Harnessing Google Health Trends Data for Epidemiologic Research.

Interest in using internet search data, such as that from the Google Health Trends Application Programming Interface (GHT-API), to measure epidemiologically relevant exposures or health outcomes is growing due to their accessibility and timeliness. Researchers enter search term(s), geography, and time period, and the GHT-API returns a scaled probability of that search term, given all searches within the specified geographic-time period. In this study, we detailed a method for using these data to measure a construct of interest in 5 iterative steps: first, identify phrases the target population may use to search for the construct of interest; second, refine candidate search phrases with incognito Google searches to improve sensitivity and specificity; third, craft the GHT-API search term(s) by combining the refined phrases; fourth, test search volume and choose geographic and temporal scales; and fifth, retrieve and average multiple samples to stabilize estimates and address missingness. An optional sixth step involves accounting for changes in total search volume by normalizing. We present a case study examining weekly state-level child abuse searches in the United States during the coronavirus disease 2019 pandemic (January 2018 to August 2020) as an application of this method and describe limitations.

Is economic hardship associated with young children's cortisol levels?

Economic hardship during childhood has been linked to poor physical and mental health. This study examines cross-sectional and longitudinal associations of a summed economic hardship score of poverty, food insecurity, and financial hardship with hair cortisol in young children. Data from 24-month (Time 1, mean age 5 years) and 36-month (Time 2, mean age 6 years) follow-up from the NET-Works obesity prevention trial (NET-Works, NCT0166891) were used. Hair cortisol measures obtained at each time point were log-transformed and regressed on economic hardship at Time 1 and a cumulative economic hardship from Time 1 to Time 2, using generalized linear regressions. All models were adjusted for child age, sex, race/ethnicity, and intervention (prevention vs. control) arm. The final analytic sample sizes ranged from 248 to 287. Longitudinal analyses indicated that for every 1-unit higher economic hardship score at Time 1, hair cortisol at Time 2 follow-up was on average 0.07 log-picograms per milligram (pg/mg) higher (95% confidence interval [CI]: 0.01, 0.13). For every 1-unit increase in the cumulative economic hardship score between Time 1 and 2, there was a 0.04 log-pg/mg (95% CI: 0.00, 0.07) average higher level of hair cortisol at Time 2 follow-up. Results show suggestive but limited evidence for an association between economic hardship and cortisol in young children.

Violence in the Great Recession.

Substantial evidence suggests that economic hardship causes violence. However, a large majority of this research relies on observational studies that use traditional violence surveillance systems that suffer from selection bias and over-represent vulnerable populations, such as people of color. To overcome limitations of prior work, we employed a quasi-experimental design to assess the impact of the Great Recession on explicit violence diagnoses (injuries identified to be caused by a violent event) and proxy violence diagnoses (injuries highly correlated with violence) for child maltreatment, intimate partner violence, elder abuse, and their combination. We used Minnesota hospital data (2004-2014), conducting a difference-in-differences analysis at the county level (n = 86) using linear regression to compare changes in violence rates from before the recession (2004-2007) to after the recession (2008-2014) in counties most affected by the recession, versus changes over the same time period in counties less affected by the recession. The findings suggested that the Great Recession had little or no impact on explicitly identified violence; however, it affected proxy-identified violence. Counties that were more highly affected by the Great Recession saw a greater increase in the average rate of proxy-identified child abuse, elder abuse, intimate partner violence, and combined violence when compared with less-affected counties.

Classes of lifetime adversities among emerging adult women by race/ethnicity and their associations with weight status in the United States.

This cross-sectional study examines the association of childhood and adolescent/adult adversities with obesity across four racial/ethnic groups among emerging adult women aged 18 to 25 (n = 9310). Latent class analysis was used to identify racial/ethnicity-specific classes arising from childhood and adolescent/adult adversity indicators in the 2015 and 2018 College Student Health Surveys (sampled from Minnesota, U.S.) Distal outcome procedure and Bolck-Croon-Hagenaars methods were used to assess each class's association with body mass index (BMI) and obesity probability. Models were adjusted for post-secondary school type and parental education. We identified 7 classes for White women, 4 classes for Asian and Latina women, and 5 classes for Black women. Weight distributions of Black and Latina women leaned towards "overweight", whereas White and Asian women's BMI leaned towards "normal weight." Latina and Black women had a wider BMI range (~5 kg/m2) between classes with the highest versus lowest BMI than White and Asian women (~3 kg/m2), suggesting a stronger association between adversities and BMI. For Asian, Black, and White women, the "Low Adversities" class had the lowest obesity prevalence, while the "High Lifetime Adversities" class had the highest prevalence. In contrast, Latina women had the lowest obesity prevalence in the "High Adolescent/Adult Adversities & Low Childhood Adversities" class, and highest prevalence in the "Household Mental Illness" class. Results indicate that racial/ethnic disparities in obesity-related measures are reduced when racial/ethnic groups experience low adversity. Future research should explore tailored adversity interventions that consider adversity exposure differences across race/ethnicity as a strategy for reducing obesity risk.

US shelter in place policies and child abuse Google search volume during the COVID-19 pandemic.

The COVID-19 pandemic has led to unemployment, school closures, movement restrictions, and social isolation, all of which are child abuse risk factors. Our objective was to estimate the effect of COVID-19 shelter in place (SIP) policies on child abuse as captured by Google searches. We applied a differences-in-differences design to estimate the effect of SIP on child abuse search volume. We linked state-level SIP policies to outcome data from the Google Health Trends Application Programming Interface. The outcome was searches for child abuse-related phrases as a scaled proportion of total searches for each state-week between December 31, 2017 and June 14, 2020. Between 914 and 1512 phrases were included for each abuse subdomain (physical, sexual, and emotional). Eight states and DC were excluded because of suppressed outcome data. Of the remaining states, 38 introduced a SIP policy between March 19, 2020 and April 7, 2020 and 4 states did not. The introduction of SIP generally led to no change, except for a slight reduction in child abuse search volume in weeks 8-10 post-SIP introduction, net of changes experienced by states that did not introduce SIP at the same time. We did not find strong evidence for an effect of SIP on child abuse searches. However, an increase in total search volume during the pandemic that may be differential between states with and without SIP policies could have biased these findings. Future work should examine the effect of SIP at the individual and population level using other data sources.

Excess Google Searches for Child Abuse and Intimate Partner Violence During the COVID-19 Pandemic: Infoveillance Approach.

BACKGROUND: The COVID-19 pandemic has created environments with increased risk factors for household violence, such as unemployment and financial uncertainty. At the same time, it led to the introduction of policies to mitigate financial uncertainty. Further, it hindered traditional measurements of household violence. OBJECTIVE: Using an infoveillance approach, our goal was to determine if there were excess Google searches related to exposure to child abuse, intimate partner violence (IPV), and child-witnessed IPV during the COVID-19 pandemic and if any excesses are temporally related to shelter-in-place and economic policies. METHODS: Data on relative search volume for each violence measure was extracted using the Google Health Trends application programming interface for each week from 2017 to 2020 for the United States. Using linear regression with restricted cubic splines, we analyzed data from 2017 to 2019 to characterize the seasonal variation shared across prepandemic years. Parameters from prepandemic years were used to predict the expected number of Google searches and 95% prediction intervals (PI) for each week in 2020. Weeks with searches above the upper bound of the PI are in excess of the model's prediction. RESULTS: Relative search volume for exposure to child abuse was greater than expected in 2020, with 19% (10/52) of the weeks falling above the upper bound of the PI. These excesses in searches began a month after the Pandemic Unemployment Compensation program ended. Relative search volume was also heightened in 2020 for child-witnessed IPV, with 33% (17/52) of the weeks falling above the upper bound of the PI. This increase occurred after the introduction of shelter-in-place policies. CONCLUSIONS: Social and financial disruptions, which are common consequences of major disasters such as the COVID-19 pandemic, may increase risks for child abuse and child-witnessed IPV.

Classes of lifetime adversity in emerging adult women and men and their associations with weight status.

The aim of this paper was to better understand how child and adult adversities cluster together into classes, and how these classes relate to body weight and obesity. Analyses included 2015 and 2018 data from emerging adults (18-25 years old) who participated in a state surveillance system of 2- and 4-year college students in Minnesota (N = 7475 in 2015 and N = 6683 in 2018). Latent Class Analyses (LCA) of 12 child and adult adversities were run stratified by gender and replicated between 2015 and 2018. The distal outcome procedure and three-step Bolck-Croon-Hagenaars approach were used to estimate predicted BMI means and predicted probabilities of obesity for each class, adjusted for covariates. The LCA identified seven classes in women and 5 in men. In women, BMI ranged from 23.9 kg/m2 in the lowest-BMI class ("Adult Adversities and Childhood Household Dysfunction"; 95% CI: 22.6-25.1) to 27.3 kg/m2 in the highest-BMI class ("High Lifetime Adversities"; 95% CI: 25.9-28.7), a statistically significant difference of 3.4 kg/m2. In men, the adjusted BMIs ranged from 24.6 kg/m2 ("Low Adversities"; 95% CI: 24.3-25.0) to 26.0 kg/m2 ("Childhood Household Mental Illness"; 95% CI: 25.1-26.9), a statistically significant difference of 1.4 kg/m2. The pattern was similar for obesity. These results indicate that specific classes of child and adult adversities are strongly associated with BMI and obesity, particularly in women. A key contribution of LCA appeared to be identification of small classes at high risk for excess weight.

Exploring the Links Between Immigration and Birth Outcomes Among Latine Birthing Persons in the USA.

BACKGROUND: Birth outcomes are worse for birthing people and infants in the USA than other high-income economies and worse still for underprivileged communities. Historically, the Latine community has experienced positive birth outcomes, despite low socioeconomic status and other socio-political disadvantages, leading to what has been termed as the Hispanic birth paradox. However, this perinatal advantage and protective effect appears to have been shattered by unfavorable policies, structural conditions, societal attitudes, and traumatic events impacting Latine immigrants, leading to negative effects on the health and well-being of birthing Latines-regardless of citizenship status and increasing rates of preterm birth and low birth weight infants. METHODS AND RESULTS: We conducted a comprehensive literature review and identified two pathways through which birth outcomes among Latine birthing persons may be compromised regardless of citizenship status: (1) a biological pathway as toxic levels of fear and anxiety created by racialized stressors accumulate in the bodies of Latines and (2) a social pathway as Latines disconnect from formal and informal sources of support including family, friends, health care, public health programs, and social services during the course of the pregnancy. CONCLUSION: Future research needs to examine the impact of immigration climate and policies on health and racial equity in birth outcomes among Latines regardless of citizenship status. Attaining health and racial equity necessitates increased awareness among health providers, public health practitioners, and policy makers of the impact of larger socio-political pressures on the health of Latine birthing persons.

Temporal and spatial shifts in gun violence, before and after a historic police killing in Minneapolis.

OBJECTIVE: To determine the impact of the police murder of George Floyd in Minneapolis, MN on firearm violence, and examine the spatial and social heterogeneity of the effect. METHODS: We analyzed a uniquely constructed panel dataset of Minneapolis Zip Code Tabulation Areas from 2016-2020 (n = 5742), consisting of Minnesota Hospital Association, Minneapolis Police Department, Minneapolis Public Schools, Census Bureau, and Minnesota Department of Natural Resources data. Interrupted time-series and random effects panel models were used to model the spatiotemporal effects of police killing event on the rate of firearm assault injuries. RESULTS: Findings reveal a rising and falling temporal pattern post-killing and a spatial pattern in which disadvantaged, historically Black communities near earlier sites of protest against police violence experienced the brunt of the post-killing increase in firearm assault injury. These effects remain after adjusting for changes in police activity and pandemic-related restrictions, indicating that rising violence was not a simple byproduct of changes in police behavior or COVID-19 response. CONCLUSIONS: The results suggest that the increases in firearm violence as a result of police violence are disproportionately borne by underserved communities.

Economic Hardship and Violence: A Comparison of County-Level Economic Measures in the Prediction of Violence-Related Injury.

Economic hardship may lead to a wide range of negative outcomes, including violence. However, existing literature on economic hardship and violence is limited by reliance on official reports of violence and conflation of different measures of economic hardship. The goals of this study are to measure how violence-related injuries are associated with five measures of county-level economic shocks: unemployment rate, male mass layoffs, female mass layoffs, foreclosure rate, and unemployment rate change, measured cross-sectionally and by a 1-year lag. This study measures three subtypes of violence outcomes (child abuse, elder abuse, and intimate partner violence). Yearly county-level data were obtained on violence-related injuries and economic measures from 2005 to 2012 for all 87 counties in Minnesota. Negative binomial models were run regressing the case counts of each violence outcome at the county-year level on each economic indicator modeled individually, with population denominator offsets to yield incidence rate ratios. Crude models were run first, then county-level socio-demographic variables and year were added to each model, and finally fully-adjusted models were run including all socio-demographic variables plus all economic indicators simultaneously. In the fully-adjusted models, a county's higher foreclosure rate is the strongest and most consistently associated with an increase in all violence subtypes. Unemployment rate is the second strongest and most consistent economic risk factor for all violence subtypes. Lastly, there appears to be an impact of gender specific to economic impacts on child abuse; specifically, male mass-lay-offs were associated with increased rates while female mass-lay-offs were associated with decreased rates. Understanding the associations of different types of economic hardship with a range of violence outcomes can aid in developing more holistic prevention and intervention efforts.

The influence of childhood and early adult adversities on substance use behaviours in racial/ethnically diverse young adult women: a latent class analysis.

Childhood and adult adversities occur more frequently among women and persons of colour, possibly influencing racial/ethnic disparities in substance use behaviours. This study investigates how childhood and adult adversities cluster together by race/ethnicity and how these clusters predict binge drinking, tobacco, e-cigarette, and marijuana use. Latent class analysis (LCA) was used in a combined sample from the 2015 to 2018 Minnesota College Student Health Survey to identify clusters of childhood and adult adversities among Asian, Black, Latina, and White women aged 18-25. Each substance use outcome was regressed on each adversity cluster across each race/ethnicity group. Across all racial/ethnic groups and substance use outcomes, the high adversity cluster exhibited the greatest risk. Significant racial/ethnic disparities were observed across several substance use behaviours; these were attenuated among women with fewer adversities. The reduced substance use disparities found among those with lower adversities suggest that prevention of adversities may advance health equity.

Criminal punishment and violent injury in Minnesota.

BACKGROUND: Violence is one of the leading causes of injury and death in the United States. One-way society attempts to eliminate violence is through criminal punishment. Yet, in many contexts, punishment fails to reduce violence and may cause other harms. Current research on violence often suffers from same-source bias which can produce spurious associations. This study assesses the associations of different forms of criminal punishment (monetary sanctions, incarceration, and probation) with violent injuries in two unique datasets. METHODS: This study examines a unique combination of hospital discharge data and court administrative data, two Minnesota county-level data sources. First, we assess the spatial distribution of the three criminal punishment variables and two violent injury variables, violent injury overall and violent injury in children by county from 2010 to 2014, using Moran's I statistic and Local Indicators of Spatial Autocorrelation. Then we assess the association of criminal punishment on violent injury and child abuse injury using a two-way fixed effects panel models. RESULTS: Child abuse injuries are relatively rare in our data but are significantly concentrated geographically, unlike violent injuries which are more dispersed throughout Minnesota. Incarceration and probation are significantly geographically concentrated in similar regions while monetary sanctions are not geographically concentrated. We find a link between probation loads and violent injury, specifically, with a 1 day increase in per capita probation supervision associated with a 0.044 increase in violent injury incidence per 1000 people. In contrast, monetary sanctions and incarceration loads have little association with either violent injury or child abuse injury incidence. CONCLUSIONS: Criminal punishment is intended to reduce harm in society, but many argue that it may bring unintended consequences such as violence. This study finds that county-level probation has a modest positive association with county-level violent injury rates, but monetary sanctions and incarceration are less associated with violence injury rates. No measure of criminal punishment was associated with a reduction in violence. This study addresses a gap in previous literature by examining the association of punishment and violence in two unrelated datasets. High rates of criminal punishment and violent injury are both urgent public health emergencies. Further individual-level investigation is needed to assess potential links.

Measuring the hidden burden of violence: use of explicit and proxy codes in Minnesota injury hospitalizations, 2004-2014.

PURPOSE: Commonly-used violence surveillance systems are biased towards certain populations due to overreporting or over-scrutinized. Hospital discharge data may offer a more representative view of violence, through use of proxy codes, i.e. diagnosis of injuries correlated with violence. The goals of this paper are to compare the trends in violence in Minnesota, and associations of county-level demographic characteristics with violence rates, measured through explicitly diagnosed violence and proxy codes. It is an exploration of how certain sub-populations are overrepresented in traditional surveillance systems. METHODS: Using Minnesota hospital discharge data linked with census data from 2004 to 2014, this study examined the distribution and time trends of explicit, proxy, and combined (proxy and explicit) codes for child abuse, intimate partner violence (IPV), and elder abuse. The associations between county-level risk factors (e.g., poverty) and county violence rates were estimated using negative binomial regression models with generalized estimation equations to account for clustering over time. RESULTS: The main finding was that the patterns of county-level violence differed depending on whether one used explicit or proxy codes. In particular, explicit codes suggested that child abuse and IPV trends were flat or decreased slightly from 2004 to 2014, while proxy codes suggested the opposite. Elder abuse increased during this timeframe for both explicit and proxy codes, but more dramatically when using proxy codes. In regard to the associations between county level characteristics and each violence subtype, previously identified county-level risk factors were more strongly related to explicitly-identified violence than to proxy-identified violence. Given the larger number of proxy-identified cases as compared with explicit-identified violence cases, the trends and associations of combined codes align more closely with proxy codes, especially for elder abuse and IPV. CONCLUSIONS: Violence surveillance utilizing hospital discharge data, and particularly proxy codes, may add important information that traditional surveillance misses. Most importantly, explicit and proxy codes indicate different associations with county sociodemographic characteristics. Future research should examine hospital discharge data for violence identification to validate proxy codes that can be utilized to help to identify the hidden burden of violence.