Although average contraceptive use has increased globally in recent decades, an estimated 222 million (26%) of women of child-bearing age worldwide face an unmet need for family planning—defined as a discrepancy between fertility preferences and contraception practice, or failing to translate desires to avoid pregnancy into preventative behaviours and practices. While many studies have reported relationships between availability/quality of contraception and family planning, infant mortality, and fertility, these relationships have not been evaluated quantitatively across a broad range of low- and middle-income countries. Using publicly available data from 64 low- and middle-income countries, we collated test and control variables in six themes: (i) availability of family planning, (ii) quality of family planning, (iii) female education, (iv) religion, (v) mortality, and (vi) socio-economic conditions. We predicted that higher nation-level availability/quality of family-planning services and female education reduce average fertility, whereas higher infant mortality, greater household size (a proxy for population density), and religious adherence increase it. Given the sample size, we first constructed general linear models to test for relationships between fertility and the variables from each theme, from which we retained those with the highest explanatory power within a final general linear model set to determine the partial correlation of dominant test variables. We also applied boosted regression trees, generalised least-squares models, and generalised linear mixed-effects models to account for non-linearity and spatial autocorrelation. On average among all countries, we found the strongest associations between fertility and infant mortality, household size, and access to any form of contraception. Higher infant mortality and household size increased fertility, whereas greater access to any form of contraception decreased fertility. Female education, home visitations by health workers, quality of family planning, and religious adherence all had weak, if any, explanatory power. Our models suggest that decreasing infant mortality, ensuring sufficient housing to reduce household size, and increasing access to contraception will have the greatest effect on decreasing global fertility. We thus provide new evidence that progressing the United Nation’s Sustainable Development Goals for reducing infant mortality can be accelerated by increasing access to family planning.

Although average contraceptive use has increased globally in recent decades, an estimated 222 million (26%) of women of child-bearing age worldwide face an unmet need for family planning — defined as a discrepancy between fertility preferences and contraception practice, or failing to translate desires to avoid pregnancy into preventative behaviours and practices.While many studies have reported relationships between availability of contraception, infant mortality, and fertility, these relationships have not been evaluated quantitatively across a broad range of low- and middle-income countries. Using publicly available data from 46 low- and middle-income countries, we collated test and control variables in six themes: (i) availability of family planning, (ii) quality of family planning, (iii) maternal education, (iv) religion, (v) mortality, and (vi) socio-economic conditions. We predicted that higher nation-level availability/quality of family-planning services, maternal education, and wealth reduce average fertility, whereas higher infant mortality and religious adherence increase it. Given the sample size, we first constructed general linear models to test for relationships between fertility and the variables from each theme, from which we retained those with the highest explanatory power within a final general linear model set to determine the partial correlation of dominant test variables. We also applied boosted regression trees, generalised least-squares models, and a generalised linear mixed-effects models to account for non-linearity and spatial autocorrelation. On average among all countries, we found an association between all main variables and fertility, with reduced infant mortality having the strongest relationship with reduced fertility. Access to contraception was the next-highest correlate with reduced fertility, with female secondary education, home health visitations, and adherence to Catholicism having weak, if any, explanatory power. Our models suggest that decreasing infant mortality and increasing access to contraception will have the greatest effect on decreasing global fertility. We thus provide new evidence that progressing the United Nation’s Sustainable Development Goals for reducing infant mortality can be accelerated by increasing access to any form of family planning.

Background Monitoring countries’ progress towards the achievement of their nutrition targets is an important task, but data sparsity makes monitoring trends challenging. Childhood stunting and overweight data in the European region over the last thirty years had low coverage and frequency, with most data only covering a portion of the complete age interval of 0–59 months. Objectives We implemented a statistical method to extract useful information on child malnutrition trends from sparse longitudinal data for these indicators. Methods Heteroscedastic penalised longitudinal mixed models were used to accommodate data sparsity and predict region-wide, country-level trends over time. We leveraged prevalence estimates stratified by sex and partial age intervals (i.e., intervals that do not cover the complete 0–59 months) which expanded the available data (for stunting: from 84 sources and 428 prevalence estimates to 99 sources and 1,786 estimates), improving the robustness of our analysis. Results Results indicated a generally decreasing trend in stunting and a stable, slightly diminishing rate for overweight, with large differences in trends between low- and middle-income countries versus high-income countries. No differences were found between age groups and between sexes. Cross-validation results indicated that both stunting and overweight models were robust in estimating the indicators for our data (root mean squared error 0.061 and 0.056; median absolute deviation 0.045 and 0.042 for stunting and overweight respectively). Conclusions These statistical methods can provide useful and robust information on child malnutrition trends over time, even when data are sparse.

BackgroundDire forecasts predict that an increasingly hostile environment globally will increase the threats to human health. Infants and young children are especially at risk because children are particularly vulnerable to climate‐related stressors. The childhood diseases most affected, the breadth and magnitude of future health problems and the time frame over which these problems will manifest remain largely unknown.ObjectivesTo review the possibility that spacially explicit analyses can be used to determine how climate change has affected children's health to date and whether these analyses can be used for future projections.MethodsAs an example of whether these objectives can be achieved, all available Australian environmental and health databases were reviewed.ResultsEnvironmental and health data in Australia have been collected for up to 30 years for the same spatial areas at ‘Statistical Area level 1’ (SA1) scale. SA1s are defined as having a population of between 200 and 800 people and collectively they cover the whole of Australia without gaps or overlap. Although the SA1 environmental and health data have been collected separately, they can be merged to allow detailed statistical analyses that can determine how climate change has affected the health of children.ConclusionsThe availability of environmental and health datasets that share the same precise spatial coordinates provides a pathway whereby past and emerging effects on child health can be measured and predicted into the future. Given that the future health and well‐being of children is one of society's greatest concerns, this information is urgently needed.