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Relative importance of demographic, socioeconomic and health factors on life expectancy in low- and lower-middle-income countries.

ABSTRACT: BACKGROUND:We attempted to identify the pathways by which demographic changes, socioeconomic inequalities, and availability of health factors influence life expectancy in low- and lower-middle-income countries. METHODS:Data for 91 countries were obtained from United Nations agencies. The response variable was life expectancy, and the determinant factors were demographic events (total fertility rate and adolescent fertility rate), socioeconomic status (mean years of schooling and gross national income per capita), and health factors (physician density and human immunodeficiency virus [HIV] prevalence rate). Path analysis was used to determine the direct, indirect, and total effects of these factors on life expectancy. RESULTS:All determinant factors were significantly correlated with life expectancy. Mean years of schooling, total fertility rate, and HIV prevalence rate had significant direct and indirect effects on life expectancy. The total effect of higher physician density was to increase life expectancy. CONCLUSIONS:We identified several direct and indirect pathways that predict life expectancy. The findings suggest that policies should concentrate on improving reproductive decisions, increasing education, and reducing HIV transmission. In addition, special attention should be paid to the emerging need to increase life expectancy by increasing physician density.

SUBMITTER: Mondal MN

PROVIDER: S-EPMC3956691 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Relative importance of demographic, socioeconomic and health factors on life expectancy in low- and lower-middle-income countries.

Mondal Md Nazrul Islam MN Shitan Mahendran M

Journal of epidemiology 20131228 2

<h4>Background</h4>We attempted to identify the pathways by which demographic changes, socioeconomic inequalities, and availability of health factors influence life expectancy in low- and lower-middle-income countries.<h4>Methods</h4>Data for 91 countries were obtained from United Nations agencies. The response variable was life expectancy, and the determinant factors were demographic events (total fertility rate and adolescent fertility rate), socioeconomic status (mean years of schooling and g ...[more]

PMID: 24390415

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Project description:BackgroundNon-communicable diseases are the leading global cause of death and disproportionately afflict those living in low-income and lower-middle-income countries (LLMICs). The association between socioeconomic status and non-communicable disease behavioural risk factors is well established in high-income countries, but it is not clear how behavioural risk factors are distributed within LLMICs. We aimed to systematically review evidence on the association between socioeconomic status and harmful use of alcohol, tobacco use, unhealthy diets, and physical inactivity within LLMICs.MethodsWe searched 13 electronic databases, including Embase and MEDLINE, grey literature, and reference lists for primary research published between Jan 1, 1990, and June 30, 2015. We included studies from LLMICs presenting data on multiple measures of socioeconomic status and tobacco use, alcohol use, diet, and physical activity. No age or language restrictions were applied. We excluded studies that did not allow comparison between more or less advantaged groups. We used a piloted version of the Cochrane Effective Practice and Organisation of Care Group data collection checklist to extract relevant data at the household and individual level from the included full text studies including study type, methods, outcomes, and results. Due to high heterogeneity, we used a narrative approach for data synthesis. We used descriptive statistics to assess whether the prevalence of each risk factor varied significantly between members of different socioeconomic groups. The study protocol is registered with PROSPERO, number CRD42015026604.FindingsAfter reviewing 4242 records, 75 studies met our inclusion criteria, representing 2 135 314 individuals older than 10 years from 39 LLMICs. Low socioeconomic groups were found to have a significantly higher prevalence of tobacco and alcohol use than did high socioeconomic groups. These groups also consumed less fruit, vegetables, fish, and fibre than those of high socioeconomic status. High socioeconomic groups were found to be less physically active and consume more fats, salt, and processed food than individuals of low socioeconomic status. While the included studies presented clear patterns for tobacco use and physical activity, heterogeneity between dietary outcome measures and a paucity of evidence around harmful alcohol use limit the certainty of these findings.InterpretationDespite significant heterogeneity in exposure and outcome measures, clear evidence shows that the burden of behavioural risk factors is affected by socioeconomic position within LLMICs. Governments seeking to meet Sustainable Development Goal (SDG) 3.4-reducing premature non-communicable disease mortality by a third by 2030-should leverage their development budgets to address the poverty-health nexus in these settings. Our findings also have significance for health workers serving these populations and policy makers tasked with preventing and controlling the rise of non-communicable diseases.FundingWHO.

Project description:ImportanceMany randomized clinical trials (RCTs) led by high-income countries (HICs) now enroll patients from lower middle-income countries (LMICs) and upper middle-income countries (UMICs). Although enrolling diverse populations promotes research collaborations, there are issues regarding which countries participate in RCTs and how this participation may contribute to global research.ObjectiveTo describe which UMICs and LMICs participate in RCTs led by HICs.Design, setting, and participantsA cross-sectional study of all oncology RCTs published globally during January 1, 2014, to December 31, 2017, was conducted. The study cohort was restricted to RCTs led by HICs that enrolled participants from LMICs and UMICs. Study analyses were conducted in November 1, 2021, to May 31, 2022.Main outcomes and measuresA bibliometric approach (Web of Science 2007-2017) was used to explore whether RCT participation was proportional to other measures of cancer research activity. Participation in RCTs (ie, percentage of RCTs in the cohort in which each LMIC and UMIC participated) was compared with country-level cancer research bibliometric output (ie, percentage of total cancer research bibliometric output from the same group of countries that came from a specific LMIC and UMIC).ResultsAmong the 636 HIC-led RCTs, 186 trials (29%) enrolled patients in LMICs (n = 84 trials involving 11 LMICs) and/or UMICs (n = 181 trials involving 26 UMICs). The most common participating LMICs were India (42 [50%]), Ukraine (39 [46%]), Philippines (23 [27%]), and Egypt (12 [14%]). The most common participating UMICs were Russia (115 [64%]), Brazil (94 [52%]), Romania (62 [34%]), China (56 [31%]), Mexico (56 [31%]), and South Africa (54 [30%]). Several LMICs are overrepresented in the cohort of RCTs based on proportional cancer research bibliometric output: Ukraine (46% of RCTs but 2% of cancer research bibliometric output), Philippines (27% RCTs, 1% output), and Georgia (8% RCTs, 0.2% output). Overrepresented UMICs include Russia (64% RCTs, 2% output), Romania (34% RCTs, 2% output), Mexico (31% RCTs, 2% output), and South Africa (30% RCTs, 1% output).Conclusions and relevanceIn this cross-sectional study, a substantial proportion of RCTs led by HICs enrolled patients in LMICs and UMICs. The LMICs and UMICs that participated in these trials did not match overall cancer bibliometric output as a surrogate for research ecosystem maturity. Reasons for this apparent discordance and how these data may inform future capacity-strengthening activities require further study.

Project description:Background:Non-communicable diseases (NCDs) are the leading cause of death globally. Eighty-two percent of premature NCD deaths occur within low- and lower middle-income countries (LLMICs). Research to date, largely drawn from high-income countries, suggests that disadvantaged and marginalized groups have a higher NCD burden, but there has been a dearth of research studying this relationship within LLMICs. The purpose of this systematic review is to map the literature on evidence from LLMICs on the socio-economic status (SES) gradient of four particular NCDs: cardiovascular disease, cancer, diabetes, and chronic respiratory diseases. Methods:We conducted a comprehensive literature search for primary research published between 1 January 1990 and 27 April 2015 using six bibliographic databases and web resources. We included studies that reported SES and morbidity or mortality from cardiovascular disease, cancer, diabetes and chronic respiratory diseases within LLMICs. Results:Fifty-seven studies from 17 LLMICs met our inclusion criteria. Fourteen of the 18 papers that reported significant associations between cancer and SES suggested that low SES groups had the highest cancer risk. Eleven of 15 papers reporting significant relationships between CVD and SES suggested that low SES groups have higher risk. In contrast, seven of 12 papers reporting significant findings related to diabetes found that higher SES groups had higher diabetes risk. We identified just three studies on the relationship between chronic respiratory diseases and SES; none of them reported significant findings. Conclusions:Only 17 of the 84 LLMICs were represented, highlighting the need for more research on NCDs within these countries. The majority of studies were medium to high quality cross-sectional studies. When we restricted our analyses to high quality studies only, for both cancer and cardiovascular disease more than half of studies found a significantly higher risk for those of lower SES. The opposite was true for diabetes, whilst there was a paucity of high quality research on chronic respiratory disease. Development programmes must consider health alongside other aims and NCD prevention interventions must target all members of the population. Systematic review registration number:Prospero: CRD42015020169.

Project description:Although retirement ages are rising in the United Kingdom and other countries, the average number of years people in England can expect to spend both healthy and work from age 50 (Healthy Working Life Expectancy; HWLE) is less than the number of years to the State Pension age. This study aimed to estimate HWLE with the presence and absence of selected health, socio-demographic, physical activity, and workplace factors relevant to stakeholders focusing on improving work participation. Data from 11,540 adults in the English Longitudinal Study of Ageing were analysed using a continuous time 3-state multi-state model. Age-adjusted hazard rate ratios (aHRR) were estimated for transitions between health and work states associated with individual and combinations of health, socio-demographic, and workplace factors. HWLE from age 50 was 3.3 years fewer on average for people with pain interference (6.54 years with 95% confidence interval [6.07, 7.01]) compared to those without (9.79 [9.50, 10.08]). Osteoarthritis and mental health problems were associated with 2.2 and 2.9 fewer healthy working years respectively (HWLE for people without osteoarthritis: 9.50 years [9.22, 9.79]; HWLE with osteoarthritis: 7.29 years [6.20, 8.39]; HWLE without mental health problems: 9.76 years [9.48, 10.05]; HWLE with mental health problems: 6.87 years [1.58, 12.15]). Obesity and physical inactivity were associated with 0.9 and 2.0 fewer healthy working years respectively (HWLE without obesity: 9.31 years [9.01, 9.62]; HWLE with obesity: 8.44 years [8.02, 8.86]; HWLE without physical inactivity: 9.62 years [9.32, 9.91]; HWLE with physical inactivity: 7.67 years [7.23, 8.12]). Workers without autonomy at work or with inadequate support at work were expected to lose 1.8 and 1.7 years respectively in work with good health from age 50 (HWLE for workers with autonomy: 9.50 years [9.20, 9.79]; HWLE for workers lacking autonomy: 7.67 years [7.22, 8.12]; HWLE for workers with support: 9.52 years [9.22, 9.82]; HWLE for workers with inadequate support: 7.86 years [7.22, 8.12]). This study identified demographic, health, physical activity, and workplace factors associated with lower HWLE and life expectancy at age 50. Identifying the extent of the impact on healthy working life highlights these factors as targets and the potential to mitigate against premature work exit is encouraging to policy-makers seeking to extend working life as well as people with musculoskeletal and mental health conditions and their employers. The HWLE gaps suggest that interventions are needed to promote the health, wellbeing and work outcomes of subpopulations with long-term health conditions.

Project description:BackgroundThe heavy and ever rising burden of non-communicable diseases (NCDs) in low- and middle-income countries (LMICs) warrants interventions to reduce their underlying risk factors, which are often linked to lifestyles. To effectively supplement nationwide policies with targeted interventions, it is important to know how these risk factors are distributed across socioeconomic segments of populations in LMICs. This study quantifies the prevalence and socioeconomic inequalities in lifestyle risk factors in LMICs, to identify policy priorities conducive to the Sustainable Development Goal of a one third reduction in deaths from NCDs by 2030.MethodsData from 1,278,624 adult respondents to Demographic & Health Surveys across 22 LMICs between 2013 and 2018 are used to estimate crude prevalence rates and socioeconomic inequalities in tobacco use, overweight, harmful alcohol use and the clustering of these three in a household. Inequalities are measured by a concentration index and correlated with the percentage of GDP spent on health. We estimate a multilevel model to examine associations of individual characteristics with the different lifestyle risk factors.ResultsThe prevalence of tobacco use among men ranges from 59.6% (Armenia) to 6.6% (Nigeria). The highest level of overweight among women is 83.7% (Egypt) while this is less than 12% in Burundi, Chad and Timor-Leste. 82.5% of women in Burundi report that their partner is "often or sometimes drunk" compared to 1.3% in Gambia. Tobacco use is concentrated among the poor, except for the low share of men smoking in Nigeria. Overweight, however, is concentrated among the better off, especially in Tanzania and Zimbabwe (Erreygers Index (EI) 0.227 and 0.232). Harmful alcohol use is more concentrated among the better off in Nigeria (EI 0.127), while Chad, Rwanda and Togo show an unequal pro-poor distribution (EI respectively - 0.147, - 0.210, - 0.266). Cambodia exhibits the largest socioeconomic inequality in unhealthy household behaviour (EI - 0.253). The multilevel analyses confirm that in LMICs, tobacco and alcohol use are largely concentrated among the poor, while overweight is concentrated among the better-off. The associations between the share of GDP spent on health and the socioeconomical distribution of lifestyle factors are multidirectional.ConclusionsThis study emphasizes the importance of lifestyle risk factors in LMICs and the socioeconomic variation therein. Given the different socioeconomic patterns in lifestyle risk factors - overweight patters in LMICs differ considerably from those in high income countries- tailored interventions towards specific high-risk populations are warranted to supplement nationwide policies.

Dataset Information

Relative importance of demographic, socioeconomic and health factors on life expectancy in low- and lower-middle-income countries.

Publications

Relative importance of demographic, socioeconomic and health factors on life expectancy in low- and lower-middle-income countries.

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