Urban Scaling of Health Outcomes: a Scoping Review

Time series analysis and scaling law characteristics of viral hepatitis from 2004 to 2023 in Zhejiang Province, China

BACKGROUND

Hepatitis significantly increases the global disease burden and has become a major public health issue worldwide. China is a high-risk area for viral hepatitis, which is also a serious public health problem.

METHODS

The scaling relationship between various types of hepatitis and population size was explained by a scaling law. Fixed-effects and random-effects meta-analyses were used to calculate a combined index of β based on the single-scale index from 2004 to 2023. Furthermore, the X11 process was employed to identify the structural components of the time series of various types of hepatitis.

RESULTS

In the past 20 years, the proportion of patients with viral hepatitis in Zhejiang Province has changed significantly, and hepatitis B remains the main type of hepatitis, accounting for approximately 70% of all hepatitis cases. The proportion of hepatitis C and E cases has been increasing, whereas the proportion of hepatitis A cases has been decreasing since 2004 and has remained at a low level (approximately 3%) since 2010. The combined scaling exponents of hepatitis A, hepatitis B, hepatitis C, hepatitis E and unclassified hepatitis based on the random effects model were 0.88 (95% confidence interval(CI): 0.78 to 0.98), 0.78 (95% CI: 0.70 to 0.86), 1.18 (95% CI: 1.11 to 1.26), 0.91 (95% CI: 0.86 to 0.97) and 0.89 (95% CI: 0.79 to 1.00), respectively.

CONCLUSION

In the past 20 years, the epidemic situation of hepatitis A, hepatitis B and unclassified hepatitis has shown a significant downward trend, whereas the proportions of hepatitis C and hepatitis E among those with viral hepatitis have increased annually. The combined scaling exponent and development trends of the five types of hepatitis show significant heterogeneity. Overall, hepatitis C exhibits superlinear characteristics, whereas other types of hepatitis exhibit sublinear characteristics. Different types of hepatitis exhibit distinct epidemic characteristics and require targeted prevention and control measures.

Associations between gun violence exposure and suicide mortality rates in US counties

PURPOSE

Gun violence traumatizes communities and places a heavy burden on the mental health of those exposed. This ecological study examines the association between gun violence exposure and suicide mortality rates in US counties for the period 1999-2020 at various urbanicity levels.

METHODS

A Bayesian hierarchical Gamma-Poisson model with state random effects was employed to model the age-adjusted suicide mortality rates which adjusted for sex ratio, urbanicity, social vulnerability, gun ownership, culture of honor, and exposure spillovers from neighbouring counties.

RESULTS

Results indicate a small significant positive association between gun violence and suicide mortality rates. Urbanicity levels do not appear to modify this association, although the association may be slightly smaller for large urban metros.

CONCLUSIONS

Gun violence exposure may be positively associated with suicide mortality in US counties.

Scaling of cardiovascular risk factors in 230 Latin American cities

Urbanization results in increased numbers of people living in cities and poses challenges and opportunities to public health policies. Studies of urban scaling have unveiled how cities' socio-economic and infrastructural attributes vary systematically with city size. Previous studies have explored the scaling properties of health outcomes across metropolitan areas in different countries, but chronic diseases have been infrequently examined. This paper examines scaling behaviors of 4 cardiovascular risk factors: hypertension, diabetes, tobacco smoking, and obesity across 230 cities in six countries of Latin America. In analyses pooled across countries, diabetes and hypertension showed weakly superlinear scaling (higher prevalence in larger cities). In comparison, obesity showed linear scaling, and tobacco showed weakly sublinear scaling (lower prevalence in larger cities), although most coefficients did not differ significantly from the null. In country-specific analyses, hypertension and diabetes tended to show a superlinear pattern across most countries, obesity tended to show a sublinear pattern in most countries, and tobacco tended to be superlinear (in contrast to the analysis pooled across countries where it was sublinear). Results suggest the need to examine further the drivers of this varying scaling of risk factors.

Associations between environmental perception and self-rated health in the city hierarchy of China: Findings from a national cross-sectional survey

Identifying environmental determinants of health and clarifying their variations is crucial for health promotion in different cities by providing tailored intervention strategies. Although the association between perceived urban environment and health (e.g., self-rated health) has been repeatedly explored, most studies have focused on cities of a specific size, and it is still unknown whether either significant environment variables or the magnitude of the association would vary across different-sized cities. This study investigated how perceived urban environment variables significantly associated with individuals' self-rated health varied from small cities to mega cities in China, based on a national survey including 5963 valid respondents. The results showed that the relationship between self-rated health and city size was U-shaped, with respondents in medium and large cities reporting a low-level self-rated health. Perceived greenness, public facilities, housing supply, and medical services were positively and significantly associated with self-rated health, with the odds ratio (OR) of 1.37 (95%CI: 1.29-1.46), 1.27 (95%CI: 1.19-1.35), 1.14 (95%CI: 1.09-1.20), and 1.17 (95%CI: 1.10-1.24), respectively. Furthermore, the magnitude of the association was significantly larger in mega cities. These findings provide useful evidence for promoting public health in cities of different sizes for achieving health equity and indicate that smaller cities and their health-supportive environment need further attention.

Scaling law characteristics and spatiotemporal multicomponent analysis of syphilis from 2016 to 2022 in Zhejiang Province, China

Background

Syphilis has caused epidemics for hundreds of years, and the global syphilis situation remains serious. The reported incidence rate of syphilis in Zhejiang Province has ranked first in the province in terms of notifiable infectious diseases for many years and is the highest in China. This study attempts to use the scaling law theory to study the relationship between population size and different types of syphilis epidemics, while also exploring the main driving factors affecting the incidence of syphilis in different regions.

Methods

Data on syphilis cases and affected populations at the county level were obtained from the China Disease Control and Prevention Information System. The scaling relationship between different stages of syphilis and population size was explained by scaling law. The trend of the incidence from 2016 to 2022 was tested by the joinpoint regression. The index of distance between indices of simulation and observation (DISO) was applied to evaluate the overall performance of joinpoint regression model. Furthermore, a multivariate time series model was employed to identify the main driving components that affected the occurrence of syphilis at the county level. The p value less than 0.05 or confidence interval (CI) does not include 0 represented statistical significance for all the tests.

Results

From 2016 to 2022, a total of 204,719 cases of syphilis were reported in Zhejiang Province, including 2 deaths, all of which were congenital syphilis. Latent syphilis accounted for 79.47% of total syphilis cases. The annual percent change (APCs) of all types of syphilis, including primary syphilis, secondary syphilis, tertiary syphilis, congenital syphilis and latent syphilis, were - 21.70% (p < 0.001, 95% CI: -26.70 to -16.30), -16.80% (p < 0.001, 95% CI: -20.30 to -13.30), -8.70% (p < 0.001, 95% CI: -11.30 to -6.00), -39.00% (p = 0.001, 95% CI: -49.30 to -26.60) and - 7.10% (p = 0.008, 95% CI: -11.20 to -2.80), respectively. The combined scaling exponents of primary syphilis, secondary syphilis, tertiary syphilis, congenital syphilis and latent syphilis based on the random effects model were 0.95 (95% CI: 0.88 to 1.01), 1.14 (95% CI: 1.12 to 1.16), 0.43 (95% CI: 0.37 to 0.49), 0.0264 (95% CI: -0.0047 to 0.0575) and 0.88 (95% CI: 0.82 to 0.93), respectively. The overall average effect values of the endemic component, spatiotemporal component and autoregressive component for all counties were 0.24, 0.035 and 0.72, respectively. The values of the autoregressive component for most counties were greater than 0.7. The endemic component of the top 10 counties with the highest values was greater than 0.34. Two counties with value of the spatiotemporal component higher than 0.1 were Xihu landscape county and Shengsi county. From 2016 to 2022, the endemic and autoregressive components of each county showed obvious seasonal changes.

Conclusion

The scaling exponent had both temporal trend characteristics and significant heterogeneity in the association between each type of syphilis and population size. Primary syphilis and latent syphilis exhibited a linear pattern, secondary syphilis presented a superlinear pattern, and tertiary syphilis exhibited a sublinear pattern. This suggested that further prevention of infection and transmission among high-risk populations and improvement of diagnostic accuracy in underdeveloped areas is needed. The autoregressive components and the endemic components were the main driving factors that affected the occurrence of syphilis. Targeted prevention and control strategies must be developed based on the main driving modes of the epidemic in each county.

The Role of Functional Urban Areas in the Spread of COVID-19 Omicron (Northern Spain)

This study focuses on the space-time patterns of the COVID-19 Omicron wave at a regional scale, using municipal data. We analyze the Basque Country and Cantabria, two adjacent regions in the north of Spain, which between them numbered 491,816 confirmed cases in their 358 municipalities from 15th November 2021 to 31st March 2022. The study seeks to determine the role of functional urban areas (FUAs) in the spread of the Omicron variant of the virus, using ESRI Technology (ArcGIS Pro) and applying intelligence location methods such as 3D-bins and emerging hot spots. Those methods help identify trends and types of problem area, such as hot spots, at municipal level. The results demonstrate that FUAs do not contain an over-concentration of COVID-19 cases, as their location coefficient is under 1.0 in relation to population. Nevertheless, FUAs do have an important role as drivers of spread in the upward curve of the Omicron wave. Significant hot spot patterns are found in 85.0% of FUA area, where 98.9% of FUA cases occur. The distribution of cases shows a spatially stationary linear correlation linked to demographically progressive areas (densely populated, young profile, and with more children per woman) which are well connected by highways and railroads. Based on this research, the proposed GIS methodology can be adapted to other case studies. Considering geo-prevention and WHO Health in All Policies approaches, the research findings reveal spatial patterns that can help policymakers in tackling the pandemic in future waves as society learns to live with the virus.

Exploring inequalities in life expectancy and lifespan variation by race/ethnicity and urbanicity in the United States: 1990 to 2019

Background/Objective

Investigating trends in life expectancy and lifespan variation can highlight disproportionate mortality burdens among population subgroups. We examined inequalities in life expectancy and lifespan variation by race/ethnicity and by urbanicity in the US from 1990 to 2019.

Methods

Using vital registration data for 322.0 million people in 3,141 counties from the National Center for Health Statistics, we obtained life expectancy at birth and lifespan variation for 16 race/ethnicity-gender-urbanicity combinations in six 5-year periods (1990-1994 to 2015-2019). Race/ethnicity was categorized as Hispanic, and non-Hispanic White, Black, and Asian/Pacific Islander. Urbanicity was categorized as metropolitan vs nonmetropolitan areas, or in six further detailed categorizations. Life expectancy and lifespan variation (coefficient of variation) were computed using life tables.

Results

In 2015-2019, residents in metropolitan areas had higher life expectancies than their nonmetropolitan counterparts (79.6 years compared to 77.0 years). The widest inequality in life expectancy occurred between Asian/Pacific Islander women and Black men, with a 17.7-year gap for residents in metropolitan areas and a 16.9-year gap for residents in nonmetropolitan areas. Nonmetropolitan areas had greater dispersion around average age at death. Black individuals had the highest lifespan variations in both metropolitan and nonmetropolitan areas. Until the mid-2010s, life expectancy increased while lifespan variation decreased; however, recent trends show stagnation in life expectancy and increases in lifespan variation. Metropolitan-nonmetropolitan inequalities in both life expectancy and lifespan variation widened over time.

Conclusion

Despite previous improvements in longevity, life expectancy is now stagnating while lifespan variation is increasing. Our results highlight that early-life deaths (i.e., young- and middle-age mortality) disproportionately affect Black individuals, who not only live the shortest lifespans but also have the most variability with respect to age at death.