Changes in life expectancy and disease burden in Norway, 1990–2019: an analysis of the Global Burden of Disease Study 2019

Bill & Melinda Gates FoundationpublishedVersio

Socioeconomic inequalities in children's weight, height and BMI trajectories in Norway

Abstract Studies exploring when social inequalities in body mass index (BMI) and its composites emerge and how these evolve with age are limited. Thus, this study explored parental income and education related inequalities in children’s weight, height, weight velocity and body mass index among Norwegian children from 1 month to 8 years. The study population included 59,927 family/children pairs participating in the Norwegian Mother, Father, and Child Cohort Study. Growth was modelled using the Jenss–Bayley model and linear mixed effects analyses were conducted. Maternal and paternal educational differences in children’s weight and BMI trajectories emerged during infancy, continuing to age 8 years. Parental income-related inequalities in children’s weight were observed from the age of 1 month to 4 years for maternal and up to 1 year for paternal income-related differences but then disappeared. Parental income-related inequalities in child’s BMI were observed from 18 months to 8 years for maternal income, and from 9 months to 8 years for paternal income-related differences. These results suggest that social inequalities in children’s BMI present early in infancy and continue to 8 years of age. The inequalities sometimes differed by indicator of socioeconomic position used. Interventions to combat these inequalities early in life are, thus needed

Mediators of differences by parental education in weight-related outcomes in childhood and adolescence in Norway

Abstract Studies exploring mediators of socioeconomic inequalities in excess weight gain in early-life and subsequent overweight/obesity (OW/OB) among youth are limited. Thus, this study examined the mediating role of prenatal and early postnatal factors and child energy balance-related behaviours (EBRB) in the effects of parental education on (i) excess weight gain from birth to 2 years and (ii) OW/OB at 5, 8 and 14 years. The Norwegian Mother, Father and Child Cohort Study was used to include participants at the ages of 2 (n = 59,597), 5 (n = 27,134), 8 (n = 28,285) and 14 (n = 11,278) years. Causal mediation analyses using the inverse odds weighting approach were conducted. Children of low-educated parents had a higher conditional excess weight gain at 2 years compared to children of high-educated parents (total effect, RR TE  = 1.06; 95% CI 1.01, 1.10). The joint mediation effects of the prenatal and early postnatal factors explained most of the total effect of low education on conditional excess weight gain at 2 years. Children of low-educated parents had a higher risk of OW/OB at 5, 8 and 14 years compared to children of high-educated parents. The mediators jointly explained 63.7%, 67% and 88.9% of the total effect of parental education on OW/OB among 5, 8 and 14 year-old-children, respectively. Of the total mediated effects at 5, 8 and 14 years, the prenatal and early postnatal mediators explained 59.2%, 61.7% and 73.7%, whereas the child EBRB explained 10.3%, 15.8.0%% and 34.8%. The mediators included were found to have a considerable mediating effect in the associations explored, in particular the prenatal and early postnatal factors. If truly causal, the findings could indicate potential targets for interventions to tackle socioeconomic inequalities in OW/OB from birth to adolescence

Mediators of socioeconomic inequalities in dietary behaviours among youth: A systematic review

Children and adolescents with a lower socioeconomic position have poorer dietary behaviours compared to their counterparts with a higher socioeconomic position. A better understanding of the mechanisms behind such socioeconomic inequalities is vital to identify targets for interventions aimed at tackling these inequalities. This systematic review aimed to summarize existing evidence regarding the mediators of socioeconomic differences in dietary behaviours among youth. A systematic literature search of MEDLINE, Embase, PsycINFO, and Web of Science databases yielded 20 eligible studies. The dietary behaviours included in the reviewed studies were the intake of fruit and vegetables, sugar‐sweetened beverages, unhealthy snacks/fast food and breakfast. The consistent mediators of the effects of socioeconomic position on dietary behaviours among youth were: self‐efficacy, food preferences and knowledge at the intrapersonal level; and availability and accessibility of food items at home, food rules and parental modelling at the interpersonal level. Few studies including mediators at the organisational, community or policy levels were found. Our review found several modifiable factors at the intrapersonal and interpersonal levels that could be targeted in interventions aimed at combating inequalities in dietary behaviours among youth. Rigorous studies exploring organisational, community and policy level mediators are warranted

Changes in life expectancy and disease burden in Norway, 1990–2019: an analysis of the Global Burden of Disease Study 2019

Background Geographical differences in health outcomes are reported in many countries. Norway has led an active policy aiming for regional balance since the 1970s. Using data from the Global Burden of Disease Study (GBD) 2019, we examined regional differences in development and current state of health across Norwegian counties. Methods Data for life expectancy, healthy life expectancy (HALE), years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) in Norway and its 11 counties from 1990 to 2019 were extracted from GBD 2019. County-specific contributors to changes in life expectancy were compared. Inequality in disease burden was examined by use of the Gini coefficient. Findings Life expectancy and HALE improved in all Norwegian counties from 1990 to 2019. Improvements in life expectancy and HALE were greatest in the two counties with the lowest values in 1990: Oslo, in which life expectancy and HALE increased from 71·9 years (95% uncertainty interval 71·4–72·4) and 63·0 years (60·5–65·4) in 1990 to 81·3 years (80·0–82·7) and 70·6 years (67·4–73·6) in 2019, respectively; and Troms og Finnmark, in which life expectancy and HALE increased from 71·9 years (71·5–72·4) and 63·5 years (60·9–65·6) in 1990 to 80·3 years (79·4–81·2) and 70·0 years (66·8–72·2) in 2019, respectively. Increased life expectancy was mainly due to reductions in cardiovascular disease, neoplasms, and respiratory infections. No significant differences between the national YLD or DALY rates and the corresponding age-standardised rates were reported in any of the counties in 2019; however, Troms og Finnmark had a higher age-standardised YLL rate than the national rate (8394 per 100 000 [95% UI 7801–8944] vs 7536 per 100 000 [7391–7691]). Low inequality between counties was shown for life expectancy, HALE, all level-1 causes of DALYs, and exposure to level-1 risk factors. Interpretation Over the past 30 years, Norway has reduced inequality in disease burden between counties. However, inequalities still exist at a within-county level and along other sociodemographic gradients. Because of insufficient Norwegian primary data, there remains substantial uncertainty associated with regional estimates for non-fatal disease burden and exposure to risk factors

Changes in life expectancy and disease burden in Norway, 1990–2019: an analysis of the Global Burden of Disease Study 2019

Background: Geographical differences in health outcomes are reported in many countries. Norway has led an active policy aiming for regional balance since the 1970s. Using data from the Global Burden of Disease Study (GBD) 2019, we examined regional differences in development and current state of health across Norwegian counties. Methods: Data for life expectancy, healthy life expectancy (HALE), years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) in Norway and its 11 counties from 1990 to 2019 were extracted from GBD 2019. County-specific contributors to changes in life expectancy were compared. Inequality in disease burden was examined by use of the Gini coefficient. Findings: Life expectancy and HALE improved in all Norwegian counties from 1990 to 2019. Improvements in life expectancy and HALE were greatest in the two counties with the lowest values in 1990: Oslo, in which life expectancy and HALE increased from 71·9 years (95% uncertainty interval 71·4–72·4) and 63·0 years (60·5–65·4) in 1990 to 81·3 years (80·0–82·7) and 70·6 years (67·4–73·6) in 2019, respectively; and Troms og Finnmark, in which life expectancy and HALE increased from 71·9 years (71·5–72·4) and 63·5 years (60·9–65·6) in 1990 to 80·3 years (79·4–81·2) and 70·0 years (66·8–72·2) in 2019, respectively. Increased life expectancy was mainly due to reductions in cardiovascular disease, neoplasms, and respiratory infections. No significant differences between the national YLD or DALY rates and the corresponding age-standardised rates were reported in any of the counties in 2019; however, Troms og Finnmark had a higher age-standardised YLL rate than the national rate (8394 per 100 000 [95% UI 7801–8944] vs 7536 per 100 000 [7391–7691]). Low inequality between counties was shown for life expectancy, HALE, all level-1 causes of DALYs, and exposure to level-1 risk factors. Interpretation: Over the past 30 years, Norway has reduced inequality in disease burden between counties. However, inequalities still exist at a within-county level and along other sociodemographic gradients. Because of insufficient Norwegian primary data, there remains substantial uncertainty associated with regional estimates for non-fatal disease burden and exposure to risk factors

Changes in life expectancy and disease burden in Norway, 1990–2019: an analysis of the Global Burden of Disease Study 2019

Background Geographical differences in health outcomes are reported in many countries. Norway has led an active policy aiming for regional balance since the 1970s. Using data from the Global Burden of Disease Study (GBD) 2019, we examined regional differences in development and current state of health across Norwegian counties. Methods Data for life expectancy, healthy life expectancy (HALE), years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) in Norway and its 11 counties from 1990 to 2019 were extracted from GBD 2019. County-specific contributors to changes in life expectancy were compared. Inequality in disease burden was examined by use of the Gini coefficient. Findings Life expectancy and HALE improved in all Norwegian counties from 1990 to 2019. Improvements in life expectancy and HALE were greatest in the two counties with the lowest values in 1990: Oslo, in which life expectancy and HALE increased from 71·9 years (95% uncertainty interval 71·4–72·4) and 63·0 years (60·5–65·4) in 1990 to 81·3 years (80·0–82·7) and 70·6 years (67·4–73·6) in 2019, respectively; and Troms og Finnmark, in which life expectancy and HALE increased from 71·9 years (71·5–72·4) and 63·5 years (60·9–65·6) in 1990 to 80·3 years (79·4–81·2) and 70·0 years (66·8–72·2) in 2019, respectively. Increased life expectancy was mainly due to reductions in cardiovascular disease, neoplasms, and respiratory infections. No significant differences between the national YLD or DALY rates and the corresponding age-standardised rates were reported in any of the counties in 2019; however, Troms og Finnmark had a higher age-standardised YLL rate than the national rate (8394 per 100 000 [95% UI 7801–8944] vs 7536 per 100 000 [7391–7691]). Low inequality between counties was shown for life expectancy, HALE, all level-1 causes of DALYs, and exposure to level-1 risk factors. Interpretation Over the past 30 years, Norway has reduced inequality in disease burden between counties. However, inequalities still exist at a within-county level and along other sociodemographic gradients. Because of insufficient Norwegian primary data, there remains substantial uncertainty associated with regional estimates for non-fatal disease burden and exposure to risk factors