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Factor Surveillance System (factor + surveillance_system)
Kinds of Factor Surveillance System Selected AbstractsNatural disasters and older US adults with disabilities: implications for evacuationDISASTERS, Issue 1 2007Lisa C. McGuire PhD We analysed 2003 and 2004 Behavioral Risk Factor Surveillance System (BRFSS) data from New Orleans-Metairie-Kenner, LA to produce estimates of the number of community dwelling people aged 65 years or older with a disability and requiring special equipment., Approximately, 47,840 (31.6 per cent) older adults with a disability and 24,938 (16.6 per cent) older adults requiring the use of special equipment were community dwelling and might require assistance to evacuate or a shelter that could accommodate special equipment. Older adults who need special equipment were likely to be female, unmarried and white, and to rate their health as fair or poor. Personnel who plan and prepare for evacuations and temporary shelter during disasters need baseline information on the number of older adults with a disability or who require special equipment. A surveillance system, such as the BRFSS, gathers information that planners can use to prepare for and to deliver services. [source] US state alcohol sales compared to survey data, 1993,2006ADDICTION, Issue 9 2010David E. Nelson ABSTRACT Aims Assess long-term trends of the correlation between alcohol sales data and survey data. Design Analyses of state alcohol consumption data from the US Alcohol Epidemiologic Data System based on sales, tax receipts or alcohol shipments. Cross-sectional, state annual estimates of alcohol-related measures for adults from the US Behavioral Risk Factor Surveillance System using telephone surveys. Setting United States. Participants State alcohol tax authorities, alcohol vendors, alcohol industry (sales data) and randomly selected adults aged , 18 years 1993,2006 (survey data). Measurements State-level per capita annual alcohol consumption estimates from sales data. Self-reported alcohol consumption, current drinking, heavy drinking, binge drinking and alcohol-impaired driving from surveys. Correlation coefficients were calculated using linear regression models. Findings State survey estimates of consumption accounted for a median of 22% to 32% of state sales data across years. Nevertheless, state consumption estimates from both sources were strongly correlated with annual r-values ranging from 0.55,0.71. State sales data had moderate-to-strong correlations with survey estimates of current drinking, heavy drinking and binge drinking (range of r-values across years: 0.57,0.65; 0.33,0.70 and 0.45,0.61, respectively), but a weaker correlation with alcohol-impaired driving (range of r-values: 0.24,0.56). There were no trends in the magnitude of correlation coefficients. Conclusions Although state surveys substantially underestimated alcohol consumption, the consistency of the strength of the association between sales consumption and survey data for most alcohol measures suggest both data sources continue to provide valuable information. These findings support and extend the distribution of consumption model and single distribution theory, suggesting that both sales and survey data are useful for monitoring population changes in alcohol use. [source] Cardiometabolic Syndrome and Its Association With Education, Smoking, Diet, Physical Activity, and Social Support: Findings From the Pennsylvania 2007 BRFSS SurveyJOURNAL OF CLINICAL HYPERTENSION, Issue 7 2010Longjian Liu MD J Clin Hypertens (Greenwich).2010;12:556,564. © 2010 Wiley Periodicals, Inc. The authors aimed to examine the prevalence of cardiometabolic syndrome (CMS) and its association with education, smoking, diet, physical activity, and social support among white, black, and Hispanic adults using data from the 2007 Pennsylvania Behavior Risk Factor Surveillance System (BRFSS) survey, the largest population-based survey in the state. The authors examined associations between CMS and associated factors cross-sectionally using univariate and multivariate methods. The study included a representative sample of 12,629 noninstitutionalized Pennsylvanians aged ,18. Components of CMS included obesity, hypercholesterolemia, angina (as a surrogate for decreased high-density lipoprotein), prehypertension or hypertension, and prediabetes or diabetes. CMS was identified as the presence of ,3 CMS components. The results show that the prevalence of CMS was 20.48% in blacks, followed by Hispanics (19.14%) and whites (12.26%), (P<.01). Multivariate logistic regression analyses indicated that physical inactivity, lower educational levels, smoking, daily consumption of vegetables and/or fruits <3 servings, and lack of social support were significantly associated with the odds of having CMS. In conclusion, black and Hispanic adults have a significantly higher prevalence of CMS than whites. The significant association between CMS and risk factors provides new insights in the direction of health promotion to prevent and control CMS in those who are at high risk. [source] Binge Drinking and Suboptimal Self-Rated Health Among Adult DrinkersALCOHOLISM, Issue 8 2010James Tsai Background:, Binge drinking accounts for more than half of the 79,000 annual deaths in the United States that are owing to excessive drinking. The overall objective of our study was to examine the prevalence of binge drinking and consumption levels associated with suboptimal self-rated health among the general population of adult drinkers in all 50 states and territories in the United States. Methods:, The study included a total of 200,587 current drinkers who participated in the 2008 Behavioral Risk Factor Surveillance System (BRFSS) survey. We estimated the prevalence of binge drinking (i.e., ,5 drinks on 1 occasion for men or ,4 drinks on 1 occasion for women) and heavy drinking (i.e., an average of >14 drinks per week for men or >7 drinks per week for women), as well as the average number of binge episodes per person during a 30-day period. Odds ratios were produced with multivariate logistic regression models using binge-drinking levels as a predictor; status of suboptimal self-rated health was used as an outcome variable while controlling for sociodemographic, health, and behavioral risk factors. Results:, We estimate that 34.7 million adult drinkers in the United States engaged in binge drinking in 2008, including an estimated 42.2% who reported either heavy drinking or at least 4 binge-drinking episodes in a 30-day period. Binge drinking with such levels was associated with a 13,23% increased likelihood of reporting suboptimal self-rated health, when compared to the nonbinge drinkers. Conclusions:, Binge drinking continues to be a serious public health concern. Frequent binge drinkers or binge drinkers who consume alcohol heavily are especially at risk of suboptimal self-rated health. Our findings underscore the importance of broad-based implementation in health care settings of screening for and brief interventions to address alcohol misuse, as well as the continuing need to implement effective population-based prevention strategies to reduce alcohol-related morbidity and mortality. [source] Characterizing and Reaching High-Risk Drinkers Using Audience SegmentationALCOHOLISM, Issue 8 2009Howard B. Moss Background:, Market or audience segmentation is widely used in social marketing efforts to help planners identify segments of a population to target for tailored program interventions. Market-based segments are typically defined by behaviors, attitudes, knowledge, opinions, or lifestyles. They are more helpful to health communication and marketing planning than epidemiologically defined groups because market-based segments are similar in respect to how they behave or might react to marketing and communication efforts. However, market segmentation has rarely been used in alcohol research. As an illustration of its utility, we employed commercial data that describes the sociodemographic characteristics of high-risk drinkers as an audience segment, including where they tend to live, lifestyles, interests, consumer behaviors, alcohol consumption behaviors, other health-related behaviors, and cultural values. Such information can be extremely valuable in targeting and planning public health campaigns, targeted mailings, prevention interventions, and research efforts. Methods:, We described the results of a segmentation analysis of those individuals who self-reported to consume 5 or more drinks per drinking episode at least twice in the last 30 days. The study used the proprietary PRIZMÔ (Claritas, Inc., San Diego, CA) audience segmentation database merged with the Center for Disease Control and Prevention's (CDC) Behavioral Risk Factor Surveillance System (BRFSS) database. The top 10 of the 66 PRIZMÔ audience segments for this risky drinking pattern are described. For five of these segments we provided additional in-depth details about consumer behavior and the estimates of the market areas where these risky drinkers resided. Results:, The top 10 audience segments (PRIZM clusters) most likely to engage in high-risk drinking are described. The cluster with the highest concentration of binge-drinking behavior is referred to as the "Cyber Millenials." This cluster is characterized as "the nation's tech-savvy singles and couples living in fashionable neighborhoods on the urban fringe." Almost 65% of Cyber Millenials households are found in the Pacific and Middle Atlantic regions of the United States. Additional consumer behaviors of the Cyber Millenials and other segments are also described. Conclusions:, Audience segmentation can assist in identifying and describing target audience segments, as well as identifying places where segments congregate on- or offline. This information can be helpful for recruiting subjects for alcohol prevention research as well as planning health promotion campaigns. Through commercial data about high-risk drinkers as "consumers," planners can develop interventions that have heightened salience in terms of opportunities, perceptions, and motivations, and have better media channel identification. [source] Exploring Pregnancy-Related Changes in Alcohol Consumption Between Black and White WomenALCOHOLISM, Issue 3 2008Daniel S. Morris Background:, Although epidemiological data indicate that White women are more likely to drink and binge drink before pregnancy, fetal alcohol syndrome (FAS) is more common in the Black population than among Whites in the United States. Differences in drinking cessation between Black and White women who become pregnant may help explain the disparity in FAS rates. Methods:, The study sample was comprised of 280,126 non-Hispanic Black and White women, ages 18 to 44, from the Behavioral Risk Factor Surveillance System (BRFSS) 2001 to 2005 data sets. Predictors of reduction in alcohol consumption (in drinks per month) and binge drinking (>4 drinks on one occasion) by pregnant and non-pregnant women were identified with logistic regression. The effect of interactions of pregnancy status with age, education, and Black or White race on drinks per month and binge occasions were explored using analysis of variance (ANOVA). Results:, Pregnant White women averaged 79.5% fewer drinks per month than non-pregnant White women (F = 1250.1, p < 0.001), and 85.4% fewer binge drinking occasions (F = 376, p < 0.001). Pregnant Black women averaged 58.2% fewer drinks per month than non-pregnant Black women (F = 31.8, p < 0.001) and 64.0% fewer binge occasions (F = 13.8, p < 0.001). Compared to Black women, White women appear to make a 38% greater reduction in drinks per month, and a 33% greater reduction in binge occasions. Conclusions:, Non-Hispanic White women appear more likely to reduce drinks per month and binge drinking occasions than non-Hispanic Black women during pregnancy. These findings may help explain disparities in FAS in the United States, though this cross-sectional sample does not permit claims of causation. To better describe the impact of differential drinking reduction on FAS rates, future studies of longitudinal data should be done. [source] A National Study of Obesity Prevalence and Trends by Type of Rural CountyTHE JOURNAL OF RURAL HEALTH, Issue 2 2005J. Elizabeth Jackson MA ABSTRACT: Context: Obesity is epidemic in the United States, but information on this trend by type of rural locale is limited. Purpose: To estimate the prevalence of and recent trends in obesity among US adults residing in rural locations. Methods: Analysis of data from the Behavioral Risk Factor Surveillance System (BRFSS) for the years 1994,1996 (n = 342,055) and 2000,2001 (n = 385,384). The main outcome measure was obesity (body mass index [BMI] ,30), as determined by calculating BMI from respondents' self-reported height and weight. Results: In 2000,2001, the prevalence of obesity was 23.0% (95% confidence interval [CI] 22.6%-23.4%) for rural adults and 20.5% (95% CI 20.2%-20.7%) for their urban counterparts, representing increases of 4.8% (95% CI 4.2%-5.3%) and 5.5% (95% CI 5.1%-5.9%), respectively, since 1994,1996. The highest obesity prevalence occurred in rural counties in Louisiana, Mississippi, and Texas; obesity prevalence increased for rural residents in all states but Florida over the study period. African Americans had the highest obesity prevalence of any group, up to 31.4% (95% CI 29.1%-33.6) in rural counties adjacent to urban counties. The largest difference in obesity prevalence between those with a college education compared with those without a high school diploma occurred in urban areas (18.4% [95% CI 17.9%-18.9%] vs 23.5% [95% CI 22.5%-24.5%], respectively); the smallest difference occurred in small, remote rural counties (20.3% [95% CI 18.7%-21.9%] versus 22.3% [95% CI 20.7%-24.0%], respectively). Conclusions: The prevalence of obesity is higher in rural counties than in urban counties; obesity affects some residents of rural counties disproportionately. [source] Parsimonious prediction model for the prevalence of dental visitsCOMMUNITY DENTISTRY AND ORAL EPIDEMIOLOGY, Issue 5 2008Hazem Seirawan Abstract,,, Objectives:, To analyze the prevalence of dental visits within the last year in the Behavioral Risk Factor Surveillance System or BRFSS (2003) national database by simple sociodemographic factors, and to predict prevalence in States that have not participated in BRFSS 2003. Methods:, Behavioral Risk Factor Surveillance System is a cross-sectional telephone survey conducted by the state-level authorities in the United States and based on a standardized questionnaire to determine the distribution of risk behaviors and health practices among noninstitutionalized adults. A multivariable logistic regression model considers the complex sample design of the BRFSS was used to predict the prevalence of dental visits based on four nonclinic parsimonious variables. Results:, White race, high income (,$35 000), education above high school, and marital status were associated with an annual dental visit with odds ratios of 1.38, 2.09, 1.61, and 1.18, respectively. Utah had the highest percentage (78%) of estimated annual users, while ,Virgin Islands' had the lowest percentage (59%). The model's correct classification rate was 61.5%. Conclusions:, State and local governments, health promotion organizations, insurance companies, and organizations that administer public health programs (such as Medicare and Medicaid in the U.S.) will benefit by applying this model to the available nonclinical databases, and will be able to improve planning of dental health services and required dental workforce. [source] Comparing self-reported and measured high blood pressure and high cholesterol status using data from a large representative cohort studyAUSTRALIAN AND NEW ZEALAND JOURNAL OF PUBLIC HEALTH, Issue 4 2010Anne Taylor Abstract Objective: To examine the relationship between self-reported and clinical measurements for high blood pressure (HBP) and high cholesterol (HC) in a random population sample. Method: A representative population sample of adults aged 18 years and over living in the north-west region of Adelaide (n=1537) were recruited to the biomedical cohort study in 2002/03. In the initial cross-sectional component of the study, self-reported HBP status and HC status were collected over the telephone. Clinical measures of blood pressure were obtained and fasting blood taken to determine cholesterol levels. In addition, data from a continuous chronic disease and risk factor surveillance system were used to assess the consistency of self-reported measures over time. Result: Self-report of current HBP and HC showed >98% specificity for both, but sensitivity was low for HC (27.8%) and moderate for HBP (49.0%). Agreement between current self-report and clinical measures was moderate (kappa 0.55) for HBP and low (kappa 0.30) for HC. Demographic differences were found with younger people more likely to have lower sensitivity rates. Self-reported estimates for the surveillance system had not varied significantly over time. Conclusion: Although self-reported measures are consistent over time there are major differences between the self-reported measures and the actual clinical measurements. Technical aspects associated with clinic measurements could explain some of the difference. Implications: Monitoring of these broad population measures requires knowledge of the differences and limitations in population settings. [source] | ||||||||||