Measuring the social impact of population trends and development : report of an expert group meeting

The meeting brought together experts from ESCAP member and associat member countries to exchange views and experiences in the area of social indicators. The conclusion reached by this group was that social indicators would be most useful for planning purposes if better techniques of analysis are developed which will alow an improved examination of the determinants of interaction among various social phenomena. The report summarizes the discussions at the meeting; the paper "Social indicators: definition, purposes and development" is included as an annex

Mapping and Classifying Settlement Locations

“Mapping and Classifying Settlement Locations” discusses GRID3’s work on collecting and analyzing settlements data. GRID3’s settlements work has two areas of focus: creating a comprehensive settlement layer that enables a real-world picture of communities, and using building footprints, geospatial data layers, and machine learning algorithms to classify structures and local areas within settlements. The paper also discusses the applications of GRID3’s methods in Nigeria, the Democratic Republic of the Congo, and Zambia. GRID3 works with countries to generate, validate and use geospatial data on population, settlements, infrastructure, and subnational boundaries. For more information, see https://grid3.org/. Keywords: area-level classification; building footprints; comprehensive settlement layer; extent; intra-settlement categorisation; machine learning; polygon layer; point layer; settlement; settlement data; settlement layer; settlement mapping; settlement point; ; GRID3; database schema; geospatial data; neighbourhood classification; open-source; health zones; participatory cartography; GIS; vaccination; immunisation; census; micro-plans; CIESIN; UNFPA; Flowminder; WorldPop; probability model; areal; built-up areas; small settlements; hamlets; hamlet areas; polio; Afric

Cartographie et classification des localités

Ce document présente le travail de GRID3 sur le recueil et l'analyse des données de localité. Les activités de GRID3 sur les localités se s’articule autour de deux axes principaux : la création d'une couche des localités exhaustive qui permet d'obtenir une image réelle des communautés, et l'utilisation d'empreintes de bâtiments, de couches de données géospatiales et d'algorithmes d'apprentissage automatique pour classer les structures et les zones locales au sein des localités. Ce document aborde également les applications des méthodes de GRID3 au Nigeria, en République démocratique du Congo et en Zambie. GRID3 accompagne les pays dans la création, la validation et l'utilisation des données géospatiales de population, localités, infrastructures et de limites infranationales. Pour plus d'informations, voir https://grid3.org/. Keywords (Mots clés) : classification au niveau de la zone ; empreintes de bâtiments ; couche de localités complète ; étendue ; catégorisation intra localité ; apprentissage automatique ; couche de polygones ; couche de points ; localités ; données de localités ; couche de localités ; cartographie de localités ; point de localités ; GRID3 ; schéma de base de données ; données géospatiales ; classification des quartiers ; source ouverte ; zones de santé ; cartographie participative ; SIG ; vaccination ; immunisation ; recensement ; micro-plans ; CIESIN ; UNFPA ; Flowminder ; WorldPop ; modèle de probabilité ; aréal ; zones bâties ; petites agglomérations ; hameaux ; zones de hameaux ; polio ; Afriqu

Harmonising Subnational Boundaries

“Harmonising Subnational Boundaries” discusses GRID3’s work to support the harmonisation, production, and use of digitised legal/administrative units, operational units, and statistical areas. GRID3’s boundaries work has three primary areas of focus: improving and harmonising operational units; fostering improved collaboration on boundary harmonisation among disparate government bodies; and using boundaries harmonisation to support census efforts. The paper focuses on case studies in Nigeria, the Democratic Republic of the Congo, and Zambia. GRID3 works with countries to generate, validate and use geospatial data on population, settlements, infrastructure, and subnational boundaries. For more information, see https://grid3.org/. Keywords: administrative units; census; community health workers; digital boundaries; emergency operations; enumeration area; GIS; gridded population data; harmonisation; health catchment; microplan; operational units; points of interest; pre-enumeration area; routine operations; semi-automated delineation; settlement; settlement layer; settlement mapping; statistical areas; statistical infrastructure; subnational boundaries; sustainable development; GRID3; health zones; participatory mapping; vaccination; immunisation; CIESIN; UNFPA; Flowminder; WorldPop; poli

Harmoniser les limites infranationales

“Harmoniser les limites infranationales” aborde le travail de GRID3 de soutien à l'harmonisation, la production et l'utilisation d'unités légales/administratives, d'unités opérationnelles et de zones statistiques numérisées. Le travail de GRID3 sur les frontières s'articule autour de trois axes principaux: l'amélioration et l'harmonisation des unités opérationnelles, la promotion d'une meilleure collaboration sur l'harmonisation des limites entre des organismes gouvernementaux disparates et l'utilisation de l'harmonisation des limites pour soutenir les efforts de recensement. Le document se penche sur des études réalisées au Nigeria, en République démocratique du Congo et en Zambie. GRID3 accompagne les pays dans la création, la validation et l'utilisation des données géospatiales de population, localités, infrastructures et de limites infranationales. Pour plus d'informations, voir https://grid3.org/. Keywords (Mots clés) : unités administratives ; recensement ; agents de santé communautaires ; limites numériques ; opérations d'urgence ; zone de dénombrement ; SIG ; données de population carroyées ; harmonisation ; bassin de santé ; microplan ; unités opérationnelles ; points d'intérêt ; zone de pré-dénombrement ; opérations de routine ; délimitation semi-automatique ; établissement ; couche d'établissement ; cartographie de l'établissement ; zones statistiques ; infrastructure statistique ; limites infranationales ; développement durable ; GRID3 ; zones de santé ; cartographie participative ; vaccination ; immunisation ; CIESIN ; UNFPA ; Flowminder ; WorldPop ; polio

Mapping Health Facilities

“Mapping Health Facilities” discusses GRID3’s work with local stakeholders and data collectors to build capacity for the production and management of geospatial data on health facilities. This paper first discusses GRID3's approach to mapping health facility data. In the next section, it discusses GRID3's support of routine and non-routine immunisation campaigns in Nigeria and the consolidation of existing health facilities data and collection of new data in the Democratic Republic of the Congo. Following that, new GRID3 initiatives are discussed, including data consolidation and collection in Zambia and work around health facilities data in Sierra Leone. For more information, see https://grid3.org/ Keywords: COVID-19; health facilities; community health workers; GIS; GTS; health catchment; microplan; microplanning; points of interest; sustainable development; Democratic Republic of the Congo; Nigeria; Sierra Leone; Zambia; GRID3; health zones; vaccination; immunisation; CIESIN; UNFPA; Flowminder; WorldPop; polio; Africa; Bill & Melinda Gates Foundation; District Health Information Software 2; Directorate of Planning, Policy, and Information; Division of the National Health Information System; Expanded Program on Immunization; Geographic Information System; Geospatial Tracking System; Local Government Area; Mapping For Health; Maternal and Child Survival Program; National Primary Health Care Development Agency; National Spatial Data Infrastructure; Open Data Kit; Public Health Services and Solutions; Quality analysis and quality control; routine immunisation; non-routine immunisation; Service Availability and Readiness Assessment; United States Agency for International Development; Vaccination Tracking System; Wild Polio Virus; Zambia Statistics Agenc

Pubertal development and prostate cancer risk: Mendelian randomization study in a population-based cohort.

BACKGROUND: Epidemiological studies have observed a positive association between an earlier age at sexual development and prostate cancer, but markers of sexual maturation in boys are imprecise and observational estimates are likely to suffer from a degree of uncontrolled confounding. To obtain causal estimates, we examined the role of pubertal development in prostate cancer using genetic polymorphisms associated with Tanner stage in adolescent boys in a Mendelian randomization (MR) approach. METHODS: We derived a weighted genetic risk score for pubertal development, combining 13 SNPs associated with male Tanner stage. A higher score indicated a later puberty onset. We examined the association of this score with prostate cancer risk, stage and grade in the UK-based ProtecT case-control study (n = 2,927), and used the PRACTICAL consortium (n = 43,737) as a replication sample. RESULTS: In ProtecT, the puberty genetic score was inversely associated with prostate cancer grade (odds ratio (OR) of high- vs. low-grade cancer, per tertile of the score: 0.76; 95 % CI, 0.64-0.89). In an instrumental variable estimation of the causal OR, later physical development in adolescence (equivalent to a difference of one Tanner stage between pubertal boys of the same age) was associated with a 77 % (95 % CI, 43-91 %) reduced odds of high Gleason prostate cancer. In PRACTICAL, the puberty genetic score was associated with prostate cancer stage (OR of advanced vs. localized cancer, per tertile: 0.95; 95 % CI, 0.91-1.00) and prostate cancer-specific mortality (hazard ratio amongst cases, per tertile: 0.94; 95 % CI, 0.90-0.98), but not with disease grade. CONCLUSIONS: Older age at sexual maturation is causally linked to a reduced risk of later prostate cancer, especially aggressive disease.This work was supported by the World Cancer Research Fund (2011/419) and Cancer Research UK (C18281/A19169). The Integrative Epidemiology Unit (IEU) is supported by the MRC and the University of Bristol (G0600705, MC_UU_12013/19), and the Integrative Cancer Epidemiology Programme is supported by Cancer Research UK programme grant C18281/A19169. The National Institute for Health Research (NIHR) Bristol Nutrition Biomedical Research Unit is funded by the NIHR and is a partnership between University Hospitals Bristol NHS Foundation Trust and the University of Bristol. The ProtecT study is supported by the UK NIHR Health Technology Assessment (HTA) Programme (HTA 96/20/99; ISRCTN20141297). Funding for PRACTICAL and the iCOGS infrastructure came from: the European Community’s Seventh Framework Programme under grant agreement n° 223175 (HEALTH-F2-2009-223175) (COGS), Cancer Research UK (C1287/A10118, C1287/A 10710, C12292/A11174, C1281/A12014, C5047/A8384, C5047/A15007, C5047/A10692, C8197/ A16565), the National Institutes of Health (CA128978), and Post-Cancer GWAS initiative (1U19 CA148537, 1U19 CA148065 and 1U19 CA148112 – the GAME-ON initiative), the Department of Defence (W81XWH-10-1-0341), the Canadian Institutes of Health Research (CIHR) for the CIHR Team in Familial Risks of Breast Cancer, Komen Foundation for the Cure, the Breast Cancer Research Foundation, and the Ovarian Cancer Research Fund. We acknowledge support from the NIHR to the Biomedical Research Centre at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust.This is the final version of the article. It first appeared from BioMed Central via http://dx.doi.org/10.1186/s12916-016-0602-

Differentials of fertility in North and South Gondar zones, northwest Ethiopia: A comparative cross-sectional study

<p>Abstract</p> <p>Background</p> <p>Ethiopia is one of the most densely populated countries in Africa with an estimated population of 77.1 million in mid-2007. Uncontrolled fertility has adversely influenced the socio-economic, demographic and environmental situations of the country. It is one of the largest and poorest countries that, even in the midst of crisis, has maintained high levels of fertility. This study was aimed at investigating the most important factors influencing fertility behavior in Northwest Ethiopia.</p> <p>Methods</p> <p>A comparative cross-sectional study which included 2424 women aged 25 years and above was undertaken in the Amhara region of Northwest Ethiopia. The study subjects were grouped into high fertile and low fertile categories. There were 1011 and 1413 women in the high and low fertile groups, respectively. A multi-stage cluster sampling stratified by place of residence was employed to select the required study subjects. Both bivariate and multivariate logistic regression techniques were used to analyze the data.</p> <p>Results</p> <p>Among the 25 variables considered in this study, only 9 of them were found significantly and independently associated with the level of fertility. Women with at least secondary education were at a lower risk of high fertility with OR = 0.37 (95% CI: 0.21 to 0.64) compared to those with no formal education. However, women with primary education did not show any significant difference when compared with the same baseline group. Age at first marriage was inversely associated with the number of children ever born alive. Place of residence, household expenditure, number of children who have died, attitude towards using contraceptives, women's knowledge on the safe period, and current marital status were the other variables that showed significant associations with the level of fertility.</p> <p>Conclusion</p> <p>Female education beyond the primary level, reduced infant and child mortality, delayed marriage and correct knowledge on the safe period during the menstrual cycle were amongst the main factors that had a bearing on high fertility.</p