Spatial Inequities in COVID-19 Testing, Positivity, Confirmed Cases, and Mortality in 3 U.S. Cities : An Ecological Study

BACKGROUND

Preliminary evidence has shown inequities in coronavirus disease 2019 (COVID-19)-related cases and deaths in the United States.

OBJECTIVE

To explore the emergence of spatial inequities in COVID-19 testing, positivity, confirmed cases, and mortality in New York, Philadelphia, and Chicago during the first 6 months of the pandemic.

DESIGN

Ecological, observational study at the ZIP code tabulation area (ZCTA) level from March to September 2020.

SETTING

Chicago, New York, and Philadelphia.

PARTICIPANTS

All populated ZCTAs in the 3 cities.

MEASUREMENTS

Outcomes were ZCTA-level COVID-19 testing, positivity, confirmed cases, and mortality cumulatively through the end of September 2020. Predictors were the Centers for Disease Control and Prevention Social Vulnerability Index and its 4 domains, obtained from the 2014-2018 American Community Survey. The spatial autocorrelation of COVID-19 outcomes was examined by using global and local Moran I statistics, and estimated associations were examined by using spatial conditional autoregressive negative binomial models.

RESULTS

Spatial clusters of high and low positivity, confirmed cases, and mortality were found, co-located with clusters of low and high social vulnerability in the 3 cities. Evidence was also found for spatial inequities in testing, positivity, confirmed cases, and mortality. Specifically, neighborhoods with higher social vulnerability had lower testing rates and higher positivity ratios, confirmed case rates, and mortality rates.

LIMITATIONS

The ZCTAs are imperfect and heterogeneous geographic units of analysis. Surveillance data were used, which may be incomplete.

CONCLUSION

Spatial inequities exist in COVID-19 testing, positivity, confirmed cases, and mortality in 3 large U.S. cities.

PRIMARY FUNDING SOURCE

National Institutes of Health.

Social inequities in cardiovascular risk factors in women and men by autonomous regions in Spain

OBJECTIVE

To describe social inequities in cardiovascular risk factors in women and men by autonomous regions in Spain.

METHOD

We used data from 20,406 individuals aged 18 or older from the 2017 Spanish National Health Survey. We measured socioeconomic position using occupational social class and used data on self-reported cardiovascular risk factors: high cholesterol, diabetes, hypertension, obesity, and smoking. We estimated the relative risk of inequality using Poisson regression models. Analyses were stratified by men and women and by region (autonomous communities).

RESULTS

Overall, the relative risk of inequality was 1.02, 1.13, 1.06, 1.17 and 1.09 for high cholesterol, diabetes, hypertension, obesity, and current smoking, respectively. Ocuupational social class inequities in diabetes, hypertension, and obesity was stronger for women. Results showed a large regional heterogeneity in these inequities; some regions (e.g. Asturias and Balearic Islands) presented wider social inequities in cardiovascular risk factors than others (e.g. Galicia, Navarra or Murcia).

CONCLUSION

In Spain, we found marked social inequities in the prevalence of cardiovascular risk factors, with wide regional and women/men heterogeneity in these inequities. Education, social, economic and health policies at the regional level could reduce health inequities in cardiovascular risk factors and, thus, prevent cardiovascular disease.

Does a physical activity supportive environment ameliorate or exacerbate socioeconomic inequities in incident coronary heart disease?

BACKGROUND

Efforts to reduce socioeconomic inequities in cardiovascular disease include interventions to change the built environment. We aimed to explore whether socioeconomic inequities in coronary heart disease (CHD) incidence are ameliorated or exacerbated in environments supportive of physical activity (PA).

METHODS

We used data from the Reasons for Geographic and Racial Differences in Stroke study, which recruited US residents aged 45 or older between 2003 and 2007. Our analyses included participants at risk for incident CHD (n=20 808), followed until 31 December 2014. We categorised household income and treated it as ordinal: (1) US$75 000+, (2) US$35 000-US$74 000, (3) US$20 000-US$34 000 and (4)

RESULTS

We found a 25% (95% CI 1.17% to 1.34%) increased hazard of CHD per 1-category decrease in household income category. Adjusting for PA-supportive environments slightly reduced this association (HR=1.24). The income-CHD association was strongest in areas without walking destinations (HR=1.57), an interaction which reached statistical significance in analyses among men. In contrast, the income-CHD association showed a trend towards being strongest in areas with the highest percentage of green land cover.

CONCLUSIONS

Indicators of a PA supportive environment show divergent trends to modify socioeconomic inequities in CHD . Built environment interventions should measure the effect on socioeconomic inequities.

Collapse

Key Words

• cardiovascular disease
• neighborhood/place
• socio-economic

Collapse

MESH Headings Collapse

Grants

• DP5 OD026429 NIH HHS
• R01 AG049970 NIA NIH HHS
• U01 NS041588 NINDS NIH HHS

Collapse

Spatial Inequities in COVID-19 Testing, Positivity, Confirmed Cases, and Mortality in 3 U.S. Cities : An Ecological Study

BACKGROUND

Preliminary evidence has shown inequities in coronavirus disease 2019 (COVID-19)-related cases and deaths in the United States.

OBJECTIVE

To explore the emergence of spatial inequities in COVID-19 testing, positivity, confirmed cases, and mortality in New York, Philadelphia, and Chicago during the first 6 months of the pandemic.

DESIGN

Ecological, observational study at the ZIP code tabulation area (ZCTA) level from March to September 2020.

SETTING

Chicago, New York, and Philadelphia.

PARTICIPANTS

All populated ZCTAs in the 3 cities.

MEASUREMENTS

Outcomes were ZCTA-level COVID-19 testing, positivity, confirmed cases, and mortality cumulatively through the end of September 2020. Predictors were the Centers for Disease Control and Prevention Social Vulnerability Index and its 4 domains, obtained from the 2014-2018 American Community Survey. The spatial autocorrelation of COVID-19 outcomes was examined by using global and local Moran I statistics, and estimated associations were examined by using spatial conditional autoregressive negative binomial models.

RESULTS

Spatial clusters of high and low positivity, confirmed cases, and mortality were found, co-located with clusters of low and high social vulnerability in the 3 cities. Evidence was also found for spatial inequities in testing, positivity, confirmed cases, and mortality. Specifically, neighborhoods with higher social vulnerability had lower testing rates and higher positivity ratios, confirmed case rates, and mortality rates.

LIMITATIONS

The ZCTAs are imperfect and heterogeneous geographic units of analysis. Surveillance data were used, which may be incomplete.

CONCLUSION

Spatial inequities exist in COVID-19 testing, positivity, confirmed cases, and mortality in 3 large U.S. cities.

PRIMARY FUNDING SOURCE

National Institutes of Health.

Urban social determinants of non-communicable diseases risk factors in Argentina

We examined associations of individual-, neighborhood- and city-level education -as proxies of SES at different levels-, with diabetes, hypertension, obesity, smoking and binge drinking (non-communicable disease risk factors -NCD/RF) among Argentinian adults. We estimated mixed models based on 21,415 individuals from the 2013 National Survey of Risk Factors, living in 2,698 neighborhoods and 33 cities. Gradients by individual-level education differed by gender and NCD/RF, and some were modified by city education. In addition, we identified contextual effects of neighborhood and city education on some NCD/RF. Urban efforts to tackle NCD/RF in Argentina should be context- and gender-sensitive, and mainly focused on socially disadvantaged groups.

[The experience of working with mobility data in order to detect inequalities during COVID-19 pandemic]

The COVID-19 pandemic has been one of the most important health crises of the last century in Spain and worldwide. Mobility reduction interventions have been among the most common public health measures implemented to mitigate the pandemic through reducing community transmission. These measures may have an unequal impact across the population. We present a methodology based on the use of publicly available data from the Instituto Nacional de Estadística and the Sociedad Espanola de Epidemiología, to study socioeconomic inequalities in mobility during the pandemic. We describe an application of this methodology for a province (Asturias), showing socioeconomic rural-urban patterns. The use of geographic information system tools can provide useful evidence to explore the social determinants of health at multiple levels.

Social inequalities in mobility during and following the COVID-19 associated lockdown of the Madrid metropolitan area in Spain

Spain has been one of the most affected regions by the COVID-19 worldwide, and Madrid its most affected city. In response to this, the Spanish government enacted a strict lockdown in late March 2020, that was gradually eased until June 2020. We explored differentials in mobility by area-level deprivation in the functional area of Madrid, before, during, and after the COVID-19 lockdown. We used cell phone-derived mobility indicators (% of the population leaving their area) from the National Institute of Statistics (INE), and a composite measure of deprivation from the Spanish Society of Epidemiology (SEE). We computed changes in mobility with respect to pre-pandemic levels, and explored spatial patterns and associations with deprivation. We found that levels of mobility before COVID-19 were slightly higher in areas with lower deprivation. The economic hibernation period resulted in very strong declines in mobility, most acutely in low deprivation areas. These differences weakened during the re-opening, and levels of mobility were similar by deprivation once the lockdown was completely lifted. Given the existence of important socioeconomic differentials in COVID-19 exposure, it is key to ensure that these interventions do not widen existing social inequalities.

Understanding Immigration as a Social Determinant of Health: Cardiovascular Disease in Hispanics/Latinos and South Asians in the United States

PURPOSE OF REVIEW

The main purpose of this review is to summarize the epidemiology of cardiovascular disease and its risk factors among two of the largest and most diverse immigrant groups in the United States (Hispanics/Latinos and South Asians).

RECENT FINDINGS

While the migration process generates unique challenges for individuals, there is a wide heterogeneity in the characteristics of immigrant populations, both between and within regions of origin. Hispanic/Latino immigrants to the United States have lower levels of cardiovascular risk factors, prevalence, and mortality, but this assessment is limited by issues related to the "salmon bias." South Asian immigrants to the United States generally have higher levels of risk factors and higher mortality. In both cases, levels of risk factors and mortality generally increase with time of living in the United States (US). While immigration acts as a social determinant of health, associations between immigration and cardiovascular disease and its risk factors are complex and vary across subpopulations.

Variation in Non-external and External Causes of Death in Peru in Relation to the COVID-19 Lockdown

Introduction: Lockdowns are designed to slow COVID-19 transmission, but they may have unanticipated relationships with other aspects of public health. Assessing the overall pattern in population health as a country implements and relaxes a lockdown is relevant, as these patterns may not necessarily be symmetric. We aimed to estimate the changing trends in cause-specific mortality in relation to the 2020 COVID-19 related lockdowns in Peru. Methods: Based on data from the Peruvian National Death Information System (SINADEF), we calculated death rates per 10 million population to assess the trends in mortality rates for non-external and external causes of death (suicides, traffic accidents, and homicides). We compared these trends to 2018-2019, before, during, and after the lockdown, stratified by sex, and adjusted by Peruvian macro-region (Lima & Callao (capital region), Coast, Highland, and Jungle). Results: Non-external deaths presented a distinctive pattern among macro-regions, with an early surge in the Jungle and a later increase in the Highland. External deaths dropped during the lockdown, however, suicides and homicides returned to previous levels in the post-lockdown period. Deaths due to traffic accidents dropped during the lockdown and returned to pre-pandemic levels by December 2020. Conclusions: We found a sudden drop in external causes of death, with suicides and homicides returning to previous levels after the lifting of the lockdown. Non-external deaths showed a differential pattern by macro-region. A close monitoring of these trends could help identify early spikes among these causes of death and take action to prevent a further increase in mortality indirectly affected by the pandemic.

Linking historical discriminatory housing patterns to the contemporary food environment in Baltimore

Food access literature links disinvested communities with poor food access. Similarly, links are made between discriminatory housing practices and contemporary investment. Less work has examined the relationship between housing practices and food environment disparities. Our central premise is that these practices create distinctions in food environment quality, and that these disparities may have implications for food system advocacy and policymaking. In this paper, we link an objective food environment assessment with a spatial database highlighting redlining, blockbusting, and gentrification in Baltimore, Maryland, USA. Standard socioeconomic and housing characteristics are used to control for race, income, and housing composition in a multivariate regression analysis. Our findings highlight that blockbusting-rather than redlining-most strongly shapes poor food access. Redlining and gentrification, meanwhile, are associated with better food access. These findings raise important points about future policy discussions, which should instead be focused on ameliorating more contemporary patterns of housing inequality.

Monitoring life expectancy levels during the COVID-19 pandemic: Example of the unequal impact of the first wave on Spanish regions

BACKGROUND

To provide an interpretable summary of the impact on mortality of the COVID-19 pandemic we estimate weekly and annual life expectancies at birth in Spain and its regions.

METHODS

We used daily death count data from the Spanish Daily Mortality Monitoring System (MoMo), and death counts from 2018, and population on July 1st, 2019 by region (CCAA), age groups, and sex from the Spanish National Statistics Institute. We estimated weekly and annual (2019 and 2020*, the shifted annual calendar period up to 5 July 2020) life expectancies at birth as well as their differences with respect to 2019.

RESULTS

Weekly life expectancies at birth in Spain were lower in weeks 11-20, 2020 compared to the same weeks in 2019. This drop in weekly life expectancy was especially strong in weeks 13 and 14 (March 23rd to April 5th), with national declines ranging between 6.1 and 7.6 years and maximum regional weekly declines of up to 15 years in Madrid. Annual life expectancy differences between 2019 and 2020 also reflected an overall drop in annual life expectancy of 0.9 years for both men and women. These drops ranged between 0 years in several regions (e.g. Canary and Balearic Islands) to 2.8 years among men in Madrid.

CONCLUSIONS

Life expectancy is an easy to interpret measure for understanding the heterogeneity of mortality patterns across Spanish regions. Weekly and annual life expectancy are sensitive and useful indicators for understanding disparities and communicating the gravity of the situation because differences are expressed in intuitive year units.

Longitudinal changes in the retail food environment in Mexico and their association with diabetes

The retail food environment is a potential population-level determinant of diet and nutrition-related chronic diseases, yet little is known about its composition and association with diabetes in low- and middle-income countries. Our objectives were: (1) to describe changes in the composition of the retail food environment in Mexican neighborhoods from 2010 to 2016 and (2) to examine the association between these changes and diabetes cases diagnosed over the same period. Individual level data came from the 2016 Mexican Health and Nutrition Survey (N = 2808 adults). Neighborhood level retail food environment data for 2010 and 2016 came from the National Directory of Economic Units of Mexico. Multilevel logistic regression was used to examine the adjusted association between changes in the neighborhood density per km² of fruit and vegetable stores, chain convenience stores and supermarkets with diabetes. Small store formats still predominate in Mexico's food environment, however there is evidence of fast increase in chain convenience stores and supermarkets. Adults living in neighborhoods that saw a decline in fruit and vegetable store density and a simultaneous increase in chain convenience store density experienced higher odds of diabetes, compared to adults who lived in neighborhoods where fruit and vegetable and convenience stores did not change (OR 3.90, 95% CI 1.61, 9.48). Considering the complex interplay between store types, understanding the mechanisms and confirming the causal implications of these findings could inform policies that improve the quality of food environments in cities.

•

We examined changes in the retail food environment in Mexican cities.

•

We also examined whether those changes were associated with new diabetes cases.

•

Small food stores still predominate but evidence of fast increase in chain convenience stores and supermarkets.

•

Odds of diabetes were highest when fruit and vegetable stores declined and chain convenience stores increased.

•

Changes in the density of supermarkets were not associated with diabetes.

Adaptation and Evaluation of the Nutrition Environment Measures Survey in Stores to Assess Mediterranean Food Environments (NEMS-S-MED)

The Nutrition Environment Measures Surveys are valid and reliable measures of community and consumer food environments. This article describes the adaptation and evaluation of the Nutrition Environment Measures Survey in Stores (NEMS-S) for Mediterranean urban contexts (NEMS-S-MED). Trained raters used the adapted NEMS-S-MED tool to observe and rate food outlets in 21 census tracts and 43 food stores across the city of Madrid, Spain. We evaluated inter-rater and intra-rater reliabilities, construct validity, and the tool's ability to discriminate between store types and between stores by area-level Socio-Economic Status (SES). Overall, the mean NEMS-S-MED score was 20.7 (SD = 9.8), which ranged from 7 to 43. Most food items displayed substantial or almost perfect inter-rater and intra-rater agreements; the percentage agreement across availability items was almost perfect and kappa statistics were also very high (median κ = 1.00 for inter-rater; κ = 0.92 for intra-rater). Furthermore, the NEMS-S-MED tool was able to discriminate between store types and census tracts of different SES. The adapted NEMS-S-MED instrument is a reliable and valid audit tool to assess the consumer food environment in Mediterranean urban contexts. Well-constructed measurement tools, such as the NEMS-S-MED, may facilitate the development of effective policy interventions to increase healthy food access and affordability.

The Upcoming Epidemic of Heart Failure in South Asia

Currently, South Asia accounts for a quarter of the world population, yet it already claims ≈60% of the global burden of heart disease. Besides the epidemics of type 2 diabetes mellitus and coronary heart disease already faced by South Asian countries, recent studies suggest that South Asians may also be at an increased risk of heart failure (HF), and that it presents at earlier ages than in most other racial/ethnic groups. Although a frequently underrecognized threat, an eventual HF epidemic in the densely populated South Asian nations could have dramatic health, social and economic consequences, and urgent interventions are needed to flatten the curve of HF in South Asia. In this review, we discuss recent studies portraying these trends, and describe the mechanisms that may explain an increased risk of premature HF in South Asians compared with other groups, with a special focus on highly relevant features in South Asian populations including premature coronary heart disease, early type 2 diabetes mellitus, ubiquitous abdominal obesity, exposure to the world's highest levels of air pollution, highly prevalent pretransition forms of HF such as rheumatic heart disease, and underdevelopment of healthcare systems. Other rising lifestyle-related risk factors such as use of tobacco products, hypertension, and general obesity are also discussed. We evaluate the prognosis of HF in South Asian countries and the implications of an anticipated HF epidemic. Finally, we discuss proposed interventions aimed at curbing these adverse trends, management approaches that can improve the prognosis of prevalent HF in South Asian countries, and research gaps in this important field.

Estimating and mapping cigarette butt littering in urban environments: A GIS approach

BACKGROUND

Cigarette butts are some of the most common form of litter in the World, causing severe environmental damage. Analysing spatial distribution of cigarette butts in the urban environment may lead to useful insights for further interventions to reduce this form of litter. In this study, we present a GIS-based methodology to estimate the density of cigarette butts across a large urban area.

METHODS

We collected information about discarded cigarette butts in outdoor public spaces by systematic social observation in a diverse sample of areas in Madrid, Spain. We used these data to estimate the density of cigarette butts in public spaces around the entire city by performing GIS analyses based on Kernel Density Estimations. Last, we validated these measures using on-field observations in a set of locations across the city.

RESULTS

Hospitality venues and public transportation stops were the places with the highest concentrations of cigarette butts, followed by the entrances to educational venues and playgrounds. Central districts showed the highest amount of cigarette butts in contrast to peripheral ones. We found that our measure had good validity, with a correlation coefficient of 0.784.

DISCUSSION

This is the first study estimating and mapping cigarette butt litter in a large urban area. We identified a set of outdoor public places with high concentrations of cigarette butts and found geographical unevenness in the distribution of this pervasive form of litter across the study area. Our findings demonstrate the ubiquitous nature of cigarette butts in the urban environment and the need for interventions to reduce its impact on both people's health and the environment.