We now live in a new geological age, the Anthropocene – the age of humans – the start of which coincides with the founding of the International Union for Health Promotion and Education (IUHPE) 70 years ago. In this article, we address the fundamental challenge facing health promotion in its next 70 years, which takes us almost to 2100: how do we achieve planetary health? We begin with a brief overview of the massive and rapid global ecological changes we face, the social, economic and technological driving forces behind those changes, and their health implications. At the heart of these driving forces lie a set of core values that are incompatible with planetary health. Central to our argument is the need for a new set of values, which heed and privilege the wisdom of Indigenous worldviews, as well as a renewed sense of spirituality that can re-establish a reverence for nature. We propose an Indigenous-informed framing to inspire and inform what we call planetary health promotion so that, as the United Nations Secretary General wrote recently, we can make peace with nature.
To determine whether a gout polygenic risk score (PRS) is associated with age at gout onset and tophaceous disease in European, East Polynesian, and West Polynesian men and women with gout.Methods. A 19-variant gout PRS was produced in 7 European gout cohorts (N = 4,016), 2 East Polynesian gout cohorts (N = 682), and 1 West Polynesian gout cohort (N = 490). Sex-stratified regression models were used to estimate the relationship between the PRS and age at gout onset and tophaceous disease.Results. The PRS was associated with earlier age at gout onset in men (β = -3.61 in years per unit PRS [95% confidence interval (95% CI) -4.32, -2.90] in European men; β = -6.35 [95% in East Polynesian men; β = -3.51 [95% CI -5.46, -1.57] in West Polynesian men) but not in women (β = 0.07 [95% CI -2.32, 2.45] in European women; β = 0.20 [95% CI -7.21, 7.62] in East Polynesian women; β = -3.33 [95% CI -9.28, 2.62] in West Polynesian women). The PRS showed a positive association with tophaceous disease in men (odds ratio [OR] for the association 1.15 [95% CI 1.00, 1.31] in European men; OR 2.60 [95% CI 1.66, 4.06] in East Polynesian men; OR 1.53 [95% CI 1.07, 2.19] in West Polynesian men) but not in women (OR for the association 0.68 [95% CI 0.42, 1.10] in European women; OR 1.45 [95% CI 0.39, 5.36] in East Polynesian women). The PRS association with age at gout onset was robust to the removal of ABCG2 variants from the PRS in European and East Polynesian men (β = -2.42 [95% ] and β = -6.80 [95% CI -10.06, -3.55], respectively) but not in West Polynesian men (β = -1.79 [95% 1.16]).Conclusion. Genetic risk variants for gout also harbor risk for earlier age at gout onset and tophaceous disease in European and Polynesian men. Our findings suggest that earlier gout onset involves the accumulation of gout risk alleles in men but perhaps not in women, and that this genetic risk is shared across multiple ancestral groups.
The minor allele of rs373863828, a missense variant in CREB3 Regulatory Factor, is associated with several cardiometabolic phenotypes in Polynesian peoples. To better understand the variant, we tested the association of rs373863828 with a panel of correlated phenotypes (body mass index [BMI], weight, height, HDL cholesterol, triglycerides, and total cholesterol) using multivariate Bayesian association and network analyses in a Samoa cohort (n = 1632), Aotearoa New Zealand cohort (n = 1419), and combined cohort (n = 2976). An expanded set of phenotypes (adding estimated fat and fat‐free mass, abdominal circumference, hip circumference, and abdominal‐hip ratio) was tested in the Samoa cohort (n = 1496). In the Samoa cohort, we observed significant associations (log10 Bayes Factor [BF] ≥ 5.0) between rs373863828 and the overall phenotype panel (8.81), weight (8.30), and BMI (6.42). In the Aotearoa New Zealand cohort, we observed suggestive associations (1.5 < log10BF < 5) between rs373863828 and the overall phenotype panel (4.60), weight (3.27), and BMI (1.80). In the combined cohort, we observed concordant signals with larger log10BFs. In the Samoa‐specific expanded phenotype analyses, we also observed significant associations between rs373863828 and fat mass (5.65), abdominal circumference (5.34), and hip circumference (5.09). Bayesian networks provided evidence for a direct association of rs373863828 with weight and indirect associations with height and BMI.
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