Poor social and economic circumstances affect the health of individuals throughout the life cycle. The purpose of the study was to examine whether state-level and individual-level socioeconomic factors are associated with mentally or physically unhealthy days in the general U.S. population of adults. The Behavioral Risk Factor Surveillance System and the American Community Survey in 2016 were used to examine state-level social determinants of health and the number of self-reported mentally unhealthy days in the last 30 days using Zero-Inflated Negative Binomial (ZINB) regression models. Men, older individuals, minorities, persons with higher educational attainment levels, persons who were employed, persons who were married, or with a partner, and persons with one or zero chronic condition were more likely to report excessive zeros for responses to the mentally, and physically unhealthy days. The negative binomial regression results indicated that higher state-level poverty rates, higher income inequity, lower median income, and higher unemployment rates were related to the higher number of reported mentally, and physically unhealthy days. Persons with higher educational attainment, and who were employed reported lower mentally, and physically unhealthy days. The findings show significant relationships between socioeconomic contexts and general health status. Health planners and policymakers may use the results to allocate resources and guide public policies and programs. © The Author(s) 2023.

Despite significant declines in the use of cigarettes, a significant proportion of adults smoke. This study explores the association between smoking and health-related quality of life (HRQoL) by age. The 2016 Behavioral Risk Factor Surveillance System survey was administered to adults in 50 states and District of Columbia (n = 437,195). Physically unhealthy days (PUDs) and mentally unhealthy days (MUDs)) were regressed on age strata (18-24, 25-34, 35-44, 45-54, 55-64, ≥ 65 years) and smoking status (never, former, someday, and everyday) using negative binomial regression models with adjustment for sociodemographic covariates. For each age group, everyday smoking highly predicted PUDs and MUDs. Predicted PUDs increased with age; predicted MUDs decreased with age. Among adults aged 45-54 and 55-64 years, 3-day difference in PUDs was observed between never smokers and everyday smokers. Among young adults (18-24 years), a 4.3-day difference in MUDs was observed between everyday and never smokers. The discrepancies were nonlinear with age. The observed relationship between smoking and HRQoL provides novel information about the need to consider age when designing community-based interventions. Additional research can provide needed depth to understanding the relationship between smoking and HRQoL in specific age groups.

This study examines exposure to multiple forms of violence among Malawian children and youth and their association with mental health outcomes. The Malawi Violence Against Children and Young Women Survey was conducted among a nationally representative sample of males and females aged 13 to 24 years ( n = 2,162) in Malawi in 2013. The experience of sexual, physical, and emotional violence prior to age 18 and during the past 12 months and associated health outcomes were ascertained using a comprehensive interview. Latent factors of sexual violence, physical violence, and emotional violence as well as psychological distress were constructed. We examined whether the experience of violence was related to psychological distress after controlling for age and gender. Violence exposure prior to age 18 (early life) and during the past 12 months (proximal) were valid indicators for a latent factor representing overall lifetime violence exposure. Females were more likely to experience sexual violence, whereas males were more likely to experience physical violence. Experience of any type of violence decreased with age whereas experience of psychological distress increased with age. Current psychological distress was directly associated with exposure to sexual and emotional violence recently or during childhood. Exposure to multiple forms of violence during lifetime was related to two to seven folds higher odds of experiencing psychological distress compared with those who had never experienced violence. Future intervention strategies should address three forms of violence against children simultaneously in light of the associated adverse mental health outcomes.

BACKGROUND: Under most circumstances, the lifetime experience of sexual violence (SV) among girls and young women would likely increase with age. However, the empirical data from a retrospective study may not necessarily conform to this belief. METHODS: Data from a nationally representative sample of females aged 13-24 years in Malawi in 2013 (n=1029) were analyzed. SV was defined as unwanted touching or attempted, pressured, or physically forced sex. The distribution of four types of SV among victims was compared between younger (13-18 years) and older (19-24 years) age groups. The strength of association between SV exposure and health outcomes was examined by age group. RESULTS: The risk of experiencing SV during their lifetime was three times greater for younger than that for older age females (Hazard ratio=3.32). Among females who had experienced SV, older age females were more likely to report forced or pressured sex (41.2%) as their initial SV experience than younger age females (17.8%). The strength of association between the SV exposure and health outcomes did not differ by age group. CONCLUSIONS: The self-report lifetime and childhood victimization to sexual violence may not necessarily higher among older than that among younger females. The current risk of exposure to sexual violence seems to influence the recall of lifetime and childhood victimization to a great extent. In order to make the field aware of this phenomenon, prevalence estimates from all three time frames (lifetime, childhood, and during the past 12 months) should be reported separately by age group.

INTRODUCTION: Hypertension is the leading cause of chronic disease and premature death in the United States. To date, most risk factors for hypertension have been identified at the individual (micro) level. The association of macro-level (area) socioeconomic factors and hypertension prevalence rates in the population has not been studied extensively. METHODS: We used the 2011 Behavioral Risk Factor Surveillance System to examine whether state socioeconomic status (SES) indicators predict the prevalence of self-reported hypertension. Quintiles of state median household income, unemployment rate among the population aged 16 to 64 years, and the proportion of the population under the national poverty line were used as the proxy for state SES. Hypertension status was determined by the question "Have you ever been told by a doctor, nurse, or other health professional that you have high blood pressure?" Logistic regression was used to assess the relationship between state SES and hypertension with adjustment for individual covariates (demographic and socioeconomic factors and lifestyle behaviors). RESULTS: States with a median household income of $43,225 or less (odds ratio [95% confidence interval] = 1.16 [1.08-1.25]) and states with 18.7% or more of residents living below the poverty line (odds ratio [95% confidence interval] = 1.14 [1.04-1.24]) had a higher prevalence of hypertension than states with the most residents in the most advantageous quintile of the indicators. CONCLUSION: The observed state SES-hypertension association indicates that area SES may contribute to the burden of hypertension in community-dwelling adults.

The 2010 Deepwater Horizon oil spill had enormous consequences on the environment. Prevalence of mental and physical health conditions among Gulf residents after the disaster, however, are still being assessed. The Gulf State Population Survey (GSPS) was a representative survey of 38,361 residents in four Gulf States and was conducted from December 2010 to December 2011. Analysis of the GSPS data showed that differences in individual characteristics and direct or indirect exposure to the disaster drove the individual-level variation in health outcomes (mental distress, physical distress, and depression). Direct exposure to the disaster itself was the most important determinant of health after this event. Selected county-level characteristics were not found to be significantly associated with any of our health indicators of interest. This study suggests that in the context of an overwhelming event, persons who are most directly affected through direct exposure should be the primary focus of any public health intervention effort.

INTRODUCTION: Quitting smoking is a critical step toward diabetes control. It is not known whether smoking rates in adults with diabetes are similar to rates among adults who do not have the disease or whether people with diabetes have increased motivation to quit. We examined prevalence trends of current smoking and quit attempts among US adults with and without diagnosed diabetes from 2001 through 2010. METHODS: We used data from the 2001 through 2010 Behavioral Risk Factor Surveillance System, a state-based telephone survey of noninstitutionalized US adults, and conducted linear trend analysis and log linear regression. RESULTS: The adjusted prevalence of cigarette smoking among adults with diagnosed diabetes was 9% less than adults without diagnosed diabetes (adjusted prevalence ratio [APR], 0.91; 99% confidence interval [CI], 0.89-0.93). Declines in smoking prevalence were greater among adults without diabetes than adults with diagnosed diabetes (P < .001). Among smokers, the adjusted prevalence of quit attempts among adults with diagnosed diabetes was 13% higher than among adults without diagnosed diabetes (APR, 1.13; 99% CI, 1.11-1.15). Among adult smokers with diagnosed diabetes, quit attempts were stable over time for those aged 18 to 44 years and those with a high school education or less. Quit attempts were also stable for older smokers, non-Hispanic African Americans, and Hispanic smokers, regardless of diagnosed diabetes status. CONCLUSION: A large proportion of smokers with diagnosed diabetes seemed to have quit smoking, but more research is needed to confirm success and how difficult it was to achieve.

CONTEXT AND OBJECTIVE: Epidemiological studies show the apparent link between excessive alcohol consumption and hypertension. However, the association between alcohol intake and blood pressure among non-hypertensive individuals is scarcely examined. METHODS: This analysis included participants in the 1999-2004 National Health and Nutrition Examination Survey who were aged 20 to 84 years without a diagnosis of cardiovascular disease, hypertension or pregnancy, whose systolic/diastolic blood pressure (SBP/DBP) was lower than 140/90 mmHg, who were not on antihypertensive medication, and who consumed 12 drinks or more during the past 12 months (N = 3957). Average drinking volume (average alcohol intake per day), usual drinking quantity (drinks per day when drinking) and frequency of binge drinking were used to predict SBP/DBP. Covariates included age, gender, race/ethnicity, education level, smoking status, average physical activity level, and daily hours spent on TV/ video/computer. RESULTS: Drinking volume was directly associated with higher SBP in a linear dependent manner (an increment of 10 g of alcohol per day increased average SBP by 1 mmHg among both men and women). Drinking above the US Dietary Guidelines (men more than two drinks and women more than one drink per drinking day) was associated with higher SBP. Binge drinking was associated with both higher SBP and higher DBP. Average intake greater than two drinks per day was particularly associated with higher DBP among women (P = 0.0003). CONCLUSION: This analysis from a population-based survey indicates a direct association between higher alcohol consumption and a higher prevalence of prehypertension among non-hypertensive drinkers.

PURPOSE: To examine whether alcohol drinking status and drinking pattern are associated with self-reported visual impairment. METHODS: We used data from the Behavioral Risk Factor Surveillance System, a state-based telephone health survey conducted by random-digit dialing among non-institutionalized US adults. The Visual Impairment and Access to Eye Care module was implemented among 42,713 adults aged 50 years and older in 2005 and 2006. Visual impairment was defined as any degree of difficulty experienced in recognizing a friend across the street or reading print in newspaper, magazine, recipe, menu, or numbers on the telephone with usual correction. Drinking patterns included drinking quantity (drinks per drinking day), frequency (drinking days in the past month), and binge drinking. RESULTS: After adjustment for age, sex, race/ethnicity, educational attainment, smoking status, Body Mass Index, history of cardiovascular diseases, diabetes, and eye diseases, current drinking status was not associated with distance and/or near vision impairment. However, drinking more than 1 drink per drinking day (odds ratio [OR], 1.21; 95% confidence intervals [CI], 1.09-1.35) and binge drinking (OR, 1.32; 95% CI, 1.14-1.53) were associated with visual impairment among current drinkers. CONCLUSION: Among current drinkers, drinking patterns were significantly associated with near and distance vision impairment. Longitudinal studies are needed to confirm whether drinkers who drink beyond drinking guidelines, especially binge drinkers, are at higher risk of visual impairment than those who drink at lower levels.

This study investigated whether state-level socioeconomic deprivation and income inequality are associated with depression prevalence. Current depressive symptoms within a two-week timeframe were assessed using the patient health questionnaire-2 from the 2006 and 2008 behavioral risk factor surveillance system (BRFSS) administered in selected states. State socio-economic deprivation indexes (percent of people below poverty level; employment/population ratio for the population 16 to 64 years old; median household income) were obtained from the 2006 and 2008 American community survey (ACS). State Gini indexes (indicating income inequality) were obtained from 2000 U.S. Census. After controlling for age, sex, race/ethnicity, marital status, educational attainment, annual household income, and chronic physical health condition index, adults residing in states with median household income in the lowest quintile (OR (95% CI)=1.18 (1.16 to 1.20) vs. others), in states with population below poverty line greater than the fourth quintile (OR (95% CI)=1.22 (1.20 to 1.24), vs. others), in states with employment/population ratios in the lowest quintile (OR(95% CI)=1.31 (1.29 to 1.34), vs. others), and in states with higher income inequality (GINI index >0.452) (OR(95% CI)=1.22 (1.21-1.24), vs. others) had higher odds of current depression. The results suggest that state-level socioeconomic factors are associated with depression prevalence among U.S. adults beyond individual level socioeconomic characteristics.

INTRODUCTION: Some potentially modifiable risk factors and chronic conditions cause significant disease and death during pregnancy and promote the development of chronic disease. This study describes recent trends of modifiable risk factors and controllable chronic conditions among reproductive-aged women. METHODS: Data from the 2001 to 2009 Behavioral Risk Factor Surveillance System, a representative state-based telephone survey of health behavior in US adults, was analyzed for 327,917 women of reproductive age, 18 to 44 years. We calculated prevalence ratios over time to assess trends for 4 selected risk factors and 4 chronic conditions, accounting for age, race/ethnicity, education, health care coverage, and individual states. RESULTS: From 2001 to 2009, estimates of 2 risk factors improved: smoking declined from 25.9% to 18.8%, and physical inactivity declined from 25.0% to 23.0%. One risk factor, heavy drinking, did not change. From 2003 to 2009, the estimates for 1 risk factor and 4 chronic conditions worsened: obesity increased from 18.3% to 24.7%, diabetes increased from 2.1% to 2.9%, high cholesterol increased from 10.3% to 13.6%, asthma increased from 13.5% to 16.2%, and high blood pressure increased from 9.0% to 10.1%. All trends were significant after adjustment, except that for heavy drinking. CONCLUSION: Among women of reproductive age, prevalence of smoking and physical inactivity improved, but prevalence of obesity and all 4 chronic conditions worsened. Understanding reasons for the improvements in smoking and physical activity may support the development of targeted interventions to reverse the trends and help prevent chronic disease and adverse reproductive outcomes among women in this age group.

INTRODUCTION: Tobacco use is the leading preventable cause of death in the United States. Visual impairment, a common cause of disability in the United States, is associated with shorter life expectancy and lower quality of life. The relationship between smoking and visual impairment is not clearly understood. We assessed the association between smoking and visual impairment among older adults with age-related eye diseases. METHODS: We analyzed Behavioral Risk Factor Surveillance System data from 2005 through 2008 on older adults with age-related eye diseases (cataract, glaucoma, age-related macular degeneration, and diabetic retinopathy; age ≥50 y, N = 36,522). Visual impairment was defined by self-reported difficulty in recognizing a friend across the street or difficulty in reading print or numbers. Current smokers were respondents who reported having smoked at least 100 cigarettes ever and still smoked at the time of interview. Former smokers were respondents who reported having ever smoked at least 100 cigarettes but currently did not smoke. We used multivariate logistic regressions to examine the association and to adjust for potential confounders. RESULTS: Among respondents with age-related eye diseases, the estimated prevalence of visual impairment was higher among current smokers (48%) than among former smokers (41%, P < .05) and respondents who had never smoked (42%, P < .05). After adjustment for age, sex, race/ethnicity, education, and general health status, current smokers with age-related eye diseases were more likely to have visual impairment than respondents with age-related eye diseases who had never smoked (odds ratio, 1.16, P < .05). Furthermore, respondents with cataract who were current smokers were more likely to have visual impairment than respondents with cataract who had never smoked (predictive margin, 44% vs 40%, P = .03), and the same was true for respondents with age-related macular degeneration (65% of current smokers vs 57% of never smokers, P = .02). This association did not hold true among respondents with glaucoma or diabetic retinopathy. CONCLUSION: Smoking is linked to self-reported visual impairment among older adults with age-related eye diseases, particularly cataract and age-related macular degeneration. Longitudinal evaluation is needed to assess smoking cessation's effect on vision preservation.

PURPOSE: To examine the association between age-related eye disease (ARED), visual impairment, and health-related quality of life (HRQOL). METHODS: We used data from the 2006 and 2008 Behavioral Risk Factor Surveillance System to examine self-reported visual impairment and two HRQOL domains-physical impairment (including poor general health, physical unhealthy days, activity-limitation days, and disability) and mental distress (including mental unhealthy days, life dissatisfaction, major depression, lifetime depression, and anxiety) for people aged 65 years or older, by ARED status. RESULTS: People with any ARED were more likely than those without to report visual impairment as well as physical impairment and mental distress. The prevalence of visual impairment (P trend <0.001) and physical impairment (P trend <0.001) increased with increasing number of eye diseases after controlling for all covariates. There was no significant linear trend, however, in mental distress among people with one or more eye diseases. CONCLUSION: ARED was found to be associated with visual impairment and poorer HRQOL. Increasing numbers of AREDs were associated with increased levels of visual impairment and physical impairment, but were not associated with levels of mental distress.

PURPOSE: Epidemiologic studies suggest that several gene variants increase the risk of stroke, and population-based studies help provide further evidence. We identified polymorphisms associated with the prevalence of self-reported stroke in US populations using a representative sample. METHODS: Our sample comprised US adults in the Third National Health and Nutrition Examination (NHANES III) DNA bank. We examined nine candidate gene variants within ACE, F2, F5, ITGA2, MTHFR, and NOS3 for associations with self-reported stroke. We used multivariate regression and Cox proportional hazards models to test the association between these variants and history of stroke. RESULTS: In regression models, the rs4646994 variant of ACE (I/I and I/D genotypes) was associated with higher prevalence adjusted prevalence odds ratio [APOR] = 2.66 [1.28, 5.55] and 2.23 [1.30, 3.85], respectively) compared with the D/D genotype. The heterozygous genotype of MTHFR rs1801131 (A/C) was associated with lower prevalence of stroke (APOR = 0.48 [0.25, 0.92]) compared with A/A and C/C genotypes. For rs2070744 of NOS3, both the C/T genotype (APOR = 1.91 [1.12, 3.27]) and C/C genotype (APOR = 3.31 [1.66, 6.60]) were associated with higher prevalence of stroke compared with the T/T genotype. CONCLUSION: Our findings suggest an association between the prevalence of self-reported stroke and polymorphisms in ACE, MTHFR, and NOS3 in a population-based sample.

BACKGROUND: Evidence on the associations of emerging cardiovascular disease risk factors/markers with genes may help identify intermediate pathways of disease susceptibility in the general population. This population-based study is aimed to determine the presence of associations between a wide array of genetic variants and emerging cardiovascular risk markers among adult US women. METHODS: The current analysis was performed among the National Health and Nutrition Examination Survey (NHANES) III phase 2 samples of adult women aged 17 years and older (sample size n = 3409). Fourteen candidate genes within ADRB2, ADRB3, CAT, CRP, F2, F5, FGB, ITGB3, MTHFR, NOS3, PON1, PPARG, TLR4, and TNF were examined for associations with emerging cardiovascular risk markers such as serum C-reactive protein, homocysteine, uric acid, and plasma fibrinogen. Linear regression models were performed using SAS-callable SUDAAN 9.0. The covariates included age, race/ethnicity, education, menopausal status, female hormone use, aspirin use, and lifestyle factors. RESULTS: In covariate-adjusted models, serum C-reactive protein concentrations were significantly (P value controlling for false-discovery rate < or = 0.05) associated with polymorphisms in CRP (rs3093058, rs1205), MTHFR (rs1801131), and ADRB3 (rs4994). Serum homocysteine levels were significantly associated with MTHFR (rs1801133). CONCLUSION: The significant associations between certain gene variants with concentration variations in serum C-reactive protein and homocysteine among adult women need to be confirmed in further genetic association studies.

OBJECTIVE: To explore opportunities for more effective interventions on lifestyle modifications among hypertensives. METHODS: Using 2007 data from the Behavioral Risk Factor Surveillance System from the United States, we assessed the prevalence of various lifestyle behaviors and receipt of preventive health care services among US adults aged 45 years or older based on hypertension and treatment status (n=218,228). RESULTS:. Compared with non-hypertensives, hypertensives were significantly less likely to engage in recommended levels of physical activity and to be more obese regardless of treatment status. Compared to non-hypertensives, hypertensives on medical treatment were less likely to consume five or more servings of fruit and vegetables per day, be current smokers, and binge drinkers. Hypertensives not on medical treatment were more likely to be current smokers, binge and heavy drinkers. Hypertensives on medical treatment were more likely to have routine health check-up, have blood cholesterol check-up within previous five years and have a flu shot within the previous year than hypertensives not on treatment. CONCLUSION: Different patterns of lifestyle behaviors and use of preventive health care services were found based on treatment status among hypertensives. Intervention programs should be tailored accordingly to achieve optimal outcome on lifestyle modification.