Inequalities in US Life Expectancy by Area Unemployment Level, 1990-2010

This study examined the association between unemployment and life expectancy in the United States during 1990-2010. 

Census-based unemployment rates were linked to US county-level mortality data. Life expectancies were calculated by age, sex, race, and unemployment level during 1990-2010. Differences in life expectancy were decomposed by age and cause of death. 

Life expectancy was consistently lower in areas with higher unemployment rates. In 2006-2010, those in areas with high unemployment rates (≥9%) had a life expectancy of 76.9 years, compared with 80.7 years for those in areas with low unemployment rates (<3%). The association between unemployment and life expectancy was stronger for men than for women. 

Life expectancy ranged from 69.9 years among black men in high unemployment areas to 90.0 years among Asian/Pacific Islander women in low unemployment areas. Disparities persisted over time. In 1990-1992, life expectancy was 4.7 years shorter in high unemployment than in low unemployment areas. In 2006-2010, the life expectancy difference between the lowest and highest unemployment areas decreased to 3.8 years. Heart disease, cancer, homicide, unintentional injuries, diabetes, HIV/AIDS, and liver cirrhosis contributed most to the lower life expectancy in high unemployment areas. High unemployment areas recorded larger gains in life expectancy than low unemployment areas, contributing to the narrowing gap during 1990-2010.

Below:  Life expectancy at birth by sex and area unemployment level, United States, 1990–2010

Below:  Survivorship by age, race, and unemployment level, United States, 1990–2010

Below:  Conditional probability of survival between ages of 25 and 64 years by unemployment level, United States, 1990–2010

Full article at:   http://goo.gl/FI27Gt

By:  Singh GK1, Siahpush M2.

• 1US Department of Health and Human Services, 5600 Fishers Lane, Rockville, MD 20857, USA.
• 2Department of Health Promotion, Social and Behavioral Health, University of Nebraska Medical Center, College of Public Health, Omaha, NE 68198-4365, USA.
• Scientifica (Cairo). 2016;2016:8290435. doi: 10.1155/2016/8290435. Epub 2016 Mar 17. 

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The Geography of Gender Inequality

Reducing gender inequality is a major policy concern worldwide, and one of the Sustainable Development Goals. However, our understanding of the magnitude and spatial distribution of gender inequality results either from limited-scale case studies or from national-level statistics. 

Here, we produce the first high resolution map of gender inequality by analyzing over 689,000 households in 47 countries. Across these countries, we find that male-headed households have, on average, 13% more asset wealth and 303% more land for agriculture than do female-headed households. However, this aggregate global result masks a high degree of spatial heterogeneity, with bands of both high inequality and high equality apparent in countries and regions of the world. Further, areas where inequality is highest when measured by land ownership generally are not the same areas that have high inequality as measured by asset wealth. 

Our metrics of gender inequality in land and wealth are not strongly correlated with existing metrics of poverty, development, and income inequality, and therefore provide new information to increase the understanding of one critical dimension of poverty across the globe.

Below:  Wealth inequality between male- and female-headed households

Below:  Land inequality between male- and female-headed households

Full article at:   http://goo.gl/Kp7cm3

By:  

Brendan Fisher 
Gund Institute, Rubenstein School of Environment and Natural Resources, Aiken Center, University of Vermont, Burlington, Vermont, United States of America

Brendan Fisher, Robin Naidoo 

World Wildlife Fund, Washington, DC, United States of America

Robin Naidoo 

Institute for Resources, Environment and Sustainability, University of British Columbia, Vancouver, British Columbia, Canada

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Vulnerability of Wives of Nepalese Labor Migrants to HIV Infection: A Socio-Epidemiological Study

The vulnerability paradigm accounts for women's susceptibility to HIV infection being a consequence of socio-economic and cultural factors, and there is a strong need for socio-epidemiological analysis to understand and address vulnerability of Nepalese women to HIV infection. Therefore, to assess the risk factors and vulnerability of the wives of Nepalese labor migrants to HIV infection, we conducted a mixed-methods study in which a descriptive case study was embedded within a case-control study. 

A total of 224 wives of labor migrants were interviewed in the case-control study and two focus group discussions were conducted in the descriptive case study. Data was analyzed using hierarchical conditional logistic regression analysis in the case-control study and thematic analysis in the descriptive case study. We found that illiteracy, low socio-economic status and gender inequality contributed to poor knowledge and poor sexual negotiation among the wives of labor migrants and increased their risk of HIV through unprotected sex. 

Among male labor migrants, illiteracy, low socio-economic status, migration to India before marriage and alcohol consumption contributed to visit female sex workers and increased the risk of HIV in their wives through unprotected sex. Both labor migrants and their wives feared disclosure of positive HIV status due to HIV stigma and thus were less likely to be tested for HIV. 

Interventions targeting the general population, such as access to basic education, income generation and mass awareness, and interventions targeting specific subpopulations, such as gender-related training and involving men in HIV-related programs, should be combined to reduce vulnerability of Nepalese women to HIV infection.

Via:  http://goo.gl/1tOAMg  

By: Subash Thapa,1 Nirmala Bista,2 Karin Hannes,3 Anne Buve,4 Mieke Vermandere,5 and Catharina Mathei5

²Department of Public Health, Nobel College Pokhara University, Kathmandu, Nepal

³Faculty of Psychology and Educational Sciences, KU Leuven, Leuven, Belgium

⁴Department of Public Health, Institute of Tropical Medicine, Antwerp, Belgium

⁵

1KU Leuven, Leuven, Belgium

2Department of Public Health, Nobel College Pokhara University, Kathmandu, Nepal

3Faculty of Psychology and Educational Sciences, KU Leuven, Leuven, Belgium

4Department of Public Health, Institute of Tropical Medicine, Antwerp, Belgium

5Department of Public Health and Primary care, KU Leuven, Leuven, Belgium 

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A First Look at Gender Inequality as a Societal Risk Factor for Dating Violence

One of ten U.S. high school students is a victim of adolescent dating violence (ADV). Understanding ADV risk factors guides prevention efforts; however, research examining community- and societal-level risk factors is scant. Societal gender inequality is a known risk factor for violence against women, but has yet to be explored in relation to ADV. This study aims to determine whether the Gender Inequality Index (GII) correlates with levels of physical and sexual ADV victimization across U.S. states.

State-representative prevalence rates of self-reported physical and sexual ADV victimization were obtained from the 2013 Youth Risk Behavior Survey. The state GII includes five indicators: (1) maternal mortality; (2) adolescent birth rate; (3) government representation; (4) educational attainment; and (5) labor force participation. Pearson correlation coefficients determined the association between physical and sexual ADV victimization, the GII, and GII indicators. Analyses were conducted in August 2014.

Among U.S. states, the prevalence of physical ADV victimization in 2013 ranged from 7.0% to 14.8%, and the prevalence of sexual ADV victimization ranged from 7.8% to 13.8%. The GII was significantly associated with the state prevalence of female physical ADV victimization but not female sexual ADV victimization. Neither physical nor sexual male ADV victimization was associated with the GII.

This exploratory study suggests that gender inequality may be a societal-level risk factor for female physical ADV victimization. As ADV prevention strategies are implemented at the state level, further research examining the effect of gender inequality on ADV is needed.

Via: http://ht.ly/S9Z1j 

By: Gressard LA1, Swahn MH2, Tharp AT3.

• 1Department of Epidemiology and Biostatistics, School of Public Health, Georgia State University, Atlanta, Georgia. Electronic address: lagressard@gmail.com.
• 2Department of Epidemiology and Biostatistics, School of Public Health, Georgia State University, Atlanta, Georgia.
• 3Division of Violence Prevention, CDC, Atlanta, Georgia.