This paper seeks to determine the prevalence of chronic respiratory diseases in urban and rural Uganda and to identify risk factors for these diseases. The population-based, cross-sectional study included adults aged 35 years or older. All participants were evaluated by spirometry according to standard guidelines and completed questionnaires on respiratory symptoms, functional status and demographic characteristics. The presence of four chronic respiratory conditions was monitored: chronic obstructive pulmonary disease, asthma, chronic bronchitis and a restrictive spirometry pattern. The age-adjusted prevalence of any chronic respiratory condition was 20.2%; the age-adjusted prevalence of chronic obstructive pulmonary disease was significantly greater in rural than urban participants, whereas asthma was significantly more prevalent in urban participants: 9.7% versus 4.4% in rural participants. The age-adjusted prevalence of chronic bronchitis was similar in rural and urban participants, as was that of a restrictive spirometry pattern. For chronic obstructive pulmonary disease, the population attributable risk was 51.5% for rural residence, 19.5% for tobacco smoking, 16.0% for a body mass index over 18.5 kg and 13.0% for a history of treatment for pulmonary tuberculosis. The prevalence of chronic respiratory disease was high in both rural and urban Uganda.
Equity in Health
Tuberculosis can be treated, prevented, and cured. Rapid, sustained declines in tuberculosis deaths in many countries during the past 50 years provide compelling evidence that ending the pandemic is feasible. Yet this disease—which has plagued humanity since before recorded history and has killed hundreds of millions of people over the past two centuries—remains a relentless scourge. In 2017, 1.6 million people died from tuberculosis, including 300 000 people with HIV, representing more deaths than any other infectious disease. Moreover, in many parts of the world, drug-resistant forms of tuberculosis threaten struggling control efforts. The world can no longer ignore the enormous pall cast by the tuberculosis epidemic. Going forward, the global tuberculosis response must be an inclusive, comprehensive response within the broader sustainable development agenda. No one-size-fits-all approach can succeed.
WHO Director-General Dr Tedros Adhanom Ghebreyesus and WHO Regional Director for Africa, Dr Matshidiso Moeti, visited Butembo, in the Democratic Republic of the Congo. It was in Butembo on 19 April that WHO epidemiologist Dr Richard Mouzoko was killed by armed men while he and colleagues were working on the Ebola response. Dr Tedros and Dr Moeti traveled to Butembo to express their gratitude and show support to WHO and partner organization staff, while also assessing the next steps needed to strengthen both security and the Ebola response effort. They also met with local political, business and religious leaders, and called on them to accelerate their efforts to stabilize the surrounding environment. They urged the international community to step up support to contain the Ebola outbreak, including filling the funding gap that threatens to stymie the Ebola response. Most Ebola response activities, including community engagement, vaccination, and case investigation, have been re-launched following a slowdown in the wake of the attack that left Dr. Mouzoko dead and two people injured. However, they expressed deep concern that a rise in reported cases in recent weeks is straining resources even further. Only half of the currently requested funds have been received, which could lead to WHO and partners rolling back some activities precisely when they are most needed.
It is important to assess whether regional progress toward achieving the Millennium Development Goals (MDGs) has contributed to human development and whether this has had an effect on the triple burden of disease in Africa. This analysis investigates the association between the human development index (HDI) and co-occurrence of HIV/AIDS, tuberculosis (TB), and malaria as measured by MDG 6 indicators in 35 selected sub-Saharan African countries from 2000 to 2014. The analysis used secondary data from the United Nations Development Programme data repository for HDI and disease data from WHO Global Health observatory data repository. Generalized Linear Regression Models were used to analyze relationships between HDI and MDG 6 indicators. HDI was observed to improve from 2001 to 2014, and this varied across the selected sub-regions. There was a significant positive relationship between HDI and HIV prevalence in East Africa and Southern Africa. A significant positive relationship was observed with TB incidence and a significant negative relationship was observed with malaria incidence in East Africa. Observed improvements in HDI from the year 2000 to 2014 did not translate into commensurate progress in MDG 6 goals.
Considerable evidence has emerged that some population groups in urban areas may be facing worse health than rural areas and that the urban advantage may be waning in some contexts. The authors used a descriptive study undertaking a comparative analysis of 13 child health indicators between urban and rural areas using seven data points provided by nationally representative population based surveys—the Malawi Demographic and Health Surveys and Multiple Indicator Cluster Surveys. Rate differences between urban and rural values for selected child health indicators were calculated to denote whether urban-rural differentials showed a trend of declining urban advantage in Malawi. The results show that all forms of child mortality have significantly declined between 1992 and 2015/2016 reflecting successes in child health interventions. Rural-urban comparisons, using rate differences, largely indicate a picture of the narrowing gap between urban and rural areas albeit the extent and pattern vary among child health indicators. Of the 13 child health indicators, eight show clear patterns of a declining urban advantage particularly up to 2014. However, U-5MR shows reversal to a significant urban advantage in 2015/2016, and slight increases in urban advantage are noted for infant mortality rate, underweight, full childhood immunization, and stunting rate in 2015/2016. The findings suggest the need to rethink the policy viewpoint of a disadvantaged rural and much better-off urban in child health programming. Efforts should be dedicated towards addressing determinants of child health in both urban and rural areas.
This paper examines how changes in the social determinants of health have impacted health inequalities over the last decade, the second since the end of apartheid. Data was drawn from information on social determinants of health and on health status in the 2004, 2010 and 2014 South African General Household Surveys. The results show that inequalities in ill-health are consistently explained by socio-economic inequalities relating to employment status, while provincial differences in ill health narrowed considerably over the studied periods. Disability inequalities were largely explained by socio-economic inequalities relating to racial groups, educational attainment and provincial differences. The authors indicate that the extent of employment, location and education inequalities suggests the need for improved health care management and further delivery of education and job opportunities.
Despite progressive health policy, disease burdens in South Africa remain patterned by deeply entrenched social inequalities. The authors suggest that accounting for the relationships between context, health and risk can provide important information for equitable service delivery. This research used a participatory research process with communities in a low income setting in the Agincourt health and socio–demographic surveillance site (HDSS) in rural north–east South Africa. Three village–based discussion groups were convened and consulted about conditions to examine, one of which was under–5 mortality. A series of discussions followed in which routine HDSS data were presented and participants’ subjective perspectives were elicited and systematized into collective forms of knowledge using ranking, diagramming and participatory photography. The process concluded with a priority setting exercise. Visual and narrative data were thematically analysed to complement the participants’ analysis. Participants identified a range of social and structural root causes of under–5 mortality: poverty, unemployment, inadequate housing, unsafe environments and shortages of clean water. Despite these constraints, single mothers were often viewed as negligent. A series of mid–level contributory factors in clinics were also identified: overcrowding, poor staffing, delays in treatment and shortages of medications. However, blame and negativity were directed toward clinic nurses in spite of the systems constraints identified. Actions to address these issues were prioritized as: expanding clinics, improving accountability and responsiveness of health workers, improving employment, providing clean water, and expanding community engagement for health promotion.
This study examines how changes in the social determinants of health have impacted health inequalities in South Africa over the last decade, the second since 1994. Information collected on social determinants of health and on health status was obtained from the 2004, 2010 and 2014 questionnaires in the South African General Household Surveys. The health indicators considered include ill-health status and disability. Concentration indices and Oaxaca-Blinder decomposition of change in a concentration index methods helped to unravel changes in socio-economic health inequalities and their key social drivers over the studied time period. The results show that inequalities in ill-health are consistently explained by socio-economic inequalities relating to employment status. Provincial differences narrowed considerably over the studied periods. Relatedly, disability inequalities are largely explained by shrinking socio-economic inequalities relating to racial groups, educational attainment and provincial differences. The extent of employment, location and education inequalities suggests the need for improved health care management and further delivery of education and job opportunities.
South Africans are likely to live, on average, seven years longer in 2040 than they do now, but the country will see only modest improvement in its global ranking as longevity increases worldwide, according to a study published in the Lancet. SA had an average life expectancy of 62.4 years in 2016, and ranked 171 among 195 countries. If recent health trends continue, SA could see life expectancy increasing to 69.3 years. But it will only rise two places in the global rankings, to 169, as life expectancy is expected to increase in most countries. The authors of the study forecast a range of scenarios for each country, which for SA show that life expectancy could increase by as much as 12.9 years to 75.3 years if the country stepped up its efforts to improve the health of the nation. But in the worst-case scenario, life expectancy could fall by as much as 8.1 years. The study forecast a large global shift in deaths from infectious diseases to deaths from noncommunicable diseases such as diabetes, chronic obstructive pulmonary disease, kidney disease and lung cancer. The top 10 causes of death in SA in 2016 were HIV/Aids, lower respiratory infections, road injuries, interpersonal violence, tuberculosis, diabetes, ischemic heart disease, diarrhoeal diseases, stroke and premature birth complications. By 2040, however, diabetes will be the leading cause of death, followed by road injuries, lower respiratory infections, HIV/AIDS, interpersonal violence, ischemic heart disease, tuberculosis, chronic kidney disease, stroke and diarrhoeal diseases.
This paper analyzed the estimated prevalence, and modeled possible determinants of, moderate acute malnutrition and severe acute malnutrition (SAM) for Indigenous Batwa and non-Indigenous Bakiga of Kanungu District in Southwestern Uganda. The authors characterize possible mechanisms driving differences in malnutrition. Retrospective cross-sectional surveys were administered to 10 Batwa communities and 10 matched Bakiga Local Councils during April of 2014. Individuals were classified as moderate acute malnutrition and SAM based on middle upper-arm circumference for their age-sex strata. Malnutrition is high among Batwa children and adults, with nearly half of Batwa adults and nearly a quarter of Batwa children meeting moderate acute malnutrition criteria. SAM prevalence is lower than moderate acute malnutrition prevalence, with SAM highest among adult Batwa males. SAM prevalence among children was higher for Batwa males compared to Bakiga males. Models that incorporated community ethnicity explained the greatest variance in middle upper-arm circumference values. This research demonstrates inequality in malnutrition between the Indigenous Batwa and non-Indigenous Bakiga of Kanungu District, Uganda, with model results suggesting further investigation into the role of ethnicity as an upstream social determinant of health.