences the lowest temperatures.

Conclusions: The burden of CSDs in Brazil has increased since 1990 considering non-communicable and communicable diseases. The potential impact of climate change on such diseases must be evaluated considering disease dynamics and spatial specificities, such as land cover and climate patterns. The main challenges in Brazil related to CSDs are the investments needed for research regarding the increase in the burden of CSDs, for vector control and social health determinants mitigation.

Background: The COVID-19 pandemic has significantly increased mortality rates, disrupting historical trends and making it challenging to forecast future life expectancy levels. São Paulo, the first city in Brazil to report a COVID-19 case and death, saw a decrease of over four years in life expectancy at birth for males and over three years for females between 2019 and 2021. São Paulo has been at the forefront of the demographic transition in the country and experienced a nonlinear mortality decline over the twentieth century. The city's historical mortality trajectory and the disruptive effects of COVID-19 have introduced challenges to mortality forecasting.

Methods: In this study, we used a unique dataset dating 1920-2022 to forecast life expectancy in São Paulo until 2050 using the Lee-Carter and Lee-Miller methods. Mortality rates were obtained from a combination of deaths gathered by the SEADE Foundation (SEADE) and population collected by the Brazilian Institute of Geography and Statistics. To mitigate the dependency on the fitting period's choice and better incorporate the effects of the recent mortality shock, we used different baseline periods, using all years from 1920 to 1995 as the starting year of the analysis and six scenarios for post-pandemic mortality levels. Prediction intervals were derived from simulated trajectories of the models' time indices. Based on 73,200 simulations for each year between 2023 and 2050, we synthesized the resulting life expectancy forecasts into median values and 95% prediction intervals (PI).

Results: By 2050, we predict that life expectancy at birth in São Paulo will reach approximately 81.4 years for men and 88.3 years for women. Also, within the 95% PI, we estimated that by 2045, male life expectancy could reach the levels of best-performing countries.

Conclusions: Our approach is among the first attempts to forecast mortality in the presence of shocks. Additionally, by evaluating different baseline periods, we advocate for the adoption of more accurate forecasting strategies, particularly in contexts of recent mortality decline. These findings provide valuable resources for policymakers and researchers working to address public health challenges arising from the pandemic and plan for the future well-being of many populations.

Background: The COVID-19 pandemic profoundly disrupted workplace attendance, yet its impact on cause-specific work absence remains largely unexplored.

Aim: To estimate the cause-specific excess/reduced work absence associated with COVID-19 in Poland.

Methods: Following the concept of excess mortality, we define excess work absence as the difference between observed and expected absence, where the latter reflects the level anticipated in the absence of the pandemic. Using time-series analysis (Seasonal Autoregressive Integrated Moving Average) on pre-pandemic (2012-2019) quarterly (Q) social insurance data, we forecasted absence rates for disease groups (classified by ICD-10 chapters) and caregiving-related absenteeism. Forecasted absence rates were then compared to observed values during 2020-2024, allowing for the identification of excess or reduced work absence.

Results: We observed notable deviations in work absence rates during the pandemic period (until the end of Q1-2022). The highest excess absence was identified in caregiving-related absenteeism at the pandemic's onset, exceeding expected levels by over fivefold. A mental health crisis that began with the pandemic resulted in four consecutive quarters of excess absence, reaching a 54% excess in Q2-2020. We identified a notable excess absence in three ICD-10 chapters that reflect the indirect effects of the pandemic, such as increased diagnostic uncertainty, modified coding practices during early COVID-19 waves, and widespread implementation of public health interventions. Absence rates were lower than expected in neoplasms, endocrine and digestive diseases until the end of the pandemic period, likely reflecting reduced healthcare accessibility. Similarly, absence related to injuries and poisoning was below the expected level until mid-2022, indicating decreased social mobility.

Conclusions: COVID-19 substantially reshaped work absence patterns in Poland, particularly during the early pandemic phase. Pronounced increases and decreases were identified across disease categories. These diverging trends plausibly reflect both the COVID-19's effects on the development of other conditions and disruptions in healthcare access. These findings highlight the need for disease-specific policy responses to mitigate future health crises and ensure continuity of care during pandemics.

Background: Previous research has explored the association between the ratio of high-density lipoprotein cholesterol to C-reactive protein (HDL-C/CRP) and the mortality risk in individuals with heart failure. This study aims to investigate the correlation between HDL-C/CRP ratio and all-cause mortality through the analysis of extensive data derived from the general public.

Methods: This study analyzed NHANES data and surveyed 28,544 adults from America. Survival outcomes were evaluated using Kaplan-Meier curves, while a survey-weighted multivariable Cox proportional hazards model was employed. Restricted cubic splines (RCS) and hierarchical analysis were used to investigate associations and interactions, respectively. Additionally, the ability of lnHDL-C/CRP to predict all-cause death was assessed using receiver operating characteristic curves.

Results: During a mean follow-up period of 156.5 months, 5965 (20.9%) died from any cause. Weighted RCS analysis revealed an L-shaped association between HDL-C/CRP ratio and all-cause mortality. Below a lnHDL-C/CRP of 6.65 (HDL-C/CRP ratio of 773), the likelihood of all-cause death decreased by 14% with every 1-point rise in lnHDL-C/CRP [HR (95% CI) 0.86 (0.81, 0.90)]. Including lnHDL-C/CRP in the baseline risk model significantly enhanced its predictive power for mortality. Consistent findings were observed in subgroups, with individuals under 60 years or with a BMI over 30 showing a stronger correlation between HDL-C/CRP ratio and overall mortality risk.

Conclusions: The association between HDL-C/CRP ratio and overall mortality in the general US adult population is non-linear, particularly significant in adults under 60 years old and obese individuals. HDL-C/CRP ratio could be regarded as a potential marker for assessing mortality risk.