Cancer Survivors’ Health Behaviors and Outcomes: A Population-Based Study of Sexual and Gender Minorities

BACKGROUND: Most case-control studies compare cancer survivors with general population controls without considering sexual orientation or gender identity. This case-control analysis compared health risk behaviors and health outcomes among sexual and gender minority cancer survivors to those of matched sexual and gender minority participants without cancer (controls). METHODS: Using data from the 2014-2021 Behavioral Risk Factor Surveillance System, a population-based sample of 4507 cancer survivors who self-identified as transgender, gay men, bisexual men, lesbian women, or bisexual women were 1:1 propensity score matched, using age at survey, race and ethnicity, marital status, education, access to health care, and US census region. Within each sexual and gender minority group, behaviors and outcomes were compared between survivors and participants without cancer, and survivors\u27 odds ratios and 95% confidence intervals calculated. RESULTS: Gay male survivors had higher odds of depression, poor mental health, limited usual activities, difficulty concentrating, and fair or poor health. Few differences were observed between bisexual male survivors and participants without cancer. Compared with controls, lesbian female survivors had greater odds of overweight-obese status, depression, poor physical health, and fair or poor health. Bisexual female survivors had the highest rates of current smoking, depression, poor mental health, and difficulty concentrating across all sexual and gender minority groups. Statistically significantly different from transgender controls, transgender survivors had greater odds of heavy alcohol use, physical inactivity, and fair or poor health. CONCLUSIONS: This analysis revealed an urgent need to address the high prevalence of engaging in multiple health risk behaviors and not following guidelines to avoid second cancers, additional adverse outcomes, and cancer recurrences among sexual and gender minority cancer survivors

Ambient air pollution exposure and full-term birth weight in California

<p>Abstract</p> <p>Background</p> <p>Studies have identified relationships between air pollution and birth weight, but have been inconsistent in identifying individual pollutants inversely associated with birth weight or elucidating susceptibility of the fetus by trimester of exposure. We examined effects of prenatal ambient pollution exposure on average birth weight and risk of low birth weight in full-term births.</p> <p>Methods</p> <p>We estimated average ambient air pollutant concentrations throughout pregnancy in the neighborhoods of women who delivered term singleton live births between 1996 and 2006 in California. We adjusted effect estimates of air pollutants on birth weight for infant characteristics, maternal characteristics, neighborhood socioeconomic factors, and year and season of birth.</p> <p>Results</p> <p>3,545,177 singleton births had monitoring for at least one air pollutant within a 10 km radius of the tract or ZIP Code of the mother's residence. In multivariate models, pollutants were associated with decreased birth weight; -5.4 grams (95% confidence interval -6.8 g, -4.1 g) per ppm carbon monoxide, -9.0 g (-9.6 g, -8.4 g) per pphm nitrogen dioxide, -5.7 g (-6.6 g, -4.9 g) per pphm ozone, -7.7 g (-7.9 g, -6.6 g) per 10 <it>μ</it>g/m³particulate matter under 10 μm, -12.8 g (-14.3 g, -11.3 g) per 10 <it>μ</it>g/m³particulate matter under 2.5 μm, and -9.3 g (-10.7 g, -7.9 g) per 10 <it>μ</it>g/m³of coarse particulate matter. With the exception of carbon monoxide, estimates were largely unchanged after controlling for co-pollutants. Effect estimates for the third trimester largely reflect the results seen from full pregnancy exposure estimates; greater variation in results is seen in effect estimates specific to the first and second trimesters.</p> <p>Conclusions</p> <p>This study indicates that maternal exposure to ambient air pollution results in modestly lower infant birth weight. A small decline in birth weight is unlikely to have clinical relevance for individual infants, and there is debate about whether a small shift in the population distribution of birth weight has broader health implications. However, the ubiquity of air pollution exposures, the responsiveness of pollutant levels to regulation, and the fact that the highest pollution levels in California are lower than those regularly experienced in other countries suggest that precautionary efforts to reduce pollutants may be beneficial for infant health from a population perspective.</p

CDKN2A/B T2D GWAS Risk-SNPs Impact Locus Gene Expression and Proliferation in Human Islets

Genome-wide association studies link the CDKN2A/B locus with T2D risk, but mechanisms increasing risk remain unknown. The CDKN2A/B locus encodes cell cycle inhibitors p14, p15, and p16, MTAP, and ANRIL, a lncRNA. The goal of this study was to determine whether CDKN2A/B T2D risk-SNPs impact locus gene expression, insulin secretion, or beta cell proliferation, in human islets. Islets from non-diabetic donors (n=95) were tested for SNP genotype (rs10811661, rs2383208, rs564398, rs10757283), gene expression (p14, p15, p16, MTAP, ANRIL, PCNA, KI67, CCND2), insulin secretion (n=61) and beta cell proliferation (n=47). Intriguingly, locus genes were co-regulated in islets in two physically overlapping cassettes: p14-p16-ANRIL, which increased with age, and MTAP-p15, which did not. Risk-alleles at rs10811661 and rs2383208 were differentially associated with expression of ANRIL, but not p14, p15, p16 or MTAP, in age-dependent fashion, such that younger homozygous-risk donors had higher ANRIL expression, equivalent to older donor levels. We identified several risk-SNP haplotype combinations that may impact locus gene expression, suggesting possible mechanisms by which SNPs impact locus biology. Risk-allele carriers at ANRIL coding SNP rs564398 had reduced beta cell proliferation index. In conclusion, CDKN2A/B locus SNPs may impact T2D risk by modulating islet gene expression and beta cell proliferation

Mapping Climate Change Exposures, Vulnerabilities, and Adaptation to Public Health Risks in the San Francisco Bay and Fresno Regions

This study reviewed first available frameworks for climate change adaptation in the public health arena. The authors propose a conceptual framework with a three‐step procedure to assess climate change vulnerabilities.&nbsp;&nbsp; First, the study team identified and modeled heat stress, environmental, social, and health factors that are closely related to climate change and vulnerability. Second, the team quantified the cumulative impacts of four high‐priority factors at regional level using the cumulative environmental hazard inequality index. Third, the team applied the environmental justice screening tool to map the four high‐priority factors to identify areas with increased vulnerability to the health impacts of climate change. In addition to the heat stress estimated using air monitoring data, the team applied satellite data to create models of the land surface temperature at 30‐meter resolution and provided a measure of small‐scale variations in the urban heat island. Regionally, based on the cumulative environmental hazard inequality index, adaptive capacity had the greatest cumulative inequality in both the San Francisco Bay Area and Fresno regions, and those inequalities were largely contributed by inequalities from tree canopy shading. Social and health vulnerability had the second largest cumulative inequality in both regions. Lack of car ownership was the major impact in creating such inequalities. Air pollution inequality came third, based on the main pollutants in both regions, and this was mainly contributed by inequalities from diesel particulate matter exposure. By contrast, cumulative inequalities in heat stress were the least. However, heat stress inequality was still significant different from the equality line. Locally, based on the environmental justice screening tool, downtown urban areas for both Fresno County and the San Francisco Bay Area showed cumulatively higher vulnerability than more outlying areas, with the exception of the rural western portion of Fresno County. The cumulative inequalities calculated by the cumulative environmental hazard inequality index and the environmental justice screening method can be a useful tool for highlighting areas of greatest vulnerability for targeting adaptation planning

Mapping Climate Change Exposures, Vulnerabilities, and Adaptation to Public Health Risks in the San Francisco Bay and Fresno Regions

This study reviewed first available frameworks for climate change adaptation in the public health arena. The authors propose a conceptual framework with a three‐step procedure to assess climate change vulnerabilities.&nbsp;&nbsp; First, the study team identified and modeled heat stress, environmental, social, and health factors that are closely related to climate change and vulnerability. Second, the team quantified the cumulative impacts of four high‐priority factors at regional level using the cumulative environmental hazard inequality index. Third, the team applied the environmental justice screening tool to map the four high‐priority factors to identify areas with increased vulnerability to the health impacts of climate change. In addition to the heat stress estimated using air monitoring data, the team applied satellite data to create models of the land surface temperature at 30‐meter resolution and provided a measure of small‐scale variations in the urban heat island. Regionally, based on the cumulative environmental hazard inequality index, adaptive capacity had the greatest cumulative inequality in both the San Francisco Bay Area and Fresno regions, and those inequalities were largely contributed by inequalities from tree canopy shading. Social and health vulnerability had the second largest cumulative inequality in both regions. Lack of car ownership was the major impact in creating such inequalities. Air pollution inequality came third, based on the main pollutants in both regions, and this was mainly contributed by inequalities from diesel particulate matter exposure. By contrast, cumulative inequalities in heat stress were the least. However, heat stress inequality was still significant different from the equality line. Locally, based on the environmental justice screening tool, downtown urban areas for both Fresno County and the San Francisco Bay Area showed cumulatively higher vulnerability than more outlying areas, with the exception of the rural western portion of Fresno County. The cumulative inequalities calculated by the cumulative environmental hazard inequality index and the environmental justice screening method can be a useful tool for highlighting areas of greatest vulnerability for targeting adaptation planning