ABSTRACT
Social determinants of health (SDoH), which encompass the economic, social, environmental, and psychosocial factors that influence health, play a significant role in the development of cardiovascular disease (CVD) risk factors as well as CVD morbidity and mortality. The COVID-19 pandemic and the current social justice movement sparked by the death of George Floyd have laid bare long-existing health inequities in our society driven by SDoH. Despite a recent focus on these structural drivers of health disparities, the impact of SDoH on cardiovascular health and CVD outcomes remains understudied and incompletely understood. To further investigate the mechanisms connecting SDoH and CVD, and ultimately design targeted and effective interventions, it is important to foster interdisciplinary efforts that incorporate translational, epidemiological, and clinical research in examining SDoH-CVD relationships. This review aims to facilitate research coordination and intervention development by providing an evidence-based framework for SDoH rooted in the lived experiences of marginalized populations. Our framework highlights critical structural/socioeconomic, environmental, and psychosocial factors most strongly associated with CVD and explores several of the underlying biologic mechanisms connecting SDoH to CVD pathogenesis, including excess stress hormones, inflammation, immune cell function, and cellular aging. We present landmark studies and recent findings about SDoH in our framework, with careful consideration of the constructs and measures utilized. Finally, we provide a roadmap for future SDoH research focused on individual, clinical, and policy approaches directed towards developing multilevel community-engaged interventions to promote cardiovascular health.
Subject(s)
Cardiovascular Diseases/epidemiology , Social Determinants of Health/statistics & numerical data , Health Equity/statistics & numerical data , HumansABSTRACT
OBJECTIVE: Both diabetes and smoking significantly increase the risk of cardiovascular disease (CVD). Understanding whether a diagnosis of diabetes can be leveraged to promote smoking cessation is a gap in the literature. METHODS: We used data from the US National Health Interview Survey, 2006 to 2018, to investigate the relationship between self-report of diagnosis of diabetes and subsequent smoking abstinence among 142,884 respondents who reported regular smoking at baseline. Effect sizes were presented as hazard ratios (HRs) derived from multivariable Cox regression models adjusted for potential confounders using diabetes as a time-dependent covariate. Subgroup-specific estimates were obtained using interaction terms between diabetes and variables of interest. RESULTS: A self-reported diagnosis of diabetes was associated with smoking abstinence (HR: 1.21; 95% CI: 1.16 to 1.27). The strength of the association varied based on race (P for interaction: 0.004), where it was strongest in African Americans (HR: 1.44; 95% CI: 1.29 to 1.60); income (P for interaction <0.001), where it was strongest in those with a yearly income less than $35,000 (HR: 1.45; 95% CI: 1.36 to 1.53); and educational attainment (P for interaction <0.001), where it was strongest in those who did not attend college (HR: 1.48; 95% CI: 1.40 to 1.57). CONCLUSION: Among adults who smoke, a diagnosis of diabetes is significantly associated with subsequent smoking abstinence. The association is strongest in socially disadvantaged demographics, including African Americans, low-income individuals, and those who did not attend college.
ABSTRACT
Few studies have examined the role of perceived neighborhood characteristics such as neighborhood safety, social cohesion, and contentedness on sedentary behavior (SB) and physical activity (PA) among adolescents. Furthermore, no studies have investigated how these associations are moderated by gender and race. This study aimed to examine the associations of the perceived neighborhood social environment with (SB) and moderate-to-vigorous physical activity (MVPA). Data from 6504 adolescents (aged 15.4 ± 0.03 years) who participated in the National Longitudinal Study of Adolescent Health was used. SB and PA were considered continuously and dichotomously. PNSE variables include safety, social cohesion, and contentedness, where higher values of PNSE indicate a more favorable neighborhood perception. Weighted linear and logistic regression models were used to examine the association of PNSE with continuous total SB (hours/week) and MVPA (bouts/week), and binary excessive SB (14 h/week) and meeting MVPA guidelines (≥ 5 bouts/week), respectively. Associations were stratified by gender and race to test moderation effects. Models were adjusted for demographic, health, parental, and neighborhood covariates. This study found that neighborhood safety and contentedness were negatively associated with SB, whereas neighborhood social cohesion and contentedness were positively associated with PA. Gender-specific and race-specific results remained somewhat consistent with overall findings; however, neighborhood safety was not associated with SB among female and non-White adolescents, respectively. Similarly, neighborhood safety and contentedness were not associated with MVPA for non-White adolescents. Findings suggest that an adolescent's neighborhood environment, gender, and race should be considered when implementing strategies to reduce SB and increase PA.
Subject(s)
Exercise , Residence Characteristics , Sedentary Behavior , Social Environment , Humans , Adolescent , Male , Female , Longitudinal Studies , Residence Characteristics/statistics & numerical data , Adolescent Behavior/psychology , Neighborhood Characteristics , Sex Factors , United States , SafetyABSTRACT
To determine the effects of age and variants of concern on transmission of SARS-CoV-2, we analyzed infection rates among close contacts over 4 periods in Toyama Prefecture, Japan. Among household contacts, odds of infection were 6.2 times higher during the period of the Omicron variant than during previous periods, particularly among children and adolescents.
Subject(s)
COVID-19 , SARS-CoV-2 , Adolescent , Child , Humans , COVID-19/epidemiology , Japan/epidemiologyABSTRACT
PURPOSE: We describe the epidemiology of invasive Haemophilus influenzae disease (IHD) among adults in Japan. METHODS: Data for 200 adult IHD patients in 2014-2018 were analyzed. The capsular type of H. influenzae was determined by bacterial agglutination and polymerase chain reaction (PCR), and non-typeable Haemophilus influenzae (NTHi) was identified by PCR. RESULTS: The annual incidence of IHD (cases per 100,000 population) was 0.12 for age 15-64 years and 0.88 for age ≥ 65 years in 2018. The median age was 77 years, and 73.5% were aged ≥ 65 years. About one-fourth of patients were associated with immunocompromising condition. The major presentations were pneumonia, followed by bacteremia, meningitis and other than pneumonia or meningitis (other diseases). The case fatality rate (CFR) was 21.2% for all cases, and was significantly higher in the ≥ 65-year group (26.1%) than in the 15-64-year group (7.5%) (p = 0.013). The percentage of cases with pneumonia was significantly higher in the ≥ 65-year group than in the 15-64-year group (p < 0.001). The percentage of cases with bacteremia was significantly higher in the 15-64-year group than in the ≥ 65-year group (p = 0.027). Of 200 isolates, 190 (95.0%) were NTHi strains, and the other strains were encapsulated strains. 71 (35.5%) were resistant to ampicillin, but all were susceptible to ceftriaxone. CONCLUSION: The clinical presentations of adult IHD patients varied widely; about three-fourths of patients were age ≥ 65 years and their CFR was high. Our findings support preventing strategies for IHD among older adults, including the development of NTHi vaccine.
Subject(s)
Bacteremia , Haemophilus Infections , Meningitis , Humans , Infant , Aged , Japan/epidemiology , Haemophilus Infections/epidemiology , Haemophilus Infections/microbiology , Haemophilus influenzae , Meningitis/complications , Bacteremia/epidemiology , Bacteremia/complicationsABSTRACT
Genetic testing using reverse transcriptase real-time polymerase chain reaction (rRT-PCR) is the mainstay of diagnosis of COVID-19. However, it has not been fully investigated whether infectious viruses are contained in SARS-CoV-2 genome-positive specimens examined using the rRT-PCR test. In this study, we examined the correlation between the threshold Cycle (Ct) value obtained from the rRT-PCR test and virus isolation in cultured cells, using 533 consecutive clinical specimens of COVID-19 patients. The virus was isolated from specimens with a Ct value of less than 30 cycles, and the lower the Ct value, the more efficient the isolation rate. A cytopathic effect due to herpes simplex virus type 1 contamination was observed in one sample with a Ct value of 35 cycles. In a comparison of VeroE6/TMPRSS2 cells and VeroE6 cells used for virus isolation, VeroE6/TMPRSS2 cells isolated the virus 1.7 times more efficiently than VeroE6 cells. There was no significant difference between the two cells in the mean Ct value of the detectable sample. In conclusion, Lower Ct values in the PCR test were associated with higher virus isolation rates, and VeroE6/TMPRSS2 cells were able to isolate viruses more efficiently than VeroE6 cells.
Subject(s)
COVID-19 , SARS-CoV-2 , Cell Line , Diagnostic Tests, Routine , Humans , Real-Time Polymerase Chain ReactionABSTRACT
BACKGROUND: The increasing prevalence of smartphone apps to help people find different services raises the question of whether apps to help people find physical activity (PA) locations would help better prevent and control having overweight or obesity. OBJECTIVE: The aim of this paper is to determine and quantify the potential impact of a digital health intervention for African American women prior to allocating financial resources toward implementation. METHODS: We developed our Virtual Population Obesity Prevention, agent-based model of Washington, DC, to simulate the impact of a place-tailored digital health app that provides information about free recreation center classes on PA, BMI, and overweight and obesity prevalence among African American women. RESULTS: When the app is introduced at the beginning of the simulation, with app engagement at 25% (eg, 25% [41,839/167,356] of women aware of the app; 25% [10,460/41,839] of those aware downloading the app; and 25% [2615/10,460] of those who download it receiving regular push notifications), and a 25% (25/100) baseline probability to exercise (eg, without the app), there are no statistically significant increases in PA levels or decreases in BMI or obesity prevalence over 5 years across the population. When 50% (83,678/167,356) of women are aware of the app; 58.23% (48,725/83,678) of those who are aware download it; and 55% (26,799/48,725) of those who download it receive regular push notifications, in line with existing studies on app usage, introducing the app on average increases PA and decreases weight or obesity prevalence, though the changes are not statistically significant. When app engagement increased to 75% (125,517/167,356) of women who were aware, 75% (94,138/125,517) of those who were aware downloading it, and 75% (70,603/94,138) of those who downloaded it opting into the app's push notifications, there were statistically significant changes in PA participation, minutes of PA and obesity prevalence. CONCLUSIONS: Our study shows that a digital health app that helps identify recreation center classes does not result in substantive population-wide health effects at lower levels of app engagement. For the app to result in statistically significant increases in PA and reductions in obesity prevalence over 5 years, there needs to be at least 75% (125,517/167,356) of women aware of the app, 75% (94,138/125,517) of those aware of the app download it, and 75% (70,603/94,138) of those who download it opt into push notifications. Nevertheless, the app cannot fully overcome lack of access to recreation centers; therefore, public health administrators as well as parks and recreation agencies might consider incorporating this type of technology into multilevel interventions that also target the built environment and other social determinants of health.
Subject(s)
Mobile Applications , Black or African American , Exercise , Female , Humans , Obesity/epidemiology , Obesity/prevention & control , OverweightABSTRACT
OBJECTIVES: Little is understood about associations between neighborhood characteristics and depression, a cardiovascular disease (CVD) risk factor, in diverse populations. We examined relationships between perceived/objective neighborhood characteristics, depression, and CVD markers within the Washington, DC CV Health/Needs Assessment, an evaluation among predominantly African-American (AA) adults in resource-limited DC communities. METHOD: Factor analysis of overall neighborhood environment perception (NEP) identified three NEP sub-scores:1) violence; 2) physical/social environment; 3) social cohesion (higher score = more favorable perception). Objective neighborhood characteristics were measured by geospatially-derived scores of walkability, transportation, and crime. Depression was defined by the revised Center for Epidemiologic Studies Depression Scale (CESD-R). We used linear-regression modeling to examine neighborhood measures and CESD-R associations. To investigate a subsequent connection with CVD risk, we examined relationships between CESD-R and CVD-associated cytokines in a population subset. RESULTS: Participants (N = 99; mean age = 59.06; 99% AA) had a mean CESD-R score = 5.8(SD = 8.88). In adjusted models, CESD-R scores decreased by 0.20 units (p = 0.01) for every overall NEP unit-increase. Perceived physical/social environment (ß = -0.34, p = 0.04) and social cohesion (ß = -0.82, p = 0.01) were related to CESD-R while perceived violence was not (ß = -0.28, p = 0.1). Of objective neighborhood environment measures (i.e. walk, transit, bike, personal crime, and property crime scores), only property crime score was associated with depression (ß = 4.99, p < 0.03). In population subset (n = 42), higher CESD-R associated with higher IL-1ß (ß = 21.25, p < 0.01) and IL-18 (ß = 0.006, p = 0.01). CONCLUSION: Favorable neighborhood perceptions are related to lower depressive symptoms in a predominantly AA cohort from Washington, DC resource-limited communities. Neighborhood perceptions appear to be strongly associated with depressive symptoms compared to objective characteristics. Increasing CESD-R scores were related to higher pro-inflammatory markers. Improving neighborhood perceptions may be beneficial to psychological well-being and CV health for urban minority residents.
Subject(s)
Cardiovascular Diseases , Aged , Cardiovascular Diseases/epidemiology , Depression/epidemiology , District of Columbia/epidemiology , Heart Disease Risk Factors , Humans , Middle Aged , Needs Assessment , Perception , Residence Characteristics , Risk FactorsABSTRACT
There is no established method for processing data from commercially available physical activity trackers. This study aims to develop a standardized approach to defining valid wear time for use in future interventions and analyses. Sixteen African American women (mean age = 62.1 years and mean body mass index = 35.5 kg/m2) wore the Fitbit Charge 2 for 20 days. Method 1 defined a valid day as ≥10-hr wear time with heart rate data. Method 2 removed minutes without heart rate data, minutes with heart rate ≤ mean - 2 SDs below mean and ≤2 steps, and nighttime. Linear regression modeled steps per day per week change. Using Method 1 (n = 292 person-days), participants had 20.5 (SD = 4.3) hr wear time per day compared with 16.3 (SD = 2.2) hr using Method 2 (n = 282) (p < .0001). With Method 1, participants took 7,436 (SD = 3,543) steps per day compared with 7,298 (SD = 3,501) steps per day with Method 2 (p = .64). The proposed algorithm represents a novel approach to standardizing data generated by physical activity trackers. Future studies are needed to improve the accuracy of physical activity data sets.
Subject(s)
Exercise , Fitness Trackers , Algorithms , Body Mass Index , Female , Heart Rate , HumansABSTRACT
BACKGROUND: Cardiovascular disease (CVD) is the leading cause of death in the world. Given the role of immune cells in atherosclerosis development and progression, effective methods for characterizing immune cell populations are needed, particularly among populations disproportionately at risk for CVD. RESULTS: By using a variety of antibodies combined in one staining protocol, we were able to identify granulocyte, lymphocyte, and monocyte sub-populations by CD-antigen expression from 500 µl of whole blood, enabling a more extensive comparison than what is possible with a complete blood count and differential (CBC). The flow cytometry panel was established and tested in a total of 29 healthy men and women. As a proof of principle, these 29 samples were split by their race/ethnicity: African-Americans (AA) (N = 14) and Caucasians (N = 15). We found in accordance with the literature that AA had fewer granulocytes and more lymphocytes when compared to Caucasians, though the proportion of total monocytes was similar in both groups. Several new differences between AA and Caucasians were noted that had not been previously described. For example, AA had a greater proportion of platelet adhesion on non-classical monocytes when compared to Caucasians, a cell-to-cell interaction described as crucially important in CVD. We also examined our flow panel in a clinical population of AA women with known CVD risk factors (N = 20). Several of the flow cytometry parameters that cannot be measured with the CBC displayed correlations with clinical CVD risk markers. For instance, Framingham Risk Score (FRS) calculated for each participant correlated with immune cell platelet aggregates (PA) (e.g. T cell PA ß = 0.59, p = 0.03 or non-classical monocyte PA ß = 0.54, p = 0.02) after adjustment for body mass index (BMI). CONCLUSION: A flow cytometry panel identified differences in granulocytes, monocytes, and lymphocytes between AA and Caucasians which may contribute to increased CVD risk in AA. Moreover, this flow panel identifies immune cell sub-populations and platelet aggregates associated with CVD risk. This flow cytometry panel may serve as an effective method for phenotyping immune cell populations involved in the development and progression of CVD.
Subject(s)
Blood Volume , Cardiovascular Diseases , Black or African American , Cardiovascular Diseases/diagnosis , Female , Granulocytes , Humans , Male , Monocytes , Pilot Projects , White PeopleABSTRACT
BACKGROUND: Little is known about the associations between perceived neighborhood social environment (PNSE) and depressive symptoms among African Americans. Furthermore, the role of physical activity (PA) as a mediator of this association has not been investigated. The two-fold objectives of this study, therefore, were (1) to examine the associations between PNSE and depressive symptoms among African Americans, and (2) to test the degree to which these associations were mediated by total PA. METHODS: We used baseline data from the Jackson Heart Study (JHS), a single-site, prospective, community-based study of African-American adults (n = 2209) recruited from Jackson, Mississippi. PNSE variables included scores for neighborhood violence (i.e., higher score = more violence), problems (higher score = more problems), and social cohesion (higher score = more cohesion). Depressive symptoms were measured by the 20-item Center for Epidemiological Studies Depression (CES-D) score. First, multilevel modeling, controlling for census tract clustering effects, was used to estimate associations between each PNSE variable and CES-D score, adjusting for covariates, including demographic, health-related, and population density. Second, validated, self-reported total PA, based on active living, sport, and home indices, was tested as the mediator. Multivariable linear regressions with bootstrap-generated 95% bias-corrected confidence intervals (BC CIs) were estimated to test for significant unstandardized indirect effects, controlling for all covariates. RESULTS: Our participants were 64.2% female with a mean age of 52.6 (SD = 12.2) and a mean CES-D score of 10.8 (SD = 8.1). In the fully-adjusted model, neighborhood violence and problems were positively related to depressive symptoms (B = 3.59, 95%CI = 0.93, 6.26, and B = 3.06, 95%CI = 1.19, 4.93, respectively). Neighborhood violence and problems were also indirectly related to depressive symptoms via total PA (B = 0.26, 95%BC CI = 0.05, 0.55; and B = 0.15, 95%BC CI = 0.02, 0.34, respectively). Social cohesion was neither directly nor indirectly related to depressive symptoms. CONCLUSIONS: We found that higher levels of perceived neighborhood problems and violence were directly and positively associated with depressive symptoms. These associations may be explained in part by lower total PA levels. Future interventions to reduce depressive symptoms attributed to neighborhood features should consider emphasizing built environment features that facilitate PA increases in conjunction with community efforts to reduce neighborhood violence and problems.
Subject(s)
Depression/epidemiology , Exercise/psychology , Residence Characteristics , Social Environment , Adult , Black or African American , Aged , Female , Humans , Longitudinal Studies , Male , Middle Aged , Mississippi/epidemiology , Prospective Studies , ViolenceABSTRACT
Objective: To examine the association between state-level tobacco control measures and current use estimates of both e-cigarettes and cigarettes, while accounting for socio-demographic correlates. Methods: Using the 2012-2013 and 2013-2014 National Adult Tobacco Survey (NATS), we assessed prevalence estimates of US adults' e-cigarette and cigarette current use. Four state groups were created based on the combined state-specific prevalence of both products: low cigarette/e-cigarette (n = 15), high cigarette/e-cigarette (n = 16), high cigarette/low e-cigarette (n = 11), and low cigarette/high e-cigarette) (n = 9). To evaluate the implementation of state-level tobacco control measures, Tobacco Control Index (TCI) was calculated using the State of Tobacco Control annual reports for 2012 and 2013. Multinomial logistic regression models were used to examine differences among the four groups on socio-demographic factors and TCI. Low cigarette/e-cigarette group was used as the referent group. Results: Current use estimates of each product varied substantially by state; current e-cigarette use was highest in Oklahoma (10.3%) and lowest in Delaware (2.7%), and current cigarette use was highest in West Virginia (26.1%), and lowest in Vermont (12.6%). Compared to low cigarette/e-cigarette, all other US-state categories had significantly lower TCI scores (high cigarette/e-cigarette: adjusted Relative Risk Ratio [aRRR] = 0.61; 95% confidence interval [CI]: 0.60-0.61, high cigarette/low e-cigarette: aRRR = 0.74; 95% CI: 0.73-0.74, and low cigarette/high e-cigarette: aRRR = 0.72; 95% CI: 0.71-073). Conclusions: Enforcing existing tobacco control measures likely interacts with e-cigarette use despite being cigarette-focused. Continuing to monitor e-cigarette use is critical to establish baseline use and evaluate future e-cigarette specific federal and state-level tobacco regulatory actions while accounting for the existing tobacco control environment. Implications: This study investigates state-level current use estimates of e-cigarettes and cigarettes among US adults; and their association with four existing tobacco control measures. The overall score of these measures was negatively associated with state-level current use estimates such that states with low current e-cigarette and cigarette use had the highest mean overall score. This study assesses the potential relationship between existing state-level tobacco control measures and e-cigarette use and calls for improving the enforcement of the known-to-work tobacco control measures across all US states, while developing evidence-based regulations and interventions specific to e-cigarettes within the existing US tobacco use environment.
Subject(s)
Electronic Nicotine Delivery Systems/statistics & numerical data , Smoking Cessation/statistics & numerical data , Surveys and Questionnaires , Tobacco Products/statistics & numerical data , Tobacco Smoking/epidemiology , Tobacco Smoking/psychology , Adolescent , Adult , Aged , Female , Humans , Male , Middle Aged , Prevalence , Time Factors , United States/epidemiology , Young AdultABSTRACT
BACKGROUND: The built environment predicts walking in older adults, but the degree to which associations between the objective built environment and walking for different purposes are mediated by environmental perceptions is unknown. PURPOSE: We examined associations between the neighborhood built environment and leisure and utilitarian walking and mediation by the perceived environment among older women. METHODS: Women (N = 2732, M age = 72.8 ± 6.8 years) from Massachusetts, Pennsylvania, and California completed a neighborhood built environment and walking survey. Objective population and intersection density and density of stores and services variables were created within residential buffers. Perceived built environment variables included measures of land use mix, street connectivity, infrastructure for walking, esthetics, traffic safety, and personal safety. Regression and bootstrapping were used to test associations and indirect effects. RESULTS: Objective population, stores/services, and intersection density indirectly predicted leisure and utilitarian walking via perceived land use mix (odds ratios (ORs) = 1.01-1.08, 95 % bias corrected and accelerated confidence intervals do not include 1). Objective density of stores/services directly predicted ≥150 min utilitarian walking (OR = 1.11; 95% CI = 1.02, 1.22). Perceived land use mix (ORs = 1.16-1.44) and esthetics (ORs = 1.24-1.61) significantly predicted leisure and utilitarian walking, CONCLUSIONS: Perceived built environment mediated associations between objective built environment variables and walking for leisure and utilitarian purposes. Interventions for older adults should take into account how objective built environment characteristics may influence environmental perceptions and walking.
Subject(s)
Environment Design , Leisure Activities , Motivation , Walking , Aged , Aged, 80 and over , Female , Humans , Middle Aged , Residence CharacteristicsABSTRACT
OBJECTIVE: To investigate the state-specific prevalence, regional differences, and correlates of hookah use among U.S. adults. METHODS: We analyzed the most recent nationally representative data of adults from the National Adult Tobacco Survey (NATS) 2012-2013 (n = 60192). State-specific prevalence of lifetime and current hookah use was calculated and mapped. Multivariate logistic regression was performed to determine the association between sociodemographic characteristics, regional differences, and hookah use. RESULTS: Among U.S. adults (≥18 years), overall prevalence of lifetime hookah use was 12.3%, while current use was 3.9%. Mapping of state-specific prevalence revealed that the West tended to have higher rates of use, while the South tended to have lower ones. In the adjusted model, we observed that current hookah use was positively associated with younger adults, males, non-Hispanic adults, those with higher education and income statuses, being single, those living in the West, and current cigarette use. CONCLUSION: The prevalence of hookah use varies by state, region, and sociodemographic characteristics among adults. Future research, including longitudinal studies, are needed to identify geographic and sociodemographic characteristics and trends among hookah users, investigate hookah-related health outcomes, and evaluate targeted public health efforts aimed at this emerging threat. IMPLICATIONS: This study investigates state-level prevalence, regional differences, and sociodemographic characteristics of hookah use among U.S. adults, using the most recent NATS. Hookah use was positively associated with younger adults and those living in the West. This study adds to the understanding of the geographic and sociodemographic factors underlying hookah use, which can be used to develop much needed evidence-based regulations and programs that are responsive to the needs of different risk groups.
Subject(s)
Water Pipe Smoking/epidemiology , Adolescent , Adult , Aged , Cross-Sectional Studies , Demography , Female , Humans , Interviews as Topic , Logistic Models , Male , Middle Aged , Prevalence , Smoking Cessation/methods , United States , Young AdultABSTRACT
Little is known about how neighborhood noise influences cardiovascular disease (CVD) risk among low-income populations. The aim of this study was to investigate associations between neighborhood noise complaints and body mass index (BMI) and blood pressure (BP) among low-income housing residents in New York City (NYC), including the use of global positioning system (GPS) data. Data came from the NYC Low-Income Housing, Neighborhoods and Health Study in 2014, including objectively measured BMI and BP data (N = 102, Black = 69%), and 1 week of GPS data. Noise reports from "NYC 311" were used to create a noise complaints density (unit: 1000 reports/km2) around participants' home and GPS-defined activity space neighborhoods. In fully-adjusted models, we examined associations of noise complaints density with BMI (kg/m2), and systolic and diastolic BP (mmHg), controlling for individual- and neighborhood-level socio-demographics. We found inverse relationships between home noise density and BMI (B = -2.7 [kg/m2], p = 0.009), and systolic BP (B = -5.3 mmHg, p = 0.008) in the fully-adjusted models, and diastolic BP (B = -3.9 mmHg, p = 0.013) in age-adjusted models. Using GPS-defined activity space neighborhoods, we observed inverse associations between noise density and systolic BP (B = -10.3 mmHg, p = 0.019) in fully-adjusted models and diastolic BP (B = -7.5 mmHg, p = 0.016) in age-adjusted model, but not with BMI. The inverse associations between neighborhood noise and CVD risk factors were unexpected. Further investigation is needed to determine if these results are affected by unobserved confounding (e.g., variations in walkability). Examining how noise could be related to CVD risk could inform effective neighborhood intervention programs for CVD risk reduction.
Subject(s)
Blood Pressure/physiology , Body Mass Index , Noise , Poverty/statistics & numerical data , Adolescent , Adult , Cross-Sectional Studies , Female , Geographic Information Systems , Humans , Male , Middle Aged , New York City/epidemiology , Public Health Surveillance , Residence Characteristics/statistics & numerical data , Young AdultABSTRACT
The objective was to detect geospatial clustering of sugar-sweetened beverage (SSB) intake in Boston adolescents (age = 16.3 ± 1.3 years [range: 13-19]; female = 56.1%; White = 10.4%, Black = 42.6%, Hispanics = 32.4%, and others = 14.6%) using spatial scan statistics. We used data on self-reported SSB intake from the 2008 Boston Youth Survey Geospatial Dataset (n = 1292). Two binary variables were created: consumption of SSB (never versus any) on (1) soda and (2) other sugary drinks (e.g., lemonade). A Bernoulli spatial scan statistic was used to identify geospatial clusters of soda and other sugary drinks in unadjusted models and models adjusted for age, gender, and race/ethnicity. There was no statistically significant clustering of soda consumption in the unadjusted model. In contrast, a cluster of non-soda SSB consumption emerged in the middle of Boston (relative risk = 1.20, p = .005), indicating that adolescents within the cluster had a 20% higher probability of reporting non-soda SSB intake than outside the cluster. The cluster was no longer significant in the adjusted model, suggesting spatial variation in non-soda SSB drink intake correlates with the geographic distribution of students by race/ethnicity, age, and gender.
Subject(s)
Beverages/analysis , Dietary Sugars/administration & dosage , Nutritive Sweeteners/administration & dosage , Adolescent , Body Weight , Boston , Cluster Analysis , Diet , Female , Humans , Male , Nutrition Surveys , Self Report , Spatial Analysis , Students , Young AdultABSTRACT
BACKGROUND: Using validated measures of individuals' perceptions of their neighborhood built environment is important for accurately estimating effects on physical activity. However, no studies to date have examined the factorial validity of a measure of perceived neighborhood environment among older adults in the United States. The purpose of this measurement study was to test the factorial validity of a version of the Abbreviated Neighborhood Environment Walkability Scale (NEWS-A) modified for seniors in the Nurses' Health Study (NHS). FINDINGS: A random sample of 2,920 female nurses (mean age = 73 ± 7 years) in the NHS cohort from California, Massachusetts, and Pennsylvania completed a 36-item modified NEWS-A for seniors. Confirmatory factor analyses were conducted to test measurement models for both the modified NEWS-A for seniors and the original NEWS-A. Internal consistency within factors was examined using Cronbach's alpha. The hypothesized 7-factor measurement model was a poor fit for the modified NEWS-A for seniors. Overall, the best-fitting measurement model was the original 6-factor solution to the NEWS-A. Factors were correlated and internally consistent. CONCLUSIONS: This study provided support for the construct validity of the original NEWS-A for assessing perceptions of neighborhood environments in older women in the United States.
Subject(s)
Environment Design , Residence Characteristics , Walking , Aged , Aged, 80 and over , California , Cohort Studies , Female , Humans , Massachusetts , Middle Aged , Motor Activity , Pennsylvania , Surveys and QuestionnairesABSTRACT
BACKGROUND: Identifying spatial clusters of chronic diseases has been conducted over the past several decades. More recently these approaches have been applied to physical activity and obesity. However, few studies have investigated built environment characteristics in relation to these spatial clusters. This study's aims were to detect spatial clusters of physical activity and obesity, examine whether the geographic distribution of covariates affects clusters, and compare built environment characteristics inside and outside clusters. METHODS: In 2004, Nurses' Health Study participants from California, Massachusetts, and Pennsylvania completed survey items on physical activity (N = 22,599) and weight-status (N = 19,448). The spatial scan statistic was utilized to detect spatial clustering of higher and lower likelihood of obesity and meeting physical activity recommendations via walking. Clustering analyses and tests that adjusted for socio-demographic and health-related variables were conducted. Neighborhood built environment characteristics for participants inside and outside spatial clusters were compared. RESULTS: Seven clusters of physical activity were identified in California and Massachusetts. Two clusters of obesity were identified in Pennsylvania. Overall, adjusting for socio-demographic and health-related covariates had little effect on the size or location of clusters in the three states with a few exceptions. For instance, adjusting for husband's education fully accounted for physical activity clusters in California. In California and Massachusetts, population density, intersection density, and diversity and density of facilities in two higher physical activity clusters were significantly greater than in neighborhoods outside of clusters. In contrast, in two other higher physical activity clusters in California and Massachusetts, population density, diversity of facilities, and density of facilities were significantly lower than in areas outside of clusters. In Pennsylvania, population density, intersection density, diversity of facilities, and certain types of facility density inside obesity clusters were significantly lower compared to areas outside the clusters. CONCLUSIONS: Spatial clustering techniques can identify high and low risk areas for physical activity and obesity. Although covariates significantly differed inside and outside the clusters, patterns of differences were mostly inconsistent. The findings from these spatial analyses could eventually facilitate the design and implementation of more resource-efficient, geographically targeted interventions for both physical activity and obesity.
Subject(s)
Environment Design/statistics & numerical data , Motor Activity , Obesity/epidemiology , Residence Characteristics/statistics & numerical data , Aged , Body Weight , California/epidemiology , Cluster Analysis , Data Collection , Environment , Female , Humans , Likelihood Functions , Massachusetts/epidemiology , Middle Aged , Pennsylvania/epidemiology , Population Density , Spatial Analysis , WalkingABSTRACT
There are few studies of built environment associations with physical activity and weight status among older women in large geographic areas that use individual residential buffers to define environmental exposures. Among 23,434 women (70.0 ± 6.9 yr; range = 57-85) in 3 states, relationships between objective built environment variables and meeting physical activity recommendations via walking and weight status were examined. Differences in associations by population density and state were explored in stratified models. Population density (odds ratio [OR] =1.04 [1.02, 1.07]), intersection density (ORs = 1.18-1.28), and facility density (ORs = 1.01-1.53) were positively associated with walking. Density of physical activity facilities was inversely associated with overweight/obesity (OR = 0.69 [0.49, 0.96]). The strongest associations between facility density variables and both outcomes were found among women from higher population density areas. There was no clear pattern of differences in associations across states. Among older women, relationships between accessible facilities and walking may be most important in more densely populated settings.
Subject(s)
Architectural Accessibility , Environment Design , Obesity , Population Density , Walking , Aged , Architectural Accessibility/methods , Architectural Accessibility/standards , Architectural Accessibility/statistics & numerical data , Body Mass Index , California , Environment Design/standards , Environment Design/statistics & numerical data , Environmental Exposure/statistics & numerical data , Female , Health Behavior , Humans , Massachusetts , Motor Activity , Obesity/diagnosis , Obesity/physiopathology , Obesity/psychology , Odds Ratio , Pennsylvania , Residence Characteristics/statistics & numerical data , Socioeconomic Factors , Walking/physiology , Walking/psychologyABSTRACT
COVID-19 vaccinations are widely available across the United States (U.S.), yet little is known about the spatial clustering of COVID-19 vaccinations. This study aimed to test for geospatial clustering of COVID-19 vaccine rates among adolescents aged 12-17 across the U.S. counties and to compare these clustering patterns by sociodemographic characteristics. County-level data on COVID-19 vaccinations and sociodemographic characteristics were obtained from the COVID-19 Community Profile Report up to April 14, 2022. A total of 3,108 counties were included in the analysis. Global Moran's I statistic and Anselin Local Moran's analysis were used, and clustering patterns were compared to sociodemographic variables using t-tests. Counties with low COVID-19 vaccinated clusters were more likely, when compared to unclustered counties, to have higher numbers of individuals in poverty and uninsured individuals, and higher values of Social Vulnerability Index (SVI) and COVID-19 Community Vulnerability Index (CCVI). While high COVID-19 vaccinated clusters, compared to neighboring counties, had lower numbers of Black population, individuals in poverty, and uninsured individuals, and lower values of SVI and CCVI, but a higher number of Hispanic population. This study emphasizes the importance of addressing systemic barriers, such as poverty and lack of health insurance, which were found to be associated with low COVID-19 vaccination coverage.