Associations of the Neighborhood Built Environment with Gestational Weight Gain

Objective This study aimed to determine whether specific factors of the built environment related to physical activity and diet are associated with inadequate and excessive gestational weight gain (GWG). Study Design This analysis is based on data from the Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-To-Be, a prospective cohort of nulliparous women who were followed from the beginning of their pregnancies through delivery. At each study visit, home addresses were recorded and geocoded. Locations were linked to several built-environment characteristics such as the census tract National Walkability Score (the 2010 Walkability Index) and the number of gyms, parks, and grocery stores within a 3-km radius of residential address. The primary outcome of GWG (calculated as the difference between prepregnancy weight and weight at delivery) was categorized as inadequate, appropriate, or excessive based on weight gained per week of gestation. Multinomial regression (generalized logit) models evaluated the relationship between each factor in the built environment and excessive or inadequate GWG. Results Of the 8,182 women in the analytic sample, 5,819 (71.1%) had excessive GWG, 1,426 (17.4%) had appropriate GWG, and 937 (11.5%) had inadequate GWG. For the majority of variables examined, built environments more conducive to physical activity and healthful food availability were associated with a lower odds of excessive or inadequate GWG category. For example, a higher number of gyms or parks within 3 km of a participant's residential address was associated with lower odds of having excessive (gyms: adjusted odds ratio [aOR] = 0.93 [0.89–0.96], parks: 0.94 [0.90–0.98]) or inadequate GWG (gyms: 0.91 [0.86–0.96]; parks: 0.91 [0.86–0.97]). Similarly, a higher number of grocery stores was associated with lower odds of having excessive GWG (0.94 [0.91–0.97]). Conclusion Among a diverse population of nulliparous women, multiple aspects of the built environment are associated with excessive and inadequate GWG. Key Points

Household secondary attack rate of COVID-19 by household size and index case characteristics

In this population-wide study in Ontario, Canada, we investigated the household secondary attack rate (SAR) to understand its relationship to household size and index case characteristics. We identified all patients with confirmed COVID-19 between July 1 and November 30, 2020. Cases within households were matched based on reported residential address; households were grouped based on the number of household contacts. The majority of households (68.2%) had a SAR of 0%, while 3,442 (11.7%) households had a SAR ≥75%. Overall household SAR was 19.5% and was similar across household sizes, but varied across index case characteristics. Households where index cases had longer delays between symptom onset and test seeking, households with older index cases, households with symptomatic index cases, and larger households located in diverse neighborhoods, were associated with greater household SAR. Our findings present characteristics associated with greater household SARs and proposes immediate testing as a method to reduce household transmission and incidence of COVID-19.

Automation of cleaning and reconstructing residential address histories to assign environmental exposures in longitudinal studies

Background We have developed an open-source ALgorithm for Generating Address Exposures (ALGAE) that cleans residential address records to construct address histories and assign spatially-determined exposures to cohort participants. The first application of this algorithm was to construct prenatal and early life air pollution exposure for individuals of the Avon Longitudinal Study of Parents and Children (ALSPAC) in the South West of England, using previously estimated particulate matter ≤10 µm (PM10) concentrations. Methods ALSPAC recruited 14 541 pregnant women between 1991 and 1992. We assigned trimester-specific estimated PM10 exposures for 12 752 pregnancies, and first year of life exposures for 12 525 births, based on maternal residence and residential mobility. Results Average PM10 exposure was 32.6 µg/m3 [standard deviation (S.D.) 3.0 µg/m3] during pregnancy and 31.4 µg/m3 (S.D. 2.6 µg/m3) during the first year of life; 6.7% of women changed address during pregnancy, and 18.0% moved during first year of life of their infant. Exposure differences ranged from -5.3 µg/m3 to 12.4 µg/m3 (up to 26% difference) during pregnancy and -7.22 µg/m3 to 7.64 µg/m3 (up to 27% difference) in the first year of life, when comparing estimated exposure using the address at birth and that assessed using the complete cleaned address history. For the majority of individuals exposure changed by <5%, but some relatively large changes were seen both in pregnancy and in infancy. Conclusions ALGAE provides a generic and adaptable, open-source solution to clean addresses stored in a cohort contact database and assign life stage-specific exposure estimates with the potential to reduce exposure misclassification.

Long-Term Exposure to Ambient Fine Particulate Matter and Mortality From Renal Failure: A Retrospective Cohort Study in Hong Kong, China

Numerous studies have indicated that ambient particulate matter is closely associated with increased risk of cardiovascular disease, yet the evidence for its association with renal disease remains underrecognized. We aimed to estimate the association between long-term exposure to fine particulate matter, defined as particulate matter with an aerodynamic diameter less than or equal to 2.5 μm (PM2.5), and mortality from renal failure (RF) among participants in the Elderly Health Service Cohort in Hong Kong, China, from 1998 to 2010. PM2.5 concentration at the residential address of each participant was estimated based on a satellite-based spatiotemporal model. We used Cox proportional hazards regression to estimate risks of overall RF and cause-specific mortality associated with PM2.5. After excluding 5,373 subjects without information on residential address or relevant covariates, we included 61,447 participants in data analyses. We identified 443 RF deaths during the 10 years of follow-up. For an interquartile-range increase in PM2.5 concentration (3.22 μg/m3), hazard ratios for RF mortality were 1.23 (95% confidence interval: 1.06, 1.43) among all cohort participants and 1.42 (95% confidence interval: 1.16, 1.74) among patients with chronic kidney disease. Long-term exposure to atmospheric PM2.5 might be an important risk factor for RF mortality in the elderly, especially among persons with existing renal diseases.

Consent to data linkage in a large online epidemiological survey of 18–23 year old Australian women in 2012–13

Background Consent to link survey data with health-related administrative datasets is increasingly being sought but little is known about the influence of recruiting via online technologies on participants’ consents. The goal of this paper is to examine what factors (sociodemographic, recruitment, incentives, data linkage information, health) are associated with opt-in consent to link online survey data to administrative datasets (referred to as consent to data linkage). Methods The Australian Longitudinal Study on Women’s Health is a prospective study of factors affecting the health and well-being of women. We report on factors associated with opt-in consent to data linkage at the end of an online survey of a new cohort of 18–23 year old Australian women recruited in 2012–13. Classification and Regression Tree analysis with decision trees was used to predict consent. Results In this study 69% consented to data linkage. The provision of residential address by the individual, or not (as a measure of attitudes towards privacy), was the most important factor in classifying the data into similar groups of consenters (76% consenters versus 47% respectively). Thereafter, for those who did not provide their residential address, the incentives and data linkage information that was offered was the next most important factor, with incentive 2: limited-edition designer leggings and additional information about confidentiality showing increases in consent rates over Incentive 1: AUD50 gift voucher: 60% versus 37%. Conclusions In young Australian women, attitudes towards privacy was strongly associated with consenting to data linkage. Providing additional details about data confidentiality was successful in increasing consent and so was cohort appropriate incentives. Ensuring that prospective participants understand the consent and privacy protocols in place to protect their confidential information builds confidence in consenting to data linkage.

An Investigation Into Repeat Requests for Charity: Evidence From the St Vincent de Paul Society Queensland, Australia

In advanced industrialized economies, charitable organizations work alongside formal social services provided through welfare states to assist people living in poverty. The work of charities with socially and economically marginalized people, however, often takes place in the absence of robust evidence about what impact charity has on people’s lives. This study draws on a large administrative database to investigate what determines repeat requests for charity and how people may achieve dignity. Our findings show that frequent residential address changes seem to make people more reliant on charity, whereas the more time spent with people receiving charity significantly decreases repeat requests for charity. We propose that the provision of charity can be an opportunity to promote connectedness.

Impact of Cross-Jurisdictional Data Exchange on the Estimating of HIV Population Living in the District of Columbia (Preprint)

BACKGROUND Accurate HIV surveillance data is essential to monitoring the trends to end the HIV epidemic. Due to strict policies around data security and confidentiality, HIV surveillance data has not been routinely shared across jurisdictions, with the exception of a biannual case-by-case review process to identify and remove duplicate cases (Routine Interstate Duplicate Review, RIDR). HIV surveillance estimates for the District of Columbia (DC) are complicated by migration and care-seeking throughout the metropolitan area, which includes Maryland (MD) and Virginia (VA). To address gaps in HIV surveillance data, the health departments of DC, MD and VA established HIV surveillance data sharing agreements. While the Black Box (a privacy data integration tool external to the health departments) facilitated the secure exchange of data between DC, MD and VA, its previous iterations were limited by frequency and scope of information exchanged. The health departments of DC, MD and VA engaged in data sharing to further improve HIV surveillance estimates. OBJECTIVE The objectives of this evaluation were to assess the impact of cross-jurisdictional data-sharing on the estimation of persons living with HIV (PLWH) in DC and the reduction of cases in the RIDR process. METHODS The data sharing agreements established in 2014 allowed for the exchange of HIV case information (e.g. current residential address) and laboratory information (e.g. test types, result dates and results) from the enhanced HIV/AIDS Reporting System (eHARS). Regular data exchanges began in 2017. The participating jurisdictions transferred data (via secure file transfer protocol) for individuals having a residential address in a partnering jurisdiction at the time of HIV diagnosis and/or evidence of receiving HIV-related services at a facility located in a partnering jurisdiction. DC DOH compared the data received to the DC eHARS and imported updated data that matched to existing cases. Evaluation of changes in current residential address and HIV prevalence were conducted by comparing data before and after the HIV surveillance data exchanges. RESULTS After the HIV surveillance data exchange, an average of 390 fewer cases were estimated to be living in DC for each year from 2012 to 2016. Among cases with a residential status change, 66.4% of cases had relocated to MD and 19.8% had relocated to VA; the majority of these cases had relocated to counties bordering DC. Relocation in and out of DC differed by mode of transmission, race/ethnicity, age group and gender. After the data exchange, the volume of HIV cases needing RIDR decreased by 74% for DC-MD and 81% for DC-VA. CONCLUSIONS The HIV surveillance data exchange between the public health departments of DC, MD and VA reduced the number of cases misclassified as DC residents and reduced the number of cases needing RIDR. Continued data exchanges will enhance the ability of the DC DOH to monitor the local HIV epidemic.