Health-related Behavioral Risk Factors Research Articles

Gender differences in the relationship between loneliness and health-related behavioral risk factors among the Hakka elderly in Fujian, China.

To explore gender differences in the relationship between loneliness and health-related behavioral risk factors (BRFs) among the Hakka elderly. Loneliness was measured by the UCLA Loneliness Scale Short-form (ULS-8). Seven BRFs were examined. Mann-Whitney U, Kruskal-Wallis, and post hoc tests were conducted to compare the differences in ULS-8 scores among the Hakka elderly with different BRFs. Generalized linear regression models were employed to examine the associations of specific BRF and its number with the ULS-8 scores among the Hakka elderly in male, female, and total samples. Physical inactivity (B = 1.96, p < 0.001), insufficient leisure activities participation (B = 1.44, p < 0.001), unhealthy dietary behavior (B = 1.02, p < 0.001), and irregular sleep (B = 2.45, p < 0.001) were positively correlated with the ULS-8 scores, whereas drinking (B = -0.71, p < 0.01) was negatively associated with the ULS-8 scores in the total sample. In males, insufficient leisure activities participation (B = 2.35, p < 0.001), unhealthy dietary behavior (B = 1.39, p < 0.001), and irregular sleep (B = 2.07, p < 0.001) were positively associated with the ULS-8 scores. In females, physical inactivity (B = 2.69, p < 0.001) and irregular sleep (B = 2.91, p < 0.001) was positively correlated with the scores of ULS-8, while drinking (B = -0.98, p < 0.05) was negatively associated with the ULS-8 scores. More BRFs were significantly related to greater loneliness (p < 0.001). There are gender differences in the relationship between loneliness and BRFs among the Hakka elderly, and individuals with more BRFs were more likely to feel loneliness. Therefore, the co-occurrence of multiple BRFs requires more attention, and integrated behavioral intervention strategies should be adopted to reduce the loneliness of the elderly.

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

IntroductionHealth-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.MethodsWe 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.ResultsNationwide, 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.ConclusionsThe 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.

The Relationship between the Number of Daily Health-Related Behavioral Risk Factors and Sleep Health of the Elderly in China.

This study examined the cross-sectional association among a number of daily health-related behavioral risk factors and sleep among Chinese elderly. A sample of 4993 adults, aged 60 years and older, from the China’s Health-Related Quality of Life Survey for Older Adults 2018 was included in this study. Five daily health-related behaviors, which included smoking, drinking, unhealthy eating habits, insufficient leisure activities, and physical inactivity were measured. Sleep disturbances and sleep quality were used to represent the respondents’ sleep status. Multiple logistic regression models and multiple linear regression models were established. The odds ratios (ORs) of sleep disturbances for those with one to five health-related risk behaviors were 1.41 (95% CI = 1.11 to 1.78), 2.09 (95% CI = 1.66 to 2.63), 2.54 (95% CI = 1.99 to 3.25), 2.12 (95% CI = 1.60 to 2.80), and 2.49 (95% CI = 1.70 to 3.65), respectively. Individuals with one health-related risk behavior (B = 0.14, 95% CI = −0.23 to −0.06), two health-related risk behaviors (B = 0.21, 95% CI = −0.30 to −0.13), three health-related risk behaviors (B = 0.46, 95% CI = −0.55 to −0.37), four health-related risk behaviors (B = 0.50, 95% CI = −0.62 to −0.39), and five health-related risk behaviors (B = 0.83, 95% CI = −1.00 to −0.66) showed lower scores of self-perceived sleep quality. Having multiple health-risk behaviors was positively correlated with a higher risk of sleep disturbances among Chinese elderly. Moreover, elderly individuals with multiple health-related risk behaviors were significantly associated with poorer sleep quality.

The Influence of Health Behaviours in Childhood on Attention Deficit and Hyperactivity Disorder in Adolescence.

Attention-deficit and hyperactivity disorder (ADHD) in children and adolescents is a global public health burden. Identification of health-related behavioral risk factors including diet quality and physical and sedentary activities for ADHD is important for prioritizing behavioral intervention strategies to improve mental health. This study aimed to examine the association of diet quality, physical activity, and sedentary behaviours in childhood with ADHD throughout adolescence. We linked data from grade five students aged primarily 10 and 11 years old who participated in a population-based lifestyle survey in the Canadian province of Nova Scotia with their administrative health care data. We applied negative binomial regression methods to examine the associations between health behaviours and ADHD. Of the 4875 students, 9.7% had one or more diagnoses of ADHD between the ages of 10/11 and 18 years. The number of primary diagnoses with ADHD was statistically significantly lower among students with better diet quality, higher levels of physical activity, and those that spent less time playing computers and video games (p < 0.05). These findings suggest that health promotion programs aiming to improve children’s diets and active lifestyles may also reduce the public health burden of ADHD.

Trends in health-related behaviors of Korean adults: study based on data from the 2008-2014 Community Health Surveys.

Unhealthy lifestyle behaviors such as smoking, alcohol consumption, and physical inactivity (multiple risks) often lead to serious health consequence and impaired health status. The purpose of this study was to investigate the trend in health-related behavioral factors over time among adults in South Korea (hereafter Korea). The data of 1,595,842 Koreans older than 19 years who participated in the 2008-2014 Korea Community Health Survey were analyzed to assess the trend in the prevalence of behavioral risk factors. Individual or clustering health-related behaviors were assessed according to sex, age, and region among 228,712 adults who participated in the 2014 survey. From 2008 to 2014, the age-adjusted prevalence of obesity and high-risk alcohol use increased the prevalence of male current smoking and marginally decreased walking ability. Over 7 years, the percentage of adults who reported having all three healthy behaviors (i.e., currently not smoking, not consuming alcohol or having high-risk alcohol use, and engaging in walking) decreased from 35.2% in 2008 to 29.6% in 2014. Increased efforts to emphasize multiple health-related behavioral risk factors, including reducing alcohol use and smoking, and to encourage walking are needed in the thirties and forties age groups in Korea.

Oral Health in North Carolina: Relationship With General Health and Behavioral Risk Factors.

Oral health is an integral part of general health, and loss of teeth may affect both physical and mental health. We examined how an individual's perception of his or her general health is related to oral care and loss of teeth, as well as how socioeconomic and behavioral factors are related to loss of teeth and oral care. Logistic regression was used to analyze data from the North Carolina Behavioral Risk Factor Surveillance System (BRFSS) survey to investigate how oral health relates to general health. We examined the effects of loss of teeth and recency of dental clinic visits on perceived general health; we also examined the effects of demographic characteristics and health-related behavioral risk factors on oral health. Adults who had lost 6 or more teeth were more likely to report poor or fair general health, especially among those who were younger than 65 years (adjusted odds ratio = 3.59) compared to those who were 65 years or older (adjusted odds ratio = 1.87). Those who had not visited a dentist within the past year, those who had less education, those with lower incomes, and smokers were more likely to have lost 6 or more teeth. BRFSS is a large-scale survey that collects self-reported data using random telephone methods; during the years included in this analysis, the sample included only households with landline phones that answered the survey. The measure of general health is subjective. As the BRFSS survey is a cross-sectional survey, causal relationships cannot be established. Loss of teeth and poor oral care are significant predictors of poor general health, indicating that oral health and oral care are integral parts of general health. Loss of teeth and oral care are affected by demographic factors such as educational attainment, income, and health-related risk factors.

Trends in Health-Related Behavioral Risk Factors Among Pregnant Women in the United States: 2001–2009

Unhealthy lifestyle behaviors during pregnancy often predispose women to multiple risks including adverse pregnancy outcomes and impaired health status for mothers. This study assessed the trends in the prevalence of health-related behavioral risk factors over time among U.S. pregnant women. Data from 22,604 pregnant women aged 18-44 years who participated in the 2001-2009 Behavioral Risk Factor Surveillance System were analyzed to assess the trends in the prevalence of behavioral risk factors. Correlates of having individual or clustering healthy behaviors were also assessed among 2295 pregnant women in the 2009 survey. From 2001 to 2009, among pregnant women, the age-adjusted prevalence of engaging in leisure-time exercise and receiving influenza vaccination increased significantly (p<0.05 for linear trends); the prevalence of any alcohol consumption decreased marginally (p=0.065 for linear trend); and the prevalence of binge drinking, smoking, and consuming fruits and vegetables ≥5 times/day varied little. Over the 9 years, the percentages of pregnant women who reported having all four healthy behaviors (i.e., not currently smoking, no alcohol consumption, engaging in leisure-time exercise, and receiving influenza vaccination) increased linearly from 7.3% in 2001 to 21.2% in 2009 (p<0.001). Sociodemographic characteristics, perceived health status, and health-care availability were differentially associated with certain individual or clustered healthy behaviors. Increased efforts emphasizing multiple health-related behavioral risk factors including reducing alcohol use, binge drinking, and smoking and improving fruit and vegetable consumption during pregnancy are needed.

Metabolic Risk Profiles and Associated Risk Factors Among Vietnamese Adults in Ho Chi Minh City

A clustering of metabolic risk factors increases the likelihood of cardiovascular diseases. This study reports the metabolic risk profiles and the prevalence of metabolic risk factors and associated factors among Vietnamese adults in Ho Chi Minh City. A cross-sectional study was carried out in a representative sample of adults aged 25-64 years in Ho Chi Minh City in 2005. Metabolic risk factors, including central obesity, elevated fasting glucose, elevated total cholesterol, and raised blood pressure, were collected to estimate their prevalence and association with socioeconomic and health-related behavioral risk factors. Multivariate logistic models were performed to examine the associations between socioeconomic and behavioral risk factors and the odds of having metabolic risk factors. The prevalence of individual risk components was: 28.9% high blood pressure, 18.3% central obesity, 16.8% high total cholesterol, and 6.4% high fasting glucose. There were significant gender differences in central obesity and high blood pressure. The prevalence of metabolic risk cluster (two or more risk factors) was 17.0% in men and 17.6% in women. The metabolic risk cluster appeared earlier in men, but women showed higher rates at older ages. Increasing age and household wealth were associated with the metabolic risk cluster across both genders, but additional risk factors in men were smoking in the past and in women education level and sitting and reclining time. Strategies to prevent metabolic risk factors through the prevention of abdominal obesity must be established for young adults and should include promoting physical activity, healthy eating, and preventing alcohol abuse and tobacco use.

Area-level poverty and preterm birth risk: A population-based multilevel analysis

BackgroundPreterm birth is a complex disease with etiologic influences from a variety of social, environmental, hormonal, genetic, and other factors. The purpose of this study was to utilize a large population-based birth registry to estimate the independent effect of county-level poverty on preterm birth risk. To accomplish this, we used a multilevel logistic regression approach to account for multiple co-existent individual-level variables and county-level poverty rate.MethodsPopulation-based study utilizing Missouri's birth certificate database (1989–1997). We conducted a multilevel logistic regression analysis to estimate the effect of county-level poverty on PTB risk. Of 634,994 births nested within 115 counties in Missouri, two levels were considered. Individual-level variables included demographics factors, prenatal care, health-related behavioral risk factors, and medical risk factors. The area-level variable included the percentage of the population within each county living below the poverty line (US census data, 1990). Counties were divided into quartiles of poverty; the first quartile (lowest rate of poverty) was the reference group.ResultsPTB < 35 weeks occurred in 24,490 pregnancies (3.9%). The rate of PTB < 35 weeks was 2.8% in counties within the lowest quartile of poverty and increased through the 4th quartile (4.9%), p < 0.0001. High county-level poverty was significantly associated with PTB risk. PTB risk (< 35 weeks) was increased for women who resided in counties within the highest quartile of poverty, adjusted odds ratio (adjOR) 1.18 (95% CI 1.03, 1.35), with a similar effect at earlier gestational ages (< 32 weeks), adjOR 1.27 (95% CI 1.06, 1.52).ConclusionWomen residing in socioeconomically deprived areas are at increased risk of preterm birth, above other underlying risk factors. Although the risk increase is modest, it affects a large number of pregnancies.