Cross-sectional associations of gender identity and sexual orientation, with co-occurrence and clustering of health-related behaviours among British adolescents: Millennium cohort study

PURPOSE

We examined whether gender identity and sexual orientation were associated with seven health-related behaviours, and with co-occurrence and clustering of these behaviours among British adolescents.

METHODS

Millennium Cohort Study (age 17 wave) provided data on the exposures, gender identity (male, female, genderqueer) and sexual orientation (heterosexual, bisexual, gay or lesbian, or other), and seven self-reported health-related behaviours (binge drinking, drug use, no consumption of breakfast, no consumption of fruits or vegetables, physical inactivity, poor sleep, and smoking or vaping). Poisson regressions examined associations between the exposures and single behaviours (reporting prevalence ratios (PRs)); and multinomial logistic regressions were used for behavioural cumulative co-occurrence score (reporting PRs). Cluster patterns were identified using Ward's agglomerative hierarchical cluster analysis while associations with cluster membership were performed using logistic regressions (reporting odds ratios (ORs)).

RESULTS

Our sample included 6022 adolescents (55.4% female, 1.5% genderqueer, 11.6% non-heterosexual). Adolescents who identified as genderqueer had the highest prevalence of not eating breakfast (PR: 60.5% [95%CI 48.4-71.4]) and poor sleep (68.7% [95%CI 55.6-79.3]). Those who identified as bisexual had a higher PR of co-occurring behaviours (2.46 [95%CI 1.39-4.27]). Among the three clusters identified (1: Multiple risk behaviours; 2: Physical inactivity and binge drinking; 3: Poor diet and physical inactivity), adolescents who identified as genderqueer or other sexual orientation showed the highest prevalence in cluster 3.

CONCLUSION

Gender and sexual minority British adolescents showed a higher prevalence of risky health-related behaviours, and higher risk of co-occurring behaviours. Physical inactivity and poor diet behaviours commonly clustered together for these groups.

Inequality in Physical Activity in Organized Group Settings for Children: A Cross-Sectional Study

BACKGROUND

Adult-led organized settings for children (eg, classrooms) provide opportunities for physical activity (PA). The structure of setting time may influence inequalities (ie, unequalness) in the distribution of PA. This study examined differences in PA inequality by setting and time-segment purpose in time-segmented organized group settings for children.

METHODS

PA and setting meetings were assessed using accelerometer and video observation data from school, before-/after-school, and youth club groups (n = 30) for third- through sixth-grade children (n = 699) in 2 rural US communities. Meetings (n = 130) were time-segmented into smaller units (sessions; n = 835). Each session was assigned a purpose code (eg, PA). Accelerometer data were paired with the meetings and sessions, and the Gini coefficient quantified inequality in activity counts and moderate to vigorous PA minutes for each segment. Beta generalized estimating equations examined differences in PA inequality by setting and session purpose.

RESULTS

Activity count inequality was lowest (P < .05) during youth club meetings (Gini = 0.17, 95% CI, 0.14-0.20), and inequality in moderate to vigorous PA minutes was greatest (P < .01) during school (Gini = 0.34, 95% CI, 0.30-0.38). Organized PA sessions (Gini = 0.20, 95% CI, 0.17-0.23) had lower activity count inequality (P < .0001) than academic (Gini = 0.30, 95% CI, 0.27-0.34), enrichment (Gini = 0.31, 95% CI, 0.27-0.36), and nonactive recreation (Gini = 0.30, 95% CI, 0.25-0.34) sessions. Inequality in moderate to vigorous PA minutes was lower (P < .05) in organized PA (Gini = 0.26, 95% CI, 0.20-0.32) and free play (Gini = 0.28, 95% CI, 0.19-0.39) than other sessions.

CONCLUSIONS

PA inequality differed by setting time structure, with lower inequality during organized PA sessions. The Gini coefficient can illuminate PA inequalities in organized settings and may inform population PA improvement efforts in rural communities.

The introduction of a minimum wage in Germany and the effects on physical activity participation

The relationship between income and physical activity has been extensively studied. This paper utilizes the introduction of the minimum wage in Germany in 2015 as a quasi-experiment to determine the causal effect of minimum wages on the frequency of physical activity participation. Employing survey data from the German Socio-Economic Panel between 2013 and 2017, regression-adjusted difference-in-difference models combined with matching techniques are estimated. Our findings reveal a notable negative effect immediately after the minimum wage implementation on physical activity frequency. Given that the introduction of the minimum wage did not increase monthly gross income but reduced working hours, it appears that affected individuals exhibit preferences and engage in utility maximization that do not emphasize healthy behaviors. This effect is particularly pronounced among older females in white-collar occupations.

Physical inactivity among American single-female caregivers: An analysis of the 2020 behavioral risk factor surveillance system

BACKGROUND

Many adults in the United States do not reach the recommended levels of activity needed for health benefits. Single-female caregivers present a unique and vulnerable population that is often less active than their partnered peers or single-male caregivers.

OBJECTIVE

The primary objective of this cross-sectional investigation was to identify the prevalence of physical inactivity in single-family, female-led households and determine differences in personal factors and social characteristics between physically active and not physically active single-female caregivers. A secondary objective was to examine associations among the social characteristic variables and physical inactivity in single-female caregiver households. Finally, we examined the odds single-female caregivers who are physically inactive reported chronic health conditions.

DESIGN

Cross-sectional survey design.

METHODS

We used the 2020 Behavioral Risk Factor Surveillance System (BRFSS) data. Participants were selected based on pre-determined criteria for inclusion.

RESULTS

There was a 39.3% prevalence of physical inactivity among single-female caregivers in the sample. Single-female caregivers who were physically inactive had greater odds of having a history of multiple chronic health conditions.

CONCLUSION

Healthcare providers and other community stakeholders should explore existing physical activity promotion strategies to increase physical activity in single-female caregivers. Future research should employ more rigorous, prospective research designs to determine if these chronic conditions and various social characteristics are caused by physical inactivity.

Measuring Racial Differences in Obesity Risk Factors in Non-Hispanic Black and White Men Aged 20 Years or Older

Obesity prevalence in the United States has increased drastically in the last two decades. Racial differences in obesity have emerged with the increase in obesity, with temporal trends because of individual, socioeconomic, and environmental factors, eating behaviors, lack of exercise, etc., raising questions about understanding the mechanisms driving these racial differences in the prevalence of obesity among non-Hispanic Black (NHB) and non-Hispanic White (NHW) men. Although many studies have measured obesity using body mass index (BMI), little is known about waist circumference (WC). This study examines variations in obesity among NHW and NHB using BMI and WC. We used National Health and Nutrition Examination Surveys (1999-2016) with a sample of 9,000 NHW and 3,913 NHB men aged 20 years or older. To estimate the association between the prevalence of obesity (BMI ≥30) and race, we applied modified Poisson regression; to explore and decompose racial differences, we used Oaxaca-Blinder decomposition (OBD). We found that NHW had higher abdominal obesity (WC ≥102) than NHB, but NHB were more likely to be obese (BMI ≥30) during most years, with some fluctuations. Modified Poisson regression showed that NHB had a higher prevalence of obesity (prevalence ratio [PR]: 1.11, 95% confidence interval [CI] = [1.04, 1.18]) but lower abdominal obesity (PR: 0.845; 95% CI = [0.801, 0.892]) than NHW. OBD showed that age, access to health care, smoking, and drinking contributed to the differences in abdominal obesity. The study identifies a significant increase in obesity among men over the last two decades; generalized obesity (based on BMI) was more problematic for NHB men, but abdominal obesity was more problematic for NHW men.

Contextualizing physical activity in rural adults: Do relationships between income inequality, neighborhood environments, and physical activity exist?

OBJECTIVE

To examine if income inequality, social cohesion, and neighborhood walkability are associated with physical activity among rural adults.

DATA SOURCE

Cross-sectional data came from a telephone survey (August 2020-March 2021) that examined food access, physical activity, and neighborhood environments across rural counties in a southeastern state.

STUDY DESIGN

Multinomial logistic regression models assessed the likelihood of being active versus inactive and insufficiently active versus inactive in this rural population. Coefficients are presented as relative risk ratios (RRRs). Statistical significance was determined using 95% confidence intervals (CIs). All analyses were performed in STATA 16.1.

DATA COLLECTION/EXTRACTION METHODS

Trained university students administered the survey. Students verbally obtained consent, read survey items, and recorded responses into Qualtrics software. Upon survey completion, respondents were mailed a $10 incentive card and printed informed consent form. Eligible participants were ≥18 years old and current residents of included counties.

PRINCIPAL FINDINGS

Respondents in neighborhoods with relatively high social cohesion versus low social cohesion were more likely to be active than inactive (RRR = 2.50, 95% CI: 1.27-4.90, p < 0.01), after accounting for all other variables in the model. Income inequality and neighborhood walkability were not associated with different levels of physical activity in the rural sample.

CONCLUSIONS

Study findings contribute to limited knowledge on the relationship between neighborhood environmental contexts and physical activity among rural populations. The health effects of neighborhood social cohesion warrant more attention in health equity research and consideration when developing multilevel interventions to improve the health of rural populations.

Psychosocial Factors Associated With Physical Activity Among Low-Income Overweight or Obese Mothers with Young Children

PURPOSE

Investigate the associations between psychosocial factors and physical activity.

DESIGN

Secondary data analysis utilizing baseline data of a large-scale community-based randomized controlled lifestyle behavior intervention.

SETTING

The Special Supplemental Program for Women, Infants, and Children in Michigan, USA.

SUBJECTS

Low-income overweight or obese mothers with young children (N = 740, 65% response rate).

MEASURES

Survey data were collected via phone interview. Predictors included self-efficacy, autonomous motivation, emotional coping, and social support. Self-reported leisure physical activity was the outcome variable. Covariates were age, race, smoking, employment, education, body mass index, and postpartum status.

ANALYSIS

A multiple linear regression model was applied.

RESULTS

Self-efficacy (β = .32, 95% CI = .11, .52, P = .003) and autonomous motivation (β = .10, 95% CI = .03, .17, P = .005) were positively associated with physical activity. However, emotional coping and social support were not associated with physical activity.

CONCLUSION

Future research should examine the longitudinal association of key psychosocial factors with physical activity.

Recovery shape of physical activity after COVID-19 pandemic

BACKGROUND

Since the shutdowns associated with the coronavirus disease 2019 pandemic, there has been limited discourse on physical activity (PA) recovery (i.e., the ability of individuals to resume PA at pre-pandemic levels), including recovery rate, speed of recovery, which individuals are able to return quickly, who is left behind, and what are the causes of those differences. This study aimed to estimate the level and shape of PA recovery rate in Thailand.

METHODS

This study employed 2 rounds (2020 and 2021) of Thailand's Surveillance on Physical Activity dataset for the analysis. Each round included over 6600 samples from individuals aged 18 years or older. PA was assessed subjectively. Recovery rate was calculated from the relative difference in the cumulative minutes of MVPA from 2 different periods.

RESULTS

The Thai population experienced a medium level of recession of PA (-26.1%) and a moderate level of recovery of PA (37.44%). PA recovery in the Thai population resembled an imperfect V shape, reflecting a sharp decline followed by an immediate upturn; still, recovered PA remained lower than pre-pandemic levels. The quickest recovery was found among older adults, whereas students, young adults, residents of Bangkok, the unemployed, and those who had a negative attitude toward PA experienced the highest recession of PA and were among the slowest to recover.

CONCLUSION

The level of recovery of PA among Thai adults is largely determined by the preventive behaviors demonstrated by groups within the population who have a higher awareness of their health. The effect of the mandatory coronavirus disease 2019 containment measures on PA was temporary. However, the slower recovery rate of PA among some individuals was caused by a combination of restrictive measures and socioeconomic inequality, which required more time and effort to overcome.

College student aerobic and muscle-strengthening activity: the intersection of gender and race/ethnicity among United States students

Objective: To adopt an intersectional approach to examine differences in aerobic and muscle-strengthening participation based on the intersection of gender and race/ethnicity among college students. Methods: Data from the American College Health Association (ACHA) National College Health Assessment collected between 2015 and 2018 were analyzed. Differences in the prevalence of meeting activity recommendations based on the intersection of gender and race/ethnicity were computed and displayed graphically. Odds of meeting activity recommendations were determined by calculating odds ratios controlling for age, year of enrollment, sexual orientation, and health status. Results: Aerobic and muscle-strengthening activity differed significantly between races within genders, and between genders within races. With minor exceptions, men were more likely to meet aerobic and muscle-strengthening activity recommendations than women of the same race/ethnicity. Disparities based on race varied considerably between genders. Conclusions: The intersection of gender and race/ethnicity should be considered when examining and addressing physical activity disparities.

The Relationship between Inequalities in Household Sports Consumption Expenditures and Income Level

Inequalities in income, wealth, quality of life, health and education are an intensively researched field of economics. In this study, we examine the inequality in sports expenditures of Hungarian households. We hypothesize that the development of income inequalities will also correlate significantly to inequalities in sports consumption, and this trend has been intensifying over the past two decades. The research is based on the Household Budget Survey database of Hungarian households for the period 2005-2017. The net income conditions of the population and the sports expenditure items recorded on the basis of the COICOP nomenclature are examined by income decile. Data is analysed using descriptive statistics, inequality indicators and correlation calculations. Aggregate household expenditures on passive sports consumption show a stagnant trend, while aggregate expenditures on active sports consumption follow a slightly upward trend among the Hungarian population. Inequality indicators show growing inequalities in terms of income and sports expenditure over the reviewed period. Income inequality and sports spending inequality move together. The Hungarian population is becoming polarised in terms of both income and level of sports expenditure.

Beyond "Exercise as Medicine" in Physical Therapy: Toward the Promotion of Exercise as a Public Good

Physical therapists are uniquely positioned through their knowledge and skills to help people become more physically active, which may reduce the consequences of physical inactivity for health-related quality of life and the global economy. The "Exercise Is Medicine" campaign was introduced in 2007. It holds that exercise may be prescribed like a medicine. Although this analogy doubtlessly has promoted innumerable life-changing conversations between clinicians and patients, there are important shortcomings to considering physical activity and exercise as medicine. In the United States, many of these shortcomings relate to how medical services are provided and remunerated. Medical care is provided in the context of exclusive groups, which are established by insurance, preferred service populations, or other characteristics that determine a basis for providing care. Exclusivity means that medical care is frequently provided in a type of club. The club structure of medical care jeopardizes the ability of nonmembers to benefit. Medical care clubs based on payment create an environment in which nonpaying customers may not benefit in the same manner as paying customers from approaches that consider exercise prescribed as medicine. This clinical perspective reviews the characteristics of exercise as a good, focusing on how it is prescribed by physical therapists. It discusses how physical therapists may become involved in the process of making exercise a public good by reducing its exclusivity. Multiple levels of involvement are recommended at the societal, community, and individual levels. These involvements may be guided by an existing construct proposed by the World Health Organization, which would bring the global physical therapy profession into a common alignment. This Perspective concludes with a discussion that anticipates the shortcomings of conceptualizing exercise as a public good to be addressed in future service delivery models.

Income Inequality, Race/Ethnicity, and Obesity in U.S. Men 20 Years and Older: 1999 to 2016

Obesity is a significant public health problem globally and within the United States. It varies by multiple factors, including but not limited to income. The literature indicates little evidence of the association between income and obesity. We examined the association between income and obesity in U.S. adult men ages 20 years and older and tested racial and ethnic differences. We used data from the 1999 to 2016 National Health and Nutrition Examination Surveys for analyses. Obesity was determined using body mass index ≥30 kg/m2. We used poverty income ratio (PIR) as a proxy for income and calculated the Gini coefficient (GC) to measure income inequality. We then categorized low-, medium-, and high PIR to examine the relationship between income inequality and obesity. We used Modified Poisson regression in a sample of 17,238 adult men, including 9,511 White Non-Hispanic White (NHW), 4,166 Non-Hispanic Black (NHB), and 3,561 Mexican Americans (MA). We controlled the models for age category, racial and ethnic groups, marital status, education, health behaviors, health insurance coverage, self-reported health, comorbidity, and household structure. Results of our adjusted models suggested a positive and significant association between PIR and obesity among NHWs and NHBs in medium and high PIR; this association was not significant in MAs. Results of our analyses using GC in obese men indicate that compared with NHWs (GC: 0.306, SE: 0.004), MAs (GC: 0.368, SE: 0.005), and NHBs (GC: 0.328, SE: 0.005) had experienced higher-income inequality. In treating obesity, policymakers should consider race/ethnicity strategies to reduce inequality in income.

Refining index to measure physical activity inequality: which group of the population is the most vulnerable?

BACKGROUND

The existing body of research mostly discusses inequality in physical activity (PA) based on the difference in the level of moderate-to-vigorous physical activity (MVPA). Evidence is lacking on the quantified inequality measures (e.g., how big the inequality is, and the distribution) in order to identify the most vulnerable groups of a population. This study measured PA inequality among Thai adults by using three parameters to construct an inequality index: (1) Proportion of the population with sufficient MVPA; (2) Cumulative minutes of MVPA; and (3) The Gini coefficient.

METHODS

This study employed three rounds of data from Thailand's Surveillance on Physical Activity (SPA) 2019-2021. In each round, over 6,000 individuals age 18-64 years were selected as nationally-representative samples, and were included in the analysis. PA inequality was constructed by using three parameters, with a combination of the three as the final measure, to identify the sub-groups of the Thai adults who are most vulnerable: groups with the least MVPA, highest insufficiency, and highest inequality index (Gini).

RESULTS

Covid-19 containment measures have widened the gap in PA inequality, as shown by a declining proportion of the population meeting the recommended guidelines, from 74.3% in 2019 to 56.7% in 2020 and 65.5% in 2021. PA inequality existed in all sub-populations. However, by combining three parameters, the most vulnerable groups during the Covid-19 epidemic were identified as follows: (1) Those with no income; (2) The unemployed; (3) Those who have no access to PA facilities; (4) Older adults aged 60 + years; and (5) Those earning < 3,500 baht per month. Further, residents of Bangkok, young adults aged 18-24, individuals who attained primary level education or less, those who had no exposure to a PA awareness campaign and those who have a debilitating chronic disease also had elevated risk of PA insufficiency.

CONCLUSION

A concerning level of PA inequality existed in all sub-populations. The use of combined indicators in measuring PA inequality should aid in determining the most vulnerable groups of the population with a refined procedure. This method can be applied in many settings since the baseline data used to measure inequality (i.e., percent sufficient and cumulative minutes of MVPA) are widely available.

Nível de atividade física de adultos: associação com escolaridade, renda e distância dos espaços públicos abertos em Criciúma, Santa Catarina

RESUMO O objetivo do estudo foi avaliar a associação entre o nível de atividade física com a escolaridade e renda de adultos e distância dos espaços públicos abertos de Criciúma, Santa Catarina, Brasil. Aplicou-se um questionário para avaliar o perfil da população criciumense, e a avaliação dos espaços foi em in loco por meio do instrumento Physical Activity Resource Assessment – PARA. Identificou-se 100 espaços e entrevistou-se 820 residentes de ambos os sexos. Verificou-se que 74,9% da população não alcança a recomendação mínima de atividade física semanal. A variável escolaridade apresentou associação positiva com o nível de atividade física. Conclui-se que há necessidade de desenvolver estratégias que estimulem comportamentos ativos e reformulação de políticas públicas para utilização dos espaços públicos, promovendo uma cidade saudável.

How Income Inequality and Race/Ethnicity Drive Obesity in U.S. Adults: 1999-2016

Obesity is a major public health problem both globally and within the U.S. It varies by multiple factors, including but not limited to income and sex. After controlling for potential covariates, there is little evidence to determine the association between income and obesity and how obesity may be moderated by sex and family income. We examined the association between income and obesity in U.S. adults aged 20 years and older, and tested whether this relationship differs by race or ethnicity groups. For this analysis, we used data from the 1999-2016 National Health and Nutrition Examination Surveys (NHANES). Obesity was determined using Body Mass Index ≥ 30 kg/m2; the Gini coefficient (GC) was calculated to measure income inequality using the Poverty Income Ratio (PIR). We categorized the PIR into five quintiles to examine the relationship between income inequality and obesity. For the first set of analyses, we used a modified Poisson regression in a sample of 36,665 adults, with an almost equal number of men and women (women's ratio was 50.6%), including 17,303 white non-Hispanics (WNH), 7475 black non-Hispanics (BNHs), and 6281 Mexican Americans. The models included age, racial/ethnic groups, marital status, education, health behaviors (smoking and drinking status and physical activities), health insurance coverage, self-reported health, and household structure (live alone and size of household). Adjusting for potential confounders, our findings showed that the association between PIR and obesity was positive and significant more frequently among WNH and BNH in middle and top PIR quintiles than among lower-PIR quintiles; this association was not significant in Mexican Americans (MAs). Results of GC in obese women showed that in comparison with WNHs (GC: 0.34, S.E.: 0.002), BNHs (GC: 0.38, S.E.: 0.004) and MAs (GC: 0.41, S.E.: 0.006) experienced higher income inequality, and that BNH obese men experienced the highest income inequality (GC: 0.45, S.E.: 0.011). The association between PIR and obesity was significant among WNHs and BNHs men in the 3rd, 4th and 5th PIR quintiles. The same association was not found for women. In treating obesity, policymakers should consider not only race/ethnicity and sex, but also strategies to reduce inequality in income.

Assessment of muscle-strengthening exercise in public health surveillance for adults: A systematic review

There is strong scientific evidence that muscle-strengthening exercise (i.e. use of weight machines, push-ups, sit-ups) is independently associated with a reduced risk of multiple chronic diseases (e.g. diabetes, hypertension, cardiovascular disease). However, prevalence rates for meeting the muscle-strengthening exercise guideline (≥2 times/week) are significantly lower (~20%) than those reported to meet the aerobic physical activity guideline (e.g. walking, jogging, cycling) (~50%). It is therefore important to understand public health surveillance approaches to assess muscle-strengthening exercise. The aim of this review was to describe muscle-strengthening exercise assessment in public health surveillance. Informed by the PRISMA guidelines, an extensive keyword search was undertaken across 7 electronic data bases. We identified 86,672 possible articles and following screening (n = 1140 in full-text) against specific inclusion criteria (adults aged ≥18 years, English, studies containing <1000 participants), extracted data from 156 manuscripts. Fifty-eight different survey systems were identified across 17 countries. Muscle-strengthening exercise frequency (85.3%), duration (23.7%) and intensity (1.3%) were recorded. Muscle-strengthening exercise questions varied significantly, with some (11.5%) requiring a singular 'yes' vs 'no' response, while others (7.7%) sought specific details (e.g. muscle groups targeted). Assessments of duration and intensity were inconsistent. Very few studies measured the validity (0.6%) and reliability (1.3%) of muscle-strengthening exercise questions. Discrepancy exists within the current assessment systems/surveys used to assess muscle-strengthening exercise in public health surveillance. This is likely to impede efforts to identify at risk groups and trends within physical activity surveillance, and to accurately assess associations between muscle-strengthening exercise and health-related outcomes.

Inequality in physical activity, global trends by income inequality and gender in adults

Background

Physical inactivity is a global pandemic associated with a high burden of disease and premature mortality. There is also a trend in growing economic inequalities which impacts population health. There is no global analysis of the relationship between income inequality and population levels of physical inactivity.

Methods

Two thousand sixteen World Health Organisation’s country level data about compliance with the 2010 global physical activity guidelines were analysed against country level income interquantile ratio data obtained from the World Bank, OECD and World Income Inequality Database. The analysis was stratified by country income (Low, Middle and High) according to the World Bank classification and gender. Multiple regression was used to quantify the association between physical activity and income inequality. Models were adjusted for GDP and percentage of GDP spent on health care for each country and out of pocket health care spent.

Results

Significantly higher levels of inactivity and a wider gap between the percentage of women and men meeting global physical activity guidelines were found in countries with higher income inequality in high and middle income countries irrespective of a country wealth and spend on health care. For example, in higher income countries, for each point increase in the interquantile ratio data, levels of inactivity in women were 3.73% (CI 0.89 6.57) higher, levels of inactivity in men were 2.04% (CI 0.08 4.15) higher and the gap in inactivity levels between women and men was 1.50% larger (CI 0.16 2.83). Similar relationships were found in middle income countries with lower effect sizes. These relationships were, however, not demonstrated in the low-income countries.

Conclusions

Economic inequalities, particularly in high- and middle- income countries might contribute to physical inactivity and might be an important factor to consider and address in order to combat the global inactivity pandemic and to achieve the World Health Organisation target for inactivity reduction.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12966-020-01039-x.

State-level income inequality and the odds for meeting fruit and vegetable recommendations among US adults

Background

Previous research indicates that income inequality is associated with risk for mortality, self-rated health status, chronic conditions, and health behavior, such as physical activity. However, little is known about the relationship between income inequality and dietary intake, which is a major risk factor for common chronic diseases including heart disease, stroke, diabetes, and certain types of cancers. The objective of this study is to determine the association between US state income inequality and fruit and vegetable consumption among adults.

Methods

Cross-sectional data on 270,612 U.S. adults from the U.S. 2013 Behavioral Risk Factor Surveillance System was used. Fruit and vegetable consumption was assessed from the six-item fruit and vegetable frequency questionnaire, which is part of the Behavioral Risk Factor Surveillance System. Multilevel modeling was used to determine whether US state-level income inequality (measured by the z-transformation of the Gini coefficient) was associated with fruit and vegetable consumption adjusting for individual-level and state-level covariates.

Results

In comparison to men, women were more likely to consume fruits and vegetables ≥5 times daily, fruits ≥2 times daily, vegetables ≥3 times of daily, and less likely to consume fruit juice daily. Among both men and women, a standard deviation increase in Gini coefficient was associated with an increase in consuming fruit juice daily (OR = 1.07, 95% CI = 1.03, 1.11). However, among women, a standard deviation increase in Gini coefficient was associated with a decreased likelihood in meeting daily recommended levels of both fruits and vegetables (OR = 0.93; 0.87–0.99), fruits only (OR = 0.95; 95% CI, 0.92–0.99) and vegetables only (OR = 0.92; 95% CI, 0.89–0.96).

Conclusions

This study is one of the first to show the relationship between income inequality and fruit and vegetable consumption among U.S. adults empirically. Women’s health is more likely to be detrimentally affected when living in a state with higher income inequality.

A "Swiss paradox" in the United States? Level of spatial aggregation changes the association between income inequality and morbidity for older Americans

Although a preponderance of research indicates that increased income inequality negatively impacts population health, several international studies found that a greater income inequality was associated with better population health when measured on a fine geographic level of aggregation. This finding is known as a “Swiss paradox”. To date, no studies have examined variability in the associations between income inequality and health outcomes by spatial aggregation level in the US. Therefore, this study examined associations between income inequality (Gini index, GI) and population health by geographic level using a large, nationally representative dataset of older adults. We geographically linked respondents’ county data from the 2012 Behavioral Risk Factor Surveillance System to 2012 American Community Survey data. Using generalized linear models, we estimated the association between GI decile on the state and county levels and five population health outcomes (diabetes, obesity, smoking, sedentary lifestyle and self-rated health), accounting for confounders and complex sampling. Although state-level GI was not significantly associated with obesity rates (b = − 0.245, 95% CI − 0.497, 0.008), there was a significant, negative association between county-level GI and obesity rates (b = − 0.416, 95% CI − 0.629, − 0.202). State-level GI also associated with an increased diabetes rate (b = 0.304, 95% CI 0.063, 0.546), but the association was not significant for county-level GI and diabetes rate (b = − 0.101, 95% CI − 0.305, 0.104). Associations between both county-level GI and state-level GI and current smoking status were also not significant. These findings show the associations between income inequality and health vary by spatial aggregation level and challenge the preponderance of evidence suggesting that income inequality is consistently associated with worse health. Further research is needed to understand the nuances behind these observed associations to design informed policies and programs designed to reduce socioeconomic health inequities among older adults.

Area-level and individual correlates of active transportation among adults in Germany: A population-based multilevel study

This study aimed at estimating the prevalence in adults of complying with the aerobic physical activity (PA) recommendation through transportation-related walking and cycling. Furthermore, potential determinants of transportation-related PA recommendation compliance were investigated. 10,872 men and 13,144 women aged 18 years or older participated in the cross-sectional 'German Health Update 2014/15 - EHIS' in Germany. Transportation-related walking and cycling were assessed using the European Health Interview Survey-Physical Activity Questionnaire. Three outcome indicators were constructed: walking, cycling, and total active transportation (≥600 metabolic equivalent, MET-min/week). Associations were analyzed using multilevel regression analysis. Forty-two percent of men and 39% of women achieved ≥600 MET-min/week with total active transportation. The corresponding percentages for walking were 27% and 28% and for cycling 17% and 13%, respectively. Higher population density, older age, lower income, higher work-related and leisure-time PA, not being obese, and better self-perceived health were positively associated with transportation-related walking and cycling and total active transportation among both men and women. The promotion of walking and cycling among inactive people has great potential to increase PA in the general adult population and to comply with PA recommendations. Several correlates of active transportation were identified which should be considered when planning public health policies and interventions.

Indicators of Physical Activity Among Children and Youth in 9 Countries With Low to Medium Human Development Indices: A Global Matrix 3.0 Paper

BACKGROUND

This study compares results of physical activity report cards from 9 countries with low to medium human development indices, participating in the Global Matrix 3.0 initiative.

METHODS

Country-specific report cards were informed by relevant data and government policy documents, reporting on 10 core indicators of physical activity for children and youth. Data were synthesized by report card working groups following a harmonized process. Grade assignments for each indicator utilized a standard grading rubric. Indicators were grouped into one of 2 categories: daily behaviors and settings and sources of influence. Descriptive statistics (average grades) were computed after letter grades were converted into interval variables. Spearman's rank correlation coefficients were calculated for all correlation analyses.

RESULTS

Mean grades for daily behaviors were higher (C) than those for settings and sources of influence (D+). Twenty-nine out of the possible 90 grades were assigned an incomplete. There were moderate to strong positive and negative relationships between different global indices and overall physical activity, organized sport and physical activity, active play, family, community and environment, and government.

CONCLUSIONS

Findings demonstrate an urgent need for high-quality data at the country level in order to better characterize the physical activity levels of children and youth in countries with low to medium human development indices.

Geographic Association Between Income Inequality and Obesity Among Adults in New York State

Introduction

In addition to economic factors and geographic area poverty, area income inequality — the extent to which income is distributed in an uneven manner across a population — has been found to influence health outcomes and obesity. We used a spatial-based approach to describe interactions between neighboring areas with the objective of generating new insights into the relationships between county-level income inequality, poverty, and obesity prevalence across New York State (NYS).

Methods

We used data from the 2015 American Community Survey and 2013 obesity estimates from the Centers for Disease Control and Prevention for NYS to examine correlations between county-level economic factors and obesity. Spatial mapping and analysis were conducted with ArcMap. Ordinary least squares modeling with adjusting variables was used to examine associations between county-level obesity percentages and county-level income inequality (Gini index). Univariate spatial analysis was conducted between obesity and Gini index, and globally weighted regression and Hot Spot Analysis were used to view spatial clustering.

Results

Although higher income inequality was associated with lower obesity rates, a higher percentage of poverty was associated with higher obesity rates. A higher percentage of Hispanic population was associated with lower obesity rates. When tested spatially, higher income inequality was associated with a greater decrease in obesity in southern and eastern NYS counties than in the northern and western counties, with some differences by sex present in this association.

Conclusion

Increased income inequality and lower poverty percentage were significantly linked to lower obesity rates across NYS counties for men. Income inequality influence differed by geographic location. These findings indicate that in areas with high income inequality, currently unknown aspects of the environment may benefit low-income residents. Future studies should also include environmental factors possibly linked to obesity.