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Mitchell E, Bennett LR. Infertility in the Pacific: A crucial component of the sexual and reproductive health and rights agenda. Aust N Z J Obstet Gynaecol 2024; 64:297-299. [PMID: 38263768 DOI: 10.1111/ajo.13791] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Accepted: 01/06/2024] [Indexed: 01/25/2024]
Abstract
Across Pacific Island countries, women and men are disproportionately affected by several risk factors for infertility, including sexually transmissible infections, complications from unsafe abortions, postpartum sepsis, obesity, diabetes, tobacco smoking and excessive alcohol consumption. Despite this, little is known about community awareness of infertility, behavioural risk factors, the lived experiences of infertile couples or the contexts in which they access fertility care. In this opinion piece we discuss the current evidence and gaps in evidence regarding infertility in Pacific Island countries and the importance of locally tailored approaches to preventing infertility and the provision of fertility care.
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Affiliation(s)
- Elke Mitchell
- Kirby Institute, UNSW Sydney, Sydney, New South Wales, Australia
- Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Linda Rae Bennett
- Nossal Institute for Global Health, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Victoria, Australia
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Cai J, Hu W, Yang Y, Chen S, Si A, Zhang Y, Jing H, Gong L, Liu S, Mi B, Ma J, Yan H, Chen F. Healthy life expectancy for 202 countries up to 2030: Projections with a Bayesian model ensemble. J Glob Health 2023; 13:04185. [PMID: 38146817 PMCID: PMC10750449 DOI: 10.7189/jogh.13.04185] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2023] Open
Abstract
Background Healthy life expectancy (HLE) projections are required for optimising social and health service management in the future. Existing studies on the topic were usually conducted by selecting a single model for analysis. We thus aimed to use an ensembled model to project the future HLE for 202 countries/region. Methods We obtained data on age-sex-specific HLE and the sociodemographic index (SDI) level of 202 countries from 1990 to 2019 from the Global Burden of Disease (GBD) database and used a probabilistic Bayesian model comprised of 21 forecasting models to predict their HLE in 2030. Results In general, HLE is projected to increase in all 202 countries, with the least probability of 82.4% for women and 81.0% for men. Most of the countries with the lowest projected HLE would be located in Africa. Women in Singapore have the highest projected HLE in 2030, with a 94.5% probability of higher than 75.2 years, which is the highest HLE in 2019 across countries. Maldives, Kuwait, and China are projected to have a probability of 49.3%, 41.2% and 31.6% to be the new entries of the top ten countries with the highest HLE for females compared with 2019. Men in Singapore are projected to have the highest HLE at birth in 2030, with a 93.4% probability of higher than 75.2 years. Peru and Maldives have a probability of 48.7% and 35.3% being new top ten countries in male's HLE. The female advantage in HLE will shrink by 2030 in 117 countries, especially in most of the high SDI and European countries. Conclusions HLE will likely continue to increase in most countries and regions worldwide in the future. More attention needs to be paid to combatting obesity, chronic diseases, and specific infectious diseases, especially in African and some Pacific Island countries. Although gender gaps may not be fully bridged, HLE could partially mitigate and even eliminate them through economic development and improvements in health care.
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Affiliation(s)
- Jiaxin Cai
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Weiwei Hu
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Yuhui Yang
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Shiyu Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Aima Si
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Yuxiang Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Hui Jing
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Lingmin Gong
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Sitong Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Baibing Mi
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University, Xi’an, Shaanxi, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Jiaojiao Ma
- Department of Neurology, Xi’an Gaoxin Hospital, Xi’an, Shaanxi, China
| | - Hong Yan
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University, Xi’an, Shaanxi, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Fangyao Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University, Xi’an, Shaanxi, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi’an Jiaotong University, Xi’an, Shaanxi, China
- Department of Radiology, First Affiliate Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China
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Boxer B, Trübswasser U, Lesi V, Naika A, Dahal P, Sagan S, Joshi K, Irache A, Singh P, Nand D, Kama A, Deo A, Goudet S. Rapid review of factors influencing dietary behaviors in Fiji. Front Nutr 2023; 10:1164855. [PMID: 37621737 PMCID: PMC10445140 DOI: 10.3389/fnut.2023.1164855] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Accepted: 07/20/2023] [Indexed: 08/26/2023] Open
Abstract
Introduction In Fiji, multiple burdens of malnutrition including undernutrition, overweight/obesity, and micronutrient deficiencies coexist at the individual, household, and population levels. The diets of children, adolescents, and adults are generally unhealthy. The objective of this review was to understand how the dietary behaviors of children, adolescents, and women in Fiji are influenced by individual, social, and food environment factors. Methods This rapid review was conducted to synthesize existing evidence, identify research gaps in the evidence base, and make recommendations for future research. The Cochrane Rapid Reviews Methods and the updated guideline for reporting systematic reviews were used. The search strategy for this rapid review was based on the Population Context Outcome [P(E)CO] framework, including search terms for population (children, adolescents, and adults), context (Fiji), and outcome (dietary behaviors). Searches were conducted in PubMed, Scopus, PsycINFO, and Google Scholar. Results The 22 studies included in this review identified different factors influencing dietary behaviors in Fiji. Individual preferences for processed and imported foods, especially of younger generations, and social dynamics, especially gender norms and social pressure, to serve meat and overeat appeared to be prominent in driving dietary habits. The ongoing nutrition transition has led to increasing availability and affordability of ultra-processed and fast foods, especially in urban areas. Concerns about food safety and contamination and climate change and its effect on local food production also appear to influence dietary choices. Discussion This review identified different dynamics influencing dietary behaviors, but also research gaps especially with regard to the food environment, calling for an integrated approach to address these factors more systemically.
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Affiliation(s)
| | | | - Viola Lesi
- Nutrition Research, Dikoda, London, United Kingdom
| | - Asaeli Naika
- Nutrition Research, Dikoda, London, United Kingdom
| | | | | | | | - Ana Irache
- Nutrition Research, Dikoda, London, United Kingdom
| | - Pragya Singh
- School of Public Health and Primary Care, College of Medicine, Nursing and Health Sciences, Fiji National University, Suva, Fiji
| | - Devina Nand
- Ministry of Health and Medical Services, Suva, Fiji
| | - Ateca Kama
- Ministry of Health and Medical Services, Suva, Fiji
| | - Alvina Deo
- National Food and Nutrition Centre, Suva, Fiji
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