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The Sustainable Development Goals (SDGs) are now steering the global health and development agendas. Notably, the SDGs contain no mention of primary health care, reflecting the disappointing implementation of the Alma-Ata declaration of 1978 over the past four decades. The draft Astana declaration (Alma-Ata 2·0), released in June, 2018, restates the key principles of primary health care and renews these as driving forces for achieving the SDGs, emphasising universal health coverage. We use accumulating evidence to show that countries that reoriente their health systems towards primary care are better placed to achieve the SDGs than those with hospital-focused systems or low investment in health. We then argue that an even bolder approach, which fully embraces the Alma-Ata vision of primary health care, could deliver substantially greater SDG progress, by addressing the wider determinants of health, promoting equity and social justice throughout society, empowering communities, and being a catalyst for advancing and amplifying universal health coverage and synergies among SDGs.

Armed conflicts have major indirect health impacts in addition to the direct harms from violence. They create enduring political instability, destabilise health systems, and foster negative socioeconomic and environmental conditions-all of which constrain efforts to reduce maternal and child mortality. The detrimental impacts of conflict on global maternal and child health are not robustly quantified. This study assesses the association between conflict and maternal and child health globally. Data for 181 countries (2000-2019) from the Uppsala Conflict Data Program and World Bank were analysed using panel regression models. Primary outcomes were maternal, under-5, infant, and neonatal mortality rates. Secondary outcomes were delivery by a skilled birth attendant and diphtheria, pertussis, and tetanus (DPT) and measles vaccination coverage. Models were adjusted for 10 confounders, country and year fixed effects, and conflict lagged by 1 year. Further lagged associations up to 10 years post-conflict were tested. The number of excess deaths due to conflict was estimated. Out of 3,718 country-year observations, 522 (14.0%) had minor conflicts and 148 (4.0%) had wars. In adjusted models, conflicts classified as wars were associated with an increase in maternal mortality of 36.9 maternal deaths per 100,000 live births (95% CI 1.9-72.0; 0.3 million excess deaths [95% CI 0.2 million-0.4 million] over the study period), an increase in infant mortality of 2.8 per 1,000 live births (95% CI 0.1-5.5; 2.0 million excess deaths [95% CI 1.6 million-2.5 million]), a decrease in DPT vaccination coverage of 4.9% (95% CI 1.5%-8.3%), and a decrease in measles vaccination coverage of 7.3% (95% CI 2.7%-11.8%). The long-term impacts of war were demonstrated by associated increases in maternal mortality observed for up to 7 years, in under-5 mortality for 3-5 years, in infant mortality for up to 8 years, in DPT vaccination coverage for up to 3 years, and in measles vaccination coverage for up to 2 years. No evidence of association between armed conflict and neonatal mortality or delivery by a skilled birth attendant was found. Study limitations include the ecological study design, which may mask sub-national variation in conflict intensity, and the quality of the underlying data. Our analysis indicates that armed conflict is associated with substantial and persistent excess maternal and child deaths globally, and with reductions in key measures that indicate reduced availability of organised healthcare. These findings highlight the importance of protecting women and children from the indirect harms of conflict, including those relating to health system deterioration and worsening socioeconomic conditions.

Universal health coverage (UHC) can play an important role in achieving Sustainable Development Goal (SDG) 10, which addresses reducing inequalities, but little supporting evidence is available from low- and middle-income countries. Brazil's Estratégia de Saúde da Família (ESF) (family health strategy) is a community-based primary healthcare (PHC) programme that has been expanding since the 1990s and is the main platform for delivering UHC in the country. We evaluated whether expansion of the ESF was associated with differential reductions in mortality amenable to PHC between racial groups. Municipality-level longitudinal fixed-effects panel regressions were used to examine associations between ESF coverage and mortality from ambulatory-care-sensitive conditions (ACSCs) in black/pardo (mixed race) and white individuals over the period 2000-2013. Models were adjusted for socio-economic development and wider health system variables. Over the period 2000-2013, there were 281,877 and 318,030 ACSC deaths (after age standardisation) in the black/pardo and white groups, respectively, in the 1,622 municipalities studied. Age-standardised ACSC mortality fell from 93.3 to 57.9 per 100,000 population in the black/pardo group and from 75.7 to 49.2 per 100,000 population in the white group. ESF expansion (from 0% to 100%) was associated with a 15.4% (rate ratio [RR]: 0.846; 95% CI: 0.796-0.899) reduction in ACSC mortality in the black/pardo group compared with a 6.8% (RR: 0.932; 95% CI: 0.892-0.974) reduction in the white group (coefficients significantly different, p = 0.012). These differential benefits were driven by greater reductions in mortality from infectious diseases, nutritional deficiencies and anaemia, diabetes, and cardiovascular disease in the black/pardo group. Although the analysis is ecological, sensitivity analyses suggest that over 30% of black/pardo deaths would have to be incorrectly coded for the results to be invalid. This study is limited by the use of municipal-aggregate data, which precludes individual-level inference. Omitted variable bias, where factors associated with ESF expansion are also associated with changes in mortality rates, may have influenced our findings, although sensitivity analyses show the robustness of the findings to pre-ESF trends and the inclusion of other municipal-level factors that could be associated with coverage. PHC expansion is associated with reductions in racial group inequalities in mortality in Brazil. These findings highlight the importance of investment in PHC to achieve the SDGs aimed at improving health and reducing inequalities.

Since 2015, a major economic crisis in Brazil has led to increasing poverty and the implementation of long-term fiscal austerity measures that will substantially reduce expenditure on social welfare programmes as a percentage of the country's GDP over the next 20 years. The Bolsa Família Programme (BFP)-one of the largest conditional cash transfer programmes in the world-and the nationwide primary healthcare strategy (Estratégia Saúde da Família [ESF]) are affected by fiscal austerity, despite being among the policy interventions with the strongest estimated impact on child mortality in the country. We investigated how reduced coverage of the BFP and ESF-compared to an alternative scenario where the level of social protection under these programmes is maintained-may affect the under-five mortality rate (U5MR) and socioeconomic inequalities in child health in the country until 2030, the end date of the Sustainable Development Goals. We developed and validated a microsimulation model, creating a synthetic cohort of all 5,507 Brazilian municipalities for the period 2017-2030. This model was based on the longitudinal dataset and effect estimates from a previously published study that evaluated the effects of poverty, the BFP, and the ESF on child health. We forecast the economic crisis and the effect of reductions in BFP and ESF coverage due to current fiscal austerity on the U5MR, and compared this scenario with a scenario where these programmes maintain the levels of social protection by increasing or decreasing with the size of Brazil's vulnerable populations (policy response scenarios). We used fixed effects multivariate regression models including BFP and ESF coverage and accounting for secular trends, demographic and socioeconomic changes, and programme duration effects. With the maintenance of the levels of social protection provided by the BFP and ESF, in the most likely economic crisis scenario the U5MR is expected to be 8.57% (95% CI: 6.88%-10.24%) lower in 2030 than under fiscal austerity-a cumulative 19,732 (95% CI: 10,207-29,285) averted under-five deaths between 2017 and 2030. U5MRs from diarrhoea, malnutrition, and lower respiratory tract infections are projected to be 39.3% (95% CI: 36.9%-41.8%), 35.8% (95% CI: 31.5%-39.9%), and 8.5% (95% CI: 4.1%-12.0%) lower, respectively, in 2030 under the maintenance of BFP and ESF coverage, with 123,549 fewer under-five hospitalisations from all causes over the study period. Reduced coverage of the BFP and ESF will also disproportionately affect U5MR in the most vulnerable areas, with the U5MR in the poorest quintile of municipalities expected to be 11.0% (95% CI: 8.0%-13.8%) lower in 2030 under the maintenance of BFP and ESF levels of social protection than under fiscal austerity, compared to no difference in the richest quintile. Declines in health inequalities over the last decade will also stop under a fiscal austerity scenario: the U5MR concentration index is expected to remain stable over the period 2017-2030, compared to a 13.3% (95% CI: 5.6%-21.8%) reduction under the maintenance of BFP and ESF levels of protection. Limitations of our analysis are the ecological nature of the study, uncertainty around future macroeconomic scenarios, and potential changes in other factors affecting child health. A wide range of sensitivity analyses were conducted to minimise these limitations. The implementation of fiscal austerity measures in Brazil can be responsible for substantively higher childhood morbidity and mortality than expected under maintenance of social protection-threatening attainment of Sustainable Development Goals for child health and reducing inequality.

Background Non-pharmaceutical interventions have been implemented around the world to control Covid-19 transmission. Their general effect on reducing virus transmission is proven, but they can also be negative to mental health and economies, and transmission behaviours can also change voluntarily, without mandated interventions. Their relative impact on Covid-19 attributed mortality, enabling policy selection for maximal benefit with minimal disruption, is not well established due to a lack of definitive methods. Methods We examined variations in timing and strictness of nine non-pharmaceutical interventions implemented in 130 countries and recorded by the Oxford COVID-19 Government Response Tracker (OxCGRT): 1) School closing; 2) Workplace closing; 3) Cancelled public events; 4) Restrictions on gatherings; 5) Closing public transport; 6) Stay at home requirements (‘Lockdown’); 7) Restrictions on internal movement; 8) International travel controls; 9) Public information campaigns. We used two time periods in the first wave of Covid-19, chosen to limit reverse causality, and fixed country policies to those implemented: i) prior to first Covid-19 death (when policymakers could not possibly be reacting to deaths in their own country); and, ii) 14-days-post first Covid-19 death (when deaths were still low, so reactive policymaking still likely to be minimal). We then examined associations with daily deaths per million in each subsequent 24-day period, which could only be affected by the intervention period, using linear and non-linear multivariable regression models. This method, therefore, exploited the known biological lag between virus transmission (which is what the policies can affect) and mortality for statistical inference. Results After adjusting, earlier and stricter school (− 1.23 daily deaths per million, 95% CI − 2.20 to − 0.27) and workplace closures (− 0.26, 95% CI − 0.46 to − 0.05) were associated with lower Covid-19 mortality rates. Other interventions were not significantly associated with differences in mortality rates across countries. Findings were robust across multiple statistical approaches. Conclusions Focusing on ‘compulsory’, particularly school closing, not ‘voluntary’ reduction of social interactions with mandated interventions appears to have been the most effective strategy to mitigate early, wave one, Covid-19 mortality. Within ‘compulsory’ settings, such as schools and workplaces, less damaging interventions than closing might also be considered in future waves/epidemics.

Background Armed conflict can indirectly affect population health through detrimental impacts on political and social institutions and destruction of infrastructure. This study aimed to quantify indirect mortality impacts of armed conflict in civilian populations globally and explore differential effects by armed conflict characteristics and population groups. Methods We included 193 countries between 1990 and 2017 and constructed fixed effects panel regression models using data from the Uppsala Conflict Data Program and Global Burden of Disease study. Mortality rates were corrected to exclude battle-related deaths. We assessed separately four different armed conflict variables (capturing binary, continuous, categorical, and quintile exposures) and ran models by cause-specific mortality stratified by age groups and sex. Post-estimation analyses calculated the number of civilian deaths. Results We identified 1118 unique armed conflicts. Armed conflict was associated with increases in civilian mortality—driven by conflicts categorised as wars. Wars were associated with an increase in age-standardised all-cause mortality of 81.5 per 100,000 population ( β 81.5, 95% CI 14.3–148.8) in adjusted models contributing 29.4 million civilian deaths (95% CI 22.1–36.6) globally over the study period. Mortality rates from communicable, maternal, neonatal, and nutritional diseases ( β 51.3, 95% CI 2.6–99.9); non-communicable diseases ( β 22.7, 95% CI 0.2–45.2); and injuries ( β 7.6, 95% CI 3.4–11.7) associated with war increased, contributing 21.0 million (95% CI 16.3–25.6), 6.0 million (95% CI 4.1–8.0), and 2.4 million deaths (95% CI 1.7–3.1) respectively. War-associated increases in all-cause and cause-specific mortality were found across all age groups and both genders, but children aged 0–5 years had the largest relative increases in mortality. Conclusions Armed conflict, particularly war, is associated with a substantial indirect mortality impact among civilians globally with children most severely burdened.

Expanding delivery of primary healthcare to urban poor populations is a priority in many low- and middle-income countries. This remains a key challenge in Brazil despite expansion of the country's internationally recognized Family Health Strategy (FHS) over the past two decades. This study evaluates the impact of an ambitious program to rapidly expand FHS coverage in the city of Rio de Janeiro, Brazil, since 2008. A cohort of 1,241,351 low-income adults (observed January 2010-December 2016; total person-years 6,498,607) with linked FHS utilization and mortality records was analyzed using flexible parametric survival models. Time-to-death from all-causes and selected causes were estimated for FHS users and nonusers. Models employed inverse probability treatment weighting and regression adjustment (IPTW-RA). The cohort was 61% female (751,895) and had a mean age of 36 years (standard deviation 16.4). Only 18,721 individuals (1.5%) had higher education, whereas 102,899 (8%) had no formal education. Two thirds of individuals (827,250; 67%) were in receipt of conditional cash transfers (Bolsa Família). A total of 34,091 deaths were analyzed, of which 8,765 (26%) were due to cardiovascular disease; 5,777 (17%) were due to neoplasms; 5,683 (17%) were due to external causes; 3,152 (9%) were due to respiratory diseases; and 3,115 (9%) were due to infectious and parasitic diseases. One third of the cohort (467,155; 37.6%) used FHS services. In IPTW-RA survival analysis, an average FHS user had a 44% lower hazard of all-cause mortality (HR: 0.56, 95% CI 0.54-0.59, p < 0.001) and a 5-year risk reduction of 8.3 per 1,000 (95% CI 7.8-8.9, p < 0.001) compared with a non-FHS user. There were greater reductions in the risk of death for FHS users who were black (HR 0.50, 95% CI 0.46-0.54, p < 0.001) or pardo (HR 0.57, 95% CI 0.54-0.60, p < 0.001) compared with white (HR 0.59, 95% CI 0.56-0.63, p < 0.001); had lower educational attainment (HR 0.50, 95% CI 0.46-0.55, p < 0.001) for those with no education compared to no significant association for those with higher education (p = 0.758); or were in receipt of conditional cash transfers (Bolsa Família) (HR 0.51, 95% CI 0.49-0.54, p < 0.001) compared with nonrecipients (HR 0.63, 95% CI 0.60-0.67, p < 0.001). Key limitations in this study are potential unobserved confounding through selection into the program and linkage errors, although analytical approaches have minimized the potential for bias. FHS utilization in urban poor populations in Brazil was associated with a lower risk of death, with greater reductions among more deprived race/ethnic and socioeconomic groups. Increased investment in primary healthcare is likely to improve health and reduce health inequalities in urban poor populations globally.

Background Racial and ethnic inequalities in access to healthcare services pose a significant challenge for many countries, with ethnic minorities and Afro-descendants frequently experiencing poorer access to services and health outcomes. However, little is known about the factors that drive racial inequalities in access to healthcare, especially in low- and middle-income countries. Methods This is a cross-sectional, observational study that uses data from the National Health Survey (2019) in Brazil and assesses the contribution of predisposing, facilitating, and need-for-care factors to inequalities in healthcare access between White, Black and Pardo (Brown) Brazilians. The Oaxaca-Blinder method was used to separate differences between racial groups into explained and unexplained determinants. Variables included in the models were age, sex, marital status, family size and composition, access to sanitation, health insurance, primary care coverage, income quintile, employment status, education, and self-rated health status. Results The responses from 204,918 individuals were analysed. White Brazilians reported better access to healthcare and medications than Black or Pardo Brazilians, with the largest racial inequalities in unmet needs for healthcare services and access to medication. Racial inequalities are mostly explained by observable factors (between 35% and 87%), most notably the access to financial resources (income and access to private health insurance). Being covered by the Family Health Program and higher levels of education were associated with reduced inequalities between racial groups. The unexplained portion of inequalities was the greatest when comparing Black and White individuals, implying that factors beyond socioeconomic status likely drive these inequalities including community, cultural or behavioural factors, and inequalities and bias in healthcare services. Conclusions While investments in universal healthcare and education may be important for reducing racial inequalities in access to healthcare, better understanding of cultural and contextual factors and targeted public policies and services interventions for addressing racial inequalities are needed.

Background Race and ethnicity are important drivers of health inequalities worldwide. However, the recording of race/ethnicity in data systems is frequently insufficient, particularly in low- and middle-income countries. The aim of this study is to descriptively analyse trends in data completeness in race/color records in hospital admissions and the rates of hospitalizations by various causes for Blacks and Whites individuals. Methods We conducted a longitudinal analysis, examining hospital admission data from Brazil’s Hospital Information System (SIH) between 2010 and 2022, and analysed trends in reporting completeness and racial inequalities. These hospitalization records were examined based on year, quarter, cause of admission (using International Classification of Diseases (ICD-10) codes), and race/color (categorized as Black, White, or missing). We examined the patterns in hospitalization rates and the prevalence of missing data over a period of time. Results Over the study period, there was a notable improvement in data completeness regarding race/color in hospital admissions in Brazil. The proportion of missing values on race decreased from 34.7% in 2010 to 21.2% in 2020. As data completeness improved, racial inequalities in hospitalization rates became more evident – across several causes, including assaults, tuberculosis, hypertensive diseases, at-risk hospitalizations during pregnancy and motorcycle accidents. Conclusions The study highlights the critical role of data quality in identifying and addressing racial health inequalities. Improved data completeness has revealed previously hidden inequalities in health records, emphasizing the need for comprehensive data collection to inform equitable health policies and interventions. Policymakers working in areas where socioeconomic data reporting (including on race and ethnicity) is suboptimal, should address data completeness to fully understand the scale of health inequalities.

Background Evidence is limited on racial/ethnic group disparities in multimorbidity and associated health outcomes in low- and middle-income countries hampering effective policies and clinical interventions to address health inequalities. Methods This study assessed race/ethnic and socioeconomic disparities in the prevalence of multimorbidity and associated healthcare utilisation, costs and death in Rio de Janeiro, Brazil. A cross-sectional analysis was carried out of 3,027,335 individuals registered with primary healthcare (PHC) services. Records included linked data to hospitalisation, mortality, and welfare-claimant (Bolsa Família) records between 1 Jan 2012 and 31 Dec 2016. Logistic and Poisson regression models were carried out to assess the likelihood of multimorbidity (two or more diagnoses out of 53 chronic conditions), PHC use, hospital admissions and mortality from any cause. Interactions were used to assess disparities. Results In total 13,509,633 healthcare visits were analysed identifying 389,829 multimorbid individuals (13%). In adjusted regression models, multimorbidity was associated with lower education (Adjusted Odds Ratio (AOR): 1.26; 95%CI: 1.23,1.29; compared to higher education), Bolsa Família receipt (AOR: 1.14; 95%CI: 1.13,1.15; compared to non-recipients); and black race/ethnicity (AOR: 1.05; 95%CI: 1.03,1.06; compared to white). Multimorbidity was associated with more hospitalisations (Adjusted Rate Ratio (ARR): 2.75; 95%CI: 2.69,2.81), more PHC visits (ARR: 3.46; 95%CI: 3.44,3.47), and higher likelihood of death (AOR: 1.33; 95%CI: 1.29,1.36). These associations were greater for multimorbid individuals with lower educational attainment (five year probability of death 1.67% (95%CI: 1.61,1.74%) compared to 1.13% (95%CI: 1.02,1.23%) for higher education), individuals of black race/ethnicity (1.48% (95%CI: 1.41,1.55%) compared to 1.35% (95%CI: 1.31,1.40%) for white) and individuals in receipt of welfare (1.89% (95%CI: 1.77,2.00%) compared to 1.35% (95%CI: 1.31,1.38%) for non-recipients). Conclusions The prevalence of multimorbidity and associated hospital admissions and mortality are greater in individuals with black race/ethnicity and other deprived socioeconomic groups in Rio de Janeiro. Interventions to better prevent and manage multimorbidity and underlying disparities in low- and middle-income country settings are needed.