Ultra-processed food consumption and risk of chronic respiratory diseases mortality among adults: evidence from a prospective cohort study.

PURPOSE: The purpose of the study was to determine the relationships between ultra-processed food (UPF) consumption and risk of mortality due to chronic respiratory diseases (CRDs) overall, chronic obstructive pulmonary disease (COPD), and lung cancer. METHODS: A total of 96,607 participants aged 55 years and over were included from the Prostate, Lung, Colorectal and Ovarian (PLCO) cancer trial. Dietary intake was measured using food frequency questionnaire. Cox regression was fitted to estimate the risk of all-cause mortality and mortality due to CRDs overall, COPD and lung cancer associated with UPF intake. Competing risk regression was used to account for deaths from other causes and censoring. RESULTS: During the follow-up of 1,379,655.5 person-years (median 16.8 years), 28,700 all-cause, 4092 CRDs, 2015 lung cancer and 1,536 COPD mortality occurred. A higher intake of UPF increased the risk of mortality from CRDs overall by 10% (HR 1.10; 95% CI 1.01, 1.22) and COPD by 26% (HR 1.26; 95% CI 1.06, 1.49) but not associated with lung cancer mortality risk (HR 0.97; 95% CI 0.84, 1.12). However, the risk of lung cancer increased by 16% (HR 1.16; 95% CI 1.01, 1.34) in the highest UPF intake after multiple imputation. Dose-response relationships existed for CRDs and COPD mortality but not lung cancer. CONCLUSION: UPF consumption was associated with an increased risk of CRD mortality. The association between UPF consumption and lung cancer mortality is inconclusive and only significant when multiple imputation was applied.

Healthy lifestyle is associated with reduced cardiovascular disease, depression and mortality in people at elevated risk of sleep apnea.

We assessed: (1) the independent and joint association of obstructive sleep apnea risk and healthy lifestyle with common consequences (excessive daytime sleepiness, depression, cardiovascular disease and stroke) of obstructive sleep apnea; and (2) the effect of healthy lifestyle on survival in people with increased obstructive sleep apnea risk. Data from 13,694 adults (median age 46 years; 50% men) were used for cross-sectional and survival analyses (mortality over 15 years). A healthy lifestyle score with values from 0 (most unhealthy) to 5 (most healthy) was determined based on diet, alcohol intake, physical activity, smoking and body mass index. In the cross-sectional analysis, obstructive sleep apnea risk was positively associated with all chronic conditions and excessive daytime sleepiness in a dose-response manner (p for trend < 0.001). The healthy lifestyle was inversely associated with all chronic conditions (p for trend < 0.001) but not with excessive daytime sleepiness (p for trend = 0.379). Higher healthy lifestyle score was also associated with reduced odds of depression and cardiovascular disease. We found an inverse relationship between healthy lifestyle score with depression (p for trend < 0.001), cardiovascular disease (p for trend = 0.003) and stroke (p for trend = 0.025) among those who had high obstructive sleep apnea risk. In the survival analysis, we found an inverse association between healthy lifestyle and all-cause mortality for all categories of obstructive sleep apnea risk (moderate/high- and high-risk groups [p for trend < 0.001]). This study emphasises the crucial role of a healthy lifestyle in mitigating the effects of obstructive sleep apnea risk in individuals with an elevated obstructive sleep apnea risk.

The Good Sleeper Scale-15 items: a questionnaire for the standardised assessment of good sleepers.

Research with 'good sleepers' is ubiquitous, yet there are no standardised criteria to identify a 'good sleeper'. The present study aimed to create and validate a questionnaire for identifying good sleepers for use in research studies known as the Good Sleeper Scale-15 items (GSS-15). Data were derived from a population-based survey of Australian adults (n = 2,044). A total of 23 items were chosen for possible inclusion. An exploratory factor analysis (EFA) was conducted on ~10% of the survey dataset (n = 191) for factor identification and item reduction. A confirmatory factor analysis (CFA) was conducted on the remaining data (n = 1,853) to test model fit. Receiver operating characteristic curves and correlations were conducted to derive cut-off scores and test associations with sleep, daytime functioning, health, and quality-of-life. The EFA identified six factors: 'Sleep Difficulties', 'Timing', 'Duration', 'Regularity', 'Adequacy', and 'Perceived Sleep Problem'. The CFA showed that model fit was high and comparable to other sleep instruments, χ2 (63) = 378.22, p < 0.001, root mean square error of approximation = 0.05, with acceptable internal consistency (α = 0.76). Strong correlations were consistently found between GSS-15 global scores and outcomes, including 'a good night's sleep' (r = 0.7), 'feeling un-refreshed' (r = -0.59), and 'experienced sleepiness' (r = -0.51), p < 0.001. Cut-off scores were derived to categorise individuals likely to be a good sleeper (GSS-15 score ≥40) and those very likely to be a good sleeper (GSS-15 score ≥45). The GSS-15 is a freely available, robust questionnaire that will assist in identifying good sleepers for the purpose of sleep research. Future work will test relationships with other sleep measures in community and clinical samples.

Associations of baseline obstructive sleep apnea and sleep macroarchitecture with cognitive function after 8 years in middle-aged and older men from a community-based cohort study.

Previous prospective studies examining associations of obstructive sleep apnea and sleep macroarchitecture with future cognitive function recruited older participants, many demonstrating baseline cognitive impairment. This study examined obstructive sleep apnea and sleep macroarchitecture predictors of visual attention, processing speed, and executive function after 8 years among younger community-dwelling men. Florey Adelaide Male Ageing Study participants (n = 477) underwent home-based polysomnography, with 157 completing Trail-Making Tests A and B and the Mini-Mental State Examination. Associations of obstructive sleep apnea (apnea-hypopnea index, oxygen desaturation index, and hypoxic burden index) and sleep macroarchitecture (sleep stage percentages and total sleep time) parameters with future cognitive function were examined using regression models adjusted for baseline demographic, biomedical, and behavioural factors, and cognitive task performance. The mean (standard deviation) age of the men at baseline was 58.9 (8.9) years, with severe obstructive sleep apnea (apnea-hypopnea index ≥30 events/h) in 9.6%. The median (interquartile range) follow-up was 8.3 (7.9-8.6) years. A minority of men (14.6%) were cognitively impaired at baseline (Mini-Mental State Examination score <28/30). A higher percentage of light sleep was associated with better Trail-Making Test A performance (B = -0.04, 95% confidence interval [CI] -0.06, -0.01; p = 0.003), whereas higher mean oxygen saturation was associated with worse performance (B = 0.11, 95% CI 0.02, 0.19; p = 0.012). While obstructive sleep apnea and sleep macroarchitecture might predict cognitive decline, future studies should consider arousal events and non-routine hypoxaemia measures, which may show associations with cognitive decline.

The association between diet quality, plant-based diets, systemic inflammation, and mortality risk: findings from NHANES.

PURPOSE: To our knowledge, no studies have examined the association of diet quality and plant-based diets (PBD) with inflammatory-related mortality in obesity. Therefore, this study aimed to determine the joint associations of Healthy Eating Index-2015 (HEI-2015), plant-based dietary index (PDI), healthy PDI (hPDI), unhealthy PDI (uPDI), pro-vegetarian dietary index (PVD), and systemic inflammation with all-cause, cardiovascular disease (CVD), and cancer mortality risks by obesity status. METHODS: Participants from NHANES were included in cross-sectional (N = 27,915, cycle 1999-2010, 2015-2018) and longitudinal analysis (N = 11,939, cycle 1999-2008). HEI-2015, PDI, hPDI, uPDI, and PVD were constructed based on the 24-h recall dietary interview. The grade of inflammation (low, moderate, and high) was determined based on C-reactive protein (CRP) values and multivariable ordinal logistic regression was used to determine the association. Cox proportional hazard models were used to determine the joint associations of diet and inflammation with mortality. RESULTS: In the fully adjusted model, HEI-2015 (ORT3vsT1 = 0.76, 95% CI 0.69-0.84; p-trend = < 0.001), PDI (ORT3vsT1 = 0.83, 95% CI 0.75-0.91; p trend = < 0.001), hPDI (ORT3vsT1 = 0.79, 95% CI 0.71-0.88; p trend = < 0.001), and PVD (ORT3vsT1 = 0.85, 95% CI 0.75-0.97; p trend = 0.02) were associated with lower systemic inflammation. In contrast, uPDI was associated with higher systemic inflammation (ORT3vsT1 = 1.18, 95% CI 1.06-1.31; p-trend = 0.03). Severe inflammation was associated with a 25% increase in all-cause mortality (ORT3vsT1 = 1.25, 95% CI 1.03-1.53, p trend = 0.02). No association was found between PDI, hPDI, uPDI, and PVD with mortality. The joint association, between HEI-2015, levels of systemic inflammation, and all-cause, CVD and cancer mortality, was not significant. However, a greater reduction in mortality risk with an increase in HEI-2015 scores was observed in individuals with low and moderate inflammation, especially those with obesity. CONCLUSION: Higher scores of HEI-2015 and increased intake of a healthy plant-based diet were associated with lower inflammation, while an unhealthy plant-based diet was associated with higher inflammation. A greater adherence to the 2015 dietary guidelines may reduce the risk of mortality associated with inflammation and may also benefit individuals with obesity who had low and moderate inflammation.

Socio-demographic correlates of unhealthy lifestyle in Ethiopia: a secondary analysis of a national survey.

BACKGROUND: Multiple lifestyle risk factors exhibit a stronger association with non-communicable diseases (NCDs) compared to a single factor, emphasizing the necessity of considering them collectively. By integrating these major lifestyle risk factors, we can identify individuals with an overall unhealthy lifestyle, which facilitates the provision of targeted interventions for those at significant risk of NCDs. The aim of this study was to evaluate the socio-demographic correlates of unhealthy lifestyles among adolescents and adults in Ethiopia. METHODS: A national cross-sectional survey, based on the World Health Organization's NCD STEPS instruments, was conducted in Ethiopia. The survey, carried out in 2015, involved a total of 9,800 participants aged between 15 and 69 years. Lifestyle health scores, ranging from 0 (most healthy) to 5 (most unhealthy), were derived considering factors such as daily fruit and vegetable consumption, smoking status, prevalence of overweight/obesity, alcohol intake, and levels of physical activity. An unhealthy lifestyle was defined as the co-occurrence of three or more unhealthy behaviors. To determine the association of socio-demographic factors with unhealthy lifestyles, multivariable logistic regression models were utilized, adjusting for metabolic factors, specifically diabetes and high blood pressure. RESULTS: Approximately one in eight participants (16.7%) exhibited three or more unhealthy lifestyle behaviors, which included low fruit/vegetable consumption (98.2%), tobacco use (5.4%), excessive alcohol intake (15%), inadequate physical activity (66%), and obesity (2.3%). Factors such as male sex, urban residency, older age, being married or in a common-law relationship, and a higher income were associated with these unhealthy lifestyles. On the other hand, a higher educational status was associated with lower odds of these behaviors. CONCLUSION: In our analysis, we observed a higher prevalence of concurrent unhealthy lifestyles. Socio-demographic characteristics, such as sex, age, marital status, residence, income, and education, were found to correlate with individuals' lifestyles. Consequently, tailored interventions are imperative to mitigate the burden of unhealthy lifestyles in Ethiopia.

Comorbid insomnia and sleep apnoea is associated with all-cause mortality.

BACKGROUND: Increased mortality has been reported in people with insomnia and in those with obstructive sleep apnoea (OSA). However, these conditions commonly co-occur and the combined effect of comorbid insomnia and sleep apnoea (COMISA) on mortality risk is unknown. This study used Sleep Heart Health Study (SHHS) data to assess associations between COMISA and all-cause mortality risk. METHODS: Insomnia was defined as difficulties falling asleep, maintaining sleep and/or early morning awakenings from sleep ≥16 times per month, and daytime impairments. OSA was defined as an apnoea-hypopnoea index ≥15 events·h-1. COMISA was defined if both conditions were present. Multivariable adjusted Cox proportional hazards models were used to determine the association between COMISA and all-cause mortality (n=1210) over 15 years of follow-up. RESULTS: 5236 participants were included. 2708 (52%) did not have insomnia/OSA (reference group), 170 (3%) had insomnia-alone, 2221 (42%) had OSA-alone and 137 (3%) had COMISA. COMISA participants had a higher prevalence of hypertension (OR 2.00, 95% CI 1.39-2.90) and cardiovascular disease (CVD) (OR 1.70, 95% CI 1.11-2.61) compared with the reference group. Insomnia-alone and OSA-alone were associated with higher risk of hypertension but not CVD compared with the reference group. Compared with the reference group, COMISA was associated with a 47% (hazard ratio 1.47, 95% CI 1.06-2.07) increased risk of mortality. The association between COMISA and mortality was consistent across multiple definitions of OSA and insomnia. CONCLUSIONS: COMISA was associated with higher rates of hypertension and CVD at baseline, and an increased risk of all-cause mortality compared with no insomnia/OSA.

The association of co-morbid insomnia and sleep apnea with prevalent cardiovascular disease and incident cardiovascular events.

Insomnia and obstructive sleep apnea commonly co-occur (co-morbid insomnia and sleep apnea), and their co-occurrence has been associated with worse cardiometabolic and mental health. However, it remains unknown if people with co-morbid insomnia and sleep apnea are at a heightened risk of incident cardiovascular events. This study used longitudinal data from the Sleep Heart Health Study (N = 5803) to investigate potential associations between co-morbid insomnia and sleep apnea and cardiovascular disease prevalence at baseline and cardiovascular event incidence over ~11 years follow-up. Insomnia was defined as self-reported difficulties initiating and/or maintaining sleep AND daytime impairment. Obstructive sleep apnea was defined as an apnea-hypopnea index ≥ 15 events per hr sleep. Co-morbid insomnia and sleep apnea was defined if both conditions were present. Data from 4160 participants were used for this analysis. The prevalence of no insomnia/obstructive sleep apnea, insomnia only, obstructive sleep apnea only and co-morbid insomnia and sleep apnea was 53.2%, 3.1%, 39.9% and 1.9%, respectively. Co-morbid insomnia and sleep apnea was associated with a 75% (odd ratios [95% confidence interval]; 1.75 [1.14, 2.67]) increase in likelihood of having cardiovascular disease at baseline after adjusting for pre-specified confounders. In the unadjusted model, co-morbid insomnia and sleep apnea was associated with a twofold increase (hazard ratio, 95% confidence interval: 2.00 [1.33, 2.99]) in risk of cardiovascular event incidence. However, after adjusting for pre-specified covariates, co-morbid insomnia and sleep apnea was not significantly associated with incident cardiovascular events (hazard ratio 1.38 [0.92, 2.07]). Comparable findings were obtained when an alternative definition of insomnia (difficulties initiating and/or maintaining sleep without daytime impairment) was used.

Multidimensional sleep health is associated with mental well-being in Australian adults.

The few studies assessing the relationship between mental health and a multidimensional measure of sleep have been conducted in samples of almost exclusively women. In the present study, we therefore assessed associations of multidimensional sleep health with mental well-being in Australian adults. A cross-sectional, national online survey of sleep health was conducted in 2019 in 2,044 community dwelling adults aged 18-90 years. Composite scores of self-reported healthy sleep were based on Ru-SATED (R-SATED) dimensions of satisfaction, alertness, timing, efficiency and duration scored 0 (never/rarely), 1 (sometimes) or 2 (usually/always), and regularity (social jet lag) was scored 0 (≥1 hr) or 1 (<1 hr). Mental well-being was identified by a report of no problem on the EuroQol (European quality of life) five dimension five level scale (EQ-5D-5L) anxiety/depression scale, as well as absence of six chronic depressive symptoms. Ordinal logistic regression analyses determined associations of mental well-being with sleep dimensions, and total R-SATED (range 0-11) and SATED scores (0-10), adjusted for sociodemographic and health factors. In males and females, healthy categories of SATED dimensions (but not regularity) were associated with mental well-being. A 1 unit increase in the total SATED score (mean [SD] 6.6 [2.1]) was associated with less problems on the EQ-5D-5L (odds ratio [OR] 1.11, 95% confidence interval [CI] 1.08-1.14) and fewer chronic depressive symptoms (OR 1.20, 95% CI 1.17-1.23). These estimates did not differ when the total R-SATED score was considered. Sleep health promotion focussing solely on traditional messaging around healthy sleep duration may limit mental health gains. Rather, a more holistic approach to public health messaging to improve sleep health literacy may be beneficial for mental well-being.

Eating architecture in adults at increased risk of type 2 diabetes: associations with body fat and glycaemic control.

Eating architecture is a term that describes meal frequency, meal timing and meal size and the daily variation in each of these. The aim of this study was to determine the relationship between components of eating architecture on body fat and markers of glycaemic control in healthy adults at increased risk of type 2 diabetes (T2DM). Participants (n 73, 39 males, age 58·8 (8·1) years, BMI 33·4 (4·4) kg/m2) recorded food intake and wore accelerometers and continuous glucose monitors (CGM) for 7-14 d under free-living conditions. Body fat and glycated Hb (HbA1c) were also measured. The mean and day-to-day variation (calculated as the standard deviation during the monitoring period) of each component of eating architecture were calculated. Multivariable linear regression models were constructed for three separate outcome variables (body fat mass, mean CGM glucose and HbA1c) for each component of eating architecture before and after adjustment for confounders. Higher variability in the time of first meal consumption was associated with increased body fat mass after adjusting for confounders (ß = 0·227, 95 % CI: 0·019, 0·434, P = 0·033). Increased variability in the time lag from waking to first meal consumption was also positively associated with increased HbA1c after adjustment (ß = 0·285, 95 % CI: 0·040, 0·530, P = 0·023). Low day-to-day variability in first meal consumption was associated with lower body fat and improved glucose control in adults at increased risk of T2DM. Routine consumption of meals may optimise temporal regulation to anticipate and respond appropriately to a glucose challenge.

A bi-directional association between weight change and health-related quality of life: evidence from the 11-year follow-up of 9916 community-dwelling adults.

PURPOSE: To examine the prospective associations between body mass index (BMI) and health-related quality of life (HRQoL). METHODS: Data were extracted from a longitudinal, nationally representative sample of 9916 men and women aged 18 years and over who were followed annually between 2006 and 2016 in the Household, Income and Labour Dynamics in Australia (HILDA) survey. HRQoL was assessed using the self-administered SF-36 questionnaire annually between 2006 (baseline) and 2016. BMI was calculated from self-reported height and weight and was classified into the following four categories of baseline BMI: underweight (< 18.5 kg/m2), normal weight (18.5-24.9 kg/m2), overweight (25-29.9 kg/m2) and obese (≥ 30 kg/m2). We used linear mixed-effects regression models to investigate the associations between change in BMI (kg/m2) and concurrent changes in HRQoL scores over 11 years. RESULTS: BMI gain was associated with deterioration of Physical Component Summary (PCS) (P < 0.001), but not with change in Mental component summary (MCS) over the 11-year period. BMI gain was inversely associated (P < 0.001) with five of the eight HRQoL domains (physical functioning, role physical, bodily pain, general health and vitality) with a significant graded association according to baseline BMI category. Over the 11-year study period, every unit increase in PCS was associated with a decrease of 0.02 (P < 0.001), 0.03 (P < 0.001) and 0.04 (P < 0.001) BMI units per year among participants who were normal, overweight and obese at baseline, respectively. Five of the eight domains of HRQoL (physical functioning, role physical, bodily pain, general health and vitality) were inversely associated with BMI (P < 0.001) with a significant graded association according to baseline BMI category. CONCLUSIONS: Weight gain was not only associated with deterioration of HRQoL, and vice versa. The bi-directional association was stronger for physical than mental domains of HRQoL.

Burden and trend of diet-related non-communicable diseases in Australia and comparison with 34 OECD countries, 1990-2015: findings from the Global Burden of Disease Study 2015.

BACKGROUND: Diet is a major determining factor for many non-communicable chronic diseases (NCDs). However, evidence on diet-related NCD burden remains limited. We assessed the trends in diet-related NCDs in Australia from 1990 to 2015 and compared the results with other countries of the Organization for Economic Co-operation and Development (OECD). METHODS: We used data and methods from the Global Burden of Disease (GBD) 2015 study to estimate the NCD mortality and disability-adjusted life years (DALYs) attributable to 14 dietary risk factors in Australia and 34 OECD nations. Countries were further ranked from the lowest (first) to highest (35th) burden using an age-standardized population attributable fraction (PAF). RESULTS: In 2015, the estimated number of deaths attributable to dietary risks was 29,414 deaths [95% uncertainty interval (UI) 24,697 - 34,058 or 19.7% of NCD deaths] and 443,385 DALYs (95% UI 377,680-511,388 or 9.5% of NCD DALYs) in Australia. Young (25-49 years) and middle-age (50-69 years) male adults had a higher PAF of diet-related NCD deaths and DALYs than their female counterparts. Diets low in fruits, vegetables, nuts and seeds and whole grains, but high in sodium, were the major contributors to both NCD deaths and DALYs. Overall, 42.3% of cardiovascular deaths were attributable to dietary risk factors. The age-standardized PAF of diet-related NCD mortality and DALYs decreased over the study period by 28.2% (from 27.0% in 1990 to 19.4% in 2015) and 41.0% (from 14.3% in 1990 to 8.4% in 2015), respectively. In 2015, Australia ranked 12th of 35 examined countries in diet-related mortality. A small improvement of rank was recorded compared to the previous 25 years. CONCLUSIONS: Despite a reduction in diet-related NCD burden over 25 years, dietary risks are still the major contributors to a high burden of NCDs in Australia. Interventions targeting NCDs should focus on dietary behaviours of individuals and population groups.

Trends of mortality attributable to child and maternal undernutrition, overweight/obesity and dietary risk factors of non-communicable diseases in sub-Saharan Africa, 1990-2015: findings from the Global Burden of Disease Study 2015.

OBJECTIVE: To assess trends of mortality attributable to child and maternal undernutrition (CMU), overweight/obesity and dietary risks of non-communicable diseases (NCD) in sub-Saharan Africa (SSA) using data from the Global Burden of Disease (GBD) Study 2015. DESIGN: For each risk factor, a systematic review of data was used to compute the exposure level and the effect size. A Bayesian hierarchical meta-regression analysis was used to estimate the exposure level of the risk factors by age, sex, geography and year. The burden of all-cause mortality attributable to CMU, fourteen dietary risk factors (eight diets, five nutrients and fibre intake) and overweight/obesity was estimated. SETTING: Sub-Saharan Africa.ParticipantsAll age groups and both sexes. RESULTS: In 2015, CMU, overweight/obesity and dietary risks of NCD accounted for 826204 (95 % uncertainty interval (UI) 737346, 923789), 266768 (95 % UI 189051, 353096) and 558578 (95 % UI 453433, 680197) deaths, respectively, representing 10·3 % (95 % UI 9·1, 11·6 %), 3·3 % (95 % UI 2·4, 4·4 %) and 7·0 % (95 % UI 5·8, 8·3 %) of all-cause mortality. While the age-standardized proportion of all-cause mortality accounted for by CMU decreased by 55·2 % between 1990 and 2015 in SSA, it increased by 63·3 and 17·2 % for overweight/obesity and dietary risks of NCD, respectively. CONCLUSIONS: The increasing burden of diet- and obesity-related diseases and the reduction of mortality attributable to CMU indicate that SSA is undergoing a rapid nutritional transition. To tackle the impact in SSA, interventions and international development agendas should also target dietary risks associated with NCD and overweight/obesity.

A comparison of principal component analysis, partial least-squares and reduced-rank regressions in the identification of dietary patterns associated with bone mass in ageing Australians.

PURPOSE: The relative advantages of dietary analysis methods, particularly in identifying dietary patterns associated with bone mass, have not been investigated. We evaluated principal component analysis (PCA), partial least-squares (PLS) and reduced-rank regressions (RRR) in determining dietary patterns associated with bone mass. METHODS: Data from 1182 study participants (45.9% males; aged 50 years and above) from the North West Adelaide Health Study (NWAHS) were used. Dietary data were collected using a food frequency questionnaire (FFQ). Dietary patterns were constructed using PCA, PLS and RRR and compared based on the performance to identify plausible patterns associated with bone mineral density (BMD) and content (BMC). RESULTS: PCA, PLS and RRR identified two, four and four dietary patterns, respectively. All methods identified similar patterns for the first two factors (factor 1, "prudent" and factor 2, "western" patterns). Three, one and none of the patterns derived by RRR, PLS and PCA were significantly associated with bone mass, respectively. The "prudent" and dairy (factor 3) patterns determined by RRR were positively and significantly associated with BMD and BMC. Vegetables and fruit pattern (factor 4) of PLS and RRR was negatively and significantly associated with BMD and BMC, respectively. CONCLUSIONS: RRR was found to be more appropriate in identifying more (plausible) dietary patterns that are associated with bone mass than PCA and PLS. Nevertheless, the advantage of RRR over the other two methods (PCA and PLS) should be confirmed in future studies.

Associations of childhood, maternal and household dietary patterns with childhood stunting in Ethiopia: proposing an alternative and plausible dietary analysis method to dietary diversity scores.

BACKGROUND: Identifying dietary patterns that consider the overall eating habits, rather than focusing on individual foods or simple counts of consumed foods, better helps to understand the combined effects of dietary components. Therefore, this study aimed to use dietary patterns, as an alternative method to dietary diversity scores (DDSs), and investigate their associations with childhood stunting in Ethiopia. METHODS: Mothers and their children aged under 5 years (n = 3788) were recruited using a two-stage random cluster sampling technique in two regions of Ethiopia. Socio-demographic, dietary and anthropometric data were collected. Dietary intake was assessed using standardized dietary diversity tools. Household, maternal and child DDSs were calculated and dietary patterns were identified by tetrachoric (factor) analysis. Multilevel linear and Poisson regression analyses were applied to assess the association of DDSs and dietary patterns with height-for-age z score (HAZ) and stunting, respectively. RESULTS: The overall prevalence of stunting among children under-five was 38.5% (n = 1459). We identified three dietary patterns each, for households ("fish, meat and miscellaneous", "egg, meat, poultry and legume" and "dairy, vegetable and fruit"), mothers ("plant-based", "egg, meat, poultry and legume" and "dairy, vegetable and fruit" and children ("grain based", "egg, meat, poultry and legume" and "dairy, vegetable and fruit"). Children in the third tertile of the household "dairy, vegetable and fruit" pattern had a 0.16 (ß = 0.16; 95% CI: 0.02, 0.30) increase in HAZ compared to those in the first tertile. A 0.22 (ß = 0.22; 95% CI: 0.06, 0.39) and 0.19 (ß = 0.19; 0.04, 0.33) increase in HAZ was found for those in the third tertiles of "dairy, vegetable and fruit" patterns of children 24-59 months and 6-59 months, respectively. Those children in the second (ß = -0.17; 95% CI: -0.31, -0.04) and third (ß = -0.16; 95% CI: -0.30, -0.02) tertiles of maternal "egg, meat, poultry and legume" pattern had a significantly lower HAZ compared to those in the first tertile. No significant associations between the household and child "egg, meat, poultry and legume" dietary patterns with HAZ and stunting were found. Statistically non-significant associations were found between household, maternal and child DDSs, and HAZ and stunting. CONCLUSION: A higher adherence to a "dairy, vegetable and fruit" dietary pattern is associated with increased HAZ and reduced risk of stunting. Dietary pattern analysis methods, using routinely collected dietary data, can be an alternative approach to DDSs in low resource settings, to measure dietary quality and in determining associations of overall dietary intake with stunting.

Burden of disease attributable to suboptimal diet, metabolic risks and low physical activity in Ethiopia and comparison with Eastern sub-Saharan African countries, 1990-2015: findings from the Global Burden of Disease Study 2015.

BACKGROUND: Twelve of the 17 Sustainable Development Goals (SDGs) are related to malnutrition (both under- and overnutrition), other behavioral, and metabolic risk factors. However, comparative evidence on the impact of behavioral and metabolic risk factors on disease burden is limited in sub-Saharan Africa (SSA), including Ethiopia. Using data from the Global Burden of Disease (GBD) Study, we assessed mortality and disability-adjusted life years (DALYs) attributable to child and maternal undernutrition (CMU), dietary risks, metabolic risks and low physical activity for Ethiopia. The results were compared with 14 other Eastern SSA countries. METHODS: Databases from GBD 2015, that consist of data from 1990 to 2015, were used. A comparative risk assessment approach was utilized to estimate the burden of disease attributable to CMU, dietary risks, metabolic risks and low physical activity. Exposure levels of the risk factors were estimated using spatiotemporal Gaussian process regression (ST-GPR) and Bayesian meta-regression models. RESULTS: In 2015, there were 58,783 [95% uncertainty interval (UI): 43,653-76,020] or 8.9% [95% UI: 6.1-12.5] estimated all-cause deaths attributable to CMU, 66,269 [95% UI: 39,367-106,512] or 9.7% [95% UI: 7.4-12.3] to dietary risks, 105,057 [95% UI: 66,167-157,071] or 15.4% [95% UI: 12.8-17.6] to metabolic risks and 5808 [95% UI: 3449-9359] or 0.9% [95% UI: 0.6-1.1] to low physical activity in Ethiopia. While the age-adjusted proportion of all-cause mortality attributable to CMU decreased significantly between 1990 and 2015, it increased from 10.8% [95% UI: 8.8-13.3] to 14.5% [95% UI: 11.7-18.0] for dietary risks and from 17.0% [95% UI: 15.4-18.7] to 24.2% [95% UI: 22.2-26.1] for metabolic risks. In 2015, Ethiopia ranked among the top four countries (of 15 Eastern SSA countries) in terms of mortality and DALYs based on the age-standardized proportion of disease attributable to dietary and metabolic risks. CONCLUSIONS: In Ethiopia, while there was a decline in mortality and DALYs attributable to CMU over the last two and half decades, the burden attributable to dietary and metabolic risks have increased during the same period. Lifestyle and metabolic risks of NCDs require more attention by the primary health care system of the country.

Incidence, prevalence and mortality rates of malaria in Ethiopia from 1990 to 2015: analysis of the global burden of diseases 2015.

BACKGROUND: In Ethiopia there is no complete registration system to measure disease burden and risk factors accurately. In this study, the 2015 global burden of diseases, injuries and risk factors (GBD) data were used to analyse the incidence, prevalence and mortality rates of malaria in Ethiopia over the last 25 years. METHODS: GBD 2015 used verbal autopsy surveys, reports, and published scientific articles to estimate the burden of malaria in Ethiopia. Age and gender-specific causes of death for malaria were estimated using cause of death ensemble modelling. RESULTS: The number of new cases of malaria declined from 2.8 million [95% uncertainty interval (UI) 1.4-4.5 million] in 1990 to 621,345 (95% UI 462,230-797,442) in 2015. Malaria caused an estimated 30,323 deaths (95% UI 11,533.3-61,215.3) in 1990 and 1561 deaths (95% UI 752.8-2660.5) in 2015, a 94.8% reduction over the 25 years. Age-standardized mortality rate of malaria has declined by 96.5% between 1990 and 2015 with an annual rate of change of 13.4%. Age-standardized malaria incidence rate among all ages and gender declined by 88.7% between 1990 and 2015. The number of disability-adjusted life years lost (DALY) due to malaria decreased from 2.2 million (95% UI 0.76-4.7 million) in 1990 to 0.18 million (95% UI 0.12-0.26 million) in 2015, with a total reduction 91.7%. Similarly, age-standardized DALY rate declined by 94.8% during the same period. CONCLUSIONS: Ethiopia has achieved a 50% reduction target of malaria of the millennium development goals. The country should strengthen its malaria control and treatment strategies to achieve the sustainable development goals.

National disability-adjusted life years (DALYs) for 257 diseases and injuries in Ethiopia, 1990-2015: findings from the global burden of disease study 2015.

BACKGROUND: Disability-adjusted life years (DALYs) provide a summary measure of health and can be a critical input to guide health systems, investments, and priority-setting in Ethiopia. We aimed to determine the leading causes of premature mortality and disability using DALYs and describe the relative burden of disease and injuries in Ethiopia. METHODS: We used results from the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015) for non-fatal disease burden, cause-specific mortality, and all-cause mortality to derive age-standardized DALYs by sex for Ethiopia for each year. We calculated DALYs by summing years of life lost due to premature mortality (YLLs) and years lived with disability (YLDs) for each age group and sex. Causes of death by age, sex, and year were measured mainly using Causes of Death Ensemble modeling. To estimate YLDs, a Bayesian meta-regression method was used. We reported DALY rates per 100,000 for communicable, maternal, neonatal, and nutritional (CMNN) disorders, non-communicable diseases, and injuries, with 95% uncertainty intervals (UI) for Ethiopia. RESULTS: Non-communicable diseases caused 23,118.1 (95% UI, 17,124.4-30,579.6), CMNN disorders resulted in 20,200.7 (95% UI, 16,532.2-24,917.9), and injuries caused 3781 (95% UI, 2642.9-5500.6) age-standardized DALYs per 100,000 in Ethiopia in 2015. Lower respiratory infections, diarrheal diseases, and tuberculosis were the top three leading causes of DALYs in 2015, accounting for 2998 (95% UI, 2173.7-4029), 2592.5 (95% UI, 1850.7-3495.1), and 2562.9 (95% UI, 1466.1-4220.7) DALYs per 100,000, respectively. Ischemic heart disease and cerebrovascular disease were the fourth and fifth leading causes of age-standardized DALYs, with rates of 2535.7 (95% UI, 1603.7-3843.2) and 2159.9 (95% UI, 1369.7-3216.3) per 100,000, respectively. The following causes showed a reduction of 60% or more over the last 25 years: lower respiratory infections, diarrheal diseases, tuberculosis, neonatal encephalopathy, preterm birth complications, meningitis, malaria, protein-energy malnutrition, iron-deficiency anemia, measles, war and legal intervention, and maternal hemorrhage. CONCLUSIONS: Ethiopia has been successful in reducing age-standardized DALYs related to most communicable, maternal, neonatal, and nutritional deficiency diseases in the last 25 years, causing a major ranking shift to types of non-communicable disease. Lower respiratory infections, diarrheal disease, and tuberculosis continue to be leading causes of premature death, despite major declines in burden. Non-communicable diseases also showed reductions as premature mortality declined; however, disability outcomes for these causes did not show declines. Recently developed non-communicable disease strategies may need to be amended to focus on cardiovascular diseases, cancer, diabetes, and major depressive disorders. Increasing trends of disabilities due to neonatal encephalopathy, preterm birth complications, and neonatal disorders should be emphasized in the national newborn survival strategy. Generating quality data should be a priority through the development of new initiatives such as vital events registration, surveillance programs, and surveys to address gaps in data. Measuring disease burden at subnational regional state levels and identifying variations with urban and rural population health should be conducted to support health policy in Ethiopia.

National mortality burden due to communicable, non-communicable, and other diseases in Ethiopia, 1990-2015: findings from the Global Burden of Disease Study 2015.

BACKGROUND: Ethiopia lacks a complete vital registration system that would assist in measuring disease burden and risk factors. We used the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015) estimates to describe the mortality burden from communicable, non-communicable, and other diseases in Ethiopia over the last 25 years. METHODS: GBD 2015 mainly used cause of death ensemble modeling to measure causes of death by age, sex, and year for 195 countries. We report numbers of deaths and rates of years of life lost (YLL) for communicable, maternal, neonatal, and nutritional (CMNN) disorders, non-communicable diseases (NCDs), and injuries with 95% uncertainty intervals (UI) for Ethiopia from 1990 to 2015. RESULTS: CMNN causes of death have declined by 65% in the last two-and-a-half decades. Injury-related causes of death have also decreased by 70%. Deaths due to NCDs declined by 37% during the same period. Ethiopia showed a faster decline in the burden of four out of the five leading causes of age-standardized premature mortality rates when compared to the overall sub-Saharan African region and the Eastern sub-Saharan African region: lower respiratory infections, tuberculosis, HIV/AIDS, and diarrheal diseases; however, the same could not be said for ischemic heart disease and other NCDs. Non-communicable diseases, together, were the leading causes of age-standardized mortality rates, whereas CMNN diseases were leading causes of premature mortality in 2015. Although lower respiratory infections, tuberculosis, and diarrheal disease were the leading causes of age-standardized death rates, they showed major declines from 1990 to 2015. Neonatal encephalopathy, iron-deficiency anemia, protein-energy malnutrition, and preterm birth complications also showed more than a 50% reduction in burden. HIV/AIDS-related deaths have also decreased by 70% since 2005. Ischemic heart disease, hemorrhagic stroke, and ischemic stroke were among the top causes of premature mortality and age-standardized death rates in Ethiopia in 2015. CONCLUSIONS: Ethiopia has been successful in reducing deaths related to communicable, maternal, neonatal, and nutritional deficiency diseases and injuries by 65%, despite unacceptably high maternal and neonatal mortality rates. However, the country's performance regarding non-communicable diseases, including cardiovascular disease, diabetes, cancer, and chronic respiratory disease, was minimal, causing these diseases to join the leading causes of premature mortality and death rates in 2015. While the country is progressing toward universal health coverage, prevention and control strategies in Ethiopia should consider the double burden of common infectious diseases and non-communicable diseases: lower respiratory infections, diarrhea, tuberculosis, HIV/AIDS, cardiovascular disease, cancer, and diabetes. Prevention and control strategies should also pay special attention to the leading causes of premature mortality and death rates caused by non-communicable diseases: cardiovascular disease, cancer, and diabetes. Measuring further progress requires a data revolution in generating, managing, analyzing, and using data for decision-making and the creation of a full vital registration system in the country.

Trends and causes of maternal mortality in Ethiopia during 1990-2013: findings from the Global Burden of Diseases study 2013.

BACKGROUND: Maternal mortality is noticeably high in sub-Saharan African countries including Ethiopia. Continuous nationwide systematic evaluation and assessment of the problem helps to design appropriate policy and strategy in Ethiopia. This study aimed to investigate the trends and causes of maternal mortality in Ethiopia between 1990 and 2013. METHODS: We used the Global Burden of Diseases and Risk factors (GBD) Study 2013 data that was collected from multiple sources at national and subnational levels. Spatio-temporal Gaussian Process Regression (ST-GPR) was applied to generate best estimates of maternal mortality with 95% Uncertainty Intervals (UI). Causes of death were measured using Cause of Death Ensemble modelling (CODEm). The modified UNAIDS EPP/SPECTRUM suite model was used to estimate HIV related maternal deaths. RESULTS: In Ethiopia, a total of 16,740 (95% UI: 14,197, 19,271) maternal deaths occurred in 1990 whereas there were 15,234 (95% UI: 11,378, 19,871) maternal deaths occurred in 2013. This finding shows that Maternal Mortality Ratio (MMR) in Ethiopia was still high in the study period. There was a minimal but insignificant change of MMR over the last 23 years. The results revealed Ethiopia is below the target of Millennium Development Goals (MGDs) related to MMR. The top five causes of maternal mortality in 2013 were other direct maternal causes such as complications of anaesthesia, embolism (air, amniotic fluid, and blood clot), and the condition of peripartum cardiomyopathy (25.7%), complications of abortions (19.6%), maternal haemorrhage (12.2%), hypertensive disorders (10.3%), and maternal sepsis and other maternal infections such as influenza, malaria, tuberculosis, and hepatitis (9.6%). Most of the maternal mortality happened during the postpartum period and majority of the deaths occurred at the age group of 20-29 years. Overall trend showed that there was a decline from 708 per 100,000 live births in 1990 to 497 per 100,000 in 2013. The annual rate of change over these years was -1.6 (95% UI: -2.8 to -0.3). CONCLUSION: The findings of the study highlight the need for comprehensive efforts using multisectoral collaborations from stakeholders for reducing maternal mortality in Ethiopia. It is worthwhile for policies to focus on postpartum period.