Population Health Metrics最新文献

Purpose: Public health surveillance systems require high-quality data to represent the population. In the absence of comprehensive or random testing throughout the COVID-19 pandemic, we have developed a proxy method for synthetic random sampling to estimate the actual community-level viral incidence, based on viral testing of patients who are asymptomatic and present for elective procedures within a hospital system.

Methods: The approach collects routine testing data on SARS-CoV-2 exposure among outpatients and performs statistical adjustments of sample representation using multilevel regression and poststratification (MRP), a procedure that adjusts for nonrepresentativeness of the sample and yields stable small group estimates. We extend MRP to accommodate time-varying data and granular geography.

Results: We have developed an open-source, user-friendly MRP interface for public implementation of the Bayesian analysis workflow. We illustrate the MRP interface with an application to track community-level COVID-19 viral transmission in Michigan. We present the estimated infection rate over time for the targeted population and across demographic and geographic subpopulations.

Conclusion: The interface provides timely, substantive insights into population health trends and serves as a valuable surveillance tool for future epidemic preparedness. Beyond monitoring COVID-19, the MRP interface can analyze a wide range of health and social science data, making it broadly applicable to diverse research areas with reproducibility and scientific rigor.

Globally, cardiometabolic diseases (CMDs) are major health issues that affect the health of workforce. This study aimed to investigate the impact of employment status on transition from a healthy state to cardiometabolic multimorbidity in Chinese population. Data from China Health and Retirement Longitudinal Study (2011-2020) was utilised. Analytical sample comprised 7,681 men and women (≥ 45 years) free of CMDs at baseline. A multistate model was applied to investigate the impact of baseline employment status on the transition rates from a healthy state to cardiometabolic mono-morbidity and subsequently to multimorbidity. Inverse probability weighting was applied to account for the complex survey design. During an average follow-up time of 5.7 years, 3,324 (43.28%) participants developed one or more CMDs. After adjusting for age and sex, compared to non-agricultural employees, non-agricultural retirees had significantly higher risks and agricultural self-employed workers had only marginally higher risk of CMDs. After further adjustment for sociodemographic factors, health behaviours, and BMI, non-agricultural retirees remained significantly associated with a higher rate of transition from a healthy state to cardiometabolic mono-morbidity [HR 1.24 (95% CI 1.01-1.54)] compared to non-agricultural employees. There was no statistically significant increase in transition to multimorbidity risk in any group. Control of CMDs in Chinese older population should consider people's employment characteristics.

This study investigates territorial disparities in healthcare outcomes and service provision across Italian regions through a multidimensional analysis based on the BES (Equitable and Sustainable Well-being) framework. Two distinct but complementary sets of indicators are considered: one focusing on health outcomes (life expectancy, healthy life expectancy, and avoidable mortality), and the other on the structural availability and accessibility of healthcare services (residential beds, home care, access difficulties, and unmet needs). Using the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm, the study identifies spatial clusters of regions with similar profiles. Results reveal persistent North-South divides in both health and service indicators, with southern regions consistently exhibiting lower performance. While the Health dataset shows relatively homogeneous clusters, the Services dataset highlights more marked disparities. The use of DBSCAN proves effective in detecting regional groupings even in a relatively small sample, offering a valuable tool for territorial policy planning and sustainability-oriented healthcare strategies.

Background: Indonesia is the second-highest contributor to global tuberculosis (TB) cases, accounting for 10% of the total. While previous studies have explored TB patterns in specific regions, a comprehensive nationwide analysis at a fine spatial scale is lacking. This study investigated spatiotemporal patterns of TB incidence and mortality, identified geographical hotspots, and examined their association with risk factors to inform public health policy.

Methods: This retrospective study analyzed notified TB cases and deaths during treatment from Indonesia's National Tuberculosis Surveillance System across 514 districts between 2017 and 2022. Spatiotemporal Bayesian hierarchical modeling was employed to identify high-risk areas and assess associations with potential risk factors. The best-fitting model was determined by evaluating various spatial and temporal random effect structures and likelihood assumptions.

Results: TB incidence fluctuated with a trough during the COVID-19 pandemic and an overall increase, while mortality increased over time. Incidence hotspots clustered in urbanized areas, while mortality hotspots were scattered across the country. The best-fitting model to estimate risk factors for both outcomes was Poisson likelihood. This indicated that TB incidence was spatiotemporally positively linked to better healthcare access (RR: 1.016; 95% CI: 1.007-1.025) and higher municipal human development index (MHDI, RR: 1.062; 95% CI: 1.049-1.075). Mortality was associated with low treatment coverage (RR: 0.610; 95% CI: 0.552-0.674) and success rates (RR: 0.595; 95% CI: 0.491-0.721).

Conclusions: Fluctuating TB incidence, hotspots concentrated in urbanized areas with better healthcare access and higher MHDI as well as increasing mortality linked to poor treatment outcomes underscore the need for targeted public health interventions to expand access to care, improve treatment adherence, and address the socioeconomic disparities driving TB mortality.

Background: Achieving equitable global health frameworks requires the intentional integration of diverse voices-both professional and lived-from across the high-resourced Global North (GN) and low-resourced South (GS). It is, however, rare that Core Set development using the International Classification of Functioning, Disability and Health (ICF) has equal data representation from both regions. Using the data from the development of Core Sets on deafblindness, we explored a unique opportunity, given the geographic distribution of data sources. We compared ICF category frequencies from the GN and GS across body structure, body function, activities and participation, and environmental factors.

Methods: We divided the data from an expert survey (n = 105) and from interviews with deafblind individuals (n = 72) by country of origin into GN and GS using the Brandt Line, representing all six regions of the WHO (28 countries). Using the ICF coding system to identify perceived categories of functioning, aggregated frequencies of unique ICF categories were compared across ICF components and chapters using chi-square statistics.

Results: Survey data showed no significant geographic differences across activities and participation or environmental factors; however, qualitative interviews revealed significant deviations. For activities and participation, GN emphasized d9205 (socializing) and d940 (human rights), while GS highlighted d760 (family relationships). For environmental factors, GN focused on e5800 (health services) and e298 (environmental adaptations), whereas GS emphasized e5550 (associations), e310 (family), and e325 (community supports). Within the GN, survey and interview data also differed. Surveys emphasized e310, e315 and e320 (supports), while interviews highlighted e410, e425, e450, and e455 (attitudes). For activities and participation, d660 (assisting others) was more frequent in interviews. The GS showed significant within-region differences for e4 (attitudes), d9 (community, social and civic life) and d2 (general tasks and demands).

Conclusions: Findings highlight the regional variations in activities and participation among individuals with deafblindness as they reflect differences in environmental factors. Rooted in cultural and resource differences, geographic region itself constitutes a key environmental factor. Expert perspectives may underrepresent differences in lived environmental realities of individuals with deafblindness. Future Core Set development will benefit from including more diverse sources.

Background: Arterial hypertension (AH) is a major contributor to cardiovascular morbidity and mortality worldwide. This study aimed to identify sociodemographic and biological factors associated with hypertension in a nationally representative adult sample in Kazakhstan.

Methods: A cross-sectional WHO STEPS survey (October 2021-May 2022) included 6,720 adults aged 18-69 years from all regions of Kazakhstan. Sociodemographic, behavioral, physical and biochemical data were collected, hypertension was defined by ESC/ESH criteria.

Results: Crude AH prevalence was 16.0% (95% CI 15.1-16.8) and increased sharply with age from 3.0% at 18-24 years to 46.7% at ≥ 65 years (p < 0.001). Men had higher systolic (SBP) and diastolic blood pressure (DBP) than women (126/82 vs. 119/79 mmHg, p < 0.001) and a less favorable BP profile. Urban residents were younger and more likely to report smoking and alcohol use than rural residents (21.4% vs. 14.8% and 6.5% vs. 3.2%, p < 0.001), whereas rural participants had higher BMI, SBP, DBP, total cholesterol and HbA1c (p < 0.05). Hypertension prevalence showed marked regional heterogeneity, from 9.5% in Kyzylorda and 9.6% in Astana to 25.3% in Akmola and 23.7% in North Kazakhstan. In adjusted models, hypertension was independently associated with older age (OR 1.894, 95% CI 1.780-2.014, p < 0.001), higher BMI (OR 1.597, 95% CI 1.484-1.719, p < 0.001), higher total cholesterol (OR 1.171, 95% CI 1.098-1.249, p < 0.001) and urban residence (OR 1.304, 95% CI 1.121-1.517, p = 0.001), while female sex was protective (OR 0.596, 95% CI 0.511-0.696, p < 0.001). Smoking, HbA1c, education and ethnicity were not significant after adjustment, and alcohol intake showed a statistically detectable but clinically minimal association (OR 0.997, 95% CI 0.995-0.999).

Conclusion: In 2021-2022, hypertension affected roughly one in six adults in Kazakhstan and rose steeply with age. Modifiable metabolic factors, particularly excess body weight and elevated cholesterol, were the main drivers of risk, while an independent urban effect and pronounced north-south regional differences highlight the need for targeted weight and lipid management and intensified long-term risk control, especially in cities and high-prevalence northern regions.

Background: The term "Deaths of Despair" (DoD) refers to mortality due to alcohol consumption, drug use, and suicides. While extensively studied in the United States, where these deaths have markedly increased, less is known about their patterns in other contexts. This study explores the relevance of this concept to Italy, a country with comparatively lower rates, to determine whether these causes of death exhibit common trends and can be meaningfully grouped under a single category.

Methods: We use cause-specific mortality data from the Italian National Institute of Statistics covering the period 1983 to 2018. Data are aggregated by gender and five-year age groups at the NUTS1 regional level. The Potential Gain in Life Expectancy is used to assess the impact of each cause on overall mortality. To explore potential long-term relationships between the causes and across regions, we apply Cointegration Analysis to the time series.

Results: The analysis shows a general decline in mortality from causes typically associated with despair in Italy, mainly driven by a reduction in alcohol-related deaths. Drug-related mortality and suicide show more heterogeneous trends across regions and over time. Cointegration Analysis reveals no evidence of long-term dependency among these causes or across regions, with only a few exceptions. This indicates that the observed causes do not share a common underlying temporal structure.

Conclusions: Findings suggest that in the Italian context, deaths from alcohol, drugs, and suicide do not follow a unified pattern and should not be treated as a single category. Rather, they represent distinct public health issues with different regional trajectories and determinants. As such, they require targeted and differentiated policy responses rather than a unified approach.

Background: Loneliness and social isolation are more prevalent among obese individuals. This study aims to explore the association of the level of loneliness and social isolation with the excess risk of mental disorders among obese people compared with non-obese people.

Methods: A total of 219,086 participants (109,543 obese participants and 109,543 matched non-obese participants) from the UK Biobank were included at baseline. Loneliness and social isolation were assessed using a two-item scale and a three-item scale, respectively. Incident mental disorders, including substance use, psychotic disorders, mood disorders, depression, anxiety disorders, post-traumatic stress disorder, and behavioral syndromes, were ascertained through linkage to primary and secondary care records.

Results: During a median (IQR) follow-up of 12.40 (11.50-13.20) years, a total of 18,280 obese participants developed mental disorders. Compared to the least lonely group, obese people in the moderate and most lonely groups had a significantly and progressively higher risk of mental disorders (moderately lonely: HR 1.37, 95% CI 1.33-1.42; most lonely: HR 1.73, 95% CI 1.65-1.81; P-trend < 0.001). We observed a similar pattern in terms of social isolation. The relative importance of loneliness and social isolation in predicting mental disorders ranked third and eighth among traditional risk factors. Compared to non-obese individuals, the excess risk of mental disorders for obese individuals varied considerably by levels of loneliness and social isolation, with HRs ranging from 1.05 in the least lonely to 1.79 in the most lonely, and from 1.14 in the least isolated to 1.36 in the most isolated.

Conclusion: Alleviating loneliness and social isolation was associated with lower obesity-related excess risk of mental disorders. Our finding suggests the incorporation of social networking platforms and support systems into intervention strategies to effectively mitigate the mental health issues in obese population.

Clinical trial registration number: Not applicable. (This study is an observational analysis based on UK Biobank data and does not involve a clinical trial. This research was conducted under UK Biobank application no. 88159. The UK Biobank study was approved by the North West Multi-Centre Research Ethics Committee (11/NW/0382). All participants provided informed consent through electronic signature at baseline assessment.).

Background: Financial resources beyond housing may influence survival in later life. Given China's rapid population aging and high home ownership, focusing on non-housing assets can clarify wealth-health links. We therefore examined the association between total non-housing assets and all-cause mortality among Chinese middle-aged and older adults.

Methods: A nationwide cohort of 12,670 adults (aged 45-85) was established using the harmonized CHARLS dataset (2011-2018). All-cause mortality was ascertained through 2020 by supplementing harmonized data with vital status information from the raw CHARLS 2020 wave. The main exposure was total non-housing assets. In addition, non-housing assets were combined with household consumption (median split) to create four joint groups: Group 1 (low assets/low consumption), Group 2 (low assets/high consumption), Group 3 (high assets/low consumption), and Group 4 (high assets/high consumption). All-cause mortality was tracked. Baseline characteristics and mortality were presented by asset quartile and asset consumption group. Survival curves, Cox models (adjusted for confounders), and restricted cubic splines assessed associations. Subgroup and interaction analyses, especially for marital status, were visualized using forest and stratified plots.

Results: During a 9-year follow-up, 2,418 deaths occurred. Higher total non-housing assets were associated with lower mortality: Q4 (highest) vs. Q1 (lowest), adjusted HR = 0.79 (95% CI 0.68-0.91). In fully adjusted models, we also observed a graded inverse association across asset-consumption groups (P for trend < 0.001); high-consumption categories remained protective (Group 2: HR = 0.85, 95% CI 0.74-0.97; Group 4: HR = 0.75, 95% CI 0.65-0.85). Marital status showed a significant interaction with asset level (P‑interaction < 0.001).

Conclusions: Greater non-housing assets was associated with lower mortality. Marital status has a significant interacting effect on this association. Focus should be on vulnerable elderly groups with middle-low assets, low consumption, or those who are non-married.