Racial and Ethnic Differences in Social Determinants of Health and Health-Related Social Needs Among Adults - Behavioral Risk Factor Surveillance System, United States, 2022.

Social determinants of health (SDOH) are a broad array of social and contextual conditions where persons are born, live, learn, work, play, worship, and age that influence their physical and mental wellbeing and quality of life. Using 2022 Behavioral Risk Factor Surveillance System data, this study assessed measures of adverse SDOH and health-related social needs (HRSN) among U.S. adult populations. Measures included life satisfaction, social and emotional support, social isolation or loneliness, employment stability, food stability/security, housing stability/security, utility stability/security, transportation access, mental well-being, and health care access. Prevalence ratios were adjusted for age, sex, education, marital status, income, and self-rated health. Social isolation or loneliness (31.9%) and lack of social and emotional support (24.8%) were the most commonly reported measures, both of which were more prevalent among non-Hispanic (NH) American Indian or Alaska Native, NH Black or African American, NH Native Hawaiian or other Pacific Islander, NH multiracial, and Hispanic or Latino adults than among NH White adults. The majority of prevalence estimates for other adverse SDOH and HRSN were also higher across all other racial and ethnic groups (except for NH Asian) compared with NH White adults. SDOH and HRSN data can be used to monitor needed social and health resources in the U.S. population and help evaluate population-scale interventions.

Estimation of Numbers of Testing Personnel and Test Volume in the Clinical Laboratory Improvement Amendments of 1988 Certificate of Accreditation and Certificate of Compliance Laboratories in the United States.

CONTEXT.­: Two major categories of laboratories performing nonwaived testing under the Clinical Laboratory Improvement Amendments of 1988 (CLIA) are the Certificate of Accreditation (CoA) and Certificate of Compliance (CoC) laboratories. Accreditation organizations collect more detailed laboratory personnel information than the Centers for Medicare & Medicaid Services (CMS) Quality Improvement and Evaluation System (QIES). OBJECTIVE.­: To estimate total numbers of testing personnel and testing volumes in CoA and CoC laboratories, by laboratory type and state. DESIGN.­: We developed a statistical inference method by using the respective correlations between testing personnel counts and test volume by laboratory type. RESULTS.­: QIES reported 33 033 active CoA and CoC laboratories in July 2021. We estimated testing personnel to be 328 000 (95% CI, 309 000-348 000), which is supported by the count of 318 780 reported by the US Bureau of Labor Statistics. There were twice as many testing personnel in hospital laboratories as in independent laboratories (158 778 versus 74 904, P < .001). Independent laboratories had the highest test volume per person, which was twice as high as physician office laboratories (62 228 versus 30 102, P < .001). Hospital and independent laboratories comprised 34% of all CoA and CoC laboratories but performed the largest portion of testing (81%). Physician office laboratories, accounting for 44% of all CoA and CoC laboratories, performed a comparatively low proportion of total tests (9%). CONCLUSIONS.­: Numbers of testing personnel vary considerably by laboratory type and across states. These data can provide valuable insight when assessing laboratory workforce training needs and planning for public health emergencies.

Analysis of Interview Breakoff in the Behavioral Risk Factor Surveillance System, 2018 and 2019.

Introduction: Survey breakoff is an important source of total survey error. Most studies of breakoff have been of web surveys-less is known about telephone surveys. In the past decade, the breakoff rate has increased in the Behavioral Risk Factor Surveillance System, the world's largest annual telephone survey. Analysis of breakoff in Behavioral Risk Factor Surveillance System can improve the quality of Behavioral Risk Factor Surveillance System. It will also provide evidence in research of total survey error on telephone surveys. Methods: We used data recorded as breakoff in the 2018 and 2019 Behavioral Risk Factor Surveillance System. We converted questions and modules to a time variable and applied Kaplan-Meier method and a proportional hazard model to estimate the conditional and cumulative probabilities of breakoff and study the potential risk factors associated with breakoff. Results: Cumulative probability of breakoffs up to the end of the core questionnaire was 7.03% in 2018 and 9.56% in 2019. The highest conditional probability of breakoffs in the core was 2.85% for the physical activity section. Cumulative probability of breakoffs up to the end of the core was higher among those states that inserted their own questions or optional modules than among those that did not in both years. The median risk ratio of breakoff among all states was 5.70 in 2018 and 3.01 in 2019. Survey breakoff was associated with the length of the questionnaire, the extent of expected recollection, and the location of questions. Conclusions: Breakoff is not an ignorable component of total survey error and should be considered in Behavioral Risk Factor Surveillance System data analyses when variables have higher breakoff rates.

Individual, Community, and Health Facility Predictors of Postnatal Care Utilization in Rural Tanzania: A Multilevel Analysis.

INTRODUCTION: Postnatal care (PNC) is an underused service in the continuum of care for mothers and infants in sub-Saharan Africa. There is little evidence on health facility characteristics that influence PNC utilization. Understanding PNC use in the context of individual, community, and health facility characteristics may help in the development of programs for increased use. METHODS: We analyzed data from 4,353 women with recent births in Kigoma Region, Tanzania, and their use of PNC (defined as at least 1 checkup in a health facility in the region within 42 days of delivery). We used a mixed-effects multilevel logistic regression analysis to explain PNC use while accounting for household, individual, and community characteristics from a regionwide population-based reproductive health survey and for distance to and adequacy of proximal health facilities from a health facility assessment. RESULTS: PNC utilization rate was low (15.9%). Women had significantly greater odds of PNC if they had a high level of decision-making autonomy (adjusted odds ratio [aOR]: 1.56; 95% confidence interval [CI]=1.11, 2.17); had a companion at birth (aOR: 1.57; 95% CI=1.19, 2.07); had cesarean delivery (aOR: 2.27; 95% CI=1.47, 3.48); resided in Kasulu district (aOR: 3.28; 95% CI=1.94, 5.52); or resided in a community that had at least 1 adequate health facility within 5 km (aOR: 2.15; 95% CI=1.06, 3.88). CONCLUSION: Women's decision-making autonomy and presence of companionship at birth, as well as proximity to a health facility with adequate infrastructure, equipment, and workforce, were associated with increased PNC use. More efforts toward advocating for the health benefits of PNC using multiple channels and increasing quality of care in health facilities, including companionship at birth, can increase utilization rates.

Maternal death surveillance efforts: notification and review coverage rates in 30 low-income and middle-income countries, 2015-2019.

OBJECTIVE: Performance of maternal death surveillance and response (MDSR) relies on the system's ability to identify and notify all maternal deaths and its ability to review all maternal deaths by a committee. Unified definitions for indicators to assess these functions are lacking. We aim to estimate notification and review coverage rates in 30 countries between 2015 and 2019 using standardised definitions. DESIGN: Repeat cross-sectional surveys provided the numerators for the coverage indicators; United Nations (UN)-modelled expected country maternal deaths provided the denominators. SETTING: 30 low-income and middle-income countries responding to the Maternal Health Thematic Fund annual surveys conducted by the UN Population Fund between 2015 and 2019. OUTCOME MEASURES: Notification coverage rate ([Formula: see text]) was calculated as the proportion of expected maternal deaths that were notified at the national level annually; review coverage rate ([Formula: see text]) was calculated as the proportion of expected maternal deaths that were reviewed annually. RESULTS: The average annual [Formula: see text] for all countries increased from 17% in 2015 to 28% in 2019; the average annual [Formula: see text] increased from 8% to 13%. Between 2015 and 2019, 22 countries (73%) reported increases in the [Formula: see text]-with an average increase of 20 (SD 18) percentage points-and 24 countries (80%) reported increases in [Formula: see text] by 7 (SD 11) percentage points. Low values of [Formula: see text] contrasts with country-published review rates, ranging from 46% to 51%. CONCLUSION: MDSR systems that count and review all maternal deaths can deliver real-time information that could prompt immediate actions and may improve maternal health. Consistent and systematic documentation of MDSR efforts may improve national and global monitoring. Assessing the notification and review functions using coverage indicators is feasible, not affected by fluctuations in data completeness and reporting, and can objectively capture progress.

Breast Milk Feeding of Infants at Birth Among People With Confirmed SARS-CoV-2 Infection in Pregnancy: SET-NET, 5 States, March 29, 2020-December 31, 2020.

Objectives. To describe prevalence of breast milk feeding among people with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection during pregnancy and examine associations between breast milk feeding, timing of maternal infection before delivery, and rooming-in status during delivery hospitalization. Methods. We performed a retrospective cohort study using data from Massachusetts, Minnesota, Nebraska, Pennsylvania, and Tennessee of whether people with confirmed SARS-CoV-2 infection during pregnancy in 2020 initiated breast milk feeding at birth. Results. Among 11 114 (weighted number) people with SARS-CoV-2 infection in pregnancy, 86.5% (95% confidence interval [CI] = 82.4%, 87.6%) initiated breast milk feeding during birth hospitalization. People with infection within 14 days before delivery had significantly lower prevalence of breast milk feeding (adjusted prevalence ratio [APR] = 0.88; 95% CI = 0.83, 0.94) than did those with infection at least 14 days before delivery. When stratified by rooming-in status, the association between timing of infection and breast milk feeding remained only among infants who did not room in with their mother (APR = 0.77; 95% CI = 0.68, 0.88). Conclusions. Pregnant and postpartum people with SARS-CoV-2 infection should have access to lactation support and be advised about the importance of breast milk feeding and how to safely feed their infants in the same room. (Am J Public Health. 2022;112(S8):S787-S796. https://doi.org/10.2105/AJPH.2022.307023).

Health-Related Behavioral Risk Factors and Obesity Among American Indians and Alaska Natives of the United States: Assessing Variations by Indian Health Service Region.

INTRODUCTION: Health-related behavioral risk factors and obesity are linked to high risk for multiple chronic diseases. We examined the prevalence of these risk factors among American Indians and Alaska Natives (AI/ANs) compared with that of non-Hispanic Whites and across Indian Health Service (IHS) regions. METHODS: We used 2017 Behavioral Risk Factor Surveillance System data from participants in 50 states and the District of Columbia to assess 4 behavioral risk factors (current cigarette smoking, heavy drinking, binge drinking, and physical inactivity) and obesity. We analyzed disparities in these risk factors between AI/AN and non-Hispanic White participants, nationwide and by IHS region, by conducting log-linear regression analyses while controlling for potential confounders. RESULTS: Nationwide, crude prevalence of current smoking, physical inactivity, and obesity were significantly higher among AI/AN than non-Hispanic White participants. After adjustment for sociodemographic characteristics, AI/AN participants were 11% more likely to report current smoking (P < .05) and 23% more likely to report obesity (P < .001) than non-Hispanic White participants. These patterns persisted in most IHS regions with some exceptions. In the Southwest region, AI/AN participants were 39% less likely to report current smoking than non-Hispanic White participants (P < .001). In the Pacific Coast region, compared with non-Hispanic White participants, AI/AN participants were 54% less likely to report heavy drinking (P < .01) but 34% more likely to report physical inactivity (P < .05). Across IHS regions, AI/AN participants residing in Alaska and the Northern Plains regions had the highest prevalence of current smoking and binge drinking, and those in the Southwest and Pacific Coast regions had the lowest prevalence of current smoking. AI/AN participants in the Southwest region had the lowest prevalence of physical inactivity, and those in the Southern Plains region had the highest prevalence of obesity. CONCLUSIONS: The findings of this study support the importance of public health efforts to address and improve behavioral risk factors related to chronic disease in AI/AN people, both nationwide and among IHS regions, through culturally appropriate interventions.

Estimating bias from internet non-use for a hybrid web vaccination survey - 2013-2017 Behavioral Risk Factor Surveillance System.

OBJECTIVE: To maintain acceptable response rates, the cost has grown for vaccination surveys that use traditional data collection modes, such as face-to-face and telephone interviews. Conducting a web or internet survey could be a low-cost alternative. However, because the internet is not used by everyone, we need to study how prevalence estimates in web surveys for vaccination surveillance could be affected by internet non-use. METHOD: We analyzed data from the 2013-2017 Behavioral Risk Factor Surveillance System to assess undercoverage biases from internet non-use by partitioning into proportion of internet non-users and difference in prevalence of influenza and pneumococcal vaccinations between internet and internet non-users, respectively. RESULTS: The proportion of internet non-users decreased monotonically from 43.3% in 2013 to 35.4% in 2017; however, the undercoverage bias from internet use for pneumococcal vaccination increased from 0.8 to 1.5 percentage points at the same time. Overall, the undercoverage bias was -1.1 and 1.5 percentage points for influenza vaccination and pneumococcal vaccination in 2017, respectively. For both vaccinations, we found large absolute and relative biases among certain demographic subgroups. CONCLUSIONS: Although the proportion of internet non-users decreased in recent years, undercoverage bias of hybrid internet survey for influenza and pneumococcal vaccinations did not decrease. Despite a small overall undercoverage bias, the bias in subpopulation groups was not negligible.

Health-related behaviors and health insurance status among US adults: Findings from the 2017 behavioral risk factor surveillance system.

Health insurance coverage has increased overtime in the US. This study examined the associations between health insurance status and adoption of health-related behaviors among US adults. Using data collected through the 2017 Behavioral Risk Factor Surveillance System on health insurance coverage and type of insurance, we examined four health-related behaviors (i.e., no tobacco use, nondrinking or moderate drinking, meeting aerobic physical activity recommendations, and having a healthy body weight) and their associations with health insurance status. We conducted log-linear regression analyses to assess the associations with adjustment for potential confounders. Results showed the percentages of adults who reported no tobacco use or meeting physical activity recommendations were significantly higher, and the percentages of adults with a healthy body weight were significantly lower among those who were insured versus uninsured, or among adults with private insurance versus uninsured. Adults with health insurance also had a higher prevalence of reporting all 4 health-related behaviors than those uninsured. These patterns persisted after multivariable adjustment for potential confounders including sociodemographics, routine checkup, and number of chronic diseases. Adults with public insurance were 7% more likely to report no tobacco use than adults who were uninsured. Additionally, adults with private insurance were 8% and 7% more likely to report no tobacco use and meeting physical activity recommendations, respectively, but 10% less likely to report nondrinking or moderate drinking than adults with public insurance. In conclusion, we found significant associations existed between having health insurance coverage and engaging in some health-related behaviors among US adults.

Estimating Undercoverage Bias of Internet Users.

INTRODUCTION: In the last decade, response rates to the Behavioral Risk Factor Surveillance System (BRFSS) surveys have been declining. Attention has turned to the possibility of using web surveys to complement or replace BRFSS, but web surveys can introduce coverage bias as a result of excluding noninternet users. The objective of this study was to describe undercoverage bias of internet use. METHODS: We used data from 402,578 respondents who completed BRFSS questions in 2017 on internet use, self-reported health, current smoking, and binge drinking. We examined undercoverage bias of internet use by partitioning it into a product of 2 components: proportion of noninternet use and difference in the prevalences of interest (self-reported health, current smoking, and binge drinking) between internet users and noninternet users. RESULTS: Overall, the weighted proportion of noninternet use overall was 15.0%; the proportion increased with an increase in age and a decrease in education and, by race/ethnicity, was lowest among non-Hispanic white respondents. The overall relative bias was -19.2% for self-reported health, -4.0% for current cigarette smoking, and 8.4% for binge drinking. For all 3 variables of interest, we found large biases and relative biases in some demographic subgroups. CONCLUSION: Undercoverage bias of internet use existed in the 3 studied variables. Both proportion of noninternet users and difference in prevalences of studied variables between internet users and noninternet users contributed to the bias to different degrees. These findings have implications on helping health-related behavioral risk factor surveys transition to more cost-effective survey modes than telephone only.

Racial/Ethnic Disparities Among US Children and Adolescents in Use of Dental Care.

INTRODUCTION: Dental care among children has increased over the past decade, and racial/ethnic disparities have narrowed for some groups. We measured changes in racial/ethnic disparities in annual dental care for children and adolescents aged 2 to 17 years and conducted multivariate analysis to study factors associated with changes in disparities over time. METHODS: We used Medical Expenditure Panel Survey data to obtain crude prevalence estimates of dental care use and calculated absolute disparities and changes in disparities for 3 racial/ethnic groups of children and adolescents compared with non-Hispanic white children and adolescents relative to fixed points in time (2001 and 2016). We pooled all single years of data into 3 data cycles (2001-2005, 2006-2010, and 2011-2016) and used multivariate regression to assess the relationship between dental care use and race/ethnicity, controlling for the covariates of age, sex, parents' education, household income, insurance status, and data cycle (time). RESULTS: Use increased by 18% only in low-income children and adolescents. Low-income Hispanic (adjusted prevalence ratio [aPR] = 0.98; 95% CI, 0.94-1.02) and Asian (aPR = 0.92; 95% CI, 0.83-1.02) participants showed no difference in dental care use relative to non-Hispanic white participants, but non-Hispanic black participants had significantly lower use (aPR = 0.84; 95% CI, 0.81-0.88). Public and private insurance were associated with a doubling of use among low-income children. CONCLUSION: We saw a modest increase in dental care use and a narrowing of disparities for some low-income children and adolescents. Use among low-income Hispanic and Asian participants "caught up" with use among Hispanic white participants but remained well below that of children and adolescents in families with middle and high incomes. Disparities persisted for non-Hispanic black participants at all income levels.

Comparisons of Estimates From the Behavioral Risk Factor Surveillance System and Other National Health Surveys, 2011-2016.

INTRODUCTION: The Behavioral Risk Factor Surveillance System (BRFSS) is composed of telephone surveys that collect state data from non-institutionalized U.S. adults regarding health-related risk behaviors and chronic health conditions. A new design was implemented in 2011 to include participants on cellular telephones. It is important to validate estimates since 2011. METHODS: A total of 10 key and widely used variables between BRFSS and the National Health and Nutrition Examination Survey (NHANES) or National Health Interview Survey (NHIS) in 2011-2016 were compared. Data analysis was conducted in 2018. RESULTS: Between BRFSS and NHANES, similar linear time trends of prevalences or means were found for 8 of 9 studied variables. There were no significant differences in the prevalences of the following variables: self-reported fair/poor health, ever told have diabetes, and ever told to have hypertension. In trend comparison of BRFSS versus NHIS, interactions of prevalence between survey and time period were not found for 5 variables: current smoking, self-reported fair/poor health, ever told have diabetes, and self-reported height and weight. Although there were significant differences in many estimates between BRFSS and either NHANES or NHIS, the absolute differences across years were rather small. CONCLUSIONS: Comparing BRFSS time trends with those of 2 national benchmark surveys in 10 key and widely used variables suggests that the trends of prevalences (or means) from BRFSS, NHANES, and NHIS are mostly similar. For many variables, despite statistically significant differences in the prevalences (or means) between surveys, absolute differences in most cases were small and not meaningful from a public health surveillance perspective.

Prevalence of Disability and Disability Types by Urban-Rural County Classification-U.S., 2016.

INTRODUCTION: In the U.S., disability affects approximately 61.4 million (25.7%) adults, with mobility disability being the most prevalent type, affecting about 1 in 7 U.S. adults. However, little is known about the prevalence of disability and functional disability types by urbanization level. METHODS: Data from the 2016 Behavioral Risk Factor Surveillance System were analyzed. The prevalences of disability, overall and by functional disability type, were estimated among U.S. adults across 6 levels of urban-rural county categories based on the 2013 National Center for Health Statistics Urban-Rural Classification Scheme for Counties. Adjusted prevalence ratios with 95% CIs were estimated by conducting log-linear regression analyses with robust variance estimator while adjusting for study covariates. Data analyses were conducted in 2018. RESULTS: The prevalences of having any disability, functional disability type, or multiple disabilities were lowest in large metropolitan centers and fringe metropolitan counties and highest in noncore (rural) counties. After controlling for age, sex, race/ethnicity, education, and federal poverty level, adults living in noncore counties were 9% more likely to report having any disability, 24% more likely to report having 3 or more disabilities, and 7% (cognition) to 35% (hearing) more likely to report specific disability types than the adults living in large metropolitan centers. CONCLUSIONS: Results of this study suggest that significant disparities in the prevalence of disability exist by level of urbanization, with rural U.S. residents having the highest prevalence of disability. Public health interventions to reduce health disparities could include people with disabilities, particularly in rural counties.

Cigarettes point of purchase patterns in 19 low-income and middle-income countries: Global Adult Tobacco Survey, 2008-2012.

BACKGROUND: There is little information on cigarette-purchasing behaviour among smokers globally. Understanding cigarette purchase and point-of-sale patterns can help guide the development and implementation of tobacco-control strategies in retail environments. OBJECTIVE: The purpose of this study was to identify where adults in 19 countries last purchased cigarettes. METHODS: Data were from 19 low-income and middle-income countries that conducted the Global Adult Tobacco Survey (GATS) during 2008-2012. GATS is a nationally representative household survey of adults aged 15 years or older using a standardised protocol to measure tobacco-related behaviours. Data were weighted to yield nationally representative estimates within each country and summarised by using descriptive statistics. RESULTS: Overall prevalence of current cigarette smoking ranged from 3.7% in Nigeria to 38.5% in the Russian Federation. Among current cigarette smokers, locations of last purchase were as follows: stores, from 14.6% in Argentina to 98.7% in Bangladesh (median=66.8%); street vendors, from 0% in Thailand to 35.7% in Vietnam (median=3.0%); kiosks, from 0.1% in Thailand to 77.3% in Argentina (median=16.1%); other locations, from 0.3% in China and Egypt to 57.5% in Brazil (median=2.6%). CONCLUSION: Cigarettes are purchased at various retail locations globally. However, stores and kiosks were the main cigarette purchase locations in 18 of the 19 countries assessed. Knowledge of where cigarette purchases occur could help guide interventions to reduce cigarette accessibility and use.

Effect of Proxy Responses on Tobacco Use Surveys in Thailand, 2011.

Proxy responses are often allowed in household tobacco surveys when all household members are included in a sample. To assess the effect of proxy responses on prevalence estimates, we compared 2 surveys in 2011 that gauged tobacco use in Thailand: the Cigarette Smoking and Alcohol Drinking Survey (SADS) and the Global Adult Tobacco Survey (GATS). Both surveys had similar nonsampling errors and design, but SADS allowed proxy responses and GATS did not. When proxy responses were included in SADS, the prevalence estimate was 10% lower in GATS for men (41.69% in GATS vs 46.55% in SADS) and 18% lower in GATS for women (2.14% in GATS vs 2.61% in SADS). Eliminating proxy responses is recommended to increase accuracy of tobacco-use surveillance.

Self-Perceived Poor/Fair Health, Frequent Mental Distress, and Health Insurance Status Among Working-Aged US Adults.

We examined associations of health insurance status with self-perceived poor/fair health and frequent mental distress (FMD) among working-aged US adults from 42 states and the District of Columbia using data from the 2014 Behavioral Risk Factor Surveillance System. After multiple-variable adjustment, compared with adequately insured adults, underinsured and never insured adults were 39% and 59% more likely to report poor/fair health, respectively, and 38% more likely to report FMD. Compared with working-aged adults with employer-based insurance, adults with Medicaid/Medicare or other public insurance coverage were 28% and 13% more likely to report poor/fair health, respectively, and 15% more likely to report FMD. Increasing insurance coverage and reducing cost barriers to care may improve general and mental health.

Evaluation of a federally funded mass media campaign and smoking cessation in pregnant women: a population-based study in three states.

OBJECTIVES: In 2012, theCenters for Disease Control and Prevention initiated a national anti-smoking campaign, Tips from Former Smokers (Tips). As a result of the campaign, quit attempts among smokers increased in the general population by 3.7 percentage points. In the current study, we assessed the effects of Tips on smoking cessation in pregnant women. METHODS: We used 2009-2013 certificates of live births in three US states: Indiana, Kentucky and Ohio. Smoking cessation by the third trimester of pregnancy was examined among women who smoked in the 3 months prepregnancy. Campaign exposure was defined as overlap between the airing of Tips 2012 (March 19-June 10) and the prepregnancy and pregnancy periods. Women who delivered before Tips 2012 were not exposed. Adjusted logistic regression was used to determine whether exposure to Tips was independently associated with smoking cessation. RESULTS: Cessation rates were stable during 2009-2011 but increased at the time Tips 2012 aired and remained elevated. Overall, 32.9% of unexposed and 34.7% of exposed smokers quit by the third trimester (p<0.001). Exposure to Tips 2012 was associated with increased cessation (adjusted OR: 1.07, 95% CI 1.05 to 1.10). CONCLUSIONS: Exposure to a national anti-smoking campaign for a general audience was associated with smoking cessation in pregnant women.

Cigarette Smoking Among Inmates by Race/Ethnicity: Impact of Excluding African American Young Adult Men From National Prevalence Estimates.

INTRODUCTION: Cigarette smoking prevalence is more than two times greater among incarcerated adults, a population usually excluded from national health surveys. African American young adult (18-25) men are less likely to smoke cigarettes than their white counterparts. However, they are two and a-half-times more likely to be incarcerated. This study estimated smoking prevalence with noninstitutionalized and incarcerated samples combined to determine if excluding incarcerated adults impacts smoking prevalence for certain populations. METHODS: The Bureau of Justice Statistics last fielded the Survey of Inmates in State and Federal Correction Facilities in 2003-2004. We combined data from Survey of Inmates in State and Federal Correction Facilities (n = 17 910) and the 2003 and 2004 National Health Interview Survey (n = 61 470) to calculate combined cigarette smoking estimates by race/ethnicity, sex, and age. RESULTS: Inmates represented the greatest proportion of smokers among African American men. Among African American young adult men, inmates represented 15.2% of all smokers in the combined population, compared to 2.0% among white young adult men. Cigarette smoking prevalence was 17.6% in the noninstitutionalized population of young adult African American men and 19.7% in the combined population. Among white young adult men, cigarette smoking prevalence was 29.8% in the noninstitutionalized population, and 30.2% in the combined population. There was little difference in estimates among women. CONCLUSIONS: The exclusion of incarcerated African American young adult men may result in a small underestimation of cigarette smoking prevalence in this population. Increasing access to smoking cessation support among inmates may reduce smoking prevalence in disproportionately incarcerated segments of the US population. IMPLICATIONS: The exclusion of incarcerated adults from national survey data should be considered when examining differences in cigarette smoking prevalence estimates between African American and white young adult men. Approximately one in six African American young adult men who smoke were incarcerated. Increasing access to smoking cessation support among inmates may reduce smoking prevalence among disproportionately incarcerated segments of the population.

Tobacco advertising, promotion, and sponsorship (TAPS) exposure, anti-TAPS policies, and students' smoking behavior in Botswana and South Africa.

OBJECTIVE: We examined the change over time in tobacco advertising, promotion and sponsorship exposure and the concurrent changes in cigarette smoking behavior among students age 13 to 15years in two African countries with different anti-tobacco advertising, promotion and sponsorship policies. In South Africa, anti-tobacco advertising, promotion and sponsorship policies became more comprehensive over time and were more strictly enforced, whereas the partial anti-tobacco advertising, promotion and sponsorship policies adopted in Botswana were weakly enforced. METHOD: We analyzed two rounds of Global Youth Tobacco Survey data from South Africa (1999, n=2342; 2011, n=3713) and in Botswana (2001, n=1073; 2008, n=1605). We assessed several indicators of tobacco advertising, promotion and sponsorship exposure along with prevalence of current cigarette smoking and smoking susceptibility for each data round. Logistic regression was used to examine changes over time in tobacco advertising, promotion and sponsorship exposure and smoking behavior in both countries. RESULTS: Between 1999 and 2011, South African students' exposure to tobacco advertising and sponsorship decreased significantly by 16% (p value, <0.0001) and 14% (p value, <0.0001), respectively. Exposure to tobacco promotion was lower and did not decrease significantly. Botswanan students' tobacco advertising, promotion and sponsorship exposure did not change significantly between 2001 and 2008. South African students' prevalence of cigarette smoking decreased over time (OR, 0.68) as did susceptibility to smoking (OR, 0.75), but declines did not remain significant after adjusting for parents' and friends' smoking. In Botswana, students' prevalence of cigarette smoking increased significantly over time (OR, 1.84), as did susceptibility to smoking (OR, 2.71). CONCLUSION: Enforcement of strong anti-tobacco advertising, promotion and sponsorship policies is a vital component of effective tobacco control programs in Africa. Such regulations, if effectively implemented, can reduce tobacco advertising, promotion and sponsorship exposure among adolescents and may influence cigarette smoking behavior.

Tobacco and Marijuana Initiation Among African American and White Young Adults.

INTRODUCTION: African American youth use marijuana at similar rates and tobacco at lower rates compared with white youth; however, in adulthood, tobacco use is similar. Tobacco and marijuana use are closely associated; differing initiation patterns may contribute to observed racial differences in tobacco prevalence by age. Therefore, it is important to assess tobacco and marijuana initiation patterns by race. METHODS: Data were obtained from 56,555 adults aged 18-25 who completed the 2005-2012 National Survey on Drug Use and Health. The analysis was restricted to those who reported ever use of marijuana and combustible tobacco (cigarettes and/or cigars). Three mutually exclusive categories of initiation patterns were evaluated: use of marijuana before tobacco; marijuana and tobacco at the same age; and tobacco before marijuana. Multivariable regression models were used to assess changes over time and compare these outcomes by race while controlling for sociodemographics, risk perceptions, and current substance use. RESULTS: In 2005, 26.6% of African American and 14.3% of white young adults used marijuana before tobacco, compared with 41.5% of African American and 24.0% of white young adults in 2012 (P < .001). Overall, African American young adults had greater odds of using marijuana before tobacco (AOR = 1.79; 95% CI: 1.67, 1.91) compared with whites. CONCLUSION: African American young adults were more likely than whites to use marijuana before tobacco and both groups were increasingly likely to use marijuana before tobacco over time. A greater understanding of how marijuana initiation interacts with tobacco initiation could inform more effective tobacco and marijuana use prevention efforts. IMPLICATIONS: Among ever users of combustible tobacco and marijuana, greater proportions of African American young adults used marijuana before tobacco or at the same age than their white counterparts. Moreover, both African Americans and whites were more likely to use marijuana before tobacco in 2012 compared with 2005. Tobacco control policy may benefit from a broader understanding of the patterns of initiation to tobacco and marijuana use. Some public health interventions aimed at preventing and reducing combustible tobacco use among African American young adults may be strengthened by considering marijuana use.